Acknowledgements

We offer special thanks to Nancy Ostrove, recently retired from her position 

as Director, Risk Communication Staff, Office of Planning of the US Food and 

Drug Administration (FDA), and Lee Zwanziger, Designated Federal Official for 

FDA’s Risk Communication Advisory Committee. Without them, this guide, like 

so many of FDA’s initiatives, would not have happened. We also thank Nancy 

Derr and Elena Ketelhut for their thoughtful and patient help in seeing the 

guide through the production process. Finally, we thank the guide’s authors 

and reviewers. Each has either served on the Committee or supported its work. 

Each has also had a role in creating the field of risk communication, producing 

its research foundations or making communications work in ways that are 

faithful to the science being communicated and to the needs of those whom 

it serves. 

We also thank the following publishers for kind permission to reuse figures: 

Elsevier (Chapter 4, figure 1 and Chapter 8, figure 2), John Wiley and Sons 

(Chapter 4, figure 2 and Chapter 8, figure 1), Nature Publishing Group 

(Chapter 4, figure 3), Lawrence Erlbaum Associates (Chapter 15), and University 

of California Press (print) and Lisa M. Schwartz (electronic) (Chapter 6, 

figure 1). Other figures were obtained from open sources such as governmental 

publications, created by the authors for this volume, or were owned by the 

authors for purposes of reuse in their own works. 
Published by the Food and Drug Administration (FDA), US Department of Health and 

Human Services, August 2011. 

Contributors to this compilation are past or current members or consultants of the FDA’s 

Risk Communication Advisory Committee. For more information on the committee, 

see http://www.fda.gov/AdvisoryCommittees/CommitteesMeetingMaterials/ 

RiskCommunicationAdvisoryCommittee/default.htm 

FDA Disclaimer: The findings and conclusions in this compilation are those of the 

individual authors and do not necessarily represent the views of the Food and Drug 

Administration. 

There is no copyright in U.S. government work (per 17 U.S.C. 105), and the work 

provided here is considered U.S. government work. 

Communicating Risks and Benefits: An Evidence-Based User’s Guide is available on FDA’s 

Web site at http://www.fda.gov/ScienceResearch/SpecialTopics/RiskCommunication/ 

default.htm 

US Department of Health and Human Services,
	

Food and Drug Administration
	

10903 New Hampshire Ave, Silver Spring, MD 20993
	

Cover photo: Nancy M. Ostrove, Rock formation, Valley of Fire State Park, 2009 

Cover design: Erica Munoz, 2011 
 

 

 

 

Communicating Risks and Benefits: 

An Evidence-Based User’s Guide 

Table of Contents 

Introduction to Evidence-Based Communication Page

Chapter 1: Introduction - (Editors)...................................................................................... 1
	

Chapter 2: Goals - Noel Brewer........................................................................................... 3
	

Chapter 3: Evaluation - Julie Downs.................................................................................. 11
	

Chapter 4: Duty to Inform - Baruch Fischhoff ................................................................... 19
	

Chapter 5: Language - Musa Mayer.................................................................................. 31
	

Evidence-Based Best Guesses at Best Practices

 Basic Processes 

Chapter 6: Definitions - Baruch Fischhoff ......................................................................... 41
	

Chapter 7: Quantitative Information - Angie Fagerlin, Ellen Peters.................................. 53
	

Chapter 8: Qualitative Information - Julie Downs, Baruch Fischhoff ................................ 65
	

Chapter 9: Health Literacy - Michael Wolf........................................................................ 77
	

Chapter 10: Affect and Emotion - Ellen Peters.................................................................. 89
	

Chapter 11: Information and Persuasion - Mary Brown, Christine Bruhn ...................... 101
	

Chapter 12: Across the Life Span - Valerie Reyna ........................................................... 111
	

Chapter 13: Health Care Professionals - Betsy Sleath, Michael Goldstein ...................... 121

 Communication Design 

Chapter 14: Readability, Comprehension, and Usability - Linda Neuhauser, Kala Paul.... 129
	

Chapter 15: Warnings and Disclosures - J. Craig Andrews.............................................. 149
	

Chapter 16: Human Factors - Gavin Huntley-Fenner ...................................................... 163
	

Chapter 17: Shared Decision Making - Nananda Col...................................................... 173
	

Chapter 18: News Coverage - Gary Schwitzer ................................................................ 185
	

Chapter 19: Inside the Organization - Caron Chess ........................................................ 195
	

Implementing Evidence-Based Communication

Chapter 20: Practitioner Perspectives - Lee Zwanziger .................................................. 205
	

Chapter 21: An Agency Perspective - Nancy Ostrove ..................................................... 215
	

Chapter 22: Strategic Planning - (Editors)....................................................................... 223
	

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 1
	

Chapter 1: Introduction

Baruch Fischhoff, PhD - Carnegie Mellon University 

Noel T. Brewer, PhD - University of North Carolina 

Julie S. Downs, PhD - Carnegie Mellon University 

Organizations bear economic, legal, and ethical obligations to provide 

useful information about the risks and benefits of their products, policies, and 

services. Failure to fulfill those obligations can be costly, as seen with Three 

Mile Island, Hurricane Katrina, Vioxx, and other cases when people believe 

that they have been denied vital information. Less dramatic versions of these 

problems arise with poorly handled produce recalls, badly labeled appliances, 

and confusing medication instructions. Financial analysts estimate that 70% 

of a typical private firm’s assets are intangibles, like goodwill, that can be lost 

when communications fail. Public institutions’ reputations often depend on 

their ability to communicate. 

Risk communication is the term of art used for situations when people need 

good information to make sound choices. It is distinguished from public affairs 

(or public relations) communication by its commitment to accuracy and its 

avoidance of spin. Having been spun adds insult to injury for people who have 

been hurt because they were inadequately informed. Risk communications 

must deal with the benefits that risk decisions can produce (e.g., profits from 

investments, better health from medical procedures), as well as the risks — 

making the term something of a misnomer, although less clumsy than a more 

inclusive one. 

The risk communication research literature is large and diverse, including 

results from many contributing disciplines (e.g., psychology, decision science, 

sociology, communications) and a wide range of applications. Unfortunately, 

the norms of academic research make it inaccessible to outsiders, filling it with 

jargon and technical details. Moreover, academic researchers’ theoretical 

interests often lead to studying communication processes in isolation, leaving 

gaps as to how research results apply to complex, real-world situations. Unable 

to access the research literature, practitioners rely on their intuition, unproven 

best practices, and popular accounts of psychological research. 

This guide seeks to fill that gap, making evidence-based communication 

possible. The chapters that follow cover key topics in risk communication, 
2 | Chapter 1: Introduction
	

focusing on three questions: 

(1) What does the science say about that aspect of human behavior? 

(2) What are the practical implications of those scientific results? 

(3) How can one evaluate communications based on that science? 

These questions assume that sound communications must be evidencebased in two related ways. One is that communications should be consistent 

with the science — and not do things known not to work nor ignore known 

problems. The second is communications should be evaluated — because even 

the best science cannot guarantee results. Rather, the best science produces 

the best-informed best guesses about how well communications will work. 

However, even these best guesses can miss the mark, meaning that they must 

be evaluated to determine how good they are and how they can be improved. 

Each chapter in the guide is self-contained, so that its issues can be studied 

on their own. Each is written as simply as possible, consistent with fidelity 

to the science it reports. Each includes both the references documenting 

its claims and an annotated list of further readings. They offer evaluation 

methods suited to practitioners with no budget, a small budget, and a budget 

worthy of the stakes riding on the communication — so that evaluation can 

become part of every application. 

Some chapters deal with the audience (e.g., how people interpret 

quantitative information, how emotions — and age — affect risk perceptions), 

others with communications (e.g., decision aids, mass media). Introductory 

chapters consider the goals of risk communications (Chapter 2), methods 

for evaluating them (Chapter 3), standards for assessing their adequacy 

(Chapter 4), and the language that they use (Chapter 5). The first of three 

concluding chapters reports the perspectives of the committee’s practitioner 

members (Chapter 20). The second concluding chapter places the guide in the 

context of the strategic communication initiatives of the U.S. Food and Drug 

Administration (FDA), including the Risk Communication Advisory Committee, 

which created the guide (Chapter 21). The final chapter summarizes the state 

of the science and the steps that organizations can take toward evidence-based 

communication (Chapter 22). 

FDA regulates some 20% of the U.S. consumer economy, including food, 

drugs, medical devices, and dietary supplements. This guide applies not only 

to all those products, but to any situation with a duty or desire to inform. We 

hope that it will help to foster a community of researchers and practitioners 

committed to evidence-based communications. We invite readers to join that 

community. Membership should not only aid their own work, but also help 

to protect the commons of public goodwill upon which all communications 

depend. Everyone benefits when individuals receive needed information in 

a timely, concise, comprehensible way, building warranted trust in their own 

decision-making abilities and in the institutions that support them. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 3
	

Chapter 2: Goals

Noel T. Brewer, PhD - University of North Carolina 

Summary

This chapter reviews three goals for risk communication. Just presenting risk 

information is an inadequate goal. More ambitious and defensible is to change 

what people think, or possibly, to change their behavior. Aiming to change 

beliefs or behavior provides specific outcomes for evaluating whether the risk 

communication worked. 

Introduction

Risk messages are so common that we often barely think about them: 

Smoking increases your risk for cancer. Don’t drink and drive. The terrorism 

threat level is orange. But what’s the point? Some risk messages seem to be 

merely about sharing information, or just getting it said. Others seem to be 

about changing what people believe or how they behave. As people charged 

with the task of communicating risk, we need to think carefully about what we 

can expect from specific risk messages and from broader risk communication 

efforts. The National Research Council emphasizes the need to link goals and 

outcomes: “A risk communication is successful to the extent that it contributes 

to the outcomes its sponsor desires.” 1 

Scarce resources raise the stakes for risk communication, because you may 

not get a second chance to have impact. A paradox is that you should think 

first about goals rather than resources. Experts in planning risk communication 

start with tools like logic models2 that allow them to think first about what 

outcomes they want to achieve. These specific outcomes will suggest goals 

that you can refine to meet your resources. However, making available 

resources the starting point can limit creativity and shut down options before 

they can be explored. 
4 | Chapter 2: Goals 

This chapter presents three simple goals of risk communication (Figure). 

Three potential goals of risk communication

Share

information

Change

beliefs

Change

behavior

They don’t apply to all audiences, communicators, or problems. It will be up 

to you to decide what fits your risk communication needs. It comes down to 

Alice’s dilemma in Alice in Wonderland 3: 

“Would you tell me, please, which way I ought to go from here?” 

“That depends a good deal on where you want to get to,” said the Cat. 

“I don’t much care where—” said Alice. 

“Then it doesn’t matter which way you go,” said the Cat. 

“—so long as I get somewhere,” Alice added as an explanation. 

“Oh, you’re sure to do that,” said the Cat, “if you only walk long enough.” 

It’s probably not enough to try something and hope it will work. Doing so, may 

leave you in Alice’s dilemma of just trying to get “somewhere.” 

Goal 1. Share information

The simplest form of risk communication has the goal of just putting risk 

information out there. It does not need to be easy to understand or have 

a clear message about what people need to do. Just say it. We see these 

messages all the time on consumer products. Many legal disclaimers have the 

flavor of just saying it. A company or agency relieves a legal responsibility by 

making the information available. 

The goal of just saying it will rarely match the implicit goals of responsible 

and ethical risk communication. Indeed, ethics may require that people 

understand the risk message. Some risk communication materials seem almost 

willfully hard to understand. Package inserts for drugs are one example. 

Prescription drugs come with detailed information about how to take them, 

their side effects, and how they work in the body. However, package inserts 

often come in very small type, printed on paper that is folded over on itself a 

half dozen times. Taken as a whole, it fairly shouts: “Don’t read me!” 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 5
	

This just-say-it approach can be well intended. Consent forms tell 

participants about risks and benefits of being in a research study. Scientific 

papers share the latest epidemiological evidence. Press releases recite specific 

scientific findings about a new hazard. If people are skilled and motivated, 

they can make sense of it. More often, I suspect, they are bored or confused 

by these long, technical documents written using complex language. Lawyers, 

editors, and scientists may insist on saying things precisely, but it does little to 

help everyday people. 

Negative effects of unclear or confusing risk messages include that people 

may ignore the messages or even laugh at them. Everyone knows mattress 

warning labels say removing them can be illegal, but few people know why. 

One result is that mattress warning labels have become a familiar punch line 

for jokes. Labels that are just plain odd include labels on sleeping pills that 

say they cause drowsiness or labels on hair dryers that say they should not be 

used while asleep. Such silly warning labels have inspired web sites, contests, 

and even books (“Remove Child before Folding: The 101 Stupidest, Silliest, and 

Wackiest Warning Labels Ever”).4

 These odd labels don’t create trust among 

consumers, and I suspect they have not saved lives. 

A more positive form of this just-say-it approach is a community forum for 

sharing risk information. The community may benefit from the process of 

receiving the risk information, regardless of whether people truly understand 

what they heard. They may feel valued for having been chosen to receive 

the information, come to understand one another better, or interact in 

various ways that reinforce the fabric of their community. Thus, receiving and 

discussing the risk information can be a good enough outcome. However, even in 

such cases, risk communicators should always strive to do more than just say it. 

Goal 2. Change beliefs

A more ambitious goal for risk communication is to change what people 

know and believe. They might come to know and understand new facts, or 

come to feel at risk for harm. Less helpfully, they might even accrue erroneous 

beliefs. I refer to knowledge, attitudes, and opinions simply as beliefs, though 

some social scientists make important distinctions among these things. In 

this chapter, I discuss the goal of changing beliefs in a general way, but later 

chapters discuss in more detail how to craft messages to persuade people they 

are at risk (Chapter 10) using accessible approaches (Chapters 11, 14). 

Changing risk beliefs is a good goal for risk communication when we can’t 

recommend one course of action for everyone. Sometimes we know that 

a health behavior is right for everyone, or at least specific groups, but very 

often we are not sure. In this case, it is especially important to share risk and 

benefit information to allow people to make their own informed decisions. For 

example, doctors do not yet know the best treatment for men with elevated 

prostate specific antigen or PSA test results.5

 Men could decide to have surgery, 
6 | Chapter 2: Goals
	

a type of radiation therapy, or another treatment — or they may choose to do 

nothing at all. As none of these treatments is known to have the best outcome, 

these men’s choices will depend solely on their values. And making the choice 

well requires men to know the risks and benefits of each option. In contrast, 

the goal of changing beliefs (but not behavior) would be inappropriate for 

women contemplating cervical cancer screening. It saves lives, and for this 

reason guidelines clearly recommend most adult women get screened. 

Communicating to be understood is consistent with the National 

Research Council’s recommended approach to risk communication: “Risk 

communication is successful only if it adequately informs the decision maker.”1 

It also meets what some argue are the ethical requirements for informed 

decision making.6 

One challenge is that not all people wish to make decisions about low- or 

even high-stakes issues or be informed of the various risks and benefits. In a 

recent study, one in eight women with breast cancer wanted minimal or no 

involvement with decisions about whether to get chemotherapy.7 Indeed, 

delegating decisions to experts or other trustworthy sources can be efficient, 

even when the decision is as important as getting treated for cancer. Life 

would quickly become impossible if all of one’s daily activities required a 

careful cost-benefit analysis of all the options to find the best one to choose.8 

For this reason, people routinely take mental shortcuts to make decisions 

easier. Thus, risk communicators need to know that not all people will want all 

possible information. 

Although making sure that people understand risk information can be an 

important goal, sometimes people mistakenly aim to change risk beliefs when 

they really want to change behavior. 

Goal 3. Change behavior

Another goal for risk communication is to change people’s behavior. We 

might want them to stop smoking, get a flu shot, or not eat eggs subject to a 

food recall due to salmonella contamination. In other words, having people 

think about it and make a careful decision is not a primary goal. We just want 

them to act. 

During a recent voluntary recall of eggs, FDA wanted people not to eat eggs 

from certain contaminated facilities. The idea of consumers thinking about the 

pros and cons of eating these eggs was not on the table by the time the recall 

happened. There was one message: Don’t eat these eggs. 

Changing behavior as a goal for risk communication requires that we know 

what the best course of action is. Ideas about what people ought to do can 

come from many places. They might come from research: Most sexually active 

women should get cervical cancer screening, unless they have had their cervix 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 7
	

removed in a total hysterectomy. They might come from expert advice: Older 

adults should get an annual flu shot as it is likely to save lives (even though no 

one can say for sure how well each year’s shots will work). They might come 

from an abundance of caution: The government routinely discourages people 

from visiting countries that are at war. The common element is that we want 

people to do a specific thing. Helping them understand the risks and benefits 

may be a secondary goal or perhaps not a goal at all. 

Contrast the decision to get prostate cancer screening (which medical 

studies offer conflicting advice about) with the decision to get cervical cancer 

screening. We know that cervical cancer is preventable with regular screening 

and early treatment. More than half of cervical cancer deaths are among 

women who never or rarely get screened.9

 The public health imperative for 

adult women is clear: Get screened. Indeed, many doctors feel so strongly 

about this that they withhold birth control pills until women get their annual 

Pap screening. This is very different from merely informing women about risks 

to change their beliefs and then just letting them decide about screening. It is 

still important to make sure women understand why they will be screened, and 

an individual woman and her doctor may come to their own decision about 

screening, but experts charged with the health of populations should send 

eligible women a clear message to get screened. 

Communicating to change behavior need not be for the public’s benefit. 

Much advertising has a goal of getting consumers to buy products. Cigarette 

ads promote a deadly product and in doing so make a lot of money for tobacco 

companies. They do this by promoting cigarettes as slimming, cool, and sexy. 

As a counterweight, the FDA’s cigarette warning labels take the same highly 

visual and high-impact approach to show that smoking is ugly, disgusting, and 

lethal. 

Our thinking about changing health and risk behaviors has a long history. 

Many scientific theories suggest that feeling at risk leads people to protect 

themselves. 10,11 Ample evidence supports this idea.12 Indeed, people who 

feel at risk for harm are somewhat more likely to try to protect themselves 

by taking actions like getting a flu shot or taking their medication. However, 

getting people to believe they are at risk and then to change their behavior 

turns out to be a tough task. 

If behavior change is the goal, risk communication may not be the only, or 

even the best, solution. We have this idea that merely sharing risk information 

will change what people do. But does this match what we know to be true 

in our own lives? Just telling a friend that trans-fats are bad for him or that 

seat belts save lives is unlikely to make him put down the donuts or buckle up. 

Many, many studies document failed risk communication campaigns that were 

designed using state of the art methods by well meaning people.13,14 This is one 
8 | Chapter 2: Goals
	

of the paradoxes of risk communication. People who feel at risk are more likely 

to take action, but it can be hard to get them to believe they are at risk and 

then to follow through. 

A take home message is that if the main goal is to change behavior, risk 

communication alone can be a weak way to do that. Public health successes 

often rely on policy changes, like banning trans-fats in food as New York 

City did in 2006 or in mandating that cars include seat belts and that people 

use them as the United States did decades ago. The FDA already adopts 

this approach with food scares. When possible, they prompt a recall of the 

questionable product. They also communicate with the public about the risk, 

but this is a stopgap measure meant to deal with supplies of the food already in 

people’s homes. 

Other policy approaches to changing behavior rely on increasing taxes 

on unhealthy products. Tobacco taxes are the single most effective way to 

decrease smoking,15 which is the leading killer of Americans due to its many ill 

health effects that include stroke, heart disease, and a long list of cancers.16 An 

increasingly popular and flexible policy change is to make healthier options the 

default.17 In my own work, we find that asking parents to consent to all teen 

vaccines increases consent for HPV vaccine above asking about just that vaccine 

on its own.18 Policies can supplement or even replace risk communication 

efforts as a way to benefit the public’s health and meet program goals. 

Evaluation

Each of these goals should lead us to think about evaluation. Just saying 

it means you have no expectation of impact, and thus you do not need to 

evaluate the impact. Communicating to change risk beliefs, however, clearly 

suggests assessing whether risk beliefs actually changed. And communicating 

to change behavior suggests assessing whether behavior did indeed change. 

Evaluation is not always needed: One can intervene but not evaluate. This will 

require using already tested methods and tools with few changes to them. 

Chapter 3 addresses evaluation in greater depth. 

One challenge is that risk messages can have unexpected effects on what 

people believe. Sometimes they work just fine. In some cases, however, 

people resist believing they are at risk. In other cases, merely mentioning risks, 

even very small ones, can cause people to overestimate potential harms and 

undervalue the benefits. These unexpected effects should not discourage us, 

but they mean that evaluation of the impact of messages can be important. 

Another challenge is that people may tune out risk messages. We exhaust 

consumers by talking about every possible hazard. Consumers expect us to 

share information that passes some minimum level of import and relevance. 

The complexity arises in deciding whether risk and benefit communication 

meets that need, and evaluation can help. 
 

 

 

 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 9
	

Conclusions

Choosing a goal for risk communication is fundamentally important. It 

affects what activities you choose, and what results you can expect. Choose 

the just-say-it approach if you want to make your lawyers happy, and then 

say it in language that is as hard to understand as possible. Choose the riskbelief-change approach if you’re not sure what the best course of action is 

for the whole population, but you have credible information about risks and 

benefits. Choose the behavior-change approach if you know what is best for 

the population, and then use belief change as a back-up or reinforcement. 

Whatever you do, make sure you don’t join Alice in asking which way to go as 

long as you get somewhere. 

Additional resources

1. http://www.re-aim.org/tools/Planning%20Tool.pdf. This helpful website has a checklist for 

planning interventions, but it can also be applied to risk communication campaign planning. 

2. Logic models. For a nice graphical way to show program inputs, outputs and outcomes, search 

the web for “logic models” or look at the paper by Millar, A., Simeone, R.S., & Carnevale, J.T. 

(2001). Logic models: A systems tool for performance management. Evaluation and Program 

Planning, 24:73-81. 

Endnotes

1 Committee on Risk Perception and Communication (1989). Improving Risk Communication. 

Washington, DC: National Academy Press. 

2 Millar, A., Simeone, R. S., & Carnevale, J. T. (2001). Logic models: A systems tool for performance 

management. Evaluation and Program Planning. 24:73-81. 

3

 Carroll, L. (1865, 2000). Alice in Wonderland. New York, Harper. 

4 Jones, B. D. (2007). Remove child before folding: The 101 Stupidest, Silliest, and Wackiest Warning 

Labels Ever. New York: Grand Central Publishing. 

5 Wilt, T. J., MacDonald, R., et al. (2008). Systematic review: comparative effectiveness and harms 

of treatments for clinically localized prostate cancer. Annals of Intern Medicine, 148, 435-448. 

6 Braddock, C. H., Edwards, K. A., Hasenberg, N. M., Laidley, T. L., & Levinson W. (1999). Informed 

decision-making in outpatient practice: time to get back to basics. JAMA, 282:2313-2320. 

7 Tzeng, J. P., Mayer, D., Richman, A. R., Lipkus, I. M., Han, P. K. J., Reitel, V., Valle, C., Carey, L. A., 

& Brewer, N. T. (2010). Women’s experiences with genomic testing for breast cancer recurrence 

risk. Cancer, 116, 1992-2000. 

8

 Simon, H. A. (1957). Models of Man. New York: Wiley.
	

9 Spence A. R., Goggin P., Franco E. L., et al. (2007). Process of care failures in invasive cervical 

cancer: systematic review and meta-analysis. Preventive Medicine, 45, 93-106.
	

10 Savage, L. J. 1954. The Foundations of Statistics. New York, Wiley.
	

11 Becker, M. H., Ed. (1974). The Health Belief Model and personal health behavior. Health 

Education Monographs 2:324–473. 
 

 

 

 

 

 

10 | Chapter 2: Goals
	

12 Brewer, N. T., Chapman, G. B., Gibbons, F. X., Gerard, M., McCaul, K. D., & Weinstein, N. D. 

(2007). Meta-analysis of the relationship between risk perception and health behavior: The 

example of vaccination. Health Psychology, 26, 136-145. 

13 Lipkus, I. M., Skinner, C. S., Dement, J., et al. (2005). Increasing colorectal cancer screening 

among individuals in the carpentry trade: Test of risk communication interventions. Preventive 

Medicine, 40, 489-501. 

14 Vernon, S. W. (1999). Risk perception and risk communication for cancer screening behaviors: A 

review. Journal of the National Cancer Institute Monographs, 1999, 101-119. 

15 Chaloupka, F. J., Straif, K., & Leon M. E. (2010). Effectiveness of tax and price policies in tobacco 

control. Tobacco Control [Epub ahead of print]. 

16 Mokdad, A. H., Marks, J. S., Stroup,D. F., & Gerberding, J. L. (2004). Actual causes of death in the 

United States, 2000. JAMA, 291(10):1238-1245. 

17 Johnson, E. J. & Goldstein, D. G. (2003). Do defaults save lives? Science, 302, 1338-1339. 

18 Reiter, P. L., McRee, A.-L., Kadis, J. A., & Brewer, N. T. (2011). Default policies and parents’ 

consent for school-located HPV vaccination. Unpublished manuscript. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 11
	

Chapter 3: Evaluation

Julie S. Downs, PhD - Carnegie Mellon University 

Summary

Risk communications are all around us, but rarely evaluated. Formal 

evaluations can improve communications and separate those that work from 

those that don’t, making best use of scarce resources of time and money. 

This chapter discusses the role of formative, process, and outcome evaluation 

in avoiding common pitfalls that might undermine a communication’s 

effectiveness 

Introduction

Risk communications pervade our daily lives. Public service announcements 

educate us about early signs of a stroke. Cars beep at us to fasten our safety 

belts. Television shows how our brains will look on drugs. Cigarette packs 

warn of the hazards of using the products they contain. Such communications 

typically operate on the assumption that providing a little information – or 

motivation – about a risk will help people to avoid it. 

However, these messages don’t always produce optimal behavior change. 

The sheer omnipresence of warnings may undermine any single warning’s 

effectiveness.1

 We are accustomed to warnings even for risks that are minimal 

or self-evident, like a fishing lure that is “harmful if swallowed.”2 So perhaps 

it is not surprising that we react to new communications with inattention, 

rather than heightened alertness. When a computer message pops up, we swat 

it away without even reading it.3 When credibility is low or ulterior motives 

are suspected, such as concern for liability, messages may be discredited.4 A 

brazen example comes from the game Pass-Out, which has Pink Elephant cards 

instructing players to “take 5 drinks” but warning them that it is “not intended 

for use with alcoholic beverages.” 

Even noticing a risk message is no guarantee of responding appropriately. 

To do so, one also needs to understand what it is asking,5 agree with that 

recommended course of action,6 and have the ability to do it.7 Promoting these 

steps toward improving a communication’s effectiveness and determining 

whether it has worked requires evaluation. 
 

 

 

 

12 | Chapter 3: Evaluation
	

Why formal evaluation is important

Communicators sometimes forego evaluation as an unnecessary and 

costly step that merely demonstrates what they think they know already.8 

After devoting time, energy, and passion to creating and disseminating a 

communication, people deeply desire to believe that it works. But faith is 

no substitute for scientific evidence of effectiveness. Reliance on intuition 

and anecdotal observation can result in devoting scarce resources to wellintentioned but ineffective communications.9 

A formal evaluation will dispassionately reveal whether a communication 

is effective. If it’s not, the communication should be revised or discontinued, 

freeing up resources so that more promising communications get wider 

audiences. Future work can then build on the evidence of successes and 

failures. 

Evaluation informs three areas of communication development. Formative 

evaluation guides development by identifying the optimal content, format, 

delivery channels, and other critical aspects of the message. Process evaluation 

assesses communication delivery, measuring outreach, consistency, and 

implementation. Outcome evaluation determines whether a communication 

meets its goals. 

Formative evaluation. Creating a risk communication requires choices about 

the best approach. Formative evaluation is used to form the communication, 

helping designers choose content, format, and delivery strategies through 

participatory (user-centered) design.10 Sound research focuses members of 

the target audience on their understanding of the target risk, rather than 

hypothetical situations, as people have little insight into their reasons for 

action.11 

The focus group is a popular method.12 Unfortunately, the rich data from 

interactions among group members are difficult to analyze and, indeed, often 

largely ignored.13 Statistical analyses of focus groups require large samples 

because the interdependency of what members say requires using groups 

(rather than individuals) as the unit of analysis.14 Usability testing, popular in 

engineering, asks prospective users of a new tool or communication to “think 

aloud” as they review it.15,16 Key informant interviews, popular in ethnography, 

ask select individuals to share their experience and expertise.17 The mental 

models approach uses semi-structured interviews and quantitative surveys to 

map understanding into a scientifically derived expert model.5,18 

All these approaches requiring listening to members of the target audience 

to inform communication development, a labor-intensive step that can be 

tempting to skip, relying instead on intuition. It’s exciting to have a flash of 

insight into how to get across a message. Indeed, the best communications 

typically do start out as an idea in the communicator’s head. Unfortunately, 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 13
	

that’s how the worst ones start out, too. Such intuitions can miss the mark, in 

part, because the communicator is often not part of the target audience. For 

example, scientists studying a specific risk may feel that nobody would chance 

exposure, if they just knew about the risk. According to this intuition, mere 

awareness of the problem and knowledge of personal susceptibility should 

be sufficient to motivate action. However, professionals who have dedicated 

their lives to reducing a particular risk may not appreciate the perspective of 

people for whom that problem is just one of many. Such misunderstandings 

increase when the communicator is not a member of the target audience at all. 

For example, public health officials, parents, and teachers hoping to educate 

adolescents about drug abuse may have little insight into how teenagers think 

about drugs and, hence, how they will perceive well-intentioned, but tonedeaf, messages. 

A research-based approach takes the guesswork out of communication 

development. Formative research needs to incorporate creative input 

when creating a risk communication. However, testing is needed to guide 

improvements of draft communications so as to promote audience members’ 

comprehension, trust, and empowerment. 

Process evaluation. The path from the developer’s desk to the target 

audience presents many obstacles. Process evaluation assesses how well this 

path is followed, documenting each step to ensure that a communication 

has maximal impact.19 Evaluators describe the program and document 

the procedures needed to implement it, identifying who will deliver the 

communication and who will receive it. Such evaluators develop a data 

collection plan with steps, such as identifying stakeholders for consultation 

or observation and developing instruments to measure their variables of 

interest.20 A process evaluation can help to explain why a communication had 

the effects that it did and let others know what to expect if they follow a similar 

strategy. 

Process evaluation is particularly valuable for assessing how well procedures 

follow the communication plan conceived during development. Assessing 

fidelity to the plan is especially important when there is variability across 

settings, differences in the communication media, or other opportunities for 

variability. Deviating from well-conceived procedures can undermine the value 

of careful formative research. 

One common trap is changing a communication’s content or delivery to meet 

perceived needs of a specific audience segment. For example, educators may 

change a communication hoping to make it even better for their own students. 

Because teachers know their students better than far-off researchers and take 

pride in their sometimes-difficult job, it is only natural for them to want to 

try to improve an intervention in ways that suit their classroom and students. 

Unfortunately, without a research base for guidance, such idiosyncratic 
14 | Chapter 3: Evaluation
	

tailoring is more likely to weaken the communication than improve it. If 

audiences differ sufficiently in their needs to justify such changes, tailoring 

mechanisms should be devised as part of formative evaluation. 

Communication procedures should plan for foreseeable contingencies 

affecting the planned distribution. People who deliver information or facilitate 

discussions should be well trained. Unless they are very highly skilled and 

knowledgeable, their authority to change the content should be minimized. 

Delivery systems that rely on the Socratic method (asking questions so that 

audience members infer the message by themselves) or other audiencegenerated content require special care to ensure that the critical information 

will be reliably conveyed. Process evaluation can identify and alleviate such 

problems with dissemination and implementation, and provide documentation 

to guide future communications. 

Outcome evaluation. A high-quality development process should create 

communications with the best chances of working. The best-laid plans, 

however, often go awry. To find out if a communication actually has had its 

intended effect, outcome evaluation is needed.21 

Outcomes can take many forms, including behaviors (quitting smoking), 

attitudes (decreased prejudice), knowledge (emergency evacuation plans), skills 

(using a condom correctly), or intentions (exercising daily). Some outcomes 

may serve as proxies for larger goals that are difficult to measure. The more 

distant the outcome is from the goal, the less confidence can be drawn from 

positive results.22 

Although any outcome evaluation is better than none, high-quality 

evaluations are costly, making it tempting to cut corners. One common 

shortcut is to rely on immediate post-test surveys, rather than waiting for 

changes in behavior. However, self-reports on surveys are often problematic, 

especially for attitudes, knowledge, and intentions. The attitudes that 

participants report may be biased by their desire to help the researcher or to 

look good, leading them to answer how they think they should, rather than give 

their real opinions. Such demand effects are particularly prevalent following 

transparent communications: Presenting risks of smoking and then asking 

how the audience feels about smoking is likely to generate biased answers. 

Self-reported knowledge levels can be unreliable, too, insofar as people tend 

to be poor judges of how much they know, failing to appreciate what they 

do not know; a validated test assessing actual knowledge of relevant facts is 

preferred. Self-reported intentions to engage in behavior can suffer from both 

demand effects and lack of self-insight (seen in forecasting errors). The more 

abstract the stated intention, the less well it predicts behavior. For example, 

the intention “to give blood today at 3:15 at the blood drive in my building” will 

be a better predictor of actually giving blood than a general intention to help 

others. Even specific intentions may not predict behavior very well, as people 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 15
	

are often unaware of what causes their behavior.11 When imagining future 

behaviors, people tend to neglect the situational details that might interfere 

with even the best of intentions. 

Another common, but problematic, approach is to compare those who 

happened to see or use a communication — possibly due to their own 

choice — to others who didn’t see it. Such self-selection can reflect group 

differences that are confounded with evaluation outcomes, making 

comparisons tricky. For example, diners ordering from children’s menus 

probably order fewer martinis than diners with regular menus, but nobody 

would argue that children’s menus constitute an effective anti-drinking 

campaign. Similarly, the finding that diners who read calorie information on 

menus eat lower-calorie meals (compared to those who say they didn’t look 

at that information)23 says little about the causal effects of calorie labeling. 

Correlation need not imply causation. In this case, concern about nutrition may 

have motivated both the reading and the eating. 

Rigorous outcome evaluations (Table) compare the outcomes for a 

group that is given a communication to a group that doesn’t get it, but is 

otherwise equivalent.24 The strongest design is a randomized controlled trial, 

with participants randomly assigned to receive the communication or to a 

control group, making it possible to attribute differences in outcomes to the 

communication. 

Outcome evaluation research designs

Design type Factors to consider

Randomized controlled 

trials 

Highest quality design for outcome evaluation 

Can definitively establish causality 

Can assess mediators to demonstrate process 

Observation of 

environmental changes 

Useful when external validity is especially important 

Gradual, long-term changes 

Inclusion of yoked control population raises confidence in results 

Limited comparisons 

(pre- versus postcommunication) 

Can be done with very small budget 

Partial support of causality, if other factors are well controlled 

Better than nothing, if measures are well designed 

In addition to determining the effect of a communication, randomized 

controlled trials can measure intervening variables that may explain the 

mechanisms underlying any observed effects. For example, a communication 

promoting mammography screening was found to increase the perceived 

benefits of screening. A mediation analysis found that it worked by increasing 

readers’ perceived susceptibility to breast cancer, not by increasing the 

perceived severity of the cancer.25 
16 | Chapter 3: Evaluation
	

Randomized controlled trials are not always feasible, such as when 

behaviors are subject to multiple situational forces or the intervention occurs 

naturally (e.g., exposure to a widely publicized celebrity’s illness). In such 

cases, a quasi-experimental design can still be useful, such as systematically 

exploring differences between people who were and were not exposed to the 

communication. Crisis communications (e.g., regarding the anthrax attacks or 

the SARS outbreak) typically have such confounds and are evaluated poorly, if 

at all.26 However, whatever the limits to a systematic retrospective evaluation, 

it is still better than relying on intuition, which can be misleading or even selfserving. Often, reasonable inferences can be made, given precautions such as 

selecting comparison groups to ensure maximum similarity to those receiving 

the communication (e.g., drawing people from nearby, similar regions). A 

mixed-methods design might, for example, combine quantitative reports of 

knowledge or behavior with qualitative descriptions of reactions to the risk 

communication, to triangulate measures.27 Evaluating crisis communications 

before they are deployed can both improve their effectiveness (e.g., by 

reducing terms that mislead or offend recipients) and clarify their impacts (e.g., 

by knowing how well they are understood in different groups). 

When a high-quality comparison is needed, but the resources are lacking, 

any evaluation is better than none, as long as its limits are understood. 

One might just measure outcomes of interest in a single group before and 

after exposure to a communication, taking as much care as possible to craft 

measures that avoid demand effects (e.g., by using disinterested intermediaries 

to elicit candid and critical responses) and forecasting errors (e.g., by eliciting 

knowledge of preferred behaviors, rather than predictions of intended 

ones). Thoughtful measures that find substantial improvement in pre/post 

comparisons might even provide the impetus to secure additional funding for a 

rigorous evaluation. In this spirit, each chapter in the next section of this guide 

considers how to evaluate one’s success in applying its lessons with no budget, 

a small budget, or an appropriate budget. 

Conclusions

Formative evaluation can help create a promising risk communication, 

process evaluation can improve and document its delivery, and outcome 

evaluation can quantify its effects. Using strong research methods at each 

stage will improve both the chances for immediate success and for learning 

from experience. Understanding those methods can not only make the best 

of a limited budget, but can also help avoid using misleading methods, such 

as asking people whether they believe a communication would affect their 

behavior. The key principle underlying sound evaluation is to measure the 

desired outcomes as directly as possible (e.g., actual behavior or knowledge), 

rather than trusting distant proxies (e.g., general intentions or attitudes) or, 

worse, relying on intuition. 
 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 17
	

Organizations that view communication as a strategic function28 will find 

ways to evaluate critical communications, including those that will be used 

only in rare circumstances. They will realize, for example, that even though 

telling people to evacuate a burning building may seem to require no testing, 

a proper process evaluation will ensure that exits are clearly marked—with 

familiar words and symbols—near doors that allow effective evacuation.15 

They will realize that even messages that seem very simple (e.g., roping off 

a slippery surface to prevent falls) require evaluation (e.g., whether people 

choose alternate routes that are actually safer.)29 In these cases, a little 

forethought and casual input from others can help avoid problems stemming 

from assumptions that other people will act as we anticipate. Becoming more 

aware of the assumptions that we make about communication may be the first 

step in making them better. 

Additional resources

1. Royse, D., Thyer, B. A., Padgett, D. K., & Logan, T. K. (2010). Program Evaluation: An Introduction 

(5th edition), Belmont, CA: Wadsworth. This book provides a detailed guide to evaluating 

programs, including risk communications, with examples describing different methodological 

approaches to formative, process, and outcome evaluation. 

2. National Research Council, (1989). Improving Risk Communication. Washington, DC: National 

Academy Press. This report focuses on the needs of government and industry, covering both 

social choices, such as regulation, and personal choices, such as health behaviors. 

3. Renn O and Levine D. (1991). Credibility and trust in risk communication. In: Kasperson R, Stallen 

P, Eds. Communicating Risks to the Public. Boston, MA: Kluwer Academic Publishers; 175–218. 

This chapter discusses the need for openness and public involvement in communicating about 

risk. 

4. http://www.socialresearchmethods.net/kb/design.php This website provides links to many 

different research designs that are appropriate to evaluation, with fuller descriptions than are 

possible within this chapter. 

Endnotes

1 Purswell, J.L., Schlegal, R.E., Kejriwal, S.K., (1986). A prediction model for consumer behavior 

regarding product safety. In: Proceedings of the Human Factors Society 30th Annual Meeting. 

Human Factors Society, Santa Monica, CA, pp. 1202–1205. 

2 sds.hss.cmu.edu/risk/fishhook.pdf 

3 Kim, S. & Wogalter, M. S. (2009). Habituation, dishabituation, and recovery effects in visual 

warnings. Human Factors and Ergonomics Society Annual Meeting Proceedings, 53(20), 1612-

1616. 

4 Siegrist, M. & Cvetkovich, G. (2000). Perception of hazards: The role of social trust and knowledge. 

Risk Analysis, 20(5), 713-719. 

5 Morgan, M.G., Fischhoff, B., Bostrom, A., & Atman, C. (2001). Risk Communication: The Mental 

Models Approach. New York: Cambridge University Press. 

6 Cialdini, R. B. (2007). Influence: The Psychology of Persuasion. New York: HarperCollins. 

7 Bandura, A. (1997). Self-Efficacy: The Excercise of Control. New York: Freeman. 
18 | Chapter 3: Evaluation
	

8 Robinson, T. N., Patrick, K., Eng, T. R., & Gustafson, D., for the Science Panel on Interactive 

Communication and Health. (1998). An evidence-based approach to interactive health 

communication: A challenge to medicine in the information age. JAMA, 280, 1264-1269. 

9 Buchanan, D. R. & Wallack, L. (1998). This is the partnership for a drug-free America: Any 

questions? Journal of Drug Issues, 28(2), 329-356. 

10 Chen, H. (2005). Practical Program Evaluation, Thousand Oaks, CA: Sage. 

11 Bargh, J. A. (Ed.) (2006). Social Psychology and the Unconscious: The Automaticity of Higher 

Mental Processes. Philadelphia: Psychology Press. 

12 Fern, E. F. Advanced Focus Group Research. Thousand Oaks, CA: Sage. 

13 Duggleby, W. (2005). What about focus group interaction data? Qualitative Health Research, 

15(6), 832-840. 

14 Tremblay, M. C., Hevner, A. R., & Berndt, D. J. (2010). The use of focus groups in design science 

research. Design Research in Information Systems, 22, 121-143. 

15 Huntley-Fenner, G. Human factors. This volume. 

16 Nielsen, J. (1993). Usability Engineering. San Francisco, CA: Morgan Kaufman. 

17 Gilchrist, V. J. (1992). Key informant interviews. In: Crabtree, B. F.& Miller, W. L. (Eds). Doing 

Qualitative Research. London: Sage. 

18 Downs, J.S., & Fischhoff, B. Qualitative information. This volume. 

19 Oakley, A., Strange, V., Bonell, C., Allen, E., Stephenson, J., & RIPPLE Study Team (2006). Process 

evaluation in randomized controlled trials of complex interventions. British Medical Journal, 332, 

413-416. 

20 Scarpitti, F. R., Inciardi, J. A. & Pottieger, A. E. (1993). Process evaluation techniques for 

corrections-based drug treatment programs. Journal of Offender Rehabilitation, 19(3), 71-79. 

21 Davidson, J. E. (2005). Evaluation Methodology Basics: The Nuts and Bolts of Sound Evaluation, 

Thousand Oaks, CA: Sage. 

22 Sheeran, P. (2002). Intention–behavior relations: A conceptual and empirical review. European 

Review of Social Psychology, 12, 1–36. 

23 Bassett, M.T., Dumanovsky, T., Huang, C., Silver, L.D., Young, C., Nonas, C., et al. (2008). 

Purchasing behavior and calorie information at fast-food chains in New York City, 2007. American 

Journal of Public Health, 98(8), 1457-1459. 

24 Rosen L, Manor O, Engelhard D, Zucker D. (2006). In defense of the randomized controlled trial 

for health promotion research. American Journal of Public Health. 96, 1181–1186. 

25 Aiken, L. S., West, S. G., Woodward, C. K., Reno, R. R., & Reynolds, K. D. (1994). Increasing 

screening mammography in asymptomatic women: Evaluation of a second-generation, theorybased program. Health Psychology, 13(6), 526-538 

26 Glik, D. C. (2007). Risk communication for public health emergencies, Annual Review of Public 

Health, 28, 33-54. 

27 Kadushin, C., Hecht, S., Sasson, T., & Saxe, L. (2008). Triangulation and mixed methods designs: 

practicing what we preach in the evaluation of an Israel experience educational program, Field 

Methods, 20, 46-65. 

28 Fischhoff, B., Brewer, N.T., & Downs, J.S. Strategic planning. This volume. 

29 Andrews, J.C. Warnings and disclosures. This volume. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 19
	

Chapter 4: Duty to Inform

Baruch Fischhoff, PhD - Carnegie Mellon University 

Summary

After using the best available science and their limited resources to design 

and evaluate communications, agencies must decide whether the result is 

adequate to demonstrate fulfilling their duty to inform and use their resources 

efficiently. To be considered adequate, communications must pass three tests: 

Contain the information that users need, connect users with that information, 

and be understood by users. 

Introduction

A Definition of Adequacy. The ultimate test of any communication is 

enabling effective action. To that end, users must receive the communication 

and extract the information they need. 

A communication is adequate if

• it contains the information needed for effective decision making, 

• users can access that information, and 

• users can comprehend what they access. 

This chapter elaborates on these three tests and the choices they pose for 

policy makers in deciding whether inevitably imperfect communications are, 

nonetheless, good enough. 

Evaluating whether a communication contains the information needed 

for effective decision making. One way to capture this aspect of adequacy 

is found in the legal doctrine of informed consent. About half of U.S states 

require physicians to provide the information that is material to their patients’ 

decisions — the other states have a professional standard and require 

physicians to provide the information that is the customary practice in their 

specialty.1

 Applied to communications, this test leads to a materiality standard 

for communication content. 

A materiality standard for communication content: A communication 

is adequate if it contains any information that might affect a significant 

fraction of users’ choices. 
20 | Chapter 4: Duty to Inform
	

This standard could apply to both persuasive communications, designed to 

encourage desired behaviors (e.g., not smoking, evacuating dangerous places), 

and to non-persuasive communications, designed to facilitate independent 

choices, when those could legitimately vary across individuals (e.g., whether to 

undergo a medical procedure with both risks and benefits). In either case, the 

test takes users’ perspective, asking what they need to know to make decisions 

that provide giving them the best chance of realizing their goals. 

One way to formalize this test is with value-of-information analysis, a 

standard decision theory method.2-4 It asks how much knowing each possible 

item of information would affect users’ ability to choose the best option. In a 

communication context, value-of-information analysis sets priorities, showing 

which facts are most worth knowing and which would affect few, if any, 

decisions. The analysis might find that one item (e.g., a dreaded side effect, 

a highly valued benefit) is so decisive that a communication is adequate if it 

includes just that fact. Or, it might identify several potentially relevant facts, 

which the analysis ranks by decreasing marginal utility. Without setting such 

priorities, meeting this test could mean failing the other two tests — there is 

too much information to access and comprehend the facts that really matter. 

When users’ information priorities vary, applying this test also requires 

setting priorities among those users. One possible policy is to treat all users 

equally, so that communications focus on the facts most needed by the most 

users. Table 1 shows such an application, analyzing the information most 

material to patients deciding about carotid endarterechtomy. This common 

surgery reduces stroke risk for qualified patients. However, it also poses 

its own risks, some unique to the procedure, others associated with major 

surgery per se. The table shows some of these risks, along with the estimated 

percentage of patients who should decline the surgery, if told about each risk. 

For example, learning about the risk of death should dissuade 15%, whereas 

learning about the risk of broken teeth should dissuade only a very few patients 

(for whom the surgery has only marginal benefit). Based on this analysis, 

including the top three risks (death, stroke, facial paralysis) would satisfy the 

materiality standard for most users. Not hiding the other, less material, risks is 

important for other reasons (e.g., transparency). 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 21 

Table 1. Value of information for carotid endarterechtomy decisions

(percent of patients who would decline surgery, if they knew of each risk) 

death 15.0% 

stroke 5.0 

facial pparalysis 3.0 

myocardial infarction 1.1 

lung damage 0.9 

headache 0.8 

resurgery 0.4 

tracheostomy 0.2 

gastrointestinal upset 0.09 

broken teeth 0.01 

Source: Merz et al. (1993)27 

These information priorities might be different, however, if some users 

were particularly important to policy makers. For example, a communication 

with just the top three risks in Table 1 would be less adequate if myocardial 

infarction (#4) were material to the decisions of some especially important 

users (e.g., those with special needs or without other access to information). 

When needs vary, any definition of adequacy makes a policy statement about 

how important users are, if only to say that that they are all treated equally. 

Feldman-Stewart and her colleagues analyze the adequacy of communications 

for men with different information needs regarding early stage prostate 

cancer.5,6 

Figure 1 shows a less formal materiality analysis, looking at the facts that 

might be conveyed to parents deciding about immunizing their children against 

measles-mumps-rubella (MMR). The full analysis (partially grayed in the figure) 

is an expert model of the factors affecting the risks and benefits of vaccination, 

patterned after the influence diagrams used in risk and decision analysis.2, 7 

The nodes represent variables; the arrows indicate dependencies (such that 

knowing the value of a tail variable should influence predictions of the head 

variable). 
22 | Chapter 4: Duty to Inform
	

Figure 1. Expert model of factors relevant to vaccination decisions 

vaccine 

program vaccinate child 

screening 

supply

chain 

vaccine 

availability 

public health

strategy 

multiple

vaccines 

risk of 

vaccinating 

personal

values 

identify

reactions 

herd 

immunity 

immunity 

treat 

reactions 

public health

credibility 

benefit of 

vaccinating 

healthcare 

providers 

health 

information 

preventable

disease reporting and

tracking 

vaccine safety

research total 

dose 

quality of

vaccine 

vaccine 

effectiveness 

disease 

surveillance 

Each node represents a factor predicting the personal or public health outcomes of vaccination 

decisions through the pathways described by the arrows. The darkness of the nodes and the 

arrows indicate how frequently they were mentioned by first-time mothers participating in 

in-depth (mental models) interviews. 

Source: Downs et al. (2008)8 

The dark nodes and links are the ones mentioned most frequently by a 

sample of first-time mothers as being material to their decisions. Thus, for 

example, all mentioned the connection between vaccination and disease 

prevention for their child. None, however, spontaneously mentioned the role of 

herd immunity, a concern that would be material to decisions that considered 

public health benefits, such as reducing disease prevalence so as to protect 

people whose health precludes being vaccinated. Some were concerned about 

adverse reactions; none, however, mentioned research designed to improve 

vaccine safety (e.g., post-licensing surveillance). A communication audit was 

used to map publicly available messages into the expert model, as indicators 

of the topics that their authors considered material. It found that, compared to 

public health officials, vaccine skeptics did a better job of addressing the issues 

that the interviewees considered material.8

 For example, the officials’ messages 

did not to present their view of vaccine safety. 

Applying a materiality standard requires knowing what people know already, 

so as to focus on the facts that they still need to be told. Repeating known 

facts not only wastes a limited communication opportunity, but can shrink it, 

by showing insensitivity to users’ information needs. As stressed throughout 

this volume, even modest studies of users’ current beliefs can reduce this risk. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 23 

Evaluating whether users can access that information. People face two 

potential barriers to accessing the information that they need (assuming that it 

has been included in a communication). One barrier is not connecting with the 

communication. The second is not finding the information in it. In that light, 

adequate communications must meet a proximity standard for Information 

accessibility. 

A proximity standard for information accessibility: A communication 

is adequate if it puts most users within X degrees of separation from the 

needed information, given their normal search patterns. 

Access to Information Sources. Adequate communications require 

distribution systems that reach their audiences. Those systems could include 

direct links, such as informed consent briefings (e.g., with surgery or human 

subjects research), standard warnings (e.g., vaccine information sheets, 

consumer medication pages, home delivered boil-water notices), and computer 

alerts (e.g., product recalls, airline fare changes). These systems could also 

include indirect links, such as physicians who relay information that they 

receive directly (e.g., from the pitches of pharmaceutical detailers, Dear Doctor 

letters, or continuing medical information), friends who follow an issue, or 

media reports. 

If natural distribution channels are inadequate, then communicators 

must create additional ones. For example, pharmaceutical communications 

rely on the natural, indirect channel of having health care professionals 

convey information that they receive directly, but then supplement it by 

delivering information directly at the point of purchase. The success of the 

former channel is partially revealed by studies of how often various kinds of 

information are conveyed in physician–patient interactions.9,10 The success 

of the latter channel is partially seen in the finding that most U.S. consumers 

receive mandated consumer medication information along with their 

prescriptions.11 In the United States, federally mandated vaccine information 

sheets may have even higher coverage rates. On the other hand, Downs et al. 

found that the search terms used by the first-time mothers were more likely 

to take them to web sites of vaccine skeptics, compared to those of vaccine 

proponents (meaning that the latter are less accessible).8 

Heterogeneous target populations may require heterogeneous channels. For 

example, some people are reached most easily by mail, product labels, radio, 

television, landline, mobile phone, or various social networks. Some people rely 

on channels within their ethnic, language, faith, or ideological communities. 

Some need help with seeing, hearing, reading, or concentrating. Some need 

handholding with technical or threatening information. 
Contamination of 

Drinking Water 

Utility 

Treatment 

Options 

Routine 

Testing 

Results 

Trigger 

Events 

Utility 

Awareness 

Utility 

Communique 

Joint Task 

Force 

Special 

Studies 

Medical 

Awareness 

Consumption of 

Treated Water 

Consumption of 

Well Water 

Averting 

Behavior for 

Public 

Systems 

Averting 

Behavior for 

Private Wells 

Consumer 

Awareness for 

Private Wells 

Miscellaneous 

Announcement 

Tap Test Info Sources Well Test 

Media 

Coverage 

Consumer 

Awareness for 

Public Systems 

Health 

Department 

Awareness 

Health Effects 

24 | Chapter 4: Duty to Inform
	

Social network analysis provides methods for assessing the flow of 

information through various channels and to various people, depending on 

how they are connected.12,13 One general lesson from the research is that 

these flows can be unintuitive, in terms of how quickly word gets around and 

who gets left out. Christakis and Fowler summarize many network effects, 

such as the seeming “contagion” of obesity and divorce.14 Flawed intuitions 

about networks can lead communicators to overestimate the accessibility of 

their messages, as when organizations rely too heavily on their partners to 

contact constituents, or to underestimate it, as when people expect their email 

communications to remain private forever.15 

The science of networks and the practice of partnering16,17 offer guidance on 

how to design effective channels. Their success is always an empirical question. 

It can be answered either by assessing which users receive messages or by 

modeling distribution channels. In an example of the latter approach, Casman 

et al., created the model in Figure 2 to predict the efficacy of different ways 

to reduce the health effects of contaminants in domestic water supplies.18 In 

an application to cryptosporidium intrusions, for which detection is slow, they 

found that boil water notices would reach vulnerable (immuno-compromised) 

individuals too late to be of any value. Thus, for those users, access to the 

communication would be wholly inadequate. For water contaminants that 

can be detected more rapidly, the same distribution system might allow timely 

access. 

Figure 2. Model predicting the effects of measures to reduce health effects

of contaminants in domestic water supplies

Source: Casman et al. (2000)18 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 25
	

Access to Message Content. Once users have connected with a 

communication, they must find the information that they need in it. That 

process requires effective document design. The principles of such design are 

well understood.19-23 They involve addressing both technical issues, such as 

legibility and clutter, and cognitive ones, such as how attention is directed, how 

urgency is evoked, and how authority is established. Design guidelines typically 

provide best guesses for how to meet the needs of modal users, meaning 

that they cannot guarantee success with any individual, much less a diverse 

audience.24 

As a result, users’ access to information within messages is also an empirical 

question, which also can be answered by direct observation or with models 

using empirically based assumptions. As an example of the former kind of 

evidence, Winterstein and Kimberlin found that, although most users receive 

consumer medication information sheets, few can access needed information 

within them — or even try.11 Online information about protecting personal 

privacy or computer security is similarly inaccessible to many users, even when 

system operators are eager to enlist their support.25 Electric utility bills often 

have information about rates, taxes, conservation, ancillary services, and other 

things. However, most of that information just gets in the way of users looking 

for the box that says, “Pay this amount.” 

Figure 3 shows results from an assessment of information accessibility, 

focused on the risks of methylene chloride-based paint stripper, a probable 

carcinogen. A quantitative risk analysis determined the materiality of 

information about possible protective measures (e.g., move across the room 

while the solvent is curing, open windows with a fan blowing inward — or 

outward), by estimating inhalation doses for users who follow them. The 

analysis then assumes that users adopt each measure that they access on the 

product label. It determines access based on how they search the label and 

whether that natural search pattern takes them to where the information is 

located on it. The figure shows doses for users who naturally read the first 

five items that they encounter. With Product B, such users would access much 

more useful information than with the other labels. Users with other search 

patterns (e.g., read everything on the front, read only warnings, read only 

use instructions) would access different information and experience different 

exposures. Information has little value, if users cannot find it with a reasonable 

effort. 
26 | Chapter 4: Duty to Inform
	

Figure 3. Predicted effects of using methylene chloride-based paint stripper

3.0

2.5

2.0

1.5

1.0

0.5

0.0

0 20 40 60 80 100 120

Time (min) 

A, C, E 

D, F 

B

Potential Inhalation Dose (g) 

Each curve shows the inhalation exposure expected for individuals who read the first five items on the labels 

of six products and follow those instructions. 

Source: Riley et al. (2000)28 

Evaluating whether users can understand that information. Accessing 

material content is necessary but not sufficient for users to learn what they 

need. They must also comprehend the content well enough to incorporate it 

in their decision making. How well communicators succeed is expressed in a 

comprehensibility standard for user understanding. 

A comprehensibility standard for user understanding: A communication is 

adequate if most users can extract enough information to make sound choices. 

Applying this standard means comparing the decisions made by users with 

access to the communication to the decisions that fully informed decision 

makers would make. A poor communication can pass this test if users happen 

to know enough without it. For example, Eggers and Fischhoff examined how 

a court-mandated disclaimer for dietary supplements affected user decisions.26 

They found that the disclaimer, which said that FDA had not approved the 

product, confused many users. Some mistakenly thought that the disclaimer 

reflected antipathy to alternative medicine (meaning that FDA would never 

approve any dietary supplement); some mistakenly thought that it meant that 

the product was so effective that FDA allowed its side effects. However, in a 

case study of effects on men’s decisions regarding saw palmetto (an herb that 

may provide symptomatic relief for benign prostatic hyperplasia), the poor 

disclaimer appeared to do no harm. The only way that this specific decision 

can go badly wrong is if users self-medicate with the supplement, while leaving 
 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 27
	

serious problems untreated. However, none of the men in this study had 

enough faith in saw palmetto to self-medicate for long. In decisions involving 

other products and other users, the disclaimer might fail the comprehensibility 

standard. That is an empirical and analytical question. 

Thus, each decision requires its own evaluation. For example, based on the 

analysis in Table 1, a communication about carotid endarterechomy would 

pass the comprehensibility test if its users understood the three top risks well 

enough to apply that knowledge to their surgery decisions. Based on the study 

in Figure 1, a vaccine communication would pass if it left most users sufficiently 

informed about the safety assurances to incorporate that information in their 

decisions. Based on the study in Figure 3, a paint stripper label should lead 

users to have fans blow outward from their workspaces (the most effective 

safety measure) or to knowingly accept the risks of other work practices. 

(There is no comprehensibility test for communications about cryptosporidium 

intrusions (Figure 2), as they can say nothing that will enable users to protect 

themselves.) 

Thus, the materiality standard asks whether communications have the 

information that users must master, the accessibility standard assesses 

whether that information has reached users, and the comprehensibility 

standard considers whether users have integrated it well enough with their 

existing knowledge to apply it when making decisions (Table 2). Other chapters 

in this volume summarize the science relevant to meeting these tests, when 

conveying information that is quantitative (Chapters 7, 15), qualitative 

(Chapter 8), emotion laden (Chapters 5, 10), unfamiliar (Chapters 8, 12, 14), 

technical (Chapters 7, 9, 12, 16), or persuasive (Chapter 11). 

Table 2. Adequacy tests in communication design

A communication is adequate if

• It contains the information needed for effective decision making, 

• users can access that information, and 

• users can comprehend what they access. 

A Materiality Standard for Communication Content

A communication is adequate if it contains any information that 

might affect a significant fraction of users’ choices. 

A Proximity Standard for Information Accessibility

A communication is adequate if it puts most users within X degrees 

of separation of the needed information, given their normal search 

patterns. 

A Comprehensibility Standard User Understanding

A communication is adequate if most users can extract enough 

information to make sound choices. 
 

28 | Chapter 4: Duty to Inform
	

Policy judgments in adequacy decisions. Each of these standards includes 

verbal quantifiers that must be resolved for it to be applied. For example, 

the materiality standard recognizes that users’ information needs might be 

so varied that no single communication could serve more than a significant 

fraction of users, without becoming hopelessly cluttered (and then fail the 

accessibility standard). Scientists can try to create designs reducing that 

fraction, then run studies estimating its size. However, policy makers must 

decide whether the remaining fraction achieved is acceptable (and the 

communication adequate). 

Similarly, the accessibility standard recognizes that reaching all users directly 

may be infeasible. Hence, it allows putting most users within X degrees of 

separation from the communication. Here, too, scientists can create better 

designs and evaluate their success (e.g., how well partner organizations 

relay communications to their constituents). However, policy makers must 

decide whether too many users are still too far away from the information, 

however material and comprehensible it might be. Their deliberations 

might consider such issues as when people are best served by relying on 

trusted intermediaries, rather than receiving messages directly, so that more 

separation is better. 

Similar questions arise with the other standards. In resolving each, policy 

makers must decide whether to treat all users equally — and when, for 

example, communicating well with a few very vulnerable users justifies serving 

less vulnerable users less well. For example, if forced to choose, policy makers 

with limited resources might favor hand-delivering boil water notices to 

immune-compromised individuals over mailing the notices to everyone else. 

They might also decide that any communication is inadequate and invest those 

resources in providing vulnerable users with bottled water. 

Conclusions

Communications are adequate if they reach people with the information that 

they need in a form they can use. The adequacy tests presented here specify 

those requirements in terms that allow assessing compliance, using methods 

drawn from social and decision science. The results of these assessments 

characterize the decisions facing policy makers in determining whether a 

communication is adequate. If it passes the tests, then policy makers may be 

able to reduce the resources invested in communication. If it fails, then the 

tests show where the problems lie and how resources might be redeployed 

(e.g., “People read our messages and understand what we’re saying. However, 

we aren’t telling them what they need to know. We should invest more in 

figuring out what the content of our messages should be.”). Having these 

test results might even help to secure the resources needed for better 

communications, by demonstrating unacceptable risks created by inadequate ones. 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 29
	

Endnotes

1 Merz, J. (1991). An empirical analysis of the medical informed consent doctrine. Risk, 2, 27-76. 

2 Clemen, R.T., & Reilly, T. (2003). Making Hard Decisions. Boston: Duxbury. 

3 Raiffa, H. (1968). Decision analysis. Belmont, MA: Addison-Wesley. 

4 vonWinterfeldt, D., & Edwards, W. (1986). Decision Analysis and Behavioral Research. New York: 

Cambridge University Press. 

5 Feldman-Stewart, D., Brundage, M.D., Hayter, C. et al. (2000). What questions do patients with

curable prostate cancer want answered? Medical Decision Making, 20, 7-19. 

6 Feldman-Stewart, D., Brennenstuhl, S., Austoker, J., et al. (2006). A systematic review of

information in decision aids. Health Expectations, 10, 46-61. 

7 Fischhoff, B., Bruine de Bruin, W., Guvenc, U., Caruso, D., & Brilliant, L. (2006). Analyzing disaster

risks and plans: An avian flu example. Journal of Risk and Uncertainty. 33, 133-151. 

8 Downs, J. S., Bruine de Bruin, W., & Fischhoff, B. (2008). Patients’ vaccination comprehension 

and decisions, Vaccine, 26, 1595-1607. (http://www.sciencedirect.com/science/journal/026446. 

9 Col, N. Shared decision making. This volume. 

10 Sleath, B., & Goldstein, M. Health care professionals. This volume. 

11 Winterstein, A.G., & Kimberlin, C.L. (2010). Usefulness of consumer medication information 

dispensed in retail pharmacies. Archives of Internal Medicine, 170, 1314-1324. 

12 Scott, J.P. (2000). Social Network Analysis. Thousand Oaks, CA: Sage. 

13 Wasserman, S., & Faust, K. (1994). Social Network Analysis. New York: Cambridge University Press. 

14 Christakis, N.A., & Fowler, J.H. (2009). Connected. New York: Little, Brown. 

15 Weisband, S.P., & Reinig, B.A. (1995). Managing user perceptions of email privacy. Proceedings 

of the ACM, 38(12), 40-47. 

16 Schwitzer, G. News coverage. This volume. 

17 Chess, C. Inside the organization. This volume. 

18 Casman, E., Fischhoff, B., Palmgren, C., Small, M., & Wu, F. (2000). Integrated risk model of a 

drinking waterborne Cryptosporidiosis outbreak. Risk Analysis, 20, 493-509. 

19 Ishizaki, S. (2003). Improvisational Design. Cambridge, MA: MIT Press. 

20 Wogalter, M. (Ed). (2006). The Handbook of Warnings. Hillsdale, NJ: Lawrence Erlbaum 

Associates. 

21 Neuhauser, L., & Paul, K. Readability, comprehension, and usability. This volume. 

22 Andrews, J.C. Warnings and disclosures. This volume. 

23 Huntley-Fenner, G. Human factors. This volume. 

24 Reyna, V. Across the lifespan. This volume. 

25 Cranor, L.F., & Garfinkel, S. (Eds.). (2005). Security and Usability: Designing Secure Systems that 

People Can Use. Sebastopol, CA: O’Reilly & Associates, Inc. 

