Evidence Report/Technology Assessment

Number 221

Behavioral 

Programs for

Diabetes Mellitus

Evidence-Based

Practice
Evidence Report/Technology Assessment

Number 221

Behavioral Programs for Diabetes Mellitus

Prepared for:

Agency for Healthcare Research and Quality

U.S. Department of Health and Human Services 

540 Gaither Road 

Rockville, MD 20850

www.ahrq.gov

Contract No. 290-2012-00013-I

Prepared by:

University of Alberta Evidence-based Practice Center

Edmonton, AB, Canada

Investigators:

Jennifer Pillay, B.Sc.

Pritam Chordiya, B.D.S., M.Sc.

Sanjaya Dhakal, M.B.B.S., M.P.H.

Ben Vandermeer, M.Sc.

Lisa Hartling, Ph.D.

Marni J. Armstrong, Ph.D., R.C.E.P.

Sonia Butalia, M.D., M.Sc.

Lois E. Donovan, M.D.

Ronald J. Sigal, M.D., M.P.H.

Robin Featherstone, M.L.I.S.

Megan Nuspl, B.Sc.

Donna M. Dryden, Ph.D.

AHRQ Publication No. 15-E003-EF

September 2015
ii

This report is based on research conducted by the University of Alberta Evidence-based Practice 

Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), 

Rockville, MD (Contract No. 290-2012-00013-I). The findings and conclusions in this document 

are those of the authors, who are responsible for its contents; the findings and conclusions do not 

necessarily represent the views of AHRQ. Therefore, no statement in this report should be 

construed as an official position of AHRQ or of the U.S. Department of Health and Human 

Services.

The information in this report is intended to help health care decisionmakers—patients and 

clinicians, health system leaders, and policymakers, among others—make well informed 

decisions and thereby improve the quality of health care services. This report is not intended to 

be a substitute for the application of clinical judgment. Anyone who makes decisions concerning 

the provision of clinical care should consider this report in the same way as any medical 

reference and in conjunction with all other pertinent information, i.e., in the context of available 

resources and circumstances presented by individual patients. 

AHRQ or U.S. Department of Health and Human Services endorsement of any derivative 

products that may be developed from this report, such as clinical practice guidelines, other 

quality enhancement tools, or reimbursement or coverage policies, may not be stated or implied. 

This report may periodically be assessed for the currency of conclusions. If an assessment is 

done, the resulting surveillance report describing the methodology and findings will be found on 

the Effective Health Care Program Web site at www.effectivehealthcare.ahrq.gov. Search on the 

title of the report. 

This document is in the public domain and may be used and reprinted without special 

permission. Citation of the source is appreciated. 

Persons using assistive technology may not be able to fully access information in this report. For 

assistance contact EffectiveHealthCare@ahrq.hhs.gov. 

None of the investigators have any affiliations or financial involvement that conflicts with the 

material presented in this report. 

Suggested citation: Pillay J, Chordiya P, Dhakal S, Vandermeer B, Hartling L, Armstrong MJ, 

Butalia S, Donovan LE, Sigal RJ, Featherstone R, Nuspl M, Dryden DM. Behavioral Programs

for Diabetes Mellitus. Evidence Report/Technology Assessment No. 221. (Prepared by the 

University of Alberta Evidence-based Practice Center under Contract No. 290-2012-00013-I.) 

AHRQ Publication No. 15-E003-EF. Rockville, MD: Agency for Healthcare Research and 

Quality; September 2015. www.effectivehealthcare.ahrq.gov/reports/final/cfm. DOI: https://

doi.org/10.23970/AHRQEPCERTA221.
iii

Preface

The Agency for Healthcare Research and Quality (AHRQ), through its Evidence-based 

Practice Centers (EPCs), sponsors the development of systematic reviews to assist public- and 

private-sector organizations in their efforts to improve the quality of health care in the United 

States. These reviews provide comprehensive, science-based information on common, costly 

medical conditions, and new health care technologies and strategies. 

Systematic reviews are the building blocks underlying evidence-based practice; they focus 

attention on the strength and limits of evidence from research studies about the effectiveness and 

safety of a clinical intervention. In the context of developing recommendations for practice, 

systematic reviews can help clarify whether assertions about the value of the intervention are 

based on strong evidence from clinical studies. For more information about AHRQ EPC 

systematic reviews, see www.effectivehealthcare.ahrq.gov/reference/purpose.cfm.

AHRQ expects that these systematic reviews will be helpful to health plans, providers, 

purchasers, government programs, and the health care system as a whole. Transparency and 

stakeholder input are essential to the Effective Health Care Program. Please visit the Web site 

(www.effectivehealthcare.ahrq.gov) to see draft research questions and reports or to join an 

email list to learn about new program products and opportunities for input. 

We welcome comments on this systematic review. They may be sent by mail to the Task 

Order Officer named below at: Agency for Healthcare Research and Quality, 540 Gaither Road, 

Rockville, MD 20850, or by email to epc@ahrq.hhs.gov.

Richard G. Kronick, Ph.D.

Director

Agency for Healthcare Research and Quality

Stephanie Chang, M.D., M.P.H. 

Director EPC Program

Center for Evidence and Practice Improvement

Agency for Healthcare Research and Quality

Arlene S. Bierman, M.D., M.S.

Director

Center for Evidence and Practice Improvement

Agency for Healthcare Research and Quality

Aysegul Gozu, M.D., M.P.H.

Task Order Officer

Center for Evidence and Practice Improvement

Agency for Healthcare Research and Quality
iv

Key Informants

In designing the study questions, the EPC consulted several Key Informants who represent 

the end-users of research. The EPC sought the Key Informant input on the priority areas for 

research and synthesis. Key Informants are not involved in the analysis of the evidence or the 

writing of the report. Therefore, in the end, study questions, design, methodological approaches, 

and/or conclusions do not necessarily represent the views of individual Key Informants. 

Key Informants must disclose any financial conflicts of interest greater than $10,000 and any 

other relevant business or professional conflicts of interest. Because of their role as end-users, 

individuals with potential conflicts may be retained. The TOO and the EPC work to balance, 

manage, or mitigate any conflicts of interest.

The list of Key Informants who participated in developing this report follows:

Christy Alberts

Patient Representative

Children’s Diabetes Foundation

Denver, CO

Ann Albright, Ph.D., R.D.

Director, Division of Diabetes Translation

National Center for Chronic Disease 

Prevention and Health Promotion

Centers for Disease Control and Prevention

Atlanta, GA

Jean Baltz, C.D.E., R.D., M.M.Sc., M.S.W.

Diabetes Strategic Consultant

Humana Inc.

Louisville, KY

Victoria DeFiglio, R.N.

Associate Clinical Director

Camden Coalition of Healthcare Providers

Camden, NJ

Philip Eager, M.Ed., N.C.C.

Patient Representative

Spokane, WA

Korey Hood, Ph.D.

Clinical Professor, Pediatrics 

(Endocrinology and Diabetes), and 

Psychiatry and Behavioral Sciences

Stanford University School of Medicine

Stanford, CA

Christine Hunter, Ph.D., A.B.B.P.

Director, Behavior Research

National Institute of Diabetes and Digestive 

and Kidney Diseases

Bethesda, MD

Jeff Johnson, B.S.P., Ph.D.

Professor

School of Public Health

University of Alberta

Edmonton, AB, Canada

Ann Lewis

Chief Executive Officer

CareSouth Carolina

Hartsville, SC

Molly McElwee, R.N., C.D.E., C.R.C. 

Clinical Research Coordinator

Center for Diabetes Technology

School of Medicine, University of Virginia

Charlottesville, VA
v

Technical Expert Panel

In designing the study questions and methodology at the outset of this report, the EPC 

consulted several technical and content experts. Broad expertise and perspectives were sought.

Divergent and conflicting opinions are common and perceived as healthy scientific discourse that 

results in a thoughtful, relevant systematic review. Therefore, in the end, study questions, design,

methodologic approaches, and/or conclusions do not necessarily represent the views of 

individual technical and content experts.

Technical Experts must disclose any financial conflicts of interest greater than $10,000 and 

any other relevant business or professional conflicts of interest. Because of their unique clinical 

or content expertise, individuals with potential conflicts may be retained. The TOO and the EPC 

work to balance, manage, or mitigate any potential conflicts of interest identified.

The list of Technical Experts who participated in developing this report follows:

Ann Albright, Ph.D., R.D.

Director, Division of Diabetes Translation

National Center for Chronic Disease 

Prevention and Health Promotion

Centers for Disease Control and Prevention

Atlanta, GA

Martha Funnell, M.S., R.N., C.D.E.*

Associate Research Scientist

Department of Learning Health Sciences

University of Michigan Medical School

Ann Arbor, MI

Korey Hood, Ph.D.

Clinical Professor, Pediatrics 

(Endocrinology and Diabetes), and 

Psychiatry and Behavioral Sciences

Stanford University School of Medicine

Stanford, CA

Christine Hunter, Ph.D., A.B.B.P.*

Director, Behavior Research

National Institute of Diabetes and Digestive 

and Kidney Diseases

Bethesda, MD

Andrea Kriska, Ph.D.*

Professor, Epidemiology

Graduate School of Public Health

University of Pittsburgh

Pittsburgh, PA

Carla Miller, Ph.D., R.D.*

Professor, Human Nutrition

Department of Human Sciences

The Ohio State University

Columbus, OH

Shelagh Mulvaney, Ph.D.

Assistant Professor, School of Nursing

Assistant Director, Effective Health 

Communication Core

Vanderbilt Institute for Clinical and

Translational Research

Vanderbilt University Medical Center

Nashville, TN

Gretchen Piatt, M.P.H., Ph.D.*

Assistant Professor

Department of Learning Health Sciences, 

School of Medicine

Department of Health Behavior and Health 

Education, School of Public Health

University of Michigan

Ann Arbor, MI

*TEP members who provided comments on 

the draft report.
vi

Peer Reviewers

Prior to publication of the final evidence report, EPCs sought input from independent Peer 

Reviewers without financial conflicts of interest. However, the conclusions and synthesis of the 

scientific literature presented in this report do not necessarily represent the views of individual 

reviewers.

Peer Reviewers must disclose any financial conflicts of interest greater than $10,000 and any 

other relevant business or professional conflicts of interest. Because of their unique clinical or 

content expertise, individuals with potential nonfinancial conflicts may be retained. The TOO 

and the EPC work to balance, manage, or mitigate any potential nonfinancial conflicts of interest 

identified.

The list of Peer Reviewers follows:

Sharon A. Brown, Ph.D., R.N., FAAN

Joseph H. Blades Centennial Memorial 

Professor in Nursing

The University of Texas at Austin

Austin, TX

Rongwei (Rochelle) Fu, Ph.D.

Associate Professor

Department of Public Health and 

Preventative Medicine

Oregon Health & Science University

Portland, OR 

Steven T. Johnson, Ph.D.

Assistant Professor

Athabasca University

Edmonton, AB, Canada

Maya O’Neil, Ph.D.

Assistant Professor of Psychology

Departments of Psychiatry and Medical 

Informatics & Clinical Epidemiology

Oregon Health & Science University

Portland, OR
vii

Behavioral Programs for Diabetes Mellitus

Structured Abstract

Objectives. To conduct a systematic review focusing on the effectiveness of behavioral 

programs for type 1 diabetes (T1DM) and identifying factors contributing to program 

effectiveness for type 2 diabetes (T2DM). 

Data sources. MEDLINE®, Cochrane Central Register of Controlled Trials, Embase®, CINAHL, 

PsycINFO® (January 1, 1993, to January 2015), and PubMed® (2015); ClinicalTrials.gov, World 

Health Organization International Clinical Trials Registry Platform, conference proceedings 

(2011–14); reference lists of relevant studies.

Methods. Two reviewers independently assessed studies for fit with predetermined selection 

criteria and assessed risk of bias. We included prospective controlled studies and randomized 

controlled trials (RCTs) for T1DM and RCTs for T2DM, evaluating behavioral programs 

compared with usual care, active controls (e.g., didactic education), or other behavioral 

programs. One reviewer extracted data, with verification by a second reviewer. For T1DM, we 

conducted pairwise meta-analysis to assess program effectiveness; subgroup analyses to examine 

patient variables (e.g., age, race/ethnicity, glycemic control); and metaregressions to assess 

potential moderators of effectiveness, such as program components (i.e., diabetes selfmanagement education [DSME], DSME plus support, lifestyle), intensity, delivery format, and 

personnel. For T2DM, we conducted network meta-analysis (incorporating direct and indirect 

comparisons) to assess potential moderation of program effectiveness, and subgroup analyses to 

assess the impact of patient variables. Strength of evidence (SOE) for key outcomes in T1DM 

was assessed to determine our confidence in the results.

Results. The searches identified 47,149 citations, of which we included 34 studies for T1DM 

and 132 RCTs for T2DM. All trials had a medium or high overall risk of bias. 

For T1DM, there was moderate SOE showing greater reductions in percent hemoglobin A1c

(HbA1c) levels at 6-month postintervention followup for individuals receiving a behavioral 

program compared with usual care (0.31) or an active control (0.44); both were statistically 

significant, and the latter was considered clinically important based on our prespecified threshold 

of ≥0.4 unit change in percent HbA1c. There was low SOE showing no difference in HbA1c at end 

of intervention and at 12-month or longer followup. Generic health-related quality of life was no 

different at end of intervention in comparisons with usual care (moderate SOE). There was either 

low SOE or insufficient SOE for all other outcomes, including self-management and lifestyle 

behaviors, body composition, diabetes-specific quality of life, diabetes distress, and 

complications. From the subgroup analysis for percent HbA1c by age in comparison with usual 

care, the effect for the adult subgroup appeared to be greater (0.28) than the effect for the youth 

subgroup (0.00) at end of intervention, although neither result reached statistical significance. In 

comparisons with active controls, the SOE of the findings for youths and adults was insufficient.

Program intensity (duration, contact hours, frequency of contacts) appeared not to influence 

program effectiveness for T1DM; individual delivery (vs. group) may be beneficial. 

For T2DM, relative to usual care, the effect sizes for all minimally intensive (≤10 contact hours) 

DSME programs were not considered clinically important based on our prespecified threshold of 

≥0.4 unit change in percent HbA1c for glycemic control. Programs having greater benefit for 
viii

HbA1c reduction were more often delivered in person. For body mass index, lifestyle programs 

(usually combining structured diet and exercise) provided the most benefit. In subgroup analyses, 

results for reduced HbA1c favored participants with suboptimal baseline glycemic control (≥7%

HbA1c), adults <65 years, and minority participants (sample ≥75% nonwhite and/or Hispanic); 

the findings by race/ethnicity were confounded by poorer baseline glycemic control among 

minorities.

Conclusion. Behavioral programs for T1DM offer some benefit for glycemic control when 

followup extends beyond end of intervention up to 6 months. There was no statistically 

significant difference at end of intervention or followup timepoints longer than 6 months, 

although our confidence in these findings is low and benefit cannot be ruled out. More evidence 

is required to determine the effects of behavioral programs for other outcomes, including 

lifestyle behaviors, body composition, diabetes-specific quality of life, diabetes distress, and 

complications. For T2DM, our analyses showed limited benefit in glycemic control from DSME

programs offering ≤10 hours of contact with delivery personnel and suggested that in-person 

delivery of behavioral programs is more beneficial than communicating the information with 

incorporation of technology. Behavioral programs seem to benefit individuals having suboptimal 

or poor glycemic control more than those with good control. Tailoring programs to ethnic 

minorities appears to be beneficial.

Prospero Registration No. CRD42014010515
ix

Contents

Executive Summary.................................................................................................................ES-1

Introduction....................................................................................................................................1

Background................................................................................................................................1

Pathophysiology...................................................................................................................1

Epidemiology and Burden of Disease..................................................................................1

Diabetes Care and Self-Management...................................................................................2

Rationale for Evidence Review .................................................................................................3

Scope of Review and Key Questions.........................................................................................4

Analytic Frameworks.................................................................................................................6

Organization of This Report ......................................................................................................7

Methods.........................................................................................................................................10

Topic Refinement and Review Protocol..................................................................................10

Literature Search Strategy........................................................................................................10

Inclusion and Exclusion Criteria..............................................................................................11

Study Selection ........................................................................................................................14

Data Extraction ........................................................................................................................15

Risk of Bias Assessment of Individual Studies.......................................................................15

Data Synthesis..........................................................................................................................16

Synthesis for T1DM (KQs 1–4).........................................................................................19

Synthesis for T2DM (KQs 5 and 6)...................................................................................20

Strength of the Body of Evidence............................................................................................22

Applicability ............................................................................................................................23

Peer Review and Public Commentary .....................................................................................23

Results...........................................................................................................................................24

Literature Search and Screening ..............................................................................................24

Type 1 Diabetes Mellitus.........................................................................................................25

Literature Search and Screening ........................................................................................25

Characteristics of Included Studies....................................................................................25

Risk of Bias of Individual Studies.....................................................................................29

KQ 1. Behavioral Programs for T1DM and Behavioral, Clinical, and Health 

Outcomes; Diabetes-Related Health Care Utilization; and Program 

Acceptability................................................................................................................30

KQ 2. Subgroups for Effectiveness in T1DM ...................................................................49

KQ 3. Potential Moderation of Effectiveness for T1DM: Components, Intensity, 

Delivery Personnel, Method of Communication, Degree of Tailoring, 

and Level of Community Engagement ........................................................................52

KQ4. Harms for T1DM......................................................................................................53

Type 2 Diabetes Mellitus.........................................................................................................53

Literature Search and Screening ........................................................................................54

Characteristics of Included Studies....................................................................................54

Risk of Bias of Individual Studies.....................................................................................55

Effectiveness of Behavioral Programs Across Outcomes .................................................56

KQ 5. Potential Moderation of Effectiveness for T2DM: Components, Intensity, 

Delivery Personnel, Method of Communication, Degree of Tailoring, 

and Level of Community Engagement ........................................................................60
x

KQ 6. Subgroups for Factors Moderating Effectiveness in T2DM...................................69

Discussion......................................................................................................................................73

Key Findings and Discussion for Type 1 Diabetes Mellitus (Key Questions 1–4).................73

KQ 1. Behavioral Programs for T1DM and Behavioral, Clinical, 

and Health Outcomes; Diabetes-Related Health Care Utilization; 

and Program Acceptability ..........................................................................................73

KQ 2. Subgroups for Effectiveness in T1DM ...................................................................74

KQ 3. Potential Moderation of Effectiveness for T1DM: Components, Intensity, 

Delivery Personnel, Method of Communication, Degree of Tailoring, 

and Level of Community Engagement ........................................................................74

KQ 4. Harms for T1DM.....................................................................................................74

Discussion of Key Findings for T1DM .............................................................................74

Key Findings and Discussion for Type 2 Diabetes (KQs 5 and 6)..........................................76

Effectiveness of Behavioral Programs Across Outcomes .................................................76

KQ 5. Potential Moderation of Effectiveness for T2DM: Components, Intensity, 

Delivery Personnel, Method of Communication, Degree of Tailoring, 

and Level of Community Engagement ........................................................................77

KQ 6. Subgroups for Factors Moderating Effectiveness for T2DM .................................77

Discussion of Key Findings for T2DM .............................................................................78

Findings in Relation to What Is Already Known.....................................................................80

Applicability ............................................................................................................................82

Type 1 Diabetes .................................................................................................................82

Type 2 Diabetes .................................................................................................................83

Limitations of the Comparative Effectiveness Review Process..............................................84

Limitations of the Evidence Base ............................................................................................86

Research Gaps..........................................................................................................................87

Conclusions..............................................................................................................................88

References.....................................................................................................................................90

Abbreviations and Acronyms ...................................................................................................108

Tables

Table A. Categorization of program components and implementation factors.......................ES-10

Table B. Type 1 diabetes: summary of key findings and strength of evidence 

for behavioral programs compared with usual care...........................................................ES-15

Table C. Type 1 diabetes: summary of key findings and strength of evidence 

for behavioral programs compared with an active control ................................................ES-17

Table D. Potential research needs by Key Question................................................................ES-25

Table 1. Inclusion criteria for type 1 diabetes (Key Questions 1–4) .............................................13

Table 2. Inclusion criteria for type 2 diabetes (Key Questions 5 and 6) .......................................14

Table 3. Categorization of program components and delivery factors..........................................18

Table 4. Other clinical and behavioral outcomes for type 1 diabetes............................................40

Table 5. Behavioral programs for type 1 diabetes compared with usual care: generic 

health-related quality of life at 6-, 12-, and 24-month postintervention..................................42

Table 6. Behavioral programs for type 1 diabetes compared with usual care: 

diabetes-related health care utilization at end of intervention, 6-, 12-, 

and 24-month postintervention followup.................................................................................45
xi

Table 7. Type 1 diabetes: summary of key findings and strength of evidence 

for behavioral programs compared with usual care .................................................................47 

Table 8. Type 1 diabetes: summary of key findings and strength of evidence 

for behavioral programs compared with an active control ......................................................49 

Table 9. Type 1 diabetes: summary of key findings and strength of evidence 

for subgroups (by age) receiving behavioral programs compared with usual care .................51 

Table 10. Type 1 diabetes: summary of key findings and strength of evidence 

for subgroups (by age) receiving behavioral programs compared with 

active controls ..........................................................................................................................52 

Table 11. Type 1 diabetes: results from univariate meta-regressions analyzing 

the association between different program factors and the effectiveness 

of behavioral programs in improving HbA1c for T1DM ..........................................................53 

Table 12. Network meta-analysis for effect moderation on HbA1c results in T2DM: 

description of nodes and results ...............................................................................................63 

Table 13. Network meta-analysis for effect moderation on body mass index results 

in T2DM: description of nodes and results ..............................................................................67 

Table 14. Results for race/ethnicity subgroups using univariate meta-regressions 

analyzing the association between different program factors and the effectiveness 

of behavioral programs for T2DM compared to usual care in improving 

HbA1c for T2DM ......................................................................................................................72 

Table 15. Potential research needs, by Key Question ....................................................................87 

Figures

Figure A. Analytic framework for behavioral programs for type 1 diabetes mellitus ...............ES-6 

Figure B. Analytic framework for behavioral programs for type 2 diabetes mellitus ...............ES-7 

Figure C. Flow diagram of study retrieval and selection .........................................................ES-13 

Figure D. Plot of network meta-analysis results for HbA1c .....................................................ES-20 

Figure 1. Analytic framework for behavioral programs for type 1 diabetes mellitus..................... 8 

Figure 2. Analytic framework for behavioral programs for type 2 diabetes mellitus..................... 9 

Figure 3. Flow diagram of study retrieval and selection .............................................................. 24 

Figure 4. Risk of bias summary for trials of behavioral programs for type 1 diabetes ................ 30 

Figure 5. Behavioral programs for type 1 diabetes compared with usual care: HbA1c

at the end of intervention ........................................................................................................ 32 

Figure 6. Behavioral programs for type 1 diabetes compared with usual care: HbA1c

at 6-month postintervention .................................................................................................... 33 

Figure 7. Behavioral programs for type 1 diabetes compared with usual care: HbA1c

at 12-month postintervention (youth only) ............................................................................. 34 

Figure 8. Behavioral programs for type 1 diabetes compared with active control: HbA1c

at end of intervention .............................................................................................................. 35 

Figure 9. Behavioral programs for type 1 diabetes compared with active control: HbA1c

at 6-month postintervention .................................................................................................... 36 

Figure 10. Behavioral programs for type 1 diabetes compared with active control: HbA1c

at 12-month postintervention .................................................................................................. 36 

Figure 11. Behavioral programs for type 1 diabetes compared with usual care: 

self-monitoring of blood glucose (tests per day) at end of intervention ................................. 37 

Figure 12. Behavioral programs for type 1 diabetes compared with usual care: 

self-monitoring of blood glucose (tests per day) at 6-month postintervention ....................... 38 
xii

Figure 13. Behavioral programs for type 1 diabetes compared with usual care: 

generic health-related quality of life at end of intervention.................................................... 42

Figure 14. Behavioral programs for type 1 diabetes compared with usual care: 

diabetes-specific health-related quality of life at end of intervention..................................... 43

Figure 15. Behavioral programs for type 1 diabetes compared with usual care: 

diabetes distress/stress at end of intervention ......................................................................... 44

Figure 16. Behavioral programs for type 1 diabetes compared with usual care: 

diabetes distress at 6-month postintervention followup.......................................................... 44

Figure 17. Behavioral programs for type 1 diabetes compared with usual care: 

participant attrition.................................................................................................................. 46

Figure 18. Risk of bias summary for trials of behavioral programs for type 2 diabetes .............. 56

Figure 19. Plot of network meta-analysis results for effect moderation on HbA1c

in T2DM.................................................................................................................................. 66

Figure 20. Plot of network meta-analysis results for effect moderation on body mass 

index in T2DM........................................................................................................................ 69

Appendixes

Appendix A. Operational Definitions

Appendix B. Literature Search Strategies

Appendix C. Very High Human Development Index Countries

Appendix D. Studies Excluded After Full-Text Review

Appendix E. Risk of Bias

Appendix F. Description of Studies and Interventions

Appendix G. Type 1 Diabetes Mellitus: Summary of Results From Observational Studies

Appendix H. Strength of Evidence Tables for Type 1 Diabetes Mellitus

Appendix I. Effectiveness Across Outcomes for Type 2 Diabetes Mellitus

Appendix J. Network Meta-Analysis Results for Glycemic Control and Age Subgroup Analyses
ES-1

Executive Summary

Introduction

The high burden of diabetes necessitates careful attention to factors contributing to optimal 

diabetes care and self-management, including lifestyle behaviors and medication adherence. 

Over the past few decades, much of the care and education of people with diabetes in the United 

States has been transferred from hospitals to outpatient settings, and several guidelines and 

diabetes management programs have been developed to improve diabetes care in the 

community.1 However, an evaluation of initiatives to implement guidelines and processes of care 

in community health centers did not find improved control of hemoglobin A1c (HbA1c) levels for 

patients with diabetes.2

Approaches for supporting patients with diabetes to change behaviors include interventions 

such as diabetes self-management education (DSME), with or without an additional support 

(clinical, behavioral, psychosocial, or educational) phase; lifestyle interventions; and medical 

nutrition therapy. Interventions vary widely in terms of content, duration, intensity, and delivery 

methods. The effectiveness of these interventions for patients with type 1 diabetes (T1DM) has 

not been evaluated in recent years and the few existing reviews have been inconclusive.3-7 In 

contrast, there is a diverse evidence base supporting the effectiveness of these approaches for 

type 2 diabetes (T2DM). However, it is unknown what combination(s) of program components 

and delivery mechanisms are most effective for success for T2DM. 

Epidemiology and Burden of Disease

In 2012, 29.1 million Americans had a form of diabetes (diagnosed and undiagnosed). This 

represents 9.3 percent of the entire population and 12.3 percent of the adult population 20 years 

or older.8 Older adults are disproportionately affected with diabetes; 25.9 percent of people age 

65 years or older have diabetes. African Americans, Hispanic Americans, American Indians and 

Alaska Natives, and some Asian Americans have a higher risk of T2DM than non-Hispanic 

whites.8 Although most cases of diabetes are T2DM, T1DM is one of the most common chronic 

diseases in childhood and adolescence, and its prevalence in the United States (1 of 433 youths

<20 years of age) has increased over the past couple of decades.9 Non-Hispanic white youths are 

affected with T1DM more often than any other racial or ethnic group.10

Diabetes-related care accounts for 11 percent of all U.S. health care expenditures,

11

equating 

to $245 billion in total costs in 2012.8 Average medical expenses are more than twice as high for 

a person with diabetes as they are for someone without diabetes.12 When considering medical 

and productivity costs, some calculations provide even more extreme differentials, particularly in 

relation to T1DM: 2007 national costs per case were $2,864 for undiagnosed diabetes, $9,677 for 

diagnosed T2DM, and $14,856 for T1DM.11 Complications from diabetes include cardiovascular 

disease, retinopathy, neuropathy, nephropathy, and cerebrovascular disease, as well as 

comorbidities such as depression and other mental health conditions.13

Diabetes Care and Self-Management

The mainstay of treatment for T1DM is lifelong insulin therapy. In order to achieve optimal 

glycemic control, people with T1DM (and especially those on multiple-dose insulin or insulin 

pump therapy) should self-monitor their blood sugar levels frequently during the day and adjust 

their insulin dose, diet, and/or physical activity accordingly.14 The benefit of intensive control of 
ES-2

glycemia in reducing the incidence and progression of micro- and macrovascular complications 

was clearly demonstrated in the Diabetes Control and Complications Trial and its related 

longitudinal study.15,16 Recently, these findings have extended to demonstrate reduced 

mortality.17 Although these findings are promising, a meta-analysis of 12 trials (2,230 

participants) of intensive versus conventional glucose control in T1DM confirmed the reduction 

in development but not progression of microvascular complications, and stressed that the 

benefits should be weighed against the risks of severe hypoglycemia.18

People with T2DM are often managed progressively, with an initial focus on diet (e.g., 

medical nutrition therapy) and physical activity, subsequent addition of one or more oral 

hypoglycemic medications, and in many cases also use of insulin (or sole use of insulin) to 

obtain optimal blood glucose control. The importance of tight glycemic control for reducing the 

risk of microvascular complications in T2DM was shown in the United Kingdom Prospective 

Diabetes Study.19,20 As with T1DM, though, a meta-analysis pooling results from 28 trials 

(34,912 participants) of intensive control in T2DM found no significant differences for all-cause 

mortality or cardiovascular deaths, or for macrovascular complications, including nonfatal 

myocardial infarction.21

Factors other than blood glucose control are important to address. Reducing the risk for 

diabetes-related complications in T1DM and T2DM often requires lifestyle and/or 

pharmacological management of body weight, blood pressure, and cholesterol levels.14,22-24 For 

instance, intensive lowering of blood pressure in people with diabetes has been shown to reduce 

major cardiovascular events by 11 percent.

25 Lifestyle interventions targeted at weight loss, 

diabetes nutrition, and physical activity recommendations have been shown to be associated with 

weight control and improved glycemic control.26-29 Additionally, findings from two large crossnational studies—the Diabetes, Attitudes, Wishes, and Needs (DAWN) studies—have 

demonstrated the need to address other outcomes of importance for patients, such as diabetesrelated distress and depression.30

A critical element of diabetes care is education and support to enable patients to adopt and 

adhere to several self-care or self-management and lifestyle behaviors. Because knowledge 

acquisition alone is insufficient for behavioral changes,26,31 the focus of many national and 

international guidelines and recommendations for DSME has shifted from traditional didactic 

educational services to more patient-centered methodologies incorporating interaction and 

problem-solving.32-35 In addition, the national standards for DSME developed by the American 

Association of Diabetes Educators and the American Diabetes Association have incorporated the 

provision of ongoing diabetes self-management support “to encourage behavior change, the 

maintenance of healthy diabetes-related behaviors, and to address psychological concerns.”32 In 

addition to DSME, a diverse range of interventions and programs have been developed that focus 

on supporting patients’ efforts in changing lifestyle behaviors in order to better manage glycemia 

and prevent complications.27

Despite the availability of new medications and devices (e.g., insulin pumps, continuous 

glucose monitoring), several standards for care management and DSME programs, and 

implementation of lifestyle interventions, the National Health and Nutrition Examination Survey 

found that 45 percent of adults with diabetes in the United States do not achieve glycemic 

targets.36
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Rationale for Evidence Review

Health providers working in outpatient and primary care settings in the community struggle 

with how to best support, educate, and work with patients with diabetes to improve their disease 

control. To date, it is not clear whether there is (or what constitutes) a set of best practices 

associated with behavioral programs that can be implemented in the community health setting. 

For the purpose of this review, community health settings include ambulatory care (i.e., 

outpatient) clinics, primary care clinics, family physician clinics, and federally qualified health 

centers (i.e., Community Health Centers and Rural Health Centers).

Self-management and lifestyle interventions have been shown to improve glycemic control 

for T2DM to a clinically significant extent, at least in the short term;37-44 the evidence for these 

programs in T1DM is less conclusive and based on older literature. Many previous systematic 

reviews on topics relevant to this review for T2DM have included studies evaluating a broad 

scope of interventions, some of them falling short of meeting current recommendations and 

others incorporating some enhancement of medical management that may confound the effects 

of the behavioral program. Many reviews have also included studies evaluating interventions 

targeted at a single behavior/component (e.g., diet) rather than multiple behaviors, as seems 

necessary for optimal disease self-management. Moreover, few reviews assessed factors 

contributing to the success of the interventions,37,39,43,45,46 and even fewer analyzed the data in a 

manner that assessed multiple factors simultaneously:

45 the moderating effects of program 

content and characteristics have therefore not been fully investigated.

Our focus for T1DM was to determine the effectiveness of behavioral programs and for 

T2DM was to identify factors contributing to the effectiveness of multicomponent programs. We 

investigated a range of outcomes and conducted a network meta-analysis (enabling simultaneous 

assessment of multiple variables and a wide variety of comparisons) to analyze potential 

moderators of effectiveness, such as delivery personnel, effective community linkages, and 

demographic characteristics. Because of our focus on moderation of effectiveness for T2DM, we 

did not examine harms, as we did for T1DM. This review provides information regarding the 

effectiveness and harms of behavioral programs (T1DM) and the combination of program 

components and delivery methods that is most effective for implementation of these programs in 

community health settings (T2DM). 

Scope and Key Questions

For the purpose of this review we developed an operational definition of behavioral programs 

that encompasses DSME (without or with an additional clinical, psychosocial, or behavioral 

support phase—i.e., “DSME plus support”), as well as other programs incorporating interactive 

components that target multiple important behavioral changes (e.g., diet and physical activity). A 

commonality of all programs was that they incorporated one or more behavior change 

techniques,47 with or without explicit use of a theory or model of behavior change. Our 

operational definition of a behavioral program is as follows:

An organized, multicomponent diabetes-specific program with repeated interactions by 

one or more trained individuals, with a duration of ≥4 weeks, to improve disease control 

and/or patient health outcomes, and consisting of at least one of the following: (a) 

DSME; (b) a structured dietary intervention (related to any of the following: weight loss, 

glycemic control, or reducing risk for complications) together with one or more 

additional components; or (c) a structured exercise or physical activity intervention 
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together with one or more additional components. Additional components for (b) and (c) 

may include interventions related to diet or physical activity; behavioral change 

(including but not limited to goal-setting, problem-solving, motivational interviewing, 

coping-skills training, cognitive behavioral therapy strategies); relaxation or stress 

reduction; blood glucose regulation; medication adherence; or self-monitoring for 

diabetic complications (foot, eye, and renal tests).

We addressed the following six Key Questions (KQs):

Key Question 1. For patients with T1DM, are behavioral programs 

implemented in a community health setting effective compared with usual 

or standard care, or active comparators in—

a. Improving behavioral, clinical, and health outcomes?

b. Improving diabetes-related health care utilization?

c. Achieving program acceptability as measured by participant attrition 

rates? 

Key Question 2. For patients with T1DM, do behavioral programs 

implemented in the community health setting differ in effectiveness for 

behavioral, clinical, and health outcomes; their effect on diabetes-related 

health care utilization; or program acceptability for the following subgroups 

of patients?

a. Age—children and adolescents (≤18 years) and their families, young 

adults (19–30 years), adults (31–64 years), older adults (≥65 years) 

b. Race or ethnicity 

c. Socioeconomic status (e.g., family income, education level, literacy)

d. Time since diagnosis (≤1 year vs. >1 year) 

e. Baseline level of glycemic control (HbA1c <7% vs. ≥7%)

Key Question 3. For patients with T1DM, does the effectiveness of 

behavioral programs differ based on the following factors? 

a. Program components 

b. Intensity (i.e., program duration, frequency/periodicity of interactions) 

c. Delivery personnel (e.g., dietitian, exercise specialist, physician, 

nurse practitioner, certified diabetes educator, lay health worker) 

d. Method of communication (e.g., individual vs. group, face to face, 

interactive behavior change technology, social media) 
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e. Degree of tailoring based on needs assessment (e.g., 

educational/behavioral deficits, age or other demographics, readiness 

to change) 

f. Level and nature of community engagement

Key Question 4. For patients with T1DM, what are the associated harms 

(i.e., activity-related injury) of behavioral programs implemented in a 

community health setting compared with usual care, standard care, or 

active comparators?

Key Question 5. Among behavioral programs targeted at adults with 

T2DM implemented in a community health setting, what factors contribute 

to (a) their effectiveness for behavioral, clinical, and health outcomes; (b) 

their effect on diabetes-related health care utilization; and (c) program 

acceptability as measured by participant attrition rates? Factors include the 

following: 

a. Program components 

b. Program intensity 

c. Delivery personnel 

d. Methods of delivery and communication 

e. Degree of tailoring 

f. Community engagement 

Key Question 6. Do the factors that contribute to program effectiveness for 

patients with T2DM vary across the following subpopulations? 

a. Age—young adults (19–30 years), adults (31–64 years), older adults 

(≥65 years) 

b. Race or ethnicity 

c. Socioeconomic status (e.g., family income, education level, literacy) 

d. Time since diagnosis (≤1 year vs. >1 year) 

e. Baseline level of glycemic control (HbA1c <7% vs. ≥7%)

Analytical Frameworks

We developed two analytic frameworks to guide the systematic review process and specific 

KQs for T1DM and T2DM (Figure A and Figure B, respectively). The figures illustrate the 

populations of interest and the outcomes that we reviewed. 
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Figure A. Analytic framework for behavioral programs for type 1 diabetes mellitus

HbA1c = hemoglobin A1c; KQ = Key Question
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Figure B. Analytic framework for behavioral programs for type 2 diabetes mellitus

HbA1c = hemoglobin A1c; KQ = Key Question
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Methods

Literature Search Strategy

We used the same approach and search strategies for T1DM and T2DM. Our research 

librarian searched the following bibliographic databases from 1993 to May 2014: Ovid 

MEDLINE® and Ovid MEDLINE® In-Process & Other Non-Indexed Citations, Cochrane 

Central Register of Controlled Trials via Cochrane Library, Embase® via Ovid, CINAHL Plus 

with Full Text via EBSCOhost, PsycINFO® via Ovid, and PubMed® via the National Center for 

Biotechnology Information Databases. We limited the search to prospective controlled studies 

published in English. On January 15, 2015, we performed a search update in all databases except 

Embase, from which none of the previously included studies was exclusively obtained. We 

reviewed the reference lists of relevant systematic reviews and of all included studies. We 

searched ClinicialTrials.gov and the World Health Organization International Clinical Trials 

Registry Platform. We searched the conference proceedings (2011–14) from the American 

Diabetes Association, American Association of Diabetes Educators, National Institute of 

Diabetes and Digestive and Kidney Diseases, Canadian Diabetes Association, European 

Association for the Study of Diabetes, International Diabetes Federation, Society of Behavioral 

Medicine, and International Society for Behavioral Nutrition and Physical Activity.

