Greater Than

the Sum

Systems Thinking in

Tobacco Control

NCI TOBACCO CONTROL MONOGRAPH SERIES

U.S. DEPARTMENT 

OF HEALTH AND 

HUMAN SERVICES

National Institutes 

of Health

National Cancer Institute

Edited by

Allan Best, Ph.D.

Pamela I. Clark, Ph.D.

Scott J. Leischow, Ph.D.

William M. K. Trochim, Ph.D.

18
Other NCI Tobacco Control Monographs

Strategies to Control Tobacco Use in the United States: A Blueprint for Public Health Action 

in the 1990’s. Smoking and Tobacco Control Monograph No. 1. NIH Pub. No. 92-3316, 

December 1991.

Smokeless Tobacco or Health: An International Perspective. Smoking and Tobacco Control 

Monograph No. 2. NIH Pub. No. 92-3461, September 1992.

Major Local Tobacco Control Ordinances in the United States. Smoking and Tobacco Control 

Monograph No. 3. NIH Pub. No. 93-3532, May 1993.

Respiratory Health Effects of Passive Smoking: Lung Cancer and Other Disorders. Smoking 

and Tobacco Control Monograph No. 4. NIH Pub. No. 93-3605, August 1993.

Tobacco and the Clinician: Interventions for Medical and Dental Practice. Smoking and 

Tobacco Control Monograph No. 5. NIH Pub. No. 94-3693, January 1994.

Community-based Interventions for Smokers: The COMMIT Field Experience. Smoking and 

Tobacco Control Monograph No. 6. NIH Pub. No. 95-4028, August 1995.

The FTC Cigarette Test Method for Determining Tar, Nicotine, and Carbon Monoxide Yields 

of U.S. Cigarettes. Report of the NCI Expert Committee. Smoking and Tobacco Control 

Monograph No. 7. NIH Pub. No. 96-4028, August 1996.

Changes in Cigarette-Related Disease Risks and Their Implications for Prevention and Control.

Smoking and Tobacco Control Monograph No. 8. NIH Pub. No. 97-4213, February 1997.

Cigars: Health Effects and Trends. Smoking and Tobacco Control Monograph No. 9. NIH Pub. 

No. 98-4302, February 1998.

Health Effects of Exposure to Environmental Tobacco Smoke. Smoking and Tobacco Control 

Monograph No. 10. NIH Pub. No. 99-4645, August 1999.

State and Local Legislative Action to Reduce Tobacco Use. Smoking and Tobacco Control 

Monograph No. 11. NIH Pub. No. 00-4804, August 2000.

Population Based Smoking Cessation. Smoking and Tobacco Control Monograph No. 12. NIH 

Pub. No. 00-4892, November 2000.

Risks Associated with Smoking Cigarettes with Low Machine-Measured Yields of Tar and 

Nicotine. Smoking and Tobacco Control Monograph No. 13. NIH Pub. No. 02-5047, October 2001.

Changing Adolescent Smoking Prevalence. Smoking and Tobacco Control Monograph No. 14. 

NIH Pub. No. 02-5086, November 2001.

Those Who Continue to Smoke. Smoking and Tobacco Control Monograph No. 15. NIH Pub. 

No. 03-5370, September 2003.

ASSIST: Shaping the Future of Tobacco Prevention and Control. Tobacco Control Monograph 

No. 16. NIH Pub. No. 05-5645, May 2005.

Evaluating ASSIST: A Blueprint for Understanding State-level Tobacco Control. Tobacco 

Control Monograph No. 17. NIH Pub. No. 06-6058, October 2006.

Note, when citing this monograph in other works, please use the following format:

National Cancer Institute. Greater Than the Sum: Systems Thinking in Tobacco Control. Tobacco 

Control Monograph No. 18. Bethesda, MD: U.S. Department of Health and Human Services, National 

Institutes of Health, National Cancer Institute. NIH Pub. No. 06-6085, April 2007.
iii

Contents

Illustrations................................................................................................................................ vii

Foreword...................................................................................................................................... xi

Message from the Series Editor................................................................................................ xiii

Preface .........................................................................................................................................xv

Acknowledgments ......................................................................................................................xix

Acronyms...................................................................................................................................xxv

Chapter 1—Overview................................................................................................1

Introduction ................................................................................................................................. 2

Monograph Framework................................................................................................................ 3

Summary ...................................................................................................................................... 5

Major Conclusions........................................................................................................................ 5

Chapter Conclusions.................................................................................................................... 6

References .................................................................................................................................... 9

Chapter 2—Tobacco Control at a Crossroads ................................................... 11

Introduction ............................................................................................................................... 12

Need for a New Approach .......................................................................................................... 13

Population-Level Tobacco Control Efforts: Beginnings of an Integrated System .................. 20

Current Tobacco Control Research and Practice: Systems Problems...................................... 25

Summary .................................................................................................................................... 29

Conclusions ................................................................................................................................ 30

References................................................................................................................................... 30

Chapter 3—Systems Thinking: Potential to Transform Tobacco Control....37

Introduction ............................................................................................................................... 38

Systems and Systems Thinking................................................................................................. 39

Systems Thinking: Toward an Integrated View .........................................................................47

Application of Systems Thinking in Tobacco Control ...............................................................51

Summary .................................................................................................................................... 54

Conclusions ................................................................................................................................ 55

References................................................................................................................................... 56

Chapter 4—How to Organize: Systems Organizing .........................................61

Introduction ............................................................................................................................... 62

Traditional Management Theory............................................................................................... 63

Systems Organizing Model ........................................................................................................ 65

Collaboratively Constructed Concept Maps for Systems Organizing: Case Studies ............... 83

Summary .................................................................................................................................... 95
iv

C o n t e n t s

Conclusions ................................................................................................................................ 96

Appendix 4A. Description of Concept-Mapping Methodology.................................................. 97

References..................................................................................................................................104

Chapter 5—How to Anticipate Change in Tobacco Control Systems .......109

Introduction ..............................................................................................................................110

System Dynamics......................................................................................................................111

System Dynamics Application to Tobacco Control..................................................................116

Simulation Results................................................................................................................... 133

Summary ...................................................................................................................................141

Conclusions ...............................................................................................................................142

Appendix 5A. Detailed Development of a System Dynamics Model........................................143

References .................................................................................................................................146

Chapter 6—Understanding and Managing Stakeholder Networks ..........147

Introduction ..............................................................................................................................148

Overview of Network Theory ....................................................................................................148

Effective Organizational Networks.......................................................................................... 154

Value of Organizational Networks........................................................................................... 155

Application of Network Analysis.............................................................................................. 159

Use of Network Methods for Tobacco Control..........................................................................160

Case Study of Network Analysis in Tobacco Control Evaluation ...........................................169

Summary ...................................................................................................................................180

Conclusions ...............................................................................................................................181

References .................................................................................................................................181

Chapter 7—What We Know: Managing the Knowledge Content ..............185

Introduction ..............................................................................................................................186

Knowledge Management and Translation................................................................................187

Knowledge Management Concepts...........................................................................................189

Framework for Strategy of Knowledge Management and Translation...................................194

Case Study: Knowledge Management in Tobacco Control........................................................197

Case Study: Concept Mapping of Knowledge Base for Tobacco Control................................ 209

Summary ...................................................................................................................................216

Conclusions ...............................................................................................................................217

Appendix 7A. 4P-Knowledge Management and Translation Infrastructures: 

Strategy and Outcome Maps.....................................................................................................218

Appendix 7B. Discussion Questions Used in National Cancer Institute Review of 

Knowledge Management and Translation................................................................................221

References................................................................................................................................. 223

Chapter 8—ISIS: Synthesis and Conclusions .................................................225

Introduction ............................................................................................................................. 226

Synthesis: Looking Back and Looking Over the Horizon ...................................................... 227
v

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

General Conclusions .................................................................................................................231

Specific Conclusions ................................................................................................................ 234

Summary .................................................................................................................................. 245

References................................................................................................................................. 246

Appendix A—Initiative on the Study and Implementation of 

Systems: A Project History ..................................................................................249

References..................................................................................................................................257

Appendix B—Systems Thinking in Tobacco Control: A Framework 

for Implementation.................................................................................................259

Integrated Systems Thinking: Story Line for the Future....................................................... 260

Putting Systems Thinking into Practice................................................................................. 266

Implementing Systems Thinking in Tobacco Control: Open Questions and Next Steps...... 273

References................................................................................................................................. 275

Index..........................................................................................................................277

vii

Tables

Table 3.1 Richmond’s Seven Skills of Systems Thinking ................................................. 42

Table 3.2 Capra’s Six Principles of Ecology ...................................................................... 44

Table 3.3 Core Areas Examined by ISIS and Goals........................................................... 48

Table 3.4 Framework of Integration and Implementation Sciences................................ 49

Table 4.1 Four Functions of Classical Management Theory and Descriptors ................. 65

Table 4.2 Systems Organizing Methods by Principle........................................................ 84

Table 6.1 Ratings of Political and Financial Climates for 10 States in 2002 ..................172

Table 7.1 Integrated Concepts of Knowledge Management and Translation..................193

Table 7.2 4P-Knowledge Management and Translation Strategy Map............................198

Table 7.3 Strategy Map for Knowledge Management and Translation 

Infrastructure ....................................................................................................198

Table 7.4 High-Level Map of Tobacco Control Knowledge ............................................. 207

Table 7.5 Example of Detailed Knowledge Management and Translation Strategy 

Checklist for Cancer Control PLANET: One Knowledge Resource Being 

Deployed in Tobacco Control ............................................................................210

Table 7.6 Example of Knowledge Management and Translation Strategy and 

Outcome Map for Tobacco Control, Based on Resources for Tobacco 

Control Knowledge and Potential Linkage to Desired Outcomes...................211

Table 7.7 Categories for Knowledge Base Taxonomy and Related Clusters from 

Concept Mapping...............................................................................................213

Table 7A.1 Example of Detailed 4P-Knowledge Management and Translation 

Strategy Checklist for Production of Particular Type of Knowledge ............. 220

Table 7A.2 Example of Knowledge-Outcome Map............................................................. 220

Table 8.1 Examples of Recent Systems Efforts in Tobacco Control ............................... 229

Table 8.2 Common Methodological Elements across ISIS Systems Approaches........... 230

Table 8.3 Initial Conclusions about Directions for Systems Thinking........................... 233

Table B.1 Steps for Implementation of Conclusions in Specific Stakeholder Groups ... 271

Illustrations

Figures

Figure 1.1 Model of Stakeholder Groups and Systems Approaches in Tobacco Control..... 3

Figure 2.1 ASSIST Interventions and Delivery Channels .................................................. 23

Figure 2.2 Multiple Variables Affecting Tobacco Control and Its Outcomes..................... 24

Figure 3.1 Combining ISIS Approaches for Applications .................................................. 49

Figure 4.1 Continuum from Traditional Management to Systems Organizing ................ 66

Figure 4.2 Systems Organizing Model................................................................................. 66
viii

Figure 4.3 Optimal Placement of Tobacco Control Initiatives in the Continuum 

of Traditional and Systems Approaches............................................................. 68

Figure 4.4 Elements of Evaluation Framework .................................................................. 82

Figure 4.5 Final Interpreted Concept Map .......................................................................... 88

Figure 4.6 Cluster Rating Map............................................................................................. 89

Figure 4.7 Pattern Match for Relationship of Cluster Averages for Importance 

Versus Feasibility ................................................................................................ 90

Figure 4.8 Pattern Match for Degree of Consensus between Practitioners 

and Researchers on Average Importance Ratings............................................. 90

Figure 4.9 Bivariate Go-Zone Plot of Importance and Feasibility Ratings of 

Practitioners, for Diffusion/Dissemination Cluster ...........................................91

Figure 4.10 Concept Map Showing Clusters, Cluster Labels, and Interpretations 

of Dimensions and Regions................................................................................ 93

Figure 4.11 Cluster Average Ratings of Responsibility ......................................................... 94

Figure 4A.1 Final Cluster-Rating Concept Map for Strategic Planning..............................101

Figure 4A.2 Pattern Matching Ladder Graph of Degree of Consensus between 

Importance Ratings for Groups A and B for Concept Map in Figure 4A.1......102

Figure 4A.3 Go-Zone Plot of Feasibility Versus Importance for Methodology Cluster 

in Concept Map (Figure 4A.1) ...........................................................................103

Figure 5.1 Feedback Loops in a System Dynamics Model.................................................114

Figure 5.2 Sample of Graphs on Tobacco Use Factors from Expert Participants at 

2003 Conference on ISIS...................................................................................118

Figure 5.3 Causal Map Segment, Incorporating Social Norm and Tobacco 

Grower Factors...................................................................................................119

Figure 5.4 Expanded Causal Map Segment, Incorporating Awareness of Tobacco 

Health Risk ....................................................................................................... 120

Figure 5.5 Causal Map Adding Impact of Antitobacco Constituencies.............................121

Figure 5.6 Causal Map Adding Government Awareness of Tobacco as a Health Risk ..... 122

Figure 5.7 Causal Map Adding Impact of Protobacco Constituencies ............................. 122

Figure 5.8 Causal Map Adding Impact of Greater Willingness to Legislate 

Tobacco Control................................................................................................ 123

Figure 5.9 Causal Map Adding Impact of Government Tax Revenues and Funding 

for Tobacco Control .......................................................................................... 124

Figure 5.10 Final Causal Map of System Dynamics Model for Tobacco Control in the 

Initiative on the Study and Implementation of Systems................................ 125

Figure 5.11 Model of Public Opinion Factors...................................................................... 126

Figure 5.12 Model of Aging Chains of Smokers (Birth to Death) ...................................... 127

Figure 5.13 Model of Research and Dissemination Factors................................................ 127

Figure 5.14 Model of Government Sector ........................................................................... 130

Figure 5.15 Expanded Model of Public Opinion Factors......................................................131

Figure 5.16 Model Data Versus Actual Data on Population Fractions of Current and 

Former Smokers............................................................................................... 132

Figure 5.17 Stock Values for Public Opinion over Time (Baseline).................................... 132

Figure 5.18 Feedback Loops Affecting Public Opinion....................................................... 133

Figure 5.19 Feedback Loops with Change in Feedback Levels........................................... 133

I l l u s t r a t i o n s
ix

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Figure 5.20 Effect of Public Opinion on Adult Uptake........................................................ 134

Figure 5.21 Effect of Public Opinion on Rate of Smoking Cessation among Adults......... 135

Figure 5.22 Causal Loops for Public Opinion and Support of Tobacco Control................ 136

Figure 5.23 Effect of Public Support for Tobacco Control on Research Fraction ............. 136

Figure 5.24 Causal Map for Research and Public Support for Tobacco Control.................137

Figure 5.25 Effect of Research on Tobacco Use....................................................................137

Figure 5.26 Effects of Translated Research on Public Opinion.......................................... 138

Figure 5.27 Effects of Translated Research on Undecided Public ...................................... 138

Figure 5.28 Percentage of Undecided Public over Time...................................................... 139

Figure 5.29 Effect of Research on Population Fraction of Smokers .................................. 139

Figure 5.30 Effects of Government Intervention on Shift from Support for Tobacco 

Control to Undecided and from Undecided to Support for Tobacco Use .........140

Figure 5.31 Effect of Government Intervention on Public Supporters of Tobacco 

Control ...............................................................................................................140

Figure 5A.1 Tobacco Use Sector............................................................................................143

Figure 5A.2 Tobacco Research and Education Sector..........................................................144

Figure 5A.3 Government Sector............................................................................................144

Figure 5A.4 Public Opinion Sector .......................................................................................145

Figure 6.1 Contact Networks for Two States with Strong Financial and Political 

Climates .............................................................................................................173

Figure 6.2 Contact Networks for Two States with Weak Financial and Political 

Climates .............................................................................................................173

Figure 6.3 Role of Informal Interactions in Referral Patterns ..........................................174

Figure 6.4 Change in Tobacco Control Program Funding for Indiana from 2002 to 

2004....................................................................................................................175

Figure 6.5 Change in Perceived Political Support for Tobacco Control from Two 

Indiana Governors, Governor Frank O’Bannon (2002) and Governor 

Joseph Kernan (2004)........................................................................................176

Figure 6.6 Change in Indiana’s Tobacco Control Contact Network Structure from 

2002 to 2004 ......................................................................................................176

Figure 7.1 Overview of a Knowledge Management and Translation Framework for 

the Health System .............................................................................................189

Figure 7.2 Conceptual Framework for Knowledge Management..................................... 190

Figure 7.3 Conceptual Framework for Knowledge Translation ........................................192

Figure 7.4 Integrated Knowledge Management and Translation Strategy Framework....195

Figure 7.5 4P-Knowledge Management and Translation Infrastructures Strategy Map... 199

Figure 7.6 4P-Knowledge Management and Translation Strategy Maps: Templates 

for Knowledge Resources Needed in Tobacco Control.....................................210

Figure 7.7 Cluster Rating Map for Tobacco Knowledge Base ............................................212

Figure 7.8 Pattern Matching to Compare Importance of Cluster Ratings in 

Demographic Subgroups of Participants..........................................................215

Figure 7A.1 4P-Knowledge Management and Translation Infrastructures Strategy Map...218

Figure 7A.2 Detailed Knowledge Management and Translation Strategy Map: 

Template for 4P-KMT and KMT Infrastructures..............................................219
x

I l l u s t r a t i o n s

Figure 7A.3 Example of Template for Detailed 4P-Knowledge Management and 

Translation Strategy Map for Production, Use, and Refinement of 

Particular Type of Knowledge ..............................................................................219

Figure 7B.1 Knowledge Management and Translation Framework in Health .................. 222

Figure 8.1 Trends over Time in Tobacco Control Strategy and Methodology ................. 228

Figure A.1 Evolution of Tobacco Control Approaches toward Systems Thinking ........... 250

Figure B.1 Common Framework for Integrating Systems Approaches............................ 266

Figure B.2 Integrated Approach that Benefits Scientists and Practitioners.................... 268

Figure B.3 Tailoring of Integrated Approaches to Specific Applications.......................... 269
xi

Foreword

As we have come to see time and time again, complexity is the hobgoblin of health policy. 

This is of course no surprise to biologists. During a time in the mid-twentieth century when 

penicillin was driving pneumonia and wound infection into retreat, and when vaccine was 

beginning to stop the polio epidemic in its tracks, the biologist Ludwig von Bertalanffy was 

proposing what came to be called “systems theory.” In some respects a direct reaction to the 

reductionist single organ system or “silver bullet” notions of disease and its control, systems 

theory emphasizes that the behavior of any entity—be it an organization, an individual, 

a human body—can only be truly understood not by focusing on the properties of its 

component parts, but by examining and characterizing the collective nature of the positions 

and relationships among the parts.

Tobacco—and the control of its use and impact—offers a splendid model for using a systems 

perspective to advantage and gleaning insights about potentially broader applications in 

health. We have for some time known that health status is the product of the dynamics at play 

within several domains of influence: our genetic predispositions, our social circumstances, 

the physical environments within which we live, the behavior patterns we choose, and the 

medical care we receive. We are also learning that often more important than what happens 

within any given domain is what happens between and among domains. How does the 

interplay of our genetic predispositions with our physical environments or behavior choices 

influence our risk for disease? How do social circumstances affect the medical care we receive 

and our responses to it? How are our behavioral choices influenced by our social and physical 

environments?

In tobacco, some of the answers to these questions are coming into closer focus—certainly 

that is the case for a stronger appreciation of the complexity. We are long past the time 

that tobacco use is purely a matter of “individual choice” and its control dependent on 

a strategy of “one-person-at-a-time.” Tax policy, school interventions, clean indoor air 

regulations, agricultural initiatives, advertising campaigns, medical care initiatives, 

community mobilization, and political action are all among the elements at work to reduce 

the use of tobacco among Americans. The results have been impressive, deriving from the 

loosely coordinated contributions of often disparate players. The challenge now is to better 

understand how these efforts work best in concert under different circumstances. If, through 

accurate characterization of the nature of the relationships at work, we can develop testable 

hypotheses about the circumstances in which elements of tobacco control are more, or less, 

effective, we can accelerate the push to the next level of tobacco control.

The Initiative on the Study and Implementation of Systems (ISIS), a four-year project 

sponsored by the National Cancer Institute (NCI), represents an innovative and potentially 

important contribution in that respect. Through ISIS, NCI has supported a careful 

exploration of four elements of systems approaches to improving tobacco control: systems 

organizing, system dynamics, system networks, and systems knowledge. This monograph 

reflects the first two years of the project. Beginning with the identification of key stakeholder 

groups—practitioners, leaders, advocates, and researchers—ISIS has carefully worked to 
xii

identify characteristics, apparent and subtle, that shape, and are shaped by, the characteristics 

of the interactions and networks both within and among stakeholder groups; the structure 

of the feedback loops involved in fostering synergy; and the role of learning as an integral 

feature of the systems at play. The lessons of that exploration are presented in this monograph 

as potential insights for the ways organization, management, adaptation, and learning might 

be enhanced for tobacco control and, by reflection, for work in other areas.

The possibilities for application to a broad range of public health challenges are clear. 

Complexity is simply the central feature to be addressed in the terms of effective engagement 

for any public health initiative. What we used to think of as the products of personal 

behavior—diet, physical activity, obesity, substance abuse, teen pregnancy, violence—we 

now know to be the dynamic results of complex physiologic, social, and environmental 

influences. Whereas we formerly thought of social circumstances as simply shaping exposures 

to health risks and complicating the ability to defend against them, we are now beginning 

to understand that they may in fact be integral components in the etiology of disease 

and disability. And rapidly occurring climate changes that interact with urbanization and 

population growth to accelerate altered ecological equilibrium, with potentially dramatic and 

irreversible implications for human health, underscore the necessity to better understand not 

only the system dynamics, but also the urgency of the mandate.

As important as are the issues presented in this monograph, equally compelling is the need 

to keep the concepts accessible and to guard against the creation of a new guild of systems 

theorists. The ISIS project has performed an important service by giving emphasis and structure 

to the reality, embodied in both physics and philosophy, that entities and actions interrelate, 

and that true understanding derives from understanding the nature of the relationships. 

This is a notion so fundamental that it must be a central feature of problem analysis, strategy 

formulation, program development, and research design in every social endeavor—not 

cordoned off as the province of those who have access to the credentials and the thesaurus.

The times are different now from when elements of systems theory were initially advanced. 

Now we have the tools from epidemiology, statistics, large-scale databases, and computational 

science that allow more structured exploration of the dynamics. But an impedance to 

progress when various academic disciplines were beginning to explore systems theory in the 

1960s may have been the inclination—typical of many academic pursuits of the time—to 

construct structures and terms that defined its separateness and limited its accessibility. The 

irony is obvious for a concept rooted in commonality.

Laudably, the ISIS project and this monograph give emphasis to the importance of 

translation, linkages, synergies, and common perspectives, as work proceeds. We should be 

grateful to NCI and the ISIS leadership for this insightful contribution.

J. Michael McGinnis, M.D., M.P.P.

Senior Scholar

Institute of Medicine

National Academy of Sciences

F o r e w o r d
xiii

Message from the Series Editor

The evolution of the Tobacco Control Monograph Series underscores its growing importance 

as a resource for researchers, practitioners, and policy makers in tobacco control as well as 

in other areas of public health. Lessons learned from tobacco prevention and control can be 

applied to a variety of public health issues, including physical activity, diet and nutrition, 

overweight and obesity, and substance abuse. The National Cancer Institute (NCI) is 

committed to disseminating this cross-cutting knowledge to the widest possible audience so 

that others can benefit from the experience of the tobacco prevention and control community. 

By so doing, NCI is increasing the evidence base for effective public health interventions and 

improving the translation of research to practice and policy.

In 1991, NCI published the first monograph in a series designed to address cutting-edge issues 

and research on tobacco control. That monograph, Strategies to Control Tobacco Use in the 

United States: A Blueprint for Public Health Action in the 1990’s, was visionary in its scope 

and focus: not only did it acknowledge that tobacco use was a complex problem that demanded 

new ways of thinking and acting, but it also encouraged expanded exploration of tobacco 

use issues by the tobacco control community. The three-axis model for the American Stop 

Smoking Intervention Study for Cancer Prevention (ASSIST), described in Monograph 1, was 

designed to address the complex interplay of varied target populations, critical channels for 

intervening (e.g., health care, schools, worksites, and community groups), and intervention 

types (e.g., mass media, program services, and policy). (See Monograph 16: ASSIST: Shaping 

the Future of Tobacco Prevention and Control and Monograph 17: Evaluating ASSIST: A 

Blueprint for Understanding State-level Tobacco Control for more details.) 

Although it did not adopt the “systems” nomenclature, Monograph 1 laid the foundation 

for this monograph (Monograph 18), which provides a new and expanded vision of tobacco 

control as a complex adaptive system. This new model encourages the tobacco control 

community to (1) collect and use vast arrays of data more effectively; (2) develop and optimize 

networks to enable the community to more efficiently address varied populations, critical 

channels for intervention, and intervention types; and (3) support the analysis of complex 

systems so that more effective strategic decisions are made. Monograph 18 builds on the 

foundation laid by Monograph 1 by explicitly encouraging (1) the development of informatics 

infrastructures and collaborative networks, (2) analysis of complex interacting variables, 

and (3) adoption of new interventions that can speed research to practice (and practice to 

research). Monograph 18, as the conceptual heir to Monograph 1, provides a new framework 

for thinking about and acting on the complex relationships among causal factors of public 

health threats, and it challenges us to consider not just whether we can more effectively use 

our knowledge of informatics and information management, networks, and complex systems, 

but whether we will use those essential tools to more rapidly benefit the public’s health. 

Stephen E. Marcus, Ph.D.

Monograph Series Editor

April 2007

xv

Preface

The world of tobacco control has become increasingly complex over the past several decades. 

It involves more extensive collaborations; new structures and configurations for coordinating 

efforts; and multilevel social, professional, and knowledge networks to improve information 

sharing for public health. Given such complexity, there has been a corresponding increased 

need to address tobacco control issues using a systems perspective that enables one to better 

understand and navigate the dynamic and evolving nature of the terrain to achieve the next 

generation of improved health outcomes.

This monograph describes the results of the initial two years of the Initiative on the Study and 

Implementation of Systems (ISIS), a four-year project. This initiative is one of the first major 

coordinated efforts to study and implement a systems thinking perspective using several 

systems approaches and methodologies that appeared to be promising for tobacco control in 

itself and as an exemplar for other complex issues in today’s public health environment. In 

the ancient, revered Egyptian myth, the goddess Isis breathed clean air into her late husband 

Osiris to restore him to life. In analogous fashion, the ISIS project hopes to contemporize the 

myth in a tobacco control context and encourage systems perspectives that have the potential 

to help people breathe cleaner air and be restored to a smoke-free life.

Although this work is aimed at the efforts of the tobacco control community, the word 

“tobacco” intentionally appears only in the subtitle of this monograph. That is because ISIS 

was a research effort that focused on the tobacco control environment to examine how to 

apply systems approaches to issues that have become endemic throughout public health, 

including the need for

n Better understanding of outcomes, including the unintended consequences of 

complex interventions and events

n Effective capture, dissemination, and management of knowledge throughout the 

multilayered public health system

n More efficient organization and linkage of the efforts of multiple, diverse stakeholders

n Adoption of evidence-based practices that inform practice and improve outcomes

n Strengthening of collaborative networks of scientists, policy makers, government 

and foundation managers, practitioners, and the public

This work was undertaken to help address some of the fundamental organizational issues in 

tobacco control and, by corollary, much of public health. The goal was to investigate the potential 

There is always an easy solution to every human problem—neat, plausible, and wrong.

—H. L. Mencken (1880–1956)
xvi

P r e f a c e

*

Committee on Quality of Health Care in America, Institute of Medicine. 2001. Crossing the quality 

chasm: A new health system for the 21st century. Executive summary. Washington, DC: National 

Academies Press. http://books.nap.edu/execsumm_pdf/10027.pdf.

of integrated, systems-based approaches to facilitate the efforts of all stakeholders to make 

substantive changes in public health outcomes. The lack of such linkages poses a particularly 

serious challenge to the public health system. For example, a 2001 Institute of Medicine report, 

Crossing the Quality Chasm, points to “a health care system that frequently falls short in 

its ability to translate knowledge into practice...”*(p3) In this view, the lack of progress is due 

to (1) a system that fosters research that does not always translate directly into outcomes in 

patients and (2) practitioners who do not often have a voice in this research community. These 

types of disconnections illustrate the need for more synergistic teamwork, within a system of 

systems, that has the potential to dramatically improve public health outcomes.

In ISIS, the term systems plays a central role. However, its definition remains elusive. 

The term has multiple manifestations and meanings in the world of tobacco control, 

encompassing everything from the structure of organizations, to the arrangement of 

networks, to the dynamics of change, to the patterning of information. The evolution of this 

project puts it squarely in the trajectory of some of the key trends in contemporary public 

health, all of which can be viewed as essentially “systems” issues:

n There is a growing macro-level focus in tobacco control and public health. A review 

of the history of tobacco control efforts shows that the earliest initiatives were aimed 

at the individual and cessation; intermediate efforts increasingly focused on the 

community level and collaborative interventions; and subsequent efforts emphasized 

larger population groups and more broad-based interventions, such as legislative 

changes, taxation, and media advocacy. A systems-level focus on tobacco control is a 

logical next step in understanding and managing the complex nature of tobacco use, 

as both an epidemiological and a personal health issue.

n There is a growing need to better integrate research and practice. The core concerns 

of putting evidence-based knowledge about tobacco control into practice and giving 

practitioners a voice in the research agenda point to a need to re-examine the basic 

paradigms of science, how it interfaces with society, and how society’s investment in 

research and development is understood.

n The tobacco control environment has, in and of itself, become a system of systems.

Understanding and navigating a landscape that includes national organizations, 

community-based advocacy groups, health practitioners, public health officials, 

researchers, funding sources, and the community itself have become the next major 

challenge in creating and implementing evidence-based practice that changes public 

health outcomes.

n The systems of systems that now characterize tobacco control are embedded within 

a larger public health context with important focal outcomes such as reduced 

morbidity and mortality. Tobacco control has had tremendous successes in reducing 
xvii

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

consumption, prevalence, morbidity, and mortality. Universally applying what we 

know would have a tremendous impact on tobacco control and disease reduction. 

Being able to do so and reaching the next level of achievements in outcomes, 

however, require a better understanding of the complex interrelationships and 

dynamics of the tobacco control system, its connections to both the public health 

system and the public, and its dynamic relationships with the industry that continues 

to generate both products and profits. 

These trends, at many levels, reflect the evolution of public health itself—from treatment of 

specific diseases, to prevention, to social and policy movements, to the study of interrelated 

factors and beyond. This monograph is the result of that evolution; its aim is to contribute 

to continued evolution by encouraging consideration and use of systems thinking in tobacco 

control and potentially in public health in general.

xix

Editors

Allan Best, Ph.D.

Principal Investigator

Senior Scientist

Centre for Clinical Epidemiology and 

Evaluation

Vancouver Coastal Health Research Institute

Clinical Professor, Health Care and 

Epidemiology

University of British Columbia

Professional Staff

British Columbia Cancer Agency

Vancouver, British Columbia, Canada

Pamela I. Clark, Ph.D.

Principal Investigator

Co-lead, Chapter 2

Senior Health Research Scientist

Battelle Centers for Public Health Research 

& Evaluation

Baltimore, MD 

Scott J. Leischow, Ph.D.

Principal Investigator

Co-lead, Chapter 2

Professor, Department of Family and 

Community Medicine

Deputy Director for Strategic Partnerships 

and Policy 

Arizona Cancer Center 

The University of Arizona 

Tucson, AZ

Stephen E. Marcus, Ph.D.

Monograph Series Editor

Epidemiologist 

Tobacco Control Research Branch

Behavioral Research Program

Division of Cancer Control and Population 

Sciences

National Cancer Institute

Bethesda, MD

William M. K. Trochim, Ph.D.

Principal Investigator

Co-lead, Chapter 3

Co-lead, Chapter 4

Professor

Policy Analysis and Management

Cornell University

Ithaca, NY 

Authors

Gabriele Bammer, Ph.D.

Co-lead, Chapter 3

Co-lead, Chapter 5

Professor

National Centre for Epidemiology and 

Population Health 

College of Medicine and Health Sciences

The Australian National University

Canberra, Australia

Hauser Center for Nonprofit Organizations

Harvard University

Cambridge, MA

This monograph was developed by the National Cancer Institute under the editorial direction 

of Stephen E. Marcus, Monograph Series Editor, and Senior Scientific Editors Allan Best, 

Pamela I. Clark, Scott J. Leischow, and William M. K. Trochim. Individual chapters of this 

monograph and the entire volume were subjected to extensive peer review and revision.

Acknowledgments
xx

Alex Berland, R.N., M.Sc.

President

A. Berland Inc.

Adjunct Professor

Department of Healthcare and Epidemiology

University of British Columbia

Vancouver, British Columbia, Canada

Derek Cabrera, Ph.D.

Co-lead, Chapter 3

Co-lead, Chapter 4

National Science Foundation Post Doctoral 

Associate in Human Ecology 

National Science Foundation/IGERT Fellow 

in Nonlinear Systems 

Cornell University 

Ithaca, NY 

Noshir Contractor, Ph.D.

Co-lead, Chapter 6

Professor

Departments of Speech Communication

and Psychology

University of Illinois at Urbana-Champaign

Urbana, IL 

William C. Horrace, Ph.D.

Associate Professor 

Department of Economics and Center for 

Policy Research

Syracuse University

Syracuse, NY 

Timothy Huerta, Ph.D. 

Scientist

Child and Family Research Institute and

Provincial Health Research Authority

Vancouver, British Columbia, Canada

Assistant Professor

Rawls College of Business

Texas Tech University

Lubbock, TX

Francis Lau, Ph.D.

Lead, Chapter 7

Associate Professor 

School of Health Information Science

University of Victoria

Vancouver, British Columbia, Canada

Douglas A. Luke, Ph.D.

Director

Center for Tobacco Policy Research

Saint Louis University School of Public 

Health

St. Louis, MO 

Bobby Milstein, Ph.D., M.P.H.

Behavioral Scientist

Syndemics Prevention Network

Centers for Disease Control and Prevention

Atlanta, GA 

Keith Provan, Ph.D.

Co-lead, Chapter 6

McClelland Professor of Public 

Administration and Policy

Director of the SPAP Ph.D. Program

School of Public Administration and Policy 

Eller College of Management

University of Arizona

Tucson, AZ

George P. Richardson, Ph.D.

Co-lead, Chapter 5

Chair

Department of Public Administration

and Policy

Nelson A. Rockefeller College of Public 

Affairs and Policy

University at Albany

State University of New York

Albany, NY 

James W. Shaw, Ph.D., Pharm.D., M.P.H.

Assistant Professor

Department of Pharmacy Administration 

and Center for Pharmacoeconomic 

Research

College of Pharmacy

University of Illinois at Chicago

Chicago, IL 

A c k n o w l e d g m e n t s
xxi

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Ramkrishnan (Ram) V. Tenkasi, Ph.D.

Professor of Organizational Change

Ph.D. Program in Organization 

Development and Change

Department of Management and 

Organizational Behavior

Benedictine University

Lisle, IL 

Reviewers

Michele Bloch, M.D., Ph.D.

Medical Officer

Tobacco Control Research Branch

Behavioral Research Program

Division of Cancer Control and Population 

Sciences

National Cancer Institute

Bethesda, MD

Jonathan P. Caulkins, Ph.D.

Professor of Operations Research and Public 

Policy

Qatar Campus, H. John Heinz School of 

Public Policy and Management 

Carnegie Mellon University 

Doha, Qatar

Tom Cummings, Ph.D.

Department Chair

Management and Organization Department

Marshall School of Business

University of Southern California

Los Angeles, CA

Susan J. Curry, Ph.D.

Director

Institute for Health Research and Policy

Professor

Health Policy and Administration

School of Public Health

University of Illinois, Chicago

Chicago, IL 

Samuel R. Friedman, Ph.D.

Senior Research Fellow

Director, Social Theory Core

Center for Drug Use and HIV Research

National Development and Research 

Institutes, Inc.

New York, NY

Russell E. Glasgow, Ph.D.

Senior Scientist

Clinical Research Unit

Kaiser Permanente 

Aurora, CO

Linda M. Harris, Ph.D.

Senior Health Communication Scientist

Health Communication and Informatics 

Research Branch

Behavioral Research Program

Division of Cancer Control and Population 

Sciences

National Cancer Institute

Rockville, MD

William S. (Bill) Harris Jr.

Principal

Facilitated Systems 

Everett, WA 

Jack B. Homer, Ph.D.

Homer Consulting

Voorhees, NJ

Corinne Husten, M.D., M.P.H.

Acting Director 

Office on Smoking and Health

Centers for Disease Control and Prevention 

Atlanta, GA

David M. Introcaso, Ph.D.

Health Policy Analyst

Office of Health Policy Research and Planning

Office of the Assistant Secretary for Planning 

and Evaluation

U.S. Department of Health and Human 

Services

Washington, DC
xxii

Brick Lancaster, M.A., CHES

Chief

Program Services Branch

Office on Smoking and Health

Centers for Disease Control and Prevention

Atlanta, GA 

Ken McLeroy, Ph.D.

Associate Dean for Academic Affairs

School of Rural Public Health

Texas A&M Health Science Center

College Station, TX

Gerald Midgley, Ph.D.

Professor

Institute of Environmental Science

and Research

Christchurch Science Centre

Christchurch, New Zealand

John Millar, M.D.

Executive Director

Population Health Surveillance & Disease 

Control Planning

Provincial Health Services Authority

Vancouver, British Columbia, Canada 

Jonathan A. Morell, Ph.D.

Senior Policy Analyst

NewVectors

Ann Arbor, MI 

David Mowat, M.B.Ch.B., M.P.H., F.R.C.P.C.

Deputy Chief Public Health Officer

Public Health Practice and Regional 

Operations

Public Health Agency of Canada

Ottawa, Ontario, Canada

Diana Newman, Ed.D., R.N.

Professor

School of Nursing

Massachusetts College of Pharmacy and 

Health Sciences

Boston, MA

Brian Oldenburg, Ph.D.

Professor and Chair

International Public Health

Department of Epidemiology and 

Preventive Medicine

Monash University

Melbourne, Australia

C. Tracy Orleans, Ph.D.

Senior Scientist and Distinguished Fellow

Robert Wood Johnson Foundation

Princeton, NJ

William A. Pasmore, Ph.D.

Partner

Mercer Delta Organizational Consulting

New York, NY

Peter Robertson, Ph.D.

Associate Professor

School of Policy, Planning, and Development

University of Southern California

Los Angeles, CA 

Khalid Saeed, Ph.D.

Professor of Economics

Department Head

Social Science and Policy Studies

Worcester Polytechnic Institute

Worcester, MA

Gregory J. Sherman, Ph.D.

Senior Health Architect

Science and Research Advisory Unit

Office of Public Health Practice

Public Health Agency of Canada

Ottawa, Ontario, Canada

Glorian Sorensen, Ph.D., M.P.H.

Professor

Harvard School of Public Health

Director

Center for Community Based Research

Dana-Farber Cancer Institute

Boston, MA 

A c k n o w l e d g m e n t s
xxiii

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Stephen Taplin, M.D., M.P.H.

Senior Scientist

Applied Research Program

Division of Cancer Control and Population 

Sciences

National Cancer Institute

Bethesda, MD

Thomas W. Valente, Ph.D.

Associate Professor and Director

Master of Public Health Program

Department of Preventive Medicine

School of Medicine

University of Southern California

Alhambra, CA 

K. Viswanath, Ph.D. 

Associate Professor

Department of Medical Oncology

Dana-Farber Cancer Institute

Associate Professor

Department of Society, Human 

Development, and Health

Harvard School of Public Health

Harvard University

Boston, MA

Saul Weingart, M.D., Ph.D.

Vice President for Patient Safety

Dana-Farber Cancer Institute

Boston, MA

Bob Williams 

Wellington

Aotearoa, New Zealand

Derek Yach, M.B.Ch.B., M.P.H.

Director

Health Equity

The Rockefeller Foundation

New York, NY

The editors wish to acknowledge the 

contributions of the following individuals

to the ISIS project:

Lawrence W. Green, Dr.P.H.

Adjunct Professor

Department of Epidemiology and 

Biostatistics

Co-Leader

Society, Diversity and Disparities Program

Comprehensive Cancer Center

University of California at San Francisco

San Francisco, CA 

Jack Henningfield, Ph.D.

Vice President for Research and Policy 

Pinney Associates

Professor

Behavioral Biology 

Johns Hopkins School of Medicine

Baltimore, MD

Peter Robertson, Ph.D.

Associate Professor

School of Policy, Planning, and Development

University of Southern California

Los Angeles, CA 

Carol L. Schmitt, Ph.D.

Senior Health Research Scientist

Battelle Centers for Public Health Research 

& Evaluation

Baltimore, MD

Frances A. Stillman, Ed.D.

Co-Director

Institute for Global Tobacco Control

Associate Professor

Department of Epidemiology

Bloomberg School of Public Health

Johns Hopkins University

Baltimore, MD 
xxiv

The editors would like to acknowledge the 

contributions of the following staff who 

provided technical and editorial assistance 

in the preparation of this monograph:

Jennifer S. Brown, M.A.

Ph.D. Candidate

Department of Human Development

Cornell University

Ithaca, NY

Richard S. Gallagher

Chief Science Writer

R.S. Gallagher and Associates

Newfield, NY

Snjezana Huerta-Kralj

Project Coordinator and Research Assistant

Department of Psychology

Simon Fraser University

Burnaby, British Columbia, Canada

Gregg Moor

Project Coordinator 

UBC Institute for Health Promotion 

Research

Centre for Clinical Epidemiology & 

Evaluation

Vancouver Coastal Health Research Institute

Vancouver, British Columbia, Canada

April Roggio

Research Assistant

Department of Public Administration and 

Policy

Nelson A. Rockefeller College of Public 

Affairs and Policy

University at Albany

State University of New York

Albany, NY

In addition, the editors wish to acknowledge 

and thank those who participated in the 

brainstorming and planning process leading 

to the ISIS project as well as the many 

others who shared their insights with the 

ISIS project.

Last, the editors would like to acknowledge 

the publication support services provided for 

this monograph:

American Institutes for Research

Margot Raphael, Project Director

Elizabeth Bruce, Monograph Editor

Michael Rollins and Matthew Mowczko, 

Production Artists

Cygnus Corporation

Terry Kelly, Publications Manager

Ruth Christie, Copyeditor

Mary Bedford, Proofreader 

A c k n o w l e d g m e n t s
xxv

Acronyms

4P-KMT Four P-knowledge management and translation 

ACS American Cancer Society

ALA American Lung Association

ASSIST American Stop Smoking Intervention Study for Cancer Prevention

caBIG Cancer Biomedical Informatics Grid

CAS complex adaptive systems

CBPR community-based participatory research

CDC Centers for Disease Control and Prevention

CHP Consumer Health Profiles

CISNET Cancer Intervention and Surveillance Modeling Network

COMMIT Community Intervention Trial for Smoking Cessation

DHHS U.S. Department of Health and Human Services

FCTC Framework Convention on Tobacco Control

FY fiscal year

GTRN Global Tobacco Research Network

ISIS Initiative on the Study and Implementation of Systems

KMT knowledge management and translation

KTNs knowledge-translation networks

LGIs large-group interventions

MDS multidimensional scaling

MSA Master Settlement Agreement and Amendments

NCI National Cancer Institute

NIH National Institutes of Health

PLANET Plan, Link, Act, Network with Evidence-based Tools

SEER Surveillance, Epidemiology, and End Results

SES socioeconomic status

SoTC Strength of Tobacco Control

TTURC Transdisciplinary Tobacco Use Research Center

1

1

Overview

Tobacco control and public health have evolved into a complex set of interconnected and 

largely self-organizing systems. Their components include international, national, and 

local governmental agencies; individual advocacy groups; policy makers; health care 

professionals; nonprofit foundations; and the general population itself. The issues require 

the exploration of approaches and methodologies that speak to the evolving, dynamic 

nature of this systems environment.

This monograph focuses on the first two years of the Initiative on the Study and 

Implementation of Systems (ISIS), which was funded by the National Cancer Institute 

to examine the potential for systems thinking in tobacco control and public health. ISIS 

explored the general idea of a systems thinking rubric encompassing a great variety 

of systems-oriented methodologies and approaches. Four approaches have particular 

promise for their applicability to tobacco control and public health and thus were chosen 

as areas for initial investigation: (1) organizing and managing as a system, (2) system 

dynamics and how to model those dynamics, (3) system networks and their analysis, and 

(4) systems knowledge and its management and translation. 

As a transdisciplinary effort that linked both tobacco control stakeholders and systems 

experts, ISIS combined a number of exploratory projects and case studies within these 

four approaches with a detailed examination of the potential for systems thinking in 

tobacco control. Its end product was a set of expert consensus guidelines for the future 

implementation of systems thinking and systems perspectives for tobacco control and 

public health.
2

1 . O v e r v i e w

Introduction

Tobacco use remains a leading cause of 

preventable death. Even though reductions 

in the prevalence of tobacco use and 

cigarette consumption over the past four 

decades have been substantial, tobacco use 

continues to be a major challenge for public 

health.1–3 With the recent development 

of clear, evidence-based best practices in 

tobacco control, along with funding new 

research to better understand the complex 

and changing tobacco environment, the 

potential exists to improve public health 

outcomes substantially in the future.

However, the promise of implementing 

demonstrably effective tobacco control 

initiatives to achieve greater gains in health 

outcomes remains only partly realized. 

Strong scientific evidence exists for effective 

tobacco control practices. Nonetheless, 

desired outcomes remain at levels far lower 

than what is achievable in areas such as 

the prevalence of tobacco use and product 

consumption and related morbidity and 

mortality.2,4 This situation is attributable to 

numerous factors, ranging from multiple 

diverse stakeholders, to declining funding, 

to the systematic efforts of the tobacco 

industry to undermine the efforts of the 

tobacco control community.

It is increasingly apparent that the 

implementation and, more important, the 

integration of systems approaches (e.g., 

systems organization, system dynamics, 

system networks, and systems knowledge) 

have the potential to significantly enhance 

the efforts of groups of tobacco control 

stakeholders to improve outcomes 

associated with tobacco control initiatives 

(e.g., increased smoking cessation, 

reduced initiation to tobacco use, and 

above all, reduced morbidity and mortality 

associated with smoking).5 These efforts, 

applied to tobacco control practices, can 

be an essential foundation for creating a 

new, scientifically credible framework for 

future public health efforts.

The ISIS project was undertaken to examine 

the value and potential impact of systems 

thinking for tobacco control, both to 

improve its outcomes and as a template 

for strategies to apply these methods to 

other public health issues. This monograph 

describes the findings of the first two 

years of this project and their potential 

implications for tobacco control and public 

health. The monograph examines the 

synthesis of four key systems approaches 

applied to the fundamental problems of 

tobacco control (figure 1.1):

1. Systems organizing to understand and 

foster the development of participatory, 

complex, and adaptive collaborative 

systems in tobacco control; ensure their 

effective facilitation and management; 

and encourage productive system action 

and learning

2. System dynamics to understand and 

model the complex dynamic interactions 

involved in the tobacco control system 

and among the factors influencing tobacco 

use, including political actions such as 

taxes and legislation, research advances, 

tobacco control activities, industry 

forces, and social and cultural factors

3. System networks to understand 

and analyze effective collaborative 

relationships among stakeholders, 

improve collaboration strategies, and 

help reduce duplication of effort

4. Systems knowledge to develop and 

manage the knowledge infrastructure 

required for effective dissemination 

and evolution of scientifically credible, 

evidence-based practices, together with 

an effective strategy to package, deliver, 

and maintain this knowledge

Most important, integration of these systems 

approaches promises to help in the creation 
3

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

of a more consistent and adaptive researchbased infrastructure for effective tobacco 

control and, by corollary, for public health 

in general. The ISIS project is an important 

step in bringing such an environment to 

fruition and, in turn, changing the practice 

of tobacco control to take the next step to 

improve health outcomes.

Monograph Framework

This monograph is structured as a discussion 

of the core issues in systems thinking 

for tobacco control, followed by detailed 

consideration of specific systems approaches 

and their potential synthesis, together with 

consensus guidelines for future systems 

efforts in tobacco control and public health. 

The monograph’s core areas include

n An overview of the state of tobacco 

control and the potential for using 

systems thinking approaches to address 

future tobacco control issues;

n A detailed examination of four initial 

systems thinking approaches chosen for 

potential applicability to tobacco control 

and public health: systems organizing 

and management, system dynamics and 

its modeling, system network analysis, 

and systems knowledge management and 

translation; and

n A look at the potential areas of synthesis 

among these and other systems approaches 

and methods. The general rubric of systems 

thinking is used, together with guidelines 

for exploring how a future systems 

thinking environment for tobacco control 

can affect each of the major stakeholders 

Figure 1.1 Model of Stakeholder Groups and Systems Approaches in Tobacco Control

Integrated Systems 

Approaches to

Tobacco Control

Systems

Organizing

Systems

Knowledge

System

Networks

Advocates

– Harness global efforts

– Share efforts/approaches

– Develop shared purpose

Researchers

– Transdisciplinary approach

– More complex issues

– Linkage with stakeholders

System

Dynamics

Practitioners

– Voice in research

– Network with others

– Improved outcomes

Leaders

– Break down silos of activity

– Build infrastructure

– Create systems processes
4

1 . O v e r v i e w

in tobacco control and potentially improve 

public health outcomes.

Chapter 2, “Tobacco Control at a Crossroads,” 

examines the state of tobacco control, the 

immediate context for exploring systems 

thinking within this area, and the evolution 

of tobacco control efforts. It tracks the 

development of current views of tobacco 

use and discusses systems approaches as the 

logical next step in addressing tobacco use. 

Chapter 3, “Systems Thinking: Potential to 

Transform Tobacco Control,” then lays out 

the case for the four broad systems thinking 

approaches examined within this project. 

The chapter summarizes the value of systems 

thinking, the approaches and issues that 

drive systems thinking, and the potential 

of systems thinking to change outcomes in 

tobacco control. In the process, the chapter 

examines the research underpinnings of 

a variety of systems thinking methods, 

including system dynamics modeling, 

network analysis, knowledge management, 

systems organizing and management, and 

the synthesis of these and other approaches. 

Chapter 4, “How to Organize: Systems 

Organizing,” examines the management, 

operational, and logistic aspects of working 

in a diverse systems environment involving 

multiple stakeholders. This section explores 

the view that systems thinking is becoming 

an integral feature of contemporary 

management. It presents a model for 

systems organizing that encompasses 

and extends the traditional management 

model around a systems framework of 

vision, structure, action, and learning. It 

also examines current thinking in crossorganizational systems, including the use of 

participatory mixed methods for planning 

and evaluation that integrate with a systems 

approach, together with the concept 

of effective complex adaptive systems 

for tobacco control and public health, 

illustrating systems organizing principles 

with several empirical case studies. 

Chapter 5, “How to Anticipate Change in 

Tobacco Control Systems,” follows this 

organization framework with a look at the 

specifics of modeling public health issues as 

a system to better understand them and plan 

more effective interventions. This chapter 

focuses on understanding the nature of 

system dynamics, including the development 

of dynamic models that include feedback 

processes and the use of system dynamics 

modeling as a technology for understanding 

tobacco control outcomes, together with 

results from a study developing a system 

dynamics representation of tobacco control 

variables and simulation of the aging chain 

of smokers.

Chapter 6, “Understanding and Managing 

Stakeholder Networks,” explores system 

network theory and methods, examining 

the question of “who works with whom” in 

a system and how organizations are brought 

together based on concepts of network 

analysis and related approaches. It also 

examines applications of network analysis 

to improve community and public health 

collaboration, including a case study of 

network analysis for evaluation of tobacco 

control. 

Chapter 7, “What We Know: Managing the 

Knowledge Content,” focuses on the role 

of managing systems knowledge content, 

including research findings on knowledge 

management issues for health care 

environments, the results of a knowledge 

management review project to evaluate 

existing research dissemination efforts at the 

National Cancer Institute, recommendations 

for a general knowledge infrastructure 

for tobacco control efforts, and a systemsoriented conceptual modeling project used 

to develop the taxonomy for a tobacco 

control knowledge base.

The monograph closes in chapter 8, 

“Synthesis and Conclusions,” by examining 

the critical issue of integrating component 

systems thinking disciplines within a 
5

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

broader framework of systems thinking 

in tobacco control. The chapter explores 

synergies across the areas studied in this 

project, existing trends toward systems 

approaches, and common methodological 

elements, together with consensus 

guidelines summarized in the “Major 

Conclusions” section of this chapter.

Two appendices describe the project’s 

history and its formative decisions, as well 

as a potential framework for implementing 

systems thinking approaches in the real 

world of tobacco control.

Summary

To work efficiently and effectively in 

today’s tobacco control environment, the 

tobacco control community must explore 

the systems methodologies that drive the 

competitiveness of the private sector. Such 

methodologies have strong potential for 

successful translation of science into practice 

and the achievement of desired outcomes. 

The goal of the first two years of the ISIS 

project was to take a critical first step toward 

bringing this potential to fruition.

The ISIS project represents a significant 

step in investigating approaches for 

systems thinking to improve outcomes of 

tobacco control efforts. It also serves as the 

framework for a new, rigorous approach 

to other public health issues. The findings 

and lessons learned in the first two years 

of this project were synthesized by its core 

members as a set of consensus guidelines for 

the future exploration and implementation 

of systems thinking approaches in tobacco 

control. The following “Major Conclusions” 

section and chapter 8 summarize these 

guidelines, which emphasize systems 

thinking as an ecological process rather 

than a cluster of methodologies.

The benefits of an integrated systems 

approach to tobacco control can go far 

beyond dollars and cents, to the estimated 

1,200 people per day in the United States 

who die prematurely from smoking-related 

causes, according to the Centers for Disease 

Control and Prevention.2 The vision is that 

by integrating technologies that address 

systems organizing, system dynamics, 

system networks, and systems knowledge in 

a framework of systems thinking, tobacco 

control organizations will be able to work 

more effectively and collaboratively and 

use evidence-based best practices more 

effectively in the field. More important, this 

effort leverages current systems research to 

create a bold new approach to integrating 

science and practice to achieve desired 

health outcomes.

Major Conclusions

1. Tobacco control is at a crossroads 

because tobacco use is increasingly 

recognized as a complex adaptive system 

involving biological, behavioral, and 

environmental influences.

2. Systems thinking has the potential to 

transform tobacco control research, 

practice, and policy by improving 

collaboration and by providing a more 

dynamic and adaptive evidence base for 

practice and a deeper knowledge about 

the impact of tobacco prevention and 

control activities.

3. Systems organizing encourages the 

transformation to a systems culture 

by addressing the core issues: vision 

and paradigm, barriers, leadership, 

and the need for an ongoing learning 

environment for systems thinking. Such 

an environment encompasses a wide 

variety of structured group processes, 

many of which may involve quantitative 

frameworks. Systems organizing 

implies a synthesis of the classic linear 

management processes of planning, 

organizing, leading, and controlling with 

a more adaptive environment expressed 
6

1 . O v e r v i e w

around concepts of vision, structure, 

action, and learning.

4. System dynamics encompasses 

qualitative and mathematical simulation 

approaches to model dynamic 

relationships that evolve over time, 

and can simulate behavior including 

possible unintended consequences and 

long-term effects. Efforts to develop 

and apply systems methods and 

processes involve theory and research 

development, mixed-methods systems 

thinking, and participatory assessment 

of systems needs. At a practical level, 

the infrastructure for system dynamics 

is addressed by fostering an ecological 

perspective on implementation, as well 

as a systems approach to evaluation.

5. System networks of tobacco control 

stakeholders form a foundation for a 

systems environment in tobacco control, 

replacing “silos” with linkages of people 

and resources that transcend geography 

and discipline. This process involves 

building and maintaining stakeholder 

relationships by creating networks 

of stakeholders for systems thinking, 

studying the dynamics and effects of 

these networks, linking disciplines of 

stakeholders in tobacco control, and 

preparing for the impact of demographic 

change.

6. Systems knowledge management and 

translation form a key component of 

systems approaches for tobacco control, 

examining purpose, people, process, and 

products within a broader knowledge 

infrastructure. This involves building 

system and knowledge capacity by 

expanding public health data, integrating 

information silos, fostering the skills and 

culture to affect processes and outcomes, 

and creating networks for knowledge 

translation.

7. Integration and synthesis of systems 

approaches are key to a systems 

thinking environment for tobacco 

control, moving toward a more adaptive 

system that changes public health 

outcomes. Approaches such as systems 

organizing, system dynamics modeling, 

network methods, and knowledge 

management contain synergies in areas 

ranging from participatory stakeholder 

networks to simulation and knowledge 

environments. Achievement of this goal 

involves creating a vision, developing 

capacity, building planning models, and 

establishing meaningful and adaptive 

evaluation measurements.

8. Capacity building for systems thinking 

touches on the resources needed for 

bringing a systems thinking environment 

to fruition in tobacco control. These 

include fundamental infrastructure 

issues such as creating networks and 

linking them with systems knowledge 

in other fields, as well as specific action 

items such as creating systems curricula 

for academia and national professional 

associations, and holding conferences for 

systems thinking in public health.

Chapter Conclusions

Chapter 2. Tobacco Control at a 

Crossroads

1. The prevalence of smoking among adults 

has been reduced by approximately 

one-half since 1950. However, tobacco 

use remains the nation’s leading 

cause of premature preventable death. 

The success of efforts to reduce the 

prevalence of adult smoking to the 

Healthy People 2010 goals of 15% or less 

remains elusive. 

2. Increasingly, tobacco use is seen as 

a population-level health problem 

that involves forces from the tobacco 

industry, current tobacco users and 

nonusers, and the environment. 

3. Tobacco control efforts have evolved 

from a focus on individual interventions 
7

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

toward population-level interventions, 

as the nature of tobacco use has become 

better understood. These efforts have 

evolved into a complex system involving 

multiple stakeholders and environmental 

factors, ranging from social attitudes 

toward smoking to the countervailing 

efforts of the tobacco industry.

4. Some research findings suggest that 

systems approaches are critical to 

further substantive gains in tobacco 

control. The success of early tobacco 

control efforts at the population level 

gives impetus to further exploration of 

this hypothesis.

Chapter 3. Systems Thinking: Potential 

to Transform Tobacco Control

1. The key challenges in tobacco control and 

public health today are fundamentally 

systems problems, involving multiple 

forces and stakeholders. Systems thinking 

is an innovative approach to address these 

challenges and improve health outcomes.

2. Numerous frameworks exist for systems 

thinking, a concept that encompasses a 

broad synthesis of systems approaches. 

These approaches provide a theoretical 

basis for applying specific systems 

methods, such as system dynamics 

modeling, structured conceptualization, 

and network analysis.

3. The Initiative on the Study and 

Implementation of Systems encompasses 

four key areas of systems thinking, and 

their integration: how people organize 

(managing and organizing as a system); 

how people understand dynamic 

complexity (system dynamics modeling); 

who people are (network analysis); 

and what people know (knowledge 

management and knowledge transfer).

4. Examination of systems approaches has 

the potential to address key questions and 

problems faced by the various stakeholder 

groups involved in tobacco control.

5. Potential benefits of systems thinking 

in tobacco control include improving 

collaboration among stakeholders; 

harnessing resources toward evidencebased practice; eliminating duplication 

of effort; and gaining deeper knowledge 

about the impact of tobacco control 

activities.

Chapter 4. How to Organize: Systems

Organizing

1. Systems organizing implies a move away 

from the classical linear management 

processes of planning, organizing, 

leading, and controlling toward a more 

adaptive, participatory environment 

expressed here around the concepts of 

vision, structure, action, and learning:

n Vision encompasses a move from 

an environment of leading and 

managing to one of facilitating and 

empowering.

n Structure encompasses a move from 

organizing to self-organizing.

n Action encompasses a move from 

delegation to participation.

n Learning encompasses a move from 

discrete evaluation to continuous 

evaluation.

2. Two concept-mapping projects explored 

key areas of organizing as a system. One 

project, examining issues in accelerating 

the adoption of cancer control research 

into practice, yielded clusters of action 

items in areas of research, practice, policy, 

and partnerships. The other project 

examined components of strong local 

and state tobacco control programs and 

provided the framework for a logic model 

of process and outcome ranging from 

near-term to long-term objectives.

Chapter 5. How to Anticipate Change in 

Tobacco Control Systems

1. Tobacco control consists of dynamic 

relationships over time and requires 
8

1 . O v e r v i e w

approaches, such as system dynamics 

modeling, that can address such dynamics.

2. Understanding of tobacco control and 

public health issues has evolved from 

simple cause-and-effect studies and logic 

models to more complex, ecological 

problems that involve feedback and 

evolving behavior.

3. System dynamics uses mathematical 

simulation approaches based on stocks, 

flows, and feedback loops, which can 

model system structures and simulate 

future system behavior, including 

possible unintended consequences and 

long-term effects.

4. Demonstration projects, such as the 

system dynamics simulation of tobacco 

prevalence and consumption developed 

for the Initiative on the Study and 

Implementation of Systems, show the 

potential to model and simulate future 

tobacco issues to design more effective 

interventions.

5. Opportunities are likely to surface for 

integrating system dynamics modeling 

and other systems thinking approaches 

at epistemological and methodological 

levels. Systems approaches can and 

should integrate within a larger systems 

thinking environment encompassing 

components such as systems organizing, 

networks, and knowledge management.

Chapter 6. Understanding and Managing 

Stakeholder Networks

1. Solving complex future issues in tobacco 

control will require replacing silos of 

information and activity with greater 

linkage of tobacco stakeholders through 

networks.

2. Networks of tobacco control stakeholders 

form a foundation of the systems 

environment envisioned for the future 

of tobacco control. Many components of 

a systems approach are built around the 

presumption of stakeholder networks 

that span multiple levels of tobacco 

control activity and transcend geography 

and discipline. These components 

include building organizational capacity; 

participatory approaches to planning, 

implementation, and evaluation; 

optimization of resources and effort; and 

dissemination of knowledge and best 

practices. 

3. Network analysis holds the potential for 

facilitating understanding and strategic 

management of linkages between 

stakeholder groups.

4. Numerous theories of network behavior 

currently coexist, and core concepts 

that describe networks now have broad 

acceptance, particularly those related to 

network attributes and behavior.

5. Network applications in public health 

are at an early stage. However, they 

have shown promise in recent studies, 

particularly in areas where disparate 

organizations have a common goal. 

Recent tobacco control applications of 

networks include the North American 

Quitline Consortium and Global Tobacco 

Research Network.

6. Network attributes potentially serve 

as a measure of the health of tobacco 

control efforts, as evidenced by a case 

study correlating network centrality with 

the strength of political and financial 

support for tobacco control.

7. In the future, tobacco control programs 

could consist of multiple networks with 

specific functional objectives, linked in 

turn as part of a “network of stakeholders.”

Chapter 7. What We Know: Managing 

the Knowledge Content

1. Effective knowledge management is 

based on a social context revolving 

around knowledge production, use, 

and refinement, as well as an ecological 

context based on audience, motivations, 

and mechanisms.
9

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

2. A formal strategy for knowledge 

management is essential to the creation 

of a consistent knowledge environment. 

One framework defines knowledge 

capabilities in terms of purpose, people, 

process, and products, together with a 

knowledge management and translation 

infrastructure defined in terms of its 

underlying organization, technology, 

information, and finance infrastructures.

3. A review of resources for tobacco control 

knowledge at the National Cancer 

Institute confirmed the existence of 

extensive resources for tobacco control, 

combined with growth areas for the 

future, such as integration, visibility 

among stakeholders, and knowledge gaps.

4. A concept-mapping project that 

engaged stakeholders to examine 

specific information needed for tobacco 

prevention, control, or research yielded 

clusters of knowledge categories that 

helped form the taxonomy for a planned 

knowledge base for tobacco control.

References 

1. U.S. Department of Health and Human 

Services. 2000. Reducing tobacco use: A 

report of the Surgeon General. Atlanta: U.S. 

Department of Health and Human Services, 

Centers for Disease Control and Prevention, 

National Center for Chronic Disease 

Prevention and Health Promotion, Office 

on Smoking and Health.

2. Centers for Disease Control and Prevention. 

2002. Annual smoking-attributable 

mortality, years of potential life lost, and 

economic costs: United States, 1995–1999. 

Morbidity and Mortality Weekly Report 51 

(14): 300–303. 

3. U.S. Department of Health and Human 

Services. 2004. The health consequences 

of smoking: A report of the Surgeon 

General. Atlanta: U.S. Department of 

Health and Human Services, Centers for 

Disease Control and Prevention, National 

Center for Chronic Disease Prevention 

and Health Promotion, Office on Smoking 

and Health.

4. Centers for Disease Control and Prevention. 

2004. Cigarette smoking among adults—

United States, 2002. Morbidity and 

Mortality Weekly Report 53 (20): 427–31. 

5. Best, A., R. Tenkasi, W. Trochim, 

F. Lau, B. Holmes, T. Huerta, G. Moor, 

S. Leischow, and P. Clark. 2006. Systemic 

transformational change in tobacco control: 

An overview of the Initiative for the Study 

and Implementation of Systems (ISIS). 

In Innovations in health care: A reality 

check, ed. A. L. Casebeer, A. Harrison, and 

A. L. Mark, 189–205. New York: Palgrave 

Macmillan.

11

2

Tobacco Control at a Crossroads

This chapter outlines key issues defining the state of tobacco control at the beginning 

of the twenty-first century and introduces the systems approaches under study in 

the Initiative on the Study and Implementation of Systems (ISIS) to improve public 

health outcomes related to tobacco use. The problem of tobacco use is discussed 

within a framework of the interaction of product, person, the tobacco industry, and the 

environment in which all exist. The chapter also discusses population-level efforts as early 

systems models for tobacco control, as well as some of the issues that frame the use of 

systems methods. The chapter concludes that the interaction of complex factors points to 

the need for a strategic systems approach to support future reductions in the prevalence 

of tobacco use.

For thy sake, tobacco, I would do anything but die.

—Charles Lamb (1775–1834)
12

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

Introduction

The need for systems approaches in tobacco 

control is largely framed by trends in the 

evolution of tobacco control and public 

health over the last few decades. These 

trends, and their role as a backdrop to the 

systems approaches addressed by ISIS, are 

examined here. Subsequent chapters present 

the argument for these systems approaches 

and explore them in more detail in a public 

health context. This chapter discusses (1) how 

the scientific view of tobacco use evolved 

from a model focused on individual behavior 

to a broader model that considers the full 

complexity of the problem and (2) how that 

evolution leads to a global systems orientation 

toward eradication of tobacco use.

Tobacco use is the most important preventable 

cause of disability and death in the United 

States1 and is a risk factor for four of the five 

leading causes of death (heart disease, cancer, 

chronic obstructive lung disease, and stroke).2

Analysis of the number of tobacco-related 

deaths from all causes during the 1997–2001 

period shows that cigarette smoking was 

responsible for approximately 438,000 deaths 

each year in the United States.3 Cigarettes and 

other tobacco products are highly engineered 

to create and maintain dependence. Many 

of the compounds in cigarette smoke are 

toxic, mutagenic, or carcinogenic.2 Use of 

these products has long-term public health 

and economic consequences. Successful 

prevention of tobacco use and its associated 

morbidity and mortality is a national priority; 

it can also illustrate best practices and 

approaches to addressing other major public 

health problems. 

Tobacco control research and practice 

have led to significant public health 

accomplishments in the past half-century. 

The prevalence of smoking among U.S. men 

decreased from nearly 60% in the 1950s 

to 24% in 2005.4 During the same period, 

smoking prevalence among U.S. women 

decreased from approximately 30% to 18%.4

Because tobacco use is the most important 

modifiable risk factor for chronic disease 

and early mortality, this represents a major 

victory for public health. 

However, tobacco control is now at a critical 

juncture. Previous successes may be in 

jeopardy because of systematic barriers to 

tobacco control efforts. An ever-vigilant 

and highly profitable tobacco industry has 

become more sophisticated in its approach to 

marketing tobacco products and developing 

new marketing schemes and products that 

outstrip the responsiveness of tobacco 

control research and practice. Moreover, in 

some cases, research funds are being shifted 

to other health priorities, such as obesity.5

Healthy People 2010 provides the United 

States with a comprehensive, nationwide 

health promotion and disease prevention 

agenda. Among the many objectives to be 

achieved by 2010 are to reduce the adult 

smoking prevalence to 12% and to reduce 

high school student smoking prevalence 

to 16%.6 However, it does not appear that 

the nation will meet these goals. More than 

45 million U.S. adults are current cigarette 

smokers,4 and each day, approximately 

4,000 young people between the ages of 

12 and 17 years initiate cigarette smoking.7

Worldwide prevalence of smoking is 

increasing and, if current trends continue, 

tobacco use will become the leading global 

cause of death within 30 years.8

Tobacco manufacturers spent more than 

$15 billion in 2003 to advertise and promote 

tobacco products.9 However, combined 

public and private resources for tobacco 

control amount to only a small fraction of 

this figure, and tobacco control initiatives 

are often fragmented. Additionally, 

because funds from tobacco taxes and 

other related sources often help sustain 

vital governmental infrastructure, the 

incentives to reduce or eliminate tobacco 

use and tobacco-related harm may not be as 
13

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

strong as they should be, despite tobacco’s 

enormous negative impact on society.10 The 

slow progress in tobacco control is likely due 

to many complex and overlapping factors 

that must be better understood if more 

effective action is to be taken.

Societal and environmental factors have 

continuously changed both tobacco use 

and the tobacco control environment. The 

resource-rich tobacco industry has paid 

close attention to the myriad intersecting 

threats to its business, with the aim 

of maintaining or increasing sales and 

undermining industry critics. The continued 

existence of the industry depends heavily 

on its ability to counter antitobacco efforts. 

The companies continue to invest billions 

of dollars in advertising and promotion, 

including payments to retailers.11 They 

have advocated for state laws that 

preempt the ability of local communities 

to enact evidence-based tobacco control 

measures.12,13 Tobacco use permeates the 

popular media, competing with the growing 

efforts of antitobacco advocates to decrease 

the acceptability of tobacco use.14–16

The battle against tobacco use has resulted in 

substantial victories. Today, more than onehalf of all adults who have ever smoked have 

quit.17 However, to increase the proportion 

of former smokers, more efficacious 

behavioral and pharmacological therapies 

must be developed and community and 

policy interventions need to be improved. In 

both clinical and community environments, 

translating research efficacy into real-world 

effectiveness is essential. For example, the 

efficacy of nicotine replacement therapy has 

been shown in numerous studies; however, 

these medications are often not used in the 

real world as they were in clinical trials.18–20

As a result, changing nicotine replacement 

therapies from prescription to over-thecounter status does not seem to have had 

the predicted population effect.21 Research 

is needed to better understand and address 

this issue.

To more effectively counter the tobacco 

industry’s efforts, the tobacco control 

community must become better organized. 

Tobacco control resources must be used 

more judiciously and include approaches 

that have the greatest strategic effect in a 

system that optimizes the outcomes of all 

efforts. This goal of being more effective in 

practice is inexorably linked to construction 

of a more integrated system of scientific 

discovery, development, and delivery. 

Need for a New 

Approach 

Most twentieth century research has been 

driven by reductionism, the process of 

attempting to understand a problem by 

first deciphering its components.22 The 

result has been an attempt to grasp the 

whole of tobacco use and tobacco control 

by understanding the parts, including 

the biological basis of nicotine addiction, 

the structure and function of cigarettes, 

the advertising and marketing of tobacco 

products, the economics of tobacco use, and 

the effectiveness of different tobacco control 

programs. Much has been learned about 

these dissociated aspects of tobacco use and 

tobacco control. However, few strides have 

been made in understanding the whole or in 

reducing tobacco use through systemwide 

change. Barabási puts it well: “Riding 

reductionism, we run into the hard wall of 

complexity.”22(p6) A new paradigm must be 

adopted to address the complexities and 

ultimately improve the health of the public. 

Because of the complex problems involved, 

systems thinking is needed in tobacco 

control efforts.

Tobacco Use as a Complex 

System

To illustrate that population-level tobacco 

use and control involve a complex system, 

it is helpful to think in terms of the 
14

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

system of tobacco products: the industry 

that produces, distributes, and promotes 

the use of its products, and the people or 

populations who start, maintain, and stop 

using tobacco, or are harmed by exposure 

to secondhand smoke. In addition, the 

system includes the environment that helps 

to promote or prevent tobacco use and 

forces related to public policy, family and 

community norms, culture, and history. 

Product

Tobacco products are diverse and include 

conventional cigarettes, pipes, cigars, 

smokeless tobacco, bidis, kreteks, and others.

Some of the complexity of the product is 

illustrated by conventional cigarettes. A 

commercial cigarette is not simply a column 

of tobacco wrapped in paper to which a 

filter is attached. The modern commercial 

cigarette is a highly engineered nicotinedelivery device. It is specifically designed 

for the rapid delivery of nicotine to the 

brain, allowing nicotine to enter a smoker’s 

bloodstream via gas or particle deposition 

in the respiratory tract and mucous 

membranes. This rapidity of nicotine 

delivery results in immediate reinforcement 

of smoking behavior and enables the 

smoker to exert exquisite control over his 

or her nicotine intake, from one puff to 

the next.23 Smokers may self-dose with 

nicotine several hundred times a day. For 

example, a one-pack-per-day smoker likely 

inhales smoke 70,000–100,000 times per 

year.23 Experienced smokers are expert at 

dose titration, with much of the process 

occurring with little conscious control. 

Commercial cigarettes are engineered to 

allow significant flexibility in the delivery 

of nicotine and other components of 

smoke that reinforce smoking behavior. 

As smokers became more aware of the 

health consequences of smoking, tobacco 

manufacturers responded with changes 

to the cigarette’s design that purported to 

reduce the delivery of toxins to the user. With 

the advent of filters, including ventilated 

filters, and porous cigarette papers, the 

average machine-measured, sales-adjusted 

yields of tar fell from 21.6 mg in 1968 to 

12.0 mg in 1998,24 while those for nicotine 

fell from 1.35 mg to 0.88 mg per cigarette.

These dramatic reductions might have been 

expected to yield significant public health 

benefits, but there is no convincing evidence 

that they have resulted in important health 

benefits to either smokers or the whole 

population.25 The high degree of elasticity 

of delivery afforded by modern cigarettes 

has allowed smokers to compensate for 

the decreased machine-smoked yields 

of nicotine. Smokers use multiple 

compensatory mechanisms for increasing 

nicotine delivery, including increasing the 

number and volume of puffs and blocking 

filter ventilation holes.26–31 Data indicate that 

cigarettes with low or medium quantities of 

nicotine are smoked much more intensely 

than is indicated by the test data from 

machine smoking analyses.

Moreover, use of the Federal Trade 

Commission method of measuring 

yields from machine-generated smoke 

Key Terms and Definitions

System: A set of elements interrelated 

among themselves and within the 

environment

Systems approaches: Theories that use 

systems methods in an organized framework 

to address systems (e.g., chaos theory or 

complexity theory)

Systems methods: Specialized techniques 

or procedures for researching and 

understanding systems (e.g., system 

dynamics modeling, structured 

conceptualization, or network analysis)

Systems thinking: Use of systems approaches 

to view the world
15

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

leads to overestimations of the degree of 

exposure reduction afforded by low-yield 

cigarettes.27,32 Most studies that compare 

smoking behavior in people who smoke 

cigarettes with different yields of nicotine 

reveal at least partial compensation for 

lower levels of nicotine by smoking behavior. 

This finding suggests that cigarettes with 

lower yields are smoked more intensely than 

are those with higher yields.23

Additionally, cigarettes may be manufactured 

to increase the potential for addiction by 

making more of the nicotine in smoke 

available for rapid transfer to the brain. 

The “free-base” (unprotonated) form of 

nicotine is volatile and is more rapidly and 

efficiently absorbed through the lungs and 

mucous membranes than is the “non-freebase”(monoprotonated) form of nicotine.33–35

It has been postulated that rapid absorption 

increases the speed of nicotine delivery 

to the brain, increasing the potential for 

addiction.36,37 The free-base form of nicotine 

has been likened to the free-base form of 

cocaine (“crack” cocaine)—both are rapidly 

absorbed, resulting in an explosive effect on 

the nervous system.38

The sensory and hedonistic qualities of 

cigarettes, including immediate perceptions 

of impact and satisfaction,39,40 contribute to 

their high liability for abuse. The addictive 

consequences of swift delivery of nicotine 

to the brain became apparent when the 

subjective responses of smokers were 

examined. For example, a 1974 Liggett report 

demonstrates that a cigarette with a high 

proportion of free-base nicotine has “...more 

free nicotine in its smoke, and consequently, 

a higher nicotine impact.”39(Bates no. 2073832754)

Similarly, a 1976 R.J. Reynolds document 

describes free-base nicotine as “more rapidly 

absorbed by the body and more quickly 

gives a ‘kick’ to the smoker.”41(Bates no. 502420399)

Another document notes that nicotine in 

its free-base form is more readily absorbed 

through the body tissue.42 Hence it is the free 

nicotine that is associated with impact; that 

is, the higher the level of free nicotine, the 

higher the impact.43

It is apparent that the reinforcing and 

rewarding effects of cigarettes are such that 

the smoker is likely to become addicted and 

have great difficulty in stopping smoking. 

Personal characteristics also can make a 

person particularly susceptible to starting 

to smoke and having difficulty in stopping 

smoking.

Person

Nearly all people in the United States are 

exposed to advertising and promotion of 

tobacco products and to others smoking 

around them. However, not everyone 

initiates cigarette smoking or uses other 

tobacco products. Some people can stop 

smoking easily, while others may experience 

great difficulty.

Early research focused on the biobehavioral 

aspects of smoking initiation and cessation. 

For example, a person’s level of educational 

attainment is an important predictor of 

smoking status. In 2004, smoking levels 

were higher among adults with a general 

equivalency diploma (43.2%) or 9–11 years 

of education (32.6%) than among adults 

with an undergraduate degree (women: 

9.6%; men: 11.9%) or a graduate degree 

(women: 7.4%; men: 6.9%).4 Additionally, 

cigarette smoking is more common among 

adults with incomes below the poverty level 

(29.9%) than among those with incomes at 

or above the poverty level (20.6%).4

The prevalence of smoking among adults 

has declined considerably in recent decades. 

However, cigarette smoking among 

adolescents rose in the late 1980s through 

the mid-1990s, before decreasing.44 Among 

children and adolescents, associations have 

been reported between starting to smoke 

and factors related to the spheres of family, 

peers, personality, and environment. For 

example, higher smoking prevalence has 
16

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

been reported among adolescents who 

show symptoms of depression, have poor 

academic performance, or are prone to 

rebelliousness.45 Smoking among family 

members and friends, and exposure to 

tobacco advertising and promotion, are 

associated with higher levels of childhood 

cigarette smoking.45–49 Parental support and 

negative parental attitudes toward youth 

smoking are protective factors.50–52 Traits 

such as impulsivity are associated with 

both starting to smoke and relapsing after 

attempting to stop smoking, suggesting 

that nicotine may be disproportionately 

rewarding for some people.53

The proportion of young adults (18–24 years 

old) who started to smoke cigarettes and who 

transitioned to regular smoking increased 

during the late 1990s.54–57 In 2005, the 

prevalence of smoking among young adults 

was 24.4%, statistically equal to the rate of 

adults aged 25–44 years (24.1%),4 the age 

group that traditionally had the highest 

prevalence. It is unlikely that the increase in 

smoking among college-age young adults is 

solely the result of adolescents aging into the 

group. Rather, specific targeting by advertising 

and promotion of tobacco companies has 

probably contributed to the increase.55

Emerging evidence suggests a genetic basis 

for some aspects of smoking behaviors in 

some individuals, which may explain part 

of the variation in smoking patterns among 

individuals. Behaviors in which genetics 

have been implicated include initiation of 

cigarette smoking, onset of addiction, and 

success in stopping smoking. Heritability 

has been implicated in starting to smoke, for 

men more than women, and for persistence 

in smoking.58 Monozygotic twins have been 

shown to have a greater concordance for 

failure to stop smoking than have dizygotic 

twins.59 One study of twins reported that 

genetic factors may account for 50% of 

the variance in risk for starting to smoke 

and 70% of the variance for continuing to 

smoke.60 A review61 of published studies 

relates DRD2 Taq1A, CYP2A6, DAT VNTR, and 

5HTT LPR genetic polymorphisms (different 

forms of genes) to smoking patterns. The data 

were insufficient for performance of a metaanalysis. However, the authors conclude that 

the contribution of specific known genes to 

smoking behavior is probably modest. 

Cigarette manufacturers place their product 

in the person’s environment and promote 

its use. Particular activities of the tobacco 

industry are especially potent in countering 

public health efforts to eradicate tobacco use. 

These counterefforts underscore the need for 

a systems approach to tobacco control.

Tobacco Industry

Prior to the invention and patenting of 

the cigarette rolling machine in 1880, 

cigarettes were not the most popular 

tobacco product. The “cigarette market 

was small.... Cigarettes were expensive 

and hand rolled by the cigarette girls. Most 

manufacturers didn’t see a use for that many 

cigarettes.”62 The advent of the cigarette 

rolling machine, which could produce 

120,000 cigarettes in 10 hours, “led not 

only to the widespread use of cigarettes 

as America’s favored form of tobacco, 

but to the modern era of mass-market 

advertising and promotion.”62 The success 

of mass marketing was also enhanced by 

the availability of bright (Virginia or fluecured) tobacco, which produced smoke 

that was more easily inhaled than that of 

other tobaccos in previous use. In 2003, 

despite a ban on advertising on radio, 

television, and billboards,63 the U.S. cigarette 

manufacturers together spent more than 

$15 billion—more than $41 million each 

day—to advertise and promote cigarettes.9

Tobacco companies maintain a sophisticated 

distribution system that results in the 

widespread availability of cigarettes. It 

is virtually impossible for consumers to 

avoid protobacco messages while going 

about their day-to-day activities. While 
17

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

communities often limit the number of 

outlets for the sale of alcohol by restricting 

the number of retail licenses or the 

density of stores, tobacco outlets are not 

similarly restricted. Most retail stores that 

sell necessities such as milk and bread 

also sell cigarettes. More than 80% of all 

cigarette advertising and promotional 

dollars are spent in ways that affect the 

retail environment. Ninety-seven percent 

of retail tobacco outlets contain at least 

one advertisement or promotional item, 

aside from the tobacco product itself. The 

average number of such items per store rose 

from 13 in 2001 to 17 in 2002 (P. I. Clark, 

pers. comm., October 21, 2005). No other 

consumer product is as heavily promoted in 

retail stores,11,64 and the Master Settlement 

Agreement did not include provisions for 

restricting retail advertising. 

In the earliest years of cigarette manufacturing, the tobacco companies had only 

to manufacture and distribute their products 

and convince people to buy and use them. 

However, by the early 1950s, reports about 

the association between smoking and 

adverse health outcomes began to appear in 

the scientific literature.65,66 On January 11, 

1964, Surgeon General of the Public Health 

Service Luther Terry released the report of 

the Surgeon General’s Advisory Committee 

on Smoking and Health. The first Surgeon 

General’s report, based on more than 

7,000 articles from the biomedical literature, 

concluded that cigarette smoking causes 

lung cancer and stated that “cigarette 

smoking is a health hazard of sufficient 

importance in the U.S. to warrant appropriate 

remedial action.”67(p33) The report was 

released to the public on a Saturday to avoid 

a strong reaction from Wall Street.68

Within weeks of the public release of the 

first Surgeon General’s report, the tobacco 

companies fought back. George Weissman, 

then president of Philip Morris, reacted 

to the report by sending a confidential 

memorandum to Joseph Cullman III, then 

Philip Morris’s chair and chief executive 

officer, which referred to the report as a 

“propaganda blast” and provided ideas about 

how the tobacco industry could counteract 

it. In this memorandum, Mr. Weissman 

noted that he had originally supported 

a mild federal labeling act to thwart the 

efforts of the individual states, saying, “If 

possible, the state legislatures could be 

held off on the basis that this is a federal 

matter and the federal can be the subject 

of many hearings.” He suggested working 

clandestinely to ridicule the findings of the 

Surgeon General’s report, saying, “While it 

should not be done in the industry’s name, 

someone ought to be contacting all the 

cartoonists, television gag writers, satirical 

reviews, etc....” He continued, “...However, at 

some point, reflecting the same seriousness 

with which we met the report, we must 

in the near future provide some answers 

which will give smokers a psychological 

crutch and a self-rationale to continue 

smoking....”69(Bates no. 1005038559–8561)

Since that time, the tobacco companies 

have countered every major public health 

initiative with varying degrees of success. 

An extensive body of peer-reviewed 

literature describes the diverse strategies 

and tactics the tobacco industry has used to 

undermine public health.70–78 The industry 

has long been concerned that large-scale, 

comprehensive tobacco control programs 

would reduce smoking and thus reduce 

profits.79 An important example of a program 

that the industry perceived as a threat was 

the American Stop Smoking Intervention 

Study for Cancer Prevention (ASSIST), a 

17-state initiative that sought to reduce 

tobacco use by changing the sociopolitical 

environment through policy and media 

advocacy and through the development 

of state infrastructures to deliver tobacco 

control.80–82 Given the scope of ASSIST, it 

is not surprising that the program caught 

the attention of the tobacco industry.73,79

While local, state, and federal governments 

expended resources to reduce smoking rates 
18

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

and promote tobacco control, the tobacco 

industry expended significant resources to 

promote sales of their products, influence 

governmental bodies, and undermine 

programs such as ASSIST.73,79

The tobacco industry has relied heavily on 

lobbying and campaign contributions to 

oppose antitobacco legislative initiatives.83–86

Some tobacco company efforts have made 

use of front groups or third-party allies to 

advance their goals.87 For example, tobacco 

companies have used financial analysts from 

the investment banking industry, as though 

from an independent source, to promote the 

tobacco industry’s public policy agenda.74

Early on, the tobacco industry realized that 

policies to reduce exposure to secondhand 

smoke were a serious threat to profits. 

For example, Philip Morris estimated that 

smoke-free workplaces would increase 

smoking cessation rates and reduce 

cigarette consumption by 11%–15% and 

that widespread restrictions on smoking 

in the workplace would severely affect the 

industry.72 In response to the threat, the 

industry paid scientists and academicians 

to present research countering the evidence 

against the health hazards of exposure 

to secondhand smoke.88–91 The tobacco 

industry developed a network of experts on 

ventilation who represented themselves as 

independent consultants. However, these 

consultants promoted strategies of the 

tobacco industry under close, but generally 

undisclosed, industry supervision.72 The 

ventilation consultants were used to steer 

public concerns about indoor air quality 

away from secondhand smoke, arguing that 

it was an insignificant component of a much 

larger problem of poor indoor air quality 

and inadequate ventilation. The consultants 

carried this message to businesses, 

particularly the hospitality business, and to 

regulatory and legislative groups.72

Over time, the tobacco companies developed 

strategies to counter or co-opt public health 

initiatives and maintain company profits. 

For many years, the major U.S. cigarette 

companies were able to coordinate their 

efforts through the Tobacco Institute, a 

trade association formed in 1958 to promote 

the tobacco industry’s positions, primarily 

through public relations and lobbying 

activities. For many decades, the Tobacco 

Institute was a major force in the effort 

to counter antitobacco initiatives.92 The 

Tobacco Institute was required to dissolve in 

1998, pursuant to litigation brought by the 

state Attorneys General.