26 Eggers, S.L. and Fischhoff, B. (2004). Setting policies for consumer communications: A behavioral 

decision research approach. Journal of Public Policy and Marketing, 23(1): 14-27. 

27 Merz, J., Fischhoff, B., Mazur, D.J., & Fischbeck, P.S. (1993). Decision-analytic approach to 

developing standards of disclosure for medical informed consent. Journal of Toxics and Liability, 

15, 191-215. 

28 Riley, D.M., Small, M.J., & Fischhoff, B. (2000). Modeling methylene chloride exposurereduction options for home paint-stripper users. Journal of Exposure Analysis and Environmental

Epidemiology, 10(3), 240-250. 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 31
	

Chapter 5: Language

Musa Mayer - Patient Advocate 

It has been well over two decades since I learned I had breast cancer, but 

every moment of the day of my diagnosis is still etched permanently in my 

brain: the look on my husband’s face when we were told, the steadying hand 

of the surgeon and his reassurance that released a flood of tears — and then, 

later, a sharp stab of anger: how did he know I’d be okay? The throb of the 

biopsy incision as the local anesthetic wore off. The intolerable brightness and 

noise of the traffic on First Avenue on the ride home. I also felt betrayal, and 

a sense of shame. My diagnosis had been delayed for well over a year as this 

tumor grew. How could I have been so gullible, to have blindly accepted my 

gynecologist’s false reassurance that because the palpable lump in my breast 

wasn’t visible on the mammogram, it was nothing to be concerned about? How 

could he have failed to send me to a surgeon sooner? 

Although that afternoon was clouded with emotion, the strongest imperative 

I felt was to understand, to learn. What, exactly, was I dealing with? I had to 

know. The biopsy had taken place that same morning, followed within hours 

by the diagnosis, so my husband and I had been too stunned to think straight 

when we’d spoken to the surgeon that afternoon. We didn’t know what 

questions to ask. That day, all I knew was that I had choices to make and that 

they were choices that would change my life. 

Within the next few days I would somehow need to absorb a flood of 

terrifying information about surgery, radiation, and chemotherapy; about 

whether or not my large tumor had already spread to the lymph nodes under 

my arm. I was only 46 and had yet to directly confront my mortality. Suddenly, 

here we were talking about Stage II and optimizing my chances for survival. 

There was so much to learn, and so little time to learn it. I was clearly in strange 

territory, with no medical or scientific background and only a slim patient 

brochure that spoke in useless generalities. This was 1989, before the Internet, 

before the many patient guides that have since been published. Before we left, 

we made an appointment to talk with the surgeon again, after the weekend. 

But how would I manage until then? Where to turn? Who to talk to? 

That evening after work, my brother-in-law, a surgeon, dropped off the 

medical text I’d asked him to buy for me, entitled Cancer of the Breast. Unable 
32 | Chapter 5: Language
	

to sleep, I sat up all that night and the next day and night, devouring its 800 

pages, a medical dictionary at my side, trying to avoid the disturbing pictures of 

tumors that had broken through the skin and escaped the breast. 

Over the next week my crash course expanded as I consulted not only 

radiation and medical oncologists and a plastic surgeon, but friends of friends, 

and some of my doctors’ other patients who were willing to share their own 

experiences. These generous women helped most of all—offering warmth, 

perspective, and the simple but profound observation that I could get through 

this, as they had, and that life would go on, as it had for them. Quite literally, 

they bared their breasts to me. 

It’s worth noting that when weighing the risks and benefits of my treatment 

decisions, I was as much guided by these women’s experiences as I was by my 

research, or the advice of my doctors. Had I met a woman whose immediate 

breast reconstruction had failed or been complicated by infection, I might 

have made a different choice. Later, much later, I met a few women with side 

effects so severe that they were unable to complete their chemotherapy, but 

at the time, my point of reference became the cheerful woman my oncologist 

introduced me to, who appeared to be sailing easily through her treatments. 

In the mind of a woman in crisis, a fellow patient you can actually talk to may 

influence you more than any data. A vivid anecdote can easily trump evidence. 

By the night before my mastectomy, I felt I understood, at least on a basic 

level, what I was confronting. I’d cobbled together a small shelter of facts, 

studies, and first-hand experiences, and that would have to be enough, 

whatever unknowns inhabited the shadows. As I lay in my hospital bed that 

night, looking out at the lights of the city, that first desperate turbulence of 

feelings and dilemmas subsided into a kind of resignation as the scenario I’d 

chosen began to play itself out. Intense as it was, my crash course had worked, 

for me. I felt at peace with the choices I’d made. I feel that way now, although 

in retrospect there was plenty I didn’t understand that might have factored into 

those choices. However limited in its scope, my decision was informed. 

Over the years, in my role as patient advocate, I’ve accompanied many 

women along the precarious path of treatment decision-making. Some are 

newly diagnosed; others, having far outlived expectations, bargain for more 

time. Some have rosy prognoses; others linger at the threshold of hospice care. 

All struggle with the choices before them. 

There is the evidence to draw on, clinical trials of greater or lesser size, merit, 

and relevance. When talking with these women, I always stress the evidence — 

when there is evidence. Once you move past initial diagnosis and treatment, 

however, good evidence from randomized trials is often slim or absent. The 

term “evidence-based medicine” may be viewed with suspicion. Quoting 

David Sackett’s corrective definition doesn’t help much: “The integration 

of best research evidence with clinical expertise and patient values.”1

 The 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 33
	

term has become politicized, tainted by labels like “rationing,” or “socialized 

medicine.” Besides, can numbers based on groups of patients be relied on to 

describe an individual? “I am not a statistic!” women protest, claiming that 

their circumstances do not fit the cookie cutter formulas they associate with 

treatment guidelines based on the results of clinical trials. 

Personalized medicine is the new buzzword. The emerging genomic reality 

that breast cancer is not a single disease, but at least five distinct entities, 

each having its own prognosis and requiring its own set of treatments, only 

adds further confusion. As molecular markers join staging as a determinant of 

treatment recommendations, the firm foundation of the large adjuvant trials 

in early breast cancer begins to erode. Yet, the tools to individualize care are 

still buried somewhere in a mountain of data and unvalidated biomarkers. 

Straightforward answers remain few. Discoveries exciting to clinicians and 

researchers prove unnerving for patients. No one can reliably predict which 

treatment will work. Complexity reigns. No wonder women feel confused. 

Because breast cancer is so common, most people know someone with the 

disease. We are strongly influenced by the personal experiences of people 

we know — or even learn about indirectly. Stories of outrage and inspiration, 

stories of real people trying to cope, are everywhere online, in blogs and on 

bulletin boards. Understandably anxious about what is to come, the newly 

diagnosed are often hungry, as I was, for stories that offer a glimpse of what 

to expect. And as every journalist knows, personal stories can be far more 

compelling than scientific studies. 

One sobering example of this has stayed with me over the years. During 

the 1990s, repeated media accounts told of young mothers with advanced 

breast cancer fighting for insurance coverage of an unproven treatment 

known as bone-marrow or stem-cell transplant. Women were give doses of 

chemotherapy high enough to kill them (and hopefully eradicate the cancer), 

then rescued by their own previously donated bone marrow or stem cells. 

These dramatic stories of a drastic treatment for dire circumstances cast the 

patient warriors and their heroes, the savior transplanters, against the evil 

insurers. 

In one such case, an HMO called HealthNet refused to pay for a transplant 

for Nelene Fox, a 40-year-old California woman with advanced breast cancer, 

on the grounds that the treatment was unproven, and therefore experimental 

— which was true. But emotion trumped data. She received her transplant 

anyway, having raised $212,000 privately, but died eight months later in 1993. 

The family sued HealthNet, and the jury awarded them $89 million in punitive 

damages and for reckless infliction of emotional distress. Though later reduced, 

this huge award set a precedent for across-the-board insurance coverage for 

bone marrow transplants and further legitimized and enabled the widespread 

delivery of what was an unproven and highly toxic treatment, undergone by an 

estimated 40,000 American women by the end of the decade.2 
 

34 | Chapter 5: Language
	

Oncologists had been persuaded by early-phase studies that showed a 

greater tumor response, confirming the prevailing dose-response theory that 

more chemotherapy must be better and by the technology that permitted 

the stem-cell harvesting and reinfusion that could pull the patient back from 

the brink of death. Never mind the lack of randomized trials — these doctors 

were certain it would work, citing patients they knew who had benefitted and 

recovered fully. 

When the randomized trials were finally completed at the end of the 

decade — the definitive studies that had languished for years, accruing at a 

snail’s pace because of the prevailing belief that the transplants worked — no 

benefit over standard chemotherapy could be found. By then, the treatment 

itself had killed thousands of women, many more than it helped. 

Although many breast cancer advocates were still helping women with 

locally advanced and metastatic breast cancer gain access to this treatment, 

cruel circumstance had mobilized me in the opposite direction. I’d already had 

two close friends die horrible deaths from this treatment, a loss made doubly 

horrible when I learned — too late! — how scanty the evidence was. What 

happened to Pat and Mary, the way that they died, will probably always haunt me. 

This was a treatment that made people desperately ill, that required 

hospitalization and isolation, that was hugely expensive. What made it so 

compelling? Certainly the heart wrenching stories in the media played a role. 

Another part of the answer may lie in language, in the warlike metaphors 

so common to the public discourse on cancer that we barely notice them 

anymore: Clearly, this treatment was “the big guns,” engaging patients in 

a heroic, last-ditch fight that brought them to the brink, then pulled them 

back. Cancer, the devious invader, is fought with the strongest weapon. 

Often described as “brave warriors,” those with the disease either “emerge 

victorious,” or they die, having “lost their battles,” to quote the typical 

obituary. Those who survive being “slashed, burned, and poisoned,” as surgery, 

radiation, and chemo have been characterized, are celebrated as courageous 

survivors. 

Cancer patients certainly deserve our respect for enduring the rigors of 

treatment, but my point is that when it comes to treatment choices, warlike 

habits of language and thought may have unwelcome consequences. They 

encourage overly aggressive treatment and burden end-of-life decisions with 

the shame-inducing freight of “surrender” and “giving up the fight.” 

Entwined with the military metaphors is the entrenched belief that stronger, 

more arduous treatment must be better. Women newly diagnosed with 

metastatic breast cancer have just received the devastating news that their 

disease is no longer curable and will ultimately cost them their lives. Emerging 

from the shock and grief of that prognosis, they prepare to do battle. Yet more 

likely than not, their oncologists prescribe a once-a-day anti-estrogenic pill 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 35
	

that for most has few side effects. This worries them. “Shouldn’t I be getting 

something stronger?” they want to know. Actually, no, I explain: this little pill is 

the most effective targeted treatment for your particular kind of breast cancer, 

more effective than strong chemo would be, more long-lasting and less toxic 

— and you won’t lose your hair! I show them the data, and I can see them 

struggling to reconcile this with their previous beliefs about what constitutes 

effective treatment, that being sick and bald is proof of potency. 

But paradigms are changing in cancer treatment. For some patients different 

metaphors work better. “I really find myself drawn to living with, and finding 

accommodations,” wrote Jenilu Schoolman. At Stage IV, her cancer could 

not be cured, so she chose to see herself cohabiting in relative peace with 

her cancer, in what she called a “multi-cultural housing unit.”3 Many imagine 

a journey to an unfamiliar land, including writer Susan Sontag, who argued 

for a language of illness purged of metaphor. “Illness is the night-side of life, 

a more onerous citizenship,” Sontag wrote. “Everyone who is born holds 

dual citizenship, in the kingdom of the well and in the kingdom of the sick. 

Although we all prefer to use only the good passport, sooner or later each of 

us is obliged, at least for a spell, to identify ourselves as citizens of that other 

place.”4 

We definitely require new metaphors, or perhaps no metaphors beyond 

the science itself. Where military metaphors persist, it’s clearly becoming a 

different kind of war. These days, we’re talking about the new “smart bombs” 

that avoid “collateral damage.” Other misunderstandings can color treatment 

decisions. Hope conspires with lack of evidence to make treatments that are 

new look far more appealing than older, approved approaches whose efficacy 

and safety are well-characterized. But newer may not be better. Because 

they’ve undergone only limited testing in select patient groups, a minimal 

amount is known about cancer drugs when they are first approved by FDA. 

Describing an arc familiar to those who follow cancer drug development, hope 

and excitement flourish for each new agent in its early days. Inevitably this 

honeymoon is followed by disappointment, as evidence for resistance, lessened 

efficacy and side-effects begins to emerge. 

In making treatment decisions, we’re also encumbered by our own history 

and memories. A woman I knew who had witnessed her father suffering 

terribly from chemotherapy when she was a child, was so traumatized by that 

memory that she refused treatment altogether for her Stage II breast cancer. 

Yet, after meeting several women who were tolerating their chemotherapy 

well, she felt able to begin treatment. 

Complicating treatment choices further is the yearning we all feel for some 

kind of certainty. When your life is threatened, you want these choices to 

be simple and obvious. You want the treatment whose benefit is proven. 

You want the answer. But what if the truth is far more complicated? Some 
 

36 | Chapter 5: Language
	

questions — including those most important to us — have no ready answers: 

“Will my cancer come back? Am I cured?” Sometimes, even the most avid 

information-seekers feel very small, overtaken by a childlike longing for 

reassurance and certainty. 

Even when the facts are presented clearly to us, we may not be able to take 

them in. Selective listening and avoidance may be in some ways protective, 

serving to keep hope alive. Yet, informed consent for treatment and clinical 

trials participation depends upon a realistic understanding of the benefits and 

risks of treatment. When they are scared, people will often underestimate risk, 

and overestimate benefits. They may be willing to take very significant risks of 

being harmed by treatment for a very small likelihood of benefit. Where clinical 

trials are concerned, this has been called the “therapeutic misconception.” 

Bioethics expert Paul Applebaum estimates that as many as 70% of patients 

enrolling in research studies believe that the research will offer them a direct 

benefit, despite an informed consent process that clearly states otherwise.5 

One ethical requirement for controlled, randomized trials — the studies that 

offer the highest level of evidence — is “clinical equipoise,” which holds that 

the researchers must not know which of the treatments being compared is 

superior.6 Yet both patients and investigators may share a strong belief in the 

superiority of the experimental treatment long before the outcome of the trial 

is known, sometimes even before the trial begins. This may lead them to see 

such a trial as unethical. 

Misperceptions of benefits and risks are not only the result of human 

foibles. They are purposefully cultivated by forces in society. Media alarmism, 

exaggeration, and oversimplification of health care issues is pervasive. Although 

often justified as educational, marketing and advertizing of drugs and other 

products to physicians and patients is carefully crafted to enhance perception 

of benefits and minimize perception of risk. Marketing works, as our massive 

consumption of these products clearly demonstrates. The lack of comparative, 

quantifiable data in direct-to-consumer drug marketing makes any kind of 

deliberative process almost impossible. All of this is compounded by an almost 

total lack of education in how to be an informed consumer of health care. How 

do we know what we know in medicine? Where does the evidence come from, 

and how believable is it? Most people have no idea. 

Faced with diagnosis, each woman with breast cancer discovers her own 

path. I’ve learned that some do not thirst for all the medical details, nor do 

they want to learn anything specific about the research that supports one 

choice over another. Many just want the bottom line. Their quest is for a 

trusted doctor to tell them what’s best for them. Some find their equilibrium 

much more easily; others are simply overwhelmed. Some make their choices 

quickly, while others agonize for weeks. Some find relief in focusing on the 

cancer, diving as deep as they can into a sea of information, as I did; others 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 37
	

seek distraction and screen out most medical details. Some need to know 

the worst that can happen, but many more do not and turn away from any 

discussion of prognosis. Some only want to be alone, while others find great 

relief in sharing. As I reached out to help others, I learned not to impose my 

way on them and to take their lead. 

Filled with conflicting emotions, desperate to know, yet struggling to absorb 

and understand, and with so much to learn in the way of context — this is what 

it is like to be a patient diagnosed with a life-threatening disease, especially at 

first. We can be rational, brave, even a bit cavalier, at one moment, but give 

us a bit of bad news, or another bitter dose of uncertainty, and we abruptly 

find ourselves weeping and feeling betrayed by our bodies, once again. In the 

beginning, it doesn’t take much. In time, we adapt and stabilize, as the strange 

and once-frightening landscape of cancer becomes familiar ground. 

I’ve tried here to suggest some of the ways in which circumstance, 

personality, expectations, hopes, and fears can complicate a rational weighing 

of risks and benefits for patients. Clearly, we need an anchor in turbulent 

waters, so as not to be swept away. I believe that truth must be that anchor 

— even if we find it upsetting, even if we can’t look at it for long, or absorb 

it easily, even if we need to revisit it repeatedly to grasp what is actually 

being said. We may not seek out the truth ourselves, or be able to pay much 

attention to it in moments of crisis, but we need to know it is there when we 

and our family members are ready to face it. Answers may be what we long for, 

but it is truth, however incomplete, that sustains us in the end. 

We deserve accurate, quantified information about the known benefits 

of treatments we are considering. We need answers to questions like how 

good the treatments are that we’re being asked to consider, and what level of 

evidence we have for their use. How long have they been studied, and in how 

many patients? Are those patients like us, or do they differ in meaningful ways? 

If high-quality research has not yet produced the answers we seek, we need 

to know that too. Although we would love to banish uncertainty, we would far 

rather face the unknown mindfully than blindly. 

We deserve to learn about both short- and long-term risks of treatments, 

in so far as they are known. Many of the drugs cancer patients take are highly 

toxic. Not only do they make us sick and tired and bald while we are taking 

them, but they can damage our hearts and other organs, and cause secondary 

cancers in the years that follow. Although we appreciate the protective 

instincts that lead our health care professionals to simplify and soft-pedal 

toxicities, sparing us these scary possibilities is fundamentally untruthful and 

leads to decisions in which we do not fully participate and may later regret. 

What we really need are the tools that can help us make sense of potential 

benefits and potential harms. 
38 | Chapter 5: Language
	

We deserve accurate, readily available, culturally sensitive, evidence-based 

patient informational materials on diseases and conditions, drugs and other 

forms of treatment, prepared by independent arbiters of information skilled 

in risk communication. Although good examples do exist online, we lack a way 

to reliably guide people to the best sources. Much of what I do as a patient 

advocate is to tailor such information for patient needs, not only to help people 

find the information and research relevant to their particular situation, but also 

to aid them in developing the ability to search on their own. 

We deserve to be taught the fundamentals of how evidence is gathered 

in medicine as a matter of public education and public health and how 

to evaluate its quality. Since we are all lifelong health care consumers, 

understanding research ought to be as fundamental to our education as 

reading and math. Personal health crises are arguably the worst time to 

try to make sense of these complex issues. Yet without some sort of basic 

understanding, we are easily misled and confused. We need to learn, as part of 

the curriculum, about observational studies, clinical trials, levels of evidence, 

and the basics of assessing risk. If we can learn to balance our checkbooks and 

prepare our taxes, surely a simple grounding in statistics is not completely out 

of reach. 

We deserve to know when we are being marketed and who stands to 

profit from the treatments we take. The usual defense of direct-to-consumer 

marketing is that it educates patients about diseases and conditions, who may 

then be helped by the product in question. Although some patient educational 

materials produced by industry are clearly well-intentioned and well-designed, 

how are patients to know where the unbiased information leaves off and the 

flat-out promotion begins? Advertising works for the companies and their 

shareholders, but how much does it really benefit the patient? As a citizen of 

one of the only two countries in the world that permits public advertising of 

prescription drugs, I have a hard time believing that the disproportionately 

larger quantities of drugs and medical procedures we consume in the United 

States have made us healthier—not when World Health Organization statistics 

tell us we lag far behind most other developed countries in measures of public 

health.7 

We deserve research that asks and answers questions that matter, 

especially comparative effectiveness research to resolve important clinical 

uncertainties. In my view, too much current research asks questions that 

really don’t matter to patients. Every year at the San Antonio Breast Cancer 

Symposium I find myself wondering: how many more single–arm, phase II trials 

of chemo combinations do we need? Is anyone helped by these studies? Where 

are the large comparative trials to help us find the best treatment among 

similar drugs? Where are the studies that incorporate non-drug strategies, 

like lifestyle changes? We need large, simple studies and expanded access 

programs of promising agents in late-phase development. The lack of such 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 39
	

studies is surely a contributory factor to low enrollment in cancer clinical 

trials and to the dearth of safety data in real-world populations prior to drug 

approval. 

We deserve time with our health care professionals to help us make 

informed decisions. Most patients count on their doctors as learned 

intermediaries, to help them navigate difficult treatment decisions. Yet too 

often, appointments are brief and rushed. Our doctors and nurses are not 

reimbursed for the time it takes to sit down and talk through a complex issue. 

But there is no substitute for the time a doctor spends with a prepared patient 

and family. By prepared, I mean that patients will have already learned and 

absorbed the bad news, perhaps at an earlier visit, had time to process their 

feelings and be comforted by those who love them, and that they will have 

had access to some basic information about the condition and their treatment 

options. 

I see patient education as the most important part of my work as an 

advocate, helping women with metastatic breast cancer and their families learn 

about the specific form of the disease they have and available treatments. 

How far they take this learning process varies according to their abilities and 

motivation, but all can grasp the fundamentals—or a trusted family member 

can learn and act on their behalf. My goal is to empower women and their 

families with the information they need, to help them enter into a collaborative 

process of informed decision-making with their doctors. 

I will end where I began, with that vulnerable patient having to make tough 

and irrevocable choices based on imperfect knowledge. This is the human 

condition; nothing is more basic or more necessary for us to understand. 

We should never lose sight of how lost that woman is feeling and how much 

she depends on all of us, working together, to offer her the very best we can 

provide. 

Endnotes

1 David L. Sackett, et al. Evidence-based Medicine: How to Practice and Teach EBM (2nd edition). 

Edinburgh; NewYork: Churchill Livingstone, 2000. 

2 Richard A. Rettig, Peter D. Jacobson, Cynthia M. Farquhar and Wade M. Aubry, False Hope: Bone 

Marrow Transplantation for Breast Cancer, Oxford University Press, 2007. 

3 Jenilu Schoolman, personal correspondence, 1996. 

4 Susan Sontag, Illness as Metaphor, and AIDS and Its Metaphors, Picador Press, 2001. 

5 Paul S. Appelbaum, Clarifying the Ethics of Clinical Research: A Path toward avoiding the 

therapeutic misconception. The American Journal of Bioethics, Volume 2, Number 2, Spring 2002, 

pp. 22-23. 

6 See this term in Wikipedia, http://en.wikipedia.org/wiki/Clinical_equipoise Accessed October 19, 2010. 

7 Christopher J.L. Murray and Julio Frenk, Ranking 37th — Measuring the Performance of the U.S. 

Health Care System, New England Journal of Medicine, January 6, 2010. 

http://healthpolicyandreform.nejm.org/?p=2610 Accessed October 19, 2010 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 41
	

Chapter 6: Definitions 

Baruch Fischhoff, PhD - Carnegie Mellon University 

Summary

Useful communications must address the outcomes that interest users. 

Meeting that challenge means appropriately defining the risks, other costs, and 

benefits of the choices facing users. Social and decision science research offers 

ways to avoid missing the target, when choosing the topics of communications. 

Introduction

Successful communications tell people what they need to know about the 

risks, other costs, and benefits of the decisions they face. Non-persuasive 

communications, which make no recommendations, succeed if recipients know 

enough to choose the option most likely to achieve their goals. Persuasive 

communications succeed if recipients feel that they are being told to do the 

things that they would choose, were they fully informed. 

Both kinds of communication require knowing which outcomes matter to 

people. Those may include uncertain negative outcomes, or risks (e.g., possible 

drug side effects); certain negative outcomes, or costs (e.g., the price of a drug); 

certain positive outcomes, or benefits (e.g., social approval), and uncertain 

positive outcomes (e.g., better health). For example, open-heart surgery has a 

risk of dying, certain costs of pain and expense, and uncertain benefits of better 

health and longer life. 

Without knowing which outcomes their audience values, communicators 

cannot know which facts to gather and convey. Research has identified 

several barriers to getting the outcomes right. Some reflect communicators 

not understanding their audiences’ circumstances (e.g., talking about the 

importance of regular medical checkups to people who lack the health 

insurance needed to pay for it; talking about safety to teens who also want 

to have fun). Some reflect their audiences not understanding their own 

circumstances (e.g., what does palliative care entail? What else do I need to 

know about it? How can I compare it to intensive care?). 

Theoretical background: what does the science say?

The design of any communication should begin by asking which options 

its recipients might choose and how that choice might affect outcomes that 
 

42 | Chapter 6: Definitions
	

matter to them. Technical specialists are an obvious source of knowledge 

about what those outcomes might be (e.g., the scientists who manage a 

medical clinical trial, the engineers who analyze system failures, or the 

designers who create new products). However, the research finds that people 

cannot reliably predict which outcomes matter to other people; indeed, they 

sometimes cannot even predict what they themselves value. As a result, 

determining the content of communications requires consulting with both 

experts and decision makers, along with research that reveals perspectives that 

they miss. 

People exaggerate how well they understand others’ perspectives.

This general tendency, perhaps familiar to most people in their everyday 

communication1 has many expressions. One is the common knowledge 

effect2 : People exaggerate how much of their knowledge is shared by others. 

As a result, they fail to say important things, expecting others to know them 

already. Thus, a physician might assume that patients know that they will be 

tired long after a surgery; salespeople might assume that customers know 

that they will be hot (or itchy) wearing a new fabric; grocers may assume that 

people know that bar codes do not guarantee that a food is traceable to its 

source, in case of an outbreak. Without knowing what people know already, 

communicators cannot know which outcomes to include in their messages. 

Researcher sometimes fall prey to this bias when they charge people 

with attitude-behavior inconsistency,3 when attitudes (e.g., healthy living is 

important to me) do not predict behavior (e.g., diet, exercise). However, those 

charges are misplaced if researchers have overlooked other outcomes that 

influence those choices (e.g., Healthy living is important, however, I also need 

to spend time with my family and have a long commute. I know that I should 

eat better, but it’s hard to get fresh vegetables in my neighborhood). Some 

miscommunication arises when people do not realize that they are using the 

same term to refer to different outcomes. For example, healthy living might 

imply eating right, exercising often, or being spiritually balanced — to different 

people. Eating right might refer to fat, calories, animal content, or processed 

food content. Animal content might or might not include fish, cheese, or honey. 

Even elaborate communications can miss the mark if they neglect important 

outcomes. For example, women entering college often receive instruction 

in how to reduce their risk of sexual assault. However, that instruction often 

addresses one outcome, physical wellbeing, when young women also consider 

others, such as developing sustained (and safe) relationships.4 Instruction 

is also limited if it defines key terms (e.g., sex, coerced, safe sex) differently 

than do members of its audience.5 Vaccine communications can miss the 

mark if they fail to mention relevant benefits, such as the protection that 

herd immunity provides to people who cannot get vaccinated because of 

other health problems — or if they fail to address costs relevant to some 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 43
	

recipients, such as the effects of compulsory vaccination on civil liberties.6 The 

communicators may reject those costs or see straightforward ways to opt out 

of compulsory vaccination. However, unless they address these outcomes, 

their communications are incomplete.7 

When faced with novel choices or difficult tradeoffs, people may not 

know what matters most to them, making them vulnerable to how options 

are presented (or framed). Psychologists have demonstrated many context 

effects, whereby seemingly irrelevant changes in wording affect choices. For 

example, people are typically more willing to refuse to allow an action (e.g., 

smoking near a building) than they are willing to forbid it, even though the 

outcome is the same.3 People are more likely to be organ donors if that option 

is the default on their driver’s license than if they must choose that status, even 

when opting in or out is easy.8 People will often pay more for a good, if the 

bidding starts at a higher price.9 People make promises when feeling energetic 

(or calm) that they find hard to keep when feeling tired (or angry).10 

In such situations, when people do not know what they want, they must 

construct their preferences from whichever concerns come to mind.11 Under 

favorable conditions, the construction process produces stable preferences, 

immune to context effects. For example, some people figure out what kind of 

end-of-life care they want, then stay the course come what may (in their health 

status, family pressure, etc.). One condition favorable to achieving stable 

preferences is being shown alternative perspectives. That way, for example, 

patients won’t find themselves suffering from regret (e.g., I didn’t think about 

palliative care as a form of treatment and not just giving up. I wish I had). A 

second favorable condition is getting an appreciation of the range of possible 

outcomes. That way, for example, patients don’t find themselves suffering 

from needless surprises (e.g., I never realized that the treatment could be so 

painful (satisfying, expensive, etc.)). Except for sacred values that cannot be 

compromised (e.g., taboos, deeply shared cultural norms), the importance of 

any outcome depends on that range.12 Thus, even people obsessed with money 

worry about other outcomes, when all options have roughly similar prices.13

 Personal advisors (e.g., client-centered counselors; decision consultants) 

try to create these conditions, so that people understand all the outcomes 

that their choices might affect and why they might care about them. 

Communicators addressing broader audiences, however, cannot engage in the 

extended interactions needed to explore alternative definitions of the costs, 

risks, and benefits of a decision. Unless they have studied the audience, their 

communications may not raise perspectives that people want to consider. Not 

showing the full context of a decision can lead to biased choices — even when 

no bias is intended. For example, drivers renewing their licenses might think, 

“If I have to make an effort to become an organ donor, I guess that’s not what 

most people do (or what my society values).” 
44 | Chapter 6: Definitions
	

Values are sometimes embedded in how choices are defined. Some context 

effects reflect deliberate attempts to manipulate choices by highlighting 

particular perspectives. Others are unwitting results of communicators’ natural 

ways of thinking, such that they do not even realize which values they are 

conveying. Uncovering hidden values has long been a focus of risk research. 

For example, if a decision entails a chance of dying, that outcome will be part 

of the definition of risk. One common way to define dying is in terms of annual 

fatalities. Although seemingly uncontroversial, that definition makes a strong 

value statement, namely that all deaths are equal.14 An alternative definition of 

the risk of dying is in terms of life-years lost when a person dies prematurely. 

It places greater weight on deaths of young people, as more years are 

lost when they die — and hence on accidents, which affect young people 

disproportionately. Quality-adjusted life years (QALYs; pronounced “kwallies”), 

a definition favored by some health policy analysts, considers the health of the 

deceased, placing greater value on losing a healthy year than an unhealthy one. 

However risk (or cost or benefit) is defined, its expected size must be 

expressed in some statistical term. That choice, too, can favor some 

perspectives over others. For example, McNeil et al.,15 observed that lung 

cancer patients who had surgery (rather than radiation) were more likely to 

be alive five years later, but not two years later — because surgery extended 

the life of those who survived it. As a result, reporting survival statistics for 

just one period (two or five years) presents an incomplete picture. Similarly, 

reporting just the lifetime probability of a disease obscures how those risks are 

distributed over time, such as how breast and prostate cancers occur primarily 

late in life. Another statistical choice is between reporting relative or absolute 

risks. Because there is no way to infer the latter from the former, absolute 

risks are always more informative. Doubling a risk means very different things 

if that entails going from 10% to 20% or from 0.001% to 0.002%.16 Even when 

they contain the same information, different summaries can highlight different 

perspectives, hence bias choices.17

 Although quantitative summaries can be problematic, they are essential for 

communicating how big risks (and benefits) are. Verbal expressions (e.g., rare, 

possible, large) are known to mean different things to different people and to 

the same people in different contexts.18 Among themselves, say, physicians 

may know what one another means by a “rare side effect”; however, patients 

can only guess, hence might misunderstand the risk they are facing. However, 

an undue focus on readily quantifiable outcomes can obscure other features 

that matter when evaluating risks. In a seminal analysis, Starr19 proposed that 

people treat voluntary and involuntary risks differently, demanding greater 

benefits from involuntary ones, before finding them acceptable. Subsequent 

research identified many other features that people sometimes consider 

when evaluating risks. These features include how uncertain, uncontrollable, 

inequitable, and dreaded risks are.20 Unless these qualitative features of risk 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 45
	

are mentioned explicitly, people may overlook them or think that they are 

less legitimate than the quantitative measures of risk that are presented. 

Analogous issues arise with measures of benefits and costs. Fortunately, the 

science that has identified these potential problems also offers ways to address 

them. 

What general practical advice can the science support?

The first step in any communication is to define risks, costs, and benefits in 

ways that allow people to construct stable, informed preferences. Doing so 

requires knowing what is at stake, crafting suitable measures, and testing the 

result to see how well it serves users’ needs. 

Life would be simpler, if there were a universal set of basic human values 

that all communications could address. Indeed, there have been some notable 

attempts to identify such values.21 Unfortunately, the lists are typically both too 

long and too general to guide any specific communication. Thus, knowing, say, 

that people have a need for achievement or for self-realization is not that much 

help to deciding what to say about the costs, risks, or benefits of a medical 

procedure or financial product. A more feasible strategy might be to create 

standard general definitions for particular kinds of decisions. Three examples 

follow, each combining substantive knowledge (of what the outcomes might 

be), analytical expertise (in defining those outcomes), and empirical research 

(into how the communications actually work). 

Use standard definitions for risks with multiple outcomes. At times, 

people know so little that they must rely on experts to identify the outcomes 

that might matter to them. For example, nutrition facts boxes present some 

food constituents related to some health outcomes. The boxes require 

users to make the connections, such as the complex one between sodium 

and hypertension. Lists of ingredient report everything that is in a product, 

enabling knowledgeable users to make connections to any outcome that 

matters to them (although they won’t know how much there is of each). As 

a result, these lists are necessary, but not sufficient, for users to create their 

own outcome measures. The Drug Fact box in Figure 1 has experts choose 

outcomes for specific products (rather than have the same items for every 

product). The box also structures the choice for users, by comparing two 

options (taking the drug or sugar pill) on seven outcomes (for this product), 

without saying how they should be weighed. Most people can extract the 

information needed for decision-making purposes from such displays.22 The 

same strategy could be tried wherever experts can identify and quantify the 

risks and benefits that matter to users. 

Use standard definitions for risks with multiple features. Figure 2 shows 

an approach to capturing the many features that a single outcome (such as the 

risk of dying) may have.19,20 On the left, it includes readily quantified outcomes 
788 healthy adults with insomnia for at least 1 month -- sleeping less than 6.5 hours

per night and/or taking more than 30 minutes to fall asleep -- were given LUNESTA

or a sugar pill nightly for 6 months. Here’s what happened:

What difference did LUNESTA make?

Did LUNESTA help?

LUNESTA users fell asleep faster (15 minutes faster)

Did LUNESTA have side effects?

Life threatening side effects

No difference between LUNESTA and sugar pill

Symptom side effects

More had unpleasant taste in their mouth

 (additional 20% due to drug)

More had dizziness

 (additional 7% due to drug)

More had drowsiness

 (additional 6% due to drug)

More had dry mouth

 (additional 5% due to drug)

More had nausea

 (additional 5% due to drug)

LUNESTA users slept longer (37 minutes longer)

What is this drug for?

Who might consider taking it?

Who should NOT take it?

Recommended testing

Other things to consider doing

To make it easier to fall or to stay asleep

Adults age 18 and older with insomnia for at leat 1

month

People under 18

No blood tests, watch out for abnormal behavior

Reducing caffeine (especially at night), exercise,

regular bedtime, avoid daytime naps

Lunesta was approved by FDA in 2005. As with all new drugs we simply don’t know how its safety

record will hold up over time. In general, if there are unforeseen, serious drug side effects, they

emerge after the drug is on the market (when a large enough number of people have used the drug).

How long has the drug been in use?

People given

a sugar pill

People given

LUNESTA (3 mg each night)

45 minutes

to fall asleep

30 minutes

to fall asleep

5 hours

45 minutes

None observed

26%

26 in 100

10%

10 in 100

9%

9 in 100

7%

7 in 100

11%

11 in 100

6%

6 in 100

3%

3 in 100

3%

3 in 100

2%

2 in 100

6%

6 in 100

6 hours

22 minutes

Prescription Drug Facts: Lunesta (Eszopiclone)

LUNESTA Study Findings

Figure 1. A sample Drug Fact box 

(deaths, other forms of physical harm). On the right, it has six features chosen 

to represent qualitative features of risk, recognizing that people may judge 

risks differently if they are uncertain, uncontrollable, inequitable, or dreaded 

than if they have the complementary properties. For example, people often 

are more accepting of familiar risks, perhaps because they have a better feeling 

for what they entail. They are often less accepting of inequitably distributed 

risks, perhaps because of moral objections or fear of the insult added to 

injury, if they are treated badly. The British government, which advanced 

this proposal,23 found it straightforward to complete the left-hand side with 

This display offers precise definitions of outcomes identified in clinical trials, 

presented in a format based on behavioral science and evaluated empirically. 

It includes quantitative estimates of risks, costs, and benefits, as well as 

indicating the quality of the evidence. 

Source: Schwartz, L.M., Woloshin, S. and Welch, G.. Self-published,

The Center for Medicine and the Media at The Dartmouth Institute,

http://tdi.dartmouth.edu/documents/cmm/LUNESTA_box.pdf.

46 | Chapter 6: Definitions
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 47
	

Figure 2. A standard method for defining risks. 

Cost-benefit analysis (CBA) can be used to estimate the economic value attributes on the left (death, 

harm), producing the amount that one should be willing to pay (WTP) to avoid them. The ones on 

the right are judged on five levels of each attribute. As an example, for dread, these levels are: (1) 

trivial, temporary, and commonplace; (2) potentially serious, but treatable; (3) serious, long-term but 

natural; (4) serious, permanent and unethical; or (5) catastrophic, permanent and highly feared. 

CBA 

(Cost-benefit analysis) 

Deaths 

‘Baseline’ WTP 

Decision Making 

Societal Concerns 

Concern 

factor 

1 Familiarity 

2 Understanding 

3 Equity 

4 Dread 

5 Control 

6 Trust 

Concern Assessment Framework 

Expert

views 

Public 

Harm views

Source: HM Treasury (2005). Managing risks to the public. London: Author. 

routinely produced estimates, and the right-hand side with simple surveys 

of members of staff and of the public. Studies find that people can use such 

displays to construct stable preferences.24 

Use standard definitions for outcomes that occur over time. Some 

decisions involve streams of outcomes, such as regular payments or the varying 

chance of something going wrong at different times. According to economic 

theory, future monetary outcomes should be discounted because the money 

could be invested at interest (the discount rate) in the interim. (If invested 

money earns 5% annually, then $100 today is worth $105 in a year.) That 

logic does not extend to non-monetary outcomes. There is no principled 

reason, though, why, say, pain tomorrow should be less aversive than pain 

today — although people are free to have that personal preference. Table 1 

summarizes behavioral research into reason why people may treat an outcome 

differently depending on when it is received.25 The first is simply caring less (or 

more) about one’s present self than one’s future self. Other reasons include 

caring less about future outcomes because one might not live to receive 

them or have less ability to enjoy them (e.g., having lost one’s sweet tooth or 

sense of novelty). Based on this research, communications about outcomes 

experienced over time must convey when those outcomes may occur. They 

should also help recipients to think through which of these reasons matter to 

them (e.g., Will you enjoy (or hate) thinking about this possibility in your future 
 

 

48 | Chapter 6: Definitions 

(or past)? Offering such prompts could help people avoid the regret of having 

missed something seemingly obvious (e.g., I should have known that I would 

not be able to get it out of my mind). 

Table 1. Reasons for valuing outcomes differently at different times

Differences in Explanation

Pure time preference We care less (or more) about our future selves. 

Probability We are less certain about receiving the promised 

outcome at different times. 

Objective consequence The outcome will have different properties at 

different times. 

Utility The pleasure (or pain) from the outcome will be 

different at different times. 

Anticipation The pleasure (or pain) from anticipating the outcome 

depends on when it is experienced. 

Memory The pleasure (or pain) from remembering an 

outcome depends on when it is experienced. 

Opportunity cost The value of the outcome depends on how related 

resources are invested and consumed.

 Source: Adapted from Frederick, S., Loewenstein, G. & O’Donoghue, T. (2002). Time discounting and time

 preference: A critical review. Journal of Economic Literature, 40, 351-401 

Evaluation

No expense. The minimal test of how well a communication includes 

the outcomes that matter to people is its face validity: Does it include the 

outcomes relevant to recipients’ choices? Making that determination 

requires analyzing what is known about the recipients (i.e., which outcomes 

generally matter to them) and the choices (i.e., which of those valued 

outcomes are at stake). Problems are to be expected if the communication 

team (1) lacks some of the requisite expertise (subject matter knowledge, 

analytical ability, behavioral science), (2) is socially distant from the audience 

(and its perspectives), or (3) has different goals than that audience (e.g., 

focuses on health effects to the exclusion of all other outcomes). 

Low expense. With a small budget, one can conduct think-aloud interviews 

with people like the eventual recipients, asking them to read through 

successive drafts, interpreting as they go, encouraged to report problems. 

Their observations (recorded and perhaps transcribed) can be evaluated for: 

(1) Comprehensibility: Do they interpret the content as it was intended? Do 

they feel like they understand it? 

(2) Bias: Do they find the wording biased or offensive? Do they feel 

inappropriate pressure to make particular choices? 
 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 49
	

(3) Completeness: Do they perceive omissions? What inferences do they 

make about the quality of the science? 

In a pinch, interviews with staff members not on the communication team, 

or even friends and family, can provide valuable input if is clear that the 

drafts are being tested (and not the interviewees). Community samples can 

often be recruited inexpensively (e.g., in return for contributions to favorite 

organizations). 

Modest expense. A larger budget allows assessing construct validity, asking 

how sensitive users are to relevant variations in the communications and 

insensitive to irrelevant ones? For example, the top and bottom sections of 

Table 2 represent the same outcomes in two different frames, cast in positive 

or negative terms (e.g., survival or mortality). If presenting just the top or the 

bottom section leads to different choices, each would be inadequate alone. 

Conversely, one can examine users’ sensitivity to the different statistics in the 

two columns or in the cells, if the five risk factors at the top are varied. Like all 

tests of construct validity, these require an independent assessment of which 

differences should matter to which people.26 

Table 2. NICHD Neonatal Research Network (NRN): 

Extremely preterm birth outcome data 

Based on the following characteristics: 

Gestational Age (Best obstetric Estimate in Completed Weeks: 24 weeks 

Birth Weight: 700 grams 

Sex: Male 

Singleton Birth: Yes 

Antenatal Corticosteroids: Yes 

Estimated outcomes for infants in the NRN sample are as follows: 

Outcomes Outcomes for 

All Infants 

Outcomes for Mechanically

Ventilated Infants 

Survival 62% 64% 

Survival without Profound 

Neurodevelopmental Impairment 44% 46% 

Survival without Moderate to Severe 

Neurodevelopmental Impairment 27% 29% 

Death 38% 36% 

Death or Profound 

Neurodevelopmental Impairment 56% 54% 

Death or Moderate to Severe 

Neurodevelopmental Impairment 73% 71% 

A standard representation for the predicted outcomes of intensive care (resuscitation) for extremely

premature infants, with the alternative choice being palliative (comfort) care. It considers just physical

outcomes, saying nothing about social and psychological consequences that cannot be predicted from

the physical ones. It presents all outcomes in both a positive frame (chances of survival and escaping

disability) and a negative one (chances of death and disability), hoping to avoid the context effect that 

might arise with just one frame. 

Source: NICHD Neonatal Health Network 

http://www.nichd.nih.gov/about/org/cdbpm/pp/prog_epbo/epbo_case.cfm (accessed June 11, 2011). 
 

50 | Chapter 6: Definitions
	

Conclusions

Relevant communications describe the outcomes that matter in the 

decisions that users face. Unless they define those outcomes appropriately, 

communications cannot serve users’ needs. One threat to such definitions 

is exaggerating how well one understands the audience. A second is not 

realizing the values embedded in alternative definitions. A third is presenting 

incomplete perspectives, thereby biasing the choices. As a result, getting the 

definitions right requires systematically analyzing the decision and studying the 

users. Its execution can draw on all the knowledge represented in this volume. 

Additional resources

1. Fischhoff, B., and Kadvany, J. (2011). Risk: A Very Short Introduction. London: Oxford University 

Press. An overview of the science and practice of risk decisions, emphasizing the role of 

appropriate definitions and written for a general audience, with diverse examples. 

2. Glickman, T.S., and Gough, M. (Eds.). (1990). Readings in Risk. Washington, DC: Resources for 

the Future. Accessible articles from the professional literature, focused on health, safety and 

environmental risks. 

3. Hammond, J.S., Keeney, R.L., and Raiffa, H. (1999). Smart Choices. New York: Broadway. A howto guide focused on identifying and defining decision outcomes, grounded in decision analysis 

and behavioral research. 

4. Kammen, D.M., and Hassenzahl, D.M. (2001). Should We Risk It? Princeton: Princeton 

University Press. A text introducing risk analysis, including behavioral issues. 

5. Morgan, M.G., and Henrion, M. (1990). Uncertainty. New York: Cambridge University Press. An 

overview of analytical and behavioral approaches to conceptualizing, assessing, representing, 

and communicating uncertainty. 

Endnotes

1 Epley, N., Keysar, B., VanBoven, L., and Gilovich, T. (2004). Perspective taking as egocentric 

anchoring and adjustment. Journal of Personality and Social Psychology, 87, 327-339; Keysar, B., 

Lin, S., and Barr, D.J. (2003). Limits on theory of mind use in adults. Cognition, 89. 25-41. 

2 Nickerson, R. A. (1999). How we know – and sometimes misjudge – what others know: Imputing 

our own knowledge to others. Psychological Bulletin, 125, 737-759. 

3 Plous, S. (1993). The Psychology of Judgment and Decision Making. New York: McGraw-Hill. 

4 Fischhoff, B. (1992). Giving advice: Decision theory perspectives on sexual assault. American 

Psychologist, 47, 577-588; Yeater, E. A., and O’Donohue, W. (1999). Sexual assault prevention 

programs: Current issues, future directions, and the potential efficacy of interventions with 

women. Clinical Psychology Review, 19, 739-77. 

5 McIntyre S and West P (1992). What does the phrase “safer sex” mean to you? Understanding 

among Glaswegian 18 year olds in 1990. AIDS, 7, 121-26. 

6 Mnookin, S. (2011). The Panic Virus. New York: Simon & Schuster. 

7 Thaler, R., and Sunstein, C. (2009). Nudge: Improving Decisions About Health, Wealth and 

Happiness. New Haven, CT: Yale University Press. 

8 Johnson, E.J., and Goldstein, D. (2003). Do defaults save lives? Science, 302, 1338-1339. 

9 Bazerman, M.H., and Moore, D.A. (2009). Judgment in Managerial Decision Making. New York: 

Wiley. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 51
	

10 Loewenstein, G. (1996). Out of control: Visceral influences on behavior. Organizational Behavior 

and Human Decision Processes, 65, 272-292. 

11 Fischhoff, B. (1991). Value elicitation: Is there anything in there? American Psychologist, 46, 

835-847; Fischhoff, B. (2005). Cognitive processes in stated preference methods. In K-G. Mäler 

and J. Vincent (Eds.), Handbook of Environmental Economics (pp. 937-968). Amsterdam: Elsevier; 

Lichtenstein, S., and Slovic, P. (eds.) (2006). Construction of preferences. New York: Cambridge 

University Press.; Payne, J.W., Bettman, J.R., and Schkade, D.A. (1999). Measuring constructed 

preferences: Towards a building code. Journal of Risk and Uncertainty, 19, 243-270. 

12 Atran, S., Axelrod, R., and Davis, R. (2007). Sacred barriers to conflict resolution. Science, 317, 

1039-1040. 

13 vonWinterfeldt, D., and Edwards, W. (1986). Decision Analysis and Behavioral Research. New 

York: Cambridge University Press. 

14 Crouch, E.A.C., and Wilson, R.A. (2004). Risk-Benefit Analysis. Cambridge, MA: Harvard Center 

for Risk Analysis; Fischhoff, B., Lichtenstein, S., Slovic, P., Derby, S. L. and Keeney, R. L. (1981). 

Acceptable Risk. New York: Cambridge University Press. 

15 McNeil, B.J., Weichselbaum, M.D. and Pauker, S.G. (1978). Fallacy of the five-year survival rate in 

lung cancer. New England Journal of Medicine, 289, 1397-1401. 

16 Akl EA, Oxman AD, Herrin J, Vist GE, et al. (2011). Using alternative statistical formats for 

presenting risks and risk reductions. Cochrane Database of Systematic Reviews, Issue 3. Art. No.: 

CD006776. DOI: 10.1002/14651858.CD006776.pub2. 

17 Chapter 7; Politi, M.C., Han, P.K.J., and Col. N. (2007). Communicating the uncertainty of harms 

and benefits of medical procedures. Medical Decision Making, 27, 681-695. 

18 Budescu, D.F., and Wallsten, T.S (1995). Processing linguistic probabilities: General principles 

and empirical evidence. In J.R. Busemeyer, R. Hastie, and D.L. Medin (Eds.), Decision Making 

from a Cognitive Perspective (pp. 275-318). New York: Academic Press; Kent, S. (1964). Words 

of estimative probability. https://www.cia.gov/library/center-for-the-study-of-intelligence/ 

csi-publications/books-and-monographs/sherman-kent-and-the-board-of-national-estimatescollected-essays/6words.html (accessed 4/5/10). 

19 Starr, C. (1969). Social benefit versus technological risk. Science, 165 (3899), 1232-1238. 

20 Fischhoff, B., Slovic, P., Lichtenstein, S., Read, S. and Combs, B. (1978). How safe is safe enough? 

A psychometric study of attitudes towards technological risks and benefits. Policy Sciences, 9, 

127-152; Slovic, P. (2001). The Perception of Risk. London: Earthscan. 

21 Maslow, A. (1943). A theory of human motivation. Psychological Review, 50, 370-396; Murray, 

H. (1938). Explorations in Human Psychology. New York: Oxford University Press; Rokeach, M. 

(1973). The Nature of Human Values. New York: Wiley. 

22 Schwartz, L.M., Woloshin, S., and Welch, G. (2009). Using a drug facts box to communicate drug 

benefits and harms: Two randomized trials. Annals of Internal Medicine, 150, 516-527; Woloshin, 

S., Schwartz, L.M., and Welch, G. (2008). Know Your Chances: Understanding Health Statistics. 

Berkeley, CA: University of California Press. 

23 HM Treasury (2005). Managing Risks to the Public. London: Author. 

24 Morgan, K.M., DeKay, M.L., Fischbeck, P.S., Morgan, M.G., Fischhoff, B., and Florig, H.K. (2001). 

A deliberative method for ranking risks (2): Evaluation of validity and agreement among risk 

managers. Risk Analysis, 21, 923-938; Willis, H.H., DeKay, M.L., Fischhoff, B., & Morgan, M.G. 

(2005). Aggregate and disaggregate analyses of ecological risk perceptions. Risk Analysis, 25, 

405-428. 

25 Frederick, S., Loewenstein, G. and O’Donoghue, T. (2002). Time discounting and time preference: 

A critical review. Journal of Economic Literature, 40, 351-401. 

26 Clemen, R.T., and Reilly, T. (2003). Making Hard Decisions. Boston: Duxbury. 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 53
	

Chapter 7: Quantitative Information

Angela Fagerlin, PhD - Ann Arbor Veterans Health Services Affairs,
	

Research & Development Center; University of Michigan 

Ellen Peters, PhD - Ohio State University
	

Summary

For patients to make informed decisions about their health care, they 

must understand the risks and benefits of their treatment options, including 

the numeric likelihoods. Unfortunately, many patients have difficulty 

understanding numerical information. Evidence-based recommendations are 

made for improving the communication of numerical information. 

Introduction

Approximately 50% of Americans cannot accurately calculate a tip.1 Almost 

a quarter of college educated adults do not know what is a higher risk: 1%, 

5%, or 10%.2 The innumeracy that plagues Americans has a profound impact 

on patients’ ability to understand statistical rates of the risks and benefits of 

treatment options. Thus, it is not sufficient to simply tell patients that 10% of 

people experience a side effect...because in many cases, the patients will not 

be able to understand that information or incorporate it into their decision 

making. 

In the present chapter, we review the concept and measurement of 

numeracy and summarize the evidence for communicating quantitative health 

information. We close the chapter by offering practical evidence-based advice 

on how best to communicate quantitative health information. 

What does the science say about this aspect of communication? 

Numeracy: its concept, measurement, and influence on information 

processing. Numeracy has been defined in a number of ways,3 with the 

broadest definition being the ability to comprehend, use, and attach meaning 

to numbers. Numeracy is assessed using both objective and subjective 

measures. Objective measures are basically math tests. Among the first 

objective measures of numeracy was a three-item test created by Schwartz 

et al.4

 The questions revolved around probability, the ability to convert 

percentages to proportions and vice versa. This scale was incorporated into 

larger measures by Lipkus et al.,2

 and Peters et al.,5 that used health-related 

questions. Other objective numeracy measures include the Test of Functional 
54 | Chapter 7: Quantitative Information
	

Health Literacy (TOFHLA)6 the Medical Data Interpretation Test,7 which 

measures ability to interpret medical statistics and understand information 

related to disease, and the New Vital Sign, which uses nutrition panels as 

the context.8 Objective measures of numeracy provide the best estimate of 

people’s ability to understand and use numbers. A weakness of such measures 

is the significant time required to complete them, which may reduce their 

usefulness in research or clinical practice, and the frustration people report 

when completing them.9 

Subjective numeracy scales assess numerical ability without asking 

participants to perform mathematical computations. Rather, people assess 

their own ability to handle numeric information. Several measures currently 

use this approach. The Subjective Numeracy Scale (SNS) asks four questions 

that measure perceived ability (e.g., How good are you at calculating a 15% 

tip?) and four that measure preference for receiving information.9,10 The SNS 

measure takes less time to complete than Lipkus et al.’s objective numeracy 

measure and is less frustrating and stressful to complete.9 Furthermore, it 

has been found to correlate moderately with Lipkus’s objective numeracy 

measure and to predict some of the behaviors and abilities that Lipkus’s 

measure predicts (e.g., comprehension of survival curves).10 Additionally, the 

STAT-Confidence scale assesses people’s confidence in their understanding of 

medical statistics.11 

Individuals with higher numeracy skills comprehend more health 

information12 and attend to, remember, weigh, and, ultimately, use quantitative 

information more in their judgments and decisions.13-16 Less numerate 

individuals, on the other hand, appear more likely to weigh and use nonquantitative information, such as narratives and their own mood states, to 

inform their decision making. 

In sum, researchers interested in numeracy have two types of measures from 

which to choose: objective and subjective. The best measure for any study will 

depend on the time constraints of participants, the importance of retaining 

participants in follow-up studies, and the value of obtaining actual numeric 

ability. 

Communicating risk and benefit in qualitative vs. quantitative terms.

Risks and benefits of patient treatments can be described qualitatively and/ 

or quantitatively. With a qualitative description, a patient might be told there 

is a “low chance” of a side effect from a surgical procedure. In contrast, a 

quantitative description would describe the same risk numerically — the 

patient has a 1 out of 100 (1%) chance of developing the side effect. The two 

approaches, however, are not equally effective.17 One significant concern 

is the lack of agreement about what terms, such as low risk, mean. To one 

person a low risk is equated with a risk of 1%, whereas to a second person a 

low risk might be 10%.18 Furthermore, research has shown that, in the absence 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 55
	

of numeric benefits and risks (with only verbal descriptors of likelihood), 

consumers exhibit heightened (and perhaps exaggerated) perceptions of risks 

and benefits and are less able to identify which are the superior drugs.19-21 

To make quantitative information easier to understand, it is critical that the 

information be presented in an understandable way. 

Making numerical information comprehensible and useable 

Less Is more. In three studies, Peters and colleagues tested whether 

providing lay decision makers with less information, rather than more, could 

result in the best outcomes.5 These studies showed that requiring less cognitive 

effort (e.g., by providing less information) in hospital quality reports resulted 

in better decision making through improved comprehension and higher quality 

choices, particularly among participants with lower numeracy skills. 

This effect was also demonstrated with the breast cancer communication 

tool called “Adjuvant Online!” (http://www.adjuvantonline.com). This online tool is designed to help oncologists communicate patient benefits from 

receiving hormonal therapy and chemotherapy.22 Typically, patients are 

presented with the risks of no additional treatment, each treatment alone, or 

both hormonal therapy and chemotherapy. However, for most women, only 

two choices are appropriate. Zikmund-Fisher and colleagues tested the impact 

of providing only those two choices and found that, when fewer options were 

presented, knowledge and speed of processing increased significantly.23 These 

studies point towards the importance of having medical experts identify more 

and less critical elements of a decision so that risk communicators can choose 

strategically how to present them. 

Gain and loss framing. Gain and loss framing refers to how one describes 

risks and benefits (e.g., the number of people who survive or die, respectively). 

Research has shown that decisions are sensitive to this information framing.24-29 

For example, McNeil and colleagues asked patients, graduate students, and 

physicians to imagine they had lung cancer and make a treatment decision 

(surgery vs. radiation) based on cumulative probabilities and life-expectancy 

data.30 The authors manipulated the description of surgery, presenting it in 

terms of survival or mortality chances. In all three populations, more individuals 

chose surgery when they were told that it had a 90% survival rate than when 

they were told that the surgery had a 10% mortality rate. 

Edwards and colleagues’ review of the literature found that loss frames 

messages were generally more effective than gain frames.31 When the target 

behavior is prevention (e.g., infant car restraints, regular physical exercise), 

however, gain-framed messages are more effective 25,27 as gain frames work 

better in situations where the outcomes are certain (e.g., using car seats 

decreases injuries and deaths of children). On the other hand, with uncertainty 

and risk (e.g., whether a mammogram will result in a cancer diagnosis), loss 

frames are more effective in promoting the desired behavior.25 
 

56 | Chapter 7: Quantitative Information
	

Absolute risk, relative risk, and number needed to treat (NNT). When 

explaining risks associated with treatment, three approaches exist to describe 

how the treatment changes risk. For example, when explaining the benefits 

of taking chemoprevention to prevent breast cancer, risk reduction could be 

described as (1) a 50% risk reduction (relative risk reduction), (2) a reduction 

from a 6% risk of breast cancer to 3% (absolute risk reduction) or (3) the 

number of women needed to take chemoprevention to prevent cancer in one 

of them (NNT). 

Comprehension of information and risk perceptions differ across these three 

formats. Sheridan and colleagues found that NNT was the most difficult format 

for patients to understand and recommended that it never be the sole way that 

information is presented.32 Additionally, when information is presented in a 

relative risk format, the risk reduction seems larger and treatments are viewed 

more favorably than when the same information is presented using an absolute 

risk format.33-35 This is as true for the lay public as it is for medical students.36 

Natural frequency versus percentages. When providing data to patients 

about the risks and benefits of treatment, clinicians can present the data using 

either percentages (10% of patients) or natural frequencies (10 out of every 

100 patients). A number of studies have examined people’s understanding 

of risk and benefit information based on whether the data were presented in 

terms of frequencies or percentages. Results (and their underlying explanation) 

have been equivocal.37-40 

The choice between frequencies and percentages also can affect people’s 

perceptions of the riskiness of the treatment.41 For instance, Peters and 

colleagues asked participants to imagine they had severe headaches and that 

a medicine existed that could decrease headache frequency.42 Participants 

read about a possible side effect of the drug in a percentage format (10% of 

patients get a blistering rash) or frequency format (10 patients out of 100 get 

a blistering rash). Less numerate participants perceived the medicine as less 

risky when side-effect information was presented using percentages rather 

than frequencies. Peters et al., interpreted their results as being due to the 

frequency formats eliciting greater emotional imagery compared to percentage 

formats, which were relatively abstract and meaningless. 

Time frames. When considering the time frame to use when presenting 

risk or benefit information, it is critical to consider the following: (1) the time 

frame for which the best statistics are currently available, (2) the time frame 

over which events occur, and (3) the time frame that is most understood by 

patients.43 

The time span chosen can influence both knowledge and risk perceptions. 

People often fail to adjust their risk perceptions to account for longer time 

spans. For example, people are more likely to increase their use of seatbelts if 

told they have a 33% lifetime risk of serious injury without seat belts compared 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 57
	

with being told the much smaller risk of injury in a single trip.44 Even when 

people receive risk information in survival graph format (which explicitly shows 

how risk changes with time), they often fail to adjust their risk perceptions to 

account for the time span displayed.45,46 

Graphical presentation of risk. It is often recommended that graphs be used 

in addition to presenting numerical information.46 Graph types each have their 

advantages and drawbacks.47,48 Identifying the goal of the communication can 

help to identify the best graph type. If the goal is to help people comprehend 

comparisons, bar graphs are an excellent choice. If understanding trends over 

time is the goal, a line graph would be most beneficial. Similarly, pie graphs 

are superior for accurate judgments about proportions, whereas pictographs 

are most successful at highlighting the number of people affected, and not 

affected, by a medical treatment. 

Graphs can influence more than one kind of comprehension. Some graphs 

influence verbatim understanding of precise information, whereas others 

facilitate understanding the gist of information.49 A recent study compared the 

ability of five graph types (bar graph, pie graph, clock graph, pictograph, and 

sparkplug) to communicate gist and verbatim information (See Figure 1).12 Pie 

and pictographs were superior for communicating gist information (e.g., Which 

drug resulted in the fewest number of patients needing a bypass surgery?), 

whereas bar graphs and pictographs were best at communicating verbatim 

knowledge (accurate reporting of precise numerical information). Systematic 

studies of the effects of graphs, however, have not been conducted with 

increasing numbers of attributes (e.g., a medication with ten side effects that 

each required its own graph). Graphs can influence behavior too. For example, 

graphs that emphasize the numerator of a risk produce more risk-avoidant 

behaviors. Conversely, pictographs, which display numerator and denominator 

information, decrease risk-avoidant behaviors.39 

Incremental risk format. As most treatments have side effects, it is 

important for patients to understand the likelihood they will experience one. 

Thus, it is important to make clear the differences between the baseline risk 

of a side effect (i.e., risk that is present without treatment) and the additional/ 

incremental risk experienced due to the treatment. 

One method to facilitate comprehension is to visually separate baseline 

risk from treatment risk. To do this, an initial pictograph presents the 

patient’s baseline risk. A second pictograph adds a new color to represent 

the additional people who would experience the side effect due to treatment 

(See Figure 2). In a study of over 600 women considering taking tamoxifen as 

chemoprevention, we found that this method reduced worry about medication 

side effects and reduced perceived likelihoods of experiencing a side effect.50 

Debate exists in the literature whether this approach can be used successfully 

with tables.50,51 
Bar Graph 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

* Each graph

 represents

100 people 

Need bypass 

surgery 

Pictograph 

Spark Plug 

Pie Graph 

* Each graph

 represents

100 people 

Need bypass 

surgery 

Clock Graph 

0 

90 10 

80 20

60 40

50 

70 30

* Each graph

 represents

100 people 

Need bypass 

surgery 

­­­100

­­­90

­­­80

­­­70

­­­60

­­­50

­­­40

­­­30

­­­20

­­­10

­­­0

* Each graph

 represents

100 people 

Need bypass 

surgery 

llllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllll 

llllllllllllllll 

0 10 20 30 40 50 60 70 80 90 100 

* Each graph Need bypass 

represents surgery

100 people 

58 | Chapter 7: Quantitative Information
	

Figure 1. Five types of graphical formats
 

­­­100

­­­90

­­­80

­­­70 Cataracts 

­­­60 Cataracts make one or both eyes cloudy, and

make it hard to see. 

­­­50 Among 100 women our age who did take 

­­­40 tamoxifen... 

­­­30 The additional risk caused by taking

tamoxifen: 

­­­20 0.4 more women out of 100 (0.4%) would 

­­­10 now get cataracts. 

­­­0 PREVIOUS PAGE NEXT PAGE 

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Communicating Risks and Benefits: An Evidence-Based User’s Guide | 59
	

Figure 2. Pictograph showing added risk

The use of interpretive labels. People making decisions can be quite poor 

at using numeric information in making decisions. Interpreting the meaning 

of numeric information (e.g., tell patients how good or bad a 9% risk is) can 

have a robust influence in health judgments and choices across diverse adult 

populations.14 In one series of studies, providing interpretive labels resulted 

in greater use of numeric quality-of-care information in judgments and less 

reliance on an irrelevant affective state among the less numerate. Decision 

makers given interpretive labels nonetheless appeared to process the numeric 

information (and not ignore it due to the presence of labels). In another 

study, interpretive labels for test results (that a test came back “positive” 

or “abnormal”) induced larger changes to risk perceptions and behavioral 

intentions than did numeric results alone.52 The normative appropriateness of 

these changes is often unclear, however, so that interpretive labels should be 

applied with great care. 

What general practical advice can the science support? 

In this final section, we recommend ways to nudge individuals towards 

better comprehension and greater welfare. How to present information is an 

important choice for information providers that should be made with care 

using an evidence-based approach. 