Eligibility Criteria

The research team developed eligibility criteria with respect to populations, interventions, 

comparators, outcomes, timing, and setting (PICOTS). For both T1DM and T2DM, we included 

studies conducted in the United States or other highly developed countries48 and published in the 

English language on or after 1993. The publication date limit was chosen because of changes to 

usual care/medical management (the comparator in most cases in this review) resulting from the 

findings of landmark trials published from 1993 onward.15,24,49 For T1DM, we included 

prospective comparative studies—i.e., randomized controlled trials (RCTs), nonrandomized 

controlled trials (non-RCTs), prospective cohort studies, and controlled before-after studies. For 

T2DM, we included RCTs. 

For T1DM, we included studies of patients (any age) diagnosed with T1DM who had 

undergone basic diabetes education. For T2DM, we included studies of adults with T2DM who 

had undergone basic diabetes education.

For behavioral programs, we included studies of interventions that met the criteria included 

in our operational definition. The comparators were usual care (i.e., usual medical management 

provided to all participants), an active comparator (i.e., an intervention not meeting our 

definition of a behavioral program, such as basic education or a dietary or physical activity 

intervention), or another behavioral program. When two or more behavioral programs were 

compared, we considered this an evaluation of comparative effectiveness. 

Study Selection

Two reviewers independently screened all titles and abstracts using broad inclusion criteria. 

We retrieved the full text of any publications marked for inclusion by either reviewer. Two 

reviewers independently assessed the full texts using a priori inclusion criteria and a standard 

form. We resolved disagreements by consensus or consulting a third member of the review team. 
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Risk of Bias

Two reviewers independently assessed the risk of bias of included studies. Discrepancies 

were resolved through discussion and consensus. We assessed the internal validity of RCTs and 

non-RCTs using the Cochrane Risk of Bias tool.50 The tool examines seven domains of potential 

bias (sequence generation, concealment of allocation, blinding of participants and personnel, 

blinding of outcome assessment, incomplete outcome data, selective outcome reporting, and 

“other” sources of data) and is used to categorize the overall risk of bias. Each domain was rated 

as having low, medium, or high risk of bias.

We assessed the risk of bias for prospective cohort studies and controlled before-after studies 

using the Newcastle-Ottawa Scale.51 This tool uses a star system to assess methodological 

quality across three categories: selection of participants, comparability of study groups, and 

ascertainment of the outcome of interest. The star rating indicates the quality of a study, with a 

maximum assessment of nine.

Data Extraction

We used structured data extraction forms to gather pertinent information, including 

characteristics of study populations, settings, interventions, comparators, and outcomes; study 

designs; and methods. We extracted data directly into the Systematic Review Data RepositoryTM 

(http://srdr.ahrq.gov/).52 One reviewer extracted data, and a second reviewer checked the data for 

accuracy and completeness. We resolved disagreements through consensus or by consulting a 

third member of the review team.

Data Synthesis

We analyzed data separately for T1DM and T2DM, with different approaches for each KQ. 

For each condition we summarized the characteristics of included studies qualitatively and 

presented important features of the study populations, interventions, and comparators in 

summary tables. All outcome data were extracted and reported in figures of meta-analyses (if 

pooled) or in outcomes tables. We extracted and analyzed data from different postintervention

followup timepoints: end of intervention to ≤1 month postintervention, >1 month to ≤6 months, 

>6 months to ≤12 months, >12 months to ≤24 months, and >24 months.

We focused on the following key outcomes: HbA1c, quality of life, development of microand macrovascular complications, all-cause mortality, adherence to diabetes self-management 

behaviors, change in body composition, change in physical activity or fitness, and change in 

dietary or nutrient intake. To enable interpretation of the results in terms of clinical significance 

and the precision of the effect sizes during assessment of the strength of the body of evidence for 

our key outcomes, discussed later, we defined a threshold for clinical importance when there was 

literature to provide guidance. For HbA1c, we used a difference of 0.4 percent (e.g., 7.6% vs. 

8.0%).53 For quality-of-life measures and other patient-reported outcomes represented by 

continuous data, we used a difference of one-half standard deviation (SD)—i.e., 0.50 

standardized mean difference (SMD)—based on the mean SD from the pooled studies, which has 

been shown to represent a universal conservative estimate of a meaningful difference.54,55 For 

adherence to self-management behaviors, we did not apply a threshold for clinical importance 

because of poor reporting of the scoring and unknown meaning of a threshold for an optimal 

number of self-monitoring tests (the most common reporting for this outcome).
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With input from our Technical Expert Panel, we categorized various components and 

implementation methods, as outlined in Table A. Many behavioral programs comprised DSME 

with or without the addition of a support component (i.e., DSME + support); we separated these 

into two categories to recognize that the support phase was often of a lower intensity (e.g., less 

frequent contacts) and focused on different content, such as psychosocial support, as compared 

with the DSME phase. Programs not considered DSME were considered “lifestyle” programs.

Table A. Categorization of program components and implementation factors

Program Factors Categories and Description Variables

Program componentsa 1. DSME

2. DSME + support: DSME plus an added phase to extend program duration and 

support; often clinically focused but may be psychosocial, educational, or 

behavioral

3. Lifestyle programs: Behavioral programs focused on diet and/or physical activity 

rather than on diabetes-specific self-management behaviors; may also include 

other components as long as program does not meet the criteria for DSME with 

emphasis on education/training

Duration of program No categories; duration was used as a continuous variable for the regression analyses 

for KQs 3 and 6

Intensitya (contact hours; 

where contact hours could 

not be calculated, we used 

number of contacts as a 

proxy)

1. ≤10 hoursb

2. 11 to 26 hours (e.g., weekly for up to 6 months) 

3. ≥27 hours (allowing for monthly followup for 1 year) 

Frequency of contacts No categories; this was a composite variable combining duration and intensity 

(hours/month); the continuous variable was used for the regression analyses for T1DM

Method of communicationc 1. In person only

2. Mixture of in person and technology

3. All technology with minimal interaction with providers

Method of deliveryd 1. Individual

2. Mixed individual and group

3. Group

Delivery personnele 1. Delivered entirely by non–health professional (e.g., lay/community health worker, 

undergraduate student) after training and under some supervision

2. One health professional for large majority (>75%) of delivery 

3. Provision by multidisciplinary team of health professionals

Degree of tailoringf 1. None/minimal—no tailoring or only small portion is tailored (e.g., personalized diet 

prescription in otherwise highly structured lifestyle program or delivery based on 

flexible hours but same content for all) 

2. Moderate/maximum—most of program has content and/or delivery tailoring (e.g., 

topics are based on needs assessment, and delivery timing/duration/location is 

based on participant’s schedule/needs/location preferences)

Level and nature of 

community engagement

1. Present—e.g., peer delivery of program or peer support groups for support stage, 

use of community resources (infrastructure) for delivery or maintenance stages 

2. Absent—e.g., nothing reported or, at most, providing written information about 

community resources 

Presence of support 

persong

1. Family or parent involved in >1 session

2. No family or parent involvement in sessions

DSME = diabetes self-management education; KQ = Key Question; T1DM = type 1 diabetes mellitus a

In analyses for KQ 5 and 6 only. b

Based on the current number of hours billable for patients eligible for public health care administered by the Centers for 

Medicare & Medicaid Services in the United States (described by Technical Expert Panel as a practical limitation on 

implementing programs having higher intensity). c

2 and 3 were combined for analysis. d

1 and 2 were combined for analysis. e

2 and 3 were combined for KQs 5 and 6. f

Used in summary tables and the analysis for T1DM. g

For T1DM only.
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Synthesis for T1DM (KQs 1–4)

For each comparison of interest, we conducted a pairwise meta-analysis when two or more 

eligible trials were sufficiently similar on the basis of study design and clinical homogeneity. We 

present both pooled and subgroup analysis based on age when there was more than one trial in 

each age category at any timepoint. We used the Hartung-Knapp-Sidik-Jonkman random-effects 

model56,57 for all meta-analyses and used Stata 11.2 and Excel 2010 software. We calculated 

pooled mean differences (MDs), SMDs, and risk ratios (RRs) with corresponding 95%

confidence intervals (CIs), as appropriate, and weighted by sample size and variance. We 

analyzed outcomes at different postintervention timepoints. 

For KQ 2, we searched for subgroup analyses reported by individual trials that focused on 

whether a particular behavioral program was more or less effective for the outcome reported by 

the most studies (i.e., HbA1c) based on variables of interest. (See Figure A.) We also compared 

subgroups of studies—for example, when the mean age of participants fell within one of the age 

categories. 

To assess whether the effectiveness of behavioral programs differed based on various 

program factors (KQ 3), we performed univariate metaregressions for comparisons between 

behavioral programs and usual care for HbA1c from each study’s longest followup timepoint. 

Each behavioral program was coded using the categorization scheme in Table A, and these 

variables were used in the analysis. For KQ 4, harms (i.e., activity-related injury), we planned to 

descriptively summarize all outcomes presented in studies. 

Synthesis for T2DM (KQs 5 and 6)

Before synthesizing findings to answer KQs 5 and 6, we performed pairwise meta-analyses 

for all outcomes identified in the PICOTS using the same analytical approach described for KQ 

1. To answer KQs 5 and 6, we performed network meta-analyses for key outcomes reported by 

the most studies (HbA1c and BMI). A network meta-analysis allows for simultaneous evaluation 

of a suite of comparisons, and considers both direct and indirect evidence while preserving the 

within-study randomization. A network of different comparisons is constructed (with “nodes” 

representing groupings of sufficiently similar interventions and comparators). To assess the 

effectiveness of programs based on different combinations of moderator variables, we grouped 

the behavioral programs into nodes after coding them in terms of the program components and 

implementation factors described in Table A. We also formed three categories for the comparator 

groups: usual care, active “non-DSME education” control (i.e., basic education not meeting our 

criteria for DSME), and active “other” control (e.g., stand-alone dietary or physical activity 

interventions). The analysis was conducted using a Bayesian network model. Results are 

presented as estimates of the treatment effects (MDs) relative to usual care with 95-percent 

credibility intervals, as well as the rank probabilities for each behavioral program strategy (e.g., 

probability that a particular combination of components and delivery methods for a behavioral 

program is the “best program”). 

KQ 6 focused on whether variability between population groups affected the role of potential 

factors contributing to effectiveness of behavioral programs for the key outcome with the most 

data (i.e., HbA1c). We first conducted subgroup analyses of the pairwise meta-analysis results for 

HbA1c for behavioral programs compared with usual care and active controls at longest 

followup; subgroup analyses based on between-study baseline glycemic control (HbA1c), age, 

and ethnicity were performed. For baseline glycemic control and age, we then performed 

subgroup analysis of the network meta-analysis used for KQ 5 using only studies in which
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participants had suboptimal baseline glycemic control (>7% HbA1c), or were under 65 years of 

age. For subgroups based on race/ethnicity (≥75% vs. <75% percent nonwhite and/or Hispanic), 

the number of trials in either subgroup was not sufficient to perform a meaningful network metaanalysis (i.e., the number of studies in each node would be very low, thus limiting the validity of 

this method), so we conducted a set of univariate metaregressions using the variables in Table A

and methods outlined for KQ 2. All of our results for this KQ relied on between-study rather than

within-study comparisons, such that the effect of randomization is removed and the results are 

considered observational and possibly biased through confounding by other study-level 

characteristics. 

Strength of the Body of Evidence

We followed the “Methods Guide for Effectiveness and Comparative Effectiveness Reviews”

(Methods Guide)

58 to evaluate the strength of evidence (SOE) for KQ 1 for all health outcomes 

(i.e., quality of life, development of micro- and macrovascular complications, all-cause 

mortality) and selected behavioral and clinical outcomes (i.e., glycemic control, adherence to 

diabetes self-management behaviors, change in body composition, change in physical activity or 

fitness, and change in dietary or nutrient intake). For KQ 2, we assessed SOE for HbA1c, which 

was the outcome reported by the most studies and thus the focus of this KQ. SOE assessments 

were based on evidence from trials. The body of evidence was graded by one reviewer and 

reviewed by a second reviewer. Disagreements were resolved through discussion or by 

consulting with a third reviewer, as needed.

For each outcome, we assessed five major domains of most relevance to reviews of RCTs 

(anticipated to be the large majority of included studies): risk of bias (rated as low, medium, or 

high), consistency (rated as consistent, inconsistent, or unknown), directness (rated as direct or 

indirect), precision (rated as precise or imprecise), and reporting bias (rated as suspected or not 

suspected). A precise estimate is one that allows for a clinically useful conclusion. The overall 

SOE was graded as high, moderate, low, or insufficient. High, moderate, and low SOE reflect the 

confidence we have in the effect estimate and the likelihood that the estimate will change with 

further research. Insufficient SOE implies that we are unable to estimate an effect, that we had no 

or very little evidence, or that the 95% CI included clinically important effects both for and 

against behavioral programs.

Applicability

We assessed applicability of the body of evidence following guidance from the Methods 

Guide.58 We used the PICOTS framework to explore factors that may affect applicability. 

Results

Our database and gray literature searches identified 47,141 citations, and 11 additional 

records were identified from reference lists of systematic reviews and included studies. For 

T1DM, we included 34 studies described in 44 publications. For T2DM, we included 132 studies 

described in 161 publications. Figure C describes the flow of literature through the screening 

process.
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Figure C. Flow diagram of study –

T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus

a

One study was included for both T1DM and T2DM.

T1DM: Description and Risk of Bias of Studies 

Twenty-five studies were conducted in children and adolescents; nine were conducted in 

adults. Most trials were two-arm trials comparing DSME with usual care. For most studies 

(70%), the mean HbA1c was 8.5 percent or higher. For studies targeting children and adolescents, 

the mean age across most studies ranged from 12 to 15 years; because of this, we refer to the

included studies as being conducted in “youths.” For studies targeting adults, the mean age 

ranged from 30 to 49 years. No studies specifically targeted older adults (≥65 years). The mean 
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duration of diabetes ranged from 2.7 to 7.3 years among studies that targeted youths and from 

2.5 to 23 years for those targeting adults. 

The total duration of the behavioral programs for youths ranged from 1.2 to 25 months 

(median = 5.6 months). The number of contact hours ranged from 1 to 48 hours (median = 9.5

hours). Five trials delivered the programs to youths only; 16 delivered the programs to both 

youths and their parents or family members. There was a mixture of delivery to individuals and 

to groups, and programs were delivered by a variety of personnel, with seven trials not using 

health care professionals.

In studies on adults, the total duration of the behavioral programs ranged from 1.5 to 12 

months (median = 6 months), and the number of contact hours ranged from 9 to 52 hours 

(median = 16 hours). There was a mixture of individual and group formats. All trials were 

provided by health care professionals; one used a peer who served as coleader.

All trials were assessed as having either moderate or high overall risk of bias. For objective 

outcomes (i.e., HbA1c), 58 percent of trials had a medium risk of bias and 42 percent had a high 

risk. The assessment of high risk was largely driven by incomplete outcome data (i.e., loss to 

followup). For trials reporting subjective outcomes of interest to this review (e.g., health-related 

quality of life [HRQL], patient-reported self-management behaviors), all but one trial had a high 

risk of bias (95%), primarily because of lack of blinding of participants, study personnel, and 

outcome assessors. 

T1DM: Results for KQs 1–4

A summary of the key findings and SOE assessments for behavioral programs compared 

with usual care and active controls are presented in Tables B and C, respectively.

When comparing behavioral programs with usual care, there was moderate SOE showing 

reduction in HbA1c at 6-month postintervention followup, with percent HbA1c reduced by 0.31. 

This result failed to reach our threshold of clinical significance of a change by 0.4 percent 

HbA1c. For all other timepoints, there was no significant difference in HbA1c; the SOE was low 

because of risk of bias and imprecise effect estimates. For followup timepoints of 12 months or 

longer, the 95% CIs included our threshold for clinical importance such that we cannot rule out 

benefit for behavioral programs based on the available evidence. For individuals who were 

enrolled in behavioral programs compared with those receiving an active control, there was 

moderate SOE showing a statistically significant and clinically important reduction in percent 

HbA1c of 0.44 at 6-month postintervention followup. There was no difference in HbA1c at other 

timepoints; however, the SOE was low and we cannot rule out a benefit for behavioral programs.

There was low SOE showing no difference in adherence to diabetes self-management 

behaviors (i.e., frequency of blood glucose checks or overall self-management) at end of 

intervention and 6-month followup for comparisons with usual care; for comparisons with active 

controls, there was insufficient SOE for this outcome at any followup timepoint. For participants 

receiving behavioral programs compared with usual care, there was no difference in generic 

HRQL at the end of intervention (moderate SOE). Few trials reported on generic HRQL at 

longer followup timepoints. In comparisons with usual care, there was insufficient SOE to assess 

whether there was any effect on diabetes-specific HRQL at any timepoint, and low SOE of no 

difference for diabetes distress at end of intervention and 6-month followup. The 95% CIs for 

diabetes distress included our threshold for clinical importance such that we cannot rule out a 

favorable effect for behavioral programs. There were no data on HRQL for comparisons of 

behavioral programs with active controls. Few trials reported on symptoms of depression or on 
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episodes of severe hypo- or hyperglycemia. No trials reported on micro- and macrovascular 

complications or on all-cause mortality.

Few trials reported on the number of diabetes-related hospital admissions or emergency 

department admissions. Behavioral programs appear to be acceptable to patients with T1DM; our 

meta-analysis found a 21-percent higher risk of attrition for individuals receiving usual care 

compared with those receiving the behavioral program. 

Table B. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with usual care

Outcome Outcome 

Timing

# Trials

(# Subjects); Tool if 

Applicable

Mean Difference or Standardized 

Mean Difference

Strength of 

Evidence

HbA1c EOI 16 (1,155) MD, -0.11; 95% CI, -0.33 to 0.11a Low for no

significant

difference

HbA1c 6m followup 12 (1,463) MD, -0.31; 95% CI, -0.47 to -0.15 Moderate for 

benefitb

HbA1c 12m 

followup 

7 (1,333) MD, -0.22; 95% CI, -0.49 to 0.05 Low for no

significant

difference 

HbA1c ≥12m 

followup 

4 (1,138) MD, -0.40; 95% CI, -0.92 to 0.12 

(>12m to <24m)

MD, -0.08; 95% CI, -1.96 to 1.8 

(≥24m)

Low for no

significant

difference

Adherence to 

diabetes selfmanagement 

EOI 4 (282); SMBG

1 (74); SDSCA

1 (54); DSMP

1 (74); DSCI

MD, 0.15; 95% CI, -0.54 to 0.84 

MD, 1.4 days; 95% CI, 0.35 to 2.43

MD, 5.00; 95% CI, 0.60 to 9.40

MD, 0.22; 95% CI, -0.60 to 1.04

Low for no

significant 

difference

Adherence to 

diabetes selfmanagement 

6m followup 5 (252); SMBG

1 (244); SDSCA

2 (471); DSMP

MD, 0.40; 95% CI, -0.36 to 1.16

MD, -0.06; 95% CI, -0.60 to 0.48

No difference (different measures)

Low for no

significant

difference

Adherence to 

diabetes selfmanagement 

12m 

followup 

1 (54); DSMP

1 (180); skipping 1 or 

more doses in past 

month

MD, 4.00; 95% CI, -1.69 to 9.69

OR, 0.82; 95% CI, 0.48 to 0.1.38

Insufficient

Adherence to 

diabetes selfmanagement 

>12m 

followup 

1 (390); SMBG

1 (190); skipping 1 or 

more doses in past 

month

MD, -0.36; 95% CI, -0.69 to -0.03 

(≥24m)

OR, 1.30; 95% CI, 0.78 to 2.17 (24m)

Insufficient

Change in body 

composition (BMI

[kg.m-2])

EOI 1 (60) MD, 0.08; 95% CI, -0.35 to 0.51 Insufficient

Change in body 

composition (BMI

[kg.m-2])

6m followup 1 (227) MD, -0.21; 95% CI, -0.62 to 0.20 Insufficient

Change in body 

composition (kg)

EOI 1 (61) MD, -0.50; 95% CI, -5.69 to 4.69 Insufficient

Change in 

physical activity 

(fitness, VO2 max) 

EOI 1 (43) MD, 0.59; 95% CI, 0.22 to 0.96 Insufficient

Change in 

physical activity 

(intensity/duration)

EOI 2 (91) SMD, 0.16; 95% CI, -0.25 to 0.57 Insufficient
ES-16

Table B. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with usual care (continued)

Outcome Outcome 

Timing

# Trials

(# Subjects); Tool if 

Applicable

Mean Difference or Standardized 

Mean Difference

Strength of 

Evidence

Change in 

physical activity 

(intensity/duration)

6m followup 2 (272) SMD, -0.26; 95% CI, -1.00 to 0.49 Insufficient

Change in dietary 

or nutrient intake 

(energy [kcal/day]) 

EOI 1 (61) MD, -247.10; 95% CI, -281.7 to -

212.5

Insufficient

Change in dietary 

or nutrient intake 

(% saturated fat) 

EOI 1 (61) MD, -1.80; 95% CI, -3.53 to -0.07 Insufficient

Generic HRQL EOI 7 (474) SMD, 0.10; 95% CI, -0.18 to 0.38 Moderate for 

no difference

Generic HRQL 6m followup 1 (53) SMD, -0.29; 95% CI, -0.83 to 0.26 Insufficient

Generic HRQL 12m 

followup

2 (405) SMD, 0.02; 95% CI, -0.11 to 0.15 Insufficient

Generic HRQL ≥12m 

followup

1 (291) SMD, -0.04; 95% CI, -0.27 to 0.19 Insufficient

Diabetes-specific 

quality of life

EOI 3 (212) SMD, 0.08; 95% CI, -1.44 to 1.60 Insufficient

Diabetes distress EOI 4 (209) SMD, -0.31; 95% CI, -0.83 to 0.21 Low for no

significant

difference

Diabetes distress 6m followup 4 (236) SMD, -0.28; 95% CI, -0.94 to 0.38 Low for no

significant

difference

BMI = body mass index; CI = confidence interval; DSCI = Diabetes Self-Care Inventory (scale not reported; higher scores 

better); DSMP = Diabetes Self-Management Profile (scale not reported; higher scores better); EOI = end of intervention to

≤1month postintervention followup (interventions 1.5–25 months); HbA1c = hemoglobin A1c; HRQL = health-related quality of 

life; m = month; MD = mean difference; OR = odds ratio; SDSCA = Summary of Diabetes Self-Care Activities (days per week 

adhering to self-management behaviors); SMBG = self-monitoring of blood glucose (frequency; tests per day); 

SMD = standardized mean difference; VO2max = maximal oxygen uptake a

Negative values for MDs or SMDs are favorable for HbA1c, change in body composition, change in dietary intake, and diabetes 

distress. 

b

This point estimate did not meet the threshold for clinical significance, although the 95% CI included a clinically important 

difference.
ES-17

Table C. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with an active control

Outcome Outcome 

Timing

# Trials (# 

Subjects); Tool if 

Applicable

Mean Difference Strength of 

Evidence

HbA1c EOI 4 (566) MD, -0.32; 95% CI, -0.78 to 0.14a Low for no

significant

difference

HbA1c 6m followup 4 (504) MD, -0.43; 95% CI, -0.62 to -0.24 Moderate for

benefit

HbA1c 12m followup 3 (342) MD, -0.34; 95% CI, -0.71 to 0.03 Low for no

significant

difference

Adherence to 

diabetes selfmanagement 

EOI 1 (54); DSMP

1 (149); DBRS

MD, 2.40; 95% CI, -2.46 to 7.26

No data reported; those in behavioral 

program did more poorly 

Insufficient

Adherence to 

diabetes selfmanagement 

6m followup 1 (149); SMBG

1 (149); DBRS

MD, -0.20; 95% CI, -0.76 to 0.36

No data reported; those in behavioral 

program did more poorly

Insufficient

Adherence to 

diabetes selfmanagement 

12m followup 1 (54); DSMP

1 (149); DBRS

MD, 2.00; 95% CI, -3.78 to 7.78

No data reported; those in behavioral 

program did more poorly

Insufficient

CI = confidence interval; DBRS = Diabetes Behavior Rating Scale (scale not reported; higher scores better); DSMP = Diabetes 

Self-Management Profile (scale not reported; higher scores better); EOI = end of intervention; HbA1c = hemoglobin A1c; 

m = month; MD = mean difference; SMBG = self-monitoring of blood glucose (frequency; tests per day) a

Negative values for MDs are favorable for HbA1c.

For KQ 2, we examined the differential effect of patient characteristics on the effectiveness 

of behavioral programs for T1DM. In comparisons with usual care, results for the subgroups of 

studies in adults and in youths were consistent with the results when looking at all studies 

combined for KQ 1. At 6 months, behavioral programs reduced HbA1c in studies of youths by a 

statistically significant 0.28 percent and in studies of adults by a non–statistically significant 0.38 

percent. At end of intervention, the point estimates indicated greater benefit in the adult subgroup

(0.28) than in the youth subgroup (0.00), although neither of these values reached statistical 

significance. None of the point estimates exceeded the clinically important difference of 0.4

percent HbA1c, which was established a priori. In the comparisons with active controls based on 

age of study participants, the small number of studies in most subgroups provided insufficient 

SOE.

One trial reported results separately for youths with baseline HbA1c ≥8 percent and found 

favorable results for this subgroup; no other subgroup analysis was conducted because the 

majority of trials enrolled participants with poor control (HbA1c >8.5%). No trials reported on 

HbA1c by race or ethnicity, socioeconomic status, or time since diagnosis.

For KQ 3, our univariate metaregressions did not find any statistically significant differences 

for moderation by any program factor. Examining the coefficients (e.g., change in HbA1c from

switching from one category to another or adding an increment in a continuous variable such as 

program hours) and their 95% CIs suggested that program intensity (duration, contact hours, 

frequency of contacts) did not influence effectiveness, and that individual (vs. group) delivery 

was beneficial. No studies reported on the associated harms (i.e., activity-related injury) of 

behavioral programs (KQ 4).
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T2DM: Description and Risk of Bias of Studies 

The majority of RCTs were two-arm trials, with many comparing DSME with usual care (55 

trials) or an active control (7 trials); 16 three- or four-arm trials were included, as were several 

trials comparing two different behavioral programs (21 trials). Trials were conducted in 16 

countries, but the majority (63%) were undertaken in the United States. Several trials evaluated 

more than one behavioral program; there were 166 intervention arms in total. The mean age of 

the participants ranged from 45 to 72 years (median = 58). Baseline HbA1c ranged from 6.3 to

12.3 percent (median = 8%). Median duration of diabetes was 8.1 years (range, 1–18 years). The 

proportion of nonwhite and/or Hispanic participants was between 0 and 100 percent; the majority 

(≥75%) of participants in 32 trials reported nonwhite and/or Hispanic race/ethnicity.

Overall, median program duration was 6 months (range, 1–96) and median number of contact 

hours was 12 (range, 1–208). Sixty-four programs were delivered to individuals only, 56 were 

delivered to groups only, and 44 had some mixture of individual and group delivery. A small 

majority of programs were delivered by one health care professional, with or without the 

assistance of a non–health care professional; other programs were delivered by a 

multidisciplinary team or solely by non–health care professionals. Technology was the primary 

method of communication for 17 programs studied in 16 trials and was used in combination with 

in-person communication in 25 programs; based on our inclusion criteria, all programs were 

delivered with some form of communication with delivery personnel.

All trials were assessed as having a medium or high overall risk of bias. For objective 

outcomes (e.g., HbA1c, weight, blood pressure), 42 percent of trials had a medium risk of bias 

and 58 percent had a high risk. The assessment of high risk was largely driven by incomplete 

outcome data (i.e., loss to followup). Of trials (n = 92) reporting on subjective outcomes of 

interest for this review (e.g., HRQL, depression), 13 percent had a medium risk of bias; the 

remainder (87%) had a high risk of bias. This was primarily because of lack of blinding of 

participants, study personnel, and outcome assessors. See the Supplementary File: Full Text 

Screening Form, Risk of Bias Tools, and Results of Meta-Analyses for T2DM Across Outcomes

(available at http://srdr.ahrq.gov) for a description of decision rules for these assessments.

T2DM: Overall Effectiveness of Behavioral Programs and Results 

for KQs 5 and 6

Effectiveness of Behavioral Programs Across Outcomes

There is evidence showing a beneficial effect of behavioral programs compared with both 

usual care and active interventions at end of intervention for glycemic control; however, for 

followup timepoints of 6 and 12 months, only the results at 6 months for comparisons with active 

controls were statistically significant. None of the results were considered to be clinically 

important based on our prespecified threshold of a 0.4 change in percent HbA1c. There was 

substantial statistical heterogeneity in these pairwise meta-analyses, supporting our subsequent 

analysis for KQs 5 and 6 to determine which program factors and population characteristics 

mediate (and optimize) the effects.

Compared with usual care but not active controls, behavioral programs showed some benefits 

in terms of reducing BMI (0.2–0.9 kg/m2

) up to 12-month followup. There were reductions in 

weight (1.3–1.7 kg) and waist circumference (3.2 cm) at end of intervention, and (vs. usual care) 

in daily energy intake (65–150 kcal per day at 6 months). Few studies reported on outcomes 
ES-19

related to changes in physical activity and medication adherence, and findings were consistently 

of no difference.

HRQOL was reported by fewer studies than anticipated, and the results mostly showed no 

difference. Results for diabetes distress favored behavioral programs compared with usual care at 

end of intervention (MD, -1.8; not clinically important based on prespecified threshold of 0.5 SD 

from the pooled studies), but not at longer followup. Diabetic retinopathy was reduced by 14

percent and very high–risk chronic kidney disease was reduced by 31 percent in participants 

receiving an intensive lifestyle program lasting 8 years or longer compared with didactic 

education and support in the largest trial, conducted by the LookAHEAD research group. Allcause mortality was 14 percent lower for those receiving behavioral programs than active control 

groups (RR, 0.86).

KQ 5. Potential Mediators of Effectiveness for T2DM 

When interpreting the results for potential modifiers of effectiveness (components, intensity, 

delivery personnel, method of communication, degree of tailoring, and level of community 

engagement), we relied primarily on the relative ranking of the nodes that represented grouped 

factors and looked for trends in the findings based on program variables that appeared to 

determine whether the effects would offer clinical benefit. Some nodes had very few studies, 

small sample sizes, and/or wide credibility intervals. Thus we did not make any firm conclusions 

for a single node or for differences in 561 potential comparisons, but rather from looking across 

nodes with similar features.

In a network meta-analysis with usual care serving as the main reference, programs 

demonstrating relative effect sizes for HbA1c above our threshold for clinical importance (i.e., 

0.4%) represented all three major program component categories of DSME, DSME plus support, 

and lifestyle. The effect sizes of minimally intensive DSME programs (≤10 contact hours) were 

all less than our threshold for clinical importance but were all higher than the effect sizes of 

active controls of educational interventions not meeting our criteria for a behavioral program 

(e.g., didactic education programs). Programs having higher effect sizes were more often 

delivered in person rather than including technology; the effective programs incorporating 

technology were all of moderate or high intensity (>10 contact hours). Figure D summarizes the 

results of the network meta-analysis for HbA1c. 
ES-20

Figure D. Plot of network meta-analysis results for HbA1c

DSME = diabetes self-management education; HbA1c = hemoglobin A1c; HCP = health care practitioner

This plot depicts the results from our network meta-analysis for the outcome of HbA1c (negative values favorable) when 

comparing groups (“nodes”) of interventions, with each group differing by at least 1 level in the categories of program 

component, intensity, mode of communication, delivery method, and (for DSME programs only) delivery personnel. (See Table 

A for categorization schema.) The factors of program duration, program tailoring, and community engagement were not used for 

the analysis because of overlap in meaning with other factors (e.g., community engagement often attained through use of non–

health care providers) and ability to categorize based on reporting (e.g., tailoring). The dots and lines represent the mean 

difference (MDs) and 95% credibility intervals for the represented programs relative to usual care; the figure indicates which 

MDs meet or exceed our predetermined threshold for clinical importance (change of ≥0.4% HbA1c).

For the network meta-analysis of BMI, we created nodes using four variables (i.e., program 

component, program intensity, method of communication, and method of delivery). Lifestyle 

programs resulted in the highest effect sizes for BMI. Program intensity appeared to be less 

important than method of delivery; providing some in-person delivery appears to be beneficial.

KQ 6. Subgroups for Factors Mediating Effectiveness in T2DM

In terms of overall effectiveness at longest followup for HbA1c, participants with suboptimal 

glycemic control (≥7% HbA1c) appear to benefit more than those with good control (<7%) from 

behavioral programs when compared with usual care and active controls. The effect sizes were 

not clinically important for either group. Few differences were evident when a network metaanalysis was used to evaluate potential mediation by program factors in a subgroup of studies 

having participants with suboptimal baseline glycemic control. 
ES-21

At longest followup, older adults (≥65 years) did not benefit in terms of reduction in HbA1c 

from behavioral programs compared with usual care or active controls. In adults <65 years, the 

effect size for behavioral programs compared with active controls at longest followup (up to 12 

months) was clinically important. When using the studies of only participants <65 in the network 

analysis, the active “other” control group (e.g., dietary or physical activity intervention) showed 

clinically important benefit for glycemic control (MD, -0.55). 

Programs offered to predominantly minority participants (≥75% nonwhite and/or Hispanic) 

appear to provide more benefit than those offered to populations with a lower proportion (<75%) 

of minority participants. The effect size for minority participants reached clinical importance.

None of the program implementation factors (e.g., intensity, delivery personnel) reached 

statistical significance for influencing the effectiveness of behavioral programs compared with

usual care on HbA1c. Lifestyle programs appeared to be favorable over DSME or DSME plus 

support for the group of studies (n = 24) with predominantly white non-Hispanic individuals (p =

0.07); the difference in reduction in HbA1c between these two categories approached our 

threshold for clinical importance. Our results for ethnicity need to be interpreted with caution 

because of the apparent worse baseline glycemic control in studies of minority versus white nonHispanic participants (8.8% vs. 7.6% HbA1c); because behavioral programs seem to 

preferentially benefit those with higher baseline HbA1c, this factor may account for much of the 

increase in benefit.

Discussion

Type 1 Diabetes Mellitus

Overall, behavioral programs appear to have benefit in T1DM for reducing HbA1c when 

followup extends beyond the immediate postintervention period up to 6 months. The delay in 

benefit may in part reflect the time required for this marker of glycemic control, indicating 

control over the past 2 to 3 months, to demonstrate change. Notable, though, is the large diversity 

in program duration, whereby end of intervention was anywhere between 1.5 and 25 months

from the beginning of the program. Another contributor to the delay in benefit may be that a 

period of time is needed to integrate newly learned self-management behaviors into one’s life; 

however, the largely insufficient level of evidence for the behavioral outcomes does not allow us 

to determine this with any certainty. These beneficial findings for HbA1c at 6 months appear to 

be tempered by those of no difference at longer followup timepoints (≥12 months), although we 

are unable to confidently rule out benefit at long-term followup because of low SOE. Our 

findings may underestimate the effect of these programs should they be implemented in routine 

practice. The usual care group in several studies received some form of attention from the 

investigators (e.g., periodic telephone calls to maintain contact and encourage study 

participation), which may have resulted in improved glycemic control for the comparator group 

and reduced the relative effects observed for the behavioral program. Participants, or their 

providers, in the usual care or active control groups (not being blinded to group assignment in 

most studies) may have become more motivated to practice better self-management (including 

blood glucose regulation using insulin titrations), which could also attenuate differences between 

groups. Differences in the “usual care” provided may have also played a role, although this effect 

may be minimal considering recent evidence that variations in standard care in studies of 

behavioral interventions for youths with T1DM did not significantly impact study results.58
ES-22

The positive findings for behavioral programs compared with active controls are notable. By 

offering an intervention to both study arms, these studies may also have introduced less potential 

bias from lack of allocation concealment and blinding. Our finding of a statistically significant 

and clinically important reduction (by 0.44%) in HbA1c at 6-month followup for these 

comparisons is promising. 

Self-management of T1DM during adolescence is complex, often characterized by personal 

challenges and uncertainty, transitions to adult care, less frequent health care visits, and 

diminished parental involvement; consequently, glycemic control deteriorates over the course of 

childhood and adolescence for many youths with T1DM.59-62 For these reasons, many of the 

studies included in this review aimed to prevent deterioration of glycemic control rather than to 

improve it. The statistically significant reductions in HbA1c at 6-month followup (vs. usual care) 

and the clinically important reductions in HbA1c at 6- and 12-month followup (0.60% and 0.52%, 

respectively) in comparisons with active controls in youths lend substantial support for these 

programs. Likewise, incorporating more demanding self-management behaviors may negatively 

impact social and emotional functioning, such that our findings of no difference in generic 

HRQL at end of intervention may be viewed positively.

For T1DM, there was the suggestion that effectiveness was not moderated by program 

intensity (i.e., duration, contact hours, or frequency of contacts) and that individual versus group 

delivery may be beneficial. Because of insufficient data, we were unable to examine the 

difference between educational and lifestyle programs, or the benefit from addition of a support 

component to DSME programs.

Type 2 Diabetes Mellitus

Moderate- and high-intensity (≥11 hours contact time) programs appear to be necessary to 

provide individuals with clinically important effects on glycemic control. This outcome may also 

benefit from in-person delivery rather than incorporating technology. For BMI, providing some 

individual delivery, rather than solely relying on group formats, appears to be beneficial. 

Lifestyle programs, focusing more on weight reduction and increases in physical activity 

than diabetes self-care, may provide similar or more benefit than DSME programs for improving 

glycemic control for individuals with T2DM. Our review also confirms previous suggestions that 

programs that have an interactive nature and employ behavioral change techniques are beneficial 

when compared with didactic educational interventions. While some of our findings may not 

result in clinically important changes at an individual level, the burgeoning growth of this 

disease means that even small gains in glycemic control from behavioral programs may serve as 

a substantial benefit for public health. 

Our network meta-analysis results suggest that both individual and group delivery of 

programs is beneficial. Delivery format may be highly dependent on the population served and 

program content. Studies having clinically important effect sizes that offered programs in groups 

tended to be those offered to minorities, in which support from peers was incorporated as a key 

program feature. 

We were unable to draw any conclusions about the choice of delivery personnel from the 

network meta-analysis. Drawing from the pairwise meta-analysis of five RCTs (647 subjects) 

comparing two or more interventions, there may be no difference between program delivery 

conducted by health care professionals or by lay providers (e.g., peers with diabetes, community 

health workers). One reason that programs delivered by health care professionals were not 
ES-23

superior may be that physicians, nurses, and dietitians receive little or no training in behavioral 

techniques as part of their formal education. 

Our findings suggest that people with suboptimal, or poor, baseline glycemic control (≥7%

HbA1c), younger age (<65 years), and racial/ethnic minority status may benefit the most from 

behavioral programs. Because there were apparent differences in baseline glycemic control 

between subgroups of race/ethnicity (i.e., 8.8% HbA1c in the ≥75% minority group vs. 7.6%

HbA1c in the <75% minority group), it is hard to distinguish if ethnicity or glycemic control is 

more likely to have the greater influence in moderating program effectiveness. There are likely 

several other factors to also consider. Many investigators enrolling a large proportion of ethnic 

minorities in the trials included in this review also adapted programs in ways to make them more 

culturally and linguistically acceptable, often including peers in the delivery or social support 

groups, which appeared to enhance their effectiveness. Our reliance on study-level data to create 

subgroups (i.e., the entire study was delivered to minorities) may have limited our ability to 

capture differences in effects from programs delivered to a wider population base, which may 

reflect routine practice in many community health settings. 