Tobacco and Public Officials: A Complex Relationship

While the tobacco industry is seen by tobacco control professionals as a “vector” for disease, its 

relationship with the public sector can be considerably more complex. The financial aftermath 

of the 1998 Master Settlement Agreement (MSA) is a case in point. As a result of a class action 

lawsuit in Illinois, Philip Morris was required to place billions of dollars in escrow while the case 

was appealed.a The company argued that such a bond could result in bankruptcy, jeopardizing 

funds the states were to receive under the MSA. In response, 37 state and territorial Attorneys 

General submitted a friend-of-the-court (amicus curiae) brief, requesting that Philip Morris be 

allowed to decrease the amount of bond required by the court. The court granted this request. It 

appears that, on occasion, dependence on MSA funds has provided an incentive for states to take 

positions that support the continued financial health of the tobacco industry.

a

Altria Group. 2003. Illinois court reduces $12 billion bond: Philip Morris USA set to begin appeal; To make 

MSA payment to states. Press release. New York: Altria Group. http://www.altria.com/media/03_06_04_12_04_

pricerpr.asp. 
19

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

The tobacco industry continues to influence 

attitudes and behaviors toward smoking, 

particularly in areas in which it retains an 

economic influence. This influence occurs 

both at the micro level, through retailers, 

restaurant owners, and others, and at the 

macro level, where tobacco interests form 

a significant part of regional economies. 

At the micro level, tobacco interests 

often form coalitions with economic 

partners. For example, the industry may 

partner with hospitality industry allies to 

challenge a comprehensive clean indoor 

air law.93,94 At the macro level, studies have 

shown that tobacco-producing states have 

substantially lower tobacco taxes,95 fewer 

laws restricting smoking,96 and less overall 

control of tobacco use97 than do other states. 

Economic factors such as these remain a 

challenge to address.

The product, the person, and the tobacco 

producer operate in an environment of 

national-, state-, and community-level 

factors. The significant influence of the 

environment on tobacco use is evident 

from the wide variation in smoking 

prevalence across the states. In 2005, the 

median prevalence of cigarette smoking 

among U.S. adults was 20.9%; however, the 

prevalence ranged from 11.5% in Utah to 

28.7% in Kentucky.98 Outside the 50 states 

and the District of Columbia, the median 

prevalence of cigarette smoking among 

adults was 13.6%, ranging from 10% in 

the U.S. Virgin Islands to 34% in Guam.99

Image and the Tobacco Industry: A Systems Response

Market leader Philip Morris has demonstrated the tobacco industry’s ability to change in response 

to pressure. In the early 1990s, Philip Morris faced pressure from the public health community 

and groups promoting the rights of nonsmokers. The company’s own polling data showed that 

Philip Morris was viewed far less favorably by the public than other companies, including Exxon 

following the Exxon Valdez oil spill. In response, Philip Morris decided to revamp its corporate 

image by developing an image-enhancement campaign, “Philip Morris in the 21st Century,” 

which included changing the company name to Altria, to distance itself from the negative image 

of a tobacco company. 

Philip Morris and the other major U.S. tobacco companies have continued to use imageenhancement programs, including those focused on youth smoking prevention, and Web-based 

quit smoking assistance. Research to date demonstrates that these programs are either ineffective 

or actually harmful.a However, they may serve to help relieve some of the public pressure on the 

tobacco industry.b

The early years of the twenty-first century have been marked by decreased funding for tobacco 

control programs, including the near eradication of highly successful programs in Massachusetts 

and Florida. The transformation made by the tobacco companies provides evidence that tobacco 

control initiatives have been successful and that tobacco control strategies need to be sufficiently 

nimble to continue to apply pressure on the industry, especially in light of its recent efforts 

to reposition itself in the public eye. An integrated system of tobacco control will provide the 

needed agility. 

a

Henriksen, L., A. L. Dauphinee, Y. Wang, and S. P. Fortmann. 2006. Industry sponsored anti-smoking ads and 

adolescent reactance: Test of a boomerang effect. Tobacco Control 15 (1): 13–18.

b

Hirschhorn, N. 2005. Corporate social responsibility and the tobacco industry: Hope or hype? Tobacco 

Control 13 (4): 447–53.

Sources. Smith, E. A., and R. E. Malone. 2003. Altria means tobacco: Philip Morris’s identity crisis. American 

Journal of Public Health 93 (4): 553–56. Warner, K. E., and D. M. Burns. 2003. Hardening and the hard-core 

smoker: Concepts, evidence, and implications. Nicotine & Tobacco Research 5 (1): 37–48.
20

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

Environmental factors such as clean 

indoor air laws and regulations, economic 

dependence on tobacco (e.g., tobaccogrowing regions), and levels of taxation on 

tobacco products may contribute to this 

variation. 

The interrelationship of environmental 

factors, combined with the broader 

relationship of product, person, and producer 

of tobacco products, provides a focus on 

understanding and managing behaviors 

associated with tobacco use as an integrated 

system. This approach is not entirely new, as 

is illustrated by the history of the evolution 

of systems thinking in tobacco control.

Population-Level 

Tobacco Control 

Efforts: Beginnings of 

an Integrated System 

Tobacco use was once seen primarily as 

a problem of individual behavior, to be 

addressed at the individual level through 

interventions such as health education and 

assistance for smoking cessation. Today, 

experts recognize that population-level 

factors related to tobacco use function as a 

system. Moreover, population- and policylevel changes have a measurable influence 

on health outcomes. Indeed, this premise 

was reflected in the very first National 

Cancer Institute (NCI) Smoking and 

Tobacco Control Monograph, Strategies to 

Control Tobacco Use in the United States: 

A Blueprint for Public Health Action in the 

1990’s.81 That seminal monograph delineated 

the framework for a “systems approach” by 

characterizing tobacco control as a complex 

interplay of priority populations, channels 

for reaching priority populations, and 

individual and community interventions. 

Beyond the direct impact of these types of 

population-level interventions, the resulting 

changes in social attitudes toward smoking 

also affect overall tobacco use. For example, 

although clean indoor air laws are primarily 

aimed at protecting nonsmokers, they also 

help decrease smoking prevalence and 

consumption, which in turn, changes the 

social environment toward smoking.1–8,100–102

Clean indoor air laws may also have helped 

to change attitudes toward secondhand 

smoke, including helping to decrease the 

social acceptability of smoking in homes 

and cars. Voluntary bans on smoking in 

the home are associated with longer and 

more frequent attempts by adults to stop 

smoking, lower rates of relapse to smoking 

in adults,103,104 and lower rates of smoking 

among youth and young adults.105

Some tobacco control efforts focus on the 

biopsychosocial determinants of tobacco use. 

Interventions are targeted to the individual, 

such as use of medications to quit smoking. 

At the same time, some tobacco control 

interventions, such as banning smoking in 

bars and restaurants or increasing tobacco 

taxes, target policy and environmental 

influences on tobacco use. In the complex 

tobacco control environment, individual 

and policy approaches interact and 

influence each other in ways that need to 

be better understood. At the same time, 

tobacco companies continue to attempt 

to undermine individual and policy 

interventions. For example, major media 

campaigns encourage smokers who want 

information on quitting to visit the Philip 

Morris Web site.106 Such campaigns may 

permit Philip Morris, a leading promoter 

of cigarette smoking, to gain credibility 

with the public. Philip Morris has also 

recently expressed support for legislation 

that would give the U.S. Food and Drug 

Administration authority to regulate 

tobacco products, despite having opposed 

this in the past. These and other efforts by 

the tobacco industry result in perturbations 

in the complex tobacco control system 

and will require new thinking, analysis, 

and action. 
21

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

The growing realization that tobacco 

use is a systems problem has led to an 

increasing number of population-level 

tobacco control efforts, which serve as a 

precursor to the kinds of systems methods 

under study in ISIS. Three earlier efforts in 

Europe and the United States illustrate the 

evolution of thinking in tobacco control: 

the North Karelia Project, the Community 

Intervention Trial for Smoking Cessation 

(COMMIT), and ASSIST.

North Karelia Project

Tobacco use is mediated by social forces. 

Therefore, concerted efforts to change 

tobacco-related social and environmental 

influences may reduce tobacco use. An 

early intervention program attempted to 

approach tobacco use as a problem amenable 

to social change rather than individual 

change. The North Karelia (Finland) Project 

began in 1972 in response to unusually 

high rates of cardiovascular disease in 

Finland.100 Three risk factors were identified 

for targeted community interventions: 

hypertension, hypercholesterolemia, and 

cigarette smoking. Health care personnel 

were trained to give advice on quitting 

smoking, to give dietary advice, and to 

conduct blood pressure and cholesterol 

measurements. A variety of activities were 

implemented to increase public awareness 

and to reduce risk factors of cardiovascular 

disease. These included, for example:

n Organization of cholesterol-lowering 

competitions between villages 

n Working with food manufacturers 

and supermarkets to facilitate dietary 

changes, including development of 

low-fat dairy and meat products and the 

reduction of salt in a number of food 

items

n Workplace weight loss and smoking 

cessation programs, and the introduction 

of more vegetables in workplace 

cafeterias 

n Broadcasts of nationwide television series 

in which people would volunteer to make 

healthy changes in their lifestyles with 

expert help

n A project that encouraged people to grow 

berries

Many factors contributed to the observed 

drop in smoking prevalence among men, 

including “buy in” from the media that 

resulted in extensive media coverage, 

educating health care providers to give 

advice on smoking cessation, group sessions 

for help with smoking cessation, using lay 

leaders to educate the public, prohibiting 

smoking in most indoor public places, 

eliminating tobacco advertising, and 

dedicating a portion of tobacco taxes for 

tobacco control programs. As a result of 

the program, smoking among men dropped 

by one-third. Although smoking increased 

among women, the prevalence was low. 

Fewer than one in six women smoked 

cigarettes.101 The success of the project may 

be attributed to several factors, including

n Institution of a massive knowledge 

management process that integrated 

systems ranging from health care records 

to researchers

n Comprehensive efforts aimed at schools, 

workplaces, homes, and communities 

using a variety of channels and 

interventions

n Use of network-centric approaches to link 

networks within the province

The project was extremely influential and 

paved the way for several other communitybased systems efforts. In the 1980s, three 

studies of community health education 

were conducted in the United States: the 

Stanford Five-City Project, the Minnesota 

Heart Health Program, and the Pawtucket 

Heart Health Program.102,107 The effects 

of these interventions were modest and 

failed to reach statistical significance in 
22

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

many cases, perhaps because of positive 

changes in the environments of the control 

communities.102,107

COMMIT

In 1982, NCI’s Division of Cancer Prevention 

and Control launched the Smoking, 

Tobacco, and Cancer Program. Recognizing 

that the link between tobacco use and cancer 

death had been persuasively demonstrated, 

this research effort was aimed at identifying, 

developing, and evaluating effective means 

of reducing tobacco use. Intervention 

trials were conducted to examine schoolbased prevention programs, self-help and 

minimal intervention strategies, advice 

delivered by physicians and dentists, massmedia approaches, and community-based 

programs. Interventions focused on youth, 

racial and ethnic minorities, women, users 

of smokeless tobacco, and heavy smokers. 

These interventions were later delivered 

through NCI’s COMMIT, a randomized 

community trial to determine whether a 

community-level, multichannel effort could 

increase rates of smoking cessation.108,109

The intervention phase of COMMIT was 

conducted from 1988 to 1992. Trial activities 

were implemented through five major 

channels: community mobilization—an 

overarching effort to organize the 

community around tobacco control; health 

care providers; worksites and organizations; 

program services; and public education.110

One community in each of 11 matched 

community pairs was randomly assigned to 

the intervention, and the other community 

in the pair served as a comparison 

community. Following the intervention, 

10,019 heavy smokers and 10,328 lightto-moderate smokers were surveyed by 

telephone. There were no differences found 

between intervention and comparison 

communities among heavy smokers (more 

than 25 cigarettes per day). However, 

at the project’s end, 30.6% of light-tomoderate smokers (less than 25 cigarettes 

per day) in the intervention communities 

quit smoking, as compared with only 

27.5% in the comparison communities.110

COMMIT’s impact on light-to-moderate 

smokers, although modest, had a significant 

public health impact. Additionally, the 

trial provided valuable lessons about 

how to mobilize communities to support 

environmental change. As in previous 

community trials, COMMIT’s limited 

effectiveness was thought to result, at least 

in part, from secular trends in comparison 

communities.109

ASSIST

In 1991, NCI launched ASSIST to prevent 

or reduce cigarette prevalence and 

consumption, primarily through state 

policy-based approaches to alter the social 

environment.81 The principal focus of 

ASSIST was to alter the environmental and 

social influences affecting cigarette smoking 

through development of skills in media 

advocacy; promotion of local and state 

clean indoor air laws; reduction of youth 

access to tobacco products; limitation of 

tobacco advertising, especially that targeting 

children, women, and members of minority 

groups; increases in tobacco taxes; and 

increases in demand for smoking cessation 

services.111

The COMMIT strategy, which ASSIST 

extended across entire states, recognized 

that powerful social forces affect tobacco use, 

and that the community must be mobilized 

to make smoking socially unacceptable. 

In community mobilization, networks 

of public and private organizations and 

special interest groups pool and coordinate 

resources—personnel, time, money, goods, 

and services—to support a broad range 

of tobacco control activities. Through 

ASSIST, state- and community-based 

coalitions for tobacco control were formed. 

These coalitions comprised community 

organizations capable of coordinating and 

delivering effective interventions. 
23

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

NCI joined the American Cancer Society 

(ACS) and 17 state health departments 

in planning and managing ASSIST. ACS 

had long been involved in local smoking 

prevention and control activities and had 

a strong network of volunteers to mobilize 

communities and expand the delivery 

of tobacco use prevention and control 

interventions. Health departments—with 

their commitment to public health, 

experience in working in a culture of 

institutional partnerships, access to priority 

populations of smokers, and guaranteed 

continuing presence—competed to receive 

ASSIST contracts. 

ASSIST was oriented toward developing, 

implementing, and evaluating multiple 

interventions, using a variety of channels 

to reach multiple populations. ASSIST 

used a three-dimensional cube (figure 2.1) 

as a model to define its scope.111 This cube 

represents the domains of focus for states 

participating in ASSIST and provides a 

graphic reminder that the components 

(interventions, channels, and priority 

populations) are interrelated and represent 

critical constituents in a comprehensive 

approach to tobacco control. 

By developing a matrix approach to the 

complex tobacco control enterprise, it 

was possible to create and improve on a 

framework for state tobacco control efforts. 

The ASSIST evaluation and modeling led to 

development of a revised model (figure 2.2) 

that retains the perspective that multiple 

variables interplay in a complex way, but 

includes factors not considered in the 

ASSIST cube (e.g., tobacco industry efforts 

to impede tobacco control). The evaluation 

effort was developed to enable both (1) a 

comparison of tobacco control in ASSIST 

and non-ASSIST states and (2) a modeling 

Figure 2.1 ASSIST Interventions and Delivery Channels 

Program Services

Mass Media

Policy

Worksites

Schools

Health

Care

Settings

Community

Groups

Axis 3

Interventions

Axis 1

Priority Populations

Axis 2

Channels

Source. Adapted from National Cancer Institute. 1991. Strategies to control tobacco use in the United States: A blueprint for 

public health action in the 1990’s (Smoking and tobacco control monograph no. 1, NIH publication no. 92-3316), xii. Bethesda, MD: 

National Cancer Institute.
24

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

of the complex relationships among tobacco 

control program components to begin 

exploring their relative impacts. 

ASSIST and similar intervention programs 

have been important to tobacco control 

efforts for several reasons. States that 

participated in ASSIST experienced a greater 

decrease in smoking prevalence than states 

that did not.112 At a time of devolution from 

federal to state funding of tobacco control 

efforts, participating states demonstrated 

the ability to mobilize tobacco control 

resources. They also showed that investment 

in building state tobacco control capacity 

and in promoting tobacco control policy 

change was an effective strategy for reducing 

tobacco use.112

Before NCI and ACS instituted ASSIST, 

few state health departments had tobacco 

control programs of significance. In 

1994, the Centers for Disease Control and 

Prevention (CDC) funded the remaining 

non-ASSIST states (excepting California, 

which had Proposition 99 funding) and 

the District of Columbia to implement 

tobacco control programs through a 

program titled Initiatives to Mobilize for the 

Prevention and Control of Tobacco Use. The 

emphasis of these initiatives was to develop 

comprehensive state tobacco prevention and 

control programs involving participation of 

diverse community groups, coalitions, and 

community leaders. In 1999, CDC created 

the National Tobacco Control Program to 

provide funding to the state and territorial 

tobacco control programs. 

In 1993, the Robert Wood Johnson 

Foundation founded the SmokeLess 

States Program, designating the American 

Medical Association to serve as the National 

Program Office. The goals of the program 

were to concentrate efforts in three general 

areas: (1) increased public awareness of the 

Figure 2.2 Multiple Variables Affecting Tobacco Control and Its Outcomes

Initial outcomes Intermediate outcomes Final outcomes Changing disease outcomes

Tobacco control interventions

Individual characteristics

Tobacco industry tactics

Individual Local State National

Individual Local State National

Race Sex Age SES Geoloc

Non-smoker Experimenter Smoker Former smoker

Note. SES = socioeconomic status; Geoloc = geographic location. From Institute for Global Tobacco Control. 2002. Evaluating 

comprehensive tobacco control interventions: Challenges and recommendations for future action. Report of a workshop convened 

by the Institute for Global Tobacco Control, Johns Hopkins Bloomberg School of Public Health. Tobacco Control 11 (2): 140–45. 

Figure 1. Framework for evaluating comprehensive tobacco control programmes, 141. Reproduced with permission from the BMJ 

Publishing Group.
25

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

dangers of tobacco use, (2) public education 

on effective tobacco control policies 

(e.g., increasing excise taxes, promoting 

clean indoor air), and (3) enhancement of 

local smoking prevention and treatment 

programs. The program initially funded 

statewide coalitions in 19 states; two years 

later, additional funding raised the number 

of coalitions to 30.113

Programs such as those described here 

highlight a growing focus on populationlevel tobacco control interventions that 

seek to create environmental change. They 

provide evidence that systems approaches 

make a difference in tobacco control 

efforts and tobacco use. These approaches 

represent an important evolutionary step, 

but alone they are not sufficient. There is 

a growing realization that relationships 

evolve among the individual and his or her 

environment, the tobacco product, and 

the industry that produces and promotes 

that product. It is increasingly important 

to approach tobacco control research 

and practice from a systems perspective, 

understanding the complex interactions 

among these components.

Current Tobacco 

Control Research and 

Practice: Systems 

Problems

The tobacco control problems that 

remain are systems problems—complex, 

interdependent issues that lie within the 

fundamental nature of today’s tobacco 

control environment. Applying what is 

known about tobacco use as a system and 

what has been learned from earlier tobacco 

control efforts helped the ISIS team identify 

the following problems:

n Numerous disparate communities of 

interest and duplication of effort

n Ineffective integration of research and 

practice 

n Competition from a well-financed and 

organized tobacco industry that has wellintegrated dissemination and networking 

efforts

n In some cases, lack of evidence for 

effectiveness of specific tobacco control 

efforts on key outcomes such as smoking 

cessation, morbidity, and mortality

n Diffuse tobacco control efforts reflecting 

a lack of strategic, multipartner planning 

and execution

The ISIS team concluded that these 

substantial and often overlapping challenges 

must be overcome to bring tobacco control 

resources and efforts into an integrated 

system. Identifying problems provides 

direction for tobacco control efforts. 

Moving tobacco control forward will 

require the recognition that the landscape 

today is different from that of 10 years 

ago. The tobacco industry has responded 

to tobacco control efforts with a new 

level of sophistication. As in many fields, 

good science frequently sits in scientific 

journals and reports, unused by many 

who could benefit from it. The tobacco 

control community is likely responsible 

for “tipping” the national consciousness in 

favor of reduced acceptance of tobacco use. 

However, the community has not adequately 

addressed long-term strategies and is, on 

occasion, at odds with itself over issues such 

as harm reduction.

To proceed to the next level and to more 

effectively translate scientific discoveries 

into practice, the ISIS team concluded 

that it is necessary to move beyond 

familiar approaches and toward systems 

methods that address fundamental 

issues of complexity, interdependency, 

knowledge management, and engagement 

of organizations as a system. Because the 
26

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

current challenges in tobacco control are 

related to the complexities and dynamics 

of the systems in which tobacco control 

is embedded, the solutions must lie in 

addressing those systems.

Lessons from ISIS 

Unlocking the promise of systems 

approaches requires a participatory, 

collaborative environment among the 

stakeholders. In turn, this requires 

a fresh approach to management, 

leadership, and interactions within and 

among organizations. ISIS explored how 

organizations can function as systems 

through facilitation, empowerment, selforganization, participation, and continuous 

evaluation. The aim of ISIS was to apply 

methods of systems thinking to practices in 

tobacco control. Chapters 4 and 7 discuss 

systems thinking in the framework of a 

systems approach to organization and 

management and creation of a “combined 

toolbox” for the development of outcomeoriented implementation strategies for 

tobacco control. 

ISIS is based on the idea that the growth 

of systems methods in areas such as 

epidemiology,114 organizational behavior,115

and national defense116 are applicable to 

tobacco control. Here, the argument is 

made for applying integrated methods for 

strategic systems thinking in response 

to critical needs in tobacco control and 

as a proof of concept for applying these 

approaches to similar challenges in other 

key areas of public health. Six key facets 

of the ISIS perspective also are discussed 

here: (1) using a transdisciplinary approach; 

(2) transcending or integrating diverse 

cultures and missions; (3) accelerating 

transfer from discovery, to development, 

to delivery; (4) setting evidence-based 

priorities; (5) creating a federation 

of systems, also called “networks of 

stakeholders” in this monograph; and 

(6) setting long-term goals. 

Using a Transdisciplinary Approach

Researchers, practitioners, policy makers, 

and other stakeholders approach tobacco 

control from the perspective of their own 

disciplines, which include law, economics, 

epidemiology, the behavioral sciences, 

neurobiology, toxicology, chemistry, 

addiction medicine, and public health. 

Members of these disciplines speak different 

languages, use different research and 

intervention tools and models, and read 

and contribute to different literature bases. 

To most researchers and practitioners, the 

composite whole of tobacco control and 

related literature is inaccessible and use 

of the full scientific basis for practice is 

unlikely. 

Understanding the complex problems of 

tobacco use and tobacco control requires 

true transdisciplinary collaboration in both 

research and practice and between research 

and practice. However, creating the mindset and functionality of a transdisciplinary 

approach is difficult, because it represents 

a worldview requiring increased 

teamwork across a wide array of fields and 

disciplines. This approach may also be 

more time consuming, at least initially, 

because it depends on the development 

and maintenance of relationships and 

infrastructures among diverse partners.

Disciplines serve a critical function by 

ensuring depth of knowledge in a particular 

field, partly through the exchange of 

information within discipline-specific social 

networks. They have also allowed relatively 

rapid gains in knowledge. However, 

disciplines may also become “stovepiped,” 

in that the knowledge from one discipline 

gives rise to unique terminology that tends 

to isolate it from others. The lack of linkage 

among disciplines has created the effect of 

“silos dotting the landscape.” These silos 

are effective in holding their contents but 

inefficient at allowing carryover from one 

silo to another.
27

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

It is encouraging that efforts to link 

disciplines—to increase transdisciplinary 

and multidisciplinary thinking and 

action—are now recognized as valuable. For 

example, in 1999, NCI, the National Institute 

on Drug Abuse, and the Robert Wood 

Johnson Foundation provided funding for 

the Transdisciplinary Tobacco Use Research 

Centers. This paradigm shift has now been 

expanded beyond tobacco control; NCI also 

has funded several transdisciplinary centers 

to investigate obesity and energy balance.117

Additionally, the National Institutes of 

Health (NIH) has recently created the 

“Roadmap Initiative,” a transdisciplinary 

and transinstitutional initiative to identify 

major opportunities and gaps in biomedical 

research that no single NIH institute could 

tackle alone.118 The gradual increase in 

linkage among disciplines could lead to 

more rapid knowledge discoveries, which 

could facilitate delivery of interventions.

Transcending or Integrating Diverse 

Cultures and Missions

Among the barriers to the creation of 

an integrated system is the reality that 

many partners and potential partners 

have different missions, practices, and 

cultures. In many cases, priorities overlap 

or are complementary, but little effort 

goes into exploring the areas of overlap 

and complementarity. On the other hand, 

planned redundancy may have value to 

ensure that a particular need is fully 

addressed and that decreased funding to one 

organization will not jeopardize survival of a 

critical infrastructure.

Accelerating Transfer from Discovery, 

to Development, to Delivery

Another major challenge in tobacco 

control, as in other domains of public 

health and medical care, is the less than 

optimal progression from scientific 

discovery to the development, delivery, 

and widespread use of interventions. One 

analysis indicated that 17 years can pass 

between the time of a discovery and its 

use in clinical practice.119 This finding 

indicates a pipeline that is cumbersome 

and not oriented toward optimizing the 

flow and use of new knowledge. In this 

information age, it is time to optimize the 

progression from discovery to delivery. For 

example, in 2003, NCI provided $19 million 

for research on the treatment of tobacco 

addiction (C. Backinger, pers. comm., 

Tobacco Control: A Multitude of Stakeholder Organizations

Organizations that focus on tobacco control vary greatly. For tobacco control efforts to succeed, 

it may be necessary to develop a strategic and collaborative vision and action. Major government 

research agencies such as the National Cancer Institute and the National Institute on Drug Abuse 

have different but overlapping areas of focus. The same holds true for more public health and 

practice-oriented government agencies, such as the Centers for Disease Control and Prevention 

and the Substance Abuse and Mental Health Services Administration. Furthermore, within the 

agencies that address public health research and practice, still more areas of focus overlap. When 

organizations such as the Robert Wood Johnson Foundation, the American Legacy Foundation, 

the Campaign for Tobacco-Free Kids, state health departments, and corporate leaders such as 

the Chief Executive Officer Roundtable on Cancer are also considered, the challenge of and 

opportunity for optimizing the missions of these many potential partners into a functional 

network oriented to achieving the greatest public good in the most efficient way are expanded. 

Fortunately, in diversity there is strength. Diversity allows for breadth of thinking and action. 

One key challenge is to harness and focus within that diversity to achieve the ultimate goal.
28

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

October 18, 2005). However, insufficient 

infrastructure exists to ensure that the 

knowledge gained through this research 

will be shared systematically with other 

investigators. Furthermore, not enough 

effort has been made to develop a network of 

scientists studying the treatment of tobacco 

addiction, so that these investigators can 

rapidly share knowledge of methods and 

research outcomes.

Despite the existence of Web-based social 

networks that allow the rapid exchange 

of information and rapid publication 

via scientific e-journals, the scientific 

community has largely held to the practices 

of the past. In addition, once new knowledge 

is developed about interventions for clinics 

and communities, little effort is made to link 

scientists and community interventionists 

to determine the most effective strategies 

for disseminating and implementing the 

interventions. There are examples of timely, 

successful transition from discovery to 

delivery of interventions for tobacco control 

and development of networked collaboration 

between scientists and public health 

practitioners—for example, the proliferation 

of toll-free telephone quitlines to provide 

smoking cessation assistance. Unfortunately, 

these examples demonstrate the potential 

rather than common experience.

Setting Evidence-Based Priorities

Despite evidence that it is cost effective, 

disease prevention is not the primary 

paradigm of the U.S. health care system. The 

system’s orientation toward diagnosis and 

treatment of disease, which is fundamental 

to the training of health care providers, 

continues because a different paradigm has 

not gained prominence. The United States 

spends billions of dollars to care for patients 

with health conditions caused by tobacco 

use but does not consistently support 

preventing these conditions. A greater focus 

on prevention may be viewed as a zero-sum 

gain, because it may require decreased 

spending on diagnosis and treatment in 

the short term, absent new investments. 

Changing the status quo is not easy, even 

in the face of mounting evidence that 

prevention is a good long-term investment. 

Creating a Federation of Systems: Can 

Tobacco Control Learn a Lesson from 

the Department of Defense?

In the U.S. military, command and control 

issues are widely discussed and developed. 

Krygiel116 defines an environment in 

which there is no direct command and 

control (i.e., no top-down hierarchy) as a 

Moving from Clinical Trials to Real Life

The problem of effective dissemination and implementation often extends to clinical interventions 

as well. For example, once the U.S. Food and Drug Administration approved medications to 

help smokers stop smoking, these drugs were marketed rapidly to health care providers and the 

public, even though how they would be used in the “real world” was not well understood. The 

lack of a surveillance system to assess the effectiveness of medications being used to treat tobacco 

addiction has resulted in some confusion. Many in the scientific and public health communities 

cite numbers derived not from studies conducted in real-world settings but rather from highly 

controlled clinical trials. The development of surveillance systems to collect and analyze data on 

the progression of knowledge as a science-to-practice value chain could ensure that (1) those 

involved in each stage of discovery, development, and delivery are informed about what has been 

learned from each stage; and (2) delivery is not an end point but rather a rich environment for 

discovery through applied science. The process of progression from discovery, to development, to 

delivery is more interactive than linear.
29

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

federation of systems. For example, the U.S. 

military operated collaboratively within 

the command and control structure of the 

North Atlantic Treaty Organization during 

the Bosnian War; no single controlling 

organization existed.116 To function 

optimally, the military forces had to work 

together to compromise and develop a 

coordinated and collaborative mission 

based on common goals and objectives. 

This orientation is similar to what exists in 

tobacco control.

Perhaps the best comparison in tobacco 

control was the process of developing 

and implementing the World Health 

Organization’s Framework Convention 

for Tobacco Control (FCTC). As a result of 

leadership and collaboration by the World 

Health Organization, many organizations 

around the world developed a common 

goal and worked together to achieve that 

goal.120 The FCTC is an important example 

of what can be accomplished by developing 

synchronous networks of organizations 

or a federation of systems that direct their 

efforts toward a common outcome. This 

collaborative effort is also an excellent 

example of using the fruits of scientific 

discovery to develop effective policies that 

can benefit humanity. 

Setting Long-Term Goals

Little organized consideration of the longterm goals of the tobacco control movement 

has occurred. Stakeholder goals may vary 

widely from reducing the prevalence of 

smoking to the lowest possible level, to 

dismantling tobacco companies as they now 

exist.121 The long-term goals envisioned 

by the tobacco companies must also be 

considered. For example, a strategic analysis 

by Philip Morris considered the complex 

interacting influences in the business 

system, changes in knowledge, networkenabled direct marketing, and a shift in the 

corporate paradigm toward development as 

a pharmaceutical company.69

Unfortunately, the tobacco control 

community has not implemented efforts to 

model the many complex components that 

support and impede tobacco control efforts, 

so as to develop a more strategic vision of 

the future. Such an effort would not be 

simple, in part because different groups 

may identify and pursue different longterm strategies. However, exploring these 

strategies and the structures and functions 

needed to achieve them has the potential to 

inform the tobacco control community and 

supportive policy makers about what can 

and cannot be achieved. Working backward 

from various long-term goals would make 

it possible to better understand which 

structures and functions are needed to 

achieve them. The scenarios would likely 

represent new, highly nonlinear models 

with complex and dynamic components, 

requiring large quantities of data over 

time. By exploring both data-driven and 

theoretical (or simulation) models, the 

scientific and public health communities 

also could encourage the development of 

data sources that can be used to develop 

data-driven models, which have the 

potential to predict outcomes of known 

interventions. 

Summary

Moving tobacco control forward requires 

the recognition that the landscape today 

is fundamentally different from that 

of even 10 years ago. Many significant 

advances have occurred in tobacco control, 

but the tobacco industry has responded 

to these successes with a new level of 

sophistication. ISIS identified several 

critical needs and priorities for addressing 

tobacco and other public health threats in 

the future:

n Using a transdisciplinary approach

n Transcending or integrating diverse 

cultures and missions
30

2 . To b a c c o C o n t r o l a t a C r o s s r o a d s

n Accelerating transfer from discovery, 

to development, to delivery

n Setting evidence-based priorities

n Creating a federation of systems (or 

networks of stakeholders)

n Setting long-term goals

Thus, the tobacco control community 

needs to set long-term goals that take 

into account changing tobacco industry 

tactics. Progress toward improving the 

translation of discoveries into practice will 

require moving beyond familiar approaches 

and toward systems methods that address 

fundamental issues of complexity, 

interdependency, knowledge management, 

and engagement of organizations as a 

system. Current challenges are related 

to the complexities and dynamics of 

the systems in which tobacco control is 

embedded. Therefore, the solutions must 

lie in addressing those systems.

ISIS was a pilot effort to better understand 

the complexities of addressing tobacco use 

as a major public health threat. However, 

it also reflects a continuation of the vision 

delineated in the very first NCI tobacco 

control monograph to better understand 

those complexities. Just as the ideas put 

forth in the first monograph led to new 

thinking and action on tobacco control, it 

is believed that the implementation and 

integration of systems approaches have the 

potential to further advance tobacco control 

and improve the public’s health. 

Conclusions

1. The prevalence of tobacco use and 

levels of cigarette consumption among 

adults have dropped considerably since 

1950. However, tobacco use remains 

the nation’s leading cause of premature 

preventable death. The success of 

efforts to reduce the prevalence of adult 

smoking to the Healthy People 2010

goal of 12% or less remains elusive. 

2. Increasingly, tobacco use is seen as 

a population-level health problem 

that involves forces from the tobacco 

industry, current tobacco users and 

nonusers, and the environment. 

3. Tobacco control efforts have evolved 

from a focus on individual interventions 

toward population-level interventions, 

as the nature of tobacco use has become 

better understood. These efforts have 

evolved into a complex system involving 

multiple stakeholders and environmental 

factors, ranging from social attitudes 

toward smoking to the countervailing 

efforts of the tobacco industry.

4. Some research findings suggest that 

systems approaches are critical to 

further substantive gains in tobacco 

control. The success of early tobacco 

control efforts at the population level 

gives impetus to further exploration of 

this hypothesis.

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Tobacco Institute lobbying at the state and 

local levels of government in the 1990s. 

Tobacco Control 11 Suppl. 1: I102–I109. 

93. Samuels, B., and S. A. Glantz. 1991. The 

politics of local tobacco control. JAMA: 

The Journal of the American Medical 

Association 266 (15): 2110–17. 

94. Traynor, M. P., M. E. Begay, and S. A. 

Glantz. 1993. New tobacco industry strategy 

to prevent local tobacco control. JAMA: 

The Journal of the American Medical 

Association 270 (4): 479–86. 

95. National Cancer Institute. 2006. Evaluating 

ASSIST: A blueprint for understanding 

state-level tobacco control (Tobacco control 

monograph no. 17, NIH publication no. 

06-6058). Bethesda, MD: National Cancer 

Institute. http://cancercontrol.cancer.gov/

tcrb/monographs/17/index.html.

96. Chaloupka, F. J., and H. Saffer. 1992. Clean 

indoor air laws and the demand for cigarettes. 

Contemporary Policy Issues 10 (2): 72–83. 

97. Chriqui, J. F., M. Frosh, R. C. Brownson, 

D. M. Shelton, R. C. Sciandra, R. Hobart, 

P. H. Fisher, R. El Arculli, and M. H. Alciati. 

2002. Application of a rating system to 

state clean indoor air laws (USA). Tobacco 

Control 11 (1): 26–34. 

98. Centers for Disease Control and Prevention. 

2006. State-specific prevalence of current 

cigarette smoking among adults and 

secondhand smoke rules and policies in 

homes and workplaces—United States, 

2005. Morbidity and Mortality Weekly 

Report 55 (42): 1148–51. 

99. Centers for Disease Control and Prevention. 

2002. Annual smoking-attributable 

mortality, years of potential life lost, and 

economic costs: United States, 1995–1999. 

Morbidity and Mortality Weekly Report

51 (14): 300–303. 

100. Guest, I. 1978. Preventing heart disease 

through community action: The North 

Karelia Project. Developmental Dialogue

1: 51–58. 

101. Korhonen, T., A. Uutela, H. J. Korhonen, 

and P. Puska. 1998. Impact of mass media 

and interpersonal health communication 

on smoking cessation attempts: A study 

in North Karelia, 1989–1996. Journal of 

Health Communication 3 (2): 105–18. 

102. Fortmann, S. P. , and A. N. Varady. 2000. 

Effects of a community-wide health 

education program on cardiovascular 

disease morbidity and mortality: The 

Stanford Five-City Project. American 

Journal of Epidemiology 152 (4): 316–23. 

103. Farkas, A. J., E. A. Gilpin, J. M. Distefan, and 

J. P. Pierce. 1999. The effects of household 

and workplace smoking restrictions on 

quitting behaviours. Tobacco Control 8 (3): 

261–65. 

104. Gilpin, E. A., M. M. White, A. J. Farkas, and 

J. P. Pierce. 1999. Home smoking restrictions: 

Which smokers have them and how they are 

associated with smoking behavior. Nicotine & 

Tobacco Research 1 (2): 153–62. 

105. Clark, P. I., M. W. Schooley, B. Pierce, 

J. Schulman, A. M. Hartman, and C. L. 

Schmitt. 2006. Impact of home smoking 

rules on smoking patterns among 

adolescents and young adults. Preventing 

Chronic Disease 3 (2): A41. 

106. Philip Morris USA. 2007. Our initiatives 

and programs: QuitAssist. http://www

.philipmorrisusa.com/en/our_initiatives/

quit_assist.asp.

107. Winkleby, M. A., H. A. Feldman, and D. M. 

Murray. 1997. Joint analysis of three U.S. 

community intervention trials for reduction 

of cardiovascular disease risk. Journal of 

Clinical Epidemiology 50 (6): 645–58. 

108. American Journal of Public Health. 1995. 

Community Intervention Trial for Smoking 

Cessation (COMMIT): 1. Cohort results 

from a four-year community intervention. 

American Journal of Public Health 85 (2): 

183–92. 

109. Bauman, K. E., C. M. Suchindran, and 

D. M. Murray. 1999. The paucity of effects 
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in community trials: Is secular trend the 

culprit? Preventive Medicine 28 (4): 426–29. 

110. National Cancer Institute. 1995. 

Community-based interventions for 

smokers: The COMMIT field experience

(Smoking and tobacco control monograph 

no. 6, NIH publication no. 95-4028). 

Bethesda, MD: National Cancer Institute. 

http://cancercontrol.cancer.gov/tcrb/

monographs/6/index.html.

111. National Cancer Institute. 2005. ASSIST: 

Shaping the future of tobacco prevention 

and control (Tobacco control monograph 

no. 16, NIH publication no. 05-5645). 

Bethesda, MD: National Cancer Institute. 

http://cancercontrol.cancer.gov/tcrb/

monographs/16/index.html.

112. Stillman, F. A., A. M. Hartman, B. I. Graubard, 

E. A. Gilpin, D. M. Murray, and J. T. Gibson. 

2003. Evaluation of the American Stop 

Smoking Intervention Study (ASSIST): A 

report of outcomes. Journal of the National 

Cancer Institute 95 (22): 1681–91. 

113. Gerlach, K. K., and M. A. Larkin. 2005. The 

SmokeLess States Program: To improve 

health and health care. http://www.rwjf

.org/files/publications/books/2005/chapter_

02.pdf.

114. Centers for Disease Control and 

Prevention. 2005. Syndemics overview: 

When is it appropriate or inappropriate 

to use a syndemic orientation? Atlanta: 

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Services, Centers for Disease Control and 

Prevention, National Center for Chronic 

Disease Prevention and Health Promotion, 

Syndemics Prevention Network. http://www

.cdc.gov/syndemics/overview-uses.htm.

115. Senge, P. M. 1990. The fifth discipline: 

The art and practice of the learning 

organization. New York: Currency 

Doubleday.

116. Krygiel, A. J. 1999. Behind the wizard’s 

curtain: An integration environment for 

a system of systems. Washington, DC: 

Institute for National Strategic Studies.

117. National Institutes of Health. 2006. Clinical 

Nutrition Research Unit Core Centers. RFA 

announcement. http://grants.nih.gov/grants/

guide/rfa-files/RFA-DK-06-013.html.

118. National Institutes of Health. 2006. 

Exploratory Centers for Interdisciplinary 

Research. Bethesda, MD: U.S. Department 

of Health and Human Services, National 

Institutes of Health, Office of Portfolio 

Analysis and Strategic Initiatives. http://

nihroadmap.nih.gov/interdisciplinary/

exploratorycenters.

119. Institute of Medicine. 2004. The chasm 

in quality: Select indicators from recent 

reports. Washington, DC: Institute of 

Medicine. http://www.iom.edu/?id=14991.

120. World Health Organization. 2003. World 

Health Assembly Resolution 56.1. Geneva: 

World Health Organization. http://www.who

.int/tobacco/framework/final_text/en.

121. Callard, C., D. Thompson, and N. Collishaw. 

2005. Transforming the tobacco market: 

Why the supply of cigarettes should be 

transferred from for-profit corporations to 

non-profit enterprises with a public health 

mandate. Tobacco Control 14 (4): 278–83. 
37

3

Systems Thinking: Potential to 

Transform Tobacco Control

The preceding chapter explored contemporary challenges faced by proponents of tobacco 

control, particularly with respect to improving public health outcomes. This chapter 

presents a view of systems thinking as an endeavor that encompasses a broad and rich 

historical tradition of systems fields that could help address the increasingly complex 

challenges that tobacco control faces. The chapter addresses the application of systems 

approaches to tobacco control by examining 

n	 Current systems thinking approaches, including theories and issues 

encompassed by or closely allied to systems thinking

n	 Four promising systems approaches under study in the Initiative on the Study 

and Implementation of Systems (ISIS) project, which are explored in detail 

in subsequent chapters within the broader context of an integrated systems 

environment

n	 Key questions of tobacco control practitioners, researchers, and policy makers 

that are addressed by systems thinking

The goals of this chapter are to describe several frameworks for understanding what 

is meant by systems thinking, present a brief overview of the vast terrain of systems 

concepts, suggest an integrated view of the idea of systems thinking that is emerging 

in part from the work conducted in this project, and outline some of the implications 

of systems thinking for three key stakeholder groups in tobacco control—practitioners, 

policy makers, and researchers.

First come hints, then fragments of systems, then defective systems, then complete and 

harmonious systems. [And] thus, the great progress goes on.

—Thomas Babington Macaulay (1800–59)
38

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

Introduction

This chapter begins to frame the process 

of applying systems thinking to key 

issues in tobacco control as a prelude to 

more detailed examinations of individual 

systems approaches and their synthesis 

in subsequent chapters. The first section 

offers a brief overview of the idea of systems 

thinking and the many systems concepts 

that help inform it. The next section 

suggests the contours of an integrated 

framework for systems thinking. It does so 

by introducing the four systems approaches 

that were the specific focus of the ISIS 

project (systems organization, system 

dynamics, network analysis, and knowledge 

management and transfer). The central 

role of participatory approaches to human 

systems is described, and suggestions are 

offered about how these might be integrated 

within a new field of study. The chapter 

concludes with specific questions these 

systems approaches might help answer 

for several groups of tobacco control 

stakeholders: practitioners, researchers, 

and policy makers.

Public health issues such as tobacco control 

are not simple, linear cause-and-effect 

problems. They are systems bound together 

by a network of factors that influence and 

react with each other, much like a living 

organism. The prevalence of tobacco use 

and tobacco product consumption has 

decreased substantially in the United States 

in the past few decades in response to 

interventions such as consumer education, 

telephone quitlines for smoking cessation, 

advertising restrictions, increased taxation, 

clean indoor air restrictions, and health 

warnings. Nevertheless, tobacco use remains 

responsible for hundreds of thousands of 

preventable deaths each year. Moving past 

the current plateau in tobacco control 

outcomes requires dealing with a complex 

interplay of evolving actors and factors that 

must be addressed as a system. The purpose 

of ISIS has been to explore the potential 

of key systems approaches that address 

challenges in tobacco control, including

n Disparate communities of interest and 

frequent duplication of effort

n Limited integration of research 

and practice, so that the best 

science frequently sits unread and 

unimplemented

n A paucity of organized dissemination and 

collaboration methods

n Competition from a well-financed and 

well-organized tobacco industry that has 

integrated dissemination and networking 

efforts

n The need for more experience in evaluating 

(1) the interconnected dynamics of the 

tobacco control system and efforts of the 

tobacco industry and (2) the effects of 

these dynamics on key outcomes such 

as tobacco cessation and morbidity and 

mortality due to tobacco use

Successful program development in any 

field requires both effective strategy and 

powerful implementation—sometimes 

characterized as “doing the right thing 

right.” The ultimate primary goal of these 

systems approaches in tobacco control is to 

improve performance. Documentation of 

improvement requires direct measures of 

outputs and outcomes, such as (1) decreases 

in smoking prevalence; (2) greater efficiency 

in terms of the number of smokers served 

by direct contact programs (e.g., clinics, 

Web sites, and hotlines) per dollar invested 

and over time; and (3) higher proportions of 

programs and policies meeting standards for 

“evidence-based” interventions. The promise 

of systems approaches, backed by a growing 

body of evidence, is increased facilitation of 

progress toward such desired outcomes. 

Systems approaches may help cast new 

light on issues that affect program 

delivery in the real world: staff turnover, 
39

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

the glut of information and directives, 

isolation, multiple demands on programs, 

and multiple roles for managers. The 

world does not stand still as proponents 

of tobacco control attempt to manage 

this environment. A well-funded tobacco 

industry has the resources to anticipate 

and thwart novel initiatives. Even wellintentioned, beneficial efforts can have 

unintended negative-feedback effects. 

Therefore, flexible strategies based on widely 

accepted philosophy and best practices are 

essential. However, these strategies also 

must enable response to emerging science 

and systemic feedback.

At the broadest level, a fresh, transdisciplinary approach to thinking about 

intervention systems is likely needed, 

one that integrates a balanced and 

comprehensive blend of program and 

policy tools. Program, policy, budgetary, 

and legislative issues all arise from the 

identification and implementation of 

strategies for best practice, which are 

themselves often in flux. Moreover, the 

underlying philosophy of public health 

continues to evolve. As stated in an overview 

of the syndemics initiative of the Centers 

for Disease Control and Prevention,1 “The 

medical model of disease specialization, 

once praised for its utility and versatility, 

is proving inadequate for confronting. . . 

contemporary public health challenges.” 

The statement echoes a growing move 

toward researching public health problems 

as both multidimensional population-level 

issues and individual issues. Unless these 

crosscutting factors are viewed from a 

systems perspective, it is likely that progress 

on any initiative can become mired in the 

many interacting and competing forces. 

Developing capacity for integrated strategies 

to tackle the complexity of these issues is a 

major focus of ISIS.

Already, developments in tobacco control 

and in public health in general are starting 

to move in this direction. As outlined 

in chapter 2, tobacco control strategy 

has mirrored the shift in emphasis from 

individual behavior change to populationlevel and policy-level change. There is 

a concomitant shift from controlled 

studies of individuals to population-level 

efforts involving logic models, networks, 

and collaborations among multiple 

stakeholders—all historical precursors to 

the systems approaches described here. 

The ISIS project springs from a clear 

trend that these approaches—and more 

important, their synthesis—hold a potential 

key to solving more complex issues in the 

prevalence of tobacco use and tobacco 

product consumption and, in turn, making 

further substantive positive changes in 

public health. 

Systems and Systems 

Thinking

The Merriam-Webster Dictionary offers 

12 distinct definitions of “system.”2

The principal definition is “a regularly 

interacting or interdependent group of 

items forming a unified whole.”2 In the field 

of systems theory, system is defined as “a set 

of elements standing in interrelation among 

themselves and with the environment.”3(p159)

Hidden within these simple definitions is 

considerable complexity, a history of ideas 

spanning centuries, and the basis of a new 

scientific and philosophical paradigm.

In this monograph, systems methods

are considered specialized techniques 

or procedures for researching and 

understanding systems (e.g., system 

dynamics modeling, structured 

conceptualization, or network analysis). 

Systems approaches are broader theories or 

traditions that use systems methods within 

an organizing framework to address systems 

(e.g., general systems theory, chaos theory, 

and complexity theory). Systems thinking

is the use of systems approaches and the 
40

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

general logic that underlies them to view 

the world.

The modern idea of systems theory is 

credited to the biologist Ludwig von 

Bertalanffy, who wrote General System 

Theory: Foundations, Development, 

Applications4 in 1968. However, thinking 

about systems has a much longer history. 

The relationship between part and whole 

that serves as a foundation for systemsbased approaches5–7 is as old as European 

philosophy.3 Aristotle’s hypothesis that 

formal nature (e.g., the whole form) 

is of greater importance than material 

nature—more commonly known today as 

the principle that “the whole is more than 

the sum of its parts”—still is an accurate 

description of one of the central premises 

of systems theory.8 In the 15th century, 

Nicholas of Cusa linked medieval mysticism 

with the origins of modern science through 

the idea of coincidentia oppositorum—the 

“fight” between part and whole.3

Systems thinking spans 2,600 years to 

the time of Lao Tzu and the first formal 

description of a complex system in the yin 

and yang of the Tao. Systems thinking was 

not “born yesterday.”3 However, its modern 

incarnation has risen simultaneously from 

several fields, including quantum physics, 

biology, ecology, cybernetics, psychology, 

and sociology.3,6 It can be found in the 

physical, natural, and social sciences and is 

common in business9–11 and education.9,12–18

Depending on how wide one casts the 

net, systems thinking approaches span 

centuries, hundreds of fields, and thousands 

of scholars.19 A family tree of systemic 

thought20 includes in its “genealogy” ancient 

and contemporary scholars in a wide range 

of fields19 and illustrates the variety of 

traditions in systems thinking.

The reader who is new to systems thinking 

may be daunted by the complexity and 

volume of literature. However, these 

variations and distinct traditions of systems 

thinking have some common themes. 

These themes include the notions of 

holism, integration, interconnectedness, 

organization, perspective taking, 

nonlinearity, and constructivism. Biological, 

ecological, and organismic metaphors are 

widely used to describe these themes.4,6,7,21–29

Common misconceptions are (1) that 

systems thinking rejects traditional 

scientific views3,4,6,28–30 that emphasize linear, 

reductionist, mechanistic, and atomistic 

thinking; and (2) that systems thinking is 

framed by mechanical metaphors.31 These 

are not correct. Although systems thinking 

does emphasize holistic thinking,3,4,6,28–30 it 

complements traditional reductionist science 

rather than rejecting it. Von Bertalanffy 

wrote that it “is apparent that [systems 

epistemology] is profoundly different from 

the epistemology of logical positivism or 

empiricism even though it shares their 

scientific attitude.”4(pxxii)

Another misconception is that systems 

thinking superficially emphasizes holistic 

thinking and lacks the rigor of traditional 

science. To the contrary, systems thinking 

uses differential equations and other more 

complex mathematics to describe system 

dynamics,3,32,33 formalized qualitative systems 

methods,34 and well-reasoned systems 

metaphors,3,24,28,30,35,36 along with specific 

applications in virtually every field.6,10,11,37

The roots of systems theory4,19 have grown 

into what is sometimes described as the 

“new sciences”: general systems theory;4

complexity science;33,38–41 chaos theory and 

nonlinear dynamics;42,43 cybernetics;44,45

control theory, information theory, and 

computational simulation;46 relational 

mathematics, game theory, decision theory, 

and system dynamics;11,32 and ecology and 

set, graph, and network theory.47–50 Systems 

thinking is used to better understand system 

behaviors and to identify systems principles 

such as feedback loops, stocks and flows, 

open versus closed systems, decentralized 
41

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

versus hierarchical systems, selforganization,33,40 autopoiesis,35,51 nonlinear 

systems,43 complex adaptive systems 

(CAS),33,38,40,41,45,52 boundary conditions, 

scaling and power laws, silo effects, smallworld phenomena,47,48 emergence,53 cellular 

automata,45 and fractal self-similarity.54

Many examples of systems thinking 

contribute to an understanding of the world. 

From the systems thinking of chaos theory, 

one can learn that minuscule changes 

in initial conditions can lead to dramatic 

emergent effects and that resistant systems 

can be directed to change. From complexity 

science, one can see that complexity 

emerges from simple rules acting locally on 

independent variables. That is, biological 

and social systems often do not have 

hierarchical controls that coordinate their 

behavior but are instead self-organizing. 

From system dynamics one can learn that, 

as systems thinker Senge puts it, “cause 

and effect are not closely related in time 

and space”9(p63) and that feedback can lead 

to unintended and unforeseen outcomes. 

Understanding of control systems has been 

expanded from an “input-blackbox-output” 

paradigm3 to one that includes inputs, 

outputs, feedback, processes, flows, and 

control. These are just a few examples of 

systems thinking concepts from a broad 

range of disciplines.

Frameworks for Systems 

Thinking

There is no single and correct method of 

systems thinking. Borrowing an idea from 

Collins and Porras,55 systems thinking 

rejects the “tyranny of either/or” and 

embraces the “genius of and/both.” Systems 

thinking is a worldview that balances 

part and whole and focuses on complex 

interrelationships and patterns from 

multiple perspectives.28,37 An inherently 

transdisciplinary approach that blends many 

perspectives, it has been characterized as 

an Odyssean thinking style that combines 

Apollonian and Dionysian perspectives.56,57

Systems thinking is an epistemological 

stance transcending reductionist, critical 

realist, and constructivist perspectives. As 

an applied science, it bridges theory and 

practice. It is a conceptual revolution that 

has led to an emerging understanding of the 

complexities of the systems that make up 

the world. Systems thinking provides new 

tools to address practical, complex problems 

in much the same way mechanical thinking 

enabled previous generations to build 

agricultural or industrial structures. 

A number of scholars have developed 

frameworks for systems thinking—sets of 

principles, rules, skills, or ideas that they 

claim underlie systems thinking. Each 

framework has advantages and disadvantages 

and was developed in the context of a 

particular purpose. Each was created 

from a different perspective or systems 

tradition. The summaries of some of the 

frameworks presented here are not meant 

to be exhaustive or definitive. However, each 

one gives a glimpse of systems thinking, and 

collectively they help to convey the essence 

of systems thinking. 

Some scholars see system dynamics as 

a branch of systems theory. Others see 

systems theory as a branch of system 

dynamics. Scholars of system dynamics 

often use the term “systems thinking” to 

refer to system dynamics thinking,9,58–64

dropping the word “dynamics” as a 

descriptor. For example, “systems thinking” 

is defined by one source as follows:

Systems thinking is an approach for 

studying and managing complex feedback 

systems, such as one finds in business and 

other social systems. In fact, it has been 

used to address practically every sort of 

feedback system. System dynamics is more 

or less the same as systems thinking, but 

[it] emphasizes the usage of computersimulation tools. System dynamics is based 
42

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

on systems thinking, but [it] takes the 

additional steps of constructing and testing 

a computer-simulation model.65

Richmond offers an example of a framework 

for system dynamics thinking in his book 

The “Thinking” in Systems Thinking: Seven 

Essential Skills.59 He compares seven skills 

of systems thinking that are derived from 

system dynamics with skills of traditional 

styles of thinking (table 3.1).59 Richmond’s 

framework illustrates some of the key notions 

of systems (dynamics), including the ideas of 

causal linkages and feedback loops. Chapter 5 

in this monograph explores system dynamics 

in greater depth. 

System dynamics is a type of systems 

thinking that has gained popularity in 

business settings such as organizational 

learning. In The Fifth Discipline: The Art 

and Practice of the Learning Organization,9

Senge lays out five disciplines for building 

a “learning organization.” According to 

Senge, learning organizations are adaptive 

and generative and are necessary for survival 

and competition. His five disciplines66 are as 

follows:

1. Systems thinking: The integrative [fifth] 

discipline that fuses the other four into a 

coherent body of theory and practice

2. Personal mastery: Approaching life and 

work “as an artist would approach a work 

of art”

3. Mental models: Deeply ingrained 

assumptions or mental images “that 

influence how we understand the world 

and how we take action”

4. Shared vision: With genuine vision 

“people excel and learn, not because they 

are told to, but because they want to”

Table 3.1 Richmond’s Seven Skills of Systems Thinking

Traditional skill Systems thinking skill

Static thinking

Focusing on particular events

Dynamic thinking

Framing a problem in terms of a pattern of behavior over 

time

System-as-effect thinking

Viewing behavior generated by a system as driven by 

external forces

System-as-cause thinking

Placing responsibility for a behavior on internal actors who 

manage the policies and plumbing of the system

Tree-by-tree thinking

Believing that really knowing something means 

focusing on the details

Forest thinking

Believing that to know something requires understanding 

the context of relationships

Factors thinking

Listing factors that influence or are correlated with 

some result

Operational thinking

Concentrating on causality and understanding how a 

behavior is generated

Straight-line thinking

Viewing causality as running in one direction, with each 

cause independent from other causes

Closed-loop thinking

Viewing causality as an ongoing process, not a one-time 

event, with effect feeding back to influence the causes 

and the causes affecting each other

Measurement thinking

Searching for perfectly measured data

Quantitative thinking

Accepting that one can always quantify, even though one 

cannot always measure

Proving-truth thinking

Seeking to prove models to be true by validating them 

with historical data

Scientific thinking

Recognizing that all models are working hypotheses with 

limited applicability

Note. From Richmond, B. 2000. The “thinking” in systems thinking: Seven essential skills. Toolbox Reprint series. Waltham, MA: 

Pegasus Communications. Used with permission.
43

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

5. Team learning: Engagement of team 

members in true dialogue, with 

assumptions suspended

Senge9 outlines 11 laws of the fifth 

discipline, which he derives from lessons in 

fields as diverse as chaos theory, complexity 

theory, organizational theory, management 

theory, and system dynamics:

1. Today’s problems come from yesterday’s 

solutions.

2. The harder you push, the harder the 

system pushes back.

3. Behavior grows better before it grows 

worse.

4. The easy way out usually leads back in.

5. The cure can be worse than the disease.

6. Faster is slower.

7. Cause and effect are not closely related 

in time and space.

8. Small changes can produce big results, 

but the areas of highest leverage often 

are the least obvious.

9. You can have your cake and eat it too, 

but not all at once.

10. Dividing an elephant in half does not 

produce two small elephants.

11. There is no blame. 

Similarly, Gelb sees systems thinking as 

the glue that binds his seven principles 

of effective thinking. Gelb proposes that 

effective thinking in today’s world can be 

framed by seven principles67,68 he claims are 

characteristic of Leonardo da Vinci’s genius:

1. An insatiable quest for knowledge and 

continuous improvement

2. Learning from experience

3. Sharpening the senses

4. Managing ambiguity and change

5. Whole-brain thinking

6. Body–mind fitness

7. Systems thinking

Gelb believes68 that da Vinci’s principles will 

help people to cultivate creativity every day, 

balance analysis with imagination, sustain 

continuous learning, embrace ambiguity 

and uncertainty, nurture creativity and 

innovation in the workplace, and apply 

systems thinking to problem solving. 

Capra, a physicist and systems thinker, 

proposed ecological thinking, a systems 

thinking model he defines as “core concepts 

in ecology that describe the patterns and 

processes by which nature sustains life.”6(p231)

Table 3.2 illustrates his six principles of 

ecology. Like system dynamics thinking, 

ecological thinking emphasizes cyclic 

thinking, processes over time, and feedback. 

However, it also gives more salience to 

networks, being nested, and development. 

Checkland developed soft systems 

methodology in the 1960s. In the classic 

form of these methods,69,70 a researcher or 

an observer experiencing a problem makes 

as few presumptions about the nature of 

the problem as possible. A “rich picture” 

then is developed by attempting to capture 

in detail the logic, relationships, value 

judgments, and feel (tone) of the problem 

situation. Essential features of the system 

(root definition) are then characterized. The 

mnemonic device CATWOE is used in this 

step: customers, who are beneficiaries of 

the system; actors, who transform inputs to 

outputs; transformation of input to output; 

weltanshauung (relevant worldviews); 

owners, who have veto power over the 

system; and environmental constraints. 

CATWOE is used to construct the root 

definition, which takes the following form: 

“A system that does P (what) by Q (how) to 

contribute to achieving R (why).” Then a 

“cultural analysis” is undertaken to explore 

the roles, norms, values, and politics 
44

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

relevant to the root definition. A systems 

model is developed by using only the 

elements of the root definition and cultural 

analysis in a way that flows logically from 

the two elements. The focus of this step is 

to limit the number of possible components 

to the six or fewer CATWOE elements, 

while demonstrating all the properties of 

the system. Thus, the focus is to balance 

the simplicity of few components with the 

complexity of system properties. Different 

root definitions and CATWOE elements 

are used to construct several models 

illustrating how multiple perspectives relate 

to the problem. Finally, these models are 

discussed, compared, and contrasted by 

using the problem situation and insight 

from this process to identify ways to improve 

the problem situation.

In his book Hidden Order: How Adaptation 

Builds Complexity,71 Holland details a 

framework for studying CAS, proposing 

seven basics.71(p10) “We aggregate similar 

things into categories (and) then treat 

them as equivalent.”71(p10) Aggregations 

are reusable and recombinable and, once 

formed, can act as agents or meta-agents. 

“Tagging facilitates the formation of 

aggregates.”71(p12) Holland gives the example 

of a banner or flag that “is used to rally 

members of an army or people of similar 

political persuasion.”71(p13) He explains 

that CAS use tagging to “manipulate 

symmetries” and to “ignore certain 

details while directing our attention to 

others.”71(p12) Another property of CAS 

is nonlinearities, which “almost always 

make the behavior of the aggregate more 

complicated than would be predicted by 

summing or averaging.”71(p23) A property 

Holland calls flows includes two types 

of effects: multiplier and recycling. The 

property of flows explains how resources 

move and change as they proceed through 

the system. In describing the property of 

diversity, Holland writes, “it should be 

evident then that we will not find CAS 

settling to a few highly adapted types that 

exploit all opportunities. Perpetual novelty 

is the hallmark of CAS.”71(p31) Anticipation is 

a critical capability for CAS. CAS anticipate 

or make predictions by using internal 

models. For example, “insectivorous birds 

Table 3.2 Capra’s Six Principles of Ecology 

Networks At all scales of nature, we find living systems nesting within other living systems—

networks within networks. Their boundaries are not boundaries of separation but 

boundaries of identity. All living systems communicate with one another and share 

resources across their boundaries.

Cycles All living organisms must feed on continual flows of matter and energy from their 

environment to stay alive, and all living organisms continually produce waste. However, an 

ecosystem generates no net waste, one species’ waste being another species’ food. Thus, 

matter cycles continually through the web of life.

Solar Energy Solar energy, transformed into chemical energy by the photosynthesis of green plants, 

drives the ecological cycles.

Partnership The exchanges of energy and resources in an ecosystem are sustained by pervasive 

cooperation. Life did not take over the planet by combat but by cooperation, partnership, 

and networking.

Diversity Ecosystems achieve stability and resilience through the richness and complexity of their 

ecological webs. The greater their biodiversity, the more resilient they will be.

Dynamic Balance An ecosystem is a flexible, ever-fluctuating network. Its flexibility is a consequence of 

multiple feedback loops that keep the system in a state of dynamic balance. No single 

variable is maximized; all variables fluctuate around their optimal values.

Note. From Capra, F. 2002. The hidden connections: Integrating the biological, cognitive, and social dimensions of life into a science 

of sustainability, 231. New York: Doubleday.
45

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

anticipate the bitter taste of butterflies 

with a particular orange and black wing 

pattern.”71(p31) One paradox CAS must solve 

is how to use internal models based on 

repetition in constantly changing and novel 

situations. How can CAS use an internal 

model based on a repeating pattern if each 

situation is slightly different or totally 

novel? Holland proposes that building 

blocks are used and reused, allowing CAS 

to decompose novel situations into parts, as 

a child’s building blocks are used to create 

novel structures.

Systems Concepts

Important systems concepts are relevant to 

different types of systems and constitute a 

unique lexicon of systems thinking. Here, 

several major systems concepts that inform 

systems thinking are introduced. Rather 

than being comprehensive, the intent is to 

present notable systems concepts within 

this rich historical tradition. Each concept 

may represent an entire specialized field of 

study, networks of scholars and researchers, 

scientific journals, conferences, and societies. 

CAS self-organize, adapt, and evolve over 

time. In a CAS, semiautonomous agents 

interact on the basis of simple local rules. 

The term “complex adaptive system” often 

is used interchangeably with the term 

“complexity theory,” which proposes that 

higher level complexity emerges from lower 

level simplicity. In an example highlighted 

in this chapter (see sidebar, this page), 

the boids, sporting fans, fish, or birds are 

adaptive agents because they adapt to their 

environments. The environment of an 

adaptive agent includes other adaptive agents.

Interaction between adaptive agents or 

systems often is called feedback, which 

refers to the mutual causality of the 

relationship (e.g., positive/exciting or 

negative/dampening). In a similar vein, the 

term cellular automata, originally developed 

Simple Rules and Superorganisms

In 1986, Reynolds made a computer model of coordinated animal motion such as bird flocks and 

fish schools, calling the simulated flocking creatures “boids.”a The basic flocking model consisted 

of three simple “steering behaviors”:

n Separation: Steer to avoid crowding local “flockmates.”

n Alignment: Steer toward the average heading of local flockmates.

n Cohesion: Steer to move toward the average position of local flockmates.

Each boid reacts “only to flockmates within a small neighborhood,” so the boids are interacting only 

with neighbors. Flockmates that lie outside the individual boid’s neighborhood are ignored. 

Reynolds’s computational experiment models the complex flocking behavior of boids, fish, and birds 

by using simple local rules acting on independent variables. The result is emergent complexity—a 

collection of individual organisms that act like a single superorganism. 

An even simpler example of the complex behavior of superorganisms that is based on simple rules 

can be found at national sporting events. The stadium wave, in which fans simulate an undulating 

elliptical blanket around the stadium, is based on a single, simple, local rule: if your left neighbor 

stands up, then stand up. The initial starting condition for this complex phenomenon is a single line 

of standing people.

Note. Adapted from Cabrera, D. 2002. Patterns of knowledge: Knowledge as a complex, evolutionary system; 

An educational imperative. In Creating learning communities, ed. R. Miller. Brandon, VT: Solomon Press.

a

Reynolds, C. 2006. Boids: Background and update. http://www.red3d.com/cwr/boids.
46

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

by von Neumann72 in the computing 

arena, also refers to the idea of modeling 

biological or artificial self-reproduction 

by using simple interacting “cells” that 

follow simple, local rules.72 Computational 

cellular automata models are popular and 

useful because they explicate many of the 

essential patterns found in more complex, 

self-organizing, real-world systems. Selforganization occurs in CAS as spontaneous 

patterns or features of a system that emerge 

at macro levels resulting from the collective 

interactions of microscale independent 

agents and local rules. These features are 

often called dissipative structures, because 

they persist as stable structures for longer 

durations, even though, internally, there is 

a continuous and dynamic flow of matter 

or energy. The concept of emergence is 

related because it refers to the existence of 

properties at a higher level (e.g., the level of 

the whole) that cannot be found at a lower 

level (e.g., the level of the parts). 

The concept of autopoiesis (literally, selfproduction), which refers to self-producing 

systems, also is related. Two Chilean 

biologists, Maturana and Varela,51 developed 

the concept of autopoiesis. Autopoiesis is 

similar to Kauffman’s autocatalytic theory of 

sets in which the origin of life occurs when a 

collection of molecules catalyze each other. 

Kauffman writes, “Whenever a collection of 

chemicals contains enough different kinds 

of molecules, a metabolism will crystallize 

from the broth.”33(p43),40

Nonlinear systems are systems in which the 

whole does not equal the sum of its parts 

or, more technically, systems that can be 

represented by a curvilinear pattern, rather 

than a linear pattern. Nonlinear systems 

are capable of self-organization and chaos. 

There are many implications of chaos. Chief 

among them is the understanding that small 

changes in initial conditions can result 

in large, systemwide effects (sensitivity to 

initial conditions). The popularized story 

of Lorenz’s butterfly—an insect that by 

flapping its wings causes a chain of events 

leading to a hurricane on the other side of 

the world—often is used as an anecdote for 

understanding chaos theory. 

Both linear and nonlinear systems are 

attracted to a subset of their phase space 

called an attractor. Attractors are modes or 

phases of system behavior. Attractors (e.g., 

fixed-point, periodic, or strange) determine 

the behavior of a system within a particular 

space. A marble tossed into a salad bowl 

will, over time, settle into an attractor at the 

bottom of the bowl (the basin of attraction). 

A chaotic (strange) attractor is fractal. 

Fractals are geometric patterns, a set of 

points, or structures that are self-similar 

across different levels of scale. Fractals, 

discovered by Mandelbrot, have become 

popular in science and art; many fractal 

patterns are strikingly beautiful. When a 

system exhibits fractal geometry, the parts 

appear to be similar to the whole, even 

though they belong to different scales. The 

branching pattern of trees is fractal, as are 

the coastline of England and the branching 

alveoli of the lung.54 All systems evolve 

in some way. Evolution can be defined in 

Darwinian terms as natural selection and 

the descent of species, or in more general 

terms, as behavior over time. 

Finally, network theory is a general theory 

used throughout physics, biology, and the 

social sciences that explores the behaviors, 

structure, and function of an interacting 

set of items (e.g., objects, people, concepts, 

or points).47,48,50,54,73,74 Networks are made 

up of vertices (a set of items) and edges

(connections among the items). Vertices and 

edges are called sites and bonds in physics, 

nodes and links in computer science, and 

actors and bonds in sociology.50 Chapter 6, 

“Understanding and Managing Stakeholder 

Networks,” in this monograph, presents 

network approaches to systems thinking. 

Systems thinking can be simple and 

complex, theoretical and practical, 
47

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

scientifically rigorous and philosophically 

grounded. In the context of tobacco control, 

it is important to consider the types of 

systems questions that people with different 

roles in tobacco control need to address. 

Chapters 4 through 7 address in depth 

four broad systems approaches—systems 

organizing and management, system 

dynamics modeling, network analysis, 

and knowledge management—and their 

implications for tobacco control.

Systems Thinking: 

Toward an Integrated 

View

As understanding of systems thinking, 

systems approaches, and systems methods 

increases, it becomes apparent that there is 

a need to integrate the diverse and myriad 

traditions into a more coherent whole. The 

ISIS project is an initial and somewhat 

limited foray into such an endeavor. 

Nevertheless, one can begin to sketch some of 

the central components of a more integrated 

view of systems for tobacco control and public 

health, based on the work done to date. In 

addition to consideration of the construct of 

systems thinking, an integrated approach to 

systems thinking would include the following 

components (and likely much more):

n Case studies of systems approaches.

This would include studies of the variety 

of systems approaches and the methods 

that are associated with them. The 

ISIS project has begun studies in four 

systems approaches: systems organizing, 

system dynamics, network analysis, and 

knowledge management.

n Participatory methods for systems 

thinking. In human systems like 

tobacco control and public health, better 

participatory methods for modeling 

systems and for thinking from a systems 

perspective need to be developed.

n Evolution of systems studies. As more 

studies of systems approaches and 

methods are developed, the evolution 

of a “field” of systems studies that 

integrates across diverse traditions will be 

encouraged.

Case Studies of Systems 

Approaches 

An integrated approach to systems thinking 

should involve trial-and-error experimenting 

with a variety of potentially promising 

systems approaches and methods to learn 

how they work and what their potential 

advantages and costs are in real-world 

contexts. A central purpose of ISIS has been 

to identify several promising approaches 

and apply them to help “navigate” current 

problems in tobacco control. 

The four core systems approaches examined 

by ISIS are outlined in table 3.3 along 

with brief descriptions of the goals of each 

approach and the case studies conducted in 

the ISIS project. Many of these approaches 

are newly developing. Other approaches, such 

as system dynamics, have been available for 

years but have rarely been applied in this 

area. Because the application of systems 

thinking to tobacco control is in its early 

stages, the excitement and the promise of this 

undertaking are just beginning to be realized.

These approaches all serve as parts of a 

broad, systems-based view of the world that 

can be applied specifically to tobacco control 

and more generally to public health. More 

important, these approaches reflect more 

general trends of using systems approaches 

to understand and manage increasingly 

complex phenomena in all walks of life, 

ranging from organizational behavior9 to 

national defense.75 These four approaches 

were chosen because of their promise in 

key areas of tobacco control. They are not 

the only systems approaches, nor are they 

necessarily the best. They are part of a much 
48

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

larger diverse mosaic of potential systems 

approaches hinted at in the review earlier in 

this chapter.

The methods described here as part of the 

ISIS project have the potential to deliver 

incremental improvements in tobacco 

control and public health outcomes. 

However, each method also complements 

the others. Together, these methods provide 

a fundamentally new way to address the 

complex root causes of current tobacco use. 

Frameworks that enable integration of a 

number of systems-based approaches also 

would be useful. 

An integrated approach to systems thinking 

will likely result in the evolution of one or 

more fields of study that enable researchers 

and practitioners to learn about the construct 

of systems thinking, and the history and 

variety of approaches and methods, and 

to begin to develop crosscutting and 

cross-disciplinary perspectives on systems 

thinking. Such fields already are emerging. 

For example, frameworks such as Integration 

and Implementation Sciences76 (described in 

table 3.4 and in the sidebar in Appendix B, 

p. 272) propose a core theoretical base from 

which systems methodologies may be 

developed and applied to specific areas. They 

provide a potential transdisciplinary base 

for studying system-level problems faced 

in tobacco control efforts and may help fill 

important gaps in methodologies between 

complementary disciplines. For example, 

chaos and complexity theory often takes an 

exploratory approach to the behavior of a 

system based on simulations of interactions 

of individual agents who follow simple 

rules, whereas traditional system dynamics 

seeks to identify relationships and optimize 

Table 3.3 Core Areas Examined by ISIS and Goals

Core area Long-term goals ISIS case studies 

How we organize: 

Systems organizing

Participatory, stakeholder-based 

approaches to systems organizing 

Concept-mapping studies of local 

strength of tobacco control factors 

and of designing for research 

dissemination

How we understand dynamic 

complexity:

System dynamics modeling

n Development of systems models 

for tobacco control factors and 

processes for analyzing and 

evaluating them n Telling the tobacco control 

“story” in qualitative as well as 

quantitative terms, so it can reach 

a wider audience

n Causal model for tobacco cessation 

based on data in clinical and 

community guides n Quantitative simulation of 

intervention impacts in different 

age groups

Who we are:

Network analysis

Network-based structures for future 

collaborative tobacco control efforts

n Examination of network issues 

in the Global Tobacco Research 

Network n Case study of network analysis in 

ongoing multistate tobacco control 

evaluation project 

What we know:

Knowledge management and 

knowledge transfer

Infrastructure for knowledge 

management and transfer in tobacco 

control efforts, incorporating both 

explicit and tacit knowledge 

Review of current dissemination 

efforts (e.g., NCI’s Cancer Control 

PLANET initiative)a and analysis of 

knowledge management needs

Note. ISIS = Initiative on the Study and Implementation of Systems; NCI = National Cancer Institute; PLANET = Plan, Link, Act, 

Network with Evidence-based Tools.

a

Cancer Control PLANET is an NCI-funded portal providing on-line access to research results, partner organizations, and evidencebased programs and products for cancer control, available at http://cancercontrolplanet.cancer.gov.
49

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

outcomes.77 An integrated systems study 

field can enhance understanding of the 

advantages of these different approaches and 

suggest how new hybrid approaches might 

be formed by combining or integrating 

features of each. For example, figure 3.1 

illustrates how the four systems approaches 

studies in the ISIS project can potentially 

be coupled in various pairings and even 

integrated as a set. The framework of 

Integration and Implementation Sciences 

(table 3.4) serves as one example of using an 

integrative approach to link these disciplines 

to address core problems in public health 

(e.g., the paradox of society’s inability to 

implement known cost-effective solutions to 

the 10 leading causes of preventable death 

worldwide, as identified by the World Health 

Organization).78 The ISIS project sought to 

apply key components from this framework 

to existing problems in tobacco control, as a 

proof of concept for how they can integrate 

to form a new approach to complex public 

health issues.

ISIS is only a first step in applying systems 

approaches to tobacco control. An aim of 

this monograph is to show the potential 

value of these approaches individually and 

in combination and to point to broader 

frameworks for further development of these 

approaches. In this sense, ISIS attempts both 

to encourage and model how an emergent 

field of systems studies might approach its 

task. It is not clear at this point whether such 

a field eventually will be a formal academic 

Figure 3.1 Combining ISIS Approaches for Applications 

SDM + NA

+ KM

NA + KM

SDM

SO + SDM

SDM 

NA

KM

S0

SO + SDM

+ NA + KM

Note. ISIS = Initiative on the Study and Implementation of Systems; SO = systems organizing; SDM = system dynamics modeling; 

NA = network analysis; KM = knowledge management.

Table 3.4 Framework of Integration and Implementation Sciences

Integration and Implementation Sciences 

framework ISIS case studies

Systems thinking and complexity science System dynamics simulation

Participatory methods System dynamics simulation; concept-mapping projects 

with multiple stakeholders

Knowledge management, exchange, and implementation Network analysis 

Knowledge management and knowledge transfer
50

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

discipline, a transdisciplinary specialization, 

or some other form. But however the field 

evolves, the idea of systems studies is one 

whose time has come.

Participatory Methods for 

Systems Thinking

An integrated approach to systems thinking 

needs to include the recognition that 

participatory methods are integral to human 

systems approaches. All four of the systems 

approaches studied in the ISIS project 

integrate participatory methods into how 

they address systems. An integrated approach 

would have the study and evolution of 

participatory methods as a major focus.

Brown and colleagues79 outline a framework 

for stakeholder inclusion that views 

participatory methods as forms of structured 

engagement among researchers, community 

representatives, business groups, and policy 

makers to accomplish the collective solution 

of problems as a system. They recognize the 

importance of individuals, societies, and 

cultures as aspects of complexity.

Participatory methods encompass a wide 

range of engagements, including action 

research, Delphi methods, consensus 

building, and numerous intuitive unnamed 

methods.80 These methods involve two or 

more parties and a range of disciplines 

and sectors, can be short- or long-term, 

can challenge elites or be controlled by 

them, and can vary in the degree to which 

they empower marginalized groups. 

Participatory methods enable practitioners 

and researchers to learn together about 

problems of mutual interest in a way that 

provides reciprocal benefits. They can 

combine perspectives to build new concepts, 

insights, and/or practical innovations that 

they could not produce alone.

The four key elements in contemporary 

thinking about participatory methods 

are (1) paradigms, goals, and interests; 

(2) relationships and organization; (3) methods 

and technologies; and (4) contextual forces 

and institutions. Engagement between 

researchers and practitioners must take into 

account different social, political, and ethical 

paradigms; different engagement goals and 

interests; and different expectations about 

accountability. Furthermore, the relationships 

and organization must be able to accommodate 

power differences; build trust; and develop 

effective control, ownership, division of work, 

and decision-making processes. The methods 

and technologies used within this framework 

can be divided into four types:

1. Participatory, focused, puzzle-solving 

methods are appropriate when answers 

to well-defined problems are needed. 

Such methods make efficient use of the 

comparative advantages of each party 

and do not require expensive ongoing 

relationships.

2. Exploration of issues and agenda 

setting are appropriate when multiple 

views are needed for understanding 

complex, ill-structured problems. 

These methods allow many voices to be 

involved in identifying issue patterns and 

implications and set the stage for wide 

participation in problem solving.

3. Participatory intervention and 

assessment methods document, analyze, 

and improve the quality of interventions 

and best practices. They focus on 

existing programs and activities and are 

particularly useful for identifying the 

costs and benefits of possible solutions.

4. Participatory methods for long-term 

development of domains involve ongoing 

co-inquiry to build perspectives, theory, 

and practice in new domains. These 

methods are particularly useful in 

providing in-depth analysis of poorly 

understood problems over the longer 

term. They can produce new paradigms 

for understanding intractable problems 
51

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

and lead to fundamental changes in 

theory and/or practice.

Contextual forces and institutions are the 

final element of the framework. They take 

into account the broad range of factors such 

as political, social, and economic forces on 

global, national, and local levels that are at 

play at the time of engagement. This element 

also allows for the impact of the auspices 

under which the participatory methods are 

conducted and of the institutional bases of 

the researchers and practitioners.

Participatory methods are central to 

bringing stakeholders into the consideration 

of complex problems. Ideally, their use 

enables those affected to have a say in the 

management of uncertainties and of the 

inability to find perfect solutions. However, 

strategies for guiding researchers on which 

methods to use still are being created, and 

experience with key issues (such as how 

to build trust) is limited. This scenario 

underscores the need for continuous 

evolution of closer links between systems 

thinking and participatory methods. 

Chapter 4 of this monograph considers 

participatory methods in greater detail 

and describes their critical role in systems 

organization and management. 

Application of Systems 

Thinking in Tobacco 

Control

Systems thinking approaches are by their 

very nature context dependent. Public health 

issues such as tobacco control provide an 

ideal laboratory for their implementation. 

The next section describes several 

frameworks for understanding systems 

thinking and presents a brief overview of the 

vast terrain of systems concepts, suggests 

an integrated view of the idea of systems 

thinking that is emerging in part from the 

work conducted in this project, and outlines 

some of the implications of systems thinking 

for three key stakeholder groups in tobacco 

control—practitioners, policy makers, and 

researchers.

Case Studies of Systems 

Approaches 

On a practical level, stakeholders certainly 

will question how systems thinking and 

systems approaches apply to real-life 

situations they regularly encounter. Each 

of the approaches, either in part or in 

combination, provides promising methods 

for tackling the sometimes disparate 

problems faced by various stakeholder 

groups. The next three subsections present 

some of the “real-world” questions several 

groups of tobacco control stakeholders 

might pose about their most pressing 

issues. Here, three stakeholder groups 

that are especially important for early 

implementation of systems thinking 

and approaches in tobacco control are 

considered:

1. Practitioners: Stakeholders and 

managers of “agencies” that deliver state 

or local programs for prevention and 

cessation of tobacco use.

2. Researchers: Scientists and analysts 

who develop the evidence base for 

effective tobacco control, such as heads 

of research institutes or those working 

at the interface of tobacco control 

programs and research.

3. Policy makers: Politicians and national 

agency executives who make decisions 

about policy and strategy.

ISIS and the Practitioner

Practitioners often represent the front line 

in delivering tobacco control interventions 

to individuals and populations. The 
52

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

following questions suggest practitioner 

issues that could be addressed via systems 

approaches.

n How can I cope with competition 

from other organizations for scarce 

resources? Funding is almost always a 

concern for practitioners. The changing 

political climate and the previous 

successes of tobacco control efforts 

make it difficult for practitioners to 

argue effectively for resources that often 

are scarce. Practitioners frequently 

are faced with competition from 

similar organizations and must find 

a balance between effectively stating 

a need for funding and presenting 

their organization and previous 

accomplishments positively.

n How do I communicate the positive 

outcomes my organization has 

achieved while arguing for continued/

additional funding? When applying for 

a continuation of funds, practitioner 

organizations face a dilemma. The 

program must appear to be effective, yet 

justify the need for continued work. This 

is a common issue in which practitioners 

and policy makers interface. It is 

particularly salient in the evidence-based 

environment of tobacco control efforts.

n How can I maintain trust with my 

clients when changes in funding levels 

alter the services I am able to provide?

Practitioners committed to tobacco 

control and to their clientele may find 

it difficult to reduce or restrict services 

they view as necessary. Frequently, 

little notice is given when changes 

occur. Practitioners must be prepared 

to communicate “bad news” to smokers 

and other clients who rely on their 

services and who may feel unimportant, 

frustrated, and angry. Decisions about 

the changing nature of services often 

are made outside the organization, and 

practitioners may feel as though they are 

voiceless in the policy arena.

n How can I spend more time in the 

field and less time with administrative 

details? The effects of top-down decision 

making also are evident in the amount 

of bureaucratic paperwork that requires 

increasingly more of the practitioner’s 

time. In an attempt to ensure that 

money is being spent only on highquality, effective programs, policy 

makers frequently require increased 

reporting from funded agencies. These 

requirements often take valuable time 

away from the “real work” that needs to 

be accomplished. Moreover, it may seem 

as though more time is spent reporting 

on what is being done than on doing 

anything to help smokers. This situation 

is especially frustrating when funding 

levels are reduced or when increased 

reporting responsibilities accompany 

reductions in funding. 

n Where can I find succinct, clear, and 

practical information on best practices?

Because of the limited time practitioners 

often have to accomplish their goals, 

keeping abreast of the latest research 

discoveries and finding information 

relevant to the practitioner’s organization 

can be particularly difficult. Research 

journals are designed for researchers 

rather than practitioners and often 

are not organized for simple access to 

knowledge.

ISIS and the Researcher

Researchers play a key role in developing the 

evidence base and underlying science behind 

tobacco control efforts. The following 

questions present researcher issues that 

could be addressed via systems approaches.

n How do we keep our research from 

sitting unread in journals? Academic 

institutions place a high value on 

publications in peer-reviewed journals 

and frequently discount writing that is 

geared toward practitioners. Taking the 
53

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

time to write for a more general audience 

is not highly valued, and researchers 

often are pressed for time. Research 

discoveries are shared with other 

researchers from similar fields in journals 

or at conferences, but the ideas are rarely 

put into practice.

n Why don’t more people use the science 

that we develop? Researchers often work 

in isolated groups and do not have access 

to practitioners and others who might 

put their work into practice. Although 

dissemination often is a goal, the existing 

pathways of dissemination are not highly 

effective. Moreover, as described here, 

practitioners frequently have trouble 

finding time to keep abreast of research. 

At a deeper level, research may not 

connect with the immediate goals and 

priorities of practitioners.

n Where can we connect with other 

researchers who have common or 

complementary interests but are 

in different departments or fields?

In addition to dealing with weak 

networks between researchers and 

practitioners, researchers often 

struggle to make connections with 

other researchers outside their primary 

disciplines. Although tobacco control 

is a transdisciplinary field that relies on 

knowledge from a wide variety of areas, 

it often is difficult to identify appropriate 

collaborators with different backgrounds.

At another level, even though funding 

agencies are increasingly interested 

in transdisciplinary collaborations, 

partnerships are difficult to form in an 

environment in which research silos are 

the predominant force. Collaborations 

traditionally have been formed by 

researchers who work in the same field, 

read the same journals, and attend 

the same conferences. The changing 

environment makes the development 

of extended, well-funded networks a 

challenge for ongoing research.

n How can we streamline the process of 

approval and funding for our work?

Large funding bodies make it more 

difficult for individual researchers and 

laboratories to obtain funding, because 

their focus increasingly shifts toward 

funding large-scale projects involving 

multiple principal investigators. Such 

projects require (1) a great deal of 

logistical support, not only to conduct 

the project, but also to organize 

proposals and apply for funding; (2) a 

high level of understanding of the needs 

of the target population; and (3) the 

ability to adequately articulate practical 

implications of the research to the 

funding organizations.