1. Provide numeric likelihoods of risks and benefits. Describing risks solely 

with words, such as You have a low chance of experiencing a side effect is 

ineffective. It does not provide patients with the details needed to make 

an informed decision; it increases risk perceptions, and patients vary in 

their interpretations of what low and high risks are. Thus, it is imperative 

to provide patients with numerical estimates of the risks and benefits 

associated with treatment options. The existence of individuals with lower 

numeracy skills does not mean that we should avoid presenting numerical 
 

 

 

 

 

 

 

 

60 | Chapter 7: Quantitative Information
	

information. Instead, we should work to make numbers more accessible 

for all individuals. Furthermore, making numbers more accessible is 

unlikely to have a negative impact on those with higher numeracy skills 

as they can more flexibly understand information presented in different 

formats. In addition, information-processing skills decrease under stress. 

Thus, even highly numerate people can benefit from simple educational 

materials. 

2. Provide absolute risks, not just relative risks. Patients are unduly 

influenced when risk information is presented using a relative risk 

approach; this can result in suboptimal decisions. Thus, an absolute risk 

format should be used. 

3. Keep denominators constant for comparisons. It is difficult for patients 

to compare across treatments when different denominators are used. A 

single denominator should be chosen for comparisons (e.g., 1 in 10,000, 

337 in 10,000). It is easier for patients to understand whole numbers (e.g., 

1 in 10,000) rather than fractions or decimals (.01 in 100); thus, if risks are 

very small, larger denominators will be necessary. 

4. Keep time frames constant. To facilitate comparisons, use the same time 

frame when presenting risks and benefits. 

5. Use pictographs and other visual aids when possible. Graphs make 

numeric information easier to understand and pictographs are the best 

graph for communicating both gist and verbatim knowledge. 

6. Make the differences between baseline and treatment risks and benefits 

clear. Use pictographs to show baseline risks in one color and the risks due 

to treatment in a different color. 

7. Reduce the amount of information shown as much as possible. Health 

educators and clinicians are often motivated to provide patients with as 

much information as possible. However, with more information, patients 

may not know where to focus their attention and what information should 

be most important in their decisions. Thus, it is critical that providers of 

medical information think carefully about which information is key and 

exclude non-critical information. 

8. Provide both positive and negative frames. People, particularly those 

who are less numerate, are unduly influenced by whether a treatment is 

described in positive or negative terms (e.g., survival rates versus mortality 

rates). Whenever possible, describe the risks and benefits using both 

frames. For instance “60% of men who have surgery to treat their prostate 

cancer will be impotent. This means that 40% of men will not experience 

impotence.” 

9. Take care using interpretive labels or symbols to convey the meaning of 

important information. Interpreting the meaning of numeric information 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 61
	

(in terms of its goodness or badness) can affect people’s risk perceptions 

and change their decision making. It can also improve integration of 

multiple pieces of numeric information. This technique should, however, 

be used only when it appears that decision makers are using numeric 

information inappropriately (e.g., ignoring objective quality-of-care 

indicators in hospital judgments). 

10. Test communications prior to use. It is critical to test educational 

materials prior to use to determine understandability and to make sure 

patients do not perceive bias in the materials and like them well enough 

to use. An iterative testing process is critical (see below for suggestions). 

How does one evaluate communications implementing this advice?

No budget. Even when developing communications with no budget, 

opportunities exist to evaluate them. First, ask experts to review the materials 

for accuracy and balance. Second, ask coworkers (e.g., housecleaning and 

cafeteria staff), colleagues, friends, or family (particularly those with less 

education and experience in risk communication) to evaluate and comment on 

materials. Ask (1) how understandable the material seemed, (2) whether the 

amount of information was right, (3) how balanced the material was (in terms 

of presenting the treatment options), (4) how much they would recommend 

this material, and (5) how it could be improved. 

Modest budget. Additional strategies include one-on-one cognitive 

interviews. During the cognitive interviews, you can (1) test for comprehension 

of the materials (e.g., with quizzes after each section) and (2) ask participants 

to describe their emotional reactions to different sections. It is especially 

important to include people with less education and lower numeracy and 

literacy levels and those of different races and genders. 

Serious budget. Additional strategies include (1) employ a literacy expert to 

test the reading and numeracy levels of materials to ensure they are around 

6th to 8th grade level (and to provide recommendations for improving the 

materials if necessary) and (2) test your materials (and alternatives) with a 

representative sample. 

Conclusions

Just as it is no longer appropriate for physicians to dictate treatments to 

patients, it is also no longer appropriate to write educational materials without 

thought for how people will understand or use it. Although it is a significant 

challenge to create materials understandable to populations with low literacy 

and numeracy skills, the reality is that many individuals have difficulty reading 

simple text and working with numbers.1,2 Therefore, care must be taken to 

ensure that patients can use educational materials and understand the risks 

and benefits of their options to make an informed decision. 
 

62 | Chapter 7: Quantitative Information
	

Additional resources

1. Collaboration IPDAS. (2006). Background Evidence Reports from Expert Panels for 12 Quality 

Domains. Retrieved September, from http://ipdas.ohri.ca/ 

2. Gigerenzer, G., Gaissmaier, W., Kurz-Milcke, El, Schwartz, L.M., and Woloshin, S. (2007). Helping 

doctors and patients make sense of health statistics. Psychological Science in the Public Interest, 

8(2), 53-96. 

3. Lipkus, I. (2007). Numeric, verbal, and visual formats of conveying health risks: suggested best 

practices and future recommendations. Medical Decision Making, 27(5), 696-713. 

4. Nelson, W., Reyna, V., Fagerlin, A., Lipkus, I., and Peters, E. (2008). Clinical implications of 

numeracy: Theory and practice. Annals of Behavioral Medicine, 35(3), 261-274. 

5. Peters, E., Vastfjall, D., Slovic, P., Mertz, C. K., Mazzocco, K., and Dickert, S. (2006). Numeracy 

and decision making. Psychological Science, 17(5), 407-413. 

6. Reyna, V. F. (2004). How people make decisions that involve risk: A dual-processes approach 

Current Directions in Psychological Science, 13(2), 60-66. 

7. Reyna, V. F., Nelson, W.L., Han, P.K., and Dieckmann, N.F. (2009). How numeracy influences risk 

comprehension and medical decision making. Psychological Bulletin, 135 (6) 943-973. 

8. Rothman, A. J., and Salovey, P. (1997). Shaping perceptions to motivate healthy behavior: The 

role of message framing. Psychological Bulletin, 121(1), 3-19. 

Endnotes

1 Kirsch IS, Jungeblut A, Jenkins L, Kolstad A. Adult Literacy in America. A First Look at the Results of 

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2 Lipkus IM, Samsa G, Rimer BK. General performance on a numeracy scale among highly educated 

samples. Medical Decision Making. 2001;21(1):37-44. 

3 Nelson W, Reyna VF, Fagerlin A, Lipkus IM, Peter E. Clinical implications of numeracy: Theory and 

practice. Annals of Behavioral Medicine. 2008;35(3):261-274. 

4 Schwartz LM, Woloshin S, Black WC, Welch HG. The role of numeracy in understanding the benefit 

of screening mammography. Annals of Internal Medicine. 1997;127(11):966-972. 

5 Peters E, Dieckmann NF, Dixon A, Hibbard JH, Mertz CK. Less is more in presenting quality 

information to consumers. Medical Care Research and Review. 2007;64(2):169-190. 

6 Parker RM, Baker DW, Williams MV, Nurss J. The test of functional health literacy in adults: A new 

instrument for measuring patients’ literacy skills. Journal of General Internal Medicine. October 

1995;10:537-541. 

7 Schwartz LM, Woloshin S, Welch HG. An assessment of the medical data interpretation test. 

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8 Weiss BD, Mays MZ, Martz W, Castro KM, Hale FA. Newest vital sign. Annals of Family Medicine. 

2005;3:514-522. 

9 Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy 

without a math test: Development of the subjective numeracy scale. Medical Decision Making. 

2007;27(5):672-680. 

10 Zikmund-Fisher BJ, Smith DM, Ubel PA, Fagerlin A. Validation of the subjective numeracy scale 

(SNS): Effects of low numeracy on comprehension of risk communications and utility elicitations. 

Medical Decision Making. 2007;27(5):663-671. 

11 Woloshin S, Schwartz LM, Welch HG. Patients and medical statistics interest, confidence, and 

ability. Journal of General Internal Medicine. 2005;20(11):996-1000. 
 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 63
	

12 Hawley ST, Zikmund-Fisher B, Ubel P, Jankovic A, Lucas T, Fagerlin A. The impact of the format 

of graphical presentation on health-related knowledge and treatment choices. Patient Education 

and Counseling. 2008;73(3):448-455. 

13 Hibbard JH, Peters E, Dixon A, and Tusler M. Consumer competencies and the use of 

comparative quality information: It isn’t just about literacy. Medical Care Research & Review. 

2007;64(4):379394. 

14 Peters E, Dieckmann NF, Vastfjall D, Mertz CK, Slovic P, and Hibbard J. Bringing meaning to 

numbers: The impact of evaluative categories on decisions. Journal of Experimental Psychology: 

Applied. 2009;15(3):213-227. 

15 Dieckmann NF, Slovic P, and Peters E. The use of narrative Evidence and explicit probability by 

decision makers varying in numeracy. Rick Analysis. 2009;29(10):1473-1488. 

16 Lipkus IM, Peters E, Kimmick G, Liotcheva V, and Marcom P. Breast cancer patients’ treatment 

expectations after exposure to the decision aid program, Adjuvant Online: The influence of 

numeracy. Medical Decision Making. 2010;30(4):464-473. 

17 Burkell J. What are the chances? Evaluating risk and benefit information in consumer health 

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18 Wallsten TS, Budescu DV, Rapoport A, Zwick R, and Forsyth B. Measuring the vague meaning of 

probability terms. Journal of Experimental Psychology: General. 1986;115(4):348-365. 

19 Schwartz LM, Woloshin S, Welch HG. The drug facts box: Providing consumers with simple tabular 

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20 Schwartz LM, Woloshin S, Welch HG. Using a drug facts box to communicate drug benefits and 

harms two randomized trials. Annals of Internal Medicine. 2009;150(8):516-527. 

21Berry DC, Raynor DK, Knapp P, Bersellini E. Patients’ understanding of risk associated with 

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22 Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions 

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2001;19(4):980-991. 

23 Zikmund-Fisher B, Fagerlin A, Ubel P. Improving understanding of adjuvant therapy options via 

simpler risk graphics. Cancer. 2008;113(12):3382-3390. 

24 Kahneman D, and Tversky A. Choices, values, and frames. American Psychologist. 

1984;39:341-350. 

25 Apanovitch A, McCarthy D, Salovey P. Using message framing to motivate HIV testing among lowincome, ethnic minority women. Health Psychology. 2003;22(1):60-67. 

26 Banks SM, Salovey P, Greener S, et al. The effects of message framing on mammography 

utilization. Health Psychology. 1995;14(2):178-184. 

27 Rothman AJ, Martino SC, Bedell BT, Detweiler JB, Salovey P. The systematic influence of gain- and 

loss-framed messages on interest in and use of different types of health behavior. Personality and 

Social Psychology Bulletin. 1999;25(11):1355-1369. 

28 Rothman AJ, Salovey P. Shaping perceptions to motivate healthy behavior: The role of message 

framing. Psychological Bulletin. 1997;121(1):3-19. 

29 Rothman AJ, Salovey P, Antone C, Keough K, Martin CD. The influence of message framing on 

intentions to perform health behaviors. Journal of Experimental Social Psychology. 1993;29:408-

433. 

30 McNeil BJ, Pauker SG, Sox HC, Jr., Tversky A. On the elicitation of preferences for alternative 

therapies. New England Journal of Medicine. 1982;306(21):1259-1262. 

31 Edwards A, Elwyn G, Covey J, Matthews E, Pill R. Presenting risk information a review of 

the effects of framing and other manipulations on patient outcomes. Journal of Health 

Communication. 2001;6(1):61-82. 
 

 

 

 

 

64 | Chapter 7: Quantitative Information
	

32 Sheridan SL, Pignone MP, Lewis CL. A randomized comparison of patients’ understanding of 

number needed to treat and other common risk reduction formats. Journal of General Internal 

Medicine. Nov 2003;18(11):884-892. 

33 Malenka DJ, Baron JA, Johansen S, Wahrenberger JW, Ross JM. The framing effect of relative and 

absolute risk. Journal of General Internal Medicine. 1993;8(10):543-548. 

34 Forrow L, Taylor WC, Arnold RM. Absolutely relative: how research results are summarized can 

affect treatment decisions. American Journal of Medicine. 1992;92:121-124. 

35 Baron J. Confusion of relative and absolute risk in valuation. Journal of Risk and Uncertainty. 

1997;14:301-309. 

36 Chao C, Studts JL, Abell T, et al. Adjuvant chemotherapy for breast cancer: How presentation of 

recurrence risk influences decision-making. Journal of Clinical Oncology. 2003;21(23):4299-4305. 

37 Hoffrage U, Gigerenzer G. Using natural frequencies to improve diagnostic inferences. Academic 

Medicine. 1998;73(5):538-540. 

38 Cuite C, Weinstein N, Emmons K, Colditz G. A test of numeric formats for communicating risk 

probabilities. Medical Decision Making. 2008;28(3):377-384. 

39 Waters E, Weinstein N, Colditz G, Emmons K. Formats for improving risk communication in 

medical tradeoff decisions. Journal of Health Communication. 2006;11(2):167-182. 

40 Reyna VF, Brainerd, C.J. Numeracy, ratio bias, and denominator neglect in judgments of risk and 

probability. Learning and Individual Difference. 2008;18(1):89-107. 

41 Slovic P, Monahan J, MacGregor DG. Violence risk assessment and risk communication: The 

effects of using actual cases, providing instruction, and employing probability versus frequency 

formats. Law & Human Behavior. 2000;24(3):271-296. 

42 Peters E, Hart, PS, Fraenkel, L. Informing patients: The influence of numeracy, framing, and 

format of side-effect information on risk perceptions. Medical Decision Making. 2010. 

43 Collaboration IPDAS. Background evidence reports from expert panels for 12 quality domains. 

http://ipdas.ohri.ca/. Accessed September, 2006. 

44 Schwalm ND, Slovic P. Development and Test of a Motivational Approach and Materials for 

Increasing Use of Restraints. Woodland Hills, CA: Perceptronics, Inc.;1982. PFTR-1100--82--3. 

45 Zikmund-Fisher BJ, Fagerlin A, Ubel PA. Inattention to the length of time displayed biases 

comprehension of survival graphs. Risk Analysis. 2005;25(3):589-595. 

46 Collaboration IPDAS. IPDAS 2005: Criteria for Judging the Quality of Patient Decision Aids. 2005. 

47 Lipkus IM. Numeric, verbal, and visual formats of conveying health risks: Suggested best practices 

and future recommendations. Medical Decision Making. 2007;27(5):696-713. 

48 Ancker JS, Senathirajah Y, Kikafka R, and Starren JB. Design features of graphs in health risk 

communication: A systematic review. Journal of American Medical Informatics Association. 

2006;13(6):608-618. 

49 Reyna V. How people make decisions that involve risk: A dual-processes approach. Current 

Directions in Psychological Science. 2004;13(2):60-66. 

50 Zikmund-Fisher BJ, Ubel PA, Smith DM, et al. Communicating side effect risks in a tamoxifen 

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51 Schwartz LM, Woloshin, S, and Welch, HG. Using a drug facts box to communicate drug benefits 

and harms two randomized trials. Annals of Internal Medicine. 2009; 150(8):516-527. 

52 Zikmund-Fisher BJ, Fagerlin A, Keeton K, Ubel PA. Does labeling prenatal screening test results as 

negative or positive affect a woman’s responses? American Journal of Obstetrics and Gynecology. 

2007;197(5):528.e521-528.e526. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 65
	

Chapter 8: Qualitative Information

Julie S. Downs, PhD - Carnegie Mellon University 

Baruch Fischhoff, PhD - Carnegie Mellon University
	

Summary

People often need to understand not only how large risks and benefits 

are, but also why they are that large. Such qualitative knowledge can make 

quantitative estimates more intuitive and credible. It enables people to 

understand their circumstances and adapt their actions when conditions 

change. Qualitative knowledge affords people active mastery and a warranted 

feeling of self-efficacy. As a result, it should help people to make better, 

more confident decisions. Communications designed to improve qualitative 

knowledge begin by describing the intuitive theories (or mental models) that 

people currently hold and then proceed to addressing critical gaps in their 

knowledge. As with all communications, empirical evaluation is needed to 

determine their adequacy. 

Introduction

A simple model of persuasive communication envisions people receiving 

expert advice and then following it as instructed. A simple model of nonpersuasive communication envisions people receiving authoritative risk and 

benefit estimates and then using them to make independent decisions. For 

either simple model of communication to work, people must accept the 

content of the communications without further explanation. 

At times, though, people want to know why communications make their 

claims. That is, they need qualitative information about the processes that 

create the risks and benefits that their actions might bring — whether they 

follow a recommendation or make the choice on their own. One reason why 

qualitative information is needed is to evaluate claims by seeing the evidence 

supporting them. A second reason is to master a topic to be able to act more 

effectively, adapt to changing circumstances, and make sense of competing 

claims. A third reason is to have a warranted feeling of self-efficacy, which 

comes with understanding one’s environment. A fourth reason is to receive 

the respect that comes with being offered an explanation, rather than being 

expected to accept claims on faith. 
 

 

66 | Chapter 8: Qualitative Information
	

Creating communications for qualitative information follows the same basic 

steps as creating communications for quantitative information1: Identify the 

most relevant information, determine audience members’ current beliefs, 

draft messages focused on critical gaps, evaluate those drafts, revise them as 

needed,2 and assess the resulting communication’s adequacy, relative to the 

demands placed on it.3 An added burden on qualitative communications is that 

recipients must be able to integrate the new information with their existing 

beliefs. Unless they can create a coherent mental model from all they have 

learned, the new information will confuse, rather than inform them.4 

Theoretical background: what does the science say?

Qualitative information can vary widely in its importance. There are many 

factors that affect the risks and benefits of foods, pharmaceuticals, motor 

vehicles, life styles, and most other things. However, typically, only a few 

of those factors really matter.5 Focusing on those few factors makes best 

use of individuals’ inevitably limited attention. For dieters, a critical piece of 

information might be how the body metabolizes whole versus refined grains. 

For homeowners with radon concerns, it might be how the gas concentrates 

and dissipates. For patients managing chronic health issues, it might be how 

drugs interact with one another and with foods (e.g., statins and grapefruit). 

People interpret specific situations by assembling mental models from 

general beliefs that they have acquired over their lives. These mental models 

enable them to make inferences in diverse, even novel situations. However, 

those inferences will be flawed if the mental models are incomplete or include 

erroneous beliefs. For example, fears of electromagnetic fields are exacerbated 

by not realizing how quickly they fall off, as one moves away from them.6 

Fears of hypertension are attenuated by not realizing the threat lurking in an 

asymptomatic condition.7 People believe that their homes will heat (or cool) 

faster if they turn their thermostat past the target value, increasing the chance 

that it will get too hot (or cold).8 Often, such misconceptions are easy enough 

to correct, if one knows that they are there. 

Some physical and biological processes are unintuitive. When that happens, 

people may not appreciate the efficacy of protective behaviors. For example, 

people who cannot imagine how tenaciously some pathogens adhere to porous 

surfaces are less likely to wash their hands (or their cantaloupe) adequately. 

People who expect underinflated tires to be visibly flat are less likely to check 

their air pressure. People who think that having a fan circulate the air protects 

them from dangerous fumes are less likely to have one blowing outward 

through an open window. People who think that expansive lawns represent 

healthy environments are less likely to plant pollinators. Correcting these 

mental models may require offering new ways of thinking about the unintuitive 

processes (e.g., how pathogens hang on, how air circulates in rooms, how tires 

hold their shape, how complex healthy ecosystems are). 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 67
	

Some behavioral processes are unintuitive. The social and behavioral 

sciences exist because people have incomplete insight into how they, and 

others, respond to many situations.9

 For example, people are often surprised 

to learn that one is more likely to get help in an emergency if there is just one 

person nearby than if there are dozens, or that panic is rare in disasters, or 

that most people adjust even to great adversity.10 Here, too, creating stable 

changes in individuals’ mental models requires offering them new ways to 

think about these processes, in effect, teaching them the relevant social and 

behavioral theory. For example, communications might explain how diffusion 

of responsibility makes helping less likely; how panic seems common because 

we see it in movies, but not reality; how status quo bias leads to exaggerating 

the value of our current state and underestimating our ability to find meaning 

in a new one. 

Some dynamic processes are unintuitive. Even when individual processes 

are understood, their interactions may not be. For example, patients may 

unwittingly take risks not realizing that taking two over-the-counter drugs for a 

problem exceeds the safety limit of a shared ingredient (e.g., acetaminophen). 

Dieters may be unpleasantly surprised when improving one eating habit 

triggers negative changes in another. Proponents of abstinence-only education 

may experience unexpected disappointment when formerly abstinent teens fail 

to use protection because they have not learned to manage sexual encounters. 

Climate and the economy are other familiar domains in which individually 

comprehensible components interact in unintuitive ways. Sometimes, learning 

the integrating principle will be enough to correct these problems (e.g., 

acetaminophen adds up); sometimes, the implications must be spelled out 

(e.g., how foods interact to affect craving). 

Some termstrigger inappropriate mental models. Because individuals must 

assemble a mental model for each risk decision, they are vulnerable to 

descriptions that prompt inappropriate inferences. For example, mentioning 

that radon intrusions involve radioactivity evokes beliefs about long-term 

contamination from nuclear waste that are accurate, but irrelevant, given the 

rapid decay of radon byproducts (meaning that the problem vanishes once 

the intrusions stop). Palliative care can be seen as giving up, rather than as 

an alternative form of treatment.11 Potential systemic effects of silicon breast 

implants, though questionable, are so widely known that the undisputed risks 

of local complications may not come to mind.12 

Qualitative understanding may not translate into quantitative 

understanding. Processes that are easily understood in the short run often 

have unintuitive properties as they develop over time — if people consider the 

long term at all.13 For example, when thinking about the benefits of savings, 

people are familiar with annual interest rates; however, they underestimate 

how interest compounds over time and, therefore, the value of saving at all 
 

68 | Chapter 8: Qualitative Information
	

and the impact of seemingly small differences in interest rates.14 Similarly, 

people underestimate how quickly risks increase through repeated exposure, 

whether of driving, unprotected sex, contraceptive failure, or small doses of 

radiation. And they may not appreciate the importance of early responses to 

exponentially growing problems, whether cancers or invasive species.15 For 

those processes, intuitive estimation is so difficult that it may be necessary to 

run the numbers for people.16 

What general practical advice can the science support?

Any communication must consider how its new information can be 

integrated with existing beliefs to create a more accurate mental model. The 

research process for achieving this goal has three steps: 

Step 1. Identify the main factors determining the risks and benefits of 

a choice, along with the relationships among them. Figures 1 and 2 show 

two examples of a standard representation of such factors and relationships, 

patterned after the influence diagrams of decision theory.17 The nodes 

represent factors predicting the risks and benefits; the arrows represent 

predictive relationships. In Figure 1, the critical outcome is the health effects 

from a cryptosporidium intrusion in water supplies; it appears in the upper 

right corner.18 In Figure 2, the critical outcome (again in the upper right) is 

the health effects associated with uptake of measles-mumps-rubella (MMR) 

vaccine.19 

Figure 1. Model predicting the effects of measures to reduce health effects

of contaminants in domestic water supplies

Contamination of 

Drinking Water 

Utility 

Treatment 

Options 

Routine 

Testing 

Results 

Trigger 

Events 

Utility 

Awareness 

Utility 

Communique 

Joint Task 

Force 

Special 

Studies 

Medical 

Awareness 

Consumption of 

Treated Water 

Consumption of 

Well Water 

Averting 

Behavior for 

Public 

Systems 

Averting 

Behavior for 

Private Wells 

Consumer 

Awareness for 

Private Wells 

Miscellaneous 

Announcement 

Tap Test Info Sources Well Test 

Media 

Coverage 

Consumer 

Awareness for 

Public Systems 

Health 

Department 

Awareness 

Health Effects 

Source: Casman et al. (2000)18 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 69
	

Although there are many things that might be learned about these complex 

domains, the only facts that decision makers need to know are those that 

predict the outcomes that matter. Sketching diagrams like Figures 1 and 2 

provides a structured way to identify those facts. Creating them requires no 

expertise in formal modeling, just clear thinking, informed by substantive 

knowledge of the domains. 

Figure 2. Model predicting health effects associated with uptake of

measles-mumps-rubella (MMR) vaccine 

vaccine 

program 

vaccinate 

child 

screening 

supply

chain 

vaccine 

availability 

public health

strategy 

multiple

vaccines 

risk of 

vaccinating 

personal

values 

identify

reactions 

herd 

immunity 

immunity 

treat 

reactions 

public health

credibility 

benefit of 

vaccinating 

healthcare 

providers 

health 

information 

preventable

disease reporting and

tracking 

vaccine safety

research total 

dose 

quality of

vaccine 

vaccine 

effectiveness 

disease 

surveillance 

Source: Downs et al. (2008)19 

Models are created by working backward from the outcomes, adding the 

factors that affect them, then the factors that affect those proximal factors, 

and so on, going as far upstream as desired. That analysis entails hard, clear 

thinking by people who know about the issues, reviewing one another’s work 

until the logic of the model seems right. Table 1 offers rules to use to check the 

work. Although models can be made precise enough to produce quantitative 

predictions, analyses done to structure communications often have the more 

modest goal of potential computability: The model’s variables and relationships 

should be defined clearly enough to allow quantitative predictions were all 

the needed data available. However, getting the structure right, without the 

numbers, can identify the qualitative story explaining quantitative estimates. 
 

 

 

 

70 | Chapter 8: Qualitative Information 

Table 1. Methodology for assessing the clarity of an expert model

Review the Nodes

1. Check that the name of the variable at each node is appropriate. 

2. Consider possible values for each variable. 

3. Consider ways to measure each variable. 

Review Individual Links

1. Write a statement explaining the causal or predictive relationship 

for each link. 

2. Summarize the evidence for each link and its quality (use dashed 

lines for speculative or disputed links). 

3. Identify ways to study each link. 

4. Identify strategies for interventions affecting each link. 

Review Relationships Between Links

1. Consider eliminating nodes with one input and one output. 

2. Consider combining nodes with identical inputs and outputs. 

3. Avoid circular chains of links. 

Review Overall Model

1. Ensure that critical endpoints are easily identifiable. 

2. See if connecting unconnected nodes will improve predictive value. 

3. Allow for feedback from endpoint to earlier nodes if there are time 

dependencies. 

4. Identify “index variables” (e.g., demographics) that affect many 

values. 

Source: Adapted from Fischhoff et al. (2006)20 

Step 2: Characterize existing beliefs in terms comparable to the formal 

model. Many risks are so complex, novel, and unintuitive that one cannot 

presume to guess how people will conceptualize them. As a result, one needs 

an open-ended approach to determine which factors come to people’s minds 

and how they think about them. A standard approach uses semi-structured 

interviews that begin by asking people to offer any thoughts that they have 

on the topic (e.g., “what have you heard about the MMR vaccine?”). Followup questions ask them to elaborate on each issue that they raise, using their 

own terms, so as not to prejudge what they say. Once those thoughts have 

been exhausted, interviewees can be asked increasingly specific questions 

about topics in the formal models (e.g., “Have you heard anything about 

vaccine risks?” “Do you have any thoughts about how vaccines are tested?”). 

Table 2 presents text for introducing such an interview and encouraging the 

conversation it is meant to have. 

Once transcribed, the interviews can be separated into discrete thoughts and 

then coded into the formal model. With a well-defined model, such coding can 

typically be done quite reliably. If resources permit, two (or more) coders can 

jointly define the coding scheme, apply it independently, compare their work, 

and then refine the scheme as needed. After the coding has been completed, 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 71 

comments falling into each topic can be examined to identify common beliefs 

and ways of thinking and expression. If people raise topics outside the formal 

model, those must be analyzed as well, either as misconceptions that should be 

corrected or as issues that the formal model has missed. 

Table 2. Representative introduction and cues for semi-structured interviews.

Excerpt from introduction: “Our discussion should take about 30 minutes. I have 

some questions to guide us, but please feel free to raise whatever thoughts 

come to mind as we go along. There are no right or wrong answers, and all 

the comments that we get will add value to our research.... We will start very 

generally, just talking about the purpose of vaccines.” 

1. Can you tell me, to the best of your knowledge, how vaccines are supposed 

to work in the body to prevent a disease?

Follow-up: Can you tell me anything about what happens once many 

people get vaccinated for a disease? Prompt if necessary: Do you think that 

would make any difference in preventing the disease? 

16. How do you feel about letting parents choose whether to get the MMR 

vaccination for their children, as opposed to being required by the state?

Follow-up: Are your feelings about this any different for your own children 

versus other children? 

22. Have you read or heard that some parents are choosing not to give their 

children the MMR vaccine?

Follow-up if yes: Can you tell me what you’ve heard? Where did you hear 

about that? 

23. What do you think about these parents’ decision not to vaccinate their 

children?

Follow-up: Do you think their decision helps or hurts their children in any 

way? Do you think their decision helps or hurts other children in any way? 

Source: Adapted from the research protocol for Downs et al. (2008)19 

Such in-depth interviews are an irreplaceable source of insight into audience 

members’ intuitive ways of thinking about a topic. Without them, one can 

miss critical information needs and opportunities to connect new information 

with existing beliefs. If members of the target population have relatively 

homogeneous beliefs, a modest sample (20 or 30) should reveal each belief 

held by any significant fraction. However, even the most representative 

sample of that size can provide only a rough estimate of the prevalence of 

those beliefs, especially given respondents’ role in defining the direction of the 

interviews and which topics are raised. If more precise estimates are needed, 

a structured survey can be constructed, asking standard questions of a suitably 

sized sample. Creating questions that represent the factors in a formal model 

affords such a survey a kind of ecological validity — in the sense that it touches 

the issues that affect the outcomes that matter.21 
 

72 | Chapter 8: Qualitative Information
	

Step 3: Draft, test, and redraft communications, addressing the critical 

differences between what people know and what they need to know.

Identifying those differences requires expertise in risk analysis and human 

behavior. For example, interviews structured about the risk analysis in Figure 

1 revealed misconceptions about several critical facts. One is the erroneous 

belief that consumers can tell when their water is bad, either by inspection or 

by in-home tests. A second is that vulnerable individuals will receive warnings 

in time to take protective actions, which is not the case for hard-to-detect 

pathogens (e.g., cryptosporidium). A third is how to boil water effectively. 

Communications addressing these beliefs would have to convey: “You can’t 

tell if your water is bad”; “The water authorities may not be able to tell either”; 

“Here’s what ‘boil water’ means.”18 

In the interviews based on Figure 2, one critical gap was ignorance about 

vaccine safety research, including the post-licensing surveillance programs 

designed to catch negative reactions. A second was not realizing the protection 

that herd immunity provides to those who cannot be vaccinated due to 

allergies or health conditions. Communications addressing these beliefs would 

have to describe safety programs and herd immunity authoritatively, in ways 

that addressed the accounts offered by vaccine skeptics.19,22 

These suggested messages, like all other ones, are speculative until they have 

been subjected to empirical testing. They might make immediate sense, for 

example, if consumers are generally skeptical about the efficacy of home tests, 

about the water authorities doing their job, or about their ability to boil water. 

Or, they might require explanations that complete parts of their mental models 

(e.g., “Cryptosporidium is hard to culture and detect. If we have trouble 

testing, then do-it-yourself kits will only leave you overestimating how much 

you know.”). Similarly, a mere reminder of herd immunity may allow people to 

complete the picture of vaccination effects. Or, they may need help working 

through the risks to vulnerable individuals moving about a population X% of 

which has not been vaccinated. The interviews (Step 2) and the basic research 

literature (described briefly above) will suggest problems and solutions; 

evaluations will show how adequate the resulting communications are. 

Evaluation

The goal of qualitative communication is not to achieve general mastery 

of the domain, as measured by tests of financial, health, or climate literacy. 

Rather, it is to ensure that people know the facts germane to specific decisions, 

building on their existing mental models. Depending on the decision and their 

prior knowledge, people may need to learn a little or a lot. 

No expense. A simple, straightforward evaluation method asks a few people 

from the target audience to review the draft communication, thinking aloud 

as they go, raising any issues that come to mind, but without receiving any 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 73
	

feedback. Once finished, they are asked to summarize its content to someone 

else, being explicit enough for a subject-matter expert to evaluate the accuracy 

of their accounts. Finally, an expert presents a fuller account than that in 

the draft communication, then sees which facts surprise or confuse the test 

readers. The communication is then revised to address the residual problems 

and tested again until it is adequate — or can no longer be improved. 

Low expense. With a small budget, one can conduct more formal versions 

of the no-expense tests. Rather than impressionistic evaluation of test readers’ 

responses, one can create transcripts of their comments for review by the 

communication team, being sure that the test readers’ concerns, confusions, 

and suggestions are heard. Particular attention should be paid to perceptions 

of comprehensibility and fairness (especially with controversial topics) and 

readers’ ability to draw inferences from its content, indicating that they 

have active mastery. In all cases, it should be made clear that it is the draft 

communications that are being evaluated, not the test readers, whose help has 

been enlisted. 

Modest expense. A more systematic evaluation would create questions 

testing for knowledge of the key factors affecting the critical risks and benefits. 

The communication’s success would be evaluated in terms of test users’ ability 

to answer these questions — which could be used in both pre-tests and field 

tests. The evaluation should be able to detect negative as well as positive 

effects on understanding, by including questions that people typically get right 

without the communication, as well as ones that they typically get wrong. 

Results should be published in the peer-review literature, both to improve 

their quality and to create an accessible archive of solutions (and failures) in 

conveying the qualitative information needed to explain risks and benefits. 

Conclusions

Communication of qualitative information involves the same steps as 

communication of quantitative information. First, determine what information 

people need to know if they are to understand the processes creating the 

risks and benefits that could follow from their decisions. Second, characterize 

their current beliefs in terms that enable comparing them with the analysis 

of what they need to know. Third, design, evaluate, refine, and re-evaluate 

communications that seek to bridge the critical knowledge gaps. If successful, 

qualitative communications leave recipients with a warranted sense of having 

mastered the relevant aspects of a topic, enabling them to make effective 

decisions on their own and evaluate recommendations made by others. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

74 | Chapter 8: Qualitative Information
	

Additional resources

1. Fischhoff, B. (2009). Risk Perception and Communication. In R. Detels, R. Beaglehole, M.A. 

Lansang, and M. Gulliford (Eds), Oxford Textbook of Public Health, Fifth Edition (pp. 940-952). 

Oxford: Oxford University Press. This chapter describes both quantitative and qualitative risk 

communication. 

2. Furnham, A. (1996). Lay Theories: Everyday Understanding of Problems in the Social Sciences. 

Whurr Publishers. Research into the intuitive theories that guide lay interpretations of behavior. 

3. Gentner, D. and Stevens, A.L. (Eds.) (1983). Mental Models. Hillsdale, NJ: Erlbaum. A collection 

showing some of the diverse approaches to capturing mental models. 

4. Morgan, M.G., Fischhoff, B, Bostrom, A, and Atman, C. (2001). Risk communication: The Mental 

Models Approach. New York: Cambridge University Press. This book illustrates the steps 

described in the current chapter, with examples of interviews and communications. 

5. Slovic, P. (Ed.) (2000). The Perception of Risk. London: Earthscan. An important collection 

showing diverse approaches to describing and informing risk perceptions. 

Endnotes

1 Fagerlin, A., and Peters, E. Quantitative information. This volume.
	

2 Downs, J.S. Evaluation. This volume.
	

3 Fischhoff, B. Duty to inform. This volume.
	

4 Gentner, D. and Stevens, A.L. (Eds.) (1983). Mental Models. Hillsdale, NJ: Erlbaum; Rouse, W.B., 

and Morris, N.M. (1986). On looking into the black box: Prospects and limits in the search for 

mental models. Psychological Bulletin, 110, 349-363. 

5 Fischhoff, B., and Downs, J. (1997). Accentuate the relevant. Psychological Science, 8(3), 1-5. 

6 Morgan, M.G., Fischhoff, B., Bostrom, A., and Atman, C. (2001). Risk Communication: The Mental 

Models Approach. New York: Cambridge University Press. 

7 Leventhai, H., and Cameron, L. (1987). Behavioral theories and the problem of compliance. Patient 

Education and Counseling, 10, 117-138. 

8 Kempton, W. (1986). Two theories of home heat control. Cognitive Science, 10, 75-90. 

9 Furnham, A. (1996). Lay Theories: Everyday Understanding of Problems in the Social Sciences. 

Whurr Publishers. 

10 Gilbert, D. (2006). Stumbling Toward Happiness. New York: Borzoi. 

11 Mayer, M. Language. This volume. 

12 Byram, S., Fischhoff, B., Embrey, M., Bruine de Bruin, W., and Thorne, S. (2001). Mental models 

of women with breast implants regarding local complications. Behavioral Medicine, 27, 4-14. 

13 Shaklee, H. and Fischhoff, B. (1990). The psychology of contraceptive surprises: Judging the 

cumulative risk of contraceptive failure. Journal of Applied Psychology, 20, 385-403. 

14 Lusardi, A., and Mitchell, O.S. (2007). Baby Boomer retirement security: The roles of planning, 

financial literacy, and household wealth. Journal of Monetary Economics, 54, 205-224. 

15 Wagenaar, W.A., and Sagaria, S. (1975). Misperception of exponential growth. Perception and 

Psychophysics, 18(6), 416-422. 

16 Sterman, J.D. (2008). Risk communication on climate: Mental models and mass balance. 

Science, 322, 532-533. 

17 Burns W.J., Clemen R.T.: Covariance structure models and influence diagrams. Management 

Science 1993;39:816-34. 
 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 75
	

18 Casman, E., Fischhoff, B., Palmgren, C., Small, M., and Wu, F. (2000). Integrated risk model of a 

drinking waterborne Cryptosporidiosis outbreak. Risk Analysis, 20, 493-509. 

19 Downs, J. S., Bruine de Bruin, W. and Fischhoff, B. (2008). Parents’ vaccination comprehension 

and decisions. Vaccine, 26, 1595-1607.(http://www.scienedirect.com/science/journal/0264410x) 

20 Fischhoff, B., Bruine de Bruin, W., Guvenc, U., Caruso, A., Brilliant, L. (2006) Analyzing disaster 

risks and plans; An avian Flue example. Journal of Risk and Uncertainty, 33, 133-151. 

21 Bruine de Bruin, W., Downs, J.S., Fischhoff, B., and Palmgren, C. (2007). Development and 

evaluation of an HIV/AIDS knowledge measure for adolescents focusing on misconceptions. 

Journal of HIV/AIDS Prevention in Children and Youth, 8(1), 35-57. 

22 Downs, J. S., Bruine de Bruin, W. and Fischhoff, B. (2008). On message, off target: Official advice 

on vaccination is often poorly transmitted (editorial). Nature, 452(13), 128. 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 77
	

Chapter 9: Health Literacy

Michael S. Wolf, PhD - Northwestern University 

Summary

Health literacy reflects both individual capabilities and the complexity of 

demands placed on the individual by the health care system. Over the past 

two decades, an extensive body of research has linked various functional 

literacy and numeracy skills to a range of health outcomes. The literature is 

summarized in this chapter, as are some practical steps for addressing known 

health literacy barriers in the larger context of health communication. 

Introduction

In 2004, the Institute of Medicine (IOM) convened an expert panel to 

review the evidence, generating a seminal report entitled Health Literacy: A 

Prescription to End Confusion.

1 The agreed on definition of health literacy 

put forth by the IOM was that it is “the degree to which individuals have the 

capacity to obtain, process, and understand basic health information and 

services needed to make appropriate health decisions.” In a similar yet slightly 

different perspective of the topic, the World Health Organization (WHO) 

recognized a definition presented earlier by Don Nutbeam, referring to health 

literacy as “the cognitive and social skills which determine the motivation and 

ability of individuals to gain access to, understand and use information in ways 

which promote and maintain good health.”2

 Both the IOM and WHO therefore 

recognize health literacy as comprising cognitive and psychosocial abilities that 

serve as antecedents to health behavior. 

Both Nutbeam and Wolf and colleagues acknowledge that despite these 

accepted definitions, there is often disagreement among health professionals 

and researchers in this field as what health literacy truly means.2-4 For some, 

it is a broad public health agenda to promote clear health communication 

and individual engagement in health care. And to others, health literacy is an 

underlying clinical risk factor for misunderstanding medical instructions, worse 

self-care, and poorer health — the latter view being derived from the body of 

evidence that has served as the foundation for the field of health literacy. Early 

studies linking health literacy to health knowledge and outcomes have assessed 

and continue to assess the construct using crude measures of vocabulary, 

reading fluency, or numeracy.5

 More recent, but less-used, tools have relied on 
78 | Chapter 9: Health Literacy
	

subjective assessment or even the use of population data to derive individual 

skills.6,7 Clearly, there is a disconnect between the findings manifested in the 

literature and the broad interpretations and implications set forth by some. 

However, all can agree that health literacy is a multifaceted concept; reading 

ability and numeracy as measured by the most commonly used tests in the field 

are just a few of the fundamental components. 

What does the science say about health literacy? 

According to the National Assessment of Adult Literacy (NAAL) of 2003, 

approximately 14% of U.S. adults possess skills in the lowest level of prose 

and document literacy (below basic), and 22% are at the lowest level for 

quantitative literacy.8 These individuals can perform only the most simple 

and concrete tasks associated with each of these domains. However, those 

with only basic literacy proficiency have limited abilities and are likely to be 

hindered in routine daily activities. When considering individuals with basic 

and below basic skills combined, as many as 34% to 55% of U.S. adults have 

limited literacy skills. Those who are older, less educated, belonging to racial or 

ethnic minority groups, socioeconomically disadvantaged, and from rural areas 

of the country have higher rates of limited health literacy. Similar population 

estimates and associations have been found in the United Kingdom, throughout 

Europe, Australia, and Canada.9 

As health information and tasks may be more difficult and unfamiliar to 

many, estimates of health literacy using general literacy assessments in these 

national surveys may under-estimate the problem. Therefore, the NAAL 

included a health literacy component.10 The report showed the average health 

literacy scores of Americans to be lower than average general literacy scores of 

adults, although general literacy proficiency is strongly correlated with health 

literacy. 

The methods for assessing adult literacy and health literacy skills follow 

traditional approaches used in education for evaluating basic reading and 

numeracy skills. All of the current tools used in the health literacy literature 

rely on individuals pronouncing words, retrieving information, and/or making 

inferences from print materials, including prose text and tables. By far the 

most common measures of literacy in health care include the Rapid Estimate 

of Adult Literacy in Medicine (REALM) and the Short Test of Functional Health 

Literacy in Adults (S-TOFHLA).11,12 Other measures have emerged to improve 

the timeliness of assessment or to provide opportunities for measuring literacy 

across languages.5,13 All of these new tools, whether they leverage technologies 

or expand assessment tasks, fall back on the same premise: that mainly reading 

fluency and/or numeracy skills are to be evaluated to determine health literacy. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 79
	

Extent and associations. Although the relationship between literacy and 

health outcomes is not entirely clear, there are plausible mechanisms by which 

literacy could directly affect health behaviors, compliance with medications, 

and other pathways to health.1,14,15 Empirical data collected over the past 

two decades support these links.5 It is this body of literature demonstrating 

associations between measures of reading skills and numeracy with outcomes 

(>1,000 related studies to date) that has driven the formation of the health 

literacy field. Specifically, lower literacy has repeatedly been associated with 

less health knowledge, worse self-management skills, higher hospitalization 

rates, poorer health, and greater mortality.5,16,17 In prospective analyses, literacy 

is more strongly associated with these outcomes than years of education.5,17 

Health knowledge. The large number of relevant empirical studies have 

most often linked limited literacy with less health knowledge.18,19 Early work by 

Williams and colleagues found patients presenting to an emergency room with 

low health literacy had poorer asthma knowledge.20 In a similar study, lower 

literate patients with hypertension and diabetes were also reported to have 

poorer understanding of disease.21 Other research studies have since confirmed 

this relationship in a multitude of contexts. Among individuals living with HIV/ 

AIDS, those with limited literacy were less able to define CD4 lymphocyte count 

and viral load and to identify antiviral medications in their regimen even with 

the aid of pictures.22,23 

A great deal of attention has also highlighted the association between 

low health literacy and treatment misunderstanding, including medication 

names, indications, and instructions. Davis, et al., conducted two multi-site 

studies among adults and found those with limited literacy had higher rates 

of misunderstanding their directions for medications provided by either the 

physician or pharmacist.24,25 The problem extended to text and icons used 

for medication warnings and precautions. Wolf and colleagues most recently 

reported that lower literate patients would over-complicate multi-prescription 

drug regimens, taking medicine at more times a day than necessary.26 Finally, 

in perhaps one of the most indicting studies linking literacy skills to medical 

understanding, Gazmararian, Williams, Peel, and Baker interviewed patients 

with asthma, hypertension, diabetes, or congestive heart failure and found 

that low health literacy was an independent predictor of poor functional 

understanding across each of these chronic conditions.18 

Self-efficacy and health behaviors. Fewer studies have directly examined the 

relationship between literacy skills and individual health-related self-efficacy 

and behaviors, and some of the evidence on these outcomes is conflicting. 

For self-efficacy, Wolf and colleagues examined self-efficacy, knowledge, 

and medication adherence among a sample of patients living with HIV/AIDS 

in Chicago and Shreveport, LA.27 Those with limited literacy had lower selfefficacy to engage in treatment. Self-efficacy was found to mediate the literacymedication adherence association. Yet DeWalt and colleagues did not find an 
80 | Chapter 9: Health Literacy
	

association between literacy skills and self-efficacy among a sample of diabetic 

patients.28 

Research on health literacy and health behaviors offers some insights and, 

similarly, a lack of concordant findings. In a single sample, Arnold, Davis, 

Berkel, and colleagues reported on an association between smoking and 

health literacy.29 However, Wolf, Gazmararian, and Baker found no significant 

associations between literacy skills and health risk behaviors (smoking, 

alcohol use, physical activity, body mass index) in a large multi-site sample of 

Medicare managed care enrollees.30 Findings are more conclusive with regard 

to the significance of the association between literacy and health promoting 

behaviors, including cancer screening and vaccinations. Schillinger and 

colleagues presented seminal evidence of the relationship between limited 

literacy and inadequate self-care for diabetes, although recent studies have 

not been able to replicate these findings.31 In addition, there are an equivalent 

number of studies that document associations between literacy and medication 

adherence as those that report this relationship to not be significant.23,27,32 

Clinical outcomes and mortality risk. Individuals with limited health literacy 

experience poorer health. Baker, Parker, Williams, and Clark examined the 

relationship between literacy and self-reported health among patients at two 

urban public hospitals.33 Patients with low literacy were more than twice as 

likely to self-report poor health, even after adjusting for demographic and 

socioeconomic factors. Wolf, Gazmararian, Baker investigated the relationship 

between low literacy and self-reported functional health status among older 

adults.16 Those with low literacy had a higher prevalence of diabetes and 

congestive heart failure, reported worse physical and mental health, greater 

difficulties with activities of daily living, and limitations due to physical health. 

Likewise, Mancuso and Rincon reported that among adult asthma patients, 

limited health literacy was associated with poorer physical health, worse 

quality of life, and a greater number of emergency department visits.34 Two 

studies by Baker and colleagues had previously reported that patients with 

inadequate health literacy had a greater risk of hospital admission- compared 

to those with adequate literacy.33,35 

Most recently, research has identified low health literacy as a significant risk 

factor to greater mortality. Sudore and colleagues reported that low health 

literacy was associated with a 75% increased risk for all-cause mortality, 

compared to those with adequate health literacy.36 Similarly, Baker, Wolf and 

colleagues found low health literacy to be significantly and independently 

associated with a 51% greater mortality risk; the association was found to be 

significant for cardiovascular causes but not for cancer.17 

Limitations of available evidence. Among the hundreds of studies that 

have evaluated the literacy–health relationship, only a limited number to date 

have gone beyond cross-sectional investigations to report on prospectively 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 81
	

collected outcomes, thereby truly being able to comment on causality. Also, 

as the far majority of the research examines individual comprehension of 

health information and instructions, without the extended connection to actual 

clinical outcomes, many have criticized the legitimacy of health literacy as a 

true risk factor to poorer health. 

Paasche-Orlow and Wolf previously proposed certain causal pathways in 

which it would be plausible to assume how limited literacy and health literacy 

skills affect health outcomes, (see Figure 1), although further research is 

needed to elucidate these connections.14 For instance, it has been proposed 

that individuals with limited literacy may face greater difficulty in accessing 

health information in a timely manner, engaging with health care practitioners 

during spoken encounters, and following through on medical instructions 

and the everyday problem-solving required to promote, protect, and 

maintain optimal health. In addition, those with low literacy may feel shame 

and consequently lack the self-efficacy to seek out clarification or acquire 

information elsewhere.37-39 Over time, these factors contribute to poorer health 

as a result of inadequate use of health services, negative health behaviors, 

and poorer self-care. While this conceptual framework is logical, the evidence 

reviewed above has shown that there is evidence supporting and also refuting 

a few of these pathways, making the big picture not entirely clear as of yet. 

On a final related note, unlike longstanding public health research into health 

behavior and health education, the field of health literacy continues to lack a 

unifying theory. Regardless of these limitations, the evidence that continues to 

be gathered on the topic demands considerable attention. 

Figure 1. Proposed causal pathwayslinking health literacy to health outcomes

Health

Literacy

Health

Outcomes

Access and Utilization 

of Healthcare 

Self-Care 

Provider-Patient 

Interaction 

Age 

Race / Ethnicity 

Education 

SES 

Culture / Language 

Sensory / Perception 

Cognition 

Adapted from Paasche-Orlow and Wolf (2007)14 
 

82 | Chapter 9: Health Literacy
	

What general practice advice can the science support?

Although there are a multitude of research studies that have examined the 

problem of limited health literacy, only a fraction currently report on viable 

solutions to address known mitigating effects in various health contexts.40,41 

Most of the early interventions that have been published began by solely 

rewriting health materials at a simpler reading level or following other design 

techniques to improve comprehension.42,43 Further research is necessary to 

fully understand how to reduce known health literacy disparities, however, a 

few studies have highlighted some approaches that could be very promising. 

Specifically, identified targets for health literacy interventions include (1) 

the content and design of health materials, including print and multimedia 

communications; (2) counseling skills of health care practitioners and allied 

health professionals; and (3) the delivery of health care services. 

Numerous longstanding resources and related references already exist that 

can inform best practices for designing health care materials, whether it be 

a print brochure, web site, or educational video. The Table describes some 

key techniques identified by prominent practitioners in the field. Studies 

have shown that the majority of audiences, regardless of literacy level, prefer 

health materials that are clear and concise. What may vary is the depth of 

information desired, therefore limiting and layering content is essential. This 

means that materials should both provide individuals with triage, need-toknow information on a topic, but also opportunities to seek out more detailed 

background content. 

‘Best Practices’ for Rx labeling

Organize label components The label should be organized to reflect how patients process instructions. The 

most important information should be prominently featured. 

Emphasize patient content Critical information should be easy to locate. Patient name, drug name, strength, 

and instructions should be located at the top of the label. Less critical information 

should be located in a separate area. 

Simplify language Jargon / medical terminology should be removed; short sentences should be used. 

Give explicit time periods Use standard time periods (morning, noon, evening, bedtime), instead of vague 

instructions based on times per day (twice daily) or hourly intervals (every 12 hours). 

Include purpose for use Use simple terms to describe indication (high blood pressure instead of hypertension). 

Limit auxiliary information Provide only the most salient information to not overload the patient. 

Address English proficiency Provide instructions in multiple languages. Ensure that translations are accurate 

and of high quality. 

Select appropriate font Optimize typography by using high-contrast print, simple, uncondensed fonts 

(Times Roman or Arial), in a large font size (11-12 point). Refrain from using ALL 

CAPITALIZED letters. 

Improve readability Use numeric rather than alphabetic characters when possible (Take 2 tablets 

instead of Take two tablets). Maximize white space (25-30% of point size) and 

utilize highlighting, bolding or typographical cues to enhance readability. Text should 

be oriented horizontally, not vertically. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 83
	

Some evidence is available that suggests the use of visual aids may help 

lower literate patients attend to, process, and remember health information. 

One study demonstrated that subjects who listened to medical instructions 

accompanied by a pictograph remembered 85% of what they heard in contrast 

to 14% for patients who did not receive a visual aid.44 Wolf and colleagues also 

found the inclusion of patient-centered icons on auxiliary drug warning labels 

significantly improved comprehension, compared to concordant text messages 

without the icons. Those with lower literacy benefited the most.45 As described 

by Webb and colleagues, visual aids can be optimized for individuals across all 

literacy levels so long as the picture or symbol matches mental representations 

held by the intended viewer.46 Therefore, the target audience should be 

included in the development and evaluation of visual aids. 

Beyond health materials, limited research is available describing efforts to 

improve how health care providers verbally communicate to effectively engage 

with patients. There are some initial evaluations of interactive communication 

strategies, such as confirming understanding using the teach back technique, 

or through guided imagery approaches during clinical encounters with patients 

that support the efficacy of these methods. 

The teach back technique is a particularly useful and simple way to confirm 

patient understanding during the encounter.47 After describing a diagnosis and 

or recommending a course of treatment, the health care practitioner asks the 

patient to reiterate what has been discussed by reviewing the core elements 

of the encounter. If a patient provides incorrect information, the practitioner 

can review the information again and give the patient another opportunity to 

demonstrate understanding. In this manner, the practitioner gains assurance 

that the patient has adequately understood instructions and information. In 

contrast, guided imagery requires the patient to not only reiterate content of 

a spoken encounter, but to describe how a recommended behavior should 

be performed in the specific context of the individual’s personal situation. 

This might include explicitly asking a patient when they will take a prescribed 

medicine, where they will store the medicine, and how they will remind 

themselves of the activity. In essence, the practitioner is requiring the patient 

to perform a dress rehearsal of the behavior. Park and colleagues found the use 

of guided imagery to significantly improve adherence.48 

A final health literacy strategy, and perhaps the most daunting, is that of 

practice redesign. The interventions that have demonstrated the greatest 

effectiveness in closing the health literacy gap have been intensive care 

management strategies among patients with certain chronic conditions, such as 

heart failure and diabetes.40,41,49 These include minimizing, whenever possible, 

the patient’s role and responsibilities in managing health. For instance, 

health care practices can streamline tasks, more closely track and follow-up 

chronically ill patients, use navigators or other forms of care coordination to 
84 | Chapter 9: Health Literacy
	

deliver preventive services or set action plans for disease management. These 

broad strategies have incorporated several of these approaches to address 

system complexity, unfortunately, making it difficult to elucidate the true cause 

for any reduction in the effect of health literacy on outcomes. It is also unclear 

whether these comprehensive interventions involving system change can be 

sustained and/or translated to other settings. 

Perhaps the biggest challenge the health literacy field has brought to light 

is finding a way to incorporate a long-term objective in health care pertaining 

to orienting people to the health care system and their role and responsibility 

within it.3

 This will likely require standard training and education early in life 

(i.e., through schools) that deconstructs everyday tasks across the life course, 

how to more effectively communicate with health care practitioners, or giving 

explicit guidance on typical questions one should always ask. This equates to 

providing anticipatory guidance to individuals and families to convey typical 

expectations and experiences when interacting with health care practitioners 

and systems. The intention would likely be to increase self-efficacy to seek 

and obtain health information in a more productive manner and to develop 

effective health and health care problem solving skills. 

How does one evaluate communications implementing this advice?

Addressing health literacy in practice can refer to a range of activities, 

many of which can be performed easily with minimal orientation and at little 

or no cost. For instance, health systems and practitioners should review the 

manner in which they communicate with patients and families and take steps 

to ensure that distributed materials can be understood by patients with more 

limited literacy. For print tools, the readability of materials can be analyzed 

using several different formulas and internet tools. One recommended 

assessment includes Lexile analysis, which can be accessed with a free 

subscription on the internet.50 Davis and colleagues previously found that 

readability as determined by Lexile scores was a significant independent 

predictor of patient comprehension of drug warning information.24 Doak, 

Doak, and Root’s Suitability Assessment of Materials (SAM) is another more 

comprehensive procedure for systematically critiquing materials for low literate 

audiences.51 In general, there are a multitude of available options that can offer 

an initial, although crude, assessment of the quality and comprehendibility of 

print content, whether conveyed via print tools or the web. 

Another inexpensive approach to evaluating the extent of health literacy 

concerns within a health system or community is to use demographic data to 

gain estimates of limited health literacy. Algorithms that include age, race or 

ethnicity, and educational attainment have considerable predictive power in 

determining the likelihood of low literacy and could be used to promote the 

need for health literacy interventions in more resistant corporate cultures and 

systems.6

 Some currently recommend performing basic surveys that include a 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 85
	

literacy assessment among a representative sample within a practice setting, 

albeit this would be at a nominal cost. 

With modest funds, patient and practitioner surveys could be performed 

to determine and identify with more precision any health literacy concerns 

and needs. Surveys of patients might go beyond a literacy assessment; the use 

of the Consumer Assessment of Healthcare Providers and Systems (CAHPS) 

survey developed by the Agency for Healthcare Research and Quality (AHRQ) 

includes health literacy-related questions pertaining to patient satisfaction 

with practitioner professionalism and spoken communication. This could be 

performed periodically after a baseline has been established to evaluate any 

ongoing efforts to improve communications, particularly among patients with 

limited literacy. Other tools similar to the CAHPS are available. More costly, 

but informative for continuing education opportunities, would be to videorecord clinical encounters before and after any training activities and engage 

in fidelity assessments of any new strategies to improve patient access to 

health information. For instance, a practice may seek to confirm that patients 

are receiving mailings, phone calls, emails, and requests from patient portals 

embedded in electronic health records. 

In all, a standard uniform approach to delivering health information 

is necessary and practitioners and health systems should coordinate their 

efforts to ensure patients and families have multiple access points to receive 

the same content. A recent example in the health literacy literature has been 

with medication education and labeling. The use of a universal medication 

schedule (UMS) has been proposed to standardize the way physicians prescribe 

medicines in the most patient-centered manner and to equally request 

pharmacies to use the same instructions and information when labeling and 

dispensing medicines (see Figure 2).52 

Figure 2. Universal medication schedule

Take 1 pill in the morning (bedtime)

Take 1 pill in the morning 

1 pill in the evening

Take 1 pill in the morning 

1 pill at noon

1 pill in the evening

Take 1 pill in the morning 

1 pill at noon

1 pill in the evening

1 pill at bedtime

Morning: 

Noon: 

Evening: 

Bedtime: 

6­8 am

11­1 pm

4­6 pm

9­11 pm

Source: IOM Workshop summary 52 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

86 | Chapter 9: Health Literacy
	

Conclusion

In its seminal 2004 health literacy report, A Prescription to End Confusion, 

the IOM recognized that patients’ health-related knowledge, skills, and 

behaviors are primarily shaped by: (1) cultural background, (2) health system 

demands, and (3) prior learning opportunities.1 This report aptly frames 

limited health literacy not as an individual problem, but as a challenge to 

health care practitioners and health systems to reach out and more effectively 

communicate with those they serve. Long-term health literacy interventions 

must engage communities to develop sustainable health promotion strategies. 

The educational system must support public health efforts by imparting 

relevant skills and familiarizing learners to the U.S. health care system and their 

role within it. Most important, steps can be taken now to increase the quality 

of and access to meaningful health information and simplify the health care 

experiences of those in greatest need. 

Endnotes

1 Institute of Medicine. Health literacy: A Prescription to End Confusion. Washington DC: National 

Academy Press; 2004. 

2 Nutbeam D. The evolving concept of health literacy. Soc. Sci. Med. Dec 2008;67(12):2072-2078. 

3 Wolf MS, Wilson EAH, Rapp DN, et al. Literacy and learning in healthcare. Pediatrics. 

2009;124:S275-S281. 

4 Nutbeam D. Health Literacy. In: Heggenhougen K, Quah S, eds. International Encyclopedia of 

Public Health. Vol 3. San Diego: Academic Press; 2008:204-211. 

5 DeWalt DA, Berkman ND, Sheridan S, Lohr KN, Pignone MP. Literacy and health outcomes: a 

systematic review of the literature. J. Gen. Intern. Med. 2004;19(12):1228-1239. 

6 Hanchate AD, Ash AS, Gazmararian JA, Wolf MS, Paasche-Orlow MK. The demographic assessment 

for health literacy (DAHL): A new tool for estimating associations between health literacy and 

outcomes in national surveys. J. Gen. Intern. Med. Oct 2008;23(10):1561-1566. 

7 Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health 

literacy. Fam. Med. Sep 2004;36(8):588-594. 

8 Kutner M, Greenberg E, Jin Y, Paulsen C, White S. The Health Literacy of America’s Adults: Results 

from the 2003 National Assessment of Adult Literacy: National Center for Education Statistics: US 

Department of Education; 2006. 

9 Rudd RE. Health literacy skills of US adults. American Journal of Health Behavior. 2007;31(supp):8-18. 

10 Kutner M, Greenberg E, Baer J. A First Look at the Literacy of America’s Adults in the 21st Century 

(NCES 2006-470). Washington, DC: National Center for Education Statistics; 2005. 

11 Davis TC, Long SW, Jackson RH, et al. Rapid estimate of adult literacy in medicine: a shortened 

screening instrument. Fam. Med. 1993;25(6):391. 

12 Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J. Development of a brief test to 

measure functional health literacy. Patient Educ. Couns. Sep 1999;38(1):33-42. 

13 Weiss BD, Mays MZ, Martz W, et al. Quick assessment of literacy in primary care: the newest vital 

sign. Annals of Family Medicine. 2005;3:514-522. 

14 Paasche-Orlow MK, Wolf MS. The causal pathways linking health literacy to health outcomes. Am 

J Health Behav. Sep-Oct 2007;31 Suppl 1:S19-26. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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15 Baker DW. The meaning and the measure of health literacy. J. Gen. Intern. Med. 2006;21(8):878-

883. 

16 Wolf MS, Gazmararian JA, Baker DW. Health literacy and functional health status among older 

adults. Arch. Intern. Med. Sep 26 2005;165(17):1946-1952. 

17 Baker DW, Wolf MS, Feinglass J, Thompson JA, Gazmararian JA, Huang J. Health literacy and 

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18 Gazmararian JA, Williams MV, Peel J, Baker DW. Health literacy and knowledge of chronic 

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19 Pandit AU, Tang JW, Bailey SC, et al. Education, literacy, and health: Mediating effects on 

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20 Williams MV, Baker DW, Honig EG, Lee TM, Nowlan A. Inadequate literacy is a barrier to asthma 

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21 Williams MV, Baker DW, Parker RM, Nurss JR. Relationship of functional health literacy to 

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22 Wolf MS, Davis TC, Cross JT, Marin E, Green K, Bennett CL. Health literacy and patient knowledge 

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23 Kalichman SC, Ramachandran B, Catz S. Adherence to combination antiretroviral therapies in HIV 

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24 Davis TC, Wolf MS, Bass PF, 3rd, et al. Low literacy impairs comprehension of prescription drug 

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25 Davis TC, Wolf MS, Bass PF, 3rd, et al. Literacy and misunderstanding prescription drug labels. 

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26 Wolf MS, Curtis LM, Waite K, et al. Helping patients simplify and safely use complex prescription 

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27 Wolf MS, Davis TC, Osborn CY, Skripkauskas S, Bennett CL, Makoul G. Literacy, self-efficacy, and 

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28 DeWalt DA, Boone RS, Pignone MP. Literacy and its relationship with self-efficacy, trust, and 

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29 Arnold CL, Davis TC, Berkel HJ, Jackson RH, Nandy I, London S. Smoking status, reading level, 

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30 Wolf MS, Gazmararian JA, Baker DW. Health literacy and health risk behaviors among older 

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32 Paasche-Orlow MK, Cheng DM, Palepu A, Meli S, Faber V, Samet JH. Health literacy, antiretroviral 

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33 Baker DW, Gazmararian JA, Williams MV, et al. Functional health literacy and the risk of hospital 

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34 Mancuso CA, Rincon M. Impact of health literacy on longitudinal asthma outcomes. J. Gen. Intern. 

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35 Baker DW, Parker RM, Williams MV, Clark WS. Health literacy and the risk of hospital admission. 

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36 Sudore RL, Yaffe K, Satterfield S, et al. Limited literacy and mortality in the elderly: The health, 

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37 Wolf MS, Williams MV, Parker RM, Parikh NS, Nowlan AW, Baker DW. Patients’ shame 

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38 Parikh NS, Parker RM, Nurss JR, Baker DW, Williams MV. Shame and health literacy: the unspoken 

connection. Patient Educ. Couns. 1996;27(1):33. 

39 Waite KR, Paasche-Orlow M, Rintamaki LS, Davis TC, Wolf MS. Literacy, social stigma, and HIV 

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40 Pignone M, DeWalt DA, Sheridan S, Berkman N, Lohr KN. Interventions to improve health 

outcomes for patients with low literacy: A systematic review. J. Gen. Intern. Med. Feb 

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41 Clement S, Ibrahim S, Crichton N, Wolf M, Rowlands G. Complex interventions to improve 

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2009;75(3):340-351. 