Applicability

Type 1 Diabetes Mellitus

The results of this report may be most applicable to individuals with suboptimal and poor 

glycemic control. Nevertheless, clinicians may view the results as highly relevant to their patient 

population, of whom many—particularly in their pubertal years—are struggling to achieve 

optimal control. The results should be generally applicable to older children and adolescents 

(youth studies), and middle-aged adults. 

It is unclear whether the results are applicable to youths or adults with recently diagnosed 

T1DM. We did not find evidence to confirm or refute whether behavioral programs are more or 

less efficacious for other subgroups, including males or females, or racial or ethnic minorities. 

All of the studies targeting adults were conducted in the United Kingdom, Europe, or New 

Zealand. It is unclear whether the results from these studies are applicable to community health 

settings in the United States. For youths, most studies (73%) were conducted in the United 

States; the remaining studies were conducted in Europe and Australia. Despite potential 

differences in settings and health systems, results were similar across the studies. The studies 

were conducted primarily in outpatient diabetes clinics affiliated with a secondary or tertiary care 

hospital. Our findings are generally applicable to these settings in the United States.

Type 2 Diabetes Mellitus

Our results appear to be applicable to the majority of people enrolling in behavioral 

programs. There were few studies of older (≥65 years) adults or for those with good glycemic 

control. Our exclusion criteria related to duration of diabetes (mean <1 year)—implemented in 

order to capture programs providing training in ongoing self-management and lifestyle 

behaviors—limit the relevance of this review for newly diagnosed patients. The results appear to 

be applicable to both men and women, and for people on a variety of diabetes treatment 

regimens (19.2% were on insulin). Overall, there was fairly good representation of individuals 

reporting a minority racial/ethnic background. 

The results seem to be applicable to community health settings in the United States. The 

majority (63%) of trials were conducted in the United States, and based on our inclusion criteria 
ES-24

related to the Human Development Index,

48 all studies were performed in countries of similar 

development status. Although reported inconsistently, health systems differences (i.e., usual 

care) may vary widely between study populations and could potentially influence the results 

from behavioral programs. The effect from this difference should be minimal for this review, 

since we limited our results to changes from baseline between groups randomly assigned and 

judged to receive similar medical care. 

Limitations of the Comparative Effectiveness Review Process

This review followed rigorous methodological standards, which were detailed a priori. 

Nevertheless, several limitations are inherent within systematic reviews in general. 

First, there is a possibility of selective reporting bias (e.g., reporting only positive outcomes) 

and publication bias, whereby unexpectedly strong results from large trials are selectively 

reported. In terms of selective outcome reporting, we were able to locate several trial registries 

and protocols to compare planned and published outcome reporting; most studies included in this 

review were judged as having low bias in this respect. Our prespecified tests for publication bias 

provided no significant indication of bias. Selected studies were confined to the English language 

because we felt that these reports would be most applicable to the end-users of this review, who 

create recommendations or implement programs for people with diabetes within the United 

States. Moreover, effect sizes in language-restricted reviews have shown to not differ 

significantly (overestimating effect sizes by 2%) from those not having restrictions.63 Study 

selection bias was limited by having two independent reviewers perform screening and selection; 

we feel confident that study exclusion was based on explicit and appropriate reasoning, which 

was clearly understood by reviewers. 

The interventions evaluated in the included trials were highly diverse in their content, 

delivery, and setting; accordingly, some of our statistical analyses indicated substantial 

heterogeneity. Our analyses for KQs 3, 5, and 6 were designed to determine some of the factors 

leading to variability in success for behavioral programs. Variability may still exist in terms of 

several factors. An example is length of followup; our analyses for these KQs were based on 

longest followup to maximize study inclusion and capture outcome durability. Another example, 

applicable to T2DM, is within-program intensity; DSME plus support and lifestyle programs 

often had lower intensity maintenance phases of varying durations. 

The effects of programs delivered solely through technology (i.e., no interaction with 

personnel) were not assessed. Cost analysis of implementing differing behavioral programs was 

not addressed in this review. 

Limitations of the Evidence Base

The evidence base was inadequate to fully answer the KQs, particularly with respect to the 

limited number of outcomes evaluated in several studies. We were unable to fully evaluate all 

outcomes of interest for several KQs. For KQ 1, for T1DM, limited data were available to assess 

the SOE for many outcomes, including behavioral outcomes related to changes in dietary intake 

or physical activity, and clinical and health outcomes apart from HbA1c. No studies contributed 

data for our assessment of harms (KQ 4). Our assessment of factors contributing to effectiveness 

of behavioral programs for T1DM (KQ 3) was limited to the outcome of HbA1c and to univariate 

metaregressions. 

For KQs 5 and 6, related to T2DM, our network meta-analysis allowed for multiple 

comparisons (i.e., all comparison groups and followup timepoints), but there were still too few 
ES-25

studies reporting on outcomes besides HbA1c and BMI. The metaregressions used for the 

subgroup analysis on ethnicity in KQ 6 are limited by comparator (only usual care), and the 

number of studies did not allow us to capture multiple variables in a single analysis. Moreover, 

our reliance on study-level data for the subgroup analyses makes these results exploratory.

Several outcomes of importance to patients and policymakers, such as quality of life, 

development of complications, and health care use, were reported by too few studies to 

confidently support conclusions of effect or to analyze in terms of mediation by implementation 

factors. 

Many trials had methodological limitations introducing some risk of bias. Blinding of 

participants and personnel is arguably difficult for trials of behavioral programs, especially when 

the comparator is usual care. According to our decision rules for assessing risk of bias, a low risk 

of bias for participant and personnel blinding was granted if the comparator was an active control

or another program, the authors stated some means to blind the study hypothesis from 

participants, and personnel followed a structured training and protocol. Participant blinding in 

this manner was rarely reported. Similarly, blinding of outcome assessors, highly feasible in any 

situation, was rarely reported or sufficient. These two domains resulted in medium or high risk of 

bias being assigned for the subjective outcomes of most trials. For both subjective and objective 

outcomes, medium or high risk of bias was assigned in many cases from lack of intention-to-treat 

analysis (e.g., reporting only on results for completers) and/or from high participant attrition. 

Some studies had small sample sizes, and a few failed to achieve baseline comparability in their 

samples. 

Research Gaps

Table D highlights some potential research needs based on our KQs.

Table D. Potential research needs by Key Question

KQ Potential Research Needs

1 

Effectiveness 

for T1DM

There were limited data to determine the effectiveness of behavioral programs for T1DM at 

durations of followup beyond 6 months. Future studies should strive to assess outcomes at 

longer term followup, to better determine the effects of these programs for periods of time 

that may better influence long-term outcomes of complications and quality of life.

1 

Effectiveness 

for T1DM

There was insufficient evidence to demonstrate whether lifestyle programs (i.e., combining 

structured physical activity and dietary interventions) are effective for T1DM. Many 

individuals with T1DM under good glycemic control may have other risk factors (e.g., 

overweight, hyperlipidemia, hypertension) for which these programs may be warranted. Trials 

of lifestyle programs enrolling people with both types of diabetes should undertake subgroup 

analysis.

1 & 3 

Effectiveness 

& moderating 

factors for 

T1DM

The effectiveness of adding a clinical, behavioral, psychosocial, or educational support phase 

to programs for T1DM is unknown. These may be useful for prolonging the effects of 

behavioral programs and to address some of the psychosocial aspects of the disease 

(particularly in adolescents) to a greater extent.

3

Moderating 

factors for 

T1DM

Only one study in T1DM compared behavioral programs delivered in person with those 

delivered via some form of technology allowing for interaction between the provider and 

patient. Transitioning individuals with diabetes between pediatric and adult care facilities and 

providers can be challenging, hampered by the scheduling structure of traditional clinics at a 

time in life when contact information and location of home, work, and education are often 

changing frequently. As a result, further research on providing behavioral programs via 

technology or creative scheduling is warranted for adolescents and young adults with 

diabetes. 
ES-26

Table D. Potential research needs by Key Question (continued)

KQ Potential Research Needs

3

Moderating 

factors for 

T1DM

Several studies for T2DM included a small subsample of people with T1DM. Trials of lifestyle 

programs that incorporate exercise need to perform subgroup analysis by type of diabetes,

particularly when evaluating the outcome of glycemic control. Adjustment of insulin for 

exercise in individuals with T1DM can be challenging and could result in differential effects of 

lifestyle programs on glycemic control, depending on the medical management of the 

participants. 

3 & 5

Moderating 

factors for 

T1DM & 

T2DM

There was large diversity in the reporting and use of behavior change techniques employed 

within the programs. An evaluation of the effects of different strategies may shed additional 

light on the factors (within components) determining effectiveness for behavioral programs.

5

Moderating 

factors for 

T2DM

The identification of the combination of providers (e.g., physician, nurse, dietitian, 

pharmacist, social worker, psychologist, and trained lay individual) that is best for 

implementation of behavioral programs for T2DM deserves further evaluation. 

5

Moderating 

factors for 

T2DM

Clinical psychologists are often employed to deliver program components that incorporate 

advanced behavioral approaches, such as motivational interviewing; this approach may not 

be feasible for all settings or within all program budgets. More research is required to 

determine the effectiveness of similar programs when delivered by other personnel trained to 

use these behavioral techniques.

5

Moderating 

factors for 

T2DM

Few trials directly compared interactive programs delivered in person with those delivered via 

technology. Because a technology-based approach may lessen resource burden, help to 

reach patients living in rural areas, and/or be desirable for younger adults more familiar with 

technology, its effectiveness needs further evaluation.

6

Effectiveness 

for different 

subgroups in 

T2DM

Trials including populations of diverse ethnic backgrounds should perform subgroup analysis 

based on age, race/ethnicity, and baseline glycemic control to further explore outcomes for 

these groups from programs that are not designed specifically for them, as might be common 

in most community health settings. 

All

Few trials evaluated outcomes important to patients and decisionmakers (e.g., quality of life, 

micro- and macrovascular complications, health care use) in a manner that allowed pooling

of results across studies. Use of widely accepted generic quality-of-life measures would be 

beneficial. 

All Study attrition rates affected the overall risk of bias substantially. More research on methods 

for maintaining study participation is required.

All

The risk of bias from participant and personnel blinding was high in most trials. Although 

many trials compared behavioral programs with active controls (limiting risk of bias because 

of blinding) comparisons with usual care would benefit from some mechanism to blind 

participants from the study hypothesis. Blinding of outcome assessors should always be 

attempted for subjective outcomes.

All

There is a need for consensus on what constitutes clinically important differences in 

outcomes for behavioral programs, such that they can be interpreted in meaningful ways for 

clinicians and patients. 

KQ = Key Question; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus

Conclusions

Behavioral programs for T1DM offer some benefit for glycemic control when followup 

extends beyond end of intervention up to 6 months. There was no significant difference at end of 

intervention or followup longer than 6 months, although our confidence in these findings is low

and we cannot rule out benefit. There was no difference in generic HRQL at end of intervention, 

or in diabetes distress or self-management behaviors at up to 6-month followup, although the 

SOE was low for these findings with the exception of generic HRQL at end of intervention 

(moderate SOE). Behavioral programs appear to be acceptable to patients with T1DM, given a 

21-percent lower rate of attrition among those in behavioral programs than among those 
ES-27

receiving usual care. Data were insufficient to draw any conclusions for other outcomes,

including diabetes-specific HRQL, change in body composition or lifestyle behaviors, microand macrovascular complications, and mortality. Encouraging patients with T1DM to participate 

in behavioral programs to improve outcomes apart from HbA1c is not supported by the current 

evidence. 

For T2DM, our analyses showed limited benefit in glycemic control from DSME programs 

offering ≤10 hours of contact with delivery personnel and suggested that in-person delivery of 

behavioral programs is more beneficial than incorporation of technology. We found that 

programs focused on lifestyle or on DSME can have similar benefit in terms of glycemic control, 

and that lifestyle programs appear to be better for reducing BMI. Whether the behavioral 

program is delivered by a health care professional or a trained lay person, or via individual or 

group format, appears to be less important based on the available evidence. Behavioral programs 

seem to benefit individuals having suboptimal or poor glycemic control more than those with 

optimal control. Tailoring programs to ethnic minorities—such as offering culturally appropriate 

materials and incorporating group interaction with peers—appears to be beneficial. While efforts 

should be made to provide culturally sensitive programs, community health settings that serve 

populations that are diverse in language and ethnicity may not have the opportunity to provide 

this flexible programming to meet each group’s needs. 

Efforts at integrating behavioral programs into care settings that incorporate the latest 

management guidelines should be prioritized. Program evaluation is an important component to 

build into the implementation of any behavioral program for diabetes, to ensure that it is the 

correct fit to be effective for the population that it is meant to serve. At this time, there remains a 

need for clinicians to evaluate each patient’s success after participating in these programs, in 

case additional means are necessary to control their disease more adequately to prevent 

devastating complications.
ES-28

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1

Introduction

Background 

The high burden of diabetes necessitates careful attention to factors contributing to optimal 

diabetes care and self-management including lifestyle behaviors and medication adherence. Over 

the past few decades, much of the care and education of people with diabetes in the United States 

has transferred from hospitals to outpatient settings, and several guidelines and diabetes 

management programs have been developed to improve diabetes care in the community.1

However, an evaluation of initiatives to implement guidelines and processes of care in 

community health centers did not find improved control of hemoglobin A1c (HbA1c) levels for 

patients with diabetes.2

Approaches for supporting patients with diabetes to change behaviors include interventions 

such as diabetes self-management education (DSME) with or without an additional support

(clinical, behavioral, psychosocial, or educational) phase, lifestyle interventions, and medical 

nutrition therapy. Interventions vary widely in terms of content, duration, intensity, and delivery 

methods. The effectiveness of these interventions for patients with type 1 diabetes (T1DM) has 

not been evaluated in recent years and the few existing reviews have been inconclusive.

3-7 In

contrast, there is a diverse evidence base supporting moderate effectiveness of these approaches 

for type 2 diabetes (T2DM). However, it is unknown what combination(s) of program 

components and delivery mechanisms are most effective for the success for T2DM. Health 

providers struggle with how to best support, educate, and work with patients to improve their 

disease control. To date, it is not clear whether there is (or what constitutes) a set of best 

practices associated with behavioral programs that could be implemented in community health 

settings.

Pathophysiology

The American Diabetes Association defines diabetes mellitus as “... a group of metabolic 

diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin 

action, or both.”8 T1DM and T2DM are the major classes of diabetes although several others 

exist. T1DM accounts for 5–10 percent of cases of diabetes and usually results when the body’s 

immune system destroys the beta cells of the pancreas, the only cells that make insulin.8 The 

incidence of T1DM peaks in adolescents although it can occur at any age. 

T2DM accounts for 90–95 percent of cases of diabetes. It usually begins with insulin 

resistance in which it takes more than the usual amount of insulin to achieve a given degree of 

glucose regulation. T2DM occurs if, over time, the pancreas is progressively less able to secrete 

enough insulin to normalize blood glucose.8,9 T2DM is associated with obesity, family history of 

diabetes, history of gestational diabetes, impaired glucose metabolism, physical inactivity, and 

nonwhite race or ethnicity.

Epidemiology and Burden of Disease

In 2012, 29.1 million Americans had diabetes (all types diagnosed and undiagnosed). This 

represents 9.3 percent of the entire population and 12.3 percent of the adult population (20 years 

or older).9 Older adults are disproportionately affected with diabetes; 25.9 percent of people over 

the age of 65 years have diabetes. African Americans, Hispanic Americans, American Indians 

and Alaska Natives, and some Asian Americans have a higher risk of T2DM compared to non-
2

Hispanic whites.9 Although most cases of diabetes are T2DM, T1DM is one of the most common 

chronic diseases in youth, and its prevalence in the United States (1 of 433 youth aged <20) has 

increased over the past couple decades.10 Non-Hispanic white youth are affected with T1DM 

more often than all other racial or ethnic groups.11

In addition to disparities in disease prevalence, several subpopulations are considered 

vulnerable to poor health care access and outcomes for a variety of individual and social reasons. 

Race or ethnicity and socioeconomic considerations including literacy, educational levels, and 

household income have been shown to be associated with sub-optimal care2,12 and poorer 

diabetes outcomes for both T1DM and T2DM. 13-15

Diabetes-related care accounts for 11 percent of all U.S. health care expenditure16 equating to 

$245 billion in total costs in 2012.9 Average medical expenses are more than twice as high for a 

person with diabetes as they are for someone without diabetes.17 When considering medical and 

productivity costs, some calculations provide even more extreme differentials particularly in 

relation to T1DM, with national costs in 2007 per case of $2,864 for undiagnosed diabetes, 

$9,677 for diagnosed T2DM, and $14,856 for T1DM.16

Complications from diabetes include cardiovascular disease, retinopathy, neuropathy, 

nephropathy, and cerebrovascular disease, as well as comorbidities such as depression and other 

mental health conditions.18 In adults, the most frequent first-listed diagnoses among hospital 

discharges in 2010 were diseases of the circulatory system (24 percent) and diabetes (12 

percent). Between 5 and 11 percent of emergency department visits are for diabetes-related 

complications.16 For children and adolescents in 2009, 74 percent of hospital discharges and 42 

percent of emergency visits had diabetes listed as the first diagnosis. About 64 percent of these 

discharges and 46 percent of the emergency visits were for diabetic ketoacidosis.9

Diabetes Care and Self-Management

The mainstay of treatment for T1DM is lifelong insulin therapy. In order to achieve optimal 

glycemic control, people with T1DM (and especially those on multiple-dose insulin or insulin 

pump therapy) should self-monitor their blood sugar levels frequently during the day and adjust 

their insulin dose, diet and/or physical activity accordingly.19 The benefit of intensive control of 

blood glucose in reducing the incidence and progression of micro- and macrovascular 

complications was clearly demonstrated in the Diabetes Control and Complications Trial 

(DCCT) and a related longitudinal study.20,21 Recently, these findings have extended to 

demonstrate reduced mortality.22 Although these findings are promising, a meta-analysis of 12 

trials (2,230 participants) of intensive versus conventional glucose control in T1DM only 

confirmed the reduction in development (but not progression) of microvascular complications, 

and stressed that the benefits should be weighed against the risks of severe hypoglycemia.23

People with T2DM are often managed progressively with an initial focus on diet (e.g., 

medical nutrition therapy) and physical activity, and subsequent addition of one or more oral 

hypoglycemic medications and in many cases also (or sole use of) insulin to obtain optimal 

blood glucose control. The importance of tight glycemic control for reducing the risk of 

microvascular complications in T2DM was first shown in the United Kingdom Prospective 

Diabetes Study.24,25 As with T1DM though, a meta-analysis pooling results from 28 trials 

(34,912 participants) of intensive control in T2DM found no significant differences for all-cause 

mortality or cardiovascular deaths, or for macrovascular complications including non-fatal 

myocardial infarction.26
3

Factors other than blood glucose control are important to address. Reducing the risk for 

diabetes-related complications in T1DM and T2DM often requires lifestyle and/or 

pharmacological management of body weight, blood pressure, and cholesterol levels.19,27-29 For 

instance, intensive lowering of blood pressure has shown to reduce major cardiovascular events 

by 11%.30 Lifestyle interventions targeted at weight loss, diabetes nutrition, and physical activity 

recommendations have been shown to be associated with weight control and improved glycemic 

control.31-34 Additionally, findings from two large cross-national (Diabetes, Attitudes, Wishes, 

and Needs [DAWN]) studies have demonstrated the importance to address other outcomes of 

importance for patients such as diabetes-related distress and depression.35,36

A critical element of diabetes care is education and support to enable patients to adopt and 

adhere to several self-care or self-management and lifestyle behaviors.37,38 DSME is designed to 

“reduce the burden of diabetes on individuals, families, communities and healthcare systems, 

and, by supporting good health, prevent or delay the onset of diabetes-related long-term 

complications.”39 Because knowledge acquisition alone is insufficient for behavioral 

changes,40,41 the focus of many national and international guidelines and recommendations for 

DSME has shifted from traditional didactic educational services to more patient-centered 

methodologies incorporating interaction and problem-solving.39,42-44 In addition, the national 

standards for DSME developed by the American Association of Diabetes Educators and the 

American Diabetes Association have incorporated the provision of ongoing diabetes selfmanagement support “...to encourage behavior change, the maintenance of healthy diabetesrelated behaviors, and to address psychological concerns.”42 In addition to DSME, a diverse 

range of interventions and programs have been developed that focus more on supporting 

patients’ efforts in changing lifestyle behaviors in order to better manage glycemia and prevent 

complications.32

Despite the availability of new medications and devices (e.g., insulin pumps, continuous 

glucose monitoring), several standards for care management and DSME programs, and 

implementation of lifestyle interventions, the National Health and Nutrition Examination Survey 

found that 45 percent of adults with diabetes in the United States do not achieve glycemic 

targets.45 Further, the Centers for Disease Control and Prevention’s Behavioral Risk Surveillance 

System found that 36 percent of adults diagnosed with diabetes reported no physical activity in 

the past 30 days.17 Other reported risk factors for diabetes-related complications included 

smoking (20 percent), self-reported overweight or obesity (86 percent), hypertension (58 

percent), and high cholesterol (58 percent).8

Rationale for Evidence Review

Health care providers working in outpatient and primary care settings in the community 

struggle with how to best support, educate, and work with patients with diabetes to improve their 

disease control. To date, it is not clear whether there is (or what constitutes) a set of best 

practices associated with behavioral programs that can be implemented in the community health 

setting. For the purpose of this review, community health settings include ambulatory care (i.e., 

outpatient) clinics, primary care clinics, family physician clinics, and federally qualified health 

centers (i.e., Community Health Centers, and Rural Health Centers).

Self-management and lifestyle interventions have been shown to improve glycemic control 

for T2DM to a clinically significant extent at least in the short term.

46-53 The evidence for these 

programs in T1DM is less conclusive. Many previous systematic reviews on topics relevant to 

this review for T2DM have included studies evaluating a broad scope of interventions, some of 
4

which fall short of meeting current recommendations (e.g., didactic educational interventions

focused on relaying information without some form of interactive or collaborative training), and 

others which incorporate some enhancement of medical management (e.g., treatment algorithms) 

which may confound the effects of the behavioral program. Many reviews have also included 

studies evaluating interventions targeted at a single behavior/component (e.g., diet) rather than 

multiple behaviors as seems necessary for optimal disease self-management. Moreover, few

assessed factors contributing to the success of the interventions,

46,48,51,54,55 and even fewer 

analyzed the data in a manner to assess multiple factors simultaneously54―the moderating

effects of program content and characteristics have therefore not been fully investigated.

Our focus for T1DM was to determine the effectiveness of behavioral programs, and for 

T2DM was to identify factors contributing to the effectiveness of multicomponent programs. We 

investigated a range of outcomes and conducted network meta-analysis (enabling simultaneous 

assessment of multiple variables and a wide variety of comparisons) to analyze potential 

moderation of effectiveness, by factors such as delivery personnel, effective community 

linkages, and demographic characteristics. Because of our focus on moderation of effectiveness 

for T2DM, we did not examine harms as we did for T1DM. This review provides information 

regarding the effectiveness and harms of behavioral programs (T1DM), and what combination of 

program components and delivery methods are most effective for implementation of these 

programs in community health settings (T2DM). 

Scope of Review and Key Questions

A member of the public nominated this topic; the nominator wanted to know whether there is 

a set of best practices associated with behavioral interventions for diabetes that could be 

replicated in community health centers in the United States. The nominator commented that 

while diabetes behavioral programs that promote self-management have demonstrated various 

benefits, the efforts of community health centers to improve their patients’ diabetes control have 

achieved poor results.

To address these issues, we conducted a systematic review and meta-analysis of the 

effectiveness of behavioral programs for diabetes. For the purpose of this review we developed 

an operational definition of behavioral programs that encompasses DSME (without or with an 

additional clinical, psychosocial, or behavioral support phase, i.e., “DSME plus support”) as well 

as other programs incorporating interactive components that target multiple behaviors (e.g., diet 

and physical activity) (see Appendix A). A commonality with all programs was that they 

incorporated one or more behavior change techniques,56 with or without an explicit use of a 

theory or model of behavior change. This definition focuses on programs, defined as “...a plan 

of action for an event or sequence of actions over a period that may be short or prolonged.... A 

health program is generally long term and often multi-faceted, whereas a health project is usually 

short-term and narrowly focused.”57 Our operational definition of a behavioral program is as 

follows. 

An organized, multicomponent diabetes-specific program with repeated interactions by 

one or more trained individuals, with a duration of ≥4 weeks, to improve disease control 

and/or patient health outcomes, and consisting of at least one of the following: (a) 

DSME; (b) a structured dietary intervention (related to any of the following: weight loss, 

glycemic control, or reducing risk for complications) together with one or more 

additional components; or (c) a structured exercise or physical activity intervention 

together with one or more additional components. Additional components for (b) and (c) 
5

may include interventions related to diet or physical activity; behavioral change 

(including but not limited to goal-setting, problem-solving, motivational interviewing, 

coping-skills training, cognitive behavioral therapy strategies); relaxation or stress 

reduction; blood glucose regulation; medication adherence; or self-monitoring for 

diabetic complications (foot, eye, and renal tests).

We include contact with those delivering the program, rather than relying solely on 

“interactive behavior change technology” (e.g., patient-centered websites, automated telephone 

calls, and touch screen kiosks). While these tools show great promise for helping health systems 

meet the growing demand for diabetes management and support, they have been shown to be 

most effective when they support human contact.58

We address the following six Key Questions (KQs):

Key Question 1. For patients with T1DM, are behavioral programs 

implemented in a community health setting effective compared with usual 

or standard care, or active comparators in—

a. Improving behavioral, clinical, and health outcomes?

b. Improving diabetes-related health care utilization?

c. Achieving program acceptability as measured by participant attrition 

rates? 

Key Question 2. For patients with T1DM, do behavioral programs 

implemented in the community health setting differ in effectiveness for 

behavioral, clinical, and health outcomes; their effect on diabetes-related 

health care utilization; or program acceptability for the following subgroups 

of patients?

a. Age—children and adolescents (≤18 years) and their families, young 

adults (19–30 years), adults (31–64 years), older adults (≥65 years) 

b. Race or ethnicity 

c. Socioeconomic status (e.g., family income, education level, literacy)

d. Time since diagnosis (≤1 year vs. >1 year) 

e. Baseline level of glycemic control (HbA1c <7% vs. ≥7%)

Key Question 3. For patients with T1DM, does the effectiveness of 

behavioral programs differ based on the following factors? 

a. Program components 

b. Intensity (i.e., program duration, frequency/periodicity of interactions) 

c. Delivery personnel (e.g., dietitian, exercise specialist, physician, 

nurse practitioner, certified diabetes educator, lay health worker) 
6

d. Method of communication (e.g., individual vs. group, face to face, 

interactive behavior change technology, social media) 

e. Degree of tailoring based on needs assessment (e.g., 

educational/behavioral deficits, age or other demographics, readiness 

to change) 

f. Level and nature of community engagement

Key Question 4. For patients with T1DM, what are the associated harms 

(i.e., activity-related injury) of behavioral programs implemented in a 

community health setting compared with usual care, standard care, or 

active comparators?

Key Question 5. Among behavioral programs targeted at adults with 

T2DM implemented in a community health setting, what factors contribute 

to (a) their effectiveness for behavioral, clinical, and health outcomes; (b) 

their effect on diabetes-related health care utilization; and (c) program 

acceptability as measured by participant attrition rates? Factors include the 

following: 

a. Program components 

b. Program intensity 

c. Delivery personnel 

d. Methods of delivery and communication 

e. Degree of tailoring 

f. Community engagement 

Key Question 6. Do the factors that contribute to program effectiveness for 

patients with T2DM vary across the following subpopulations? 

a. Age—young adults (19–30 years), adults (31–64 years), older adults 

(≥65 years) 

b. Race or ethnicity 

c. Socioeconomic status (e.g., family income, education level, literacy) 

d. Time since diagnosis (≤1 year vs. >1 year) 

e. Baseline level of glycemic control (HbA1c <7% vs. ≥7%)

Analytic Frameworks

We developed two analytic frameworks to guide the systematic review process. The figures 

illustrate the populations of interest and the outcomes that we reviewed. Figure 1 for T1DM 

notes four KQs. KQ 1, KQ 2, and KQ 4 address the potential benefits and harms of behavioral 
7

programs. The overarching boxes (components, program features) address KQ 3 related to how 

program components and features contribute to the effectiveness of behavioral programs. 

Figure 2 for T2DM notes KQ 5 and KQ 6 that address how program components and features 

contribute to the effectiveness of behavioral programs. 

Organization of This Report

The remainder of the report describes our methods in detail and presents the results of our 

synthesis of the evidence with key points and detailed syntheses. For KQ 1 we also present our 

assessment of the strength of evidence. The results section is organized by type of diabetes—

T1DM (KQs 1-4) and T2DM (KQs 5-6). The discussion section offers our conclusions, 

summarizes our findings, and provides other information relevant to the interpretation of this 

work for clinical practice and future research. References and a list of abbreviations and 

acronyms follow the discussion section.

The report includes a number of appendices to provide further detail on our methods, the 

studies assessed, and the results not presented in the text. There is also reference to a 

supplementary file which may be accessed for additional information on the methods for study 

selection and risk of bias assessment, and for the syntheses of outcomes for T2DM which were 

not directly applicable to our KQs. The appendixes and supplementary file are as follows: 

• Appendix A: Operational Definitions

• Appendix B: Literature Search Strategies 

• Appendix C: Very High Human Development Index Countries

• Appendix D: Studies Excluded After Full-Text Review

• Appendix E: Risk of Bias

• Appendix F: Description of Studies and Interventions

• Appendix G: Type 1 Diabetes Mellitus: Summary of Results From Observational Studies

• Appendix H: Strength of Evidence Tables for Type 1 Diabetes Mellitus

• Appendix I: Effectiveness Across Outcomes for Type 2 Diabetes Mellitus

• Appendix J: Network Meta-analysis Results for Glycemic Control and Age Subgroup 

Analyses 

• Supplementary File: Full Text Screening Form, Risk of Bias Tools, and Results of MetaAnalyses for T2DM Across Outcomes (available at http://srdr.ahrq.gov)
8

Figure 1. Analytic framework for behavioral programs for type 1 diabetes mellitus

HbA1c = hemoglobin A1c; KQ = Key Question
9

Figure 2. Analytic framework for behavioral programs for type 2 diabetes mellitus

HbA1c = hemoglobin A1c; KQ = Key Question
10

Methods

The methods for this review of behavioral programs for diabetes mellitus are based on the 

methods specified in the Agency for Healthcare Research and Quality (AHRQ) “Methods Guide 

for Effectiveness and Comparative Effectiveness Reviews” (Methods Guide).59 The main 

sections in this chapter reflect the elements of the protocol established for the review.

60 The 

methods and analyses were determined a priori, except where otherwise specified. 

Topic Refinement and Review Protocol

The Centers for Disease Control and Prevention (CDC) are partners with AHRQ in this 

review. During the topic development and refinement processes, we developed draft versions of 

the analytic frameworks, Key Questions (KQs), and inclusion/exclusion criteria in the form of 

PICOTS (populations, interventions, comparators, outcomes, timing, settings). The processes 

were guided by the information provided by the topic nominator, a scan of the literature, and 

discussions with methods and contents experts, and Key Informants (KIs); we worked with CDC 

and nine KIs during topic refinement. Subsequently, the analytic frameworks, KQs and PICOTs 

were posted for public comment on AHRQ’s Effective Health Care Web site from January 8 

through January 27, 2014. After consultation with AHRQ and responding to the public 

comments, we engaged representatives from CDC and a Technical Expert Panel (TEP)—

including two of the KIs—to develop the systematic review protocol. Conference calls and 

discussions through email were undertaken to review the analytic framework, KQs, PICOTS, 

and operational definition of a behavioral program (Appendix A), and to gain input on 

categorizing the interventions based on the various program components and delivery methods. 

The final protocol was posted on AHRQ’s Effective Healthcare Web site on June 12, 2014.60

The protocol was registered with the PROSPERO database (No. CRD42014010515) on July 11, 

2014. 

Literature Search Strategy

We used the same approach and search strategies for type one diabetes mellitus (T1DM) and 

type two diabetes mellitus (T2DM). Our research librarian searched the following databases 

from 1993 to May 2014: Ovid MEDLINE and Ovid MEDLINE® In-Process & Other NonIndexed Citations, Cochrane Central Register of Controlled Trials via Cochrane Library, 

EMBASE® via Ovid, CINAHL Plus with Full Text via EBSCOhost, PsycINFO® via Ovid, and 

PubMed® (2014 only) via the National Center for Biotechnology Information Databases. On 

January 15, 2015, we performed a search update in all databases except EMBASE, from which 

none of the previously included studies was exclusively obtained.

We limited the search to prospective controlled studies published in English. Search 

strategies included a combination of subject headings and keywords for diabetes, behavioral 

interventions, and diabetes education. We applied a validated search filter for randomized 

controlled trials (RCTs) and a search filter to identify prospective comparative studies.61 The 

search strategy was developed in MEDLINE, peer reviewed by a second librarian, and adapted to 

accommodate the controlled vocabularies and search languages of the other databases. Appendix 

B presents the full search strategy for each database. 

We reviewed the reference lists of relevant systematic reviews and of all included studies. 

We searched for trials in ClinicialTrials.gov and the World Health Organization International 

Clinical Trials Registry Platform. We hand searched the conference proceedings from the 
11

American Diabetes Association, American Association of Diabetes Educators, National Institute 

of Diabetes and Digestive and Kidney Diseases, Canadian Diabetes Association, European 

Association for the Study of Diabetes, International Diabetes Federation, Society of Behavioral 

Medicine, and International Society for Behavioral Nutrition and Physical Activity from 2011 to 

2014 (when available). When a trial protocol or abstract met our screening criteria, we searched 

online for associated publications and contacted the authors to enquire whether a report was 

available to undergo full-text screening.

We used EndNote® database (Thomson Reuters, New York, NY) to manage the results of our 

literature searches.

Inclusion and Exclusion Criteria

The eligibility criteria are outlined in the PICOTS for T1DM and T2DM for the KQs (Tables 

1 and 2). For both T1DM and T2DM, we included studies conducted in the United States or 

other high-income countries (Appendix C) and published in the English language.

62 We included

studies conducted in high-income countries because we believed that the results would be more 

relevant to community health settings in the United States. We included English-language 

publications because we believed it was unlikely that we would miss important data reported in 

non-English articles. The earliest publication date for studies was 1993. This date was chosen 

because of changes to usual care/medical management (the comparator in most cases in this 

review) resulting from the findings of landmark trials published from this date onwards.

20,29,63

For T1DM, we included prospective comparative studies (i.e., RCTs, nonrandomized 

controlled trials [non-RCTs], prospective cohort studies, controlled before-after studies).64 For 

T2DM we included RCTs. RCTs are the gold standard for determining the effectiveness of 

interventions particularly when there are multiple potential confounding patient and intervention 

factors that may bias the results.65 Our preliminary searches during topic refinement identified 

over 400 potentially relevant RCTs involving patients with T2DM and we believed that there 

would be sufficient trials and variability with respect to program factors to address the relevant 

KQs. We did not have a minimum sample size for inclusion, or a threshold for extent of 

incomplete followup or participant attrition. 

We included a broad range of comparators to behavioral programs and categorized them as 

follows. Usual (standard) care control arms consisted of usual medical management (often 

multidisciplinary and including some form of education) provided to all study participants 

regardless of study participation; this could be provided by the study investigators or other health 

care professionals. Because medical care is so diverse between settings, some study arms (i.e., 

receiving educational pamphlets or an individual session with a dietitian) were classified as usual 

care even when described by the authors as active control. Interventions that were offered for the 

purposes of the study and provided content addressing behavior changes, but did not meet our 

operational definition of a behavioral program, were considered active controls. Examples of 

active controls include a dietary intervention or a basic education program of short duration or

not including behavioral approaches. We categorized some control arms as attention control, 

when the group received similar contact time as the intervention arm but no intervention 

hypothesized to promote behavioral change. These arms were grouped with usual care arms for 

analysis and sensitivity analysis was conducted (i.e., removal of these arms) when the 

heterogeneity in the meta-analysis was substantial (see Data Synthesis). All trial arms that met 

our definition of a behavioral program were considered “interventions”; when two intervention 
12

arms were compared “head-to-head” we considered this to evaluate their comparative 

effectiveness.

To help distinguish between the effects of behavioral programs (targeting patient behaviors) 

and other interventions, we excluded studies where the intervention was a disease/care 

management program (e.g., consisting of one or more interventions actively adjusting diabetesrelated medications, monitoring patient medical data, or coordinating care provision)66 or other 

quality improvement programs that incorporate strategies targeting health systems or providers.67

This criterion was further refined after the protocol was published. Specifically, usual medical 

management (usual care) of all study participants needed to be stated by the authors or judged by 

the reviewers to be similar; for example, studies were excluded if the intervention arm(s) 

received stricter targets for glycemic control or more intensive medication regimes than the 

control arm. Additionally, studies investigating behavioral programs as one component of 

innovative medical care models (e.g. group appointments, pharmaceutical care) were only 

included if the effect of the behavioral program could be isolated. Other exclusion criteria 

included: (1) studies focusing exclusively on newly diagnosed patients, who do not represent our 

target population; (2) reports of studies where the outcomes were not of interest to this review 

(e.g., short-term effects on glucose sensitivity, C-reactive protein), or when the only difference 

between the study groups was a factor outside of the review’s scope (e.g., two intervention arms 

differing only by diet composition rather than delivery method, personnel etc.); (3) studies 

evaluating behavioral programs targeted at hospital inpatients; (4) studies evaluating communitybased programs that were not implemented in affiliation with a community health setting (e.g., 

school-based programs); (5) studies published exclusively in abstract form (e.g., conference 

abstracts). Where relevant abstracts were identified we searched for a complete report including 

contacting authors, as needed.
13

Table 1. Inclusion criteria for type 1 diabetes (Key Questions 1–4)

Parameter Criteria

Population • Patients with T1DM (any age) who have undergone basic diabetes education 

Interventions • Multicomponent behavioral program that includes at least one of:

- Diabetes self-management education; OR

- Structured dietary intervention (related to any of weight loss, glycemic control, or reducing 

risk for complications) together with one or more additional components; OR 

- Structured exercise/physical activity intervention together with one or more additional 

components.

- Additional components may include interventions related to: diet or physical activity, 

behavioral change (including but not limited to: goal setting, problem solving, motivational 

interviewing, coping skills training, cognitive behavioral therapy strategies), relaxation or 

stress reduction, blood glucose awareness, medication adherence, or self-monitoring for 

diabetic complications (foot, eye, and renal tests). 