ISIS and the Policy Maker

Policy makers not only provide leadership 

among tobacco control stakeholders groups, 

but also play a key role in the funding 

decisions and policy interventions that are 

increasingly becoming central to tobacco 

control efforts. The following questions 

focus on policy maker issues that could be 

addressed via systems approaches.

n What priorities dictated past resource 

allocation, and what priorities does 

the future dictate? Policy makers, as 

the primary source of funding for both 

research and tobacco control programs, 

have the unique role of bridging 

both research and practice. Financial 

implications are at the forefront of many 

decisions and are a critical concern for 

most policy makers.

n How can we get more “bang for our 

buck” in research expenditures? The 

changing tobacco control environment 

alters the amount of funding available 

and places limitations on how available 

funds can be spent. Lessons learned must 

be considered when decisions about 

future allocations are made, and the 
54

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

available money must be stretched to 

cover many pressing needs. 

n How can we synthesize all of the “silos” 

of information out there? To accomplish 

more for less, research endeavors 

need to be more streamlined and 

collaboration across disciplines must 

increase. There is a constant struggle 

between the desire to fund short-term 

projects with immediate results versus 

longitudinal projects that explore longterm health outcomes.

n How can we reduce or eliminate 

duplication of effort among stakeholder 

organizations? Coordinating the sharing 

of resources and information also is a 

struggle for practitioners. Policy makers 

have the responsibility to ensure that 

efforts are not duplicated and that 

ineffective practices are not implemented.

n How can we persuade more professionals 

to make use of evidence-based practices?

Holding organizations accountable 

and requiring reporting are the tools 

policy makers use to address these 

concerns. However, organizations 

frequently complain that they do not 

have the time or resources to conduct 

complex evaluations that will provide 

the necessary information. Without 

proper evaluations, policy makers 

cannot determine whether funds are 

wisely spent, whether organizations are 

achieving desired outcomes, or whether 

best practices are being used. 

From Stakeholders to Synthesis

Questions such as those discussed 

previously highlight issues of concern to 

specific stakeholders in tobacco control. 

Systems approaches hold the potential to 

address these issues. However, they also 

speak to a much broader area, moving 

from an environment of “What’s in it for 

me?” to one in which professionals have 

sufficient understanding of their own 

systems to ask, “What’s in it for all of us?” 

With improved linkage, visibility, and 

participation—driven by approaches such as 

systems models, networks, and knowledge 

bases—stakeholders such as those discussed 

here have the potential to address broader 

questions:

n How can we engage the public generally 

and people at risk from smoking to build 

a consensus agenda for how best to 

reduce smoking prevalence and tobacco 

consumption?

n How can we link our efforts to work more 

efficiently?

n How can we learn from each other’s 

knowledge to forge better solutions to the 

problems we address? 

n How can we better integrate research and 

practice?

Within the answers to such questions are 

the keys to realizing the potential of systems 

approaches to make substantive change 

in tobacco control, while at the same time 

addressing individual stakeholder issues 

such as those outlined here. The lesson of 

many systems, whether they are successful 

organizations or natural ecosystems, is 

that fundamental interconnectedness is, 

unto itself, critical to achieving successful 

outcomes. A major aim in the ISIS project 

was to combine systems approaches that 

address specific needs by setting a much 

broader goal, namely, the linkage of 

these approaches and their communities 

of interest into a new tobacco control 

environment that holds a much greater 

benefit for all parties.

Summary

The current tobacco control environment 

consists of a broad mosaic of individuals 

and organizations with a common goal of 
55

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

reducing smoking prevalence and tobacco 

consumption and associated morbidity 

and mortality. The path to this goal still 

suffers from a gap in the linkage between 

current science and clinical and public 

health practice. The general premise offered 

here is that integrated systems thinking, 

approaches, and methods can help fill this 

gap. The application of systems thinking 

to tobacco control holds the promise of an 

integrated, dynamic process with several 

potential benefits, including the following:

n Development of clearer, collaborative 

relationships within the tobacco control 

community

n Improved alignment of resources and 

networks toward effective, evidence-based 

practices

n More efficient, nonduplicating use of 

resources

n Better understanding of the impact 

of tobacco control activities on public 

health outcomes

One goal of ISIS was to examine and explore 

the integration of four key approaches to 

systems thinking—systems organizing, 

system dynamics modeling, network analysis, 

and knowledge management. Such an effort, 

while potentially useful for many issues, 

may be especially apt for helping to create 

an integrated framework that will facilitate 

efficient and effective dissemination and 

implementation of evidence-based tobacco 

control practices. One hope is that efforts of 

ISIS will contribute to the foundation extant 

in the Guide to Clinical Preventive Services81

and Guide to Community Preventive Services82

and existing dissemination efforts to create a 

new, scientific, integrated systems approach 

to evidence-based public health practice. This 

would involve a shift in approach—one that 

seeks to transform a profession, not just to 

integrate methodologies. With this in mind, 

the role of ISIS could be framed with the 

following arguments:

n Tobacco control is at a crossroads, with 

many tasks accomplished, but difficult 

and complex challenges lie ahead.

n Approaches that are known to work are 

not being adopted in practice,83 despite 

significant efforts. One hypothesis is 

that tobacco control efforts have not 

succeeded because the systems of 

research and the systems of practice do 

not intersect effectively. 

n To reach the next level of outcomes, 

professionals in the system have to work 

more effectively and efficiently as a 

system. The most significant challenges 

today are systems challenges.

n Therefore, a goal of ISIS was to transform 

tobacco control by addressing systems 

issues to encourage more effective 

integration of research and practice and 

dramatically improve health outcomes.

Applying systems thinking to more 

effectively integrate the systems of research 

and practice is key to achieving more 

effective use of science in tobacco control 

initiatives and, more important, within 

public health as a whole. The chapters that 

follow outline in detail the specific systems 

approaches and methodologies studied in the 

ISIS project. Collectively, they point to a new 

and more comprehensive view of the field—

as a systems problem that can be addressed 

by using systems approaches to achieve 

dramatic improvements in outcomes.

Conclusions

1. The key challenges in tobacco control and 

public health today are fundamentally 

systems problems, involving multiple 

forces and stakeholders. Systems 

thinking is an innovative approach to 

address these challenges and improve 

health outcomes.

2. Numerous frameworks exist for systems 

thinking, a concept that encompasses a 
56

3 . S y s t e m s T h i n k i n g : P o t e n t i a l t o T r a n s f o r m To b a c c o C o n t r o l

broad synthesis of systems approaches. 

These approaches provide a theoretical 

basis for applying specific systems 

methods, such as system dynamics 

modeling, structured conceptualization, 

and network analysis.

3. The Initiative on the Study and 

Implementation of Systems encompassed 

four key areas of systems thinking, and 

their integration: how people organize 

(managing and organizing as a system); 

how people understand dynamic 

complexity (system dynamics modeling); 

who people are (network analysis); 

and what people know (knowledge 

management and knowledge transfer).

4. Examination of systems approaches has 

the potential to address key questions 

and problems faced by the various 

stakeholder groups involved in tobacco 

control.

5. Potential benefits of systems thinking 

in tobacco control include improving 

collaboration among stakeholders; 

harnessing resources toward evidencebased practice; eliminating duplication 

of effort; and gaining deeper knowledge 

about the impact of tobacco control 

activities.

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61

4

How to Organize:

Systems Organizing

Unlocking the promise of systems approaches in tobacco control requires a participatory, 

collaborative environment among stakeholders. This in turn requires a fresh approach 

to management, leadership, and interactions in and between organizations. This chapter 

describes an adaptive systems view of organizing that represents a well-documented 

evolution in management theory and serves as a cornerstone to implementation of 

systems methods and approaches.

The chapter reviews the evolving field of management theory and explores possible 

changes in traditional management theory with the addition of a systems perspective. 

It proposes a model for facilitating and organizing purposeful and adaptive organizations 

and describes associated “systems-friendly” methods that researchers and practitioners 

can use. The framework for the model includes four major interrelated dimensions: 

n	 Vision: From leading and managing to facilitating and empowering

n	 Structure: From organizing to self-organizing

n	 Action: From delegation to participation

n	 Learning: From discrete evaluation to continuous evaluation

The chapter presents two real-world case studies that use concept mapping, a method 

for organizing participatory systems, to address two tobacco control issues: integration 

of research and practice and development of criteria for high-quality state and local 

initiatives to control tobacco use.

Science is organized knowledge. Wisdom is organized life.

—Attributed to Immanuel Kant (1724–1804)
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

Introduction

The springboard for this chapter is the 

premise that traditional approaches to 

management will not be sufficient to 

address the complex environment of 

systems in tobacco control specifically and 

public health generally in the twenty-first 

century. Traditional management theory is 

predicated on the notion of the corporation 

and focuses primarily on command and 

control using hierarchical structures 

and theories of directive leadership to 

accomplish planning, implementation, 

and control functions. These traditional 

approaches to management are evolving 

as the complex management challenges of 

today are addressed.

This chapter also focuses on how to organize 

tobacco control efforts from the viewpoint 

of systems thinking, and its central purpose 

is reconciliation of the tension between the 

idea of a purposeful organization and an 

adaptive one. Organizations generally are 

thought of as purposeful, with goals, vision, 

and planning toward specific means and 

ends. Purposeful organizations purportedly 

do what they were designed to do. However, 

they might be expected to have greater 

difficulty adapting to novel situations. 

In contrast, adaptive organizations are 

subject to the processes of evolution, with 

no prescribed purpose, no a priori design, 

and no rational designer. Both purposeful 

and adaptive organizations are systems, 

composed of parts brought into relationship 

as a whole. Purposeful organizations 

benefit from the command-and-control 

structures that bring about goal-seeking 

activities. Adaptive organisms benefit from 

the adaptivity that enables survival in 

unpredictable and changing environments. 

This chapter suggests how systems thinking 

can be used to better understand both 

types of systems and to incorporate their 

features into tobacco control efforts. The 

term organization is used in this chapter 

in a broad “ecological” sense encompassing 

loose affiliations, traditional organizations, 

and more complex interorganizational 

structures, such as coalitions, networks, 

initiatives, collaborations, and partnerships 

comprising many distinct organizations. 

In chapter 2, tobacco control is shown 

to be a complex and continually evolving 

collaboration of stakeholders and 

organizations that increasingly requires 

cooperation in networks to accomplish 

crosscutting tasks. Contemporary practice 

of public health in general increasingly 

depends on cross-organizational 

collaborations and networks to address 

complex problems. In this increasingly 

networked environment, member groups 

come to the table with mixed agendas, 

competing interests, and often, dramatically 

different resources and capabilities. 

Typically, no overarching command-andcontrol decision structure exists. 

Collaborating organizations create their 

own governance mechanisms and negotiate 

differences as they evolve. Frequently, the 

system has a motivating purpose (e.g., 

desire for greater efficiency, need for better 

coordination, or intent to concentrate 

efforts). However, the organizations usually 

serve voluntarily or because of overt or 

covert inducements or incentives. In a 

rapidly changing environment, such systems 

are extremely fragile, and many do not 

survive for long. Members can and do leave, 

and the system changes and either adapts 

or dissolves when leadership of member 

organizations changes, strategic interests 

of key members become threatened, or 

the political and economic context is 

dramatically altered. Organization is really 

about how these complex systems are 

steered toward a purpose without sacrificing 

their profoundly powerful adaptive qualities.

Chapter 3 introduces the idea of systems 

thinking as a more effective approach to 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

understanding and adapting to complexity. 

In this chapter, systems thinking is 

viewed as it applies to organizational 

and management theory. A model and 

methods for managing from a systems 

thinking perspective are outlined. A systems 

approach to management is essential for 

enabling collaborative networks in tobacco 

control to organize, learn, and adapt to a 

rapidly changing environment and to the 

competitive forces of the continuously 

subversive and creative tobacco industry.1

These evolving approaches to management 

will be required to achieve more effective 

integration of research and practice, build 

a tobacco control system with sufficient 

agility to anticipate and counter strategies 

of the tobacco industry, efficiently use 

diminishing resources, and reach the next 

level of health outcomes in today’s public 

health environment.

Traditional 

Management Theory

Concepts of management have evolved 

considerably over the past century. 

Management experts have arrived at broad 

agreement on the general contours of the 

evolution. In approximate chronological 

order, management theory has progressed 

through four general phases:2,3 (1) classical 

or technical management, (2) humanistic 

or behavioral perspective, (3) management 

science or quantitative perspective, 

and (4) integrative or contemporary 

management approaches. 

Classical or technical management

originated during the industrial revolution 

of the late nineteenth and early twentieth 

centuries. This approach tends to 

use a mechanistic metaphor, viewing 

organizations as machines, leaders as 

engineers, and workers as mechanical parts. 

It emphasizes (1) the division of labor that 

divides work into a subseries of basic tasks 

and (2) the use of production or assembly 

lines that incorporate efficient application 

of technology. Taylor4 called these strategies 

“scientific management.”

The humanistic or behavioral perspective

arose in the late 1920s through the human 

relations movement, born of research at 

the Hawthorne facilities of the Western 

Electric Company and led by Elton Mayo. 

In these approaches, the organization is 

viewed through the behavioral and social 

sciences, with an emphasis on the concept 

that workers are people rather than simply 

parts of a machine. These perspectives 

include the human relations movement 

and origins of the fields of organizational 

development and organizational behavior. 

The focus generally is on human behaviors, 

motivation, and the socioemotional factors 

of organizational life.

The management science or quantitative 

perspective originated after World War II. 

Frequently confused with the classical or 

technical perspective, this viewpoint was 

distinctive for its reliance on quantitative 

modeling as a general approach to 

management issues. The approach includes 

the fields of management science, operations 

research, operations management, and 

information sciences.

Integrative or contemporary management 

theories tend to combine or integrate across 

traditional approaches, using each perspective 

as appropriate. For instance, the contingency 

perspective argues that the management 

approach in any organization or situation 

should be contingent on the circumstances. 

In this approach, managers adapt methods 

from classical, behavioral, or quantitative 

traditions as needed and required.

Most surveys of management theory include 

systems perspectives within contemporary 

management theories. This scenario 

suggests both their recent evolution and the 

degree to which management is adopting 
64

4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

them. The history of management and 

organization theory supports the contention 

in this monograph that management theory 

is evolving to a form that incorporates 

systems thinking as a major emphasis. 

The basic management process as presented 

in typical courses in management is 

multiphased. The assumptions are that 

the organization is the primary unit of 

management and that such organizations 

are hierarchical, use command-and-control 

procedures, and have leaders who initiate 

and implement planning and control of 

key processes. This process is described 

in multiple texts on contemporary 

management.2,3 Four functions typically are 

associated with this traditional view of the 

management process: planning, organizing, 

leading, and controlling.

The planning function in management 

emphasizes actions that can achieve goals. 

Planning typically occurs in a specialized 

department (planners) and is implemented 

by the executive team and disseminated 

to the lower ranks. Planning involves a 

short-term (often 1 to 2 years or less) or a 

long-term (5-year) timeline tied to goals 

and more efficient processes. Planning is 

conceived as a linear process that proceeds 

from mission, goals, and objectives to 

actions and timelines.

The organizing function in management 

involves “...the assignment of tasks, the 

grouping of tasks into departments, and 

the assignment of authority and allocation 

of resources across the organization.”3(p7)

Organizing also includes allocation of 

resources and authority into hierarchical 

levels and often is associated with 

individuals or departments (organizers).

The leading function is rooted in the idea 

of a top-down organization motivated 

and driven by the passions, foresight, 

and charisma of its leader. Leadership is 

thought of as a function of the executive, 

and the power to lead is ascribed through 

status roles, with decreasing power through 

each lower level. In this view, the leader is 

metaphorically a driver and the corporation 

is a well-engineered and well-oiled machine.

The controlling function is associated 

with monitoring activities and making 

corrections. Specialized individuals or 

departments (controllers) perform essential 

control functions. In addition, control 

frequently is derived from financial or legal 

structure.

The model of the four-phase management 

process also is consonant with a long 

tradition in planning and evaluation that 

construes the basic planning–evaluation 

cycle as consisting of three phases—

planning, implementation, and evaluation.5

In this model, the planning function is 

retained, the two functions of organizing 

and leading are integrated into the broader 

function of implementing, and the term 

evaluation is substituted for the related 

“controlling function.” 

The four functions of management theory 

are derived from a number of assumptions 

about how organizations work. The 

organization is viewed as a type of machine, 

driven and directed by one or more leaders, 

in which ideas, resource allocation, power, 

and information flows are pushed through 

the hierarchical levels. The metaphor of 

a machine is a derivative of the time and 

thinking in which the classical management 

theory was developed—the preindustrial 

and industrial ages. Power is allocated by 

positions of ascribed status in a hierarchical 

structure that is broad at the base and small 

and exclusive at the pinnacle. Organizations 

are controlled by controllers; strategy and 

execution could be planned by planners, 

managed by managers, and led by leaders; 

specialization yields efficiency; and little 

crossover of duties or roles exists. The four 

functions are related to common descriptors 

in table 4.1.
65

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

This management paradigm yielded results 

that were judged as positive by those who 

benefited. The Industrial Revolution owes 

its dominance to the classical management 

approach, but times are changing. The 

world’s peoples and nations are increasingly 

more interconnected and interdependent 

as the result of globalization. Information 

flows rapidly in many directions. Organized 

arrangements are more complex. Traditional 

command-and-control structures are 

difficult to establish and maintain. Even 

the relationship between employee and 

employer has been reframed so that both 

intrinsic and extrinsic motivations and 

motivational strategies are different. 

Chapter 2 of this monograph presents the 

recent evolution of tobacco control and 

points to the need for new models that 

deal with systems issues. Systems thinking 

offers promising extensions to a classical 

management theory that is not adequate to 

handle these complexities.

Systems Organizing 

Model

Moving tobacco control toward a systems 

approach to management does not mean 

abandonment of the traditional functions 

of management. Some degree of planning, 

organizing, leading, and controlling, or 

alternatively, planning, implementation, 

and evaluation, will always be required 

in organizations. A new model is offered 

here that integrates the advantages of 

the traditional and the systems views of 

organizations and enables leaders or agents 

to deal flexibly with myriad organizational 

contexts. A continuum ranging from the 

traditional management model to a systems 

organizing model is envisioned. This model 

is based on four principles (vision, structure, 

action, and learning [VSAL]) that enable 

movement between these two hypothetical 

end points, as a bead moves on a string 

(figure 4.1). The VSAL model is adapted 

from Cabrera’s “operating system”6 and is 

offered here as an organizing framework 

for its utility and applicability in managing 

complex systems.

Using these four principles, organizational 

leaders may choose a balance of 

traditional approaches (such as leadership, 

management, delegation, organized 

structures, and discrete evaluations) and 

systems approaches (such as facilitation and 

empowerment, self-organizing structures, 

participatory action, and continuous 

Table 4.1 Four Functions of Classical Management Theory and Descriptors

Management function Descriptors

Planning n Leadership driven and vision of leader enforced n Motivation through charisma of leadership team

Organizing n Goal oriented, efficiency centered, hierarchical n Agenda set by planners n Exclusive planning process, few executives/planners, 1- to 5-year plans, 

and planning department n Structured n Starts with mission, goals, objectives, and timeline

Leading n Assignment of tasks and grouping of tasks into departments n Allocation of resources and authority n Hierarchical

Controlling n Activities monitored and corrections made n Departmental function n Hierarchical n Exercise of control at regular intervals 
66

4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

evaluation), depending on the context and 

circumstances. This “systems organizing” 

model is compatible with both traditional 

and systems perspectives (figure 4.2). The 

continua within each principle illustrate 

how a leader has the freedom to move 

among positions on the four continua much 

as one tunes the equalizer on a stereo, 

matching the organizational situation to a 

particular style for each of the principles. 

However, because of the uniqueness and 

complexity of the interorganizational 

structures of contemporary tobacco 

control initiatives, much of value will be 

found in the systems organizing end of 

the continuum. This is not to say that the 

systems approach eclipses the traditional 

approach. In many organizations, a topdown, leader-centered, command-andcontrol structure is ideal, and subsystems 

Figure 4.1 Continuum from Traditional Management to Systems Organizing

systems

organizing

paradigm

traditional

management

paradigm

V S

L A

Notes. VSAL = vision, structure, action, and learning. From Cabrera, D. A. 1998. Knowledge Age Operating System (KAOS): Four 

principles of organizational design. Loveland, CO: Project N Press. Reprinted with permission.

Figure 4.2 Systems Organizing Model

similar to traditional

practice domain

Vision Structure

Learning Action

similar to traditional

research domain

similar to traditional

planning function

similar to traditional

evaluation function

similar to traditional

implementation 

function

leading &

managing

facilitating &

empowering organizing selforganizing

delegation participation discrete

evaluation

continuous

evaluation

Note. From Cabrera, D. 2001. Knowledge Age Operating System: Four principles of project design. Version 1.0. Loveland, CO: 

Project N Press. Reprinted with permission.
67

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

better suited to more traditional approaches 

may exist within the larger tobacco control 

network. However, as was illustrated in 

chapter 2, tobacco control efforts typically 

have many interorganizational parts, each 

with its own policies, culture, history, 

expertise, and methods. To manage such 

a system from a traditional approach is 

to neutralize the system’s most potent 

advantages—diversity, adaptivity, selforganization, and creativity.

The systems organizing model shown 

in figure 4.2 has four principles: vision, 

structure, action, and learning. Each 

of these principles is associated with a 

different continuum. On the left side of each 

continuum is a descriptor of that principle 

from a traditional view. On the right side is 

a descriptor associated with a systems view 

as follows:

n Vision: From leading and managing to 

facilitating and empowering

n Structure: From organizing to selforganizing

n Action: From delegation to participation

n Learning: From discrete evaluation to 

continuous evaluation

The four principles can be thought of as 

similar to the traditional progression of 

planning, implementation, and evaluation. 

In figure 4.2, the planning, implementation, 

and evaluation functions are depicted 

by the outer lines that enclose the VSAL 

boxes. Therefore, vision is associated 

with the traditional planning function; 

learning, with the traditional evaluation 

function; and structure and action, with the 

traditional implementation function. These 

similarities help ease the transition from 

a traditional linear model to a continuous 

systems model, but they also may hinder an 

understanding of the integrated nature of 

systems organizing. The traditional model 

of planning, implementation, and evaluation 

is a linear and discrete progression usually 

performed by “experts”: planning comes 

first, then implementation, then evaluation. 

In the systems organizing model, planning, 

implementation, and evaluation can occur 

throughout the system, continuously over 

time; they are not the private domain of 

expert planners or evaluators. 

Likewise, there are similarities between the 

systems organizing model and the traditional 

domains of research and practice. The center 

line in figure 4.2 distinguishes between the 

traditional research domain (vision and 

learning) and the traditional practice domain 

(structure and action). Because VSAL is 

an integrated model, these distinctions 

are relatively unimportant. However, it is 

relevant that there are areas in common 

between traditional functions and the newer 

systems organizing model. The traditional 

view assumes that (1) research is distinctly 

separate from practice, (2) research is the 

driver of practice, and (3) research and 

practice are the domains of specialized 

experts. In contrast, the systems organizing 

model makes no such distinctions. An 

organization is just as likely to benefit from 

evidence-based practice as from practicebased research. The boundaries between 

planning, implementation, and evaluation 

and between research and practice are 

blurred in the systems organizing model.

Both the traditional and systems models 

have four interrelated components. In 

the traditional management process, the 

four components are considered to be 

management functions. However, in the 

systems organizing model, they are more 

analogous to principles. It is tempting to 

assume that the planning, organizing, 

leading, and evaluating functions are 

analogous to the VSAL principles. Although 

these functions appear to be similar, they 

are subtly and importantly different. For 

example, consider the following descriptions 

of the four functions of traditional 

management (table 4.1):
68

4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

n Planning: Select goals and ways to attain 

them

n Organizing: Assign responsibility for 

accomplishment of tasks

n Leading: Use influence to motivate 

n Controlling: Monitor activities and make 

corrections

The perspective of each function is 

leader–follower centered. A leader selects 

goals, assigns responsibilities to followers, 

uses influence to motivate followers, and 

monitors activities and makes corrections. 

The traditional management functions 

are based on leadership and management, 

because the assumption is that leaders and 

managers can direct, delegate, motivate, and 

control their organizations. Thus, although 

traditional functions and systems principles 

appear to be similar, they are not similar. 

The systems principles are agent–system

centered, rather than leader–follower

centered. For example, the vision principle 

does not live in the private domain of people 

at the top of the organization. Any agent in 

the system can possess and be directed by 

a vision. Consider, for example, that many 

innovations in science and society do not 

“trickle down from the top.” Instead, they 

“percolate up from the bottom.” Another 

key difference between the traditional and 

systems views is the role of “thinking” versus 

“doing,” which is alternatively an alias 

for “ideal versus real” or “research versus 

practice.” In the traditional paradigm, these 

functions are differentiated, whereas in the 

systems paradigm, they are integrated.

In general, contemporary tobacco control 

efforts are likely to be better served by 

systems perspectives toward the right side 

of these continua. The proposed location 

of tobacco control initiatives is depicted in 

figure 4.3. Likewise, most tobacco control 

efforts are better served by the right side of 

the specific continua associated with VSAL 

(figure 4.2).

Same but Different

Within a systems organizing context, the 

traditional roles of planning, organizing, 

leading, and controlling take on a different 

perspective:

n The traditional planning function is 

goal oriented, with an emphasis on 

actions that can achieve leader-defined 

goals. Reaching organizational goals is 

predicated on a paradigm centered on 

leaders and followers, in which the leader 

Figure 4.3 Optimal Placement of Tobacco Control Initiatives in the Continuum of Traditional 

and Systems Approaches

Traditional Approach Systems Approach

agent/system

centered

integrated

research & practice

leader/follower

centered

differentiated

research & practice

Tobacco Control

Initiatives

V S

L A

Note. The VSAL model, developed by D. A. Cabrera, was originally published in 1998 (see figure 4.1 Note). Figure 4.3 and the 

figures in the VSAL sections that follow are adapted from the 1998 model.
69

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

sets the goals and motivates, organizes, 

and controls followers. In the systems 

organizing perspective, leaders become 

more like facilitators. The focus is shifted 

to a principle of collaboratively developed 

vision, suggesting a more collective sense 

of purpose.

n The organizing function in traditional 

management involves “...the assignment 

of tasks, the grouping of tasks into 

departments, and the assignment of 

authority and allocation of resources 

across the organization.”3 In a systems 

organizing perspective, the emphasis 

is shifted to include both purposefully 

organized structure and provision for 

self-organizing structures.

n The traditional leading function, which 

is described as “using influence to 

motivate,” has been transformed to an 

agent-centered principle. Individual 

agents of a system are not thought 

of as inert bodies waiting for a leader 

to delegate and motivate them to 

action. Instead, they are self-motivated 

individuals or organizations alternatively 

capable of motivating other agents and 

driven by internal goals and constraints. 

Agents are not merely active; they also 

are participatory.

n Finally, the controlling or evaluation

function in the traditional model is 

transformed into agent and systemwide 

learning. Evaluation is not merely a 

discrete and linear process accomplished 

by impact assessments or by counting 

outcomes. Instead, evaluation is a 

continuous process of evaluative feedback 

that is critical to adaptation, creativity, 

innovation, and survival.

Other subtle differences exist between 

the two approaches. First, in the systems 

organizing model, these categories are 

not discrete, whereas in the traditional 

management model they are discrete. 

The principles of systems organizing are 

themselves a system, so the four systems 

organizing principles are integrally 

interconnected.

Second, systems organizing principles have 

no set order, whereas there is an assumed 

phasing of the four traditional management 

functions. In a systems organizing model, 

participants may self-organize, learn 

together, and then realize they are working 

toward a common vision. In addition, agents 

may develop a common vision and then 

self-organize, adapt, and learn who needs to 

take what action to achieve the vision. The 

VSAL sections that follow describe a family 

of potentially useful methodological models 

that could be used to manage the four 

principles of systems organizing.

Third, the systems organizing model, like its 

traditional predecessor, also is related to the 

three phases of planning, implementation, 

and evaluation.5 However, a systems 

perspective transforms the meaning of these 

three functions. Like the four principles, 

they are not discrete and/or sequential; 

they can be entered into in any sequence. 

Sometimes one implements and then learns; 

in other situations, one may evaluate and 

then implement. The three functions are 

continually interacting.

Finally, the systems organizing model 

explicitly incorporates the ideas of research 

and practice. In general, the traditional view 

of research is associated with planning and 

evaluation, whereas a traditional view of 

practice is associated with implementation. 

The dynamic relationship between research 

and practice in the systems organizing 

model suggests that systems thinking may 

help to address the integration of research 

and practice.

Many aspects of traditional management 

must be used to effectively manage systems. 

Consequently, the four principles (vision, 

structure, action, and learning) can be 

adapted to a more traditional approach by 
70

4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

“moving the slider” to the left on any one 

of the continua. For example, it is common 

for a catalytic and influential leader to “have 

a vision” and then use a more traditional 

leadership style (e.g., ascribed power or 

influence) to promote that vision. However, 

at a critical point, the leader may realize 

that shifting to more participatory action 

will better accomplish the vision than 

will delegating actions to individuals. 

The four principles allow for this type of 

transition across each of their dimensions. 

Some of the differences highlighted here 

demonstrate the transformation that is 

occurring in management and that more 

aptly addresses the complexities of systems 

environments, especially in tobacco 

control settings.

It is tempting to describe the systems 

organizing approach as an “end of 

the chapter” tool for increasing the 

understanding of contemporary 

management. In almost every chapter of 

every current textbook on management, 

a future-looking section near the end of 

the chapter explores the latest thinking in 

management theory and is populated with 

phrases such as3 “new workplace”; “learning 

organization”; “virtual organization 

approach”; and “increasing participation 

in decision making.” Such wording gives 

a glimpse into the future of contemporary 

management theory. These sections reveal 

that management thinking is evolving 

to address a more complex, networked, 

and dynamic world. The suggestions in 

this chapter and in the model of systems 

organizing that is presented are not 

meant to be antithetical to contemporary 

management thinking. These suggested 

approaches seem to be right there, at the 

end of the chapters of nearly every modern 

textbook on management.

The following sections discuss each of 

the four principles and primary methods 

associated with them. Because all of 

the principles are interrelated, the 

methodologies are interrelated as well. 

Although methods are discussed in 

connection with specific principles, they 

should be viewed as crosscutting. 

Vision: From Leadership and 

Management to Facilitation 

and Empowerment

A collective vision is one that is shared 

throughout the organization. It is not 

the exclusive purview of the “leaders” or 

hierarchy in an organization but is “held” 

in common by each of the agents in the 

network. The more agents in a network 

share the same vision and “see” the same 

possibilities, the more a system can be 

said to have a collective vision. The job 

of a leader is to facilitate the acquisition 

of a collective vision. Because each agent 

holds part of the collective vision, each 

is capable of influencing another agent’s 

vision and, in turn, the whole system. In 

this way, collective vision takes on three 

important qualities that are different from 

the traditional vision.

First, collective vision is distributed

throughout the network. Second, collective 

vision is a dissipative structure, that is, the 

structure remains stable despite changing 

flows through it. This characteristic makes 

collective visions more durable and timeless, 

because they are not radically changed 

by the natural recidivism of the network. 

Third, collective vision is adaptive and 

dynamic. Although the vision is a durable 

dissipative structure, it also is susceptible to 

the dynamics of the network and can adapt 

over time. The systems organizing leader 

will find that many traditional techniques 

of planning remain useful in facilitating 

collective vision. However, he or she 

should reframe these traditional planning 

techniques in light of the characteristics of 

these important changes to the traditional 

vision (e.g., distributed, dissipative, adaptive, 

and dynamic).
71

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Vision is not always a collaborative

process, but it should always be collective.

Organizational leaders may need to establish 

a vision. However, one that is not broadly 

held to be important will have little support 

and thus lack the necessary support from 

individual agents. Also, it is not necessary 

to establish the vision before moving to 

the other systems organizing principles. 

A collective vision could be an emergent 

property of a complex system or the catalyst 

for a set of discrete agents to self-organize 

into a network. Some of the methods 

discussed later in this chapter are well 

suited for facilitating a collective vision. 

Systems leaders play a key role in facilitating 

processes that help agents link local and 

semiautonomous action (mission) to the 

collective vision.

The idea of “management,” which has 

the same Greek root as “manipulate” and 

implies an action “at the hand of” a leader 

(L. manus, hand), is challenged by the 

evolving paradigm toward systems. The 

organizational leader does not manage per 

se but becomes a facilitator of organization 

(L. facilis, to make easier). A leader makes 

self-organization easier by removing 

constraints on the system, rather than 

adding them.

In the traditional management framework, 

planning usually is considered a top-down 

process with leadership from the highest 

levels of the organization. This traditional 

view has been challenged, especially in the 

area of strategic planning, where it became 

clear that the planning function often was 

in conflict with the development of strategy. 

Mintzberg argues that planning efforts 

often stifle commitment and innovation and 

confine the organization and its members.7

He proposes a model in which planners 

are more facilitative and supportive, rather 

than structural and proscriptive. The past 

decade brought a transformation of the 

idea of planning along these lines that 

parallels the shift to systems thinking 

generally. Historically, planning in large 

organizations tended to be confined to a 

department or unit. The planners worked 

with top management in a tightly structured 

process that proceeded from the statement 

of mission and goals to objectives, actions, 

and delineation of timelines, responsibilities, 

and costs. Today, planning has evolved into a 

more collaborative and collective endeavor, 

in which planners are facilitators, rather 

than leaders. Moreover, the process itself has 

shifted from being a goal-oriented exercise 

to more of an adaptive one.

A broad range of methods and processes can 

be applied in systems planning to encourage 

development of a collective vision. Here 

the territory is briefly sketched, and more 

detailed descriptions of methodological 

choices are cited.8 Many of these strategies 

fall within the broad rubric of collaborative 

needs assessment.9 One of the oldest 

collaborative group methods used in 

planning is traditional brainstorming.10 The 

nominal groups approach11 is a structured 

participatory method in which people 

work individually to brainstorm and then 

share ideas. Focus groups12 essentially 

are a type of group interview to generate 

ideas in response to a focus prompt or 

stimulus. The Delphi technique13 began as 

a relatively delimited, iterative, structured 

group method of surveying participants and, 

through feedback of results, moving the 

group toward consensus. As they evolved, 

Delphi methods became so broadly defined 

as to be virtually indistinguishable from 

any structured collaborative methods for 

identifying and assessing planning options.

A broad range of planning methods 

are particularly relevant to the notion 

that “vision” has as a root the idea of a 

“visual” model. Visual models involve the 

construction and use of maps of ideas. 

Some, such as the concept-mapping

methods of Novak14 or Buzan and Buzan’s15

mind maps, are primarily tools for use by 

individuals, although collaborative use 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

may be possible. Explicitly collaborative 

concept mapping,16 sometimes referred 

to as structured conceptualization, is a 

participatory mixed-methods approach 

that integrates group process activities 

(brainstorming, unstructured pile 

sorting, and rating of brainstormed items) 

with multivariate statistical analyses 

(multidimensional scaling and hierarchical 

cluster analysis) to yield both statistical 

and graphic representations of a conceptual 

domain. This approach is designed around 

a well-informed, group-oriented, decisionmaking process that drives both planning 

and evaluation. In public health, it has 

been used to address statewide planning in 

Delaware17 and Hawaii,18 development of 

an evaluation framework for a center grant 

initiative of the National Cancer Institute 

(NCI),19 and articulation of an expert model 

of the activities the tobacco industry uses 

to undercut public health efforts.1 This 

concept-mapping method is illustrated in 

detail in the case study later in this chapter. 

Other map-based approaches to planning 

incorporate the idea of causation and consist 

of sequential paths of expected or predicted 

activities and outcomes: 

n Strategy maps20 pictorially link 

perspectives in an organization to 

encourage strategic alignment that leads 

to greater value.

n Cognitive maps21 are among the earliest 

causal maps that were widely used.

n Logic models22 are designed to link 

planning and evaluation by mapping the 

causal connections between program 

activities and outputs and outcomes.

n System dynamics models23,24 are causal 

maps that can be integrated into the 

planning function. Chapter 5 considers 

these models in detail.

n Outcome maps25 are ways of depicting 

the changes in behavior of an individual, 

group, or organization with which a 

program or intervention works.

An array of collaborative, participatory 

methods that have value in the planning 

function come from the field of 

organizational development and are used 

in large-scale efforts toward organizational 

change. Many are ideal for facilitating 

and empowering a collective vision. Such 

methods include the following:

n Future-search conferences are events, 

typically approximately three days in 

duration, designed to help an organization 

find an ideal future and aim for it.26

n The conference model27,28 is a 

comprehensive system designed for a topto-bottom redesign of an organization. 

It involves factors such as a customer/

supplier conference, vision conference, 

technical conference, and design 

conference, across separate two- or threeday events.

n The large-scale interactive process29 is 

an intervention encompassing mix-andmatch table groups of 8 to 10 people 

usually over approximately three days.

n Real-time strategic change30 is an 

approach that grew out of Dannemiller 

and Jacobs’s29 work in large-group 

interventions and also is used to 

implement organization-wide change, as 

the beginning of a process that aims to 

change the way an organization works, 

rather than planning only one event.

n Participative work redesign31 emphasizes 

a democratic approach to job design, 

in which the people who do the work 

determine how it should be done, in 

groups of 8 to 10. It often follows a 

search conference, and the vision for the 

future of the organization frequently is 

established before this event occurs.

n Open-space meetings32–34 are minimally 

structured events where a group gathers, 

a blank page on the wall constitutes the 

agenda, and participants are encouraged 

to sponsor a discussion by writing the 
73

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

title of the session on one of the many 

flipcharts in the room.

n Appreciative inquiry summit 

methodology,35 pioneered by Cooperrider 

and Whitney, cofounders of the Taos 

Institute (Chagrin Falls, Ohio), focuses 

attention on expanding an organization’s 

capacity for positive change through 

inquiry into its positive core of strengths, 

gifts, and life-giving forces.

n The search conference36 is a highly 

participative and democratic planning 

process developed to empower an 

organization to identify, design, and enact 

its most desired future, in which people 

create strategic goals and action plans 

that develop the organization or system.

The variety of methods available for 

participatory, collaborative planning and 

the establishment of a collective vision 

illustrate both the potential and the 

challenge for systems organizers. Many of 

the methods share common features (e.g., 

brainstorming and ranking). Moreover, 

systematic, empirical comparative evidence 

of relative strengths and weaknesses needs 

to be developed. Even so, explicit structured 

processes for participatory planning and for 

helping systems develop maps describing 

the collective vision of the group or 

organization are critical tools for systems 

organizers.

Structure: From Organizing to 

Self-Organizing

Despite the limitations of the traditional 

management paradigm, one of its strengths 

is its usefulness in leading an organization 

toward a predefined purpose. However, 

no organizational leader, no matter how 

skilled or charismatic, can single-handedly 

move a complex organization toward a 

desired goal. Organizations are complex 

and evolving “organisms” encompassing 

diverse stakeholder groups, political and 

cultural processes, and competing demands. 

Especially in the context of tobacco control 

efforts, in which loosely knit coalitions and 

collaboratives form with limited central 

control, the traditional approach alone is 

not sufficient. Therefore, the central task of 

a new management model is to reconcile the 

paradox between purposeful organization

and adaptive self-organization. The real 

power of complex organizations is the ability 

to self-organize, adapt, and evolve. However, 

the self-organization and evolution must 

be directed toward a purposeful goal. These 

countervailing forces speak to fundamental 

issues of power and infrastructure in 

organizations, particularly as they move 

toward a systems environment.

When Darwin wrote his treatise on evolution 

by natural selection,37 he began with 

examples of domestic breeding for selective 

traits in pigeons to provide an analog 

for what would prove to be a profoundly 

influential argument: a similar kind of 

selection that resulted from natural causes, 

rather than divine inspiration or intelligent 

design38 (W. B. Provine, pers. comm., 2004). 

The phylogeny of organs like the human 

eye, organisms like the kangaroo, or 

superorganisms like a colony of ants, is 

the result of good genes combined with a 

modest amount of good fortune.38,39

Instead of developing traditional commandand-control systems, the systems manager 

facilitates (eases the formation of) systems 

that encourage self-organization. This end 

frequently is accomplished by reducing 

restraining forces, instead of adding 

directing forces. Systems organizing leaders 

must facilitate and empower interaction of 

all kinds. When adaptive agents are allowed 

to freely interact, self-organization typically 

results. Many of the structures, policies, 

and rules in a traditional organization are 

designed to direct, control, or otherwise 

inhibit interaction. Departmentalization and 

imposed specialization are driving forces 

for organization, but they restrain self-
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

organization. Self-organizing systems may 

cluster into subsystems that may adapt to fill 

specialized roles, but they do so organically.

Systems organizers understand that systems 

allowed to form naturally are better able to 

adapt and evolve. When agents self-organize, 

they often form novel bonds in the network 

that can help decrease the relative distances 

in the network, making the world smaller.40

In turn, a “smaller” world can be navigated 

more quickly and may be better able to adapt 

to rapid changes in the environment. Because 

these novel, “long” bonds connect discrete 

clusters, they facilitate the flow of critical 

system components, such as information, 

resources, knowledge, learning, and power, 

from one part of the system to another. 

The issue of structure in systems organizing 

is closely related to the issue of networks, 

because networks either constitute the 

structure or can be used to represent it. 

This finding is consonant with a literature 

on collaboration in networks41 and the idea 

of “network organizations”42 that addresses 

structural issues (types of networks) and 

how to perform facilitation effectively in 

networked contexts. Chapter 6 considers 

networks and network analysis as they relate 

to systems thinking. However, much of that 

discussion is relevant here.

The systems organizing leader recognizes 

similarities between efforts to encourage 

structures that enable self-organization and 

the traditional implementation functions. 

However, the paradigm shift to systems 

thinking requires a transformation of 

traditional thinking. The rules of the 

traditional manager become “recipes”43 to 

the systems organizer. Where rules attempt 

to control, recipes suggest. Encouraging 

structures that allow self-organization is a 

complex and difficult process, but it need 

not be any more difficult than traditional 

approaches. The systems organizer must 

develop a keen sense of the behavior of 

complex adaptive systems and must be 

a catalyst for systems change at critical 

times, while “letting go” to self-organizing 

processes at other times.

The organizational environment that 

currently characterizes tobacco control can 

be viewed as a loosely coupled system, a 

term Weick44 coined in studying educational 

organizations. Loosely coupled systems are 

Going with the Flow

Consider the following anecdote, which differentiates between purposeful organizing and adaptive 

self-organizing. In the world of river-raft guiding, novice guides can be distinguished from seasoned 

guides because novices work harder and expert guides work smarter. Novice guides rely on raw 

power and young muscles to maneuver the raft. A great deal of effort is expended fighting against 

the natural flow of the river. The seasoned guide surrenders the boat to the flow of the river and pays 

close attention to critical moments when a single stroke in the right place, at the right time, with the 

right amount of force can alter the course of the raft, transitioning the boat from one turbulent flow 

to another. The differences between the novice and expert guide are subtle but profound. 

The parallels to management and organizations are obvious: the leader, manager, or agent of change 

floating on the turbulent flows of a complex organization cannot hope to move an organization 

toward a goal or objective. However, well-placed and well-timed actions, based on a thorough 

understanding of the system’s complexities and behaviors, can lead to purposeful and adaptive 

change. In this anecdote, “going with the flow” does not mean simply letting the river take the 

boat wherever it takes it without a care for outcomes or path. Instead, going with the flow means 

understanding the effects of the larger systems at work and coordinating one’s actions to use and 

leverage these systems toward purposeful ends.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

distinguishable from the command-andcontrol environments normally found in the 

business sector. They are characterized by 

several factors.44 They exist in situations in 

which several means can produce the same 

result. There is a lack of coordination or 

dampened coordination and an absence of 

regulations throughout the system. These 

systems consist of connected networks 

with very slow feedback times. The various 

subsystems evidence causal independence, 

and planned unresponsiveness exists in 

the system. Orton and Weick45 summarize 

major advantages and disadvantages of loose 

coupling: 

n Persistence: Stability and continued 

operation in the good sense; resistance to 

change and reduced responsiveness in the 

bad sense

n Buffering: Inclination to seal off and 

prevent the spread of problems, which 

also can manifest itself in the lack of 

communications that may have led to 

problems such as the Three Mile Island 

accident46

n Adaptability: Great tendency to experiment 

and find local solutions to problems

n Satisfaction: Fostering of efficacy and 

self-determination44 and creation of an 

environment in which deviance and 

experimentation are protected;47 loosely 

coupled systems can also contribute to 

loneliness,48 reducing satisfaction levels

Orton and Weick reach several conclusions 

on the best management of loosely coupled 

systems.45 They recommend subtle leadership 

that focuses on providing centralized 

direction and coordination while recognizing 

the value of increased discretion on the part 

of agents. The investigators suggest focusing 

attention on specific relationships in the 

system by use of strategies such as carefully 

selecting targets; managing/controlling 

resources; and initiating focused, forceful 

action as appropriate. Orton and Weick 

advise an emphasis on shared values and 

tight cultural couplings to counteract loose 

couplings between policies and actions.45 The 

study of loosely coupled systems suggests 

four insights about navigating collaborations 

in public health:

1. The focus should be on the interfaces—

defining the inputs and end products 

required for each participating 

organization, rather than activities that 

occur within each.

2. The system should rely less on detailed 

instructions and more on encouraging 

mutually agreed upon operational 

milestones for each partner and 

facilitating economic incentives that are 

driven by fulfilling explicit operational 

milestones.

3. The systems organizer should anticipate 

that in the course of the system’s 

evolution, it may be necessary to 

substitute new participants for others 

who have left or are not performing well.

4. Structuring the system’s work so that 

it can be accomplished with minimal 

disruption to the system is essential.

Moreover, the systems organizer should 

encourage development of distinctive 

competencies by (1) providing opportunities 

for partners to become involved in activities 

that use their expertise and (2) reassigning 

activities that can be better performed by 

other partners. 

While this chapter maintains that tobacco 

control is a loosely coupled system, this 

should not be taken to suggest that it cannot 

or should not organize. Many issues in 

tobacco control are best addressed through 

well-coordinated, orchestrated, organized 

efforts on the part of the system. For example, 

efforts to lobby state legislatures around 

specific tobacco control legislation being 

considered (e.g., cigarette taxes, clean indoor 

air laws) need to be planned and executed 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

carefully to be effective. In a loosely coupled 

system, this often will require that multiple 

groups or organizations come together and 

self-organize to achieve such ends. 

Power, Conflict, and Structure

The structure that is used in a system 

is directly related to the potential for 

power and conflict to arise. For example, 

issues surrounding the distribution of 

power among key stakeholders are a 

common theme whenever researchers and 

community members form a partnership. 

Historically in such cases, researchers 

control the resources and thus are the 

primary decision makers. Community-based 

participatory research, which is discussed 

later in this chapter, attempts to adjust the 

balance so that researchers and community 

members equally share power, funds, and 

responsibility.49 This research has important 

insights for systems organizing in situations 

of power disparities. If participants do 

not address issues of power and develop 

relationships built on trust, they are unlikely 

to embrace the results of the research,50–52

a factor that may contribute to the lack of 

research utilization in public health practice. 

The literature on open systems and selfmanaged teams is particularly relevant to 

the issue of structure and its relationship to 

power and conflict in systems. Proponents of 

the open systems framework53 argue that, in 

any environment, there is a set of factors so 

interrelated that a change in one may create 

changes in the others. As factors of a system 

interact, members of the organization 

receive feedback on whether they are 

accomplishing their goals.53,54 This feedback 

is especially apt in a context of contemporary 

dynamic systems that require participants 

to monitor and adapt to external changes to 

survive.55 Within this context, systems must 

themselves be able to adapt.

In traditional management, the idea of selfmanaging teams emerged as a solution to 

help organizations manage the dynamics 

of a more complex environment.54,55 The 

concept of self-management often is 

used interchangeably with terms such as 

self-controlling and self-regulating. The 

idea behind self-managing teams is that 

when the manager is removed from the 

interaction, the team is left to self-regulate 

and consequently becomes better able to 

adapt to the organization’s changing needs 

and goals.55 The assumption is that giving 

groups control over decision making and 

behavior leads them to better organize and 

direct their work, more rapidly address 

problems, and have a stronger sense of 

commitment.

Much of the discussion about governance 

in self-managed groups is essentially a 

consideration of the role of conflict in 

such systems. There are several types of 

conflict, and each one may have different 

implications for governance. Conflict 

over tasks involves disagreement about 

the nature of the task or prioritization of 

tasks. Conflict over relationships pertains 

to personal differences among participants. 

Conflict over process relates to tensions 

about how to address tasks. The literature 

on conflict within a team suggests that 

some level of conflict can enhance team 

performance, but excessive conflict has 

negative effects.56

Power differentials create the need for 

interaction guidelines that can form a 

basis for working together in a systems 

environment. For example, based on a 

review of the literature and stakeholder 

research, Cordero-Guzmán identified 

several key factors for such collaborations 

in community-based organizations (CBOs), 

including an explicit mechanism for the 

selection of participants and concrete 

criteria for selection.57 Possible criteria 

include identification of members who share 

a stake in both the process and outcome and 

those who have the ability to compromise 

and resolve disagreements on goals, 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

programs, and procedures. Development of 

mutual respect, understanding, and trust is 

another essential early step. The challenge 

is how best to promote development of 

respect.57 A structured participatory process 

may be critical in early phases of systems 

development (e.g., engagement in an active 

and professionally led planning process 

that involves significant involvement of 

participants). Efforts should be made to 

create opportunities for the collaborating 

organizations to engage in group activities, 

discuss common interests, develop clear 

expectations, and build trust.

Although cross-organizational systems are 

unlikely to be as structured as organizations 

themselves are, it is important that roles 

and policies are clearly defined. Open and 

frequent communication and established 

formal and informal communication 

links are especially important in crossorganizational systems in which 

opportunities for regular face-to-face 

exchanges are likely to be less frequent. 

It is important to be clear and selective in 

targeting the types and contexts of activities 

related to the work of the system. Starting 

an initiative with concrete and visible 

projects that can show clear and early gains 

is desirable. This approach enables the 

systems team to gain experience working 

as a group and to obtain a quick success 

that can increase self-confidence. As in any 

organization, the pressures of day-to-day 

demands tend to crowd out plans for longer 

term strategic issues related to the system. 

Having a process that promotes planning 

for long-term systems strategies and goals is 

critical. Finally, and perhaps paradoxically, 

it is important to manage the exit of 

organizations from the collaborative group.

Action: From Delegation to 

Participation

One important concept gained from complex 

systems research is that interactions of local 

semiautonomous agents unaware of larger 

goals can lead to emergent complexity, 

adaptivity, and self-organization. Using this 

knowledge, the systems organizing leader 

must enable individuals to connect their 

daily objectives and actions (mission) to the 

larger collective vision of the whole system. 

One can imagine a system of active agents 

who are not participating in a larger effort. 

In everyone’s experience, they are people 

who are very busy but accomplish little. 

As soon as agents make the link between 

their local mission and the collective vision, 

they move from being “active” to being 

“participatory.” When agents are called on 

to participate, rather than merely to take 

action, they are encouraged to connect their 

actions to the collective vision of the whole.

One key concept of the systems organizing 

model is the intimate link between mission 

and vision—between the action of the parts 

and the action of the whole. To benefit 

from a purposeful process, mission must 

be linked to a collective vision. To benefit 

from the powers of self-organization 

and emergence, agents must become 

participants. Like establishing a vision, 

establishing a mission is a continuous rather 

than a discrete process. Agents require time 

to determine how they can participate and 

in turn contribute to the collective vision. 

Many unique gifts and talents of individuals 

are unknown to their leaders and frequently, 

even to themselves. However, a systems 

organizing leader empowers and facilitates 

a process that helps individuals identify 

key contributions. Such leaders do not say, 

“We’re going to do X, and I need you to 

do Y.” Instead, they say, “We want to do X. 

What can you contribute?”

The first step in exploring the concept of 

facilitative leadership to achieve participant 

missions is examination of the literature on 

management for contexts similar to those 

of complex and dynamic interorganizational 

systems. One leading candidate is the 

field of large group interventions (LGIs),58
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

collaborative interventions involving 

the systems, practices, and policies of 

transorganizational environments. In 

traditional organizations, such interventions 

embody strategies to involve both internal 

and external systems in the change 

process.59 These methods are designed to 

create alignment and consensus around 

strategic direction and global issues for an 

organization. Generally, they are processes 

involving key stakeholders at all levels of 

the organizational environment. LGIs, also 

known as critical mass events, large group 

interactive events, whole systems change, 

and large-scale organizational change, grew 

out of the field of organizational development 

in the 1950s, with the formulation of the 

theory of sociotechnical systems.60

An emerging paradigm of change has arisen 

to formally challenge and compete with the 

more traditional sociotechnical systems 

approaches. LGIs have been embraced by 

many as the preferred method of change, 

because they bring a higher level of 

consciousness and an ecology of the whole 

system.61 Whole-systems approaches to 

organizational change are rooted in the 

philosophy that organizations act as living 

systems or communities and that overall 

health must be viewed from the perspective 

of the total system. A whole-systems 

perspective involves understanding how all 

parts of the system (e.g., people, resources, 

knowledge, processes, and leadership) 

contribute to the successful functioning 

of the system and how each of the parts 

relates to each other and to the whole. Other 

approaches to redesigning organizations 

to improve productivity, quality, and 

organizational effectiveness include total 

quality management and business process 

reengineering. LGIs can trace their ancestry 

to a diverse set of approaches including 

systems theory,53,60,62 sociotechnical systems 

and social constructionism,63,64 values 

theory,65,66 social psychology,67 futuring,68,69

group dynamics,70–73 and large group 

dynamics.74–78

Several essential design principles 

support LGI methodology58 and are 

worth consideration in the context of 

organizing tobacco control. Dialogue 

among stakeholders is necessary to 

transform understanding and find deeper 

meaning, essentially an affirmation of the 

critical importance of collaborative and 

participatory approaches in this context. 

Through powerful and generative dialogue 

processes, people are capable of extreme 

change that becomes the source of collective 

action and collaboration. Community 

building and relationship formation 

practices foster interdependence and 

interconnectedness among the participants 

in the system. Collective learning increases 

a system’s capacity to produce results 

that matter. Diversity through shared 

inquiry promotes system vitality, synergy, 

resourcefulness, and growth. Self-managing 

methods build dynamic and synergistic 

energy that fosters commitment and shared 

responsibility.

In addition to LGI methods, approaches 

such as participatory action research 

are well suited to linking a participatory 

Agents and Missions

When religious missionaries go on a mission, 

they are active participants in the vision of 

a larger system. They understand the part 

their participation plays in serving the vision 

of the whole. Even though each mission 

is different, all the missions share abstract 

or general qualities. The same is true for 

agents in a system. Each agent may have 

a mission uniquely suited to him or her, 

and the collective effect of these missions is 

attainment of a collective vision. Missions 

are not “statements” on a boardroom wall. 

They are collective, distributed, adaptive, and 

dynamic actions and interactions. Unlike the 

dissipative structure of visions that makes 

them dynamically timeless, missions are 

timely. They change.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

mission to a collective vision. The systems 

organizing leader finds that many of the 

traditional techniques of planning and 

implementation remain useful in linking 

this participatory mission. However, these 

traditional techniques should be reframed in 

light of these important systems changes to 

the traditional mission “statement.” 

Learning: From Discrete 

Evaluation to Continuous 

Evaluation

Learning is the adaptive function of societies 

and organizations. In the traditional 

management model, learning is most 

like evaluation. The field of evaluation is 

undergoing changes parallel to those in 

science that were discussed in chapter 3 

and to the changes in organizational and 

management thinking discussed earlier 

in this chapter. The field of evaluation is 

evolving away from the discrete and linear 

control model of planning, implementing, 

and evaluating to more dynamic models 

that constitute collective adaptive learning. 

At the cutting edge of the evaluation field, 

scholars already are moving evaluation 

criteria from researcher-defined approaches 

to a participatory, stakeholder-based 

model consonant with linking theory to 

practice and evaluation to learning. When 

evaluation becomes a stakeholder-driven 

process that integrates both the goals of 

researchers and the needs of practitioners, 

the problem addressed is one of the most 

critical roadblocks in the current science 

model—the gap between research and 

implementation of evidence-based practices.

Developing a learning organization23

means that agents view themselves as both 

students and teachers in a continuous 

process in which making mistakes, taking 

risks, acquiring new knowledge, and sharing 

that knowledge with others are critical 

advantages, not just fanciful and occasional 

reflective indulgences. Individuals in the 

system must be encouraged not only to 

reflect on what they are doing and adjust 

their mental models but also to report or 

disseminate what they learn to others.

Evaluation as a conscious empirical 

endeavor can trace its roots back hundreds 

or even thousands of years.79,80 However, 

evaluation emerged in its modern form 

primarily as a coherent field, at least in 

the United States, in the era of the Great 

Society during President Lyndon Johnson’s 

administration. From the outset, evaluation 

involved a confluence of many fields, both 

research based and practice oriented, 

including most of the applied social sciences 

and substantive areas of education, health, 

and social welfare. Thus, it encompassed 

an eclectic mix of methodologies ranging 

from experimental and quasiexperimental 

approaches to qualitative anthropological 

and field-based strategies and addressed 

a broad range of concerns from technical 

and scientific to managerial and practical. 

Charting the history and evolution of the 

various strands of evaluation is easily a 

book in itself.79–89 Nonetheless, here it 

is important to identify the most recent 

directions and how they relate to systems 

learning in systems organizing.

This section focuses on three broad areas 

of evaluation methodology illustrating the 

evolution of systems organizing principles: 

participatory evaluation, program theory 

and logic models, and system models for 

evaluation.

Participatory Evaluation

Participatory evaluation embodies the 

kind of collaborative, multistakeholder 

approach envisioned in the four principles 

of system organizing. Traditionally, the gap 

between researchers and practitioners has 

served as one of the major impediments to 

dissemination and adoption of evidencebased practices. In public health in 

general, there frequently is a dissonance 
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between research results and the needs of 

practitioners and other stakeholders, often 

to the point that community members 

have a well-documented mistrust of health 

researchers.90 There are some key structural 

reasons for this dissonance.51 Dissemination 

of research findings frequently is not by 

itself an effective tool for initiating behavior 

change. Best practices, which traditionally 

result from applied research, often are 

viewed suspiciously by potential users. 

Moreover, much of the research that informs 

the development of guidelines for best 

practices is conducted in distant places by 

unknown researchers.

Incorporating the knowledge and expertise 

of practitioners and community members 

strengthens the quality of the research.91

When research questions address issues 

important to both researchers and 

practitioners, the data collected are more 

applicable to the scientific hypothesis under 

study.92 Likewise, a close, collaborative 

relationship between the evaluator and 

the consumers of the evaluation increases 

the quality and effectiveness of program 

evaluation.93

Community-based participatory research

(CBPR) is an evaluation approach 

that facilitates collaboration between 

researchers and community members. 

The three key elements of participatory 

research are collaboration, education, and 

action,91 which enable the development 

of effective interventions and address 

specific community health needs.94 The 

involvement of all participants in all 

aspects and at all stages of the research 

is essential to CBPR.49,52,92,94,95 Each 

participant adds important expertise to any 

research endeavor and can increase the 

understanding of factors contributing to 

poor health outcomes and thus enhance 

the quality of the research.90,91,96 To ensure 

that the voices of community members are 

heard, the research must involve an active 

partnership with a CBO, a community 

advisory committee, community forums, 

and public presentations, and must include 

formative data collection, including 

interviews with community members.92

CBPR can be viewed as an overarching term 

that encompasses a variety of participatory 

evaluation methods. Participatory action 

research is an iterative process of inquiry, 

reflection, and action, in which a researcher 

participates with stakeholders to define 

a problem, generate knowledge, perform 

research, take action, and evaluate results.97

The participatory intervention model is 

a closely related approach that integrates 

theory and research on interventions that 

are sensitive to culture and context.98 This 

partnership between investigators and 

communities is designed to promote longterm sustainable involvement of affected 

stakeholders. Empowerment evaluation99 is 

a collaborative approach to the development 

and use of program evaluation criteria, 

driven by community stakeholders, as well as 

investigators. Many of these approaches use 

the methods described earlier in the section 

on “vision.” They overlap with the emphases 

described in the discussion of large group 

interactions in the section on “structure.” 

Development of a partnership is facilitated 

by establishing research priorities, funding, 

and mechanisms for collaboration and 

decision making early in the collaborative 

process.94 Establishing and maintaining 

trust also are essential to an effective 

collaboration and require the flexibility 

and patience of all stakeholders.49,90,94 To 

ensure the success of a partnership in 

research, it is advisable to determine the 

roles of all stakeholders, define principles of 

collaboration, and develop a code of ethics 

before a project is started.52,90,91,100

Even though CBPR has many benefits, 

it does pose challenges, including time 

constraints, cost-effectiveness issues, and 

lack of program durability. Funding agencies 

generally do not provide adequate time for 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

performance of CBPR projects, making 

detailed community analysis difficult.52,101,102

In addition, most community research 

projects primarily are concerned with 

determining whether the intervention has 

an effect, not whether the program will 

endure.100,102 Despite these concerns, CBPR 

has much to commend it, especially in the 

context of open systems.

Program Theory and Logic Models

One of the most important changes in 

evaluation over the past few decades 

has been the recognition that good 

evaluation depends on understanding the 

underlying theory of how programs or 

interventions might affect outputs and 

outcomes, a concept known as program 

theory.103 Program theory was a reaction 

to the traditional experimental and 

quasiexperimental approach104 that tends 

to treat the program or intervention as a 

“black box” and assess causality without 

concentrating on the processes that bring 

about effects. Program theory also can be 

viewed as a transitional step from a more 

reductionist and hierarchical view of causal 

relationships toward one that is more 

dynamic and systems oriented. Paralleling 

this evolution to program theory were two 

trends that have implications for systems 

organizing.

First, methods and processes that would 

enable comprehensible description and 

depiction of implicit theories were needed. 

It was not sufficient for individual scientists 

and researchers to perform this function 

alone. Many of the most detailed causal 

models were likely to be implicitly held in 

the minds of practitioners and community 

members who were close to the phenomena. 

Thus, the problem became one of identifying 

methods to help groups of stakeholders, 

including researchers, practitioners, policy 

makers, and consumers, articulate their 

implicit models of how interventions work 

to affect outcomes. Then these models 

could be used to perform more sensitive 

evaluations through methods such as 

matching of theoretical patterns of expected 

outcomes with the observed patterns 

obtained through measurement.105–107 Not 

surprisingly, many of the processes that 

proved useful came from the planning 

context (see the section on “vision,” earlier 

in this chapter). This is because planners 

historically used methods to surface implicit 

models based on the input of heterogeneous 

groups of stakeholders.

Second, there had been a rise in emphasis 

on developing visual models that capture 

the complexity of the program–outcome 

process, in parallel with the growth of 

stakeholder-driven models. Perhaps primary 

among these is the use of logic models

representing structured evaluation criteria 

that link outcomes with program activities 

and processes, as well as the theoretical 

assumptions and principles of the 

program.22 Logic models represent causal 

models of evaluation in which actions lead 

to measurable outcomes. As such, they are 

precursors to the more dynamic analyses 

with feedback that comes from system 

dynamics (see chapter 5), where the effects 

of actions can influence factors, which in 

turn affect the relationships between actions 

and outcome.

System Models for Evaluation

The evaluation framework of the Centers 

for Disease Control and Prevention 

(CDC; figure 4.4) is a recent example of a 

participatory evaluation system model that 

is integrated with use of logic models. This 

framework illustrates well the shift that 

is occurring to more collaborative system 

models for evaluation and systems learning. 

This model involves a six-step process108

in which engagement of stakeholders is 

the initial activity in an evaluation effort, 

preceding the definition of more formal 

aspects of the evaluation, such as the 

program design and logic models used, 
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evaluation design, and expected outcomes. 

This framework also is set in the context of 

four core standards (figure 4.4, center) that 

are relevant to the evaluating function of 

systems organizing: 

1. Utility—Degree to which the 

information needs of intended users are 

served by evaluation

2. Feasibility—Potential for achievement in 

terms of project scope, cost, and political 

factors

3. Propriety—Conformity to legal and 

ethical standards and acceptable benefit 

to affected parties

4. Accuracy—Technically accurate 

information

This framework represents an evolution 

of evaluation methodology within a large 

hierarchical organization such as CDC and 

further evidence of systems organizing 

trends combining quantitative and mixedmethod techniques with an increased level 

of stakeholder input.

Summary of Systems Organizing 

Model

From the perspective of complex systems, 

the local interactions of semiautonomous 

agents lead to emergent complex 

phenomena. To facilitate achievement of 

purposeful ends in a complex adaptive 

system, the system as a whole must 

have a stated goal (vision principle) and 

participatory action of individual agents 

(action principle). Agents also need to 

connect their actions (missions) to the 

collective vision and understand that the 

vision and the mission of the system are 

in constant feedback with each other; 

they are distributed, dissipative, dynamic, 

and adaptive. Structures that afford 

self-organization rather than simple 

Figure 4.4 Elements of Evaluation Framework

Engage

stakeholders

Steps

Standards

Utility

Feasibility

Propriety

Accuracy

Gather credible

evidence

Describe

the program

Focus the

evaluation

design

Justify

conclusions

Ensure use

and share

lessons learned

Note. From Framework for program evaluation in public health. 1999. Morbidity and Mortality Weekly Report Recommendations 

and Reports 48 (RR-11): 1–40, Figure 1.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

organization also should be encouraged 

(structure principle). In addition, the 

culture must be infused with a passion 

for learning (learning principle) and 

ongoing evaluation. It also is critical that 

mission be intimately linked with vision 

and vice versa and that the capacities for 

self-organization and learning are mapped 

onto vision and mission. Using these four 

principles, organizational leaders may 

choose between more traditional approaches 

(e.g., leadership, management, delegation, 

organized structures, and discrete 

evaluations) and systems approaches 

(e.g., facilitation and empowerment, selforganizing structures, participatory action, 

and continuous evaluation). 

The leader has the freedom to move between 

these positions on the continua much like 

the equalizer on a stereo is tuned, matching 

the organizational situation and immediate 

context to a particular style. However, 

because of their unique and complex 

interorganizational structures, tobacco 

control initiatives can benefit greatly from 

moving toward the systems end of the 

continua. Numerous methods are available 

for the systems organizing leader. By linking 

(mapping) the purposeful principles of 

vision and action to the emergent principles 

of structure and learning, a balance 

between powerful emergent properties and 

purposeful constitution can be achieved. 

In addition, because the self-organizing 

system is participatory and because mission 

is linked to vision, systems-friendly methods 

can be used to link semiautonomous 

and local action and the larger goals and 

objectives of the whole.

In the discussion of the four systems 

organizing principles, a wide variety of 

methods were presented. Table 4.2 shows 

a matrix that relates the four principles of 

systems organizing to those methods. Each 

method is classified in terms of its primary 

and secondary emphases related to the four 

principles. This classification is not meant 

to be definitive; different people would likely 

classify the methods differently. Some of the 

methods are ideally suited for one principle; 

others could be used for several or all of the 

principles. Excluded from this table and 

chapter are the great variety of methods 

relevant to systems organizing that come 

from the traditions of system dynamics 

modeling (chapter 5), network analysis 

(chapter 6), and knowledge management 

and transfer (chapter 7), because these 

methods are considered in detail in those 

chapters.

Collaboratively 

Constructed Concept 

Maps for Systems 

Organizing: Case 

Studies

A major challenge in systems organizing 

(of consortia, networks, or partnerships) is 

the development of methods and processes 

appropriate for complex interorganizational 

contexts. Two case studies illustrate 

incorporation of the ideas of systems 

organizing into real-world contexts. One 

study was conducted to improve integration 

of research and practice in public health, 

and the other was conducted to develop a 

conceptual model of the characteristics of 

strong, cooperative local and state tobacco 

control programs. Both case studies 

involve key issues in tobacco control 

and provide examples of the creation of 

outcomes through a structured process 

in a participatory, multistakeholder 

environment—a system of organizations. 

At a deeper level, both also produced 

results that would not have been possible 

in the absence of organizing a system of 

stakeholders. The intent is not to argue 

for a specific methodology but rather to 

underscore the importance of engaging 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

Table 4.2 Systems Organizing Methods by Principle

Systems organizing methods

Planning 

collective 

vision

Organizing and 

participatory 

self-organizing

Facilitating 

mission 

leadership

Evaluating 

and systems 

learning

Collaborative needs assessment9 X

Brainstorming10 X X X X

Nominal groups approach11 X X X X

Focus groups12 X X X X

Delphi technique13 X X X

Concept-mapping structured conceptualization109 XX XX X X

Concept mapping (mind mapping, idea 

mapping)14,15

X X

Strategy maps20 X X

Cognitive maps21 X X X

Outcome mapping25 X X XX

Logic models22 X X X X

Future-search conferences26 XX X X X

Conference model27,28 X X X

Large-scale interactive process29 X

Real-time strategic change30 X X

Participative work redesign31 X XX

Open-space meetings32–34 XX XX

Appreciative inquiry summit methodology35 XX

Search conference36 XX X X

Large group interventions58 X X X X

Total quality management X

Business process reengineering X

Community-based participatory research XX

Participatory action research X

Participatory intervention model XX

Empowerment evaluation99 XX

Appreciative inquiry as methodology35 XX

CDC evaluation framework XX

Notes. X = method suited for systems organizing function; XX = method especially suited for systems organizing function; 

CDC = Centers for Disease Control and Prevention.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Managing a Complex National System of Organizational Partners: Notes from the Real World

Systems organizing issues are well illustrated by an example from a field in public health that 

neighbors tobacco control, the field of obesity control and nutrition. The latter has a much longer 

history of attempts to coordinate across sectors and organizations. One such effort was a national 

coalition sponsored by a foundation seeking to mobilize the major national players in nutrition 

around a campaign called Project Low-Fat Eating for America Now (Project LEAN) in 1988–92. 

Organizations in the public, private, voluntary, and independent sectors were convened to form 

a coalition to coordinate their nutrition messages, products, and services around the theme of 

low-fat eating. The systems organizing issues that needed to be addressed in building a system 

or coalition of disparate stakeholder organizations were examined by creating vision, structure, 

action, and learning:

Creating vision. Who is the leader? The first of several caveats on coalitions that one could draw 

from this example is, “Everybody wants coordination, but nobody wants to be the coordinatee.” 

One corollary is that designation of a chairperson for the meeting of disparate partners in a 

coalition immediately establishes a perception of imbalance in the partisan positions of the 

various sectors or organizations. The private sector versus the public sector views of foodlabeling policies, for example, would be perceived to be tilted in one direction or the other by the 

designation of anyone selected to chair the meetings.

Creating structure. The first system problems encountered at the first meeting related to 

managing the balance of power—governance questions such as who should chair the meetings and 

what the representation and the voting rights and weights should be of the various organizations. 

Considering the vastly different sizes and power of the organizations at the table, it was clear that 

the conveners could treat them equally only at the peril of the cohesiveness of the coalition. 

Moreover, a corollary of the coordinator–coordinatee dilemma mentioned here is that large 

organizations with considerable stake in an issue are loathe to be at the mercy of a coalition’s 

decisions and are the first to break ranks and leave the coalition when they find that their 

influence is diminished by their membership. The first point at which they may feel diminished 

is in selection of the chairperson. However, a more compelling reason to bolt arises when they 

realize that their vote counts equally with the votes of many small partner organizations. They 

will be even more concerned if they sense that some smaller organizations are or could be 

ganging up on them in the voting or using the coalition as a platform to berate them or disparage 

their products or motivations.

Creating action. Another systems issue arises in managing the chain of command in the coalition 

as the meetings unfold. The first meeting might be attended by many of the chief executive 

officers of several organizations, and the second and third meetings, by their deputies. By the 

time of the third meeting and later meetings, depending on the size of the organizations, the 

people around the table might not be in a position to cut deals or cast a vote that would commit 

their organization to a plan or an offering of support. Meetings begin to bog down and end in 

stalemates because many of those present must defer a vote on decisions or withhold support for 

actions until they can check with superiors.

Creating learning. Finally, following through on the initial vision can be yeoman’s work. A set 

of coalition systems issues arise in the phasing from initial meetings on consensus building 

and declaration of common purposes, where coalitions are at their best, to later meetings 

on implementation, where coalitions frequently are at their worst. Coalitions make blunt 

instruments for micromanagement and often collapse under the weight of their own cumbersome 

managerial and decision-making structures when they come to the implementation phase.

Over time, there have been a growing number of successful systems organizing efforts in 

public health practice and literature, ranging from coalition-building efforts such as the Global 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

tobacco control from a systems organizing 

perspective.

These case studies involve the use of 

concept mapping, one of many systems 

organizing approaches discussed earlier in 

this chapter. (For a detailed explanation of 

concept mapping, see appendix 4A.) Concept 

mapping, sometimes called structured 

conceptualization, is a participatory and 

integrated mixed-methods approach 

facilitating the collaboration of tens or 

hundreds of people synchronously or 

asynchronously on a project, in person 

or using Web technology, in a manner 

that enables active involvement of each 

participant.16 The primary product of this 

method is a series of “maps” that summarize 

the collective thinking of the group, 

consensus matches to explore the diversity 

of participant views, bivariate graphs that 

enable considerable detail to be organized 

for action planning and implementation, 

and a broad array of summary data. The 

method integrates qualitatively based, 

judgmentally oriented individual and group 

processes (brainstorming, sorting, rating, 

and interpretation of results) with a series of 

multivariate statistical analyses to produce 

the maps and related outputs. The products 

enhance the ability of groups or networks 

to purposefully envision, enact, and manage 

systems changes that increase the capacities 

for self-organizing and/or learning.

As one example of systems organizing 

“friendly” methods, concept mapping is 

especially useful to build collective vision 

and the perception that an individual’s daily 

actions are situated in a larger contextual 

purpose. Metaphorically, concept mapping 

results in a “you are here” map of the 

larger system that allows each agent in the 

system to understand how his or her efforts 

(mission) are situated in the larger collective 

action (vision). In addition, methods such 

as concept mapping provide groups and 

individuals with a powerful reflective 

learning process. Finally, any methodology 

that increases the bonds between agents in 

a network, especially special types of bonds 

such as long bonds or a combination of weak 

and strong ties across diverse networks, 

can create capacity for desired outcomes. 

These include phenomena of small worlds, 

in which small numbers of links bridge any 

two points within a network,40 as well as selforganization, adaptation, complexity, and 

emergence. 

There are several reasons for using concept 

mapping as the vehicle for illustrating 

systems organizing approaches. First, 

it is a good exemplar of a structured 

participatory method, a key feature of 

systems organizing. Second, it is a hybrid 

method that integrates well-known 

qualitative (brainstorming, sorting) and 

quantitative (multidimensional scaling, 

hierarchical cluster analysis) methods. In a 

sense it is a conglomerate of several other 

systems organizing methods (various group 

processes and formal modeling methods), 

and, as a result, the examples illustrate 

some of the major features of each. Third, 

it was timely; several projects that were 

particularly apt illustrations for public 

health and tobacco control either were in 

Tobacco Research Networka to the case studies outlined later in this chapter. At the same time, 

understanding the kinds of roadblocks that have occurred in past efforts such as Project LEAN 

can help to inform the kinds of social and organizational issues that must be addressed to make 

these systems efforts practical and effective. 

a

Research for International Tobacco Control. 2002. Bridging the research gaps in global tobacco control: 

A synthesis document. Ottawa, ON: Research for International Tobacco Control.
87

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

progress or had been recently completed 

at the time of this project. Despite its 

advantages as a method for illustrating 

systems organizing approaches, the use of 

concept mapping in these examples is not 

meant to convey any inherent distinction 

over other systems organizing methods. 

Many methods are available—this is an 

extremely dynamic area. Each of them 

would likely contribute to and complement 

the results obtainable through concept 

mapping.

Case Study 1: Closing the Gap 

between Research Discovery 

and Program Delivery

The 2001 report of the Institute of 

Medicine,110 which determined that the lag 

time from a scientific discovery to use in 

practice was typically 15–20 years, drove 

the motivation for closing the gap between 

research discovery and program delivery. 

NCI, the Center for the Advancement of 

Health, and the Robert Wood Johnson 

Foundation held a collaborative conference 

as a foundation for developing a more 

integrated effort to close the gap between 

research discovery and program delivery in 

cancer control.

To make the most of participants’ time 

at the conference, the sponsoring 

organizations asked them to take part in 

a preconference collaborative project to 

help them understand the perspective of 

experts—practitioners, researchers, and 

others who work in health promotion, 

disease prevention, and cancer control. The 

focus was primary ways for major agencies 

affiliated with the U.S. Department of Health 

and Human Services (e.g., NCI, CDC, Agency 

for Healthcare Research and Quality, Centers 

for Medicare & Medicaid Services, Health 

Resources and Services Administration, 

and National Institutes of Health) and the 

national, state, and local partners to work 

together to accelerate adoption of cancer 

control research discoveries into practice. 

The results of the conference were then 

used to develop a logic model and related 

action plans for implementation. The same 

framework will subsequently be used to 

evaluate progress on these plans and to 

capture the individual and organizational 

learning that took place.

Thus, the example encompasses both 

the purposeful (vision and mission) and 

emergent (self-organizing and learning) 

principles of the systems organizing 

framework. Participants were asked to 

brainstorm online in response to the 

following focus prompt: 

One thing that should be done to 

accelerate the adoption of cancer control 

research discoveries by health service 

delivery programs is...

Approximately 55 people contributed more 

than 200 statements that were subsequently 

synthesized by the steering committee into 

98 unique ideas. The statements were sorted 

by 19 members of the planning committee. 

The data were aggregated and analyzed 

with a sequence of multivariate analyses 

that included multidimensional scaling and 

hierarchical cluster analysis. The resulting 

map grouped the 98 ideas into 12 conceptual 

categories. The participants also were asked 

to identify clusters of clusters that seemed 

to belong together and provide a label for 

each such region of the map. Participants 

identified four major regions: (1) policy, 

consisting of policy issues that would enable 

more integration of research and practice, 

as opposed to policy that results from 

such efforts; (2) research; (3) practice; and 

(4) partnerships and support.

In addition, a broader region of 

intermediaries, both government and 

private, was defined by participants, 

encompassing the regions of policy, 

research, and practice. Figure 4.5 illustrates 

the final labeled concept map. 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

Figure 4.5 can be interpreted meaningfully 

beginning with the policy region. To 

enhance the integration of research 

and practice, begin with “policies” that 

promote such activities. Then move 

counterclockwise to “research,” especially 

explicit funding for the integration 

of research and practice. Continue 

counterclockwise to “practice,” where 

tools, messages, and dissemination 

mechanisms are critical. Intermediaries, 

both government and not-for-profit 

agencies, provide the “glue” for this process, 

advocating for policy change, supporting 

the research community, and helping to 

translate and disseminate research. This 

process relies throughout on partnerships 

and support that provide the network 

context needed and the input and feedback 

loop between researchers and practitioners, 

including the community of relevance. 

Participants also were asked to rate each 

of the statements on importance and 

feasibility. Figure 4.6 shows the average 

importance ratings for all participants for 

each of the 12 clusters. More layers in a 

cluster signify higher average importance; 

fewer layers indicate lower importance. The 

figure shows several clusters with relatively 

high importance ratings: “diffusion/

dissemination,” “strategies,” and “service 

standards.” On the other hand, the “training 

and support” and “barriers” clusters were 

rated as having relatively low importance. 

Maps for rating clusters also were produced 

for different subgroups (e.g., practitioners 

and researchers) and for the feasibility 

ratings. Each of these cluster rating maps 

can be thought of as a “pattern” of the rating 

across the map.

Figure 4.7 illustrates the pattern match 

comparing importance and feasibility ratings 

for these clusters. Importance is depicted on 

the vertical left axis, and feasibility is shown 

on the vertical right axis. Each horizontal 

line represents one of the cluster averages. 

The point at which the line hits the axis 

indicates a cluster’s average value.

Figure 4.5 Final Interpreted Concept Map

Strategies

Diffusion/Dissemination

User Tools 

& Messages

Community

Involvement

Research/Practice 

Partnerships

Training & Support

Barriers

Service

Standards

Methods Challenges

& Opportunities

Research/Practice

Funding

Dissemination

Research

Funding

Electronic

Dissemination

Practice

Partnerships & Support

Research

Policy

I ntermediaries

Note. Map shows 12 clusters with labels provided by participants and 4 regions of clusters.
89

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

The correlation at the bottom of the 

pattern matching is a standard Pearson 

product-moment correlation, indicating 

the strength of the overall relationship. In a 

strong positive relationship, the lines would 

mostly be horizontal. In this case, there 

are a considerable number of crossover 

lines, suggesting that the relationship of 

importance and feasibility is relatively low. 

The lines that cross over most dramatically 

are the clusters most different in relative 

importance and feasibility. For example, 

“service standards” was considered to be 

one of the most important clusters and one 

of the least feasible. In contrast, “electronic 

dissemination” was judged to be most 

feasible but relatively low in importance.

The ratings of importance provided by 

practitioners and researchers are compared 

in figure 4.8. This match indicates 

considerable differences in what each group 

considers to be important. The correlation 

suggests virtually no relationship between 

the average importance ratings of these 

two groups. This result constitutes one 

of the most salient findings of this study, 

a finding with considerable implications 

for integration of practice and research in 

this context. It suggests that practitioners 

and researchers have markedly different 

priorities and indicates which areas are 

relatively more important for each group.

A major goal of this project was action 

planning to improve the integration of 

research and practice. Because pattern 

matching revealed fundamental differences 

in the perspectives of subgroups on the 

issues, the decision was made to address 

action planning separately for each major 

subgroup and to subsequently combine 

the separate subgroup plans into an 

integrated action plan. This is an excellent 

example of identifying individual and/or 

group needs to establish a mission for 

their daily action while also understanding 

the place of that mission among other 

missions and its linkage to the collective 

vision. To accomplish action planning, 

a “go-zone” bivariate plot is often used. 

Figure 4.9 shows the go-zone plot for the 

Figure 4.6 Cluster Rating Map

Strategies

Diffusion/

User Tools & Messages Dissemination

Community Involvement

Research/Practice Partnerships

Training & Support

Barriers

Service Standards

Methods Challenges & 

Opportunities

Research/Practice

Funding

Dissemination

Research

Funding

Electronic

Dissemination

Layer Value

1 3.46 to 3.53

2 3.53 to 3.60

3 3.60 to 3.66

4 3.66 to 3.73

5 3.73 to 3.80

Notes. Map shows average rating for importance, by cluster, for all participants. Legend shows average ranges for clusters by 

numbers of layers in graph.
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

Figure 4.8 Pattern Match for Degree of Consensus between Practitioners and Researchers on 

Average Importance Ratings (correlation coefficient, r)

r = .05

Practitioners Researchers

4.11

3.73

3.86

3.36

Training & Support

Electronic Dissemination

Barriers

User Tools & Messages

Dissemination Research Funding

Community Involvement

Methods Challenges & Opportunities

Service Standards

Research/Practice Funding

Strategies

Research/Practice Partnerships

Diffusion/Dissemination

Barriers

Community Involvement Diffusion/Dissemination

Service Standards

Training & Support

Research/Practice Partnerships

Electronic Dissemination

User Tools & Messages

Research/Practice Funding

Dissemination Research Funding

Strategies

Methods Challenges & Opportunities

Figure 4.7 Pattern Match for Relationship of Cluster Averages for Importance Versus 

Feasibility (correlation coefficient, r)

r = .36

Importance Feasibility

3.8

3.46

3.83

2.76

Barriers

Service Standards

Training & Support

Research/Practice Funding

Community Involvement

Research/Practice Partnerships

User Tools & Messages

Methods Challenges & 

Opportunities

Dissemination Research

Funding

Diffusion/Dissemination

Strategies

Electronic Dissemination

Barriers

Training & Support

Electronic Dissemination

Methods Challenges

& Opportunities

Community Involvement

User Tools & Messages

Research/Practice Funding

Dissemination Research Funding

Research/Practice Partnerships

Strategies

Service Standards

Diffusion/Dissemination
91

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

diffusion/dissemination cluster for the 

practitioner group. Ideas rated highly on 

both importance and feasibility are shown in 

the upper-right quadrant. The go-zone plot 

shows the data in finer detail, listing actual 

cluster statements as used in the analysis, 

and indicating which statements have high 

importance and feasibility at the statement 

level as opposed to the cluster level.

The go-zone plot helps point to potential 

action, but it does not prescribe it. One 

would not automatically proceed to 

implementing just the ideas that are in 

the upper right quadrant. Other factors 

may be critically important to decisions 

about action. For example, it is possible 

that an idea is high in feasibility and only 

moderately high in importance. Should it 

be implemented? The answer may very well 

depend on some other variable, such as cost. 

If the moderately important action costs 

almost nothing to implement (probably 

part of what contributed to its high 

feasibility rating), it might be implemented 

for that reason, even though there are 

statements that have higher importance 

ratings. Go-zones, like all of the products 

in concept mapping, are more useful for 

their suggestive power than as prescriptive 

mechanisms.

Across all analyses, results show that each 

group (researchers, practitioners, and 

intermediaries) holds different ideas about 

its own role and the roles of other groups in 

disseminating and implementing evidencebased interventions. Participants agreed that 

the responsibility for dissemination must 

be shared. The concept map acted as the 

foundation for development of action plans 

(missions) that would help the participants 

navigate more effectively toward a more 

integrated research and practice effort 

(vision). The ability of each individual or 

subgroup to establish this important link 

between mission and vision is critical, 

because this is the purposeful function of 

systems organizing. Meanwhile, because it 

is collaborative, bond forming, inclusive of 

Figure 4.9 Bivariate Go-Zone Plot of Importance and Feasibility Ratings of Practitioners, 

for Diffusion/Dissemination Cluster

3.0 3.5 4.0 4.5

4.5

3.5

2.5

Feasibility

Provide best practice examples of how programs

adopt evidence-based interventions. (77)

Synthesize and communicate research results in

ways that are understandable to practitioners. (81)

Encourage JNCI to publish dissemination studies in each 

issue. (92)

Create mechanisms to distribute practical information

(e.g., procedural details) from research discoveries. (11)

Synthesize available research results to reduce the barrage

of variable findings from each new "study of the week." (15)

Publish key findings in the form of inserts in targeted

magazines. (21)

Develop inexpensive, nontraditional ways to disseminate 

research findings. (37)

Establish a central clearinghouse to evaluate new 

discoveries and place them in proper perspective. (39)

Work with the media to disseminate research results

in a clear, nonconfusing manner. (45)

Annually publish NCI-funded interventions shown

to be effective. (47)

Have NCI hire science writers who can translate

research articles into practical advice for practitioners. (73)

Importance

11

39 15

21 92

73

77

45 81 37

47

Note. JNCI = Journal of the National Cancer Institute.
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

diverse groups and individuals, and process 

oriented, the concept mapping activity 

reinforces many of the important qualities 

of self-organization. The very process is 

capacity forming.

Participants in the project agreed that 

ongoing interaction among researchers, 

practitioners, and intermediaries is 

essential to improving the effectiveness of 

activities for cancer control. Participants 

also noted that there are few incentives and 

opportunities to focus on these topics in 

the course of their daily work lives. Several 

groups suggested strategies to sustain the 

momentum begun at the meeting, and plans 

for follow-up were formulated. This result is 

fairly common in meetings of all kinds, but 

there often is not enough time to do all that 

is desired. Instead of developing initiatives, 

it might be more beneficial to search the 

system network to find local or small-scale 

examples of success. By adjusting the flow of 

resources or information to such initiatives, 

the systems organizer transfers leadership 

and planning functions, as well as the 

collective interests of the group (established 

in this process), temporarily to one part of 

the system. 

Subsequent to the action-planning 

conference, a logic model22 was developed 

to use the results of the concept-mapping 

project to integrate research and practice. 