42 Davis TC, Fredrickson DD, Arnold C, Murphy PW, Herbst M, Bocchini JA. A polio immunization 

pamphlet with increased appeal and simplified language does not improve comprehension to an 

acceptable level. Patient Educ. Couns. 1998;33(1):25-37. 

43 Gerber BS, Brodsky IG, Lawless KA, et al. Implementation and evaluation of a low-literacy 

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44 Houts PS, Doak CC, Doak LG, Loscalzo MJ. The role of pictures in improving health 

communication: A review of research on attention, comprehension, recall, and adherence. 

Patient Educ. Couns. May 2006;61(2):173-190. 

45 Wolf MS, Davis TC, Bass PF, et al. Improving prescription drug warnings to promote patient 

comprehension. Arch. Intern. Med. Jan 11 2010;170(1):50-56. 

46 Webb J, Davis TC, Bernadella P, et al. Patient-centered approach for improving prescription drug 

warning labels. Patient Educ. Couns. Sep 2008;72(3):443-449. 

47 Schillinger D, Piette J, Grumbach K, et al. Closing the loop: physician communication with diabetic 

patients who have low health literacy. Arch. Intern. Med. Jan 13 2003;163(1):83-90. 

48 Park DC, Gutchess AH, Meade ML, Stine-Morrow EA. Improving cognitive function in older adults: 

Nontraditional approaches. J. Gerontol. B. Psychol. Sci. Soc. Sci. Jun 2007;62 Spec No 1:45-52. 

49 Rothman RL, Malone R, Bryant B, et al. A randomized trial of a primary care-based disease 

management program to improve cardiovascular risk factors and glycated hemoglobin levels in 

patients with diabetes. Am. J. Med. Mar 2005;118(3):276-284. 

50 Stenner AJ, Horablin I, Smith DR, Smith M. The Lexile Framework. Durham, NC: MetaMetrics, Inc.; 

1988. 

51 Doak CC, Doak LG, Root JH. Teaching Patients with Low Literacy Skills: Philadelphia: JB Lippincott; 

1996. 

52 Institute of Medicine. Standardizing Medication Labels: Confusing Patients Less: Workshop 

Summary. Washington DC: National Academy Press; 2008. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 89
	

Chapter 10: Affect and Emotion

Ellen Peters, PhD - Ohio State University 

Summary

Affect and emotion influence perceptions of likelihood, value, and the 

risk–benefit balance. These feelings and thoughts interact but also separately 

predict risk perceptions and decisions. Feelings can limit effective risk 

communication sometimes, but are often critical to good decision-making; their 

power can be harnessed in persuasive and non-persuasive communication. 

Introduction

Early psychological research on risk perception and communication 

focused on cognitive forces that shape risk attitudes and behaviors.1,2 More 

recent research has developed and tested theories of risk perception that 

incorporate affect and emotion as key components. Within these theories, 

integral feelings (good and bad feelings experienced about a stimulus, e.g., 

prescription drugs) and incidental feelings (positive and negative feelings, such 

as mood states that are stimulus-independent but may be misattributed to 

it) are used to predict and explain how people react to risks in our complex 

world. The experience of mild affect and emotion is ubiquitous in everyday 

life. It influences the decisions of consumers, including patients, as well as 

the decisions of physicians, health care providers, and risk communicators.3 

Although these feelings can have a negative impact on decision making (he 

was overcome with fear; she was filled with grief; both persons are incapable 

as decision makers). Damasio4 and others argue (and provide evidence) that 

feelings generally increase the accuracy and efficiency of the decision process, 

and their absence degrades decision performance. Communication efforts can 

be improved by understanding this descriptive research and its implications for 

risk communication. 

What does the science say about this aspect of communication?

Two main and interrelated theoretical frameworks exist. The first concerns 

affect — simple, valenced, good/bad feelings — and is represented by research 

on the Affect Heuristic5,6 and the Risk-As-Feelings hypothesis.7 The second 

framework is the Appraisal–Tendency framework, which elaborates on 

cognitive–appraisal theories and examines the influence on risk perceptions of 
 

90 | Chapter 10: Affect and Emotion
	

the appraisals and behavioral motivations underlying specific emotions, such as 

anger and fear.8,9 The two frameworks are related in that both focus primarily 

on feelings experienced at the moment of judgment or choice, and valenced 

affect is similar to pleasantness — a primary appraisal underlying specific 

emotions. 

Valence and the affect heuristic. Support for the first framework and the 

relationship between affective valence and risk perceptions comes from a 

variety of experimental, survey, and field studies. Whereas risks and benefits 

tend to be positively correlated in the world (e.g., risky stocks tend to offer 

higher return; if they don’t, they don’t last long in the market). However, risk 

and benefit perceptions tend to be negatively correlated (e.g., prescription 

drugs tend to be perceived as high benefit and low risk1). This inverse relation 

between perceived risks and perceived benefits has been linked to the strength 

of positive or negative affect associated with the product or activity.10 People 

seem to use an affect heuristic and base their judgments of an activity or 

product not only on what they think about it but also on how they feel about it. 

If they feel good about an activity, they tend to judge risks as low and benefits 

as high; if they feel bad about it, they may judge the opposite — high risk and 

low benefit. Under this model, affect comes prior to and acts as information 

in judgments of risk and benefit (e.g., in the domain of prescription drugs11). 

Peters12,13 extended the Affect-Heuristic model to examine multiple ways that 

affect influences judgment and decision processes. For example, apart from 

information, affect also can act as a spotlight, causing some decision-related 

information to be used while other information is ignored. 

Although much Affect-Heuristic evidence is correlational, experimental 

manipulations also exist. Research demonstrates that reliance on affect (and 

the negative correlation between risk and benefit perceptions) increases under 

time pressure.5 Additionally, providing one type of information (e.g., about 

increased risk in the absence of any benefit information) influences perceptions 

of the other (i.e., perceptions of benefit are reduced5). Affect can also be 

manipulated incidentally to examine its causal impact on risk perceptions. 

In one paper and consistent with the Affect-Heuristic model, increasing 

negative affect through a mood manipulation (reading an unpleasant news 

story) increased risk perceptions of a variety of hazards and diseases whereas 

increasing positive affect in a similar manner decreased risk perceptions.14 

Finally, effects of individual differences such as affective reactivity can also 

be seen on risk perceptions, with individuals higher in neuroticism and other 

measures of negative reactivity perceiving greater risk.15,16 Some evidence also 

exists that older adults and less numerate adults may perceive greater risk 

than those who are younger and those who are more numerate17-21; the results 

presumably are due to older and less numerate populations relying more on 

affect (and less on deliberation) to derive their risk perceptions. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 91
	

Incidental and integral sources of affect appear to influence risk reactions 

(and, based on Affect-Heuristic findings, likely influence benefit perceptions 

although this has not been studied systematically). Decision makers also appear 

to be insensitive to probabilities of risky events that are strongly affective.7,22,23 

Moreover, greater risk is communicated through the use of frequency data 

(the number of people at risk) than through a percentage format (the percent 

of people at risk). The greater impact of frequencies compared to percentages 

appears due to focusing on and imagining the numerator (the number of 

people at risk) and neglecting the denominator, resulting in more affective 

risk-relevant images.6,24-26 Finally, existing data do not support the idea of 

a curvilinear relationship with extreme negative affect and worry inhibiting 

action; instead, they suggest that the more worry one has (if nonpathological), 

the more one is motivated to take on self-protective health behaviors.27-29 

Affect also appears to play an important role when numeric risks are 

compared.6 For example, Fagerlin, Zikmund-Fisher and Ubel21 found that 

women asked to estimate their personal risk of breast cancer over-estimated 

their risk (with more negative affect about cancer associated with higher risk 

estimates, consistent with the Affect Heuristic). In addition, after being told 

their actual risk (and presumably comparing it to the higher risk estimate 

they just produced), they reported feelings of greater relief and lesser anxiety 

compared to women who did not estimate their personal risk first. The authors 

suggest that risk perceptions “are not merely cognitive appraisals of numeric 

risk ... They include intuitive and emotional reactions, which translate being 

“high” or “low” into “something to worry about” or “something to be relieved 

about” (p.143). 

Of course, because much Affect-Heuristic research has been conducted using 

self-reported affect and emotion, it is not always clear whether results are 

due entirely to experienced feelings or to thoughts about the product (“I feel 

it’s good” and “I think it’s good” can be quite similar). Effects of experimental 

manipulations of experienced feelings on risk perceptions, however, support 

the causal role of affect in risk perceptions.14 Research on specific emotions 

poses a different challenge to the Affect-Heuristic approach. As reviewed in the 

next section, some research suggests that emotions of the same valence (anger 

and fear) can have opposing effects on risk perceptions. 

Discrete-emotion research and implications for risk communication. Public 

reaction to risks also can include more complex feelings such as fear and 

anger that go beyond valenced affect. These emotions are generally thought 

to be derived, in part, from feelings of goodness or badness, but they also 

appear to result from additional cognitive appraisals of the environment, 

such as predictability and coping potential.30,31 These specific emotions are 

generally studied as incidental emotion states (e.g., angry mood32), but they 

can be studied as integral to (part of the representation of) an object, such as a 

prescription drug or FDA itself.15 
 

92 | Chapter 10: Affect and Emotion
	

Some elegant work by Lerner and Keltner8,9 highlights the benefits of 

examining risk perceptions in an emotion-specific manner. For example, 

they predicted and found that fear and anger had opposite effects on risk 

perception. Whereas fearful people expressed pessimistic risk estimates and 

risk-averse choices, angry people expressed optimistic risk estimates and 

risk-seeking choices. Lerner, Gonzalez, Small, and Fischhoff33 found that an 

experimental manipulation of fear (writing about what makes you most fearful 

about terrorist attacks and then listening to a fear-inducing audio clip about 

bioterrorism) increased risk estimates of a future terrorist attack and plans 

for precautionary measures after the September 11 attack; a similar anger 

manipulation did the opposite. 

Little evidence exists, however, for naturally occurring emotion states, 

whether incidental or integral, existing in such pure states for time periods 

long enough to exert significant emotion-specific effects; mixed emotions and 

mixed appraisal patterns appear to dominate.15 However, individuals who tend 

to be more angry than fearful may generally perceive less risk.9,33 In addition, 

emotion-specific effects may have important effects in risk communications 

that can convey more pure emotions. Nabi,34 for example, experimentally 

manipulated anger versus fear about drunk driving and demonstrated an 

impact in subsequent policy preferences for retribution versus protection, 

respectively. Research is needed to understand the effects of more complex 

mixtures of incidental and integral sources of affect and emotion on risk 

perceptions. 

Predictive power of feelings versus thoughts. Research suggests that 

our feelings about risks are important. They can diverge from and be more 

predictive of behaviors and behavioral intentions than thoughts about those 

risks.7 For example, Diefenbach, Miller, and Daly27 found that affect (cancerspecific worry) predicted mammography adherence whereas a cognitive 

variable (perceived likelihood of cancer) did not. Similarly, Peters, Burraston, 

and Mertz15 demonstrated that radiation-related stigma responses (e.g., to 

nuclear power) emerged more from negative emotion (mixed fear and anger 

responses) and less from an activation of risk perceptions (of potential hazards 

or threats). 

The power of feelings versus thoughts to influence behaviors and intentions 

can be altered. Experimental evidence suggests that increasing deliberation, 

for example, by having participants provide reasons for a choice or even doing 

math problems prior to a choice reduces the influence of affect in decisions.35-37 

Conversely, methods exist to increase affective input into decisions by 

decreasing the capacity to think (e.g., time pressure and cognitive load5,38) and 

by increasing affective meaning (e.g., through the use of ordering, symbols, 

evaluative categories and other methods to make the “gist” of information 

more easily accessible39-41). 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 93
	

What general practical advice can the science support? 

Understand what is important to know about the regulated product 

and know the audience for the risk/benefit communication. A descriptive 

understanding of the various effects that emotions and affect can have on 

consumer behavior related to FDA-regulated products — combined with a 

normative analysis of whether those effects are harmful or helpful to individual 

or public health concerns — can lead to development of prescriptive advice 

about how to harness or rein in the power of affect and emotions. For 

example, a case can be made for the targeted use of affect and emotion to 

decrease smoking through graphic warning labels on cigarette packages.42 In 

situations (e.g., statins) where long-term benefits of a medication are difficult 

for a patient to evaluate, but short-term costs are clear and obvious, promoting 

adherence might require highlighting the affective meaning of long-term 

benefits. Affect and emotion can be used to promote public health; they can 

also undermine it. 

Often, however, the normative appropriateness of altering affect towards a 

product or towards information is unclear. Should benefit information about 

a medication be made easier to evaluate so that consumers use it more? 

Should extreme negative affect associated with the side effect of a particular 

medication be reduced in patient communications? The use of affect and 

emotion to alter behaviors and the comprehension and use of information 

poses serious ethical concerns. On the other hand, neglecting to consider their 

effects also poses ethical concerns. Understanding their effects allows policy 

makers to make thoughtful choices about how and what information to present 

rather than making such choices in random fashion, naïve to their effects. 

Provide risk and benefit information about taking an action. If the Affect 

Heuristic is correct and providing information about increased risk (e.g., 

about a medication) reduces benefit perceptions (in the absence of benefit 

information), then FDA and others should provide information about both risks 

and benefits in communications. 

Consider presenting risks and benefits of not taking an action. Because 

comparisons influence affective evaluations and thereby subsequent behaviors, 

a fully informed consumer should have information about what happens if she 

takes an action (e.g., a recommended medication) and if she does not. 

Make the affective meaning of important information easy to access.

Simply providing information is not enough. Research suggests that, when 

provided information that does not convey affective meaning, consumers are 

unable to use that information. The use of evaluative labels (excellent, fair), 

symbols (e.g., similar to Consumer Reports), or ordering can help consumers to 

access the meaning of important information and thereby use it in place of less 

relevant sources of information. Use of these techniques can also facilitate the 

integration of important information.40 
94 | Chapter 10: Affect and Emotion
	

When emotions are expected to be high (and potentially harm decisions), 

provide methods to “stop and think” to reduce affective input. Consumers 

and patients sometimes react with fear, alarm, anger, or dread in ways that can 

overwhelm their ability to understand and use risk communications and make 

effective decisions. In cases where FDA or others can predict this may happen, 

encouraging the patient or consumer to stop and think (including to think and 

try to better understand their own emotional reactions) may help to reduce 

strong reactions so that, for example, a patient can weigh pros and cons of 

treatment options. 

Fight fire with fire. In cases where FDA believes that persuasive 

communication is the best approach, emotional communications, especially 

those that are fear-based, can be used to increase risk perceptions and change 

behaviors.43 An example of this might be requiring the use of particularly 

graphic warning labels on cigarette packages. 

Consider the effects of advertising, brand names, and other promotional 

efforts on perceptions of the risks and benefits of products that FDA 

regulates. Work on the affect-heuristic and risk-as-feelings hypotheses 

have demonstrated that incidental sources of positive and negative affect, 

respectively, can reduce and increase risk perceptions. Promotional efforts 

intended to increase sales often do so by conveying positive affect; they show 

happy, successful patients, not those who are suffering. As a result, these 

promotional efforts (even in the absence of any information about benefits) 

likely increase perceptions of those benefits and decrease perceptions of risks. 

Their effects, however, are less clear and predictable given the preponderance 

of side-effect information generally required in FDA-regulated advertisements; 

this topic deserves further study. 

How does one evaluate communications implementing this advice? 

Evidence collected across a wide variety of domains, using diverse 

experimental and survey methods, highlight the potential importance of 

affective processes in how consumers and patients process and use information 

related to FDA-regulated products. The scientific study of affect and emotion in 

risk perception and decision making is relatively new, however, and differences 

exist across situations with respect to the nature of emotional sources of 

information (e.g., whether integral or incidental, specific to fear and worry 

or involving depression) and of the normative appropriateness of emotional 

experience (and the many situations where the normative appropriateness is 

unclear). This combination suggests that communications should be tested for 

their impact on affect and emotions, thoughts, risk and benefit perceptions, 

and, ultimately, health behaviors prior to their use. Such research should 

be conducted in appropriate populations and particularly in vulnerable 

populations who are likely to or should be affected by the communication. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 95
	

Affect and emotions can be measured in a variety of ways, including simple 

self-report measures36 (“How do you feel about it?” on scales that range from 

good to bad or not at all angry to very angry). Pictorial scales44 may provide a 

particularly accessible method to measure affect in less literate populations. 

Less reportable affect can be measured using reaction times and physiological 

measures (e.g., heart rate or skin conductance responses). Individual 

differences in affective reactivity and experimental manipulations of affect or 

particular emotions can also be employed (See Peters12 for a brief review). 

Without any budget for testing communications, FDA can nonetheless ask 

its internal experts to prioritize information from most to least important and 

highlight the affective meaning of the most important information. The agency 

can develop communications that present both risk and benefit information, 

including comparative risks and benefits of not taking an action. FDA can 

conduct semi-structured cognitive interviews with employees (particularly 

those with less education and experience in risk communication) who evaluate 

and comment on the message. Is the message clear? Is there anything that 

is not understood? If FDA knows from internal conversations that previous 

messages have “missed the mark” in some way (e.g., comprehension of 

a particular aspect of an important message), targeted questions can be 

asked. Risk communication experts, with knowledge about the role of affect 

and emotion, should be included early on in discussions about possible 

regulatory approval of products to maximize the potential for strategic risk 

communication. 

With a modest budget, the methods above can be used to refine a specific 

communication before conducting one-on-one cognitive interviews with 

individuals who read and evaluate FDA’s message. Testing of message 

comprehension is critical, and it is particularly important to include people 

with less education and lower levels of numeracy and literacy. This testing 

should include comparative testing with previous messages (or alternative 

message forms that emerged in earlier testing) in order to examine how the 

communication alters feelings and perceptions of risks and benefits of the 

disease and possible treatments. If FDA has a particular message that decision 

analysis has revealed as important, does the communication successfully 

convey the message? 

A serious budget for the testing of risk communications would allow FDA to 

take a more refined approach to testing specific messages, and also to fund 

and/or conduct research to uncover the general mechanisms underlying how 

consumers and patients process and use information that FDA provides or 

regulates. For specific messages, semi-structured interviews can be used to 

refine different versions of the message and then a nationally representative 

test of the messages can be conducted to maximize comprehension and use of 

information highlighted by the normative analysis of the particular situation. It 
96 | Chapter 10: Affect and Emotion
	

could allow for a randomized controlled trial of that specific communication in 

the specific segment of the population that will most likely use the product and 

to test the messages in relevant vulnerable patient populations. 

Testing could also be more systematic and uncover general underlying 

mechanisms to guide FDA in future risk communications across a range of 

products and situations. Systematic research across different FDA-regulated 

products could reveal, for example, how and when direct-to-consumer 

advertising influences benefit and risk perceptions. Systematically varying the 

information-presentation format (e.g., percentages vs. frequencies) with which 

benefits and/or risks of prescription drugs are presented across different types 

of drugs and devices could assist FDA in predicting what formats will work 

best to facilitate comprehension and use of information and in what kinds of 

situations. Such systematic studies could have impact within and beyond FDA. 

It is through such systematic studies that a general theoretical framework of 

effective risk communication will ultimately emerge. 

Additional resources

1. Slovic, P., Peters, E., Finucane, M.L., and MacGregor, D.G. (2005). Affect, risk, and decision 

making. Health Psychology, 24, S35-S40. The authors examine evidence supporting the affect 

heuristic and discuss its implications for risk communication and health decision making. 

2. Loewenstein, G. F., Weber, E. U., Hsee, C. K., and Welch, E. S. (2001). Risk as feelings. 

Psychological Bulletin, 127(2), 267-286. The authors present their risk-as-feelings hypothesis and 

show that emotional reactions to risky situations often diverge from cognitive assessments of 

those risks. 

3. Lerner, J. S., and Keltner, D. (2001). Fear, anger, and risk. Journal of Personality and Social 

Psychology, 81(1), 146-59. Drawing on an appraisal-tendency framework, the authors found that 

fear and anger have opposite effects on risk perception with fearful people being risk averse and 

angry people being risk seeking. 

4. McComas, K.A. (2006). Defining moments in risk communication research: 1996-2005. Journal of 

Health Communication, 11(1), 75-91. This article reviews risk communication research appearing 

in the published literature from 1996-2005. 

5. Wardman, J.K. (2006). Toward a critical discourse on affect and risk perception. Journal of Risk 

Research, 9(2), 109–124. The author examines critiques of the affect-heuristic and appraisaltendency frameworks in risk perception research. 

6. Kees, J., Burton, S., Andrews, C., and Kozup, J. (in press). Understanding how graphic pictorial 

warnings work on cigarette packing. Journal of Public Policy and Marketing. The authors 

hypothesized and found that more graphic pictorial warning depictions strengthen smokers’ 

intentions to quit smoking and that this effect was mediated by fear. 

7. Hibbard, J.H. and Peters, E. (2003). Supporting informed consumer health care choices: Data 

presentation approaches that facilitate the use of information in choice. Annual Review of Public 

Health, 24, 413-433. This paper reviews barriers to effective consumer use of information in 

choice as well as evidence for the efficacy of different presentation strategies to propose an 

initial framework concerning how to present information to support consumer choice. 

8. Peters, E., Dieckmann, N.F., Västfjäll, D., Mertz, C.K., Slovic, P., and Hibbard, J. (2009). Bringing 

meaning to numbers: The impact of evaluative categories on decisions. Journal of Experimental 

Psychology: Applied, 15, 3, 213–227. The authors present evidence that decision makers are 

quite poor in using numeric information in choice, but that adding evaluative meaning to the 

numbers facilitates that use. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 97
	

9. Zikmund-Fisher, B.J., Fagerlin, A. and Ubel, P.A. (2010). Risky feelings: Why a 6% risk of cancer 

does not always feel like 6%. Patient Education and Counseling, 81(Suppl. 1), S87-S93. The 

authors review evidence that emotions are often more influential in health decision making 

(particularly due to risk comparisons) than is factual knowledge. 

Endnotes

1 Fischhoff, B., Slovic, P., Lichtenstein, S., Reid, S., and Coombs, B. (1978). How safe is safe enough? 

A psychometric study of attitudes towards technological risks and benefits. Policy Sciences, 9, 

127-152. 

2 Slovic, P., Fischhoff, B., & Lichtenstein, S. (1979). Rating the risks. Environment, 21(3), 14-20, 36-

39. 

3 Epstein, R.M. and Peters, E. (2009). Beyond information: Exploring patients’ preferences. JAMA, 

302(2), 195-197. 

4 Damasio, A. R. (1994). Descartes’ error: Emotion, Reason, and the Human Brain. New York: Avon. 

5 Finucane, M. L., Alhakami, A., Slovic, P., and Johnson, S. M. (2000). The affect heuristic in 

judgments of risks and benefits. Journal of Behavioral Decision Making, 13, 1-17. 

6 Slovic, P., Peters, E., Finucane, M. L., and MacGregor, D. G. (2005). Affect, risk, and decision 

making. Health Psychology, 24, S35-40. 

7 Loewenstein, G. F., Weber, E. U., Hsee, C. K., and Welch, E. S. (2001). Risk as feelings. Psychological 

Bulletin, 127, 267-286. 

8 Lerner, J. S., Keltner, D. (2000). Beyond valence: Toward a model of emotion-specific influences on 

judgment and choice. Cognition & Emotion, 14, 473-493. 

9 Lerner, J. S., Keltner, D. (2001). Fear, anger, and risk. Journal of Personality and Social Psychology, 

81, 146-159. 

10 Alhakami, A. S., and Slovic, P. (1994). A psychological study of the inverse relationship between 

perceived risk and perceived benefit. Risk Analysis, 14, 1085–1096. 

11 Slovic, P., Peters, E., Grana, J., Berger, S., and Dieck, G. (2007). Risk perception of prescription 

drugs: Results of a national survey. Drug Information Journal, 41, 81-100. 

12 Peters, E. (2006). The functions of affect in the construction of preferences. In S. Lichtenstein & 

P. Slovic (Eds.), The Construction of Preference. (pp. 454-463). New York: Cambridge University 

Press. 

13 Peters, E., Lipkus, I., and Diefenbach, M. (2006). The functions of affect in health communication 

and in the construction of health preferences. Journal of Communication, 56, S140-S162. 

14 Johnson, E. J., and Tversky, A. (1983). Affect, generalization, and the perception of risk. Journal of 

Personality and Social Psychology, 45, 20–31. 

15 Peters, E., Burraston, B., and Mertz, C.K. (2004). An emotion-based model of stigma 

susceptibility: Appraisals, affective reactivity, and worldviews in the generation of a stigma 

response. Risk Analysis, 24, 1349-1367. 

16 Peters, E., Slovic, P., Hibbard, J.H., and Tusler, M. (2006). Why worry? Worry, risk perceptions, 

and willingness to act to reduce medical errors. Health Psychology, 25, 144-152. 

17 Dieckmann, N.F., Slovic, P., and Peters, E. (2009). The use of narrative evidence and explicit 

probability by decision makers varying in numeracy. Risk Analysis, 29, 1473-1488. 

18 Lipkus, I. M., Peters, E., Kimmick, G., Liotcheva, V., & Marcom, P. (2010). Breast cancer patients’ 

treatment expectations after exposure to the decision aid program, Adjuvant Online: The 

influence of numeracy. Medical Decision Making, 30, 464-473. 

19 Peters, E., Hess, T.M., Västfjäll, D., and Auman, C. (2007). Adult age differences in dual 

information processes: Implications for the role of affective and deliberative processes in older 

adults’ decision making. Perspectives on Psychological Science, 2, 1-23. 
 

 

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20 Peters, E., Hibbard, J.H., Slovic, P., and Dieckmann, N.F. (2007). Numeracy skill and the 

communication, comprehension, and use of risk and benefit information. Health Affairs, 26, 

741-748. 

21 Fagerlin, A., Zikmund-Fisher, B. J., and Ubel, P. A. (2005). How making a risk estimate can change 

the feel of that risk: Shifting attitudes toward breast cancer risk in a general public survey. Patient 

Education and Counseling, 57, 294-299. 

22 Rottenstreich, Y., and Hsee, C. K. (2001). Money, kisses, and electric shocks: On the affective 

psychology of risk. Psychological Science, 12, 185–190. 

23 Klein, W. M. P., Zajac, L. E., and Monin, M. M. (2009). Worry as a moderator of the association 

between risk perceptions and quitting intentions in young adult and adult smokers. Annals of 

Behavioral Medicine, 38, 256-261. 

24 Slovic, P., Monahan, J., and MacGregor, D. M. (2000). Violence risk assessment and risk 

communication: The effects of using actual cases, providing instructions, and employing 

probability vs. frequency formats. Law and Human Behavior, 24(3), 271-296. 

25 Peters, E., Hart, S., and Fraenkel, L. (2011). Informing patients: The influence of numeracy, framing, 

and format of side-effect information on risk perceptions. Medical Decision Making, 31(3), 432-436. 

26 Reyna, V.F. and Brainerd, C.J. (2008). Numeracy, ratio bias, and denominator neglect in 

judgments of risk and probability. Learning and Individual Differences, 18(1), 89-107. 

27 Diefenbach, M. A., Miller, S. M., and Daly, M. (1999). Specific worry about breast cancer predicts 

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532–536. 

28 McCaul, K. D., Schroeder, D. M., and Reid, P. A. (1996). Breast cancer worry and screening: Some 

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29 McCaul, K. D., Branstetter, A. D., Schroeder, D. M., and Glasgow, R. E. (1996). What is the 

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30 Ellsworth, P. C., and Scherer, K. R. (2003). Appraisal processes in emotion. In R. J. Davidson, K. R. 

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31 Smith, C. A., and Ellsworth, P. C. (1985). Patterns of cognitive appraisal in emotion. Journal of 

Personality and Social Psychology, 48, 813-38. 

32 Loewenstein, G. and Lerner, J. S. (2003). The role of affect in decision making. In R. Davidson, 

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33 Lerner, J. S., Gonzalez, R. M., Small, D. A., and Fischhoff, B. (2003). Effects of fear and anger on 

perceived risks of terrorism: A national field experiment. Psychological Science, 14, 144-50. 

34 Nabi, R. L. (2003). Exploring the framing effects of emotion: Do discrete emotions differentially 

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Research, 30, 224–247. 

35 Hsee, C. K., and Rottenstreich, Y. (2004). Music, pandas, and muggers: On the affective psychology 

of value. Journal of Experimental Psychology: General, 133, 23-30. 

36 Peters, E. and Slovic, P. (2007). Affective asynchrony and the measurement of the affective 

attitude component. Cognition and Emotion, 21, 300-329. 

37 Wilson, T. D., Lisle, D. J., Schooler, J. W., Hodges, S. D., Klaaren, K. J., & LaFleur, S. J. (1993). 

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38 Mather, M., and Knight, M. (2005). Goal-directed memory: The role of cognitive control in older 

adults’ emotional memory. Psychology and Aging, 20, 554-70. 
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39 Hibbard, J.H. and Peters, E. (2003). Supporting informed consumer health care choices: Data 

presentation approaches that facilitate the use of information in choice. Annual Review of Public 

Health, 24, 413-433. 

40 Peters, E., Dieckmann, N.F., Västfjäll, D., Mertz, C.K., Slovic, P., and Hibbard, J. (2009). Bringing 

meaning to numbers: The impact of evaluative categories on decisions. Journal of Experimental 

Psychology: Applied, 15, 213–227. 

41 Rivers, S.E., Reyna, V.F. and Mills, B. (2008). Risk taking under the influence: A Fuzzy-Trace theory 

of emotion in adolescence. Developmental Review, 28(1), 107–144. 

42 Hammond, D., Fong, G. T., McDonald, P. W., Brown, K.S., and Cameron, R. (2004). Graphic 

Canadian cigarette warning labels and adverse outcomes: Evidence from Canadian smokers. 

American Journal of Public Health, 94, 1442-1445. 

43 Witte, K. & Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public 

health campaigns. Health Education & Behavior, 27, 591-615. 

44 Bradley, M. M., and Lang, P. J. (1994). Measuring emotion: The Self-Assessment Manikin and the 

semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25, 49-59. 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 101
	

Chapter 11: Information and Persuasion

Mary Brown, PhD - University of Arizona
	

Christine M. Bruhn, PhD - University of California, Davis
	

Summary

Research on informative and persuasive communication shows that many 

well-known health behavior change theories and other research can help 

practitioners create, disseminate, and evaluate effective health messages. 

Characteristics of the message, the sender, recipients, channel, and situation 

can affect how audiences respond. Evaluation is essential to measure success 

and should be based on the message purpose and the resources available. 

Introduction

People make many decisions daily that affect their health, usually with a 

degree of uncertainty about what is the best course of action. The public health 

information role of government agencies like FDA is to provide the public with 

the factual information they need, in a timely, appropriate way, to understand 

issues of concern and to make informed decisions about their health. The 

primary goal of public health communication is to engage, inform, and educate 

the audience, thereby equipping them to take actions that promote their 

health. The intended outcomes often involve changes in health behavior that 

well-informed persons would make. In this way public health communication 

can be both informative and persuasive. With this dual role of informing 

and influencing behavior in mind, in this chapter we present an overview of 

research and recommendations about effective public communication that 

aims to protect or promote public health. 

What does the science say about this aspect of communication?

Communication researchers agree that the message a communicator intends 

to convey is never exactly the same message that the recipient receives. 

Research has shown that multiple factors, both internal and external, can 

affect whether communication succeeds in achieving its purpose, including, 

for example, the skill and credibility of the communicator, the suitability of 

the message, the way in which the message is delivered, the receptivity of the 

audience, and distractions in the environment. Because of the influence of such 

factors the intended outcome of a public health message often varies from 
 

102 | Chapter 11: Information and Persuasion
	

the actual outcome. Given the many potential obstacles, how can we achieve 

outcomes that are closer to our intentions as public health communicators? 

Many theories that concern the effects of informative and persuasive 

messages on target audiences are considered touchstones in the field of health 

communication. These theories originate from many fields, such as social 

psychology, communication, and advertising. They concern how aspects of the 

sender, the message, the channel, the receiver, and the environment affect 

knowledge, attitudes, and behavior of the intended audience. Descriptions 

of major theories, their strengths and weaknesses, and related research can 

be found in recent texts.1,2 These theories have been tested individually and 

supported by correlational, experimental, quasi-experimental and survey 

research, but randomized controlled studies are rare. And since there are few 

studies that directly compare these theories against each other, we don’t yet 

have strong empirical data on which ones are better in different situations. 

Aside from theory-based research, many factors have been shown to 

contribute to changes in audience knowledge, attitudes, and behavior. Much 

of this research has been in the area of persuasion. Following are noteworthy 

findings for public health professionals. 

Communicator factors. Whether the message sender is a person or an 

organization, the source can affect how audiences interpret and respond to 

messages. Evidence suggests that an audience is most likely to believe sources 

that they perceive to be credible (expert, trustworthy, and concerned about 

the audience’s interests), likeable, appealing, and similar to them. Credibility 

and likeability appear to have the strongest impact on an audience. Credibility 

is influential when it is established before the message is given. Generally, the 

credibility and attractiveness of the communicator have more influence on 

receivers who are not highly involved with the issue.3

 Culturally appropriate 

messages tend to be more accepted by their intended audience. 

Message factors. Many aspects of the message have been shown to affect 

audience outcomes. Written messages are helpful when the information 

is difficult to understand. In contrast, live, interactive, or video messages 

are often more effective when content is simple.4 In written materials, 

illustrations such as cartoons, charts and pictographs labeled with numbers aid 

understanding.5-7 Reductions in risk tend to be more persuasive when they are 

presented in relative terms rather than in absolute terms.8 

Words affect audience perceptions and responses. Labels, euphemisms, 

and language familiarity, vividness, and intensity can influence how receivers 

react to messages.3 Information describing what can be gained by changing 

health behavior is more persuasive than describing what can be lost.10 Written 

information can improve knowledge, but the evidence is generally not strong 

enough to say whether written information is effective in changing attitudes 

and behaviors related to taking medicines.9 Messages that present two sides 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 103
	

of an argument and refute the opposing side are more effective than one-sided 

messages.4

 Finally, repetition with variation and consistent reinforcement 

increase the effectiveness of messages.10,11 

Receiver factors. To be affected by a message, a person must not only pay 

attention to it, but understand it. Receivers’ responses to messages may occur 

through arousal of emotion and/or through careful consideration. Evidence 

suggests that when the audience is distracted or not highly interested in the 

topic, they are likely to process the information superficially. If a message is 

not relevant or appealing, they may ignore it altogether.12 In contrast, people 

who are highly involved with the topic are more likely to pay attention to detail, 

remember the message longer, evaluate the message more completely, and act 

upon the message.13 

People who are confident in their ability to perform a recommended action 

(high in self-efficacy) and believe that a recommendation will be effective are 

more likely to respond to messages about health threats.14 Recall of medical 

information is often inaccurate, especially when the patient is old or anxious. 

Messages that use warnings or other fear appeals can be more effective with 

older adults or with youth and young adults, depending on the subject and 

situation. In addition to age, several other demographic variables may affect 

how public health messages affect receivers. Common variables include gender, 

cultural background, ethnicity, literacy, primary language, and education level. 

Channel factors. Properties of the channel or medium (e.g., Internet, TV, 

radio, social media, written materials) can influence the effects of messages. 

Different communication channels serve as primary health information sources 

for different population segments. People who are health conscious and 

health-oriented use communication channels that involve active seeking and 

processing of information, such as print media (e.g., newspapers, magazines), 

Internet and interpersonal networks, as primary sources for health information. 

In contrast, people who are not health oriented tend to use passive 

consumption channels such as TV and radio as primary sources of health 

information.15 The Internet is a particularly effective channel for tailoring 

messages to the needs of individual consumers. A majority of Americans go 

to the Internet first for health information, rather than to a practitioner,16 

and new web-based applications are making the Internet and social networks 

increasingly more accessible, user-friendly, and personalized channels for 

health messages. Television is still the primary source of information on food 

safety and many other health topics, and television and radio have wider reach, 

serving larger, more diverse audiences than other media. However use of the 

Internet for health messages, such as the CDC’s use of social media in the H1N1 

campaign, is rapidly increasing. The Internet is considered a more credible 

source than television. Family and friends are also frequently used and credible 

information sources.17 
104 | Chapter 11: Information and Persuasion
	

Health information in mass media may result in changes in the use of health 

services and health care interventions, both through planned campaigns and 

unplanned coverage. However, how long these effects last is uncertain due to a 

lack of studies with adequate follow-up.18 

Environmental factors. Both physical and social environments play an 

important role in personal health decisions and can influence how audiences 

respond to health messages. Social norms and pressure to conform, as well 

as external stressors, competing messages and physical barriers, can diminish 

message impact. For example, moderate to strong environmental distractions 

reduce the comprehension and effectiveness of educational or persuasive 

messages.4 

Translating research findings into real-life practices can be problematic 

because studies have been conducted in a variety of settings using different 

designs and outcome measures. Furthermore, real-world circumstances, 

audiences, and conditions occur in unique combinations that can result in 

outcomes that differ from research findings. Although the research does not 

translate cleanly into practice, the consistency of evidence across settings 

enables us to offer several general recommendations. 

What general practical advice can the science support?

Understand the problem, the audience, and the situation to determine 

how best to design and deliver the message. First, thoroughly research 

the problem of concern and clearly define it. Understanding the nature 

of the problem is vital to the success of the message.19 Assess audience 

understanding of an issue, the information they want to receive, and the 

way they want to receive it. Include members of the target audience when 

developing the message. Adapt the message to their needs, preferences, 

values, and circumstances. For example, information needs of people with very 

serious chronic conditions, such as life-threatening allergies and blood clots, 

were assessed through personal interviews and or focus groups. The resulting 

educational materials were evaluated by the target audience and made 

available as pdf files for patients and/or physicians through free internet access 

or continuing medical education.20,21 

Behavior is more likely to change if people understand the reason for the 

change and it fits within their existing practices. For example, to improve 

safe handling of fresh produce to reduce the likelihood of food-borne illness, 

a nationwide survey identified current practices, and consumer research 

determined what people were currently doing, what they were willing to do, 

and how they wanted to receive information. Based on this information, a flyer 

was developed and refined with the target audience.22 See Hoffman et al., for 

the application of a food safety message model to special audiences.23 
 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 105
	

Design the message that is most likely to succeed in the given situation 

with the intended audience. Based on the identified problem, set a goal 

for the message with a clear endpoint. Establishing the intended outcome 

guides planning and measures of success. Evaluation of the message should be 

included in the planning process.19 Examples of outcome measures include 

reductions in adverse drug events or rates of food-borne illness. 

We encourage practitioners to review the literature and use appropriate 

health behavior change theories in designing and evaluating public health 

messages. Select theories based on evidence supporting their suitability for the 

purpose, the situation and the intended audience.24 

Health messages should be tailored to their audience to enhance their selfefficacy and overcome barriers to self-efficacy.14 Therefore, include specific 

recommendations for avoiding potential risks and provide reassurances that 

following these recommendations will control or reduce potential harm. 

Communicators should consider using pictographs labeled with numbers to 

communicate risk and benefit information to patients of different numeracy 

levels.25 Even people with a high level of literacy prefer material that is easy 

to read. People ask that text be kept to a minimum, important points be 

bolded, and pictures used to illustrate recommended practices.20,22 Clear 

communication techniques are especially recommended for people with low 

health literacy. These techniques include only giving advice that is immediately 

essential, dividing information into easy-to-understand parts, using bullets and 

summaries of important information, using active voice and conversational 

style, using culturally appropriate content, using ample margins and white 

space, and using a minimum 12-point font size.26 

Pretest the message before sending it. Research shows that outcomes are 

more likely to succeed when targeted recipients are involved in the design 

and dissemination of health communication.16 Involving the community can 

be especially effective when cultural values are recognized. A good example 

is the grandmother project. Hispanic families were experiencing a high rate of 

miscarriages due to listeriosis which was traced to illegal cheese manufacturer. 

Rather than advising Hispanic families not to buy traditional cheese from out 

of market vendors, the Cooperative Extension educators worked with the 

Hispanic community to develop safe ways to make traditional cheese. Rather 

than external groups prohibiting traditional cheese use, Hispanic grandmothers 

encouraged eating safe cheese to protect family health.27 

Decide on the best channel to deliver the message. Base the choice of 

communication channels on a thorough audience analysis, matching channels 

to media preferences of the audience. However, be careful not to exclude 

important audience segments. As Neuhauser and Kreps state, “If we overlook 

barriers of literacy, language, culture, and disability, we are likely to miss our 

goal of improving health for all.28 Often the best approach is to repeat health 
 

106 | Chapter 11: Information and Persuasion
	

messages using several different channels because different people use and 

prefer different channels.29 Multiple channels also increase the possibility 

that opinion leaders, friends and family members will relay media messages to 

others.30 

Monitor to determine the success of the message and use knowledge 

gained to improve subsequent messages. Determining if a message is 

heard, believed, and acted on is a critical part of all communication systems. 

Monitoring is important not only for assessing message effectiveness, but for 

modifying subsequent communications to better achieve their goal with the 

intended audience. Individual interviews or focus groups can provide insight as 

to the relevance of a message and why or why not a message has been acted 

on. This information can be used to revise or adjust the content and delivery 

medium. Several good resources for using these recommendations and for 

evaluating messages are available in the Additional Resources list. 

How does one evaluate communications implementing this advice?

Health messages in the mass media should be evaluated in the context of 

an overall planning and evaluation model that specifies goals, objectives, and 

indicators of success prior to sending the message. When possible, evaluation 

should include measures of process (was the message delivered as intended?), 

reach (what proportion of the targeted recipients did the message theoretically 

reach?), exposure (how many of the targeted recipients actually received and 

remembered the message?), and impact or outcome (what effects — intended 

and unintended — did the message have?).19,31 A variety of methods can be 

used, depending on the message purpose and the resources available.32,33 

Minimum budget. Assess whatever is feasible and affordable. Ask qualified 

in-house and external colleagues to evaluate messages or materials prior 

to widespread distribution. Assess impact by using surveys or focus groups 

of accessible volunteers who are similar to the target audience in regard to 

resources, interest, and literacy. Partner with interested academics who can 

help with program evaluation and service, professional or school groups who 

can help defray evaluation costs. Track easy-to-obtain indicators of reach and 

exposure, such as web hits, Internet-based media coverage, and local man-onthe-street interviews. Collect audience responses via short online interviews 

using free survey programs such as Surveymonkey. 

Modest budget. The above measures can be expanded or enhanced, 

including providing compensation for volunteers’ time and collecting data 

from more sources such as Internet news; TV and radio coverage; and relevant 

social media activity. In some cases, public uptake of messages can be tracked 

through their use in entertainment programming. In addition, use a simple and 

inexpensive evaluation design such as a pretest-posttest design or a post-test 

only design including a retrospective pretest. These survey-based approaches 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 107
	

can assess changes in self-reported knowledge, attitudes and behavior in the 

intended recipients. 

Unlimited budget. A comprehensive evaluation approach can be used 

that incorporates strong evaluation designs to provide sound evidence 

of effectiveness, such as a randomized controlled trial or a time series 

(longitudinal) design with a control or comparison group. Multiple measures 

can be used, such as observation, validated self-report measures, and 

appropriate biomedical data to assess outcomes.34 Although personal reports 

and observation can indicate if people are applying the communication, 

changes in medical indicators are the most definitive gauge of success. In the 

Hispanic cheese scenario, for example, rates of listeriosis and incidence of 

miscarriage decreased while the project was on-going. 

Conclusions

There has been a great deal of research on the effects of informative and 

persuasive communication about health. However, the available evidence 

is not sufficient to recommend clear best practices. The literature generally 

lacks direct comparisons of different approaches using randomized controlled 

studies, and the use of different outcome measures in different domains makes 

conclusions difficult. However, as the editors of this book have stated, we 

have accumulated enough evidence and experience to make good guesses at 

best general practices for communicating useful informative messages to help 

the public make informed decisions about their health. This chapter provides 

a brief overview of these good guesses. We encourage readers to consult the 

resources and references in this chapter for more detailed information. 

Additional resources 

1. U.S. Department of Health and Human Services, National Institutes of Health, National Cancer 

Institute: Making Health Communication Programs Work. Available online at http://www. 

cancer.gov/cancertopics/cancerlibrary/pinkbook/page1. A free, practical step-by-step guide for 

planning, implementing and evaluating health communication programs. 

2. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. 

Office of the Director, Office of Strategy and Innovation. (2005). Introduction to program 

evaluation for public health programs: A self-study guide. Atlanta, GA: Centers for Disease 

Control and Prevention. A free “how to” manual for planning and implementing evaluation 

activities that includes helpful worksheets from the CDC. Available online at http://www.cdc.gov/ 

eval/evalguide.pdf. 

3. K. Witte, G. Meyer, and D. P. Martell. (2001). Effective Health Risk Messages: A Step-By-Step 

Guide. Thousand Oaks, CA: Sage Publications. A practical guide with step-by-step instructions 

and worksheets for developing theoretically-based campaigns. 

4. Maibach, E. W. and Parrot, R. L. (Eds.). (1995). Designing Health Messages: Approaches from 

Communication Theory and Public Health Practice. Thousand Oaks, CA: Sage Publications. A 

text and reference book with chapters from recognized authorities, providing practical advice for 

designing theory-based, audience-centered health messages. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

108 | Chapter 11: Information and Persuasion
	

5. McKenzie, J. F., Neiger, B. L., and Thackeray, R. (2009). Planning, Implementing, and Evaluating 

Health Promotion Programs: A Primer (5th Ed.). San Francisco, CA: Benjamin Cummings/Pearson. 

A comprehensive, unified overview of the practical and theoretical skills needed to plan, 

implement, and evaluate health promotion programs. 

6. Eagleson, R. D., Jones, G. and Hassall, S. (1997). Writing in Plain English. Australian Government 

Publishing Service. A helpful step-by-step guide to planning, writing, designing and testing 

documents developed for public servants. 

7. Centers for Medicare & Medicaid Services. (2010). Toolkit for Making Written Material Clear and 

Effective. Available at https://www.cms.gov/WrittenMaterialsToolkit/. This online health literacy 

resource is a comprehensive set of tools to help make written material in printed formats easier 

for people to read, understand, and use. 

Endnotes

1 Glanz, K., Rimer, B. K. and Viswanath, K. (Eds.). (2008). Health Behavior and Health Education (4th 

Ed.). San Francisco: Jossey-Bass. 

2 DiClemente, R. J., Crosby, R. A., & Kegler, M. (Eds.) (2009). Emerging Theories in Health Promotion 

Practice and Research (2nd Ed.). San Francisco: Jossey-Bass. 

3 Gass, R. H. & Seiter, J. S. (2010). Persuasion, Social Influence and Compliance Gaining (4th Ed.). 

Boston: Allyn & Bacon. 

4 Stiff, J. B., & Mongeau, P. A. (2003). Persuasive Communication (2nd Ed.). New York: Guilford Press. 

5 Trevena, L. J., Davey, H. M., Barratt, A., Butow, P., Caldwell, P. (2006). A systematic review on 

communicating with patients about evidence. Journal of Evaluation in Clinical Practice,12, 13–23. 

6 Houts, P. S., Doak, C. C., Doak, L. G. and Loscalzo, M. J. (2006). The role of pictures in improving 

health communication: A review of research on attention, comprehension, recall, and adherence. 

Patient Education and Counseling, 61(2), 173-190. 

7 Akl, E. A., Oxman, A. D., Herrin, J., Vist, G. E., Terrenato, I., Sperati, F., Costiniuk, C., Blank, 

D., Schünemann, H. (2010). Using alternative statistical formats for presenting risks and risk 

reductions. Cochrane Database of Systematic Reviews, Issue 3. CD006776. 

8 O’Keefe, D. J. and Jensen, J. D. (2007). The relative persuasiveness of gain-framed and loss framed 

messages for encouraging disease prevention behaviors: A meta-analytic review. Journal of 

Health Communication, 12, 623–44. 

9 Nicolson, D., Knapp, P., Raynor, D.K., and Spoor, P. (2009). Written information about individual 

medicines for consumers. Cochrane Database Systematic Review, Apr. 15(2). CD002104. 

10 Moons, W. G., Mackie, D. M., and Garcia-Marques, T. (2009). The impact of repetition-induced 

familiarity on agreement with weak and strong arguments. Journal of Personality and Social 

Psychology, 96(1), 32-44. 

11 Changjo, Y., Hae-Kyong, B., and Youngchan, K. (2009). The effects of a consistent ad series on 

consumer evaluations. International Journal of Advertising, 28(1), 105-123. 

12 Petty, R. E., and Cacioppo, J. T. (1986). Communication and Persuasion: Central and Peripheral 

Routes to Attitude Change. New York: Springer. 

13 Petty, T. and Cacioppo, J. T. (1981). Attitudes and Persuasion: Classic and Contemporary 

Approaches. Dubuque, IA: Wm. C. Brown. 

14 Murray-Johnson, L. and Witte, K. (2003). Looking toward the future: Health message design 

strategies. In T. L. Thompson, A. M. Dorsey, K. I. Miller & R. Parrot (Eds.), Handbook of Health 

Communication (pp. 473-495). Mahwah, NJ: Lawrence Erlbaum Associates. 

15 Dutta-Bergman, M. (2004). Primary sources of health information: Comparisons in the domain of 

health attitudes, health cognitions, and health behaviors. Health Communication, 16(3), 273-288. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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16 Hesse, B.W., and B. Shneiderman. (2007). eHealth research from the user’s perspective. American 

Journal of Preventive Medicine 32, S97-103. 

17 Food Marketing Institute. (2009). Grocery Shopper Trends 2009: Arlington VA. 

18 Grilli, R., Ramsay, C. and Minozzi, S. (2002). Mass media interventions: Effects on health services 

utilization. Cochrane Database of Systematic Reviews, Issue 1, Art. No. CD000389. 

19 McKenzie, J.F., Neiger, B. L., and Thackeray, R. (2009). Planning, Implementing, and Evaluating 

Health Promotion Programs: A Primer (5th Ed.). Benjamin Cummings/Pearson: San Francisco, CA. 

20 Olson, B., Teuber, S. and Bruhn, C. M. (2009). Development of an educational packet for persons 

with life threatening food allergies. Journal of Food Science Education, 8, 73-77. 

21 Visit http://www.azcert.org/consumers/warfarinpatients.cfm to view educational materials for 

patients taking warfarin in English and Spanish. 

22 Li-Cohen, A.E., Klenk, M., Nicholson, Y., Harwood, J. and Bruhn, C. M. (2002). Refining consumer 

safe handling educational materials through focus groups. Dairy, Food and Environmental 

Sanitation 22(7), 539-551. 

23 Hoffman, E.W., Bergmann, V., Shultz, J. A., Kendall, P. A., Medeiros, L., and Hillers, V. N. (2005). 

Application of a five-step message development model for food safety educational materials 

targeting people with HIV/AIDS. Journal of the American Dietetic Association,105,1597-1604. 

24 Brewer, N. T. and Rimer, B. K. (2008). Perspectives on health behavior theories that focus on 

individuals. In K. Glanz, B. K. Rimer and K. Viswanath (Eds), Health Behavior and Health Education 

(4th ed, pp. 149-165). San Francisco: Jossey-Bass. 

25 S.T. Hawley, S.T., Zikmund-Fisher, B., Ubel, P., Jancovic, A., Lucas, T. and Fagerlin, A. (2008) 

The impact of the format of graphical presentation on health-related knowledge and treatment 

choices. Patient Education and Counseling,73(3), 448-455. 

26 Root, J., and Stableford, S. (1999). Easy-to-read consumer communications: A missing link in 

Medicaid managed care. Journal of Health Politics, Policy and Law, 24, 1-26. 

27 Hillers, V. (2001). The abuela project: A community based food safety intervention. Available at 

http://www.foodsafety.wsu.edu/consumers/factsheet.htm. Assessed May 10, 2011. 

28 Neuhauser, L. and Kreps, G. L. (2010). eHealth communication and behavior change: Promise and 

performance. Social Semiotics, 20(1), 9-27. 

29 Du Pre, A. (2009). Communicating About Health: Current Issues and Perspectives (3rd Ed.). Oxford 

University Press. 

30 Rogers, E. M. (1995). Diffusion of Innovations (4th Ed.). New York: Free Press. 

31 Schooler, C., Chafee, S. H., Flora, J. A. and Roser, C. (1998). Health campaign channels: Tradeoffs 

among reach, specificity, and impact. Health Communication Research, 24, 410-432. 

32 Windsor, R.W., Baranowski, T. B., Clark, N. C., and Cutter, G. C. (1994). Evaluation of Health 

Promotion, Health Education and Disease Prevention Programs (2nd Ed.). Mountain View, CA: 

Mayfield. 

33 Rossi, P. H., Lipsey, M. W., and Freeman, H. E. (2004). Evaluation: A Systematic Approach. 

Thousand Oaks, CA: Sage Publications. 

34 Pechmann, C. and Andrews, J. C. (2010). Methodological issues and challenges in conducting 

social impact evaluations. In P. N. Bloom & E. Skloot (Eds.), Scaling Social Impact: New Thinking 

(pp. 219-250). New York: St. Martins Press. 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 111
	

Chapter 12: Across the Life Span

Valerie Reyna, PhD - Cornell University 

Summary

Risk communication messages bombard people, from cartoon characters 

promoting cigarettes to direct-to-consumer drug advertisements. Messages 

that have an impact are processed and remembered — cognitive abilities that 

change dramatically from childhood to old age. Overall, these abilities improve 

early in life, but then gradually decline. However, the ability to remember 

the gist (meaning) of information grows in childhood and remains strong in 

the healthy brain. Remembering the gist of information is important because 

it lasts longer and is relied on to make most decisions. Instilling the gist of a 

message should be the goal of risk communication, which can be assessed 

using tests of recall, recognition, and comprehension. 

Introduction

The audience for risk communications ranges from children to older adults. 

One might assume that, at the younger end of the age spectrum, children do 

not make risk–benefit decisions; adults make decisions for them. However, 

this assumption would be false. Minors make risky decisions with enormous 

consequences for public health, including decisions to consume products 

regulated by the FDA. 

For example, the FDA recently issued warnings to 25 Mississippi convenience 

stores to stop selling cigarettes to minors. Children influence family food 

purchases and make food choices at school (and those who buy, rather than 

bring, lunch are more likely to be obese).1

 Adolescents buy food for themselves 

and shop for their families, too. Children and adolescents also make decisions 

about drugs and about adherence to medical regimens. They may have to 

self-administer drugs (e.g., inject insulin) or adhere to dietary restrictions (e.g., 

refuse foods with peanuts or other allergens). 

Moreover, many adult attitudes about risks and benefits take root in 

childhood or adolescence (e.g., eating disorders, alcohol and drug use, and 

other risky behaviors).2,3 Risk communication begins early in life: 91% of 

six-year-olds recognized Old Joe, a cartoon character promoting cigarettes.4 In 

another study, four-year-olds preferred foods if they thought they were from 

a highly advertised fast-food chain.5

 Children and youth are among the most 
 

112 | Chapter 12: Across the Lifespan
	

vulnerable recipients of persuasive messages, despite efforts to limit their 

access to risky substances.6 

At the opposite end of the lifespan, older adults face a bewildering array 

of risky decisions. Older adults make risk–benefit decisions about diagnostic 

tests, medications, and surgical procedures, as well as retirement-related 

and other important financial decisions. National surveys suggest that older 

adults are less likely than other age groups to understand risk.7 Older adults 

are also more likely to be cognitively impaired, further compromising their 

comprehension of complex risks.8-10 To have an impact, risk communication 

must change what is being processed and remembered. 

Here, I briefly review age changes in memory and information processing 

relevant to risk communication. Those changes include variation in the speed 

of information processing; the capacity to bring information into temporary 

memory and maintain it (to encode it into working memory so that it can be 

thought about and acted on); and the ability to store and retain information 

in long-term memory for later use.11 I also discuss recent work distinguishing 

verbatim (exact memory for details) from gist (essential meaning) memories.12 

Remembering gist is important for risk communication because it lasts longer 

and forms the basis for decision making. 

What does the science say about these aspects of communication? 

People process information faster as they age from childhood through 

young adulthood, but then more slowly from young adulthood to old 

age.13,14 Children are less able to keep up with the pace of rapidly presented 

information than young adults are, and they take away less. Initial increases 

in speed of processing during childhood are ascribed to the development of 

myelination in the brain. Myelin is a fatty sheath that surrounds and insulates 

nerves, improving the conduction of nerve signals. In old age, conversely, 

demyelination occurs, along with other abnormities in white matter resulting 

from trauma and disease, which contributes to general slowing of processing. 

Sensory changes beginning in middle age, such as loss of hearing or visual 

acuity, can also contribute to slow motor response. Thus, the hardware of the 

brain changes across the lifespan in ways that affect information-processing 

speed, but not always the quality of responses (i.e., some responses can be 

slow but accurate). Speed affects accuracy when it limits the capacity of the 

temporary memory store or working memory. 

Like processing speed, analogous increases in childhood and decreases in 

adulthood are posited for working memory capacity. Working memory refers 

to the ability to maintain and manipulate information, as well as to selectively 

inhibit irrelevant information (also referred to as executive processes). Capacity 

per se is relatively constant during childhood, but speed of processing, 

resistance to interference, and chunking information into meaningful units 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 113
	

increases, augmenting functional capacity — the ability to hold and operate on 

information. 

Thus, children have difficulty maintaining information long enough to act on 

it by extracting meaning, solving problems, or drawing inferences. Younger 

children require more repetition of information (more opportunities to study) 

to achieve the same level of learning compared to older children or adults. 

Their rate of learning is slower: They learn less than older children do from the 

same presentations of information. 

Working memory is used immediately, but long-term memory stores 

information over days, weeks, or even years. Long-term recall (what were the 

side effects the doctor told me about?; which foods have calcium in them?) 

improves from childhood to adulthood and declines in adulthood. Recognition 

(was fever a side effect?; does spinach have calcium?) shows a similar 

trajectory, but is a less sensitive measure because questions provide items, 

resulting in better performance. The rate of change in long-term memory 

slows as children get older, so that differences between adolescents and young 

adults are subtle.15 Again, the upside-down U-shaped developmental curve is 

observed, with improvement in childhood followed by noticeable decline in old 

age. There are also individual differences in the decline of long-term memory: 

Education is a major protective factor for cognitive impairment. However, 

people with genetic markers, such as the ε4 allele of the APOE gene that 

predisposes some to Alzheimer’s disease, show declines in memory prior to 

disease onset, often in late middle age. 

The information-processing model of computer as mind stresses rote 

memory, including capacity of short-term buffers and accuracy of long-term 

stores. Although the computer metaphor of mind has been very useful, newer 

approaches, such as fuzzy-trace theory, emphasize the meaning of information, 

not just memorization of rote facts.16 Understanding information, as opposed 

to merely memorizing it, helps people retain and apply learning to new 

problems or situations. 

For example, Bransford and Franks found that new sentences that combined 

information — sentences that “connected the dots”— were “recognized” 

more often than presented sentences that did not integrate information.17 

Presented with sentences such as “The bird is in the cage” and “The cage is 

under the table,” people falsely recognize having heard the sentence “The 

bird is under the table.” Despite crucial constraints on this effect (instructions 

must specify that true but unpresented sentences should be rejected), the 

finding that memory emphasizes meaning has been upheld.18 That is, children 

and adults misremember the gist of presented information as having been 

presented (although they also retain verbatim memories to a surprising degree, 

contrary to Bransford & Franks,17 and other older studies). Told that the risk of 

dying during surgery is 2%, for instance, patients misremember the risk as zero 

if the meaning they infer is “no risk.”19 
 

 

 

114 | Chapter 12: Across the Lifespan
	

Older adults rely on gist (meaning-based memories) more than young adults 

do.20 Similarly, semantic knowledge, such as vocabulary, characterized as 

crystallized rather than fluid intelligence, remains stable during old age. As the 

labels “crystallized” and “fluid” imply, world knowledge may remain stable and 

even improve after about age 30.14 

It is important to separate effects of verbatim memory (which can be used to 

reject meaning-based lures* on a recognition test) from effects of gist memory 

(which can be used to wrongly accept meaning-based lures on a recognition 

test). Thus, increases in gist-based responding can be due to either decreases 

in verbatim memory or increased reliance on gist memory. The net effect of 

these two, independent parts of memory determine memory performance in 

the laboratory and in real life. 

Both verbatim and gist memories improve in childhood, with gist often 

improving more rapidly than verbatim memory.15 This pattern leads to greater 

meaning-based recognition and recall as children get older and, paradoxically, 

greater meaning-based memory errors (net lower accuracy, once guessing 

and other response biases are eliminated). Figure 1 illustrates this paradoxical 

pattern for recall of semantically related lists of words: Recall of presented 

words and intrusions of semantically related (but non-presented) words both 

increase in childhood and adolescence, but the latter gist-based intrusions 

increase more. (During adolescence, the ability to use gist effectively — to 

judge reconstructed gist to be familiar — goes up; Figure 2.) Hence, net 

accuracy actually goes down from childhood to adulthood, as shown by the 

convergence of the true and false recall lines in Figure 1. Discovered in 2002, 

this effect has been replicated in more than 50 studies.21,22

 Verbatim and gist memory decline reliably in old age, but verbatim 

memory declines more than gist. Memory for gist carries most of the load of 

remembering during old age, sustaining performance. Therefore, understand 

meaning is crucial for older adults. Transitions from healthy aging to memory 

impairment are marked by a decline in this backup system of gist-based 

memory.10 

Recall of word lists is the most often used neuropsychological assessment of 

memory impairment, and the most predictive single test of conversion from 

impairment to Alzheimer’s disease. Memory for word lists predicts memory for 

more complex and ecologically valid stimuli, too, such as narratives. Models 

that fit data for word lists also fit data for narratives, using the same concepts 

of verbatim and gist memory. Gist applies to the level of individual words or 

sentences as well as to semantic integrations across words or sentences, such 

as the theme of related words or inferences that integrate related sentences, 

*

Tempting, but wrong, answers. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 115
	

as well as to numbers and other kinds of meaningful information. Small 

numbers are understood early in life, but it is difficult to get the gist of ratio 

concepts such as probability or risk (e.g., 1 out of 8 women will develop breast 

cancer) even for many adults.23 

Many of the group differences that have been discussed in this chapter are 

summarized in Figure 2: Verbatim memory and both types of gist memory 

increase from childhood to young adulthood, and then they decline. Gist-based

familiarity judgment increases sharply from adolescence to adulthood. When 

gist memory estimates are combined, the paradoxical pattern from childhood 

to adulthood of greater growth in gist (compared to verbatim memory) is 

evident, as is the greater decline in verbatim memory (compared to gist) for 

Alzheimer’s patients. 

The last pair of groups on the right, of older adults and Alzheimer’s patients, 

was presented with materials that provided greater verbatim support 

(materials for all other pairs were similar to one another). As can be seen 

from the figure, older adults’ verbatim memory in that task can be as strong 

as younger adults’ verbatim memory in a harder task, illustrating that memory 

performance is not a fixed quantity. Instead, performance is a function of 

both task and ability. I now turn to the implications of these differences in 

information processing for risk communication. 

Children

AdolescentsAdolescents

Young Adults 

Younger Adults

Older Adults 

Older Adults

Alzheimer’s

0 

P

r

o

p

o

r

t

i

o

n

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.9 

0.8 

0.7 P 

a 

r 0.6 a 

m 

e 0.5 

t 

e 

r 0.4 

V 

a 0.3 

l 

u 

e 0.2 

0.1 

0

5 7 11 20

Ve rba �m Gist Gist Familiarity False Recall True Recall

Figure 1. Age-Related Increases in the

Proportion of True and Gist-Based “False” Recall

for Semantically Related Word Lists

Figure 2. Estimates of Verbatim Readout,

Gist Reconstruction, and Gist Familirity in

Recall of word Lists across Groups

Figure 2 shows results from recall tests for a list of unrelated words across the life span, including 

Alzheimer’s patients. Two groups are compared at a time (e.g., children to adolescents) regarding 

their memories for the same materials, averaging across studies (see Brainerd et al., 2009 for details).15 

Verbatim memory (exact recall of presented words) and two kinds of gist memory are depicted: The 

ability to reconstruct the gist meaning of presented words and the ability to judge reconstructed gist 

as sufficiently familiar to report it as a recalled item. Parameter values are empirical estimates of these 

abilities, using mathematical models tested for fit with recall data. 
 

116 | Chapter 12: Across the Lifespan
	

What general practical advice can the science support? 

Messages about risks and benefits are received from family, schooling, 

the media (e.g., from advertising), and other cultural influences and may be 

explicit or implicit (e.g., role modeling). In the laboratory, boundaries are 

drawn between cognitive, social, and emotional factors, but, in practice, these 

factors are intertwined.24 Social values and emotional reactions are often 

learned by processing cultural messages, and, conversely, information must be 

processed to elicit emotional reactions.25 In the preceding section, evidence 

was presented that how information is processed differs developmentally and 

across individuals. 