• Repeated provision by one or more trained individuals

• Duration of intervention: minimum 4 weeks

Comparators • Usual or standard care (i.e., medical management provided to all study participants), an active 

control (i.e., intervention in addition to usual care but not meeting our operational definition of 

behavioral program), or another behavioral program

• Delivery methods (personnel, intensity, communication methods etc.) as reported for studies

Outcomes • Behavioral outcomes 

- Self-regulation of insulin based on diet, physical activity, and glucose monitoring results

- Change in physical activity (e.g., volume of activity per week) or fitness (e.g. 

cardiorespiratory fitness, strength)

- Change in dietary or nutrient intake (i.e., energy intake, saturated fat consumption)

- Adherence to treatment, including self-monitoring and medication

• Clinical outcomes

- Glycemic control (HbA1c) 

- Change in body composition (i.e., weight, BMI, waist circumference, % body fat)

- Episodes of severe hypoglycemia68

- Treatment for hyperglycemia (ketoacidosis)

- Control of blood pressure and lipids

- Development or control of depression or anxiety

• Health outcomes 

- Quality of life (e.g., validated tools for health-related quality of life, life satisfaction, 

psychosocial adaptation to illness, patient satisfaction)

- Development of micro- and macrovascular complications (i.e., retinopathy, nephropathy, 

neuropathy, cardiovascular outcomes)

- Mortality (all-cause)

• Diabetes-related health care utilization

- Hospital admissions

- Length of stay in hospital

- Emergency department admissions

- Visits to specialist clinics

• Program acceptability as measured by participant attrition rates 

• Harms from program as reported for studies

- Activity-related injury

Timing • Any length of postintervention followup

Study design • Prospective comparative studies using a best evidence approach based on hierarchy of 

evidence: randomized controlled trials, nonrandomized controlled trials, prospective cohort 

studies, controlled before-after studies

Settings • Community health setting (i.e. ambulatory care clinics, outpatient clinics, primary care clinics, 

family physician clinics, Community Health Centers, Rural Health Centers)

• United States or other high-income countries with a very high Human Development Index62

Language • English

BMI = body mass index; HbA1c = hemoglobin A1c; T1DM = type 1 diabetes
14

Table 2. Inclusion criteria for type 2 diabetes (Key Questions 5 and 6)

Parameter Criteria

Population • Adults (≥18 years) with T2DM who have undergone primary diabetes education

Interventions • Multicomponent behavioral programs that include at least one of:

- Diabetes self-management education; OR

- Structured dietary intervention (related to any of weight loss, glycemic control, or reducing 

risk for complications) together with one or more additional components; OR 

- Structured exercise/physical activity intervention together with one or more additional 

components.

- Additional components may include interventions related to: diet or physical activity, 

behavioral change (including but not limited to: goal setting, problem solving, motivational 

interviewing, coping skills training, cognitive behavioral therapy strategies), relaxation or 

stress reduction, blood glucose awareness, medication adherence, or self-monitoring for 

diabetic complications (foot, eye, and renal tests). 

• Repeated provision by one or more trained individuals

• Duration of intervention: minimum 4 weeks

Comparators • Usual or standard care (i.e., medical management provided to all study participants), an active 

control (i.e. intervention in addition to usual care but not meeting our operational definition of 

behavioral program), or another behavioral program

• Delivery methods (personnel, intensity, communication methods etc.) as reported for studies

Outcomes • Behavioral outcomes 

- Change in physical activity (e.g., volume of activity per week) or fitness (e.g., 

cardiorespiratory fitness, strength)

- Change in dietary or nutrient intake (i.e., energy intake, saturated fat consumption)

- Adherence to medication

• Clinical outcomes

- Glycemic control (HbA1c) 

- Change in body composition (i.e., weight, BMI, waist circumference, % body fat)

- Control of blood pressure and lipids

- Sleep apnea or sleep quality

- Development or control of depression or anxiety

• Health outcomes 

- Quality of life (e.g., validated tools for health-related quality of life, life satisfaction, 

psychosocial adaptation to illness, patient satisfaction)

- Development of micro- and macrovascular complications (i.e., retinopathy, nephropathy, 

neuropathy, cardiovascular outcomes)

- Mortality (all-cause)

• Diabetes-related health care utilization

- Hospital admissions

- Length of stay in hospital

- Emergency department admissions

- Visits to specialist clinics

• Program acceptability as measured by participant attrition rates

Timing • Any length of postintervention followup

Study design • Randomized controlled trials

Settings • Community health setting (i.e., ambulatory care clinics, outpatient clinics, primary care clinics, 

family physician clinics, Community Health Centers, Rural Health Centers)

• United States or other high-income country with a very high Human Development Index62

Language • English

BMI = body mass index; HbA1c = hemoglobin A1c; T2DM = type 2 diabetes

Study Selection

Two members of the research team independently screened all titles and abstracts (when 

available) using broad inclusion/exclusion criteria (Tables 1 and 2). We retrieved the full text of 

any publications marked for inclusion by either reviewer. Two reviewers independently assessed 

the full texts using a standard form that outlined the inclusion and exclusion criteria (see Figure 
15

S1 in the Supplementary File). The reviewers resolved any disagreements through consensus or 

by consulting a third member of the review team. 

We used an internally developed online tool to manage the title and abstract screening and 

full text review. The results from the full text review were then exported to an EndNote® 

database. We recorded the principal reason for excluding full text publications that did not 

satisfy the eligibility criteria.

Data Extraction

We extracted data directly into the Systematic Review Data Repository (SRDRTM). One 

reviewer extracted data, and a second reviewer checked the data for accuracy and completeness. 

We resolved disagreements through consensus or by consulting a third member of the review 

team. We extracted the following data: author identification, year of publication, source of 

funding, study design, population (i.e., inclusion and exclusion criteria, number of participants 

enrolled, study withdrawals, duration of followup), baseline characteristics (e.g., age, duration of 

diabetes, HbA1c, race/ethnicity, weight, body mass index), details of the interventions and 

comparators, and outcomes. When more than one publication reported the results of a single 

study, we considered the earliest published report of the main outcome data to be the primary 

publication. We extracted data from the primary publication first and then any additional data 

reported in the associated publications; this report cites all study results to the primary 

publication. We only extracted outcome data at or after the end-of-intervention timepoint; 

interim results prior to the end of any intervention contact were not included. We recorded 

intention-to-treat results, if possible. Other decision rules were developed for extraction of 

outcome data: 1) when both subjective and objective assessment was performed for change in 

dietary or nutrient intake, or physical activity (e.g., exercise duration/intensity via self-report and 

accelerometer) we only extracted the objective data; and 2) for clinical or health outcomes 

relying on questionnaires (e.g., depression, anxiety, quality of life) we only extracted data when 

composite or component scores were provided.

For studies where it was unclear whether patients had T1DM or T2DM, we developed

decision rules based on mean age of study population, duration of diabetes, and the description 

of medical management. In studies where both types of patients were included and results were 

not reported separately, if more that 75 percent were one type of diabetes we included the study 

with that disease group. 

Risk of Bias Assessment of Individual Studies 

Two reviewers independently assessed the risk of bias (ROB) of the included studies. 

Discrepancies were resolved through discussion and consensus.

We assessed the internal validity of RCTs and non-RCTs using the Cochrane Risk of Bias 

tool.69 The tool examines seven domains of potential bias (sequence generation, concealment of 

allocation, blinding of participants and personnel, blinding of outcome assessment, incomplete 

outcome data, selective outcome reporting, and “other” sources of data), and a categorization of 

the overall ROB.

Each domain was rated as having “low,” “unclear (medium),” or “high” ROB. We assessed

blinding and incomplete outcome data separately for subjective outcomes (e.g., quality of life) 

and objective outcomes (e.g., HbA1c); we only rated the ROB for those outcomes of interest to 

this review and on which we report. We reported additional sources of bias, including baseline 

imbalances and design-specific ROB, in the “other” sources of bias domain. 
16

We created decision rules for consideration of blinding of participants, personnel, and 

outcome assessors (see Figure S2 in the Supplementary File). Examples which met the criteria 

for low ROB for these domains include: 1) for participants, when the comparator was an 

attention control, active control, or another behavioral program, and the authors reported some 

mechanism for blinding the participants from the study hypothesis; 2) for personnel, if they 

followed a standard protocol and received structured training in program delivery; and 3) for 

outcome assessment, double blinding of participant and outcome assessor was deemed not 

necessary for subjective outcomes if the participants were blinded (as above) and independently 

completed questionnaires. 

The overall ROB assessment was based on the responses to individual domains. If one or 

more individual domains had a high ROB, we rated the overall score as high ROB. We rated the 

overall ROB as low only if all components were assessed as having a low risk. In all other 

situations, the overall ROB was rated as medium. 

We assessed the ROB for prospective cohort studies and controlled before-after studies using 

the Newcastle-Ottawa Scale (Figure S3 in Supplementary File).

70 This tool uses a star system to 

assess methodological quality across three categories: selection of participants, comparability of

study groups, and ascertainment of the outcome of interest. The star rating indicates the quality 

of a study with a maximum assessment of nine. If a study scored eight or nine, we rated the 

overall ROB as low. We rated the overall risk as medium if the score was between five and 

seven. For scores below five, the overall ROB was rated as high.

Data Synthesis

We analyzed data separately for T1DM and T2DM with different approaches for each KQ as 

outlined below. For each condition we summarized the characteristics of included studies 

qualitatively and presented important features of the study populations, interventions, and 

comparators in summary tables. Outcome data are reported in figures of meta-analyses (if 

pooled) and/or outcomes tables. We calculated mean differences (MD) or standardized mean 

differences (SMD) for continuous variables, and risk ratios (RR) for dichotomous data. The 

findings represent differences between the intervention and comparator arm. When possible we 

used (or computed) change from baseline data; otherwise final values were used. If standard

deviations were not given, they were computed from p-values, 95% confidence intervals (95% 

CIs), z-stats, or t-stats. If computation was not possible they were estimated from upper bound pvalues, ranges, inter-quartile ranges, or (as a last resort) by imputation using the largest reported 

SD from the other studies in the same meta-analysis. When computing standard deviations for 

change from baseline values, we assumed a correlation of 0.5, unless other information was 

present in the study that allowed us to compute it more precisely. Results are reported with 

accompanying 95% CIs. 

The focus of our analysis (and for determining which outcomes to grade for strength for 

evidence for KQs 1 and 2 [see relevant section in this chapter]) rested on outcomes we 

considered most clinically relevant or important to patients; we refer to these as “key outcomes”. 

Included in this category were all health outcomes (i.e., quality of life, development of microand macrovascular complications, all-cause mortality) and selected behavioral and clinical 

outcomes (i.e., glycemic control, adherence to diabetes self-management behaviors, change in 

body composition, change in physical activity or fitness, and change in dietary or nutrient 

intake). Where guidance from the literature was available, we defined a minimum clinically 

significant difference (i.e., the smallest difference between groups that can be considered 
17

clinically significant); we refer to this in the results and discussion chapters by commenting on 

whether results were clinically important. For HbA1c, we used a difference of 0.4 units in percent

HbA1c (e.g., 7.6% vs. 8.0% HbA1c), which is based on the value used by the U.S. Food and Drug 

Administration.68 For quality of life measures and other patient-reported outcomes represented 

by continuous data, we used a difference of one-half standard deviation (i.e., 0.50 SMD) based 

on the mean SD from the pooled studies, which has been shown to represent a universal, 

conservative estimate of a meaningful difference.71,72 For adherence to self-management 

behaviors, we did not apply a threshold for clinical importance because of poor reporting of the 

scoring and unknown meaning of a threshold for an optimal number of self-monitoring tests (the 

most common reporting for this outcome).

With input from the TEP, we categorized various components and delivery mechanisms (e.g., 

program intensity, method of communication, presence of community engagement) as outlined 

in Table 3. We separated DSME and DSME plus support into two categories to recognize that 

the support phase was often (1) of a lower intensity (i.e., less frequent contacts), and (2) focused 

on different content such as psychosocial support, as compared with the DSME phase. The cutpoints used for creating the intensity categories were based on practical considerations. The 10-

hour “minimal intensity” limit was based on the current number of hours billable for patients 

eligible for public healthcare administered by the Centers for Medicare and Medicaid Services in 

the United States; this was described by our TEP as an important practical limitation on 

implementing programs having higher intensity. The value of 27 hours was based on what would 

be considered the lower range of highly intense (e.g., at least weekly 1-hour sessions for 6 

months). The categories were used in the summary tables to describe the behavioral program(s) 

for each study, and for coding the variables used for the regression and network meta-analyses 

for KQs 3, 5, and 6 (described later in this section). For the network meta-analyses performed for 

KQs 5 and 6, the categories were used to define groups (nodes) of interventions that were 

“sufficiently similar” in terms of the factors of interest. Table 3 also indicates that actual values 

were used for program duration, intensity, and frequency of contacts where suitable (i.e., 

regression analyses for KQs 3 and 6). When calculating contact hours, we assumed telephone 

calls (when described in number and serving as more than a reminder/basic followup) would be 

10 minutes each if their duration was not reported; this was based on reviewing studies from our 

preliminary searches that indicated most followup calls were reported as approximately 15 

minutes (variable compliance) and that the duration of calls used for providing more substantial 

content were often not reported. Care was taken to avoid counting time/contacts required solely 

for research purposes (e.g., outcome assessment). Initially, the program components category 

included more items (i.e., diet plus additional component, physical activity plus additional 

component; see Appendix A for operational definitions) but because of very few studies 

evaluating these categories we collapsed all programs that were not DSME, or DSME plus 

support, into a “lifestyle” category largely containing programs focusing on diet and physical 

activity. 
18

Table 3. Categorization of program components and delivery factors

Program Factors Categories and Description Variables

Program Componentsa 1. DSME

2. DSME + Support: DSME plus a phase to extend program duration and provide 

support (often clinically focused but may be psychosocial, educational or 

behavioral)

3. Lifestyle programs: Behavioral programs focused on diet and/or physical activity 

rather than on diabetes-specific self-management behaviors; may also include 

other components as long as does not meet the criteria for DSME with emphasis 

on education/training

Duration of program No categories; duration (m) was used as a continuous variable for the regression 

analyses for KQs 3 and 6

Intensity of programcontinuousNo categories; intensity (h) was used as a continuous variable for the regression 

analyses for KQs 3 and 6

Intensity-categoricala

(contact hours; where 

contact hours could not be 

calculated, we used

number of contacts as a 

proxy)

1. ≤10h 

2. 11 to 26h (e.g., weekly for up to 6m) 

3. ≥27h (allowing for monthly followup for 1yr) 

Frequency of contacts No categories; this was a composite variable combining duration and intensity (h/m); 

the continuous variable was used for the regression analyses 

Method of communicationb 1. In person only

2. Mixture of in person and technology

3. All technology with minimal interaction with providers

Method of deliveryc 1. Individual

2. Mixed individual and group

3. Group

Delivery personneld 1. Delivered entirely by non-health professional (e.g., lay/community health worker, 

undergraduate students) after training and under some supervision

2. One health professional for large majority (>75%) of delivery 

3. Provision by multidisciplinary team of health professionals

Degree of tailoringe 1. None/Minimal – none or only small portion is tailored (e.g., personalized diet 

prescription in otherwise highly structured lifestyle program or delivery based on 

flexible hours but same content for all) 

2. Moderate/maximum – most of program has content and/or delivery tailoring (e.g., 

topics are based on needs assessment and delivery timing/duration/location is 

based participant’s schedule/needs/location preferences)

Level and nature of 

community engagement

1. Present, e.g., peer delivering program or peer support groups for support stage, 

use of community resources (infrastructure) for delivery or maintenance stages 

2. Absent, e.g., unreported or provision of information about community resources 

Presence of support 

personf

1. Family or parent involved in >1 session

2. No family or parent involvement in sessions

DSME = diabetes self-management education; h = hour; m = month; T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes 

mellitus; yr = year

a

For network meta-analysis only. b

2 and 3 were combined for analysis. c

1 and 2 were combined for analysis. d

2 and 3 were combined for analysis for KQ 5 and 6. e

Used in summary tables only. f

For studies of youth/adolescents only.
19

Synthesis for T1DM (KQs 1–4)

KQ 1: Behavioral Programs for T1DM and Behavioral, Clinical, and 

Health Outcomes; Diabetes-Related Health Care Utilization; and 

Program Acceptability

For each comparison of interest, we conducted a pairwise meta-analysis when two or more 

eligible trials were sufficiently similar on the basis of study design, clinical homogeneity of 

patient populations, interventions, comparators, outcomes, and timepoints. Because we assumed 

that behavioral programs for T1DM would be sufficiently different when developed for and 

studied in children and adolescents (“youth”) compared with adults, we present both pooled and 

subgroup analysis based on age when there was more than one trial in each age category at the 

relevant timepoint. We used the Hartung-Knapp-Sidik-Jonkman random effects model for all 

meta-analyses using Stata 11.2 and Excel 2010 software.73-75 We calculated pooled MD, SMD, 

or RR with corresponding 95% CIs, as appropriate and each weighted by sample size and 

variance. We analyzed outcomes at different postintervention timepoints using strata: end of 

active intervention-≤1month, 1-≤6 months, >6-12 months, >12-24 months, and >24 months. If a 

study included more than one followup timepoint in each strata, we used data from the longer

followup. We did not include the results of observational studies in any of the pooled analyses.

Sensitivity analyses (including leave-one-out analyses, assuming a fixed effects model, reanalyses after excluding a group of studies) were undertaken where appropriate (e.g., in the 

presence of studies with outlying effect sizes, for studies rated as high risk of bias in some 

domains such as incomplete [<70 percent] outcome data, to examine the effects from combining 

usual care and attention control groups). Heterogeneity was considered substantial when the I2

statistic (the proportion of variation in study estimates attributable to heterogeneity) was greater 

than 50 percent.76 We explored between-study heterogeneity using subgroup and meta-regression 

analyses where there were at least 10 studies.

77 Planned subgroups are listed in KQs 2 and 6.

Publication bias was assessed both visually and quantitatively using Egger’s test for the outcome 

with the greatest amount of data.

78

KQ 2: Subgroups for Effectiveness in T1DM 

For this KQ, we assessed the effects on subgroups for HbA1c, which was the outcome 

reported by the most studies. We searched for subgroup analyses reported by individual trials 

(i.e., within-study subgroups) that focused on whether a particular behavioral program was more 

or less effective based on age (children and adolescents [≤18 years], young adults [19-30 years], 

adults [31-64 years], older adults ≥65 years]), race or ethnicity, socioeconomic status, time since 

diagnosis (≤1 year vs. >1 year), and baseline level of glycemic control (HbA1c <7 vs. ≥7 

percent). We also considered the studies themselves as units for possible subgroup analysis—that 

is we performed between-study comparisons—for example when the mean age of participants 

fell within one of the age categories, or the majority (≥75 percent) of the participants were stated 

as racial/ethnic minorities (i.e., nonwhite but including Hispanic groups). 
20

KQ 3: Potential Moderation of Effectiveness for T1DM—Components, 

Intensity, Delivery Personnel, Method of Communication, Degree of 

Tailoring, and Level of Community Engagement 

To assess whether the effectiveness of behavioral programs differed based on various 

potential moderating factors, we performed univariate meta-regressions for comparisons between 

behavioral programs and usual care. We performed the analyses for HbA1c, which was the only 

outcome reported by at least 10 studies, and used data from each study’s longest followup 

timepoint. There were insufficient studies to perform multivariable analysis. The following 

covariates were considered: program duration, program intensity (contact time), frequency of 

contacts (contacts per month), delivery mode, delivery personnel, presence of supports (e.g.,

family members), and community engagement. Each behavioral program was coded using the 

categorization scheme in Table 3. 

KQ 4: Harms for T1DM

For harms (i.e., activity-related injury) we planned to descriptively summarize all outcomes 

presented in studies. We did not plan to conduct any quantitative analysis for this outcome. 

Synthesis for T2DM (KQs 5 and 6)

Before synthesizing findings to answer KQs 5 and 6, we performed pairwise meta-analyses 

for all outcomes identified in the PICOTS. This served to summarize the findings on outcomes 

not reported by enough studies to contribute to the analyses for KQ 5 or 6, and to provide 

information when interpreting the results of the subsequent analyses. We used the same 

analytical approach described for KQ 1. 

KQ 5: Potential Moderation of Effectiveness for T2DM—Components, 

Intensity, Delivery Personnel, Method of Communication, and Level of 

Community Engagement

Rather than providing a simple pairwise comparison of similar comparisons (e.g., a group of 

interventions versus usual care) through standard meta-analysis, a network meta-analysis allows 

for simultaneous evaluation of a suite of comparisons while still preserving the within-study 

randomization. A network of different comparisons is constructed (with “nodes” representing 

groupings of sufficiently similar interventions and comparators) to consider both direct evidence 

from comparisons of similar interventions/nodes and indirect evidence from comparisons where 

one intervention is in common, but not all (e.g., intervention A vs. usual care, and intervention A 

vs. intervention B infer knowledge about intervention B vs. usual care). Because numerous nodes 

can be created, this approach can be useful when a diverse range of interventions and 

comparators are being considered—the nuances of the various interventions can be captured.

The grouping of behavioral programs into nodes was based on the categories in Table 3. We 

also formed three categories for the comparator groups: usual care, active “non-DSME” control 

(i.e., basic education not meeting our criteria for DSME; see Appendix A), and active “other” 

control (e.g., stand-alone dietary or physical activity intervention). For the intervention arms 

(behavioral programs), we identified all plausible nodes differing by only one variable (e.g., a 

level within the intensity category) to assess the variation in effectiveness based on the potential 

moderating factors of interest for this review. We then coded all interventions and comparators 

into the various nodes; not all plausible nodes ended up containing data. The analysis was 
21

conducted for HbA1c and body mass index; because of the relatively low amount of outcome data 

for other key outcomes, only one or two variables could be considered and this was deemed to 

offer insufficient meaning.

The analysis was conducted using a Bayesian network model to compare all interventions 

simultaneously and to use all available information on treatment effects in a single analysis.79,80

These methods ensure that correlation in multi-armed trials is preserved. Mean differences were 

modeled using noninformative prior distributions. A normal prior distribution with mean 0 and 

large variance (10,000) was used for each of the trial means, whereas their between study 

variance had a uniform prior with range 0 to 2. These priors were checked for influence with 

sensitivity analyses. Markov Chain Monte Carlo simulations using WinBugs software were 

carried out to obtain simultaneous estimates of all interventions compared with placebo, as well 

as estimates of which interventions were the best. A burn-in sample of 20,000 iterations was 

followed by 300,000 iterations used to compute estimates. A sensitivity analysis that thinned the 

amount of used data to every tenth iteration was also conducted to check for proper chain 

convergence. The model formulation and WinBugs codes can be obtained at request of the 

authors. Analysis was checked for consistency by contrasting direct and indirect estimates in 

each triangular and quadratic loop using the methods described by Vernoiki.81 Results are 

presented as estimates of the treatment effects (MD) relative to usual care, 95 percent credibility 

intervals, as well as the rank probabilities for each behavioral program strategy (i.e., probability 

that a particular combination of components and delivery methods for a behavioral program is 

the “best program”). 

KQ 6: Subgroups for Factors Moderating Effectiveness in T2DM

This KQ focused on whether variability between population groups affected the role of 

potential factors contributing to effectiveness of behavioral programs for the key outcome 

reported by the most studies (i.e., HbA1c). Similar to KQ 2, we searched for subgroup analyses 

reported by individual trials that focused on whether a particular behavioral program was more 

or less effective in reducing HbA1c based on age (young adults [19-30 years], adults [31-64 

years], older adults ≥65 years]), race or ethnicity, socioeconomic status, time since diagnosis (≤1 

year vs. >1 year), and baseline level of glycemic control (HbA1c <7 vs. ≥7 percent). This 

approach did not yield any appropriate data. We then considered the studies themselves as units 

for possible subgroup analysis.

As a starting point, we conducted subgroup analyses of the pairwise meta-analysis results for 

HbA1c for behavioral programs compared with usual care and active controls at longest 

followup. When enough comparisons existed within an identified subgroup to maintain the 

structure of the network used for analysis of HbA1c for KQ 5, we then performed subgroup 

analysis of this network. This was possible for studies with baseline HbA1c ≥7 percent and with a 

mean participant age <65 years; the subgroups with baseline HbA1c <7 percent and age ≥65 years 

were too small for their own network analysis. For subgroups based on race/ethnicity (≥75 vs. 

<75 percent minorities), the number of trials in either subgroup was insufficient, so we 

conducted a set of univariate meta-regressions within each subgroup using the variables in Table 

3 and methods outlined for KQ 2. The number of studies did not allow for multivariable metaregressions using the number of variables of interest. 
22

Strength of the Body of Evidence

We followed the Methods Guide59 to evaluate the strength of evidence (SOE) for KQ 1 for 

all health outcomes (i.e., quality of life, development of micro- and macrovascular 

complications, all-cause mortality) and selected behavioral and clinical outcomes (i.e., glycemic 

control, adherence to diabetes self-management behaviors, change in body composition, change 

in physical activity or fitness, and change in dietary or nutrient intake). For KQ 2, we assessed 

SOE for HbA1c which was the outcome reported by the most studies and thus the focus of this 

KQ. SOE assessments were based on evidence from trials. The body of evidence was graded by 

one reviewer, and reviewed by a second reviewer. Disagreements were resolved through 

discussion or by consulting with a third reviewer, as needed.

We examined the five core domains most relevant to reviews of RCTs (anticipated to be the 

large majority of included studies): risk of bias, consistency, directness, precision, and reporting 

bias. We defined the risk of bias (low, medium, or high) on the basis of study design and 

methodological quality. We rated consistency (consistent, inconsistent, unknown [if there is only 

one study]) by assessing the direction and magnitude of the effects of the included studies. We 

assessed directness of the evidence (direct or indirect) on the basis of the use of surrogate 

outcomes or the need for indirect comparisons. We assessed precision (precise or imprecise) on 

the basis of the degree of certainty surrounding the effect estimate and based on sample size; for 

outcomes where clinically important thresholds were prespecified (i.e., HbA1c, HRQL, 

behavioral outcomes with continuous data), we downgraded the SOE twice for imprecision when 

the 95% CI crossed thresholds both for and against behavioral programs. A precise estimate is 

one that allows for a clinically useful conclusion. Reporting bias (suspected or unsuspected) was

evaluated with respect to publication bias, selective outcome reporting bias, and selective 

analysis reporting bias. For selective reporting and analysis biases, we evaluated the results 

across studies qualitatively on the basis of completeness of reporting for individual studies and 

reporting patterns across studies. We rated the body of evidence using four SOE grades which 

indicate our level of confidence that the evidence reflects the true effect for the major 

comparisons of interest:

• High. Very confident that the estimate of effect lies close to the true effect for this 

outcome. The body of evidence has few or no deficiencies; the findings are stable, i.e., 

another study would not change the conclusions. 

• Moderate. We are moderately confident that the estimate of effect lies close to the true 

effect for this outcome. The body of evidence has some deficiencies; the findings are 

likely to be stable, but some doubt remains. 

• Low. We have limited confidence that the estimate of effect lies close to the true effect 

for this outcome. The body of evidence has major or numerous deficiencies (or both); 

additional evidence is needed before concluding either that the findings are stable or that 

the estimate of effect is close to the true effect. 

• Insufficient. We have no (or very little) evidence, we are unable to estimate an effect, or 

we have no confidence in the estimate of effect for this outcome (i.e., the 95% CI of the 

effect estimate includes values representing clinically important magnitudes favoring 

both behavioral programs and the comparator).

We did not assess SOE for the KQs 3-6. KQ 4 assesses harms, which was a minor focus of 

this review. KQs 5 and 6 explore factors that may be associated with the effectiveness of 

behavioral programs; there is no precedent for SOE assessments for these types of questions. 
23

Applicability

We followed the Methods Guide to evaluate the applicability of the evidence to the delivery 

setting of interest (i.e., community health settings).59 We considered important population 

characteristics, behavioral program characteristics, and delivery settings that may limit 

applicability of the findings. Factors that may limit the applicability include narrow eligibility 

criteria, components or delivery elements of behavioral programs that may not be feasible in 

some settings, and health system differences.

Peer Review and Public Commentary

Experts in behavioral medicine, diabetes education, clinical epidemiology, nutrition, physical 

education, psychology, and statistics fields, and individuals representing stakeholder and user 

communities were invited to provide external peer review of this report; AHRQ and an associate 

editor also provided comments. The draft report was posted on the AHRQ website for 4 weeks to 

elicit public comment. We addressed all reviewer comments, revising the text as appropriate, and 

documented everything in a disposition of comments report that will be made available 3 months 

after the Agency posts the final report on the AHRQ Effective Healthcare website.
24

Results

This chapter begins with a summary of our literature search. We then present the findings 

separately for type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Within 

each section we present a general description of the included studies followed by our findings by 

Key Question (KQ). Specific details for the organization of the sections for T1DM and T2DM 

are included below.

Literature Search and Screening

Our database and gray literature searches identified 47,141 citations, and 11 additional 

records were identified from reference lists of systematic reviews and included studies. For 

T1DM, we included 34 studies described in 44 publications. For T2DM, we included 132 studies 

described in 161 publications. Figure 3 describes the flow of literature through the screening 

process. Appendix D provides a complete list of articles excluded at the full-text screening stage, 

with reasons for exclusion.

Figure 3. Flow diagram of study retrieval and selection

T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus

a

One study was included for both T1DM and T2DM.
25

Type 1 Diabetes Mellitus

This section begins with the results of our literature search, a general description of all 

included studies, separate summaries of studies that focused on youth followed by those that 

focused on adults, and a summary of the risk of bias (ROB) assessment. We then present results 

by KQ. We begin with results of behavioral programs compared with usual care, followed by 

studies comparing behavioral programs with an active control, and then by those comparing two 

or more behavioral programs (i.e., comparative effectiveness). The results are grouped first by 

outcome (e.g., HbA1c) and then by follow-up timepoint. For each outcome results are presented 

by age groups (youth and adults), where appropriate. We present results as mean differences 

(MD), standardized mean differences (SMD), or risk ratios (RR), with 95 percent confidence 

intervals (95% CI) in figures with meta-analyses or in summary tables. Where statistical 

heterogeneity was considered substantial (>50 percent) we report the I2 Statistic (I2%).

For each KQ, we give the key points and then present a detailed synthesis of the evidence. 

Appendix E (Table E2) includes the ROB assessments for each trial. Summary tables describing 

studies are found in Appendix F (Tables F1 and F2); they are organized alphabetically by author. 

For observational studies, we present a narrative summary of the results for HbA1c. Other 

outcomes from the observational studies are documented in Appendix G. For KQs 1 and 2, we 

summarize the strength of evidence (SOE) assessments, which are provided in detail in 

Appendix H.

Literature Search and Screening

For T1DM, we included 34 studies described in 44 publications (Figure 3). Primary reports 

were identified for 30 randomized controlled trials (RCT),

82-111 1 non-RCT,112 and 3 controlled 

before-after studies.113-115 Ten additional publications contributed information related to the 

study methodology, outcomes, or descriptions of the interventions.116-125 One of the studies 

included both T1DM (49 percent) and T2DM (51 percent) patients; results were reported for 

each patient group and the study is included in both T1DM and T2DM of this review.107

Characteristics of Included Studies

The majority of studies (30 trials, 2 observational studies) examined diabetes selfmanagement education (DSME); two studies (1 RCT,105 1 observational study114) focused on 

lifestyle programs (see Appendix A for operational definitions). For DSME, most trials (n=23) 

were two-arm trials comparing DSME to usual care. Three two-arm RCTs compared DSME to 

an active control.87,91,92 The active controls included telephone support87 and basic education.91,92

Three RCTs were three-arm trials with one having two active control arms107 and the other two 

each had a usual care and an active control arm.83,108 For one, the authors combined the usual 

care and active control arms.83 For the others, we analyzed the usual care and active control arms 

separately,

108 or combined the two active control arms.107,108 One RCT evaluated the comparative 

effectiveness of the same DSME program delivered in person compared with delivery by 

internet-based videoconferencing (SkypeTM).90 Two observational studies compared DSME with 

usual care.113,115

Both studies focusing on lifestyle programs compared them with usual care. One was a twoarm RCT105 and the other was an observational study.114
26

Youth

Clinical Trials

Twenty-three RCTs83-90,92,93,96-104,106,108,110,111 and six associated publications117-119,121,122,125

examined the effectiveness of behavioral programs among youth; only one study examined 

children, hence our use of the term youth to categorize these studies. Most RCTs were two-arm 

trials and focused on DSME compared with usual care. One RCT compared a DSME program 

delivered in person compared with delivery using Skype

90 and another compared delivery of 

DSME in person compared with a telephone support active control.

87 Two three-arm trials 

compared a DSME program with usual care and an active control (basic education 

program),

83,108 although the authors of one combined the two control groups for their analyses.83

Sixteen trials were conducted in the United States;83,84,86-88,90,92,96-100,103,104,108,110 six were conducted 

in Europe,

85,89,93,101,102,106 and one was conducted in Australia.111

The mean age of the youth participants ranged from 9.7–15.4 years (median=13.4). One 

study did not report age.97 The percentage of males ranged from 0–63 percent (median=47). The 

proportion of nonwhite participants was between 2–82 percent (median=23.5); nine trials did not 

present information on race or ethnicity.90,93,98-101,106,110,111 For most trials, the mean HbA1c was 

>7 percent and ranged from 7.4–15.7 percent (median=9.6 percent). One trial did not report 

absolute baseline HbA1c.

103

All trials in youth recruited patients/families from outpatient clinical settings providing usual 

care throughout the study period. Clinical settings mostly consisted of diabetes/endocrinology 

clinics located at university-affiliated hospitals, and care was commonly described to include 

quarterly clinic visits with a multidisciplinary team of providers offering education and 

additional consults as needed. One study’s usual care included eight visits over a one-year 

period.93 Some studies reported additional components including: regular adherence 

assessments,83,98 in-clinic goal setting and a daily phone hour with education provided between 

visits,87,88 access to an emergency hotline,89 and basic care coordination with clinic reminders 

and assistance with scheduling appointments.96,104 Three trials reported that usual care included 

more advanced education,87,88,108 and one multicenter trial’s exclusion criteria for study centers

included the availability of a group education program.85 

A basic description of the behavioral programs delivered to youth is provided in Appendix F 

(Table F1). Although all studies included in the review evaluated programs which, as reported, 

met our operational definition of a behavioral program, there was considerable diversity in terms 

of the program content and delivery. Some programs were designed to coincide with office/clinic 

visits; however, there was variability in the degree of integration with medical care and in 

program intensity. Some programs were fully integrated into the clinic visit and were delivered 

by the clinic’s health care personnel.93,101,102 Other programs were delivered by non-clinic staff 

(e.g., trained research assistant, internists) either prior to or after the patient was seen by the 

health care team.

83,92,96,98,104 One study combined in-clinic goal setting with automated weekly 

delivery of tailored education and support messages.89 Two office-based programs had relatively 

high intensity with more than 10 contacts.93,96 The majority of office-based programs were 

delivered to the family, with a focus on family teamwork, conflict, and coping.83,92,96,98,101,102,104

Programs that did not coincide with clinic/office visits largely consisted of weekly or monthly 

sessions incorporating various behavioral approaches such as problem-solving, coping, and 

empowerment training.84,86,97,99,100,103,106,110,111 Some also offered a more therapeutic approach 

together with some degree of self-management training (i.e., behavioral family systems 
27

therapy,90,99,108 motivational enhancement therapy combined with solution-focused therapy,85 and 

multisystemic therapy87,88). Many programs were targeted at adolescents,83,84,87-

90,92,93,97,99,102,103,106,108,110,111while others were tailored to children,100 or offered to mixed age 

groups.85,96,98,101,104 Below, we present a summary of the program delivery factors.

The total duration of the behavioral programs ranged from 1.2–25 months (median=5.6). The 

number of contact hours ranged from 1–48 hours (median=9.5). Four trials did not report enough 

information to calculate the number of contact hours.84,89,98,103

Five trials delivered the programs to youth only;84,86,89,103,106 16 delivered the programs to 

both youth and their parents or family members.83,85,87,88,90,92,93,96-102,104,108 Four trials delivered 

the program in person to groups of youth only,84,86,106,111 and two trials delivered the program to 

youth using a mix of in-person sessions supplemented by telephone calls103 or text messaging.89

Eight trials delivered the program in person to individual pairs of youth and family 

members.83,87,88,90,93,98,108,110 Six trials delivered the program in person to groups of youth and 

family members.85,97,100-102,106 Three trials delivered the program to individual pairs of youth and 

family members using a mix of in-person sessions supplemented by telephone calls.92,96,104 Two 

trials delivered the program to individuals using telehealth99 and Skype.90

For eight trials, the program was delivered by a single health care professional (e.g., nurse, 

psychologist, registered dietitian).84,86-88,90,106,110,111 Six trials engaged two or more health 

professionals,85,89,93,101,102,108 seven trials used non-health professionals (e.g., research assistants, 

health-related students or trainees),83,92,96,98,99,103,104 and one trial used a combination of a health 

professional and a trainee.97 One trial did not report this information.100

All of the behavioral programs had some degree of tailoring in terms of their content (e.g., 

individualized goal setting, topics based on age group) and/or delivery (e.g., coinciding with 

office visits, number of visits determined based on needs assessment). Several had a moderate–

to–high level of tailoring in both content and delivery.87,88,90,92,93,96,97,99,103,104,108,110 Four 

interventions included some degree of community engagement, including involvement of peers

and/or school personnel.85,87,88,90

Observational Studies

Two controlled before-after studies explored the effectiveness of behavioral programs 

delivered to youth and their parents or families. One study compared a DSME intervention with 

usual care;115 the other compared a lifestyle intervention with usual care.114

The study by Viner et al.115 was conducted in the United Kingdom. The target population 

was youth with poor glycemic control (HbA1c >8.5 percent). The mean ages were 13.0 and 13.1 

years for the intervention and control groups, respectively; mean HbA1c was 10.2 and 10.0 

percent for the intervention and control groups. The 1.5-month program was delivered in person 

to groups of youth (6 meetings) and, separately, to groups of parents (1 meeting). The program 

was based on motivational and solution-focused techniques, with elements of cognitive 

behavioral therapy. The content of the program was tailored to youth with adherence issues and 

also targeted changes at self-identified behaviors. No information was reported for community 

engagement.

The study by Thomas-Dobersen et al.114 examined a lifestyle program that targeted 

overweight adolescents; body mass index ranged from 22–36 kg/m2

. The study was conducted in 

the United States. The mean ages were 13.9 and 15.2 years and mean HbA1c was 12.2 and 13.1 

percent for the intervention and control groups, respectively. The 3-month program was 

delivered by a multidisciplinary team in person to groups of adolescents and, in separate group 
28

sessions, to their parents. Program content was tailored to adolescents with diabetes although 

there was minimal tailoring in the delivery of the structured group sessions. No information was 

reported for community engagement.