The logic model is a key mechanism for 

assessment of both the implementation 

and outcomes of this effort to integrate 

practice with research. For each cluster, it 

is possible to develop one or more measures 

of performance that can be monitored over 

time. The map and corresponding logic 

model can be used to organize all these 

measures and as a graphic device to display 

evaluation results. This approach will help 

to determine whether certain clusters on 

the map are neglected in action planning or 

whether certain paths in the logic model are 

not achieved in practice. 

Case Study 2: Empirical 

Conceptual Model of Strong, 

Cooperative Local and State 

Tobacco Control Programs

The objectives of this project were to describe 

the components of strong tobacco control 

programs and use the resulting framework 

to define optimal collaboration between state 

and local programs. Participants identified 

themselves as being associated with tobacco 

control at the state level, local level, or both 

levels. Participants were asked to respond to

a focus prompt for brainstorming: 

One specific component of a strong 

tobacco control program is...

Two tobacco control experts from the 

Battelle Centers for Public Health Research 

and Evaluation and one expert from the 

Johns Hopkins Bloomberg School of Public 

Health synthesized the 145 statements 

into 73 unique ideas. Sorting input from 

participants was analyzed using conceptmapping analysis,16 and the results arrayed 

the 73 statements into a 12-cluster solution. 

Figure 4.10 displays the final interpreted 

concept map. First, the map shows a distinct 

sequence from left to right. More immediate 

activities and processes are on the left, 

and longer term services and outcomes 

are toward the right. The map is divided 

into four regions (from more immediate to 

more long term): management, processes, 

programs and services, and outcomes. The 

map provides the framework for a process 

and outcome logic model of the components 

of process and outcome for strong tobacco 

control programs. 

Second, there is a distinction between an 

upper and a lower track, from left to right 

(two arrows). The upper track encompasses 

more systemic (environmental) change 

processes, such as policy advocacy and 

industry monitoring. The lower track 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

tends to focus more on efforts to change 

individual behavior, such as through media 

and education campaigns and services for 

smoking cessation. Finally, the cluster for 

youth policy and programs is in a central 

position. This position suggests that youth 

issues were felt to play a central role in 

tobacco control and that they span the full 

range of efforts from systemic to individual 

change.

Describing the components of strong 

tobacco control programs is a critical first 

step. However, it is important that the many 

organizations operating at different levels 

of the tobacco control system understand 

their roles and responsibilities relative to 

each other and to the collective vision. 

Participants also were asked to rate each of 

the program components for the degree to 

which it was a local or state responsibility. 

Figure 4.11 shows the average responsibility 

rating for each cluster of components of 

tobacco control. More layers signify greater 

state responsibility, and fewer layers signify 

more local responsibility. The areas most 

clearly considered to be the responsibility 

of the state are budgeting and monitoring 

industry, followed closely by advocacy, policy 

interventions, and outcome surveillance. 

The areas identified most often as local are 

mobilization, youth policy and programs, 

and public education. State responsibilities 

tend to be at the highest levels, with 

systemic change, and local responsibilities 

tend to predominate at the lowest levels, 

with individual change. 

A critical question is whether subgroups 

of raters perceive local and state 

responsibilities differently. The results 

of the ratings suggest that there is a 

high degree of agreement between local 

and state participants about the relative 

responsibilities for various program 

components. A similar consensus is evident 

Figure 4.10 Concept Map Showing Clusters, Cluster Labels, and Interpretations 

of Dimensions and Regions

Outcome

Surveillance

Policy Interventions

Advocacy

Youth Policy

& Programs

Infrastructure

Mobilization

Collaboration

& Technical

Assistance

Public Education

Media

Budget

Cessation

Services

Monitoring

Industry

Management Processes Programs & Services Outcomes

Systemic Change

Individual Change
94

4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

regarding ratings from participants who 

have less experience in tobacco control 

(≤5 years) and ratings from those who have 

more experience (>5 years). The results 

indicate a strong consensus across all 

subgroups about which components are 

state responsibilities and which are local 

responsibilities.

This project summarizes the components 

of a strong tobacco control program, as 

identified by the participating state and 

local stakeholders in the field of tobacco 

control. The basic map constitutes a 

conceptual framework categorizing 73 

components into 12 categories that, in turn, 

are grouped into 4 major areas that suggest 

a natural progression from management 

and infrastructure, through processes and 

programs, to outcomes. The framework also 

identifies how strong tobacco control efforts 

address both systemic and individual change 

and that the tendencies are to address 

systemic change at the state level and 

individual change at the local level. Finally, 

the results show that across all the major 

identified subgroups (e.g., state and local, 

front line and research, and experienced and 

inexperienced), there is consensus about 

which components are local responsibilities 

and which are state responsibilities.

These results can be used in several ways. 

Tobacco control systems can benefit by 

examination of efforts at the state and local 

levels to determine whether each sector is 

addressing components in its respective 

realm of responsibility. To make such an 

assessment more feasible, it is essential 

to develop one or more instruments that 

can be used at the state and local levels to 

measure the success of tobacco control 

programs. Such instruments could 

build on the strength of tobacco control 

(SoTC) measure developed as part of the 

evaluation of the American Stop Smoking 

Intervention Study.111,112 The results of the 

study presented here can inform the local 

adaptation of this instrument, originally 

designed to reflect state programs as part of 

Figure 4.11 Cluster Average Ratings of Responsibility

Layer Value

1 2.62 to 2.89

2 2.89 to 3.16

3 3.16 to 3.43

4 3.43 to 3.70

5 3.70 to 3.98

Outcome

Surveillance

Policy Interventions Advocacy

Youth Policy

& Programs

Infrastructure

Mobilization

Collaboration

& Technical

Assistance

Public

Education

Media

Budget

Cessation

Services

Monitoring

Industry

Note. Fewer layers indicate more local responsibility. More layers indicate greater state responsibility.
95

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

a national study. Furthermore, these results 

can be used to develop an appropriate 

short-form assessment instrument for rapid 

application at the local level that would 

yield results that can be linked to those of a 

more comprehensive assessment tool. For 

example, the map suggests that a simple 

12-category assessment instrument may 

be feasible, highlighting which specific 

components of the larger domain need to be 

emphasized in a local SoTC measure. 

Summary

This chapter describes a systems organizing 

approach to systems thinking, an alternative 

formulation of the traditional management 

model that, while encompassing it, goes 

significantly further. In place of the 

traditional linear progression of processes 

(planning, organizing, leading, and 

controlling), the systems organizing model 

is centered on four principles—vision, 

structure, action, and learning. These 

principles are enacted simultaneously and 

continuously in well-functioning systems. 

Tobacco control systems can benefit from 

incorporating these principles and using 

the many systems organizing methods that 

embody them. 

Two case studies of tobacco control used 

structured concept mapping16 to illustrate 

one of many methods that could be used 

in a systems organizing approach. The 

first case study focused on integration of 

research and practice in a project that was 

conducted primarily to create a logic model 

for actions to improve the dissemination 

of cancer research. The map constitutes a 

vision for members of the participant group, 

a model of their collective vision of the 

overall conceptual terrain for dissemination 

and integration of research and practice. 

The details on the map provide the basis 

for action and help the various participants 

construe the relationship of their roles to 

the broader vision. This example shows 

the sharp role differentiation between 

researchers and practitioners, revealing the 

implicit structure with respect to research 

dissemination. The map itself provided 

feedback to the participants, coupled with 

subsequent action through the logic model, 

suggesting a step in the evolutionary 

learning cycle. 

The second case study focused on the 

components of strong tobacco control 

programs at state and local levels. As 

in the first project, the map constitutes 

a conceptual model, a vision of the 

participants’ perceptions. The details of 

the map differentiate between participant 

groups, in this case, between state and 

local roles in the system. In addition, the 

map links these roles with different change 

processes, with states primarily responsible 

for systemic change and local efforts more 

directly responsible for change at the 

individual level. The map structure also 

suggests constructs for evaluation and how 

they might be organized into measures and 

collections of measures that can enhance 

system feedback and learning. 

Together, both projects illustrate the 

integrated quality of the VSAL model. 

In both, participants left with a better 

understanding of local, microscale action

and how it fits into the broader macroscale 

collective vision. Linking the multiple lines 

of the local participatory action of agents 

(missions) to the collective and emergent 

action of the system (vision) is critical in 

resolving the inherent tension between 

the purposeful nature and the adaptive 

nature of such systems. In both projects, 

the structure of the maps emerged from 

a simple rule-based process (brainstorm, 

sort, and rate) that was self-organizing. 

In both, there were clear implications for 

measurement and evaluation for the next 

round in an evolutionary cycle of feedback 

and learning. The examples provide working 

VSAL models that help to balance the 

tension between purpose and adaptation and 
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4 . H o w t o O r g a n i z e : S y s t e m s O r g a n i z i n g

between organization and self-organization 

and to illustrate the link between the model 

components (vision, structure, action, and 

learning) and various methods that relate to 

these components (table 4.2). 

Conclusions

1. Systems organizing implies a move away 

from the classical linear management 

processes of planning, organizing, 

leading, and controlling toward a more 

adaptive, participatory environment 

expressed here around the concepts of 

vision, structure, action, and learning:

n Vision encompasses a move from 

an environment of leading and 

managing to one of facilitating and 

empowering.

n Structure encompasses a move from 

organizing to self-organizing.

n Action encompasses a move from 

delegation to participation.

n Learning encompasses a move from 

discrete evaluation to continuous 

evaluation.

2. Two concept-mapping projects explored 

key areas of organizing as a system. One 

project, examining issues in accelerating 

the adoption of cancer control research 

into practice, yielded clusters of action 

items in areas of research, practice, 

policy, and partnerships. The other 

project examined components of strong 

local and state tobacco control programs 

and provided the framework for a logic 

model of process and outcome ranging 

from near-term to long-term objectives.
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Appendix 4A. Description of ConceptMapping Methodology

Concept mapping can help describe ideas16 and represent them visually in the form of a map. 

The process typically requires participants to brainstorm a large set of relevant statements, 

sort them into groups of similar statements, rate each statement on one or more scales, and 

interpret the maps resulting from data analyses. Analyses typically include two-dimensional 

multidimensional scaling (MDS) of the unstructured sort data, hierarchical cluster analysis 

of MDS coordinates, and computation of average ratings for each statement and cluster of 

statements. The maps that result show the individual statements in two-dimensional (x,y) 

space. More similar statements are located nearer to each other. Statements are grouped 

into clusters that partition the space on the map. Participants are led through a structured 

interpretation session designed to help them understand the maps and to label them in a 

substantively meaningful way.

Procedure

Trochim,16 who also gives examples of results of several concept-mapping projects,109 describes 

the general procedure for concept mapping in detail. The process can be implemented in a 

variety of ways, taking place in a continuous period as short as a two-day meeting or divided 

in phases that occur over weeks or months. It can involve as few as 10–15 participants or 

incorporate input from hundreds or thousands of stakeholders. The procedure described here 

is for a typical Web-based implementation over several months. All analyses are conducted and 

maps are produced by using Concept System computer software* designed for this process.

Generation and Structuring of Conceptual Domain 

Data are collected over the World Wide Web by using software designed for the purpose. 

Participants need only a standard Web connection and any standard Web browser. For those 

who may not have Web access, alternative mechanisms (e.g., manual mail in or faxback) also 

are made available as appropriate.

During the generation step, participants create statements by using a Web-based, 

structured brainstorming process10 guided by a specific focus prompt limiting the types of 

statements that are acceptable. The focus statement or criterion for generating statements 

is operationalized as a focus prompt that guides the participants in brainstorming. A typical 

focus prompt might read:

One specific issue that needs to be addressed in (insert topic) is...

*The Concept System computer software is used to consolidate and edit brainstormed statements, 

export and print these for sorting and rating, import and enter sorting and rating data, conduct the 

statistical analysis, including multidimensional scaling and hierarchical cluster analysis, and display a 

wide variety of map results.113
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The general rules of brainstorming apply. Participants are encouraged to generate as many 

statements as possible (upper limit, 200). Because this is a Web-based process, participation 

is anonymous. Participants cannot challenge or question the statements of others. However, 

in subsequent steps, they are able to discuss the statements. The process takes approximately 

10–15 minutes for each participant. Participants can return to the Web site repeatedly during 

the brainstorming period. Because participants work on the Web, they type statements 

directly on the computer and can immediately see their ideas along with everyone else’s. 

After the brainstorming session, the steering committee reviews the statements, editing 

them for clarity and grammar but not for content and ensuring that the statements are all 

syntactically “of a kind.” In some cases, participants or a designated subgroup are asked via 

Web/e-mail to review the edited statements and make final revisions.

The structuring step involves three distinct tasks: providing demographic information and 

sorting and rating the brainstormed statements. As with brainstorming, this information 

is collected over the Web or through alternative mechanisms for people with no access to 

the Web. Participants are asked to provide demographic information about themselves or 

the organizations they represent. These data are used to identify participants for subgroup 

analysis. For the sorting,114,115 each participant groups the statements “in a way that makes 

sense to you.” The only restrictions in this sorting task are that there cannot be (1) N groups, 

with each group having one item; (2) one group consisting of all items; or (3) a miscellaneous 

group—any unique item is to be put in a separate pile. The Web software enables the 

participant to create, delete, and name new groups and to move statements from one group 

to another. Weller and Romney115 explain why unstructured sorting (“the pile sort” method) is 

appropriate in this context:

The outstanding strength of the pile sort task is the fact that it can accommodate a large number 

of items. We know of no other data collection method that will allow the collection of judged 

similarity data among over 100 items. This makes it the method of choice when large numbers 

are necessary. Other methods that might be used to collect similarity data, such as triads and 

paired comparison ratings, become impractical with a large number of items.115(p25)

For the rating task, each participant rates each statement on a five-point, Likert-type response 

scale. The specific rating variables are determined with the steering committee before the 

concept-mapping project is started. Typically, participants rate the statements for relative 

importance, where 

1 = relatively unimportant (compared with the rest of the statements);

2 = somewhat important;

3 = moderately important;

4 = very important; and

5 = extremely important (compared with the rest of the statements).

Participants are unlikely to brainstorm statements that are totally unrelated to the focus. 

Therefore, rating should be considered a relative judgment of the importance of each item 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

in relation to all other items brainstormed. In addition, participants typically also rate the 

relative feasibility of addressing each issue, where 

1 = not at all feasible;

2 = not very feasible;

3 = somewhat feasible;

4 = moderately feasible; and

5 = very feasible.

Other ratings of the statements may be developed and accomplished as the overall project 

unfolds.

Data Analysis

The concept-mapping analysis is handled automatically by the Concept System program, 

beginning with construction from the sort information of an N × N binary, symmetric matrix 

of similarities, Xij. For any two items, i and j, a 1 is placed in Xij if the two items were placed 

in the same pile by the participant; otherwise a 0 is entered.115 The total N × N similarity 

matrix, Tij, is obtained by summing across the individual Xij matrices. Thus, any cell in 

this matrix could take integer values between 0 and the number of people who sorted the 

statements. The value indicates the number of people who placed the i,j pair in the same 

pile. The total similarity matrix Tij is analyzed by using nonmetric MDS analysis with a twodimensional solution. The solution is limited to two dimensions because, as Kruskal and 

Wish116 point out:

Since it is generally easier to work with two-dimensional configurations than with those 

involving more dimensions, ease of use considerations are also important for decisions about 

dimensionality. For example, when an MDS configuration is desired primarily as the foundation 

on which to display clustering results, then a two-dimensional configuration is far more useful 

than one involving three or more dimensions.116(p58)

The analysis yields a two-dimensional (x,y) configuration of the set of statements based on 

the criterion that statements piled together most often are located more proximately in twodimensional space and those piled together less frequently are farther apart.

The x,y configuration is the input for the hierarchical cluster analysis using Ward’s 

algorithm117 as the basis for defining a cluster. Use of the MDS configuration as input to the 

cluster analysis in effect forces the cluster analysis to partition the MDS configuration into 

nonoverlapping clusters in two-dimensional space. There is no simple mathematical criterion 

by which a final number of clusters can be selected. The typical procedure is to examine an 

initial cluster solution that was the maximum desirable for interpretation in this context. 

Then successively lower cluster solutions are examined. A judgment is made at each level 

about whether the merger seems substantively reasonable. The pattern of judgments of the 

suitability of different cluster solutions is examined. The final number of clusters is selected 

to preserve the most detail and still yield substantively interpretable clusters of statements.
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The Concept System program automatically graphs the MDS configuration of the statement 

points in two dimensions. This “point map” displays the location of all the brainstormed 

statements. Statements closer to each other generally are expected to be more similar in 

meaning. A “cluster map” also is generated that displays the original statement points 

enclosed by polygon-shaped boundaries for the clusters. 

The one-to-five importance and feasibility rating data are averaged across people for each item 

and each cluster. This rating information is depicted graphically (1) in a “point rating map” 

showing the original point map with the average rating per item displayed as vertical columns 

in the third dimension and (2) in a “cluster rating map” that shows the cluster average rating 

by using the third dimension. The following materials should be available for use in the 

session on map interpretation:

1. List of brainstormed statements grouped by cluster

2. Point map showing MDS placement of brainstormed statements and identifying 

numbers

3. Cluster map showing cluster solution

4. Point rating maps showing MDS placement of brainstormed statements and 

identifying numbers, with average statement ratings overlaid

5. Cluster rating maps showing final cluster solution, with average cluster ratings 

overlaid

All the graphics are created interactively by the Concept System and projected onto a screen 

for participants to see.

Interpretation of Concept Maps

A preliminary interpretation of results is conducted by the project facilitation team and 

used as the foundation for subsequent use. At the meeting itself, the core group participants 

convene to review and interpret the results directly. This interpretation session follows a 

structured process described in detail by Trochim.16 The facilitator begins the session by 

giving participants the list of clustered statements and reminding them of the brainstorming, 

sorting, and rating tasks performed earlier. Each participant is asked to read silently through 

the set of statements in each cluster and generate a short phrase or word to describe or label 

the set of statements as a cluster. The facilitator leads the group in a discussion, working 

cluster by cluster to achieve group consensus on an acceptable label for each cluster. In most 

cases, when people suggest labels for a specific cluster, the group readily comes to consensus. 

If the group has difficulty achieving consensus, the facilitator suggests hybrid names that 

combine key terms or phrases from several individuals’ labels.

Once the clusters are labeled, the group is shown the point map and told that statements 

frequently sorted together generally are closer to each other on the map than are statements 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

infrequently sorted together. To reinforce the notion that the analysis placed the statements 

sensibly, participants are taken on a “tour” of the map by the facilitator, who identifies 

statements in various places on the map and examines their contents. After becoming familiar 

with the numbered point map, the participants are told that the analysis also organized the 

points (i.e., statements) into groups as shown on the list of clustered statements they already 

have labeled. The cluster map is projected, and participants are told that it is a visual portrayal 

of the cluster list. The agreed-upon cluster labels are shown on the final projected map.

Participants examine this labeled cluster map to determine whether it makes sense to them. 

The facilitator reminds them that, in general, clusters closer together on the map should be 

conceptually more similar than clusters farther apart and asks them to assess whether this seems 

to be true. Participants are asked to think of a geographic map and “take a trip” across the map, 

reading each cluster to assess whether the visual structure seems sensible. They are asked to 

identify interpretable groups of clusters or “regions.” These are discussed and labeled on the map. 

Just as in labeling the clusters, the group arrives at a consensus label for each identified region.

The facilitator notes that all the material presented uses only the sorting data. The results of 

the rating task are then presented through the maps for point rating and cluster rating. It is 

explained that the height of a point or cluster represents the average rating for that statement or 

cluster of statements. Again, participants are encouraged to examine these maps to determine 

whether they make intuitive sense and to discuss possible implications of information on the 

maps in relation to the focus issue. Figure 4A.1 shows a concept map from a previous project.

Figure 4A.1 Final Cluster-Rating Concept Map for Strategic Planning

Risk Commmunication

Unscreened Populations – Who & Why?

Theory & Methods

Health Services Research Methodology

Determinants

Theory

Health Services

Policy

Disparities

Decision Making

Communication Genetic/Risk

Site Specific

Cost-effectiveness

Note. Final cluster-rating concept map for strategic planning process shows clusters of statements and average importance ratings 

(as layers) for all participants.
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Consensus Analysis 

Pattern matching105,106 is used for a number of purposes in this process. The most immediate 

use is exploration of consensus across different stakeholders or stakeholder groups. Pattern 

matching is both a statistical analysis and a graphic analysis. Graphically, a pattern match is 

portrayed by using a “ladder” graph consisting of two vertical axes (one for each “pattern”). The 

vertical axes are joined by lines indicating average values for each cluster on the concept map 

for any variable specified. Statistically, the two patterns are compared with a Pearson productmoment correlation displayed at the bottom of the ladder graph. Figure 4A.2 illustrates a 

pattern match describing the degree of consensus between two stakeholder groups. 

In a “ladder” graph, strong agreement between patterns results in a set of near-horizontal lines 

that look like a ladder. The match in figure 4A.2 highlights discrepancies in cluster importance 

ratings between these groups. In addition, the pattern match enables immediate identification 

of cluster areas showing the greatest consensus or lack of agreement. Participants explore a 

number of such matches to ascertain the degree of consensus among stakeholders.

Action Planning 

For detailed action planning, it is useful to partition the results graphically by cluster. 

Typically, go-zone plots of the type shown in figure 4A.3 are used. The bivariate plot displays 

the relative importance and feasibility of each statement in the cluster. 

Figure 4A.2 Pattern Matching Ladder Graph of Degree of Consensus between Importance 

Ratings for Groups A and B for Concept Map in Figure 4A.1

r = .38

Group A Group B

3.67

3.02

3.81

2.94

Policy

Genetic/Risk

Site Specific

Methodology

Health Services

Decision Making

Determinants

Cost Effectiveness

Disparities

Communication

Theory

Communication

Site Specific

Methodology

Decision Making

Policy

Genetic/Risk

Determinants

Disparities

Health Services

Cost Effectiveness

Theory
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Each point represents a brainstormed issue. Each statement is shown with its identifying 

number. The upper-right quadrant indicates statements that have relatively high importance 

and feasibility. The plot takes its name from this quadrant, which is sometimes called the 

go-zone to indicate that these are the first issues one should “go” to when thinking about 

action planning. The participants review these plots and use them as the basis for an initial 

discussion about action planning.

Figure 4A.3 Go-Zone Plot of Feasibility Versus Importance for Methodology Cluster in 

Concept Map (Figure 4A.1)

2.5 3.5 4.5

3.1

2.6

2.1

1.6

Feasibility

Importance

85

82

77

72

70

61

29 26

22

17

3 1

Methodology (1)
104

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5

How to Anticipate Change in 

Tobacco Control Systems

Systems methods represent an evolutionary step in the ability to solve complex problems, 

moving from simple cause-and-effect models to more realistic scenarios in which 

causes and effects influence each other with dynamic, evolving feedback. This chapter 

provides examples of the application of one systems thinking approach, system dynamics 

modeling, to current tobacco control issues. System dynamics has a rich research 

heritage, emphasizes use of simulation models for anticipating dynamic change, and 

has the potential to provide a more sophisticated understanding of key issues in tobacco 

control, especially factors that influence smoking prevalence. This chapter also presents 

the results of a research project by the Initiative on the Study and Implementation of 

Systems (ISIS) to explore the use of system dynamics to develop 

n	 A causal map of tobacco control variables, based on participatory input from 

expert stakeholders;

n	 Formal simulation models based on factors derived from these causal maps; and

n	 Simulations of tobacco use prevalence and consumption across an aging chain of 

smokers.

The systems that fail are those that rely on the permanency of human nature, and not on 

its growth and development.

—Oscar Wilde (1854–1900)
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5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

Introduction

Today’s tobacco control environment 

represents a complex and dynamic 

interrelated system of issues and 

stakeholders. In this dynamic environment, 

change is continuous and poses significant 

challenges for those who would anticipate 

change and prepare for its consequences. 

There is growing recognition that systems 

approaches need to be able to address this 

challenge of dynamics and to anticipate 

change. System dynamics modeling is 

one of the most prominent and promising 

approaches for addressing such problems 

and, in doing so, helping to achieve more 

effective integration of research knowledge 

and its practical implications.

ISIS developed a detailed illustration of 

how system dynamics modeling could be 

applied to tobacco control to demonstrate 

the potential of this approach. The goal is to 

encourage further interest in and exploration 

of the promise of systems thinking and, 

ultimately, to provide new insights into how 

to reduce tobacco use. As demonstrated 

in the overview of systems thinking in 

chapter 3 and the following chapters in 

this monograph, system dynamics is only 

one systems thinking approach to tobacco 

control. Other methods offer different 

insights, and there is considerable potential 

to develop new thinking about tobacco 

control through the skilled application of a 

range of systems approaches.

System dynamics facilitates an 

understanding of feedback processes, 

especially how self-reinforcing or “vicious” 

cycles can arise. These often are unintended 

negative consequences of interventions. 

Simple illustrative examples of such 

counterintuitive thinking include the 

following:

n Building highways to ease traffic 

congestion eventually fails because 

less congestion invites more cars and 

drivers, thus clogging the highways 

again.

n Large-scale crackdowns and violent 

responses to terrorist acts kill and harm 

innocent people. Surviving friends and 

family join the terrorists, so the violence 

escalates.

n Corporate efforts to gain advantage in the 

competition for executive talent lead to 

raises in total compensation packages. 

Other firms respond in kind, negating 

the first firm’s momentary advantage 

and creating an overall self-reinforcing 

structure of raises and counterraises. 

Ultimately, this structure drastically 

increases executive compensation 

packages across the nation.

n Tobacco control efforts intended to 

reduce smoking prevalence cause market 

pressures that force tobacco companies 

to defend their interests with advertising 

and product promotion, strategic 

pricing, new product design, and target 

marketing, which tend to increase 

smoking prevalence.

At the same time, system dynamics is 

more than an attempt to quantify vicious 

cycles and unintended consequences. 

The conceptual and quantitative models 

are tools to enhance the ability to think 

about the dynamics of systems, leading 

to better decisions. The models can 

demonstrate effects that might not 

otherwise be envisioned or that might be 

counterintuitive. These approaches can 

highlight areas of uncertainty, helping 

to set priorities for future research or 

demonstrating that some things are simply 

unknowable. At a deeper level, they also 

can be used to simulate change to help in 

predicting what lies ahead and in shaping 

a more desirable future. Early system 

dynamics efforts have been undertaken to 

address different aspects of promoting or 

controlling tobacco use, such as
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

n Individual and family factors, such as 

genetics, personality traits, and parental 

role modeling

n Community-level interventions, such as 

smoking restrictions in public places and 

restrictions on advertising and promotion 

of tobacco products in retail stores

n State and national policies and practices, 

such as laws governing the purchase of 

tobacco products by minors, subsidies to 

tobacco growers, and research funding 

for the public health effects of active and 

passive smoking

n Global policies and practices, such as 

how multinational corporations maintain 

profitability by exploiting weaknesses in 

the policies of some countries, in trade 

agreements, and in the international 

Framework Convention on Tobacco 

Control, the first international health 

treaty1

Current best practices in areas ranging 

from prevention of smoking and smoking 

cessation programs to policy interventions 

have led to impressive short-term gains 

in factors such as reduced prevalence and 

consumption and morbidity and mortality. 

At the same time, these successes often 

carry within them the seeds of future 

problems, such as reduction in funding 

for tobacco control, shifting of public 

health priorities, and the counterefforts 

of the tobacco industry. As a result, poorly 

anticipated problems frequently loom, 

ranging from higher prevalence of smoking 

among groups such as young women, 

increased global marketing of tobacco, and 

fragmentation of efforts among tobacco 

control stakeholders—issues that ultimately 

could negatively affect overall public health. 

In areas such as these, in which traditional 

tools have proved insufficient, system 

dynamics modeling can provide a way to 

extend cause-and-effect models to include 

the dynamics of feedback and thereby 

provide more accurate models on which to 

base future policy.

System Dynamics

Computer simulation is used to assist 

thinking about complex dynamic systems. 

This approach grew out of (1) advances in 

computing technology, (2) an improved 

understanding of strategic decision making, 

and (3) developments in understanding the 

Definitions: System Dynamics Versus Systems Thinking

System dynamics approaches such as those outlined here constitute one of many methods to treat 

behavior as a system. However, definition of the broader term systems thinking, which is at the core 

of this monograph, is the subject of considerable dispute. To some, systems thinking is the broad 

discipline of exploring and modeling system behavior. To others, systems thinking is more narrowly 

defined, constituting their essential approach to systems. Those involved in ISIS have taken a broadbased and more inclusive stance on the definition. This chapter provides background on this issue, 

especially as it relates to the field of system dynamics. 

Systems investigator Barry Richmond felt strongly that systems thinking had a narrow, specific 

meaning (i.e., making inferences about behavior based on its underlying structure), which 

encompassed the modeling approach inherent in system dynamics.a He represents this “operational 

definition” of systems thinking by using a Venn diagram, arguing that system dynamics modeling 

forms a large part of the broader discipline of systems thinking. He contrasts this approach 

with other views, such as that of systems pioneer Jay Forrester of the Massachusetts Institute of 

Technology.b Forrester contends that systems thinking served as a small part of the overall system 

dynamics approach. The figure that follows is adapted from Richmond’s paper.a
112

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

Forrester’s View (left) versus Richmond’s View (right) on System Dynamics and

Systems Thinking

Systems Thinking

System Dynamics System Dynamics

Systems Thinking

In comparison, many people, including those involved in ISIS, now see system dynamics 

modeling as one of the broad range of tools and methods encompassed by systems thinking. The 

best representation of this relationship may be that system dynamics modeling is one of several 

components within the broader context of systems thinking. 

System Dynamics Modeling as One Approach to Systems Thinking

Systems Thinking System Dynamics

Modeling

Systems Organizing

Network Analysis

Knowledge

Management 

The debate about system dynamics and systems thinking terminology becomes particularly 

significant in light of other methodologies that adopt the “systems” label. One such methodology 

is Peter Checkland’s soft systems methodology.c It counters the emphasis that systems thinking 

is a modeling and measurement endeavor, seeing it instead as a learning process that takes a 

phenomenological rather than deterministic stance. Checkland views systems thinking as an 
113

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

evolving process driven by the purposeful activities of its stakeholders, in which all voices are 

represented and boundaries between divergent views are free to shift. This approach, in turn, 

has become part of the critical systems thinking approach espoused by Flood and Rommd and 

Midgley,e in which systems thinking is seen as a stakeholder-driven process. In his classic book 

Systems Thinking, Systems Practice: Includes a 30-Year Retrospective, Checkland himself defines 

systems thinking as a process that “makes conscious use of the particular concept of wholeness 

captured in the word ‘system’ to order our thoughts.”c(p4)

The argument presented here is against the parochial or narrow view of systems thinking and in 

favor of viewing it as a broad range of approaches that examine behavior as a system. In addition 

to approaches described in other chapters (systems organizing, network analysis, and knowledge 

management), there are other strategies that provide different lenses for examining systems. 

These include but are not limited to the following:

n System dynamics modeling, which seeks to create mathematical simulation models 

incorporating stocks, flows, and feedback, defined later in this chapter 

n “Soft” systems approaches that focus on processes and people, such as Checkland’s 

soft systems methodology,c Midgley’s participatory stakeholder-driven approaches,e

and Senge’s concept of a learning organization.f Compared with traditional system 

dynamics, these strategies examine the evolution of a system as an ecological process, 

poorly or imperfectly reflected through mathematical simulation

n Chaos and complexity approaches that examine behavior as systems of autonomous 

agents following simple rules, such as a flock of birds that take flight by following a 

leader and maintaining a specific distance from their neighbors, or a tobacco control 

intervention modeled on agents who create effects and countereffects

A continuing part of the evolution of the systems community, which can be seen itself as a 

system, is an evolution over time from the modeling of simple cause-and-effect relationships, 

such as logic models, to complex real-world interrelationships that are depicted iteratively over 

time with feedback. This depiction allows examination of effects, such as side effects, edge effects, 

and unintended consequences. The systems community ultimately represents an evolution from 

the “black box”—used in an attempt to understand reality—toward more detailed and realistic 

models of the dynamics of reality.

This evolution mirrors trends in science and technology that in turn enable more accurate 

representation of reality. These trends range from simple problems that can be solved as single 

equations to more complex problems that must be solved adaptively with evolving feedback. 

Today, this evolution continues from simple feedback to broader concepts such as neural 

networks, cybernetics, complex adaptive systems, and other self-learning physical phenomena.

a

Richmond, B. 1994. System dynamics/systems thinking: Let’s just get on with it. Paper presented at the 

1994 International Systems Dynamics Conference, Sterling, Scotland. Reprinted with permission from ISEE 

Systems. http://www.intraxltd.com/Downloads/Files/SystemDynamicsSystemsThinking.htm.

b

Forrester, J. W. 1961. Industrial dynamics. Cambridge, MA: MIT Press.

c

Checkland, P. B. 1999. Systems thinking, system practice: Includes a 30-year retrospective. Chichester, UK: 

John Wiley and Sons.

d

Flood, R. L., and N. R. A. Romm, eds. 1996. Critical systems thinking: Current research and practice. New 

York: Plenum.

e

Midgley, G. 2000. Systemic intervention: Philosophy, methodology and practice. Contemporary Systems 

Thinking series. London: Springer.

f

Senge, P. M. 1994. The fifth discipline: The art and practice of the learning organization. New York: Currency.
114

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

role of information feedback in the dynamics 

of complex systems. System dynamics 

practitioners seek to frame system behavior 

in terms of endogenous components with 

definable and self-contained behaviors, 

which in turn interact with each other to 

produce an evolutionary outcome.

Some abbreviate this idea as the “system as 

cause.” Explaining the behavior of a system 

in terms of self-contained components 

that interact over time can force causal 

influences to double back on themselves, 

forming feedback loops of circular causality. 

The feedback concept empowers this 

component-level point of view and gives 

it structure. Thus, the system dynamics 

approach is partly characterized by its heavy 

use of a feedback perspective.

This viewpoint is so important that system 

dynamics practitioners and others might 

define systems thinking succinctly as the 

mental effort to uncover integral sources of 

system behavior. Much of system dynamics 

can be thought of as computer simulation 

in support of systems thinking. The power 

of the system dynamics approach comes 

from this component-level, feedback-rich 

viewpoint, in which all purposeful action 

takes place in the classic cybernetic loop 

that includes

n Goals for the system

n Current state of the system

n Perceptions of that current state

n The gap between goals and perceptions

n Action intended to reduce the gap, 

resulting in a new state of the system

n Revised perceptions, leading to further 

actions

Unfortunately, the world that analysts 

attempt to simulate is more complicated 

than that, as figure 5.1 suggests. The 

Figure 5.1 Feedback Loops in a System Dynamics Model

Actual state of

the system Changes in the state

of the system

Autonomous changes in

the state of the system

Intended actions

Unintended

actions

Implemented action

Ramifying effects

Implicit,

unstated goals

Planned action to

reduce gap

Perceived gap

Goals

Perceived state
115

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

bold loop in the figure is the classic 

cybernetic loop, striving to bring the 

state of the system toward some set goal. 

However, unstated goals often intervene 

and unintended effects are triggered. The 

system changes from its own forces, and 

all sorts of effects feed back to alter the 

actions of the actors. (In a system dynamics 

perspective, there are no “side” effects, 

only effects.) Moreover, complex systems 

have many actors, each with personal or 

organizational goals, so this structure is 

repeated countless times in real systems. 

The result is that actions one group takes 

to reach toward its goals disturb the system 

and prompt other groups to implement 

counteraction, striving to reassert the 

status quo or lead to a different status quo. 

In contrast, the simpler cause-and-effect 

behavior can result when these factors 

are held constant. Thus, a system often 

will compensate for changes and weaken 

or even negate them, much as a price 

cut can stimulate competitive forces that 

negate its original goal of increasing sales. 

This phenomenon is referred to as policy 

resistance.2

In complex systems, this natural policy 

resistance can be seen as a pattern of 

dynamic behavior formed by individual 

events and decisions and a conscious effort 

to perceive in this stream of decisions 

the persistent policy structure producing 

them. System dynamics models strive to 

capture that policy structure as a part of 

system structure and produce, as output, 

graphs over time that represent this 

aggregate view of events and decisions. 

For example, the destruction of the World 

Trade Center on September 11, 2001, 

clearly was a significant event in the 

contemporary world. Without diminishing 

that significance, a systems view would 

place that event in its dynamic context, 

looking back in history to trace the slow 

accumulation of pressures that gave rise 

to the event itself and the extent of the 

nation’s capacities to deal with it.

One example of system dynamics modeling 

can be seen in a welfare reform study3 that 

was conducted in three counties in New 

York State. The study was an attempt to 

help the diverse agencies providing social 

services to the poor cope with the threat of 

persistently rising costs when some families 

would begin timing out of welfare benefits 

under reform. The mapping and modeling 

work was performed with groups of welfare 

stakeholders and social service providers in 

each county. This work eventually yielded a 

formal model of more than 600 equations 

used (1) to examine a number of “what if” 

scenarios and policy options and (2) to create 

an environment in which stakeholders could 

learn from exploring the structure and 

behavior of the complex system. 

One key finding was a classic “better before 

worse” scenario commonly seen in complex 

dynamic systems (interventions work in 

the short term; compensating feedback 

involves a delay). As more families come 

off assistance, they strain employment 

resources intended to match job seekers 

with stable jobs. This increases the number 

of marginally employed families who may 

fall back into the need for assistance. The 

result is that fewer families make it to stable 

jobs and more flow back into assistance, 

eventually increasing the population at risk 

for needing assistance.

These findings suggest the need to invest 

more resources in areas such as job 

coaching, job maintenance, child care, 

transportation, and other interventions 

intended to keep people employed. These 

areas are not the traditional purview 

of social services. They rely heavily on 

coordinated efforts of the private sector 

and nongovernmental service providers. 

These types of insights led two of the three 

counties to implement strategies to increase 

resources for these efforts. It is noteworthy 

that the welfare reforms have been a huge 

success. While the role of such modeling 

in the success has not been documented, 
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5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

this example illustrates how such modeling 

influenced at least some policy makers. The 

system dynamics approach, particularly 

when used in a group context with multiple 

stakeholders and diverse viewpoints, has 

seven characteristics:

1. Engagement. Key stakeholders are 

involved as the model evolves, and their 

own expertise and insights drive all 

aspect of the analysis. 

2. Mental models. The model-building 

process uses the language and concepts 

participants bring with them to explain 

the assumptions and causal mental 

models managers use in decision 

making.

3. Alignment. The modeling process 

benefits from diverse, sometimes 

competing, viewpoints, as stakeholders 

have a chance to wrestle with causal 

assumptions in a group context. Often 

these discussions realign thinking and 

are among the most valuable portions of 

the overall group modeling effort.

4. Determination of behavior by structure.

The formal simulation models resulting 

from this approach show how system 

structure influences system behavior. 

This leads to insights based on 

familiar system stocks and flows, and 

reveals understandable but initially 

counterintuitive tendencies such as 

policy resistance or “better before worse” 

behavior.

5. Refutability. The formal model yields 

testable propositions, enabling managers 

to determine how well their implicit 

theories match available data about 

overall system performance.

6. Empowerment. By using the formal 

model, participants can envision how 

actions under their control can change 

the future of the system.

7. Estimation of parameters. The model 

can help to estimate useful parameters 

that are not otherwise available, such as 

model factors that lack an empirical base 

of values.

System Dynamics 

Application to Tobacco 

Control

A demonstration project to illustrate the 

modeling of factors in tobacco prevalence 

and consumption by using a system 

dynamics approach was undertaken as part 

of ISIS, incorporating heuristic data from 

participants in the ISIS innovation team. 

This model was designed both as a proofof-concept project for system dynamics 

simulations of macrolevel tobacco issues 

and as a starting point for discussions on 

integration of such methods with other 

transdisciplinary aspects of a systems 

thinking environment. 

Brainstorming Components of 

Tobacco Control Systems

During initial ISIS workshops in 

Washington, DC, participants helped form 

the concepts for the model presented here 

through a group brainstorming exercise. 

Workshop participants listed ideas, one per 

sheet, and then ideas were arranged on a 

wall, as a base for facilitated discussions 

on clusters of model issues. Building on 

the insights and data gained through these 

workshops, the facilitator constructed a 

causal map and simulation model based 

on factors in tobacco prevalence and 

consumption. The primary purpose of this 

model was to use it as a learning tool to 

attempt to create a simulation environment 

in which tobacco control stakeholders can 

experiment and theorize. Although the 

model was based on heuristic input from 

ISIS participants, its concepts serve as a 

prototype for future analyses using validated 

models and accurate data sources.
117

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Grouping Components 

into Sectors

The initial data used to form this model 

were derived from discussions, exercises, 

and a series of graphs created by ISIS 

conference participants (figure 5.2). 

Participants were asked to draw rough 

sketches or graphs showing how they 

thought the brainstormed components 

evolved over the past few decades and how 

they might be projected into the future. The 

graphs from these experts were grouped 

Path to System Dynamics Approaches to Tobacco Control

The system dynamics simulation model in this chapter, examining tobacco consumption and 

prevalence, is part of a growing tradition of efforts to use systems methods for policy simulation to 

address issues in tobacco control and public health. Initial projects in this area range from a 1980s 

systems study at the Massachusetts Institute of Technology projecting an accelerated decline in 

tobacco usea to the comprehensive tobacco policy model developed at the University of California 

at Irvine,b as well as proof-of-concept work undertaken at the National Cancer Institute before the 

efforts of ISIS.c More recent efforts detailed by Levy and associatesd include the following:

n SimSmoke, funded by the Substance Abuse and Mental Health Services 

Administration’s Center for Substance Abuse Prevention and the Robert Wood 

Johnson Foundation, models smoking rates and smoking mortality over a 40-year 

period. This model bases its projections from historical data on factors such as 

smoking prevalence, consumption, initiation, cessation, and mortality, as well as 

the influence of policy factors such as laws, taxes, and tobacco control activities. 

SimSmoke’s projections range from a status quo scenario gradually reducing 

prevalence from 18.5% to 15.4% by 2040, with rising annual mortality during much of 

the period because of population trends, to proportionately lower prevalence based on 

the impact of specific policy interventions.

n A system model funded by the Substance Abuse Policy Research Program of the Robert 

Wood Johnson Foundation used age-specific rates for initiation and cessation of 

smoking. It demonstrated that smoking prevalence will continue to fall under current 

trends. However, it also established the implausibility of the goals for prevalence set 

for the Healthy People 2010 initiative.

n GlaxoSmithKline sponsored a dynamic model for smoking control designed to project 

demand for its products for nicotine replacement therapy. The model focuses on the 

decision to stop smoking based on the “stages of change” model and uses empirical 

data about population demographics and behavior involved in quitting smoking. Its 

findings include the observation that lowering barriers to aids for smoking cessation, 

such as nicotine replacement therapy, increased cessation rates.

a

Roberts, E. B., J. Homer, A. Kasabian, and M. Varrell. 1982. A systems view of the smoking problem: 

Perspective and limitations of the role of science in decision-making. International Journal of Biomedical 

Computing 13 (1): 69–86.

b

Tengs, T. O., N. D. Osgood, and L. L. Chen. 2001. The cost-effectiveness of intensive national school-based 

anti-tobacco education: Results from the tobacco policy model. Preventive Medicine 33 (6): 558–70.

c

Leischow, S. 2003. Social network analysis in tobacco control. Presentation at the National Cancer Institute, 

Bethesda, MD.

d

Levy, D. T., F. Chaloupka, J. Gitchell, D. Mendez, and K. E. Warner. 2002. The use of simulation models 

for the surveillance, justification and understanding of tobacco control policies. Health Care Management 

Science 5 (2): 113–20. 
118

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

into substantive sectors to create a series of 

composite pictures, collapse the issues to a 

more manageable size, and provide useful 

talking points as the team progressed to 

modeling. Examples of sectors resulting 

from this exercise included the following:

Tobacco use. The sector on tobacco use 

examined the relationship between people 

and tobacco—whether they smoke and rates 

for starting, stopping, or resuming tobacco 

use. For this sector, participant graphs were 

supplemented with compiled data showing 

the fractions of the U.S. population who 

were current or former smokers or who 

never smoked during 1965–2000.4 Some 

of the original hand-drawn graphs were 

generated by the experts for the sector 

on tobacco use. As part of the exercise, 

participants drew a graph to show changes 

for each key variable over time. Dotted or 

shaded lines represent alternative future 

scenarios.

Tobacco industry. The sector on the tobacco 

industry examined the influence and 

lobbying efforts of the industry, combining 

participant graphs of these factors with data 

from the Economic Research Service of the 

U.S. Department of Agriculture showing 

variations in the tobacco supply from 1950 

through 2000. 

Tobacco control and government 

intervention. The sector on tobacco control 

and government intervention examined 

trends in tobacco control efforts over time. 

These included the measure for strength 

of tobacco control that was developed 

to measure state-level tobacco control 

resources, capacity, and efforts, as well 

as factors such as resources and funding, 

regulation of tobacco by the U.S. Food and 

Drug Administration, and percentage of 

restaurants with a smoking ban in place 

over time.5 The data compiled from these 

ISIS participants, supplemented with 

historical data on tobacco-related factors 

from official sources, contained many 

observed trends, such as a clear plateau 

in the historical decline in tobacco use, 

increasing near-term tobacco sales, and a 

rise and fall of tobacco control efforts over 

time, tied to recent decreases in funding for 

tobacco control.

Developing a Causal Model

A causal map typically consists of the 

following elements:

n Stocks are accumulated or integrated 

quantities with values or levels (e.g., 

number or proportion) that do not 

change instantaneously. Stocks 

accumulate in response to flows. Stocks 

are the written words on a causal 

map (e.g., tobacco revenues or people 

smoking), and stocks that are central to 

Figure 5.2 Sample of Graphs on Tobacco Use Factors from Expert Participants at 2003 

Conference on ISIS

Note. These images were hand-drafted by participants in the exercise.
119

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

specific causal loops are highlighted in 

boxes.

n Flows are varying quantities that create 

the dynamics in the system by increasing 

or decreasing stocks. Flows (e.g., 

production of tax revenues by smokers) 

are represented by the arrows on a map.

n Loops are linked, directional relationships between model parameters.

n Delays are built-in characteristics of any 

system, providing more realistic linkages 

of cause and effect that may be difficult 

to observe. For example, it takes time to 

introduce new legislation or develop a 

new marketing campaign. A delay can be 

seen as a property of a stock.

These brainstormed components, organized 

by sector, formed the basis for construction 

by the project facilitator of an overall causal 

loop model of factors in tobacco prevalence 

and consumption, as a precursor to the 

development of a formal system dynamics 

model. A causal loop model (presented later 

in this chapter) was built step-by-step as 

outlined in this section.

Causal loop diagrams are an integral part 

of system dynamics modeling, helping to 

foster group knowledge and understanding 

and providing a concise view of an 

enormous amount of complexity and a 

starting point for simulation. In ISIS, 

such diagrams act as a bridge, drawing 

information from participants and data 

sources, and resulting in a “map” that helps 

stakeholders define and, more important, 

discuss the fundamental hypotheses 

and connections leading to more formal 

modeling. (The final causal map shown later 

in this chapter was developed heuristically 

and is meant to be illustrative rather than 

authoritative.) 

One group of participants created the 

causal map and used the brainstormed 

components organized by sector and the 

graphs of functions over time to draft the 

initial flow diagram. To better explain 

development of the overall causal model, 

the model is examined a section at a time 

and the logic is described. The final causal 

loop model shown later in this chapter 

presents the full map, and figure 5.3 shows 

the segment examining social norm and 

tobacco growing issues. 

In the diagram, “smokers” represent the 

pool of people who smoke. As the number 

of smokers increases, the revenue generated 

Figure 5.3 Causal Map Segment, Incorporating Social Norm and Tobacco Grower Factors

Smokers

Tobacco marketing

activities

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

+

+ +

+

+

+

+

Tobacco products

availability

+

Tobacco

growers

+

+
120

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

by their purchase of tobacco products also 

increases, which is indicated by the plus sign 

next to the line that connects “smokers” 

and “tobacco revenues.” This increase has 

two effects: it enables the tobacco industry 

to increase tobacco production (tobacco 

growers) to meet the demand of increased 

smoking, and it generates more money for 

“tobacco marketing activities.”

Following the inside loop, the increase 

in “tobacco marketing activities” creates 

greater acceptance of smoking and tobacco 

use. Marketing activities tend to normalize 

smoking as a behavior rather than simply 

capture more market share. Marketing, for 

the tobacco industry, is a source of new 

smokers. Following the outside causal 

loop, as the capacity for tobacco production 

increases, there is an increased availability 

(e.g., discounted cost) of tobacco products. 

The establishment of “smoking as a social 

norm,” complemented by the increased 

availability of tobacco products, results in an 

increase in the number of “people starting 

to smoke,” and consequently, an increase in 

the “fraction of people smoking.”

If this initial model segment is expanded 

to a slightly larger segment (figure 5.4), 

it becomes apparent that research on the 

health effects of smoking leads to growing 

awareness of health risks from tobacco 

use, which eventually disseminates to the 

general public and helps build pressures 

and motivations for people to stop smoking. 

As the “fraction of people smoking” 

increases, the “researchers’ awareness 

of tobacco as a health risk” becomes 

clearer. This increased awareness prompts 

researchers to formulate new questions and 

apply for “funding for research on tobacco 

as a health risk.” Their work eventually 

finds its way to “public awareness of 

tobacco as a health risk.” Reports on the 

negative effects of smoking and exposure to 

secondhand smoke filter from research to 

a broader awareness. As individuals process 

this information, they choose to stop 

smoking in greater numbers.

Figure 5.4 Expanded Causal Map Segment, Incorporating Awareness of Tobacco Health Risk

Smokers Public awareness

of tobacco

health risk

Tobacco marketing

activities

People quitting

smoking

–

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

+

+ +

+

+

+

+

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

+ research

+ +

–

+

Tobacco products

availability

+

Tobacco

growers

+

+

Trend in tobacco

company revenues

+

–

–
121

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

The new causal path captures the idea that 

the “trend in tobacco company revenues” 

is a decrease because as the number of 

smokers decreased, tobacco companies 

would increase spending on “tobacco 

marketing activities.” The minus sign 

next to the line between “trend in tobacco 

company revenues” and “tobacco marketing 

activities” depicts the negative relationship 

that as tobacco revenues decrease,

marketing is increased. By an increase in 

marketing, tobacco companies would try to 

compensate for the successes of the research 

community in prompting people to try to 

stop smoking.

“Antitobacco constituencies” represent 

those who advocate against support for 

the tobacco industry. As both “researchers’ 

awareness” and “public awareness of 

tobacco as a health risk” increase, the 

number of people and organizations 

opposing tobacco use tends to grow. 

The map expanded as shown in figure 

5.5 suggests that these antitobacco 

constituencies can move more funding to 

tobacco research and control, leading to 

further growth (1) in awareness of tobacco 

as a health risk and (2) in efforts to control 

or reverse the growth of tobacco production 

and use.

The outside loop highlights some of the 

effects of tobacco control programs. As 

“funding for tobacco control programs” 

increases, “pressure on tobacco companies 

to reduce marketing activities” increases 

(e.g., via legislated bans on certain forms of 

advertising). This pressure is an additional 

factor but only one of many that determine 

levels of tobacco company marketing.

A segment on government awareness of 

tobacco as a health risk is added in figure 

5.6. The government draws from three 

sources of information to understand 

the risk posed by tobacco use. First, 

government depends on “researchers’ 

awareness of tobacco as a health risk” to 

provide information on the health risks 

of tobacco. Second, government relies on 

“public awareness of tobacco as a health 

risk” to gain a better understanding of the 

degree to which tobacco use is an issue 

among its constituents. The higher the 

public awareness of tobacco risks, the 

Figure 5.5 Causal Map Adding Impact of Antitobacco Constituencies

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

+

+

+

–

–

+

+ +

+

+

+

+

+

+

–

+

+

+

+

+

+

+

–

–

+

+

+

+
122

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

more motivated people are to pressure 

their legislators to act. Finally, government 

experiences a direct feedback loop in the 

“health care costs” associated with tobacco 

use. As the number of smokers increases, 

the health care costs associated with 

smoking also increase. The government 

directly bears many of these costs through 

Medicare. However, such costs also are 

indirectly affected by the public debate over 

the general cost of health insurance.

The influence of protobacco constituencies 

is added in figure 5.7. Protobacco 

constituencies represent those who 

advocate in favor of tobacco products 

and their increased availability. Tobacco 

companies, smokers, and those who 

Figure 5.6 Causal Map Adding Government Awareness of Tobacco as a Health Risk

+

+

+

–

–

+

+ +

+

+

+

+

+

+

–

+

+

+

+

+

+

+

–

–

+

+

+

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

Health care costs

Government

awareness of tobacco

health risk

+

+ + +

+

Figure 5.7 Causal Map Adding Impact of Protobacco Constituencies

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

Health care costs

Government

awareness of tobacco

health risk

Protobacco

constituencies

+

+

+

–

–

+

+ +

+

+

+

+

+

+

–

+

+

+

+

+

+

+

–

–

+

+

+

+ + + +

+

+ + + +

+
123

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

accept smoking as a social norm generate 

the ability to provoke action against 

tobacco control measures. From a social 

and psychological perspective, smokers 

play an important role in the protobacco 

constituency, because they often are 

interested in ease of availability and few 

limitations on smoking behavior.

Tobacco revenues create an obvious 

incentive for people to protect tobacco. 

Shareholders in tobacco companies desire 

increased revenue, and companies have 

a vested interest in the success of their 

product. Consequently, the tobacco industry 

takes steps to protect their investment. 

The willingness of government to take 

actions against tobacco interests depends 

on the balance of forces created by the 

protobacco and antitobacco constituencies 

and the government’s perceptions of health 

risks associated with tobacco use. Segments 

showing the forces influencing willingness 

to legislate are added in figure 5.8. Increased 

taxes on tobacco are an early result of this 

growing government willingness to act 

against tobacco interests. The impacts of 

taxes on individual motivation to start or 

stop smoking create a number of feedback 

loops in the system, counteracting the 

growth of the population of smokers and 

contributing to its eventual decline.

Some effects of government legislation to 

control tobacco use are added to the model 

in figure 5.9. For example, as government 

receives more money from tobacco taxes, 

it is more willing to increase that revenue 

stream. However, this loop also works in 

reverse. As government revenues from 

tobacco taxes decrease, the government 

may actually become less willing to act 

against tobacco interests because it would be 

threatening its own revenue stream.

Tobacco tax revenue is dependent on the 

taxes associated with tobacco use, as well 

as the number of people who smoke (figure 

5.9). As either increases, one would expect 

Figure 5.8 Causal Map Adding Impact of Greater Willingness to Legislate Tobacco Control

+

+

+

–

–

+

+ +

+

+

+

+

+

+

–

+

+

+

+

+

+

+

–

–

+

+

+

+ + + +

+

+

– + +

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

Health care costs

Government

awareness of tobacco

health risk

Protobacco

constituencies

Health insurers’

coverage of tobacco

quitting costs

Government willingness

to legislate tobacco

control

Tobacco

taxes

+

+

+

+ + + +

+

–
124

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

that tax revenue would also increase. 

These increased revenue streams increase 

government income. The model suggests 

that more money moving into the system 

from tobacco taxes results in increased 

funding of both basic research and tobacco 

control.

Finally, government willingness to legislate 

tobacco control ultimately leads to 

policy interventions such as antismoking 

legislation, which in turn has effects on the 

marketing of tobacco products and their 

availability. Both of these factors are affected 

directly by legislative restrictions, as well 

as by side effects such as counterefforts by 

the tobacco industry. Adding the impact of 

these factors leads to the final causal map 

(figure 5.10) drafted for this pilot project.

The building of this map, as outlined in 

figures 5.3 through 5.10, was based on 

participant identification of components, 

grouping of these components into sectors, 

and descriptions of the dynamic patterns of 

the variables over time. The facilitator used 

this information to construct the causal 

map and provided it to the participant group 

for feedback and potential revision. The 

causal map would doubtless benefit from 

input from a broader range of stakeholders, 

such as tobacco growers. This would likely 

add additional stocks and flows and open 

some current model elements to debate. 

The causal map, in turn, was used to inform 

the development of segments of the formal 

system dynamics model discussed in the 

next section.

The tobacco system articulated by this 

causal map is but a system within a larger 

system. For example, there have always been 

competing public health priorities, most 

recently exemplified by the focus on obesity. 

In many ways, playing tobacco against obesity 

competitively is a zero-sum game. With finite 

Figure 5.9 Causal Map Adding Impact of Government Tax Revenues and Funding for Tobacco 

Control

+

+

–

–

+

+ +

+

+

+

+

+

+

–

+

+

+

+

+

+

+

–

–

+

+

+

+ + + +

+

+

– + + +

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

Health care costs

Government

awareness of tobacco

health risk

Protobacco

constituencies

Health insurers’

coverage of tobacco

quitting costs

Government willingness

to legislate tobacco

control

Tobacco

taxes

Government

income from

tobacco taxes

Tax

revenues

from

smokers

Government funding

of tobacco control

+

+

–

+

+

+

+

+

+

+ +

+ + +

+
125

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

resources, the public health community must 

set priorities. If the importance of obesity 

as a health risk increases relative to that of 

tobacco use, the government’s willingness to 

act and the direction of funding for tobacco 

control and research may be affected. Issues 

such as these point to the importance of 

continuing the use of system dynamics 

models and the evolution of these models 

from original assumptions based on changes 

in the environment.

Developing System Dynamics 

Models

How does a system dynamics modeler move 

from hand-drawn graphs, empirical data, 

and the causal map to a formal system 

dynamics model? This section presents 

selected model segments that were used 

in a larger formal simulation of factors in 

tobacco use over time.

Compared with the earlier causal maps 

showing relationships among model 

factors, these “shards” of system dynamics 

models form the detailed basis for the 

estimated parameters used for simulation. 

They constitute the basic structure of 

the formal model, showing how causal 

elements discussed here were translated 

into a simulation. However, there is not 

a one-to-one correspondence between 

segments of the causal map described 

previously and these model shards. For the 

purposes of this demonstration project, 

the simulation model was informed by 

the overall content of the causal map, 

and adaptations were made according to 

the judgment of the analyst and feedback 

from participants. Only some of the 

Figure 5.10 Final Causal Map of System Dynamics Model for Tobacco Control in the Initiative 

on the Study and Implementation of Systems

+

+

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–

+

+ +

+

+

+

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+

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–

+

+

+

+

+

+

+

–

–

+

+

+

+ + + +

+

+

– + + +

– –

Funding for tobacco

control programs

Tobacco control

programs

Smokers Public awareness

of tobacco

health risk

Pressure on tobacco

companies to reduce

marketing activities

Tobacco marketing

activities

People quitting

smoking

Fraction of people

smoking

Smoking as a

social norm

People starting

smoking

Tobacco

revenues

Researchers’

awareness of tobacco

health risk

Funding for

tobacco health

research

Antitobacco

constituencies

Tobacco products

Tobacco availability

growers

Trend in tobacco

company revenues

Health care costs

Government

awareness of tobacco

health risk

Protobacco

constituencies

Health insurers’

coverage of tobacco

quitting costs

Government willingness

to legislate tobacco

control

Tobacco

taxes

Government

income from

tobacco taxes

Tax

revenues

from

smokers

Government funding

of tobacco control

Perceived importance to

focus on other health

programs

Antismoking

legislation

–

–

–

+

+

+

+

+ +

+ +

+

+

+

+ + + +

Note. An earlier version of this figure was published as Figure 1 in A. Best et al. 2006. Systemic transformational change in 

tobacco control: An overview of the Initiative for the Study and Implementation of Systems (ISIS). In Innovations in health care: 

A reality check, ed. A. L. Casebeer, A. Harrison, and A. L. Mark, 189–205. New York: Palgrave Macmillan. Reproduced with 

permission of Palgrave Macmillan. 
126

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

formal model shards are described here 

to illustrate how this part of the modeling 

process works in the context of this 

example. (The figures shown for these 

shards are taken from program output 

from the VENSIM software used for this 

simulation.)

Public Opinion Sector

The model shown in figure 5.11 relates to 

the “smoking as a social norm” portion 

of the causal maps shown in figures 

5.3–5.10. That segment of the maps was 

translated into part of the simulation 

model by building a closed set of stocks, 

linked by inflows and outflows in which it 

is assumed that opinion moves through 

this closed chain in response to pressure. 

For example, every year, some fraction 

of the undecided population moves from 

the undecided stock to public support of 

tobacco use or public support of control of 

tobacco use.

Tobacco Use Sector

Figure 5.12 depicts several “aging chains” 

used in the formal model to track the 

inflows and outflows of current and former 

smokers and people who never smoked, 

from birth to death. Formulation in this 

manner is consistent with historical 

monitoring of tobacco use and enables 

substantial comparison. If it is assumed that 

all people are born nonsmokers, one of five 

behavior scenarios takes place:

1. Youths start to smoke tobacco products 

or age into adulthood as nonsmokers. 

2. Adult nonsmokers start to smoke or 

continue as nonsmokers until they die.

3. Youths who smoke stop smoking, 

becoming former youth smokers, age 

into adulthood as former smokers, or 

resume smoking after stopping.

4. Youths who age into adulthood as 

smokers die as smokers or stop smoking 

and become former adult smokers.

5. Former adult smokers resume smoking 

or remain former smokers.

Proximate drivers of flows are built into 

the formal model in figure 5.12. As shown 

earlier in this chapter, the state of current 

opinion affects the rates at which adults 

and youths begin and stop tobacco use. 

For example, as public opinion builds 

in support of tobacco control, rates of 

initiation of smoking decline. As public 

opinion builds in support of tobacco use, 

rates of initiation increase.

Figure 5.11 Model of Public Opinion Factors

Public Supporters of

Tobacco Control

Public Supporters

of Tobacco Public Undecided

Public support to

Undecided Undecided to

Dissenting

Dissenting to

Undecided

Undecided to

Supporting

Fraction of antitobacco

becoming undecided

per year

Fraction of undecided

becoming protobacco

per year

Fraction of undecided becoming

procontrol per year

Fraction of protobacco

becoming undecided per year
127

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Research and Dissemination Sector

The simulation model in figure 5.13 

illustrates research and dissemination 

(education) factors. These factors play an 

important role in influencing public health 

awareness, as described in figure 5.5. This 

model assumes there are x numbers of 

researchers performing research on tobacco 

use and control who create initial research 

(e.g., published in peer-reviewed journals) 

or translate initial research into information 

Figure 5.12 Model of Aging Chains of Smokers (Birth to Death)

Youth

nonsmokers

Adult

nonsmokers

Youth

smokers Adult

smokers

Youth former

smokers

Aging 1 Adult never

smokers dying

Youth smoking

starts Adult smoking

starts

Youth quits Youth former

smokers smoking Adult quits

Time to age 1 Nonsmoking adult

life span

Norm youth uptake Norm adult uptake

Norm youth quit

rate

Norm adult

quit rate

Youth returning to

smoking

Adult returning to

smoking

Adult former

smokers smoking

Youth smokers

aging

Former youth

smokers aging

Former adult

smokers dying

Smoking adult

life span

Adult smokers

dying

Norm former adult

smoker life span

Time to age 2

Time to age 3

Effect of public opinion

on adult quit rate

Effect of public opinion

on adult uptake

Effect of public opinion

on youth uptake

Effect of public opinion

on youth quit rate

<Total adults>

New youth

Norm birth rate

Adult former

smokers

Note. Years are the unit of age.

Figure 5.13 Model of Research and Dissemination Factors

Research

Findings

Translated

Research

New translated

research

Translated research

aging out

New research Research aging out

Effect of available research

on publishing productivity Time for translated

research to age out

Time for published

New research per research to age out

researcher

Researchers

working on tobacco

research

Norm new

researchers

Researchers moving

to different projects

New tobacco

researchers

Time to adjust

research priorities Indicated fraction

working on publication

Fraction

working on

publication

Time to adjust

researcher fraction

Researchers publishing

initial research

Researchers publishing

more broadly

Research findings

in 1975

Translated research per

researcher 1975

Translated research per

author per year

Effect of public support on

new tobacco researchers Norm publication

fraction Effect of public support

on research fraction
128

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

Playing “What If” Games with Smoking Prevalence

If the number of children who start smoking were suddenly cut in half, how would it affect the 

number of smokers 40 years from now? As part of the ISIS system dynamics model described in 

this section, a simulation was performed by using the model for the aging chain of smokers (birth 

to death) that shows the impact of rates for smoking initiation and cessation at specific ages on 

the prevalence of tobacco use. This model was then used to test the effect of dramatic changes in 

these initiation rates, in different age groups, on prevalence over a 40-year period.

The simulation results show that cutting smoking initiation in children under age 12 years in half 

had minimal impact downstream. However, similar decreases in adolescent (ages 12–20 years) 

and adult smoking initiation produced much greater declines. Factors behind these results 

ranged from the relatively small number of child smokers to the cascading effects of each group 

on subsequent rates for smoking initiation and cessation.

Effect of 50% Declines in Child, Adolescent, and Adult Smoking Initiation in Longitudinal 

Studies of Smoking Prevalence

Childhood initiation

40

37.5

35

32.5

30

1980 1990 2000 2010 2020

Time (year)

Cut childhood smoking initiation in half

Smoking chain base

Adult smokers (millions)

Teen initiation

40

35

30

25

20

1980 1990 2000 2010 2020

Time (year)

Cut teen smoking initiation in half

Cut childhood smoking initiation in half

Smoking chain base

Adult smokers (millions)
129

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

available for dissemination to the public 

(e.g., tobacco fact sheets available for 

download on many public health Web sites 

or television news pieces on recent tobaccorelated health warnings).

Several effects of public opinion are built 

into this model. The model assumes that the 

rising tide of public support may increase the 

demand for researchers engaged in tobaccorelated projects and, likewise, increase the 

demand for materials on awareness of risk 

for dissemination to the public.

Not all of the causal map has been 

explicitly included in the model. 

Sometimes factors in the causal map are 

handled differently in formal modeling. 

This was the case for factors related 

to the tobacco industry. Instead of 

separately modeling the influence of 

these factors, this model considers the 

rate at which research translated for 

dissemination reaches the population as a 

net gain, after subtracting for an effect of 

counterresearch and propaganda from the 

tobacco industry.

Adult initiation

40

35

30

25

20

1980 1990 2000 2010 2020

Time (year)

Cut adult smoking initiation in half

Cut teen smoking initiation in half

Cut childhood smoking initiation in half

Smoking chain base

Adult smokers (millions)

Perhaps an even more important outcome from this simulation was the reaction of other tobacco 

control stakeholders, many of whom felt that this simulation would not necessarily reflect longterm outcomes in real life. Some people, particularly those involved with tobacco use issues 

among young people, thought that a sharp decline in youth smoking could become a powerful 

agent in other factors. These include social and culture change, which could in turn create 

conditions for much greater reduction in prevalence.

Although this simulation was designed only as a proof of concept project with limited data, it 

brought two important points to life for ISIS participants: that system dynamics models often 

can reveal unexpected outcomes and that the results depend strongly on the assumptions behind 

the model. These factors highlight a key limitation in system dynamics modeling, which is that 

the modeling cannot easily be validated. When surprising results occur, it is not clear whether 

they have arisen from one or more unwarranted assumptions. The second key limitation is the 

great difficulty in parameterizing system dynamics models. These limitations reinforce the point 

that system dynamics models are aids to thinking about complex issues, not tools for delivering 

“truth.”
130

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

Government Sector

Figure 5.14 examines government 

intervention. The hypothesis is that 

government intervention grows in response 

to public support for tobacco control. This 

segment of the formal model illustrates 

the idea of a delay, labeled “time to change 

government intervention.” This is interpreted 

as the time it takes to create new legislation 

or repeal existing legislation, as the support 

for tobacco control rises and falls.

Public Opinion Revisited

With the assumption of basic understanding of the tobacco use, research and 

dissemination, and government sectors, 

figure 5.15 shows the effects of the public 

opinion sector on tobacco control. 

Changes in public opinion are influenced 

by the number of smokers and nonsmokers 

in a population. This hypothesis is based on 

the assumption that, for example, a firmly 

established social norm in favor of smoking 

tends to produce more smokers, who tend to 

support the existence of the social norm.

Translated research will tend to “push” 

public opinion toward control of tobacco 

use, because the assumption is that a more 

informed population chooses reduction of 

tobacco use. The model indicates a weak 

“backlash” effect in response to increasing 

government intervention. This is based 

on the presumption that government 

constraints on personal behavior may draw 

some opinion away from support.

These segments of simulation models 

illustrate how causal maps and other factors 

such as experience and expertise in subject 

matter are translated into more formal 

simulations. Such simulations enable 

researchers and practitioners to change 

different parameters in efforts to explore the 

likely effects of these changes throughout 

the dynamic system. Based on those trials 

and how appropriate the results appear, the 

simulation itself might be revised. In this 

manner, the act of simulation constitutes 

Figure 5.14 Model of Government Sector

Government intervention

in tobacco sales and

Change in government production

intervention

Time to change government

intervention

Indicated

intervention

Effect of public support on

government intervention

Government

intervention in 1975
131

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

a type of dynamic laboratory for trial-anderror efforts to better anticipate the effects 

of different conditions. 

Validating Simulation of System 

Dynamics Models 

Simulation of system dynamics models 

means allocating numbers to the “stocks” 

in the model and activating the “flows” 

so that changes in behavior over time are 

simulated. An example of the behavior of 

the model is presented here through text 

description and graphical representation. 

This section highlights causal loops to 

provide supplementary explanations for 

important model dynamics and shows how 

simulation models are set against real-world 

data in an ongoing process of revising and 

validating the models.

The results in the initial simulation model 

are compared with outcome data in figure 

5.16. Data from the Centers for Disease 

Control and Prevention,6 represented by the 

short lines in the model, are compared with 

the simulation projections, represented by 

the long lines. The test model fits existing 

data well over time. However, the simulation 

model has the advantage of allowing 

projections into the future, represented by 

the extension of the long line over the 

short line. 

System dynamics modeling does not 

simply assume that projections into the 

future are accurate or valid because of a 

correspondence of simulation estimates with 

historical data. A multitude of simulation 

models might correspond just as closely 

with historical estimates. Modeling is done 

primarily for its probative value, as a tool for 

exploring possible effects, but modeling of 

this type can be a basis for more confident 

projections. For instance, multiple models 

that predict similar longer term outcomes, 

all making differing assumptions, form 

a stronger basis for validity than any one 

model alone would.

Figure 5.15 Expanded Model of Public Opinion Factors

Public Supporters of

Tobacco Control Public Supporters

of Tobacco Public Undecided

Public support to

Undecided Undecided to

Dissenting

Dissenting to

Undecided

Undecided to

Supporting

Fraction undecided to

procontrol in 1965

Fraction of antitobacco

becoming undecided per year

Fraction of undecided

becoming protobacco per year

Effect of translated

research on undecided

public

Fraction of undecided become

procontrol per year

Effect of translated

research on protobacco

public

Fraction of protobacco

becoming undecided per year

Fraction of protobacco to

undecided in 1965

Effect of government

intervention on

procontrol

Fraction procontrol to

undecided in 1965

Effect of government

intervention on

undecided

Fraction undecided to

protobacco in 1965

Effect of nonsmokers

on undecided public

Effect of nonsmokers on

protobacco public

Effect of smokers on

procontrol public Effect of smokers on

undecided public
132

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

The historical data progressively diverge 

from the simulation data during 1990–2000 

(figure 5.16, graph on right). This finding 

suggests that important parameters 

influencing more recent projections were 

either not included or were not properly 

weighted in the simulation. This finding 

might be used to start a series of trial-anderror revisions to the simulation model 

to explore possible reasons for such a 

discrepancy.

Estimating Parameters

An additional advantage of the model is that 

it allows exploration of sectors for which no 

data exist. Modelers use intuition to decide 

whether the model “makes sense.” For 

example, the stocks for public opinion are 

visible in figure 5.17. The initial parameters 

for the public opinion stocks are a function 

of the smoking rates in a population. For 

example, those who smoke are assumed to 

be proponents of tobacco use. Those who 

have used tobacco and stopped smoking are 

assumed to be supporters of tobacco control. 

These assumptions are open to challenge, 

but they are useful for illustrative and 

probative purposes.

Support for tobacco control has been 

increasing, although not necessarily at a 

predictable or constant rate. In this model, 

the reason public support fails to establish a 

linear positive trajectory at its end point is 

Figure 5.17 Stock Values for Public Opinion over Time (Baseline)

120

90

60

30

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

Public supporters of tobacco

Public undecided

Public supporters of tobacco control

Population (millions)

Figure 5.16 Model Data Versus Actual Data on Population Fractions of Current and 

Former Smokers

Base

Reference mode

Former smokers

30

20

10

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

40

% of population

Smokers

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

% of population

Note. Model data are indicated by the long line. Actual data are indicated by the short line.
133

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

based on several important feedback loops, 

shown in figure 5.18.

Because the model begins in 1965 with a 

substantial number of current smokers, 

the size of the smoking population allows 

support of tobacco use to continue to grow 

for several years. It is bolstered slightly by the 

effect of government intervention in the wake 

of the 1964 Report of the Advisory Committee 

of the Surgeon General on smoking and 

health.7 Until regulations on tobacco product 

warnings became institutionalized by the 

Federal Cigarette Labeling and Advertising 

Act in 1965,8 the government warning about 

tobacco use as a health risk had an effect 

opposite to that intended on the tobaccousing population.9

 This result was in keeping 

with the modeling assumptions discussed 

earlier on the effects of this intervention on 

public opinion (figure 5.19).

Momentum to control tobacco use builds 

slowly, as rates of the decline in smoking and 

public interest in intervention and research 

grow. Eventually, the stock of support for 

control overtakes the stock of tobacco use.

Simulation Results

Examination of the effects of changing 

various model parameters and their effects 

can lead to a better understanding of the 

system. These effects are grouped by model 

sectors. For each grouping, the most 

relevant scenarios are discussed, although 

they represent only a small fraction of all 

possible scenarios.

Tobacco Use Sector

An informative initial test is to evaluate the 

following proposition: the effect of public 

support for tobacco control on tobacco use 

has been underestimated. The blue baseline 

in figure 5.20 represents the original effect 

of public opinion on the adult rate of 

starting to smoke. The x axis indicates the 

input, that is, the level of public support 

for tobacco control. The y axis indicates the 

impact of this support on the current adult 

rate for smoking initiation. The shape of the 

blue baseline changes with changes in the 

Figure 5.18 Feedback Loops Affecting Public Opinion

Public support of

tobacco use

Rate of tobacco

use

Public support of

tobacco control

Effect of translated

research

Effect of government

intervention

Figure 5.19 Feedback Loops with Change in Feedback Levels

Public support of

tobacco use

Rate of tobacco

use

Public support of

tobacco control

Effect of translated

research

Effect of government

intervention
134

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

parameter of public opinion. The graph of 

new data shown by the green line suggests 

that a change in public opinion yields a 

much greater change in the rate of smoking 

initiation among adults.

The largest impact of the change is indicated 

in the graphs for adult smokers, because 

the rate of smoking initiation declines 

much more quickly than in the baseline 

simulation, which consequently reduces the 

number of former smokers. The number of 

supporters of tobacco control also is slightly 

higher, but this effect moderates quickly.

The effect of public opinion on the rate 

for smoking cessation among adults also 

may be different from that at baseline. The 

original base assumption and an altered 

assumption are both expressed in figure 

5.21. The altered assumption suggests that 

public opinion has a more significant impact 

on smoking cessation than the original 

assumption. 

When the effect of public opinion is 

amplified, predictably, fewer people are 

smoking, and a much higher percentage of 

people have stopped using tobacco. After 

1995, the percentage of people who never 

smoked also is significantly higher. As 

shown in the causal loops in figure 5.22, this 

increase is due to the feedback effect of public 

opinion on the rate of smoking initiation.

Change in the smoking cessation rate directly 

affects the numbers of smokers and former 

smokers. This model shows that the growing 

Figure 5.20 Effect of Public Opinion on Adult Uptake

Base

Reference mode

Adjusted uptake effect

Public supporters of tobacco control

150

100

50

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

200

Population (millions)

Adult smokers

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Population (millions)

300

200

100

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

400

Population (millions)

Adult smoking starts

3

2

1

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

4

Population (millions) 0.75

0.5

0.25

0

0 5 10

1

Number of articles

Public opinion

Adult nonsmokers
135

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

contingent of nonsmokers also has an effect 

on the number of adults who never smoked 

(figure 5.22). As public opinion grows, 

the rate at which adults initiate smoking 

declines. In this way, the model captures 

what might be hypothesized as an elusive 

shifting of the social norm regarding tobacco 

use. These effects have only begun to become 

visible during the more recent decades. 

Should the model capture the dynamics of 

the system accurately, it can provide useful 

details about its behavior in coming years.

Research and Dissemination 

Sector

Additional tests can be designed to explore 

the dynamic effects of public opinion in 

the research and dissemination sector. For 

example, figure 5.23 shows the results of 

simulation of the effect that public support 

for tobacco control has on altering the 

research fraction. This is the proportion 

of researchers conducting basic research 

versus the proportion translating research 

into information that can be disseminated 

to the public. Based on the assumptions of 

the model, the greater the public support 

for tobacco control is, the more emphasis 

is placed on funding basic research (figure 

5.23, top). Paradoxically, more public support 

may mean less translational research. The 

amount of funds for all research (basic plus 

translational) is growing because of public 

support. However, it does not grow as rapidly 

as the proportion for basic research that 

appears to be responsive to the public. The 

Figure 5.21 Effect of Public Opinion on Rate of Smoking Cessation among Adults

Base

Reference mode

Adjusted quit effect

Smokers

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Population (%)

70

60

50

40

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

80

Population (%)

Former smokers

30

20

10

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

40

Population (%)

Never smokers

7.5

5

2.5

0

0 5 10

10

Adult quit rates

Public opinion
136

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

model suggests that the effect of public 

support is weaker than it was at baseline 

(figure 5.23, graph at lower left). Despite the 

shift to more initial research, the simulation 

shows that the amount of translated research 

does not decline as much as might be 

expected (figure 5.23, graph at lower right). 

A compensating loop in this model 

addresses the publishing productivity of 

those who translate research. With more 

public support for tobacco control, the 

research fraction is altered to favor more 

basic research, a higher volume of such 

research is accumulated, and consequently, 

the publishing productivity of researchers 

working on translational research is affected 

negatively (figure 5.24). The change in 

translated research is significant enough to 

alter the stock of tobacco use (figure 5.25). 

Figure 5.22 Causal Loops for Public Opinion and Support of Tobacco Control

Public support of

tobacco control

Adults who have

never smoked

Rate at which adults

pick up smoking

Effect of public opinion

on the uptake rate

Effect of public opinion

on the quit rate

Adults who smoke

Rate at which

adults quit

Figure 5.23 Effect of Public Support for Tobacco Control on Research Fraction

Base

Reference mode

Adjusted research effect

Translated research

1,500

1,000

500

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

2,000

Number of articles

Research findings

450

300

150

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

600

Number of findings

4.5

3

1.5

0

0 5 10

6

Research fraction

Public support
137

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

However, the effect moderates toward the 

end of the simulation, and one suspects that 

this effect would disappear over time. 

Public Opinion Sector

Previously, a test was performed to determine 

how significantly public opinion affects the 

amount of research being performed. For the 

next test here, this assumption is reversed 

and the impact of relevant and timely 

research on public opinion is explored. As 

has been mentioned during ISIS workshops, 

providing such data to the general public is a 

vital component of a tobacco control policy.

A simple test explores the sensitivity of 

translated research by changing the time it 

takes to “age out” of the public’s awareness. 

The baseline assumption is that the public’s 

memory of awareness about tobacco use as 

a health risk is fairly long; the time until 

the research ages out is set at 25 years. The 

results of changing that parameter to 15 years 

are shown in the graphs in figure 5.26.

Because translated research flows through 

this stock more quickly and thus remains 

in the public’s mind for a shorter period, 

less of it accumulates. Less accumulation 

of research directly and negatively affects 

Figure 5.24 Causal Map for Research and Public Support for Tobacco Control

Fraction of researchers

working on initial research

Initial

Research

Research

Translated

Research translated

per researcher Effect of research volume

on publishing productivity

Public Support

for Tobacco

Control

Figure 5.25 Effect of Research on Tobacco Use

Base

Reference mode

Adjusted research effect

Smokers

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Population (%)

Adult smokers

50

40

30

20

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Smokers (millions)
138

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

the shifting social norm, and a higher stock 

of current smokers results. The life span of 

relevant tobacco research is an important 

concept, even though it may be difficult to 

accurately measure. Although it is beyond 

the scope of this simple model, it is clearly 

worthwhile to consider the quality of 

translated material. This is because quality 

undoubtedly affects the durability of tobacco 

research and education.

This simulation environment offers other 

ways to explore the effects of research. A 

new assumption suggests that, as in the 

baseline run, more translated research yields 

a greater effect (figure 5.27). In this new 

run, however, the model also reveals that 

there is a point at which more research does 

not yield greater impact but leads to less 

movement into the stock for tobacco control. 

Practically speaking, if the volume of 

antitobacco information available far exceeds 

the public’s ability to integrate it into the 

current social consciousness, it will likely 

be filtered out. A slight gain in support for 

tobacco control and, consequently, a decline 

Figure 5.26 Effects of Translated Research on Public Opinion

Base

Reference mode

Translated research aging out quickly

Adult smokers

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Smokers (millions)

Translated research

1,500

1,000

500

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

2,000

Number of articles

Figure 5.27 Effects of Translated Research on Undecided Public

Base

Reference mode

Translated research on undecided public

Smokers (%)

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Population (%)

Public supporters of tobacco control

150

100

50

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

200

Population (millions)

6

4

2

0

0 5 10

8

Undecided public

Translated research
139

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

in the fraction of people using tobacco are 

shown in figure 5.27 (lower graphs). If 

translated research has a greater effect than 

that in the baseline run, the simulations 

result in a predictable gain for the stock for 

the undecided public (figure 5.28).

The “gain” illustrated in figure 5.28, 

practically, means that 30% of the public 

has been undecided on the issue of tobacco 

control for more than two decades. Those 

without a keen eye on the long-term 

behavior of the system may be tempted to 

consider this finding as something other 

than progress. Based on this model, the 

absence of a dramatic gain for tobacco 

control could be interpreted as the natural 

evolution of the system. As the undecided 

public begins to shift toward support of 

tobacco control, a drop in rates of tobacco 

use will become apparent, as shown in 

figure 5.29.

Government Sector

A final example simulation experiment 

toggles the impact of government 

intervention. This model includes an 

assumption that government intervention 

may have the unintended effect of producing 

a backlash against tobacco control. In New 

York State, for example, laws regulating 

smoke-free restaurants and bars have 

Figure 5.28 Percentage of Undecided Public over Time

60

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

Base

Reference mode

Translated research on procontrol

Population (%)

Figure 5.29 Effect of Research on Population Fraction of Smokers

60

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

Base

Reference mode

Translated research on procontrol

Population (%)
140

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

produced a solid and well-funded campaign 

against tobacco regulation. This campaign 

threatens to weaken not only the law but 

also the movement to protect nonsmokers 

from the health effects of tobacco use.

The effects of government intervention on 

the shift from support for tobacco control to 

an undecided position and from undecided 

to a protobacco position are shown in figure 

5.30 (top left and top right, respectively).

As expected, the decreased strength of 

the effect leads to more tobacco control 

advocates and fewer supporters of tobacco. 

Over a longer period, the impact of the 

Figure 5.30 Effects of Government Intervention on Shift from Support for Tobacco Control to 

Undecided and from Undecided to Support for Tobacco Use

Base

Government intervention on undecided to procontrol or pro–tobacco use

Public supporters of tobacco

45

30

15

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

60

Population (millions)

Effect of government intervention on undecided

7.5

5

2.5

0

0 5 10

Government intervention

10

Undecided–protobacco

Effect of government intervention on procontrol

6

4

2

0

0 5 10

Government intervention

8

Procontrol–undecided

Public supporters of tobacco control

150

100

50

0

1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020

Time (year)

200

Population (millions) Figure 5.31 Effect of Government Intervention on Public Supporters of Tobacco Control

200

50

0

1965 1975 1985 1995 2005 2015 2025 2035 2045

Time (year)

Base

Government intervention on undecided 

to procontrol or pro–tobacco use

100

Population (%)

150
141

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

effect does not yield a significant change in 

behavior. The reaction of a population to a 

series of government regulations, all else 

being held constant, does not have a longstanding influence on the changing social 

norm (figure 5.31).

This model presents a simplified view 

of factors in tobacco prevalence and 

consumption, which were developed for 

illustrative purposes. Although the model 

represents only one iteration, it provides a 

base from which further modeling work, 

corrections, additions or subtractions, and 

enhancements could be easily accomplished 

as part of a more accurate simulation. 

Meanwhile, it serves as a mechanism for 

raising questions, provoking discussion, 

and gaining a deeper understanding of 

the complexity of this dynamic system. 

It also opens a valuable dialogue among 

stakeholders in tobacco control and other 

disciplines in the ISIS project.

Summary

This chapter examines the potential for 

using system dynamics modeling in tobacco 

control and public health and presents 

a case study of developing and using a 

system dynamics model to explore trends 

in tobacco use over time. It demonstrates 

use of a modeling approach to represent 

the interrelationships among key factors 

in tobacco use and their evolution over 

time. The project developed here can be 

considered a heuristic and preliminary 

model, but many of the results compare 

well with actual outcome data. Overall, this 

project serves as a valuable proof of concept 

for future systems-level modeling efforts.

This case study project was designed to 

develop clearer ideas about system dynamics 

and about the range of approaches that can 

contribute to more effective tobacco control 

and public health in general. The system 

dynamics approach arose, at least partly, 

from dissatisfaction with the limitations 

of simple cause-and-effect approaches that 

have no feedback for tackling the challenges 

of tobacco control. These approaches are 

effective in improving understanding of 

individual causal mechanisms or small 

clusters of mechanisms. However, they 

cannot provide much assistance in addressing 

the dynamic complexity of tobacco control.

The ISIS project used the rubric of systems 

thinking to establish a starting point for 

investigating the world of dynamic modeling 

and its application to tobacco control. 

Many approaches to systems thinking exist, 

sometimes with tensions evident among 

them. Nonetheless, the research outlined in 

this chapter provides a clear sense of how 

one systems approach, system dynamics, 

can help the tobacco control community 

to understand, model, and react to the 

complexities of the current tobacco control 

environment. System dynamics is an aid 

to thinking differently about the tobacco 

control world—to characterizing it in terms 

of feedback, stocks and flows, and structure 

and behavior. System dynamics elucidates 

the role of feedback, which keeps the system 

in balance and leads to change that may or 

may not be advantageous. System dynamics 

modeling also has the potential to work in 

concert with the other areas under study in 

ISIS, including the following:

n Management of organizations as a 

system, with an understanding of 

the macrodynamics of planning, 

implementation, and evaluation and how 

these constitute a feedback mechanism 

that is both driven by system forces and 

drives them (chapter 4)

n Network methods, encompassing the 

development and management of 

stakeholder groups that define the system 

of interest and its dynamics (chapter 6)

n Knowledge management and knowledge 

transfer, which facilitate the use and 

management of explicit and tacit 
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5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

knowledge (in the form of both data and 

people) that helps to describe and evolve 

system models (chapter 7)

System dynamics methods, in conjunction 

with other systems thinking approaches, 

are a useful tool for probing, exploring, 

understanding, simulating, and interacting 

with future issues in tobacco control. Many 

issues remain to be investigated to build on 

the foundations established here. At the same 

time, the concepts presented in this chapter 

represent a starting point toward developing 

a more systemic approach. This new 

approach would underpin the ability to work 

with increasingly complex, multifaceted 

tobacco control issues. It also would provide 

the foundation for transforming knowledge 

about a range of public health issues into 

effective policy and practice.