Consider the dictum to eat five or more vegetables per day, which is taught 

in schools and reported in the media. Elementary school-aged children can 

certainly count up to five and know the word vegetable. This message is 

more likely to be remembered by children if it is presented repeatedly, in 

small chunks of fewer than about five words (not long sentences) and at a 

slower pace: “Eat vegetables. Five vegetables every day. Eat five vegetables a 

day.” Pictures accompanying words are a form of repetition and can support 

memory. 

Note that verbatim repetition stamps in memories, but is unlikely to 

produce transfer or long-term retention of information. Cuing meaning 

(e.g., saying, “Vegetables make us strong. These are all vegetables” and then 

listing vegetables) can boost memory for gist or meaning in younger children 

and helps children connect the dots to new situations (raw carrots at home, 

cooked green beans in school lunches, etc.). Although these connections seem 

obvious to adults, young children can be quite literal. Also, children may be 

unable to carry out a series of instructions not because they are dumb, but 

simply because they cannot remember multiple steps. Breaking the steps 

down so that they can be executed one at a time, especially with repetition and 

reminders along the way, should improve adherence. 

As children get older, after about 11 years of age on average, verbatim 

repetition can give way to emphasizing the meaning of information. 

Environmental support for remembering verbatim information (e.g., oral or 

written reminders) remains useful at all ages as verbatim memory is evanescent 

and vulnerable to interference. However, older children and adolescents 

are more likely than younger children to integrate information, noticing 

semantic themes and drawing inferences that go beyond literal facts. (Even 

adolescents are not as readily able to spontaneously connect the dots as adults, 

for example, between actions and probable consequences despite knowing 

the consequences.) For example, older children will get the gist of a list such 

as “fries, taco, Coke, burger” (fast food or junk food) versus “apple, spinach, 

carrots, fish” (healthy food). Recognition of healthy foods is not sufficient 

for behavior change, but it can facilitate such change when accompanied by 

retrieval of relevant values in the context of behavior.12,26 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 117
	

Communications should be presented more slowly to older than younger 

adults, and their responses are likely be slowed. However, slower does not 

mean dumber; information should not be dumbed down for older adults. 

Despite general slowing and an inability to retain details, vocabulary and 

reading ability of older adults can remain high. Unlike children, despite lower 

levels of verbatim memory, older adults can rely on fairly high levels of gist 

familiarity. Therefore, for older adults, we can expect impairments in verbatim 

memory for detailed dietary instructions or in prospective memory for exact 

dosages or exact times of day to take medications. Written instructions, as well 

as alerts and reminders delivered electronically (e.g., to take medication or to 

signal that medication has already been taken) are likely to be helpful cognitive 

prosthetics because they support verbatim memory. 

Because of older adults’ conserved gist memory, it is also essential to 

explain the reasons for dietary recommendations or medications to them. 

Comprehension, or extraction of gist, is the main mechanism through which 

older adults remember information. Therefore, if they do not understand 

the meaning of information, they cannot fall back on rote recall as easily as 

younger adults can. Even patients with mild to moderate Alzheimer’s disease 

retain some ability to remember the gist of information. 

How does one evaluate communications implementing this advice?

Information must first be taken into memory to influence attitudes, values, 

or preferences, which, in turn, influence behavior. Therefore, memory tests 

can assess whether messages have been received, and if so, how they have 

been interpreted (or mentally represented). Use recall or recognition tests, not 

only to measure true or accurate memories, but to measure distortions in recall 

(intrusions) or false recognitions that reveal how the meaning of messages has 

been understood. Immediate memory tests are not sufficient, as transfer and 

long-term retention are more likely to shape behavior. Immediate memory 

performance cannot be assumed to reflect the same factors as long-term 

retention because verbatim memory is tapped more often on immediate tests 

but gist memory is tapped more often on delayed tests. 

Successful information processing should also lead to changes in attitudes, 

values clarification, and modification of preferences. Attitudes, values, and 

preferences are often assessed through verbal self-reports (or reports by 

others, such as family members). However, self-reports are subject to a 

variety of biases. In childhood, the ability to explain reasons for behaviors 

(i.e., to articulate attitudes or preferences) lags years behind the ability to 

demonstrate those attitudes or preferences. In adulthood, biases are more 

likely due to such factors as social desirability (e.g., underreporting weight). 

Thus, communications can be assessed behaviorally (e.g., by offering food 

choices and determining which options are chosen or weighing the amounts 

of particular types of food that are eaten in a controlled setting). Although 
118 | Chapter 12: Across the Lifespan
	

behavioral measures are ideal, they are not direct windows on the mind; 

self-reports do correlate with behavior, just not perfectly. Both self-reports 

and behaviors must be interpreted via theories of underlying mechanisms. 

Assessments should be designed based on theories grounded in experiments in 

which hypotheses have been tested. 

Although memory tests and attitude surveys can be administered relatively 

cheaply in the short term, long-term follow-up requires monetary incentives 

to combat attrition. Access to community samples of older adults is also 

expensive, and such subjects must be assessed for medical conditions (to 

obtain a “healthy” aged sample, isolating the effect of aging). Randomized 

assignment of people receiving different risk communications with pre-tests 

and post-tests, efforts to avoid cross-contamination, and proper statistical 

analysis remain the best methods for assessing effectiveness. Recall tests 

are more discriminating than recognition tests, but require scoring by hand 

(which is labor intensive, and therefore costly). Finally, assessing multiple 

levels of information processing, not simply acquisition of knowledge, but also 

extraction and transfer of meaning to situations that were not directly taught, 

requires extensive batteries of tests (i.e., costly multiple sessions). 

Additional resources

1. Bjorklund, D. (2012). Children’s thinking: Cognitive development and individual differences (5th 

Ed). Belmont, CA: Wadsworth/Thomson Learning. A compendium of evidence on children’s and 

adolescents’ memory and information processing, written by a respected researcher in the field. 

2. Drolet, A, Schwarz, N., and Yoon, C. (2010). The Aging Consumer: Perspectives from 

Psychology and Economics. New York: Routledge/Taylor Francis Group. An edited volume with 

contributions by leading experts on aging and information processing in real-world contexts. 

3. Fischhoff, B. (2008). Assessing adolescent decision-making competence. Developmental Review, 

28, 12–28. One of the greatest living social scientists summarizes applied research on behavioral 

decision making in adolescence. 

4. Finucane, M. L., Slovic, P., Hibbard, J., Peters, E., Mertz, C. K.,and MacGregor, D. G. (2002). Aging 

and decision-making competence: An analysis of comprehension and consistency skills in older 

versus younger adults considering health-plan options. Journal of Behavioral Decision Making, 

15, 141–164. An influential team summarizes their approach to decision competence in the aged 

in a health context. 

5. Haines, B.A., and Moore, C. (2003). Integrating themes from cognitive and social cognitive 

development into the study of judgment and decision making. In S.L. Schneider & J. Shanteau 

(Eds.), Emerging perspectives on judgment and decision research (pp. 246–286). New York: 

Cambridge University Press. Respected developmental researchers present an integrative review 

of children’s judgment and decision making. 

6. Institute of Medicine. (2010). The Science of Adolescent Risk-Taking. Workshop Summary. 

Committee on the Science of Adolescence. Washington, DC: The National Academies Press. An 

authoritative summary of research on brain and behavior related to adolescent risk taking by 

leading experts, focusing on mental and physical health. 

7. Jacobs, J. E., and Klaczynski, P. A. (Eds.). (2005). The Development of Judgment and Decision 

Making in Children and Adolescents. Mahwah, NJ: Erlbaum. A watershed volume summarizing 

contemporary theoretical and empirical approaches to the development of judgment and 

decision making. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 119
	

8. Mills, B., Reyna, V.F., and Estrada, S. (2008). Explaining contradictory relations between risk 

perception and risk taking. Psychological Science, 19, 429-33. Reports surprising but theoretically 

predictable findings on risk perception crucial for accurate measurement. 

9. Park, D. and Reuter-Lorenz, P. (2009). The adaptive brain: Aging and neurocognitive scaffolding. 

Annual Review of Psychology. 60:173–96. Comprehensive review by top experts on aging and the 

brain. 

10. Reyna, V.F., and Adam, M.B. (2003). Fuzzy-trace theory, risk communication and product 

labeling in sexually transmitted diseases. Risk Analysis, 23, 325-342. Reports research on 

differences among health experts in risk perception and communication and how labels are 

understood. 

11. Reyna, V.F., and Farley, F. (2006). Risk and rationality in adolescent decision making: 

Implications for theory, practice, and public policy. Psychological Science in the Public Interest, 

7, 1–44. A review of the literature on a wide range of risky decisions that affect teenagers, with 

over 200 references and a summary of leading explanations for risk taking. 

Endnotes

1 Schanzenbach, D. W. (2009). Do school lunches contribute to childhood obesity? Journal of Human 

Resources, 44, 684-709. 

2 Institute of Medicine. (2010). The Science of Adolescent Risk-Taking. Workshop Summary. 

Committee on the Science of Adolescence. Washington, DC: The National Academies Press. 

3 Reyna, V. F., & Farley, F. (2006). Risk and rationality in adolescent decision-making: Implications 

for theory, practice, and public policy. Psychological Science in the Public Interest, 7(1), 1-44. 

4 Fischer, P. M, Schwartz, M. P., Richards, J. W. Jr, Goldstein, A. O, & Rojas, T.H. (1991). Brand logo 

recognition by children aged 3 to 6 years. Mickey Mouse and Old Joe the Camel. Journal of the 

American Medical Association. 266, 3185-3186. 

5 Robinson, T. N., Borzekowski, D. L. G., Matheson, D., Kraemer, H. C. (2007). Effects of fast food 

branding on young children’s taste preferences. Archives of Pediatrics and Adolescent Medicine, 

161(8):792-797. 

6 Kunkel, D., Wilcox, B. L., Cantor, J., Palmer, E., Linn, S., & Dowrick, P. (2004). Report of the APA 

Task Force on Advertising and Children. Washington, DC: American Psychological Association. 

7 Reyna, V. F., & Brainerd, C. J. (2007). The importance of mathematics in health and human 

judgment: Numeracy, risk communication, and medical decision making. Learning and Individual 

Differences, 17 (2), 147-159. 

8 Brainerd, C. J., Reyna, V. F., Petersen, R. C., Smith, G. E., & Taub, E. S. (in press). Is the 

apolipoprotein E genotype a biomarker for mild cognitive impairment? Findings from a nationally 

representative study. In publication. 

9 Brewer, N. T., Salz, T., Lillie, S. E. (2007). Systematic review: The long-term effects of false-positive 

mammograms. Annals of Internal Medicine, 146, 502-510. 

10 Reyna, V. F., & Mills, B. A. (2007). Interference processes in fuzzy-trace theory: Aging, Alzheimer’s 

disease, and development. In C. MacLeod & D. Gorfein (Eds.), Inhibition in Cognition (pp. 185-

210). Washington: APA Press. 

11 Finucane, M. L., Mertz, C. K., Slovic, P., & Schmidt, E. S. (2005). Task complexity and older adults’ 

decision-making competence. Psychology and Aging, 20(1), 71-84. 

12 Reyna, V. F. (2008). Theories of medical decision making and health: Fuzzy-trace theory. Medical 

Decision Making, 28(6), 850-865. 

13 Drolet, A, Schwarz, N., & Yoon, C. (2010). The Aging Consumer: Perspectives from Psychology 

and Economics. New York: Routledge/Taylor Francis Group. 

14 Park, D. & Reuter-Lorenz, P. (2009). The adaptive brain: Aging and neurocognitive scaffolding. 

Annual Review of Psychology. 60:173–96. 
120 | Chapter 12: Across the Lifespan
	

15 Brainerd, C. J., Reyna, V. F., & Howe, M. L. (2009). Trichotomous processes in early memory 

development, aging, and neurocognitive impairment: A unified theory. Psychological Review, 116, 

783-832. 

16 Reyna, V. F. (2004). How people make decisions that involve risk: A dual process approach. 

Current Directions in Psychological Science, 13, 60-66. 

17 Bransford, J. D., & Franks, J. J. (1971). The abstraction of linguistic ideas. Cognitive Psychology, 2, 

331-350. 

18 Reyna, V. F., & Kiernan, B. (1994). The development of gist versus verbatim memory in sentence 

recognition: Effects of lexical familiarity, semantic content, encoding instruction, and retention 

interval. Developmental Psychology, 30, 178-191. 

19 Reyna, V. F., & Hamilton, A. J. (2001). The importance of memory in informed consent for surgical 

risk. Medical Decision Making, 21, 152-155. 

20 Koutstaal, W., & Schacter D. L. (1997). Gist-based false recognition of pictures in older and 

younger adults. Journal of Memory and Language, 37(4): 555–83. 

21 Brainerd, C. J., Reyna, V. F., & Forrest, T. J. (2002). Are young children susceptible to the falsememory illusion? Child Development, 73, 1363–1377. 

22 Brainerd, C. J., Reyna, V. F., & Zember, E. (2011). Theoretical and forensic implications of 

developmental studies of the DRM illusion. Memory and Cognition, 39, 365-380. 

23 Reyna, V. F., Nelson, W., Han, P., & Dieckmann, N. F. (2009). How numeracy influences risk 

comprehension and medical decision making. Psychological Bulletin, 135, 943-973. 

24 Fischhoff, B. (2008). Assessing adolescent decision-making competence. Developmental Review, 

28, 12–28. 

25 Reyna, V. F., & Rivers, S. E. (2008). Current theories of risk and rational decision making. 

Developmental Review, 28(1), 1-11. 

26 Fujita, K., & Han, H. A. (2009). Moving beyond deliberative control of impulses: The effects of 

construal levels on evaluative associations in self-control. Psychological Science, 20, 799-804. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 121
	

Chapter 13: Health Care Professionals

Betsy Sleath, PhD, RPh - University of North Carolina
	

Michael Goldstein, MD - Veterans Health Administration,
	

National Center for Health Promotion and Disease Prevention
	

Summary

This chapter reviews the existing literature on health care professional 

risk–benefit communication and offers advice to practitioners on how to 

better communicate the risks and benefits of medications, medical devices, 

and foods to patients. First, we present what the science says about health 

care professional risk–benefit communication. Next, we discuss what general 

practical advice the science can support. Finally, we give suggestions on how 

one might evaluate strategies used to improve risk–benefit communication by 

health care professionals. 

Introduction

In 2000, the Institute of Medicine published an influential report, Crossing 

the Quality Chasm, which specifies six characteristics that are essential for 

high-quality health care: patient-centered, safe, effective, timely, efficient, and 

equitable.1

 Each of these characteristics interacts with the others to influence 

quality. Thus, patient safety is linked to timely access to effective interventions. 

Patient safety is also related to effective patient-centered communications that 

help patients understand and respond to health care information, including 

information about the risks and benefits of medications, medical devices, and 

foods.1 

A substantial body of research links effective, patient-centered 

communication principles and a wide range of health outcomes, including 

symptom control, patient satisfaction and patient follow-through with 

treatment recommendations and health behavior change.2-7 However, 

we know relatively little about the impact of health professional–patient 

communication about risks and benefits on either patients’ understanding or 

their subsequent behavior. In this chapter, we will share what we do know 

about this aspect of risk communication and its implications for practitioners. 
122 | Chapter 13: Health Care Professionals
	

What does the science say about this aspect of communication? 

Physician–patient communication. According to Frosch and Kaplan, shared 

medical decision making (SDM) is a process by which patients and practitioners 

consider outcome probabilities and patient preferences, in the course of 

reaching health care decisions based on mutual agreement.8 Makoul and 

Clayman identify several essential elements of SDM: define and explain the 

problem, present options, discuss pros and cons (benefits/risks/costs), elicit 

patients’ values and preferences, discuss patient ability and self-efficacy, offer 

knowledge and recommendations, check and clarify patient understanding, 

make or explicitly defer a decision, and arrange follow-up.9 However, in studies 

that have examined actual professional–patient interactions, researchers 

find that health care professionals almost always fail to adequately educate 

patients and enlist them in a process that meets the criteria for fully informed 

decision making.10,11 For example, Braddock and colleagues’ study of 1057 

physician–patient encounters and 3552 decisions, including 893 that concerned 

medication use, found that that only 9% met their criteria for completeness 

of informed decision making. Moreover, only 8% of encounters included a 

discussion of risks and benefits, and only 1.5% included an assessment of the 

patient’s understanding of the information provided.10 

A few studies have specifically examined how physicians communicate the 

risks and benefits of medications during medical visits.12-14 Sleath and colleagues 

investigated physician and patient question-asking about medications in a 

sample of 467 audio-taped primary care visits.12 All patients were on an at least 

one prescribed medication and were on an average of four. The researchers 

found that physicians asked patients about how the medication was working 

for them during 56% of visits and about side effects during only 27% of visits. 

Patients asked about side effects during 5% of visits. This study did not examine 

physician information-giving about risks and benefits of medications. 

Two other studies focused on physician–patient communication about 

antidepressants during medical visits.13,14 In a sample of 40 audio-taped 

encounters with veterans who had previously been prescribed antidepressants, 

Sleath and colleagues found that practitioners asked only 6% of veterans about 

adverse events and only 15% of patients about how well the antidepressants 

were working.13 Practitioners gave 10% of patients information about adverse 

events and 5% information on how well it works. Young and colleagues 

used standardized patients (patients who presented to the doctor with 

standardized symptoms) to assess doctor behavior during 131 visits during 

which antidepressants were prescribed.14 In this study, physicians provided 

information about side effects to 85% of patients, but provided information 

about the benefits of the medication to only 38% of patients. A recent study 

found that older persons’ willingness to take medication for primary prevention 

of cardiovascular disease was relatively insensitive to benefit communication, 

but highly sensitive to adverse effect communication.15 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 123
	

Future research should examine how risks and benefits are communicated 

to patients when medications are first prescribed, as well as the extent to 

which physicians monitor patients’ experience of medication risks and benefits 

so that potential problems can be detected and therapy can be optimized. 

Intervention research is also needed to develop and test strategies to promote 

physician and patient participation in discussions about the risks and benefits 

of treatments and to improve the quality of shared decision making. 

Pharmacist–patient communication. Very little work has specifically 

examined how pharmacists verbally communicate medication risks and 

benefits to patients.16-18 Schommer and Wiederholt examined the number 

of pieces of information that pharmacists provided to patients about their 

medications, but did not specify the types of information provided.17 Sleath 

examined pharmacists’ question-asking and found that pharmacists asked 16% 

of patients questions related to medication use (e.g., asking about benefits, 

side effects).12 

Svarstad and colleagues evaluated pharmacists’ communication in 306 

community pharmacies in 8 states using individuals who were trained to 

act as patients with new prescriptions.18 The researchers defined adequate 

risk communication as providing information about one or more side effects 

or precautions. Adverse events were discussed for 17% of amoxicillin 

prescriptions, 31% of ibuprofen prescriptions, and 37% of paroxetine 

prescriptions. The researchers found that younger pharmacists were more 

likely to provide risk information than older ones. They also found that patients 

who received prescriptions in states with more regulatory intensity surrounding 

pharmacist counseling (e.g., states that require that patients be given face-toface counseling by pharmacists) were more likely to receive risk information 

than patients in states with weaker regulations (e.g., states that only mandate 

an offer for pharmacist counseling be given). 

Studies have also found that the written consumer medication information 

provided to patients in pharmacies is not adequate.18-20 Raynor and colleagues 

found that the side-effects section was the most commonly read section of 

written medication information.19 Most recently, Winterstein and colleagues 

trained individuals to fill prescriptions for lisinopril and metformin in 365 

pharmacies.20 The shoppers gathered the written information sheets they 

received, which were subsequently evaluated by an expert panel. The 

researchers found that, although the distribution of written information 

through pharmacies was effective, the content, format, reading level, 

and excessive length of the consumer medication information needed 

improvement. 

Patients do want to receive written medication information. However, they 

do not want written information to substitute for verbal communication from 

health care professionals.21,22 Grime and colleagues found that patients prefer 
 

124 | Chapter 13: Health Care Professionals
	

written information tailored to their conditions.21 Sleath and colleagues found 

that the majority of Latino patients in their sample wanted verbal and written 

medication information and almost one quarter wanted it in both Spanish and 

English.22 A recent Cochrane systematic review of the literature by Nicholson 

and colleagues concluded that there was not enough evidence to say whether 

written medication information positively influences patient knowledge, 

attitudes, and behaviors regarding medication taking.23 Thus, additional 

research is needed to examine whether patients read, comprehend, and use 

the written medication information that they receive in pharmacies.19 

What general practical advice can the science support? 

Health care professionals need to receive specific training on how to 

communicate with patients about the risks and benefits of treatments. 

Although relatively few studies have examined the risk and benefit 

communication practices of health care professionals, the evidence 

shows substantial room for improvement in health professionals’ use of 

communication strategies. Two controlled trials successfully demonstrated that 

health care professionals’ risk communication skills could be improved.16,24 In 

Wales, Elwyn and colleagues conducted a controlled trial with 20 physicians 

that tested several intervention efforts, including workshops that trained the 

physicians in risk communication and shared decision making.24,25 Physicians 

attended four 3-hour workshops, two devoted to risk communication and two 

focused on shared decision making. Delivery of risk information to patients 

improved dramatically after the workshops, which included the use of visual 

formats to illustrate treatment risks to patients. Rickles and colleagues 

conducted a randomized, controlled trial with patients who had received an 

initial prescription of an antidepressant.16 Patients were randomized to receive 

usual care from pharmacists or an intervention that included pharmacist 

training in guided education and monitoring. Patients were significantly more 

likely to report changes in depressive symptoms and side effects if they saw 

a pharmacist who was trained. These two trials suggest that physicians and 

pharmacists can be trained to communicate more effectively about medication 

risks and benefits, although additional trials are needed to identify the 

most efficient and effective strategies for improving professionals’ skills and 

promoting their use in actual encounters with patients. Also, existing models 

of patient-centered communication26-28 and shared decision making8,9 can be 

incorporated into this training. 

State pharmacy boards should consider requiring patient counseling on 

all prescriptions. Svarstad and colleagues found that patients who received 

prescriptions in states with more stringent regulation of pharmacist counseling 

(e.g., states that require face-to-face counseling by a pharmacist) were more 

likely to receive medication risk information than patients in states with less 

regulatory intensity.18 State pharmacy boards need to consider requiring that 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 125
	

patients receive face-to-face counseling by pharmacists, so that risk–benefit 

communication can be improved. 

Health care professionals need to provide useful written information 

about the risks and benefits of treatment to complement their verbal 

communication. Both written and verbal information regarding medication 

treatment is important to patients.21,22,24 Elwyn and colleagues found that 

practitioners used written information more often to explain treatment risks to 

patients after they received training in shared decision making.24 Given the low 

frequency of health professional–patient discussions about medication risks 

and benefits documented in the current literature, future research should also 

test: (1) the impact of communication strategies delivered by other members 

of the health care team (e.g., nurses, care managers); (2) the impact of decision 

aids that prompt professionals to communicate and facilitate information 

sharing;29 and (3) interventions delivered via alternative technologies, such as 

web-based decision aids that the patient can access between medical visits.30 

As noted above, the written information provided to patients in pharmacies 

is often not adequate to enable them to understand the risks and benefits of 

medications.18-20 Personalizing the written information (e.g. using the word 

“you”), providing risk–benefit information in different formats, and giving 

patients a reflective task to work on when reading the information may 

improve patient perceptions of risk.31-33 However, additional research is needed 

to develop better ways to promote patients’ exposure to, comprehension of, 

and actual use of the written medication information about risks and benefits 

of medication received in pharmacy settings.34 

Health care professionals should employ strategies that activate patients, 

encourage their participation in care, and increase their capacity to selfmanage their conditions. Patients who are more knowledgeable about 

their conditions, participate more actively in medical visits, and feel more 

confident about managing their conditions are more likely to follow through 

with treatment and achieve better outcomes.35-38 Thus, strategies that focus 

on increasing patient participation in care may increase the likelihood that 

patients will ask for and receive needed information about the risks and 

benefits of medical treatments. Controlled trials of self-management support 

interventions that focus on increasing patients’ confidence to self-manage 

have produced improvements in clinical outcomes across a number of other 

chronic conditions.39-41 Recent efforts to integrate self-management support 

into general health care settings suggest that the following elements are critical 

to individual patient and program success: (1) assessment of patient beliefs, 

behavior, and knowledge; (2) collaborative goal setting; (3) identification of 

personal barriers and supports; (4) skills in teaching, including problem-solving, 

to address barriers; (5) increasing access to resources and supports; and (6) 

developing a personal action plan that is based on the previous steps.42,43 
126 | Chapter 13: Health Care Professionals
	

How does one evaluate communications implementing this advice?

The ultimate test of the effectiveness of health professionals’ communication 

is direct assessment of the patients’ understanding of the risks and benefits 

and their satisfaction with the communication process. To assess the impact 

of health professional training in risk–benefit communication skills, one can 

assess the impact of the training on several levels at no cost or a low cost 

by examining: (1) were the training objectives achieved?; and (2) did health 

professionals who attended the training report an increase their knowledge, 

skills, and attitudes (e.g., importance, confidence)?. If one wants to assess the 

impact of health professional training in risk–benefit communication skills at 

a more moderate cost, one can investigate: (1) do trained professionals apply 

new knowledge and skills in actual interactions with patients; (2) do patients of 

trained professionals report increased understanding of risks and benefits of 

treatments, greater involvement in decision making, and the capacity to make 

high-quality decisions? ; and (3) are training participants in training able to 

demonstrate the use of the targeted skills in simulated interactions? 

Endnotes

1 Committee on Quality of Health Care in America, Institute of Medicine. (2001). Crossing the 

Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academy 

Press. 

2 DiMatteo, M. R. (1994). Enhancing patient adherence to medical recommendations. JAMA, 271(1), 

79, 83. 

3 Ockene, J. K., and Zapka, J. G. (2000). Provider education to promote implementation of clinical 

practice guidelines. Chest, 118(2 Suppl), 33S-39S. 

4 Roter, D., and Kinmonth, A.-L. (2002). What is the evidence that increasing participation of 

individuals in self-management improves the processes and outcomes of care? In R. Williams, A. 

Kinmonth, N. Wareham & W. Herman (Eds.), The Evidence Base for Diabetes Care: John Wiley and 

Sons. 

5 Safran, D., Taira, D., Rogers, W., Kosinski, M., and Tarlov, A. (1998). Linking primary care 

performance to outcomes of care. J Family Practice, 47, 213-220. 

6 Stewart, M., Brown, J., Donner, A., McWhinney, I., Oates, J., Weston, W., et al. (2000). The impact 

of patient-centered care on outcomes. J Fam Pract, 49(9), 805-807. 

7 Whitlock, E. P., Orleans, C. T., Pender, N., & Allan, J. (2002). Evaluating primary care behavioral 

counseling interventions: An evidence-based approach. Am J Prev Med, 22(4), 267-284. 

8 Frosch, D. L., and Kaplan, R. M. (1999). Shared decision making in clinical medicine: Past research 

and future directions. Am J Prev Med, 17(4), 285-294. 

9 Makoul, G., and Clayman, M. L. (2006). An integrative model of shared decision making in medical 

encounters. Patient Educ Couns, 60(3), 301-312. 

10 Braddock, C. H., 3rd, Edwards, K. A., Hasenberg, N. M., Laidley, T. L., and Levinson, W. (1999). 

Informed decision making in outpatient practice: Time to get back to basics. JAMA, 282(24), 2313-

2320. 

11 Street, R. L., Jr., Gordon, H. S., Ward, M. M., Krupat, E., and Kravitz, R. L. (2005). Patient 

participation in medical consultations: Why some patients are more involved than others. Med 

Care, 43(10), 960-969. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 127
	

12 Sleath, B., Roter, D., Chewning, B., and Svarstad, B. (1999). Asking questions about medication: 

Analysis of physician-patient interactions and physician perception. Medical Care, 37, 1169-1173. 

13 Sleath, B., Tulsky, J. A., Peck, B. M., and Thorpe, J. (2007). Provider-patient communication about 

antidepressants among veterans with mental health conditions. Am J Geriatr Pharmacother, 5(1), 

9-17. 

14 Young, H. N., Bell, R. A., Epstein, R. M., Feldman, M. D., and Kravitz, R. L. (2006). Types of 

information physicians provide when prescribing antidepressants. Journal of General Internal 

Medicine, 21, 1172-1177. 

15 Fried, T. R., Tinetti, M. E., Towle, V., O’Leary, J. R., and Iannone, L. (2011). Effects of benefits and 

harms on older persons’ willingness to take medication for primary cardiovascular prevention. 

Arch Intern Med, 2011.2032. 

16 Rickles, N. M., Svarstad, B. L., Stata-Paynter, J. L., Taylor, L. V., and Kobak, K. A. (2006). Improving 

patient feedback about and outcomes with antidepressant treatment: A study in eight community 

pharmacies. Journal of the American Pharmacists Association, 46, 25-32. 

17 Schommer, J. C., and Wiederholt , J. B. (1995). A field investigation of participant and 

environment effects on pharmacist-patient communication in community pharmacies. Medical Care 

33, 567-584. 

18 Svarstad, B. L., Bultman, D. C., and Mount, J. K. (2004). Patient counseling provided in community 

pharmacies: Effects of state regulation, pharmacist age, and busyness. Journal of the American 

Pharmacists Association, 44 22-29. 

19 Raynor, D. K., Silcock, J., and Edmondson, H. (2007). How do patients use medicine information 

leaflets in the UK? International Journal of Pharmacy Practice, 15, 209-218. 

20 Winterstein, A. G., Linden, S., Lee, A. E., Fernandez, E. M., and Kimberlin, C. L. (2010). Evaluation 

of consumer medication information dispensed in retail pharmacies. Archives of Internal 

Medicine, 170, 1317-1324. 

21 Grime, J., Blenkinsopp, A., Raynor, D. K., Pollock, K., and Knapp, P. (2007). The role and value of 

written information for patients about individual medicines: A systematic review. Health Expect, 

10(3), 286-298. 

22 Sleath, B., Blalock, S. J., Bender, D. E., Murray, M., Cerna, A., and Cohen, M. G. (2009). Latino 

patients’ preferences for medication information and pharmacy services. J Am Pharm Assoc 

(2003), 49(5), 632-636. 

23 Nicolson, D., Knapp, P., Raynor, D. K., & Spoor, P. (2009). Written information about individual 

medicines for consumers. Cochrane Database Syst Rev(2), CD002104. 

24 Elwyn, G., Edwards, A., Hood, K., Robling, M., Atwell, C., Russell, I., et al. (2004). Achieving 

involvement: Process outcomes from a cluster randomized trial of shared decision making skill 

development and use of risk communication aids in general practice. Fam Pract, 21(4), 337-346. 

25 Edwards, A., Elwyn, G., Hood, K., Atwell, C., Robling, M., Houston, H., et al. (2004). Patient-based 

outcome results from a cluster randomized trial of shared decision making skill development and 

use of risk communication aids in general practice. Fam Pract, 21(4), 347-354. 

26 DiMatteo, M. R. (1995). Patient adherence to pharmacotherapy: The importance of effective 

communication. Formulary, 30(10), 596-598, 601-592, 605. 

27 Makoul, G. (2001). Essential elements of communication in medical encounters: The Kalamazoo 

consensus statement. Acad Med, 76(4), 390-393. 

28 Stewart, M., Brown, J., Weston, W., McWhinney, I., McWilliam, C., and Freeman, T. (1995). 

Patient-Centered Medicine: Transforming the Clinical Method. Thousand Oaks: Sage. 

29 O’Connor, A. M., Bennett, C. L., Stacey, D., Barry, M., Col, N. F., Eden, K. B., et al. (2009). Decision 

aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev(3), 

CD001431. 
128 | Chapter 13: Health Care Professionals
	

30 Elwyn, G., Kreuwel, I., Durand, M. A., Sivell, S., Joseph-Williams, N., Evans, R., et al. (2010). How to 

develop web-based decision support interventions for patients: A process map. Patient Education 

and Counseling. 2011 Feb; 82(2): 260-5, EPub 2010 June 2. 

31 Berry, D. C., Michas, I. C., and Bersellini, E. (2002). Communicating information about medication 

side effects: Effects on satisfaction, perceived risk to health, and intention to comply. Psychology 

and Health (17), 247-267. 

32 Berry, D. C., Michas, I. C., and Bersellini, E. (2003). Communicating information about medication: 

The benefits of making it personal. Psychology and Health, 18, 127-139. 

33 Natter, H. M., and Berry, D. C. (2004). Effects of Active Information processing on the 

understanding of risk information. Applied Cognitive Psychology (19), 123-135. 

34 Raynor, D. K., Blenkinsopp, A., Knapp, P., Grime, J., Nicolson, D. J., Pollock, K., et al. (2007). A 

systematic review of quantitative and qualitative research on the role and effectiveness of written 

information available to patients about individual medicines. Health Technol Assess, 11(5), iii, 

1-160. 

35 Anderson, R., Funnell, M., Butler, P., Arnold, M., Fitzgerald, J., and Feste, C. (1995). Patient 

empowerment: Results of a randomized controlled trial. Diabetes Care, 18(7), 943-949. 

36 Greenfield, S., Kaplan, S. H., Ware, J. E., Jr., Yano, E. M., and Frank, H. J. (1988). Patients’ 

participation in medical care: Effects on blood sugar control and quality of life in diabetes. J Gen 

Intern Med, 3(5), 448-457. 

37 Hibbard, J. H., Mahoney, E. R., Stockard, J., and Tusler, M. (2005). Development and testing of a 

short form of the patient activation measure. Health Serv Res, 40(6 Pt 1), 1918-1930. 

38 Hibbard, J. H., and Tusler, M. (2007). Assessing activation stage and employing a “next steps” 

approach to supporting patient self-management. J Ambul Care Manage, 30(1), 2-8. 

39 Bodenheimer, T., Lorig, K., Holman, H., & Grumbach, K. (2002). Patient self-management of 

chronic disease in primary care. JAMA, 288(19), 2469-2475. 

40 Lorig, K. R., and Holman, H. R. (2003). Self-management education: history, definition, outcomes, 

and mechanisms. Ann Behav Med, 26(1), 1-7. 

41 Warsi, A., Wang, P. S., LaValley, M. P., Avorn, J., and Solomon, D. H. (2004). Self-management 

education programs in chronic disease: a systematic review and methodological critique of the 

literature. Arch Intern Med, 164(15), 1641-1649. 

42 Fisher, E. B., Brownson, C. A., O’Toole, M. L., Shetty, G., Anwuri, V. V., and Glasgow, R. E. (2005). 

Ecological approaches to self-management: The case of diabetes. American Journal of Public 

Health, 95, 1523–1535. 

43 Glasgow, R. E., Funnell, M. M., Bonomi, A. E., Davis, C., Beckham, V., and Wagner, E. H. 

(2002). Self-management aspects of the improving chronic illness care breakthrough series: 

Implementation with diabetes and heart failure teams. Annals of Behavioral Medicine, 24 (2), 

80–87. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 129
	

Chapter 14: Readablity, Comprehension, and Usability

Linda Neuhauser, DrPH - University of California, Berkeley
	

Kala Paul, MD - The Corvallis Group
	

Summary

More than 1,000 studies have documented the problem that most health 

information, including risk communication, greatly exceeds the comprehension 

of the average US adult. We describe specific ways to assess text readability 

and usability and practical steps to make risk communication more 

understandable, especially by engaging users in its design and testing. 

Introduction 

Playwright George Bernard Shaw famously commented: “The single biggest 

problem in communication is the illusion that it has occurred.”1 Two decades 

of research now support his witticism with evidence. Much of our wellintentioned health communication is not comprehensible, especially by people 

with barriers related to literacy, language, culture, or disability. For example, it 

is estimated that more than 90 million Americans have trouble understanding 

printed information about how to take medication correctly.2 Communication 

problems are thought to be an important reason why our nation is slow to 

achieve its health goals.3

 Fortunately, communication research and practice 

are illuminating a better path forward. US policies, like the National Action 

Plan to Improve Health Literacy and the Plain Writing Act, reflect the growing 

national movement to align health communication with people’s needs.4,5 In 

this chapter, we describe issues, evidence, and guidance to improve health risk 

communication. 

What does the science say about this aspect of communication? 

The scientific study of risk communication, “communication intended 

to supply lay people with the information they need to make informed, 

independent judgments about risks to health, safety and the environment,”6 

began in the 1970s. Risk communication about health often includes high 

concern or controversial topics or situations and is particularly relevant to the 

U.S. Food and Drug Administration’s (FDA) important safety communication to 

the public about drugs, biologics, medical devices, and food safety (see Chapter 

21). 
 

 

 

 

130 | Chapter 14: Readablity, Comprehension and Usability
	

How theory has shaped health and risk communication. Many conceptual 

models have contributed to our understanding of how people interact with 

health and risk communication. For example, social-ecological and socialcognitive models suggest that people are more likely to learn and take action 

when information is tailored to their needs and preferences and is relevant to 

their social situations.7,8 According to adult learning theory, communication is 

more effective when it builds on people’s prior experiences.9 Mental models 

concepts emphasize the importance of bridging the gaps between people’s 

initial risk perceptions and the more objectively known risks.6,10 Social semiotic 

theory helps explain how people interpret the meaning of the communication 

they receive and why health messages will only have an impact if they are 

understandable, engaging, and motivating.11 Models of participatory design 

used in communication development draw on knowledge from multiple 

disciplines, including human factors, engineering, sociology, and marketing and 

focus on the power of involving the target audiences as co-developers in those 

processes.12-14 

Comprehension issues in health and risk communication. Traditional health 

and risk communications have emphasized developing and delivering generic 

(one-size-fits-all) information that is not usually well aligned with people’s 

specific communication needs.15 Not surprisingly, substantial research 

indicates that this expert approach is often ineffective in improving people’s 

health knowledge and actions.15,16 A critical problem documented in the 

past two decades is that most health and risk communication is written and 

presented in ways that far exceed most people’s comprehension.17-21 

Literacy studies. The 2003 National Assessment of Adult Literacy (NAAL) 

defines literacy as “using printed and written information to function in society, 

to achieve one’s goals, and to develop one’s knowledge and potential.”2 The 

NAAL is a national, population-based survey conducted every decade and is the 

best data source about Americans’ literacy levels. In 2003, an estimated 43% of 

adults in the United States (approximately 93 million) had basic or below basic 

prose literacy skills — the 2 lowest of 4 levels. Most adults with a high school 

education or less and 13% of those with a college degree tested at these lower 

literacy levels.2 Although there are no national data on the average grade 

reading level of US adults, estimates have ranged between 7th and 9th grade 

levels.22-24 One study found that adults read about 4 grade levels below their 

highest grade completed.25 Furthermore, 20% of adults are estimated to read 

at the 5th grade level or below.24 

Health literacy studies. Because of its scientific content, health information is 

thought to pose literacy requirements beyond general reading comprehension, 

such as knowledge about health and medical concepts and terminology.26 

Beginning in the 1990s, the field of health literacy has emerged to focus on 

the effectiveness of health communication relative to people’s needs and 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 131
	

skills. In 2000, the US Department of Health and Human Services defined 

health literacy as “the degree to which individuals have the capacity to obtain, 

process, and understand basic health information and services needed to 

make appropriate health decisions.”27 The concept of health literacy includes 

components of reading, comprehension, speaking and numeracy “the ability to 

use and understand numbers in daily life,” such as reading a food nutrition or 

medication label (also see Chapters 7 and 9).26, 28 

The 2003 NAAL survey is also the best source of population-based data about 

Americans’ health literacy. It found that most people scoring at the lowest two 

health literacy levels (below basic and basic) were unable to answer questions 

correctly asking about hypothetical scenarios of taking medications at certain 

times of the day, filling out patient information forms, and other important 

health tasks. Those in the below basic level also had trouble correctly reading a 

health appointment slip. Even people scoring at the intermediate literacy level 

had numeracy issues, such as difficulties understanding health information 

graphs and calculating health insurance costs. Only the 12% of respondents 

who scored as proficient in health literacy were able to answer questions 

correctly on the set of health literacy tasks routinely required of Americans. 

Health literacy skills are generally lower among people with lower education, 

lower income, who are members of a minority group, or are 65 years of age or 

older.29 

Readability of health information. Because so many Americans have 

difficulties understanding health information, literacy experts recommend 

increasing text readability so that it matches audiences’ reading levels — 

especially for people with limited literacy.17,25,30,31 Readability testing is a 

standardized method to estimate the US grade reading level of text content. 

It is performed either manually or with computer software. Readability tests 

typically measure the difficulty (length) of individual words and sentences in a 

text document. 

Disturbingly, more than 1,000 studies of health print materials (including 

medication labels and packaging) and web sites have found that text readability 

significantly exceeded the estimated reading skills of the audiences for whom 

they were developed.17,32-34 Most studies have reported health text readability 

at or above the 10th grade reading level. College and graduate school levels are 

not unusual for patient health communications that describe risk and that are 

written or reviewed by lawyers and/or scientists. For example, patient consent 

documents are notoriously hard to read. In a study of more than 600 consent 

forms, average readability was at the college level; only an estimated 5% of 

the forms would be understandable to patients who read at the 8th grade (US 

average) level.35 

Readability scores provide a rough indicator of word and sentence 

difficulty at grade levels, but are not adequate proxy measures of overall 
 

 

 

132 | Chapter 14: Readablity, Comprehension and Usability
	

text comprehensibility.36 Also, readability scores are imprecise, especially at 

high and low levels, and may not accurately reflect actual reading difficulty. 

Although readability testing is an important tool, grade level scores should be 

interpreted with caution. 

Other factors that affect comprehension. Research is defining other factors 

that affect the reading ease and usability of health information for various 

audiences. Such characteristics are often grouped into clear communication 

or plain language design criteria. Although there is no agreed upon single set 

of such criteria, the recommendations provided in the Additional Resources 

section at the end of this chapter are among the most-commonly used. 

US Government reports, such as the Department of Health and Human 

Services’ Quick Guide to Health Literacy, Simply Put, Toolkit for Making Written 

Material Clear and Effective, and others describe these principles and how to 

apply them to health communication materials.36-38 The key criteria are also 

embodied in tools, such as Suitability Assessment of Materials (SAM), used to 

assess health communication materials. The SAM is the most validated and 

most commonly used tool and includes readability and 21 other evidencebased design principles as shown in Table 1 at the end of this chapter.30,39,40 

Web navigation and usability. In addition to basic literacy skills, web-based 

sources of health information pose additional computer literacy requirements, 

such as the ability to locate and search sites, spell search terms, and follow 

threads to related sources.31 Similar to findings for print materials, decades of 

research about online content have identified problems of low readability and 

usability.34, 41-43 

Participatory design. The design principles described above have contributed 

greatly to improved health communication. However, no set of design criteria 

can adequately encompass the multiplicity of factors that affect people’s 

comprehension of health risk communication. Furthermore, comprehensibility 

alone does not ensure that communication will be effective. It must also be 

engaging, personally relevant, and actionable for users.44,45 Participatory, or 

user-centered design leverages important design principles, but goes beyond 

them to engage users in more complex, realistic, and nuanced scenarios as 

co-creators of communication.12,14,46,47,50 Research over the past 30 years 

increasingly indicates that participatory design processes —structured 

formative inquiry with intended users — are critical to create successful health 

communication.13,14,16,48-50 

Strength of the scientific evidence. The past 30 years of research on health 

and risk communication provide a rich foundation on which to assess and 

improve the readability and comprehension of our communications. Strengths 

of the research include evidence about literacy and health literacy skills in 

the United States and how those relate to people’ abilities to comprehend 

and perform common health tasks and, ultimately, affect their health status. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 133
	

Likewise, substantial evidence now documents the serious gap between 

people’s literacy and health literacy skills and the readability of the health 

information they receive. Research has increasingly identified many other 

design factors that affect people’s comprehension and use of health risk 

communication. Numeracy studies have provided important evidence about 

how people understand and misunderstand the quantitative presentation 

of health risks and offer practical guidance about ways to present such 

information to make it more comprehensible, such as easier-to-understand 

graphics and medication measuring devices.28,51 Finally, research about 

user-centered design has documented the central value of these processes 

to develop and distribute effective health risk communication. Studies 

are beginning to show that adhering more closely to readability and other 

design principles can improve user’s comprehension of health and risk 

communication.16,25,28,44,46,49,50,52 

Although evidence is increasing about the value of the many non-readability 

design principles embodied in the SAM test, finer empirical testing is needed 

for each of these criteria. Further research is needed to demonstrate the 

pre-post improvement in comprehension when health risk communication is 

developed according to plain language guidelines and user-centered design 

processes. Perhaps the area in which research is most needed is in establishing 

stronger links between improved comprehension of health risk communication 

and behavioral outcomes. For example, does better understanding of 

medication instructions improve how well patients take their medications? 

What general practical advice can the science support? 

Given the current state of research evidence and the national 

recommendations related to health literacy and plain language communication, 

we suggest six key approaches to improve the readability and understandability 

of health communication. We provide only a very brief overview of these 

strategies, and refer readers to references for more detailed guidance. 

1. Learn more about health literacy and plain language communication. 

An important first step for practitioners and decision-makers interested in 

improving health risk communication is to undergo training and to study 

important background documents. Training is available from public and private 

organizations. For example, the Centers for Disease Control and Prevention 

(CDC) offers a free online overview course Health Literacy Training for Public 

Health Professionals at http://www.cdc.gov/healthmarketing/healthliteracy/ 

training. We also recommend the ten selected Additional Resources as well as 

the references at the end of this chapter. 

2. Define the intended audiences and purpose of the communication.

Because generic health communication is often ineffective, it’s important to 

identify the specific audiences and learn as much as possible about them, 
134 | Chapter 14: Readablity, Comprehension and Usability
	

including their age ranges, health conditions, cultures, languages, educational 

and income levels, literacy skills, and media preferences. Research studies, 

government reports, health care organization information and other 

documents can provide useful profiles. It is also helpful to survey or interview 

members of the intended user groups. Another key step is to define what 

the communication resource is expected to accomplish. Is the information 

intended to help patients understand how to take medication correctly? Is it 

intended to persuade them to detect and report certain side effects? Defining 

communication objectives is important to prioritize information and identify 

outcomes to evaluate. 

3. Involve the intended audiences through the design process. As discussed 

earlier, there are many known as well as poorly understood factors that 

affect the readability and understandability of health risk communication. 

The only way to ensure that the communication will meet the needs of the 

intended audiences is to involve users as co-creators from the beginning. At 

an early stage, intended user input is needed about the topic and purpose of 

the communication, including problems people have experienced related to 

the topic, such as taking diabetes medications, and ways they recommend to 

overcome those barriers. Do older adults report they have difficulty reading 

the font size of medication labels? Do Hispanic groups prefer information that 

engages multiple family members? Do people want to hear about the most 

serious risks first? 

There are many participatory, or user-centered design techniques, including 

focus groups, individual interviews, and usability testing. Usability testing 

refers to a broad range of structured methods to engage users in designing 

communication materials.12,50 Usability tests are often one-on-one situations 

that involve a tester asking a user to read and navigate a draft document or 

web site (see www.usability.gov), accomplish specific tasks related to it, and to 

recommend changes to the text, format, and graphics. The draft is then revised 

with participant input. User-centered design begins with recruiting members of 

the intended audiences. It is important to include people with limited literacy 

skills in this process — they often get left out because they have trouble 

reading the recruitment flyer or are uncomfortable about their reading skills. 

One effective and respectful approach is to recruit (and pay) people from adult 

literacy programs. Another approach is to recruit people with less than a 10th 

grade education as they are likely to have limited literacy skills. Participants’ 

health literacy skills can be assessed using tests such as the short form of the 

Test of Functional Health Literacy in Adults (TOFHLA), but such tests should be 

used sparingly, because they can embarrass participants.53 

4. Set and test for readability and other communication design criteria.

After the intended audiences are identified and researched and members of 

those groups are engaged in the communication design, design standards 

should be specified. Because it is difficult to know which patients or consumers 
 

 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 135
	

will be among the half of Americans with limited health literacy skills, federal 

agencies and other organizations recommend a universal precautions approach 

— it both minimizes risk to the most vulnerable groups and also promotes 

better understanding for all.54 Fortunately, communication studies show that 

people at all health literacy levels prefer easier-to-read information.39 

Readability levels. As discussed earlier, readability is an important 

measurement tool, but it is only a rough indicator of some aspects of 

comprehension. Therefore, it should not be mistakenly considered the prime 

indicator of easy-to-use information — as is too often done. There is no single 

best readability level, given the diversity of American’s health literacy skills. 

However, there is general agreement that readability should not exceed 7th to 

8th grade (average), the lower end of the estimated average reading level of 

the US population. In addition, because many people read below that level, a 

4th to 6th grade level (easy) is a better goal for information that is critical for 

people to understand (such as medication instructions) or that is delivered to 

groups with lower health literacy (such as older adults).36 In our experience, 

most health risk information can be written well at about a 6th grade level 

without sacrificing content or style. Most current health communications 

are written above the 9th grade (difficult) level. See the helpful readability 

discussion in the Centers for Medicaid and Medicare Toolkit.36 

Readability testing. There are more than 40 readability tests, and their 

reliability at various grade-reading levels differs, as do their underlying 

readability formulas. We recommend becoming familiar with the following 

widely used, validated tools, and their limitations. 

• SMOG (the Simplified Measure of Gobbledygook test)30,55 

• The Fry Readability Test39 

• The Flesch Reading Ease Test56 

• The Lexile® Framework for Reading57 

The Flesch-Kincaid Readability Test is incorporated into Microsoft Word’s 

(Microsoft, Redmond, WA) readability software and is easily accessible. 

However, the formula is truncated at a 12th-grade level in Microsoft Word and 

frequently presents falsely low evaluations.58 

Because the readability tests vary in their reliability at various grade levels 

(especially below 6th grade and above 12th grade) and because draft health 

communication materials often contain text at many readability levels, we 

recommend assessing materials using multiple tests (excluding the FleschKinkaid test). Content should be sampled, prepared, and tested according 

to the test instructions. Table 2 shows an original sample of health risk 

communication text and scores from four readability tests computed with two 

readability software programs. Table 3 shows a revision to improve readability 

from the original college level (15+) to a 5th-to- 6th grade level. (See Tables 2 

and 3.) 
136 | Chapter 14: Readablity, Comprehension and Usability 

Table 2. Readability assessment: first paragraph of FDA patient safety alert:

glucose test strips*

Advice for patients: serious errors with certain blood glucose monitoring test strips

Patient Concerns

If you are taking drug products or therapies that contain certain non-glucose sugars, such as maltose, 

galactose and xylose, these sugars will produce a falsely elevated glucose result if you are measuring 

your blood glucose using a GDH-PQQ test strip. If you then use this falsely elevated result to determine 

your dose of insulin, you could give yourself too much insulin, which could result in dangerously low 

blood glucose. In addition, if your blood glucose is actually low, it could go unrecognized and untreated 

because the test result could read higher than it actually is and appear to be within the normal range. 

In this case, you may not know your blood glucose is low unless you have certain symptoms, including 

confusion, hunger, nervousness, dizziness, irritability, sweating, heart pounding (palpitations), shaking, 

unusual fatigue or weakness, or tunnel or darkened vision. Low blood glucose must be recognized and 

treated promptly to avoid serious complications, such as coma and death. 

Readability Assessment

Test Grade level Reading ease % Passive Sentences

SMOG 15.0 

Flesch-Kincaid 16.2 35% (very easy to read) 0 

Fry college very long sentences 

Lexile** Graduate school 

*Advice for Patients: Serious Errors with Certain Blood Glucose Monitoring Test Strips 

(http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/PatientAlerts/ucm177189.htm) 

** A Lexile measure is a computer-driven algorithm that provides a numeric assessment (Lexile score) of the difficulty 

of a text. www.lexile.com 

Table 3. Readability assessment: revised version of FDA patient safety alert:

glucose test strips*

Patient Concerns

Do you test your blood sugar with GDH-PQQ test strips?

Do you take drugs or treatments that have maltose, galactose, or xylose?

These are sugars, but are not the same as the blood sugar you test (glucose). 

If you answer “Yes” to both questions, you could have a problem with your blood sugar test results. 

Maltose, galactose, or xylose can react with the GDH-PQQ test strips. They can make the test strips 

give false results.

 • Your test results may be falsely high when your blood glucose is really normal. If this happens, you 

might give yourself too much insulin. 

 • Your test results may be falsely normal when your blood glucose is really low. You would not know 

your blood sugar is low until you start to feel confused, hungry, or sweaty. 

In both cases, your blood sugar can get too low. This can be dangerous. If you do not treat low blood 

sugar right away, you can have seious problems, even death. 

Readability assessment

Test Grade level Reading ease % Passive Sentences

SMOG 6.3 

Flesch-Kincaid 4.5 84.6 (very easy to read) 0 

Fry 6th (5th) 

Lexile 5-6th Grade 

*Advice for Patients: Serious Errors with Certain Blood Glucose Monitoring Test Strips 

(http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/PatientAlerts/ucm177189.htm) 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 137
	

The elements of the SAM tool were shown in Table 1. They include 

readability and 21 design factors thought to be important for plain language 

health information. We recommend that at least two experienced writers 

independently score draft materials using the SAM tool. One caveat about 

the SAM tool is that readability is included as just one of 22 assessments, and 

materials could score superior even with a high reading level. We suggest an 

adequate score on readability be required for an adequate SAM score. Table 

4 shows a sample original FDA document, and Table 5 shows a SAM test of it. 

(See Tables 4 and 5 at the end of the chapter.) 

5. Use plain language writing and design strategies. There are many 

excellent sources of advice about creating easier-to-understand information. In 

addition to formal training, we recommend that readers use the tips, toolkits, 

and other resources cited in this chapter. Although comprehensive strategies 

are too detailed to present here, key advice includes: 

Writing style tips: 

• Focus on what the reader needs to know, especially for actions to take 

• Limit content to 1 to 3 main messages 

• Avoid medical jargon and use easier to understand terms 

• Use short sentences and short words 

• Use active voice and address the reader personally 

• Use positive rather than negative messages 

Visual presentation tips: 

• Use a font size of 12 (or 14 or 16 for groups with vision limitations) 

• Put text in chunks and use lots of white (clear) space around text 

• Avoid italics and words in all capital letters 

• Use colors that appeal to the intended audiences 

• Use graphics to show fractions 

• Avoid graphs and charts, when possible 

6. Test and revise communications with the intended users. In steps 1 to 5 

above, users provide input to help create the initial draft health information 

according to plain language principles. The draft is then tested and revised, if 

necessary, to meet the readability and suitability criteria. Then, further usability 

testing is needed with members of the intended audiences to ensure that the 

communication resource is readable, understandable, engaging, culturally 

respectful, and actionable (users believe they can carry out the recommended 

behaviors). These factors go beyond what is codified in readability and SAM 

testing, and beyond the basic requirements for readable and understandable 

information, but are essential if users are to actually use and benefit from the 

information. Usability testing should be done on successive drafts until diverse 

users, including those with limited health literacy skills, are satisfied with the 

communication.50 
138 | Chapter 14: Readablity, Comprehension and Usability
	

How can we evaluate communications implementing this advice?

Evaluation is critical to assess the effectiveness of health risk communication. 

In this respect, user-centered design is especially powerful. It incorporates 

formative evaluation methods (e.g., usability testing, focus groups, etc.) 

throughout the entire development process. It is also important to conduct 

outcome evaluations to test whether the intended audiences were able to 

use and ultimately benefit from the information in real-world settings.50,59 For 

example, could patients understand how to take their medication correctly and 

did they adhere to the regimen over time? If not, what were the barriers? We 

recommend several evaluation approaches at various budget levels: 

• No budget: Readability and SAM testing should be done. True usercentered design cannot be conducted without at least some testing with 

users. 

• Modest budget: Besides readability and SAM testing, conduct usability tests 

with the intended audiences. Conduct qualitative outcome evaluations with 

focus groups and/or individual interviews, as funding allows. 

• Substantial budget: In addition to the above evaluation activities, conduct 

pre-post surveys with statistical samples the intended user groups. 

Conclusions

Thirty years of scientific evidence has helped us understand the health 

literacy skills of Americans and many factors that affect the readability and 

understandability of health risk communication. Research also shows that most 

health information is too difficult for users and is often disappointing in its 

ability to improve people’s health risk awareness and behaviors. Fortunately, 

national health literacy and plain language guidelines offer practical and 

evidence-based recommendations about improving health risk communication. 

The core lesson learned is that the intended users must be co-creators and 

testers of the communications. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 139 

Table 1. Suitability assessment of materials (SAM)*

Factor to be Rated Score Comments

0 = Not Suitable 

1 = Adequate 

2 = Superior 

1. Content

 a. Purpose is evident

 b. Content about behaviors

 c. Scope is limited

 d. Summary or review included 

2. Literacy Demand

 a. Reading grade level

 b. Writing style, active voice

 c. Vocabulary with common words

 d. Context given first

 e. Learning aids via “road signs” 

3. Graphics

 a. Cover graphic showing purpose

 b. Type of graphics

 c. Relevance of illustrations

 d. List, tables, etc. explained

 e. Captions used for graphics 

4. Layout and Typography

 a. Layout easy to follow

 b. Typography appropriate

 c. Subheads (“chunking”) used 

5. Learning Stimulation and Motivation

 a. Interaction used

 b. Behaviors modeled and specific

 c. Motivation / self-efficacy 

6. Cultural Appropriateness

 a.Match in logic, language, experience

 b.Cultural image and examples 

Total SAM Score:

Total Possible Score:

Percent Score: % Not Suitable Material

Interpretation of SAM percentage ratings:
	

70 – 100% = superior material 40 – 69% = adequate material 0 – 39% = not suitable material
	

* The SAM tool was validated with 172 health care providers from several cultures, including Southwest Asians, Native 

Americans, and African Americans, as well as students and faculty from the University of North Carolina School of public 

Health and Johns Hopkins School of Medicine. The SAM was developed under the Johns Hopkins School of Medicine 

project, “Nutrition Education in Urban African Americans,” funded by the National Institutes of Health, National Heart, 

Lung and Blood Institute, Bethesda, MD, 1993. 
140 | Chapter 14: Readablity, Comprehension and Usability
	

Table 4. FDA safety alert: advice for patients: serious errors with certain blood glucose 

monitoring test strips*

U.S. Department of Health & Human Services

For

Diabetic patients and/or their caregivers 

Advice

Issued: August 13, 2009 

NEVER use GDH-PQQ* glucose meters or test strips if you are using drug products or therapies 

that contain certain sugars other than glucose.

 • GDH-PQQ stands for glucose dehydrogenase pyrroloquinoline quinone 

Issue

Diabetic patients who receive drug products or therapies containing certain sugars other than 

glucose could experience serious, although rare, injuries if they use blood glucose meters with 

a particular type of test-strip technology. Strips that use this technology, known as GDH-PQQ, 

will react with certain non-glucose sugars, including maltose, galactose and xylose, and produce 

a falsely high (elevated) result. If a diabetic patient then takes too much insulin because of this 

falsely high result, it could lead to abnormally low blood sugar (hypoglycemia), coma, or even 

death. 

Certain patients may be more likely to be using drug products or therapies that contain other 

sugars, including those who:

 • are on peritoneal dialysis 

• have recently had surgery 

Glucose test strips other than the GDH-PQQ type are not affected by this problem, and can be 

used by patients taking drug products or therapies that contain non-glucose sugars. 

List of GDH-PQQ test strips and their associated meters

List of GDH-PQQ Glucose Test Strips 

Drug products or therapies with non-glucose sugars

 • Extraneal (icodextrin) peritoneal dialysis solution 

• Some immunoglobulins: Octagam 5%, Gamimune N 5% **, WinRho SDF Liquid, Vaccinia 

Immune Globulin Intravenous (Human) and HepaGamB 

• Orencia (abatacept) 

• Adept adhesion reduction solution (4% icodextrin) 

• BEXXAR radioimmunotherapy agent 

• Any product that contains, or the body breaks down into, the sugars maltose, galactose 

or xylose 

** Within the U.S., Gamimune N 5% has not been manufactured since December 2005, and no 

lots are in distribution in the U.S. 

Patient concerns

If you are taking drug products or therapies that contain certain non-glucose sugars, such as 

maltose, galactose and xylose, these sugars will produce a falsely elevated glucose result if 

you are measuring your blood glucose using a GDH-PQQ test strip. If you then use this falsely 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 141 

Table 4. Continued. 

elevated result to determine your dose of insulin, you could give yourself too much insulin, 

which could result in dangerously low blood glucose. In addition, if your blood glucose is actually 

low, it could go unrecognized and untreated because the test result could read higher than it 

actually is and appear to be within the normal range. In this case, you may not know your blood 

glucose is low unless you have certain symptoms, including confusion, hunger, nervousness, 

dizziness, irritability, sweating, heart pounding (palpitations), shaking, unusual fatigue or 

weakness, or tunnel or darkened vision. Low blood glucose must be recognized and treated 

promptly to avoid serious complications, such as coma and death. 

Recommendations for diabetic patients using interfering drug products or therapies 

If you are a diabetic patient who uses any of the drug products or therapies that contain certain 

non-glucose sugars (or care for someone who does), you should:

 • NEVER use GDH-PQQ glucose meters or test strips. 

• Instead, use another type of glucose monitoring technology and continue to monitor your 

blood glucose as instructed by your healthcare provider. 

• Contact your healthcare provider if your results do not reflect the way you feel. 

You may be able to determine the type of glucose monitoring technology you are using by 

looking at the instructions that accompanied your meter or test strips, or at your meter’s box. 

If you can’t tell what kind of technology your meter and test strips use, ask your healthcare 

provider or pharmacist to help you find out, and/or contact the manufacturer of your meter and 

test strips. 

General recommendations for all diabetic patients

 • Continue testing your blood glucose as directed by your healthcare provider. 

• Use only test strips specified for your glucose meter. 

• Know the type of glucose monitoring technology you are using. 

• Know that GDH-PQQ meters and strips should NOT be used if you are using an interfering 

drug product or therapy. 

• Know that GDH-PQQ meters and strips are okay to use if you are not using an interfering 

drug product or therapy. 

 • Know the medications you are taking and keep a current list of your medications. If you do 

not have a current list of medications, ask your healthcare provider to provide you with a list. 

Reports received by FDA 

From 1997 - 2009, FDA received 13 reports of death associated with GDH-PQQ glucose test 

strips in which there was interference from maltose or other non-glucose sugars. The deaths 

occurred in healthcare facilities. Some reports indicated that serious patient injury, such as 

low blood glucose (hypoglycemia), confusion, neurologic deterioration, too little oxygen in the 

tissues (severe hypoxia), brain damage and coma, occurred prior to death. 

FDA is working with manufacturers to resolve the problems with GDH-PQQ glucose test strips, 

and is continuing to monitor adverse events associated with these products. 

Questions to ask your healthcare provider

 • How do I determine which glucose meter and strips I have? 

• Which drugs am I currently taking? Am I taking or receiving an interfering drug product or 

therapy? 

• Should I continue testing my blood glucose with my current meter and strips or should I get 

a new meter and strips? If so, how do I do this? 

For more information see FDA Public Health Notification: Potentially Fatal Errors with GDH-PQQ 

Glucose Monitoring Technology1 

*Advice for Patients: Serious Errors with Certain Blood Glucose Monitoring Test Strips 

(http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/PatientAlerts/ucm177189.htm) 
142 | Chapter 14: Readablity, Comprehension and Usability 

Table 5. Suitability assessment of materials for FDA safety alert: advice for patients:

serious errors with certain blood glucose monitoring test strips*

Factor to be Rated Score Comments

0= Not suitable 

1 = Adequate 

2 = Superior 

1. Content

a. Purpose is evident 1 

While the title explicitly states that the 

document is about “serious errors,” the 

document is difficult to read and may not 

alert patients to the seriousness of the issue. 

b. Content about behaviors 2 The document explains what to do, what not 

do, and who is most likely be impacted. 

c. Scope is limited 2 

The scope of the document is limited to 

essential patient information and is directly 

related to the stated purpose. 

d. Summary or review included NA No summary is provided, but a summary is 

not needed because the document is short. 

2. Literacy Demand

a. Reading grade level 0 

The reading level is between the 14th – 

16th grade (post-graduate) levels, based 

on the SMOG, Flesch Reading Ease, and 

FRY validated reading tests. The average 

American adult reads between the 7th – 9th 

grade reading levels. 

b. Writing style, active voice 0 

Sentences are frequently in the active voice, 

but most are complex and/or long. Most 

sentences contain embedded information. 

c. Vocabulary with common words 0 

Many technical words are used and the 

vocabulary is quite high. There are jargon, 

acronyms, and numerical information, little of 

which is explained or defined. 

d. Context given first 0 Minimal context is provided. 

e. Learning aids via “road signs” 1 

Headers precede text, but the headers are 

frequently unclear, misleading, or contain 

jargon. Sections could be presented in a more 

logical manner. 

3. Graphics

a. Cover graphic showing purpose 0 

There are no graphics other than the FDA/ 

HHS logos; these graphics do not attract 

attention or portray the purpose of the 

document to the intended audience. 

b. Type of graphics NA There are no graphics. 

c. Relevance of illustrations 0 The FDA and HHS graphics are not relevant to 

the key message. 

d. List, tables, etc. explained NA There are no lists or tables. 

e. Captions used for graphics NA There are no graphics to have captions. 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 143
	

4. Layout and Typography

a. Layout easy to follow 1 

The layout/sequence of information is 

consistent. There is a wide left margin [white 

space], which reduces the appearance of 

clutter. However, the amount of text per 

line is excessive and overwhelming, many 

paragraphs are too long, and there are no 

illustrations or graphics to guide the reader. 