Adults

Clinical Trials

Seven RCTs82,91,94,95,105,107,109 with four associated publications,116,120,123,124 and one nonRCT112 examined the effectiveness of behavioral programs among adults. Two RCTs included 

participants with T2DM. One RCT presented results for HbA1c separately for T1DM and T2DM 

and is included in both sections of this report.107 The other study did not report results separately 

for T1DM or T2DM; however, the majority (>75 percent) of participants had T1DM so we have 

included it in this section of the report.95 Six trials focused on DSME compared with usual 

care,

82,94,95,105,109,112 two examined DSME compared with one91 or two107 active controls, and one 

compared a lifestyle intervention with usual care.105 Six of the trials were conducted in European 

countries,82,91,94,95,109,112 one was conducted in the United States,107 and one was conducted in 

New Zealand.105

The mean age of participants ranged from 30–49 years. The percentage of males ranged from 

35–62 percent. The proportion of nonwhite participants was between 4.5–25 percent in two 

trials;94,107 the other trials did not present information on race or ethnicity. For all trials, the mean 

HbA1c was >7 percent and ranged from 7.7–9.6 percent. The mean BMI ranged from 24.8–27.6 

kg/m2

; three trials did not report BMI.95,109,112

Similar to the trials in youth, usual care was usually provided by out-patient diabetes 

clinics/centers from which the participants were recruited. Usual care was not described by 

Karlsen et al.95 who took a different approach by recruiting survey respondents, and may have 

been diverse in the trial of Perry et al.105 which supplemented clinic recruitment with that from 

radio and newspaper advertisements. Visit frequency was described less often, but for half of the 

studies was biannually to quarterly.94,105,107,112 The usual care in one trial included provision of 

and training in a continuous glucose monitoring system.82 

A basic description of the behavioral programs delivered to adults is provided in Appendix F 

(Table F2). Several of the programs incorporated elements of cognitive behavioral 

therapy,82,94,95,107 with one combining cognitive behavioral therapy with motivational 

enhancement therapy.94 In one study authors described their program as taking an empowerment 

approach,91 another incorporated guided self-determination group training,109 and one offered 

self-management training using an ongoing self-help group style.112 The program presented by 

Amsberg et al.82 included a 9-month maintenance period during which telephone support calls 

were provided; this study also incorporated training using a continuous glucose monitoring 

system. Below, we present a summary of implementation factors.

The total duration of the behavioral programs ranged from 1.5–12 months (median=6 

months). The number of contact hours ranged from 9–52 hours (median=16). One trial included 

an intense phase (2 months) followed by a 9-month support period.82 Five trials delivered the 

program in person to groups of participants,91,95,107,109,112 two delivered the program in person to 

individuals,94,105 and one trial used a mix of individual and small group sessions that were 

delivered in person and by telephone.82 For three of the trials, the program was delivered by a 

single health care professional (i.e., nurse, registered dietitian, physician).91,94,112 Four trials 

engaged two or more health professionals,82,105,107,109 and one trial used a health care professional 
29

and a peer (with diabetes and trained in program delivery) who served as coleader. All reports 

described the programs to have a moderate-to-high degree of tailoring of content to the 

participants’ individual needs; fewer had mechanisms (e.g., telephone followup, collaborative 

delivery by professional and participants) to tailor the delivery of the program.82,95,109,112 One 

trial incorporated community engagement through the use of a peer coleader;95 the remaining 

trials either involved no community engagement or did not report this information.

Observational Studies

One controlled before-after study explored the effectiveness of a DSME program among 

adults (≤65 years) who were receiving intensive insulin therapy.113 The study was conducted in 

Italy. Baseline HbA1c was ≥7.5 percent in 59 and 63 percent of the intervention and control 

groups, respectively. The 4-month intervention was an education program including 

empowerment group teaching and situation simulation, and comprised eight 2-hour group 

sessions led by a physician or dietitian. There was some tailoring of the content towards patients 

receiving intensive therapy; no information was reported for community engagement.

Risk of Bias of Individual Studies

A summary of the ROB assessments for the 31 trials is presented in Figure 4; the consensus 

assessments in all domains for each study are presented in Appendix E. All trials were assessed 

as having a medium (unclear) or high overall ROB. For objective outcomes (e.g., HbA1c, weight), 

58 percent of trials had a medium ROB and 42 percent had a high risk. The assessment of high 

risk was largely driven by incomplete outcome data (i.e., loss to followup). For trials (n=22) 

reporting subjective outcomes of interest to this review (e.g., health-related quality of life 

[HRQL], patient-reported self-management behaviors), all but one trial had a high risk of bias 

(95 percent). This was primarily due to lack of blinding of participants, study personnel, and 

outcome assessors. 

The risk of bias for the three observational studies was assessed using the Newcastle Ottawa 

Scale. The study by Viner et al.115 was assessed as having medium ROB (seven stars out of a 

possible nine); the study by Forlani et al.113 was assessed as medium ROB (five stars); and the 

study by Thomas-Dobersen et al.114 was assessed as low ROB (eight stars). For all studies there 

was concern about the control of potential confounding variables including baseline HbA1c and 

socioeconomic status. For Forlani et al. and Viner et al. there were concerns about the 

representativeness of the exposed cohort.

Five studies (15 percent) received funding from industry; 26 (76 percent) received funding 

from non-industry sources (e.g., government or foundations). Funding was not reported by three 

(9 percent) studies. 
30

Figure 4. Risk of bias summary for trials of behavioral programs for type 1 diabetes

KQ 1. Behavioral Programs for T1DM and Behavioral, Clinical, 

and Health Outcomes; Diabetes-Related Health Care Utilization; 

and Program Acceptability

Key Points: HbA1c

• There was no significant difference (low SOE) in changes in HbA1c at the end of 

intervention between behavioral programs and usual care.

• Behavioral programs compared with usual care reduced HbA1c (moderate SOE) at 6-

month postintervention followup; the change was statistically significant but not 

clinically important. 

• There was no significant difference in reduction of HbA1c between behavioral programs 

and usual care at followup timepoints longer than 6 months. The SOE for these findings 

was low because of risk of bias and imprecise effect estimates; further, because the 95% 

CIs included our threshold for clinical importance (favoring behavioral programs) we 

cannot rule out benefit for behavioral programs.

• Behavioral programs compared with an active control reduced HbA1c to a statistically 

significant and clinically important (moderate SOE) degree at 6-month followup. 

• Compared with active controls, the estimates of effect for behavioral programs showed 

no significant difference in HbA1c at end of intervention and at 12-month followup. The 

SOE was low for both; risk of bias as well as imprecise effect estimates and inclusion of 

a clinically important benefit reduces confidence in their accuracy. 

Key Points: Other Clinical and Behavioral Outcomes 

• Participants receiving behavioral programs compared with usual care did not differ in 

terms of adherence to diabetes self-management at the end of intervention or 6-month 
31

followup (low SOE for both); there was insufficient SOE for longer followup and for all 

comparisons with active controls. 

• Few trials reported on change in body composition, physical activity or fitness, or change 

in dietary or nutrient intake.

• Few trials reported on symptoms of depression, or on episodes of severe hypo- or 

hyperglycemia.

• The SOE was insufficient to determine whether behavioral programs increased or 

decreased changes in body composition, physical activity or fitness, or dietary or nutrient 

intake.

Key Points: Health Outcomes 

• For participants receiving behavioral programs compared with usual care, there was no

difference in generic HRQL at the end of intervention (moderate SOE). Few trials 

reported on generic HRQL at longer followup timepoints.

• In comparisons with usual care, there was insufficient SOE to assess whether there was 

any effect on diabetes-specific HRQL at any timepoint, and low SOE of no difference for 

diabetes distress at end of intervention and 6-month followup. The 95% CIs for diabetes 

distress included our threshold for clinical importance such that we cannot rule out a 

favorable effect for behavioral programs.

• There were no data on HRQL for comparisons of behavioral programs with active 

controls. 

• No trials reported on micro- and macrovascular complications or on all-cause mortality.

Key Points: Diabetes-Related Health Care Utilization

• Few trials reported number of diabetes-related hospital admissions, emergency 

department admissions, or other measures of health care utilization.

Key Points: Program Acceptability

• There was a 21 percent increased risk of attrition for individuals receiving usual care 

compared with those receiving a behavioral program.

Detailed Synthesis

HbA1c: Behavioral Programs Compared With Usual Care 

Figures 5-7 present our meta-analyses and forest plots of trials reporting HbA1c stratified by 

age (youth and adults). A negative MD represents a greater reduction in percent HbA1c for the 

behavioral program compared with usual care. We present separate forest plots for different 

timepoints—end of intervention, 6-month postintervention followup, and 12-month 

postintervention followup. We provide a narrative summary of the four RCTs that reported 

outcomes for longer followup timepoints. 

At the end of intervention for youth and adults combined, our meta-analysis (16 trials, 1,155

subjects) found no difference in percent HbA1c between individuals receiving a behavioral 

program and those receiving usual care (MD, -0.11; 95% CI, -0.33 to 0.11).

82-84,89,93-

96,98,99,101,105,106,108,110,112 There was no difference between groups for youth (11 trials, 653

subjects)83,84,89,93,96,98,99,101,106,108,110 or for adults (5 trials, 502 subjects)82,94,95,105,112—MD = 0.00

(95% CI, -0.33 to 0.33) and MD = -0.28 (95% CI, -0.57 to 0.01), respectively.
32

At the end of 6-month postintervention followup for youth and adults combined, our metaanalysis (12 trials, 1,463 subjects) showed that HbA1c improved for persons who received a 

behavioral program compared with those receiving usual care (MD, -0.31 percent; 95% CI, -0.47

to -0.15).84,86,88,93,94,100,102-104,108,109,111 The reduction in HbA1c was not clinically important. For 

youth (10 trials, 1,213 subjects),84,86,88,93,100,102-104,108,111 the difference between groups was 

statistically significant, but it was not clinically important (MD, -0.28 percent; 95% CI, -0.51 to -

0.05). For adults (2 trials, 250 subjects), there was no difference between groups.94,109

At the end of 12-month postintervention followup for youth, our meta-analysis (7 trials, 

1,333 youth) found no difference in HbA1c between individuals receiving a behavioral program 

and those receiving usual care (MD, -0.22 percent; 95% CI, -0.49 to 0.05).83,85,102-104,108,111

Figure 5. Behavioral programs for type 1 diabetes compared with usual care: HbA1c at the end of 

intervention 

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation
33

Figure 6. Behavioral programs for type 1 diabetes compared with usual care: HbA1c at 6-month 

postintervention

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation 
34

Figure 7. Behavioral programs for type 1 diabetes compared with usual care: HbA1c at 12-month 

postintervention (youth only)

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation

Four studies provided data at longer followup timepoints (data not shown). Three RCTs (2 

youth,103,104 1 adult;94 671 subjects) reported data at more than 1 year, but less than 2 years; there 

was no difference in HbA1c between groups (MD, -0.40; 95% CI, -0.92 to 0.12). Two trials (1 

youth,85 1 adult;94 467 subjects) reported outcomes at 24 months and found no difference in 

HbA1c (MD, -0.08; 95% CI, -1.96 to 1.8).

One trial in adolescents did not report sufficient data to be included in our meta-analysis; the 

authors found no statistically significant difference between groups at 6-month followup.97

Three observational studies (2 youth,114,115 1 adult;113 148 subjects) provided data on HbA1c

at 12-month followup. One youth study (41 subjects) reported a statistically significant and 

clinically important improvement in HbA1c for the group receiving the behavioral program (MD, 

-1.2; 95% CI, -2.24 to -0.16).115 The other youth study (17 subjects) found no difference between 

groups (MD, 0.67; 95% CI, -1.47 to 2.81).114 The study that was conducted in adults (90 

subjects) reported a statistically significant and clinically important improvement in HbA1c for 

the group receiving the behavioral program (MD, -0.70; 95% CI, -1.31 to -0.09).113 These results 

should be interpreted with caution because of concerns with bias and confounding in 

observational studies; the only study assessed as having low risk of bias found no difference.114

HbA1c: Behavioral Programs Compared With Active Control

Figures 8-10 present our meta-analyses of trials reporting HbA1c for youth and adults in 

comparisons with active controls. We present the results by followup timepoint (end of 

intervention, 6-month followup, 12-month followup) and age group. One trial in adults was a 

three-arm trial comparing a behavioral program to two different active controls (didactic 

education to either groups or individuals); these arms were combined for the meta-analysis.107

At the end of intervention, our meta-analysis for youth and adults (4 trials, 419 youth87,92,108

and 110 adults107) found no difference between behavioral programs and active controls for 

HbA1c (MD, -0.32; 95% CI, -0.97 to 0.33). When examining the results by age subgroups, 
35

similar results were found for youth (MD, -0.33; 95% CI, -1.65 to 0.99; I2

=69%).

87,92,108 and 

adults (MD, -0.35; 95% CI, -0.81 to 0.11).107

At the end of 6 months postintervention, our meta-analysis for youth and adults combined (4 

trials [259 adults,91,107 208 youth92,108]) showed that HbA1c improved for those receiving a 

behavioral program compared with those receiving an active control (MD, -0.44; 95% CI, -0.69

to -0.19); this reduction in HbA1c is clinically important. For youth, the difference was not 

statistically significant (MD, -0.60; 95% CI, -2.56 to 1.36);92,108 for adults, the difference was not 

statistically significant and the effect size was not clinically important (MD, -0.38; 95% CI, -0.93

to -0.17).91,107

At the end of 12-month followup, our meta-analysis for youth and adults combined (3 trials 

[110 adults,107 195 youth92,108) found no difference in HbA1c (MD, -0.44; 95% CI, -1.04 to 0.16). 

For youth, the difference was statistically significant and clinically important (MD, -0.52; 95% 

CI, -1.04 to 0.00); the behavioral program studied by Weinger et al.,107 failed to demonstrate any 

difference (MD, -0.14; 95% CI, -0.61 to 0.33). 

Figure 8. Behavioral programs for type 1 diabetes compared with active control: HbA1c at end of 

intervention

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation
36

Figure 9. Behavioral programs for type 1 diabetes compared with active control: HbA1c at 6-month 

postintervention

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation

Figure 10. Behavioral programs for type 1 diabetes compared with active control: HbA1c at 12-

month postintervention 

CI = confidence interval; HbA1c = hemoglobin A1c; n = number of participants; SD = standard deviation
37

HbA1c: Comparative Effectiveness of Two Behavioral Programs

One RCT (72 youth) examined the same DSME program delivered in person compared with 

delivery by Skype.90 There was no difference in HbA1c between groups at the end of intervention 

(MD, -0.04; 95% CI, -0.87 to 0.79) or at 6-month followup (MD, -0.24; 95% CI, -1.10 to 0.62).

Adherence to Diabetes Self-Management: Behavioral Programs Compared 

With Usual Care

This section presents the results from trials that reported on adherence to diabetes selfmanagement. This outcome was measured in a number of ways and we report them separately. 

The most common measure was self-monitoring of blood glucose (SMBG) and was most 

commonly reported as the frequency of blood glucose testing over 1 day.84,86,88,96,104 Two studies 

reported the frequency of testing over the past week;93,109 we converted this to the number of 

tests per day. We present separate forest plots for different timepoints (end of intervention, 6 

month followup). We provide a narrative summary of the one RCT that reported outcomes for 

longer followup. 

At the end of intervention (Figure 11), our meta-analysis (4 trials, 282 youth) found no 

difference in frequency of SMBG between youth receiving a behavioral program and those 

receiving usual care (MD, 0.15; 95% CI, -0.54 to 0.84).84,88,93,96

Figure 11. Behavioral programs for type 1 diabetes compared with usual care: self-monitoring of 

blood glucose (tests per day) at end of intervention

CI = confidence interval; n = number of participants; SD = standard deviation

At the end of 6-month postintervention for youth and adults combined (Figure 12), our metaanalysis (5 trials [4 youth,84,86,88,93 1 adult109], 252 subjects) found no difference in SMBG

between individuals receiving a behavioral program and those receiving usual care (MD, 0.40; 

95% CI, -0.36 to 1.16). Adults receiving the behavioral program in the trial of Zoffmann et al.109

increased their frequency of SMBG (MD, 1.42; 95% CI, 0.11 to 2.75).
38

Figure 12. Behavioral programs for type 1 diabetes compared with usual care: self-monitoring of 

blood glucose (tests per day) at 6-month postintervention

CI = confidence interval; n = number of participants; SD = standard deviation

One trial (390 youth) reported SMBG at 24-months postintervention.104 The results showed 

individuals receiving the behavioral program performed more poorly than those receiving usual 

care (MD, -0.36; 95% CI, -0.69 to -0.03). 

Two trials in adults measured adherence of blood glucose testing using an item from the 

Summary of Diabetes Self-Care Activities (SDSCA) questionnaire.

126 This self-report measure 

assesses the number of days in the previous week that SMBG was practiced. At the end of 

intervention one trial (74 adults) found that those in the behavioral program reported performing 

SMBG 1.4 days (95% CI, 0.35 to 2.43) more than those receiving usual care.82 At 6-month 

postintervention, one trial (244 adults) found no difference between groups (MD, -0.06; 95% CI,

-0.60 to 0.48).94

Four trials in youth used the Diabetes Self-Management Profile (DSMP)127 to assess 

adherence to the diabetes regimen at different timepoints. At the end of intervention, Wysocki et 

al.108 (54 youth) reported a clinically important improvement in the overall DSMP score for 

those who received the behavioral program compared with those receiving usual care (MD, 5.00; 

95% CI, 0.60 to 9.40). This difference had disappeared by 12-month postintervention. Two 

studies assessed adherence at 6-month postintervention followup; we did not pool the results as 

the studies reported different summary measures. In 2012, Nansel et al.104 (390 youth) found no 

difference between groups (MD, 1.31; 95% CI, -1.12 to 3.74). In an earlier study, Nansel et al.103

(81 youth) reported the proportion of adherence to an optimal diabetes regimen using the 

modified DSMP. They found no difference between groups (MD, -0.03; 95% CI, -0.06 to -0.01). 

The fourth study reported that there was no difference between groups on the DSMP at end of 

intervention; however, the authors did not provide any data.99
39

Two trials reported on adherence to medication. One trial (190 youth) used a questionnaire 

item to assess the number of times youth skipped an insulin dose in the past month.85 The authors 

reported that the odds of skipping one or more doses compared with no doses of insulin at 12-

month followup was 0.82 (95% CI, 0.48 to 1.38) and at 24-month followup was 1.30 (95% CI, 

0.78 to 2.17) for the group receiving the behavioral program. One trial in adults (74 adults) used 

the medication item of the Diabetes Self-Care Inventory128 and found no difference at the end of 

intervention between those receiving the behavioral program and those receiving usual care 

(MD, 0.22; 95% CI, -0.60 to 1.04).82

Adherence to Diabetes Self-Management: Behavioral Programs Compared 

With Active Control

One trial (149 adults) found no difference in frequency of SMBG between groups at 6-

months postintervention (MD, -0.20; 95% CI, -0.76 to 0.36).91 The same trial measured 

adherence to several diabetes self-care activities using the SDSCA and found no difference 

between groups at 6-month postintervention (MD, 0.00; 95% CI, -0.35 to 0.35).91

One trial (54 youth) used the DSMP to assess adherence to the diabetes regimen.108 At the 

end of intervention and 12-month followup, Wysocki et al.108 found no difference between the 

group that received the behavioral program compared with those receiving an active control—

MD = 2.40 (95% CI, -2.46 to 7.26) and MD = 2.00 (95% CI, -3.78 to 7.78), respectively). 

One trial (149 youth)92 used the Diabetes Behavior Rating Scale, which reflects the 

frequency of routine diabetes care behaviors over the previous week.129 No data were provided; 

however, the authors reported that at end of intervention, and 6- and 12-month followup, those 

receiving the behavioral program performed more poorly that than those in the active control

group.

Adherence to Diabetes Self-Management: Comparative Effectiveness of Two 

Behavioral Programs

One RCT (71 youth) studied the same DSME program delivered in person compared with 

delivery by Skype.90 The authors used the DSMP to assess adherence and found no difference 

between the groups at the end of intervention or at 6-month followup (MD, 0.85; 95% CI, -4.56 

to 6.26 and MD, 0.74; 95% CI, -4.97 to 6.45, respectively).

Other Clinical and Behavioral Outcomes 

Table 4 summarizes the results for other clinical and behavioral outcomes. For most 

outcomes results were reported in single trials. 
40

Table 4. Other clinical and behavioral outcomes for type 1 diabetes

Outcome Timepoint

# Trials (# 

Subjects, Control 

Group)

Study Effecta Conclusion

Change in body 

composition (BMI

[kg.m-2])

EOI 1 (60 youth, UC)89 MD, 0.08; 95% CI, -0.35 to 0.51 No difference

Change in body 

composition (BMI

[kg.m-2])

6m followup 1 (227 adults, 

UC)94 MD, -0.21; 95% CI, -0.62 to 0.20 No difference

Change in body 

composition (kg)

EOI 1 (61 adults, 

UC)105 MD, -0.50; 95% CI, -5.69 to 4.69 No difference

Change in physical 

activity 

(intensity/duration)

EOI 2 (17 youth, 73 

adults, UC)82,84 SMD, 0.16; 95% CI, -0.25 to 0.57 No difference

Change in physical 

activity 

(intensity/duration)

6m followup 2 (17 youth, 255 

adults, UC)84,94 SMD, -0.26; 95% CI, -1.00 to 0.49

No difference

Change in physical 

activity (fitness [VO2

max])

EOI 1 (43 adults, 

UC)105 MD, 0.59; 95% CI, 0.22 to 0.96 Improved with behavioral 

program

Change in dietary or 

nutrient intake (% 

saturated fat)

EOI 1 (61 adults,

UC)105 MD, -1.80; 95% CI, -3.53 to -0.07 Improved with behavioral 

program

Change in dietary or 

nutrient intake

(energy [kcal/day])

EOI 1 (61 adults, 

UC)105 MD, -247.10; 95% CI, -281.7 to -212.5

Improved with 

behavioral 

program

Severe hypoglycemia 

(# episodes needing 

3rd party assistance)

EOI 1 (60 youth, UC)

89 MD, -1.02; 95% CI, -2.16 to 0.11 No difference

Severe hypoglycemia 

(# episodes needing 

3rd party assistance)

6m followup 1 (160 adults, 

AC)

91 MD, -0.10; 95% CI, -0.48 to 0.28 No difference

Severe hypoglycemia 

(# episodes needing 

3rd party assistance)

6m followup 1 (227 adults, 

UC)

94 MD, -0.62; 95% CI, -1.61 to 0.37 No difference

Severe hypoglycemia 

(# episodes needing 

3rd party assistance)

12m followup 1 (295 youth, 

UC)

102 MD, -0.05; 95% CI, -0.22 to 0.12 No difference

Severe hypoglycemia 

(# episodes needing 

3rd party assistance)

>12m 

followup

1 (343 youth, 

UC)85 RR, 0.55; 95% CI, 0.10 to 2.97 No difference

Diabetic ketoacidosis 

(requiring treatment)

EOI 1 (61 youth, UC)

89 MD, -0.38; 95% CI, -1.43 to 0.67 No difference

Diabetic ketoacidosis 

(requiring hospital 

admission)

12m followup 1 (295 youth, 

UC)

102 MD, 0.01; 95% CI, -0.09 to 0.11 No difference

Diabetic ketoacidosis 

(requiring hospital 

admission)

>12m 

followup

1 (343 youth, 

UC)85 RR, 0.96; 95% CI, 0.72 to 1.27 No difference

HDL cholesterol

(mmol/l)

EOI 1 (61 adults, 

UC)105 MD, 0.10; 95% CI, -0.06 to 0.26 No difference

LDL cholesterol

(mmol/l)

EOI 1 (61 adults, 

UC)105 MD, -0.20; 95% CI, -0.67 to 0.27 No difference

Systolic blood 

pressure (mmHg)

EOI 1 (61 adults, 

UC)105 MD, -2.00; 95% CI, -11.25 to 7.25

No difference
41

AC = active control; BMI = body mass index; CI = confidence interval; EOI = end of intervention; m = month; MD = mean 

difference; QOL = quality of life; SMD = standardized mean difference; UC = usual care a

Negative values of MDs or SMDs are favorable for change in body composition, change in dietary intake, severe hypoglycemia, 

diabetic ketoacidosis, LDL cholesterol, systolic blood pressure, triglycerides, and depression. 

Health-Related Quality of Life: Behavioral Programs Compared With Usual 

Care

Studies reporting on HRQL assessed this using generic and diabetes-specific quality of life 

measures. Generic HRQL was measured by a number of tools (e.g., World Health Organization 

Well-Being Index,130 Pediatric Quality of Life [PedsQL],

131 Wellbeing Questionnaire132), as was 

diabetes-specific HRQL (PedsQL diabetes module,131 Pediatric Diabetes Quality of Life, Wellbeing Enquiry for Diabetes133). A group of studies reported on diabetes distress/stress (tools 

included Problem Areas in Diabetes134 and Diabetes Stress Questionnaire84), for which we 

analyzed separately from diabetes-specific HRQL. For all analyses we present the results as 

SMD. Figure 13 presents our meta-analyses of trials, stratified by age (youth and adults), that 

reported generic HRQL at end of intervention. Longer-term followup results were reported for 

generic HRQL and are summarized in Table 5. The meta-analysis results in Figure 14 for 

diabetes-specific HRQL at end of intervention were not stratified by age. Figures 15 and 16 

present the meta-analyses for diabetes distress at end of intervention (stratified by age) and 6-

month followup, respectively. 

At the end of intervention for youth and adults combined (Figure 13), our meta-analysis (7

trials [5 youth,93,96-98,110 2 adult82,95], 474 subjects) found no difference in generic HRQL between 

individuals receiving a behavioral program and those receiving usual care (SMD, 0.10; 95% CI, -

0.18 to 0.38). The lack of difference remained for the subgroups of adults (2 trials, 137 subjects; 

MD, 0.35; 95% CI -1.93 to 2.63)82,95 and youth (5 trials, 337 subjects; MD, 0.01; 95% CI -0.33 

to 0.35).

93,96-98,110

Table 4. Other clinical and behavioral outcomes for type 1 diabetes (continued)

Outcome Timepoint

# Trials (# 

Subjects, Control 

Group)

Study Effecta Conclusion

Triglycerides (mmol/l) EOI 1 (61 adults, 

UC)105 MD, 0.00; 95% CI, -0.39 to 0.39 No difference

Depression

(Swedish Hospital 

Anxiety and 

Depression scale)

EOI 1 (74 adults, 

UC)82 SMD, -0.51; 95%CI, -0.97 to -0.05

Improved with 

behavioral 

program

Depression

(Patient Health 

Questionnaire-9)

6m followup 1 (235 adults, 

UC)94 SMD, 0.20; 95% CI, -0.05 to 0.46 No difference

Depression

(Center for 

Epidemiologic Studies 

Depression Scale)

6m followup 1 (149 adults, 

AC)91 SMD, -0.30; 95% CI, -0.63 to 0.02

No difference
42

Figure 13. Behavioral programs for type 1 diabetes compared with usual care: generic healthrelated quality of life at end of intervention

CI = confidence interval; n = number of participants; SD = standard deviation

Three RCTs in youth reported on generic HRQL for longer followup timepoints (Table 

5).85,93,98 There was no difference in HRQL between groups at any of the timepoints. 

Table 5. Behavioral programs for type 1 diabetes compared with usual care: generic health-related 

quality of life at 6-, 12-, and 24-month postintervention

Timepoint # Trials (#Subjects) Study Effect Conclusion

6m followup 1 RCT (53)93 SMD, -0.29; 95% CI, -0.83 to 0.26 No difference

12m followup 2 RCTs (405)85,98 SMD, 0.02; 95% CI, -0.11 to 0.15 No difference

24m followup 1 RCT (291)85 SMD, -0.04; 95% CI, -0.27 to 0.19 No difference

CI = confidence interval; m = month; RCT = randomized controlled trial; SMD = standardized mean difference

Diabetes-specific HRQL was reported by three trials at the end of intervention (Figure 14). 

Our meta-analysis of these trials (2 youth,97,110 1 adult,112 212 subjects) found no difference 

between behavioral programs and usual care (SMD, 0.08; 95% CI, -1.44 to 1.60; I

2

=73%). One 

observational study in adults (90 subjects) found no difference between groups at 12-months

postintervention (SMD, 0.03; 95% CI, -0.39 to 0.45).113
43

Figure 14. Behavioral programs for type 1 diabetes compared with usual care: diabetes-specific 

health-related quality of life at end of intervention

CI = confidence interval; n = number of participants; SD = standard deviation; Std = standardized

Distress/stress was reported for six trials; negative scores represent reduced distress. At end 

of intervention (Figure 15), our meta-analysis for youth and adults combined (4 trials [2 

youth,84,93 2 adults82,95], 209 subjects) found no statistically significant difference in diabetes 

distress for behavioral programs compared with usual care (SMD, -0.31; 95% CI, -0.83 to 0.21). 

Stratified by age, there was no difference for the studies of youth (SMD, -0.21; 95% CI, -2.84 to 

2.60) or adults (SMD, -0.41; 95% CI, -3.78 to 2.96; I2= 57%). At 6-month followup for youth 

and adults combined (4 trials [3 youth,84,93,111 1 adult109], 236 subjects), changes to diabetes 

distress did not differ for behavioral programs compared with usual care (SMD, -0.28; 95% CI, -

0.94 to 0.38) (Figure 16).
44

Figure 15. Behavioral programs for type 1 diabetes compared with usual care: diabetes 

distress/stress at end of intervention

CI = confidence interval; n = number of participants; SD = standard deviation; Std = standardized

Figure 16. Behavioral programs for type 1 diabetes compared with usual care: diabetes distress at 

6-month postintervention followup

CI = confidence interval; n = number of participants; SD = standard deviation; Std = standardized
45

Health-Related Quality of Life: Behavioral Programs Compared With Active 

Control

One trial in youth failed to demonstrate a difference in diabetes-related quality of life

between a behavioral program and an active control at 12-month followup (130 subjects; 

insufficient data reported to calculate SMD).92

Diabetes-Related Health Care Utilization: Behavioral Programs Compared 

With Usual Care

Diabetes-related health care utilization was reported infrequently and only for trials 

comparing behavioral programs to usual care. We summarize the results in Table 6. One RCT in 

youth found a reduced risk of diabetes-related hospital admissions at end of intervention and at 

6-month followup for those receiving behavioral programs compared with usual care.88 The 

same trial also reported fewer admissions to the emergency department at the end of 

intervention. Another RCT in youth85 and one in adults94 found no difference in hospital

admission at any timepoint. One trial reported that there was no difference in the number of 

diabetes-related hospital and emergency department admissions at the 6-month followup; 

however, the authors did not provide any data.97

Table 6. Behavioral programs for type 1 diabetes compared with usual care: diabetes-related 

health care utilization at end of intervention, 6-, 12-, and 24-month postintervention followup

Outcome Timepoint # Trials 

(#Subjects) Study Effect Conclusion

Hospitalizations

(# admissions)

EOI 1 (95 youth)88 RR, 0.28; 95% CI, 0.15 to 0.55 Lower risk of admissions 

for behavioral program 

Hospitalizations

(# admissions)

6m followup 1 (98 youth)88 RR, 0.41; 95% CI, 0.21 to 0.78 Lower risk of admissions 

for behavioral program 

Hospitalizations

(# admissions)

24m followup 1 (343 youth)85 RR, 0.78; 95% CI, 0.45 to 1.34 No difference

Hospitalizations

(# admissions)

EOI 1 (159 adults)94 RR, 1.88; 95% CI, 0.49 to 7.25 No difference

Hospitalizations

(# admissions)

6m followup 1 (198 adults)94

RR, 0.90; 95% CI, 0.35 to 2.32 No difference

Emergency Dept 

(# admissions)

EOI 1 (98 youth)88 MD, -0.21; 95% CI, -0.34 to -

0.08

Fewer admissions for 

behavioral program 

CI = confidence interval; EOI = end of intervention; m = month; MD = mean difference; RR = risk ratio

Program Acceptability: Behavioral Programs Compared With Usual Care

Figure 17 presents our meta-analysis stratified by age (youth and adults) of trials that 

reported participant attrition at their longest followup timepoint. Our meta-analysis (21 trials, 

2,503 subjects) found a 21 percent increased risk of attrition for individuals receiving usual care 

compared with those receiving the behavioral program (RR, 1.21; 95% CI, 1.05 to 1.39).82-

86,88,89,93-95,99,100,102-106,108-111
46

Figure 17. Behavioral programs for type 1 diabetes compared with usual care: participant attrition

CI = confidence interval; n = number of participants

Program Acceptability: Behavioral Programs Compared With Active Control

Three RCTs (218 youth87,108 and 160 adults91) compared behavioral programs with active 

comparators. The pooled analysis (data not shown) found no difference between the groups for 

participant attrition (RR, 1.05; 95% CI, 0.46 to 2.4). 

Program Acceptability: Comparative Effectiveness of Two Behavioral

Programs

One RCT (72 youth) compared the same DSME program delivered in person compared with 

delivery by Skype.90 There was no difference between the groups in participant attrition (RR, 

0.55; 95% CI, 0.28 to 1.11).

Summary of Key Findings and Strength of Evidence for KQ 1

There was moderate SOE showing differences in HbA1c at 6-month postintervention 

followup with greater reduction in HbA1c for individuals who were enrolled in behavioral 

programs compared with those receiving usual care (Table 7). For other timepoints, there was 

low SOE for no significant difference in HbA1c. At followup greater than 6 months, the 
47

estimated effects were imprecise and because the 95% CIs included our threshold for clinical 

importance we cannot rule out benefit for behavioral programs. There was low SOE showing no

difference in adherence to diabetes self-management at end of intervention and 6-month 

followup. There was moderate SOE of no difference at the end of intervention for generic 

HRQL, and low SOE of no difference for diabetes distress at end of intervention and at 6-month 

followup. The 95% CIs for diabetes distress included our threshold for clinical importance such 

that we cannot rule out a favorable effect for behavioral programs. There was insufficient SOE

for diabetes-related HRQL, and for outcomes related to changes in body composition, physical 

fitness, and dietary intake.

Table 7. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with usual care

Outcome Outcome 

Timing

# Trials

(# Subjects); Tool if 

Applicable

Mean Difference or Standardized 

Mean Differencea Strength of 

Evidence

HbA1c EOI 16 (1,155)82-84,89,93-

96,98,99,101,105,106,108,110,112 MD, -0.11; 95% CI, -0.33 to 0.11 Low for no

significant 

difference

HbA1c 6m followup 12 

(1,463)84,86,88,93,94,100,102-

104,108,109,111

MD, -0.31; 95% CI,-0.47 to -0.15 Moderate 

for benefitb

HbA1c 12m 

followup 

7 (1,333)83,85,102-104,108,111 MD, -0.22; 95% CI, -0.49 to 0.05 Low for no

significant

difference

HbA1c >12m 

followup 

4 (1,138)

85,94,103,104 MD, -0.40; 95% CI, -0.92 to 0.12 

(>12m, <24m)

MD, -0.08; 95% CI, -1.96 to 1.8 

(≥24m)

Low for no

significant

difference

Adherence to 

diabetes selfmanagement 

EOI 4(282);84,88,93,96 SMBG

(tests per day; higher 

better)

1 (74);82 SDSCA (days 

per week)

1 (54);108 DSMP (higher 

scores better)

1 (74);82 DSCI (higher 

scores better)

MD, 0.15; 95% CI, -0.54 to 0.84 

MD, 1.4; 95% CI, 0.35 to 2.43

MD, 5.00; 95% CI, 0.60 to 9.40

MD, 0.22; 95% CI, -0.60 to 1.04

Low for no

significant

difference 

Adherence to 

diabetes selfmanagement 

6m followup 5 (252);84,86,88,93,109 SMBG 

1 (244);94 SDSCA

2 (471);103,104 DSMP

MD, 0.40; 95% CI, -0.36 to 1.16

MD, -0.06; 95% CI, -0.60 to 0.48

No difference (different measures)

Low for no 

significant 

difference

Adherence to 

diabetes selfmanagement 

12m 

followup 

1 (54);108 DSMP

1 (180);85 skipping one or 

more doses in past month

MD, 4.00; 95% CI, -1.69 to 9.69

OR, 0.82; 95% CI, 0.48 to 0.1.38

Insufficient

Adherence to 

diabetes selfmanagement 

>12m 

followup 

1 (390); SMBG 104

1 (190);85 skipping one or 

more doses in past month

MD, -0.36; 95% CI, -0.69 to -0.03 

(≥24m)

OR, 1.30; 95% CI, 0.78 to 2.17

(24m)

Insufficient

Change in body 

composition (BMI

[kg.m-2])

EOI 1 (60)

89 MD, 0.08; 95% CI, -0.35 to 0.51 Insufficient

Change in body 

composition (BMI)

[kg.m-2])

6m followup 1 (227)94 MD, -0.21; 95% CI, -0.62 to 0.20 Insufficient

Change in body 

composition (kg)

EOI 1 (61)105 MD, -0.50; 95% CI, -5.69 to 4.69 Insufficient
48

Table 7. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with usual care (continued)

Outcome Outcome 

Timing

# Trials

(# Subjects); Tool if 

Applicable

Mean Difference or Standardized 

Mean Differencea Strength of 

Evidence

Change in 

physical activity 

(fitness – VO2

max) 

EOI 1 (43)105 MD, 0.59; 95% CI, 0.22 to 0.96 Insufficient

Change in 

physical activity 

(intensity/duration)

EOI 2 (91)

82,84 SMD, 0.16; 95% CI, -0.25 to 0.57 Insufficient

Change in 

physical activity 

(intensity/duration)

6m followup 2 (272)

84,94 SMD, -0.26; 95% CI, -1.00 to 0.49 Insufficient

Change in dietary 

or nutrient intake 

(energy [kcal/day]) 

EOI 1 (61)

105 MD, -247.10; 95% CI, -281.7 to -

212.5

Insufficient

Change in dietary 

or nutrient intake 

(% saturated fat) 

EOI 1 (61)

105 MD, -1.80; 95% CI, -3.53 to -0.07 Insufficient

Generic HRQL EOI 7 (474)82,93,95-98,110 SMD, 0.10; 95% CI, -0.18 to 0.38 Moderate 

for no 

significant 

difference 

Generic HRQL 6m followup 1 (53)

93 SMD, -0.29; 95% CI, -0.83 to 0.26 Insufficient

Generic HRQL 12m

followup

2 (405)

85,98 SMD, 0.02; 95% CI, -0.11 to 0.15 Insufficient

Generic HRQL ≥12m

followup

1 (291)

85 SMD, -0.04; 95% CI, -0.27 to 0.19 Insufficient

Diabetes-specific 

quality of life

EOI 3 (212)97,110,112 SMD, 0.08; 95% CI, -1.44 to 1.60 Insufficient

Diabetes distress EOI 4 (209)82,84,93,95 SMD, -0.31; 95% CI, -0.83 to 0.21 Low for no 

significant 

difference

Diabetes distress 6mo 

followup

4 (236)84,93,109,111 SMD, -0.28; 95% CI, -0.94 to 0.38 Low for no

significant

difference

BMI = body mass index; CI = confidence interval; DSCI = Diabetes Self Care Inventory; DSMP = Diabetes Self-Management 

Profile; EOI = end of intervention - <1 month followup (interventions lasted 1.5-25 months); HbA1c = hemoglobin A1c; 

HRQL = health-related quality of life; kcal=kilocalories; m=month; MD = mean difference; SDSCA = Summary of Diabetes 

Self-Care Activities; SMBG = self-monitoring of blood glucose; SMD = standardized mean difference a

Negative values are favorable for MDs or SMDs for HbA1c, change in body composition, change in dietary intake, and diabetes 

distress. 

b

This point estimate did not meet threshold for clinical significance, although the 95% CI included clinically important 

difference.