Conclusions

1. Tobacco control consists of dynamic 

relationships over time and requires 

approaches, such as system dynamics 

modeling, that can address such dynamics.

2. Understanding of tobacco control and 

public health issues has evolved from 

simple cause-and-effect studies and logic 

models to more complex, ecological 

problems that involve feedback and 

evolving behavior.

3. System dynamics uses mathematical 

simulation approaches based on stocks, 

flows, and feedback loops, which can 

model system structures and simulate 

future system behavior, including 

possible unintended consequences and 

long-term effects.

4. Demonstration projects, such as the 

system dynamics simulation of tobacco 

prevalence and consumption developed 

for the Initiative on the Study and 

Implementation of Systems, show the 

potential to model and simulate future 

tobacco issues to design more effective 

interventions.

5. Opportunities are likely to surface for 

integrating system dynamics modeling 

and other systems thinking approaches 

at epistemological and methodological 

levels. Systems approaches can and 

should integrate within a larger 

systems thinking environment 

encompassing components such as 

systems organizing, networks, and 

knowledge management.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Appendix 5A. Detailed Development of a 

System Dynamics Model

This section outlines the specific system dynamics model sectors created for a demonstration 

model of tobacco prevalence and consumption from 1965 to the present. This model was 

designed to simulate the effects of specific changes to model variables on prevalence and 

consumption of tobacco over time. Specific model segments are shown in detail in this 

appendix.

Figure 5A.1 Tobacco Use Sector

Youth

nonsmokers

Adult

nonsmokers

Youth

smokers Adult

smokers

Youth former

smokers

Aging 1 Adult never

smokers dying

Youth smoking

starts Adult smoking

starts

Youth quits Youth former

smokers smoking Adult quits

Time to age 1 Nonsmoking adult

life span

Norm youth uptake Norm adult uptake

Norm youth quit

rate

Norm adult

quit rate

Effect of public opinion

on youth quit rate

Adult returning to

smoking

Adult former

smokers smoking

Youth smokers

aging

Former youth

smokers aging

Former adult

smokers dying

Smoking adult

lifespan

Adult smokers

dying

Norm former adult

smoker lifespan

Time to age 2

Time to age 3

Effect of public opinion

on adult quit rate

Effect of public opinion

on adult uptake

Effect of public opinion

on youth uptake

Youth returning to

smoking

<Total adults>

New youth

Norm birth rate

Adult former

smokers

Note. Years are the unit of age.
144

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

Figure 5A.2 Tobacco Research and Education Sector

Research

Findings

Translated

Research

New translated

research

Translated research

aging out

New research Research aging out

Effect of available research

on publishing productivity Time for translated

research to age out

Time for published

New research per research to age out

researcher

Researchers

working on tobacco

research

Norm new

researchers

Researchers moving

to different projects

New tobacco

researchers

Time to adjust

research priorities Indicated fraction

working on publication

Fraction

working on

publication

Time to adjust

researcher fraction

Researchers publishing

initial research

Researchers publishing

more broadly

Research findings

in 1975

Translated research per

researcher 1975

Translated research per

author per year

Effect of public support on

new tobacco researchers Norm publication

fraction Effect of public support

on research fraction

Figure 5A.3 Government Sector

Government intervention

in tobacco sales and

Change in government production

intervention

Time to change government

intervention

Indicated

intervention

Effect of public support on

government intervention

Government

intervention in 1975
145

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Figure 5A.4 Public Opinion Sector

Public Supporters of

Tobacco Control Public Supporters

of Tobacco Public Undecided

Public support to

Undecided Undecided to

Dissenting

Dissenting to

Undecided

Undecided to

Supporting

Fraction undecided to

procontrol in 1965

Fraction of antitobacco

becoming undecided per year

Fraction of undecided

becoming protobacco

per year

Effect of translated

research on undecided

public

Fraction of undecided becoming

procontrol per year

Effect of translated

research on protobacco

public

Fraction of protobacco

becoming undecided per year

Fraction of protobacco to

undecided in 1965

Effect of government

intervention on

procontrol

Fraction procontrol to

undecided in 1965

Effect of government

intervention on

undecided

Fraction undecided to

protobacco in 1965

Effect of nonsmokers

on undecided public

Effect of nonsmokers on

protobacco public

Effect of smokers on

procontrol public Effect of smokers on

undecided public

Fraction of population that

supports tobacco control

Fraction of

population undecided

Fraction of population

that supports tobacco

Total public

opinion
146

5 . H o w t o A n t i c i p a t e C h a n g e i n To b a c c o C o n t r o l S y s t e m s

References 

1. Framework Convention Alliance for Tobacco 

Control. 2005. The WHO Framework 

Convention on Tobacco Control: A public 

health movement. http://www.fctc.org. 

2. Sterman, J. D. 2000. Business dynamics: 

Systems thinking and modeling for a 

complex world. New York: McGraw-Hill/

Irwin.

3. Zagonel, A. A., J. Rohrbaugh, G. P. 

Richardson, and D. F. Andersen. 2004. Using 

simulation models to address “what if” 

questions about welfare reform. Journal of 

Policy Analysis and Management 23 (4): 

890–901. 

4. Centers for Disease Control and Prevention. 

2004. Percentage of adults who were 

current, former, or never smokers, overall 

and by sex, race, Hispanic origin, age, 

and education. National Health Interview 

Surveys, selected years—United States, 

1965–2000. Atlanta: U.S. Department of 

Health and Human Services, Centers for 

Disease Control and Prevention, National 

Center for Chronic Disease Prevention 

and Health Promotion, Office on Smoking 

and Health. http://www.cdc.gov/tobacco/

research_data/adults_prev/adstat1print.htm. 

5. National Cancer Institute. 2006. Evaluating 

ASSIST: A blueprint for understanding 

state-level tobacco control (Tobacco control 

monograph no. 17, NIH publication no. 

06-6058). Bethesda, MD: National Cancer 

Institute. http://cancercontrol.cancer.gov/

tcrb/monographs/17/index.html.

6. Centers for Disease Control and Prevention. 

2004. Cigarette smoking among adults—

United States, 2002. Morbidity and 

Mortality Weekly Report 53 (20): 427–31.

7. U.S. Department of Health, Education, and 

Welfare. 1964. Smoking and health: Report 

of the Advisory Committee of the Surgeon 

General of the Public Health Service (PHS 

publication no. 1103). Washington, DC: 

U.S. Department of Health, Education, and 

Welfare, Public Health Service, Center for 

Disease Control.

8. Federal Cigarette Labeling and Advertising 

Act. 1965. Pub. L. No. 89–92, 79 Stat. 282 

(1965).

9. Hyland, M., and J. Birrell. 1979. Government 

health warnings and the “boomerang” effect. 

Psychological Reports 44:643–47.
147

6

Understanding and Managing 

Stakeholder Networks

The current environment for tobacco control consists of many “silos” of organizations 

and expertise, with connectedness within disciplines but few clear linkages between 

disciplines and among stakeholder groups. There may be a future for the tobacco control 

field in which linked, interdependent resources are used collaboratively to build synergy, 

share expertise, and reduce duplication of effort. The processes of creating, analyzing, and 

maintaining networks of tobacco control stakeholders are key to functioning in a systems 

environment. 

This chapter provides an overview of network theory and analysis methods and 

approaches for using knowledge to provide a deeper understanding of strategies to 

promote collaboration of people and organizations in a public health context. The chapter 

explores issues involved in applying networks to tobacco control and implications for 

research in the field. Finally, findings are presented from a case study using network 

analysis for evaluation of the tobacco control process.

Society must be reconceptualized as a complex network of groups of interacting 

individuals whose membership and communication patterns are seldom confined to one 

such group alone.

—Diana Crane, Invisible Colleges (1972)
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

Introduction

The complexity of tobacco use is such that 

no one person or organization is likely 

to “solve” the problem. Effective tobacco 

control programs are comprehensive and 

have components that attack the problem 

at individual, organizational, community, 

and societal/environmental levels. For 

example, intervention programs aimed 

at the individual (e.g., offering advice on 

smoking cessation) are more likely to reduce 

smoking in the population if they coincide 

with interventions at the organizational 

level (e.g., smoking bans in the workplace 

and at home) and at the environmental 

level (e.g., increased price of cigarettes 

through increases in excise taxes or passage 

of minimum price laws). Comprehensive 

tobacco control programming requires 

collaboration among a mix of individuals 

and organizations with varied interests, 

talents and skills, knowledge, and resources. 

Similarly, because of the complex and 

multidimensional determinants of tobacco 

use, no one scientific discipline is likely to 

solve the problem either. Instead, a high 

degree of transdisciplinary collaboration 

is required, leading to development of 

new research tools and conceptual models 

and, finally, to interventions that take into 

account the full spectrum of biobehavioral 

and environmental aspects of tobacco use. 

This complexity requires collaboration among 

tobacco control practitioners and scientists. 

In addition, the work of the scientists must 

be made accessible to practitioners, and the 

experiential knowledge of the practitioners 

must be accessible to scientists. This 

will ensure that the appropriate research 

questions relevant to tobacco control are 

being asked and answered.

This chapter examines the questions of “who 

works with whom” in a system and how 

organizations and individuals are brought 

together. The approach here focuses on the 

concepts in network analysis theories and 

the applications of network analysis that can 

be used to improve collaboration among and 

between the communities of public health 

practice and science.

Overview of Network 

Theory

In their recent book, Social Networks and 

Organizations, Kilduff and Tsai1 provide a 

useful introduction to the importance of 

networks. They cite the example of Paul 

Revere and his famous “midnight ride” in 

1775 to alert local townspeople near Boston, 

Massachusetts, of the imminent arrival of 

British soldiers. Most Americans know this 

story, thanks to Longfellow’s poem. It is 

not so well known that on the same night, 

another rider, William Dawes, carried the 

same message and rode the same number 

of miles to other towns in the Boston area. 

Thanks to Revere, the message that the 

British were arriving spread rapidly. For 

Dawes, however, the message went largely 

unheeded, so most people, including the 

local militia leaders, were unprepared. Why 

was there such a difference? The answer, 

according to Kilduff and Tsai, is that 

Revere knew very well the communities he 

visited that night, and thus, he knew which 

individuals to contact so his message would 

spread rapidly. Because Dawes did not know 

many people in the communities he rode 

through, he contacted very few of the right 

people. Those he did contact were not well 

connected to others who could both spread 

the word quickly and initiate action to 

prepare for the coming invasion.

This example, whether apocryphal or not, 

demonstrates the importance and value of 

networks. Despite good intentions, similar 

resources, and high motivation, success 

in getting things done is often highly 

dependent on having an effective social 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

network. Most people by now understand 

this point, at least regarding the importance 

of their personal network for such things 

as obtaining a desired job, achieving a 

promotion, or accomplishing politically 

sensitive tasks. The role networks play in 

society has been popularized through the 

movie Six Degrees of Separation and by 

the work of Watts,2 who discusses “smallworld” properties of networks. He argues 

that small-world networks, which exhibit 

only a few degrees of separation between 

any two nodes, can be used to explain 

the operation of both social and physical 

systems and the connection between 

seemingly random actions. It is far less 

well known how the study of networks, 

through network analysis, can be a valuable 

tool for organizational administrators and 

policy officials, in their efforts to address 

complex health and social problems through 

multiorganizational collaboration. Networks 

are critical to organizational life. However, 

attempts to apply what scholars know about 

networks to enhance the effectiveness of 

multiorganizational efforts in complex areas 

such as tobacco control, obesity, and chronic 

disease have been extremely limited.

Networks have been defined in a variety 

of ways, and no single definition is widely 

accepted. Even the term network is not 

always used. Many who study community 

and other organizational networks prefer to 

talk about partnerships, strategic alliances, 

interorganizational relationships, coalitions, 

or collaborative agreements.3 Many also 

focus only on dyads (relationships between 

two persons or two organizations). Despite 

differences, nearly all definitions refer to 

certain common themes, including social 

interaction, relationships, collaboration, 

collective action, trust, and cooperation. 

Here, a network is defined as a group 

of three or more individuals, groups, or 

organizations connected in ways that 

are believed to facilitate achievement 

of a common goal. The relationships 

among network members are primarily 

nonhierarchical and have partial and often 

substantial operating autonomy. Network 

members can be linked by many types of 

connections and flows, such as information, 

materials, economic resources, services, and 

social support. Examination and analysis of 

a network include relationships, the absence 

of relationships, and the implications of 

both for achieving outcomes.

No single, grand “theory of networks” 

exists. Instead, scholars in a wide range 

of disciplines, including anthropology, 

communication, economics, management, 

psychology, political science, and sociology, 

have used a number of theories over the 

years to help explain network structure 

and processes in interpersonal networks 

and organizational networks. Because the 

focus of this chapter is interorganizational 

networks, the theories, concepts, and 

measures are discussed, whenever possible, 

as they apply to organizations. To use 

the terminology of network analysis, 

organizations are considered as the “nodes” 

of the network. The primary caveat is that 

organizations consist of individuals. Social 

interaction among organizations ultimately 

occurs primarily between individuals acting 

on behalf of organizations.

Network Perspectives from Two 

Levels of Analysis 

Network theory can be thought of as coming 

from two different but complementary 

perspectives: the view from the individual 

(actor) level and the view from the network 

level of analysis. Wasserman and Galaskiewicz4

also make this distinction, referring to a 

microlevel versus a macrolevel network focus.

Individual-level theories have a long 

tradition in social research and have guided 

most of the knowledge about networks. 

Individual-level views, often considered to 

be egocentric, are concerned with trying to 

explain how involvement of an individual 
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

or organization in a network affects its 

actions and outcomes. For example, some 

individual-centered theories focus on an 

organization and its “embeddedness”5 in 

a network. Prominent examples in the 

organizational literature include work by 

Burkhardt and Brass,6 Burt,7 and Uzzi.8

Frequently, the focus of this research is 

dyadic relationships between organizations.9

Dyads are the basic building blocks of 

networks. However, dyad-focused research is 

limited in that the network is primarily seen 

as a collection of two-party relationships, 

rather than as a unique, multiorganizational 

social structure in its own right.

Individual-level theories and related 

research can help to answer questions such 

as (1) which types of links are most or least 

beneficial to individual network members; 

(2) which network positions might be most 

or least influential; and (3) how the position 

of organizations in a network might shift 

over time in response to changes within and 

outside the network. 

Structural issues that are typically examined 

and used to explain networks and network 

outcomes on an individual level include the 

following:

n In-degree and out-degree centrality.

Does an organization occupy a central 

position or a more peripheral position 

in the network based on the number of 

networking ties it sends to or receives 

from other organizations? Degree 

centrality is based on the number of direct

links maintained by an organization. 

Calculation of in-degree and out-degree 

centrality is based on the balance of assets 

such as resources, information, and 

clients coming into an organization from 

others in the network versus those being 

sent out to other organizations. 

n Closeness centrality. Is an organization 

in a structural position to discern or 

spread information that might reside 

in any organization in the network, 

even through indirect ties? Central 

organizations have short “paths” 

(connections) to all other organizations 

in the network. Closeness centrality 

is thus calculated by considering the 

shortest path connecting an organization 

to all other organizations in the network. 

Direct connections, where A is connected 

to B, are shorter than indirect ones, 

where A is connected to B only indirectly 

through ties to C, which is tied directly 

to B. Unlike the case with degree 

centrality, in closeness centrality, indirect

connections are viewed as valuable 

conduits of exchange.

n Betweenness centrality. Does an 

organization serve as a gatekeeper within 

the network? If so, it must maintain 

intermediary links between organizations 

that are not directly connected with 

one another. Hence, the organization’s 

betweenness centrality is calculated 

by considering the extent to which an 

individual’s position in the network lies 

“between” the positions of other individuals. 

n Multiplexity. What is the strength 

of the relationship an organization 

maintains with network partners, based 

on the number of types of links (e.g., 

joint programs, referrals, and research) 

connecting them? Multiplex ties are 

thought to be an indicator of the strength 

and durability of links, because they 

enable the connection between two 

organizations to be sustained even if 

one type of link dissolves. 

n Broker relationships and structural holes. 

To what extent does an organization span 

gaps (structural holes) in a network, 

and what are the implications of this for 

the organization? Organizations that 

span structural holes are considered to 

be brokers, often occupying positions of 

considerable influence.

n Cliques. Cliques are clusters of three or 

more organizations connected to one 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

another. The level of connectedness in a 

clique affects organizational outcomes in 

ways that are different from the effects of 

dyadic involvement.

Network-level theories draw on and use 

many of the ideas and measures developed 

by individual researchers. However, the focus 

is not on the individual organization but on 

explaining properties and characteristics of 

the network as a whole. The key consideration 

is outcomes on the network level, rather 

than on the organization level. For instance, 

instead of examining how organizational 

centrality might affect the performance or 

influence of individual member organizations, 

the network-level perspective would focus 

on overall network structures and processes. 

Network-level characteristics would be 

determined, compared across networks, and 

then used to answer questions such as how 

overall sustainability or absorptive capacity 

of the network could be enhanced or how 

the multiorganizational services provided to 

a client group might be strengthened. This 

perspective presumes that a network involves 

many organizations working collaboratively 

toward a common goal and that the success 

of one network organization may or may not 

be critical to the success of the entire network 

and its client group. The preference is for 

optimization of the network even if it comes 

at the cost of local maximization for any node 

or group of nodes in the network.

Work at the network level has blossomed 

over the past decade, but it has primarily 

been conceptual, anecdotal, or based on 

single case studies performed at one point 

in time. Networks have been used in studies 

of mental health,10–13 and comparative 

empirical work has been done in other 

settings.14–17 These and other studies used 

many of the structural issues discussed 

previously in this section for individual-level 

networks. Typically, these structural issues 

are aggregated across an entire network and 

then compared with those of other networks 

providing similar services. Unique networklevel properties also are considered in those 

studies, including the following:

n Density. What is the overall level of 

connectedness among organizations in 

the network? Are some networks more 

fully connected than others? How much 

density is beneficial versus detrimental to 

the effectiveness of the network?

n Fragmentation. Are all or most network 

members connected, either directly 

or indirectly (i.e., through another 

organization), or is the network 

broken into fragments of unconnected 

organizations, dyads, and cliques? 

Fragmented networks have many 

structural holes.

n Governance. What mechanism is used 

to govern and/or manage the overall 

network? This mechanism can range 

from self-governance, with network 

members collectively running the 

system, to lead-agency models governed 

by a single organization that also 

provides critical core services, to a 

network administrative organization 

model. In this model, a separate entity 

is established for the sole purpose of 

facilitating network activity.

n Degree, closeness, and betweenness 

centralization. To what extent are a 

small proportion of the organizations in 

the network considerably more central 

in terms of degree, betweenness, or 

closeness centrality, as opposed to a 

network in which most organizations 

have relatively similar levels of centrality? 

Highly centralized networks may be 

organized in a manner approximating 

a hub-and-spoke pattern, popularized 

recently as “scale free” networks. 

Decentralized networks are far more 

dispersed, with links spread more evenly 

among members. 

n Cliques. What is the clique structure 

of the network? How many cliques 

exist? Which types of organizations are 
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

involved? How large are the cliques? 

Are they connected to other cliques or 

fragmented? How much overlap is there 

across cliques, depending on the type of 

link involved (e.g., shared information or 

joint programs)?

Theories of Social Networks and 

Network Behavior

As previously noted, there is no single, 

unified theory of networks. Some 

researchers18,19 even argue that there is no 

network theory at all. Rather, they claim that 

the study of networks is, at this point, more 

of an attempt to study social relationships 

by using a particular set of analytic methods 

and concepts (e.g., centrality). Most who 

study networks, however, do draw on one 

or more of a number of theories developed 

to explain networks and network behavior. 

These theories are discussed in considerable 

depth in two recent books: one by Monge 

and Contractor20 on communication 

networks and the other by Kilduff and Tsai1

on organizational networks. A brief overview 

of the major categories of theories that have 

been used to explain network behavior is 

provided here.

n Self-interest. Self-interest theories, 

drawing on economic principles of 

maximization of individual value, explain 

network behavior based on the selfinterest of those involved in the network. 

In its simplest form, this explanation 

contends that organizations seek network 

links with other organizations if and 

only if it is in their interest to do so. 

For instance, one organization might 

want to create a network link to another 

organization from which it seeks to draw 

knowledge, skills, or resources. Network 

members can build their own social 

capital and thus enhance their outcomes 

by acting as social entrepreneurs and 

brokers, spanning structural holes.7

Transaction cost economics also has 

been used to explain networks based 

on self-interest. Using this approach, 

network members seek connections that 

allow them to operate most efficiently by 

minimizing the cost of transactions (e.g., 

overhead, distance, and accessibility) and 

maximizing the gains from transactions 

(gross value of services or materials being 

sought). Theories of self-interest are 

most useful in understanding networks 

in which the organization with the selfinterest has the ability to coerce other 

organizations to be a part of its network.

n Exchange and resource dependence.

A more viable network explanation is 

premised on theories of exchange and 

resource dependence. According to this 

perspective, organizations seek and form 

network ties with other organizations 

to reduce uncertainty and attract 

needed resources. The nature of these 

interorganizational ties is based on implicit 

consideration of the relative terms of 

exchange. The primary issue is power or its 

reciprocal, dependence. One organization 

may develop strong ties to another based 

on resource needs (e.g., money and 

information). However, it also seeks to 

balance this dependence through mutual 

dependencies with its linkage partner (i.e., 

exchange of needed resources) or through 

the influence and power this relationship 

provides for dealing with others in the 

network.21,22 Decisions to be part of a 

network thus involve a complicated set 

of exchange relationships between and 

among all network members.

n Collective action. The two previous 

approaches are based on individual 

organizations structuring their network 

to draw resources from one another. 

Theories of collective action, on the 

other hand, explain situations in which 

organizations create network links 

with other organizations, not to seek or 

exchange resources with one another, 

but to maximize their joint ability to seek 

resources from or provide them to third 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

parties. For instance, organizations might 

choose to share information to mobilize 

more effectively in a campaign to promote 

smoking cessation. Theories of collective 

action explain the viability of network 

links based on the mutual interest and 

benefits associated with joint action by 

the two organizations. These theories 

build on public goods theory23 with the 

idea that individuals and organizations are 

motivated to join and work in networks to 

reap the benefits of collective action. The 

benefits presumably could not be obtained 

by acting through motives of self-interest 

or social exchange, even in a network 

context. Theories of collective action 

are broadly useful for explaining why 

organizations might form and sustain 

a network. Researchers24 have explored 

reasons behind the formation of particular 

network structures and which structures 

might be most effective under particular 

conditions.

n Social contagion. The perspective of 

social contagion focuses on the impact 

of network involvement on subsequent 

behaviors. Contagion occurs as a result 

of interacting with network members 

and being “infected” by their attitudes 

and behaviors. In general, greater 

involvement (embeddedness) results in 

greater contagion, leading to similar 

attitudes, beliefs, and behaviors among 

network members. In the organizational 

literature, network involvement has 

frequently been used to explain why 

some organizations mimic the behavior 

of others, such as adopting total quality 

management; other “trendy” solutions 

to management problems;25 or certain 

attitudes, innovations, or ideas.

n Homophily. The approach of homophily 

provides relatively simple but compelling 

reasons for why networks form and to 

a lesser extent, why they are sustained. 

Homophily is based on the assumption 

that individuals and organizations 

are more likely to create links with 

one another if they are similar. It is 

the “birds of a feather flock together” 

argument.26 The underlying contention 

here is that there is a “comfort zone” 

associated with maintaining links with 

like-minded individuals or organizations. 

Although such networks may be 

attractive, it is reasonable to infer from 

research on group decision making that 

homogeneous networks also are likely to 

be less creative and innovative. 

n Proximity. Like homophily, proximity 

provides a simple but powerful 

explanation for the maintenance 

of network links. Early research in 

organizational settings indicates that 

the frequency of face-to-face dyadic 

communication drops precipitously 

after the first 75–100 feet.27,28 Proximity 

is based on the concept that physical 

closeness is likely to result in more 

opportunities for a social relationship 

than is separation by longer distances. 

More recent studies29 considered the 

effect of communication technologies 

(e.g., e-mail and instant messaging) 

on the impact of physical proximity. 

Findings suggest that the effects of 

higher levels of interactions via electronic 

channels have a bimodal distribution. 

The impact is highest among those with 

the closest physical proximity and those 

who are the greatest distance apart.

n Change and evolution. Theories of 

organizational change and evolution 

have focused nearly exclusively on 

internal change or on the evolution of 

organizational populations.30 However, 

some researchers have made efforts to 

extend what is known about change and 

evolution to networks by examining the 

influence of network involvement on 

organizational survival and on evolution 

of the network itself. The work on 

network involvement addressed network 

life-cycle stages and the importance of 

building legitimacy if the network is to 

be sustained.31 A central assumption is 
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that organizations create network links 

to maximize the “fitness” of the entire 

network and thereby to be “selected” 

from an ecology of other networks in the 

community. This perspective might explain 

why organizations involved in the tobacco 

control network might strategically create 

ties that help to preserve the long-term 

viability of the tobacco control community 

relative to other networks in health care 

communities, such as those focusing on 

obesity control. 

Researchers have used all of these theoretical 

approaches to explain key aspects of network 

behavior. In some sense, they are competing 

theories, because all are attempts to explain 

the same basic phenomenon. However, 

networks are complex mechanisms, and an 

explanation of the actions and structures 

of network members and the network as a 

whole cannot be boiled down to one simple 

theory. Individuals and organizations 

typically join and sustain their involvement 

in networks for multiple reasons. The 

theories merely reflect this complexity. 

Indeed, there is a compelling case for the use 

of multitheoretical, multilevel models for 

explaining, simulating, and designing realworld networks.17,20

Effective 

Organizational 

Networks

Drawing on these theories, researchers 

have studied many networks in a broad 

range of settings. On the basis of research 

at the network level of analysis, a number 

of tentative conclusions can be drawn about 

criteria for an effective network. This list 

is not exhaustive, but it provides a brief 

overview of much of the existing knowledge 

about organizational networks. It also forms 

the basis of the subsequent discussion about 

application of network analysis to build and 

strengthen tobacco control efforts.

n Multiple levels of collaboration.

Collaboration should occur at multiple 

organizational levels. Having network 

ties at only one organizational level (e.g., 

top-level administrators) minimizes 

commitment to the network by lowerlevel organizational participants. This 

reduces the chances of successful 

implementation of network strategies. 

Involving multiple people in an 

organization also increases the likelihood 

that network links will be maintained 

when someone leaves the organization.

n Focused integration. Extremely dense 

networks are inefficient, requiring a great 

deal of time and energy to maintain. 

Effective networks should have moderate 

levels of integration among members, with 

some fragmentation and structural holes. 

n Strong links. The strength of linkages 

(multiplexity) among network members 

should be varied, depending on critical 

network needs. Some organizations 

should be connected through multiple 

ties, but other network members can and 

should maintain weak ties.

n Network governance. Governance of 

the network should be based on the 

size and complexity of the network and 

on its stage of evolution. Generally, 

small networks can be self-governed, 

but larger networks are most effective 

when governed through a lead agency or 

network administrative organization.

n Involvement. Most network relationships 

should be based on trust and commitment to network goals, even when 

contractual ties (e.g., funding) are 

present. Trust and commitment generally 

need to be built gradually, often first 

through low-intensity ties.

n Legitimacy. Networks must build 

legitimacy as they grow, both internally 

(through network members) and 

externally (e.g., through outside funding 

and the media). Legitimacy helps to build 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

commitment to the network and its goals 

and is critical for sustaining the network.

n Resources. Effective networks have 

sufficient resources to work on networklevel goals and activities, rather than 

focusing solely on internal organizational 

issues. Resources can come from network 

members or from outside sources. 

Minimally, resources are needed for basic 

business necessities, such as staffing, 

telephones, and a newsletter.

n Knowledge repositories. Organizations 

that publish materials in digital 

knowledge repositories (e.g., Web sites) 

are more likely, not less likely, to be 

targeted for direct communication from 

other organizations. Organizations 

use published information in digital 

repositories to identify “who knows 

what” and “who knows whom.” Then, 

rather than being content to download 

the published information in these 

repositories, they seek out the “who” 

directly for further clarification and 

collaboration. In essence, a knowledge 

repository serves as an effective signal of 

the organization’s knowledge but not as 

an effective substitute for disseminating 

knowledge to other organizations within 

the network.

n Dedicated network alliance function.

Nodes in effective networks have 

developed an in-house dedicated network 

alliance function as part of human 

resources activities. The purpose is to 

help build “learning” about how to grow 

the network more effectively and to 

monitor for action cues to dissolve some 

network links.

n Exploration, exploitation, and 

mobilization. Organizations use “dense” 

(highly connected) networks to effectively 

exploit resources. This practice may 

contribute to incremental innovation. 

However, organizations use sparse 

small-world networks to explore novel 

ideas. This approach is most appropriate 

for identifying disruptive technologies 

and might contribute to disjunctive 

innovations. In addition, organizations use 

“star” networks to enable mobilization. 

This strategy is most appropriate for 

formulating and implementing standards, 

policies, or procedures.

n Goals. Long-term goals such as improved 

health status are important, but results 

are frequently not apparent for many 

years. Thus, networks must have goals 

that are specific, attainable, and appealing 

to a broad range of network members. 

To build commitment and legitimacy, 

network members must have a sense of 

accomplishment. Such goals can focus on 

network structure, processes, and shortrange outcomes.

n Stability. Although networks are 

designed for flexibility, major system 

upheavals are not conducive to the 

effectiveness of networks, especially after 

early formation and growth. Major system 

change can disrupt established, trustbased relationships that have evolved over 

a long period.

Value of Organizational 

Networks

Use of cooperative networks of organizations 

has become a key strategy for addressing the 

public’s most pressing health and human 

services needs. These networks have become 

important mechanisms in many states 

and communities, as well as nationally 

and internationally. Their functions are as 

follows:

n Building capacity to recognize complex 

health and social problems

n Planning strategies systematically to best 

meet critical public health needs

n Developing and implementing policy 

related to public health needs
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

n Mobilizing, leveraging, and obtaining 

scarce resources

n Facilitating the flow of knowledge and 

information to address complex problems

n Delivering needed services

By working together as a network, 

organizations can improve both their 

efficiency and the effectiveness of the 

services and programs they offer.32,33

Potential benefits of network involvement 

are substantial. They include improved 

services, better access to services, less 

duplication of effort, better communication 

and access to information, improved 

innovation, and ultimately, more sensitive 

and reliable indicators of health status. 

Research has demonstrated that networks 

are especially valuable for nonprofit and 

public organizations working to address 

a broad range of problems in community 

and regional health and human services.12,34

Organizational networks offer the following 

benefits to health care providers:

n Provide a team approach to complex 

public health issues. Networks are 

especially helpful for addressing 

problems that are complex and 

seemingly intractable.32 The magnitude 

of many problems in health and human 

services is simply too great for any one 

organization to resolve single-handedly. 

Such problems require a “fishing net” 

approach—a structure of organizations 

that is agile, flexible, easily reconfigured, 

and yet robust, and that can rapidly 

bring together the set of diverse skills, 

resources, and expertise required to 

address these problems effectively.

n Address multiple needs. Networks can 

work with clients who have multiple 

needs (e.g., education, disease prevention, 

treatment, and referral), as well as 

requirements to treat combinations 

of illnesses (e.g., substance abuse and 

mental illness or cancer and depression).

n Counteract fragmentation of multipleprovider organizations. Despite the 

multiple needs of clients, health care 

providers usually offer a limited range 

of services. Such fragmentation may 

be cultural or it may be based on 

differing treatment philosophies and 

methods, traditions, or funding streams. 

When services are fragmented, clients 

generally suffer, receiving only partial 

treatment or being forced to deal with 

multiple providers on their own. When 

organizations establish a network, 

however, fragmented services can be 

integrated across providers, enabling 

clients to enter a system for delivery 

of services that meets a broad range of 

needs across multiple organizations. 

n Ease problems related to geographic 

dispersion. Organizations in large 

cities, rural areas, or different states, 

regions, or countries often can benefit 

immensely by sharing information, ideas, 

and resources. However, geographical 

dispersion often keeps them isolated. 

Networks provide a formal mechanism 

to encourage and facilitate collaboration, 

even when face-to-face contact is not 

possible. 

n Optimize use of resources. Networks 

are efficient mechanisms for providing 

needed services under the constraints 

of limited resources. When provided 

through a network, scarce resources can 

be shared and duplication of services can 

be minimized through the coordinated 

efforts.

n Facilitate transfer of knowledge and 

enhance learning. Organizations have 

considerable knowledge and expertise, 

but that information frequently stays 

within the organization or is shared 

only sparingly. To address complex 

health care problems, however, the 

broad sharing of knowledge is critical. 

By establishing formal mechanisms to 

facilitate information transfer and by 
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creating the framework for more informal 

interactions, networks can enhance the 

flow of knowledge across organizations. 

This improves both the amount and 

speed of learning by participants in the 

organization. In addition, networks can 

be used to build “transactive memory 

systems”35 in which highly differentiated 

but easily accessible pockets of specialized 

knowledge are distributed across the 

network. Such networks can enhance the 

efficiency (speed) and effectiveness (quality) 

of learning across a broad range of areas, 

including client needs, delivery of services, 

advocacy, research, policy, and funding.

Networks also have shortcomings that can 

seriously undermine their effectiveness, 

even resulting in dissolution. Challenges 

to building and maintaining a successful 

network are numerous, but several factors 

affecting networks stand out as being most 

common, based on the research conducted.

n Undermining of autonomy in decision 

making. The downside of collaboration 

in any setting is that participants can no 

longer focus solely on their own needs. In 

organizational networks, members must 

consider the interests and expectations 

of other network members, thereby 

limiting their autonomy in decision 

making. The problem is most acute 

for network members who cooperate 

very closely, because decisions made 

by one member have a major impact 

on the other member(s). In addition, 

most contemporary organizations are 

confronted with the dilemma of having 

to cooperate with many of the same 

organizations they compete with in other 

contexts. A generic form of this dilemma 

occurs when organizations cooperate to 

provide complementary health services 

in a local community but compete for 

resources from local, state, and federal 

agencies to provide these services. 

This phenomenon of cooperation and 

competition36 in the network further 

undermines autonomy in decision making.

n Generation of conflicting loyalty and 

commitment. Even in organizational 

networks, the key links are among 

Putting Network Analysis to Work on Rural Chronic Disease

A team led by University of Arizona professor Keith Provana explored the impact of community 

networks on management of chronic disease in a rural county of southern Arizona, using classic 

network analysis measures and self-assessment by participants.

This project, with support from a Turning Point grant funded by the W.K. Kellogg and Robert 

Wood Johnson Foundations, involved creation of a participatory coalition led by the Cochise 

County department of health to address issues of chronic disease. This group included 

stakeholders such as local politicians, law enforcement groups, faith-based organizations, and 

service providers. The work of the group was repeatedly evaluated during the two-year study, 

through data-collection efforts and participation in focus groups.

Results include a higher level of collaboration over an increased number of channels, including 

a near doubling in the number of nonredundant referrals and a broad perception (>90% of the 

22 respondents) that collaboration had enhanced the agency’s ability to serve its clients. At the 

same time, key issues for future network efforts were identified, including the need for strong 

leadership and continued funding.

a

Provan, K. G., L. Nakama, M. A. Veazie, N. I. Teufel-Shone, and C. Huddleston. 2003. Building community 

capacity around chronic disease services through a collaborative interorganizational network. Health 

Education and Behavior 30 (6): 646–62.
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individuals. These individuals are employed 

by, trained by, and socialized in one 

organization. Network involvement means 

going beyond the employing organization, 

in effect, becoming a multiorganizational 

participant. Often, however, loyalty and 

commitment to the organization are 

stronger than those to the network, 

even though organizational goals may 

best be accomplished through network 

collaboration. Some also may have internal 

conflicts, advocating network goals in their 

organization but encountering resistance 

from those who do not share this view. In 

general, having a narrow, organizational 

perspective can severely limit the 

achievements of a network.

n Requirements for additional time and 

resources. One of the main benefits of 

networks is that they can overcome 

deficiencies in systemwide resources. 

Nevertheless, they do require resources 

to become established and to operate. 

These resources may come from external 

sources, such as government agencies 

or foundations, or they may consist of 

contributions from network members. In 

either case, however, network members 

may feel that these resources could best 

be spent on their own organization and 

its clients. This problem is especially true 

considering the contribution of time 

required to participate in maintaining the 

network and its management. Directors 

of health and human service agencies 

generally embrace the network concept 

but not necessarily the time, effort, and 

money required to build and maintain 

an effective network. This is one of the 

reasons some effective organizations have 

invested in the creation of a “dedicated 

network alliance function” to nurture the 

network.

n Need to manage collaboratively 

rather than hierarchically. Traditional 

bureaucratic forms of control may 

not be widely accepted in most health 

and human service settings. However, 

organizational employees still work 

in hierarchical settings governed by 

rules, procedures, and the decisions 

of supervisors and top management. 

This mechanism is efficient and well 

understood. In contrast, networks 

are mostly not hierarchical. Some 

organizational members may clearly 

be more influential than others, and 

some networks are constructed around 

funding and/or regulatory relationships. 

Yet, members can always withdraw from 

the network, despite consequences. As a 

result, network decisions can be messy, 

time consuming, and often frustrating, 

especially to those accustomed to 

working in a hierarchy. Some networks 

are designed to only share information, 

which limits this problem. However, many 

others are designed to coordinate delivery 

of services and programs, requiring 

significant agreement from participants. 

Although network decisions need not be 

consensual, they do need to be based on 

trust and reciprocity if the network is to 

be successful over an extended period. 

These shortcomings are very real and can 

limit the accomplishments of networks. 

Nonetheless, most health and human 

services professionals recognize the 

advantages of networks, at least generally, 

and they believe strongly in the value of 

the collaborative process. However, many 

of those involved in networks, especially 

network leaders, may have difficulty 

recognizing and demonstrating progress 

in building the network. In light of the 

potential problems mentioned here, it 

may be relatively easy to conclude that the 

potential of the network is not being fully 

realized. The apparent lack of progress 

and tangible outcomes can be frustrating, 

especially for those who played a leadership 

role in building the network and are 

strongly committed to its success. 

One problem is that most health leaders do 

not feel equipped to take steps to examine 
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the quality and functioning of their network. 

This can best be accomplished through an 

objective and systematic process, but most 

network participants do not have the tools 

to do this. In addition, most tend to view the 

network from the perspective of the effect on 

their organization of network relationships. 

This view limits an objective understanding 

of the network as a whole. If collaborative 

efforts are to be effective, participants must 

look beyond their own needs, interests, 

and perspectives and consider how a 

multiorganizational network might be 

structured and governed to maximize its 

capacity to address critical health and 

human service problems.

In the academic and research literature 

of the past two decades, a great deal of 

knowledge about organizational networks 

has been generated.3 Unfortunately, very 

little of this work has reached the world 

of health practice, except in a very general 

way.37,38 Nonetheless, network analysis, as 

developed in the scholarly literature, can be 

used in a very applied way to help public and 

nonprofit organizations build and sustain 

networks across a broad range of health 

and human services, including control 

of tobacco use, chronic diseases such as 

diabetes and HIV/AIDS, obesity control, 

child and youth health, mental health, 

and substance abuse. Network analysis 

techniques offer four key benefits to these 

efforts:

1. They offer a global view, which helps 

participants understand the network and 

its components and how the network 

operates.

2. They help stakeholders to see exactly 

where their organization fits in the 

structure of the network, based not just 

on their own impressions but on the 

actual experiences of the other network 

participants.

3. They give managers access to data 

that they can use to shift priorities 

and resources to become more or less 

involved either in the network as a whole 

or with certain key organizations that 

may be critical to their own effectiveness 

and the effectiveness of the network as a 

whole.

4. They provide members of the network 

with the tools to visually navigate the 

network and seek out relevant partners 

to help them solve specific problems. In 

this way, network analysis techniques 

help people involved in tobacco control 

to learn more about “who knows what” 

and where to go to obtain needed 

information.

Application of 

Network Analysis

As described previously, network analysis is 

a method of collecting and analyzing data 

from multiple individuals or organizations 

that may be interacting with one another. 

Unlike more traditional methods, the unit 

of analysis is the relationship between 

organizations, not the organization itself. 

Network analysis allows for examination 

and comparison of the relationship between 

one organization and another (dyads), 

among clusters or cliques of three or 

more organizations, and among all the 

organizations that constitute the network 

as a whole. Depending on the type of data 

collected, it is possible to examine a range of 

issues across these organization groupings. 

Issues include the following:

n Overall level of involvement among 

organizations in the network

n Pattern or structure of involvement

n Number of other organizations to which 

any one organization is linked

n Specific organizations and types of 

organizations to which any organization 

is connected
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n Types of interactions between 

organizations (e.g., client referrals, 

shared resources, and shared 

information)

n Organizational level of the relationship 

(e.g., administrative or service level)

n Extent to which network ties are 

narrow (e.g., relationship between two 

individuals) or broad (e.g., relationships 

among multiple individuals in each 

organization)

n Extent or strength of each relationship 

(e.g., through referrals only or referrals 

and shared resources)

n Level of trust each organization has in its 

dealings with every other organization

n Perceived benefits and drawbacks of 

network involvement

Because network analysis focuses on 

relationships across and among all network 

members, once collected, data generally are 

displayed and analyzed by using a matrix 

reflecting each organization’s links with 

every other organization in the network. 

Typically, data are collected from every 

network member (e.g., agency head or 

program director) by using questionnaires 

or structured interviews. The next section 

presents details about network datacollection methods focused specifically on 

tobacco control. Monge and Contractor20

provide a more comprehensive description 

of techniques for measurement of 

communication networks.

Once network data are collected and 

analyzed, this information can be used 

in a variety of ways to assist leaders in 

understanding the structure and condition 

of the network and to facilitate strategic 

planning to strengthen the network. A recent 

publication of Provan and associates39 offers 

a series of guidelines for this process. Their 

work forms the basis of a set of practical 

research questions that are developed at the 

end of this chapter to guide the study and 

use of network analysis in tobacco control. 

Even though network analysis can be 

extremely helpful for building the “capacity” 

of a stakeholder community40,41 to address its 

most critical health needs through enhanced 

collaboration, it is certainly not a panacea. 

Network analysis is useful to demonstrate 

connections and relationships among 

agencies, reflecting the structure of the 

network. However, structure alone provides 

only a partial understanding of the reason(s) 

a network may or may not be effective. 

Networks having few and/or weak ties based 

on low trust are unlikely to be effective. 

Having many structural ties does not, in 

itself, guarantee the success of the network. 

Network goals must still be clearly established 

and collectively addressed, and effective 

network leadership is critical to the process.

Use of Network 

Methods for Tobacco 

Control

Once the applicability and value of network 

analysis are established for critical issues in 

health care, particularly within a tobacco 

control context, the question becomes one 

of defining the key issues in conducting a 

network study. What information should be 

collected? How should data be collected? What 

might be the results of data analysis? This 

section addresses these questions, focusing 

specifically on networks in tobacco control. 

The discussion is guided by knowledge of 

two emerging but very different networks 

in tobacco control—the North American 

Quitline Consortium and the Global Tobacco 

Research Network (GTRN). 

n North American Quitline Consortium. On 

February 3, 2004, the U.S. Secretary of 

Health and Human Services announced 

a plan to establish a nationwide toll-free 
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telephone number (1-800-QUIT NOW) 

that will serve as a single access point to a 

national network of “quitlines” (hotlines 

for obtaining help to stop smoking). 

At the time of the announcement, 38 

states had independent quitlines to 

deliver information, advice, support, and 

referrals to smokers or their surrogates. 

Telephone counselors at the Cancer 

Information Service, National Cancer 

Institute (NCI), were charged with 

providing assistance to individuals in 

states with no quitlines until those states 

could develop their own systems. The 

launch of the nationwide access number 

triggered a need for closer collaboration 

among the previously independent 

state-sponsored quitlines, which used 

different technologies, offered different 

services, and received funding and 

technical support from different sources. 

Working toward a national capacity to 

deliver quitline services will require 

collaboration among state and provincial 

health departments, quitline vendors, 

researchers, and national organizations.

n Global Tobacco Research Network. GTRN 

was started with the goal of enhancing 

research by promoting collaboration and 

partnerships, providing information, 

facilitating training, and sharing research 

tools among investigators around the 

world. The network is being developed 

around three core concepts: global 

network consolidation, global knowledge 

management, and global knowledge 

sharing. It aims to consolidate the weakly 

interlinked multisector community of 

researchers and institutions involved in 

the broad spectrum of research addressing 

the determinants, consequences, and 

control of tobacco production; promotion 

and consumption of tobacco products; 

and exposure to tobacco smoke. The NCIfunded initiative is timely, because of 

the need to implement the World Health 

Organization-sponsored Framework 

Convention on Tobacco Control, a 

framework for consistent global tobacco 

control policy and legislation.

Information Needed for Network 

Analyses

Network studies must address certain 

fundamental questions about the type of 

information to be collected—Who? What? 

How? Where? When? The question of “who?” 

is probably the most basic. It refers to 

which organizations, groups, or individuals 

are involved or should be involved in the 

network for provision of tobacco control 

services. These are the nodes of the network. 

The nodes may vary from network to 

network (e.g., from one state to another). 

Therefore, a key first step is to determine 

who is and who should be involved in the 

network being studied. For example, in the 

Quitline network, relevant organizations 

might include the following:

n Tobacco control advocacy groups

n Research groups (e.g., government 

agencies, universities, nonprofit 

organizations, and drug firms)

n Sources of funding (e.g., governments 

and foundations)

n Agencies and groups disseminating 

information

n Providers of technical services (e.g., state 

and provincial health departments)

n Providers of treatment services

n Health insurers and health maintenance 

organizations

n Mental health agencies and institutions 

treating substance abuse

The list may seem daunting at first. A 

critical problem in network analysis 

research has been to determine who 

qualifies to be included in the network 

(i.e., the problem of “network bounding”). 

Most network researchers prefer to cast a 
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relatively wide net initially—for example, 

including all organizations that might be 

involved in tobacco control in a particular 

state or region in a state quitline network. 

Once data collection begins, many of these 

organizations may “self-select” out of the 

process, informing researchers that they 

have little or no involvement in tobacco 

control efforts. In addition, the actual 

analysis of the network data ultimately 

collected determines which organizations 

are central, which are peripheral, and which 

are not involved at all.

On the other hand, researchers conducting a 

network study must be adequately informed 

before data are collected so that all relevant 

organizations are included. Decisions on 

which organizations to include and which to 

exclude from the study often are based on a 

procedure known as reputational “snowball” 

sampling. In this procedure, people who 

are known to be centrally involved in the 

network are asked to identify organizations 

and individuals active in tobacco control in 

a particular community, state, or region or 

in a certain domain of policy or research. 

This process is continued with other 

key informants until no new names are 

generated.

The second question for network data 

collection is “what?” This question involves 

more deeply examining the services offered 

by each of the types of organizations 

identified here as relevant to quitlines. 

These services are in a broad range of areas 

including but not limited to education, 

language (e.g., translation), referral, clinical 

treatment, funding, counseling, research, 

pharmacy, policy and advocacy, training 

and technical assistance, and outreach. 

These areas also may include categories 

that focus on target communities to which 

these services are offered—for example, 

low-income children in minority groups and 

older single women.

In their work in mental health, Provan 

and Milward12 identify the concept of a 

Global Network for Tobacco Control

Far too often, “silos” of information and knowledge in tobacco control exist within the borders 

of countries and organizations. To address this problem, the Global Tobacco Research Network 

(GTRN)a has evolved as a Web-based portal for linkage and knowledge sharing in the international 

tobacco control community. Current features include the following:

n Contact directories, opportunities, and event calendars related to global tobacco control

n Access to country profiles and industry documents

n Research resources ranging from youth programs to epidemiology, including both 

source materials and presentations

n A searchable database of tobacco control literature

n Employment and learning opportunities

n An ambitious Tobacco Atlas of statistics and information

n A Research Assistance Matching project linking researchers in developing countries 

with appropriate experts in the network

GTRN is administered by the Bloomberg School of Public Health, Johns Hopkins University, 

Baltimore, Maryland, with a technology infrastructure provided by GLOBALink. GTRN itself operates 

in a network environment, through the governance of a steering committee. Members include NCI, 

the American Cancer Society, and tobacco control research and advocacy organizations.

a

Global Tobacco Research Network. 2006. Web site. http://www.tobaccoresearch.net.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

“service implementation network,” which 

is highly relevant here. This concept refers 

to involvement of parts of an organization, 

rather than the entire organization, in a 

program effort. In tobacco control, the 

organizations identified by answering the 

question “who?” may be only partially 

involved in tobacco control, through a 

single service, or they may provide multiple 

tobacco control services. In either case, 

to understand fully how the network is 

structured and operates, it is essential to 

collect data on services, not just data on 

organizations.

This concept helps to provide a better 

understanding of the importance of the 

“what?” question. In most states or cities, 

for example, a public health department 

manages many programs, including but 

certainly not limited to tobacco control. 

Thus, the connection of a public health 

department to 10 other agencies has 

relevance to tobacco control only if the 

connection is based on tobacco control 

services and activities. Furthermore, it is 

critical to know whether the department 

is involved in only one aspect of tobacco 

control efforts or in multiple aspects. Thus, 

to know that a public health department 

is a node in a state quitline network may 

be interesting, but only a more thorough 

understanding of the network reveals its 

value to tobacco control efforts. Some 

examples are presented here.

n The public health department in one state 

may be linked to other organizations in 

the quitline network through funding, 

treatment, referrals, and technical 

support. In contrast, in another state, 

the department may be linked to the 

same number of other quitline network 

organizations, but solely through the 

technical support it provides. This 

difference in level of involvement may 

be critical for explaining why the first 

network is effective and the second is 

struggling.

n By obtaining a full range of specific types 

of tobacco control services, it is possible 

to tell, for example, how certain types of 

services and activities are clustered in 

the network, if certain types of services 

and activities are underrepresented or 

are being duplicated, and which other 

organizations’ network members might 

seek to acquire needed advice, expertise, 

and treatment for clients.

n In the case of GTRN, knowledge of which 

organizations are involved in the network 

and the types of information that are 

differentially exchanged would help to 

reveal the pattern of knowledge transfer 

among different types of members (e.g., 

health agencies and research centers) 

and whether such patterns differ across 

geographic regions.

The third question for network data 

collection is “how?” This question refers 

to the type and frequency of network 

relationships. These may be either formal 

or informal and ongoing or intermittent. 

Formal relationships are specifically 

constructed with a strategic purpose in 

mind. Examples are joint programs, funding 

contracts, and memoranda of agreement. 

Most of these relationships are established by 

organizational directors and administrators, 

and they tend to be governed by enforceable 

contracts and/or operating guidelines.

Such relationships may be highly 

cooperative and may be used to solidify the 

ties between two or more organizations. 

On the other hand, the relationship may 

be somewhat distant (at arm’s length) and 

may involve considerable monitoring. 

The formal relationships described 

here are mostly ongoing, because they 

typically establish the framework for a 

relationship that occurs regularly over an 

extended period. More intermittent formal 

relationships might include meetings 

among network members. Such meetings 

would be formalized to ensure that network 
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

members have a specific opportunity to 

share ideas, concerns, or issues with each 

other. However, such meetings generally 

would occur only occasionally, particularly 

when difficulties are involved in bringing all 

members together at one time or place. 

Informal relationships also are common. 

They represent the real “glue” that holds 

any network together. Ring and Van de Ven42

discuss the relationship between formal 

and informal aspects of interorganizational 

relationships. If network members are 

bound together only through formal 

mechanisms, they frequently do not develop 

the trust that enables a network to operate 

effectively as a network, as opposed to a 

loose collection of organizations with a more 

or less common goal. Informal relationships 

also can be ongoing or intermittent. 

However, like any social relationship, the 

less frequently the tie is used, the more 

likely the relationship is to dissolve.

The most common type of informal 

relationship is likely to be shared 

information. Information can be shared 

through channels such as e-mail, telephone 

calls, and personal meetings. Many of these 

activities may initially be based on friendship. 

Yet, when people try to construct a viable 

network to improve health outcomes, the 

evolution of informal ties can be encouraged 

through use of more formal mechanisms 

such as electronic mailing lists and 

conferences. GTRN provides a good example 

of how ties based on informal information 

sharing can be encouraged and formalized 

to establish a mechanism for building 

global understanding of research on tobacco 

control. The mechanism itself has been 

formalized. However, the flow of information 

on research and policy is informal, based 

on the needs, interests, and expertise of 

the network members operating in many 

different countries throughout the world.

In the area of services delivery, an important 

additional source of informal relationships 

is client referrals. Referrals typically are 

based on an informal understanding among 

organizations that clients/patients can be 

served most effectively through the efforts of 

multiple, interconnected providers. In tobacco 

control, this might mean that a patient 

enters the system through a quitline but is 

referred to several other agencies for services 

such as treatment, counseling, or education. 

Each agency involved is part of a knowledge 

network and therefore has a more or less 

accurate understanding of the expertise 

and capacities of the other organizations in 

the network. Each agency refers patients 

accordingly, on a trust-based assumption that 

other agencies in the knowledge network will 

do their part to help the patients. 

The fourth question is “where?” This 

question refers to the location of the 

levels of involvement that constitute a 

network. Essentially, networks can form 

either vertically or horizontally, and often 

both forms are involved. Vertical networks 

might include relationships between 

organizations operating at the community 

level and those operating at the state or 

provincial level. They could also include 

the interactions between state and national 

organizations or between community and 

national organizations. Vertical networks 

are frequently formal, involving ties between 

funding sources and recipients, technical 

service ties, and connections between policy 

formulation and implementation.

Horizontal relationships are network ties 

that occur within a community, state, 

province, or nation, or internationally, 

as is the case with GTRN. Horizontal 

relationships can be formal or informal. 

Informal, trust-based ties usually make up 

a large part of most successful horizontal 

networks. At the same time, however, the 

network could have a formalized governance 

structure, designed to facilitate network 

collaboration and interactions, attract 

funding, and act to resolve conflicts. 

Horizontal relationships are most common 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

when organizations recognize the need 

to cooperate to achieve common goals 

and interests. However, the services and 

activities they perform are complementary, 

rather than competitive.

The fifth and final question is “when?” 

The vast majority of research on networks 

is cross-sectional, focusing only on data 

collected at one point in time. However, 

networks are constantly evolving as new 

organizations enter and old ones leave 

and as network members change their 

partners and mode of interaction. The 

theorizing42,43 and limited longitudinal 

research on network evolution clearly 

point to differences in the ways in which 

relationships develop.44 Identifiable 

stages of evolution are even suggested, 

from initial formation and early growth, 

through maturity, to sustainability or 

ultimate demise.31 When data are collected 

from multiple networks, caution must be 

exercised so comparisons are made only 

across networks at relatively similar stages 

of development. In addition, network 

data collected at one point in time should 

be interpreted with the knowledge that 

conclusions drawn may be unique to that 

particular stage of network evolution. 

To summarize, in studies of networks in 

tobacco control, five types of data are needed 

for full understanding of network structure 

and processes. 

n “Who?”—Which organizations are and 

should be involved in the network?

n “What?”—What specific services and 

activities are exchanged by each network 

member?

n “How?”—How are relationships among 

network members constructed (i.e., what 

types of ties)? How frequently do these 

relationships occur?

n “Where?”—Where do the relationships 

among network members occur? Do 

these relationships involve vertical and/or 

horizontal ties?

n “When?”—When do different kinds of 

network relationships develop? How do 

they change over time? 

Conducting Research on 

Tobacco Control Networks

Despite the lack of previous research on 

tobacco control networks, the case made 

thus far is that networks offer valuable 

mechanisms for building the strength of the 

tobacco control system at multiple levels 

(i.e., community, regional, national, and 

international). However, to maximize the 

impact and benefit of networks, one must 

fully understand them both conceptually 

and analytically. Thus, network analysis 

can be a powerful and important tool for 

strengthening tobacco control efforts. 

The previous section discusses types of 

information needed to conduct such 

an analysis. Details of data collection 

are presented here. Again, discussion of 

methods focuses on the quitline networks 

and GTRN. 

The quantitative analysis of organizational 

networks is not more common in health 

care in general and in tobacco control 

in particular for two reasons. First, most 

social scientists are trained in traditional 

data-collection methods, especially 

random sampling and data analysis 

with use of inferential statistics. These 

methods generally are not appropriate for 

network analysis, although more and more 

researchers have become familiar with 

network methods in recent years. Second, 

network analysis is not more common 

because the research can be costly and 

time consuming. This is true especially if 

data are collected over multiple periods, 

across multiple networks, and using both 

quantitative and qualitative methods. This 

sort of research is critical for advancing 

knowledge about the operation and 
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

evolution of networks, and it can contribute 

to the solution of complex health problems. 

Typically, little or no data are available from 

secondary sources on relationships between 

and among organizations involved in a 

network, except perhaps through formal ties 

such as contracts. As a result, most network 

data must be collected from primary 

sources. Longitudinal data collection 

performed across multiple networks 

requires large-scale grant funding from 

federal agencies or private foundations.

In view of the importance and prevalence of 

networks in most areas of health, the time 

has come to apply what is known about 

both the theory and methods of networks 

to help strengthen tobacco control efforts. 

To that end, a number of sequential steps 

can be followed to collect the data described 

in the previous section. The approach 

used by Provan and colleagues14,31,45,46 in 

multiple network studies is outlined here, 

but it can be adapted for use in a variety of 

settings. Presentation of this comprehensive 

approach is followed by several more 

streamlined alternatives that can be used if 

time and cost considerations are paramount. 

n Select the network(s) that will be the 

focus of investigation (e.g., quitline 

networks, GTRN, or national networks for 

tobacco control policy).

n Ascertain whether the study focus will 

be a single network (i.e., the quitline 

network or GTRN) or comparison of 

multiple networks with similar focus—

that is, a study examining and comparing 

networks of researchers in each of the 

Transdisciplinary Tobacco Use Research 

Centers, based at eight major universities 

across the United States.

n Talk with key network leaders to build 

an initial understanding of what the 

network is doing, which organizations 

are involved, and at which levels (e.g., 

community, regional, or national; see 

“where?” question in previous section). 

n Try to determine the types of involvement 

critical to the network (see “what?” 

question)—for example, patterns of 

information sharing or research capacity 

in GTRN or referrals, contracts, shared 

information, or technical support 

for quitline networks. The “how?” 

question also may be addressed at this 

point, especially to limit the types of 

involvement to be studied—for example, 

deciding not to consider intermittent 

referrals.

n Develop an inclusive list of network 

organizations that use “reputational” 

sampling techniques (see “who?” 

question). Reputational sampling19,47 is an 

iterative process relying on cumulative 

knowledge of network participants about 

who is involved in the network. The 

procedure starts with questioning those 

who are presumed to be the most central 

network members and then moving 

outward, depending on who is named.

n Determine (e.g., through telephone calls) 

the key individuals at each organization 

who are most likely to be knowledgeable 

about the network activities and 

involvement of their organization. 

Decide whether only one or several of 

these “key informants” should provide 

data on the network involvement of 

their organization. Because individuals 

in the same organization, especially 

a large organization with diverse 

services, often interact with outside 

organizations, responses of multiple 

informants about network involvement 

should be aggregated to form a single 

organizational response. Some of these 

key informants may have helped to define 

the network initially (i.e., the “who?” 

question). However, in the absence of 

objective data on which organizations 

are included in the network (e.g., an 

official membership list) or on specific 

network activities and ties, some 

cross-contamination is likely to be 

unavoidable.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

n Develop broad cooperation and support 

from network participants for conducting 

the network analysis. If possible, make 

one or more presentations to the 

members of each network studied, 

demonstrating the type of data to be 

collected; how data will be collected; 

what is expected of them as respondents; 

how results will be reported to them;39

and how the findings might be used to 

strengthen tobacco control efforts for 

their organization, their network, and 

other tobacco control networks.

n To achieve the best response rate, 

obtain one or more letters of support/

endorsement of the study from the most 

important and/or influential network 

members, especially from key funding 

agencies such as NCI or the Centers for 

Disease Control and Prevention (CDC).

n Create a survey instrument that addresses 

who, what, how, and where and that 

provides sufficient information to develop 

a comprehensive understanding of the 

network (see list in previous section on 

“Application of Network Analysis”). One 

member of the Initiative on the Study and 

Implementation of Systems (ISIS) team14

recently used this questionnaire in a study 

of a broad-based community coalition 

addressing chronic disease prevention 

and treatment. The organizations in 

the network are listed on the survey, so 

that every organization responds to an 

identical and complete list of network 

participants. Additional questions can and 

should be added to obtain specific data on 

individual organizations and respondents. 

Such data might include organizational 

funding, involvement with tobacco 

control relative to other health issues, 

types of services offered, and perceptual 

indicators of network effectiveness.

n Send the survey by mail or e-mail, along 

with letters of support and a cover letter 

explaining the project, to all network 

organizations and potential respondents. 

The survey can be Web based or 

handwritten. If it is mailed, include a 

postage-paid return envelope. 

n One week after mailing, follow up with 

a telephone call to each respondent and 

discuss receipt of the survey and any 

questions about completion. Continue 

follow-up by telephone call and/or 

e-mail weekly or every other week, until 

further efforts seem fruitless. Aim for 

approximately 80%–90% response. 

Dillman48 reviews effective general survey 

methods using both mail and telephone.

n Depending on the number of networks 

studied, the size of each network, and 

budget constraints, visit each site 

shortly after the survey is mailed and 

interview as many network members as 

possible, especially those who are most 

heavily involved. If the survey form has 

not been completed, go through the 

questionnaire during the interview to 

maximize the response rate and discuss 

in-depth perceptions and attitudes about 

network involvement to help provide 

a rich contextual understanding of the 

operation and evolution of the network 

and its goals.

n Obtain all key available secondary 

data relevant to the study, including 

contextual data such as differences in 

tobacco use and tobacco control funding 

across networks, if multiple networks 

are being compared. Ideally, multiple 

outcome indicators also would be 

available for comparison with networklevel measures over time.

n Code, analyze, and interpret all 

network data. Decide whether to use 

symmetrical and confirmed network 

data, symmetrical and unconfirmed 

network data, or both for the analysis. 

Unconfirmed data are the raw survey 

results for network involvement, based 

on the reports from each organization in 

the network. Confirmed data, validated 

against parties listed in the survey 
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responses, are considered to be far more 

reliable if the goal of the research is 

to establish the existence of links in 

the absence of objective data. In the 

absence of symmetry and confirmation, 

unconfirmed data can be used. These 

data can provide potentially valuable 

information on “weak tie” relationships.49

In addition, asymmetrical ties may 

be desired to reflect certain types of 

links, such as when trying to determine 

reputation or network influence (i.e., who 

lists whom as most influential).

n Report baseline network findings within 

each network studied and across multiple 

networks to network participants and 

key officials involved in tobacco control 

policy.

n Repeat the data-collection process 

after about 12–18 months and/or after 

a significant event that might alter 

network activities and structure in 

major ways (see “when?” question). 

Data should be collected at least twice 

and preferably three times to enable 

thorough understanding and explanation 

of network evolution and progress. Code, 

analyze, and interpret the results from 

all data-collection efforts, and compare 

findings within and across networks over 

time. Compare network data with tobacco 

control outcomes.

As noted previously, this data-collection 

method is extremely thorough and will 

provide an in-depth understanding of network 

structures and processes in tobacco control. 

Conducting this sort of data collection is 

highly recommended, but budget and time 

constraints may limit what is possible. To 

accommodate these constraints, the approach 

can be streamlined in several ways. Several 

alternatives to the full-blown data-collection 

effort are listed below.

n Use a limited procedure for reputational 

sampling. Identification of most network 

organizations can usually be obtained 

from a subgroup of the members of 

the full network, especially those who 

are most heavily involved in and most 

knowledgeable about the network. 

Caution should be exercised here, 

however, because this approach tends to 

underidentify network members who are 

not well connected.

n Conduct a partial network analysis 

by focusing only on a limited set of 

organizations that most informants believe 

to be the key network members. This 

approach might involve collecting data 

from 20–25 organizations versus 50–75 

or more in the full network. Connections 

among the subsets of network agencies 

can be confirmed because they would 

report their links to one another. 

Connections to the larger network could 

still be reported, but these links would not 

be confirmed, providing a somewhat less 

reliable picture of the full network.

n Collect data from a small number 

of networks. This approach limits 

generalizability but can still produce 

valuable information on network “best 

practices” if the networks studied are 

carefully selected. For example, two or 

three quitline networks in states with 

well-established programs could be 

compared with two or three quitline 

networks in other states in which the 

program is just getting started. Another 

option is to study GTRN in two or three 

regions, comparing network structures 

and patterns of involvement.

n Limit the number of types of network 

involvement to only the two or three 

most important ones (e.g., resource 

sharing, information sharing, and 

referrals).

n Collect data on network involvement 

only from a single key informant at each 

organization, rather than using multiple 

informants. Single informants can be 

asked to check with other organizational 

members to ensure that survey 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

responses reflect the organization’s

network and not just the respondent’s 

network.

n Do not conduct interviews with network 

members. Limit network visits to one or 

two before data collection and one visit 

later to present and discuss findings. 

Substitute on-site interviews of most 

network members with telephone 

interviews as part of the survey followup process. Use of limited interviews is 

especially appropriate when multiple 

networks are compared or when network 

members are scattered geographically 

across a wide area, as with GTRN.

n Examine network evolution across two 

time periods only (instead of three or 

more), and conduct data collection at 

two-year intervals.

The information collected from either of 

these approaches can be used to develop 

an exercise for mapping network assets for 

the development, deployment, analysis, 

redesign, and simulation of networks.

Case Study of Network 

Analysis in Tobacco 

Control Evaluation 

As a case study of network analysis in 

tobacco control, a project headed by Doug 

Luke of Saint Louis University, Missouri, 

is examined here. The project, performed 

in 2004, shows how the technique can be 

used as part of the process evaluation of 

tobacco control programs. Evaluation of the 

tobacco control process typically focuses on 

“counting” activities. Program evaluation 

includes determination of factors such as 

the amount of funding, numbers and types 

of prevention activities, and the number 

of countermarketing advertisement spots 

aired. This type of evaluation of local and 

state tobacco control programs ignores 

the complexity of the systems of agencies, 

organizations, and people who coordinate 

activities to achieve a common goal of 

reducing the health burden of smoking and 

tobacco use.

A state comprehensive tobacco control 

program typically consists of a lead agency 

directing tobacco control funds to a series of 

state and local contractees. The lead agency 

also coordinates activities with voluntary 

agencies such as the American Cancer 

Society (ACS) and the American Lung 

Association (ALA). State and local coalitions 

provide guidance and outreach. Finally, a 

state program may include other types of 

partners, including public relations firms, 

local law enforcement agencies, or state 

attorney general offices. Network analysis 

is an analytic tool that is particularly 

appropriate for evaluating state tobacco 

control programs by using this type of 

systems perspective. The purpose of this case 

study is to show how network analysis is 

being used in an ongoing multistate project 

to evaluate tobacco control programs. 

Collection of Network Data from 

State Tobacco Control Programs

The network analysis data reported here 

came from two large-scale multistate 

projects to evaluate tobacco control 

programs. These projects were conducted 

by the Center for Tobacco Policy Research, 

Saint Louis University School of Public 

Health,50 and were funded by the American 

Legacy Foundation and the Chronic 

Disease Directors Association. The primary 

goals of these process evaluation studies 

were to assess (1) the implementation 

of CDC guidelines for Best Practices for 

Comprehensive Tobacco Control Programs51

by state tobacco control programs, and 

(2) changes in state programs in response to 

massive cuts in funding.

The network analysis data were collected 

to facilitate understanding of the 
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

structure of these complex state tobacco 

control programs, to identify other state 

characteristics related to program structure, 

and to determine whether changes in 

program funding and political support 

are associated with changes in program 

structure. The network analysis had three 

phases: network delineation, network data 

collection, and network analysis.

As discussed here, network delineation is 

the process of defining and identifying the 

network. In this case, the manager of the 

state tobacco control program was asked to 

identify every agency partner that played a 

critical role in planning and implementing 

the state tobacco control program. A 

modified snowball sampling approach 

was used to complete the list of program 

partners by contacting members on the 

initial list and asking whether any important 

partners had been omitted from the list. For 

the states evaluated in 2002, the tobacco 

control networks typically ranged from 14 to 

17 partners. In addition to the lead agency 

(usually the state health department), the 

other commonly observed types of program 

partners included regional coalitions (in 

all 10 states), statewide coalitions (9 of 10 

states), contractees (10 states), ACS (10 

states), ALA (7 states), and the American 

Heart Association (6 states).

Once the network for each state was defined, 

an expert informant from each network 

partner agency was asked to participate 

in the study. In the network analysis, 

four primary pieces of relational network 

information were collected: (1) funding 

relationships among partners, (2) frequency 

ISIS Examines Its Own Network

To bring home the concepts of network analysis for ISIS members, a short proof-of-concept 

exercise was performed before a summit meeting in the Washington, DC, area in January 2004.

A questionnaire was designed and distributed to the meeting participants, who represented 

government agencies such as NCI and CDC, tobacco control research and advocacy organizations, 

and academic institutions. Each stakeholder was asked eight questions. The questions included 

requests for identification of their greatest needs and desired future interactions and other 

organizations with which they had financial, professional, or networking interactions.

Network involvement was analyzed based on these responses by using the Inquiring Knowledge 

Networks On the Web system from the University of Illinois at Urbana-Champaign. This system 

is a Web-based environment for conducting network analyses. Network results were illustrated 

graphically by using a series of network plots reflecting which organizations were linked and the 

ways in which they were linked. (See network on facing page.)

Within a very small nonrepresentative sample, this exercise nonetheless provided the ISIS 

stakeholders with a good overview of many of the network concepts discussed in this chapter, 

including centrality, cliques, and referral networks. More important, it served as a catalyst for 

productive dialogue between experts in networks and other disciplines, with an eye toward 

integrating network methods as part of a broader systems approach to tobacco control.

Note. TTAC = Tobacco Technical Assistance Consortium; U of Wisc = University of Wisconsin; ACS = American 

Cancer Society; TTURC = Transdisciplinary Tobacco Use Research Center; RWJF = Robert Wood Johnson 

Foundation; CTC = Center for Tobacco Cessation; CDC = Centers for Disease Control and Prevention; CFTFK 

= Campaign for Tobacco-Free Kids; Legacy = American Legacy Foundation; NCI = National Cancer Institute; 

SDSU = San Diego State University; JHSPH = Johns Hopkins School of Public Health; IGTC = Institute for 

Global Tobacco Control; RTI = Research Triangle Institute International; Uni of IL Chi = University of Illinois 

at Chicago; ORI = Oregon Research Institute; SAMHSA = Substance Abuse and Mental Health Services 

Administration.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

of contact, (3) degree of cooperation, 

and (4) perceived importance of network 

partners in achieving state tobacco control 

goals. The next section presents results from 

the question on frequency of contact.

Information Learned about 

Tobacco Control Program 

Networks

A primary purpose of the evaluation of state 

tobacco control programs was to explore 

the influence of state financial and political 

climates on the structure and processes of 

tobacco control programs. Financial and 

political climate ratings were produced for 

each state according to a number of criteria. 

States were seen as having a positive 

financial climate for tobacco control if they 

(1) were meeting CDC recommendations for 

the amount of money budgeted for tobacco 

control, (2) had relatively high levels of per 

capita spending on tobacco control, (3) had 

set a high excise tax on cigarettes, and 

(4) had not securitized funding from the 

Master Settlement Agreement. States were 

rated as having a positive political climate 

if they had (1) multiple tobacco control 

“champions” in positions of authority and 

influence, (2) support for tobacco control 

from the governor, (3) support for tobacco 

control from the legislature, and (4) a low 

tobacco industry presence in the state. The 

Network Connectivity from ISIS Exercise

SmokeLess States

TTAC

ACS

U of Wisc

SAMHSA

IGTC

Boston Public Health

Pinney Associates

JHSPH

ORI

SDSU

RTI

Uni of IL Chi

CTC

TTURC

CDC

RWJF

CFTFK

Battelle Roswell

Legacy

NCI
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6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

ratings for political and financial climates 

were combined in a summary scale that 

could range from –9 to +9. Table 6.1 shows 

the ratings for the states evaluated in 2002. 

During this time, Indiana, Mississippi, and 

Hawaii had relatively positive climates 

for tobacco control. However, Wyoming, 

Michigan, Oklahoma, and Missouri had 

more challenging environments. 

To determine whether political or financial 

climate was related to network structure, 

the contact networks for each state were 

examined. The contact networks for Indiana 

and Mississippi, two states with relatively 

positive climates, are shown in figure 6.1. 

A link connects two partners if they have 

contact with each other at least once per 

month. Contact is defined broadly and 

includes face-to-face meetings, telephone 

conversations, and e-mail. Examination 

of this network reveals which partners 

are more centrally located in the contact 

network and which are more peripheral. For 

example, the Indiana Tobacco Prevention 

and Cessation Agency (ITPC) is the lead 

agency for Indiana, and it has frequent 

contact with all 14 other network members. 

Boys and Girls Clubs (B&G Clubs), on the 

other hand, meets only monthly with three 

of the network members. Thus, ITPC plays 

a more central role in the communication 

network in the Indiana tobacco control 

program. This result can be measured 

more formally by calculating Freeman’s 

betweenness centrality—the measure of how 

often a particular network member lies “in 

between” any two other network members, 

linking members who are not directly 

connected.52

A high score for betweenness centrality 

indicates a node that is central in a network 

and can be considered to be a gatekeeper or 

controller of information. In the network 

figures here, nodes with the highest scores 

for betweenness are colored purple and 

nodes with the lowest scores are colored 

yellow. For both Indiana and Mississippi, the 

agency with the greatest centrality is the 

lead agency for the state tobacco program. 

Finally, the centrality for an entire network 

can be assessed with the centralization 

index. This index is calculated by summing 

the differences between all centrality scores 

and the maximum centrality score. The 

scores for Indiana and Mississippi are both 

higher than 20%. This finding indicates 

a moderate amount of communication 

hierarchy—that is, both networks have a few 

highly central nodes and many peripheral 

nodes.

The contact networks for Michigan and 

Oklahoma, two states with much poorer 

Table 6.1 Ratings of Political and Financial Climates for 10 States in 2002

State Political support Financial support Total score

Indiana Very strong Strong +5

Mississippi Very strong Strong +4

Hawaii Strong Very Strong +4

Pennsylvania Moderate Strong +2

Washington Strong Moderate 0

New York Moderate Moderate –1

Wyoming Challenging Strong –3

Michigan Challenging Moderate –3

Oklahoma Challenging Challenging –5

Missouri Challenging Challenging –9
173

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Figure 6.1 Contact Networks for Two States with Strong Financial and Political Climates 

(Indiana, left; Mississippi, right)

DOH

ITPC

ACS AHA

TS IN

SFAC

MC TCP

IMHC

Latino Inst

Black Expo

B&G Clubs SF IN

ITPC Board

MZD ISMA

Partnership

ACS

ALA Alliance

Coahoma

Attala

U. Medi U. of S. Miss. cal

IQH

Frontline

MS DOH AG

NOT HERE

Scouts

MWB

Jackson

Warren/Claiborne

Notes. Indiana (left) had a centralization index of 22.7%, and Mississippi (right) had a centralization index of 20.5%. ITPC = Indiana 

Tobacco Prevention and Cessation Agency; TS IN = Tobacco Smart Indiana; MC TCP = Marion County Tobacco Control Program; 

ACS = American Cancer Society; AHA = American Heart Association; B&G Clubs = Indiana Alliance of Boys and Girls Clubs; 

Latino Inst = Indiana Latino Institute; SF IN = Smokefree Indiana; MZD = MZD Advertising; ISMA = Indiana State Medical 

Association; DOH = Indiana State Department of Health; SFAC = Smokefree Allen County; Black Expo = Indiana Black Expo; 

IMHC = Indiana Minority Health Coalition; U. Medical = University Medical Center; U. of S. Miss. = University of Southern 

Mississippi; IQH = Information and Quality Healthcare; Scouts = Girl Scouts of Gulf Pines; Jackson = Partnership for a Healthy 

Jackson County; AG = Attorney General’s Office; Partnership = Partnership for a Healthy Mississippi; MS DOH = Mississippi 

State Department of Health; MWB = Maris, West & Baker; Alliance = Mississippi SmokeLess States Alliance; ALA = American 

Lung Association; Warren/Claiborne = Partnership for a Healthy Warren/Claiborne Counties; Frontline = Frontline State Board; 

Coahoma = Partnership for a Healthy Coahoma; Attala = Partnership for a Healthy Attala.

Figure 6.2 Contact Networks for Two States with Weak Financial and Political Climates 

(Michigan, left; Oklahoma, right)

MDCH TS

ACS

AHA

ALA

TFMAC

Marquette

Wayne

Cristo

Gerontology

FACED

Genesee

CTUPR

Law & Policy

U of M Health

TUPS

ACS

ALA

Alliance

NE Coalition

SW Coalition

OSMA

TulsaHD

PWorkz

UofO

Latino

OICA Trust

Notes. Michigan (left) had a centralization index of 10.4%, and Oklahoma (right) had a centralization index of 6.6%. FACED = Faith 

Access to Community Economic Development Corporation; Cristo = Cristo Rey Community Center; TFMAC = Tobacco Free 

Michigan Action Coalition; Genesee = Genesee County Smokefree Multi-Agency Resource Team; ACS = American Cancer Society; 

ALA = American Lung Association; MDCH TS = Michigan Department of Community Health, Tobacco Section; Wayne = Wayne 

County Smoking and Tobacco Intervention Coalition; Gerontology = Center for Social Gerontology; U of M Health = University of 

Michigan Health System; AHA = American Heart Association; Law & Policy = Tobacco Control Law & Policy Consulting; Marquette 

= Marquette County Tobacco-Free Coalition; CTUPR = Center for Tobacco Use Prevention and Research; OICA = Oklahoma 

Institute for Child Advocacy; Trust = Tobacco Settlement Endowment Trust; UofO = University of Oklahoma Health Sciences 

Center; Latino = Latino Agency; SW Coalition = Southwest Tobacco Free Oklahoma Coalition; TUPS = Oklahoma State Department 

of Health Tobacco Use Prevention Service; OSMA = Oklahoma State Medical Association; Alliance = Oklahoma Alliance on 

Health or Tobacco; TulsaHD = Tulsa City-County Health Department; NE Coalition = Northeast Tobacco Free Oklahoma Coalition; 

PWorkz = PreventionWorkz.
174

6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

Figure 6.3 Role of Informal Interactions in Referral Patterns

TTAC

TTURC

Legacy

RTI

ACS

SmokeLess States CDC

Ctr. for Tob. Ctrl.

Roswell Park

CFTFK Battelle

Boston Pub. Hlth.

Chicago

Uni. IL

RWJF

NCI

Notes. TTAC = Tobacco Technical Assistance Consortium; ACS = American Cancer Society; Legacy = American Legacy Foundation; 

TTURC = Transdisciplinary Tobacco Use Research Center; RTI = Research Triangle Institute International; Ctr. for Tob. Ctrl. = Center 

for Tobacco Control; CDC = Centers for Disease Control and Prevention; RWJF = Robert Wood Johnson Foundation; Boston Pub. 

Hlth. = Boston Public Health; Uni. IL = University of Illinois; NCI = National Cancer Institute; CFTFK = Campaign for Tobacco-Free 

Kids.

climates for tobacco control, are shown in 

figure 6.2. One difference between these 

two networks is that instead of having only 

one highly central agency, each state has 

three central agencies, again indicated by 

purple nodes. For example, in Oklahoma, 

the Latino Agencies (Latino) and ACS join 

the lead agency, the Tobacco Use Prevention 

Service (TUPS), and are collectively the 

most central nodes in the state network. The 

low network centralization indices (10.4% 

for Michigan and 6.6% for Oklahoma) also 

show that these networks have a much more 

active communication structure than was 

seen for Indiana and Mississippi. 

The preliminary interpretation of these 

patterns is the presence of a relationship 

between financial and political climates 

and structures for communication about 

tobacco control. The hypothesis is that lead 

agencies in states with positive financial 

and political climates have the financial and 

political resources that allow them to take a 

strong leadership role in the tobacco control 

program. Conversely, in states that have 

poor climates, lead agencies no longer have 

these resources, and thus no longer are the 

most central agencies in the programs. In 

fact, a process of network adaptation may be 

in effect. When funds and support are scarce, 

tobacco control agencies may reconfigure 

their relationships to ensure sustainability 

of the program. In a sense, they may be 

“sharing the load” when times are tough.

This relationship is apparent for all 10 states, 

as evidenced by a fitted linear regression 

line and a smoothed local regression curve 

(locally weighted scatterplot smoother) 

(figure 6.3).53 In addition, the relationship 

between the financial and political climates 
175

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

for tobacco control and the communication 

structure is moderately positive. The more 

positive the climate, the more hierarchical is 

the communication network (r = .32).

Because of the small number of states 

considered in the calculations, these 

interpretations must necessarily be 

tentative. However, a second phase of the 

state evaluation project allowed longitudinal 

examination of this hypothesis. In 2004, 

eight state tobacco control programs 

were evaluated, including a return visit to 

Indiana. Between the two evaluation periods, 

there was major upheaval in the Indiana 

program. The tobacco control program 

lost approximately one-half of its funding 

(figure 6.4). In addition, the state had a new 

governor who was perceived as being much 

less supportive of tobacco control (figure 

6.5). Consequently, Indiana had a much 

more challenging financial and political 

climate for tobacco control in 2004 than it 

had in previous years. The communication 

networks for both 2002 and 2004 are shown 

in figure 6.6. The tobacco control network 

is the same size in 2004, but it has a very 

different structure. The centralization index 

is much lower (decrease from 23% to 13%). 

This finding indicates a communication 

structure that is more active. At the same 

time, the density has increased from 49% to 

59%. Density is the proportion of observed 

ties to possible ties. The higher density 

indicates that more of the agency partners 

talked to each other directly in 2004. Thus, 

there has been a shift in Indiana—as the 

climate worsened, the network apparently 

adapted by “flattening” the communication 

structure and increasing the amount of 

direct contact. This change over time is 

consistent with the hypothesis that state 

climates influence structures of the state 

tobacco control program.

Network Research Questions 

for Tobacco Control, Discovery, 

Diagnosis, and Design 

The research described above provides an 

example of how network analysis can be 

conducted in a tobacco control context, but 

it is highly descriptive. Based on research 

like this, however, network leaders can 

use findings to help build and strengthen 

Figure 6.4 Change in Tobacco Control Program Funding for Indiana from 2002 to 2004

Rollover from

previous FY

American Legacy

Foundation

CDC OSH

MSA

40

35

30

25

20

15

10

5

$0

Dollars (millions)

2002 2004

Notes. FY = fiscal year; CDC OSH = Centers for Disease Control and Prevention, Office on Smoking and Health; MSA = Master 

Settlement Agreement.
176

6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

their network. Recent work by Provan 

and colleagues39 was discussed earlier in 

this chapter. These researchers proposed 

a series of questions that might be asked 

by network leaders and participants to 

guide their efforts in translating network 

data into practice. In addition, Contractor 

and colleagues54 at the “collaboratory” 

of Science of Networks in Communities 

at the University of Illinois at UrbanaChampaign have proposed an innovative, 

high-risk, high-payoff strategy for basic 

Figure 6.6 Change in Indiana’s Tobacco Control Contact Network Structure from 2002 (left) to 

2004 (right)

DOH

ITPC

ITPC Board

ACS

AHA

TFK

SFMC

Bartholomew

MZD

B&G of IN

St. Joseph

SF IN

IU School of Med

Latino Inst

MHP

DOH

ITPC

ACS AHA

TS IN

SFAC

MC TCP

IMHC

Latino Inst

Black Expo

B&G Clubs SF IN

ITPC Board

MZD ISMA

Size 15 Size 15

Density .49 Density .59

Centrality .23 Centrality .13

Notes. Bartholomew = Bartholomew County; St. Joseph = St. Joseph County; ITPC = Indiana Tobacco Prevention and Cessation; Latino 

Inst = Indiana Latino Institute; MZD = MZD Advertising; DOH = Indiana State Department of Health; B&G of IN = Indiana Alliance 

of Boys and Girls Clubs; AHA = American Heart Association; TFK = Tobacco Free Kids; SF IN = Smokefree Indiana; MHP = Madison 

Health Partners; SFMC = Smokefree Marion County; IU School of Med = Indiana University School of Medicine; ACS = American 

Cancer Society; TS IN = Tobacco Smart Indiana; MC TCP = Marion County Tobacco Control Program; ISMA = Indiana State Medical 

Association; SFAC = Smokefree Allen County; IMHC = Indiana Minority Health Coalition; Black Expo = Indiana Black Expo.

Figure 6.5 Change in Perceived Political Support for Tobacco Control from Two Indiana 

Governors, Governor Frank O’Bannon (2002, left) and Governor Joseph Kernan 

(2004, right)

Bioterrorism

Medical Care

Maternal & Child Health

Tobacco Control

Mental Health

Environmental Health

Bioterrorism, Medical Care

Maternal & Child Health

Tobacco Control

Environmental Health, Obesity & Physical Activity

Mental Health

0.5

1.0

1.5

2.0

Relative ranking

0.5

1.0

1.5

2.0

Relative ranking
177

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

network research and its transfer to the 

practice of enabling networks within various 

communities. They refer to it as the “3D”—

discovery, diagnosis, and design—model.

Drawing on ideas from both groups of 

researchers, this chapter proposes a series 

of questions that can guide the development 

of research on tobacco control networks. In 

addition, the questions proposed have a very 

practical orientation, demonstrating how 

network leaders and policy officials might 

use network analysis in tobacco control. 

The questions are organized around the 

concepts of discovery, or learning about 

who is connected to whom; diagnosis, or 

analyzing network relationships; and design, 

which involves application of findings 

to build, maintain, and strengthen the 

network.

Discovery

The questions listed here are designed 

to help a community discover existing 

communication and knowledge networks. 

(If only the tobacco control network 

knew what the tobacco control network 

knows.) These questions focus on some 

ways in which network data collection can 

contribute to a deeper understanding of 

the structure of a tobacco control network. 

An important aspect of identification is 

to determine the capacity of network 

stakeholders to know “who knows what.” 

1. What specific organizations and/or 

individuals constitute a particular 

tobacco control network?

2. Are individual tobacco control 

stakeholders able to identify which 

organizations are included in the 

network and which are not?

3. Are there large differences between selfidentification of network ties and the 

reports of others in the tobacco control 

network (i.e., unconfirmed versus 

confirmed ties)? Does everyone really 

know who is connected to whom and in 

what ways?

4. Are individual tobacco control 

stakeholders able to identify others in 

the tobacco control community who 

share specific interests and areas of 

expertise so they might coalesce into a 

“community of practice”?

5. Are tobacco control stakeholders able to 

identify other key organizations and groups 

outside the tobacco control community 

that may have expertise and resources 

needed by those within the network?

6. Can tobacco control stakeholders identify 

organizations within the network that 

may have working relationships with 

these critical outside groups?