The subheads help with visual cuing. 

b. Typography appropriate 2 

Text is written in sentence case in at least a 

12-point font with a sans serif font for the 

main text. 

c. Subheads (“chunking”) used 1 

Lists are grouped under descriptive 

subheadings, or “chunks.” Most lists are less 

than 5 items, but some of the lists are too 

long to be easily read and understood. 

5. Learning Stimulation and Motivation

a. Interaction used 1 

Questions are provided for the patient to 

ask their health care provider, and links 

are provided for additional information. 

However, a question and answer format 

would be helpful and more engaging. 

b. Behaviors modeled and specific 1 Information is mainly abstract, and behaviors 

are not modeled. 

c. Motivation / self-efficacy 1 

Topics on the website are sub-divided or 

“chunked” to facilitate reading and the 

“questions” section supports self-efficacy. 

6. Cultural Appropriateness

a. Match in logic, language, experience 0 

This page appears to be available in English 

only. Font size can be increased, which is 

especially important for users with diabetes, 

but the size does not increase dramatically. 

This web page is quite advanced and assumes 

the language, literacy level, and medical 

understanding of the target audience is quite 

high. 

b. Cultural image and examples NA 

The site is not adapted to the needs (cultures) 

of all end users (seniors, people with 

disabilities, people with low incomes, etc). 

The site looks formal and professional, which 

is appropriate to a certain degree because it 

is from the FDA, but the formality may make 

some end users uncomfortable. 

Total SAM Score: 13

Total Possible Score: 34

Percent Score: 38% = “Not Suitable Material”

*Advice for Patients: Serious Errors with Certain Blood Glucose Monitoring Test Strips 

(http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/PatientAlerts/ucm177189.htm) 
144 | Chapter 14: Readablity, Comprehension and Usability
	

Additional resources

1. Nielsen-Bohlman, L., Panzer, A., and Kindig, D.A. (Eds.). (2004). Health literacy: A prescription to 

end confusion. Institute of Medicine, Committee on Health Literacy, Board on Neuroscience and 

Behavioral Health. Washington, D.C.: The National Academies Press. This document provides 

scientific description of the problem of health literacy and complex consumer health information 

with practical recommendations for improvement. 

2. US Department of Health and Human Services, Office of Disease Prevention and Health 

Promotion. (2010). National Action Plan to Improve Health Literacy. Washington, DC. Available 

at http://health.gov/communication/HLActionPlan/pdf/Health_Literacy_Action_Plan.pdf. The 

Plan (June 2010) describes health literacy problems and recommends actions at professional, 

community, organizational, and policy levels. 

3. US Office of Management and Budget, Office of Information and Regulatory Affairs. OMB 

Memorandum, M-11-05, (November 22, 2010). Preliminary Guidance for the Plain Writing Act 

of 2010, Available at http://www.whitehouse.gov/sites/default/files/omb/memoranda/2011/ 

m11-05.pdf. Preliminary guidelines, (November 2010), to inform heads of executive 

government departments about implementing the US Plain Writing Act of October 2010. 

4. US Federal Plain Language Guidelines. (March 2011). Available at http://www.plainlanguage. 

gov/howto/guidelines/bigdoc/TOC.cfm (www.plainlanguage.gov). Recommendations for Using 

Plain Language to Communicate with the Public and as Guidance for Government Agencies to 

Fulfill the Requirements of the Plain Writing Act of 2010 (see 3. Above). 

5. Doak, C, Doak, L, and Root, J. (1996). Teaching Patients with Low Literacy Skills. Philadelphia, PA. 

Retrieved from http://www.hsph.harvard.edu/healthliteracy/resources/doak-book/index.html. 

This classic book provides useful information about understanding the communication barriers of 

people with limited literacy and how to write easier-to-use materials. 

6. US Department of Health and Human Services. Office of Disease Prevention and Health 

Promotion. Quick Guide to Health Literacy. Available at http://www.health.gov/communication/ 

literacy/quickguide and US Department of Health and Human Services. Strategic and Proactive 

Communication Branch, Division of Communication Services, Office of the Associate Director for 

Communication, Centers for Disease Control and Prevention (April 2009). Simply Put. Available at 

http://www.cdc.gov/healthmarketing/pdf/Simply_Put_082010.pdf. These guides explain health 

literacy issues and provide practical tips to create plain language health materials. 

7. US Department of Health and Human Services, Centers for Medicare & Medicaid Services. 

(updated March 2011) Toolkit for Making Written Material Clear and Effective. Available at 

http://www.cms.gov/WrittenMaterialsToolkit/. This toolkit provides practical suggestions about 

designing plain language communications. 

8. US Department of Health and Human Services, Office of Disease Prevention and Health 

Promotion. (2010). Health Literacy Online: A Guide to Writing and Designing Easy-To-Use Health 

Web Sites. Washington, DC. Available at http://www.health.gov/healthliteracyonline/index.htm. 

The above site and www.usability.gov provide tips to design health websites, including usercentered design strategies. 

9. US Department of Health and Human Services, Agency for HealthCare Research and Quality. 

(2010). AHRQ Publication No. 10-0046-EF. Health Literacy Universal Precautions Toolkit. 

Available at http://www.ahrq.gov/qual/literacy. Rockville, MD: Agency for Healthcare Research 

and Quality. http://www.ahrq.gov/qual/literacy/index.html. This toolkit provides useful 

information to help health care organizations and providers assess health literacy barriers and 

improve communication with patients. 

10.The Harvard School of Public Health: Health Literacy Studies Web Site. Available at http:www. 

hsph.harvard.edu/healthliteracy. A useful site for professionals in health and education who are 

interested in health literacy and health outcomes related to communication and literacy skills. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 145
	

Endnotes

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4 US Department of Health and Human Services, Office of Disease Prevention and Health 

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health.gov/communication/HLActionPlan/pdf/Health_Literacy_Action_Plan.pdf 

5 111th US Congress, 2nd session. (January 5, 2010). Plain Writing Act of 2010 (H.R. 946). 

Washington, DC, Government Printing Office. Retrieved from http://www.gpo.gov/fdsys/pkg/ 

BILLS-111hr946enr/pdf/BILLS-111hr946enr.pdf 

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11 Neuhauser, L., and Kreps, G. (2010). eHealth communication and behavior change: Promise and 

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12 Nielsen J. (2000). Designing Web Usability. Indianapolis: New Riders Publishing. 

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21 Rudd, R.E., Comings, J.P., and Hyde, J.N. (2003). Leave no one behind: Improving health and risk 

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24 Doak, L., Doak, C., and Meade, C. (1996). Strategies to improve cancer education materials. 

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28 Peters, E., Hibbard, J. H., Slovic, P., and Dieckmann, N. (2007). Numeracy skill and the 

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748. 

29 Nielsen-Bohlman, L., Panzer, A., and Kindig, D. A. (eds.). (2004). Health Literacy: A Prescription to 

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30 Osborne H. (2005). Health Literacy from A to Z: Practical Ways to Communicate Your Health 

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31 Birru, M. S., Monaco, V. M., Charles, L., Drew, H., Njie, V., et al. (2004). Internet usage by low 

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32 Davis, T. C., Holcombe, R. F., Berkel, H. J., Pramanik, S., and Divers, S.G. (1998). Informed consent 

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33 Murphy, P. W. (1994). Reading ability of parents compared with reading level of pediatric patient 

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34 Neuhauser, L., Rothschild, R., and Rodriquez, F. M. (2007). MyPyramid.gov: Assessment of 

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35 Hopper, K. D., TenHave, T. R., Tully, D. A., and Hall, T. E. (1998). The readability of currently used 

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37 US Department of Health and Human Services, Office of Disease Prevention and Health 

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38 US Department of Health and Human Services, Centers for Disease Control and Prevention (CDC). 

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Communicating Risks and Benefits: An Evidence-Based User’s Guide | 147
	

39 Doak, C., Doak, L., & Root, J. (1996). Teaching Patients with Low Literacy Skills, Retrieved from 

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40 Mayer, G. and Villaire, M. (2007). Health Literacy in Primary Care: A Clinician’s Guide. New York, 

NY: Springer Publishing Company. 

41 Stinson, J. N., White, M., Breakey, V., Chong, A. L., Mak, I., Low, K. K. and Low, A. K. (2011). 

Perspectives on quality and content of information on the internet for adolescents with cancer. 

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42 Zarcadoolas, C., Pleasant, A., Greer, D. (2006). Advancing Health Literacy-A Framework for 

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43 Neuhauser, L. & Kreps, G. (2008). Online cancer communication interventions: Meeting the 

literacy, linguistic and cultural needs of diverse audiences. Patient Education and Counseling, 

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44 Noar, S. M., Benac, C. N., & Harris, M. S. (2007). Does tailoring matter? Meta-analytic review of 

tailored print health behavior change interventions. Psychological Bulletin, 133(4), 673-693. 

45 Szwajcer, E. M., Hiddink, G. J. Koelen, M. A., and van Woerkum, C. M. (2009). Written nutrition 

communication in midwifery practice: What purpose does it serve? Midwifery, 25(5): 509-17. 

46 Vaiana, M. E. and McGlynn, E. A. (2002). What cognitive science tells us about the design of 

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47 Vallance, J., Courneya, K., Taylor, L., Plotnikoff, R., and Mackey, J. (2008). Development and 

evaluation of a theory-based physical activity guidebook for breast cancer survivors. Health 

Education and Behavior, 35(2):174–189. 

48 Kripalani, S., Robertson, R., Love-Ghaffari, M. H., Henderson, L. E., Praska. J., et al. (2007). 

Development of an illustrated medication schedule as a low-literacy patient education tool. 

Patient Education and Counseling, 66(3), 368–377. 

49 Sudore, R. L., Landefeld, C. S., Williams, B. A., Barnes, D. E., Lindquist, K., et al. (2006). Use of a 

modified informed consent process among vulnerable patients: A descriptive study. Journal of 

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50 Neuhauser, L., Rothschild, B., Graham, C., Ivey, S., and Konishi, S. (2009). Participatory design 

of mass health communication in three languages for seniors and people with disabilities on 

Medicaid. American Journal of Public Health, 99:2188-2195. 

51 Yin, H. S., Wolf, M. S., and Dreyer, B. P. (2010). Evaluation of consistency in dosing directions and 

measuring devices for pediatric nonprescription liquid medications. JAMA, 305(8), pp: E1-E8. 

52 Dowe, M. C., Lawrence, P. A., Carlson, J., and Keyserling, T. C. (1997). Patients’, use of health 

teaching materials at three readability levels. Applied Nursing Research, 10(2); 86-93. 

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Short Version: Photocopy Master. Snow Camp, NC: Peppercorn Books. 

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55 McLaughlin, G. H. SMOG Readability Formula. Retrieved from: http://www.harrymclaughlin.com/ 

SMOG.htm 

56 Beckman, H. T., Lueger, R. J. (1997). Readability of self-report clinical outcome measures. Journal 

of Clinical Psychology, 53(8): 785–789. 

57 White, S. and Clement, J. (2001). Assessing the Lexile Framework: Results of a Panel Meeting, 

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148 | Chapter 14: Readablity, Comprehension and Usability 

58 Paasche-Orlow, M. K. (2005). The challenges of informed consent for low-literate populations. In: 

Swartzberg J, VanGeese J, Wang C, eds. Understanding Health Literacy: Implications for Medicine 

and Public Health. Chicago, IL: American Medical Association Press. 

59 Brewer, N. T., Richman, A. R., DeFrank, J. T., and Carey, L. A. Improving communication of breast 

cancer recurrence risk. (Unpublished, personal communication). 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 149
	

Chapter 15: Warnings and Disclosures

J. Craig Andrews, PhD - Marquette University 

Summary

This chapter reviews nearly six decades of research on warnings and 

disclosures, including common misperceptions and their importance to public 

health policy, and offers an answer to the key question, “Do warnings and 

disclosures really work?” Supporting theory and research applications are 

discussed. 

Introduction

Warnings and disclosures are ubiquitous and a part of everyday life. Nutrition 

disclosures greet us at breakfast; low tire pressure warnings sound off driving 

to work; signs saying “danger – do not enter” block construction sites; and 

skull and crossbones, alcohol warning labels, Drug Facts boxes, and written 

and graphic visual tobacco warnings appear on packages around the world. 

Common misperceptions about warnings are that they often are ignored, or 

they backfire (boomerang), with the audience doing exactly the opposite of 

the proposed behavior change.1 Statements in disclosures are often derided as 

containing legalese, or mouse print, in which vague qualifications, such as “Void 

where prohibited” and “Use only as directed,” are used with mind-numbing 

repetitiveness.2, 3 

Yet, when taking into account audience characteristics, prior beliefs, message 

content, and proper delivery modes, warnings and disclosures can be effective 

communication tools and remedies for consumer and public health policy. For 

example, the Federal Trade Commission (FTC) has long encouraged the use of 

clear and conspicuous disclosures to prevent possible deception and unfairness 

from ad claims.4-6 Specifically, the qualification and disclosure of ambiguous 

and misleading environmental benefit claims (“Environmentally Safe,” “Clean 

Energy,” “Carbon Neutral”) have been a priority in cases and guides over the 

years.7 Other examples include encouraging clear and conspicuous disclosures 

for misleading online ad claims,8 and qualifying material connections not 

expected by consumers between endorsers (including bloggers) and promoted 

companies.9 Likewise, the FDA has advocated warnings and disclosures to 

benefit consumers and public health. This includes the use of black box 

warnings for prescription drugs with potentially serious risks and side effects,10 

the future inclusion of graphic visual warnings on tobacco packages with text 

warnings,11 and Nutrition Facts and Drug Facts information. 
150 | Chapter 15: Warnings and Disclosures
	

Information disclosures represent potentially helpful statements that can 

clarify, deflate, or reduce misleading impressions from ad, package, or other 

claims in the marketplace.2, 12, 13 Such statements can include (1) an affirmative 

disclosure, in which a marketer is required to disclose certain information 14 

or (2) a disclosure that is more voluntary in nature. The affirmative (required) 

disclosure can be negative, triggered, or mandated. Examples of negative 

disclosures include corrective advertising, in which the advertiser is required 

to correct misleading impressions likely to linger in the minds of consumers 

(e.g., the FTC Listerine case).15, 16 Other negative disclosures include warnings, 

defined as “a special class of disclosures for the purpose of alerting consumers 

to certain risks or harms from a product or service.”12 Affirmative disclosures 

are sometimes triggered (e.g., if one mentions “cholesterol,” they must disclose 

saturated fat levels)6 or mandated for an entire industry (e.g., tobacco package 

warnings). In other instances, disclosures are more voluntary in nature, such 

as current front-of-package nutrition symbols (e.g., traffic lights) sponsored by 

U.K. grocery store chains.17 

What does the research evidence say about warnings and disclosures? 

Warning research. Research has shown that warnings can communicate 

benefits and risks to consumers successfully, but only if they are appropriately 

designed for the target audience, accounting for initial beliefs, message 

content, message modality, and source and receiver effects. McGuire’s steps 

in information processing (exposure, perception (attention), comprehension, 

agreement (credibility, attitude change), retention, retrieval, decision making 

(intentions), and action (behavior)) provide a key organizing framework for 

research evidence about warning effects.18 These output steps have been 

expanded by McGuire in his Communication-Persuasion Matrix also include 

input variables (source, message, channel, receiver, destination).19 These 

are further refined by Wogalter in his Communication – Human Information 

Processing (C-HIP) Model presented in the following Figure.20 

Communication-human information processing (C-HIP) model

Environmental Stimuli 

Other persons, objects 

lighting, sound, etc. 

Source 

R e c e i v e r

Demographics, person variables 

Channel 

Delivery 

Attention 

Switch 

Attention 

Maintenance 

Comprehension Memory 

Attitudes 

Beliefs 

Motivation 

Behavior 

Source: Wogalter, M. 2006. Communication-Human 

Information Processing (C-HIP) Model.
	

In Wogalter, M., ed., Handbook of Warnings. Lawrence 

Erlbaum Associates, 51-61.
	
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 151
	

For example, several reviews of alcohol warning label effects are organized 

around these input and output variables.21-23 Regarding source effects, 

the words Government Warning are found to improve alcohol warning 

detection times.24 For channel and delivery, audio-only and audio-visual 

formats significantly increased alcohol warning recall compared to video-only 

formats.25 National and state field surveys have shown positive effects of 

the alcohol warning labels on attention.26,27 Experimentation has found that 

visual aids (icons, color, pictorial elements)28 and enhanced conspicuity (size 

and contrast)29 both improve noticeability and recall of the warnings. Alcohol 

warnings are noticed more when they contain fewer characters per inch, 

occupy a larger area, and are more isolated.30 Although frequent drinkers are 

likely to be aware of the text-based alcohol warnings, they perceive these 

warnings as significantly less believable and less favorable than occasional or 

nonusers.31 

Six months following the appearance of the warning label, alcohol 

consumption for pregnant, lighter (non-risk) drinkers declined by a small, 

yet significant, amount.32 In the case of tobacco warnings, the more graphic 

the pictorial warning depiction on tobacco packages, the greater are smoker 

intentions to quit.33 

Although alcohol warning labels and graphic visual tobacco warnings 

have received substantial attention,33-36 many warning areas have not, and 

behavior compliance often is not measured. Such behavioral measures are 

encouraged (e.g., using accident data37), yet there is a need to have adequate 

controls, proper warning design, and exposure evidence to help gauge the 

impact of warnings on behavior. Perhaps the best method to evaluate the 

effectiveness of warnings research is with meta analyses integrating findings 

across empirical studies. In a meta analysis of 15 warning studies for 79 

experimental conditions with controls, warnings increased safe behavior 

for both non-student and student subjects.38 This conclusion held despite 

considerable variance in the absolute level of compliance and a few studies 

displaying boomerang effects. Others have explored moderator effects in meta 

analyses of warning effectiveness, across a broader array of communication 

variables. A meta analysis of moderator effects for more than 44 empirical 

studies found that (1) enhanced vividness, having on-product warnings, 

and less product familiarity increased warning attention; (2) no moderators 

influenced warning comprehension; (3) evaluating shopping (vs. convenience) 

goods increased risk perceptions; and (4) greater product familiarity and higher 

compliance costs increased warning compliance.39 Recently, a meta analysis of 

60 health communication studies (with 584 experimental conditions) revealed 

that message tactics (e.g., using specific cases, social consequences, other 

referencing, prevention focus) and audience characteristics (e.g., being female, 

high involvement) significantly influenced health intentions.40 Additional 

reviews offer valuable summaries of warnings and risk communication 

research.41, 42 
152 | Chapter 15: Warnings and Disclosures
	

Disclosure research. Disclosure effects research is not as prolific and, 

arguably, in desperate need for a meta-analysis. However, dual modality 

disclosures, in which video disclosures are accompanied by an audio voiceover, achieve higher levels of message recall than print-only disclosures43-46 

or audio-only disclosures.47 Improving disclosure conspicuity (size – 11 pt. vs. 

8pt.font; contrast – white vs. dark background) enhances recall of disclosure 

messages.2,45 Shorter disclosures (10 words or less) are comprehended better 

than longer disclosures.46 Distractors, such as background noise and ad 

clutter, tend to reduce disclosure awareness. Distinctive peripheral cues (e.g., 

color, celebrities, music) can interfere with viewers’ processing of message 

disclosures — especially if the cue is unrelated to the message.45,49 Yet, when 

related to the message, distinctive cues actually can draw attention into the 

message arguments.49,50 For disclosure content, general advisories and claims 

(e.g., “read the label,” “consult your doctor,” “healthy,” “environmentally 

friendly”) tend not to be comprehended as well as more specific 

information.36,43,47,48,51-54 However, lengthy disclosures should not be used to 

increase specificity. Finally, ability levels (age, education, literacy, knowledge) 

should be considered in the design and content of disclosures, especially for 

senior citizens and children (“Some assembly required” vs. “You have to put 

this together”). 

Experimental research has found that evaluative disclosures (e.g., 

characterizing the per-serving level of the nutrient to be “high” as determined 

by the FDA) can be effective in reducing misperceptions and inaccurate 

generalizations from nutrition claims (e.g., “No Cholesterol” and “1/3 Less 

Salt”) when related nutrients are at high levels.51,52 Yet, when the product 

is perceived to be “good for you” (e.g., soup), the effect of disclosing high 

sodium content depends on nutrition knowledge levels.52 When products are 

viewed as less nutritious (e.g., margarine), the disclosures work regardless of 

knowledge levels.51 Based on processing research, the FTC developed its “Clear 

and Conspicuous Standard” (CCS) in 1970 for effectively presenting disclosures 

in TV ads and for strengthening disclosure remedies in deception and 

unfairness cases. These elements include (1) dual modality, (2) sufficient size, 

(3) background contrast, (4) single color background, (5) sufficient duration, 

(6) no distracting sounds, (7) immediately following claims and (8) consider 

the audience (e.g., children). Content analysis of the adherence of televised 

ad disclosures to the FTC’s CCS found that 25% of prime time TV ads in 1990 

contained disclosures, yet none had all of the CCS elements.55 In 2002, 67% of 

TV ads contained disclosures, yet adherence had either declined or remained 

unchanged since 1990 for most of the CCS elements.13 

Theoretical support. Almost 60 years of research and theory development 

has been conducted on the primary mechanism and context for warnings: 

fear appeals. This research has had three primary independent variables: fear, 

perceived threat, and perceived efficacy.56-58 Typically, researchers manipulate 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 153
	

fear appeal (or warning) strength and assess its immediate impact on evoked 

fear.33, 35 Perceived threat has two components: perceived threat severity 

and perceived threat susceptibility. Perceived efficacy consists of perceived 

response efficacy (i.e., the belief that the recommended response works in 

reducing the perceived threat) and perceived self-efficacy (i.e., the belief 

about one’s ability to perform the recommended response).58 Unfortunately, 

the efficacy elements are often neglected, yet can serve as key drivers of 

preventive effectiveness for consumers. 

Early theoretical work proposed an inverted-U relationship between 

fear intensity and persuasiveness. 59, 60 However, this has not received 

consistent support.58 Indeed, considerable evidence suggests a positive linear 

relationship, with stronger fear-arousing conditions producing greater message 

acceptance.61-65 In a meta-analysis of more than 100 fear appeal articles, Witte 

and Allen58 conclude that “the stronger the fear aroused by a fear appeal, the 

more persuasive it is” (p. 601). Other strategies, such as offering a solution 

to the warning to help objective processing (e.g., 1-800-QUIT-NOW), are at 

the heart of the Parallel Response Model63 and the Health Belief Model.66 

An evaluation of the warning’s impact on all Protection Motivation Theory 

(PMT) elements (i.e., evoked fear, perceived threat (severity, susceptibility), 

and perceived efficacy (response efficacy, self-efficacy))56-58, 67 is preferable in 

gauging effectiveness of warning outcomes. 

Accounting for initial opinions and prior involvement of the target audience 

is essential in evaluating effects of warnings and fear appeals. For example, 

the use of strong graphic visual warnings may be needed to counteract 

some smokers’ biased and entrenched initial opinions about smoking and 

quitting.33,35,49,68 As supporting theory, the Elaboration Likelihood Model (ELM) 

accounts for elements that affect the persuasiveness of warnings, including the 

target audience’s initial opinion, motivation, ability, and opportunity to process 

warning information, message cogency, and other peripheral processing 

cues.49,69 

Most disclosure research has focused on regulatory, public health, or mediarelated questions, without supporting theory. However, in Andrews et al.,51 

Spreading Activation Theory70 is used to demonstrate how concepts that are 

primed (e.g., a “No Cholesterol” claim) might spread to an expanding set of 

nodes in a memory network (e.g., “Low Fat” inferences) or to fewer nodes 

due to disclosure information (e.g., “Contains 14 grams of fat per serving – an 

amount determined to be high by the FDA”). Clearly, however, there is room 

for greater theoretical development in disclosure research. 
 

154 | Chapter 15: Warnings and Disclosures
	

What general practical advice about warnings and disclosures can the 

evidence support? 

What belongs in a warning or disclosure? This important question can 

be answered by following a series of steps in developing warning/disclosure 

content proposed by Fischhoff et al.71 First, determine from experts what 

information is most critical to understanding how a risk is created and 

communicated (i.e., “What Matters”?). Second, assess consumers’ current 

beliefs regarding those facts (i.e., their “mental models”). Third, design 

messages focused on the critical gaps between what consumers know and 

what they need to know. Fourth, consumer testing should be used to evaluate 

the effectiveness of those messages in closing the gaps. Fifth, develop and 

evaluate a delivery mechanism capable (e.g., message channels and media) of 

drawing actual consumers’ interest. 

Matching warnings and disclosures with audience processing objectives. 

Once content is set, the warning or disclosure should be matched with 

the target audience’s appropriate stage(s) in information processing (e.g., 

exposure? awareness? comprehension? behavior? all of these?). Wilkie14 

illustrates these options in his landslide warning example in “Welcome to 

Mount Hazard in FTC National Park.” Options might range from the more 

cognitive (e.g., a “Danger – Landslides” sign; print literature with statistics; trail 

hazard signs; PSAs on safety measures) to the more behavioral (e.g., signing a 

release paper with a “cooling off” period; blocking trails). 

Factors influencing availability and processing of warnings and disclosures.

Even if content and communication objectives are correctly matched, certain 

audience characteristics, organization, and format issues can affect the 

availability and processing of warnings and disclosures.72 Effectiveness is 

enhanced when warning or disclosure frequency is increased, is dramatic or 

sensational, is immediate to the risk, is personally relevant, and when risk 

immunity is reduced. It also helps to reduce the number of alternatives to 

process, have sufficient processing time, provide proper framing (e.g., per 

trip vs. lifetime), format (e.g., symbols, color, type size), organization, and 

offer an expected hierarchy of warning information. The following hierarchy 

is suggested based on the natural order for which consumers are likely to use 

warning information: (1) What is the product? (2) What are its benefits and 

risks, (3) How should it be used? (4) What risks are there in use? (5) How can 

these risks be avoided? (6) What should be done if the product is not properly 

used? 73 

Unintended consequences: why do consumers fail to attend to warnings? 

Several errors by designers can lead to an inability of consumers to attend 

to warnings. As noted by Stewart and Martin,74 these include (1) inadequate 

measures of attention or recall (e.g., warning recall is not the same as message 

recall), (2) warning information that is not personally relevant, (3) consumers 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 155
	

may be already familiar with information, (4) consumers may be distracted 

from the information, and (5) consumers may be desensitized after repeated 

exposures (especially with false alarms, incorrect warnings, being more 

extreme than necessary, no immediate harm). Also, trust of the warning source 

is important in ensuring attention (e.g., countering teen reactance). 

Cautions and vulnerable populations. Finally, in addition to making sure that 

the warnings and disclosures are clear and conspicuous, and in the right media 

channels, caution is advised when focusing on vulnerable populations. When 

appealing to seniors, children, and non-native speakers, literacy and learning 

deficits are likely to reduce exposure, recall, comprehension, and coping 

strategies when presented with warning and disclosure information.75 Yet, 

warnings and disclosures often are not delivered in a vacuum. Entire integrated 

communication efforts help,20 as found in the delivery of prescription drug 

warning information (e.g., black box information, patient inserts, labeling, 

medication guides, pharmacy leaflets, and direct-to-consumer ads). 

The evaluation of warning and disclosure communication

Evaluating marketing communications, such as warnings and disclosures, 

usually involves (1) focus groups (copy and rough stage development), (2) copy 

testing (pretests), and (3) tracking (post-tests).76 Four major study designs 

are possible: (1) quasi-experiments in the field (full-scale evaluation), (2) 

experiments in the field (field tests), (3) quasi-experiments in the lab (audience 

subgroup tests without random assignment), and (4) experiments in the lab 

(random assignment in controlled copy tests).77 

No budget. In this challenging scenario, tests of warnings and disclosures 

may be limited to the use of student subjects in academic environments 

or clinical patients affected by the communication. Although students may 

respond to protection motivation or elaboration likelihood measures that 

assess warnings or disclosures, such samples may lack external validity and 

generalizability.78 For example, a lack of direct experience with the product and 

its warnings may lead to highly inconsistent correlations of product warning 

attitudes with actual behavior.79 Usually, focus groups in quasi-experiment 

studies in the lab can offer insights into the warning and disclosure stimuli, but 

cannot be used for definitive cause and effect conclusions.78,80 Other creative 

possibilities include the tracking of reactions to specific company warnings 

and disclosures on search engines that compile thousands of blog sites (e.g., 

www.blogpulse.com). Yet, this also can be problematic due to the convenience 

nature of the sample and viewpoints. 

Modest budget. Here, both focus groups (or cognitive interviews in 

pretesting), as well as controlled experiments are possible that randomly assign 

respondents to test (warning) and control (no warning) groups using covariates 

of major demographic variables.33,35-36 With adequate confound checks (i.e., 
 

 

156 | Chapter 15: Warnings and Disclosures
	

measuring what the warnings should not influence),81 use of attention filters,82 

and target audience screening, online experiments can be run to help not only 

with internal validity, but generalizability issues as well. 

Serious budget. One gold standard for evaluating public health initiatives is 

that of the National Youth Anti-Drug Media Campaign, which spent upwards of 

$100 to $200 million yearly since 1998 and used focus groups,83 copy tests with 

controls,76,84 and longitudinal tracking of attitudes, intentions and behaviors.85 

Although the impact of the campaign has been debated over the years,77,86 

including the need for an initial baseline tracking measure, it nonetheless 

provides an example of the full range of evaluation tools from focus groups 

to copy tests to tracking. A serious budget would allow such a comprehensive 

effort in the evaluation of warnings and disclosures used as part of major public 

health programs. 

Conclusions 

Warnings and disclosures are ubiquitous and a part of everyday life. Common 

misperceptions about warnings and disclosures are that they often are ignored 

due to their design (e.g., mouse print, legalese) or can backfire. Moreover, 

warnings and disclosures cannot compensate for product design flaws, and the 

effects of warnings and disclosures may be temporary when not reinforced. 

However, this review of nearly six decades of research evidence shows that 

when accounting for audience characteristics, prior beliefs, message content, 

and proper delivery modes, warnings and disclosures can indeed be effective 

communication tools and remedies for consumer and public health policy. 

Additional resources

1. Andrews, J.C. and Netemeyer, R.G. (1996). Alcohol warning label effects: Socialization, addiction, 

and public policy issues. In R. P. Hill (Ed.), Marketing and Consumer Research in the Public 

Interest, Thousand Oaks, CA: Sage, 153-175. This chapter reviews alcohol warning label research, 

then offers theoretical explanations for resistance to alcohol warning labels by at-risk groups and 

concludes by examining the alcohol socialization process, models of addiction, and public policy 

alternatives. 

2. Argo, J.J. and Main, K. J. (2004). Meta-analyses of the effectiveness of warning labels. Journal 

of Public Policy & Marketing, 23 (2), 193-208. A meta-analysis of over 44 empirical warning 

studies examines their impact across five dimensions of effectiveness: attention, reading and 

comprehension, recall, judgments, and behavioral compliance. 

3. Bettman, J. R., Payne, J. W., and Staelin, R. (1986). Cognitive considerations in designing effective 

labels for presenting risk information. Journal of Public Policy & Marketing, 5, 1-28. This thorough 

review presents how people process risk information, offers general guidelines for designing 

warning labels, and gives specific examples of these guidelines for cleaning agent and drain 

opener products. 

4. Cox, E.P., Wogalter, M.S., Stokes, S.L., and Murff, E.J.T. (1997). Do product warnings increase safe 

behavior? A meta-analysis. Journal of Public Policy & Marketing, 16 (2), 195-204. A meta analysis 

of 15 studies for 79 experimental conditions shows that (1) warnings increase safe behavior and 

(2) this increase occurs for both student and non-student subjects. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 157
	

5. Fischhoff, B., Riley, D., Kovacs, D. C., and Small, M. (1998). What information belongs in 

a warning? A mental models approach. Psychology & Marketing, 15, 663-686. A step-bystep approach is described for determining the information content of warnings, including 

understanding risk estimates, risk processes, and methods to reduce risk. 

6. Hoy, M. G., and Andrews, J.C. (2004). Adherence of prime-time televised advertising disclosures 

to the “clear and conspicuous” standard: 1990 versus 2002. Journal of Public Policy & Marketing, 

23 (2), 170-182. In a content analysis of over 1600 prime-time TV commercials in 2002, over 2/3 

contained disclosures, yet adherence to most of the FTC’s clear and conspicuous elements for 

the disclosures had either declined or remained unchanged compared to 1990. 

7. Keller, P. A., and Lehmann, D. R. (2008). Designing effective health communications: A metaanalysis. Journal of Public Policy & Marketing, 27(2), 117-130. A meta-analysis of 60 health 

communication studies indicates that message tactics and individual characteristics interact to 

determine health intentions. 

8. Kees, J., Burton, S., Andrews, J.C., and Kozup, J. (2010). Understanding how graphic pictorial 

warnings work on cigarette packaging. Journal of Public Policy & Marketing, 29 (2), 265-276. A 

between-subjects, controlled experiment with over 500 smokers indicates that stronger (versus 

moderate or less) graphic visual warnings strengthen smokers’ intentions to quit and that evoked 

fear fully mediates the effect of the graphic visual warning on intentions to quit. 

9. Morris, L.A., Mazis, M.B. and Barofsky, I. (Eds.) (1980). Banbury Report 6: Product Labeling and 

Health Risks. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory. This edited volume provides 

one of the first compilations of readings on product warning labels and health risks based on a 

conference held at the Banbury Center at Cold Spring Harbor, NY in 1980. 

10. Stewart, D. W. and Martin, I. M. (1994). Intended and unintended consequences of warning 

messages: A review and synthesis of empirical research. Journal of Public Policy & Marketing, 

13, 1-19. The authors first review the diverse literature on warnings, and then discuss their 

potential ineffectiveness due to frequent use, reactive behavior, and poor message design, 

primarily due to a lack of reliance on empirical research. 

11. Witte, K. and Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public 

health campaigns. Health Education & Behavior, 27 (5), 591-615. Fear appeal theory is first 

reviewed and a meta-analysis of more than 100 fear appeal studies is conducted showing that 

strong fear appeals and high efficacy messages produce the greatest behavior changes. 

12. Wogalter, M.S., DeJoy, D.M. and Laughery, K.R. (Eds.) (1999). Warnings and Risk 

Communication. London: Taylor & Francis. This edited volume offers an earlier review of the 

warnings and risk communication literature, organized by stages of information processing and 

concludes with a discussion of practical and legal aspects of warnings. 

Endnotes

1 Bushman, B.J. (2006). Effects of warning and information labels on attraction to television violence 

in viewers of different ages. Journal of Applied Social Psychology, 36(9), 2073-2078. 

2 Foxman, E. R., Muehling, D.D. & Moore, P.A. (1988). Disclaimer footnotes in ads: Discrepancies 

between purpose and performance. Journal of Public Policy & Marketing, 7, 127-137. 

3 Kriguer, M. (1987, July). Standard disclaimer. Nutworks Electronic Humor Magazine, 5, 1. 

4 Federal Trade Commission. (1979, June 1). Consumer Information Remedies. Washington, DC: U.S. 

Federal Trade Commission, 1-319. 

5 Federal Trade Commission. (1983, October 14). Deception Policy Statement. Washington, DC: U.S. 

Federal Trade Commission, 1-19. 

6 Federal Trade Commission. (1994 May 13). Enforcement Policy Statement on Food Advertising. 

Washington, DC: U.S. Federal Trade Commission, 1-28. 

7 Federal Trade Commission. (1992 July 28). Guides for the Use of Environmental Marketing Claims. 

Washington, DC: U.S. Federal Trade Commission, 1-27 (revised 1996, 1998, and 2010). 
158 | Chapter 15: Warnings and Disclosures
	

8 Federal Trade Commission. (2000, May 3). Dot Com Disclosures: Information About Online 

Advertising. Washington, DC: U.S. Federal Trade Commission, 1-83. 

9 Federal Trade Commission. (2009, October 5). Guides Concerning the Use of Endorsements and 

Testimonials in Advertising. Washington, DC: U.S. Federal Trade Commission, 1-12. 

10 Food and Drug Administration. (2006, January). Guidance for industry: Warnings and Precautions, 

Contraindications, and Boxed Warning Sections of Labeling for Human Prescription Drug and 

Biological Products — Content and Format. Rockville, MD: U.S. Food & Drug Administration, 1-14. 

11 Food and Drug Administration. (2010, August 25). Agency information collection activities; 

Submission for office of management and budget review; Comment request; Experimental study 

of graphic cigarette warning labels. Federal Register. 75 (164), 52352-52355. 

12 Andrews, J.C. (2007). Consumer protection. In G. Gundlach, L. Block, & W. Wilkie (eds.), 

Explorations of Marketing in Society. Mason, OH: Thomson, 302-322. 

13 Hoy, M. G., and Andrews, J.C. (2004). Adherence of prime-time televised advertising disclosures 

to the “clear and conspicuous” standard: 1990 versus 2002. Journal of Public Policy & Marketing, 

23 (2), 170-182. 

14 Wilkie, W.L. (1985). Affirmative disclosure at the FTC: Objectives for the remedy and outcomes of 

past orders. Journal of Public Policy & Marketing, 4, 91-111. 

15 Wilkie, W.L., McNeil, D.B., and Mazis, M.B. (1984). Marketing’s ‘scarlet letter’: The theory and 

practice of corrective advertising. Journal of Marketing, 48 (2), 11-31. 

16 Mazis, M.B. (2001). FTC v. Novartis: The return of corrective advertising?” Journal of Public Policy 

& Marketing, 20 (1), 114-122. 

17 Andrews, J.C., Burton, S., and Kees, J. (2011). Is simpler always better? Consumer evaluations of 

front-of-package nutrition symbols. Journal of Public Policy & Marketing, 30 (2), forthcoming. 

18 McGuire, W.J. (1976). Some internal psychological factors influencing consumer choice. Journal of 

Consumer Research, 2 (4), 302-319. 

19 McGuire, W.J. (1980). The communication-persuasion model and health-risk labeling. In L.A. 

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20 Wogalter, M.S. (2006). The communication-human information processing (C-HIP) model. In M.S. 

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21 Andrews, J.C. and Netemeyer, R.G. (1996). Alcohol warning label effects: Socialization, addiction, 

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Interest, Thousand Oaks, CA: Sage, 153-175. 

22 Hilton, M. E. (1993). An overview of recent findings on alcohol beverage warning labels. Journal of 

Public Policy & Marketing, 12(1), 1-9. 

23 MacKinnon, D.P. (1995). Review of the effects of the alcohol warning label. In R.R. Watson (Ed.) 

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24 Godfrey, S.S., Laughery, K.R., Young, S.L., Vaubel, K.P., Brelsford, J.W., Laughery, K.A., and Horn, 

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25 Ducoffe, S.J. (1990). The impact of product usage warnings in alcohol beverage advertisements. 

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26 Mazis, M. B., Morris, L. A., and Swasy, J. L. (1991). An evaluation of the alcohol warning label: 

Initial survey results. Journal of Public Policy & Marketing, 10(1), 229-241. 

27 Scammon, D. L., Mayer, R. N., and Smith, K. R. (1991). Alcohol warnings: How do you know when 

you have had one too many? Journal of Public Policy & Marketing, 10(1), 214-228. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 159
	

28 Laughery, K. R., Young, S. L., Vaubel, K. P., and Brelsford, J. W. (1993). The noticeability of 

warnings on alcoholic beverage containers. Journal of Public Policy & Marketing, 12(1), 38-56. 

29 Barlow, T., and Wogalter, M. S. (1991). Alcohol beverage warnings in print advertisements. In 

Proceedings of the Human Factors Society-35th Annual Meeting (Vol. 1, pp. 451-455). Santa 

Monica, CAL Human Factors Society. 

30 Swasy, J.L., Mazis, M.B. and Morris, L. A. (1992). Message design characteristics affecting alcohol 

warning message noticeability and legibility. Paper presented at the Marketing and Public Policy 

Conference, Washington, DC. 

31 Andrews, J. C., Netemeyer, R. G., and Durvasula, S. (1991). Effects of consumption frequency 

on believability and attitudes toward alcohol warning labels. Journal of Consumer Affairs, 25(2), 

323-338. 

32 Hankin, J. R., Firestone, I. K., Sloan, J. J., Ager, J. W., and Goodman, A. C., et al. (1993). The impact 

of the alcohol warning label on drinking during pregnancy. Journal of Public Policy & Marketing, 

12(1), 10-18. 

33 Kees, J., Burton, S., Andrews, J.C., and Kozup, J. (2010). Understanding how graphic pictorial 

warnings work on cigarette packaging. Journal of Public Policy & Marketing, 29 (2), 265-276. 

34 Hammond, D. (2009, February). Tobacco Labelling & Packaging Toolkit: A Guide to FCTC Article 

11. University of Waterloo, Department of Health Studies, 1-132. 

35 Kees, J., Burton, S., Andrews, J.C., and Kozup, J. (2006). Tests of graphic visuals and cigarette 

package warning combinations: Implications for the framework convention on tobacco control. 

Journal of Public Policy & Marketing, 25 (2), 212-223. 

36 Peters, E., Romer, D., Slovic, P., Jamieson, K. H., Wharfield, L., et al. (2007). The impact and 

acceptability of Canadian-style cigarette warning labels among U.S. smokers and nonsmokers. 

Nicotine & Tobacco Research, 9, 473-481. 

37 Arndt, S.R., Ayres, T.J., McCarthy, R.L., Schmidt, R.A., Wood, C.T., and Young, D.E. (1998). Warning 

labels and accident data. In Proceedings of the Human Factors Society – 42nd Annual Meeting 

(Vol. 1, pp. 550-553). Santa Monica, CA: Human Factors Society. 

38 Cox, E.P., Wogalter, M.S., Stokes, S.L., and Murff, E.J.T. (1997). Do product warnings increase safe 

behavior? A meta-analysis. Journal of Public Policy & Marketing, 16 (2), 195-204. 

39 Argo, J.J. and Main, K. J. (2004). Meta-analyses of the effectiveness of warning labels. Journal of 

Public Policy & Marketing, 23 (2), 193-208. 

40 Keller, P. A., and Lehmann, D. R. (2008). Designing effective health communications: A metaanalysis. Journal of Public Policy & Marketing, 27(2), 117-130. 

41 Morris, L.A., Mazis, M.B. Barofsky, I. (Eds.) (1980). Banbury Report 6: Product Labeling and Health 

Risks. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory. 

42 Wogalter,M.S., DeJoy, D.M. and Laughery, K.R. (Eds.) (1999). Warnings and Risk Communication. 

London: Taylor & Francis. 

43 Houston, M.J. and Rothschild, M.L. (1980). Policy-related experiments on information provision: A 

normative model and explication. Journal of Marketing Research, 17 (4), 432-447. 

44 Smith, S.J. (1990). The impact of product usage warnings in alcoholic beverage advertising. 

Journal of Public Policy & Marketing, 9, 16-29. 

45 Barlow, T. and Wogalter, M.S. (1993). Alcoholic beverage warnings in magazine and television 

advertisements. Journal of Consumer Research, 20 (1), 147-156. 

46 Murray, N.M., Manrai, L.A., and Manrai, A.K. (1993). Public policy relating to consumer 

comprehension of television commercials: A review and some empirical results. Journal of 

Consumer Policy, 16 (2), 145-170. 

47 Morris, L.A., Mazis, M.B. and Brinberg, D. (1989). Risk disclosures in televised prescription drug 

advertising to consumers, Journal of Public Policy & Marketing, 8, 64-80. 
160 | Chapter 15: Warnings and Disclosures
	

48 Edell, J. A. and Staelin, R. (1983). The information processing of pictures in print advertisements. 

Journal of Consumer Research, 10 (1), 45-61. 

49 Petty, R. E., and Cacioppo, J. T. (1986). Communication and Persuasion: Central and Peripheral 

Routes to Attitude Change. New York, NY: Springer-Verlag. 

50 Andrews, J.C., Akhter, S., Durvasula, S. and Muehling, D. (1992). The effects of advertising 

distinctiveness and message content involvement on cognitive and affective responses to 

advertising. Journal of Current Issues & Research in Advertising, 14 (1), pp. 45-58. 

51 Andrews, J.C., Netemeyer, R.G. and Burton, S. (1998). Consumer generalization of nutrient 

content claims in advertising. Journal of Marketing, 62 (October), 62-75. 

52 Andrews, J.C., Burton, S., and Netemeyer, R.G. (2000). Are some comparative nutrition claims 

misleading? The role of nutrition knowledge, ad claim type, and disclosure conditions. Journal of 

Advertising, 29 (3), 29-42. 

53 Laughery, K. R., Young, S. L., Vaubel, K. P., and Brelsford, J. W. (1993). The noticeability of 

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54 Maronick, T.J. and Andrews, J.C. (1999). The role of qualifying language on consumer perceptions 

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55 Hoy, M.G. and Stankey, M.J. (1993). Structural characteristics of televised advertising disclosures: 

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56 Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. Journal 

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57 Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A 

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58 Witte, K. and Allen, M. (2000). A meta-analysis of fear appeals: Implications for effective public 

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59 Janis, I.L. and Feshbach, S. (1953). Effects of fear-arousing communications. Journal of Abnormal 

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60 Ray, M.L. and Wilkie, W.L. (1970). Fear: The potential of an appeal neglected by marketing. 

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61 Berkowitz, L. and Cottingham, D. (1960). The interest value and relevance of fear arousing 

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84 Foley, D. and Pechmann, C. (2004). The national youth anti-drug media campaign copy test 

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NJ: Lawrence Erlbaum Associates. 

 

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Chapter 16: Human Factors

Gavin Huntley-Fenner, PhD - Huntley-Fenner Advisors, Inc. 

Summary

Human factors is a multi-disciplinary behavioral science concerned with 

human perceptual, cognitive, and behavioral capabilities and limitations in realworld settings. One goal of this applied field is to understand the psychological 

factors underlying effective hazard communications. 

What does the science say about this aspect of communication? 

Historically, human factors engineering emerged to study and prevent 

pilot errors in WWII military aircraft and operator errors in manufacturing. 

Today, the field is highly interdisciplinary and applied well beyond military and 

manufacturing contexts. Contributing disciplines include natural sciences, such 

as biology and physics; social sciences, such as psychology and sociology; and 

applied fields, such as industrial engineering and ergonomics. Human factors 

researchers and practitioners include cognitive psychologists, ergonomists, and 

industrial engineers. A hallmark of the human factors mindset is that product 

(or system) designers should seek to build products (design systems) that 

function safely and effectively in a broad range of real-world conditions, taking 

into account foreseeable human shortcomings. 

Human factors science developed in recognition that human error is a 

significant contributor to accidents and injuries. Researchers who study 

patterns of injury data, such as motor vehicle accident reports, partition 

causes into product design factors (e.g., brake failure, airbag malfunction), 

environmental factors (e.g., lighting, weather), and human factors (e.g., 

distraction, fatigue).1

 Human factors have been estimated to cause, or 

contribute to, 60% to 90% of motor vehicle accidents2,3 and more than 80% 

of medical errors.4 Detailed forensic analyses of specific events often find 

breakdowns in visual or auditory processing, attention, comprehension, 

reasoning, and task execution. 

Human factors researchers address human error, in part, by studying the 

impacts of visual and auditory communications, such as on-product warnings, 

workplace signs, and alarms, on perceived risk and safety-related behavior. In 

this research, communication is often conceptualized in terms of a source or 

originator, a channel or mode of communication, and a receiver or 
 

 

 

164 | Chapter 16: Human Factors
	

target.5 Each element can affect risk-related beliefs and behavior. For example, 

presenting information consistently through mutually reinforcing visual and 

auditory channels can facilitate comprehension. Because each target person 

has limited information processing capacity, important safety messages can 

become lost among less critical information, making it essential to set priorities. 

The volume of published research concerning the impact of communications 

on perceived risk has grown sharply in the past 40 years.6 Much current 

research concerns the effects of warning format and content. Studies 

mostly occur in laboratory settings and simulated real world environments.7 

Researchers use human subject experiments, surveys, and focus groups to 

examine the impact of formatting, such as color, font size/shape, symbols and 

positioning (e.g., placing safety information on the product versus embedding 

it into instructions). Researchers measure changes in safety-related attitudes 

and beliefs, behavioral intentions, and, in some cases, actual safety-related 

behavior. 

A general observation in the literature is that signal words (e.g., DANGER, 

WARNING, CAUTION), safety alert symbols (e.g., flames for fire hazards), 

and even colors (e.g., red for DANGER) can affect noticing of warnings, 

understanding of information, and even behavioral intentions. Additionally, 

environmental conditions (e.g., daylight, ambient sound levels) and target 

demographic factors, such as age, are important considerations when 

determining the potential visibility of signs, audibility of alarms, or legibility of 

written information. Nevertheless, laboratory studies find that the impact of 

such characteristics on actual safety-related behavior declines as a function of 

increasing product familiarity and difficulty of complying with instructions (even 

if the difficulty is having to walk a short distance to procure safety goggles).8 

Moreover, compliance is higher in laboratory situations than in the real world.9 

Many research findings have been incorporated into practice via standards and 

guidelines for industry (e.g., ANSI Z535 “Safety Alerting Standards” and ANSI 

AAMI HE75-2009 “Human factors engineering - Design of medical devices”). 

However, the relatively few studies of real world outcomes show mixed 

results. On one hand, some studies have found desired changes in attitudes 

and behavior, for example, smokers exposed to graphic warnings on cigarette 

packages appear to be more motivated to quit smoking10; on the other hand, 

there is no evidence of declining injury rates relative to enhanced formatting 

of warnings.11 In sum, interventions can predictably affect behavior in the 

laboratory and potentially change attitudes. However, real world behavioral 

change in response to hazard communications remains limited. 

An important limiting factor is the individual perception of risk, one of the 

best-studied areas in cognitive psychology. Many classic findings are reviewed 

in Kahneman et al. (1982).12 These perceptions are subject to systematic 

biases; for example, being swayed by whether facts are presented in ways 

that emphasize risks or benefits. Because many adverse events are quite rare, 
 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 165
	

people must rely on such imperfect inferences when estimating their risks.13 

Finally, emotions affect the perception of risk14; therefore, information that 

stimulates worry, fear, or anxiety can color our assessment of risk–benefit 

related facts15 (see also Chapter 10). 

Cognitive and social psychologists have also examined the effects of stable 

individual differences, including age, gender, culture, and other demographic 

factors, on how risk communications are perceived.16 Some of the most 

important of these factors are literacy and language barriers (see also Chapters 

9, 11, and 14). The research here contains some surprising findings: although 

symbols are intuitively a way to communicate across language barriers, 

comprehension of common symbols used in hazard communications varies 

significantly across cultures.17 For example, in 1971 thousands of Iraqi farmers 

were poisoned when they ate imported seed wheat instead of planting it.18 The 

seed, which was not intended for ingestion, had been treated with a fungicide, 

dyed red, and placed into bags marked with the skull and crossbones symbol19 

— the universal symbol of hazard. It is not necessary to cross international 

borders to find cultural disparities in risk perception. In the United States, 

African Americans are more likely to distrust the medical establishment, which 

contributes to marked racial disparities in health.20 The credibility of the source 

of hazard communications can vary tremendously even within sub-populations; 

for example, medical professionals view government health authorities as 

a credible source of health risk information,21 whereas many anti-vaccine 

activists do not. 

A general challenge for all hazard communications is that the modern world 

is full of risk information, especially in the form of warnings. Legally mandated 

on-product warnings have a long history. An 1829 New York State law requiring 

labeling for caustic substances and poisons was likely the first legal mandate 

for on-product warnings in the United States.22 By the 1850s, use of the skull 

and crossbones to warn of possible death was common. Design specifications 

for workplace safety signs began to emerge in the early 20th century.23 Yet 

until the mid-to-late 1960s, with the advent of on-package warnings for 

cigarettes, on-product warnings were confined to a narrow range of products 

such as medicines and industrial products.24 Today, we live in what some 

have described as a “culture of warnings.”25 In the United States, consumer 

products, medications and medical devices usually have associated hazard 

communications. Warnings and other health risk information appear in menus 

and even on buildings. Some of this change reflects the sharp rise in federally 

mandated on-product labeling since the mid- to late-1960s.26 Litigation has 

prompted additional warnings.5 As a consequence of the mass exposure to 

hazard communications, the American public is sometimes indifferent to news 

about risk.27 Despite this state of affairs, there are some recommendations to 

be made that the science can support. 
166 | Chapter 16: Human Factors
	

What general practical advice can the science support?

1. Use a risk-based communications design to streamline messages and 

create structured communication across multiple platforms/channels. 

Audiences are more likely to pay attention to messages that are succinct, 

relevant, and timely. The prominence of hazard information should be defined 

by the degree of risks that people face and the usefulness of the information 

in reducing them — where risk is defined in terms of the severity and 

probability of negative outcomes (see also Chapters 6 and 7). For structure 

hazard communications that are embedded in long-form documents, such 

as instructions or manuals: repeat only information about higher risks 

and use repetition across channels strategically to enhance retention and 

comprehension (e.g., drawings can reinforce key information in text-based 

messages). 

2. Use research to guide choices and avoid the failures and unintended 

consequences that can arise when risk messages are counterintuitive 

to recipients. The field of human factors contains a number of surprising 

or counterintuitive findings (some of which were discussed here; see also 

Chapters 3, 7, and 8). For example, emphasizing the expertise of authorities 

with the intention of reassuring an audience can sometimes have unintended 

consequences. Confidence declines and fear increases when experts appear 

out-of-touch or are perceived as belonging to a mistrusted government office. 

Message designers should beware of the possibility that a planned message 

could be misinterpreted due to messenger, content, or audience characteristics 

and test messages, rather than rely on their own intuitions. 

Each risk poses its own communication challenges. There is, fortunately, 

a large body of science to guide selection of message elements. See the 

Resources section for further information. In addition, organizations such 

as such as the Human Factors and Ergonomics Society (www.hfes.org) have 

publicly searchable, peer reviewed research pertaining to various audiences, 

messages and hazards. 

3. Target your audiences when they are most likely to be receptive to the 

content of you messages. As mentioned, modern environments are awash 

in risk (and benefit) information that is routinely overlooked. Audiences have 

limited attention capacity. Studies find that warnings are more effective when 

the recipient of the information is safety-minded: alert and intentionally 

seeking such information.28 Thus, communicators should try to engage the 

target audience when they are likely to be receptive. For example, persons 

searching a website for medical information may be more attentive to 

messages regarding the specific health risks associated with treatment during 

the search. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 167
	

4. To boost message credibility, be sure that both the messages and the 

messengers create trust. The credibility of messages is context dependent 

and can be influenced by the source as well as the message content.29 It 

should not be assumed that a source that is credible for a message on vaccine 

safety would be similarly credible for a message on the risk of food borne 

illness. When uncertain about which sources an audience trusts, consider 

multiple sources, such as “the Surgeon General says...,” and “Pharmacists 

recommend....” One way to identify credible sources and content is to involve 

members of the targeted group in program planning and message pre-testing. 

How does one evaluate communications based on this advice?

A number of best-practice based evaluation frameworks are available in the 

literature. For example in the 1990s, the National Cancer Institute promulgated 

evaluation guidelines in a framework document that organized evaluations 

into phases: “formative,” “process,” “outcome,” and “impact.”30 Formative 

evaluations assess “the strengths and weaknesses of materials or campaign 

strategies before implementation.” Outcome evaluations “obtain descriptive 

data on a project and document the immediate effects of the project on the 

target audience ....” At these stages, which require collection of user data, 

human factors research provides ways to develop appropriate measures, 

testing protocols, and data analyses about changes in attitudes, beliefs, and 

behaviors. 

Caveats about common approaches to formative and outcome assessments 

may be helpful. One approach to formative evaluation involves softwarebased readability analysis to determine message comprehensibility. However, 

most readability analyses focus on vocabulary rather than message content 

or grammar. Therefore, computed reading level scores should be interpreted 

with great caution. It is far preferable to evaluate reading comprehension 

using specific content-based questions (see also Chapters 11 and 14). The 

human factors research literature also contains many examples of outcome 

assessments (see Resources and the discussion above). Most involve small 

groups of test subjects in controlled laboratory conditions. A common measure 

of the effectiveness of hazard communications is to ask study participants for 

their behavioral intention (e.g., Would you comply with a warning about hazard 

x?). Note that behavioral intentions are not always reliable indictors of real 

world choices, as persons often overestimate the likelihood of their compliance 

with warnings.31 

The primary costs of evaluation arise from recruiting human subjects, 

testing, and data evaluation. Such studies can also be time consuming. When 

communicators have not been left the time for extensive evaluations, quick 

email or Internet-based surveys can be very valuable. Note, Internet-based 

approaches should be used with care as their validity can be limited. However, 
168 | Chapter 16: Human Factors 

peer-reviewed research involving commonly used online survey software is 

cited in PubMed.gov. The Table that follows illustrates the tasks involved and 

the investments for the various evaluation types. 

Evaluation tasks and Investments

Type of Evaluation Budget Level

Low Modest

(includes “low”)

Serious

(includes “moderate”)

Formative (pre 

implementation 

assessment

of strengths and 

weaknesses)

• Review message 

content internally 

taking care to 

ensure that the 

communication is 

compliant with any 

applicable standards or 

regulations 

• Review existing 

and related hazard 

communications for 

consistency, problems 

to avoid, and best 

practices 

• Gather and analyze 

any internal data that 

may inform messaging: 

consumer complaints, 

letters, questions to 

call centers, etc. 

• Develop and assess 

multiple messages 

based on internal 

brainstorming; review 

messages with internal 

panels/focus groups 

• Draw on current 

research literature 

regarding message 

• Quantitatively assess 

content, presentation 

of quantitative 

information, source 

credibility, etc. 

• Deploy email or 

Internet-based 

surveys iteratively, 

incorporating feedback 

in successive drafts 

current knowledge of 

hazard and safetyrelated behavioral 

patterns in target 

audience 

• Assess understanding 

of risk for each target 

group 

• Use target audiencebased focus group to 

develop multiple test 

messages 

• Refine final message 

based on group 

feedback, baseline 

knowledge, etc. 

Outcome (descriptive 

data regarding effects 

on target audiences)

• Test messengers/ 

sources/channels; refine 

as needed 

• Track reach in terms 

of media source 

mentions, spikes in 

Internet searches, etc. 

• Monitor published 

reports relating to riskrelated phenomena of 

interest 

• Surveillance of 

publically available 

hazard/injury data 

such as ER visits 

• Assess behavioral 

change following risk 

communication (see 

Resources) 

• Follow up with indepth interviews of 

targeted populations 

to assess reach and 

comprehension of 

messages 

Conclusion

The field of human factors can help guide effective risk communication. The 

role of human factors research in risk communication is to focus attention on 

the limitations and capabilities of human information processing and decisionmaking. Identifying those limitations and capabilities can help enhance our 

ability to conceive and implement a risk communication plan of action that will 

or, at least, mitigate the risk of injury to us or others. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 169
	

Additional resources

1. Human Factors and Ergonomics Society contains links to the society’s publications including: 

Human Factors, Ergonomics in Design, Journal of Cognitive Engineering and Decision Making, and 

HFES Proceedings. http://www.hfes.org/Publications/. 

2. Wogalter, M. S., (Ed.). (2006). Handbook of Warnings. Mahwah, NJ: Erlbaum. A recent review 

talking of general practical and theoretical considerations illustrated with useful cases studies 

and real-world examples. 

3. Bouder, F. and Löfsedt R. (2010). Improving Health and Safety: An Analysis of the HSE’s Risk 

Communication in the 21st Century. Prepared by Kings College London for the UK Health and 

Safety Executive. http://www.hse.gov.uk/research/rrpdf/rr785.pdf 

4. For a brief introduction to how issues related to human factors communications interact to 

affect device safety, see Rich, S. (2008). How human factors lead to medical device adverse 

events. Nursing, 38:6, pp. 62-63. http://www.fda.gov/MedicalDevices/Safety/AlertsandNotices/ 

TipsandArticlesonDeviceSafety/ucm070185.htm 

5. Example of standards regarding human factors and design include ANSI/AAMI HE74:2001, 

Human Factors Design Process for Medical Devices. Arlington, VA: Association for the 

Advancement of Medical Instrumentation, 2001). http://www.aami.org/index.htm 

6. Example of standards regarding human factors and design include ANSI/AAMI HE75:2009, 

Human Factors Engineering - Design of Medical Devices. Arlington, VA: Association for the 

Advancement of Medical Instrumentation, 2010. http://www.aami.org/index.htm 

7. Example of standards regarding human factors and design include ANSI Z535, Safety Alerting 

Standards. http://www.nema.org/stds/z535/ 

8. National Electronic Injury Surveillance System http://www.cpsc.gov/library/neiss.html 

9. Tinker, T. and Vaughan E. (2010). Risk and Crisis Communications: Best Practices for Government 

Agencies and Non-profit Organizations. Booz Allen Hamilton. 

10. Breakwell, G. M. 2007. The Psychology of Risk. Cambridge University Press. 

11. Evaluation Primer on Health Risk Communication Programs. http://www.atsdr.cdc.gov/risk/ 

evalprimer/index.html 

Endnotes

1 Dewar, R.E. and Olson, R. (Eds.), Human Factors in Traffic Safety. Lawyers & Judges Publishing, Tucson, AZ. 

2 Treat, J. R., Tumbas, N. S., McDonald, S. T., Shinar, D., Hume, R. D., Mayer, R. E., Stanisfer, R. L. 

and Castellan, N. J. (1977) Tri-Level Study of the Causes of Traffic Accidents. Report No. DOTHS-034-3-535-77 (TAC). 

3 Rumar, K. (1985). The Role of Perceptual and Cognitive Filters in Observed Behavior, Human 

Behavior in Traffic Safety, Eds. L. Evans and R. Schwing, Plenum Press. 

4 Cooper, J.B., Newbower, R.S., Long, C.D., and Bucknam, M. (2002). Preventable anesthesia 

mishaps: A study of human factors. Quality Management in Health Care. 3:277-282. 

5 Wogalter, M., DeJoy, D., and Loughery, K. (1999). Warnings and Risk Communication. Taylor and 

Francis, Philadelphia, PA. 

6 Miller, J.M. and Lehto, M.R. (2000). Warnings and Safety Instructions: The Annotated Bibliography, 

(4th Edition of Warnings Volume II. An Annotated Bibliography), Fuller Technical Publications, Ann 

Arbor, MI. 

7 Wogalter, M.S., (Ed.) Handbook of Warnings. Mahwah, NJ: Lawrence Erlbaum Associates. 

8 Dingus, T. A., Wreggit, S. S. and Hathaway, J. A. (1993). Warning variables affecting personal 

protective equipment use. Safety Science. 16: 655-673. 
 

170 | Chapter 16: Human Factors
	

9 Huntley-Fenner, G., Harley, E., Trachtman, D., Young D. (2007). ANSI Z535.6 and conspicuity: A test 

of the new state of the art format for instructions. Proceedings, Human Factors and Ergonomics 

Society, 51st Annual Meeting, pp. 1029–1033. 

10 Hammond, D. Fong, G.T. et al. Impact of the graphic Canadian warning labels on adult smoking 

behaviour. Tobacco Control. Vol. 12, No. 4 (December 2003), p.391-395. 

11 Young, S. L., Frantz, J. P., Rhoades, T. P., & Darnell, K. R. (2002). Safety, signs, and labels: Does 

compliance with ANSI Z535 increase compliance with warnings? Professional Safety, pp. 18-23. 

12 Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment Under Uncertainty: Heuristics and Biases. 

New York: Cambridge University Press. 

13 Lichtenstein, S., Slovic, P., Fischhoff, B., Layman, M., Combs, B. (1978). Judged frequency of lethal 

events. Journal of Experimental Psychology: Human Learning and Memory. 4:551–578. 

14 Lowenstein, G.F., Weber, E.U., Hee, C.K. and Welch, N., (2001). Risk as feelings. Psychological 

Bulletin. 127(2), pp. 267–286. 

15 Slovic, P., Finicane, Peters, E. and MacGregor (2004). Risk as analysis and risk as feelings: Some 

thoughts about affect, reason, risk, and rationality. Risk Analysis, c. 24:2. pp. 311-322. 

16 Vaughan, E. (1995). The significance of socioeconomic and ethnic diversity for the risk 

communication process. Risk Analysis, 15, pp. 169-180. 

17 Hesse, R. G., Steele, N. H., Kalsher, M. J., Mont’Alvao, C. (2010). Evaluating hazard symbols for 

the globally harmonized system (GHS) for hazard communication. Human Factors and Ergonomics 

Society Annual Meeting. Proceedings, Safety, pp. 1832-1836(5). 

18 Al-Tikriti, K. Al-Mufti, A.W. (1976). An outbreak of organomercury poisoning among Iraqi farmers. 

Bulletin of the World Health Organization, 53 (Suppl.), pp. 15-21. 