There was moderate SOE showing differences in HbA1c at 6-month postintervention 

followup with a clinically important reduction in HbA1c for individuals who were enrolled in 

behavioral programs compared with those receiving an active control (Table 8). At end of 

intervention and 12-month followup, there was low SOE showing no difference in HbA1c; 

because the 95% CIs included our threshold for a clinically important effect, we cannot rule out a 

benefit for behavioral programs. There was insufficient evidence for adherence to diabetes selfmanagement at any followup timepoint.
49

Table 8. Type 1 diabetes: summary of key findings and strength of evidence for behavioral 

programs compared with an active control

Outcome Outcome 

Timing

# Trials (# 

Subjects) Mean Differencea Strength of Evidence

HbA1c EOI 4 

(529)87,92,107,108 MD, -0.32; 95% CI, -0.97 to 0.33 Low for nosignificant

difference

HbA1c 6m followup 4 

(467)91,92,107,108 MD, -0.44; 95% CI, -0.69 to -0.19 Moderate forbenefit

HbA1c 12m followup 3 (305)92,107,108 MD, -0.44; 95% CI, -1.04 to 0.16 Low for no 

significant 

difference

Adherence to diabetes 

self-management 

EOI 1 (54);108

DSMP (higher 

scores better)

1 (149);92

DBRS (higher 

scores better)

MD, 2.40; 95% CI, -2.46 to 7.26

No data reported; those in behavioral 

program did more poorly 

Insufficient

Adherence to diabetes 

self-management 

6m followup 1 (149);91

SMBG (tests 

per day; 

higher better)

1 (149);92

DBRS

MD, -0.20; 95% CI, -0.76 to 0.36

No data reported; those in behavioral 

program did more poorly

Insufficient

Adherence to diabetes 

self-management 

12m followup 1 (54); DSMP

1 (149);92

DBRS

MD, 2.00; 95% CI, -3.78 to 7.78

No data reported; those in behavioral 

program did more poorly

Insufficient

CI = confidence interval; DBRS = Diabetes Behavior Rating Scale; DSMP = Diabetes Self-Management Profile; EOI = end of 

intervention; HbA1c = hemoglobin A1c; m = month; MD = mean difference; SDSCA = Summary of Diabetes Self-Care 

Activities; SMBG = self-monitoring of blood glucose; SMD = standardized mean difference a

Negative values are favorable for HbA1c.

KQ 2. Subgroups for Effectiveness in T1DM 

This KQ evaluated whether behavioral programs differed in effectiveness for subgroups of 

patients with T1DM. For this question, we searched for subgroup analyses reported by individual 

trials that focused on whether a particular program was more or less effective in reducing HbA1c

(the outcome reported by the most studies) based on age (children and adolescents [≤18 years], 

young adults [19-30 years], adults [31-64 years], older adults ≥65 years]), race or ethnicity, 

socioeconomic status, time since diagnosis (≤1 year vs. >1 year), and level of glycemic control 

(HbA1c <7 vs. ≥7 percent). We also looked at subgroups at the study level, for example when the 

mean age of participants fell within one of the age categories, or the majority (≥75 percent) of 

the participants was stated as racial/ethnic minorities. We evaluated the SOE for the subgroups 

based on age (Figures 5-10); insufficient data were reported or available for other subgroups.

Key Points 

• Based on between-study results for comparisons with usual care, results were consistent 

with the general trend when looking at all studies. At 6 months, behavioral programs 

reduced HbA1c in studies of youth by a statistically significant 0.28 percent and in studies 

of adults by a non-statistically significant 0.38 percent. At end of intervention, the point 

estimates indicated greater benefit for adults (0.28) than youth (0.00), although neither of 

these values reached statistical significance. None of the point estimates exceeded the a 

priori established clinically important difference of 0.4 percent HbA1c. 
50

• The effectiveness of behavioral programs compared with active controls appeared higher 

for youth than for adults at12-month followup; the effectiveness for youth was clinically 

important. The small number of studies in most subgroups provided insufficient SOE.

• One trial reported results separately for youth with baseline HbA1c≥8 percent and found 

favorable results for this subgroup. 

• No trials reported on HbA1c by race or ethnicity, socioeconomic status, or time since 

diagnosis.

Detailed Synthesis

Age

In KQ 1, we presented our results by age groups (youth and adults). Behavioral programs 

appeared to be more effective in reducing HbA1c for adults than for youth at end of intervention 

when compared to usual care (Figure 5); the effect size in the meta-analysis for adults82,94,95,105,112

was greater in absolute terms than for the youth83,84,89,93,96,98,99,101,106,108,110 (MD = -0.28 vs. 0.00 

respectively); the results for adults approached statistical significance and the 95% CI contained 

our threshold for clinical importance. At 6-month followup, the effect sizes for 

youth84,86,88,93,100,102-104,108,111 and adults94,109 appeared similar (MD = -0.28 vs. MD = -0.38, 

respectively); only the results for youth reached statistical significance, although the 95% CIs in 

both groups included a clinically important effect size favoring behavioral programs. No study in 

adults reported at 12-month followup; the youth results showed no difference (MD, -0.22; 95% 

CI, -0.49 to 0.05) although the 95% CI included a clinically important effect for behavioral 

programs.

When compared with active controls at end of intervention, the effect sizes for youth (MD, -

0.33; 95% CI -1.65 to 0.99) and adults (MD, -0.35; 95% CI -0.81 to 0.11) were both similar to 

the overall effect size and nonsignificant with imprecise 95% CIs. At 6-month followup, the 

effect size was larger for the youth92,108 than for the adults91,107 (MD -0.60 vs. -0.38) but both 

results failed to reach statistical significance. At 12-month followup, results for youth were 

statistically significant and clinically important (MD, -0.52; 95% CI, -1.04 to 0.00);92,108 for 

adults there was no difference at 12-month followup (MD, -0.14; 95% CI, -1.28 to 1.00).107. 

In the studies that included adults only, the mean age across the studies ranged from 30.3–

49.2 years. None of the studies reported results separately for young adults or older adults. 

Level of Glycemic Control

One RCT (101 youth) conducted a subgroup analysis of 54 youth with suboptimal baseline 

glycemic control (HbA1c ≥8 percent).96 At the end of intervention, Katz et al.96 found that those 

receiving the behavioral program had greater odds of maintaining or improving their HbA1c

compared with those receiving usual care (odds ratio, 3.4; 95% CI, 1.0 to 11.9). This compares 

favorably to the overall study results which found no difference in change in glycemic control 

for the group receiving the behavioral program (MD, 0.30; 95% CI, -0.22 to 0.82). No data were 

reported for the subgroup of youth with optimal baseline HbA1c. Subgroup analysis at the study 

level was not conducted because the mean baseline HbA1c was >7 percent for all studies. 

Other Subgroups

No data were reported for any of our other pre-specified subgroups: race or ethnicity, 

socioeconomic status, or time since diagnosis.
51

Summary of Key Findings and Strength of Evidence for KQ 2

At end of intervention, there was low SOE of no significant difference for both youth and 

adults, but the effect size appeared greater for adults, approached statistical significance, and its 

95% CI included a clinically important value favoring behavioral programs (Table 9). The 

pooled effect estimate for youth was precise, but there was inconsistency in the individual study 

results with clinically important effects both for and against behavioral programs. Similar to the 

SOE when combining studies of youth and adults at 6-month followup (KQ 1), there was 

moderate SOE showing greater reduction in HbA1c for youth attending behavioral programs 

compared with usual care. The SOE for adults was low for no difference due to high risk of bias 

and imprecision (related to low sample size); nevertheless, the 95% CI included a large effect 

size suggesting there may be some benefit. There were no changes to the SOE at 12-month 

followup because of the lack of adult studies reporting this data.

Table 9. Type 1 diabetes: summary of key findings and strength of evidence for subgroups (by 

age) receiving behavioral programs compared with usual care

Outcome # Trials (# Subjects) Mean Difference Strength of Evidence

Youth

HbA1c (EOI) 11 

(653)83,84,89,93,96,98,99,101,106,10

8,110

MD, 0.00; 95% CI -0.33 to 0.33 Low for no significant 

difference

HbA1c (6m) 10 (1,213)84,86,88,93,100,102-

104,108,111 MD, -0.28; 95% CI -0.51 to -0.05 Moderate for benefita

HbA1c (12m) 7 (1,333)83,85,102-104,108,111 MD, -0.22; 95% CI -0.49 to 0.05 Low for no significant 

difference

Adults

HbA1c (EOI) 5 (502)82,94,95,105,112 MD, -0.28; 95% CI -0.57 to 0.01 Low for no significant 

difference

HbA1c (6m) 2 (250)94,109 MD, -0.38; 95% CI -0.82 to 0.06 Low for no significant 

difference

HbA1c (12m) NR NR Insufficient

CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; m = month; MD = mean difference a

This point estimate did not meet threshold for clinical significance, although the 95% CI included clinically important 

difference.

For subgroups based on age in comparisons with active controls, the small number of studies 

(and sample sizes) led to wide pooled 95% CIs which in some cases included values of clinical 

importance both for and against behavioral programs; because of these factors, the SOE was 

graded as insufficient in all but two cases (Table 10). In studies of youth with followup to 12 

months, there was low SOE of a clinically important benefit for behavioral programs; in studies 

of adults with 6-month followup, there was low SOE for no difference in HbA1c.
52

Table 10. Type 1 diabetes: summary of key findings and strength of evidence for subgroups (by 

age) receiving behavioral programs compared with active controls

Outcome # Trials (# Subjects) Mean Difference Strength of Evidence

Youth

HbA1c (EOI) 3 (419)87,92,108 MD, -0.33; 95% CI -1.65 to 0.99 Insufficient

HbA1c (6m) 2 (208)92,108 MD, -0.60; 95% CI -2.56 to 1.36 Insufficient

HbA1c (12m) 2 (195)92,108 MD, -0.52; 95% CI -1.04 to 0.00 Low for benefit

Adults

HbA1c (EOI) 1 (110)107 MD, -0.35; 95% CI -0.81 to 0.11 Insufficient

HbA1c (6m) 2 (259)91,107 MD, -0.38; 95% CI -0.93 to 0.17 Low for no difference

HbA1c (12m) 1 (110)107 MD, -0.14; 95% CI -1.04 to 0.16 Insufficient

CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; m = month; MD = mean difference

KQ 3. Potential Moderation of Effectiveness for T1DM: 

Components, Intensity, Delivery Personnel, Method of 

Communication, Degree of Tailoring, and Level of Community 

Engagement 

To assess whether the effectiveness of behavioral programs differed based on various 

program factors (i.e., intensity, delivery personnel, method of communication, degree of 

tailoring, and level of community engagement), we performed univariate meta-regressions for 

comparisons between behavioral programs and usual care at longest followup (Table 11). See 

Table 3 in Methods for our classification scheme. See the Characteristics of Included Studies 

section for a summary, and the description of interventions for each study in the summary tables 

in Appendix F. 

We did not have enough studies to conduct a multiple variable meta-regression analysis, nor 

were there sufficient studies for analysis of those comparing behavioral programs with active 

controls or other behavioral programs. We conducted the analysis for HbA1c; other outcomes did 

not have sufficient studies (≥10 studies) associated with them to support meaningful analyses. 

All but one study105 fell under the category of DSME, therefore we did not conduct a regression 

analysis on program components. 

Key Points

• Program intensity, including duration, contact hours, and frequency of contacts, appeared 

not to influence program effectiveness; the results were not statistically significant but 

were very precise (i.e., narrow 95% CIs) for no incremental effect when increasing 

intensity. 

• Although not reaching statistical significance, delivery of programs to individuals 

appeared beneficial compared with delivery to groups. 

Detailed Synthesis

Table 11 summarizes the results of the univariate meta-regressions conduced with 25

studies.82-86,88,89,93-96,98-106,108-112 Duration of intervention (months), intensity (contact hours) and 

frequency of contacts were analyzed as continuous variables. Frequency of contacts is a 

composite variable combining duration and contact hours (contact hours per month). The 

delivery personnel variable had three categories. The remaining variables were dichotomized as 

shown in Table 11. The analysis for support persons assessed the impact of programs targeted at 

youth alone compared with those targeted at both youth and their parents or families; adult 
53

studies82,94,95,105,109,112

were not included in this analysis. The results indicated that the variables 

of duration, contact hours, and contact frequency appear not to influence program effectiveness; 

the coefficients are essentially zero (e.g., an additional month of program duration would not 

reduce HbA1c to any greater extent) and the 95% CIs are very precise without any indication of 

potentially producing a clinically important effect considering our threshold of 0.4. Delivery to 

individuals appears to be beneficial compared with delivery to groups (i.e., positive coefficient 

indicating switching to group delivery increased HbA1c); the result approached statistical 

significance and the 95% CI included a value meeting our threshold for clinical importance. 

Evidence was insufficient for other program factors; the lack of reporting for community 

engagement precluded any interpretation of the results.

Table 11. Results from univariate meta-regressions analyzing the association between different 

program factors and the effectiveness of behavioral programs in improving HbA1c for T1DM

Program Factors # Studies Coefficient and 95% CI P value

Duration of intervention (continuous: months) 25 0.01; 95% CI, -0.01 to 0.03 0.462

Intensity (continuous: contact hours) 25 -0.01; 95% CI, -0.02 to 0.01 0.269

Frequency (continuous: hours/month) 25 -0.02; 95% CI, -0.06 to 0.03 0.508

Method of communication (dichotomous: in-person/ 

mix of in-person & technology)

25 -0.02; 95% CI, -0.30 to 0.26 0.885

Delivery method (dichotomous: individual/ group) 25 0.22; 95% CI, -0.03 to 0.46 0.084

Delivery personnel (3 categories)

Non-health professionals only

One health professional 

Multidisciplinary team

25

-0.12; 95% CI, -0.48 to 0.23

-0.053; 95% CI, -0.39 to 0.28

-0.16; 95% CI, -0.42 to 0.095

0.479

0.745

0.203

Community engagement (dichotomous: present/none 

or NR)

25 -0.31; 95% CI, -0.65 to 0.025 0.068

Support person present (dichotomous: yes/no) 19 -0.04; 95% CI, -0.40 to 0.33 0.843

CI = confidence interval; NR = not reported

KQ4. Harms for T1DM

No studies reported on the associated harms (i.e. activity-related injury) of behavioral 

programs.

Type 2 Diabetes Mellitus

This section begins with a description of the results of our literature search and screening, a 

general description of the included RCTs and the behavioral programs investigated, and a 

summary of our ROB assessment. We follow this by presenting an overview on the effectiveness 

of behavioral programs for key outcomes, and then presenting the results for KQs 5 and 6. The 

results on effectiveness are grouped by outcome category (i.e., clinical, behavioral, and health) 

and then by comparison group (i.e., usual care, active control, and other interventions 

[comparative effectiveness]), and postintervention followup timepoint. For this section, results 

are presented as MD, SMD, or RR, with associated 95% CIs. Where statistical heterogeneity was

considered substantial (>50 percent) we report the I2 Statistic (I2

%). For results on KQs 5 and 6 

for which we performed network meta-analysis, we describe the creation of groups (nodes) of 

interventions, and present the results including the MD and associated 95 percent credibility 

intervals, the rank order of each node, and a percentage referring to the node’s “probability of 

being best” (PB). The analysis for KQ 6 also included a set of univariate meta-regressions; we 

present these results in a summary table. 
54

For each KQ, we provide key points and then present a detailed synthesis of the evidence. 

Table E2 in Appendix E includes the ROB assessments for each RCT. A summary table 

describing the studies and interventions is included in Appendix F (Table F3). Appendix I 

contains summary tables of the effectiveness for all outcomes of behavioral programs compared 

with usual care (Table I1), active controls (Table I2), and other behavioral programs (Table I3). 

The results for the network meta-analyses for HbA1c in the subgroup analyses for KQ 6 are 

found in Appendix J. The Supplementary File includes figures (forest plots) of pairwise metaanalyses between behavioral programs and usual care and active control groups, for all outcomes 

across all timepoints where more than one study reported findings. 

Literature Search and Screening

For T2DM, we included 132 primary reports of RCTs,107,135-265 and 29 associated 

publications266-294 (including one abstract)293 providing information related to the study 

methodology, outcomes, or description of the interventions (Figure 3). One of the studies was 

also included in the section on T1DM because it provided data on HbA1c outcomes separately for 

T1DM and T2DM.107

Characteristics of Included Studies

The majority of RCTs were two-arm trials with the following comparisons: 1) DSME with 

usual care (55 trials)135,136,138-143,147,149,153,155,158,162,163,171,173,176-179,183,187,193-197,203,206,211,213,215,218-

220,223-226,228,229,231,233,235,238,242,245-247,253,257-260 or an active control (7 trials),146,154,181,182,198,201,202 2) 

DSME and support with usual care (8 trials)151,189,207,208,210,216,217,222 or with an active control (1 

trial),164 3) lifestyle programs with usual care (18 trials)137,143,145,157,160,167,190,205,236,239,240,249,251,

254,255,261-263 or an active control (7 trials),156,161,165,166,169,186,252 and, 4) between two behavioral 

programs (21 trials).144,150,152,159,170,172,180,185,188,199,204,209,212,221,232,237,243,244,248,250,256,264 Thirteen 

three-arm RCTs were included, with eight comparing behavioral programs with usual 

care,188,200,214,234,241 or active control,168,192,230 and five having one intervention arm compared 

with two controls.107,174,175,184,265 Three four-arm trials148,191,227 examined (1) two lifestyle 

programs compared with two dietary interventions,148 (2) one lifestyle program compared with 

two active controls (dietary and physical activity interventions) and a usual care arm,191 and (3) 

the comparative effectiveness between DSME and three DSME and support programs delivered 

by different personnel.227 Trials were conducted in 16 countries but the majority (63 percent) 

were undertaken in the United States. The primary reports of nine RCTs (7.3 percent) were 

published prior to the year 2000,137,140,159,165,204,213,232,245,251 and 57 (46 percent) were published 

since 2010.107,135,139,146,148,152-155,162,164,167,168,170-173,175,179,181,182,191,193,194,198,199,201,202,206-211,214,216-

219,221,224,227,228,233,234,236,237,240-242,244,247-249,252,253,256

The mean age of the participants was between 45 and 72 years (median=58). Six studies did 

not report age.139,160,193,224,242,245 The percentage of males ranged from 0–100 percent (median=40 

percent). The proportion of nonwhite participants was between 0 and 100 percent; the majority 

(≥75 percent) of participants in 32 trials reported nonwhite race/ethnicity,137,141,143,151,153,162,171,179,

188,189,195,197,205-208,210,215-219,222,228,229,231,233,240,246,247,257,262 and 9 trials included few (<10 percent) 

people of nonwhite race /ethnicity.149,183-185,212,239,249,251,256 Baseline HbA1c was between 6.3 and 

12.3 percent (median=8 percent); five trials did not report this information.138,238,242,245,251 Median 

duration of diabetes was 8.1 years (range 1-18 years). The median percentage of participants 

prescribed treatment with insulin was 19.5 percent; one study assessed the effectiveness of a 

lifestyle program in a sample of patients who were all initiated on insulin therapy,145 and another 
55

studied a DSME program in patients receiving ongoing intensive insulin treatment.181 Body mass 

index ranged from 23.8–39.1 kg/m2 (median=33.0 kg/m2).

Table F3 in Appendix F includes details on each behavioral program studied. Several trials 

evaluated more than one behavioral program; there were 166 intervention arms in total. Overall, 

median program duration was 6 months (range 1–96) and median number of contact hours was 

12 (range 1–208). Technology was the primary method of communication for 17 programs 

studied in 16 trials,

138,139,147,167,171,179,185,187,194,241,247,253,258,259,264,265 and was used alone or in 

combination with in-person communication in 42 programs; based on our inclusion criteria, all 

programs were delivered with some form of communication with delivery personnel. Sixty-four 

programs were delivered to individuals only, 56 to groups only, and 44 had some mixture of 

individual and group delivery (see Table F3 for details). Half (83 of 166; 50 percent) of 

programs were delivered by one health care professional, with (n=16) or without (n=67) the 

assistance of a non-health care professional; other programs were delivered by a 

multidisciplinary team (48 arms; 29 percent) or solely by non-health care professionals (31 arms; 

19 percent) (see Table F3). Data on the delivery personnel could not be determined for two 

studies.187,236 

Risk of Bias of Individual Studies

A summary of the ROB assessments for the 132 trials is presented in Figure 18; the 

consensus assessments for all domains in each study are presented in Appendix E. All trials were 

assessed as having a medium (unclear) or high overall ROB. For objective outcomes (e.g., 

HbA1c, weight, blood pressure), 42 percent of trials had a medium ROB and 58 percent had a 

high risk. The assessment of high ROB was largely driven by incomplete outcome data (i.e., loss 

to followup). For trials (n=92) reporting on subjective outcomes of interest for this review (e.g., 

HRQL, depression), 13 percent had a medium ROB; the remainder (87 percent) had a high ROB. 

This was primarily due to lack of blinding of participants, study personnel, and outcome 

assessors (see Methods section and the Supplementary File for a description of decision rules for 

these assessments). 

Twenty-four trials (18 percent) received funding from industry. One-hundred-six (80 

percent) received funding from non-industry sources (e.g., government or foundations); of these, 

15 (11 percent) received funding from both industry and non-industry sources. Funding was not 

reported for seven (0.5 percent) studies. 
56

Figure 18. Risk of bias summary for trials of behavioral programs for type 2 diabetes

Effectiveness of Behavioral Programs Across Outcomes

We report on the overall effectiveness of behavioral programs before describing our results 

for KQs 5 and 6. This serves to summarize the findings on outcomes that did not contribute to 

the analyses for KQ 5 or 6, and to provide information for interpreting the results for KQs 5 and 

6. We provide a summary of the results for our key outcomes, based on outcome category, 

comparison group, and timepoint. Because several trials studied more than one behavioral 

program, results are usually characterized by the number of comparisons rather than trials. The 

results for all outcomes are presented in summary tables in Appendix I; Table I1 contains results 

for behavioral programs compared with usual care and Table I2 contains those for comparisons 

with active controls. Most of these results are based on meta-analyses for two or more 

comparisons, and we indicate when no outcome data were available. Behavioral programs are 

not analyzed based on their components for these analyses; KQs 5 and 6 focused on potential 

moderation in effect by program components and other factors. Table I3 contains the results for 

key outcomes at longest followup (i.e., up to 12 months) from studies reporting on comparative 

effectiveness between different behavioral programs. This table is organized by outcome 

category and is grouped by comparisons in the manner the behavioral programs differed (e.g., 

comparing delivery personnel or intensity).

Key Clinical Outcomes: HbA1c and Change in Body Composition

HbA1c

Individuals receiving behavioral programs compared with usual control improved their 

glycemic control (i.e., reduced percent HbA1c) at end of intervention (66 comparisons; 8,715 

subjects; MD, -0.35; 95% CI, -0.56 to -0.14; 
57

I

2

=74%),135,137,139,141,142,145,147,151,153,155,160,162,171,173,175-177,179,184,188-191,197,203,205-208,210,213-220,222-

226,228,229,231,233,236,239-241,247,249,253-255,257-262,265 but not at 6-month (23 comparisons; 4,138 subjects; 

MD, -0.16; 95% CI, -0.36 to 0.04; I2

=61%)136,140,143,146,163,173,178,183,193-196,211,215,229,234,235,241,246,

249,259 or 12-month followup (9 comparisons; 1,494 subjects; MD, -0.14; 95% CI, -0.4 to 0.12; 

I

2

=59%).146,158,163,173,178,193,223,234 The results were of a smaller magnitude when behavioral 

programs were compared with active control groups at end of intervention (25 comparisons; 

7,518 subjects; MD, -0.24; 95% CI, -0.41 to -0.07; I2=70%).107,154,161,164-

166,168,169,174,175,184,186,191,192,198,202,230,252,265 For 6-month followup, the effect size was similar but 

the results reached statistical significance (6 comparisons; 595 subjects; MD, -0.19; 95% CI, -

0.37 to -0.01).107,156,181,182,201 The estimate was nonsignificant and imprecise at 12-month 

followup (6 comparisons; 486 subjects; MD, -1.10; 95% CI, -2.56 to 0.36).

107,164,192,201 No result 

was clinically important based on our prespecified threshold of 0.4 unit change in percent HbA1c. 

The meta-analyses for HbA1c indicated high heterogeneity in effect between studies across 

timepoints (I2 ranged from 61–98 percent). As described in the Methods, we performed 

sensitivity analyses to explore this issue; however, none of the prespecified variables reduced the 

heterogeneity to below 50 percent so we present the original results.

In three trials (701 subjects) providing comparative effectiveness between DSME delivered 

to groups compared with delivery to individuals or via a mixture of individual and group 

delivery, there was a beneficial effect for those individuals receiving DSME in groups at up to 

12-months followup (MD, -0.36; 95% CI, -0.63 to -0.08).192,212,234 In contrast, there was a benefit 

at end of intervention shown in a trial comparing individual DSME and motivational 

interviewing with group-based empowerment DSME and supervised group exercise (143 

subjects; MD, -0.30; 95% CI, -0.58 to -0.02).

244 Several comparative effectiveness studies found 

no difference in HbA1c changes between groups. Some examples include the addition of an 

additional treatment (e.g., problem solving therapy,168 music therapy199) or a support aspect to a 

DSME or lifestyle program;172,227,230 others include comparisons between peer and health 

professional delivery of a program component (see Appendix I).144,172,227,256 

Six trials reported on HbA1c but did not provide data suitable for inclusion in the metaanalysis. Five trials comparing a behavioral program with usual care did not find a significant 

difference between groups.149,157,167,187,200 One trial comparing two behavioral interventions with 

different delivery methods also found no difference between groups.159

Visualization of funnel plots did not suggest publication bias, and using the Egger test78 for 

this outcome resulted in no significant indication of bias for comparisons with usual care 

(p=0.25) or active controls (p=0.21) at end of intervention.

Change in Body Composition

Compared with usual care, behavioral programs assisted participants in reducing their BMI 

(kg∙m-2

) at all three timepoints—end of intervention (36 comparisons; 4,280 subjects; MD, -0.51; 

95% CI, -0.66 to -0.36),135,137,139,145,151,153,155,162,171,175,179,184,189,190,206,208,210,214,215,224,226,233,239-

242,246,249,251,255,257,259-61 6-month followup (14 comparisons, 1,840 subjects; MD, -0.21; 95% CI, -

0.32 to -0.1),136,143,146,163,183,193,211,215,241,246,249,251,259 and 12-month followup (5 comparisons; 867 

subjects; MD, -0.92; 95% CI, -1.44 to -0.4).146,157,163,193,238 When compared to active controls, 

behavioral programs did not reduce BMI at any followup timepoint. Body weight (kg) was 

reduced at end of intervention in those receiving behavioral programs compared with those 

receiving usual care (37 comparisons; 4,070 subjects; MD, -1.68; 95% CI, -2.06 to -

1.30),137,141,145,147,153,160,167,176,178,184,188,190,191,200,203,205,213,214,217,222,224-226,239,246,249,254,258-263,265 or 
58

active control (15 comparisons; 6,212 subjects; MD, -1.30; 95% CI, -2.48 to -0.12; 

I

2

=78%).148,154,165,166,169,174,184,186,191,198,202,252,265 There was no reduction in weight at other 

timepoints; one trial showed an increase in weight at 12-month followup for the behavioral 

program compared with active control arm (95 subjects; MD, 3.70; 95% CI, 1.67 to 5.73).201

Waist circumference (cm) was reduced at end of intervention (17 comparisons, 1,521 

subjects),145,153,162,167,190,203,214,215,224,226,241,254,255,259,261 in those comparisons with usual care—MD

= -3.17 (95% CI, -4.36 to -1.98; I2=64%). One study found significant reduction in waist 

circumference at 6-month followup for those receiving a behavioral program compared to an 

active control (38 subjects; MD, -5.70; 95% CI, -6.54 to -4.86).156 There was no difference found 

in two studies comparing behavioral programs to usual care at 12-month followup;157,163 no data 

were available at 12-month followup for studies comparing behavioral programs to active 

control.

One comparative effectiveness trial (99 subjects) found that BMI was reduced (MD, -1.80; 

95% CI, -2.51 to -1.09) at end of intervention for individuals receiving a cognitive-behavioraltherapy based lifestyle program including a portion-controlled diet compared with DSME 

including a meal plan.

170 Participants in this study who received the lifestyle program also 

reduced their weight and waist circumference more than those receiving the DSME program—

MD = -5.10kg (95% CI, -7.22 to -2.98) and MD = -3.60cm (95% CI, -5.33 to -1.87), 

respectively. 

Behavioral Outcomes: Change in Dietary Intake and Physical Activity; 

Medication Adherence

Participants receiving behavioral programs compared with usual care reduced their energy 

intake (daily intake of kilocalories) to a small extent at end of intervention (11 comparisons; 

1,164 subjects; MD, -149.62; 95% CI, -243.01 to -56.23; I2

=68%)135,137,155,167,188,191,215,216,245,261

and 6-month followup (3 comparisons; 469 subjects; MD, -64.05; 95% CI, -96.44 to -

31.66).163,167,215 There was no significant change at any timepoint in energy intake for 

comparisons with active controls, and no effect reached statistical significance for percent 

kilocalories from saturated fat.

Changes in intensity/duration of physical activity were measured by subjective (e.g., days per 

week in most cases) and objective (via accelerometers) means. Fifty percent of the studies 

reporting days per week of physical activity used the Summary of Diabetes Self-care Activities 

(SDSCA) questionnaire. Two trials (382 subjects) found that participants of behavioral programs 

increased the number of days per week of physical activity to a greater extent than those in usual 

care arms at 12-month followup (MD, 0.90; 95% CI, 0.90 to 0.90).163,238 These and several other 

trials138,163,184,219,226,236,238-240,253 did not find any difference at end of intervention or 6-month 

followup. One trial with 40 participants showed a negative affect for a behavioral program 

compared with an active control at end of intervention (MD, -1.06; 95% CI, -1.82 to -0.31).184

There was no difference reported for objective measurements of exercise duration/intensity (7 

comparisons), or for measures of fitness (5 comparisons) in trials comparing behavioral 

programs to usual care or active controls.

Two comparative effectiveness trials found significant benefit for changes in physical 

activity. Based on self-report of days per week of engaging in moderate-to-intense physical 

activity, Vadstrup et al.244 found improvement (121 subjects; MD, 1.30; 95% CI, 0.80 to 1.80) 

for the group provided individual DSME and motivational interviewing compared with groupbased empowerment DSME and supervised group exercise. Using the Modified Canadian 
59

Aerobic Fitness Test which estimates relative maximal oxygen consumption, Plotnikoff et al.,209

found improved fitness levels from supplementing DSME and support with a physical activity 

intervention (88 subjects; SMD, 0.62; 95% CI, 0.19 to 1.05).

Measurement of medication adherence was undertaken using various tools including the 

SDSCA,138,171 the Hill-Bone Compliance Scale,168,175 and the Morisky Adherence Scale.253 A 

significant effect for medication adherence—in favor of the usual care group—was maintained 

from end of intervention to 12-month followup in one trial (191 subjects; SMD, -0.50; 95% CI -

0.79 to -0.21);238 other studies comparing behavioral programs to usual care found no difference 

at end of intervention or 6-month followup. Comparisons with active controls also found no 

difference at any followup timepoint.

Health Outcomes: Quality of Life, Micro- and Macrovascular 

Complications, All-Cause Mortality 

Quality of Life

Outcomes for quality of life were categorized into five subcategories based on their focus 

(i.e., generic vs. diabetes-specific) and the similarity between studies in measurement scales. 

Groups of studies reported outcome data based on the SF-36 Health Survey (physical and mental 

component scores), and the Problem Areas in Diabetes (PAID) scale (0–100; lower score 

favorable) measuring diabetes distress. Accordingly, three of our subcategories represent these 

tools (i.e., Quality of Life–SF36 Physical, Quality of Life–SF36 Mental, and Diabetes Distress), 

for which we present results as MD. Other subcategories were created to combine other generic 

(Quality of Life–Other; e.g., WHO Quality of Life Brief, W-BQ12, EuroQol 5D) and diabetesspecific (Diabetes-specific Quality of Life; e.g., Diabetes Quality of Life, Diabetes Distress 

Scale, Appraisal of Diabetes, Diabetes Symptom Checklist) quality of life questionnaires; these 

results are presented as SMDs. 

There was no difference in Quality of Life-SF36 (Physical) or Quality of Life-SF36 (Mental) 

when measured at end of intervention for comparisons with usual care,155,214,222,239 or up to 6-

months followup for comparisons with active controls.169,181,252 There was no difference found 

for Quality of Life–Other in comparisons (n=7) with usual care up to 6-month 

followup,195,196,206,226,249,253 or in comparisons (n=4) with active controls up to 12-months 

followup.154,192 Results favored behavioral programs compared with usual care for Diabetes 

Distress (8 comparisons, 1,384 subjects) at end of intervention (MD, -1.82; 95% CI, -3.43 to -

0.21),142,147,211,218,225,226,228,233 but not at longer followup.146,211,234 The result at end of intervention 

is not clinically important based on our prespecified threshold of a 0.5 SD using the mean SD of 

the included studies. One study (167 subjects) evaluating this outcome in a comparison to active 

controls found no difference at 6-month followup.181 There was no difference in Diabetesspecific Quality of Life at any followup timepoint to 12-month followup when comparing 

behavioral programs to usual care,146,163,175,177,189,215,253 or at end of intervention for programs 

compared with active controls.154,168,175

One trial assessed the effects on quality of life when the support phase of a DSME and 

support program was delivered by peers, clinical practice staff, or health care professionals 

(diabetes educators). Siminerio et al.227 found that Diabetes Distress worsened for the group 

receiving support from peers when compared to the group receiving support from the educators 

(74 subjects; MD, 24.70; 95% CI, 15.02 to 34.38). This effect is considered clinically important. 
60

There was no difference in Diabetes Distress when delivery of nonprofessional clinic staff was 

compared to that by health care professionals. 

Micro- and Macrovascular Complications

Authors of the LookAHEAD trial (5,145 subjects) studied outcomes of myocardial 

infarctions, stroke, heart failure, diabetic nephropathy, diabetic retinopathy, and diabetic 

neuropathy. Diabetic retinopathy was reduced by 14% (hazard ratio, 0.86; 95% CI, 0.75 to 0.98) 

in participants receiving their intensive lifestyle program compared with an active control 

(didactic education and support) over a median of 8 years.278 A secondary analysis of 

nephropathy using a post hoc outcome of very-high-risk chronic kidney disease—a combination 

of the a priori outcomes albuminuria and estimated glomerular filtration rate, found a lower 

incidence of nephropathy for the intensive lifestyle program at the 8 year end-of-intervention 

timepoint (risk difference 0.27 cases per 100 person-years; hazard ratio, 0.69; 95% CI, 0.55 to 

0.87).293 Results for the other outcomes in this trial did not reach statistical significance—

myocardial infarction (RR, 0.86; 95% CI, 0.70 to 1.05), stroke (RR, 1.06; 95% CI, 0.79 to 1.44), 

heart failure (RR, 0.83; 95% CI, 0.64 to 1.08), and diabetic neuropathy (RR, 1.13; 95% CI, 0.92 

to 1.38). 

All-Cause Mortality

One study examined all-cause mortality as an pre-specified outcome;252 there were enough 

data in 27 reports to calculate a difference in all-cause mortality for the associated comparisons. 

There was no difference in all-cause mortality between participants receiving behavioral 

programs and usual care (25 comparisons; 4,659 subjects; RR, 1.28; 95% CI, 0.84 to 1.94); 

mortality between behavioral programs and active control groups (5 comparisons, 6,050

subjects) was 14 percent lower for those receiving behavioral programs (RR, 0.86; 95% CI, 0.77 

to 0.96).

KQ 5. Potential Moderation of Effectiveness for T2DM: 

Components, Intensity, Delivery Personnel, Method of 

Communication, Degree of Tailoring, and Level of Community 

Engagement 

Key Points: HbA1c

• In a network meta-analysis with usual care serving as the reference, behavioral programs 

showing effect sizes above our threshold for clinical importance represented all three 

major program component categories of DSME, DSME and support, and lifestyle.

• The effect sizes of all minimally intensive DSME programs (≤10 contact hours) were 

lower than our threshold for clinical importance, but were all higher than that for 

educational interventions not meeting our criteria for a behavioral program (e.g., didactic 

education programs).

• Programs having the higher effect sizes and probabilities of being best (≥5 percent) were 

more often delivered in person rather than including technology. 
61

Key Points: Body Mass Index

• Lifestyle programs resulted in the highest effect sizes for BMI.

• Program intensity appeared less important than method of delivery; providing some 

individual (rather than solely group-based) delivery appears beneficial.

Detailed Synthesis

We conducted network meta-analyses for the outcomes of HbA1c and BMI. These outcomes 

represent two of our key outcomes that were reported by the most studies. Tables 12 (HbA1c) and 

13 (BMI) provide descriptions of the nodes (no two containing the same combination of 

variables), and include the results including the rank order of each node, the MD relative to usual 

care, the associated 95 percent credibility interval, and a percentage referring to the node’s 

“probability of being best” (PB). These tables also indicate which studies contributed to each 

node, with the sample size of the applicable study arms, although it should be noted that the 

network approach accounts for direct and indirect comparisons such that other information 

contributes to the results. We summarize our approach and the results for each outcome below. 

Figures 19 and 20 contain the plots showing the relative ranking of the different nodes; the 

studies within each node are cited in the accompanying tables. A consistency analysis was 

performed for the HbA1c analysis and it was found that only two quadratic loops (of a total of 43 

total quadratic and triangular loops) showed statistically significant inconsistency.