Diagnosis

Once the network has been discovered 

and identified, detailed network analysis 

methods, both qualitative and quantitative, 

are used to diagnose network structure and 

processes. They help the community to 

diagnose the “health” of the network. These 

questions focus on what specific attributes 

are normally assessed in the process of 

network diagnosis.

1. Which organizations are most central in 

the network in that they use both direct 

and indirect measures of centrality? Are 

these the organizations most essential 

for addressing client and program needs?

2. Are some network relationships 

especially strong and others weak? Is 

the relative strength of ties consistent 

with network needs for essentials such 

as information and resources? 

3. Who are the connectors, information 

brokers, and boundary spanners in the 

network who can meet network needs 

in areas such as research, funding, and 

services? Do these important roles even 

exist in the network? Do the appropriate 
178

6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

organizations and individuals occupy 

these roles?

4. Is the network broadly connected, highly 

fragmented, or divided into subgroups 

and cliques? Which specific subgroups 

of network organizations have strong 

working relationships? 

5. Is the flow of essentials such as 

information, knowledge, clients, and 

funding needed for tobacco control 

efforts being efficiently and effectively 

distributed throughout the network? 

Where are the gaps? Where are the 

redundancies?

6. Are critical network ties based solely 

on personal relationships, or have they 

become institutionalized so they are 

sustainable over time, as key individuals 

come and go?

7. Do network members have links to 

other groups and organizations outside 

the network that may be helpful to 

the full network for vital actions such 

as attracting needed resources and 

information and influencing policy?

8. How are these external ties structured? 

Are they primarily through core or 

peripheral network members? Are 

network members able to draw on these 

external ties to “explore” and/or “exploit” 

the outside environment in ways that 

might benefit tobacco control efforts?

9. How is the network governed? Are 

mechanisms and structures in place 

to facilitate and guide the coordinated 

actions of network members so tobacco 

control efforts are appropriately 

integrated and coordinated?

10. How has the network evolved over 

time, as evidenced in several waves 

of data collection? Specifically, has 

reasonable progress been made in 

establishing critical network ties and 

building effective network governance 

mechanisms?

11. What level of trust and cooperation exists 

among tobacco control agencies trying to 

work together? Have trust and cooperation 

increased or decreased over time? 

12. What have been the benefits, drawbacks, 

and expectations of network involvement? 

Have these changed over time? 

13. Within a particular service domain such 

as tobacco control, how do networks 

in some communities, states, or 

regions compare, along the dimensions 

described here, with other networks 

trying to perform similar services? 

14. What is the network’s capacity for 

scanning—that is, the extent to which 

it has human and automated “probes” 

that can bring new information into the 

network?

15. What is the network’s capability for 

absorption—that is, the extent to which 

it can absorb relevant information 

scanned from outside the network?

16. What is the network’s efficiency for 

distribution—that is, the extent to 

which it can selectively and strategically 

distribute the information it absorbs to 

the appropriate nodes that need it?

17. What is the level of congestion within 

the network due to bottlenecks—that is, 

the extent to which certain organizations 

or individuals are holding up the flow of 

knowledge or resources, because their 

“circuits are too busy with unnecessary 

networking”?

18. What is the network’s robustness against 

disruption—that is, the extent to which 

built-in redundancies in the links within 

the network help to prevent unraveling 

of the network when one individual or 

organization departs?

19. What is the network’s vulnerability to 

external sources—that is, the extent 

to which links among members of the 

network are being brokered by nodes 

outside the network?
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Design

Discovery (identification) and diagnosis 

contribute to building a deep understanding 

of one or more tobacco control networks by 

using the tools and techniques of network 

analysis. However, once this understanding 

has been established, it is up to network 

leaders and members to work with network 

researchers to put the findings to use. The 

design phase involves efforts to modify 

network structures and relationships to 

enhance the effectiveness of the network. 

The focus of this phase is on helping the 

community collectively identify strategies 

to design (tune) a network to accomplish its 

goals more effectively. This strategy could 

apply to an existing network or to a latent or 

nascent network that needs a jump-start.

Designing a network includes identifying 

links or nodes that must be restructured, 

as well as identifying social incentives 

and technical infrastructures necessary 

for the network design to be successfully 

implemented. This “rewiring” of the 

network is frequently difficult, because it 

may require changes in the structure and 

patterns of behavior that have evolved over 

the life of the network.

The recommendations made here relate 

to changes network leaders and members 

may want to consider, not changes that 

must be addressed. Such changes would be 

implemented slowly and would be guided 

by such considerations as a thorough 

understanding of network context, the 

individuals involved, and what is politically 

possible. Networks can be changed to operate 

more efficiently and effectively, and network 

analysis provides a rationale for making the 

necessary changes on the basis of data, rather 

than assumptions and general observations.

The design questions presented build on 

the identification and diagnosis questions 

already discussed. Design is simply the 

application and use of this knowledge. The 

design questions are more general than the 

questions about identification (discovery) 

and diagnosis, focusing on the types of issues 

Linking Systems and Networks: Agent-Based Models

One area that may hold promise for network methods is use of agent-based simulations of networks, 

a concept from system dynamics. In such simulations, autonomous agents operating under specific 

rules create evolutionary outcomes.a In a tobacco control context, for example, one might simulate 

the long-term consequences of including specific organizations in a network, adding links (e.g., by 

creating cross-functional teams), dropping links (e.g., by creating firewalls), or offering incentives 

for specific types of resource flows among certain members within the network. “What if” scenarios 

could then be based on these assumptions.

Interest in development of agent-based computational models and multiagent simulation 

environments has been substantial.b Blanche, a computer application developed by Contractor and 

Monge,c is one such computational network modeling environment especially well suited to simulate 

and visualize changes in a network based on multitheoretical, multilevel mechanisms. Another more 

distant but promising area is the potential “docking” of the aggregate system dynamics models and 

agent-based computational network models. Such approaches may help to improve the collective 

validity and usefulness of these models for practitioners interested in designing networks.

a

Sterman J. D. 2000. Business dynamics: Systems thinking and modeling for a complex world. New York: 

McGraw-Hill/Irwin.

b

Gilbert, N., and K. G. Troitzsch. 1999. Simulation for the social scientist. Berkshire, UK: Open Univ. Press.

c

Monge, P. R., and N. Contractor. 2003. Theories of communication networks. New York: Oxford Univ. Press.
180

6 . U n d e r s t a n d i n g a n d M a n a g i n g S t a k e h o l d e r N e t w o r k s

that might be addressed by an organizational 

network focused on tobacco control.

1. How can understanding of factors such as 

who is involved in the network, who knows 

what, and the location of key information 

and resources be enhanced? Members of 

the tobacco control network must have 

access to all network identification data so 

they can develop relationships with other 

network members as needed.

2. How can the network be redesigned 

to operate more efficiently? How can 

redundant ties be limited and weak 

or nonexistent ties in key areas be 

strengthened? Which relationships 

should be direct and which should be 

indirect, brokered by other organizations 

and individuals? Tobacco control 

organizations should collaborate to 

enhance effectiveness, but networks with 

ties that are too dense are inefficient 

because everyone is too busy networking 

to get anything else done.

3. How can the network be redesigned to 

operate more effectively? Which types of 

relationships seem to work best? How 

can these be expanded to other areas 

of the network? Networks should be 

redesigned so organizations with assets 

and skills critical for particular aspects 

of tobacco control (e.g., information 

and certain client services) have a 

high degree of centrality and are not 

peripheral in the network’s structure. 

4. Consistent with question 3, what overall 

types of network design and structure 

are most appropriate for accomplishing 

different types of network outcomes? 

For example, dense networks may 

work best for achieving collective 

action, and small-world networks with 

ties to outside groups may be best for 

exploring and importing new ideas. In 

general, however, as noted earlier in 

this chapter, effective networks typically 

display “focused integration,” with an 

appropriate mix of weak and strong ties 

and some fragmentation.

5. In light of existing levels of trust, how 

can trust be enhanced among network 

members, especially if the network is to 

be highly collaborative and not based 

on hierarchy or contracts? Should trust 

building focus on key subgroups or 

cliques of organizations first and then 

be expanded to others? Have certain 

low-trust relationships been identified 

and thus circumvented in the building of 

network ties?

6. How can the benefits of network 

collaboration that have been identified 

be maintained and reinforced? How can 

the drawbacks be minimized?

7. How can the appropriate network 

governance structure be established 

and sustained so network activities 

and interactions can be encouraged, 

coordinated, and facilitated on an 

ongoing basis? What should such a 

governance structure look like? Who 

should lead it?

8. How can critical network ties be 

institutionalized? Tobacco control 

organizations should work to ensure that 

key network ties, especially broker ties, 

are not dependent on a single individual. 

9. Based on comparative network analysis 

across multiple networks, what “best 

practices” can be established? How 

can these practices be effectively 

implemented?

Summary

Network analysis represents an important 

and currently underused approach for 

assisting leaders in health care services, 

public health practice, and development 

and implementation of health policy, 

especially in the area of tobacco control. 

Network analysis can be a powerful tool 
181

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

for strengthening tobacco control efforts 

at local, state and regional, national, and 

international levels. Network analysis can 

be done (1) by identifying existing networks 

and who is involved, (2) by diagnosing how 

these networks are structured and governed 

and how they operate, and (3) by using this 

knowledge to help network leaders design 

networks that work together more effectively 

to enhance a broad range of tobacco 

control efforts. This chapter provides an 

overview of how network analysis might be 

accomplished and why it would be beneficial 

for tobacco control programs. The structural 

data provided by network analysis must be 

combined with an in-depth knowledge of the 

nature of the problem being addressed, the 

services and capacities of the organizations 

involved, and the social and political 

contexts in which the network is embedded.

Conclusions

1. Solving complex future issues in tobacco 

control will require replacing silos of 

information and activity with greater 

linkage of tobacco stakeholders through 

networks.

2. Networks of tobacco control stakeholders 

form a foundation of the systems 

environment envisioned for the future 

of tobacco control. Many components of 

a systems approach are built around the 

presumption of stakeholder networks 

that span multiple levels of tobacco 

control activity and transcend geography 

and discipline. These components 

include building organizational capacity; 

participatory approaches to planning, 

implementation, and evaluation; 

optimization of resources and effort; and 

dissemination of knowledge and best 

practices. 

3. Network analysis holds the potential for 

facilitating understanding and strategic 

management of linkages between 

stakeholder groups.

4. Numerous theories of network behavior 

currently coexist, and core concepts 

that describe networks now have broad 

acceptance, particularly those related to 

network attributes and behavior.

5. Network applications in public health 

are at an early stage. However, they 

have shown promise in recent studies, 

particularly in areas where disparate 

organizations have a common goal. 

Recent tobacco control applications of 

networks include the North American 

Quitline Consortium and Global Tobacco 

Research Network.

6. Network attributes potentially serve 

as a measure of the health of tobacco 

control efforts, as evidenced by a case 

study correlating network centrality with 

the strength of political and financial 

support for tobacco control.

7. In the future, tobacco control programs 

could consist of multiple networks 

with specific functional objectives, 

linked in turn as part of a “network of 

stakeholders.”

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7

What We Know: Managing the 

Knowledge Content

This chapter presents a unified framework for applying knowledge management and 

translation (KMT) in public health areas, such as tobacco control. The approach 

integrates KMT in a system that considers purpose, people, process, and product. This 

framework then is used to examine two current examples of KMT methodology in 

tobacco control:

n	 Review of KMT in the tobacco control efforts of the National Cancer Institute 

(NCI) through a formal review of knowledge management based on data 

gathering and personal interviews

n	 A private-sector project that used concept mapping to help a diverse group 

of tobacco control stakeholders to collaboratively design a knowledge-base 

taxonomy for tobacco control

Knowledge is of two kinds: we know a subject ourselves, or we know where we can find 

information upon it.

—Samuel Johnson (1709–84)
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Introduction

This chapter examines issues in the 

development and maintenance of KMT 

infrastructure for tobacco control based on 

previous work applying KMT to public health, 

related work in other areas, and a summary 

of two research projects. These projects 

include a knowledge infrastructure review 

of current tobacco control efforts at NCI and 

the use of concept mapping to help tobacco 

control stakeholders develop a taxonomy for 

a tobacco control knowledge base.

More than two centuries ago, Samuel 

Johnson summarized the fundamental case 

for knowledge management in the quotation 

cited here. Today, knowing where to find 

knowledge and sharing the knowledge 

that resides within ourselves form the 

linchpin of the ability to link the efforts of 

tobacco control stakeholders in a systems 

environment. Formal KMT methodologies 

represent a process by which access to this 

knowledge can be designed and developed 

both locally and globally.

To disseminate new knowledge, tobacco 

control researchers, like researchers in 

virtually every scientific field, rely on 

publication in peer-reviewed journals. This 

dissemination tactic is necessary for two 

reasons: (1) it ensures that the research 

methods and results have been reviewed 

by knowledgeable experts, providing some 

safeguard that the information is credible; and 

(2) publishing in refereed journals still is an 

integral part of the academic promotion and 

tenure process and so is an important part of 

the culture of most academic organizations. 

Unfortunately, journals represent an 

ineffective dissemination strategy at best, 

because in virtually every scientific field, 

it often is impractical to keep abreast of a 

growing mass of published information. 

In tobacco control, because researchers 

come to the field from the perspectives of 

so many different disciplines, the literature 

is particularly fragmented. For example, a 

search for recent tobacco control citations in 

New Citations1 yields articles in publications 

specializing in medicine, pharmacology, 

cancer, psychology, addiction, and public 

health, as well as a growing number of 

journals devoted to tobacco control. Current 

Citations is a citation resource of the 

Centers for Disease Control and Prevention 

(CDC). Resources such as this are helpful for 

identifying the available literature because 

the citations are written in the language of 

the discipline in which they reside. However, 

accessibility of these resources to all 

frontline practitioners is limited. Similarly, 

resources that are excellent first steps in 

translating and synthesizing evidence from 

the extensive literature on KMT include the 

Tobacco Technical Assistance Consortium;2

CDC’s Guide to Community Preventive 

Services;

3

 and NCI’s Cancer Control Plan, 

Link, Act, Network with Evidence-based 

Tools (PLANET).4

However, practitioners often need knowledge 

refinement, tailored programmatic tools, 

and information, which are not necessarily 

available in “prepackaged” databases. There 

is a need for enhancement of these existing 

services and of mechanisms that reward 

researchers for publishing in refereed 

journals and for disseminating research 

output and other knowledge to sources 

more available to practitioners. Similar 

mechanisms must be made available for 

researchers to tap into the experiential 

knowledge of frontline practitioners and 

the tacit knowledge of experts in other 

disciplines.

Today, organizations grapple with the 

ever-increasing and complex web of 

health knowledge that influences many 

facets of life. The first step in this effort 

is to differentiate between knowledge and 

information. Information is data such as 

the pattern of adult smokers in the United 

States. Knowledge involves interpretation 
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of information within some context. 

Knowledge also includes experiences, 

expertise, and routines that sometimes 

can be expressed only through action. 

Therefore, understanding the significance 

of the pattern of adult smokers in the 

United States in terms of its economic and 

societal impacts constitutes a source of 

knowledge about tobacco control that can 

have a profound influence on the health 

of the nation. Knowledge is a fundamental 

component of how organizations function. 

Increasingly, organizations in pursuit of 

success are looking for effective ways to 

manage what they know.

Knowledge 

Management and 

Translation

Definition

Knowledge management has been formally 

defined as “the organization, creation, 

sharing and flow of knowledge within 

organizations.”5 Knowledge translation 

refers to the process by which knowledge 

is rendered usable by its end users. The 

first of these two definitions is quoted from 

Wikipedia, an Internet-based encyclopedia 

that, in and of itself, represents a good 

example of the evolution of knowledge 

management in a systems environment. 

In first-generation KMT solutions, people 

would attempt, often unsuccessfully, 

to create all-encompassing proprietary 

knowledge “systems” through means such as 

intranets and databases. Second-generation 

solutions frequently follow the core systems 

concepts of chaos and complexity theory. 

Namely, these include the adoption of simple 

rules that ultimately gather, maintain, and 

translate knowledge in forms that can be 

best used by those who need it. Wikipedia

itself uses such simple rules, built around 

interlinked components known as “wikis” 

that users can update. A stakeholder-based 

mechanism for review and acceptance 

preserves accuracy and integrity. Unlike a 

traditional top-down effort to create a new 

encyclopedia, Wikipedia harnesses the power 

of its own readers to create a knowledge base 

that is truly encyclopedic, but often updated 

within minutes after new events happen.

Within such a systems environment, 

knowledge management forms an integral 

part of a new approach to tobacco control 

and public health. Previous chapters 

in this monograph discuss the use of 

systems models—networks of stakeholders 

and adaptive organizations—to address 

increasingly complex issues in this field. 

KMT forms the “glue” that holds these 

components together by providing the 

knowledge needed for these components to 

function and interact.

At a practical level, KMT involves both the 

methodologies and infrastructure needed 

to use knowledge effectively. It comprises 

strategies, processes, and technologies 

for identifying, capturing, and leveraging 

knowledge to advance a field of study. In 

concert with other integrated systems 

approaches in tobacco control, KMT 

strategies can manage and disseminate 

knowledge ranging from evidence-based 

tobacco control practices to the needs and 

experiences of the practitioner community.

Within the cycle of planning, implementation, 

and evaluation (see chapter 4), KMT is central 

to implementation strategies as a resource 

for maintaining explicit knowledge that, in 

turn, forms an evidence base. In addition, 

such strategies also are intimately connected 

to the development of both systems and 

networks for tobacco control, by drawing on 

the large body of tacit knowledge in the form 

of the needs and expertise of tobacco control 

stakeholders. As has been demonstrated in 

other fields, such tacit knowledge is critical 

to optimizing the efforts of a widely diverse 

range of stakeholders.
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Dimensions

Nonaka and colleagues6 differentiate the raw 

data that drive the organizational knowledge 

infrastructure in terms of explicit and tacit

knowledge. Both kinds of knowledge are 

created by individuals and amplified as part 

of the knowledge system in an organization. 

Explicit knowledge constitutes factual 

information that generally is contained 

within data. It often is precise and can be 

formally articulated in organizations. Tacit 

knowledge is formally defined as “knowledge 

that enters into the production of 

behaviors and/or the constitution of mental 

states but is not ordinarily accessible to 

consciousness.”7 Tacit knowledge generally 

is present in individuals. It is the subjective 

know-how in individuals and often is more 

difficult to express than explicit knowledge, 

except through action and experience.

These two kinds of knowledge frequently 

converge, as when both the facts of a 

study and the knowledge of its principal 

investigator are important to changing 

outcomes. Leveraging this knowledge 

is perhaps the most critical issue facing 

effective implementation of a KMT 

infrastructure to link research and practice 

in tobacco control so researchers and 

practitioners can share needs, experiences, 

and best practices in support of improved 

outcomes for tobacco control.

As a formal science, KMT methodologies have 

become the cornerstone of a revolution in 

knowledge-intensive organizational behavior. 

In the context of public health and specifically 

tobacco control, development of formal 

knowledge infrastructures holds the potential 

to integrate systems approaches such as 

system dynamics and network analysis as part 

of a broader knowledge-based framework for 

the linkage between research and practice. 

The four common types of knowledge 

management projects are to build knowledge 

repositories, improve knowledge access and 

use, enhance the underlying knowledge 

environment, and manage knowledge as an 

asset. In a review of corporate knowledgemanagement projects across 24 companies, 

Davenport and colleagues8 summarize eight 

key success factors behind these systems:

1. Linkage to economic performance and 

industry value

2. Existing technical and organizational 

infrastructure

3. Standard but flexible form of knowledge 

structure

4. Knowledge-friendly culture

5. Clear purpose and language among staff

6. Change in motivational practices

7. Multiple channels of knowledge transfer

8. Senior management support

Replicating these success factors from the 

private sector to public health involves 

numerous challenges. These include 

coordination of KMT efforts across multiple 

organizations with different cultures, the 

need to develop a consistent and universally 

accepted knowledge infrastructure, and 

budgetary constraints. At the same time, 

such a knowledge infrastructure has the 

promise to form a cornerstone for evidencebased decision making in public health 

and for linking research to practice and 

practice to research. Moreover, the current 

state of tobacco control, with its multiple 

stakeholder organizations operating in an 

environment of declining financial resources, 

can particularly benefit from a consistent 

and successful knowledge infrastructure.

As part of research on the application of 

managing knowledge content from multiple 

stakeholders in the public health system, 

a metalevel framework is envisioned that 

applies knowledge management and 

knowledge translation concepts and strategies 

to the health policy, evidence, experience, and 

contact base in the field (figure 7.1).
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Knowledge 

Management Concepts

Lau9 outlines a conceptual framework for 

knowledge management that comprises 

a set of knowledge management concepts 

for the health setting, revolving around 

the production, use, and refinement of 

both explicit and tacit knowledge in an 

underlying social context. The types of 

knowledge addressed include clinical and 

administrative policy, research evidence, 

practice experience, and resource contact 

that are considered critical and relevant 

to specific settings. An overview of this 

framework, as shown in figure 7.2, 

Figure 7.1 Overview of a Knowledge Management and Translation Framework for the

Health System

KNOWLEDGE

MANAGEMENT

Production

Use

Refinement

Social Context

KNOWLEDGE

MANAGEMENT

Production 

Use

Refinement 

Social Context

KNOWLEDGE

TRANSLATION

Audience

Motivations

Mechanisms

Ecological Context

KNOWLEDGE

TRANSLATION

Audience

Motivations

Mechanisms

Ecological Context

EXPLICIT/TACIT

KNOWLEDGE

Evidence

Policy

Experience

Contact

OUTCOMES

Evidence base for Dissemination

Knowledge base for Linking Science and Practice

Implementation Framework

Interaction and Collaboration Methodology

OUTCOMES

Evidence Base for Dissemination 

Knowledge Base for Linking Science and Practice

Implementation Framework

Interaction and Collaboration Methodology

Benefits of Knowledge Infrastructure for Tobacco Control

For tobacco control, potential outcomes of a consistent knowledge infrastructure include

n Evidence base for effective dissemination, which serves as a repository for evidencebased practices in tobacco control, potentially in much the same way the Cochrane 

Collaborationa provides the medical profession with an accessible meta-analysis of 

evidence-based medical research

n Knowledge base for linking science and practice so stakeholders in both communities 

can share needs and approaches

n Implementation framework for policy changes and consensus practices in tobacco 

control

n Interaction and collaboration methodology, which links large, geographically and 

politically diverse groups of tobacco control stakeholders in a cycle of planning, 

implementation, and evaluation for ongoing tobacco control efforts

a

Cochrane Library. 2003. http://www.cochrane.org.
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7 . W h a t W e K n o w : M a n a g i n g t h e K n o w l e d g e C o n t e n t

involves three key components: knowledge 

production, use, and refinement.

Knowledge production is the process of 

creating and organizing policy, evidence, 

experience, and contacts. In a health care 

context, sources of this knowledge include 

policy syntheses, research findings, local 

practices, and resource contacts. The phase 

of knowledge production includes collection 

of local experience, such as organizational 

practice norms and values, generation of 

new knowledge from primary research (e.g., 

randomized trial or case study), synthesis 

of research findings, policy advice and 

local experience through a critical review 

process, and identification of individual or 

organizational resource contacts willing to 

share their knowledge.

As knowledge is created, a formal process 

is needed to organize this knowledge as 

artifacts or intellectual resources. This 

process involves codification of knowledge 

by using the appropriate nomenclature; 

computer-based storage for later retrieval 

and maintenance; packaging with 

appropriate content details and delivery 

modalities; and coordination of intellectual 

resource contacts on such details as 

expertise, experience, locations, and 

availability.

Knowledge use refers to the manner in 

which stakeholders use explicit and tacit 

knowledge in a local setting. In a tobacco 

control environment, these stakeholders 

can span a broad range of roles, including 

researchers, advocates, practitioners, 

leaders, and legislators. The types of 

knowledge they use can range from specific 

research results to linkage with other 

stakeholders and their expertise. Factors 

in knowledge use include distribution to 

targeted audiences through channels such 

as print and online media; sharing through 

interpersonal communication; application 

in a local setting in policy or practice; and 

adaptation to the values, cultures, and 

norms of the local environment.

Knowledge refinement refers to ways 

knowledge sources are institutionalized 

within organizations over time as part of 

routine, accepted practices. Knowledge 

refinement is an ongoing process of 

Figure 7.2 Conceptual Framework for Knowledge Management

Explicit/Tacit

Knowledge

Production

Refinement Use

collection, generation,

synthesis, identification

also

codification, storage,

packaging,

coordination

distribution, sharing, application, adaptation

integration, evaluation,

reflection,

sustainability

Social Context (structures, values, preferences)

Note. From Lau, F. 2003. Toward a conceptual knowledge management framework in health. Perspectives in Health Information 

Management 1:8. Used with permission from the American Health Information Management Association (AHIMA). Copyright 2004 

by AHIMA.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

managing the information that is extant in 

the knowledge base. Factors in knowledge 

refinement include integration with 

existing work processes and practice norms; 

evaluation by using measures (e.g., quality, 

use, and impact); reflection on the knowledge 

source through subjective interpretations by 

stakeholders; and ongoing sustainability of 

the knowledge management approach.

All three of these factors exist within a 

larger social context affecting how the 

overall stakeholder group—including 

policy makers, practitioners, researchers, 

and the public—interacts with knowledge. 

This social context encompasses the social 

structures (e.g., organizations, rules, and 

processes) in which these stakeholders 

operate; values guiding beliefs and actions; 

and preferences on a wide range of health 

issues, based on belief systems and needs. 

This context creates a unique environment 

for knowledge management that is difficult 

to replicate outside of it.

Knowledge Translation Concepts

Knowledge management focuses on the 

systematic process of producing, using, and 

refining explicit and tacit knowledge in and 

across organizations. Knowledge translation 

is concerned with the dynamics necessary 

to convert explicit knowledge to tacit 

knowledge and vice versa across individual, 

group, organizational, and societal levels. 

The proposed framework for translation 

comprises members of the audience, their 

motivations, and the different mechanisms 

for the ongoing conversion of tacit and 

explicit knowledge within an underlying 

ecological context. An overview of this 

framework, as shown in figure 7.3, involves 

three key components: an audience, 

motivations, and mechanisms. 

The audience consists of stakeholders, such 

as policy makers who make legal, financial, 

or administrative decisions; practitioners 

who assist in clinical decisions for clients and 

families; researchers involved in scientific 

inquiries to generate new health knowledge; 

and others ranging from advocates, activists, 

and legislators to the general public. An 

important dynamic that determines the 

success of any effort at knowledge translation 

is the ability to distinguish among the types 

of audiences involved. Different audiences 

have different knowledge needs that must 

be recognized when translating the policy, 

evidence, experience, or contact to address a 

particular issue.

Motivations for knowledge translation 

depend on the specific audience. Motivations 

may include decision making for clinical, 

administrative, or legislative issues; 

education to improve knowledge and 

performance; innovation to generate new 

knowledge; or advocacy to influence the 

actions of others.

Mechanisms that translate explicit and 

tacit knowledge into usable forms of health 

policy, evidence, experience, and/or personal 

contact include a combination of different 

forms of explicit knowledge to add value, 

articulation of tacit knowledge in print or 

electronic form, internalization of explicit 

knowledge as intellectual capability, and 

sharing of tacit knowledge with others 

through socialization.

This environment for knowledge translation 

exists in an ecological context that views 

the health system as an ecosystem with 

interrelated components interacting with 

each other at different levels over time, in 

a complex and unpredictable manner.10 The 

quality and effect of these interactions are 

contingent on different situational contexts. 

These include the organizational context in 

the health care environment; the cultural 

context that encompasses values, beliefs, 

and norms; the political–legal context such 

as legislation, mandates, and privacy issues; 

and the surrounding media environment for 

communication and interaction.
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Integration of Knowledge 

Management and Translation

Effective management of the content 

of explicit and tacit knowledge requires 

consideration of all of the concepts 

described in the frameworks for 

knowledge management and knowledge 

translation. Although the two frameworks 

address different aspects of managing 

and translating knowledge, they are 

complementary in nature and should be 

considered in synchrony for maximal effects. 

Therefore, in producing, using, and refining 

tobacco control knowledge such as policy, 

evidence, experience, and contact in and 

across organizations, one should also take 

into account members of the intended 

audience, their respective motivations, and 

the mechanisms available for translating 

such knowledge, within the underlying 

social and ecological contexts. Table 7.1 

summarizes specific considerations for each 

aspect of the integrated KMT concepts.

As table 7.1 implies, the integration of 

knowledge management and knowledge 

translation has specific ramifications for 

the processes of knowledge production, 

use, and refinement to address specific 

audiences and their motivations. Knowledge 

production requires consideration of factors 

related to generating knowledge for effective 

translation. These factors include the 

following:

n Collection of local experience in such a 

way that stakeholders articulate it from a 

tacit to explicit form 

n Generation of new knowledge by 

articulating tacit knowledge from 

research findings into published form 

n Synthesis of this knowledge in forms 

such as systematic reviews 

n Identification of intellectual resources as 

sources of tacit knowledge

Once generated, the knowledge should be 

organized by methods that facilitate effective 

translation. This process encompasses 

the codification of collected experience, 

evidence, and other resources into explicit 

knowledge in the following steps:

Figure 7.3 Conceptual Framework for Knowledge Translation

Explicit/Tacit

Knowledge

Audience

Mechanisms Motivations

combination,

articulation,

internalization,

socialization

decision, education, innovation, advocacy

policy maker,

practitioner,

researcher,

the public

Ecological Context (organizational, political, cultural, media)

Note. Adapted from Lau, F. 2003. Toward a conceptual knowledge management framework in health. Perspectives in Health 

Information Management 1:8.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

n Use accepted vocabularies such as that 

of the International Classification of 

Diseases (10th revision)11 and Health Level 

712 (an exchange standard for clinical data)

n Code this knowledge into online 

repositories 

n Package it in a variety of content, media, 

and delivery formats

n Coordinate intellectual resource contacts 

within this knowledge base to enhance 

their availability as sources of tacit 

knowledge

Knowledge use through translation should 

take place in contexts that are relevant to 

different audiences and their motivations. 

This context must influence factors such 

as the distribution of explicit knowledge 

in appropriate forms and the sharing of 

tacit knowledge through socialization. The 

presentation should be tailored to different 

audiences. The application and/or adaptation 

of explicit or tacit knowledge must be 

oriented to local settings. 

Knowledge refinement involves formulating 

a presentation of concepts that is geared to 

specific audiences and their motivations. 

This process requires integration of new 

knowledge with existing knowledge by 

socializing new knowledge in tacit form; 

internalizing new explicit knowledge into 

tacit knowledge; and conversely, articulating 

new knowledge from tacit to explicit form. 

The process also entails evaluation of the 

impact of this knowledge by articulating 

tacit experience into a quantifiable explicit 

form, reflection of the experience of using 

this knowledge, and assessment of the 

sustainability of the KMT effort.

The common thread running through each of 

these issues is the need to develop a consistent 

approach for KMT that encompasses the 

unique needs and motivations of each of 

the stakeholder audiences, such as policy 

makers, practitioners, and researchers. 

Moreover, as discussed later in this chapter, 

these issues point to the need to integrate 

knowledge management strategies for health 

care environments within the broader area 

of systems thinking—for example, the use 

of systems approaches involving adaptive 

behavior and feedback to address complex 

issues. Accomplishment of this integration 

requires the following procedures:

n Infusing the collection of explicit 

knowledge into research and practice 

experience 

n Leveraging the use and maintenance of 

networks as a source of tacit knowledge 

n Using this knowledge in a framework of 

systems-level planning, implementation, 

and outcomes evaluation 

Table 7.1 Integrated Concepts of Knowledge Management and Translation

Concept Audience Motivations Mechanisms

Production Who generates and/or 

organizes the knowledge 

and whom is it for?

What are the motivations for 

creating and organizing the 

knowledge?

What translation 

mechanisms should be 

included when creating and 

organizing the knowledge?

Use Who uses the knowledge? What are the motivations for 

using the knowledge?

What translation 

mechanisms should be 

included when using the 

knowledge?

Refinement Who refines the knowledge 

and whom is it for?

What are the motivations for 

refining the knowledge?

What translation 

mechanisms should be 

included when refining 

the knowledge?
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n Creating an integrated framework for 

leveraging knowledge within the broader 

public health system

Framework for 

Strategy of Knowledge 

Management and 

Translation

The concepts described under the knowledge 

management and knowledge translation 

frameworks provide a rich taxonomy and 

models of understanding that can be used 

to devise specific strategies and actions for 

implementation. Three broad strategies 

are envisioned to manage the complex 

knowledge content that spans multiple 

stakeholder organizations, as is the case 

for tobacco control: (1) the 4Ps (purpose, 

people, process, and product) of KMT; 

(2) the underlying KMT infrastructures; and 

(3) the KMT strategy maps. Figure 7.4 shows 

this KMT strategy framework.

Four Ps of Knowledge 

Management and Translation

The 4Ps of KMT refer to the four aspects of 

KMT that should be leveraged as an essential 

part of an integrated KMT strategy—

purpose, people, process, and product. 

These 4Ps provide the necessary focus and 

means to implement an effective knowledge 

infrastructure in and across organizations.

Purpose

Management of complex knowledge content, 

such as tobacco control policy, practice, and 

experience that span multiple stakeholder 

organizations or audiences, requires 

a shared understanding of the overall 

mandate, vision, goals, and objectives, even 

though they are high level, abstract, and 

evolving. Such a mental model can serve as 

a road map from which concrete plans can 

be developed and implemented. This purpose 

encompasses four key actionable items:

n Agendas are needed that are specific 

to individual audiences, such as the 

research agenda, the political agenda, and 

the public’s agenda, in the case of tobacco 

control. The intent is to ensure that 

everyone knows who should do what.

n Relevance ensures that the coordinated 

agendas fit the mandate, goals, and 

activities of the stakeholder organizations. 

The intent is to ensure that everyone 

knows that who should do what is relevant.

n Timelines provide an overall schedule 

to implement coordinated agendas for 

stakeholder organizations according 

to priority, need, and the availability of 

resources. The intent is to ensure that 

everyone knows that who should do what 

is relevant when.

n A business case with well-articulated 

justifications for proceeding is essential 

for successful implementation of KMT. 

The intent is to ensure that everyone 

knows that who should do what is 

relevant and justified when.

People

Even with the best-coordinated 

agendas, nothing will happen unless the 

appropriate human resources are in place 

to implement these plans. Within the 

complex public health system, an effective 

KMT infrastructure that spans different 

stakeholder organizations requires the 

ongoing engagement of specific types of 

people, including the following:

n Knowledge champions are leaders 

who are respected in the field or have 

positional power to lead, lobby, or 

advocate for specific causes, expecting 

others to follow or comply with their 

actions. Their presence and actions are 
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crucial in introducing change in and 

across organizations because of their 

stature and conviction.

n Knowledge brokers/managers work as 

intermediaries to translate the knowledge 

required by different audiences according 

to their specific motivations. They are 

knowledgeable in KMT methodologies 

and are responsible for translating 

knowledge such as health policy, 

evidence, experience, and contact into 

tailored content, media, and formats that 

are relevant to local practice.

n Knowledge architects are responsible for 

the planning, design, implementation, and 

support of KMT systems in organizations 

or groups. Knowledge architects usually 

are trained in KMT and are responsible 

for the strategic, financial, technical, and 

organizational aspects of the knowledge 

infrastructures.

n Communities of practice are individuals 

and groups in and across organizations 

that share common agendas and work 

practices. They provide the critical 

mass needed to collectively produce, 

use, and refine health policy, evidence, 

experience, and contact in ways that 

fit the specific motivations of different 

audiences.

Process

Process is made up of the activities that 

enable people in and across stakeholder 

organizations to work collectively on the 

coordinated KMT agendas. Key processes 

that form part of the KMT strategy and 

infrastructure include the following:

n Consensus building enables stakeholders 

to identify and negotiate a diverse set of 

issues or options to reach agreement on 

key issues or solutions.

n Capacity building enables stakeholders 

to develop local and practical expertise to 

address a specific health area or issue.

Figure 7.4 Integrated Knowledge Management and Translation (KMT) Strategy Framework

KNOWLEDGE

MANAGEMENT

EXPLICIT/TACIT

KNOWLEDGE

OUTCOMES

4P’s

STRATEGY MAPS

INFRASTRUCTURES

KNOWLEDGE

TRANSLATION

Purpose People Process Product

KMT STRATEGIES

Organization, Information, Technology, Finance 

4P-KMT KMT-Infra 4P-KMT-Infra
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n Knowledge development enables 

stakeholders to engage in specific KMT 

activities related to health issues.

n Network development enables 

stakeholders across organizations to 

collectively engage in KMT activities.

Products

Products serve as the tools that enable 

people to work collectively on coordinated 

agendas through specific KMT processes. 

Representative tools that form part of the 

KMT strategy and infrastructure include 

groupware, knowledge repositories, tools 

for knowledge development, and tools for 

knowledge access, as follows:

n Groupware includes software tools for 

communication, coordination, and 

collaboration, which allow individuals, 

groups, and organizations to work 

together electronically and virtually on 

specific KMT activities.

n Knowledge repositories usually are 

interactive knowledge bases accessible 

through the Internet that contain a wide 

range of health knowledge content in 

various media and delivery formats.

n Knowledge development tools are 

software tools for generation and 

organization of knowledge content.

n Knowledge navigation/access tools are 

software tools used by audiences to 

retrieve specific knowledge content from 

knowledge repositories according to 

specific motivations.

The 4Ps provide a framework for 

implementation of a KMT strategy. 

Moreover, their components form an 

important part of the planning checklist 

for such an implementation. In a public 

health setting such as tobacco control, 

these factors also ensure that the unique 

needs of individual stakeholder groups are 

addressed as an integral part of the design 

and implementation effort.

Underlying Infrastructures

The 4Ps provide the focus and means 

to implement KMT in and across 

organizations. However, the underlying 

KMT infrastructures provide the necessary 

foundations on which the 4P-KMT strategy 

can be deployed. Key aspects of the KMT 

infrastructures include the following:

n Organization infrastructure refers to the 

structures, procedures, and norms by 

which organizations can work collectively 

to manage and translate knowledge. The 

components include the sites of explicit 

and tacit knowledge resources in and 

across organizations; the procedures 

behind knowledge-related tasks; and 

the cultural norms and customs of 

stakeholder organizations.

n Technology infrastructure refers to the 

information technology capacity and 

tools with which organizations deploy 

the knowledge infrastructure, including 

software applications, computer 

networks, telecommunications, and 

Internet connectivity.

n Information infrastructure refers to 

the underlying electronic databases, 

library resources, and data definitions 

and taxonomies available in and 

across organizations as input into the 

knowledge infrastructure.

n Financial infrastructure encompasses 

the mechanisms used to define and 

measure the value of knowledge 

infrastructures. These mechanisms 

include the investment portfolios 

that finance the human and physical 

resources required, intellectual assets 

representing the value of knowledge 

resources, and the return-on-investment 

measures of this value relative to the 

original investment.
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These components serve to illustrate the 

larger point that a KMT infrastructure 

encompasses an integration between 

computer and database technology and the 

surrounding organizational environment. 

This point underscores the concept that 

the KMT infrastructure cannot be purely 

approached as a computing issue. Instead, it 

should be seen in the context of the larger 

goals of affected stakeholder organizations.

4P-Knowledge Management and 

Translation Strategy Maps

KMT strategy maps provide detailed 

mapping of the actionable items under the 

4P and infrastructure strategies to achieve 

the desirable outcomes. These strategy 

maps are intended to offer guidance in 

planning and implementing a knowledge 

infrastructure. Three KMT strategy 

maps are described here: 4P-KMT, KMT 

infrastructures, and 4P-KMT infrastructures. 

4P-Knowledge Management and 

Translation Strategy Map

The 4P-KMT map is focused on the 

actionable items under the 4P strategy 

for KMT in and across organizations. For 

example, with respect to purpose, one 

needs to define the relevant agendas, the 

timelines, and the business case with regard 

to who should produce, use, and refine 

the knowledge, based on members of the 

audience, their motivations, and translation 

mechanisms. At the same time, the local 

social and ecological contexts must be 

considered. Table 7.2 shows the 4P-KMT 

strategy map.

Strategy Map for Knowledge 

Management and Translation 

Infrastructure

The strategy map for KMT infrastructures 

focuses on the actionable items under the 

KMT infrastructure strategy in and across 

organizations. For example, with respect 

to organization infrastructure, one needs 

to establish the appropriate structure, 

procedures, and norms for the production, 

use, and refinement of knowledge. This 

process must take into account members 

of the audience, their motivations, and 

different translation mechanisms, as well 

as the local social and ecological contexts, 

such as affected stakeholder groups and 

their interaction with the broader health 

care system. Table 7.3 shows this strategy 

map.

Strategy and Outcome Map for 

4P-Knowledge Management and 

Translation Infrastructures 

The strategy and outcome maps for 4P-KMT 

infrastructures focus on the actionable 

items under the 4P strategy, taking into 

account issues related to the underlying 

KMT infrastructure and the desired 

outcomes. The purpose is to establish a 

comprehensive infrastructure for KMT. This 

strategy map (figure 7.5) can be used as a 

framework to expand its actionable items 

into a more detailed strategy map for each 

type of knowledge involved, which in turn 

can be expanded into detailed checklists for 

final planning and implementation. (For 

more details on 4P-KMT infrastructures, see 

appendix 7A.)

Case Study: Knowledge 

Management in 

Tobacco Control

An illustrative case study of the current 

role of KMT in tobacco control efforts 

is presented here. A series of discussion 

meetings with key informants were 

conducted in June and July 2004 to examine 

KMT in the domain of tobacco control, as 

part of a substantive study of large-scale 
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change in health systems. The scope of 

these discussions was focused mainly on the 

recent Cancer Control PLANET4 initiative 

and several related Web-based knowledge 

resources outlined here, including the 

Cancer Biomedical Informatics Grid 

(caBIG)13 and the Cancer Intervention and 

Surveillance Modeling Network (CISNET).14

These efforts provide real-life case 

illustrations of the current state of the KMT 

infrastructure that is emerging within the 

field and the challenges involved.

Key informants identified by the study team 

were invited to discussion meetings in person 

or by telephone to share their thoughts about 

KMT by using tobacco control or related 

areas as the domain. (See appendix 7B for 

discussion questions.) These key informants 

were researchers, policy makers, informationTable 7.2 4P-Knowledge Management and Translation Strategy Map

Production Use Refinement

Purpose Define relevant agendas, 

timelines, and business 

case; and decide who should 

produce what knowledge

Define relevant agendas, 

timelines, and business case, 

and decide who should use 

what knowledge

Define relevant agendas, 

timelines, and business case, 

and decide who should refine 

what knowledge

People Identify champions, brokers, 

managers, and communities 

of practice to produce 

knowledge 

Identify champions, brokers, 

managers, and communities 

of practice to use knowledge

Identify champions, brokers, 

managers, and communities 

of practice to refine 

knowledge

Process Incorporate consensus 

building and knowledgedevelopment process to 

produce knowledge 

Incorporate consensus 

building and knowledgedevelopment process to use 

knowledge

Incorporate consensus 

building and knowledgedevelopment process to refine 

knowledge 

Products Produce knowledge through 

groupware, knowledge 

development, and repository 

and access tools 

Use knowledge through 

groupware, knowledge 

development, and repository 

and access tools

Refine knowledge through 

groupware, knowledge 

development, and repository 

and access tools

Note. Each 4P-knowledge management and translation strategy is specifically based on the audience, motivations, and different 

translations in social and ecological contexts.

Table 7.3 Strategy Map for Knowledge Management and Translation Infrastructure

Production Use Refinement

Organization Establish structures, 

procedures, and norms for 

producing knowledge 

Establish structures, 

procedures, and norms for 

using knowledge 

Establish structures, 

procedures, and norms for 

refining knowledge 

Technology Establish applications, 

networks, and connectivity 

for producing knowledge 

Establish applications, 

networks, and connectivity 

for using knowledge 

Establish applications, 

networks, and connectivity 

for refining knowledge 

Information Develop internal and external 

databases and information 

resources needed for 

producing knowledge 

Develop internal and external 

databases and information 

resources needed for using 

knowledge 

Develop internal and external 

databases and information 

resources needed for refining 

knowledge 

Finance Establish investment 

portfolios, intellectual assets, 

and return on investment for 

producing knowledge 

Establish investment 

portfolios, intellectual assets, 

and return on investment for 

using knowledge 

Establish investment 

portfolios, intellectual assets, 

and return on investment for 

refining knowledge 

Note. Each 4P-knowledge management and translation strategy is specifically based on the audience, motivations, and different 

translations in social and ecological contexts.
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management professionals, community-based 

practitioners, and advocates involved with 

tobacco control and/or cancer control from 

NCI and selected partner organizations such 

as CDC and the Campaign for Tobacco-Free 

Kids. NCI was chosen as a focus organization 

because of its central role in funding and 

developing an infrastructure for tobacco 

control efforts and its key support for the 

Initiative on the Study and Implementation 

of Systems (ISIS). Definitions related to 

KMT (appendix 7A) were provided before the 

meetings to familiarize informants with KMT 

terms. The team also reviewed information 

on these initiatives that NCI published on 

its Web site. The purpose of this review was 

to facilitate an understanding of the nature 

of the KMT efforts, especially in the area of 

tobacco control.

Chapter findings are organized around 

the types of tobacco control and related 

knowledge needed and those currently 

managed, how such KMT efforts can 

be viewed as part of an emerging KMT 

infrastructure, and suggested ways to 

advance this infrastructure to better meet 

the ongoing challenges in tobacco control.

Tobacco Control and Related 

Knowledge

At the discussion meetings, different types 

of tobacco and cancer control knowledge 

resources were reviewed with key informants 

from NCI and partner organizations. 

These resources included Cancer Control 

PLANET4 as an example of an evolving Webbased knowledge repository, as well as the 

Surveillance, Epidemiology, and End Results 

(SEER)15 registry program, CISNET,14 and 

audience segmentation tools such as the 

Consumer Health Profiles (CHP),16 as related 

knowledge resources that can be leveraged 

in tobacco control as part of the KMT 

Figure 7.5 4P-Knowledge Management and Translation Infrastructures Strategy Map

PRODUCTION

Creation 

Collection

Generation

Synthesis

Identification

Organization

Codification

Storage

Packaging

Coordination

4P-KMT OUTCOMES

INFRASTRUCTURES

KNOWLEDGE TRANSLATION

Purpose

People

Process

Product

Organization, Information, Technology, Finance 

USE

Distribution

Sharing

Application

Adaptation

REFINEMENT

Integration

Evaluation

Reflection

Sustainability

KNOWLEDGE MANAGEMENT

AUDIENCES

Policy maker

Practitioner

Researcher

Public

MOTIVATIONS

Decision

Education

Innovation

Advocacy

MECHANISMS

Combination

Articulation

Internalization

Socialization Evidence

Base

Science-Practice

Linkage

Implementation

Framework

Interaction &

Collaboration

Methodology
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efforts. Key aspects of the newly established 

caBIG were presented to illustrate an 

evolving collaborative knowledge network 

that may be considered for the tobacco 

control domain. In addition, information 

was presented on the problem of missing, 

incomplete, or conflicting knowledge for 

some aspects of tobacco control, especially 

at the systems level. Related KMT efforts and 

needs are described here.

Cancer Control PLANET and 

Tobacco Control 

Cancer Control PLANET4 is a Web portal 

for cancer control launched in April 

2003 and developed over two years as a 

collaborative effort among key government 

and nongovernment agencies, including the 

following:

n National Cancer Institute: An agency 

of the U.S. Department of Health and 

Human Services (DHHS) that serves as 

the federal government’s principal agency 

devoting resources to scientific research 

on cancer; also the coordinating agency 

for PLANET. 

n Centers for Disease Control and 

Prevention: A DHHS agency focused on 

control and prevention of disease, injury, 

and disability. The Division of Cancer 

Prevention and Control of the National 

Center for Chronic Disease Prevention 

and Health Promotion is the lead CDC 

agency in the area of tobacco control.

n American Cancer Society: A nationwide 

nongovernmental organization dedicated 

to cancer prevention and treatment.

n Substance Abuse and Mental Health 

Services Administration: A federal agency 

involved with issues of substance abuse 

and mental health that provided the review 

of tobacco control programs for PLANET.

n Agency for Healthcare Research and 

Quality: A DHHS agency dedicated to 

improvement of the quality of health 

care. This agency supports the U.S. 

Preventive Services Task Force, which 

develops recommendations on effective 

clinical preventive interventions such as 

screening, counseling, and medication 

regimens.

n American College of Surgeons 

Commission on Cancer: A professional 

organization that joined as a PLANET 

partner in 2006 to help promote 

evidence-based comprehensive cancer 

control through its state-based liaison 

physician program.

PLANET’s Web portal provides profile 

data on cancer nationally and by county 

and state, risk factor data by state, and 

resource information to assist program 

planners, educators, and researchers in the 

design, implementation, and evaluation of 

evidence-based cancer control programs. 

Users of the portal are assisted in “assessing 

the profile and risks of cancer within 

a state, identifying potential partner 

organizations already working with highrisk populations, understanding current 

research findings and recommendations, 

accessing evidence-based programs and 

products, and finding guidelines for 

planning and evaluation.”4 As part of this 

Web portal, PLANET provides detailed 

step-by-step instructions for its audience to 

establish a comprehensive cancer control 

program in the local setting. 

The portal also covers a wide range of 

cancer-related topics, including information 

on specific cancers (e.g., breast cancer), diet, 

nutrition, physical activity, tobacco control, 

and sun exposure safety. In the tobacco 

control domain, the same five-step approach 

to cancer control planning is used. The user 

audience can assess local program priorities 

based on state cancer profiles and risks for 

current smokers; identify local program and 

research partners involved in work related 

to cancer and tobacco control; determine 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

the effectiveness of different tobacco control 

interventions; access research-tested 

tobacco control programs and products; and 

plan and/or evaluate a local tobacco control 

program. Key aspects of this tobacco control 

portal that illustrate the KMT efforts are 

highlighted here.

n State cancer profiles and risk factor 

data on current smokers are available 

from sources such as the SEER registry 

program, the National Program of 

Cancer Registries, the Behavioral Risk 

Factor Surveillance System, and the 

Current Population Survey Tobacco Use 

Supplement. The types of information 

that can be obtained cover such areas 

as the prevalence of cancer for specific 

sites, incidence, mortality, and survival 

statistics, as well as smoking patterns and 

targets for smoking cessation in different 

population segments at the national and 

state levels and sometimes at the regional 

level. Coupled with additional statistics 

on local tobacco control policies and 

experiences, such knowledge resources 

can be used in planning specific tobacco 

control initiatives and evaluating their 

effectiveness based on local priorities 

and needs.

n Potential partners can be identified 

through up-to-date directories listing 

regional tobacco control programs and 

information on contacting researchers. 

The organizations listed in the program 

directory include the American Cancer 

Society, the CDC Tobacco Control 

Network, and NCI’s Cancer Information 

Service, which makes available regional 

representatives to provide coordination 

and support in local tobacco control 

initiatives. The researchers are potential 

partners who already are involved with 

tobacco control research in academic 

institutions, research foundations, or 

medical centers in different regions 

of the United States. These contacts 

provide the expertise and resources 

needed to plan, implement, and evaluate 

specific tobacco control initiatives at the 

local level.

n Effective research-based tobacco 

control intervention strategies include 

current systematic reviews and 

recommendations, available electronically 

via the Web from such sources as the 

Guide to Community Preventive Services,

the Clinical Guide to Tobacco Use 

Counseling, and the Clinical Practice 

Guideline on Tobacco Cessation. These 

evidence-based knowledge resources are 

distributed by reputable groups including 

the Community Preventive Services 

Task Force, the U.S. Preventive Service 

Task Force, the Public Health Service, 

the Agency for Healthcare Research and 

Quality, CDC, and NCI.

n Research-tested tobacco control 

programs and products are appraised 

for quality and made available to the 

audience according to their specific 

needs. NCI and the Substance Abuse and 

Mental Health Services Administration 

conduct ongoing peer reviews of 

scientifically tested tobacco control 

programs and products published by 

researchers for adoption by others. These 

knowledge resources can be downloaded 

at no cost and modified for local 

implementation by following specific 

guidelines for program adaptation. The 

adaptation includes determining the 

needs of the audience, working with 

expert advisors to maintain the integrity 

of the original program, pilot testing 

the modified program, and evaluating 

the implemented program for its 

effectiveness.

n Planning and evaluation of local tobacco 

control programs can be accomplished by 

using the comprehensive cancer control 

planning framework from CDC. This 

planning framework outlines a specific 

set of objectives, planning activities, 

and outcomes that should be addressed 
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to successfully implement a cancer 

control initiative such as a local tobacco 

control program. The processes outlined 

in the framework are based on actual 

experiences from several states that 

undertook comprehensive cancer control 

planning in recent years.

The design and implementation of PLANET 

as a dynamic knowledge repository have 

been an ongoing iterative process, with a 

great deal of effort spent on ensuring that 

it provides up-to-date knowledge resources, 

translated in ways that are usable to a wide 

range of audiences. An online “train-thetrainer” course also is available on PLANET, 

based on a 3.5-hour course delivered around 

the country through Comprehensive Cancer 

Control Leadership Institutes, to increase 

the uptake of PLANET in the field. When 

the site is accessed, limited information 

automatically is collected. The information 

includes the name of the domain and 

the Internet address of the provider, the 

Web site, and the computer used; the 

date and time of the visit; and the pages 

visited. Because of privacy concerns, it is 

not feasible to monitor how the audience 

actually uses the knowledge resources 

through the site, such as which products 

were downloaded from the Research-Tested 

Intervention Programs. A more formal 

evaluation on the effectiveness of PLANET 

will be conducted through a follow-up 

survey of those who have completed the 

3.5-hour in-person training. Other issues on 

enhancing the adoption and use of PLANET 

in tobacco control include the following:

n Finding ways to encourage successful 

champions to take the evidence on what 

works in tobacco control and make it 

theirs as part of the knowledge transfer 

process

n Developing a version of PLANET for 

clinicians, with additional features such 

as real-time delivery of evidence at the 

point of patient contact, with concise 

one-page fact sheets by topic area, to 

help them incorporate the available 

evidence as their choice of interventions 

in practice

n Translating the instruments used by 

researchers to simple program evaluation 

tools and sharing their experiences with 

the appropriate audience to encourage 

the adoption of evidence as part of 

practice norms

Surveillance, Epidemiology, and 

End Results Registry

The SEER program of cancer registries15

is a broad information source on cancer 

incidence and survival in the United 

States. When used in conjunction with its 

companion suite of analytic tools, SEER 

can be a valuable knowledge resource for 

statistics on cancer. Available statistics 

include the following:

n Cancer survival based on follow-up of 

cancer cases over time, measured in a 

number of different ways depending on 

intended purpose

•n Probabilities of developing or dying from 

cancer

•n Statistics that pool data from different 

sources to analyze cancer patterns and 

trends in particular segments of the 

population

The SEER program is an important 

knowledge resource for tobacco control, 

with its extensive repository of statistical 

evidence indicating that smoking is a major 

cause of many cancers.

Cancer Intervention Surveillance 

Network 

CISNET14 is a community of NCI-sponsored 

researchers who use modeling to improve 

understanding of the impact of cancer 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

control interventions (i.e., prevention, 

screening, treatment) on population trends 

in incidence and mortality. These models 

are also used to project future trends and 

to help determine optimal cancer control 

strategies. When possible, comparative 

modeling projects are undertaken to answer 

important cancer control questions using 

an agreed upon set of common model inputs 

and outputs. CISNET’s interactive, Webbased software for profiling models enables 

researchers to document components of 

their models in predefined templates. The 

synthesis of these disparate models into 

a common format enables comparison 

of model structures, tracking of model 

versions, searching of model components, 

and replication of the model and results by 

others. The design of CISNET has been an 

iterative process, ensuring that the tools 

developed are meaningful and useful to 

the research community. CISNET can be 

a valuable knowledge resource for tobacco 

control in terms of access to modeling 

expertise in predicting the effects of 

tobacco control interventions in cancer. 

One example is Levy’s recent simulation 

study17 of the effects of tobacco policy 

on lung cancer in the population. The 

findings provide insights on (1) the effects 

of tobacco policies on the number of deaths 

attributed to smoking, (2) whether new 

tobacco products and related products may 

reduce risk of cancer, and (3) finding ways 

to coordinate tobacco control policies with 

improved detection and treatment of lung 

cancer.

Consumer Health Profiles

Being able to narrow audiences based on 

more than demographic characteristics is 

a critical component of social marketing 

approaches. Audience segmentation systems 

rely on a combination of demographic 

and lifestyle data to define lifestyle groups 

and provide insights into how to market 

to them. Systems such as these are used 

extensively in consumer marketing and have 

been applied to social marketing campaigns 

since the mid-1990s. 

NCI has developed CHP,16 a tool to 

support the use of audience segmentation 

information by health education program 

planners and implementers. The profiles in 

CHP are summaries of the demographics, 

health care attitudes, behaviors, media 

habits, and lifestyle characteristics of 

consumers in selected “lifestyle clusters.” 

These profiles also outline suggested 

strategies for reaching these audiences 

with health information and behavioral 

interventions. Organizations can use 

these profiles along with maps and reports 

as a planning aid to identify and target 

underserved or at-risk populations most 

in need of cancer education and outreach 

programs. Used in conjunction with 

other resources such as the State Cancer 

Legislative Database,18 NCI’s Making 

Health Communications Programs Work: 

A Planner’s Guide (also known as the Pink 

Book),19 CDCynergy,20 and PLANET, CHP can 

be a valuable resource for knowledge about 

tobacco control. These resources can be 

helpful in developing intervention programs 

for tobacco control by using approaches 

such as social marketing to increase reach 

and efficacy in specific population segments 

(e.g., female teenage smokers).

The knowledge resources described here 

are illustrations of KMT efforts that NCI 

has undertaken over the last few years in 

cancer and tobacco control to produce, 

use, and refine explicit and tacit knowledge 

for a specific audience. Resources such 

as PLANET, SEER, and CHP can help 

stakeholders understand the patterns and 

effects of smoking and can reveal which 

tobacco control interventions are effective. 

In addition, the CISNET initiative can 

foster interactions and collaboration across 

different groups of stakeholders, encouraging 

them to work collectively toward a common 

set of agendas for tobacco control.
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Cancer Biomedical Informatics Grid: 

Evolving Knowledge Network

Launched by NCI in February 2004, 

caBIG13 is a collaborative initiative to 

build an integrated biomedical informatics 

infrastructure for sharing data, tools, and 

expertise. Nearly 900 individuals from 

more than 50 cancer centers and 30 other 

organizations across the United States 

were participating by the end of 2006. The 

overall aim of caBIG is to create a virtual 

community of researchers to expedite cancer 

research through the development of a set 

of common vocabularies and data elements, 

with standards-based software applications 

and technology platforms. It is expected 

that the researchers and organizations that 

make up this community will be able to 

easily share the resulting data, tools, and 

infrastructures. In addition, caBIG tools and 

infrastructure are freely available to all and 

are widely applicable beyond cancer.

Members of this virtual community have 

been working to define the agenda, projects, 

and priorities for this initiative. Activities 

of caBIG are organized into “workspaces,” 

each addressing a specific area of need 

identified by the community. The two types 

of workspaces are domain specific and 

crosscutting. Overall strategic planning 

and management and two types of working 

groups have been established to coordinate 

specific pilot projects within the workspaces. 

An online knowledge repository has been 

created as an inventory to store the data, 

application, and infrastructure artifacts and 

documentation generated to support various 

caBIG projects. NCI provides financial 

support for members to take part in these 

working groups and to work on specific 

projects. Current projects under the two 

workspaces are briefly described here.

Clinical trial management systems deploy 

existing and develop new information, 

applications, processes, services, and 

infrastructures used to support the design, 

implementation, and administration of 

clinical trials. Examples include (1) the 

caBIG clinical protocols portal, a Webbased application that enables researchers 

to share protocols; and (2) the C3D, a 

remote application that captures data 

for conducting clinical trials by using 

standardized vocabularies and common 

data elements.

In vivo imaging focuses on identifying the 

ways in which the wealth of information 

provided by such imaging, performed at 

academic and other research centers across 

the country, can be shared, optimized, 

and most effectively integrated. The in 

vivo imaging technologies and modalities 

addressed include systems for research and 

clinical imaging of live patients and animals 

(including single-cell organisms) used as 

model systems for human disease.

Integrative cancer research tools are 

being developed and deployed to enable 

integration and sharing of basic and clinical 

cancer research data among researchers 

at different centers. These include tools 

used to support research on pathway 

mapping, proteomics, microarrays, and gene 

expression. In addition, raw data can be 

shared across platforms and organizations.

Tissue banks and pathology tools are 

being developed and deployed to enable 

the integration and sharing of information 

from repositories of cancer specimens from 

cancer research centers. These include tools 

that can enhance identification of tissue 

banks and access to research samples. They 

can also leverage existing sample-tracking 

systems and management systems for 

pathology information, providing additional 

support for decision making and analytic 

capabilities. 

Vocabularies and common data elements

refer to the development of cancer ontology 

content and standardization of clinical terms 
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used in cancer research. Examples include 

the NCI National Cancer Data Standards 

Repository and the Common Data Elements 

development and harmonization program. 

Because these activities and resources are 

part of the crosscutting workspace, it is 

expected that the outputs will be shared 

among other working groups and their 

projects under the domain workspace.

The architecture workspace is involved 

in developing architectural policies and 

standards based on the open-source 

environment principles. Its purpose is 

to ensure consistent application of these 

principles across groups in the caBIG 

community and to achieve seamless 

integration and sharing of the knowledge 

resources in cancer research.

In 2006, caBIG added a new special interest 

group focusing on population science. Its 

work includes analyzing key opportunities 

for and barriers to using informatics to 

strengthen population science, including 

data sharing and intellectual property 

issues, interoperability issues, and specific 

tools to enable population research (such 

as tools for generating standardized 

questionnaires).

An evolving informatics infrastructure, 

caBIG connects researchers and 

organizations in cancer and biomedical 

research to accelerate the pace at which 

their activities can be conducted in a 

coordinated and collaborative manner. 

Although its current emphasis is on the 

cancer and biomedical research community, 

the philosophy, objectives, framework, and 

process of caBIG can be readily applied to 

bringing stakeholder groups together to 

advance the field of tobacco use prevention 

and control. More important, the tobacco 

control field can build directly on caBIG’s 

interoperable infrastructure and tools to 

avoid both duplicating efforts and creating 

new “silos” that do not permit researchers to 

integrate data from multiple sources.

Systems-Level Tobacco Control 

Knowledge: Missing Pieces

Over the years, the tobacco control 

community has made great strides in the 

prevention and control of tobacco use 

by conducting research on smoking and 

implementing tobacco control policies 

and intervention programs. A vast amount 

of knowledge about tobacco control has 

been accumulated during this time, as is 

illustrated through the various KMT efforts 

in tobacco and related cancer control 

initiatives at NCI. However, for some aspects 

of tobacco control, knowledge is missing, 

incomplete, or conflicting, especially at the 

systems level. Such deficiencies are seen as 

major obstacles to effective prevention and 

control of tobacco use in society. 

During the discussion meetings on KMT, the 

key informants offered their views on the 

major types of tobacco control knowledge 

that they perceived to be missing, incomplete, 

or conflicting. These obstacles include the 

following and are described below: 

n Lack of current data on the tobacco 

industry

n Need for knowledge about current 

activities in tobacco control

n Need for knowledge of current needs in 

tobacco control efforts and who should 

address these needs

n Lack of “receptor capacity” in local settings, 

in terms of the ability of some local 

program staff with insufficient expertise 

and experience to absorb new ideas 

n Need to make research findings more 

relevant

Lack of intelligence about the tobacco 

industry is problematic because the industry 

constantly adapts to counter tobacco 

control efforts and maintain profits.21,22

Without such intelligence it is difficult to 
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know where attention should be focused 

and where the scarce resources should be 

deployed to anticipate and counteract the 

actions of the industry.

Knowing who is doing what in tobacco 

control is difficult. Many stakeholders are 

committed to tobacco control, and new 

initiatives, such as research findings, policy 

initiatives, and intervention programs, are 

continually being introduced. Even though 

these diverse initiatives are worthy in their 

own right, they tend to put tobacco control in 

a constant state of flux, making it difficult to 

keep abreast of all the happenings in the field.

Knowing who should do what in 

tobacco control also is difficult, because 

stakeholders, such as policy makers, 

researchers, practitioners, and the 

public, may have their own agendas, 

priorities, and so they engage in tobacco 

control in different ways. Such diverse 

motivations have led to duplication of 

efforts, competition for resources, and even 

conflicting results. Some efforts have been 

made to improve communication among 

stakeholders, but better coordination and 

collaboration still are needed.

Lack of receptor capacity in tobacco control 

in local settings is another obstacle to 

efficacious tobacco control. The concept 

of “receptor capacity” refers to the ability 

to absorb new ideas and paradigms. It 

has become an increasingly key issue as 

stakeholder organizations restructure 

their public health programs and combine 

multiple initiatives (e.g., obesity, smoking, 

and physical activity), often with reduced 

funding and human resources. Consequently, 

some local program staff have insufficient 

expertise and experience in tobacco control 

and thus do not know what knowledge is 

needed, where to find this knowledge, or 

how to apply it in the local setting.

Research should be more relevant to 

practitioners so it can be more applicable 

in the field setting. The current funding 

mechanisms are largely research driven, 

and less attention is given to the needs of 

stakeholders. This situation has led to gaps 

between the results of research and the 

knowledge required in the field to develop 

effective tobacco control programs. There 

also is a perception that tobacco control 

researchers conduct their studies, publish 

their findings, and move on to the next 

project without translating their knowledge 

into meaningful instruments that can be 

used by tobacco control policy makers and 

practitioners.

National Cancer Institute’s 

Emerging Knowledge 

Management and Translation 

Infrastructure

The knowledge resources and initiatives 

described thus far represent selected KMT 

efforts that NCI has undertaken over the 

past years. These efforts have evolved both 

as part of an overall organizational strategy 

and from the practical day-to-day need 

to move the cancer and tobacco control 

agendas forward. Here, these KMT efforts 

are examined under the lens of the proposed 

framework for KMT strategy. Thus, how 

the field of public health can move toward 

a systems view of establishing a coherent 

KMT strategy, leading to the intended 

KMT outcomes, can be demonstrated. The 

components of the strategy maps for 4PKMT infrastructure are briefly described 

by using tobacco control as the focus. The 

illustrations include both existing KMT 

efforts in tobacco control through NCI and 

suggested efforts drawing on those from 

cancer control. 

Tobacco Control and Related 

Knowledge Resources

Based on the types of tobacco control and 

related knowledge resources described 
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earlier in this chapter, an example of 

a high-level map of tobacco control 

knowledge can be produced according to 

explicit and tacit knowledge. The knowledge 

resource examples included are PLANET, 

SEER, CISNET, CHP, and caBIG. All of these 

resources are considered explicit knowledge 

in that they capture specific knowledge 

related to tobacco and/or cancer control 

as tangible objects. In addition, some of 

these resources, notably caBIG, focus 

more on the interaction of tacit knowledge 

with explicit knowledge by nurturing 

the formation of face-to-face and virtual 

knowledge networks within and between 

organizations. 

This knowledge map also identifies systemslevel knowledge sources for tobacco control 

that are perceived to be missing, incomplete, 

or conflicting. Examples include public data 

on tobacco industry strategies and products; 

a coordinated agenda for tobacco control 

research and practice; existing tobacco 

control policy, research, and practice 

initiatives; knowledge brokers at the local, 

state, and national levels; and improved 

mechanisms for knowledge translation, 

especially by researchers. Table 7.4 shows 

this high-level example of a tobacco control 

knowledge map.

4P-Knowledge Management and 

Translation Strategy for Tobacco 

Control

Again, the strategic components of the 4PKMT strategy for tobacco control at NCI 

are purpose, people, process, and products. 

For each strategic action, the actionable 

items that should be considered to achieve 

effective tobacco control can be defined. 

Related resources for knowledge of cancer 

control (e.g., CISNET and caBIG) should 

be expanded, adapted, and adopted for the 

tobacco control domain. The 4P strategic 

actions and the corresponding actionable 

items are described here.

Purpose

The relevant agenda, timelines, and 

business case for the production, use, and 

refinement of the resources for tobacco 

control knowledge at NCI need to be defined 

based on the specific audiences, their 

motivations, and translation mechanisms. 

The knowledge should include (1) resources 

for the explicit and tacit knowledge of 

tobacco control currently managed at NCI 

and other stakeholder organizations, and (2) 

the systems-level tobacco control knowledge 

viewed as missing or incomplete.

Table 7.4 High-Level Map of Tobacco Control Knowledge

Type of 

knowledge Explicit knowledge Tacit knowledge

Policy PLANET, caBIG, tobacco industry data, 

TC agenda, existing TC initiatives, 

knowledge translation

caBIG, tobacco industry data, TC agenda, 

existing TC initiatives, knowledge translation

Evidence PLANET, SEER, CISNET, caBIG, existing 

TC initiatives, knowledge translation

caBIG, existing TC initiatives, knowledge 

translation

Experience PLANET, CISNET, CHP, tobacco intelligence, 

existing TC initiatives, knowledge 

translation

tobacco intelligence, existing TC initiatives, 

knowledge translation

Contact PLANET, CHP, existing TC initiatives, 

knowledge brokers, knowledge 

translation

caBIG, existing TC initiatives, knowledge 

brokers, knowledge translation

Notes. PLANET = Plan, Link, Act, Network with Evidence-based Tools; caBIG = Cancer Biomedical Informatics Grid; TC = tobacco 

control; SEER = Surveillance, Epidemiology, and End Results; CISNET = Cancer Intervention and Surveillance Modeling Network; 

CHP = Consumer Health Profiles. 
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People

There is a need to identify the champions 

of tobacco control knowledge, brokers and 

managers, architects, and communities of 

practice within and outside NCI who can 

help to define and implement the resources 

for tobacco control knowledge needed as 

part of the emerging KMT strategy. This is 

especially true for tobacco control knowledge 

at the systems level in ways that can benefit 

the entire tobacco control community.

Process

Rigorous yet adaptable methods and 

approaches must be used to encourage 

interaction and collaboration among 

stakeholder organizations using the 

knowledge infrastructure at NCI. The 

tobacco control community needs methods 

for consensus building and capacity building, 

development of tobacco control knowledge 

resources, and a network in which tobacco 

control knowledge converges. These methods 

should be sufficiently generic to incorporate 

different knowledge domains, including 

tobacco control and other areas as needed.

Products

Appropriate groupware that can facilitate the 

various communication, coordination, and 

collaboration tasks needed by the tobacco 

control community needs to be incorporated 

in knowledge resources. This groupware 

includes technologies such as real-time 

Web conferencing, asynchronous discussion 

forums, and brainstorming and conceptmapping tools. Also needed are robust 

knowledge repositories with the appropriate 

navigation and access tools that can be used 

to manage and translate the resources for 

tobacco control knowledge available through 

and needed by the tobacco control community.

Knowledge Management and 

Translation Infrastructure: Strategy 

for Tobacco Control 

Application of the principles of KMT 

infrastructure outlined in this chapter as 

a strategy for tobacco control at NCI can 

be examined in terms of the underlying 

organization, technology, information, and 

finance infrastructures needed. For each 

strategic infrastructure, parameters for 

corresponding infrastructure that could 

help achieve a more effective knowledge 

framework for tobacco control can be 

proposed. Strategic components and 

corresponding parameters for infrastructure 

are described here.

Organization

There is a need to define the organizational 

structures, procedures, and norms 

appropriate for the production, use, and 

refinement of resources for tobacco control 

knowledge aimed at specific audiences based 

on their motivations and through tailored 

translation mechanisms. Because of the large 

number of stakeholders involved in tobacco 

control, the organizational infrastructures 

being used must be sufficiently flexible and 

adaptable to accommodate the different 

bureaucracies that are in place. 

Technology

Appropriate computer applications, 

networks, and connectivity components 

must be incorporated to ensure that the 

technology infrastructure can support the 

deployment of the proposed KMT framework 

for tobacco control. This infrastructure 

needs to support the ongoing interactions 

of the tobacco control community, as well 

as the day-to-day management and use of 

robust online repositories of knowledge 

and tools for knowledge development and 

navigation and access by different tobacco 

control stakeholders within and outside 

individual organizations.

Information

Electronic databases, library resources, and 

data dictionaries relevant to tobacco control 

need to be established. In particular, there is 

a need (1) to synthesize the vast amount of 

information on tobacco control and related 

issues, including all relevant tobacco control 
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policies, practices, and experiences; and (2) 

to coordinate contact information for use by 

the tobacco control community.

Finance

There is a need to establish a balanced 

investment portfolio so that the resources 

for tobacco control knowledge can be used 

effectively. A means of evaluating these 

resources as intellectual assets must be 

established. Where feasible, the return on 

investment for the production, use, and 

refinement of specific resources for tobacco 

control knowledge for selected audiences 

should be estimated.

Knowledge Management and 

Translation Strategy and Outcome 

Maps for Tobacco Control

The strategies for 4P-KMT and KMT 

infrastructures for tobacco control can be 

expanded by creating the corresponding 

detailed strategy and outcome maps. The 

intent of these maps is to provide a set of 

checklists that can be helpful for planning 

and implementing the KMT infrastructure 

for tobacco control. Figure 7.6 and tables 7.5 

and 7.6 show examples of these maps. 

KMT efforts, which often have their roots 

in addressing specific needs, must move 

toward a greater level of synthesis to serve 

the future global needs of tobacco control. 

Initial efforts in this area have tended to be 

largely centered on databases. The 4P-KMT 

framework outlined here provides a valuable 

mechanism for extending these efforts to a 

more integrated environment encompassing 

the needs of its stakeholders for both explicit 

and tacit knowledge. This environment has 

the potential to move in some important 

directions:

n From contact directories to repositories 

of tacit knowledge

n From data sources to an integrated KMT 

environment

n From silos of information and knowledge 

created for specific needs to an 

infrastructure for the global knowledge 

needs of tobacco control, driven by the 

4P-KMT framework

Moreover, these needs point to the 

importance of integrating the KMT 

environment for tobacco control with other 

systems efforts. Examples include using 

network analysis as a factor in managing 

tacit knowledge, integrating KMT with data 

that drive systems models, and leveraging 

a systems management environment in the 

ongoing planning and oversight process 

inherent to the 4Ps. Seen as part of an 

integrated systems environment, the efforts 

in process in tobacco control research and 

programs form the beginnings of a valuable 

knowledge infrastructure for tobacco 

control, with the aid of a more global view 

of their future evolution.

Case Study: 

Concept Mapping 

of Knowledge Base 

for Tobacco Control

One case study illustrates several key 

components of the KMT framework. It 

involves use of concept mapping to help 

create a knowledge base for tobacco control. 

(See chapter 4 for a more detailed description 

of methodology for concept mapping.) In 

this case study, planners from stakeholder 

organizations in the public and private 

sectors were identified and brought together 

through a coordinated effort to generate 

new tobacco control knowledge in a way that 

could be codified, stored, and packaged. In 

doing so, these planners engaged in a process 

of knowledge translation. They socialized 

through the planning session and articulated 

their tacit knowledge on tobacco control 

as ideas that eventually were turned into 

formal explicit knowledge. As the audience 
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Figure 7.6 4P-Knowledge Management and Translation (KMT) Strategy Maps: Templates for 

Knowledge Resources Needed in Tobacco Control

caBIG-TC

CISNET

Consumer Health Profiles

SEER

PLANET Production Use Refinement

Audience Motivations Mechanisms Audience Motivations Mechanisms Audience Motivations Mechanisms

Purpose Agenda

Relevance

Timelines

Case

People Agenda

Relvance

Timelines

Case

Process Agenda

Relevance

Timelines

Case

Products Agenda

Relevance

Timelines

Case

Notes. caBIG-TC = Cancer Biomedical Informatics Grid; CISNET = Cancer Intervention and Surveillance Modeling Network; 

SEER = Surveillance, Epidemiology, and End Results; PLANET = Plan, Link, Act, Network with Evidence-based Tools.

Table 7.5 Example of Detailed Knowledge Management and Translation (KMT) Strategy 

Checklist for Cancer Control PLANET: One Knowledge Resource Being Deployed 

in Tobacco Control

PLANET-RTIPs

Production

Audience Motivations Mechanisms

Purpose

Agenda Encourage researchers, 

policy makers, practitioners, 

and the public to participate 

in RTIPs; increase total 

number of RTIPs available

Identify specific motivations 

for researchers, policy 

makers, practitioners, and 

the public that can increase 

their participation in RTIPs

Increase socialization, 

articulation, and 

internalization opportunities 

for researchers, policy 

makers, practitioners, and 

the public to promote RTIP 

participation

Relevance Determine relevance of 

RTIPs for specific audiences 

to increase participation

Determine relevance of 

RTIPs based on audience 

motivations for decision, 

education, innovation, 

or advocacy to increase 

participation

Translate relevant RTIPs 

with timelines to specific 

audiences through 

articulation, internalization, 

or socialization to increase 

participation

Timelines Establish timelines to 

implement RTIPs for 

audiences that can increase 

their participation

Establish timelines to 

implement RTIPs based 

on specific audience 

motivations for decision, 

education, innovation, or 

advocacy

Translate relevant RTIPs 

with timelines to specific 

audiences through 

articulation, internalization, 

or socialization to increase 

participation

Case Develop business case to 

justify the value of RTIPs 

to specific audiences to 

increase participation

Develop business case to 

justify RTIPs with timelines 

based on specific audience 

motivations for decision, 

education, innovation, 

and advocacy to increase 

participation

Translate business case 

with justified relevant 

RTIPs and timelines to 

specific audiences through 

articulation, internalization, 

or socialization to increase 

participation

Notes. PLANET = Plan, Link, Act, Network with Evidence-based Tools; RTIPs = Research-Tested Intervention Programs.
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of this process of knowledge translation, the 

planners assumed the roles of researchers, 

policy makers, practitioners, and the public. 

They were motivated by the innovation 

in creating a tobacco control knowledge 

base. They used the mechanisms of concept 

mapping to articulate their ideas from tacit to 

explicit knowledge.

Two support companies conducted 

this project on behalf of CDC to create 

a conceptual framework to guide the 

development of a knowledge base for 

use in tobacco control programs and 

research. The project engaged members 

of a diverse stakeholder group in a process 

that mapped their ideas and defined a 

taxonomy for the subsequent knowledge 

base. A planning group identified an 

initial group of 36 participants, including 

stakeholders in the private and public 

sectors at federal, state, and local levels. 

They were asked to brainstorm ideas by 

completing the following focus prompt: 

“Specific information I would need to 

plan, implement, and evaluate a tobacco 

prevention and control program or to 

conduct tobacco control research is...”

The participant group generated 184 ideas, 

which the planning group synthesized into 

a set of 97 unique ideas used in subsequent 

Table 7.6 Example of Knowledge Management and Translation (KMT) Strategy and Outcome 

Map for Tobacco Control, Based on Resources for Tobacco Control Knowledge and 

Potential Linkage to Desired Outcomes

Type of 

knowledge Evidence base

Science–practice 

linkage

Implementation

framework

Interaction and 

collaboration 

methodology

PLANET n State cancer profiles 

relevant to TC n RTIPs n Community guides 

on TC 

n RTIPs for TC n Feedback on local 

TC programs

n Five-steps planning 

approach for TC n CDC cancer control 

planning framework 

adapted for TC

Contact list of regional 

TC programs and 

researchers

SEER Cancer epidemiology 

and statistics relevant 

to TC

People/population 

statistics for TC

Companion suite 

of tools for data 

collection, analysis, 

and reporting on TC

Sharing of experience 

with people and of 

population statistics 

for TC

CISNET n Modeling of TC 

impacts n Metadata-level 

description of 

models

Replication of model 

and results with local 

data on TC

Iterative design 

process to share 

metadata-level 

description of models

Modelers to 

understand and share 

models through 

metadata-level 

description

CHP Lifestyle clusters on 

tobacco use

Feedback on lifestyle 

clusters and link to TC

Combined use with 

other resources such 

as CDC Pink Book and 

State Legislations 

Database on TC

caBIG n Relevance of TC 

research n Feedback on TC 

programs 

TC agendas, policies, 

and infrastructures 

and projects for TC 

community

Workspaces and 

working groups for 

different focuses of 

TC (e.g., more smoking 

prevention, cessation, 

and environment)

Notes. PLANET = Plan, Link, Act, Network with Evidence-based Tools; TC = tobacco control; RTIPs = Research-Tested Intervention 

Programs; CDC = Centers for Disease Control and Prevention; SEER = Surveillance, Epidemiology, and End Results; CISNET = Cancer 

Intervention and Surveillance Modeling Network; CHP = Consumer Health Profiles; caBIG = Cancer Biomedical Informatics Grid.
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analyses. Each participant was asked to 

sort these statements into categories that 

made sense and to rate each statement 

for importance on a scale of 1 to 5 

(1 = relatively unimportant; 5 = extremely 

important).23–25

A concept mapping analysis26 was then 

performed on these statements to organize 

and display this information in a series of 

easily readable concept maps and displays 

for pattern matching.27–29 These maps show 

the relationships among the 97 ideas, the 

clustering of the ideas into themes or issues, 

and the relative importance of the ideas as 

rated by the participants (figure 7.7).

The multivariate analysis generated maps 

and other statistical results that participants 

then interpreted in a structured, facilitated 

session. Using the concept map analysis, the 

participants identified 12 clusters of issues 

relevant to knowledge management in tobacco 

control: (1) data on knowledge, attitude, and 

behavior; (2) evaluation; (3) tools to assess 

capacity; (4) collaboration for sustainability; 

(5) models and methods; (6) planning; 

(7) smoking cessation; (8) tobacco industry; 

(9) background; (10) legislation; (11) impact 

of policy; and (12) influencing policy.

Participant ratings then were displayed 

graphically on a concept map, with clusters 

that represent groupings of ideas mapped 

according to their relationship(s). Rating 

values are shown as the height of individual 

clusters, with higher clusters relatively 

more important. For instance, the clusters 

for “evaluation, knowledge, attitude, and 

behavior data,” and “tobacco industry” were 

seen as relatively important; and the cluster 

for “smoking cessation” was ranked lowest 

in importance. Figure 7.7 shows this cluster 

rating map. The planning group used these 

clusters and their ratings to create the 

taxonomy shown in table 7.7 for the planned 

knowledge base for tobacco control.

The taxonomy categories and the 97 

statements within categories provide a 

Figure 7.7 Cluster Rating Map for Tobacco Knowledge Base

Tobacco Industry

Influencing Policy

Background

Cessation

Models and Methods

Planning

Legislation

Impact of Policy

Evaluation

Tools to Assess Capacity

Knowledge, Attitude

and Behavior Data

Collaboration for Sustainability
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

comprehensive and detailed list of issues 

that should be considered in developing a 

tobacco control knowledge base. The concept 

map clusters and the ultimate taxonomy 

categories are closely correlated. Moreover, 

the statements in each cluster provide details 

on specific information the stakeholders 

wanted to see in the knowledge database. 

For example, statements in the highest rated 

cluster, “evaluation,” included both evaluation 

methods and measures for tobacco control, as 

well as their relationship to outcomes. Typical 

statements included the following:

n “Examples of evaluation designs and 

evaluation tools that could be adapted”

n “Identification of key indicators for 

evaluation—what to measure and 

monitor”

n “Measures for evaluation of health 

outcomes such as decrease in tobaccoattributable morbidity and mortality”

Similarly, statements within the cluster for 

“tobacco industry” ranged from marketing 

initiatives and policy positions to specific 

tactics to counter tobacco control efforts. 

Participants in the highly rated cluster for 

“knowledge, attitude, and behavior data” 

proposed data sources ranging from public 

attitudes to hard data (e.g., population 

surveillance data). Some of statements 

for this cluster, such as “Indicators and 

data sources for each major goal area,” 

also pointed to sublevels of taxonomy to 

be considered within the design of the 

knowledge base.

The process the planning group followed 

in defining this taxonomy from the 

concept maps serves as a good example 

of how stakeholder input can evolve into 

a pragmatic, deliverable outcome. It was 

informed by both the participant statements 

and the clusters resulting from an analysis 

of these statements, as well as participant 

ratings of these cluster categories. The end 

result was a knowledge base taxonomy that 

was isomorphic and in many cases identical 

to the categories derived from participant 

data.

Table 7.7 Categories for Knowledge Base Taxonomy and Related 

Clusters from Concept Mapping

Concept map clusters Taxonomy category

Legislation

Influencing policy

Policy

Influencing policy Influencing policy

Impact of policy Impact of policy

Planning 

Background 

Models and methods

Policy and program planning

Evaluation Policy and program evaluation

Knowledge, attitude, and behavior data Sources of data

Tools to assess capacity Assessment tools

Models and methods Models and methods

Collaboration for sustainability Working with communities

Tobacco industry Tobacco industry

Background History of tobacco control

Smoking cessation Smoking cessation

Models and methods Harm reduction
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In addition to analyzing participant input to 

help define the knowledge base categories, 

the process provided valuable input on 

how subgroups of participants differ about 

what is important. Using a technique 

known as pattern matching,27–29 the project 

compared relative importance ratings 

of several subgroups, including federal 

versus state and local levels of government 

and participants from the public sector 

versus those not from the public sector. 

Private-sector participants include 

stakeholders such as private industry and 

nongovernmental organizations. 

Figure 7.8 shows results of two pattern 

matches. The correlation between 

cluster importance ratings for the federal 

government versus those in state or local 

government was extremely high (r = .94). 

This finding indicates strong agreement 

on the relative importance of these ideas 

for inclusion in a database for tobacco 

knowledge management. However, the 

correlation between cluster importance 

ratings in the public sector and those not 

in the public sector was relatively lower 

(r = .55). This finding indicates that the 

two groups have different opinions about 

what should be included in the database 

for tobacco knowledge management. 

Representatives from public agencies 

thought that the importance of including 

ideas related to evaluation was high. 

Representatives from nonpublic agencies 

ranked ideas related to “knowledge, attitude 

and behavior data” as more important. 

This concept-mapping study had several 

immediate products. First, it created 

the potential categories for a knowledge 

management database for tobacco 

prevention and control. The detailed 

statements in each category provide more 

specific information to guide knowledge 

management. In addition, the process 

enabled prioritization of categories, 

indicating which should be emphasized 

in the database. Perhaps most important, 

the process provided a summary of the 

Concept Mapping and the 4P-Knowledge Management and Translation (KMT) Approach

The case study outlined here not only serves as a practical example of designing a knowledge base 

taxonomy from stakeholder input, but it also aligns in several key ways with the 4P approach 

outlined earlier for designing KMT strategy and infrastructure. As discussed at the beginning of 

this case study, this project served above all as a structured process that acquired tacit knowledge 

and translated it to explicit knowledge. Other parallels include the following:

n The tobacco prevention and control knowledge concepts derived from concept 

mapping serve as an innovative method of knowledge generation, as part of the 

knowledge production process.

n By including a wide range of stakeholders and analyzing their responses, this process 

highlights the generation of new knowledge by a specific audience on the basis of their 

motivations, by using the mechanism of articulation to translate tacit knowledge into 

an explicit form.

n Use of a visual map for linking knowledge to the evidence base and the science–

practice linkage is similar to the broader process described earlier of creating a 4PKMT infrastructures strategy map in designing a knowledge infrastructure.