19 Casey S. (1998). Set Phasers on Stun: And Other True Tales of Design, Technology, and Human 

Error. Santa Barbara (CA): Aegean Publishing Company. 

20 Moutsiakis, D.L., Chin, P.N. (2007). Why blacks do not take part in HIV vaccine trials. Journal 

National Medical Association. 99(3), pp. 254-257. 

21 Salmon, D.A., Moulton, L.H., Omer, S.B., Chace, L.M., Klassen, A., Talebian, P., Halsey, N.A. 

(2004). Knowledge, attitudes, and beliefs of school nurses and personnel and associations with 

nonmedical immunization exemptions. Pediatrics. 113(6):e552-9. 

22 Revised Statutes of the State of New York (1829, Sec. 22): No Person is Allowed to Sell Arsenic, 

Prussic Acid, or Any Other Substance or Liquid Usually Denominated Poisonous, Without 

Endorsing on it the Word Poison in a Conspicuous Manner. 

23 Carl, M., Hansen, M.E., 1914, Universal Safety Standards. Workers Compensation Service Bureau. 

24 Some workplace products would have contained warnings in the 1940s and 1950s, for example, 

see the Manufacturing Chemists Association, Guide to Precautionary Labeling of Hazardous 

Chemicals (1944) or the 1950s era National Paint, Varnish and Lacquer Association Labeling 

Guidelines. 

25 See for example, Murphy, C. (2001). Walking back the cat, The Atlantic Monthly, December 2001, 

v. 288 (5), pp. 20–22. 

26 Diedrich, F.J., Wood, C.T., Ayres, T.J. (2001). Analysis of trends in federally mandated warning 

labels. Proceedings, Human Factors and Ergonomics Society Annual Meeting, pp. 838–842. 

27 Huntley-Fenner, G., Wood, C.T., Sala, J.B. Study of the impact of California’s Proposition 65 

warnings on safety related awareness and behaviors. Society for Risk Analysis Proceedings 

Abstracts, San Antonio, TX, December 9–12, 2007. 

28 Ayres, T. J., Gross, M. M., Wood, C. T., Horst, D. P., Beyer, R. R., and Robinson, J. N. (1989). What 

is a warning and when will it work?, Proceedings of the. Human Factors and Ergonomics Society, 

33rd Annual meeting, pp. 426-430. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 171
	

29 Pornpitakpan, C. The persuasiveness of source credibility: A critical review of five decades’ 

evidence. J Appl Soc. Psychol 2004; 34: 243–81 

30 National Cancer Institute. 1992. Making Health Communication Programs Work: A Planner’s 

Guide. Washington, DC: National Cancer Institute, NIH Publication no. 92-1493, pgs. 64-65. 

31 Ayres, T.J., Gross, M.M., Horst, D.P., Wood, C.T., Beyer, R.R., Acomb, D.B., Bjelajac, V.M. Do 

subjective ratings predict warning effectiveness? Proceedings, Human Factors Society 34th Annual 

Meeting, 1990. 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 173
	

Chapter 17: Shared Decision Making

Nananda Col, MD, MPP, MPH, FACP - Maine Medical Center 

Summary

Shared decision making (SDM) interventions attempt to change doctorpatient communication by involving patients in clinical decision making to the 

extent that they desire. Decision aids, a common SDM intervention, decrease 

patient passivity and help patients make choices that are consistent with their 

circumstances, preferences, and values, but their impact on resources and 

clinical outcomes is uncertain. SDM should be encouraged to improve the 

processes and outcomes of health care, and new SDM approaches are needed. 

Introduction

Medical decisions are especially difficult when there are two or more 

reasonable options, and each option has good and bad features that people 

value differently. What is important for one person may be different for 

another, and no clear answer applies to everyone. Shared decision making 

(SDM) interventions help people make more informed choices in partnership 

with their clinicians. Many medical organizations1 recommend SDM, and the 

Patient Protection and Affordable Care Act of 2010 supports a national SDM 

program.2 

SDM refers to the process by which a decision is made: Patients and clinicians 

share information and come to agreement on preferred treatments.3 The 

terms SDM and informed decision making are often used interchangeably, 

though they differ in important ways. Both promote informed decisions, 

and neither presumes that the right course of action is known. However, 

informed decision making interventions need not involve clinicians nor occur 

in a clinical setting. A patient decision aid (DA), a common SDM approach, is 

an intervention designed to help a person decide among treatment options by 

providing objective information about the options and the likely consequences 

(harms and benefits) of each option. Common DAs include videos, interactive 

web programs, or printed material.

 Most are designed to be used by patients, but some target patients and 

practitioners.4,5 The level and type of tailoring varies. Some DAs provide 

quantitative risk information to practitioners to guide individualized care for 

common diseases or genetic mutations. For example, BRCAPRO,6 an interactive 
 

174 | Chapter 17: Shared Decision Making
	

website, assesses the probability of carrying a germline mutation, based on 

family history of cancer. Adjuvant!, another interactive website, estimates the 

10-year risks of breast cancer recurrence or death, informing decisions about 

adjuvant therapy.7,8

 What does the science say about shared decision making? 

Most of what we know about SDM is based on clinical trials of DAs that 

compared outcomes among patients exposed to DAs versus standard care in a 

range of health contexts.9,10 These trials typically addressed one-off screening 

or treatment decisions with short-term measures of effectiveness. Measures 

include: perceptions of being informed, decision satisfaction, decision regret, 

knowledge, perception of risks and benefits, values and expectations about 

treatment and side-effects, treatment preference, perceived usefulness, and 

acceptability. Some measured effect on treatment choice, adherence, quality 

of life, and resource use, typically as secondary or tertiary outcomes. 

Our understanding of how DAs affect decisions draws on cross-sectional 

surveys that describe how people make decisions in different contexts (e.g., 

business, health, law) and test how people’s judgments, reasoning, and 

thinking are affected by aspects of the decision context (e.g., time-pressure, 

emotion, framing). Qualitative methods assess recordings or observations 

of practice, transcripts of people thinking aloud about their reasoning while 

making decisions, and electronic monitoring of people using web sites. 

Quantitative methods assess decision preference, knowledge, affect, cognitions 

(e.g., risk perceptions, judgments, attitudes, and values), and mediating/ 

moderating traits (e.g., cognition, affect, numeracy). These studies often use 

simplified hypothetical choices in non-patient samples. Although people’s 

knowledge, values, and judgments may change with experience, inputs are 

assumed to be integrated using the same decision processes. 

Interest in SDM and decision aids. SDM occurs infrequently, either as a 

process11 or an outcome.12 Participation in SDM can require substantial time 

and attention to process complex risk information and to make difficult — often 

stressful — trade-offs. Patient interest in SDM is understandably variable (19-

68%), with higher interest among the young and educated.13 Patient barriers 

to SDM include being unaware that there is a decision to make, believing that 

clinicians prescribe the only treatment available, discomfort or inexperience 

with SDM, or preconceptions about care. 

It has been difficult to embed DAs into health care settings.14,15 Physician 

barriers include concerns about time, lack of training, pessimism about 

patients’ ability to assume a more active role, believing it is not applicable 

to their patients, the clinical situation, or clinical care patterns, difficulty 

reconciling patient preferences,16,17 and concerns that DA could bias patients to 

choose less expensive options.2 
 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 175
	

Impact of decision aids. Findings from the Cochrane Collaboration review of 

85 randomized trials of DAs10,18 are described here. 

1. Knowledge. DAs improved knowledge of options and outcomes and led to 

more realistic expectations. 

2. Decision processes. DAs helped patients match their values to their 

choices. DAs reduced decisional conflict and passivity in decision making 

and helped the undecided to decide. DAs did not improve satisfaction with 

the decision, the process of decision making, or preparation for decision 

making. 

3. Adherence to treatment. DAs do not improve adherence to medication 

(including warfarin vs aspirin, bisphosphonate, blood pressure medication, 

anti-depressants, and statins). 

4. Treatment decisions. The impact of DAs on treatment choice is modest 

and variable. DAs decreased screening rates for prostate cancer (15%), 

non-significantly increased screening rates for colorectal cancer (20%), 

and had no impact on genetic testing. Because DAs target tests perceived 

to be either overused (e.g., PSA) or underused (e.g., colorectal cancer 

screening), variable impact is expected. 

The impact of DAs on elective surgery varies by procedure and setting.9,10 

DAs had no effect on minor surgeries (circumcision, surgical abortion, or 

dental surgery). DA targeting procedures perceived to be overused led to 

decreased use. The few trials that examined DAs in the setting of underuse 

found a trend towards increased use (prostatectomy in the UK19 and 

surgery for spinal stenosis in the U.S.).20 

5. Potential harms. DAs have no known negative effect on anxiety, 

depression, or emotional distress. Some DA trials reported a higher net 

cost per patient19,21 and longer physician consultation time,22 but findings 

were variable.23,24 

6. How DAs work: Potential active ingredients in DAs include an accurate 

description of the decision with all options and consequences made 

explicit, facilitation with constructing a fair mental representation of the 

decision, and exercises that help people reason about their values and 

preferences and make tradeoffs. 

Controversies. Many DA’s were developed without a clear conceptual 

framework for how they might influence decisions. There is debate about 

how to measure a good decision when there is no clear right choice. Is a 

good decision one that is made using a good decision process (regardless 

of the outcome), one that is correct for that individual (choice is consistent 

with patient values), or one that is correct for society (most cost-effective)? 

The relevance and significance of many commonly used short-term process 

measures (knowledge, decisional conflict) have been questioned.25,26 
 

 

 

 

 

 

176 | Chapter 17: Shared Decision Making
	

Limitations of the evidence. Studies have focused on video DAs, with 

scant attention to other types of DAs or other approaches to SDM, such as 

training practitioners in SDM, incentivizing practitioners to engage in SDM, 

or restructuring care (e.g., using a coach). In addition, many DA trials were 

too short or too narrowly defined to examine their effect on long-term health 

outcomes. The impact of DAs in the real world is often incorrectly assumed to 

equal the impact observed in clinical trials. For example, in a frequently cited 

study, only 344 of 3,212 referred subjects (11%) participated.20 Most were 

excluded for clinical reasons; many refused. The 22% reduction in surgery in 

the DA group corresponds to a 2.4% reduction (22% x 11%) among the referred 

population. Accounting for eligibility and interest in SDM dilutes impact by an 

order of magnitude. 

A number of areas need further investigation: 

1. What constitutes good decision making and how do we measure this? 

2. How do SDM interventions affect health care delivery, resource use, 

unwarranted variation, and clinical outcomes? What is the costeffectiveness of different approaches to SDM?
	

3. How do we integrate SDM into routine clinical care? 

4. Are we giving patients the right information to help them with decisions? 

DAs present treatment-associated risks derived from national samples. 

Although risks vary according to where one lives, where one seeks care, 

and, for invasive procedures, who performs the procedure, such tailoring 

of risks variables is not presented. 

5. How do we ensure quality control of DAs, which could be created as 

marketing tools to encourage patients to choose more (or less) expensive 

options? Measures of bias and disclosure of conflicts of interests of groups 

creating SDM tools are needed. 

6. How do different approaches to promoting SDM compare? There are no 

head-to-head comparisons of different approaches to SDM, including 

the impact of different types of DAs, different methods of deploying DAs 

(before, during, or after the clinical encounter), training providers in SDM, 

and restructuring care (using navigators, incentives). 

7. How do different approaches to SDM influence the process of SDM and 

outcomes? 
 

 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 177
	

What general practical advice can the science support? 

Facilitate active participation and SDM. Patients should have a right to be 

involved in decisions about their health and should be encouraged to do so to 

the level that they desire. Some practical approaches for facilitating SDM are 

described here and in the Table that follows. 

1. Identify and prioritize decisions appropriate for SDM. SDM is not 

appropriate for all clinical decisions. It may not always be feasible in the 

office setting, especially for screening and chemoprevention. And clinicians 

have no obligation to initiate discussion about services that either have no 

benefit or have a net harm. However, practitioners should work with their 

patients to identify and prioritize decisions requiring SDM. Discussions 

can be staggered across several office visits. Clinicians should be prepared 

to explain why certain services are discouraged and should consider a 

proactive discussion for such services with high-visibility, special individual 

importance, or a change in evidence.1 

2. Inform patients when they need to make a decision. Patients are often 

unaware that there is a decision to be made. Clinicians should draw 

attention to problems that require a shared decision making process 

(those for which the patient’s preferences are critical in selecting 

treatment). 

3. Explain why patient input matters. Patients do not always understand 

why or how their preferences and values factor into a decision and may 

assume that their clinician knows best. Clinicians should explain that 

there is more than one way to deal with the problem, that options have 

pros and cons that need to be considered, and that there is genuine 

professional uncertainly as to the best way of managing a problem. 

4. Screen patients for their desired level of involvement in decision 

making and preferred approach to receiving information. Not all 

patients want to be involved in all decisions at all times, and patients 

have differing needs for information. Discordance between desired and 

actual involvement in decision making leads to decision regret and low 

satisfaction.27 It is possible to screen for involvement in decision making. 

For example, the clinician can ask: “Realizing that there may be risks as 

well as benefits for any treatment, who do you think should decide which 

treatment options are best for you?”28 

5. Help interested patients be more involved in SDM. Many patients want 

to participate in decision making, but lack the requisite skills, confidence, 

knowledge, or tools. Inquire about the patient’s interest in information: 

printed material, graphical data, videotapes, websites or other media. 

Clinicians can offer patients a variety of educational tools to help them 

with their decision, trying not to rely on a single developer to minimize 

bias. 
 

 

178 | Chapter 17: Shared Decision Making 

Practical ways clinicians can promote SDM with their patients

Explain why patient preferences and value matter in this decision.
	

Explain that you will support their decision.
	

Help frame the decision for the patient.
	

Focus on treatments that are effective for that patient, focus on most

important dimensions and compare options using the same outcomes.
	

Let patients know how their preferences affect the decision.
	

Inform patients of the option of doing nothing and its consequences.
	

Ask the patient to explain to you how they frame the decision, correct any

misconceptions or misunderstandings, provide any needed information.
	

Offer patients a variety of support and/or educational tools to help them with

their decision, trying not to rely on a single developer to minimize bias. 

Select decision aids, based on evaluations like those in the Ottawa A to Z 

Inventory of Decision Aids. 

Cautions. Informing patients of all options and all consequent risks and 

benefits is often unfeasible and undesirable. Too much information can 

confuse patients.29 It is best to focus on options for which the evidence is 

strongest that the benefits outweigh the risks for that patient. If the patient 

is not satisfied with the first tier treatment options, other options should be 

presented. Clinicians should always include the consequences of no treatment. 

It is important to help patients tolerate and cope with uncertainty, rather 

than simply understand it. Most patients prefer to avoid ambiguity, which can 

lead to higher risk perceptions, distrust, pessimism, and decision avoidance.30 

When physicians are comfortable with uncertainty, patient trust and 

satisfaction are high.31 

The specific content, framing, and emphasis of DAs addressing the same 

decision can vary substantially.24 No guidelines govern the selection of evidence 

to include in a DA; how information is framed, ordered, and presented (e.g., 

testimonials32) can influence values and how information is used.29 Biases can 

be intentional or not.33 Practitioners should be comfortable with the content of 

DAs they recommend to patients. 

How does one evaluate communications implementing this advice?

Drawing on chapter 1, the ultimate test of SDM communications is whether: 

1. the communication contains the information needed to support informed 

decision making, 

2. users can access that information, and 

3. users can comprehend what they access. 
 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 179
	

Because SDM requires the active involvement of both patients and clinicians, 

both perspectives are important. This section focuses on evaluating DAs, but 

also whether it supports the process of SDM between users and their clinician. 

No Budget. Rely on existing evaluations of DA, obtained through the A-Z 

inventory (http://decisionaid.ohri.ca/AZlist.html). This database can be 

searched for specific decisions, generating a list of DAs will with information on 

their content, how to access them, and includes ratings from IPDASi. This web 

site includes many, but not all DAs. Many are available free of charge. 

Modest budget. There are several validated questionnaires that can be 

incorporated into routine clinical practice or quality improvement evaluations. 

1. Whether the DA contains the information needed to support informed 

decision making can be evaluated using the validated 11-item Preparation 

for Decision Making scale. It assesses perceptions of how well a DA 

prepares the respondent to communicate with their provider and make a 

decision.34 

2. Whether users can access the information can be evaluated by asking 

patients whether they read or viewed the DA (and if not, why not). 

3. Evaluating the extent to which users understood the material is 

problematic because each DA is content-specific, and self-report may 

be inaccurate. However, one could evaluate whether the patient feels 

informed after viewing the DA by using the ‘feeling informed’ subscale 

from the validated “Decision Conflict’ scale,35 or the question: “I feel I have 

made an informed choice.” 

4. Evaluating whether SDM occurred during the clinical encounter can 

be accomplished using the 12-item OPTIONS scale (http://www. 

optioninstrument.com/), completed by observing patient encounters. This 

scale would be particularly useful for determining the effect of training 

programs in which students’ skills in SDM are evaluated before and after 

training. 

Alternatively, patients could be asked about their provider’s performance 

using the SDM quality of care measures: “In the last 12 months, (1) did a health 

practitioner talk with you about the pros and cons of each choice for your 

treatment or health care?”, and (2) when there was more than one choice for 

your treatment or health care, did a health practitioner ask which choice was 

best for you?”36 

High cost approaches. Convening an NIH ‘State of the Science on SDM’ 

would help to obtain clarity on SDM, to guide future research in this area, 

and to inform the proposed national SDM program. Because of the limited 

number of SDM interventions that have been tested, and the limited number 

of outcomes that have been tracked in these trials, rigorous randomized 

controlled trials are needed that compare alternative approaches to facilitating 
180 | Chapter 17: Shared Decision Making
	

and integrating SDM into clinical practice. Trials should measure the process of 

decision making (including decision quality and extent of SDM) and long- and 

short-term consequences of the decision: patient behavior, health outcomes, 

quality of life, and decisional regret. Trials should capture mechanisms of 

action, moderating effects, confounders, costs, and resource use, including 

potential substitution effects (the substitution of one treatment with other 

treatments or tests). The duration of the trial should be sufficiently long to 

measure persistence of choice and/or adherence to selected treatment. 

Conclusion

SDM can improve risk communication between patients and practitioners 

and can influence treatment choice, but the field is nascent. More clarity is 

needed on what constitutes SDM, what SDM interventions should accomplish, 

as well as what are realistic expectations for their impact in different settings. 

New approaches to SDM are needed that can be implemented in a range of 

clinical settings. 

Additional resources

1. Edwards, A., and Elwyn, G. Shared Decision-Making in Health Care: Achieving Evidence-Based 

Patient Choice. Second Edition. Oxford University Press, 2009. This comprehensive book 

represents the state-of-the-art overview of the field. It addresses the evidence, theoretical 

perspectives, and practical case studies from actual health care practice, covering both general 

and specific conditions, including offering tangible examples for both patients and doctors. 

2. Bekker, H.L. (2010). The loss of reason in patient decision aid research: Do checklists damage 

the quality of informed choice interventions? Patient Education and Counseling. 78, 357-364. A 

conceptual review of the field that integrates the science behind individuals’ decision making 

with the demands of designing complex, health care interventions. It discusses whether using 

the International Patient Decision Aids Standards (IPDAS) Collaboration checklist as a gold 

standard to judge interventions’ quality is premature and potentially detrimental to the validity 

of resources designed to help patients make treatment choices. 

3. Elwyn, G., O’Connor, A., Bennett, C., et al. (2009). Assessing the quality of decision support 

technologies using the international patient decision aid standards instrument (IPDASi). 

PLos ONE 4, e4705. http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal. 

pone.0004705. Describes the process and criteria for evaluating patient decision aids. Evaluation 

criteria include: content, development process, and effectiveness. The International Patient 

Decision Aids Standards (IPDAS) Collaboration is a multi-disciplinary effort to establish criteria for 

evaluating the quality of patient decision aids. 

4. Sheridan, S.L., Harris, R.P., and Woolf, S.H., The Shared Decision-Making Workgroup of the 

U.S. Preventive Services Task Force. (2004). Shared decision making about screening and 

chemoprevention: a suggested approach from the U.S. Preventive Services Task Force. American 

Journal of Preventative Medicine, 26, 55-56. http://www.ahrq.gov/clinic/3rduspstf/shared/ 

sharedba.htm. This paper clarifies the U.S. Preventive Services Task Force (USPSTF) vision for 

applying shared decision making in the execution of screening and chemoprevention. It is neither 

a systematic review nor a formal recommendation. Instead, it is a concept paper that includes a 

commentary on the current thinking and evidence regarding SDM. 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 181
	

5. Braddock, C.H., Edwards, K.A., Hasenberg, N.M., et al. (1999). Informed decision making in 

outpatient practice: Time to Get Back to Basics. JAMA. 282, 2313-2320. http://jama.amaassn.org/cgi/content/full/282/24/2313. This landmark study characterizes the nature and 

completeness of informed decision making in routine office visits of both primary care physicians 

and surgeons. It uses a cross-sectional descriptive evaluation of audiotaped office visits during 1993. 

6. Kuehn, B.M. (2009) States explore shared decision making. JAMA, 301, 24, 2539-2541. This short 

editorial summarizes the expectations SDM from a policy perspective. 

7. Rimer, B., Briss, P., Zeller, P., Chan, E., and Woolf, S. (2004). Informed decision making: what 

is the role in cancer screening? Cancer. 101, 1214-1228. This critical review of the evidence 

for SDM and cancer screening concludes that SDM improved knowledge, beliefs, and risk 

perceptions, but found little or no evidence regarding whether they result in (1) participation 

in decision making at a level consistent with patient preferences or (2) effects on patient 

satisfaction with the decision-making process. 

Endnotes

1 Sheridan, S.L., Harris, R.P., and Woolf, S.H., for the Shared Decision-Making Workgroup of 

the U.S. Preventive Services Task Force.(2004). Shared decision making about screening and 

chemoprevention. A suggested approach from the U.S. Preventive Services Task Force. American 

Journal of Preventive Medicine, 204, 26, 56-66. 

http://www.ahrq.gov/clinic/3rduspstf/shared/sharedba.htm. 

2 Council on Medical Service. Shared Decision-Making. (CMS Report 7-A-10). Chicago, IL: American 

Medical Association; 2010. http://www.ama-assn.org/ama1/pub/upload/mm/372/a10-cms-rpt-7.pdf. 

3 Charles, C., Gafni, A., and Whelan, T. (1997). Shared decision-making in the medical encounter: 

What does it mean? (Or it takes at least two to tango). Social Science & Medicine, 44, 681-692. 

4 Col. N., Ngo, L., O’Connor, A., and Goldberg, R. (2007). Can computerized decision support help 

patients make complex treatment decisions? A randomized controlled trial of an individualized 

menopause decision aid. Medical Decision Making, 27, 585-598. 

5 Mullan, R.J., Montori, V.M., Shah, N.D., Christianson, T.J.H., and Bryant, S.C., et al. (2009). The 

diabetes mellitus medication choice decision aid: A randomized trial. Archives Internal Medicine, 

169, 1560-1568. 

6 Berry, D.A., Iversen, E.S., Gudbjartsson, D.F., Hiller, E.H., and Garber, J.E. al. (2002). BRCAPRO 

validation, sensitivity of genetic testing of BRCA1/BRCA2, and prevalence of other breast cancer 

susceptibility genes. Journal of Clinical Oncology, 20(11): 2701-2712. 

7 http://www.stat.duke.edu/~gp/brcapro.html 

8 Ravdin, P.M., Siminoff, L.A., Davis, G.J., Mercer, M.B., and Hewlett, J. et al. (2001). Computer 

program to assist in making decisions about adjuvant therapy for women with early breast cancer. 

Journal of Clinical Oncology, 19(4):980–991. 

9 Ottawa Hospital Research Institute. Cochrane Decision Aid Registry. [Web Page]. Available at: 

http://decisionaid.ohri.ca/cochinvent.php. 

10 Stacey, D., Bennett, C., Barry, M., Col, N., and Eden, K. et al. (2011). Updated cochrane review of 

patient decision aids: 87 trials show increased participation and higher likelihood of achieving 

informed values-based decisions. Abstract presented at the 6th International Conference on 

Shared Decision Making, 2011. Maastrict, The Netherlands. 

11 Zikmund-Fisher, B.J., Couper, M.P., Singer, E., Ubel, P.A., and Ziniel, S., et al. (2010). Deficits and 

variations in patients’ experience with making 9 common medical decisions: the DECISIONS 

survey. Medical Decision Making, 30(5 Suppl), 85S-95S. 

12 Braddock, C.H. Edwards, K.A., Hasenberg, N.M., Laidley, T.L., and Levinson, W. (1999). Informed 

decision making in outpatient practice: Time to get back to basics. JAMA, 282,2313-2320. 
 

 

 

 

 

 

 

182 | Chapter 17: Shared Decision Making
	

13 Frosch, D.L., and Kaplan, R.M. (1999). Shared decision making in clinical medicine: Past research 

and future directions. American Journal of Preventative Medicine,17, 285-294. 

14 Elwyn, G., Légaré, F., van der Weijden, T., Edwards, A., and May, C. (2008). Arduous 

implementation: Does the normalisation process model explain why it’s so difficult to embed 

decision support technologies for patients in routine clinical practice. Implementation Sciences, 3:57. 

15 Holmes-Rovner, M., Valade, D., Orlowski, C., Draus, C., and Nabozny-Valerio, B. et al. (2001). 

Implementing shared decision-making in routine practice: Barriers and opportunities. Health 

Expectations, 3:182-191. 

16 Gravel, K., Légaré, F., and Graham, I.D. (2006). Barriers and facilitators to implementing shared 

decision-making in clinical practice: A systematic review of health professionals’ perceptions. 

Implementation Science, 1:1-12. 

17 Legare, F., Ratte, S., Gravel, K., and Graham, I.D. (2008). Barriers and facilitators to implementing 

shared decision-making in clinical practice: Update of a systematic review of health professionals’ 

perceptions. Patient Education and Counseling,73(3):526-35. 

18 O’Connor, A.M., Bennett, C.L., Stacey, D., Barry, M., Col, N.F., Eden, K.B., Entwistle, V.A., Fiset, 

V., Holmes-Rovner, M., Khangura, S., Llewellyn-Thomas, H., and Rovner, D. (2009). Decision 

aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 

2009:CD001431. 

19 Murray, E., Davis, H., Tai, S.S., Coulter, A., and Gray, A., et al. (2001). Randomised controlled trial 

of an interactive multimedia decision aid on benign prostatic hypertrophy in primary care. British 

Medical Journal, 323:493-6. 

20 Deyo, R.A., Cherkin, D.C., Weisnstein, J., Howe, J., Ciol, M., and Mulley, A.G. (2000). Involving 

patients in clinical decisions: impact of an interactive video program on use of back surgery. 

Medical Care, 38:959-969. 

21 Murray, E., Davis, H., Tai, S.S., Coulter, A., Gray, A., et al. (2001). Randomised controlled trial of 

an interactive multimedia decision aid on hormone replacement therapy in primary care. British 

Medical Journal, 323:490-3. 

22 Cohen, D., Longo, M.F., Hood, K., Edwards, A., and Elwyn, G. (2004). Resource effects of training 

general practitioners in risk communication skills and shared decision making competencies. 

Journal of Evaluation in Clinical Practice, 10:439-445. 

23 Kristiansen, I.S., and Gyrd-Hansen, D. The economics of shared decision making. Chapter 10 in 

Edwards, A., Elwyn, G. Shared Decision-Making in Health Care: Achieving Evidence-based Patient 

Choice. Second Edition. Oxford University Press, 2009, 65-71. 

24 Hansen, M., Alavian, M., and Col, N. (2009). (abstract ) Empirical evidence of bias in decision aids. 

Journal of General Internal Medicine. 

25 Charles, C., Gafni, A., Whelan, T., and O’Brien, M. (2005). Treatment decision aids: Conceptual 

issues and future directions. Health Expectations, 8, 114–25. 

26 Nelson, W.L., Han, P.K., Fagerlin, A., Stefanek, M., and Ubel, P.A. (2007). Rethinking the objectives 

of decision aids: A call for conceptual clarity. Medical Decision Making, 27:609-18. 

27 Lantz, P.M., Janz, N.K., Fagerlin, A., Schwartz, K., and Liu, L., et al. ( 2005). Satisfaction with 

surgery outcomes and the decision process in a population-based sample of women with breast 

cancer. Health Services Research, 40(3): 745–768. 

28 Degner, L.F., and Sloan, J.A. (1997). The control preferences scale. Canadian Journal of Nursing 

Research, 29, 21–43. 

29 Peters, E., Dieckmann, N., Dixon, A., Hibbard, JH, and Mertz, C.K. (2007). Less is more in 

presenting quality information to consumers. Medical Care Research Reviews, 64(2):169-190. 

30 Politi, M.C., Han, P.K.J., and Col, N.F. (2007). Communicating the uncertainty of harms and 

benefits of medical interventions; White Paper Series, Eisenberg Center. Medical Decision 

Making, 27, 681-695. 
 

 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 183
	

31 Parascandola, M., Hawkins, J., and Davis, M. (2002). Patient autonomy and the challenge of 

clinical uncertainty. Kennedy Institute of Ethics Journal, 12(3):245-64. 

32 Ubel, P., Jepson, C., and Baron, J. (2001). The Inclusion of patient testimonials in decision aids: 

Effects on treatment choices. Medical Decision Making, 21(1):60-68. 

33 Wyatt, J., and Spiegelhalter, D. (1992) Field trials of medical decision-aids: potential problems and 

solutions. National Heart & Lung Inst., Fulham Rd, London SW3 6HP, UK. 

34 Stacey, C.D., O’Connor, A.M., DeGrasse, C., Verma, S. (2003). Development and evaluation of a 

breast cancer prevention decision aid for higher risk women. Health Expectations, 6: 3-18. 

35 O’Connor, A.M. (1995) Validation of a decisional conflict scale. Medical Decision Making; 15:25-30. 

36 https://www.cahps.ahrq.gov/qiguide/content/interventions/Composites-Topics.aspx 

The CAHPS Improvement Guide Practical Strategies for Improving the Patient Care Experience. 

 

 

 

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Chapter 18: News Coverage

Gary Schwitzer - HealthNewsReview.org 

Summary

Health care news coverage can educate and inform the public and help 

people make smarter health care decisions. But it can also confuse public 

discussion on public health, health care and health policy concerns. Studies 

have shown that health care news stories often exaggerate benefits and 

minimize harms or risks. 

Introduction

Having worked in health care journalism for 37 years, I care deeply about 

helping my colleagues achieve accuracy, balance, and completeness in their 

stories. Health care news coverage can educate and inform the public and 

help people make smarter health care decisions. But it can also confuse public 

discussion on public health, health care, and health policy concerns. It is 

painful to see news coverage that promotes anecdote and emotion over data 

and evidence. 

That is what happened in much of the news coverage of the recommendations 

on mammography, released by the U.S. Preventive Services Task Force in 2009. 

This was one of the worst such episodes I have witnessed to date.1 Evidence 

was often ignored. Personal, emotional anecdotes dominated many stories. 

Benefits of mammography were exaggerated while potential harms were 

downplayed or totally ignored. A public opinion poll 17 months later showed 

that women were still confused and misinformed about what the Task Force 

had recommended.2 

In another case, the DECISIONS study found evidence of poor quality in many 

physician-patient discussions on the tradeoffs involved in prostate cancer 

screening.3 

Clinicians often report that patients come to their office visits asking 

questions about news stories they’ve seen — news stories that may be 

imbalanced on benefits and harms. If the office visit then amplifies the 

emphasis on what one stands to gain while minimizing what one stands to lose, 

the opportunity for a fully informed, shared decision-making experience is lost. 
186 | Chapter 18: News Coverage
	

This chapter is intended to help people think about the imbalance that exists 

in so many health care messages — and what can be done about it. 

What does the science say about this aspect of communication? 

Over the past 20 years, many researchers have written about how the 

news media affects consumers on behavior change issues such as smoking, 

diet, and cancer screening. But it remains unclear how consumers receive, 

comprehend, or act on news stories about the benefits and harms of health 

care interventions when uncertainty prevails. 

In 2000, Moynihan et al., published a groundbreaking analysis in the New 

England Journal of Medicine, “Coverage by the News Media of the Benefits and 

Risks of Medications.”4 Their analysis of 207 stories on three widely prescribed 

drugs showed that 40% did not quantify benefits. Of those stories that did, 

most reported only in relative, not absolute, terms. Fewer than half the stories 

mentioned potential harms. The authors concluded: 

When reporting on new forms of technology or new treatments, journalists 

and editors might consider the evidence available in relation to the following 

questions: What is the magnitude of the benefit (e.g., both absolute and 

relative), and what groups of patients can be helped? What are the associated 

risks and costs? What are the possible links between the sources of information 

(studies or experts) and those (such as the manufacturers) who promote the 

therapy? Although not exhaustive, these questions could inform attempts to 

improve the quality of medical reporting. 

Focusing on news coverage of just one issue, Woloshin and Schwartz 

published Giving Legs to Restless Legs: A Case Study of How the Media Helps 

Make People Sick, which analyzed 33 stories about restless leg syndrome over 

a two-year period.5

 Only one story quantified a benefit for the first FDAapproved drug for the condition. But about half the stories used anecdotes 

about people taking the drug (most noting substantial improvement). Of stories 

mentioning the drug, only 5 of 15 reported anything about side effects, and 

only 1 quantified that risk of harm. The authors wrote: 

Journalists should question the assumption that treatment always makes sense. 

Medical treatments always involve trade-offs; people with mild symptoms have 

little to gain, and treatment may end up causing more harm than good...Instead 

of extreme, unrepresentative anecdotes about miracle cures, journalists should 

help readers understand how well the treatment works (e.g., what is the 

chance that I will feel better if I take the medicine versus if I do not?) and what 

problems it might cause (e.g., whether I might be trading less restless legs for 

daytime nausea, dizziness, and somnolence). 

(Earlier, this same team studied medical journal news releases, finding that 

“Data are often presented using formats that may exaggerate the perceived 

importance of findings.”6 ) 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 187
	

One cancer news analysis concluded that news stories about cancer 

“rarely discuss treatment failure or adverse events...(and) may give patients 

an inappropriately optimistic view of cancer treatment, outcomes, and 

prognosis.”7 

Gigerenzer et al., “provide evidence that statistical illiteracy (a) is common to 

patients, journalists, and physicians; (b) is created by nontransparent framing of 

information that is sometimes an unintentional result of lack of understanding, 

but can also be a result of intentional efforts to manipulate or persuade 

people; and (c) can have serious consequences for health.”8 The authors place 

much of the blame on medical journals, “surprisingly, nontransparent health 

statistics such as relative risks without the base rate often appear in leading 

medical journals, and it is often from these sources that the numbers spread to 

physicians, the media, and the public.” (p.25) 

Journalism watchdog/improvement projects. Within the last 10 years, 

eight international health care journalism “watchdog” website projects have 

begun analyzing how journalists evaluate the evidence behind claims made 

about health care interventions, often with a special emphasis on how benefits 

and risks are presented. Australian, Canadian, and U.S. teams have published 

their findings, which, although coming from independent teams from three 

countries, are very similar.9-12 

Each of these projects assigns multiple reviewers to evaluate stories, each 

using the same basic set of systematic criteria. Data from thousands of stories 

in these three countries demonstrate that journalists don’t do a good job in 

quantifying benefits and harms. 

For example, our five-year, 1,400-story database on the HealthNewsReview. 

org project shows that nearly 70% of stories fail to adequately quantify the 

harms and benefits of the interventions they report on.13 

Our judges grade a story as unsatisfactory if it doesn’t quantify results or if it 

does so using only relative, not absolute, risk–benefit data. The net effect of so 

many of these stories is that they fail to explain how small the potential benefit 

is and how large the potential harm. In the course of our daily journalism 

reviews, we also see troublesome journal practices in the studies on which the 

stories are based. We have seen journal articles that use relative numbers to 

describe benefits and absolute numbers to describe harms — within the same 

article — when it seems to suit the conclusion of the study. 

The following statistics may help explain some of these criticisms. Surveys 

have shown that many daily newspaper reporters have not been trained in 

how to cover health care news or interpret statistics, and most find this a 

major challenge in their jobs.14 Additionally, 43 percent of respondents to a 

nationwide survey of health care journalists in 2008 said training opportunities 

at their news organization had decreased over the past few years; although 
 

 

 

 

 

 

 

188 | Chapter 18: News Coverage
	

20 percent had seen an increase.15 But, for many reasons, the time may have 

arrived to effect change: the large number of people now devoted to health 

care journalism improvement, the training opportunities that have arisen, and 

a growing recognition on the part of many health journalists that they need help. 

What general practical advice can the science support? 

Health care journalism training programs. Within the past decade, many 

high-quality health care journalism training opportunities have become 

available, some of them focusing on helping journalists scrutinize evidence. 

•		The National Institutes of Health hosts an annual Medicine in the Media 

workshop (http://medmediacourse.nih.gov/). 

•		The Association of Health Care Journalists (AHCJ) has more than 1,000 

members and holds national and regional meetings (http://www. 

healthjournalism.org). In 2010, AHCJ published, “Covering Medical 

Research: A Guide for Reporting on Studies” and distributed to all 

members online.16 

• The Knight Foundation funds a medical evidence boot camp for journalists 

at MIT (http://web.mit.edu/knight-science/bootcamps/fall2010.html). 

The Knight Foundation also funds public health journalism fellowships and 

a boot camp at the Centers for Disease Control and Prevention (http:// 

www.journalismtraining.org/action/provider_detail?id=869). 

• The University of Southern California Annenberg School for 

Communication offers The California Endowment Health Journalism 

Fellowships (http://www.reportingonhealth.org/fellowships). 

• There are at least 10 graduate programs in some form of health, medical, 

and science journalism at various universities across the United States. 

Researchers offer practical advice for health care journalism improvement.

Woloshin, Schwartz, and Kramer published an editorial, “Promoting Healthy 

Skepticism in the News: Helping Journalists Get It Right,”17 in which they 

announced that the Journal of the National Cancer Institute, which published 

the editorial, was “launching a web site for science and health journalists to 

help them ’get it right’ (we also think medical students, residents, practicing 

physicians, and of course the public will find these materials helpful).” The 

site includes tip sheets on absolute versus relative risks, the number needed to 

treat, p values, confidence intervals, statistics especially relevant to screening 

(survival and mortality), limitations inherent in various research designs, and 

suggested language for journalists to use or adapt when they write about these 

recurring issues. They urged medical journals to “work harder to promote the 

accurate translation of research into news” by “ensuring that both the journal 

and the corresponding press releases routinely present absolute risks found in 

the study (or estimated, when possible, in case-control studies) to describe the 

effects of interventions and to highlight study limitations.” 
 

 

 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 189
	

Gigerenzer recommends that all health communicators — journalists 

included — use “frequency statements instead of single-event probabilities, 

absolute risks instead of relative risks, mortality rates instead of survival rates, 

and natural frequencies instead of conditional probabilities.”8 

The HealthNewsReview.org web site offers free tips for understanding 

studies, http://www.healthnewsreview.org/tips-for-understanding-studies.php. 

Brief primers are available on appropriate language to describe observational 

study findings, absolute versus relative risk, the number needed to treat, the 

limitations of drawing conclusions from presentations at scientific meetings, 

the phases of drug trials, and more. 

Evidence that some news organizations are acting on the advice. The most 

recent positive trend in journalism is the publication by several major news 

organizations of regular columns devoted to evaluating the evidence in new 

studies or analyzing claims made about benefits of health care interventions. 

Examples: 

•		Los Angeles Times “Healthy Skeptic” monthly column (http://www. 

latimes.com/features/health/la-he-skeptic-sg,0,5361483.storygallery); 

•		New York Times “Really?” weekly column (http://topics.nytimes.com/
	

topics/news/health/columns/really/index.html);
	

•		Wall Street Journal “Research Report” biweekly column 

(http://online.wsj.com/public/search?article-doctype={Research+Report}&HEADER_TEXT=research+report); 

•		Washington Post “Quick Study” column (http://www.washingtonpost.
	

com/wp-dyn/content/article/2011/02/21/AR2011022102524.html). 

These are small but encouraging signs of progress. By publishing regular 

columns, these news organizations are delivering a powerful message to their 

readers that evidence must be scrutinized and that claims of efficacy and safety 

in health care interventions must be evaluated carefully. 

How does one evaluate communications implementing this advice?

Journalists have a bigger megaphone with a voice that reaches more people, 

more broadly, more often. Their work can influence both individual health care 

decision-making and public policy making. Helping journalists improve has the 

potential to affect the quality and flow of information to a broad population of 

health care consumers. 

No cost evaluation methods. It costs nothing to use the checklists that six 

international projects use to evaluate health care journalism. They are all free 

to all users on the Web. 

•		HealthNewsReview.org (U.S.) – http://www.healthnewsreview.org 

•		Media Doctor Australia - http://www.mediadoctor.org.au/ 

•		Media Doctor Canada - http://www.mediadoctor.ca/ 
 

 

 

 

 

190 | Chapter 18: News Coverage
	

•		Medien Doktor: The German HealthNewsReview – http://www.medien- doktor.de/ 

•		Media Doctor Hong Kong - http://www.mediadoctor.hk/ 

•		Media Doctor Japan - http://mediadoctor.jp/ 

Two other free resources that publish daily commentary on the quality of 

health care news, although they don’t employ the systematic criteria used by 

the projects above, are: 

•		NHS Choices “Behind the Headlines” (UK) http://www.nhs.uk/news/
	

Pages/NewsIndex.aspx
	

•		Knight Science Journalism Tracker (US) - http://ksjtracker.mit.edu/
	

category/health-medicine-stories/
	

Low-cost evaluation methods. Others could join the movement to evaluate 

the quality of health care journalism at low cost by adopting the methods 

and criteria employed by the six international projects listed above. The 

HealthNewsReview.org project in the United States evaluates only a small 

percentage of the stories published by only a few dozen news organizations. 

There are many other stories in many other formats and in many other media 

that are not being reviewed. With the growth in alternative media, web sites 

and blogs, new issues in the delivery of health care news and information arise 

every day that are worthy of evaluation. 

With a little investment of time and effort, professionals who are trained in 

the evaluation of evidence could help journals and their own medical centers 

to improve their news releases. Woloshin and Schwartz have written about 

problems with news releases from both sources.6,18 

High-cost evaluation methods. Because one of the gaps in the literature 

is an evaluation of how Americans receive, perceive, comprehend, and act 

on stories that include information about benefits and harms of health care 

interventions, a higher cost evaluation project would be to present such 

stories to a random sample of Americans and follow them over time to see if 

they affect their behavior or well-being and how. However, if we move from 

evaluation to intervention, a number of opportunities can be identified that 

can expand training for journalists, but at a greater investment. The wise old 

advice is expensive: “Tell me and I forget. Teach me and I remember. Involve 

me and I learn.” Interactive workshops or, better, individual assistance to 

help journalists evaluate their own work, can be costly. Any health care 

professional, biostatistician, epidemiologist, or anyone trained in how to 

evaluate evidence who devotes time to help journalists do a better job will 

presumably not be compensated for that effort. But this type of dedication of 

time and effort can achieve real public good. Behind most important, effective 

health care news stories, someone outside of journalism worked with someone 

in journalism to get the story right. 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 191
	

Conclusion 

Anyone who communicates to the public about health care has a stake in 

improving health care journalism. In an analysis of cancer news coverage and 

information seeking, Niederdeppe, Frosch, and Hornik suggest that physicians 

are left with an “essential role” of bridging the gap that limited news stories 

create in peoples’ minds. “Our findings indicate that many people do not seek 

additional information after hearing news reports about new studies. If news 

reports are inevitably limited in scope and do not drive much of the population 

to further information seeking, these results reinforce the view that health 

care providers play an essential role in making up for this gap. Innovative 

interventions to help a greater part of the population become more informed 

consumers of health care are warranted.”19 

Mathematics professor Rebecca Goldin thinks statisticians can help: “In an 

era in which Wikipedia and WebMD are considered by experts more reliable 

than journalism for certain kinds of information, journalists and media sources 

need to evolve to maintain their relevance. At the same time, journalists are 

under newer and greater pressures than previously due to budget cuts and 

shrinking of the news industry. Statisticians can play an important role in this: 

work with journalists to represent scientific findings accurately and wholly, and 

encourage them to promote scientific thinking in the mainstream. Statistical 

literacy is an essential part of life, not just for our students, but also for our 

media-consuming public.”20 We hope that journalists, journal editors, and 

health care and other professionals are inspired by some of these ideas. 

Additional resources

1. Eight websites around the world now evaluate health care journalism: 

• HealthNewsReview.org (U.S.) – http://www.healthnewsreview.org

 • Media Doctor Australia - http://www.mediadoctor.org.au/

 • Media Doctor Canada - http://www.mediadoctor.ca/

 • Medien Doktor: The German HealthNewsReview – http://www.medien-doktor.de/

 • Media Doctor Hong Kong - http://www.mediadoctor.hk/

 • Media Doctor Japan - http://mediadoctor.jp/

 • NHS Choices “Behind the Headlines” (UK) - http://www.nhs.uk/news/Pages/NewsIndex.aspx

 • Knight Science Journalism Tracker (US) - http://ksjtracker.mit.edu/category/health-medicine-stories/ 

2. Journalism training opportunities:

 • The Association of Health Care Journalists is the leading professional organization in this field. 

http://www.healthjournalism.org

 • The National Institutes of Health hosts an annual Medicine in the Media workshop
	

(http://medmediacourse.nih.gov/). 

• The Knight Foundation funds a medical evidence boot camp for journalists at MIT
	

(http://web.mit.edu/knight-science/bootcamps/fall2010.html). 
 

192 | Chapter 18: News Coverage
	

• The Knight Foundation also funds public health journalism fellowships and a boot camp 

at the Centers for Disease Control (http://www.journalismtraining.org/action/provider_
	

detail?id=869). 

• The University of Southern California Annenberg School for Communication offers The 

California Endowment Health Journalism Fellowships (http://www.reportingonhealth.org/
	

fellowships). 

3. Books: 

Cohn, V., and Cope, L. (2001). News & numbers: A Guide to Reporting Statistical Claims and 

Controversies in Health and Other Fields. Iowa State Press. 

Gigerenzer, G. (2002). Calculated Risks: How To Know When Numbers Deceive You. New York: 

Simon & Schuster. 

Schwitzer, G. (2010). Covering Medical Research: A Guide to Reporting on Studies. Association of 

Health Care Journalists. (E-mail: info@healthjournalism.org) 

Woloshin, S., Schwartz, L.M., and Welch, H.G. (2008). Know Your Chances: Understanding Health 

Statistics. Berkeley: University of California Press. 

Endnotes

1 Squires, L.B., Holden, D.J., Dolina, S.E., Kim, A.E., Bann, C.M. et al (2011). The Public’s Response to 

the U.S. Preventive Services Task Force’s, 2009 recommendations on mammography screening. 

Am J Prev Med 40(5):497-504. 

2 Goodwin, J. (2011). Harris Interactive/HealthDay survey finds many women disagree with new 

recommendations that screening should begin at 50. HealthDay. Retrieved from http://consumer. 

healthday.com/Article.asp?AID=652358. 

3 Hoffman, R.M., Couper, M.P., Zikmund-Fisher, B.J., Levin, C.A., McNaughton-Collins, M. et al. 

(2009). Prostate cancer screening decisions: Results from the National Survey of Medical Decisions 

(DECISIONS study). Arch Intern Med 169(17):1611-8. 

4 Moynihan, R., Bero, L., Ross-Degnan, D., Henry, D., Lee, K., Watkins, J., et al. (2000). Coverage by 

the news media of the benefits and risks of medications. N Engl J Med 342(22):1645–50. 

5 Woloshin, S., and Schwartz, L.M. (2006). Giving legs to restless legs: A case study of how the media 

helps make people sick. PLoS Med 3(4): e170. 

6 Woloshin S., and Schwartz, L.M. (2002). Press releases: Translating research into news. JAMA 

287(21):2856-8. 

7 Fishman, J., Ten Have, T., and Casarett, D. (2010). Cancer and the Media: How does the news 

report on treatment and outcomes. Arch Intern Med 170(6): 515-518. 

8 Gigerenzer G, et al. (2007). Helping doctors and patients make sense of health statistics. 

Psychological Science in the Public Interest. (8):53-96. 

9 Smith, D.E., Wilson, A.J., and Henry, D.A. (2005). Monitoring the quality of medical news reporting: 

Early experience with media doctor. Med J Aust 183(4):190–3. 

10 Schwitzer, G. (2008). How do US journalists cover treatments, tests, products, and procedures? 

An evaluation of 500 stories. PLoS Med 5(5): e95. 

11 Cassels, A., and Lexchin, J. (2008). How well do Canadian media outlets convey medical treatment 

information? Initial findings from a year and a half of media monitoring by Media Doctor Canada. 

Open Medicine (2)2. Retrieved from: http://www.openmedicine.ca/article/view/170/131. 

12 Wilson, A., Bonevski, B., Jones, A., and Henry, D. (2009). Media reporting of health interventions: 

signs of improvement, but major problems persist. PLoS ONE 4: e4831. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 193
	

13 Brainard, C. (2011). Mixed grades for medical coverage: Analysis of nearly 1,500 articles over five 

years finds pluses and minuses. Columbia Journalism Review. Retrieved from http://www.cjr.org/ 

the_observatory/mixed_grades_for_med_coverage.php. 

14 Voss, M. (2002). Checking the pulse: Midwestern reporters’ opinions on 

their ability to report health care news. Am J Public Health 92:1158–1160. 

15 Schwitzer, G. (2009). The State of Health Journalism in the U.S. – A Report to the Kaiser Family 

Foundation. Retrieved from: http://www.kff.org/entmedia/7858.cfm. 

16 Schwitzer, G. (2010). Covering Medical Research: Guide to Reporting on Studies. Association of 

Health Care Journalists. 

17 Woloshin, S., Schwartz, L.M., and Kramer, B.S. (2009). Promoting healthy skepticism in the news: 

Helping journalists get it right. J Natl Cancer Inst 101(23):1596-9. 

18 Woloshin, S., Schwartz, L.M., Casella, S.L., Kennedy, A.T., and Larson, R.J. (2009). Press releases 

by academic medical centers: Not so academic? Ann Intern Med 150:613-618. 

19 Niederdeppe, J., Frosch, D.L., and Hornik, R.C. (2008). Cancer news coverage and information 

seeking. J Health Commun (13):181-199. 

20 Goldin, R. (2009). Spinning heads and spinning news: How a lack of statistical proficiency affects 

media coverage. Proceedings of the Joint Statistical Meetings, Section on Statistical Learning. 

Retrieved from: http://stats.org/stories/2009/lack_stats_affects_media_oct8_09.html. 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 195
	

Chapter 19: Inside the Organization

Caron Chess, PhD - Rutgers University 

Summary

If risk communication is defined as, at minimum, a two-way process, 

studying the source is almost as important as studying the audience. The 

source organizations, at minimum, shape the message, and they may also be 

responsible for risk decisions that set the context for the message. In short, 

although risk communication research focuses on the perceptions of laypeople, 

relatively few studies explore the powerful organizations that serve as sources 

of the messages that dominate the dialogue. Given the importance of these 

issues, our understanding of risk communication is not as rich as it might be. 

Introduction

Studies of risk communication about anthrax* from government agencies 

in 2001 provide insight into some of the organizational factors that facilitate 

or hinder implementation of effective risk communication practices. 

Although insufficient research to generalize, there are a number of studies 

of organizational issues related to anthrax communication that can provide a 

basis for discussion. The enormity and importance of the risk communication 

effort piqued sufficient interest for multiple studies, and the crisis highlighted 

organizational issues that might otherwise go unnoticed. Anthrax 

communication took place during crisis conditions, but many of the identified 

issues have relevance to more routine communication. 

Examined as a whole, we can begin to understand how managers and staff, 

including those with expertise and commitment, may confront barriers that 

make it difficult for them to implement best practices from Risk Communication 

101. In addition, training, which could provide agency personnel with the 

risk communication fundamentals, may have limited impact because of 

these organizational barriers. This chapter argues that an understanding of 

organizational limitations and strengths is needed to develop an effective risk 

communication effort. It argues further that, if risk communication training 

does not address organizational issues, the advice in Risk Communication 101 

will remain unheeded. 

*Technically, B. anthracis is the bacterium that creates the disease called anthrax. 

For simplicity, the term anthrax is used when referring to either. 
 

 

196 | Chapter 19: Inside the Organization
	

This chapter does not attribute blame to the government agencies that 

communicated about anthrax. Much media coverage has discussed failures, 

which is not surprising in a political climate that tends to label government 

personnel as heroes or villains, according to research exploring communication 

about anthrax and West Nile virus.1 

What the science says

Not surprisingly, given the dearth of research, the science is hardly robust. 

Many studies are qualitative, which increases depth, but limits generalization. 

Consider a risk communication truism: if relevant information does not reach 

those making agency decisions about releasing risk information, the agency 

cannot effectively release the information. For example, after trace amounts of 

anthrax were found in the U.S. Postal Service Stamp Fulfillment Service Center 

in Kansas City, Missouri, public health officials in that state were swamped with 

calls. However, Inconsistent sharing of information between the Kansas City 

Public Health department (KCPH) and other public health officials meant that 

these agencies had to refer calls they received back to the overburdened KCPH. 

Communication problems at KCPH were compounded by severe deficiencies 

in communications technology;—the agency had to resort to using runners to 

carry messages between floors.2 

Local and state health departments across the country, even those far 

from contaminated sites, received calls from anxious residents about white 

powder. Idaho’s centralized emergency medical center, established to serve 

this rural state, facilitated interagency communication among public health, 

law enforcement, and hazmat officials. However, coordinating agencies’ roles, 

decisions, and communication with the public was more problematic because 

some agencies did not have strong relationships. In addition, local health 

departments were not in the loop, in part, because they did not have pagers.3 

CDC — responding to inquiries. Not surprisingly, CDC, the hub of the public 

health and communication efforts, was challenged by the unprecedented 

volume of calls. The agency adapted by combining its emergency operations 

centers into an agency-wide Emergency Operations Center with a Clinical 

Communication Team that developed communication products, an Office of 

Communication Media Team, and a Public Inquiries Team.4 

CDC developed a triage system that ultimately handled more than 11,000 

calls.4 Managers quickly understood that calls would need varying levels 

of expertise, and they developed units capable of responding differently. 

However, during the crisis when the triage system developed problems, CDC 

had difficulty adapting further because the agency was unable to learn and 

adjust in real time to the strengths and limitations of the system. For example, 

because the system to document the topics and calls was not computerized, 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 197
	

CDC used paper forms.5 But the volume of calls often prevented the staff who 

were answering the phones from efficiently updating the paper records. As a 

result, staff and managers rarely had up-to-date or complete information — 

less than 40% of records contained even basic information such as the topic 

under discussion.4 

Retrospective analysis indicated that CDC squandered the expertise of 

the epidemiologists, physicians, and veterinarians who composed the State 

Liaison Team (SLT) that was meant to field high-risk calls. Almost 75% of calls 

forwarded to the SLT did not meet the definition of high risk (p.1091).4 

CDC: learning under pressure. Another problem that limited learning 

at CDC was physical location — personnel wasted time walking the halls 

because the hub of operations was in one building; the communication staff 

developing materials for release was in a second building; and the CDC media 

staff were housed in a third building.5 In this situation when email boxes 

were jammed and all staff were immersed in solving immediate problems, in 

your face discussion was arguably critical to command scientists’ attention to 

communication issues. 

Some of the teams in the field had even greater constraints. The addition of 

CDC personnel overloaded already stressed systems, with everyone short of 

land lines, cell phones, and faxes.5 As with CDC headquarters, lack of physical 

proximity was also problematic. 

Despite these difficulties, CDC adapted well to other problems. When calls 

from reporters were overwhelming, CDC decided to start holding frequent telebriefings (telephone-based news conferences with reporters).5 This process 

was largely effective. Nonetheless, CDC personnel were sometimes dismayed 

that reporters failed to stress what CDC saw as key information. Analysis has 

shown that the agency failed to appreciate the extent to which it needed 

to emphasize and repeat specific information that was apt to be confusing, 

such as the usefulness of swabbing or changes in recommendations about 

antibiotics.6 During the crisis, CDC defined the problem as “poor reporting,” 

which was seen as largely outside the agency’s control. Instead, the problem 

was its own communication, which should have focused to a greater extent on 

misunderstandings. 

Particularly problematic was CDC’s routine process for reviewing materials 

prior to release: (1) Scientists collected and interpreted information; 

(2) communication staff and scientists discussed written material; (3) 

communication staff drafted material; (4) varied levels of personnel conducted 

internal peer review; (5) communication staff redrafted; and (6) varied levels 

of personnel further reworked material. This process, cumbersome under 

the best of circumstances, was unworkable in a crisis, let alone one of this 

magnitude. The communication staff adapted by working from transcripts of 

the tele-briefings, using these as the basis of questions and answers for the 

web and elsewhere.6 
 

 

198 | Chapter 19: Inside the Organization
	

Organizational theory. Unfortunately this area of limited empirical research 

does not have a strong theoretical base. As a recent review noted there is not 

a “robust theory that takes into account the complex nature of public services 

organizations’ institutional, governance, and structural process.”7 

According to Finger and Brand, organizational learning is a dynamic process 

facilitating adaptation and change essential for agency survival.8 Processes 

of collaboration and formation of communities of practice seem of particular 

relevance to public organizations. A “dynamic model” of organizational 

learning depends on factors related to the source organization (or unit within 

the organization), the relationships among organizations, and the external 

environment.7 

Thus, organizational learning is seen as a social process in which new 

employees learn informally from more experienced employees. According to 

this socially constructed perspective, employees must interpret information 

in ways that are meaningful to them. Learning exists within a community of 

practice, where employees use what they learn and learn from each other. 

Learning does not reside in the heads of isolated individuals.9 

Agyris and Schon have popularized the application of systems theory and 

speak of single-loop and double-loop learning.10 When considering the 

application systems theory to organizational learning, CDC communication staff 

showed single-loop learning when they developed work-arounds for getting 

information cleared.10 Double-loop learning would have required questioning 

the underlying assumptions or norms to reveal the difficulty of trying to provide 

the public quickly with practical information that also needs to be extensively 

peer-reviewed and drafted internally before it can be released. Norms, 

by definition are unexamined and value laden, hence difficult and risky to 

question. 

Based on this limited case study, CDC’s norms might be that (1) extensive 

peer review results in greater scientific accuracy and (2) science is more 

important than responsive communication. Another norm might be 

that evaluation of the science is more important than evaluation of the 

communication. Unless CDC probed the problem by questioning its underlying 

assumptions, the agency would not identify its norms and would have difficulty 

addressing this systemic problem. 

Training and organizational learning. The case of CDC’s communication 

about anthrax points to the limitations of risk communication training that 

focuses largely on building employees’ understandings of public perception or 

skills in message design. These topics dominate many basic risk communication 

trainings, and they might improve staff and managers’ ability to communicate. 

However, it is difficult to see how personnel could actually use these new 

skills. Communication trainings cannot effectively reduce agency constraints, 

such as CDC’s problems with informational systems, physical layout, transfer 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 199
	

of information, etc. If personnel do not function in a context that promotes 

(or, at minimum, does not constrain) effective communication, improving their 

skills is unlikely to improve agency communication. 

Although many federal and state agencies have conducted risk 

communication training, there are no peer-reviewed assessments. Anecdotal 

reports focus on participant satisfaction, rather than changes in knowledge, let 

alone changes in agency practice. Thus, despite consultants’ promotion of the 

importance of training, there is no evidence about its value. However, training 

development is more appealing because it is far easier than evaluating agency 

systems and norms. 

Literature reviews of training on a variety of topics in the private 

sector have found that success depends on the training’s congruence with 

organizational “constraints and conflict, that surface during a meaningful needs 

assessment.”11 Effectiveness relies not only on the training method used, but 

also on how training (and learning) is positioned, supported, and reinforced by 

the organization.11 Therefore, training requires sufficient needs assessment 

to uncover organizational problems. Positioning training in context and then 

implementing follow up activities may facilitate organizational learning. 

Suggestions for practice

Personnel. Without the input of communication experts into major agency 

decisions, communication issues are unlikely to be identified, let alone 

addressed. Therefore, an agency needs at least one senior communications 

manager in the inner-circle of the agency, the so-called dominant coalition.12 

This manager should have extensive experience integrating communications 

goals and strategies with program planning. In addition, evaluation and 

needs assessment skills are imperative. Working with other members of the 

dominant coalition, this manager may identify organizational barriers and 

facilitators of effective risk communication. 

If communication personnel are part of agency decision making, the 

communication gaps between scientists and communicators may be reduced. 

Organizational priorities, standard operating procedures, and funding decisions 

are more likely to reflect a communications perspective. 

Unfortunately, personnel whose experience is primarily limited to mass 

media may not have the necessary background in risk communication, 

communication strategy, evaluation, and stakeholder involvement. Therefore, 

media relations managers are less able to play a significant role in a dominant 

coalition, which grapples with a range of complex problems. 

Similarly, communications technicians (e.g., those who develop 

communication products, such as brochures and press releases) are necessary 

to implement communication strategies, but they are not sufficient for an 

effective communications unit.12 Technicians lack the experience or skills for 
 

200 | Chapter 19: Inside the Organization
	

designing complex programs or integrating communications and program 

development. Instead, technicians develop materials (such as press releases 

and brochures), draft presentations, and conduct routine outreach. Often, they 

are public information or media relations personnel with limited experience. 

Organizational learning. Agencies need to explore the relationship between 

internal organizational factors and external communication. The CDC case 

points out some of the problems that hindered that agency. Other agencies 

need to examine their own practices. Agencies should look at the factors 

that thwarted CDC, such as limitations in technology, interaction among 

different units, and clearance practices. However, other organizational issues 

also warrant exploration. A National Academy report on public participation 

raised issues of relevance to agency risk communication, such as strength 

of agency commitment, agency capacity and resources, and organization of 

implementation.13 

Training. Agencies need to consider how training might facilitate 

organizational goals and fit within the organizational system. A review of 

organizational constraints and conflicts is critical to determine if training 

personnel will solve the organizational problems that have been identified. 

Although skills training may be useful in some situations, agencies need to 

consider whether personnel can implement the guidance. Effectiveness 

depends in part on manager support for others practicing their skills. 

Review procedures must be workable, and agency systems must facilitate 

communication. Moreover, the training itself should reflect the research 

on design and implementation of training, including consideration of 

organizational goals and meaningful follow-up.11 

Among practitioners and scholars, there has been much discussion of 

creating learning organizations, that is, organizations with the capacity to 

learn. On-the-spot learning and activities on the job may be more instrumental 

than training programs. In addition to or instead of training, Finger and 

Brand suggest agencies might build the capacity to learn by using (1) internal 

learning sources, such as performance standards, job rotation, and mentoring; 

(2) external learning sources such as analysis of complaints, convening of 

stakeholder panels, and benchmarking of communication efforts.8 

Evaluation

As the other chapters in this volume attest, agencies too often fail to 

evaluate risk communication products or processes. Not surprisingly, 

evaluation of organizational issues lags even further behind. Evaluation goals 

and processes have yet to be formally developed for organizational aspects of 

risk communication. There is a literature dealing with organizational aspects 

of symmetric public relations, which promotes a dialogue with organizations 

and stakeholders on equal footing. However, for the most part, studies focus 

primarily on the business sector and with issues other than risk communication. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 201
	

No Budget. Developing a training program without, at minimum, an informal 

needs assessment, is likely to waste resources, according to the research on 

training. Similarly, development of a training program without evaluation and 

follow up is unlikely to succeed and likely to squander resources. If training 

exists, the agency should, at minimum, ask participants several months after 

the training to discuss their current communication practices and identify any 

changes resulting from the training. This informal feedback has significant 

limitations, but may identify the strengths and limitations of the training and 

the potential organizational barriers to communication change.

 Agencies may also routinely debrief communication efforts and consider 

the extent to which organizational factors may have facilitated or hindered 

the process. A rigorous evaluation is far preferable because developing an 

institutional memory is unlikely with such informal, undocumented processes. 

But debriefing may facilitate on the spot learning and identify potential 

improvements. Agencies might benefit from organizational units sharing their 

experiences and thus potentially learning from each other and building agency 

capacity. However, if the agency does not attend to the larger organizational 

issues, meaningful change is unlikely. 

Modest budget. Agencies might develop written protocols for debriefing 

and keep records of key learnings. These records might inform a process of 

organizational change. Using internal resources, agencies may conduct studies 

that develop some understanding of perceptions of the organizational barriers 

and facilitators of effective risk communication. Such studies may build on 

other efforts, such as the survey of employees’ risk communication practices 

conducted by the staff of the New Jersey Department of Environmental 

Protection.14 Recently, the agency developed a more in-depth understanding of 

organizational barriers.15 

Serious budget. Ideally an agency would conduct a “360 degree” study that 

explores through surveys and qualitative research the perceptions of internal 

and external stakeholders about risk communication cases. In addition to 

exploring the responses of external audiences to agency risk communication, 

the agency might simultaneously explore the internal organizational processes. 