HbA1c

Accounting for all variables of program components and delivery variables (Table 3) when 

creating the network was deemed not appropriate for various reasons. When choosing which

variables to use, we prioritized them by considering factors including the: reliability and 

specificity with which we could categorize programs in each variable based on extent of 

reporting, overlap in meaning between variables, and the ability to inform those individuals 

making decisions to implement these programs in community settings. Deciding between 

program duration (months) and intensity (contact hours), the latter was chosen because it 

accounts for duration to some extent, aligns with our focus on interactive programs, and better 

enables one to estimate resource requirements in terms of personnel and space. Degree of 

tailoring was not chosen because every program incorporated this to some extent and 

categorizing this (e.g., minimal versus moderate in terms of content and delivery) was considered 

unreliable based on study reporting. Moreover, the use of technology (captured in the delivery 

method variable) was also considered a way to tailor the program to individuals, particularly in 

cases of poor access due to travel or time constraints. The level of community engagement was 

also not used because, when incorporated, this was largely via use of lay or peer providers which 

was captured in the delivery personnel variable. The remaining variables were placed in order 

(program components, program intensity, method of communication, method of delivery, and 

delivery personnel) and we then created nodes trying to incorporate as many variables as 

possible without having numerous nodes either empty (a theoretical grouping of variables that 

did not represent a studied program), or with only one or two programs. Dividing the data by the 

first variable of program components (DSME, DSME and support, and lifestyle) resulted in a 

relatively large number of DSME comparisons. For this group, we were able to use all five 

variables to create 24 potential nodes (18 which contained comparisons). We did not capture the 

variable of delivery personnel for the DSME and support, and lifestyle groups because most 

nodes would in this case contain at most one comparison. 
62

When interpreting the results, we relied primarily on the relative ranking of the nodes, and 

looked for trends in the findings based on program variables that appeared to determine whether 

the effects would offer clinical benefit. Some nodes had very few studies, small sample sizes, 

and/or wide credibility intervals, thus we did not make any firm conclusions for a single node (or 

for differences in 561 potential comparisons) but rather from looking across nodes with similar 

features.

The results of the network meta-analysis indicated that, in comparison to the reference of 

usual care, 14 nodes produced MDs which fell at or above our clinically important threshold 

(0.4) for change in percent HbA1c. Four of these nodes represent DSME, five represent DSME 

and support, and five represent lifestyle programs. Six nodes represent medium-intensity 

programs (11–26 contact hours), six represent high-intensity programs (≥26 contact hours), and 

two (one DSME and support, and one lifestyle) represent low-intensity programs (≤10 contact 

hours). The mean contact hours for the programs represented by these effective nodes was 26.4 

(range 7-40.5 hours); the mean total program duration was 8 months (range 2-12). None of the 

nodes representing low-intensity DSME programs showed clinically important effects; all had 

greater impact on HbA1c than basic educational controls, but lower impact than a stand-alone 

dietary or physical activity intervention. Three of four nodes representing DSME programs with 

MDs showing clinically important effect were delivered by health care professionals.

Eleven of the 14 nodes representing clinically important effects were delivered in person 

rather than incorporating some form of technology. Behavioral programs in the nodes with the 

highest PB (36 and 10.7 percent, respectively) were delivered in person rather than by 

incorporating technology. Similar observations were noted for the other four nodes having PB ≥5 

percent, of which three were delivered in person and one was delivered using some form of 

technology; the latter group of studies provided supportive telephone calls between in-person 

sessions during lifestyle interventions tailored to minorities.

143,160 All effective nodes 

representing some use of technology were of moderate or high intensity. 

An outlier having an MD of 2.80 (95% CI, 1.14 to 4.48) represented a study by Brown et 

al.152 which found greater HbA1c reduction at end of intervention in a group receiving DSME 

compared with one receiving DSME with the addition of a care manager.

Body Mass Index

We created nodes using four variables for BMI (i.e., program component, program intensity, 

method of communication, and method of delivery). Of the 39 plausible nodes (each differing by 

only one level of one variable), there were studies with data to populate 26 nodes. 

Averaging the baseline values in the studies, BMI at baseline was similar for programs 

classified as DSME (32.4 kg∙m2

), DSME and support (33.0 kg∙m2), and lifestyle (32.9 kg∙m2). 

The effect sizes for BMI from behavioral programs relative to usual care ranged between -1.77 

kg∙m2 and 3.29 kg∙m2

. The node with the most beneficial MD only represented one study157

evaluating a low-intensity lifestyle program with multiple brief contacts over 6 months. Nodes 

with rank orders 2 and 3 were both lifestyle programs of low and medium intensity, respectively. 

The node having the most studies (n=12) represented a DSME program of medium intensity 

(11–26 hours) which was delivered in person to groups; the results indicated this program to 

have 0 percent PB. One difference between the programs in this node and those with higher PB 

is that the higher PB all offered some individual delivery, rather than relying only on group 

delivery. Likewise, the majority of nodes having the highest MDs (i.e., 8 of the highest 10) 

offered some individual delivery. 
63 

Table 12. Network meta-analysis for effect moderation on HbA1c results in T2DM: description of nodes and results

Arm Description

Rank Order of Effect, 

Studies & Sample Size 

of Study Arms

Intensity Method of 

Communication

Delivery 

Method

Delivery 

Personnel

MD (%HbA1c), 95% 

Credibility Interval

Probability of 

Being Best

Usual care 

(reference 

category)

NA135-137,139-

143,145,147,151,153,155,158,160,16

2,163,171,173,175-179,183,184,188-

191,193-197,203,205-

208,210,211,213-220,222-

226,228,229,231,233-236,238-

241,246,247,249,253-255,257-

262,265

N = 6,448

NA NA NA NA 0 [NA, NA] 0.0%

Active comparator 

(non-DSME) 

31107,146,154,164,168,169,175,18

1,182,184,192,198,201,252,265

N = 3,913

NA NA NA NA 0.10 [-0.23, 0.43] 0.0%

Active comparator 

(other)

15156,161,165,166,174,186,191,20

2,230

N = 241

NA NA NA NA -0.39 [-0.89, 0.10] 0.0%
64 

Table 12. Network meta-analysis for effect moderation on HbA1c results in T2DM: description of nodes and results (continued)

Arm Description

Rank Order of Effect, 

Studies & Sample Size 

of Study Arms

Intensity Method of 

Communication

Delivery 

Method

Delivery 

Personnel

MD (%HbA1c), 95% 

Credibility Interval

Probability of 

Being Best

DSME 19135,153,154,178,185,212,225,23

1,234,238,243,244,257

N= 1,161

≤10h In person Individual & 

mixed

HCP -0.29 [-0.61, 0.04] 0.0%

22107,144,146,172,173,182,199,21

1,212,234

N = 1,160

≤10h In person Group only HCP -0.22 [-0.61, 0.16] 0.0%

29144

N = 40

≤10h In person Group only Non-HCP -0.05 [-1.27, 1.16] 0.9% 

27171,175,179,185,203,226,241,25

9,265

N = 532

≤10h Some technology Individual & 

mixed

HCP -0.11 [-0.50, 0.27] 0.0%

26168,176,177,183,194,218-

220,247,253

N = 1,679 

≤10h Some technology Individual & 

mixed

Non-HCP -0.16 [-0.53, 0.21] 0.0%

24192,206,213

N = 222

11-26h In person Individual & 

mixed

HCP -0.17 [-0.81, 0.47] 0.0%

21136,141,155,158,163,170,181,19

2,193,199,223,224,235,243,260,264

N = 1,216

11-26h In person Group only HCP -0.25 [-0.53, 0.04] 0.0%

20195,196,228,229,246

N = 531

11-26h In person Group only Non-HCP -0.27 [-0.76, 0.21] 0.0%

25139,142,147,162,258

N = 611

11-26h Some technology Individual & 

mixed

HCP -0.17 [-0.66, 0.31] 0.0%

5197,233

N = 159

11-26h Some technology Individual & 

mixed

Non-HCP -0.78 [-1.57, 0.02] 3.7% a

28293

N = 46

11-26h Some technology Group only HCP -0.09 [-1.39, 1.20] 1.5%

7215

N= 15

≥27h In person Individual & 

mixed

HCP -0.73 [-1.86, 0.41] 8.1% a

1201,202,244

271

≥27h In person Group only HCP -1.37 [-2.03, -0.71] 36.0% a

11198

N = 30

≥27h Some technology Individual & 

mixed

HCP -0.49 [-1.69, 0.70] 4.0% a
65 

Table 12. Network meta-analysis for effect moderation on HbA1c results in T2DM: description of nodes and results (continued)

Arm Description

Rank Order of Effect, 

Studies & Sample Size 

of Study Arms

Intensity Method of 

Communication

Delivery 

Method

Delivery 

Personnel

MD (%HbA1c), 95% 

Credibility Interval

Probability of 

Being Best

DSME + Support 8210

N = 90

≤10h In person Individual & 

mixed

NA -0.70 [-1.80, 0.40] 6.8% a

34152

N = 48

≤10h In person Group only NA 2.83 [1.22, 4.43] 0.0%

17172,207,230

N = 334

≤10h Some technology Individual & 

mixed

NA -0.38 [-0.99, 0.23] 0.0% 

14164

N = 52

11-26h In person Individual & 

mixed

NA -0.44 [-1.76, 0.86] 4.8% a

6150,208,209

N = 267

11-26h In person Group only NA -0.74 [-1.56, 0.08] 2.8% a

16152,189,209,222

N = 240

11-26h Some technology Individual & 

mixed

NA -0.39 [-1.06, 0.28] 0.1%

10216,217

N = 197

≥27h In person Individual & 

mixed

NA -0.54 [-1.28, 0.20] 0.8% a

4150,151

N = 230

≥27h In person Group only NA -0.88 [-1.86, 0.09] 9.4% a

Lifestyle 32145,188,249

N = 171

≤10h In person Individual & 

mixed

NA 0.20 [-0.50, 0.92] 0.0%

13156,186

N = 44

≤10h In person Group only NA -0.45 [-1.35, 0.45] 0.9% a

33188

N = 67

≤10h Some technology Individual & 

mixed

NA 0.25 [-1.11, 1.62] 0.5%

12165,184,190,191,232,236

N = 138

11-26h In person Individual & 

mixed

NA -0.47 [-0.99, 0.05] 0.0% a

9169,170,205,232,255

N = 161

11-26h In person Group only NA -0.69 [-1.25, -0.12] 0.5% a

3143,160

N = 76

11-26h Some technology Individual & 

mixed

NA -0.91 [-1.72, -0.10] 7.4% a

23254

N = 74

11-26h Some technology Group only NA -0.20 [-1.28, 0.88] 0.9%

2137,161,174,214,261

N = 233

≥27h In person Individual & 

mixed

NA -1.12 [-1.72, -0.53] 10.7%a

30239,240

N = 305

≥27h In person Group only NA 0.07 [-0.67, 0.83] 0.0%

18166,252,262

N = 2643

≥27h Some technology Individual & 

mixed

NA -0.37 [-1.01, 0.27] 0.1% 

DSME = diabetes self-management education; h = hour(s); HbA1c = hemoglobin A1c; HCP = health care professional; MD = mean difference; NA = not applicable a Highlighted rows represent those nodes having effect sizes meeting or exceeding our criteria for clinical importance.
66

Figure 19. Plot of network meta-analysis results for effect moderation on HbA1c in T2DM

This plot depicts the results from our network meta-analysis for the outcome of HbA1c (negative values favorable) when 

comparing groups (“nodes”) of interventions, with each group differing by at least one level in the categories of program 

component, intensity, mode of communication, delivery method, and (for DSME programs only) delivery personnel (see Table 3 

for categorization schema and the figure legend for a description of each node). The dots and lines represent the mean difference 

(MD) and 95 percent credibility intervals for the represented programs relative to usual care; the figure indicates which MDs

meet or exceed our predetermined threshold for clinical importance (reduction in HbA1c of ≥0.4%). The estimated MDs and 95% 

credibility intervals are included in Table 12.
67

Table 13. Network meta-analysis for effect moderation on body mass index results for T2DM: description of nodes and results

Arm Description

Rank Order of Effect, 

Studies & Sample Size 

of Study Arms

Intensity Method of 

Communication Delivery Method MD (kg∙m-2

), 95% 

Credibility Interval

Probability of 

Being Best

Usual care 

(reference category)

NA135-

137,139,141,143,145,151,153,155,157,

162,163,171,173,175,179,183,184,189,

190,193,206,208,210,211,214,215,224,

226,233,238-

242,246,249,251,255,257,259-261

N = 3,341

NA NA NA 0 [NA, NA] 0.0%

Active comparator 

(non-DSME)

23146,154,169,175,184,192

N = 684

NA NA NA 0.13 [-0.64, 0.88] 0.0%

Active comparator 

(other)

15156,174,186,202

N = 99

NA NA NA -0.21 [-1.69, 1.26] 0.1%

DSME 13135,153,154,212,238,257

N = 629

≤10h In person Individual & 

mixed

-0.32 [-1.03, 0.33] 0.0%

7146,172,173,199,211,212

N = 771

≤10h In person Group only -0.61 [-1.37, 0.17] 0.1%

20171,175,179,183,226,241,259

N = 470

≤10h Some technology Individual & 

mixed

-0.14 [-0.81, 0.53] 0.0%

22192,206

N = 194

11-26h In person Individual & 

mixed

0.10 [-1.27, 1.47] 0.1%

12136,141,155,163,170,192,193,199,

224,246,260,264

N = 939

11-26h In person Group only -0.33 [-0.80, 0.12] 0.0%

9162,233,242

N = 379

11-26h Some technology Individual & 

mixed

-0.55 [-1.29, 0.25] 0.1%

24264

N = 15

11-26h Some technology Group only 0.38 [-2.97, 3.72] 5.2%

16139,215

N = 161

≥27h In person Group only -0.21 [-2.03, 1.60] 1.8%

6202

N = 3

≥27h In person Individual & 

mixed

-0.71 [-2.62, 1.19] 5.0%
68

Table 13. Network meta-analysis for effect moderation on body mass index results for T2DM: description of nodes and 

results (continued)

Arm Description

Rank Order of Effect, 

Studies & Sample Size 

of Study Arms

Intensity Method of 

Communication Delivery Method MD (kg∙m-2

), 95% 

Credibility Interval

Probability of 

Being Best

DSME + Support 19210

N = 90

≤10h In person Individual & 

mixed

-0.19 [-1.66, 1.26] 0.6%

25152

N = 48

≤10h In person Group only 3.29 [1.39, 5.19] 0.0%

8172

N = 93

≤10h Some technology Individual & 

mixed

-0.61 [-1.99, 0.78] 1.7%

14208,209

N = 153

11-26h In person Group only -0.31 [-1.69, 1.12] 0.7%

21152,189,209

N = 123

11-26h Some technology Individual & 

mixed

0.09 [-1.00, 1.21] 0.0%

11151

N = 128

≥27h In person Group only -0.34 [-2.29, 1.63] 3.0%

Lifestyle 2145,249

N = 105

≤10h In person Individual & 

mixed

-1.44 [-2.59, -0.24] 11.9%

17156,186,251

N = 79

≤10h In person Group only -0.20 [-1.94, 1.48] 0.8%

1157

N = 50

≤10h Some technology Individual & 

mixed

-1.77 [-3.93, 0.42] 32.5%

10184,190 11-26h In person Individual & 

mixed

-0.54 [-1.58, 0.67] 0.5%

5169,170,255

N = 115

11-26h In person Group only -0.80 [-1.63, -0.06] 0.5%

3143

N = 49

11-26h Some technology Individual & 

mixed

-1.38 [-5.08, 2.29] 31.6%

4137,174,214,261

N = 212

≥27h In person Individual & 

mixed

-1.24 [-2.03, -0.48] 3.1%

18239,240

N = 305

≥27h In person Group only -0.20 [-1.68, 1.28] 0.7%

DSME = diabetes self-management education; h = hour(s); MD = mean difference; NA = not applicable 
69

Figure 20. Plot of network meta-analysis results for effect moderation on body mass index for 

T2DM

DSME = diabetes self-management education; h = hours

This plot depicts the results from our network meta-analysis for the outcome of body mass index (BMI) when comparing groups 

(“nodes”) of interventions with usual care as the referent. Each group differs by at least one level in the categories of program 

component, intensity, mode of communication, and delivery method (see Table 3 for categorization schema). The dots and lines 

represent the effect size in mean difference (MD) and 95% credibility intervals for the represented programs relative to usual 

care. The MDs and 95% credibility intervals are included in Table 13.

KQ 6. Subgroups for Factors Moderating Effectiveness in T2DM

Key Points

Glycemic Control

• In terms of overall effectiveness at longest followup for HbA1c, participants with 

suboptimal glycemic control (≥7 percent HbA1c) appear to benefit more than those with 

good control (<7 percent) from behavioral programs when compared to usual care and 

active controls. The effect sizes were not clinically important for either group.
70

• Few differences were evident when evaluating potential moderation by program factors 

in a subgroup of studies having participants with suboptimal baseline glycemic control. 

Of the two nodes representing low-intensity programs that were found to have clinically 

important effects in the original network analysis, one was shown not effective for 

participants with suboptimal glycemic control. Active controls of dietary or physical 

activity interventions were not as effective for participants with suboptimal control.

Age

• Older adults (≥65 years) did not benefit at longest followup in terms of reduction in 

HbA1c from behavioral programs in comparison with usual care or active controls. In 

adults <65 years, the effect size for behavioral programs compared with active controls at 

longest followup was clinically important.

Race/Ethnicity

• Subgroup analysis of our meta-analyses comparing behavioral programs to usual care and 

active controls indicated that programs offered to predominantly minority participants (≥ 

75 percent nonwhite) appear to provide more benefit than those offered to populations 

with a lower proportion (<75 percent) of nonwhite individuals. The effect size for 

minority participants reached clinical importance.

• Based on univariate regression analyses for the subgroups based on race/ethnicity, none 

of the program factors (e.g., intensity, delivery personnel) reached statistical significance 

for influencing the effectiveness of behavioral programs compared to usual care on 

HbA1c. The subgroup of majority/white participants appeared to benefit more from 

lifestyle programs than from DSME or DSME plus support programs.

• Glycemic control appeared to be worse for the minority (HbA1c=8.8 percent) compared 

with the majority/white (HbA1c=7.6 percent) subgroup.

Detailed Synthesis

As is common with systematic reviews, all of our results for this KQ relied on betweenstudy rather than within-study comparisons, such that the effect of randomization is removed and 

the results are considered observational and possibly biased through confounding by other studylevel characteristics.

Glycemic Control

Initially, we conducted a subgroup analysis on the outcome of HbA1c by baseline glycemic 

control (HbA1c <7 vs. ≥7 percent) using the pair-wise meta-analysis results for HbA1c at longest 

followup timepoint (data not shown). For behavioral programs compared with usual care, our 

meta-analysis showed a small benefit (MD, -0.12; 95% CI, -0.22 to -0.01; I2

=3%) for HbA1c for 

participants with a baseline HbA1c <7 percent (6 trials, 1,239 subjects);194,196,223,246,249,260 the 

analysis showed greater benefit (although not clinically important) for participants with a 

baseline HbA1c ≥7 percent (76 trials; 11,086 subjects; MD, -0.32; 95% CI, -0.42 to -0.21; 

I

2

=71%). There was no difference in change in HbA1c for persons with baseline HbA1c <7 

percent receiving a behavioral program compared with an active control (3 trials, 169 

participants; MD, -1.43; 95% CI, -3.57 to 0.71; I2

=99%);174,186,201 persons with HbA1c ≥7 percent 

at baseline had greater reduction in HbA1c after receiving behavioral programs compared with an 
71 

active comparator (20 trials, 7,709 subjects; MD, -0.18; 95% CI -0.30 to -0.06; I2

=38%), but this 

was not clinically important. 

To explore potential moderation of effect based on the factors of interest, we performed a 

subgroup analysis of our network meta-analysis described in the section for KQ5. We removed 

the studies in which baseline HbA1c was <7 percent (n=9)174,186,194,196,201,223,246,249,260 and repeated 

the analysis for a subgroup with baseline HbA1c ≥7 percent; there were an insufficient number of 

studies with baseline HbA1c <7 percent to run the analysis using these studies, or to perform 

meta-regression analysis. The results are presented in Table J1 in Appendix J. The categorization 

of all nodes remained the same in relation to the variables of interest. The changes in this 

subgroup analysis include: 1) the effect sizes for nodes ranked 1 and 13 reduced substantially to 

ranks of 31 and 23 (from -1.37 to 0.09 and from -0.45 to -0.15, respectively), and 

2) the active (dietary or physical activity) control became less effective (MD -0.14 vs. -0.39) for

participants having ≥7 percent HbA1c. 

Age

The same set of subgroup analyses performed for baseline glycemic control was conducted 

for our age subgroups; the study population in nine studies reporting on HbA1c had a mean age 

≥65 years.147,155,166,196,203,218,221,223,230,236 We first performed subgroup analyses by age group (≥65 

years vs. <65 years) using the pair-wise meta-analyses results for HbA1c at longest followup 

timepoint in comparisons between behavioral programs and both usual care and active control 

(data not shown). For behavioral programs compared with usual care, the meta-analysis for 

participants <65 years indicated that HbA1c reduced to a statistically significant extent at longest 

followup (76 comparisons; 11.491 subjects; MD, -0.31; 95% CI, -0.42 to -0.21; I2=72%); for 

older adults the results indicated no difference (7 comparisons; 734 subjects; MD, -0.24; 95% CI, 

-0.50 to 0.03; I2=55%). For comparisons with active controls for participants <65 years, the 

benefit of behavioral programs was statistically and clinically significant (26 comparisons; 7,669 

subjects; MD, -0.41; 95% CI -0.70 to -0.12; I2=93%). For older adults, behavioral programs 

compared with an active control (3 comparisons, 206 subjects) failed to reduce HbA1c (MD, -

0.23; 95% CI, -0.60 to 0.14; I2

=0%).

Subsequently, we performed a subgroup analysis for populations <65 years by removing the 

data from the studies (n= 9)147,155,166,196,203,218,223,230,236

 having mean age ≥65 from our network 

meta-analysis described in the section for KQ5. The results are presented in Table J2 in 

Appendix J. The categorization of all nodes remained the same in relation to the variables of 

interest. The only notable change in this subgroup analysis was that the effect size for the active 

control of a dietary or physical activity intervention became clinically important (MD, - 0.55) 

although the PB remained at 0 percent. 

Race/Ethnicity 

We conducted subgroup analyses based on race/ethnicity (i.e. ≥75 percent nonwhite 

[minorities] and <75 percent nonwhite participants) for the outcome of HbA1c at longest 

followup for behavioral programs compared to usual care and active controls (data not shown). 

Using the pairwise meta-analysis for HbA1c when comparing behavioral programs to usual care, 

there was a clinically important effect for minority participants (33 comparisons; 4,774 

participants; MD, -0.42; 95% CI -0.56 to -0.27; I2

=55%)137,141,143,151,153,162,171,179,188,189,195,197,205-

208,210,215-219,222,228,229,231,233,240,246,247,257,262which was greater than that seen for the comparisons 

with <75 percent minorities (24 comparisons; 5,110 participants; MD, -0.16, 95% CI -0.31 to 
72

0.00; I2

=75%).139,142,147,160,175-177,183,184,194,196,214,220,224,234,235,239,249,253,254,258,259 For comparisons 

between behavioral programs and active control groups, there was no statistically significant 

reduction in HbA1c among minorities (5 comparisons, 400 participants; MD, -0.32; 95% CI -0.67 

to 0.04; I2=0%);164,173,182,198,230 studies with a larger proportion of white participants also showed 

no difference (10 comparisons, 6,214 participants; MD, -0.50; 95% CI -1.24 to 0.23; 

I

2

=99%).107,168,169,175,184,201,202,252 Glycemic control at baseline appeared to be worse for the 

minority (8.8 percent HbA1c) compared with the majority/white (7.6 percent HbA1c) subgroup.

We also conducted univariate meta-regressions for each race/ethnicity subgroup. For this 

analysis, we used outcome data for changes in HbA1c at longest followup in comparisons 

between behavioral programs and usual care. Table 14 shows the results for each variable 

examined. No statistically significant finding was generated. The subgroup of majority/white 

participants appeared to benefit more (with a difference near our threshold of change in HbA1c) 

from lifestyle programs compared with DSME or DSME plus support, but the results did not 

reach statistical significance.

Table 14. Results for race/ethnicity subgroups using univariate meta-regressions analyzing the 

association between different program factors and the effectiveness of behavioral programs 

compared to usual care in improving HbA1c for T2DM

Program Factors # Studies Coefficient and 95% CI P Value

Program component (dichotomous: 

DSME and DSME plus 

support/lifestyle)

<75% nonwhite (24) -0.35; 95% CI, -0.73 to 0.032 0.07

≥75% nonwhite (33) 0.31; 95% CI, -0.15 to 0.76 0.17

Duration of intervention (continuous: 

months) 

<75% nonwhite (24) -0.016; 95% CI,-0.05 to 0.02 0.38

≥75% nonwhite (33) 0.013; 95% CI,-0.015 to 

0.036

0.41

Intensity (continuous: contact hours) <75% nonwhite (24) -0.003; 95% CI, -0.011 to 

0.004

0.36

≥75% nonwhite (33) 0.003; 95% CI, -0.0007 to 

0.008

0.096

Frequency (continuous: hours/month) <75% nonwhite (24) -0.006; 95% CI, -0.05 to 0.05 0.78

≥75% nonwhite (33) 0.009; 95% CI, -0.042 to 

0.059 

0.73

Method of communication 

(dichotomous: in-person/ some use 

of technology)

<75% nonwhite (24) -0.17; 95% CI, -0.57 to 0.22 0.37

≥75% nonwhite (33) 0.076; 95% CI, -0.24 to 0.39 0.63

Delivery method (dichotomous: 

individual & mixed/ group only)

<75% nonwhite (24) 0.12; 95% CI, -0.30 to 0.54 0.56

≥75% nonwhite (33) 0.15; 95% CI, -0.19 to 0.49 0.37

Delivery personnel (dicotomous: nonhealth professionals only/health 

professional(s))

<75% nonwhite (24) 0.001; 95% CI, -0.40 to 0.42 0.96

≥75% nonwhite (33) -0.15; 95% CI, -0.46 to 0.16 0.33

Community engagement 

(dichotomous: present/none or NR)

<75% nonwhite (24) 0.038; 95% CI, -0.40 to 0.48 0.86

≥75% nonwhite (33) 0.12; 95% CI, -0.27 to 0.51 0.54

CI = confidence interval
73

Discussion

Key Findings and Discussion for Type 1 Diabetes Mellitus 

(Key Questions 1–4)

This section presents the main findings, followed by a discussion of the findings for key 

questions (KQs) 1-4 evaluating the effectiveness of behavioral programs for type 1 diabetes 

mellitus (T1DM). The key findings for KQs 1 and 2 include a summary of the strength of 

evidence (SOE) assessments. Further discussion is included in the subsequent sections of this 

chapter focusing on (1) the applicability of the findings, (2) contextualizing our results within 

previous literature, and (3) future research needs.

KQ 1. Behavioral Programs for T1DM and Behavioral, Clinical, 

and Health Outcomes; Diabetes-Related Health Care Utilization;

and Program Acceptability

There was moderate SOE showing reduction in hemoglobin A1c (HbA1c) at 6-month 

postintervention followup with percent HbA1c reduced by 0.31 for individuals who were enrolled 

in behavioral programs compared with those receiving usual care. For all other timepoints, there 

was no significant difference in HbA1c; the SOE was low due to risk of bias and imprecise effect 

estimates. For followup timepoints of 12 months or longer, the 95% CIs included our threshold 

for clinical importance such that we cannot rule out benefit for behavioral programs based on the 

available evidence. For individuals who were enrolled in behavioral programs compared with 

those receiving an active control, there was moderate SOE showing a clinically important 

reduction in HbA1c of 0.44 percent at 6-month postintervention followup. There was no 

difference in HbA1c at other timepoints, however the SOE was low and we cannot rule out a 

benefit for behavioral programs.

There was low SOE showing no difference in adherence to diabetes self-management (i.e., 

frequency of blood glucose checks or overall self-management behaviors) at end of intervention 

and 6-month followup for comparisons with usual care. For comparisons with active controls

there was insufficient SOE for adherence to diabetes self-management at all followup timepoints. 

There was moderate SOE of no difference at the end of intervention for generic HRQL, and 

insufficient evidence at longer followup. In comparisons with usual care, there was insufficient 

SOE to assess whether there was any effect on diabetes-specific HRQL at any timepoint, and low 

SOE of no difference for diabetes distress at end of intervention and 6-month followup. There 

were no data on HRQL for comparisons of behavioral programs with active controls. No trials 

reported on micro- and macrovascular complications or on all-cause mortality. The SOE grading 

was highly influenced by the moderate or high risk of bias (ROB) of individual studies, the 

imprecise estimates of effect, and (for insufficient SOE grades) the limited amount of data.

Evidence was insufficient to determine whether behavioral programs increased or decreased 

the number of diabetes-related hospital admissions, emergency department admissions, episodes 

of severe hypoglycemia, or episodes of severe hyperglycemia. Behavioral programs appear to be 

acceptable to patients with T1DM based on a proxy measure; our meta-analysis showed a 21

percent increased risk of attrition usual care compared with behavioral programs. 
74

KQ 2. Subgroups for Effectiveness in T1DM 

For the KQ, we examined the differential effect of patient characteristics on the effectiveness 

of behavioral programs for T1DM. In comparisons with usual care, results were consistent with 

those from KQ 1 when combining all studies of youth and adults. At 6 months, behavioral 

programs reduced HbA1c in youth by a statistically significant 0.28 percent and in adults by a 

non-statistically significant 0.38 percent. At end of intervention, the point estimates indicated 

greater benefit within the adult subgroup (0.28) than the youth subgroup (0.00), although neither 

of these values reached statistical significance. None of the point estimates exceeded the a priori 

established clinically important difference of 0.4 percent HbA1c. 

For subgroups based on age in comparisons with active controls, the small number of studies 

(and sample sizes) led to wide pooled 95% CIs which in some cases included values of clinical 

importance both for and against behavioral programs; the SOE was thus graded as insufficient in 

all but two cases. In studies of youth with followup to 12 months, there was low SOE of a 

clinically important (reduction by 0.52) benefit for behavioral programs; in studies of adults with 

6-month followup, there was low SOE of no difference in HbA1c.

KQ 3. Potential Moderation of Effectiveness for T1DM: 

Components, Intensity, Delivery Personnel, Method of 

Communication, Degree of Tailoring, and Level of Community 

Engagement 

To assess whether program factors (i.e., intensity, delivery personnel, method of 

communication, degree of tailoring, and level of community engagement) moderated the 

effectiveness of behavioral programs for T1DM, we performed univariate meta-regressions for 

comparisons between behavioral programs and usual care at longest followup. Program intensity, 

including duration, contact hours, and frequency of contacts, appeared not to influence program 

effectiveness; individual delivery appeared more favorable than group delivery of programs but 

the results did not reach statistical significance. We did not have enough studies to perform 

multivariable analysis, neither did we have enough to perform the univariate regressions for 

outcomes other than HbA1c.

KQ4. Harms for T1DM

No studies reported on the associated harms (i.e., activity-related injury) of behavioral 

programs.

Discussion of Key Findings for T1DM

Overall, behavioral programs seem to have some benefit in T1DM for reducing HbA1c, when 

followup extends beyond the immediate postintervention period up to 6 months. The delay in 

benefit may in part reflect the time required for this marker of glycemic control, indicating 

control over the past 2-3 months, to demonstrate change. Notable though, is the large diversity in 

program duration whereby end of intervention was anywhere between 1.5 and 25 months. 

Another contributor may be that a period of time is needed to integrate newly learned selfmanagement behaviors into one’s life; however, our findings of no differences in selfmanagement behaviors at any followup timepoint when behavioral programs were compared to 

usual care do not support this hypothesis. The beneficial findings for HbA1c at 6 months appear 
75

to be tempered by the findings of no difference at longer followup timepoints, although we are 

unable to confidently rule out benefit at long-term followup. An argument that the findings of 

benefit could be an artifact of differential attrition between groups—with those more motivated 

to or more successful in making positive changes returning for followup assessment—appears to 

be unlikely because of the lower (21%) attrition rate found for behavioral programs compared to 

usual care. 

There are at least a couple reasons why our findings may underestimate the effect of these 

programs should they be implemented in routine practice. The usual care group in several studies 

received some form of attention from the investigators (e.g., periodic telephone calls to maintain 

contact and encourage study participation), and this may have resulted in improved glycemic 

control for the comparator group and reduced the relative effects of the behavioral program. 

Participants (or their providers) in the usual care or active control groups (not being blinded to 

group assignment in most studies) may have become more motivated to practice better selfmanagement (including blood glucose regulation using insulin titrations), which could also 

attenuate differences between groups. Differences in the “usual care” provided may have also 

played a role, although this affect may be minimal considering recent evidence that variations in 

standard care in studies of behavioral interventions for youth with T1DM did not significantly 

impact study results.295

Our finding of a statistically significant and clinically important reduction by 0.44 percent 

HbA1c at 6-month followup for comparisons between behavioral programs and active controls is 

notable. As per our operational definition, behavioral programs consisted of interactive programs 

having a duration ≥4 weeks with the inclusion of behavior change techniques; because of this, 

traditional, didactic educational91,92,107,108 or support interventions87 were considered comparators 

rather than interventions. By offering an intervention to both study arms, these studies may have 

introduced less potential bias from lack of allocation concealment and blinding. Although quite 

promising, when drawing conclusions regarding the overall benefits of behavioral programs, this 

finding needs to be interpreted in light of results showing no differences for HbA1c at other 

timepoints and insufficient evidence to make conclusions about several other outcomes. 

Many of the included studies were directed at adolescents. Self-management of T1DM 

during adolescence is complex, often characterized by personal challenges and uncertainty, 

transitions to adult care, less frequent health care visits, and diminished parental involvement; 

consequently, glycemic control deteriorates over the course of childhood and adolescence for 

many youth with T1DM.296-299 For these reasons, many of the studies included in this review 

aimed to prevent deterioration of glycemic control rather than to improve it. The statistically 

significant reductions in HbA1c at 6-month followup (versus usual care), and the clinically 

important reductions in HbA1c at 6- and 12-month followup (0.60 and 0.52 percent, respectively) 

in comparisons with active controls in youth lend substantial support for these programs. 

Likewise, incorporating more demanding self-management behaviors may negatively impact 

social and emotional functioning, such that our findings of no difference in generic HRQL at end 

of intervention may be interpreted as positive.

Most studies for T1DM were undertaken in populations with baseline glycemic control ≥8.5 

percent HbA1c. While this may affect the applicability of the findings to some extent, clinicians 

may view this as highly relevant to their patient population of which many—particularly in their 

pubertal years—are struggling to achieve optimal control. Furthermore, the Diabetes Control and 

Complications Trial (DCCT)20 found that these individuals receive the greatest benefit from 

HbA1c reduction.
76

For T1DM, there was evidence that effectiveness appears not to be moderated by program 

intensity (i.e., duration, contact hours, or frequency of contacts), and that delivery to individuals 

compared with groups may be beneficial. We were unable to undertake any analysis to comment 

on the difference between educational and lifestyle programs, or the addition of a support 

component to DSME programs. Many individuals with T1DM under good glycemic control may 

have other risk factors (e.g., overweight, hyperlipidemia, hypertension) for which lifestyle 

programs may be warranted. Although some behavioral programs were of fairly long duration 

with highly intense contact with patients,88 only one explicitly incorporated a support 

component.82

Our pair-wise meta-analyses used the Hartung-Knapp-Sidik-Jonkman random effects 

model73-75 that typically provides a more conservative estimate of the 95% CI around pooled 

effect sizes than the common DerSimonian and Laird approach; the latter approach has been 

shown to lead to too many statistically significant results especially in the face of heterogeneity 

and few studies. The effect of our approach is that some results—especially those pooling few 

studies—are found statistically nonsignificant when another approach may find significance; 

moreover, the 95% CI in some cases spreads wider than those of the individual studies. For 

example, our reported 95% CI for the effect on HbA1c for youth receiving a behavioral program 

compared with an active control at 6-month followup is -2.56 to 1.36 (not significant due to 

inclusion of 0 [no effect]), although the DerSimonian and Laird approach provided an estimate 

of -0.95 to -0.25 (significant). This factor also applies those findings for T2DM on the overall 

effectiveness of behavioral programs across all outcomes. 

Key Findings and Discussion for Type 2 Diabetes 

(KQs 5 and 6)

This section presents the key findings for type 2 diabetes mellitus (T2DM). We begin by 

summarizing the effectiveness of behavioral programs across our key outcomes, based on 

comparator (i.e., usual care or active controls) and followup timepoint. Thereafter, we provide a 

brief summary and discussion of the findings for KQs 5 and 6 evaluating the potential of 

program components and delivery factors to moderate the effectiveness of behavioral programs 

for T2DM. Further discussion is included in the subsequent sections of this chapter focusing on 

(1) the applicability of the findings, (2) contextualizing our results within previous literature, and 

(3) potential needs for future research.

Effectiveness of Behavioral Programs Across Outcomes

There is evidence showing a beneficial effect of behavioral programs, compared to both 

usual care and other active interventions, at end of intervention for glycemic control; however, at 

longer followup results were only statistically significant at 6 months for comparison with active 

controls, and none of the results were considered to be clinically important based on our 

threshold of a 0.4 percent change in HbA1c. There was substantial statistical heterogeneity in 

these pairwise meta-analyses, supporting our subsequent analysis for KQs 5 and 6 to determine 

which program factors, and population characteristics, influence (and optimize) the effects.

Behavioral programs showed some benefits in terms of reducing BMI (0.21-0.92 kg/m2 to 

12-month followup), weight (1.3-1.68 kg; end of intervention) and waist circumference (3.2 cm; 

short term), and daily energy intake (64-150 kilocalories per day to 6 months)—mainly when 
77

compared with usual care. There was little evidence around the outcomes related to changes in 

physical activity and medication adherence, and findings were consistently of no difference.

Health-related quality of life was reported by fewer studies than anticipated. On average, 

findings of no difference were found for most studies and outcomes, except for Diabetes Distress 

where results favored behavioral programs compared with usual care at end of intervention but 

not at longer followup. Effects on diabetes complications were only reported for one study. 

Diabetic retinopathy was reduced by 14% and very-high-risk kidney disease by 31% in 

participants receiving a ≥8 year-long intensive lifestyle program compared with didactic 

education and support in the largest trial, conducted by the LookAHEAD research group.278,292

Mortality between behavioral programs and active control groups (5 comparisons; 6,050 

participants) was 14 percent lower for those receiving behavioral programs (RR, 0.86; 95% CI, 

0.77 to 0.96). There was no difference for comparisons with usual care (25 comparisons; 4,659 

participants; RR, 1.28; 95% CI, 0.84 to 1.94). 

KQ 5. Potential Moderation of Effectiveness for T2DM: 

Components, Intensity, Delivery Personnel, Method of 

Communication, Degree of Tailoring, and Level of Community 

Engagement 

In a network meta-analysis with usual care serving as the main reference, programs 

demonstrating effect sizes for HbA1c at or above our threshold for clinical importance (i.e., 0.4 

percent HbA1c difference between groups) represented all three major program component 

categories of diabetes self-management education (DSME), DSME and support, and lifestyle. 