The end product of this process is highly relevant tobacco knowledge that can be applied as 

explicit knowledge resources by using the KMT infrastructures mentioned earlier. Moreover, this 

knowledge can be expanded by using 4P-KMT strategy maps to detail the purpose, people, process, 

and products, as part of an integrated KMT effort.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Figure 7.8 Pattern Matching to Compare Importance of Cluster Ratings in Demographic 

Subgroups of Participants (correlation coefficient, r)

r = .94

Federal State/Local

4.1

3.1

4.04

2.87

Cessation

Background

Impact of Policy

Legislation

Tools to Assess Capacity

Collaboration for Sustainability

Planning

Models and Methods

Influencing Policy

Knowledge, Attitude

and Behavior Data

Tobacco Industry

Evaluation

Cessation

Impact of Policy

Background

Legislation

Tobacco Industry

Tools to Assess Capacity

Influencing Policy

Planning

Models and Methods

Collaboration for Sustainability

Knowledge, Attitude

and Behavior Data

Evaluation

r = .55

Public Non Public

4.04

2.87

3.86

3.23

Cessation

Collaboration for Sustainability

Tools to Assess Capacity

Impact of Policy

Planning

Legislation

Evaluation

Influencing Policy

Models and Methods

Background

Tobacco Industry

Knowledge, Attitude

and Behavior Data

Cessation

Background

Impact of Policy

Legislation

Tools to Assess Capacity

Collaboration for Sustainability

Planning

Models and Methods

Influencing Policy

Knowledge, Attitude

and Behavior Data

Tobacco Industry

Evaluation
216

7 . W h a t W e K n o w : M a n a g i n g t h e K n o w l e d g e C o n t e n t

perspectives of key stakeholders in the 

tobacco control field with regard to crucial 

elements and priorities for inclusion in this 

database. Through this process, a consensus 

framework based on the ideas of the 

participants was created.

Summary

An integrated KMT strategy for tobacco 

control is outlined here. This strategy, 

in turn, addresses a larger goal—the 

broad sharing of knowledge in a systems 

environment and the sustainability of this 

knowledge as this system evolves. As the 

tobacco control community moves toward 

this goal, it increases its ability to address 

more complex issues and improve public 

health outcomes.

The tobacco control domain is complex 

and dynamic, and many stakeholders are 

involved. Stakeholders in this domain need 

to address parts of a puzzle. However, no 

one has all the current requisite knowledge 

to understand or address the entire system. 

The kinds of knowledge needed range from 

very specific information, such as how many 

schools have effective smoke-free policies 

or ongoing statistics on use of hotlines 

for help in stopping smoking (quitlines), 

to the broad base of tacit information 

required for sharing of best practices or 

network building. Where can one find this 

knowledge, and how valid is it? How will 

this knowledge be updated over time? A 

system must be developed to collect and 

synthesize such knowledge for distribution 

and sharing, without causing information 

overload for the tobacco control community.

The fundamentals of a KMT infrastructure 

for the tobacco control domain are outlined 

here as a step toward the systematic 

production, use, and refinement of explicit 

Integrating Knowledge Management and Translation (KMT) with a

Systems Approach to Tobacco Control

Beyond serving as a technology infrastructure for sharing information, KMT strategies have the 

potential to share a base of knowledge that helps the tobacco control environment evolve and, 

as such, form an important part of the systems strategies discussed in other chapters of this 

monograph.

A key example is in the interface between KMT and tobacco control networks. Overcoming turf 

issues and developing more effective collaboration are critical to advancing the tobacco control 

community as a whole. Other relevant objectives include better coordination of initiatives 

from different stakeholder organizations; improved translation mechanisms to enable sharing 

of tobacco control knowledge in ways that are relevant and meaningful to the stakeholder 

organizations; and translating tobacco control knowledge into action that can be implemented 

by practitioner communities. Ongoing dialogue that results from bringing researchers, 

practitioners, policy makers, and the public together to engage in such activities as joint 

planning, sharing lessons, role playing, and thinking outside the box can help the tobacco control 

community become a network of tobacco control knowledge. 

Another challenge is to keep abreast of the strategies and actions of the tobacco industry. As 

discussed in chapter 2, this approach is analogous to the concept of disease in epidemiology. The 

host (human) has an illness (cancer) caused by an agent (tobacco) through a vector (tobacco 

industry). The vector and the agent, in this case the tobacco industry and tobacco products, 

respectively, are in a constant state of flux and disguise, leading to manifestations of the illness 

in varying forms and severity in unsuspecting or maimed hosts. The tobacco control community 

needs knowledge to be able to anticipate and counter tobacco industry actions.
217

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

and tacit tobacco control knowledge 

for specific audiences, based on their 

motivations, through different translation 

mechanisms. A strategic approach to KMT 

can advance such efforts from a projectby-project basis to becoming a coherent 

knowledge infrastructure, in which tobacco 

control and other initiatives can converge as 

a comprehensive set of knowledge resources. 

By addressing the respective components 

of the KMT framework, at the level of detail 

that makes sense for the organization based 

on its expertise and resources, the tobacco 

control community can advance to work 

collaboratively as a network of tobacco 

control knowledge enabled by technology.

Conclusions

1. Effective knowledge management is 

based on a social context revolving 

around knowledge production, use, 

and refinement, as well as an ecological 

context based on audience, motivations, 

and mechanisms.

2. A formal strategy for knowledge 

management is essential to the creation of 

a consistent knowledge environment. One 

framework defines knowledge capabilities 

in terms of purpose, people, process, and 

products, together with a knowledge 

management and translation infrastructure 

defined in terms of its underlying 

organization, technology, information, and 

finance infrastructures.

3. A review of resources for tobacco control 

knowledge at the National Cancer 

Institute confirmed the existence of 

extensive resources for tobacco control, 

combined with growth areas for the 

future, such as integration, visibility 

among stakeholders, and knowledge 

gaps.

4. A concept-mapping project that 

engaged stakeholders to examine 

specific information needed for tobacco 

prevention, control, or research yielded 

clusters of knowledge categories that 

helped form the taxonomy for a planned 

knowledge base for tobacco control.
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7 . W h a t W e K n o w : M a n a g i n g t h e K n o w l e d g e C o n t e n t

Appendix 7A. 4P-Knowledge Management 

and Translation Infrastructures: Strategy and 

Outcome Maps

The infrastructures map is focused on the actionable items under the strategy of four Ps 

(purpose, people, process, and product). The map takes into account the underlying issues of the 

infrastructure for knowledge management and translation (KMT) and the desired outcomes, to 

establish a comprehensive KMT infrastructure. Figure 7A.1 shows this strategy map.

Depending on need, the components of this 4P-KMT infrastructures strategy map can be 

expanded to provide further details. The actionable items in the 4P-KMT and the KMT 

infrastructures strategies can be elaborated into detailed strategy maps for each type of 

knowledge involved. In addition, each of the actionable items can be further elaborated into 

detailed checklists that can be used in final implementation planning and execution. The KMT 

strategy also can be mapped to outcomes to ensure that they are being achieved. Figures 7A.2 

and 7A.3 and table 7A.1 provide examples of detailed KMT strategy maps.

Figure 7A.1 4P-Knowledge Management and Translation (KMT) Infrastructures Strategy Map

PRODUCTION

Creation 

Collection

Generation

Synthesis

Identification

Organization

Codification

Storage

Packaging

Coordination

4P-KMT OUTCOMES

INFRASTRUCTURES

KNOWLEDGE TRANSLATION

Purpose

People

Process

Product

Organization, Information, Technology, Finance 

USE

Distribution

Sharing

Application

Adaptation

REFINEMENT

Integration

Evaluation

Reflection

Sustainability

KNOWLEDGE MANAGEMENT

AUDIENCES

Policy maker

Practitioner

Researcher

Public

MOTIVATIONS

Decision

Education

Innovation

Advocacy

MECHANISMS

Combination

Articulation

Internalization

Socialization Evidence

Base

Science-Practice

Linkage

Implementation

Framework

Interaction &

Collaboration

Methodology
219

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Another important knowledge map links the knowledge resources to the corresponding 

outcomes. The rationale for this knowledge-outcome map is to ensure that the KMT strategy 

for each type of knowledge resource being deployed is able to accomplish the intended 

Figure 7A.2 Detailed Knowledge Management and Translation (KMT) Strategy Map: 

Template for 4P-KMT and KMT Infrastructures

PRODUCTION

Creation 

Collection

Generation

Synthesis

Identification

Organization

Codification

Storage

Packaging

Coordination

4P-KMT OUTCOMES

INFRASTRUCTURES

KNOWLEDGE MANAGEMENT AND TRANSLATION

Purpose

People

Process

Product

Organization, Information, Technology, Finance 

USE

Distribution

Sharing

Application

Adaptation

REFINEMENT

Integration

Evaluation

Reflection

Sustainability

KNOWLEDGE MANAGEMENT

AUDIENCES

Policy maker

Practitioner

Researcher

Public

MOTIVATIONS

Decision

Education

Innovation

Advocacy

MECHANISMS

Combination

Articulation

Internalization

Socialization Evidence

Base

Science-Practice

Linkage

Implementation

Framework

Interaction &

Collaboration

Methodology

Production-AMME Use-AMME Refinement-AMME

Purpose

People

Process

Products

Knowledge champions, brokers,

architects and communities with

specific audience, motivations 

and mechanisms

Agenda, relevance, timelines,

business case for specific 

audience, motivations and 

mechanisms

Groupware, repositories and 

development tools for specific 

audience, motivations and 

mechanisms

Groupware, repositories 

nativation/access tools for 

specific audience, motivations 

and mechanisms

Consensus and capacity building, 

knowledge and network 

development for specific 

audience, motivations and 

mechanisms

Groupware, repositories and 

development tools for specific 

audience, motivations and 

mechanisms

Groupware, repositories 

nativation/access tools for 

specific audience, motivations 

and mechanisms

Agenda, relevance, timelines,

business case for specific 

audience, motivations and 

mechanisms

Knowledge champions, brokers,

architects and communities with

specific audience, motivations 

and mechanisms

Consensus and capacity building, 

knowledge and network 

development for specific 

audience, motivations and 

mechanisms

Purpose

People

Process

Products

Production-AMME Use-AMME Refinement-AMME

Note. AMME = Audience, Motivations, Mechanisms, and Ecological Context.

Figure 7A.3 Example of Template for Detailed 4P-Knowledge Management and Translation 

Strategy Map for Production, Use, and Refinement of Particular Type of Knowledge

Type of Knowledge

Production Use Refinement

Audience Motivations Mechanisms Audience Motivations Mechanisms Audience Motivations Mechanisms

Purpose Agenda

Relevance

Timelines

Case

People Agenda

Relevance

Timelines

Case

Process Agenda

Relevance

Timelines

Case

Products Agenda

Relevance

Timelines

Case

Note. Each cell can contain a detailed checklist of actionable items for implementation.
220

7 . W h a t W e K n o w : M a n a g i n g t h e K n o w l e d g e C o n t e n t

outcomes. In the study presented here, the proposed outcomes are the establishment of 

an evidence base for dissemination, a knowledge base for linking science and practice, an 

implementation framework for change, and an interaction and collaboration methodology. By 

performing mapping using the specific types of explicit and tacit knowledge resources being 

deployed, the salient aspect of each knowledge that can contribute to the respective outcome 

can be determined. Table 7A.2 shows an example of this knowledge-outcome map.

Table 7A.2 Example of Knowledge-Outcome Map

Type of 

knowledge Evidence base

Science–practice 

linkage

Implementation 

framework

Interaction and 

collaboration 

methodology

Knowledge A Web knowledge 

repository

Knowledge B Coordinated contacts 

Translated knowledge

Knowledge C 4P-KMT infrastructure 

strategy maps

Knowledge D 4P-KMT strategy 

framework

Note. 4P-KMT = 4P-knowledge management and translation.

Table 7A.1 Example of Detailed 4P-Knowledge Management and Translation (KMT) Strategy 

Checklist for Production of Particular Type of Knowledge

Type of knowledge

Production

Audience Motivations Mechanisms

Purpose

Agenda Define agendas for 

researchers, policy makers, 

practitioners, and the public

Define agendas based on 

the audience motivations 

for decision, education, 

innovation, or advocacy

Translate agendas 

for audience through 

combination, articulation, 

internalization, or 

socialization

Relevance Determine relevance of 

agendas for researchers, 

policy makers, practitioners, 

and the public

Determine relevance of 

agendas based on the 

audience motivations 

for decision, education, 

innovation, or advocacy

Translate relevant agendas 

with timelines to audience 

through combination, 

articulation, internalization, 

or socialization

Timelines Establish timelines to 

implement agendas for 

researchers, policy makers, 

practitioners, and the public

Establish timelines to 

implement agendas based 

on the audience motivations 

for decision, education, 

innovation, or advocacy

Translate relevant agendas 

with timelines to audience 

through combination, 

articulation, internalization, 

or socialization

Case Develop business case 

to justify agendas with 

timelines for researchers, 

policy makers, practitioners, 

and the public

Develop business case 

to justify agendas with 

timelines based on the 

audience motivations 

for decision, education, 

innovation, and advocacy

Translate business case 

with justified relevant 

agendas and timelines 

to audience through 

combination, articulation, 

internalization, or 

socialization

Note. Checklist outlines how the purpose of particular knowledge resource can be defined in terms of agenda, relevance, timelines, 

and business case, for specific audiences and their motivations, through different translation mechanisms.
221

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

Appendix 7B. Discussion Questions Used in 

National Cancer Institute Review of Knowledge 

Management and Translation

Discussion Questions

1. Types of knowledge being managed

(a) What do you think are the important types of knowledge needed to advance tobacco 

control in the United States? Why do you think these types of knowledge are important?

(b) How much of this tobacco control knowledge do you think is being managed through 

your organization and others? Is it being managed effectively? If so, how? If not, why not?

2. Challenges and suggestions for knowledge management and translation (KMT)

(a) What do you think are the key challenges in managing tobacco control knowledge 

across these networks of organizations? What are the barriers and incentives?

(b) What suggestions do you have to improve the ways this tobacco control knowledge is 

managed within and across the networks of tobacco control organizations? Which is 

the highest priority action item?

3. Experience of KMT in practice

(a) What should local/state communities do to share their questions, viewpoints, findings, 

and lessons regarding specific local tobacco control programs and interventions 

through your organization?

(b) What other experiences and lessons would you like to share with the study team, in 

terms of managing tobacco control knowledge within and across the networks of 

tobacco control organizations?

Definition of Knowledge Management and Translation Terms

n Knowledge—A fluid mix of framed experience, practice routines, contextual information, 

and expert insight that provides a mental framework for evaluating and incorporating new 

experiences and information in domains such as tobacco control.

n Explicit and tacit knowledge—Explicit knowledge often is precise and can be formally 

articulated in organizations such as a tobacco control policy or program. Tacit knowledge 

is the know-how or expertise in tobacco control that resides within individuals.

n Knowledge management—A set of formal and informal structures, processes, and 

measures used to manipulate explicit and tacit knowledge within and across organizations 

such as those in tobacco control.

n Knowledge conversion—Ongoing processes to translate between explicit and tacit 

knowledge, such as in tobacco control through combination, internalization, articulation, 

and socialization.
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7 . W h a t W e K n o w : M a n a g i n g t h e K n o w l e d g e C o n t e n t

n Knowledge networks—A collection of individuals, groups, and organizations with the 

requisite explicit and tacit knowledge that work collaboratively to generate ideas, products, 

and services, such as specific tobacco control policies and intervention programs within 

and across these networks of organizations.

n KMT framework in health—The production, use, and refinement of explicit and tacit 

knowledge within a particular social context of the health system such as in tobacco 

control.

Figure 7B.1 provides the KMT framework in health and illustrates linkages within knowledge 

conversion.

Figure 7B.1 Knowledge Management and Translation Framework in Health

Tacit Articulation Socialization

Explicit Combination Internalization

To Explicit Tacit

From

Knowledge Conversion

KM Framework in Health

Explicit/Tacit

Knowledge

Production

Refinement Use

collection, generation,

synthesis, identification

also

codification, storage,

packaging,

coordination

distribution, sharing, application, adaptation

integration, evaluation,

reflection,

sustainability

Social Context (structures, values, preferences)

Note. From Lau, F. 2003. Toward a conceptual knowledge management framework in health. Perspectives in Health Information 

Management 1:8. Used with permission from the American Health Information Management Association (AHIMA). Copyright 2004 

by AHIMA. KM = Knowledge Management.
223

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

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225

8

ISIS: Synthesis and Conclusions

This chapter examines common themes and potential areas of synthesis from a 

systems thinking perspective across the areas studied in the Initiative on the Study and 

Implementation of Systems (ISIS). It then presents conclusions based on the findings of 

its core group of researchers. These conclusions are based on the four core research areas 

of ISIS—systems organization, system dynamics and modeling, system network methods, 

and systems knowledge management and translation, as well as a set of crosscutting 

conclusions. The conclusions are used jointly to form a potential action plan for the 

future of systems thinking in tobacco control.

The whole is greater than the sum of its parts.

—Fritz Perls (1893–1970)
226

8 . S y n t h e s i s a n d C o n c l u s i o n s

Introduction

The ultimate aim of ISIS is better health. The 

basic premise of this project is that the next 

major round of advances in health resulting 

from tobacco control will evolve through 

the adoption of systems thinking. Tobacco 

control and public health in general stand at 

a crossroads where further large-scale gains 

will come through the ability to understand 

and solve increasingly complex, evolving 

issues. Systems thinking may provide 

the means to accomplish these gains by 

transforming the fragmented ad hoc system 

that currently characterizes tobacco control 

to one that is more effectively self-organized, 

integrated, connected, and adaptive.

This chapter examines the areas studied 

within this project from a synergistic 

systems thinking viewpoint and presents the 

current conclusions of the ISIS team. These 

conclusions have the potential to move the 

tobacco control community toward a more 

integrated environment of systems thinking. 

The underlying unifying conclusion is that 

systems thinking is an ecological process, 

rather than just the implementation of 

an assortment of techniques or methods. 

Systems thinking is not about using a 

specific tool, but as Checkland states, it 

“is a way of looking at the world.”1 It is an 

inevitable evolution toward an environment 

that equips the tobacco control community 

to solve challenging, complex issues in 

tobacco control and public health, based 

on a clear set of fundamentals:

1. Simple rules by which to navigate 

complex adaptive systems and 

participatory processes that engage 

stakeholders at all levels

2. Feedback and evaluation mechanisms 

that allow adaptive, evolutionary change

3. Tools and infrastructure needed to 

enable functioning as a system of 

networked stakeholders

4. Methods for organizing and 

transforming the knowledge in the 

system to achieve more effective 

systemic change

Tobacco control already is heading in this 

direction, and this project equally reflects 

and factors in the evolution. Consequently, 

the purpose here is to encourage and 

channel a trend that already is in process—

one in which the choice is between doing 

it well and sooner or doing it poorly over a 

longer period. With the conclusions in this 

chapter, this challenge is framed around 

guidelines that could enable the next 

steps in implementing real-world systems 

approaches to tobacco control issues.

A systems environment is dynamic. 

The general conclusions of this project 

complement the recommendations of 

individual chapters and are not independent 

of them. The systems approaches on which 

this project was based are among the most 

important of a broad array of approaches 

that can contribute substantially to the 

overall future of the systems environment 

in tobacco control. The four key research 

approaches explored in this project and the 

major conclusions relevant to them are 

presented here.

Systems Organizing

Systems organizing is about an evolution 

from traditional management theory to 

a “learning organization”2 or an adaptive 

systems perspective within a systems 

environment. Its major message is the 

evolution of current concepts of managing 

and organizing by transforming traditional 

top-down, command-and-control structures 

to encompass participatory approaches, 

community-based methods, organizational 

change and dynamics, and effective evaluation 

of such efforts. Methods of organization 

are envisioned as a continuum from formal 

organization in the traditional management 

sense to self-organizing, community-level 

groups, partnerships, or collaborations.
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

System Dynamics

System dynamics involve methods that 

facilitate a more constructive examination of 

complex adaptive systems by modeling the 

behavior of actions and their consequences, 

both intended and unintended. These 

methods are particularly well suited to 

tobacco control, which encompasses an 

ongoing struggle with countervailing 

factors that change over time and can 

be strengthened. There is considerable 

promise in a range of systems approaches, 

including formal system dynamics modeling 

techniques, group processes that harness 

the problem-solving capabilities of multiple 

stakeholders, and ancillary methods such 

as simultaneous equations modeling. 

These approaches constitute tools that 

help address problems that are increasingly 

dynamic and complex.

System Networks

Networks represent the backbone of a 

system by harnessing the power of linking 

diverse stakeholder groups. Networks offer 

the means to have the greatest influence on 

the largest number of people in the shortest 

time, even more than do system dynamics 

models and knowledge management. 

Moreover, research findings suggest that 

countervailing forces against tobacco 

control often function within a network 

environment.3 Understanding the formation 

and management of networks and using 

the knowledge to foster healthy networks in 

tobacco control are critical components of a 

systems environment in tobacco control.

Systems Knowledge

The management and transfer of shared 

knowledge form the basis of interaction 

between stakeholders in a systems 

environment. This monograph outlines a 

comprehensive, sophisticated infrastructure 

for knowledge management and transfer 

that is based on integrating existing silos 

of information and manages both explicit 

knowledge (what we know we know) and 

tacit knowledge (what we do not know 

we know; unconscious lessons from 

experience). This knowledge environment 

must be collaborative, in keeping with the 

needs of the stakeholders it supports, and 

evolving to meet the changing needs and 

methods underlying a systems approach to 

tobacco control.

This project serves the dual purposes 

of performing original research, as a 

way of demonstrating the potential for 

systems thinking approaches in tobacco 

control, and of exploring the future 

of a systems environment for tobacco 

control and public health. ISIS work was 

accomplished through the efforts of a 

diverse, transdisciplinary team, which 

itself served as an example of a successfully 

functioning system. This chapter examines 

the implications of this effort within the 

broader context of recent tobacco control 

efforts, together with their potential trends 

toward an integrated systems environment 

for tobacco control. It then presents the 

conclusions reached at the two-year point of 

this ongoing endeavor.

Synthesis: Looking 

Back and Looking Over 

the Horizon

The systems thinking approaches studied in 

this project were selected for reasons beyond 

their future applicability to tobacco control. 

In a very real sense, they were seen by the 

principals of the project as self-evident 

trends that already are starting to evolve in 

tobacco control and public health. Moreover, 

they are not simply islands of automation 

taking place in isolation. They are part of a 

consistent trend that tracks throughout the 

recent history of tobacco control efforts.

Starting with the release of the 1964 

Surgeon General’s report on smoking and 

health,4 efforts to improve public health 

by controlling tobacco use evolved from 
228

8 . S y n t h e s i s a n d C o n c l u s i o n s

interventions aimed at the individual5 to 

community-based interventions such as the 

Community Intervention Trial for Smoking 

Cessation (COMMIT) and the American Stop 

Smoking Intervention Study for Cancer 

Prevention (ASSIST), both funded by the 

National Cancer Institute (NCI). COMMIT 

focused on resources for education, health 

care, and smoking cessation,6–9 and ASSIST 

focused on policy-level interventions such 

as taxes and legislation.10,11 Interventions 

that address elements of the tobacco control 

problem as an interrelated system are a 

logical next step in the process, supported 

by recent successes in applying systems 

approaches to other areas such as business 

and defense.2,12 Figure 8.1 tracks this 

evolution in tobacco control strategy and its 

correlation with evolution toward increasing 

use of systems methods in tobacco control 

methodology.

These trends lead to a core argument 

for the future of systems thinking in 

tobacco control. It is clear that tobacco 

control is using systems methodologies 

at increasing levels over time, but much 

greater benefits would be derived from 

using them in a consistent, self-conscious, 

and methodologically integrated manner.

The most efficacious direction would be 

promotion of greater integration of systems 

approaches applied to the complex problems 

of tobacco control and public health.

Even in the absence of efforts such as this 

project, these trends toward application of 

systems methods to tobacco control would 

continue to boost use and importance. 

Focusing the work of stakeholders 

on collaborative use of these systems 

approaches would create an environment 

that drives further integration of these 

methods. Table 8.1 shows examples of recent 

efforts to apply systems methods to tobacco 

control. (For more information about any of 

the programs or references in table 8.1, see 

chapters 2 and 3.)

Figure 8.1 Trends over Time in Tobacco Control Strategy and Methodology

Tobacco Control Strategy

Emphasis on individual

behavior change

• Biobehavioral research

• Smoking cessation

• School-based programs

Emphasis on populationlevel/environmental change

• Policy/media advocacy

• Coalition model

• Explicit knowledge sources

Emphasis on system-level change

• Person-environment interaction

• Networks

• Tacit and explicit knowledge 

resources

• Research to practice to research

Tobacco Control Methodology

• Individual controlled trials

• Separate organizational focus

• Publication of results limited to peerreviewed journals

• Collaborative population-based studies

• Logic models (cause and effect)

• Broader dissemination strategies

• Web access to knowledge and data

• System models (evolving models with 

feedback)

• Participatory stakeholder-based

methodologies

• Networks and knowledge bases

The Past

The Future
229

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

The tobacco control community 

increasingly faces the limits of using 

systems approaches such as these piecemeal 

as individual components of a tobacco 

control strategy. Each of these approaches 

addresses a need, and their implementation 

in tobacco control borrows to some extent 

from the existing processes. For example, 

members of the ASSIST evaluation team 

participated in creating a logic model for 

systems evaluation as part of the strength 

of tobacco control (SoTC) measure of 

state-level tobacco control efforts.13 In 

addition, NCI’s Plan, Link, Act, Network 

with Evidence-based Tools (Cancer Control 

PLANET) project for cancer control 

encompasses elements of both knowledge 

management and networks in providing 

tools for implementing evidence-based 

tobacco control.14 Also, the project on 

Environmental Public Health Indicators 

of the Centers for Disease Control and 

Prevention (CDC) uses participatory 

methods and development of logic models.15

An integrated systems environment, 

encompassing these elements and more, 

would extend the reach of all these efforts 

by providing access to broader stakeholder 

groups, knowledge, simulation models, and 

other systems constructs. Promoting an 

integrated systems environment can lead to 

a “critical mass” and precipitate action to 

address and solve even more complex issues 

and to optimize improvement in outcomes. 

A key finding of this investigation is that 

methodological features can cut across 

systems approaches. This finding suggests 

that integration of approaches is feasible 

and would result in better performance, 

improved use, and greater efficiency. For 

example, many systems approaches use 

structured brainstorming, conceptual 

mapping, and network analysis techniques 

that share quantitative methods, such 

as multidimensional scaling and cluster 

analysis. In addition, many of these 

approaches involve creating and maintaining 

Table 8.1 Examples of Recent Systems Efforts in Tobacco Control

Systems methodology Tobacco control efforts

Systems organizing

Managing and leading as a system

■ Mapping Integration of Research and Practice Project ■ State and local SoTC mapping project ■ Projects on CDC’s Environmental Public Health Indicators 

System dynamics

Modeling and understanding dynamic 

change

■ SimSmoke simulation model of prevalence and consumptiona

■ Prototype simulation modeling effect of tobacco control on health 

outcomes in morbidity and mortality due to lung cancerb

■ Tracking evolution of SoTC versus strength of tobacco industry 

counterefforts over time

System networks

Understanding and managing 

stakeholder networks

■ Global Tobacco Research Network ■ Tobacco Harm Reduction Network ■ Tobacco Surveillance Epidemiology and Evaluation Network ■ Transdisciplinary Tobacco Use Research Centers ■ Cancer Intervention and Surveillance Modeling Network ■ Prevention Research Centers

Systems knowledge and its 

management

Managing content and infrastructure 

for explicit and tacit knowledge

■ Community Guide project ■ Cancer Control PLANET dissemination effort ■ CDC TIPS Smoking and Health databases ■ Tobacco Technical Assistance Consortium

Notes. SoTC = Strength of Tobacco Control; CDC = Centers for Disease Control and Prevention; PLANET = Plan, Link, Act, Network 

with Evidence-based Tools; TIPS = Tobacco Information and Prevention Source.

a Levy, D. T., F. J. Chaloupka, J. Gitchell, D. Mendez, and K. E. Warner. 2002. The use of simulation models for the surveillance, 

justification and understanding of tobacco control policies. Health Care Management Science 5 (2): 113–20.

b Karash, R. 2003. Applying systems thinking to tobacco control. Minutes of the 1st ISIS Systems Thinking Summit, Washington, DC.
230

8 . S y n t h e s i s a n d C o n c l u s i o n s

data in what could become common data 

environments. These commonalities fall into 

three areas:

■ Process: Logistical processes behind the 

use of a methodology

■ Technology: Hardware and software 

infrastructure on which the methodology 

is implemented

■ Analysis: Algorithms and analysis 

techniques that underlie a methodology

Some of the common methodologies across 

the systems approaches studied in the 

ISIS project are listed here by the three 

dimensions of process, technology, and 

analysis, with an eye toward how they might 

work together in the future (table 8.2).

Table 8.2 demonstrates a considerable 

overlap in methodology that, with proper 

planning and oversight, could form the basis 

for a more consistent, integrated approach 

across these and other areas. There has been 

little recognition of these methodological 

similarities among the different systems 

traditions that tend to operate independently 

of one another. Examples of overlapping 

methodologies are as follows:

■ Concept mapping and some network 

analysis methods share a common core 

of quantitative multivariate analyses, 

such as multidimensional scaling and 

cluster analysis, and could, in turn, share 

a common software architecture and 

computing environment as tools.16,17

■ Similarly, there is a great deal of 

procedural overlap between the 

brainstorming and data-gathering 

processes in nearly all of these systems 

approaches. This overlap can pave the 

way for more integrated use of group 

processes in tobacco control projects.

■ Knowledge management and translation 

and systems methods share the need to 

mine and visualize data, as well as similar 

front-end processes of data gathering.

At a broader level, all these approaches 

represent mixed methods that share 

common elements, such as collaboration, 

Table 8.2 Common Methodological Elements across ISIS Systems Approaches

Approach Process Technology Analysis

Systems organizing Concept mapping 

Structured brainstorming

Group processes 

Data gathering 

Participant feedback

Data mining

Internet use 

Database management 

Graphic visualization

Multivariate analysis 

methods (e.g., multidimensional scaling)

Clustering methods

System dynamics Structured brainstorming

Group processes 

Data gathering

Programmable modeling 

languages 

Data mining 

Database management 

Graphic visualization

Solution of differential 

equations 

Fuzzy logic 

Network analysis Data gathering

Participant feedback

Data mining

Internet use

Database management 

Graphic visualization

Multivariate analysis 

methods (e.g., multidimensional scaling)

Clustering methods

Data optimization 

Fuzzy logic

Knowledge management Data gathering 

Participant feedback

Data mining 

Database management

Graphic visualization

Data optimization 

Clustering methods

Fuzzy logic
231

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

structured processes, algorithms, and data 

representations. They have both quantitative 

and qualitative aspects in common, and 

all approach problems from a systems 

perspective. As part of an historical trend, 

they hold the potential for further systems 

integration around a larger concept that 

brings all these approaches together. Some 

examples of this potential integration 

include the following.

First, combining system dynamics 

modeling with network analysis may help 

in understanding tobacco control as an 

evolutionary process in which some system 

parts develop more productively than others. 

Depending on the overall strategy, this 

understanding can be used to set priorities 

and allocate resources. System dynamics 

modeling can indicate where networks 

might best be strengthened or developed, 

adapt more effectively, and encourage 

innovation in the system. Conversely, if 

strategy dictates, lower priority activities 

can be redirected or phased out.

Second, combining systems organizing 

with system dynamics modeling in a new 

structured form of system modeling with 

participation of multiple stakeholders can 

lead to other benefits. Currently in system 

dynamics modeling, it is typical to begin 

with brainstorming for potential elements 

of the system (“stocks” and “flows”). (See 

chapter 5 for definitions.) These elements 

usually are grouped or categorized, either 

by the analyst or by the group as a whole. 

Structured methods could be used, as in 

concept mapping, to enable each participant 

to organize the system dynamic model 

components individually. Subsequently, 

these components could be algorithmically 

or statistically combined into a group model 

that would enable exploration of stakeholder 

perspectives.

Third, system dynamics modeling can be 

combined with knowledge management to 

access existing knowledge in a particular 

area or for horizon scanning to understand 

emerging developments in areas of 

interest. These techniques also can assist in 

exploring topics not previously integrated 

with understanding or practice. For all 

stakeholders, this combination helps in 

understanding the options that are so 

important in developing strategy.

Fourth, combining network analysis and 

knowledge management has the potential to 

lead to a better understanding of unknown 

areas by confirming gaps in knowledge where 

no one has ventured. This understanding can 

be used to develop research agendas relevant 

to multiple stakeholders or to advance 

strategy development. Work in this area may 

uncover useful knowledge from networks 

that cross into other disciplines less directly 

related to tobacco control, such as public 

health factors that are concomitant with 

tobacco use. Importantly, this is an approach 

for eliciting and processing tacit knowledge 

from diverse sources for broader access by 

many tobacco control stakeholders.

Finally, combining all four approaches 

would promote a shared strategy that 

recognizes tobacco control as an adaptive 

system. The strategy should help to 

guide new ideas toward acceptance and 

implementation, rather than waiting 

for natural evolution driven by external 

processes or trying to impose such concepts 

through brute force. This project serves as 

one example of providing explicit, accessible, 

and transparent processes to engage 

stakeholders at all levels in “big picture” 

thinking. The challenge from here will be 

to develop a vision that is coherent across 

the entire tobacco control system while 

promoting locally relevant and tailored 

missions and actions. 

General Conclusions

The confluence of trends suggests that 

systems thinking as an organizing paradigm 
232

8 . S y n t h e s i s a n d C o n c l u s i o n s

in public health is increasing. The signs 

are everywhere: the Institute of Medicine’s 

report, Crossing the Quality Chasm: A New 

Health System for the 21st Century18 in the 

field of medicine; the evolution of the Santa 

Fe Institute and the study of complexity;19,20

the move to systems approaches in the 

management of large public12 and private2

organizations; and the popularization of 

the idea of chaos and the possibility of 

unexpected effects of small changes in 

initial conditions.19,21 Systems approaches 

help in grappling with complexity, 

interconnectedness, rapid change, and 

uncertainty. The intent of this monograph is 

to break similar ground for tobacco control 

and, by extension, to demonstrate the value 

of systems approaches for the entire public 

health profession.

Tobacco control constitutes an ideal 

public health test laboratory for systems 

approaches. By its very nature, tobacco 

control needs to be adaptive and ecological 

and involves complex relationships among 

a profit-making industry marketing an 

attractive, addictive, and harmful product; 

the public health profession; and the 

population. The details of this complex 

relationship are constantly developing 

and are not always fully understood. 

Systems approaches can elucidate these 

relationships at a level that guides policy 

and practice and, more significantly, their 

evolution.

Perhaps most important, systems thinking 

contributes to a better understanding of an 

environment in which the results of single 

interventions frequently have unforeseen 

and unintended negative consequences. 

For example, bans on tobacco advertising 

may have helped to create a climate in 

which tobacco firms have taken a lead in 

sophisticated and highly effective cuttingedge marketing techniques that embed their 

products in movies, magazine articles, and 

television programs. Such techniques are 

much more difficult to regulate and now 

are used throughout the private sector.22,23

As another example, dependence on tobacco 

settlement funds may have influenced 

the passage of state laws that, in the eyes 

of some people, defend the competitive 

interests of major tobacco companies.24

Systems methods hold the promise of 

an environment in which effects and 

countereffects could be more accurately 

modeled over time, across all affected 

stakeholders.

Chapter 3 presents the fundamental 

argument for applying systems methods 

to the complex issues that stand between 

stakeholders and improved health 

outcomes. Here, a roadmap for putting 

these ideas into practice is presented. The 

first two years of the ISIS endeavor and 

reflection on both the outcomes and future 

directions of systems thinking efforts 

lead to some initial conclusions about 

desirable directions for systems thinking 

in tobacco control specifically and public 

health more generally. These conclusions, 

developed as part of a group process in 

the ISIS innovation team, revolve around 

the four broad approaches under study 

in ISIS—systems organizing, system 

dynamics, system networks, and knowledge 

management—along with a complementary 

set of crosscutting recommendations 

intended as short-term action items. Table 

8.3 outlines these conclusions.

The conclusions can be viewed, in the spirit 

of complex adaptive systems, as “relatively 

simple rules [that] can lead to complex 

innovative systems behavior,”18(p64) if followed 

by the tobacco control community in the 

framework of the four core approaches 

under study in ISIS. These conclusions 

are not intended to be an exhaustive list 

of potential systems efforts but to link 

synergistically to form an interdependent, 

systems-based environment for future 

tobacco control efforts. These system efforts 

mirror current philosophy in systems 

thinking on three fronts:
233

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

1. They represent the key areas seen 

as current “gaps” in successful 

implementation of the kind of systems 

thinking environment that will lead to 

substantive improvements in health 

outcomes in tobacco control.

2. They work in concert to produce 

improvements in outcomes and are 

much less effective alone.

3. They provide the needed infrastructure 

and practice guidelines that underlie an 

ecological environment for adaptively 

solving complex issues in tobacco 

control.

In addition, these areas represent a logical 

evolution in perspective on the broader 

field of tobacco control (as outlined in 

chapter 2). From the 1980s, when NCI’s 

COMMIT represented an aggressive 

community-level intervention effort 

with modest results, to the late 1990s, 

when projects such as ASSIST focused 

Table 8.3 Initial Conclusions about Directions for Systems Thinking

Approach Directions

Systems organizing 

Encouraging transformation to systems culture

■ Encourage ongoing evolution of vision and paradigms ■ Foster a systems thinking learning environment ■ Nurture discussion about shared purpose ■ Remove barriers to adopting systems thinking ■ Engender systems leadership

System dynamics

Developing and applying systems methods and 

processes

■ Encourage and reinforce systems thinking theory and 

research development ■ Foster mixed-methods systems thinking ■ Conduct participatory assessments of systems needs ■ Encourage ecological perspective on implementation ■ Foster systems evaluation

System networks

Building and maintaining stakeholder relationships

■ Create multijurisdictional and multilevel networks of 

stakeholders for systems thinking and action ■ Study networks of stakeholders to determine their 

dynamics and effects ■ Encourage a transdisciplinary approach by fundamentally 

linking specific disciplines ■ Prepare for the impact of demographic change

Systems knowledge management and translation

Building system and knowledge capacity

■ Build capacity for systems thinking ■ Expand public health data to enable systems analyses ■ Integrate information silos through development of 

cyberinfrastructure ■ Foster skills and culture to affect processes and 

outcomes ■ Create knowledge-translation networks

Crosscutting conclusions ■ Create networks of excellence for systems thinking in 

public health ■ Develop a Web presence for systems methods in tobacco 

control ■ Foster development of systems organizing ■ Link with systems knowledge in other fields ■ Develop a systems curriculum in academia ■ Create a leadership program ■ Organize a national association and a regular national 

conference on systems thinking in public health ■ Remove organizational barriers and build capacity ■ Link with local efforts
234

8 . S y n t h e s i s a n d C o n c l u s i o n s

on population-level policy interventions, 

there is a clear trend toward intervening at 

the system level. This trend could be seen 

in terms of an epidemiological model, as 

described in chapter 2. The original ASSIST 

conceptual framework for tobacco control 

interventions (see chapter 2, figure 2.1) was 

published in NCI’s Smoking and Tobacco 

Control Monograph 1—Strategies to Control 

Tobacco Use in the United States: A Blueprint 

for Public Health Action in the 1990’s.

5

 This 

“blueprint” proposed application of policy 

and other interventions across multiple 

channels to affect outcomes across the target 

populations.

This framework, which borrows 

conceptually from earlier representations 

by epidemiologists such as Sackett and 

associates,25 now is nearly 15 years old. 

Nevertheless, it foresaw an environment in 

which tobacco control interventions needed 

to be considered in an interdependent 

context, pulling together the efforts of 

multiple stakeholder groups. In subsequent 

years, such an environment found its way 

into a broad range of tobacco control and 

public health efforts, to the point that it is 

becoming the norm for major initiatives. 

Examples include the following initiatives:

■ The PRECEDE/PROCEED framework 

for the systematic development and 

evaluation of health education programs26 

■ Participatory tobacco control research and 

planning efforts with multiple stakeholders 

at the state and federal levels27,28

■ The Transdisciplinary Tobacco Use 

Research Centers (TTURCs) initiative 

that established transdisciplinary tobacco 

control research centers at several major 

universities through a partnership of 

public and nonprofit entities29

Today, the efforts embodied in ISIS point 

toward a similar multichannel approach at 

multiple levels, combined with the growing 

realization of the need for linkage among 

researchers, practitioners, community-based 

resources, and other stakeholders, in all 

phases of tobacco control and public health. 

ISIS extends the ASSIST framework from a 

“push” model for interventions, for example, 

one that is applied to targeted channels 

from a central source to a systems-level 

model engaging all stakeholders throughout 

the entire research–practice continuum of 

tobacco control.

Specific Conclusions

ISIS is among a growing group of 

innovative efforts that address complexities 

in improving public health. Realizing 

the promise of improved public health 

outcomes in a more complex, adaptive 

environment requires a fresh look at 

how future efforts in tobacco control are 

conceived, funded, and executed and at the 

fundamentals of learning and organization. 

This section presents conclusions from each 

of the four core areas of the ISIS project, 

as well as a set of crosscutting conclusions. 

Within each of these areas, a discussion 

of the topic area is followed by the formal 

conclusion listed in italics.

Systems Organizing: 

Encouraging Transformation 

to Systems Culture

The shift to systems thinking involves a 

new look at what it means to “manage” 

tobacco control or public health efforts. 

If the public health system is a type of 

complex, self-organizing endeavor that 

requires different individuals, groups, and 

organizations to agree to coordinate efforts 

in some contexts and work independently 

in others, then traditional management 

models that were designed for top-down 

hierarchical organizations will not be 

appropriate for all circumstances. The 

move from the traditional notion of 

management to one of systems organizing 
235

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

is not a rejection of top-down management, 

but rather an envelopment of it. Such a 

change requires an understanding of the 

kinds of management challenges that can 

be organized centrally and the kinds that 

require facilitation of participatory and 

collaborative organizing. This section 

describes some of the major implications of 

this shift from managing to organizing.

Encourage Ongoing Evolution of Vision 

and Paradigms

Systems thinking about tobacco control, 

and especially the goal of achieving better 

integration of research and practice, 

represents not only the application of new 

areas of research but also a new way of 

thinking about the process of research itself. 

This type of shift in thinking already is 

taking place in other areas such as defense, 

business, and technology.2,12,30,31 

A key facet of this shift involves moving past 

a view of systems thinking as an assortment 

of methodologies toward a bolder vision 

and more robust approach for changing the 

conduct of research and practice. Reaching 

this new vision will take foresight and 

a willingness to change the status quo, 

ranging from the activities of individual 

tobacco control stakeholder groups to 

fundamental assumptions in areas such as 

infrastructure, funding mechanisms, and 

collaboration. In a system that does not 

have centralized, top-down control, it is 

important to develop and continually evolve 

a common vision. This vision will never 

be static and will continually be pressured 

from all sides to adapt to the interests of 

some of the participants. Nevertheless, this 

vision development is an essential forum for 

communication throughout the system and 

for system learning.

Support for ongoing examination of systems 

thinking and its implications for the entire 

paradigm for tobacco control and public 

health is required to adapt a new vision for 

the future.

Foster a Systems Thinking Learning 

Environment

The systems learning environment has 

been described as “continually expanding 

its capacity to create its future.”2(p14) The art 

of learning itself has evolved as society has 

moved in a systems direction. To take full 

advantage of this evolution, the learning 

paradigm itself must continue to change. 

Over time, this paradigm has moved away 

from the simple model of transferring 

static knowledge from teachers to learners 

and toward a more ecological approach in 

which teams of people adaptively pursue 

and discover knowledge in an atmosphere 

of experimentation and feedback. Similarly, 

an environment can be foreseen in which 

tobacco control stakeholders can explore 

and model issues in an interactive way that 

will lead to a broader knowledge base, better 

solutions, and improved health outcomes. 

Today, the seeds of this type of systems 

learning environment in public health can 

be seen in efforts such as the Roadmap for 

Medical Research initiative of the National 

Institutes of Health,32 which fosters a 

transdisciplinary learning approach to 

biomedical research, and CDC’s applied 

research training programs for public 

Creating “What If” Laboratories

There is a strong analogy between a 

systems learning environment and the 

way innovation has accelerated over 

time in the private sector. For example, 

companies built and tested products 

linearly in the past. Today, however, design 

teams can use computer-aided design and 

manufacturing tools as virtual laboratories 

in which countless “what if” questions 

can be explored long before hands are put 

on a manufacturing tool. The result is an 

acceleration in the pace of product design. 

This ability to learn iteratively, with feedback, 

is the hallmark of both systems thinking and 

contemporary process innovation.
236

8 . S y n t h e s i s a n d C o n c l u s i o n s

health professionals. At a deeper level, 

this direction is taking shape in areas 

such as increased cross-agency research 

teams and even a proposed integration of 

transdisciplinary academic programs for 

research.33 Such steps point to a larger trend 

toward leveraging a system, rather than 

individual expertise, in the processes 

of learning and discovery.

Systems learning environments must 

be encouraged at several levels: within 

the universities that train future public 

health professionals, within whole-oflife education, and in the course of daily 

life within existing research and practice 

environments in tobacco control. This 

process will involve engaging stakeholders 

within academia, government, professional 

practice, community, and the private 

for-profit and not-for-profit sectors. The 

further methodological development of 

systems learning environments themselves 

also is required. The outcome of such 

environments will change the process of 

learning and will be part of a process that 

facilitates the carrying capacity to tackle 

increasingly large and complex issues.

Nurture Discussion about Shared Purpose

Ultimately, the measure of ISIS’s success 

will be an increased mass of stakeholders 

sharing this new perspective of systems 

thinking. How could this process be 

accelerated to reach the “tipping point”34

of a new paradigm? One could envision 

a process, for example, in which nodes 

of practitioners, scientists, and policy 

analysts who use systems thinking create 

knowledge-translation networks (KTNs) 

around specific topics, work together 

through better networking techniques, 

adopt emerging software technologies to 

manage shared knowledge, and use system 

modeling techniques to define priorities 

and scope of work. Will such an ecological 

approach become the new landscape of 

tobacco control? In some sense it already 

is. Research efforts like the TTURCs and 

an increased emphasis on communitybased participatory research are pioneering 

many of the systems thinking approaches 

emphasized here. A key in such efforts is 

to work toward developing a strong shared 

purpose, marrying the promise of systems 

approaches with the passion of those who 

toil for tobacco control. 

Nurturing discussion about shared purpose 

is the beginning of building the foundation 

for all other strategic discussions.

Remove Barriers to Adopting Systems 

Thinking

Among the most difficult aspects of moving 

toward a systems model are the functional 

and structural barriers in today’s tobacco 

control environment. These include a lack 

of coordination across stakeholders, a lack 

of infrastructure for using participatory 

approaches to problem solving, silos of 

information, and cultural barriers ranging 

from how research is funded to expectations 

for gaining tenure in academia. Removing 

these barriers will require a broad, 

collaborative effort, and in some cases, a 

greater openness to transformative change.

Some of the precursors of such a 

collaborative systems thinking environment 

already exist in the form of databases 

linking stakeholders and public and 

proprietary tools such as the “Web of 

Science”—a commercial database linking 

transdisciplinary research citations across 

major journals.35 Precursors also exist in 

the growth of online communities and 

information resources and in the growing 

use of multiple stakeholders in planning 

and evaluation. Much as tools such as these 

were forged in response to past barriers, 

the systems environment of the future will 

continue to evolve. Understanding existing 

roadblocks will help guide this evolution in 

a more productive manner. 

An open, honest examination of the practical 

barriers to systems thinking will be a key 
237

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

and necessary component of implementing a 

systems thinking environment.

Engender Systems Leadership

Traditional management theory is evolving 

over time to encompass a more ecological, 

participatory approach both within and 

between organizations. This trend is 

examined in greater depth in chapter 4. 

The skill set of the systems leaders must 

evolve from the emphasis on managing 

to one of facilitating and empowering, 

from organizing to self-organizing, 

from delegation to participation, and 

from discrete evaluation to continuous 

evaluation. 

The public health field should actively 

develop and implement education and 

training that encourage this evolving view 

of leadership and should investigate how to 

provide career incentives and rewards for 

such leadership.

System Dynamics: Developing 

and Applying Systems Methods 

and Processes

Many of the systems approaches and 

traditions that evolved over the past halfcentury show great promise in specific 

applications. However, it has been only in 

the past 10–15 years that the potential for a 

broader view of systems that encompasses 

and integrates these varied approaches 

has been seen—both computationally and 

methodologically. Component technologies 

such as dynamic models and simulations, 

stakeholder networks, knowledge bases and 

information infrastructures, and participatory 

and systems organizing methods have begun 

to emerge. Nevertheless, their integration 

into common methodologies for practice 

remains at an early stage. ISIS represents an 

important marker in what promises to be an 

ongoing development process for systems 

methods and processes. Specific conclusions 

reached in this area are presented here.

Encourage and Reinforce Systems Thinking 

Theory and Research Development

The research efforts funded by ISIS are 

early steps in an important direction for 

tobacco control and for public health in 

general. To see these efforts to fruition, 

further development in the theoretical 

basis and research methodology behind 

systems methods is required, together with 

the resources and infrastructure, strategic 

planning, and decision making needed 

to achieve this goal. Today, individual 

components of a systems approach are having 

an impact on tobacco control and public 

health. These efforts include the following:

■ Early simulation of model outcomes such 

as reduced prevalence of tobacco use and 

consumption of tobacco products 

■ Involvement of stakeholder networks 

such as the Global Links program for 

sharing surplus surgical materials36 and 

the Global Tobacco Research Network

n Harnessing the input of stakeholders for 

planning purposes through approaches 

such as concept mapping and creation of 

integrated tobacco control knowledge bases 

Moreover, integrative efforts such as NCI’s 

Cancer Control PLANET show the value in 

linking knowledge and stakeholders together 

with tools and methodologies. At the same 

time, consensus has not been reached 

regarding what an integrated systems 

environment for the future might look like.

Expanded development of systems thinking 

theory and research methods in tobacco 

control and public health is critical to 

achieving a consensus and, thus, substantially 

improved public health outcomes.

Foster Mixed-Methods Systems Thinking

Throughout the ISIS project, polarities in 

systems thinking were discovered: between 

reductionist and holistic theories, between 

qualitative and quantitative approaches, 

and between views on “soft” systems and 
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8 . S y n t h e s i s a n d C o n c l u s i o n s

“hard” systems. For example, examination 

of systems approaches ranged from 

quantitative (simulation-based) techniques 

such as system dynamics modeling and 

network analysis to participatory and 

ecological approaches such as concept 

mapping, community-based participatory 

research, and “soft” systems methods.

An important conclusion from these efforts 

is renewed appreciation of the broad range 

of systems approaches and their role in the 

mosaic of solving complex issues in the 

future. A numerical simulation may provide 

answers that were previously hidden, and 

so might a self-adaptive process involving 

multiple levels of stakeholders. Different 

systems traditions have advantages in 

different situations, and many might be 

usefully integrated or used in concert.

Stakeholders at all levels can leverage 

formal network concepts to understand 

and manage their own strategic alliances, 

referral patterns, growth prospects, and 

even succession planning to replace and 

continue their efforts. They can use systems 

concepts to move from the cynical motto that 

“Today’s solution is tomorrow’s problem” to 

a more strategic understanding of complex 

environments. Stakeholders can harness their 

tacit knowledge in an environment in which 

subjective influences, such as perception 

and intention, shape behavior as much as 

objective influences. Above all, they can use 

mixed methods for a deeper understanding 

of cause and effect as well as barriers and 

facilitators, helping them to analyze leverage 

points and priorities for action. 

A mixed-methods systems approach should 

be encouraged and developed to more 

effectively address the multiple facets of 

complex problems.

Conduct Participatory Assessments 

of Systems Needs

Research and practice have evolved away 

from a top-down process of proposed 

solutions to problems toward a more 

dynamic process of understanding needs 

and working collaboratively to fill them. 

Many systems approaches, such as concept 

mapping or community-based participatory 

research, have the roots of their philosophy 

and methodology in a process that engages 

stakeholders to establish needs and evolve 

solutions. 

Formalized and structured assessment of 

systems needs must be a cornerstone of 

future systems efforts and of the public 

health endeavor as a whole.

Encourage Ecological Perspectives 

on Implementation

An ecological perspective recognizes the 

interrelatedness of the components in the 

environment. In systems implementation, 

one example of such a perspective is 

“environmental scanning.” This phrase, 

popularized in the private sector, refers 

to the ongoing process of observing the 

macroenvironment and making strategic 

changes based on these observations. In 

a tobacco control context, it constitutes 

a more active, interdependent, and less 

procedural approach to observing and 

reacting to factors in the environment.

The ecological approach lies at the heart of 

systems thinking in that it encompasses the 

ability to evolve according to observation 

and feedback. This cybernetic view of the 

world already has shown results in areas 

such as the concept of “shared situational 

awareness” in national defense, in which 

a networked force that shares information 

in a self-synchronizing manner has 

demonstrably led to greater effectiveness 

with smaller fighting forces.31 In public 

health, it serves as a logical next step in 

a field that has progressed from disease 

control, to prevention, to cause-and-effect 

intervention, and now toward working 

systemically to affect health outcomes. 

Such an approach does not reject a 

reductionist (single-discipline) approach to 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

science. Instead, it takes advantage of the 

interrelationships of those theoretical and 

methodological approaches to address more 

effectively some of the most difficult public 

health challenges today.

An ecological approach, including 

systematic environmental scanning, will 

become a fundamental paradigm for 

tobacco control and public health.

Foster Systems Evaluation

Any new direction that may require 

substantive change in both practice and 

culture requires a clear appraisal of its 

effectiveness. The practice of evaluation 

itself must evolve.

At a deeper level, the increasing connectivity 

across society is making research in 

behavioral and social sciences increasingly 

difficult, because control of one or more 

variables cannot be ensured. Behavioral 

and population-specific factors either 

cause or contribute to the diseases causing 

most premature mortality, so it behooves 

the scientific community to ensure that 

methods to study these factors and intervene 

appropriately are developed and adapted. 

This is fundamentally a systems process, and 

Dynamic Program Development and Evaluation Databases

The past 50 years have seen the rise of the computer and the accompanying development 

of databases that store critical information. In evaluation, those asked to provide data often 

complain that evaluation is a task they are required to do and that they get little in return for 

such efforts. Funders and decision makers wonder why their grantees resist evaluation and do 

not make use of its results. Systems thinking and approaches are beginning to change these 

dynamics. This can be seen, for example, in the data system used at Amazon.com, the online 

bookstore. Regular users of that Web site discover that when they browse for a particular book, 

they are given suggestions about other books that were purchased by people who also purchased 

the book of interest. When the user makes a purchase, this information is stored and other 

purchases are linked to it in a type of information network. This type of dynamic database 

principle adds value for all the users and enables linkages that previously were not possible.

These principles can be applied to evaluation databases. For example, imagine a Web site for 

designing a local tobacco control program. Users would enter descriptions of the programs they 

are thinking about, and its activities, outputs, and outcomes. The program could print a logic 

model based on the input. That is a static database application. It might be used, but it does not 

add much value, and it does not provide users with much incentive. However, imagine if the Web 

site was designed so that information from others could be provided to users as they enter their 

own program ideas. If users enter in a few keywords such as “local clean indoor air regulations,” 

the program might show them what others who previously designed such programs had done, 

how they had managed their campaigns, and how they evaluated results. Researchers who visit 

the site would be able to learn about what ideas local tobacco control people are searching for, 

could link in relevant evidence, and could identify potential practice sites for collaboration. 

Funders could see how interests are evolving and could provide funding as an incentive in 

real time. By the time users are finished designing their programs, they would be informed 

by other practitioners’ experience, would know the relevant evidence base, could have some 

potential evaluative tools and measures, and might have a lead on potential research and funding 

collaborations.

Many of these systems thinking principles are emerging in sites like Amazon.com, as well as wiki 

applications like wikipedia.com. Such dynamic planning and evaluation databases would provide 

greater incentives for all parties to contribute, thereby dramatically increasing the value of the 

database itself over time.
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8 . S y n t h e s i s a n d C o n c l u s i o n s

it further underscores the need to develop 

evaluation methods for assessing system 

behavior, such as (1) indirect measures of 

outcomes and (2) participatory evaluation 

criteria driven by stakeholders.

A move toward systems approaches requires 

the further development of evaluation 

methods that accurately reflect progress 

toward outcomes, while preserving the 

energy and innovation of interventions. 

In the process, it is possible to add a 

further degree of rigor to the practice of 

public health, while helping the concept of 

evidence continue to evolve.

Build and Maintain Network 

Relationships

Today’s tobacco control environment is 

characterized by a diverse and expansive 

group of stakeholders at all levels of the 

process, including researchers, funding 

agencies, public health authorities, elected 

officials, community-level organizations, 

advocacy groups, and the population groups 

affected by tobacco control interventions. 

When these groups create their own 

agendas, the result is not only inefficiency 

and duplication of effort but also a lack 

of shared information that in turn could 

change outcomes. Thus, there is a need to 

build the important structural connections 

and collaborations among tobacco control 

stakeholders and strategies to encourage 

support for improved health outcomes.

Create Multijurisdictional and Multilevel 

Networks of Stakeholders for Systems 

Thinking and Action

The formation of networks that cross levels 

of action and jurisdiction is one of the most 

promising and challenging avenues for 

changing outcomes in tobacco control and 

public health. Structured collaborations of 

multiple stakeholders can fundamentally 

change the direction of efforts and 

outcomes. Strategies such as face-to-face 

meetings of researchers, policy makers, 

practitioners, and clients and collaborative 

interaction through group processes such as 

concept mapping are essential for addressing 

the significant gaps between research 

and practice.16 Such approaches also have 

relevance to public health more generally. 

For example, the disconnect between 

research and practice is considered to be a 

root cause of the slow diffusion of successful 

cancer treatments.37

Creation of multijurisdictional, multilevel 

stakeholder networks holds the potential 

for enhancing the ability of tobacco control 

stakeholders to work effectively and 

achieve breakthrough results. Creation of 

such networks will lead to new research 

priorities and reexamination of the funding 

and career issues that drive current 

tobacco control research. Moreover, such 

a network environment represents a new 

infrastructure for future tobacco control 

practice, giving voice to a system of 

participants that, in turn, will continue to 

evolve with changes in tobacco control and 

public health.

Study Networks of Stakeholders to Determine 

Their Dynamics and Effects

The promise of having tobacco control 

stakeholders operate more effectively in 

a network environment brings with it a 

concomitant need to explore the dynamics 

of these networks and evaluate their effects, 

ranging from formative evaluation such as 

exploratory research and concept testing 

to ongoing process evaluation. Some of 

these areas will involve new approaches 

to evaluation. In addition, ancillary 

outcomes such as cost-effectiveness, timeeffectiveness, and dissemination of results 

may be important areas for further study.

The evolving networks of stakeholders 

should be actively encouraged, and 

evaluation of networks should be an 

integral part of planning for a network 

environment within tobacco control.
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Encourage a Transdisciplinary Approach by 

Fundamentally Linking Specific Disciplines

The evolution of public health over the past 

century has increasingly engaged multiple 

disciplines. Therefore, today’s tobacco 

control environment includes a broad range 

of experts such as clinicians, psychologists, 

epidemiologists, and mathematicians. 

The complexity of future tobacco control 

issues will likely require insight and 

expertise from multiple disciplines. These 

disciplines must work collaboratively to 

build a common base of understanding 

and knowledge. Moreover, the systems 

environment of the future will move from 

collaboration to integration. Disciplines 

such as these have become part of the 

overall mosaic of fields including tobacco 

control and public health.

Transdisciplinary approaches are a key 

component of a systems approach to 

tobacco control. The systems, networks, 

and knowledge infrastructures that 

evolve within this field should explicitly 

encourage integration of multiple fields 

of knowledge.

Prepare for the Impact of Demographic 

Change

Demographers make dire predictions about 

future shortages of human resources. There 

is a scarcity of skilled personnel in many 

areas of tobacco control. As in the good 

old days, key informants describe hard-tofill vacancies and staff turnover affecting 

programs throughout the United States.

From a systems perspective, retaining 

organizational memory and sharing tacit 

knowledge can help to protect tobacco 

control agencies in future demographic 

transitions. 

Systems thinking can help to mitigate 

the impact of demographic change by 

generating feedback about performance, 

developing workforce skills, improving 

teamwork, and ensuring that services are 

coordinated with other agencies.

Knowledge Management and 

Translation: Building System 

and Knowledge Capacity

If a systems environment were adopted 

within tobacco control tomorrow, what 

tools would people use? How would they 

collaborate? What mechanisms exist for 

linking stakeholder efforts? How would their 

knowledge be disseminated? These questions 

all touch on the area of building capacity: 

creating tools and procedures that underlie 

the adoption of systems methods across 

stakeholder groups within tobacco control.

Build Capacity for Systems Thinking

A clear analogy exists between the systems 

environment envisioned today and the 

computer and Internet environment 

envisioned more than a decade ago. In the 

1980s and 1990s, a diverse range of tools 

and research efforts across the public and 

private sectors ultimately coalesced into 

the integrated computer and network 

environment that is taken for granted in 

the twenty-first century. Systems thinking 

requires the same coalescence. This capacity 

development must itself be a systemsoriented effort by multiple stakeholders. 

Moreover, to gain public acceptance, this 

effort will need to engage the private sector 

to develop systems tools that have ongoing 

commercial potential in broad areas beyond 

tobacco control and public health. 

Efforts to develop tools for systems and 

knowledge capacity must move forward 

together and proceed with an eye toward 

stronger standards and improved tools as 

systems methods are more widely adopted 

across many of society’s areas of endeavor.

Expand Public Health Data to Enable 

Systems Analyses

Methods for systems thinking involve a 

move away from linear, top-down modes 

of action toward models that assess, 

interpret, react to, and incorporate feedback 
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8 . S y n t h e s i s a n d C o n c l u s i o n s

at multiple levels. Bringing such an 

environment to reality requires access to 

timely accurate data to support decisions at 

multiple levels. Examples of expansion of 

public health data include measures of the 

impact of social and political interventions, 

such as the Strength of Tobacco Control 

and the Initial Outcomes Index used in the 

recent evaluation of the ASSIST program.13

In addition, health outcome data have 

been expanded in areas such as prevalence 

of tobacco use, consumption of tobacco 

products, and morbidity and mortality at 

the population and community levels.

The analysis and delivery mechanisms for 

public health data need to be evaluated in 

the light of a growing systems thinking 

environment and implemented in a way 

that supports this environment. 

Integrate Information Silos Through 

Development of the Cyberinfrastructure

The current environment of multiple stakeholders in tobacco control involves multiple 

silos of explicit and tacit knowledge. Creditable 

efforts are under way to provide integrated 

knowledge resources in tobacco control. These 

efforts include CDC’s Tobacco Information 

and Prevention Source, a central online 

clearinghouse for published documents on 

tobacco control research; CDC’s State Tobacco 

Activities Tracking and Evaluation System; and 

NCI’s Cancer Control PLANET, which supports 

evidence-based tobacco control practice with 

links to data, tools, and resources.

The trend toward increased knowledge 

translation and transfer must continue as 

an important part of the infrastructure for 

systems thinking efforts in tobacco control. 

Further integration of stakeholder resources 

and information is clearly indicated in 

the future.

Foster Skills and Culture to Affect Processes 

and Outcomes

Capacity building for systems approaches 

to tobacco control involves much more 

than tools and data. Beyond this narrow 

slice of “capacity” is a multidimensional 

environment. This environment ranges from 

an organizational infrastructure that fosters 

collaboration and change to a culture that 

supports working as a system, for example, 

examining the processes for tenure and 

for research grants to encourage bridging 

multiple disciplines and stakeholder groups. 

The human side of knowledge capacity must 

be addressed as organizations critically 

examine how to build the skills and learning 

culture needed to affect both the processes 

and outcomes of tobacco control.

Create Knowledge-Translation Networks

Participative approaches and involvement 

of colleagues are essential for building 

capacity. A knowledge-translation network 

could formalize and focus other networks so 

they can benefit from planned development. 

It would become the vital third leg of a 

three-legged stool, balancing the evidence 

base and progressive practice. Knowledgetranslation network activities could include 

“better practice” colloquia, focus groups 

to share tacit and explicit knowledge, and 

collaboration on specific issues. In the long 

run, theory-driven exploration of better 

Beyond Islands of Knowledge:

ISIS Knowledge Review at NCI

The review of knowledge management 

undertaken as part of ISIS at NCI 

underscored the strategic importance of 

knowledge and a growing trend to make 

this knowledge accessible to a broader range 

of stakeholders. More important, the review 

provided a framework for understanding 

the gaps in current knowledge capabilities 

by exploring the scope of explicit and tacit 

knowledge in key areas, such as policy, 

evidence, experience, and contact, and 

by outlining the start of an action plan to 

fill these gaps through an integrated and 

planned knowledge environment.
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practice also can benefit from the evolving 

KTN, which provides an environment for 

practitioners to “drive the evidence.”

Knowledge-translation networks need to be 

developed to encourage greater integration 

of practice and research.

Crosscutting Conclusions

The conclusions presented here represent 

broad areas of effort and activity designed 

to accelerate an evolutionary process 

that already is beginning to take place in 

tobacco control and in public health more 

generally. The implementation of systemslevel concepts in practice remains an area 

for future study. However, a number of 

crosscutting steps would provide a basic 

foundation for future systems activity. Below 

are near-term actions that flow from these 

conclusions.

Create Networks of Excellence for Systems 

Thinking in Public Health

The tobacco control community would 

benefit from development of several 

multidisciplinary, cross-institutional 

networks designed to promote systems 

thinking. These networks could be based 

on the notion of “centers of excellence.” 

However, they would differ in that the efforts 

would be explicitly collaborative, that is, not 

based in a single institution (e.g., a specific 

university or organization). The networks 

should be dedicated to the study of systems 

thinking in tobacco control specifically and 

in public health generally. Multiple networks 

of this type are needed to encourage more 

rapid evolution and to foster a healthy 

sense of competitiveness. These networks 

should promote accelerated implementation 

of systems thinking theory and research 

development in areas such as the following:

■ Encouraging development of new 

methods

■ Exploring integration of existing methods

■ Performing research on research 

methodology itself in areas such as 

systems methods, applications, and 

evaluation

■ Researching better practices for 

participatory action research and systems 

leadership

Develop a Web Presence for Systems 

Methods in Tobacco Control

Systems methods are fundamentally 

participatory in nature. The Internet has 

emerged as a core medium for interaction, 

participation, and transfer of knowledge. The 

intention of this effort is to not end only as 

a report or monograph such as this one but 

to continue as a living, evolving process with 

one or more homes on the Internet. 

Foster Development of Systems Organizing

There is a critical need for processes that 

bring in the diverse range of stakeholders 

in tobacco control, public health, and 

related areas and create a framework for 

their collaborative effort. Existing partner 

networks and collaborations stand to gain 

considerably by pursuing such joint efforts 

within an appropriate infrastructure. 

Through closer collaboration among 

stakeholders, the tobacco control 

stakeholder community will help create 

the conditions for emergence of more 

complex and effective systems in tobacco 

control. 

Link with Systems Knowledge in Other Fields

Systems thinking is evolving rapidly, 

but much of that knowledge is diffused 

across a broad spectrum of disciplines 

in everything from physics to ecology. 

Within these disciplines, a great part of 

the systems discussion is buried in local 

technical language and conventions, making 

it less accessible to other disciplines. 

Strategies must be developed to tap into and 

understand the emerging systems thinking 

in other disciplines. One promising and 

relatively inexpensive option would be to 
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8 . S y n t h e s i s a n d C o n c l u s i o n s

seek approaches for tobacco control and 

public health to become structurally engaged 

with existing groups and organizations 

that explicitly encourage cross-disciplinary 

translation and understanding. Networks or 

collaborations in tobacco control are likely 

to be more effective than individuals in the 

field in eliciting an entré into established 

transdisciplinary endeavors.

Develop a Systems Curriculum in Academia

Much as the computer revolution was 

fueled by a fresh generation of newly 

educated technology and software experts, 

the systems environment of the future will 

be strongly aided by upcoming graduates 

of public health and related areas. With 

input from deans and administrators in 

public health programs, particularly at the 

graduate level, a curriculum addressing both 

component areas of systems approaches 

and their integration can help make this 

environment part of the reality of public 

health. An exciting recent development 

along these lines is a proposal of the 

Australian National University and the 

Australian Commonwealth Scientific and 

Research Organization for a joint institute 

for research integration33 to serve as a 

prototype for future programs on integrative 

theory and methods in public health and 

other areas. 

Create a Leadership Program

Encouraging the development of a new 

generation of leaders who can function in 

a collaborative systems environment is one 

of the most important short-term tasks 

for the adoption of systems approaches. 

Individuals must possess an unusual set of 

talents, together with a wealth of new skills 

and tools, to be effective systems leaders. 

An early priority should be to identify 

potential leaders and to nurture them 

through a broad program of education and 

experience. Stakeholders need to include 

recognized leaders in the field defining the 

characteristics, designing the program, and 

mentoring prospects.

Organize a National Association and 

a Regular National Conference on Systems 

Thinking in Public Health

A regular forum encompassing a broad 

range of stakeholders can become an 

important part of the collaborative process 

and transfer of knowledge that underlie a 

systems approach in public health. Possible 

benefits of such a conference include the 

following:

■ Creating a collaboration for systems 

thinking in public health that integrates 

existing groups such as the Syndemics 

Network and ISIS and provides a broader 

venue in tobacco control to engage people

■ Increasing the linkages between systems 

thinking groups and stakeholders in 

tobacco control and public health

■ Encouraging systems thinking in public 

health communities and vice versa

■ Establishing areas of common ground

■ Forming special interest groups

Remove Organizational Barriers and 

Build Capacity

Perhaps the most challenging but potentially 

fruitful near-term activity is to examine the 

future roles of major current stakeholders 

in tobacco control, with an eye toward an 

enhanced systems environment. The most 

important roadblocks to a truly collaborative, 

systems-based approach to tobacco control, 

such as funding issues, incentives for 

academic tenure, and organizational and 

information silos, can be resolved only 

through collaboration and engagement, as 

a true systems effort unto itself.

Link with Local Efforts

A core theme of many of the participatory 

approaches with multiple stakeholders that 

were studied within ISIS is the importance 

of community-level participation in 

tobacco control in all phases of planning, 

implementation, and evaluation. Local 

involvement is much more than a lofty 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

ideal. The disconnection between research 

and community-based practice has 

been identified by other researchers as 

a roadblock to fundamental progress in 

areas such as cancer and public health.37–39

Conversely, initiatives such as the recent 

Community–Campus Partnerships for 

Health,40 a formal effort based at the 

University of Washington in Seattle to link 

campus research and community public 

health stakeholders in a participatory 

environment, represent an important 

direction for the future. Specific action 

items in this area include establishment of 

local pilot projects for future tobacco control 

initiatives, involvement of community-level 

stakeholders in planning and evaluation 

processes, and further linkages of local 

groups with a broader spectrum of tobacco 

control stakeholders.

Near-term action items such as these 

represent tangible next steps that will help 

translate research into action in creating a 

systems environment for tobacco control. 

Taken as a group, these action items 

are part of an evolution toward larger 

objectives such as widespread adoption of 

systems approaches, creation and use of 

networks, and development of an underlying 

knowledge infrastructure. More important, 

they will help the tobacco control profession 

itself move toward the kinds of stakeholder 

collaboration and interaction that, in turn, 

will form a basis for working together more 

effectively as a system.

Summary

What would people like the world to look 

like 5 to 10 years from now? If this question 

is posed to a group of top experts in most 

fields, a deterministic vision usually 

emerges: do X, Y, and Z, and a specific 

outcome will happen. In comparison, the 

ISIS effort yielded a very different and much 

more important answer to this question. 

The vision is of a new and more ecological 

environment that could potentially allow 

innovation to flourish as never before. The 

specific steps leading to improved tobacco 

control and public health outcomes are 

not yet known. However, there is a strong 

consensus on the basics of a process that, 

if allowed to naturally evolve, could create 

these steps and in turn dramatically change 

these outcomes.

Simply stated, with more inputs, more 

stakeholders, and better evaluation and 

adaptation, the infrastructure of knowledge, 

networks, and analysis methods needed for 

the support of this adaptive environment will 

be the key to transforming the state of public 

health in the future. The rubric of “systems 

thinking” that underlies the ISIS effort is 

not simply an assemblage of component 

technologies, such as system dynamics 

models, network analyses, or knowledge 

bases. It is instead a philosophy that reflects 

the basic engine of change in life, whether 

it is in the form of biology, economic 

competition, democracy, or nature itself. 

This rubric has a strong theoretical base and 

a growing level of implementation in many 

fields. More important, it is a fundamental 

shift from much of current research and 

practice in tobacco control and public health.

Tobacco control provides a case study 

for exploring the complex interplay of 

collaborative (e.g., differing tobacco control 

programs and policies) and competing 

(e.g., tobacco companies and supporters of 

tobacco companies) factors, as demonstrated 

in the system dynamics analysis “shard” 

presented in this monograph. For example, 

NCI Tobacco Control Monographs 1611 (on 

the American Stop Smoking Intervention 

Study for Cancer Prevention—ASSIST) 

and 1713 (on the evaluation of ASSIST) 

qualitatively and quantitatively characterize 

the complex factors that influenced tobacco 

control efforts within and between states. 

The analysis presented in Monograph 17 

includes a measure called Strength of 

Tobacco Control (SoTC), which begins to 
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8 . S y n t h e s i s a n d C o n c l u s i o n s

take this complexity into account. This 

modeling effort starts to quantify the 

relationship between tobacco control efforts 

in the ASSIST states and countervailing 

influences by the tobacco companies, 

including their efforts to undermine ASSIST 

by influencing policy makers at the state and 

federal levels.

By understanding the interplay of these 

and other complex factors relative to policy 

and program implementation—that is, 

to more fully characterize the complex 

“system” of tobacco control—the tobacco 

control community increases its ability 

to improve public health efforts by 

anticipating and tracking countervailing 

influences. This approach could serve as a 

model for addressing other public health 

threats such as overweight and obesity and 

communicable disease. 

In conclusion, this monograph demonstrates 

that the ability to maximize knowledge of 

and change in such complex systems depends 

on the ability to (1) improve information 

tracking and exchange (knowledge 

management), (2) analyze and implement 

complex networks, (3) analyze relationships 

among complex and sometimes competing 

variables, and (4) understand and implement 

organizational structures and functions that 

will improve health practices. There are, 

of course, additional challenges, but these 

steps provide the essential foundation of any 

effective public health effort.

Against this backdrop, systems approaches 

clearly are a major hope for substantial 

improvement in health outcomes in 

the future. Moreover, this trend mirrors 

fundamental changes in how problems are 

solved within society as a whole. Much as 

efficient hierarchical organizations became 

a fundamental concept in the twentieth 

century, systems thinking may become a 

central concept for the twenty-first century. 

It could fundamentally change the nature 

of tobacco control and public health and 

play a key role in addressing a leading cause 

of preventable death. The conclusions 

offered here hold the promise of further 

evolution toward such a systems thinking 

environment that, in turn, holds the 

potential to substantially change the state of 

the nation’s health.

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monograph no. 1, NIH publication no. 

92-3316). Bethesda, MD: National Cancer 

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tcrb/monographs/1/index.html.

6. American Journal of Public Health. 1995. 

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from a four-year community intervention. 

American Journal of Public Health 85 (2): 

183–92. 

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(Smoking and tobacco control monograph 

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12. Krygiel, A. J. 1999. Behind the wizard’s 

curtain: An integration environment for 

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ASSIST: A blueprint for understanding 

state-level tobacco control (Tobacco control 

monograph no. 17, NIH publication no. 

06-6058). Bethesda, MD: National Cancer 

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16. Trochim, W. M. K. 1989. An introduction 

to concept mapping for planning and 

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quality chasm: A new health system for the 

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Health. 2007. http://www.ccph.info.
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Initiative on the Study and 

Implementation of Systems: 

A Project History

ISIS is interested in creating a generic approach to public health [by] using tobacco control as 

an example. Our goals include alignment of the relevant network toward policies and practices 

that work; alignment of each organization toward policies and practices that work; [and] 

uncovering and agreeing on high-leverage public health policies and practices that work.

This statement from the original 2003 summit meeting that kicked off the Initiative on the 

Study and Implementation of Systems (ISIS) project summarizes the broad goals of the 

project: to use systems thinking approaches and theory to address previously intractable 

issues, to improve the health outcomes associated with tobacco control and, by corollary, 

to improve all of public health. These goals were not conceived in isolation but were 

rather a direct response to both the growth of systems methods in recent years and the 

complexity of today’s tobacco control environment. The ideas presented had their roots in 

trends affecting not only tobacco control but also many areas of human endeavor in the 

early 21st century.1–3

Appendix

A
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The numerous approaches that fall under the rubric of “systems thinking” jointly represent 

a formal effort to deal with the natural complexities of life, as well as a natural evolution of 

problem-solving abilities. The underlying premise of this project was that the state of tobacco 

control was ripe for the integration of systems thinking, for four key reasons:

1. Tobacco control efforts encompass numerous disparate communities of interest 

with frequent duplication of effort.

2. Tobacco control efforts lack organized methods for dissemination and collaboration.

3. Tobacco control activities engender competitive responses from a well-financed 

and highly organized tobacco industry that has well-integrated dissemination and 

networking strategies.

4. Specific tobacco control efforts often lack effectiveness on key outcomes such as 

cessation of tobacco use and morbidity and mortality.

Systems thinking encompasses a set of approaches and methodologies that facilitate 

understanding of the behavior of a system in terms of both the totality of the components and 

their dynamic interaction around the knowledge/content. It also reflects a natural evolution 

in the approach to control of tobacco use (figure A.1).

Figure A.1 Evolution of Tobacco Control Approaches toward Systems Thinking

• Surgeon General’s reports

• Public service advertising

• Media campaigns

• Epidemiological models

• System models, networks, knowledge

•NCI ISIS project

• Smoking cessation tools

• Physician counseling

• Telephone quitlines

•Community-based coalitions

• Workplace smoking policies

•NCI COMMIT project

• Clean air laws

• Tobacco taxation

•NCI ASSIST

System-level

Intervention

Population-level

Intervention

Community-level

Intervention

Individual-level

Intervention

Public

Education

Notes. Quitlines indicate telephone hotlines for smoking cessation. NCI = National Cancer Institute; COMMIT = Community 

Intervention Trial for Smoking Cessation; ASSIST = American Stop Smoking Intervention Study for Cancer Prevention; 

ISIS = Initiative on the Study and Implementation of Systems.
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Since the 1964 Surgeon General’s report on smoking and health4 and resulting public 

awareness of the risks of tobacco use, early tobacco control efforts were aimed at the 

individual, through measures such as education, patient counseling, and smoking cessation 

services.5 Subsequent initiatives, such as the Community Intervention Trial for Smoking 

Cessation (COMMIT),6 underscored the importance of community-level coalitions and 

smoking policies and demonstrated their effectiveness by using a randomized community 

trial model. By 1991, the American Stop Smoking Intervention Study for Cancer Prevention 

(ASSIST)7 and other efforts, such as the privately funded SmokeLess States program,8

examined the impact of upstream population-level interventions, such as legislation, taxation, 

media advocacy, and state-level tobacco control infrastructures. Later, in 1993, the Initiatives 

to Mobilize for the Prevention and Control of Tobacco Use (IMPACT) led by the Centers for 

Disease Control and Prevention (CDC) also funded the 33 states not funded by ASSIST, to 

implement similar interventions.9 The ASSIST, SmokeLess States, and IMPACT programs were 

particularly significant in that they marked a period in which fundamental social attitudes 

toward the acceptability of tobacco use were beginning to undergo a permanent change.10

In the wake of such initiatives, it was clear to key researchers at the National Cancer Institute 

(NCI) and elsewhere that further gains in the reduction of tobacco use hinged on addressing 

the issues of tobacco use from a systems perspective by using science to address the complex 

web of forces and counterforces underlying the root causes of the prevalence of tobacco use 

and tobacco product consumption. This realization mirrored gains from adoption of systems 

approaches in other areas, such as business,2 defense,3 and social policy.11 As one of few public 

health areas that had a major industry actively opposing its efforts, together with a complex 

landscape of social, political, and economic factors, tobacco control seemed to be an ideal 

context for systems thinking.

To meet this challenge, experts in systems thinking disciplines and stakeholders from the 

tobacco control and public health communities were recruited to participate in the ISIS 

project as a transdisciplinary team with funding from NCI. After a series of summit meetings 

to define the scope and goals of the initiative and funding for specific research efforts, this 

project ultimately took shape as both a study and a proof-of-concept model for future systems 

efforts in tobacco control. 

The origins of ISIS date back to the summer of 2001, with a series of informal discussions 

between two key figures in tobacco control who were attending a conference on the National 

Blueprint for Adult Tobacco-Use Cessation—Scott Leischow, then chief of NCI’s Tobacco 

Control Research Branch, and Allan Best, a senior scientist at Vancouver Coastal Health 

Research Institute and professor at the University of British Columbia. They were concerned 

that the systems models in fields such as business and defense were not being more widely 

applied in public health.

At this conference, Best’s presentation, “Building Collaboration: Cautions from the Trenches,” 

set forth his view of core needs for dissemination of evidence-based practice. These included 

a system for interagency coordination, identification of needs, development of networks and 

sites, and acquisition of major funding. In examining the issues of dissemination, he sketched 
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the beginnings of a systems view of the world, a topic of interest to Leischow as well. This 

interest, combined with a shared concern about the state of dissemination, led to discussions 

that gave birth to the ISIS project. Perhaps more important, this shared interest had deep 

roots, going back decades, and coinciding with a similarly evolving view among researchers 

who had worked with community health systems.

Best’s interest in a systems view of the world dates back to his doctoral work in psychology, 

which involved the roles of context and social ecology in effective psychotherapy versus 

a world that “simply compared therapy A with therapy B.” His service as the principal 

investigator for the first Canadian site of COMMIT preceded eight years in the private sector 

as a consultant and director of organizational health. In these positions, he learned firsthand 

the challenges of integrating practices found in the research literature with the real-world 

needs of practitioners. Similarly, as an academic at the University of Arizona, Tucson, prior to 

coming to NCI, Leischow noted the strong parallel between the emerging systems theories 

of researchers such as Peter Checkland of Lancaster University in the United Kingdom and 

his own work in developing tobacco cessation programs involving multiple stakeholders in 

Arizona. He was especially struck by the lack of coordinated systems thinking in tobacco 

control initiatives at that time. For both Best and Leischow, the meeting on the National 

Blueprint for Adult Tobacco-Use Cessation provided the opportunity to pursue important 

changes in outcomes for the field of tobacco control.

These discussions were trendsetting on two fronts. First, they engendered a realization that 

the study of tobacco control at a systems level might lead to improved outcomes. Second, they 

were an important evolutionary step in the trajectory of integrating research and practice. 

Subsequent to his arrival at NCI, Leischow and colleagues noted three fundamental disconnects 

in the discovery, development, and delivery “system”: (1) too little discussion between 

government organizations about disseminating results from funded research to the appropriate 

programs, (2) the existence of organizational and informational “silos,” and (3) insufficient 

communication between organizations. The ISIS project became a logical extension in efforts 

to build bridges among tobacco control stakeholder organizations and reflects a broader move 

toward evidence-based tobacco control practices compared with previous efforts. 

The concept of evidence-based practice had steadily grown among the public health 

community, particularly since the advent of meta-analyses of research data, such as the 

Cochrane Collaboration in medicine, related initiatives in public health, and their extension 

to dissemination efforts such as CDC’s Guide to Community Preventive Services.12 However, 

it was clear that evidence-based practices still often sat unused on shelves. These early 

discussions among Best and Leischow and their colleagues initially examined how systems 

approaches might help dissemination of evidence-based practice in tobacco control. Over 

time, they evolved to consider the broader question of why gaps remain between the research 

of scientists and the needs of practitioners.

Ultimately, NCI determined that systems thinking in tobacco control was sufficiently 

important to warrant development of an NCI-funded initiative for more in-depth study. 

Consequently, NCI funded a formal effort that became the ISIS project and issued a contract 
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to the Battelle Centers for Public Health Research and Evaluation, under the direction of 

Pamela Clark, a noted expert in tobacco control research who had been a major contractor for 

the evaluation of ASSIST and the Global Tobacco Research Network (GTRN). With a strong 

voice in the profession and expertise ranging from technical areas such as the biochemistry 

of smoking to social research in tobacco control, Clark was a key coordinator of what quickly 

became a broad multidisciplinary project. From there, the effort progressed to a literature 

review and identification of the members of the ISIS innovation team by Best’s colleagues 

in Vancouver, British Columbia. Project coordinator Gregg Moor, who contacted experts 

ranging from industry leaders to academic specialists, spearheaded that effort. These activities 

culminated in an initial planning meeting in late 2002, in San Francisco, California, as a joint 

meeting with the evolving GTRN to explore a research effort with five modest goals:

1. Pinpoint key perspectives and literature that might contribute to transdisciplinary 

integration

2. Identify, evaluate, and synthesize seminal documents from key literature

3. Facilitate development of ongoing structures and processes for effective 

transdisciplinary collaboration

4. Develop a conceptual framework that maps key concepts for future development

5. Produce a mid- to long-term plan for further development of strategic thinking 

and strategy

Best characterized a subsequent meeting in May 2003, in Denver, Colorado, as a “first date” 

during which systems and tobacco control experts began to discuss a collaborative research 

initiative. In June 2003, a summit meeting was held in Washington, DC, featuring an open 

discussion among key tobacco control stakeholders and a facilitated workshop session with 

systems expert and consultant Rick Karash, which led to the evolution of an action plan and 

agenda. These summits served as necessary points of dialogue for establishing the scope of the 

ISIS project and the range of expertise required.

At the meeting in Washington, DC, it became clear that the problem at hand—using systems 

thinking to improve tobacco control and public health—required a focus that went far beyond 

simple system dynamics models. George Richardson, University at Albany, State University 

of New York, a key expert on system dynamics, had discussed the interaction between 

systems simulation and network analysis in his Denver presentation. He joined many others 

in arguing for broadening the focus of ISIS from its base of system dynamics. These early 

summits were designed with a focus on systems, but by the end of the first Washington, DC, 

summit, the consensus was that systems and network methods had an important synergy and 

that network methods should be included in the ISIS project.

After this meeting in Washington, DC, Noshir Contractor of the University of Illinois at 

Urbana-Champaign, a noted expert in network theory, and Keith Provan, University of 

Arizona, who had successfully applied network methods to other public health issues, became 

part of the core ISIS team. After the next ISIS summit meeting in Scottsdale, Arizona, in late 
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2003, the scope of the ISIS project grew once again to encompass both issues of knowledge 

management and the broader aspects of large-scale organizational change, aligned with Best’s 

original vision of “managing a federation of systems.” Once again, the core team expanded to 

include knowledge-management expert Francis Lau, University of Victoria, British Columbia, 

and Ramkrishnan Tenkasi, Benedictine University, Lisle, Illinois. 