Such a study should give an agency a far richer sense of how internal 

organizational issues affect specific risk communication actions. 

Additional resources

1. Chess, C. and Clark, L. (2007). Facilitation of risk communication during the anthrax attacks of 

2001: The organizational backstory. American Journal of Public Health 97, 1578-1583. Explores 

how organizational issues, particularly those related to networks, affected communication about 

anthrax. 

2. Grunig J.E. (1992). Excellence in Public Relations and Communication Management. Hillsdale, 

NJ: Lawrence Erlbaum. A classic that summarizes key research on “symmetric, two-way 

communication.” 
202 | Chapter 19: Inside the Organization
	

3. Journal of Health Communication, Volume 8, 2003. Devoted to risk communication about 

anthrax and contains several articles with organizational themes. 

4. Natural Hazards Center University of Colorado. http://www.colorado.edu/hazards. 

The disaster field has long linked organizational and communication issues. The searchable 

database provides citations to relevant articles and access to many reports. 

5. Rashman, L., Withers, E., Hartley, J. (2009). Organizational learning and knowledge in public 

service organizations: A systematic review of the literature. International Journal of Management 

Reviews, 11(4), 463-494. An excellent overview, which discusses current theories. 

6. Society for Risk Analysis. Annual meeting sessions sometimes related to organizational issues and 

risk communication. 

7. Salas, E., and Cannon-Bowers, J.A. (2001). The science of trading: A decade of progress. Annual 

Reviews, Psychology, 2001(52), 471-499. Does not deal specifically with risk communication 

training, but it provides insight into key issues that apply to such trainings. 

8. Scott and Davis. 2007. Organizations and Organizing: Rational, Natural, and Open Systems 

Perspectives. Prentice Hall, A classic summary of organizational theories. 

9. United States Environmental Protection Agency. Evaluation Toolbox. 

http://www.epa.gov/evaluate/toolbox/summary4.htm#adr. Links to many agency reports about 

stakeholder involvement. Some of the reports, which are written for practitioners, contain frank 

assessments of organizational problems. 

Endnotes

1 Maxwell, T. A. (2003). The public need to know: Emergencies, government organizations, and 

public information. Government Information Quarterly, Fall 2003. 

2 Riederer-Trainor, C., Wilkinson, T., Snook, W.D., Hoff, G.L., Griffin, R. and Archer, R. (2005). When 

bioterrorism strikes: Communication issues for the local health department. Health Promotion 

Practice (October), 424-429. 

3 Tengelsen, L., Hudson, R. Barnes, S. and Hahn, C. (2002). Coordinated response to reports of 

possible anthrax contamination, Idaho, 2001. Emerging Infectious Diseases. 8(10): p. 1093-1095. 

4 Mott, J. A., Treadwell, T.A., Hennessey, T.W., Rosenberg, P.A., Covell, M.I., Brown, C.M., and 

Butler, J.C. (2002). Call-tracking data and the public health response to bioterrorism-related 

anthrax. Emerging Infectious Disease, 8(10), 1088-1092. 

5 Robinson S.J. and Newstetter, W.C. (2003). Uncertain science and certain deadlines: CDC 

responses to the media during the anthrax attacks of 2001. Journal of Health Communication, 

2003(8), 17-34. 

6 Mbane, F., Temin, S. and Parvanta, C.F. ( 2003). Communicating anthrax in 2001: A comparison of 

CDC information and print media accounts. Journal of Health Communication, 8, 50-82. 

7 Rashman, L., Withers, E. and Hartley, J. (2009). Organizational learning and knowledge in public 

service organizations: A systematic review of the literature. International Journal of Management 

Reviews, 11(4), 463-494. 

8 Finger, M. and Brand, S.B. (1999). The concept of the learning organization applied to the public 

sector: Conceptual contributions to theory development. In M. Easterby-Smith, L. Araujo, and J. 

Burgoyne (Ed.). Organizational Learning and the Learning Organization: Developments in Theory 

and Practice. Thousand Oaks, California: Sage. 

9 Easterby-Smith, L. A. and J. Burgoyne (Eds.). Organizational Learning and the Learning 

Organization: Developments in Theory and Practice. Thousand Oaks, CA: Sage. 

10 Agyris, C. and Schon, D. (1978). Organizational Learning: A Theory of Action Approach. Reading, 

MA. : Addison Wesley. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 203
	

11 Salas, E. and Cannon-Bowers, J.A. (2001). The Science of Trading: A Decade of Progress. Annual 

Reviews, Psychology, (52), 471-499, see p. 475. 

12 Grunig, L. A. ( 1992). How public relations/communications departments should adapt to the 

structure and environment of an organization...and what they actually do. In J.E.Grunig (Ed.), 

Excellence in Public Relations and Communication Management (pp. 467-482). Hillsdale, NJ: 

Lawrence Erlbaum. 

13 Dietz, T. and Stern, P. (2008) Public Participation in Environmental Assessment and Decision 

Making. Washington DC: National Academies Press. 

14 Shaw, J. and Johnson,B. (1990). A Look Inside: Risk Communication and Public Participation Within 

the New Jersey Department of Environmental Protection. Trenton: NJDEP, Department of Science 

and Research. 

15 Chess, C. and Johnson, B. B. (2006). Organizational learning about public participation: “Tiggers” 

and “Eeyores.” Human Ecology Review, 13, 182-192. 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 205
	

Chapter 20: Practitioner Perspectives

Lee Zwanziger, PhD - Food and Drug Administration 

The following current or former members of the Risk Communication Advisory 

Committee contributed to this chapter: Jacob DeLaRosa, M.D; AnnaMaria DeSalva; 

Sokoya Finch, M.A.; Sally Greenberg, J.D.; Prerna Mona Khanna, M.D., M.P.H., FACP; 

Madeline Y. Lawson, M.S.; Kala Paul, M.D.; and Marielos L. Vega, B.S.N., R.N.* 

Summary

Communicators find most success when they shape messages to begin with 

key information that is relevant for the target audiences. Communicators 

should use plain language and formats and use pictures and stories to help 

clarify and reinforce the message for the audience. Communicators should 

check audience understanding and plan ahead for communicating in times of 

crisis. 

Introduction

Risk communication is a practice as well as a science. As practitioners of risk 

communication, we want to apply the results of scientific research on effective 

communication as discussed in previous chapters. We also see successful 

and unsuccessful communication in daily practice. We hope the following 

observations will be useful to communicators and researchers in general, but 

especially to FDA. 

Risk communication practices have changed over the years, as patients 

and consumers are taking more active roles in their health. Effective 

communication is two-way communication, and more open communications 

with health care professionals can lead to better health in the end (see 

Chapters 13 and 17). For example, one of us had an experience with a patient 

we’ll call Mrs. Smith, a 60-something-year-old grandmother anxious to shed 

a few pounds. She selected a popular weight loss program and enlisted her 

doctor’s support. Several weeks later, however, she had actually gained 

weight. Flabbergasted, her doctor asked what happened. Near tears, she 

replied “Doctor, I just don’t know. I followed the directions: I had a healthy 

breakfast and then I had a shake. I ate a hearty lunch, and then I had another 

* Thanks go also to 2010 FDA summer intern Karen Bassett and to all open public hearing speakers 

at the 2008 – 2010 meetings of the Risk Communication Advisory Committee. 
 

 

 

 

 

206 | Chapter 20: Practitioner Perspectives
	

shake. And every night I had a healthy and hearty dinner.” The doctor gently 

told Mrs. Smith that she should substitute the shake for the breakfast and 

lunch meals! 

Although little of FDA’s communication is directly person-to-person, as in 

this doctor-patient interaction, some of the common communication pointers 

still apply, like checking understanding and letting communication flow in both 

directions. Our goal here is to help practitioners, and FDA, communicate better 

and more easily, as summarized in the Table, both to provide information and 

to make recommendations (Chapter 2). 

Practitioners’ perspectives: Lessons at a glance

Communicators should: 

•		 Give the key messages at the start of the communication 

•		 Speak to the target audience and let them know who they are 

•		 Shape the message to the needs of the target audience: 

o Relevant to audience needs 

o Sensitive to audience situation 

o Accessible in format and language 

•		 Use pictures and stories for illustration and break up text in 

written communication 

•		 Check audience understanding 

•		 Plan ahead to be ready for urgent communications 

What does our practical experience suggest for communicators? 

The first point is, in brief, be brief! To be effective while brief, 

communicators should know their audience and tailor the message 

appropriately (see Chapters 7,14,16). 

As a communicator, you need to define the target audience and what that 

audience needs to know. Communicators should start by answering these key 

questions: 

• Who should pay attention to the information? 

• What should those people know about it? 

• What should those people do about it? 

Then the communication should provide a pathway for more information, for 

people who have more questions (see Chapter 4 for more on factors needed in 

adequate communication). 

Plan ahead. Our key theme: Prepare for crisis communication so the process 

itself is not a crisis. FDA must be ready to manage bad or risky situations like 

newly discovered product defects, tainted food shipments, or unexpected side 

effects (see Figure 1). Prior planning is key: The communication system cannot 
 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 207 

work to get urgent information to the public efficiently, unless the system itself 

is already set up before the crisis occurs (see Chapter 19 and Figure 1). When 

a crisis does occur, communicators should focus on delivering clear messages, 

not on inventing the process for developing and clearing communications. 

Figure 1. Planning for urgent communication of new or emerging risks1

Investigate trend: 

Inform stakeholders; 

Support affected patients; 

Prepare for potential 

intervention 

Notify Healthcare 

Professionals, Industry 

(manufacturers, retailers), 

Partner agencies and 

organizations, Work with 

news cycle for 

communicating to public 

through media 

Needs Approach 

Emerging 

Risk 

• Effective communication strategy begins far 

“upstream” as emerging risks are identified 

• It’s important to build the knowledge, 

systems networks of expertise before you 

need them in an urgent situation 

• Effective crisis and risk communication is 

essential at the time of an urgent risk event, 

but often the follow-up communication is 

central for a goos outcome 

• Stakeholder engagement, coordination 

and participation in formative and 

implementation phases is central to success 

Source: AnnaMaria DeSalva (2008)1 

Knowing your audience is key. Different audiences have different 

information needs, but they may also have points in common. For example, 

health care professionals want more detailed scientific information and 

technical directions than many patients would (see Chapter 6). Everyone 

benefits from clear, direct, and timely information. Using illustrative examples 

— pictures and stories — clarifies your message. As a communicator, you 

should be on the look out for barriers that could keep some members of the 

audience from either getting or acting on your message. 

Barriers to getting the message. First, no one should assume that everyone 

can read (see Chapter 9). More than 10 % of Americans read at only a below 

basic level, and that jumps to more than 20 % who struggle below basic if the 

information is quantitative.2

 Even people who can read general material may 

struggle with health information and find the presentations too technical. 

“Health literacy” means being able to take in and use information to make 

informed health decisions. More than 30 % of Americans struggle with health 

literacy at a level of basic or below, and a good deal of important health 

information is more complex than basic.3 People with lower health literacy 

may have difficulty making informed health decisions for themselves or their 

families and may be unable to follow health advice even though they try.4 
 

 

 

208 | Chapter 20: Practitioner Perspectives
	

Reading is important but not the only factor; stage of life also makes a 

difference (see Chapter 12). Children may be strongly affected by persuasion, 

for example, in choosing foods. 

And despite the benefit of life experience, some older people face vision, 

hearing, or cognitive challenges. Communicators should take care to explain 

risks and benefits and check listeners’ understanding. 

•		When possible, ask the audience or patients to teach the information 

back, as a check on their understanding.
	

•		Be prepared to slow down and repeat information and demonstrations for 

better audience understanding. 

Communicators can have a big impact on informed health decision making, 

especially when people have difficulty getting information from other places 

because of their literacy level, vision, or other barriers. 

Language barriers. According to the 2000 Census (latest data available), 

about 18 % of Americans live in households speaking a language other than 

English.5 Many health care documents are available in languages other than 

English, either online or from advocacy organizations.6 We applaud, but also 

stress that the intended meaning of a message can be garbled in translation, so 

take care to test the translation with the intended users. 

What the message means to the audience. As communicators, we start 

with an idea of what information is important. Audience members also bring 

experience and expectations, which affects how they hear the message. This 

experience may give our messages unintended meanings with unintended 

effects. We may try to give a limited warning, but some audience members 

may hear something severe. For example, a warning to eat only moderate 

amounts of certain types of fish while pregnant could lead some concerned 

mothers to avoid fish altogether and so miss out on the benefits of fish for their 

developing babies.7 

Audience emotional and social context can also influence whether they 

can or will take actions that the message recommends (see Chapter 10). For 

example, if the message warns of a new risk and directs patients to see their 

doctors, those without easy transportation may not be able to act quickly. And 

when we counsel patients to lose weight by balancing healthy carbohydrate, 

protein, and fat intake, we imply that everyone has access to a range of 

healthy foods. In reality, they may not have access, or more subtly, may need 

help on thinking through how to work the advice into their usual menus. 

Similarly, when we counsel patients to take their medicines as prescribed, we 

are assuming they have access to the medicine. But the copayment may be 

unaffordable, the dosing schedule may seem complicated, or the medicine 

may call for refrigeration the patient does not have. Ignoring audience context 

could cause people in the target audience to disregard the whole message as 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 209
	

unusable or irrelevant. As a communicator, you may not be able to address 

all those difficulties, but at least you should consider contextual barriers when 

designing and evaluating messages. 

Audience needs and preferences. Targeting health messages to the right 

population is important (see Chapter 11). When addressing a group of older 

men on symptom awareness of cancer, we would pick the topic of prostrate 

cancer over testicular cancer. When addressing patients with Type 2 Diabetes 

about a healthy lifestyle, however, we would cover awareness of end-organ 

damage and heart disease, rather than of range of motion exercises. Our work 

with varied audiences reminds us that we are in the end communicating with 

individuals. Diversity exists within any group, and so information needs and 

background beliefs may also vary widely. 

When the communicator speaks on a national level like FDA does, addressing 

each individual is impossible. But remembering that individual differences and 

needs exist may help avoid some communication mistakes. Some strategies for 

connecting with individuals in large and diverse audiences follow. 

Connecting with your audience. Communication is a two-way interaction 

and is most effective when communicators and audiences achieve a 

connection. In written communications, keeping the individual reader in mind 

helps create more of a connection; for example, write recommendations to 

“you” not “the patient.” 

Person-to-person. Person-to-person communication is powerful. FDA is a 

large organization that can create personal connections by developing one, 

or a few, high-profile and easily recognizable spokespersons to be the face 

and voice communicating for FDA. Another way to tap into person-to-person 

power would be for FDA to develop partnerships with organizations that can 

reach subsets of the population, extending FDA’s. People might be even more 

likely to get the message if it comes from a familiar organization. 

When FDA has to address an urgent situation, such as a possible outbreak 

of food-borne illness, oftentimes, information continues to emerge. It is 

important for communicators to be forthright about what is known and what 

is unknown. Although people may want to know more than you can tell 

them at that time, they will probably respect your honesty about the genuine 

uncertainty of the situation. 

Share stories. Sharing stories can be a powerful part of communication 

because it both offers an example and makes an interpersonal connection. 

Stories should be used to help communicate FDA’s message, not to substitute 

for or hide evidence (see Chapters 5 and 18). One way FDA has used stories 

in the past in communications is to describe cases about outbreaks, or more 

generally, to illustrate why a safety problem exists. Another way stories can 
210 | Chapter 20: Practitioner Perspectives
	

be important is that when individuals present their stories in public meetings, 

listeners remember not only the data, but the emotions and personal impact, 

of safety problems. 

Use different media channels. Fewer and fewer individuals rely only on 

traditional media or direct conversation for their health information. Many 

people are now regular users of websites and email. Still others now see 

email as totally outmoded by fast-paced social media. Partly because of the 

prevalence of public use of the Internet for health information, as well as 

the low cost to FDA and the ability to display large amounts of information, 

posting information on FDA’s website is the agency’s first choice channel of 

communication. For faster communications, FDA is also using Twitter and 

Facebook. However, the popularity of the Internet for both FDA and its 

audiences means that the FDA website must be understandable and easy 

to navigate. Yet outside users tell us they often have trouble finding what 

they need on FDA’s website. This works against the interests of millions 

of consumers who visit the site for advice and information and who might 

give up the search if they don’t find what they need. FDA continues to work 

on improving its website, with the help of regular and contract experts.8 In 

the meantime, it is important to remember that many people do not have 

regular Internet access. This is why it remains vital for FDA to partner with 

state agencies and associations that have direct connections with the public. 

Even if FDA cannot itself effectively reach the entire population, it can 

provide information in a form that other organizations can use to disseminate 

important health messages. 

Shaping your message. When you give your audience the information they 

need, in a form they can use, without unnecessary barriers, you show respect 

for them as individuals and make the information more likely to reach them 

(see Chapters 7 and 8). 

Lead with key messages. Individuals of all levels of education are not likely to 

sort through long complicated documents to find the key health messages — 

often they just don’t have the time. Health care professionals aren’t the only 

ones who are very busy; we’re all busy. The first few sentences or moments of 

communication might be your only chance to share key messages. Follow up 

with more details and contact information because some of your audience will 

want to go further and get more information. 

Use plain language. Audiences of all educational levels more readily grasp 

clear, concise messages that are written in a straightforward manner. That 

doesn’t mean dumbing down the message or avoiding quantitative data. It 

does mean avoiding unnecessary specialized vocabulary or technical terms. If 

the communication involves probabilities and uncertainty, or if information is 

still emerging, you should be frank about what you know and what you don’t 
 

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

J J J J J J J J J J

L L L L L L L L L L

Figure 2. Pictures that communicate a message

Out of 100 patients taking this drug, we’ve seen that 

10 have bothersome side effects (the L below) and

90 have small or no side effects (the J below): 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 211
	

know. When quantitative information is available, it should be presented 

clearly, with numbers. Using only words like “low,” “medium,” and “high” can 

mean different things to different people and be confusing. 

Show AND tell. Showing your audience what to do or what you mean can 

help in three ways. It can help the audience: 

• master actions 

• feel vividness, and 

• understand quantitative information. 

Demonstrations and pictures can help make directions simpler to understand 

and follow for any literacy level. For example, the directions for using a 

medical device like an Epi-Pen must be written, but a video showing what to 

do could be worth more than a thousand words. FDA discussed this in the 

program Patient Safety News and included a link to the manufacturer’s video 

instructions.9 Photos or diagrams of action steps can also be helpful and would 

probably be even more helpful as reminders, if the patient had previously seen 

them as real actions. 

Pictures can make a warning more vivid (see Chapter 15). A photo of oral 

cancer from heavy tobacco use can be so convincing that individuals are more 

likely to act on it, even if they forget the details of the message.10 At the same 

time, as with any message, you should test a picture with actual users to make 

sure that it communicates the message you intend.11 

Source: Lee Zwanziger, based on suggestions and slides from 

FDA Risk Communication Advisory Committee meetings.12 

Diagrams can help make quantitative information easier to see. For 

example, suppose we have to communicate that test results indicate that 10% 
212 | Chapter 20: Practitioner Perspectives
	

of patients taking a medicine had side effects (Figure 2). Data and practical 

experience show that this type of pictogram is a powerful aid to understanding 

quantitative risk (see Chapter 7).12 

What does our practical experience suggest about evaluating 

communications?

Audiences may receive a very different message than the one we tried 

to communicate. They may not understand our message. Or,we may not 

understand what our patients or members of the public are trying to tell us. 

The possibility of misunderstanding does not go away even with experienced 

communicators. This is why, as discussed in Chapter 3, we must keep checking 

with the audience to learn whether they heard what we meant. 

•		 In one-on-one situations, the fastest and easiest test is to ask the other 

person to “teach back” what they just heard. 

•		In written communications, we’ve all had the experience of showing a 

draft to someone else and had the fresh-eyed reader find mistakes or 

garbled sentences. 

These informal reviews become even more important in health 

communications, where unclear messages might lead to poor, or poorly 

informed, health decisions. So even without formal testing, it is important to 

find a few new readers or listeners for a draft communication. The broader the 

audience and the further removed from person-to-person contact, the more 

important understandability checking will be for effective communication. 

Conclusions

As a communicator, you will be more effective if you respect your audience. 

Give them the information they need, in a form they can use, and without 

unnecessary communication barriers. Lead with the key information. Know 

who the message is for, what these people should know, and what they 

should do about it. Make the message clear with plain language, pictures, and 

demonstrations. Finally, check audience understanding. 

Additional resources

1. Plain language: Improving communications from the federal government to the public. 

This website is the government’s advice to the rest of the government on how to communicate 

more clearly. Available at http://www.plainlanguage.gov/ 

2. Doak, C.C., Doak, L.G., Root, J.H., and Lippincott, J. B. Philadelphia, 1992. Reference for Plain 

Language writing: Teaching Patients with Low Literacy Skills, 2nd edition. 

3. Communicating Health: Priorities and Strategies for Progress. This publication provides in-depth 

action plans for each of the six Healthy People 2010 Health Communication Objectives, including 

Objectives 11-2 and 11-6 on health literacy. Available at: http://odphp.osophs.dhhs.gov/ 

projects/HealthComm/. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 213
	

4. Bibliography Understanding Health Literacy and Its Barriers. The National Library of Medicine’s 

(NLM) bibliography provides a comprehensive list of health literacy citations from varying 

disciplines and publications. The bibliography is divided into specific topic areas. Available at: 

www.nlm.nih.gov/pubs/cbm/healthliteracybarriers.html. 

5. Scientific and Technical Information: Simply Put. This guide from the Centers for Disease Control 

and Prevention (CDC) will help you translate complicated scientific and technical information into 

material that captures and keeps the interest of your intended audience. Available at: http:// 

www.cdc.gov/od/oc/simpput.pdf 

Endnotes

1 This graphic is based on several slides presented at the August 2008 meeting of the Risk 

Communication Advisory Committee by charter member AnnaMaria DeSalva. For full 

presentation see slides (accessed 1/13/2011) http://www.fda.gov/ohrms/dockets/ac/08/ 

slides/2008-4377s2-01.pdf 

2 http://nces.ed.gov/naal/kf_demographics.asp, accessed 1/13/2011. 

3 http://nces.ed.gov/naal/health_results.asp, accessed 1/13/2011. 

4 For examples and discussion, see Marcus, E. N. (2006). The silent epidemic – the health effects of 

illiteracy. New England Journal of Medicine, 355(4), 339-341. 

5 http://www.census.gov/prod/2003pubs/c2kbr-29.pdf, accessed 1/13/2011. 

6 For example, The National Diabetes Education Program provides educational materials and tools 

on diabetes awareness and maintenance tailored for Hispanic populations, see http://www.ndep. 

nih.gov (accessed 1/13/2011). 

7 For results supporting the possible change in eating habits, see Oken, E., Kleinman, K. P., Berland, 

W. E., Simon, S. R., Rich-Edwards, J. W., et al. (2003). Decline in fish consumption among pregnant 

women after a national mercury advisory. Obstetrics and Gynocology, 102(2), 346-351, and 

for results showing possible effects of changes in eating habits, see Cohen, J. T., Bellinger, D. 

C., Connor, W. E., Kris-Etherton, P. M., Lawrence, R. S., et al. (2005). A Quantitative risk-benefit 

analysis of changes in population fish consumption. American Journal of Preventive Medicine, 

29(4), 325-334. 

8 For status, see http://www.fda.gov/AboutFDA/AboutThisWebsite/default.htm, accessed 

1/13/2011. 

9 For FDA Patient Safety News, see http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/psn/printer. 

cfm?id=225, and for manufacturers video, see http://www.epipen.com/how-to-use-epipen (both 

accessed 1/13/2011). 

10 Research on graphics in warning on cigarette packages, presented at May 2010 

meeting of the Risk Communication Advisory Committee by member C. Andrews, see 

slides (accessed 1/13/2011). http://www.fda.gov/downloads/AdvisoryCommittees/ 

CommitteesMeetingMaterials/RiskCommunicationAdvisoryCommittee/UCM211341.pdf. 

11 One memorable communication featured a fried egg and the caption “this is your brain on 

drugs,” but testing later showed the campaign it was part of had little effect on reducing 

drug use. Discussed at May 2010 meeting of Risk Communication Advisory Committee by 

guest speaker Julie Downs, see slides http://www.fda.gov/downloads/AdvisoryCommittees/ 

CommitteesMeetingMaterials/RiskCommunicationAdvisoryCommittee/UCM211334.pdf 

(accessed 1/13/2011). 

12 This diagram is smaller and simpler but similar in style to those suggested in meetings 

of the Risk Communication Advisory Committee by member J. Paling, see http://www. 

riskcomm.com/paling_palettes.htm (accessed 1/13/2011). Also note that the usefulness 

of this type of diagram is supported by data presented at the May 2010 meeting of the Risk 

Communication Advisory Committee by member A. Fagerlin, see slides (accessed 1/13/2011). 

http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/ 

RiskCommunicationAdvisoryCommitteeUCM211338.pdf. 

 

 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 215
	

Chapter 21: An Agency Perspective 

Nancy M. Ostrove, PhD - Food and Drug Administration 

Summary

FDA is committed to effectively communicating about regulated products 

that affect the public on a daily basis. But challenges abound for federal 

agencies wanting to take an evidence-based approach to creating and 

regulating communications. Nonetheless, as demonstrated by its Strategic Plan 

for Risk Communication and the increasing use of external risk communication 

experts, FDA is rising to this challenge to ensure that the public has and 

understands the needed information to appropriately use products that can 

ensure a healthier and safer America. 

Introduction

Like many other federal, state, and local agencies, the Food and Drug 

Administration (FDA) communicates daily with stakeholders. Much of its 

communication focuses on the benefits and risks of regulated products. In 

recent decades, many have questioned whether federal agencies, including 

FDA, communicate as effectively as possible. As Hamburg and Sharfstein 

recently asserted, “one of the greatest challenges facing any public health 

agency is that of risk communication.”1 The National Research Council 

defined risk communication as encompassing the process of information and 

opinion exchange among individuals, groups, and institutions. It involves 

multiple messages — not strictly about risk — and is successful when it raises 

understanding of relevant issues and actions and satisfies people that they are 

reasonably informed within the limits of available knowledge.2 

FDA’s Strategic Plan for Risk Communication (SPRC) laid out three 

interlocking FDA goals as the foundation for an evidence-based approach 

to risk communication: Strengthening science, expanding capacity, and 

optimizing policy.3

 The SPRC recognizes that there is a science behind 

communications and that understanding and applying this science is critical 

to effective communication about regulated products. FDA faces a number of 

challenges in implementing the science-focused goal toward improving its risk 

communications. Some of these are common to many government agencies, 

and even to private-sector organizations, whereas some are specific to FDA. 

This chapter discusses the most significant of these challenges. 
216 | Chapter 21: An Agency Perspective
	

The context behind FDA communications 

FDA is committed to ensuring that the regulatory and policy decisions 

underlying its communications are evidence-based. However, consistent with 

the nature of scientific knowledge, that evidence inevitably evolves and is often 

uncertain. In fact, even the methodologies used to gather the data that guide 

these decisions are not perfect. 

For example, the decision to approve a sponsor’s request to market a 

new prescription drug, biologic, or novel medical device relies on data from 

randomized controlled clinical trials. These data enable clear inferences about 

causality, but only for the populations, circumstances, and specific questions 

studied. Uncertainties remain about how well the data predict a product’s 

effectiveness and safety when prescribed and used under real world conditions 

— in untested populations and circumstances. It is challenging enough to 

communicate the concept of relative safety and efficacy. Given that the legal 

descriptor for approved products — “safe and effective” — implies absolute 

safety and effectiveness, the general public may see approvals as clear yes-no 

decisions. Unfortunately, this creates ripe ground for confusion when new data 

appear on a product’s safety or effectiveness, making the communication of 

data uncertainty especially relevant to creating a fully informed understanding 

of product risks and benefits. 

Uncertainties also arise when FDA must decide whether to temporarily 

recall or completely withdraw a product already on the market. Sometimes 

products get contaminated, either deliberately or inadvertently. Sometimes, 

experience with a product in the uncontrolled (real world) market raises safety 

concerns — suggesting new problems or confirming previously suspected 

ones. For example, voluntary reports from health care professionals and 

consumers of patients’ or consumers’ adverse experiences, as well as data from 

epidemiologic studies of large databases, can signal possible product problems. 

Unfortunately, these methodologies typically cannot confidently establish 

causation, ruling out potential confounding factors. Sometimes, data obtained 

by following up on safety signals cannot be easily interpreted. For example, 

extensive detective work may still produce a weak signal regarding the cause 

of a food-borne illness outbreak — was it the tomatoes or the peppers in the 

salad? The substance initially identified ultimately may turn out to have been 

misidentified. Sometimes, the cause is never known for sure. 

This discussion of the context of FDA communications demonstrates the 

challenge of communicating effectively about evolving product problems 

and related uncertainties. Although some general research suggests how to 

accomplish this, it has not addressed FDA’s specific needs. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 217
	

Challenges to implementing evidence-based communication 

All federal agencies experience challenges in implementing an evidencebased approach to communicating with the public. This section first addresses 

challenges that are common to FDA and other agencies and then addresses 

challenges unique to FDA. 

Informed communications development and evaluation. Effective 

communication requires understanding and addressing audience needs that 

can only be identified by talking with the targeted audiences. Recognizing 

this, FDA is striving toward instituting the standard practice of testing 

communications prior to use to increase effectiveness, reduce the likelihood of 

negative responses, and guide future efforts. 

To do such testing, however, all government agencies share the challenge 

of addressing the clearance process required by the Paperwork Reduction 

Act (PRA) to obtain similar information from 10 or more individuals. The PRA 

is designed to protect the public from excessive government information 

requests, but it greatly slows the conduct of needed research. Without that 

clearance, research is limited to collecting similar information from 9 or 

fewer individuals, obviously limiting the generalizability of results. Larger 

samples require specified time periods to allow public comment on the 

proposed information collections, a detailed justification for the information 

collection, and review by the Office of Management and Budget (OMB). For 

FDA requests, the process for a new information collection typically takes at 

least 5 to 8 months. This creates a challenge to conduct research to inform 

needed communications on a fast turnaround basis. Generic clearances can 

significantly shorten the approval process for communications-related 

pre-testing and formative research.4

 As part of the SPRC, FDA has begun to 

establish additional generic clearances to facilitate expeditious approval of 

needed communications pre-testing and formative research and for survey 

questions to evaluate communication effectiveness. 

Applying past experience to planning for the future. Another challenge 

shared by other agencies is how to learn from experience (and plan for the 

future) by assessing the effectiveness of ongoing standard and emergency 

communication experiences. A challenge unique to FDA is communicating, and 

evaluating communications, while still conducting product reviews, product 

and facility inspections, and other significant work. The subject matter experts 

who carry out this ongoing work are more often than not the same experts 

who are needed to collaborate with communications staff in planning both 

ongoing and emergency communications. Once a communications event is 

past, the subject matter experts return to their daily work and communications 

professionals turn to the next topic on their list. It then becomes challenging 

to focus on evaluating the effectiveness of the now-past event. To address this 

challenge, FDA has begun instituting mechanisms to gather both process and 

impact measures of communications development and effectiveness. 
218 | Chapter 21: An Agency Perspective
	

Trust and competition from other information sources. As with many 

government agencies, FDA is not the only source of information about 

the products it regulates. Information about foods and medical products 

comes in the form of promotional and educational materials from product 

sponsors (producers and distributors of regulated products), from people 

acting on sponsors’ behalf, and from completely independent sources. 

FDA is not even the only regulatory entity that oversees information from 

producers and distributors of many FDA-regulated products.5 The explosion 

of information available through the Internet provides ever more competition 

to FDA-developed or -regulated communications. Although some of these 

communications are congruent with FDA’s messages, some are conflicting. 

For FDA, the challenge is to ensure that the public perceives the agency as 

reasonably trusted and credible. If the public does not see FDA as trusted and 

credible, its communications will be less effective — even if all its practices and 

procedures are solidly evidence-based. Lack of self-interest should make FDA 

a highly credible source of information — especially compared with product 

sponsors. However, since the passage of the first Prescription Drug User Fee 

Act of 1992, requiring sponsors to pay user fees for FDA to review prescription 

drug market approval submissions within set time frames, some members of 

the public have claimed that FDA is now too dependent on industry and cannot 

be trusted to give independent reviews. 

Public poll results show varying pictures of the degree of trust in FDA as 

a communication source. Answers to questions that ask about trust in FDA 

in general do not address trust in FDA as a source of information about 

the wide variety of regulated products (accounting for about 20 cents of 

every consumer dollar). The bottom line is that FDA needs to understand its 

perceived credibility and trustworthiness with the public for practical planning 

for effective communications. 

Precision versus understandability. FDA’s regulatory authority is not 

absolute; it is subject to nuanced constraints often clear only to those with 

scientific or legal training. The precision sought by scientists and attorneys 

who are the backbone of FDA as a science-driven regulatory agency can result 

in highly caveated statements. Unfortunately, providing a large quantity 

of information does not lend itself to effective communication. In fact, 

communicating multiple caveats and uncertainties can dilute a message to the 

point of cognitive inaccessibility (see also the discussion about audiences in 

the next section). From a perceptual perspective, the proliferation of caveats 

about uncertainties can result in discrediting the decisions to which they are so 

carefully applied. 

Range of audiences and audience needs. Like many other organizations, 

FDA has stakeholders in audiences with widely varying information needs and 

cognitive capabilities. Those audiences include the general public (patients, 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 219
	

consumers, and lay care givers), medical professionals (individuals, institutions, 

and associations), manufacturers, producers, distributors, retailers, advocacy 

groups, government (state, local, national and international), and other 

non-government organizations. Audience knowledge about products, health, 

medicine and pharmacy practice, regulations, and public policy ranges from 

very little to a lot. Audience capabilities also can vary with respect to general 

literacy, health literacy, and cognitive abilities. One challenge, discussed 

below, is how to target communications, especially in addressing the needs 

of members of the general public with lower literacy skills and cognitive 

capabilities. 

Deciding when and with whom to communicate. A communication 

challenge shared with many organizations is deciding when to communicate 

about an issue. This is especially relevant to FDA when a signal arises of a 

possible product problem. FDA receives such signals daily, but in determining 

whether to communicate about them, the agency must balance the public’s 

need to know with the risks of overburdening the public with an unwieldy 

barrage of information. Should FDA use a low threshold for public notification, 

thereby possibly crying wolf too often and perhaps lowering signal value? 

Or should FDA use a high threshold for public notification, thereby risking 

the perception that it lacks transparency and hides information critical to an 

informed public? 

Common sense might suggest a solution of communicating signals early on 

only to experts who can understand more fully the inherent uncertainties while 

delaying communication with the general public until there is greater certainty. 

However, the responsibility to be fair requires that all members of the public 

get information at the same time. Thus, for example, FDA policy is that it does 

not provide early warnings to medical providers before providing information 

to the general public about a new, increased, or decreased drug or medical 

device problem. Yet many health care practitioners have told us that they 

would like to be better prepared for the deluge of questions they can get once 

patients hear about a possible problem. 

Indirect communications. A challenge FDA shares with other regulatory 

agencies is when to communicate directly with the public rather than relying on 

regulatory influence over product sponsor communications. Historically, much 

of FDA’s communications role was indirect, ensuring that product labeling 

is accurate and comprehensive. FDA could do this because of its premarket 

approval authority over certain products. Product labeling is drafted by product 

sponsors and then reviewed and ultimately approved by FDA staff. However, 

FDA’s ability to compel sponsors to accept the agency’s interpretation of 

issues is constrained by both scientific and regulatory–legal considerations. 

FDA and sponsors often negotiate disagreements, with each side arguing for 

its interpretation of often ambiguous data. Furthermore, it is typically hard to 
220 | Chapter 21: An Agency Perspective
	

compel changes based purely on communications concerns. For example, it 

might be difficult to justify denying approval to market a product because its 

labeling explained a potential warning in language FDA believes is not optimally 

effective for communicating that danger. 

Historically, for medical products, FDA often communicated directly to the 

public when it believed a product should be recalled because of an imminent 

danger to public health. But new and uncertain signals typically would not 

generate sufficient certainty to justify the extreme action of a recall or market 

withdrawal. Instead, the focus was on ensuring revisions to the product’s 

labeling that would accurately communicate the current state of knowledge. 

Ultimately, belief about the lack of immediate danger coupled with the legal 

mandate to protect confidential information has often led to delaying public 

disclosure about a possible problem until revisions to product labeling were 

finalized. Because contentious and lengthy negotiations on proposed revisions 

often resulted from disagreements about how to interpret the data, public 

disclosure could be further delayed. 

In recent years, FDA has become increasingly likely to communicate directly 

with its public stakeholders as problems arise and rely less on communicating 

through product labeling. FDA alerts both health professionals and the general 

public to potential product problems, often despite uncertainties about what 

the data mean and what recommendations would best help stakeholders 

address the problem’s implications for them. 

Internal communications expertise. FDA has long had extensive internal 

expertise in the sciences needed to review and approve regulated products 

and to ensure their identity, strength, quality, and purity (e.g., chemistry, 

toxicology, pharmacology, physiology, engineering, statistics, nutrition, 

medicine, pharmacy). FDA has less of the internal expertise needed to 

communicate with the public about the results of its review and enforcement 

activities (e.g., social, decision, behavioral, and communication sciences). 

However, FDA has been increasing its internal capacity and using the additional 

capacity offered by external experts on the Risk Communication Advisory 

Committee FDA established in 2007. 

Range of covered products and regulatory authorities. As mentioned 

previously, FDA enforces laws covering multiple product types under different 

legal authorities and scopes. Even within the drug-focused program areas, 

new staffers learn that actions possible for one regulated drug or class are not 

possible for another. More significant differences exist across product-focused 

organizations — especially between those with and without premarketing 

approval authority. For example, although prescription drugs require prior 

approval to be marketed, foods (except for food additives) do not need 

prior approval; instead, FDA must first prove they are dangerous to be able 

to demand they be removed from marketing. Unfortunately, it is likely that 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 221
	

FDA’s public audience sees “FDA” as the source of messages, rather than the 

source being an FDA Center with authority for a particular regulated product. 

Thus, although these legal distinctions are important to FDA and its regulated 

industries, they may not be meaningful and may, in fact, be confusing to the 

public. 

Other regulatory constraints also significantly affect FDA’s ability to 

communicate. For example, laws protecting sponsor’s intellectual property 

rights constrain FDA’s disclosure of trade secret and confidential information. 

As a result, FDA often cannot communicate about a certain product without the 

sponsor’s prior approval. As mentioned before, in the face of uncertain data 

about the existence of a product safety issue, FDA and product sponsors may 

legitimately disagree about the public health risk involved. That risk judgment 

often needs to be resolved before FDA can secure a sponsor’s agreement to 

discuss the data in a public forum. 

Conclusion

Many factors, including some common to federal agencies in general, 

affect FDA’s ability to develop, disseminate, and oversee effective product 

communications in an evidence-based manner. The nature of the evidence 

that FDA uses for its decision making creates significant uncertainties 

about conclusions and consequent challenges to effective communication. 

Nonetheless, FDA’s commitment to greater transparency, its championing of an 

Advisory Committee of external risk communication experts, and its issuance 

and implementation of a Strategic Plan for Risk Communication clearly continue 

to support an evidence-based approach to communications. 

Additional resources

1. FDA Basics on the Food and Drug Administration’s Internet site provides useful information 

about FDA’s organization, staff, and transparency efforts and gives answers to commonly asked 

questions about what FDA does. (http://www.fda.gov/AboutFDA/Transparency/Basics/default.htm). 

2. FDA’s Strategic Plan for Risk Communication. (2009). outlines its plan for improving FDA risk 

communication through strengthening science, expanding capacity, and optimizing policies, with 

the underlying principles that risk communication is science-based, provides sufficient context, 

is adapted to audience needs, and is results-oriented. Retrieved from http://www.fda.gov/ 

downloads/AboutFDA/ReportsManualsForms/Reports/UCM183683.pdf. 

3. Internet site members of the public can search (under Department of Health and Human 

Services) for the information collection requests submitted under requirements of the 

Paperwork Reduction Act that are currently under review at the Office of Management and 

Budget (http://www.reginfo.gov/public/do/PRAMain). 
222 | Chapter 21: An Agency Perspective
	

Endnotes

1 Hamburg, M.A., & Sharfstein, J.M. (2009). The FDA as a public health agency. New England Journal 

of Medicine, 360, 2493-2495. doi: 10.1056/NEJMp0903764. 

2 National Research Council. (1989). Improving Risk Communication. Washington, D.C.: National 

Academy Press. 

3 Food and Drug Administration. (2009). FDA’s Strategic Plan for Risk Communication. Retrieved 

from http://www.fda.gov/downloads/AboutFDA/ReportsManualsForms/Reports/UCM183683.pdf. 

4 Office of Management and Budget. (2010). Memorandum for the Heads of Executive 

Departments and Agencies, and Independent Regulatory Agencies: Paperwork Reduction Act 

– Generic Clearances. Retrieved from http://www.whitehouse.gov/sites/default/files/omb/
	

memoranda/2011/m11-07.pdf.
	

5 For example, the Federal Trade Commission oversees the advertising of foods and all medical 

products, except human and prescription drugs and biologics and a limited category of medical 

devices. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 223
	

Chapter 22: Strategic Planning 

Baruch Fischhoff, Noel Brewer, and Julie Downs (Editors) 

With this guide, we have sought to strengthen the scientific foundations of 

risk (and benefit) communications. The guide offers lots of specific advice. 

However, not all of it has to be mastered for it to help an organization improve 

its communications. Just sampling here and there will show incremental, 

affordable steps, putting better risk (and benefit) communication within 

everyone’s reach. 

The guide offers authoritative summaries of essential research, written 

as accessibly as possible, while preserving the detail needed to represent 

the science faithfully and avoid oversimplification. That research is then 

translated into concrete recommendations for designing communications 

and coupled with the testing procedures needed to make communications 

as good as possible. The guide emphasizes practicality, hoping to improve 

communications, even when time and resources are limited. The guide intends 

to make the science of communication as sound as the science that is being 

communicated. 

Each chapter offers a concise introduction to its domain. For example, 

Chapter 16 shows how a product’s design can suggest its risks and benefits, 

then suggests ways to create designs that create more realistic expectations. 

Chapter 10 summarizes what is known about how emotions affect risk 

judgments, how to anticipate those emotions, and how to evaluate attempts 

to address them. Chapter 14 identifies the barriers to reaching low-literacy 

audiences, strategies for overcoming them, and ways to evaluate their success. 

Each chapter should help practitioners not only perform that aspect of 

their own work, but also work more effectively with the relevant experts. For 

example, knowing something about the science of product design can show 

when help is needed, how to find it, and how to speak the language of design. 

Knowing something about emotion research can sensitize communicators to 

those concerns and encourage them to work with specialists in addressing 

them. Knowing something about health literacy research can highlight the 

risks of needlessly confusing one’s audience and create an appreciation of 

the professionals who are trained to simplify a message’s language while 

preserving its content. In each case, knowing some of the science can protect 

practitioners from placing undue faith in simplistic solutions. 
FDA RISK COMMUNICATION STRATEGIC PLAN AT A GLANCE

4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

224 | Chapter 22: Strategic Planning
	

Communication as a strategic responsibility

Knowing the science should help practitioners work better with whatever 

resources they have. It might also help them gain more resources, by showing 

the stakes riding on effective communication and the challenges to delivering 

it. Table 1 shows the strategic vision of the U.S. Food and Drug Administration 

(FDA)1,2 for creating the communications needed to serve its many audiences. 

Although the details reflect FDA’s particular circumstances, all organizations 

face the same basic tasks: Strengthen the science needed to support effective 

communication, expand the capacity to deliver those communications, and 

create policies compatible with them. 

Table 1. US FDA communication principles and strategies

Strengthen the science that supports effective risk communication 

Science Strategy 1: Identify gaps in key areas of risk communication knowledge 

and implementation and work toward filling those gaps 

Science Strategy 2: Evaluate the effectiveness of FDA’s risk communication and 

related activities and monitor those of other stakeholders 

Science Strategy 3: Translate and integrate knowledge gained through -

research/evaluation into practice -

Expand FDA capacity to generate, disseminate, and oversee effective 

risk communication 

Capacity Strategy 1: Streamline and more effectively coordinate the development 

of communication messages and activities 

Capacity Strategy 2: Plan for crisis communications 

Capacity Strategy 3: Streamline processes for conducting communication research 

and testing, including evaluation 

Capacity Strategy 4: Clarify roles and responsibilities of staff involved in drafting, 

reviewing, testing, and clearing messages 

Capacity Strategy 5: Increase staff with decision and behavioral science expertise 

and involve them in communication design and message development 

Capacity Strategy 6: Improve the effectiveness of FDA’s Web site and Web tools 

as primary mechanisms for communicating with different 

stakeholders 

Capacity Strategy 7: Improve two-way communication and dissemination through 

enhanced partnering with government and nongovernment 

organizations 

Optimize FDA policies on communicating risks and benefits 

Policy Strategy 1: Develop principles to guide consistent and easily understood 

FDA communications 

Policy Strategy 2: Identify consistent criteria for when and how to communicate 

emerging risk information 

Policy Strategy 3: Re-evaluate and optimize policies for engaging with partners to 

facilitate effective communication about regulated products 

Policy Strategy 4: Assess and improve FDA communication policies in areas of 

high public health impact 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 225
	

Elsewhere in its Strategic Plan for Risk Communication, FDA identifies three 

underlying principles that could apply to any organization. Expressed in general 

terms, they are: 

1. Communication should be based on science. Without supporting 

evidence, even widely accepted best practices can be terrible. As a result, 

organizations need an evidence-based strategy if they are to survive and 

advance. That means reviewing their current practices in terms of their 

consistency with the science (i.e., Is the organization doing things known 

not to work? Is it ignoring known problems?). It also means evaluating the 

effectiveness of all communications, recognizing that even the best science 

cannot guarantee results — only provide better best guesses at how to 

communicate about specific issues with specific audiences. 

2. Communication should inform choices. Unless people know the risks 

and benefits of possible actions, they cannot evaluate the choices facing 

them. As a result, communications must focus on conveying the risks 

and benefits of those choices. That is true whether the organization 

hopes people will make a particular choice (e.g., get vaccinated) or is 

indifferent (e.g., use a drug that has been approved for sale). Informed 

choices often require knowing something about the organization behind 

the communication. For example, people may want to know why FDA has 

recommended a vaccine; why FDA has approved, but not recommended, 

a drug; why FDA has added a warning, rather than pulling a product from 

the market. 

3. Communication should be results oriented. Effective communications 

enable people to live better lives thus, placing a deservedly higher value 

on organizations that provide such help. As a result, communication must 

involve more than just pro forma fulfillment of an obligation to consult or 

inform. To have something meaningful to say, organizations must produce 

information that matters, rather than force communicators to take 

whatever they can get. 

Implementing these principles can be disruptive at first for organizations 

that have not treated communication as a strategic function. However, it need 

not be costly. Knowing the research enables organizations to use resources 

more efficiently. For example, following good communication principles 

might focus communications on the benefits of choices when the risks are 

already understood; or direct research to resolving critical uncertainties (e.g., 

evaluating the quality of postmarket monitoring). Shifting resources within an 

organization requires leadership. Clearly defining communication priorities can 

show where that leadership is needed. 
226 | Chapter 22: Strategic Planning
	

Implementing these principles can help organizations in other ways as well. 

It can reduce internal friction by providing a disciplined way to decide what to 

say and how to say it (rather than letting staff argue among themselves). It can 

make better use of external vendors of communication services by avoiding 

those who cannot demonstrate mastery of the science and a commitment 

to evaluation. It can ensure that communications get needed resources by 

demonstrating their scientific foundations. 

Organizing for evidence-based communication

The top half of Table 2 summarizes the steps in evidence-based 

communication. Accomplishing them requires the skills in the bottom half of 

the table. Although each skill is particularly important at one step, each also 

is needed throughout the process. For example, although risk and decision 

analysis are central to identifying the information most relevant to audience 

needs, identifying those needs requires behavioral science research (to know 

what matters to the audience), subject matter expertise (to know what is at 

stake), and communication work (to create trusted channels for hearing and 

addressing that audience). Leadership is needed to recruit the right people 

and then coordinate their work. Without that coordination, communicators 

may distort facts as they try to simplify them, and subject matter experts 

may provide long lectures to audiences that want just a few critical details. 

In healthy group processes, all opinions are welcome and heard, but experts 

should have the final say in their domains. 

Table 2. Organizing for evidence-based risk and benefit communications

Steps

Analysis. Identify the information most relevant to helping audience members make 

decisions that achieve their goals. 

Design. Draft communications that provide needed information in concise, 

comprehensible, usable form. 

Evaluation. Subject drafts to empirical evaluation, assessing whether people can 

extract enough information to make sound choices, then follow them through. 

Iteration. Repeat as needed, looking for weakness is the analysis, design, or 

evaluation. 

Skills

Subject matter expertise, to ensure fidelity to the best available technical knowledge. 

Risk and decision analysis, to identify facts most relevant decisions that audience 

members face.
	

Behavioral science, to design outstanding communications and evaluate them.
	

Communication, to create and sustain respectful two-way communication channels.
	

Leadership, to recruit the needed staff and coordinate their activities, consistent with 

the overall communication strategy.
	
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 227
	

Figure 1 shows a process for managing risks that enables such coordination. 

Issued by the quasi-governmental Canadian Standards Association3

, the figure 

echoes proposals from many similar bodies. In the middle are the normal steps 

in managing any risk.4 The process begins with defining the decision problem, 

then proceeds to estimating the size of the risks, evaluating their relative 

importance, devising ways to control them, taking action, and monitoring 

progress. Between each two steps is a reality check, asking whether the 

work has been done well enough to proceed (next step), whether it needs to 

be improved (go back), or whether it should be abandoned as irredeemably 

inadequate (end). 

Notably, each stage requires two-way communication between those 

responsible for managing the risk and those affected by it. Thus, members of 

the relevant audiences must be consulted when the process begins, so that 

risk management focuses on their concerns and they are not blindsided by 

its conclusions. Even after a decision has been made (at the bottom), those 

audiences must continue to be part of the process, helping to monitor what 

has been learned and reporting their own experiences. Skipping the reality 

check at any step risks leaving the audience or the organization in the dark, 

unless they know what is happening without being told. As the chapters in this 

volume show, it is unrealistic to expect people to read each others’ minds. 

Figure 1. A process for integrating communication and analysis
 

 

 

 

228 | Chapter 22: Strategic Planning
	

In executing a communication program, any scientific knowledge is better 

than relying on pure intuition. Any evaluation is better than assuming that a 

communication that looks okay is okay. However, strategic communication 

requires deeper organizational commitment, ensuring that communication 

issues become integrated with the entire risk management process (Figure 

1). Lest this seem too daunting, most organizations of any size already have 

many of the needed skills (Table 2). They could not function, if they did not 

have people who know about the risks they manage, people who handle 

press releases, people who do test marketing, and so on. The challenge is 

to complete the roster of skilled experts and get them working together. An 

organization could do that alone or pool its resources with related ones (e.g., 

industry associations, interagency research groups).5 A structure that can 

balance the routine and fluctuating needs of risk communication has: 

• An intramural core with decision analysts, behavioral scientists, and 

communication specialists dedicated to designing, evaluating, and 

disseminating communications
	

• An extramural program with opportunities for collaboration with scientists 

elsewhere, drawing them into studying communications and keeping core 

staff connected with the research world 

• Contracted services that respond to the demand for delivering specific 

communications, under the core staff’s guidance 

Assembling a strategic communication program may require additional 

resources. However, it may also mean just using current resources more 

effectively. It might even save resources by reducing activities that were never 

effective. However, even if greater resources are needed, given the stakes 

riding on sound communication, it would be a false economy not to invest 

them. Given the science available to guide that communication, it would be a 

shame to use anything less. This guide provides access to that science as well 

as instructions on how to use it. 

Endnotes

1 US Food and Drug Administration. (2009). Strategic Plan for Risk Communication. Washington, DC. 

2 Hamburg, M.A., and Sharfstein, J.M. (2009). The FDA as a public health agency. New England 

Journal of Medicine, 360, 2493-2495. 

3 Canadian Standards Association. 1997. Risk management: Guideline for decision makers 

(reaffirmed 2002). Etobicoke. 

4 HM Treasury. (2005). Managing Risks to the Public. London: National Research Council (1996).

Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: National

Academy Press; Environmental Protection Agency (1993). A Guidebook to Comparing Risks and 

Setting Environmental Priorities. Washington, DC. 

5 Pidgeon, N., and Fischhoff, B. (2011). The role of social and decision sciences in communicating 

uncertain climate risks. Nature Climate Change, 1(1), 35-41. 
 

Communicating Risks and Benefits: An Evidence-Based User’s Guide | 229
	

Biographical Sketches

J. Craig Andrews, PhD is Professor and Charles H. Kellstadt Chair in 

Marketing, Marquette University. His research focuses on advertising and 

public health issues. Andrews currently serves on FDA’s Risk Communication 

Advisory Committee, has served on the Behavior Change Expert Panel for the 

National Youth Anti-Drug Media Campaign, was Editor of the Journal of Public 

Policy & Marketing, and Consumer Research Specialist in the FTC’s Division of 

Advertising Practices in Washington, DC. Andrews’ work has appeared in the 

Journal of Marketing, Journal of Public Policy & Marketing, Journal of Consumer 

Research, Journal of Advertising, Journal of International Business Studies, 

Journal of Retailing, and the American Journal of Public Health, among others. 

Noel T. Brewer, PhD is an expert in medical decision making with an 

emphasis on risk communication about vaccination as well as the psychological 

impact of medical tests. He is Associate Professor of Health Behavior and 

Health Education in the Department of Health Behavior and Health Education 

at the University of North Carolina Gillings School of Global Public Health. His 

research projects are described at http://www.unc.edu/~ntbrewer. Dr. Brewer 

is associate editor of Health Psychology Review and on the editorial boards of 

Journal of Behavioral Medicine and Medical Decision Making. 

Mary Brown, PhD is a research associate at the University of Arizona 

College of Pharmacy and a consulting partner with Dues, Brown & Associates. 

With expertise in communication and public health, she has lectured in 

communication for more than 15 years and served for seven years as 

Education Core Director for the Arizona Center for Education and Research 

on Therapeutics. She has extensive experience designing, implementing 

and evaluating printed and web-based educational materials for health care 

providers and patients. She has co-authored two college texts and published 

observational and qualitative research on the use of medications and adverse 

drug events. 
230 | Biographical Sketches
	

Christine Bruhn, PhD is a Cooperative Extension Specialist in the Department 

of Food Science and Technology at the University of California, Davis. As 

Director of the Center for Consumer Research, she studies consumer attitudes 

and behavior and guides educational programs that inform consumers about 

food products and technologies. She has authored more than 140 professional 

papers on consumer attitudes. Dr. Bruhn is a Fellow at the Institute of Food 

Technologists (United States) and the Institute of Food Science and Technology 

(United Kingdom). She has served as an expert advisor to the Food and 

Agriculture Organization, Pan American Health Organization, and World Health 

Organization. 

Caron Chess, PhD is Professor and Director, Undergraduate Programs, for 

Rutgers University’s Department of Human Ecology, where she conducts 

research on the evaluation of public participation and the impact of 

organizational factors on public participation and risk communication. She 

was a member of two NAS committees responsible for seminal reports on 

public participation. In addition, she served as president of the Society of 

Risk Analysis. Prior to coming to academia, she coordinated environmental 

programs for state government and environmental organizations, including 

playing a central role in the campaign for the country’s first public access rightto-know law. 

Nananda Col, MD, MPP, MPH, FACP is an internist whose primary interest is 

advancing the field of shared decision making to help patients make decisions 

that reflect their personal circumstances, risks, preferences, and values. 

Trained in internal medicine, preventive medicine, public health, and clinical 

decision-making, she has served on the faculty at Tufts, Brown, Harvard, and 

Dartmouth Medical School. She is active in the International Patient Decision 

Aid Standards collaboration, which develops standards for decision aids, and 

the Cochrane Collaboration’s Review of Patient Decision Aids, which reviews 

and updates the scientific evidence. 

Julie S. Downs, PhD specializes in translational research creating 

interventions aimed at risky decision making. Her interventions have resulted 

in documented changes in behaviors and health outcomes, and have won 

numerous awards. Dr. Downs received her Ph.D. in social psychology from 

Princeton University, and her B.A. in psychology from University of California, 

Berkeley. She is Director of the Center for Risk Perception and Communication 

in the department of Social and Decision Sciences at Carnegie Mellon 

University. Her research has been published in psychological, public policy, 

economics, computer science and medical journals. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 231
	

Angela Fagerlin, PhD is a Research Scientist at the Ann Arbor VA HSR&D 

(Health Services Research and Development) Center for Clinical Management 

Research, an Associate Professor of Medicine at the University of Michigan, and 

the Co-Director of the Center for Bioethics and Social Sciences in Medicine. Her 

research has focused on the development of a measure of numeracy, testing 

risk communication methods, and the development and testing of patient 

decision aids. 

Baruch Fischhoff, PhD is Howard Heinz University Professor, in the 

Departments of Social and Decision Sciences and of Engineering and Public 

Policy at Carnegie Mellon University. A graduate of the Detroit Public Schools, 

he holds a BS in mathematics and psychology from Wayne State University 

and an MA and PhD in psychology from the Hebrew University of Jerusalem. 

He is a member of the Institute of Medicine and chairs the Food and Drug 

Administration Risk Communication Advisory Committee. He is past President 

of the Society for Judgment and Decision Making and of the Society for Risk 

Analysis. He is co-author of Acceptable Risk (Cambridge University Press, 1981) 

and Risk: A Very Short Introduction (Oxford University Press, 2011). 

Michael Goldstein, MD is Associate Chief Consultant for Preventive 

Medicine at the Veterans Health Administration’s National Center for Health 

Promotion and Disease Prevention and an adjunct professor of psychiatry 

and human behavior at Alpert Medical School, Brown University. An internist 

and psychiatrist, Dr. Goldstein is a clinician, researcher, and educator in 

the field behavioral medicine. He has conducted research to develop and 

test interventions to enhance clinician delivery of preventive counseling 

interventions, led educational programs in clinician-patient communication, 

and served as a faculty member for several regional, national and international 

quality improvement projects that have focused on activating and engaging 

patients in self-care. 

Gavin Huntley-Fenner, PhD is a human factors consultant whose firm, 

Huntley-Fenner Advisors, Inc., specializes in applied cognitive sciences, risk 

perception, and risk communication. He has developed an approach to 

consumer products hazard analysis that brings together cross-disciplinary 

teams to identify and mitigate potential hazards in the early phases of the 

product development cycle. Dr. Huntley-Fenner has served as a member of 

the Irvine Unified School Board and as an advisor to the State of California on 

autism education. He received his PhD in Brain and Cognitive Sciences from the 

Massachusetts Institute of Technology. 
 

232 | Biographical Sketches
	

Musa Mayer is a 22-year breast cancer survivor, advocate, and author of 

four books. Her articles on breast cancer and advocacy frequently appear 

in magazines and scientific journals. She is involved with clinical and basic 

research on issues pertaining to metastatic breast cancer, authors two 

web sites, and interacts daily with patient communities. She co-authored 

“Understanding Evidence-Based Healthcare: A Foundation for Action,” a free 

web course, for the U.S. Cochrane Center at Johns Hopkins. Since 2001, she has 

worked with FDA as a Patient Representative and Consultant and as a member 

of the Risk Communication Advisory Committee. Her web site is AdvancedBC.org. 

Linda Neuhauser, DrPH is Clinical Professor of Community Health and Human 

Development at the University of California, Berkeley School of Public Health. 

She focuses on using participatory approaches to translate research findings 

into health interventions that are relevant to people’s literacy levels, languages, 

cultures and disabilities. She is principal investigator of the UC Berkeley Health 

Research for Action center that works with diverse audiences to co-create 

and research communication resources that have reached over 30 million 

households in the United States and overseas. She is an advisor to FDA, other 

government agencies, and private industry about research translation and 

communication. 

Nancy M. Ostrove, PhD is a social psychologist with expertise in risk 

communication, with an emphasis on FDA-regulated products. She recently 

completed a distinguished career at FDA, where her leadership built social 

science principles and strategic thinking on communicating about regulated 

products into major FDA initiatives, including improving prescription drug 

labeling, taking a reasoned approach to regulating consumer-directed 

prescription drug promotion, developing Medication Guides to inform patients 

about especially risky prescription drugs, and establishing an external advisory 

committee to advise FDA on evidence-based communication about product 

risks and benefits. 

Kala Paul, MD is a board certified neurologist with broad experience 

in ethical pharmaceutical and nonprescription product development and 

pharmacovigilance. She currently consults in risk communication and health 

literacy and safety surveillance in the pharmaceutical industry. While she 

creates both patient and health care professional risk management documents, 

her major emphasis is medical product and device information for low literacy 

patients. Dr. Paul was a faculty member for 10 years for the DIA training 

course on product safety surveillance and currently serves on FDA’s Risk 

Communication Advisory Committee. She received her medical degree Magna 

Cum Laude from the University of Texas Medical Branch, Galveston. 
Communicating Risks and Benefits: An Evidence-Based User’s Guide | 233
	

Ellen Peters, PhD is an associate professor of psychology at Ohio State 

University. She conducts basic and applied research in judgment and decision 

making, focusing on how affective, intuitive, and deliberative processes 

help people to make decisions in an increasingly complex world. She studies 

decision making as an interaction of characteristics of the decision situation 

and characteristics of the individual. Recent areas of study include: numeracy, 

number processing, affect/emotion, and aging. In the policy area, she has 

worked extensively with federal agencies to advance the science of decision 

making as it applies to health and health policy. 

Valerie Reyna, PhD is Professor and Co-Director of the Center for Behavioral 

Economics and Decision Research at Cornell University. She is a developer of 

fuzzy-trace theory, a model of memory and decision making, widely applied in 

law, medicine, and public health. Her recent work has focused on numeracy, 

medical decision making, risk perception and risk-taking, neurobiological 

models of development, and neurocognitive impairment and genetics. Past 

President of the Society for Judgment and Decision Making, she is a fellow of 

numerous scientific societies and has served on scientific panels of the National 

Science Foundation, National Institutes of Health, and National Academy of 

Sciences. 

Gary Schwitzer has specialized in health care journalism for 37 years. He is 

Publisher of HealthNewsReview.org – an award-winning site that grades health 

news. He has taught health journalism and media ethics at the University 

of Minnesota. Gary worked in television news for 15 years – in Milwaukee, 

Dallas, and with CNN. He was founding editor-in-chief of MayoClinic.com. The 

Kaiser Family Foundation published his 2009 report, “The State of U.S. Health 

Journalism.” For members of the Association of Health Care Journalists, he 

wrote a guide on how to report on studies. One online competition named his 

blog the best medical blog of 2009. 

Betsy Sleath, PhD, RPh is George H Cocolas Distinguished Professor and 

Chair of the Division of Pharmaceutical Policy and Outcomes at the University 

of North Carolina School of Pharmacy. She is also a senior research fellow at 

the Cecil G Sheps Center for Health Services Research and co-director of the 

community engagement core of the North Carolina Translational and Clinical 

Science Institute. Her research and teaching focuses on the relationship 

between health care provider-patient communication about medications and 

patient outcomes. Her recent work focuses on glaucoma and pediatric asthma. 
 

 

234 | Biographical Sketches
	

Michael Wolf, PhD is Associate Professor of Medicine and Learning Sciences, 

and Associate Division Chief for General Internal Medicine at Northwestern 

University’s Feinberg School of Medicine. His research in health services and 

cognitive/behavioral science focuses on adult learning and cognition, specific 

to health literacy. He has received numerous awards for his work in this area, 

including a J. William Fulbright Distinguished Faculty Scholar award in the 

United Kingdom. He is the Founder and Co-Director of the Health Literacy and 

Learning Program (HeLP), a collaboration between Northwestern’s Schools of 

Medicine and Education and Social Policy. 

Lee Zwanziger, PhD is the designated federal officer for FDA’s Risk 

Communication Advisory Committee. Previous employment included FDA 

positions on communication and science advising, the President’s Council of 

Bioethics staff, and the National Academies’ Institute of Medicine. She has 

taught science and technology studies (Virginia Tech University) and basic 

sciences to student health care practitioners (Peace Corps volunteer). Her 

interest is making science available to the public and to the government. She 

holds degrees in history and philosophy of science and biological sciences. 

Practioners Perspectives Contributors:

Jacob DeLaRosa, MD, Idaho State University, Portneuf Medical Center, 

Pocatello, ID
	

AnnaMaria DeSalva, Pfizer, New York, NY 

Sokoya Finch, MA, Florida Family Network, Tallahassee, FL 

Sally Greenberg, JD, National Consumers League, Washington, DC 

Prerna Mona Khanna, MD, MPH, FACP, Fox Chicago News, Chicago, IL 

Madeline Y. Lawson, MS, Institute for the Advancement of Multicultural and 

Minority Medicine, Washington, D.C. 

Kala Paul, MD, The Corvallis Group, LLC, Summit, New Jersey 

Marielos L. Vega, BSN, RN, New Jersey Medical School 

FOOD AND DRUG 

ADMINISTRATION