At the next ISIS summit, in the Washington, DC, area in January 2004, key stakeholders from 

NCI, CDC, and major tobacco control organizations and advocacy groups met to hear formal 

presentations on the core technology areas of ISIS. Richardson showed the evolution of a 

system dynamics simulation of tobacco control efforts, including the simulation of prevalence 

of tobacco use and cigarette consumption across a 40-year “chain” of aging smokers. 

Contractor and Provan discussed methods for network analysis and their applicability to 

public health, and Lau shared findings from his recent work on the use of knowledgemanagement approaches in the health care profession.

This meeting in Washington, DC, referred to as the Bolger Summit, named after the 

conference center in which it took place, was an open forum ultimately leading to a 

fundamental shift in focus for ISIS. After the meeting, a “think piece” developed by William 

Trochim, Department of Policy Analysis and Management, Cornell University, Ithaca, New 

York, solidified the ISIS goals around systems thinking for integrating science and practice. 

This direction evolved to an examination of organization or management of the “systems of 

systems” inherent to tobacco control and public health. A consensus quickly formed around 

the think piece. A report presented at a public health conference in Banff, Alberta, Canada, 

in April 2004,1 constituted a public statement of its concepts. 

This summit and its resulting document also helped to move the focus of ISIS away from a 

study of the application of four specific methodologies and technologies (system dynamics, 

network analysis, knowledge management, and systems management) toward a much more 

synergistic effort to use systems thinking to improve public health outcomes. Gabriele 

Bammer, Australian National University, Canberra, and Harvard University’s Hauser Center 

for Nonprofit Organizations, Cambridge, Massachusetts, shared a comprehensive view of 

“integration and implementation sciences.” This presentation and the frank discussions from 

stakeholders in attending the summit helped the group to envision ISIS as the study of a 

synergistic framework for integrating public health science and practice.

A series of transdisciplinary teams to examine functional areas, such as how researchers and 

practitioners communicate and work together, anticipate change, and organize themselves 

with the federation of systems took shape and began working. A follow-up summit in April 

2004 in Vancouver solidified the ISIS core group’s direction. The original research funded as 

part of this study moved forward, ultimately leading to publication of this NCI monograph, 

which is based on the first two years of the four-year project. 

Development of this monograph was a systems effort. As the project evolved, the ISIS 

innovation team chose to depart from the traditional model of chapters contributed by 

specialists in narrow areas and instead formed a dedicated writing team with the task of 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

integrating “shards” of original research, literature reviews, and content from several broad, 

transdisciplinary teams of key experts in their fields. This writing team, led by Trochim, 

included professional science writer Rich Gallagher and research assistants Jennifer 

Brown and Derek Cabrera. Best’s team of project coordinator Moor and assistant Snjezana 

Huerta-Kralj, at the Vancouver Coastal Health Research Institute, provided logistical 

support. Timothy Huerta, then a postdoctoral fellow at the Centre for Clinical Epidemiology, 

Vancouver General Hospital, provided key literature review and synthesis support. Together, 

this bicoastal, international effort linked the contributions of a diverse group of participants 

across a high-bandwidth network of teleconferences, meetings, listserv postings, shared 

drafts, and face-to-face meetings over a two-year period, leading to the completion of a 

draft monograph.

In February 2005, members of the ISIS core group, meeting in Chicago, Illinois, reflected on 

their efforts to date and forged a set of conclusions for future needs and directions in applying 

systems thinking to tobacco control. These conclusions, which form the centerpiece of the 

closing chapter of this monograph, were put forth as next steps to further explore systems 

approaches in tobacco control. The conclusions outline the research, policy, and capacitybuilding efforts that could bring such an environment into reality.

The ideas behind these conclusions evolved considerably throughout the project and will 

undoubtedly continue to evolve as these recommendations are considered and put into 

practice by tobacco control stakeholders. The project itself represented a proof-of-concept of a 

real-life complex adaptive system, in which participants continually learned from one another 

in working toward a broad consensus that will continue to evolve in future efforts. Within this 

mosaic, each person had a unique perspective on the meaning of this initiative.

n To some, this project was fundamentally about strategy and how to develop strategic 

structures and functions to improve health and save lives; how to understand the 

nature of systems and networks; how to create the networks needed to facilitate this 

process; and what information is needed to make the system work more effectively.

n To others, the project revolves around the concept of communities of practice, in 

which stakeholders at multiple levels share collective responsibility for tobacco 

control strategies and improved outcomes. In this view, people drive the process 

and the product, so the network comes first—gathering together key stakeholders 

to reach out and achieve buy-in and bringing people and structures to build a 

sustainable platform.

n Some felt the key issue within this project was the effect of traditional commandand-control strategies in a tobacco control environment that clearly is a complex 

adaptive system, requiring a more adaptive and organic strategy.

n Others saw a clear fit between systems modeling approaches and the most frustrating 

issues in today’s tobacco control environment, such as the inability to rationalize gaps 

and redundancies in surveillance, lessons learned from unintended consequences not 

being fed back into the system, and lack of true multilevel analyses.
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A p p e n d i x A . I S I S P r o j e c t H i s t o r y

n Most shared the view that the role of efforts like this was to speed up evolution, that 

systems thinking is going to happen, and that efforts should be directed toward 

making it happen more effectively and efficiently by promoting public health practice 

that is more flexible, adaptive, and successful. Evolution is characterized by diversity 

and selective retention. There is consensus that systems thinking is about making 

these changes more quickly and more effectively.

At the same time, this very diverse team of experts quickly came to share many goals: a 

need for connectivity and sharing of information, a commitment to engage stakeholders at 

all levels, and above all, a desire to address the complexity inherent in public health issues 

through adaptive and ecological means. The concepts must now be tested in the real world, 

a broader range of stakeholders must be brought into the discussion, and mechanisms for 

feedback must be in place to guide this evolution. There are no “cookie cutter” solutions for 

local communities to begin implementing systems thinking. However, there now is a clear 

potential direction for the future of tobacco control.

The initial two-years of the ISIS project were necessarily limited by time and resources. 

Consequently, the project’s efforts and this monograph’s focus are on tobacco control for 

the home countries of the project participants, most notably the United States, Canada, and 

Australia. Given the worldwide challenge of tobacco control, it is clear that the dynamics 

of tobacco use elsewhere follow their own distinctive evolution. It is fully expected that the 

results of this study will be generalizable to, and will need to be adapted for, the unique 

tobacco control contexts of other regions and countries.

This monograph represents the research outcomes and future directions of the first two 

years of the ISIS project as part of a process that should continue beyond the document. 

The monograph acts as a current index or snapshot of a dialogue about systems thinking for 

tobacco control that must evolve beyond what is on the printed page. Social scientist Donald 

Campbell described this phenomenon somewhat tongue in cheek as “historicist dialectical 

indexicality.” As such, this project has moved from a topical research initiative to a living 

document that serves as a framework for using systems thinking to improve health outcomes 

and has evolved much as dynamic systems evolve over time.

In particular, the project has evolved from a study of system dynamics to a broader 

examination of approaches to integrated systems thinking. It ranges from network analysis 

and knowledge management to systems organizing and potentially encompassing a number 

of cutting-edge developments such as syndemics, complex adaptive systems, chaos theory, 

and complexity theory. It also has evolved from a traditional model that treats many of the 

methods of systems thinking as separate silos to a model that examines broader questions 

such as “who we are” and “what we know,” which are addressed through joint efforts of 

transdisciplinary teams. Perhaps most important, the fundamental question has evolved from 

“how to disseminate evidence-based practices in tobacco control” to the much deeper issue 

of “how to apply systems thinking to improve health outcomes”—a critical question for the 

future of all public health efforts.
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Prevention, National Center for Chronic 

Disease Prevention and Health Promotion, 

Office on Smoking and Health.

10. National Cancer Institute. 2006. Evaluating 

ASSIST: A blueprint for understanding 

state-level tobacco control (Tobacco control 

monograph no. 17, NIH publication no. 

06-6058). Bethesda, MD: National Cancer 

Institute. http://cancercontrol.cancer.gov/

tcrb/monographs/17/index.html.

11. Zagonel, A. A., J. Rohrbaugh, G. P. 

Richardson, and D. F. Andersen. 2004. Using 

simulation models to address “what if” 

questions about welfare reform. Journal of 

Policy Analysis and Management 23 (4): 

890–901. 

12. Centers for Disease Control and Prevention. 

2005. Guide to community preventive 

services. Atlanta: Department of Health 

and Human Services, Centers for Disease 

Control and Prevention, National Center 

for Health Marketing, Community Guide 

Branch. http://thecommunityguide.org.

259

Systems Thinking 

in Tobacco Control: 

A Framework for Implementation

The Initiative on the Study and Implementation of Systems (ISIS) was an exploratory effort 

to apply systems thinking to tobacco control and public health. As such, it examined trends 

in systems methods and their application through the eyes of a team composed primarily 

of researchers and leaders in both the tobacco control field and numerous systems 

thinking disciplines. The conclusions in this monograph outline a broad, general direction 

for better harnessing a systems revolution that already is under way in this and many other 

fields.

What does this effort mean to the tobacco control practitioner, the bench scientist, or 

the community activist? The answer may be “a great deal, in time.” This monograph’s 

chapters look ahead to how systems could affect daily life in practice, but the specifics 

are still unformed and the subject of much investigation to be done in the near future. 

The real value of this effort lies in setting overall directions for how systems approaches 

and, more important, their synthesis can benefit tobacco control. This appendix outlines 

some possible paths for how these directions can be put into action for tobacco control 

stakeholders.

Appendix

B
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

First, this appendix examines some of the open questions that surround the use of systems 

approaches by key tobacco control stakeholder groups. It then explores a possible future 

storyline for how these approaches might affect the work of some of these stakeholders. Next, 

it discusses some of the core issues in putting systems thinking into practice within tobacco 

control, together with possible directions for specific stakeholder groups and steps for getting 

this process started. Finally, it explores key questions that remain for implementing systems 

approaches in the future.

ISIS did not seek to “build a system.” Rather, it sought to foster an ecological process that is 

ultimately driven by simple rules, which must continue to evolve. In nature, evolution is driven 

by a process described by Campbell as “blind variation, selective retention.” In that process, 

the more diversity the system has (i.e., the more variation and selective retention it has), the 

more quickly the system converges on an optimal solution instead of remaining in a static 

monoculture.1 Similarly, in systems thinking, more variation (through broader stakeholder 

groups, systems approaches, and multiple systems) and more selective retention (through 

improved evaluation and implementation) will accelerate the results of efforts toward tobacco 

control. Thus, variation and selective retention operate in much the same way that other 

ecological models do, such as survival and economic competition. The ideas presented in this 

appendix serve as one possible starting point for simple rules within an ecological framework 

that could lead to fundamental changes in tobacco control and public health outcomes.

Integrated Systems Thinking: Story Line 

for the Future

Predicting the future is always fraught with peril: futurists of the 1950s foretold advances 

such as residential colonies on the moon and personal transportation using jet-propelled 

backpacks, but they completely missed trends like personal computers and the Internet.2 At 

the same time, their visions of a more technological and interconnected future helped to 

produce today’s reality. 

The vision of a systems future in tobacco control and in public health more generally is 

informed by inputs at multiple levels. These inputs range from ongoing trends in practice and 

methodology, to the increasing complexity and nonlinearity of outstanding issues in tobacco 

control, and even to the evolution of group thinking among the participants in the ISIS project 

during its initial two years, which itself can be seen as a systems effort. Like all predictions, 

the picture of the tobacco control field and public health overall for decades into the future 

is necessarily hazy, but the overall direction is clear—an integrated systems approach that 

becomes a natural part of daily practice at all levels of the field. Today’s world is a place where 

increasingly complex issues are understood and managed, where research and practice are 

tightly linked, and above all, where the possibility of a smoke-free and healthier environment 

with an attendant decrease in preventable mortality becomes more and more likely.

With this vision in mind, it might be instructive to revisit the real-world questions for tobacco 

control that are raised in chapter 3 and to examine how the lessons learned from systems 
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thinking might address these questions. The next step is to write a forward-looking scenario of 

how key tobacco control stakeholders might operate in the systems environment of the near 

future. First, it is useful to examine some of the questions that initially framed the ISIS study.

Practitioners

Questions relating to systems approaches and practitioners are as follows:

n How can practitioners cope with competition from other organizations for scarce 

resources?

n How do practitioners communicate the positive achievements of their organizations 

and still argue that there is a need for continued and/or additional funding?

n How can practitioners maintain trust with clients when changes in funding levels 

alter the services they are able to provide?

n How can practitioners spend more time in the field and less time with administrative 

details?

n Where can practitioners find succinct, clear, and practical information on the latest 

research?

These questions share key threads addressed by the fundamentals of systems thinking: 

concerns about isolation, access to resources and information, dissemination of results, and 

perhaps above all, the productive use of human effort. The lessons learned from this project 

include the following:

n Networks and tacit knowledge resources can provide an infrastructure for 

discovering the needs, the available resources (e.g., financial) to address them, and 

the contacts and expertise to support the process of building coalitions. A common 

data infrastructure also holds the potential to streamline administrative overhead, 

paperwork, and reporting requirements.

n Explicit knowledge bases can serve as repositories for accumulated data on local 

outcomes. Tacit knowledge bases can provide a resource for people to access the 

expertise of individual practitioners. At a more active level, networks serve as a 

foundation for organizing formal dissemination activities such as conferences, 

electronic communications, and bulletin boards.

n Data from systems models and their concomitant research results stored in 

knowledge bases can streamline the planning process and more efficiently keep 

practitioners abreast of research.

n Perhaps most important, a systems organizing approach of working in a 

participatory, information-sharing manner with other stakeholders—locally, 

nationally, and globally—can lead to adaptive changes in the course of both research 

and practice, focusing practitioners toward efforts that more effectively improve 

health outcomes.
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Researchers

Questions relating to systems approaches and researchers are as follows:

n How can researchers contribute to preventing their research from sitting unread in 

journals?

n Why don’t more people use the science developed by researchers?

n How can researchers access the experiential knowledge of practitioners to be 

certain they are providing an evidence base for the most important programmatic 

applications?

n Where can researchers connect with other researchers who have common or 

complementary interests but who may work in other departments or fields?

n How can researchers streamline the approval and funding processes for their work?

The researchers’ questions reflect a sense of responsibility to advance science, coupled with 

frustration over the funding issues that underpin researchers’ work and the dissemination 

issues that follow it, combined with what may seem to be a structural isolation from the 

stakeholders they serve. Systems approaches can address these issues in the following ways:

n Adaptive, participatory systems approaches in research can lead to research efforts 

that engage the very stakeholders the efforts are directed toward. This strategy leads 

to a more direct path to dissemination and implementation and, perhaps more 

important, to multidirectional links that push the course of research toward public 

health outcomes.

n Systems models can provide an evolving, multifactorial basis for research projects, 

which can help these projects link more directly to the needs of practitioners and 

other stakeholders.

n Networks and knowledge bases serve as an infrastructure linking researchers to 

explicit knowledge such as research data, tacit knowledge such as who shares 

common or complementary research interests, and an infrastructure that in time 

could be leveraged to streamline research funding and implementation efforts.

Policy Makers

Questions for policy makers are as follows:

n What priorities dictated past resource allocation, and what priorities will be dictated 

in the future?

n How can policy makers get a better return on investment for research 

expenditures?

n How can policy makers synthesize all the “silos” of information out there?
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n How can policy makers reduce or eliminate duplication of effort among stakeholder 

organizations?

n How can policy makers convince more professionals to use evidence-based practices?

Policy makers face the need to look ahead and “make decisions at 20,000 feet” that, in turn, 

must support the objectives of their organizations and of public health outcomes. At a more 

practical level, they also must make the best use of resources and function effectively in a 

world of multiple organizations and stakeholders. Systems tools can help in the following ways:

n Systems models can examine the potential multifaceted effects of likely future 

options to guide policy decisions, resource allocation, and priorities.

n Network and knowledge-based resources can provide access to collaborators 

and/or funding to efficiently address organizational priorities and break down 

cross-organizational barriers.

n A common knowledge infrastructure for explicit and tacit knowledge in tobacco 

control and other public health issues, particularly if linked with existing knowledge 

resources, can provide a consistent portal for information, as well as a means to 

disseminate information from organizations.

n Adopting participatory systems-organizing approaches within and outside an 

organization can tie its efforts more directly to stakeholders and outcomes.

These answers for different stakeholder groups hold promise for each of these groups but 

share an even more important characteristic—their similarity. Moreover, these answers point 

toward answers to the broader, discipline-wide issues posed in chapter 3 of this monograph. 

How can a shared vision be built to reduce the prevalence of tobacco use and consumption of 

tobacco products, link actions (missions) to this vision, learn from each other’s knowledge, 

and ultimately forge a closer integration of research and practice? By linking shared goals, 

taking action in light of enhanced mutual understanding among stakeholders, and moving 

each stakeholder group toward a collective vision, participatory action, and common 

infrastructures, systems approaches do much more than solve individual problems. They 

move all parties toward an adaptive, collaborative environment that, in turn, holds the key to 

major changes in the future of tobacco control.

Looking ahead from the lessons learned, it is possible to imagine a future integrated systems 

environment for tobacco control—not a monolithic system but an accepted environment of 

tools and procedures, analogous to today’s computing environment. Activities of hypothetical 

stakeholders might include the following:

Researcher. Jessica Smith is a public health scientist studying population-level tobacco 

control issues.

Practitioner. Michael Washington is a state public health administrator working to reduce the 

state disease burden due to tobacco use. 
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

Advocate. Stan Rodriguez is a lawyer who, years after becoming a widower due to issues of 

tobacco use, is actively involved in community antismoking efforts and provides litigation 

support to regional efforts.

Leader. Barbara Fellows is the chief executive officer of a for-profit hospital chain on the West 

Coast.

Legislator. State Representative Cheryl Stanton is a legislator who has become a key figure in 

proposing state legislative action in support of tobacco control.

The findings of this project suggest the vision of an environment in which all of these 

stakeholders interact in a variety of ways, which are discussed here.

Smith (the researcher) helped to organize an online “town hall” meeting through a central 

network of stakeholders at many levels of tobacco control to clarify future research priorities. 

Discussions at the meeting have given her a quantitative and qualitative sense of these 

priorities. Based on this input, Smith plans to research the relationship between a policy 

intervention and changes in smoking prevalence and consumption of tobacco products. The 

policy intervention is a one-cent increase in the federal excise tax on cigarettes to pay for 

expansion and promotion of national “quitline” services (hotlines for help to stop smoking). 

Going online to a repository of tobacco control knowledge, she first scans existing research 

involving quitlines and tobacco health outcomes, and the search convinces her that this 

proposed increase in excise tax is a promising area for study. Representative Stanton is prepared 

to support this effort through legislative channels on the basis of the results of the study.

Washington (the practitioner) uses the same network data to link his organization with other 

state administrators for regular online and onsite meetings, as well as a source of data on 

current tobacco control trends and practices. As part of the tacit knowledge base in tobacco 

control, Washington also frequently participates in planning and evaluation of research such 

as Smith’s. He recently used the network to link with global colleagues to collaborate on a 

peer-reviewed journal article on trends in population-level intervention.

Smith constructs systems models for her research work based on explicit data from tobacco 

control knowledge bases, as well as feedback and participation from network-based clusters 

of tobacco control stakeholders, including contacts with collaborative partner organizations, 

community activists such as Rodriguez, and leading health care professionals like Fellows. 

These stakeholders assist in developing study designs and evaluation criteria and approaching 

potential funding sources for the research.

Rodriguez has online access to data that support his advocacy efforts and linkages with 

advocates in other communities, providing communications and visibility for possible classaction legal challenges and helping him to tap into complementary community resources for 

building coalitions. More important, the data also provide information on best practices in 

community activism for tobacco control to help synchronize his efforts with the evidence base 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

of similar advocates in other parts of the country. Conversely, his work influences stakeholders 

in Smith’s research in policy interventions and Representative Stanton’s legislative agenda.

Using network data, Fellows linked with colleagues and shared practices, leading to the 

successful Tobacco Intervention for Patients program her hospital group implemented 

last year. This year, data from this program are being retrieved from the tobacco control 

knowledge base for use by researchers in another state as part of an epidemiological study 

on tobacco control interventions in the health care setting. As a participant in dialogues on 

research and dissemination efforts, Fellows also is a voice for national efforts at the patient 

level, in collaboration with stakeholders such as Smith and Washington.

Smith’s research studies frequently use an online collaborative group process, and data from 

this knowledge base are used to help identify simulation models and evaluation methods for 

her studies. Data from these studies, as well as Smith’s own growing expertise, later become 

part of the tobacco control knowledge base for future research efforts. Network channels are 

used to actively disseminate the study results among key stakeholders and to publicize them 

through appropriate industry and publication channels.

The tobacco industry knowledge base provides Representative Stanton with quantitative data 

on the nation’s disease burden and costs associated with tobacco control, as well as access to 

information she uses to counter tobacco industry lobbying efforts among colleagues. More 

recently, these data, network information, and tacit knowledge have all enabled her to become 

active in helping to set the national research agenda in policy-based interventions.

Stories such as these point to a larger environment in which many things depart from 

business as usual. Local stakeholders have a national or even global reach, clusters of people 

with common interests or expertise become known to each other, and research becomes more 

participatory and outcome based, in turn affecting the efforts of practitioners, policy makers, 

and other stakeholders. Networking, data-driven systems models, and integrated planning, 

implementation, and evaluation become the norm, leading to an environment in which the 

actions of any stakeholder ultimately affect the efforts of all stakeholders—a system unto 

itself. Above all, they create an overall environment for bidirectional linking of research and 

practice, harnessing both to uncover optimal solutions for complex problems and to change 

outcomes. However accurate the specifics of predictions such as these are over time, the 

promise of systems thinking is to create an integrated environment for tobacco control that 

uses the efforts of all its participants to produce results that could not exist today.

To keep the ideas relatively simple, this example was confined to tobacco control. A more 

likely future scenario is one in which systems methods are integrated but there also is an 

integrated approach to public health, so tobacco control is considered in a system that 

examines factors such as obesity, heart disease, healthy lung function, and stress reduction. 

Such a scenario is analogous to Milstein’s3 description of syndemics in epidemiology. Thus, 

Smith might consider a research study on promotion of a lifestyle among adolescents that 

discourages smoking, excessive drinking, and use of illicit drugs, while encouraging exercise, 
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

personal development, and community-based activity and service. Multiple stakeholders 

would be involved in defining the parameters of well-being. 

Putting Systems Thinking into Practice

Moving forward from what is currently known, a desirable near-term goal is engineering a 

synthesis of methodologies from existing systems approaches to change outcomes. Based 

on what has been learned and the potential for systems approaches, it may be critical 

to move past the current “smorgasbord” approach—choosing from among disparate 

islands of systems approaches—toward further research and development of an integrated 

environment in which the component pieces work together (figure B.1). Much as early 

research on computer networks led to the Internet, so must proactive research lead to the 

systems environment of the future in a way that engages both tobacco stakeholders and the 

technology field to build an infrastructure that can be applied within tobacco control, public 

health, and beyond.

Bringing this goal to fruition requires a process that involves tobacco control stakeholders in 

defining and implementing the future of systems in tobacco control and connecting its vision 

and missions more effectively to the context of tobacco control. Discussion here centers 

on a framework for engaging the tobacco control field to move toward an effective systems 

environment that serves its needs. Systems knowledge is not a “thing.” It is an inherently 

dynamic social process, and the end game of this process is an agenda of research that pushes 

this social process forward and implements it. At the same time, this effort must engage the 

public and private sectors, join efforts supporting other disciplines, and lead to a real change 

Figure B.1 Common Framework for Integrating Systems Approaches

Program/Policy

Integration

Knowledge Management

Integration and Implementation

Networks

Systems
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

in the functioning of the tobacco control stakeholder community, much like the evolution of 

computing described earlier.

Tobacco control is a diverse field that includes studies of issues such as population 

surveillance on the prevalence of tobacco use and consumption of tobacco products; research 

such as developing models to better understand addiction; issues related to practice such as 

community and clinical interventions and prevention strategies; and policy issues relating 

to advertising, promotion, pricing, and use of tobacco products. It is a field with a great deal 

of ongoing activity, with little underlying clarity on the global meaning of the activity, the 

efficient use of resources, and the optimal linkage of the various segments of the field to 

increase results. Moreover, because there is no tobacco control discipline per se, scientists 

and practitioners come from diverse disciplines such as medicine, public health, economics, 

marketing, health education, toxicology, and genetics. This situation creates a substantial 

degree of disconnection within the loose “system” that constitutes tobacco control.

Herein lies the challenge for integrated, adaptive efforts to change tobacco control outcomes. 

Guidance for Comprehensive Cancer Control Planning, from the Centers for Disease Control 

and Prevention,4 states, 

The scope of comprehensive cancer control involves a diverse group of stakeholders who must 

coordinate their efforts to implement such a plan....These coordinated efforts usually occur in 

the context of a formal collaboration across multiple disciplines and organizations.4 (boldface and 

italics in original)

This guidance does not address the question of how stakeholders apply this excellent advice. 

From a systems perspective, there are three requirements for tobacco control initiatives:

1. Feedback mechanisms to enable appropriate responses to changing influences on 

the system

2. Leadership and decision-making capacity to institute appropriate responses

3. A mechanism for synthesis and translation of research findings into practice

A comprehensive approach to applying systems thinking approaches such as systems 

organizing, system dynamics modeling, network analysis, and knowledge management 

techniques has the potential to create this kind of adaptive, collaborative environment. These 

tools, which are used increasingly in public health and bridge a range of systems approaches, 

may in turn create a cultural shift to help tobacco control agents “do the right thing right.” 

An integrated approach to systems thinking can help bring these models together to form a 

comprehensive strategy for prevention and cessation of tobacco use. Systems thinking also 

can increase the impact of the tobacco control strategy. Both scientists and practitioners will 

contribute to and benefit from an integrated approach to identifying how tobacco control 

could operate in a more systemic way and suggesting steps to create the infrastructure and 

processes that could make this new mind-set work. 
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

Framework for Large-Scale Change toward Systems Thinking

Between the research efforts outlined in this monograph and its recommendations lies a 

process of engaging tobacco control stakeholders to strategize and prepare for the form a 

systems environment should take. Here, broad guidelines for moving forward from theory 

to practice are examined, and the use of lessons learned to make changes in the real-world 

practice of tobacco control is explored.

Public health planning has typically proceeded incrementally and in a disjointed fashion, 

constrained by time pressures and limited guidance. Now that the view of organizations 

is far more organic than the previous industrialized view of organizations as silos, there 

is a shift away from these silos toward a systems strategy for organizing an approach to 

national priorities. International evidence about effective change management can inform 

the approach to the special case of tobacco control. The main driver of this project will be 

a synthesis of lessons about large-scale organizational change in public health that can be 

learned from knowledge management, network theory, and systems theory. This synthesis 

will help organizations look in depth at their processes and services, to plan change more 

confidently, and to implement improvements year after year.

A systems thinking approach addresses root-cause issues such as the following:

n What are the systemic leverage points at all levels?

n How should collaborative tobacco control networks be organized?

n How can research and practice be engaged more productively?

n How can tacit knowledge be captured more effectively?

Figure B.2 Integrated Approach that Benefits Scientists and Practitioners

Two-Way Knowledge Transfer

Inquiry Integration Application

Ideas

Data

Practice setting

Procedures

Efficacy

Impact

Effectiveness

Priorities

Note. Presented as bidirectional for simplicity, but multidirectional in reality.
269

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

With specific and evidence-based tools, tobacco control planning can develop an integrated 

approach in each agency and community. This integrated approach will be based on the notion 

of adapting to specific circumstances from various knowledge domains (figures B.2 and B.3). 

The process of developing an integrated approach could be broken down into steps such as 

the following:

1. Identifying an overall vision based on systems thinking and key targets for delivery, 

according to local priorities

2. Identifying relevant local actions (missions) that are aligned with the vision

3. Analyzing how to develop capacity through a local network or alliance and the 

specific responsibilities of each health care, social care, or educational organization

4. Creating models for comprehensive planning options that can show different agents 

in the tobacco control networks where they are and how their missions align to 

address a common vision

5. Establishing meaningful indicators for monitoring progress and managing 

performance across whole systems, enabling system learning and adaptation

6. Improving communications and accountability to demonstrate progress

Scope and Objectives: Audacious Vision and Focused Goals

A possible vision for systems thinking is to encourage evolution of self-organizing adaptive 

networks or federations of systems that can improve effectiveness within the field of tobacco 

Figure B.3 Tailoring of Integrated Approaches to Specific Applications

Matrix for Knowledge Transfer

Application

of

Knowledge

Novice

Expert

Application 

of

Knowledge

Novice

Expert

Domains of Knowledge Domains of Knowledge

System Dynamics

Modeling

Network 

Analysis

Knowledge 

Management

Systems

Organizing

Integrated 

Approaches for 

Tobacco Control
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

control. Resulting from collaborative development of a coherent integrated framework for 

tobacco control, this vision could ultimately lead to a significant decrease in use of tobacco 

products and a reduced toll of disease and death. With use of the systems thinking approach, 

the framework could establish a cohesive vision at national, state, and local levels, and could 

provide explicit targets for policy makers and others working in the field of tobacco control. 

The approach would not attempt to impose a single approach from all agents in the tobacco 

control system but would instead provide the context for different agents to contribute 

according to their strengths and abilities. The added power of the project would come 

from the enduring relationships across the network of experts involved in developing the 

framework. Through its specific objectives to achieve the overarching goal, a possible next 

phase could include the following accomplishments:

1. Distill broad priorities for the next 5 to 10 or 20 years through a process, including 

consultations and workshops, that builds on respectful appreciation and mutual 

understanding of different perspectives from diverse segments of the tobacco 

control field

2. Foster a sense of cohesion in the field among key opinion leaders by synthesizing 

and fostering alignment among their planning activities

3. Develop an articulated tobacco control framework that links priorities and 

strategies, providing a foundation reference for stakeholders (e.g., researchers and 

funding sources)

4. Disseminate the framework with advice for strategic implementation, such as 

critical success factors and guidelines for implementation in diverse settings

The principal outputs of this project could include the following:

n Consultation forums with key stakeholders 

n Increased understanding among stakeholders of different perspectives on the 

problem of tobacco control, the advantages and disadvantages of different 

approaches, and differences and similarities in visions of desirable future approaches 

and outcomes 

n A series of reports providing guidance to apply concepts such as systems organizing, 

network analysis, systems theory, and knowledge management to tobacco control at 

the research, policy, and practice levels

n Planning tools and templates to assist planners in applying the integrated systems 

thinking framework to local situations and priorities

n Recommendations for pilot projects to apply the systems thinking framework

n An evaluation framework for comprehensive assessment of systems approaches

Bringing the concepts of systems thinking into practice involves specific changes for each 

of the principal stakeholder groups in tobacco control. The conclusions presented in this 
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M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

monograph represent a possible first step toward making that systems future happen. At the 

same time, translating these steps into practice requires implementation of new practices at 

each stakeholder level, and the task of working out specific details remains the next phase of 

this process. Table B.1 presents one possible vision for putting these conclusions into practice 

for researchers, practitioners, advocates, and leaders.

The future does not fit neatly into little boxes. Many of these implementation objectives, such 

as creating learning environments and working across disciplines, apply to groups of multiple 

stakeholders. Other objectives are global efforts that transcend specific groups, such as the 

development, use, and maintenance of knowledge infrastructures. Nevertheless, charts such 

as these illustrate a broader point: implementation of a systems environment revolves around 

changing the “simple rules” by which each of these stakeholder groups operates in daily 

practice.

Systems thinking has the potential to become a unified discipline that is crosscutting in 

terms of other disciplines and fields of endeavor, perhaps by analogy to fields such as statistics 

that operate at three distinct levels. First, statistics represents an academic field of study unto 

itself, in which theory and methods of statistics are developed and advanced. Second, other 

fields (e.g., biology, psychology, sociology, and geography) incorporate statistical training into 

their core methodologies and have staff and research programs with a strong quantitative 

orientation. Third, statistics serves as a core competency throughout the fields of research 

and practice, with an expectation that a large proportion of research staff and students, as well 

as practitioners, will have at least a basic level of statistical competence.

Like statistics, some elements of systems thinking already are embedded in other significant 

research areas. For example, many researchers who study environmental issues incorporate 

integrated assessment, other systems approaches, and participatory approaches into their 

Table B.1 Steps for Implementation of Conclusions in Specific Stakeholder Groups

Step Researchers Practitioners Advocates Leaders

Develop and apply 

systems methods 

and processes

Move from logic 

models to systems 

models

Use participatory 

approaches for 

planning and 

evaluation

Adopt ecological 

view of impact of 

advocacy efforts

Encourage systems 

thinking and systems 

processes

Build and maintain 

network relationships

Link with 

collaborators 

within and across 

disciplines

Build global 

communities of 

practice

Harness national 

and global efforts

Study and leverage 

network dynamics

Build system and 

knowledge capacity

Use and add to 

evidence base

Adapt and 

incorporate best 

practices

Share efforts, 

successes, and 

processes

Create knowledge 

infrastructures and 

break down “silos”

Encourage 

transformation to 

systems culture

Engage practitioners 

and other 

stakeholders in 

planning and 

evaluation

Create learning 

environment

Foster shared 

purpose with other 

stakeholders

Facilitate evolution 

of vision and 

paradigm 
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A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

Integration and Implementation Science: A New Academic Field

In proposing the synthesizing field of Integration and Implementation Sciences discussed in 

chapter 3, Bammera has gone so far as to propose a full department-level academic field of study for 

the implementation of systems methods to build the kinds of shared understanding and individual 

competence that exist in established fields such as statistics. This position supports the view of a 

unified, integrated approach to systems thinking as a fundamental discipline underlying areas of 

public health such as tobacco control, in much the same way that fields such as epidemiology and 

informatics became integrated with public health in years past (see figure below). Like statistics, 

a “home” department would concentrate on the development of theory and methods, which can be 

applied in a wide range of areas. These areas can range from specific topics like tobacco control to 

health more generally, as well as environment and security. A second level of activity would be in 

sectors in which practice-based research is used to test and develop theory and methods, which in 

turn are fed back to and assessed by the home department. The third level of activity focuses more 

on application, with less interest in the development of new theory and methods.

The proposal for a structured academic field or discipline seeks to learn from the troubled history 

of systems thinking. Institutional barriers stymied attempts to introduce systems thinking in 

the 1960s and 1970s, and thus avoided a disciplinary focus. This proposal seeks to adopt and take 

advantage of existing institutional structures to create a new academic field of study, producing 

graduates prepared for the implementation of systems thinking approaches in specific fields such 

as public health.

Overview of Integration and Implementation Sciences

EDUCATION

POLICY &

GOVERNMENT

SOCIETY, HUMAN

BEHAVIOR &

CULTURE

INTERNATIONAL

DEVELOPMENT

RISK &

SECURITY

INNOVATION &

BUSINESS

HEALTH ENVIRONMENT

Application in a specific sector

Methodological development

with respect to a

single sector

Theory

and

Methods

Note. This overview shows how a specific home discipline would relate to key sectors of activity.

a

From Bammer, G. 2005. Integration and implementation sciences: Building a new specialization. Ecology 

and Society 10 (2): 6. http://www.ecologyandsociety.org/vol10/iss2/art6.
273

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

teaching and research. Public health efforts often have a strong orientation to participation 

and implementation. However, incorporation of systems thinking is largely idiosyncratic, 

without a “core curriculum” of best practices. The field of systems thinking still is growing 

and defining itself, as opposed to having well-defined core methods in the way that probability 

serves as a nucleus for statistics. 

A process such as the one proposed here for getting started in systems thinking may serve 

as an important step to prepare for planning an integrated systems environment for tobacco 

control. More important, engaging tobacco control stakeholders in the planning for such 

an environment could build a participatory framework for systems methods in the future. 

Finally, it can help to focus these systems efforts toward real-world health outcomes in 

tobacco control, as seen through the shared vision of the organizations and people working 

to deliver these outcomes.

Implementing Systems Thinking in Tobacco 

Control: Open Questions and Next Steps

Systems approaches, by their nature, involve creating the capacity to solve more complex 

problems across a broader network of stakeholders. Implementing such approaches in 

tobacco control will require key decisions, on the part of these stakeholders, to create this 

capacity. Four critical open issues remain as the tobacco control community moves forward 

with the process of integrating systems approaches and engaging stakeholders in the 

conclusions of this monograph.

1. Who will construct the infrastructure of systems for tobacco control? Who will 

take primary responsibility for moving an integrated systems environment forward? 

Will the effort be specific to tobacco control needs or leverage more generalized 

systems efforts in the broader domain?

2. Will this systems environment be open or proprietary? To use an analogy from 

computer science, will this environment be managed by a few, to serve a broad 

market, as Windows or America Online are, or by a “committee” of stakeholders, as 

Linux or the Internet are? What will its mechanisms for change be over time?

3. Will this system be in the public domain? Do the interests of tobacco control and 

public health require that ownership and management of those issues rest in the 

public sector, or can private interests provide more competitive technology and 

growth?

4. How does the field of tobacco control get where it wants to go? What is the role 

of ISIS in providing incentives for the movement down the road, in a way that is 

valuable? How does tobacco control begin and sustain the process leading to this 

systems environment?
274

A p p e n d i x B . A F r a m e w o r k f o r I m p l e m e n t a t i o n

A concerted effort to synthesize these systems approaches may hold the potential to answer 

the field’s key questions: What factors lead to prevalence of tobacco use and consumption 

of tobacco products and their related morbidity and mortality? Can good science be placed 

into the hands of practitioners within days or weeks instead of years? Can tobacco control 

stakeholders be linked to work more closely together toward common goals? Perhaps most 

important, how can the underlying mission to substantially improve health outcomes be 

fulfilled? Creation of a synthesis of systems approaches holds the promise of a new process 

that, in turn, holds the answers to these questions.

Based on observations by participants in ISIS and recommendations from key informants, 

several procedural “next steps” can potentially assist in moving such an implementation 

process forward, as well as clarify the implications of systems thinking for tobacco control 

stakeholders:

1. Identify emergent visions and missions (actions). All agencies conduct regular 

planning exercises, so this recommendation is helpful in grounding theory with 

application. Structured processes for identifying collective vision can enable 

emergent thinking from many stakeholders. Identifying existing strengths and 

successes can point to system adaptations that can improve results rapidly. The 

language of systems thinking must be made accessible to all stakeholders. These 

processes also would allow for respectful appreciation of differences in perspectives.

2. Connect system processes overall—focus on the “glue.” Addressing this 

recommendation begins with a broader and deeper awareness of tobacco control 

as a “system.” The systems perspective focuses on “context” as well as “content.” A 

first step would be to group and classify agencies based on their strategic roles and 

functions. Description and transformation in the relationships within the tobacco 

control community are needed. Therefore, the first “adhesive” process should be for 

agencies at various levels and in various groupings to redesign strategy individually 

and collectively. This process would create a setting to address the context of tobacco 

control, specifically its strengths, weaknesses, opportunities, and threats. Such 

a process should be inclusive to the extent that is realistic. The tobacco control 

stakeholder community then should consciously encourage the development of “long 

bond” connections in the network that bring together people and organizations with 

distinctly different capabilities and strengths. These connections increase both the 

adaptability and sustainability of the effort.

3. Recognize that context counts, especially in large organizations, so help 

practitioners to identify and share tacit knowledge. This recommendation also 

requires the full combination of systems thinking approaches. Identification is 

not only a knowledge management problem, because no one could cope with full 

disclosure of all tacit knowledge. System dynamics modeling and network analysis 

must be used to help determine which interventions are relevant (1) to strategic 

priorities, (2) for efficient use of resources (e.g., stakeholders’ time), and (3) for 

applicability. Systems thinking approaches can help in optimally shaping what is 

needed from this exchange of tacit knowledge. After this shaping process, initiation 
275

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

of forums for exchange is a relatively easy task. The approach of knowledge 

management would again be used to help decide who needs to know what and how.

4. Help all stakeholders bring their thoughts together on dimensions of the system, 

not just describing the current system but developing characteristics of the future 

system. This key tenet of systems thinking and organizational change also dovetails 

with the recommendations voiced by many informants throughout this project. The 

importance of participatory approaches in planning systems strategies for the future 

should be emphasized. In addition, a vision should be set forth for a forum in which 

stakeholders would use systems thinking to project the paths of tobacco control and 

the tobacco industry over the next 5 and 10 years.

The Newtonian view of the world, a world of simple causes and effects, appears to be giving 

way to a more complex environment that more closely mirrors the behavior of the real 

world. This evolution of systems is a process of autonomous agents following rules and, 

in the fashion of Darwinism, ultimately leads to more optimal results. One lesson learned 

from the science of ecology is that evolution occurs more rapidly with more variations. This 

conclusion leads to perhaps the central argument for implementation of a systems approach: 

creation of a participatory environment having multiple stakeholders with interaction across 

multiple levels and capable of modeling and solving problems of complex phenomena. Such 

an approach could lead to substantial improvement in the state of public health.

References

1. Campbell, D. T. 1974. Evolutionary 

epistemology. In The philosophy of Karl 

R. Popper, Open Court vol. 14, 413–63. 

La Salle, IL: P. A. Schilpp II.

2. Winters, R. 2003. What’s always next? 

Predictions are dicey. Past prognosticators 

vowed that these innovations would 

change our lives. A sampling of the future 

that wasn’t. Time, September 8. 

http://www.time.com/time/magazine/

article/0,9171,1005620,00.html.

3. Milstein, B. 2002. Syndemic overview: When 

is it appropriate or inappropriate to use a 

syndemic orientation? Atlanta, GA: Centers 

for Disease Control and Prevention, National 

Center for Chronic Disease Prevention and 

Health Promotion, Syndemics Prevention 

Network. http://www.cdc.gov/syndemics/

overview-uses.htm.

4. Centers for Disease Control and Prevention. 

2006. Guidance for comprehensive cancer 

control planning. Vol. 1: Guidelines. 

http://www.cdc.gov/cancer/ncccp/cccpdf/

Guidance-Guidelines.pdf.

277

Index

A

accuracy, 82, 82f

action, 7, 77–79, 82, 96

case study, 85

collective, 152–153

in VSAL model, 65, 66f, 67, 95

action planning

in concept mapping, 102–103

for research utilization, 89, 91–92, 91f

active agents, 77–78

adaptation

of collective vision, 70

in loosely coupled systems, 75

in planning, 71

adaptive agents, 45

adaptive organizations, 62, 73–74

administrative work, 52

adolescents

smoking prevalence among, 15–16

in system dynamics models, 126, 127f, 128–129

advertising, tobacco industry, 13, 16–17, 232

in causal maps, 119f, 120

advocates, participation of, 3f, 271, 271t

age factors, in system dynamics models, 126, 

127f, 128–129, 133–134, 134f

Agency for Healthcare Research and Quality, 200

agenda setting, 50, 194

agent(s)

active, 77–78

adaptive, 45

in learning organizations, 79

and missions, 77–78

network models based on, 179

participatory, 77–78

agent-centered principle, 68–69

alignment, 116

Amazon.com, 239

American Cancer Society (ACS ), 174, 200–201

American College of Surgeons Commission on 

Cancer, 200

American Legacy Foundation, 27, 169

American Medical Association, 24

American Stop Smoking Intervention Study 

for Cancer Prevention (ASSIST), 17, 22–24, 

228–229, 233–234, 251

models, 23, 23f–24f

monograph on, 245–246

strength of tobacco control measure, 48, 94–95, 

118, 229, 242, 245–246

analysis

consensus, 102

cultural, 43–44

data, 99–100, 167–168

network (See network analysis)

in systems approaches, 230–231, 231t

antitobacco constituencies, in causal maps, 121, 

121f

appreciative inquiry summit methodology, 73

approval process, streamlining of, 53

architecture workspace, 205

assessment

needs, 71

participatory methods for, 50

ASSIST project. See American Stop Smoking 

Intervention Study for Cancer Prevention 

(ASSIST)

attractor, 46

audience, for knowledge translation, 191

autonomy, networks and, 157

autopoiesis, 46

awareness of health risks, in causal maps, 120–122, 

120f–121f

B

Battelle Centers for Public Health Research and 

Evaluation, 92, 253

behavior

determined by structure, 116

models of, 45

network, 8, 152–154, 181

organizational, 63, 188

as system, 111–113, 116

tobacco use (See smoking behavior)

behavioral management, 63

Behavioral Risk Factor Surveillance System, 201

best practice. See evidence-based practice

Best Practices for Comprehensive Tobacco 

Control Programs (CDC), 169

“better before worse” scenario, 115–116

Note: Page numbers with t indicate tables; page numbers with f indicate figures.
278

I n d e x

betweenness centrality, 150–151, 172, 174

boids, 45

Boys and Girls Clubs (B&G Clubs), 172

brainstorming, 71

in concept mapping, 98

overlap with data collection, 230–231

in tobacco control systems, 116

broker relationships, 150

buffering, 75

building blocks, in complex adaptive systems, 45

bureaucratic paperwork, 52

business case, in knowledge management, 194

C

Campaign for Tobacco-Free Kids, 27, 199

Cancer Biomedical Informatics Grid (caBIG), 

198, 200, 204–205, 207

cancer control

knowledge resources, 199–206

research utilization in, 87–92, 95

Cancer Control Plan, Link, Act, Network with 

Evidence-based Tools (PLANET), 186, 198–203, 

229

knowledge management strategy, 209, 210t, 

237, 242

Cancer Information Service (CIS), 161, 201

Cancer Intervention and Surveillance Modeling 

Network (CISNET), 198, 202–203

cancer research tools, integrative, 204

capacity building

knowledge management, 195, 241–242, 244

network, 160, 177

systems thinking, 6, 241, 244

Capra, F., 43

CAS. See complex adaptive systems (CAS)

CATWOE, 43–44

causal maps, development of, 118–125, 119f–125f

causal model, 110–111, 115, 141, 231–232

development of, 118–125, 119f–125f

CBOs. See community-based organizations (CBOs)

CBPR. See community-based participatory 

research (CBPR)

CDCynergy, 203

cellular automata, 45–46

Center for Substance Abuse Prevention, 117

Center for the Advance of Health, 87

Centers for Disease Control and Prevention (CDC)

evaluation framework, 81–82, 82f

guidelines, 55, 169, 186, 201, 252, 267

IMPACT program, 24, 251

knowledge management initiatives, 199, 211

research citations, 186

syndemics initiative, 39

system dynamics model validation, 131–132, 

132f

tobacco control initiatives, 24, 201, 242

tracking systems, 229, 242

transdisciplinary efforts, 27, 235–236

centers of excellence, creation of, 243

centrality of networks, 150–151, 172, 174

centralization index, 172, 174

chaos theory, 46, 48, 113, 187, 232

Checkland, Peter, 43–44, 112–113, 226, 252

Chief Executive Office Roundtable on Cancer, 27

children

smoking prevalence among, 15–16

in system dynamics models, 126, 127f, 128–129

CHP (Consumer Health Profiles), 199, 203

Chronic Disease Directors Association, 169

cigarettes

design of, 14–15

distribution of, 16–17

history of, 16–17

CIS (Cancer Information Service), 161, 201

CISNET (Cancer Intervention and Surveillance 

Modeling Network), 198, 202–203

classical management theory, 63–65, 65t

clean indoor air laws, 20

client referrals, 164, 174–175, 174f

Clinical Guide to Tobacco Use Counseling, 201

Clinical Practice Guideline on Tobacco 

Cessation, 201

clinical trial management systems, 204

cliques, 150–152

closeness centrality, 150–151

cluster rating map, 100

examples of, 88–89, 90f, 92–93, 93f, 101f

interpretation of, 101

for tobacco knowledge base, 212, 212f

Cochrane Collaboration, 252

cognitive maps, 72

collaboration

among stakeholder groups, 54, 62, 148, 240

in collective vision, 71

in community-based participatory research, 80

in concept mapping, 83–95

facilitation of, 54, 156

knowledge base for, 189

multiple levels of, 154

navigating, 75
279

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

in networks, 74, 158

promotion of, 28–29

transdisciplinary (See transdisciplinary approach)

trust in, 80

collective action theories, 152–153

collective learning, 78

collective vision, 70–73, 84t

building, 86, 235

link between mission and, 77–79, 82–83, 95

command-and-control structures, 62, 64–65

alternatives to, 73–74

versus collaboration, 28–29

versus loosely coupled systems, 75

COMMIT (Community Intervention Trial for 

Smoking Cessation), 22, 228, 233, 251

commitment, to networks, 154–155, 157–158

Common Data Elements, 204–205

communication

in networks, 153, 175

of positive outcomes, 52

between researchers, 53

communities of practice, in knowledge 

management, 195

community-based organizations (CBOs), 76–77

community-based participatory research (CBPR), 

80, 236

community building, 78

Community-Campus Partnership for Health, 245

Community Intervention Trial for Smoking 

Cessation (COMMIT), 22, 228, 233, 251

community-level participation, 244–245

compensation, for system changes, 115

competency development, 75, 271

competition

among public health agencies, 124–125

in networks, 157, 206

for scarce resources, 52

complex adaptive systems (CAS), 44–45, 113, 

226–227, 232, 255

Comprehensive Cancer Control Leadership 

Institutes, 202

computer software

concept mapping, 97–103

for knowledge management, 196–197

for network design, 179

of system dynamics, 111–114, 142

system dynamics models, 126

concept mapping, 7, 9, 71–72, 96

case studies, 87–88, 87f, 91–93, 93f, 95

collaborative, 83–95

example of, 101

interpretation in, 100–101

methodology, 97–103

overlap with network analysis, 230–231

of tobacco control knowledge base, 209–217, 

212f, 215f, 237

Concept System computer software, 97–103

conceptual domain, generation and structuring 

of, 97–99

conference, on systems thinking, 244

conference model, 72

conflict

networks and, 157–158

structure and, 76–77

congestion, network, 178

consensus analysis, 102

consensus building, 195

Consumer Health Profiles (CHP), 199, 203

contact networks, state level, 172, 173f, 174

contemporary management theory, 63

contingency perspective, 63

controlling function

in traditional model, 64, 65t, 68

in VSAL model, 69

cooperation. See also collaboration

in networks, 157

critical mass, 229

critical systems thinking, 113

Crossing the Quality Chasm: A New Health 

System for the 21st Century (IOM), 232

cross-sectional studies, of networks, 165

Cullman, Joseph III, 17

cultural analysis, 43–44

Current Citations (CDC), 186

Current Population Survey Tobacco Use 

Supplement, 201

curriculum, systems theory, 244, 272

cybernetic loop, 114–115

D

data analysis

in concept mapping, 99–100

in network analysis, 167–168

database technology

dynamic, 239

in knowledge management, 196–197

data collection

for concept mapping, 97–100

for network analysis, 160, 165–171

overlap with brainstorming, 230–231
280

I n d e x

decentralized networks, 151

decision making, in networks, 157–158

dedicated network alliance function, 155

degree centrality, 150–151

delays, in causal maps, 119

Delphi technique, 71

demographic change, preparation for, 241

density, network, 151, 175, 178

design, network, 179–180

diagnosis, network, 176–177

diagrams, causal loop, 118–125, 119f–125f

directories, network, 201

discovery, network, 176

dissipative structure

of collective vision, 70

in complex adaptive systems, 46

distribution, of collective vision, 70

diversity, in complex adaptive systems, 44

duplication of effort, avoiding, 54, 206, 240

dyads, 149–150, 153

dynamic database principle, 239

E

ecological context, of knowledge translation, 

191, 217

ecological thinking, 43, 44t, 226, 235–236, 

238–239, 245

edges, 46

emergence, in complex adaptive systems, 46

empowerment

evaluation, 80

participants, 116

engagement, of stakeholder groups, 116

environmental factors

affecting tobacco control, 13, 19–22, 175, 232, 

236–237

knowledge translation and, 191

Environmental Public Health Indicators (CDC), 

229

environmental scanning, 178, 231, 238

evaluation

dynamic databases for, 239

empowerment, 80

fostering, 239–240

knowledge base for, 201–202

participatory, 79–82, 82f, 226

system models for, 81–82, 82f

evaluation function

in traditional model, 64, 79

in VSAL model, 67, 69, 79, 84t

evidence-based practice, 252

attitude of user toward, 80

encouragement of, 54

knowledge base for, 189, 201

evidence-based priorities, setting of, 28

evolution

concept of, 73

of management theory, 63–65, 70, 79

of networks, 153–154, 165, 178

of public health, 12–13, 39, 142, 226

of systems, 46, 113

of systems thinking, 273

of tobacco control, 12–13, 30, 39, 133, 142, 

227–228, 228f, 233–234, 250, 250f, 252

exchange theories, 152

explicit knowledge, 188, 221, 227

shift from tacit knowledge to, 193, 207, 214

exploitation, network, 155

exploration, network, 155

F

facilitation

of collective vision, 71–73

in concept-mapping interpretation, 101

facilitative leadership, 77–78, 84t

FCTC (Framework Convention for Tobacco 

Control), 29

feasibility, 82, 82f

Federal Cigarette Labeling and Advertising 

Act, 133

Federal Trade Commission, 14–15

feedback, definition of, 45

feedback loops, in system dynamics, 110, 114–115, 

114f, 132–133, 133f, 141–142, 226

filters, 14

financial climate, for state tobacco control 

programs, 171–172, 172t, 173f

financial infrastructure, for knowledge 

management, 196, 209

Finland, North Karelia Project in, 21

“fishing net” approach, 156

flocking model, 45

flows

in causal maps, 119, 131, 142, 231

in complex adaptive systems, 44
281

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

focused goals, 269–273

focused integration, 154, 180

focus groups, 71

follow-up studies, in network analysis, 167

formal relationships, network, 163–164

Forrester, Jay, 111–113

fractals, 46

fragmentation, network, 151

Framework Convention for Tobacco Control 

(FCTC), 29, 161

funding

ISIS, 252–253

for tobacco control

in causal maps, 121, 121f, 123–124, 124f, 

135–136, 136f

policy makers and, 53–54

practitioner services and, 52

state programs and, 169, 175, 175f

streamlining of, 53

future-search conferences, 72

G

General System Theory: Foundations, 

Development, Applications (von Bertalanffy), 40

generation step, in concept mapping, 97–98

genetic basis, for smoking behavior, 16

geographic dispersion, problems related to, 156

GlaxoSmithKline, 117

Global Links program, 237

Global Tobacco Research Network (GTRN), 161–

162, 237, 253

network analysis of, 160–169, 181

goals

focused, 269–273

ISIS, 48t, 54–55, 226, 254, 256

knowledge management, 48t, 216

network, 48t, 155, 160

purposeful, 73

setting of, 29

system dynamics, 84t, 114–115

tobacco control, 12

governance

network, 151, 154, 178, 180

of self-managed groups, 76

government, willingness to take action, in causal 

maps, 123, 123f

government agencies, collaboration among, 27

government awareness, of health risks, in causal 

maps, 121f, 122

government health warnings, 133

government intervention sector, in system 

dynamics models, 118, 140, 140f

government legislation, 20, 118, 133

in causal maps, 123–124, 124f

government sector, in system dynamics models, 

130, 130f, 139–141, 140f, 144f

go-zone plots, example of, 89, 91, 91f, 102–103, 

103f

group modeling, 116

groupware, 196

GTRN. See Global Tobacco Research Network 

(GTRN)

Guidance for Comprehensive Cancer Control 

Planning (CDC), 267

Guide to Clinical Preventive Services, 55

Guide to Community Preventive Services, 55, 

186, 201, 252

H

Hawaii, tobacco control program in, 171–175, 172t

health care costs, in causal maps, 122, 122f

health system, as ecosystem, 191

Healthy People 2010, 12, 30, 117

holistic thinking, 40

home, smoking in, 20

homophily, 153

horizontal networks, 164–165

hotlines, national network of. See North 

American Quitline Consortium

humanistic management, 63

human resources, shortage of, 241

I

IMPACT (Initiatives to Mobilize for the Prevention 

and Control of Tobacco Use), 24, 251

implementation framework, for systems thinking, 

259–275, 266f

implementation function

ecological perspectives on, 238–239, 260

knowledge management in, 187, 189

in traditional model, 64

in VSAL model, 67, 74

in-degree centrality, 150–151
282

I n d e x

Indiana, tobacco control program in, 171–175, 

172t, 173f, 175f–176f

Indiana Tobacco Prevention and Cessation 

Agency (ITPC), 172

individual-level network theories, 149–150

Industrial Revolution, management theory and, 65

informal relationships

client referrals and, 174–175, 174f

network, 164

information

versus knowledge, 186–187

shared, 164

information dissemination, 28, 53, 186, 252

and attitude of user, 80

network efficiency for, 178

policy makers and, 54

in system dynamics models, 127, 127f, 129, 

135–137, 136f–137f, 144f

information infrastructure, 196, 209–210, 242

Initial Outcomes Index (ASSIST), 242

Initiative on the Study and Implementation of 

Systems project. See ISIS (Initiative on the 

Study and Implementation of Systems) project

Initiatives to Mobilize for the Prevention and 

Control of Tobacco Use (IMPACT), 24, 251

Inquiring Knowledge Networks On the Web 

system, 170

Institute of Medicine

Crossing the Quality Chasm: A New Health 

System for the 21st Century, 232

2001 report, 87

institutional-community relations, 244–245

integration, focused, 154, 180

integration and implementation sciences, 254, 272

framework of, 48–49, 49t

integrative cancer research tools, 204

integrative management theory, 63

interaction guidelines, for power issues, 76–77

interfaces, focus on, 75

internal models, in complex adaptive systems, 

44–45

interorganizational ties, 152

interpretation step, in concept mapping, 100–101

intervention, participatory methods for, 50

interviews, for network analysis, 167, 169

in vivo imaging, 204

involvement, in network relationships, 154

ISIS (Initiative on the Study and Implementation 

of Systems) project

case studies, 47–50

common methodologies, 230–231, 230t

conclusions, 255–256

chapter, 6–9

crosscutting, 243–245

general, 5–6, 29–30, 231–232

specific, 234–245

as framework for public health issues, 5, 39

funding for, 252–253

future steps for, 274–275

goals of, 48t, 54–55, 226, 254, 256

history of, 249–256

implementation framework, 259–275, 266f

key facets of, 26, 48t

knowledge management review, 242

lessons from, 25–29

monograph framework, 3–5, 254–255

network analysis in, 170–171

participants in, 251, 253–254, 256

policy makers and, 53–54

practitioners and, 51–52

purpose of, 2, 26, 38–39, 55, 227

researchers and, 52–53

summit meetings, 253–255

synthesis of, 227–231

system dynamics in, 116–133, 141–142

vision of, 245, 260

issue exploration, 50

ITPC. See Indiana Tobacco Prevention and 

Cessation Agency (ITPC)

J

Johns Hopkins Bloomberg School of Public 

Health, 92, 162

journals, research published in, 52–53, 136, 

186, 236

K

key informants, in network analysis, 166, 168–

169

KMT. See knowledge management and translation 

(KMT)

knowledge

definition of, 221

explicit, 188, 221, 227

shift from tacit to, 193, 207, 214

versus information, 186–187

organization of, 190, 192–193

tacit, 188, 193, 221, 227

types of, 190, 216, 221

knowledge architects, 195
283

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

knowledge base. See tobacco control knowledge 

base

knowledge brokers/managers, 195

knowledge champions, 194–195

knowledge conversion, 221

knowledge development, 196

knowledge development tools, 196

knowledge management and translation (KMT), 

8–9, 56, 141–142, 185–222, 226–227

benefits of, 189, 216

capacity building for, 195, 241–242, 244

case studies, 48t, 197–216

current directions in, 232–233, 233t

definition of, 187, 221–222

examples of, 228, 229t

formal methodology, 186

four Ps of, 194–196, 195f, 207–208, 214, 

218–220

framework for, 188–191, 189f, 217, 222, 222f

conceptual, 189–194, 190f, 192f

strategic, 194–197, 195f

goals of, 48t, 216

infrastructures, 188, 196–197, 206–209, 

216–217, 242

integration of, 192–194, 193t, 216

ISIS conclusions on, 241–243

key factors in, 188

overlap with other approaches, 230–231, 230t

project types, 188

resources for, 186

role of, 187

social context of, 191, 217

strategy maps, 197, 198t, 199f, 209, 210f, 

210t–211t

for infrastructure, 197, 198t, 199f, 208–209, 

218–220

terminology, 221–222

knowledge map, systems-level, 207, 207t, 219–220

knowledge navigation/access tools, 196

knowledge networks, 222

knowledge-outcome map, 220

knowledge production, 190, 192

knowledge refinement, 190–191, 193

knowledge repositories, 155, 196

knowledge resources

tobacco control, 199–206

value of, 196

knowledge transfer, 56, 141–142

case studies, 48t

facilitation of, 156–157

goals of, 48t

two-way, framework for, 268–269, 268f

knowledge-translation networks (KTNs), 236, 

242–243

knowledge use, 190, 193

L

laboratories, virtual, 235

ladder graph, for pattern matching, 102, 102f

large group interventions (LGIs), 77–78

large-scale change, framework for, 268–269, 268f

large-scale interactive process, 72

Latino Agencies (Oklahoma), 174

laws

clean indoor air, 20

tobacco control, 118, 133

in causal maps, 123–124, 124f

leader–follower principle, 68–69

leadership

collective vision and, 70–71

facilitative, 77–78, 84t

fostering, 244

in knowledge management, 194–195

of loosely coupled systems, 75

participation of, 271, 271t

self-organization and, 73–74

in systems approach, 3f, 64, 68

leadership program, creation of, 237

leading function

in traditional model, 64, 65t, 68

in VSAL model, 69

learning, 7, 79–83, 96

case study, 85

collective, 78

definition of, 79

enhancement of, 156–157, 235

team, 43

in traditional model, 79

in VSAL model, 65, 66f, 67, 69, 84t, 95

learning organizations, 113, 226

development of, 42–43, 79, 235–236

legitimacy, network, 154–155

letters of support, for network analysis, 167

LGIs. See large group interventions (LGIs)

lifestyle clusters, 203

linkages, among network members, 154

local efforts, linking with, 244–245

logic models, 72, 81, 92, 95–96, 229

longitudinal studies, of networks, 165–166, 175

long-term development, participatory methods 

for, 50–51

loop(s), in causal maps, 119
284

I n d e x

loop model, causal, 118–125

loosely coupled system, 74–76

loyalty conflicts, networks and, 157–158

M

machines, organizations as, 64

Making Health Communications Programs 

Work: A Planner’s Guide (NCI), 203

management

basic process of, 64, 65t

of networks, 158

management functions

in traditional model, 64, 65t, 67–68

in VSAL model, 67–68

management science, 63

management theory

applied to tobacco control initiatives, 68, 68f

classical, 63–65, 65t

evolution of, 63–65, 70, 79

humanistic, 63

integrative, 63

phases of, 63

quantitative, 63

systems approach to (See systems organizing)

traditional, 62–65, 65t

versus systems approaches, 65–70, 66f, 83, 

95, 226, 234–235

map(s)

causal, development of, 118–125, 119f–125f

cluster rating (See cluster rating map)

cognitive, 72

knowledge, systems-level, 207, 207t, 219–220

knowledge management, 72, 197, 198t, 199f, 

207–209, 210f, 210t–211t, 218–220

mind, 71–72

outcome, 72, 220

4P-KMT, 197, 198t, 199f, 207–208

planning, 71–72, 83 (See also concept mapping)

marketing, tobacco, 13, 16–17, 232

in causal maps, 119f, 120

Massachusetts Institute of Technology, 117

Master Settlement Agreement (MSA), 18, 171, 232

matrix approach

to network analysis, 160

to tobacco control, 23, 23f

MDS. See multidimensional scaling (MDS)

mental models, 42, 116, 194

Michigan, tobacco control program in, 171–175, 

172t, 173f

mind maps, 71–72

Minnesota Heart Health Program, 21

mission

establishment of, 77

link between vision and, 77–79, 82–83, 95

Mississippi, tobacco control program in, 171–175, 

172t, 173f

Missouri, tobacco control program in, 171–175, 

172t

mobilization, network, 155

model(s)

behavior, 45

causal, 110–111, 115, 141, 231–232

development of, 118–125, 119f–125f

cellular automata, 45–46

conference, 72

evaluation, 81–82, 82f

group, 116

internal, 44–45

logic, 72, 81, 92, 95–96, 229

mental, 42, 116, 194

network, 179

participatory intervention, 80

planning, 71

system dynamics (See system dynamics 

models)

system knowledge, 4

systems organizing, 65–83, 66f

visual, 71–72

VSAL, 65, 66f, 67

motivation, for knowledge translation, 191

multidimensional scaling (MDS), 97

multidisciplinary approach. See transdisciplinary 

approach

multiple needs, addressing, 156

multiplexity, of networks, 150, 154

multivariate analysis, 230

of tobacco control, 23, 24f

of tobacco knowledge base, 212

N

National Blueprint for Adult Tobacco-Use 

Cessation, 251

National Cancer Data Standards Repository 

(NCI), 205

National Cancer Institute (NCI), 200, 228. See 

also specific NCI project

Cancer Information Service, 161, 201

Consumer Health Profiles, 199, 203
285

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

knowledge management infrastructure, 206–

209, 217, 242

knowledge management initiatives, 200–206, 

217, 221–222

National Cancer Data Standards Repository, 

205

research funding by, 27–28

research utilization initiative, 87

Smoking, Tobacco, and Cancer Program, 22

Smoking and Tobacco Control Monographs, 

20, 234, 245–246

systems dynamics simulations, 117

Tobacco Control Research Branch, 251

transdisciplinary efforts, 27

National Institute on Drug Abuse, 27

National Institutes of Health (NIH), Roadmap 

Initiative, 27, 235

National Program of Cancer Registries, 201

National Tobacco Control Program (CDC), 24

needs assessment, 71, 238

network(s), 4, 6, 8, 226–227

agent-based simulations of, 179

benefits of, 156–157

capacity building, 160, 177

centrality of, 150–151, 172, 174

creation of, 6, 243, 270

cross-organizational cooperation in, 62

definition of, 2, 149

delineation of, 170

design of, 179–180, 270

diagnosis, 176–177

discovery, 176

effective, 154–155

evolution of, 153–154, 165, 178

examples of, 228, 229t, 264–265

goals of, 155, 160

governance of, 151, 154, 178, 180

horizontal, 164–165

ISIS conclusions on, 240–241

knowledge, 222

knowledge base for, 189

location of, 153, 164–165

nodes of, 161, 172, 174

shortcomings of, 157–158

small-world, 149, 155

“star,” 155

structure of, 150–152, 160, 164–165, 172, 175, 

175f, 178–180

systems organizing structure and, 74, 141

tobacco control, research on, 165–169

unique properties of, 151

value of, 148–149, 155–159

vertical, 164

network alliance function, dedicated, 155

network analysis, 8, 56, 147–181

application of, 159–160

benefits of, 159–160, 180–181

case studies, 48t, 157, 169–180

comparative, 180

current directions in, 232–233, 233t

data collection for, 160, 165–171

definition of, 159

goals of, 48t

guidelines for, 160, 181

information needed for, 161–165

for ISIS, 170–171

ISIS conclusions on, 240–241

key informants in, 166, 168–169

levels of, 149–152

network selection for, 166, 168

organization identification for, 161–162

overlap with other approaches, 230–231, 230t

quantitative, 165–166

relationship identification for, 163–164

services identification for, 162–163, 166, 168

streamlining, 168

in tobacco control

case study, 169–180

data collection methods for, 160–169

translation into practice, 175–180

Web-based environment for, 170

network applications, in public health, 8

network attributes, as measure of tobacco control 

efforts, 8

network behavior, theories of, 8, 152–154, 181

network bounding, 161

network development, in knowledge 

management, 196

network directories, 201

network leaders, data collection from, 166

network organizations, 74

network relationships

client referrals and, 174–175, 174f

institutionalized, 180

strength of, 154, 270

type and frequency of, 163–164, 178, 180

weak, 168

network theory, 46

individual-level, 149–150

overview of, 148–154

New Citations, 186
286

I n d e x

“new sciences,” 40–41

New York State

tobacco control program in, 171–175, 172t

welfare reform study, 115

nicotine, “free-base” form of, 15

nicotine addiction, potential for, 15

nicotine delivery

efficacy of, 14–15

measurement of, 14–15

nicotine replacement therapy, 13, 28

NIH (National Institutes of Health), Roadmap 

Initiative, 27, 235

nodes, network, 161, 172, 174

nominal groups approach, 71

nonlinear systems, 44, 46

North American Quitline Consortium, 160–161

network analysis of, 160–169, 181

North Karelia (Finland) Project, 21

O

obesity control initiative, 85–86

Oklahoma, tobacco control program in, 171–175, 

172t, 173f

open-space meetings, 72–73

open systems framework, power issues and, 76

operating system, 65

operational milestones, 75

organization(s)

adaptive, 62, 73–74

definition of, 62

evolution of, 153–154

identification of, for network analysis, 161–162

learning, 113, 226

development of, 42–43, 79, 235–236

as machines, 64

“network,” 74

networks of, 62, 152

as organisms, 73, 78

purposeful, 62, 73–74

organizational behavior, 63, 188

organizational change. See also system dynamics

approaches to, 78

theories of, 153–154

organization infrastructure, for knowledge 

management, 196, 208

organizing function

in traditional model, 64, 65t, 68

in VSAL model, 69, 84t

outcome maps, 72

out-degree centrality, 150–151

P

parameters, estimation of, 116, 132–133

participants

empowerment of, 116

ISIS, 251, 253–254, 256

in knowledge management, 194–195, 195f, 208

network, data collection from, 167

substitution of, 75

participative work redesign, 72

participatory action research, 78–80, 234

participatory agents, 77–78

participatory evaluation, 79–82, 82f, 226

participatory intervention model, 80

participatory methods, 47, 50–51, 84t, 226

key elements of, 50

of needs assessment, 238

for planning, 72–73

structured process for, 77

types of, 50

value of, 50–51

participatory research

community-based, 80, 236

power balance in, 76

passive smoking, 18, 20

pathology tools, 204

pattern matching, 102

example of, 88–89, 90f, 102, 102f

for tobacco knowledge base, 214, 215f

Pawtucket Heart Health Program, 21

Pennsylvania, tobacco control program in, 

171–175, 172t

people. See also participants

in knowledge management, 194–195, 195f, 208

per capita spending, on tobacco control, 171

persistence, 75

personal mastery, 42

Philip Morris, 17–20, 29

physical proximity, networks and, 153, 164–165

Pink Book, 203

4P-KMT map, 197, 198t, 199f, 207–208

PLANET project, 186, 198–203, 229

knowledge management strategy, 209, 210t, 

237, 242

planning

dynamic databases for, 239
287

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

knowledge base for, 201–202

map-based approaches to, 71–72

model of, 71

participatory methods for, 72–73

planning function

collective vision and, 71

in traditional model, 64, 65t, 68

in VSAL model, 68–69, 84t

policy makers, participation of, 51, 53–54, 

262–263

policy resistance, 115–116

policy simulation, 117

political climate, for state tobacco control 

programs, 171–172, 172t, 173f

population-level efforts, at tobacco control, 

20–25, 30, 39

population science special interest group, 205

population surveillance systems, development 

of, 28

power, structure and, 76–77

practice domain, in systems organizing model, 

67, 69

practitioners

participation of, 3f, 51–52, 261, 271, 271t

value of networks for, 156–157

PRECEDE/PROCEED framework, 234

prevention, focus on, 28

process

in knowledge management, 195–195, 195f, 208

in systems approaches, 230–231, 231t

product

in knowledge management, 195f, 196, 208

tobacco as, 14

program development databases, 239

program evaluation, 169

program evaluation databases, 239

program theory, 81

Project Low-Fat Eating for America Now (LEAN), 

85–86

propriety, 82, 82f

protobacco constituencies, in causal maps, 

122–124, 123f

proximity, networks and, 153, 164–165

public, undecided, in system dynamics model, 

139–140, 139f–140f

publications, 52–53, 136, 186, 236

public awareness, of health risks, in causal maps, 

120–121, 120f

public goods theory, 153

public health

concept mapping in, 72

evolution of, 12–13, 39, 142, 226

ISIS project as framework for, 5, 232

knowledge management framework for, 188–

191, 189f, 222, 222f

network analysis in, 155–156, 159

system dynamics in, 117

systems approaches to, 47, 55, 235–236, 

241–242, 260

public health agencies

collaboration among, 27

competition among, 124–125

public health planning, large-scale framework for, 

268–269, 268f

public opinion, influences on, 130

public opinion sector. See also social norms

in system dynamics models, 126, 126f, 129–

134, 131f–134f, 137–141, 138f–140f, 145f

public support, and research utilization, 135–139, 

136f–139f

purpose

in knowledge management, 194, 195f, 207

shared, 236, 263

purposeful goals, 73

purposeful organizations, 62, 73–74

puzzle-solving methods, 50

Q

quality assurance, 201

quantitative analysis, of networks, 165–166

quantitative management, 63

questionnaires, for network analysis, 167

quitlines, national network of. See North 

American Quitline Consortium

R

rating task, in concept mapping, 98–99

real-time strategic change, 72

receptor capacity, lack of, 205–206

reciprocity, network, 158

referrals, client, 164, 174–175, 174f

refutability, 116

relationship(s)

broker, 150

exchange, 152
288

I n d e x

formation of, 78

network (See network relationships)

between public sector and tobacco industry, 18

reputational sampling techniques, 162, 166, 168, 

170

research

collective vision in, 235

effect on smoking prevalence, 139, 139f

funding for (See funding, specific topics)

participatory, 78–80, 234, 236

relevance of, 206

research approval, streamlining of, 53

research domain, in systems organizing model, 

67, 69

researchers

awareness of health risks, in causal maps, 

120–121, 120f

communication between, 53

participation of, 3f, 51–53, 262, 271, 271t

power issues, 76

research fraction, public support and, 135–136, 

136f, 137–139, 138f–139f

research sector, in system dynamics models, 127, 

127f, 129, 135–137, 136f–137f, 144f

research utilization, 13, 27–28, 52–53

case study, 87–92, 95

framework for, 268–269, 268f

knowledge base for, 189

networks and, 240

power issues with, 76

in system dynamics models, 135–139, 136f–139f

trust and, 80

resource(s)

for effective networks, 155

optimal use of, 156

resource allocation, 53, 158

resource dependence theories, 152

respect, development of, 76–77

responsibility, cluster rating map of, 93, 94f

Richmond, Barry, 42, 111–113

risk factor data, 201

Roadmap for Medical Research Initiative (NIH), 

27, 235

Robert Wood Johnson Foundation

research utilization initiative, 87

SmokeLess States Program, 24, 251

system dynamics simulations, 117

transdisciplinary efforts, 27

Turning Point grant, 157

root definition, 43–44

rules, versus recipes, 74

rural chronic disease, network analysis of, 157

S

Saint Louis University School of Public Health, 

Center for Tobacco Policy Research, 169

SAMHSA (Substance Abuse and Mental Health 

Services Administration), 27, 117, 200–201

Santa Fe Institute, 232

satisfaction, with loosely coupled systems, 75

“scale free” networks, 151

scanning, network capacity for, 178, 231, 238

scientific discovery. See research

scientific management, 63

search conference, 73

secondhand smoke, 18, 20

SEER registry, 199, 201–202

self-interest theories, 152

self-management, 76, 78

self-organization, 234, 269

in complex adaptive systems, 46, 62, 73–74, 83

September 11, 2001, systems view of, 115

service implementation network, 163

shared information, 164

shared purpose, 236, 263

shared situational awareness, 238

shared vision, 42–43

SimSmoke, 117

site visits, for network analysis, 167, 169

skilled personnel, lack of, 241

small-world networks, 149, 155

SmokeLess States Program, 24, 251

smokers, in causal maps, 119–120, 119f

smoking

adverse health outcomes associated with, 

first report of, 17, 133, 227, 251

passive, 18, 20

prevalence of, 15–16, 19, 30

effect of research on, 139, 139f

models of, 128–129

social attitudes toward (See social norms)

Smoking and Tobacco Control Monographs 

(NCI), 20, 234, 245–246

smoking behavior, 15–16, 20. See also tobacco 

use

genetic basis for, 16

and nicotine yield, 14–15
289

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

smoking cessation

biobehavioral aspects of, 15–16, 20

in system dynamics models, 134–135, 135f

smoking initiation

biobehavioral aspects of, 15–16, 20

in system dynamics models, 126, 127f, 128–129, 

133–134, 134f

snowball sampling approach. See reputational 

sampling techniques

social contagion, 153

social context

of knowledge management, 191, 217

of tobacco control, 13, 19–22

social networks, theories of, 152–154

social norms. See also public opinion

in causal maps, 119–120, 119f, 123, 134–135, 

134f–135f, 138

influences on, 130

socioeconomic factors, in tobacco use, 15–16

soft systems methodology, 43–44, 112–113

software. See computer software

SoTC (Strength of Tobacco Control) measure, 48, 

94–95, 118, 229, 242, 245–246

span gaps, in networks, 150

stability, network, 155, 178

stadium wave, complex behavior of, 45

stakeholder groups, 240. See also network(s)

collaboration among, 27, 54

dialogue among, 78

engagement of, 116

evaluation driven by, 79

identification of, 206

implementation of conclusions with, 271, 271t

inclusion of (See participatory methods)

knowledge management and, 193, 215–216

model of, 3f

similarities among, 263

systems thinking driven by, 113

types of, 51

Stanford Five-City Project, 21

“star” networks, 155

State Cancer Legislative Database, 203

state cancer profiles, 201

state government, tobacco control support from, 

171

state health departments, 23, 27

State Tobacco Activities Tracking and Evaluation 

Systems (CDC), 242

state tobacco control programs

cooperative, 92–95

financial and political climates, 171–172, 172t, 

173f

funding changes and, 169, 175, 175f

network analysis of, 169–180

statistical competence, development of, 271

steering behaviors, 45

stocks, in causal maps, 118–119, 131–132, 132f, 

142, 231

strategic planning, collective vision and, 71

Strategies to Control Tobacco Use in the United 

States: A Blueprint for Public Health Action in 

the 1990’s (NCI), 20, 234

strategy maps, 72

knowledge management, 197, 198t, 199f, 

207–209, 210f, 210t–211t, 218–220

SoTC (Strength of Tobacco Control) measure, 48, 

94–95, 118, 229, 242, 245–246

structural holes, in networks, 150

structure, 7, 73–77, 83, 96

behavior determined by, 116

case study, 85

of networks, 150–152, 160, 164–165, 172, 175, 

175f, 178–180

power and conflict issues with, 76–77

in VSAL model, 65, 66f, 67, 95

structured conceptualization. See concept mapping

structuring step, in concept mapping, 98

Substance Abuse and Mental Health Services 

Administration (SAMHSA), 27, 117, 200–201

superorganisms, complex behavior of, 45

Surgeon General’s Advisory Committee on 

Smoking and Health, 17, 133

Surgeon General’s report, first, 17, 133, 227, 251

Surveillance, Epidemiology, and End Results 

(SEER) registry, 199, 201–202

survey instruments, for network analysis, 167

system(s)

behavior as, 111–113, 116

as cause, 114

complex adaptive, 44–45, 113, 226–227, 232, 255

definition of, 14, 39

evolution of, 46, 113

loosely coupled, 74–76

natural formation of, 74

nonlinear, 46

structured development of, 77

tobacco use as, 13–20, 25, 141, 246

system dynamics, 4, 6–8, 56, 109–145, 227

applied to tobacco control, 116–133

brainstorming in, 116
290

I n d e x

case studies, 48t

characteristics of, 116

computer simulation of, 111–114, 142

current directions in, 232–233, 233t

definition of, 2, 41–42

examples of, 228, 229t

feedback loops in, 110, 114–115, 114f, 132–133, 

133f, 141–142, 226

goals of, 48t

ISIS conclusion on, 237–240

overlap with other approaches, 230–231, 230t

versus systems thinking, 41–42, 111–113

uses of, 110–111

system dynamics models, 4, 8, 72, 110–111, 

113, 227

causal mapping for, 118–125, 119f–125f, 

231–232

development of, 125–131, 143, 143f–145f

examples of, 115, 117

overlap with other approaches, 231

results of, 133–141

sector component groupings, 117–118, 118f

validation of, 131–132, 132f

value of, 131–132, 141

system networks. See network(s)

systems approaches

benefits of, 5, 7, 232, 238

capacity building for, 6, 241, 244

case studies of, 47–51

common methodologies across, 230–231, 230t

definition of, 14, 39

integration of, 2, 3f, 49, 49f, 55, 228–230, 

260–266

framework for, 269, 269f

importance of, 6, 30

large-scale framework for, 268–269, 268f

potential uses of, 5, 7, 38–39, 49–50, 55–56, 

226, 246, 271

versus traditional management theory, 65–70, 

66f, 83, 95, 226, 234–235

types of, 2, 4, 7

systems concepts, 45–47

systems knowledge, 4, 6

definition of, 2

management of (See knowledge management)

systems methods, definition of, 14, 39

systems organizing, 4, 56, 61–103, 226

case studies, 48t, 83–95

current directions in, 232–233, 233t

definition of, 2

development of, 243

examples of, 228, 229t

goals of, 48t

ISIS conclusions on, 234–237

model of, 65–83, 66f

overlap with other approaches, 230–231, 230t

principles of, 7, 65, 66f, 67–68, 84t, 95–96

role of, 5–6

systems theory

curriculum for, 244, 272

development of, 237, 272

evolution of, 47–50, 113

history of, 40

systems thinking, 37–59, 245, 250

barriers to, 236–237, 244

capacity building for, 6, 241, 244

critical, 113

current directions in, 232–233, 233t

definition of, 14, 39–42, 111, 113–114

evolution of, 273

examples of, 41

frameworks for, 41–45, 55–56

implementation framework for, 259–275, 266f

integrated approach to, 47, 49, 49f, 55, 228–230, 

260–266

framework for, 269, 269f

in learning organizations, 42–43

misconceptions about, 40

mixed-methods, 237–238

national conference on, 244

participatory methods for, 47, 50–51

skills of, 42, 42t

versus system dynamics, 41–42, 111–113

vision for, 269–273

T

tacit knowledge, 188, 193, 221, 227

shift from explicit to, 193, 207, 214

tagging, in complex adaptive systems, 44

tar yield, 14

taxes

in causal maps, 123–124, 124f

at state level, 171

taxonomy, for knowledge base, 4, 9, 212–214, 

213t, 217

team(s)

conflict within, 76–77

self-managing, 76

team approach, to complex issues, 156

team learning, 43

technical management theory, 63

technology, in systems approaches, 230–231, 231t
291

M o n o g r a p h 1 8 . G r e a t e r T h a n t h e S u m

technology infrastructure, for knowledge 

management, 196, 208, 242

telephone interviews, for network analysis, 169

Terry, Luther, 17

thinking

ecological, 43, 44t, 226, 235–236, 238–239, 245

effective, principles of, 43

holistic, 40

system (See systems thinking)

The “Thinking” in Systems Thinking: Seven 

Essential Skills (Richmond), 42

3D model, of network development, 176–180

time factors

in knowledge management, 194

in network analysis, 158, 165–166, 168–169, 

175

tissue banks, 204

tobacco control

cooperative programs, case study, 92–95

evolution of, 12–13, 30, 39, 133, 142, 227–228, 

228f, 233–234, 250, 250f, 252

goals of, 12

history of, 17–18, 133, 227–228

knowledge management framework for, 

188–191, 189f

case studies, 197–209

management theory applied to, 68, 68f

as model for public health, 5, 232

network analysis in, 160–169

population-level efforts, 20–25, 30, 39

societal and environmental factors affecting, 

13, 19–22

stakeholder organizations in, 27

state-level programs (See state tobacco control 

programs)

state of, 4–7, 11–30, 39, 55, 226, 267

success of, 13

system dynamics applied to, 116–133

systems approaches in, 2, 3f (See also ISIS 

(Initiative on the Study and Implementation 

of Systems) project)

application of, 51–54

beginnings of, 20–25

examples of, 228, 229t

implementation of, 273–275

need for, 12–20, 55

systems problems in, 25–29, 38–39

tobacco control knowledge base, 199–206

concept mapping of, 209–217, 212f, 215f, 237

development of, 193

infrastructure, 206–209, 207t, 242

missing pieces in, 205–206

taxonomy for, 4, 9, 212–214, 213t, 217

transdisciplinary, 243–244

Tobacco Control Network (CDC), 201

tobacco control networks

case study, 169–180

data collection, 165–169

tobacco control sector, in system dynamics 

models, 118

tobacco grower factors, in causal maps, 119–120, 

119f

tobacco health risk, awareness of, in causal maps, 

120–122, 120f–121f

tobacco industry, 16–20

advertising by, 13, 16–17, 232

business coalitions with, 19

in causal maps, 122–124, 123f

image of, 19

lack of intelligence about, 205–206, 216

public sector relationship with, 18

response to tobacco control efforts, 12–13, 

17–19, 25, 29

state-level, 171

tobacco industry sector, in system dynamics 

models, 118

Tobacco Information and Prevention Source 

(CDC), 242

Tobacco Institute, 18

tobacco marketing, 13, 16–17, 232

in causal maps, 119f, 120

tobacco products, complexity of, 14

tobacco revenues, in causal maps, 120, 120f, 

121, 123

tobacco settlement funds, 18, 171, 232

tobacco taxes, in causal maps, 123–124, 124f

Tobacco Technical Assistance Consortium, 186

tobacco use. See also smoking behavior

biobehavioral aspects of, 15–16, 20

as complex system, 13–20, 25, 141, 246

societal and environmental factors affecting, 13

Tobacco Use Prevention Service (TUPS), 174

tobacco use sector, in system dynamics models, 

118, 126, 127f, 133–135, 134f–135f, 143f

traditional management theory, 62–65, 65t

functions in, 64, 65t, 67–68

versus systems approaches, 65–70, 66f, 83, 95, 

226, 234–235

transaction cost economics, 152

transactive memory systems, 157

transdisciplinary approach

facilitation of, 53, 235–236, 240–241

in ISIS project, 254
292

I n d e x

to knowledge management, 243–244

need for, 26–27, 39, 148

Transdisciplinary Tobacco Use Research Centers 

(TTURCs), 27, 166, 234, 236

translational research. See research utilization

trust

in collaboration, 80

development of, 76–77

in networks, 154, 158, 164, 178, 180

between practitioner and client, 52

and research utilization, 80

TUPS. See Tobacco Use Prevention Service (TUPS)

Turning Point grant, 157

U

U.S. Department of Defense, 28–29

U.S. Food and Drug Administration, 28, 118

utility, 82, 82f

V

VENSIM software, 126

vertical networks, 164

vertices, 46

virtual laboratories, 235

vision, 7, 70–73, 82, 96, 235

case study, 85–86

ISIS, 245, 260

link between mission and, 77–79, 82–83, 95

shared, 42–43

for systems thinking, 269–273

in VSAL model, 65, 66f, 67, 84t, 95

visual models, 71–72

vocabularies, 193, 204–205

von Bertalanffy, Ludwig, 40

VSAL model, 65, 66f, 67

W

W. K. Kellogg Foundation, 157

Washington, tobacco control program in, 

171–175, 172t

Web-based environment, 241

knowledge resources in, 155, 198–206, 242

for network analysis, 170

for program design, 239

systems approaches in, 243

“Web of Science,” 236

Weissman, George, 17

welfare reform study (New York State), 115

whole-systems perspective, 78

Wikipedia, 187, 239

workspaces, 204–205

World Health Organization, Framework 

Convention for Tobacco Control, 29, 161

Wyoming, tobacco control program in, 171–175, 

172t