The effect sizes of minimally intensive DSME programs (≤10 contact hours) were less than our 

threshold for clinical importance, but were all higher than that of educational interventions not 

meeting our criteria for a behavioral program (e.g., didactic education programs represented by 

many active controls). Programs having larger effect sizes and higher probabilities of being best 

(≥5 percent) were more often delivered in person rather than including technology. All effective 

programs using some form of technology were of moderate or high intensity.

Lifestyle programs resulted in the largest effect sizes for BMI. Program intensity appeared 

less important than method of delivery; providing some individual (rather than solely groupbased) delivery appears beneficial for improvements in BMI at longest followup.

KQ 6. Subgroups for Factors Moderating Effectiveness in T2DM

All of our results for this KQ relied on between-study rather than within-study comparisons, 

such that the effect of randomization is removed and the results are considered observational and 

possibly biased through confounding by other study-level characteristics. 

In terms of overall effectiveness at longest followup for HbA1c, participants with suboptimal

or poor glycemic control (≥7 percent HbA1c) appear to benefit more than those with good control 

(<7 percent) from behavioral programs when compared to usual care and active controls. The 

effect sizes were not clinically important for either group. Few differences were evident when 

evaluating potential moderation by program factors after rerunning the network meta-analysis of 

KQ 5 with a subgroup of studies having participants with suboptimal or poor baseline glycemic 

control. 

Older adults (≥65 years) did not benefit at longest followup in terms of reduction in HbA1c

from behavioral programs in comparison with usual care or active controls. In adults <65 years, 
78

the effect size for behavioral programs compared with usual care was statistically significant 

(reduction of 0.31 percent) and compared with active controls at longest followup was clinically 

important (0.43 percent). In a subgroup analysis of our original network meta-analysis of 

HbA1c—removing the studies of participants with a mean age ≥65—the most noticeable change 

was the increase in effect size for active controls incorporating dietary or physical activity 

interventions, which produced clinically important effects (0.55 percent reduction in HbA1c). The 

active controls still showed zero probability of success, perhaps due to the heterogeneity 

between, or small sample sizes of, the associated comparisons.

In comparison to usual care and active controls, behavioral programs offered to 

predominantly minority participants (≥ 75 percent nonwhite) appear to provide more benefit for 

glycemic control than those offered to populations with a lower proportion (<75 percent) of 

nonwhite individuals. The effect size for minority participants reached clinical importance when 

comparing behavioral programs to usual care (0.43 percent reduction in HbA1c). Based on 

univariate regression analyses for the subgroups based on race/ethnicity, none of the program 

factors (e.g., intensity, delivery personnel) reached statistical significance for influencing the 

effectiveness of behavioral programs compared to usual care on HbA1c. Lifestyle programs 

appeared favorable over DSME or DSME plus support for the group of studies (n=24) with 

predominantly white individuals (p=0.07). 

Discussion of Key Findings for T2DM

The focus of our review for T2DM was on identifying factors contributing to the 

effectiveness of multicomponent programs. Our review includes the highest number of studies to 

date, and focuses on programs meeting current recommendations to change patient behaviors and 

patient-important outcomes (e.g., HRQL). We relied on strict inclusion criteria to study 

interactive programs incorporating behavioral strategies aiming to change multiple behaviors, 

without confounding by changes to medical management (e.g., medication changes, differing 

frequency of provider visits). Another strength of the review is our analytical approach; the 

network meta-analysis enabled differentiation of the various comparators, and incorporation of 

comparisons (e.g., intervention vs. intervention) often not amenable to other strategies. 

Moderate- and high-intensity (≥11 hours contact time) programs appear to be necessary to 

provide individuals with clinically important effects on HbA1c; this outcome may also benefit 

from in-person delivery rather than using technology. For BMI, providing some individual 

delivery, rather than solely relying on group formats, appears beneficial. 

Our review adds to previous findings in that lifestyle programs—not specifically training 

people in diabetes related self-care behaviors but focusing more on weight reduction and 

increases in physical activity—may provide similar or more benefit than DSME programs for 

improving glycemic control for individuals with T2DM. A feature of behavioral programs that 

may be particularly attractive to patients is that unlike some common drug therapies used in the 

management of type 2 diabetes, behavioral programs have the potential to reduce HbA1c without 

contributing to weight gain. Our review confirms previous suggestions that programs with an 

interactive nature, employing behavioral approaches and covering multiple behaviors, are 

beneficial when compared with didactic educational interventions. Although perhaps not to a 

clinically important degree for individuals, the burgeoning growth of this disease means that 

even small gains in glycemic control from behavioral programs may serve as a substantial 

benefit for public health. 
79

Our finding that single-topic, non-educational interventions (active controls of dietary or 

physical activity interventions) offer more benefit than do basic education interventions, supports 

the need to carefully distinguish and account for different comparators during the systematic 

review process. We used longest followup timepoint for the analyses to answer KQ 5 and 6, 

which may capture the “durability” of the programs better than restricting the analysis to the 

immediate postintervention period. 

It appears from our network meta-analysis results for HbA1c, that both individual and group 

delivery can be beneficial; this agrees with other work in this area300 (also see below section on 

Findings in Relation to What is Already Known). Our results for KQ6 suggest that other factors 

(or combination of factors) may influence the effects of this variable; for instance, delivery 

format may be highly dependent upon the population served and program content. Studies within 

nodes having high effect sizes which offered programs in groups tended to be those offered to 

minorities, including Mexican Americans,150,152,208 where support from peers was incorporated as 

a key program feature. 

We were unable to draw any conclusions about the choice of delivery personnel from the 

network meta-analysis when answering KQ 5; there were too few studies in the categories of 

DSME and support, and lifestyle to account for this variable when creating the nodes. Drawing 

from the pair-wise meta-analysis results for those trials comparing two or more interventions (i.e. 

comparative effectiveness), there may be no difference when program delivery is conducted by 

heath care professionals or by lay providers (e.g., peers with diabetes, community health 

workers). Four trials (575 subjects) found no difference (MD, 0.00; 95% CI, -0.23 to 

0.23)144,172,227,256 in effectiveness when programs were delivered by peers compared with health 

care professionals. One trial (72 subjects) found no difference when the support phase of DSME 

was provided by clinic staff compared with diabetes educators (MD, 0.02; 95% CI, -0.60 to 

0.64).227 Most trials reported on extensive training programs for those delivering their programs. 

One reason why programs delivered by health care professionals were not superior may be that 

physicians, nurses, and dietitians receive little or no training in behavioral techniques as part of 

their formal education. This may be particularly true when extensive knowledge and expertise in 

theoretically guided approaches (e.g. motivational interviewing), or several behavior change 

techniques are required. Diabetes educators, highly regarded for their thorough knowledge and 

skills in diabetes education, may require substantial training and supervision when starting to 

apply advanced behavioral techniques such as motivational interviewing; to date this technique 

has shown benefit for improved glycemic control in the short term when delivered by clinical 

psychologists232,250 but not by diabetes educators.248 It could be speculated that the benefits for 

glycemic control may improve with time after those delivering the programs gain experience.

Our findings for KQ 6 suggest that people with good baseline glycemic control (<7 percent 

HbA1c), advancing age (≥65 years), and white/European ancestry (studies not having a majority 

of minority participants) may not benefit to the same extent as participants with suboptimal or 

poor glycemic control, racial/ethnic minorities, and those of younger age. The finding of better 

success for patients with poorer glycemic control has been found in previous systematic reviews 

(for one example see Duke et al.300). Intuitively, individuals with good glycemic control may not 

achieve as much benefit from behavioral programs—there is little room for improvement and 

good self-management behaviors may already be practiced regularly. Our findings may have 

been different if we had chosen a different level of glycemic control for subgroup analysis; after 

consultation with several experts we were unable to define a “poor control” cut-point. Some 

caution is warranted when considering our findings for the age subgroups; there were limited 
80

studies where the average participant age was ≥65 years, as specified for our subgroup analysis. 

Moreover, we relied on between-study differences for these subgroup analyses rather than 

within-study analysis for individual programs. Many trials included a broad range of ages up to 

72 years, and the median age of the entire sample in this review was 58; the overall applicability 

of the results for KQ5 appear to apply to middle- and older-aged adults. Results may have 

differed for other patient-important outcomes such as quality of life; however, there were 

insufficient data for these analyses. 

The findings for ethnicity need to be interpreted in light of our method of analysis and 

differences in baseline glycemic control between subgroups. Glycemic control appeared to be 

worse for the minority (HbA1c=8.80 percent) compared with the majority/white (HbA1c=7.60 

percent) subgroup; it is thus hard to distinguish if ethnicity or glycemic control is more likely to 

have the greater influence in moderating program effectiveness. Ethnic minority groups have 

been shown to have higher HbA1c levels than Caucasian groups; this finding holds after adjusting 

for factors affecting glycemic control (i.e., age, sex, BMI, duration of disease, mean plasma 

glucose) and thus may not be influenced by behavioral programs.301 Conversely, a systematic 

review by Nam et al.302 which found benefit for culturally tailored diabetes education, found that 

lower baseline HbA1c levels better predicted positive responses to the programs. There are likely 

additional factors involved. Many investigators enrolling a large proportion of ethnic minorities 

in the trials included in this review adapted programs in ways to make them more culturally and 

linguistically acceptable—often including peers in the delivery or social support groups—which 

may have enhanced their effectiveness. Our reliance on study-level data to create subgroups (i.e., 

the entire study was delivered to minorities) may have limited our ability to capture differences 

in effects from programs delivered to a wider population base, which may reflect routine practice 

in many community health settings. 

Although our discussion has centered on our findings related to our KQs, which focus on 

effect moderation, the important benefits shown by the LookAHEAD research group252 should 

be highlighted. Reduction in retinopathy by 14 percent and nephropathy by 31 percent in those 

participating in a long-duration, intensive lifestyle program cannot be ignored.

278,293

Additionally, our findings from pairwise meta-analysis of 14 percent reduced mortality between 

those receiving behavioral programs and active controls was heavily influenced by the large 

weight (contributing to >50 percent of the pooled effect) of this study in the analysis. 

Findings in Relation to What Is Already Known

For T1DM, this review provides a current examination of the effectiveness of behavioral 

programs for multiple outcomes and across all age groups. Few systematic reviews have been 

conducted over the past decade,3,5,6 and most reviews have assessed the effects of a broad range 

of interventions (some of which were didactic education or single topic interventions) in diverse 

settings.3,4,6,7 All we identified have focused on children and adolescents, and several included 

newly diagnosed patients. When calculated, effect sizes for glycemic control and psychosocial 

outcomes in general demonstrated very modest improvement at longest followup.4,5 [Of note, 

much previous work reports results using a standardized effect size measure, rather than an 

unstandardized mean difference in absolute value of percent HbA1c, as used in this review. Our 

results of 0.31 (vs. usual care) and 0.43 (vs. active control) percent reduction at 6-month 

followup represent approximately a 0.22 and 0.28 standardized effect size, respectively, which 

are commonly considered small].303 Our results which incorporate more recent and larger studies 

confirm the findings of previous reviews. 
81

In their systematic review and meta-analysis in 2006, Murphy et al.6 called for larger, 

multicenter trails to better investigate the effects of psychoeducational interventions for T1DM. 

They also stated that no adequately powered RCT had proven effective for patients with poor 

glycemic control. Our review included reports from two multicentre trials (one by these authors) 

comparing behavioral programs (clinic-integrated group family sessions focused on family 

teamwork,102 and DSME with motivational interviewing and solution-focused brief therapy85) to 

standard care and enrolling patients with poor glycemic control (baseline HbA1c ≥9 percent in 

both trials).85,102 Neither study found benefit in terms of HbA1c. These authors also noted a need 

to determine if content or contact was what mattered most; studies (n=2) in their review that 

compared intervention to attention/active controls showed little effect due to improvements for 

the comparator group.6 Our finding of a higher effect size for comparisons with active controls

than with usual care (at 6 months) suggest that content may have an effect. In a 2000 review, 

Hampson et al.4 noted that outcomes should be evaluated at an appropriate time to reflect the 

impact of the intervention. Our results for glycemic control seem to agree with this assertion; 

HbA1c improved at 6-month followup but not at end of intervention which may have reflected 

the sensitivity of this outcome marker. 

Several systematic reviews have performed some form of analysis to identify factors 

moderating the effectiveness of self-management and educational programs for T2DM. In 2002, 

Norris et al.51 reported on a meta-regression examining several factors including intervention 

characteristics (e.g., program duration, number of contacts, contact time, group vs. individual 

delivery) on effectiveness of self-management education for HbA1c from 37 comparisons; the 

authors also evaluated the effectiveness based on baseline glycemic control and age. The only 

significant factor was the total contact time, with the authors concluding that HbA1c was reduced 

by 0.04 percent for every additional hour of contact time, over the range 1-28 hours. However, 

the meta-regression was conducted for comparisons of the educational interventions with a 

combination of usual care and active controls (“additional care delivered”)—several of which 

received the same contact time as the intervention group. When considering this factor, there was 

a nonsignificant positive relationship between the differences in contact time and improved 

HbA1c. Although our review took a different approach by using a network meta-analysis to 

incorporate a large suite of comparisons, we found very similar results—most programs showing 

effect sizes at longest followup (to 12-months) in the clinically important range have contact

times in the moderate- or high-intensity categories (≥11h) and the mean contact time was 26.4 

hours. We were also able to confirm that active controls (especially didactic educational 

programs) offer less benefit in reducing HbA1c than do behavioral programs meeting our 

operational definition. 

Another group led by Norris31 undertook regression analysis to investigate similar factors for 

22 weight loss interventions for people with T2DM. The authors found no significant interaction 

with followup interval, duration of intervention, intervention contacts, or baseline weight. Unlike 

the previous work, the authors separated out comparisons by comparator group and thus had 

little data (2-6 studies) for each analysis. Both reviews led by this author31,51 included studies 

evaluating interventions focusing on one behavior (e.g., diet only), and studies where the effects 

of the intervention could not be clearly distinguished from that of additional disease/care 

management components.304,305 This may explain in part why our effect sizes for HbA1c at end of 

intervention are smaller than that (0.76 percent) found by Norris et al.51 

Shortly after the work by Norris and colleagues, another group used a similar approach to 

analyze which variables within an educational intervention best explained the variance in 
82

glycemic control. Evaluating HbA1c results assessed immediately after 28 interventions, Ellis et 

al.54 found a similar effect size as our results (0.32 percent reduction) and that face-to-face (i.e., 

in-person) delivery, cognitive reframing teaching method, and inclusion of exercise content 

collectively explained 44 percent of the variance in HbA1c. Their failure to obtain significance 

for the “dose” of the interventions was suggested by the authors to reflect the lack of variation in 

the dose of interventions; they suggested that a better marker than number of contacts or duration 

of intervention may have been total contact hours or a combined variable (such as our use of 

contacts per month for the univariate meta-regressions). Since all of the interventions examined 

included a diet component, the benefit from adding an exercise component would seem to 

suggest these were what we usually classified as lifestyle interventions. Our results for KQ 5 are 

similar, in that they suggest in-person (face-to-face) delivery may be more efficacious than 

delivery via technology for patients with T2DM.

We can also compare our findings to those of three more recent reviews. Chodosh et al.46

examined essential components of chronic disease self-management programs (diabetes, 

hypertension, and osteoarthritis) and found statistically significant differences for diabetes 

programs (n=26) that provided feedback (e.g., support after self-management program 

completion); this effect was consistent across the outcomes of HbA1c, blood glucose, and weight. 

This finding reflects our results—suggesting DSME and support programs have higher efficacy 

than DSME programs—although the overall effect reported by these authors (0.81 percent) is 

higher than ours; again this difference in effect size may reflect an overestimate of effects of selfmanagement interventions by inclusion of studies which include changes to medical 

management.306,307 In a qualitative examination of 11 interventions showing beneficial effects for 

socially disadvantaged populations, Glazier et al.55 observed several factors contributing to 

effectiveness, including one-to-one interventions, providing feedback, and high intensities with 

>10 contact times delivered over a longer period of time (≥6 months). These are consistent with 

our findings. The findings for feedback, or “booster sessions”, and providing >10 contact hours 

were also found by Fan and Sidani48 in another qualitative comparison of effect sizes of 50 

RCTs. These authors also observed that larger effect sizes were found for one-on-one or mixed 

formats versus group formats; our results with respect to delivery method were inconclusive. 

Our findings for KQ 5 are similar to those of previous work, although we have provided 

some new insight from use of a larger sample of studies, exclusion of programs not meeting 

current recommendations or introducing possible confounding by medical care variation, and an 

innovative analytical approach to assess multiple variables and account for a suite of 

comparisons not always applicable to other techniques. 

Applicability

Type 1 Diabetes

The inclusion criteria for most studies did not specify a minimum HbA1c level; however, for 

all studies the mean HbA1c was over 7 percent. For most (70 percent), the mean HbA1c was over 

8.5 percent. The results of this report may only be applicable to individuals with suboptimal and 

poor glycemic control.

For studies targeting youth, the mean age across most studies ranged from 12 to 15 years. 

Therefore, the results should be generally applicable to older children and adolescents. One trial 

targeted younger children (8 to 12 years);100 it is unclear whether the results of this report are 

applicable to younger children.
83

For studies targeting adults, the mean age across studies ranged from 30 to 49 years. No 

studies specifically targeted older adults (≥65 years), therefore it is unclear if the results are 

applicable to older adults.

Approximately 50 percent of studies specified that participants have a minimum duration of 

T1DM of ≥1 year. For studies that targeted youth, the mean duration of diabetes ranged from 2.7 

to 7.3 years. The results of this report may only be applicable to children and adolescents who 

have been diagnosed with T1DM for at least 2 years. For studies that targeted adults, the mean 

duration of diabetes ranged from 7.5-23 years. It is unclear whether the results of this report are 

applicable to adults whose T1DM has been recently diagnosed.

We did not find evidence to confirm or refute whether behavioral programs are more or less 

efficacious for other subgroups, including sex or racial or ethnic minorities. 

All of the studies targeting adults were conducted in the United Kingdom, Europe, or New 

Zealand. It is unclear whether the results from these studies are applicable to community health 

settings in the United States. For youth, most studies (70 percent) were conducted in the United 

States; the remaining studies were conducted in Europe and Australia. Despite potential 

differences in settings and health systems, results were similar across the studies. 

The studies were conducted primarily in outpatient diabetes clinics affiliated with a 

secondary or tertiary care hospital. Our findings are generally applicable to these settings in the 

United States.

Type 2 Diabetes

The range of baseline HbA1c in the included RCTs was 6.3-12.3 percent (median=8.0) which 

would appear to make the results of this review applicable to the majority of people enrolling in 

behavioral programs. We conducted subgroup analyses for KQ 6 based on baseline glycemic 

control (<7 vs. ≥7 percent HbA1c) at the study level, which provided some insight into the 

relative effectiveness based on this level of glycemic control. This analysis may be limited by the 

small number of studies in the <7 percent subgroup (n=9 RCTs) and because the analysis was 

based on between-study rather than within-study variability in glycemic control which may not 

accurately reflect differences for individual programs. The results of this report are therefore 

most applicable to people having HbA1c levels ≥7 percent. 

The range of mean ages in the included studies was 45-72 years (median=58), therefore the 

results of the pairwise meta-analyses on overall effectiveness and of the analysis for KQ 5 are 

most applicable to middle- and older-aged adults. Our subgroup analysis for KQ 6 based on age 

(<65 vs. ≥65 years) provided some data on the relative effectiveness for these age groups, but 

similar to that for baseline HbA1c, may be limited by the small sample of studies on older adults 

(n=9) and our analytical approach. Our exclusion criteria related to duration of diabetes (mean 

<1 year)—implemented in order to capture programs providing training in ongoing selfmanagement and lifestyle behaviors—limits the relevance of this review for newly diagnosed 

patients. The mean duration of diabetes ranged from 1-18 years with a median of 8.1 years. No 

study performed subgroup analysis based on duration of diagnosis (≤1 vs. >1 year) and we were 

unable to perform this at the study level because the mean in all cases was above 1 year. The 

results appear to be applicable to both men and women, and for people on a variety of diabetes 

treatment regimens (19.2 percent were on insulin). Overall, there was fairly good representation 

of individuals reporting a minority racial/ethnic background. Subgroup analysis based on those 

studies reporting of race/ethnicity (24 comparisons for <75 percent minorities vs. 33 
84

comparisons for ≥75 percent minorities) was conducted to increase the relevancy of the findings 

to these population groups. 

The results seem applicable to community health settings in the United States. The majority 

(63 percent) of trials were conducted in the United States, and based on our inclusion criteria 

related to Human Development Index62 all studies were performed in countries of similar 

development status. Some trials were conducted in academic settings in health fields—thought to 

have application in community health settings—although there may be some differences if these 

programs were delivered in different settings. Although details were reported inconsistently, 

health systems differences (i.e., usual care) may vary widely between study populations and 

could potentially influence the results obtained from behavioral programs. The effect from this 

difference should be minimal for this review, since we limited our results to changes from 

baseline between groups randomly assigned and judged to receive similar medical care. 

Limitations of the Comparative Effectiveness Review 

Process

This review followed rigorous methodological standards, which were detailed a priori. 

Nevertheless, several limitations are inherent within systematic reviews in general. 

First, there is a possibility of selective reporting bias (e.g., researchers only reporting positive 

outcomes) and publication bias, whereby unexpectedly strong results from large trials are 

selectively reported. In terms of selective outcome reporting, we were able to locate several trial 

registries and protocols to compare planned and published outcome reporting; most studies 

included in this review were judged as having low bias in this respect. We may have missed 

some reports of behavioral programs in diabetes, particularly those showing weak results. We 

believe publication bias is minimal: (1) our literature search was comprehensive, systematic, and 

included published and unpublished literature (e.g., some reports were located by contacting 

authors of studies published in abstract form256 or without data on our outcomes of interest);90 (2) 

there was large variation in effect sizes reported; and (3) we did not have a minimum sample size 

for inclusion, and several of the included studies were small. Visualization of funnel plots did not 

suggest publication bias, and using the Egger test78 for our outcome with the most data (HbA1c) 

resulted in no significant indication of bias for comparisons with usual care (p=0.25) or active 

controls (p=0.21) at end of intervention. Selected studies were confined to the English language 

because we felt that these reports would be most applicable to the end-users of this review who 

create recommendations or implement programs for people with diabetes within the United 

States. Moreover, effect sizes in language restricted reviews have shown to not differ 

significantly (overestimating effect sizes by 2 percent) from those not having restrictions.308

Study selection bias was limited by having two independent reviewers perform screening and 

selection; we feel confident that study exclusion was based on explicit and appropriate reasoning 

which was clearly understood by reviewers. 

Our decisions on study design were based largely on the availability of studies employing 

designs having lowest potential for bias. For T1DM, we expected to have a limited amount of 

evidence from RCTs, so we included other controlled studies. For T2DM, we only included 

RCTs which may have left out some studies evaluating outcomes and issues of relevance to this 

review. The body of evidence from RCTs was known in advance to be large, and provided 132 

primary reports of trials undertaken in many health settings with diverse populations. In addition, 

adding non-RCT evidence would have substantially increased the potential bias in results. 

Behavioral interventions are already moderately complex—in terms of variability in social and 
85

environmental contextual factors—and trials of such interventions rarely include blinded 

allocation or outcomes assessment; because of these factors we thought it desirable to avoid 

additional limitations arising from selection bias and confounding, for which non-RCTs and 

observational studies are more prone.

The interventions evaluated in the included trials were highly diverse in their content, 

delivery, and setting. Our inclusion criteria attempted to reduce some of the diversity by 

including studies of interventions meeting a fairly rigid operational definition of a behavioral 

program. We also excluded studies where the effects of the behavioral program could not be 

isolated (e.g., due to confounding by differences between groups in medical care management), 

where the patient population would not have already received previous basic education (e.g., 

enrollment of only newly diagnosed patients), and when the setting was not applicable to 

community health settings in the United States. Furthermore, we categorized the comparators 

into three groups to avoid further complexity in comparisons. Our categorization of the 

comparators and interventions was based on the factors of interest in this review, was informed 

by previous literature and input from our Key Informants and Technical Expert Panel, and was 

based in several cases on multiple reviewer deliberation and consensus. Nevertheless, we likely 

did not capture all factors of importance to some stakeholders. The diversity in programs and 

other contextual factors was apparent when considering the high heterogeneity in results from 

the pairwise meta-analysis for HbA1c and some other outcomes in T2DM. Our analyses in KQs 

3, 5 and 6 related to factors influencing the effectiveness of behavioral programs for both T1DM 

and T2DM. 

Our analyses for T2DM should be interpreted based on our approaches to address program 

durability and the relatively high-level categorization of program components. Our network 

meta-analyses and subgroup analyses used outcome data at longest postintervention followup, 

which for the majority of studies was end of intervention (i.e., after all contact between 

participants and program personnel ceased) or, for fewer, between 1-6 months followup. Only 8 

of 112 trials had followup longer than 6 months. This approach was used to include as many 

studies as possible (i.e., those that did report data for end of intervention) and also to reflect the 

durability of the programs in terms of their potential for impacting long-term health. Our results 

from the pairwise meta-analyses for HbA1c in T2DM at each followup timepoint indicated 

reduced effectiveness at followup durations longer than end of intervention; this suggests that the 

mean effect sizes from our network meta-analysis at longest followup may underestimate the 

effects at end of intervention. 

One of the reasons to differentiate between DSME and DSME plus support was to account 

for the variation in intensity between these categories, due to the support or maintenance phases 

(having lower contact frequency) in DSME plus support programs. Our definition of end of 

intervention was standardized for all programs, rather than taking into account any distinct 

phases within programs. There was large variation between programs in terms of the distribution 

of contacts, including the reporting of such, and attempting to capture effects based on relative 

intensity within programs or specific to the maintenance phase would have been difficult and 

unreliable. Because of this, one might have anticipated that the effects from DSME programs 

(without a maintenance phase) would have been higher than other programs having the same 

overall contact time. This does not appear to be the case, and our results would suggest that 

adding a support phase (often offering psychosocial support and/or behavior change strategies 

targeting behavior maintenance) was an important program feature of many lifestyle and DSME 

plus support programs regardless of the distribution of visits.
86

As stated in the Results chapter, we did not include program tailoring and degree of 

community engagement in the analysis for KQ5; these factors were considered to overlap in 

meaning to some extent with delivery method (e.g., use of technology enhancing tailoring) and 

delivery personnel (e.g., use of non-health providers providing community engagement), and the 

ones we used were thought to better represent the differences between the programs assessed in 

this review. With our focus on programs incorporating interaction with program personnel, we 

cannot comment on the effects of programs delivered entirely by way of technology which may 

provide sophisticated mechanisms to interact with and motivate participants or closely monitor 

disease management. Cost analysis of implementing differing behavioral programs was not 

addressed in this review. 

Limitations of the Evidence Base

The evidence base was inadequate to fully answer the Key Questions, particularly with 

respect to the limited number of outcomes evaluated in several studies. We were unable to fully 

evaluate all outcomes of interest for several KQs. For KQ 1 for T1DM, there were limited data 

available to assess the SOE for many outcomes, including behavioral outcomes related to 

changes in dietary intake or physical activity, and clinical and health outcomes apart from HbA1c

and HRQL. Our assessment of factors contributing to effectiveness of behavioral programs for 

T1DM (KQ 3) was limited to the outcome of HbA1c and to univariate meta-regressions (rather 

than network meta-analysis to simultaneously examine multiple comparisons and factors) 

because too few studies provided data on other outcomes. No studies contributed data for our 

assessment of harms (KQ 4). For KQs 5 and 6 related to T2DM, our network meta-analysis 

allowed for multiple comparisons but there were still too few studies reporting on outcomes 

besides HbA1c and BMI to enable meaningful groupings into nodes to examine multiple factors 

simultaneously. Considering that behavioral changes are the key mediators to achieving clinical 

and health outcomes, analysis based on valid outcomes of changes to physical activity or diet 

would be ideal; greater use of these outcomes, especially via objective means, would be 

beneficial. The meta-regressions used for the subgroup analysis on ethnicity in KQ 6 are limited 

by comparator (only usual care) and did not allow us to capture multiple variables in a single 

analysis. In addition, our subgroup analyses for KQ 2 and 6 were mostly limited to indirect 

methods (i.e., relying on between-study rather than within-study comparisons). Several outcomes 

of importance to patients and policymakers, such as quality of life, development of 

complications, and health care utilization, were reported by few studies to confidently support 

conclusions of effect, or to analyze in terms of moderation by program factors.

Many trials had methodological limitations introducing some ROB. Blinding of participants 

and personnel are arguably difficult for trials of behavioral programs especially when the 

comparator is usual care. According to our decision rules for assessing ROB, a low ROB for 

participant and personnel blinding was granted if the comparator was an attention or active 

control and the authors stated some means to blind the study hypothesis from participants, and if 

there was a structured training and protocol followed for the personnel. Participant blinding in 

this manner was rarely reported. Lack of blinding of participants, and their healthcare providers, 

may result in underestimation of the effects of behavioral programs compared to comparators, 

due to cointervention; adjustments of insulin or oral antidiabetic medications may have been 

performed to a greater extent in the comparison groups than in the intervention groups. This 

effect may have been heightened because none of the studies we reviewed included any 

limitations or restrictions on adjustment of insulin or other medications. Blinding of outcome 
87

assessors was also rarely reported, despite the high feasibility of ensuring this procedure. These 

two domains resulted in medium or high ROB being assigned for most trials for their subjective 

outcomes. For both subjective and objective outcomes, medium or high ROB was assigned in 

many cases from lack of intention-to-treat analysis (e.g., only reporting on results for completers) 

and/or from high participant attrition. Despite our inclusion of only RCTs, some studies had 

small sample sizes and a few failed to achieve adequate baseline comparability in demographic 

or clinical characteristics. 

Research Gaps

Table 15 highlights some potential research needs based on our KQs.

Table 15. Potential research needs, by Key Question 

KQ Potential Research Needs

1 

Effectiveness 

for T1DM

There were limited data to determine the effectiveness of behavioral programs for T1DM at 

durations of followup beyond 6 months. Future studies should strive to assess outcomes at 

longer term followup, to better determine the effects of these programs for periods of time 

that may better influence long-term outcomes of complications and quality of life.

1 

Effectiveness 

for T1DM

There was insufficient evidence to demonstrate whether lifestyle programs (i.e., combining 

structured dietary and physical activity interventions) are effective for T1DM. Many 

individuals with T1DM under good glycemic control may have other risk factors (e.g., 

overweight, hyperlipidemia, hypertension) for which these programs may be warranted. Trials 

of lifestyle programs enrolling people with both types of diabetes should undertake subgroup 

analysis.

1 & 3 

Effectiveness 

and 

moderating 

factors for 

T1DM

The effectiveness of adding a clinical, behavioral, psychosocial, or educational support 

component to programs in T1DM is unknown. These may be useful for prolonging the effects 

of behavioral programs, and to address some of the psychosocial aspects of the disease 

(particularly in adolescents) to a greater extent.

3

Moderating 

factors for 

T1DM

Only one study in T1DM compared behavioral programs delivered in person with those 

delivered via some form of technology allowing for interaction between the provider and 

patient. Transitioning individuals with diabetes between pediatric and adult care facilities and 

providers can be challenging, hampered by the scheduling structure of traditional clinics at a 

time in life when contact information and location of home, work and education is often 

changing frequently. As a result further research on providing behavioral programs via 

technology or creative scheduling is warranted for adolescents and young adults with 

diabetes. 

3

Moderating 

factors for 

T1DM

Several studies for T2DM included a small sub-sample of people with T1DM. Trials of 

lifestyle programs that incorporate exercise need to perform subgroup analysis by type of 

diabetes particularly when evaluating the outcome of glycemic control; adjustment of insulin 

in individuals with T1DM for exercise can be challenging and could result in differential 

effects of lifestyle programs on glycemic control depending on the type of diabetes and 

medical management of the participants. 

3 & 5

Moderating 

factors for 

T1DM & 

T2DM

There was large diversity in the reporting and use of behavior change techniques employed 

within the programs. An evaluation of the effects of different strategies may shed additional 

light on the factors (within components) determining effectiveness for behavioral programs.

5

Moderating 

factors for 

T2DM

The identification of what combination of providers (e.g., physician, nurse, dietitian, 

pharmacists, social workers, psychologist, and trained lay individuals) is best for 

implementation of behavioral programs for T2DM deserves further evaluation. 
88

Table 15. Potential research needs, by Key Question (continued)

KQ Potential Research Needs

5

Moderating 

factors for 

T2DM

Clinical psychologists are often employed to deliver program components that incorporate 

advanced behavioral approaches, such as motivational interviewing; this approach may not 

be feasible for all settings or within all program budgets. More research is required to 

determine the effectiveness of similar programs when delivered by other personnel trained to 

use these behavioral techniques. 

5

Moderating 

factors for 

T2DM

Few trials directly compared interactive programs delivered in person to those delivered via 

technology. Because a technology-based approach may lessen resource burden, help to 

reach patients living in rural areas, and/or be desirable for younger adults more familiar with 

technology, its effectiveness needs further evaluation.

6

Effectiveness 

for different 

subgroups in 

T2DM

Trials including populations of diverse ethnic backgrounds should perform subgroup analysis 

based on age, ethnicity, and baseline glycemic control to further explore outcomes for these 

groups from programs that are not designed specifically for them, as might be common in 

most community health settings. 

All Few trials evaluated outcomes important to patients and decisionmakers (e.g. quality of life, 

micro- and macrovascular complications, health care utilization) in a manner that allowed 

pooling of results across studies. Use of widely accepted generic quality of life measures 

would be beneficial. 

All Study attrition rates affected the overall risk of bias substantially; more research on methods 

for maintaining study participation is required.

All The risk of bias from participant and personnel blinding was high in most trials. Although 

many trials compared behavioral programs to active controls (limiting risk of bias due to 

blinding) comparisons with usual care would benefit from some mechanism to blind 

participants from the study hypothesis. Blinding of outcome assessors should always be 

attempted for subjective outcomes.

All There is a need for consensus on what constitutes clinically important differences in 

outcomes for behavioral programs, such that they can be interpreted in meaningful ways for 

clinicians and patients. 

KQ = Key Question; T1DM = type 1 diabetes; T2DM = type 2 diabetes

Conclusions

This systematic review found that behavioral programs (especially DSME) for T1DM have 

some benefit on glycemic control when followup extends beyond the immediate postintervention 

period up to 6 months after the program. There was no significant difference at end of 

intervention or followup longer than 6 months, although our confidence in these findings is low

and we cannot rule out benefit. There was no difference in generic HRQL at end of intervention, 

or in diabetes distress or self-management behaviors at up to 6-month followup, although the 

SOE was low for these findings with the exception of generic HRQL at end of intervention 

(moderate SOE). Data were insufficient to draw any conclusions for other timepoints for generic 

HRQL, diabetes distress, and self-management, and for other outcomes including diabetesspecific HRQL, change in body composition or lifestyle behaviors, micro- and macrovascular 

complications, and mortality. Encouraging patients with T1DM to participate in behavioral 

programs to improve outcomes apart from HbA1c is not supported by the current evidence. 

For T2DM, our analyses showed limited benefit in glycemic control from DSME programs 

offering ≤10 hours of contact with delivery personnel, and suggested that in-person delivery of 

behavioral programs is more beneficial than incorporation of technology. We found that 

programs focused on lifestyle or on DSME can have similar benefit in terms of glycemic control, 

and that lifestyle programs appear better for reducing BMI. Whether the behavioral program is 

delivered by a health care professional or a trained lay person, or via individual or group format 

appears less important based on the available evidence. Behavioral programs seem to benefit 

individuals having suboptimal or poor glycemic control more than those with optimal control. 
89

Tailoring programs to ethnic minorities—such as offering culturally appropriate materials and 

incorporating group interaction with peers—appears beneficial. While efforts should be made to 

provide culturally sensitive programs, community health settings that serve populations that are 

diverse in language and ethnicity may not have the opportunity to provide this flexible 

programming to meet each group’s needs. 

The finding that behavioral programs offer some benefit in terms of glycemic control in 

individuals with diabetes underscores the need for care providers to be educated in behavioral 

techniques, and related topics such as facilitating support groups and family communication 

training—something that is often missing within the formal training of physicians, nurses, 

dietitians, and pharmacists. This review was unable to assess the differential effects on program 

success by single versus multiple health care providers, or by delivery teams having differing 

compositions of providers (including trained lay professionals)—this topic deserves further 

evaluation. Few trials evaluated patient-important outcomes (e.g., quality of life) in a manner to 

pool results across studies. Use of widely accepted quality of life measures would be beneficial.

Efforts at integrating behavioral programs into care settings that incorporate the latest 

management guidelines should be prioritized. Program evaluation is an important component to 

build into the implementation of any behavioral program for diabetes, to ensure that it is the 

correct fit to be effective for the population that it is attempting to serve. At this time, there 

remains a need for clinicians to evaluate each patient’s success after participating in these 

programs, should additional means be necessary to control their disease more adequately to 

prevent devastating complications.
90

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19754629.

297. Ingerski LM, Anderson BJ, Dolan LM, et al. 

Blood glucose monitoring and glycemic 

control in adolescence: contribution of 

diabetes-specific responsibility and family 

conflict. J Adolesc Health. 2010 

Aug;47(2):191-7. PMID: 20638012.

298. Schilling LS, Knafl KA, Grey M. Changing 

patterns of self-management in youth with 

type I diabetes. J Pediatr Nurs. 2006 

Dec;21(6):412-24. PMID: 17101399.

299. Peters A, Laffel L. Diabetes care for 

emerging adults: recommendations for 

transition from pediatric to adult diabetes 

care systems. Diabetes Care. 2011 

Nov;34(11):2477-85. PMID: 22025785.

300. Duke SaS, Colagiuri S, Colagiuri R. 

Individual patient education for people with 

type 2 diabetes mellitus. Cochrane Database 

Syst Rev. 2009(1):CD005268. PMID: 

19160249.

301. Herman WH, Dungan KM, Wolffenbuttel 

BH, et al. Racial and ethnic differences in 

mean plasma glucose, hemoglobin A1c, and 

1,5-anhydroglucitol in over 2000 patients 

with type 2 diabetes. J Clin Endocrinol 

Metab. 2009 May;94(5):1689-94. PMID: 

19276235.

302. Nam S, Janson SL, Stotts NA, et al. Effect 

of culturally tailored diabetes education in 

ethnic minorities with type 2 diabetes: a 

meta-analysis. J Cardiovasc Nurs. 2012 

Nov-Dec;27(6):505-18. PMID: 21747287.

303. Cohen J. A power primer. Psychological 

bulletin. 1992 Jul;112(1):155-9. PMID: 

19565683.

304. Sone H, Tanaka S, Iimuro S, et al. Longterm lifestyle intervention lowers the 

incidence of stroke in Japanese patients with 

type 2 diabetes: a nationwide multicentre 

randomised controlled trial (the Japan 

Diabetes Complications Study). 

Diabetologia. 2010 Mar;53(3):419-28. 

PMID: 20054522.

305. Trento M, Passera P, Bajardi M, et al. 

Lifestyle intervention by group care 

prevents deterioration of type II diabetes: a 

4-year randomized controlled clinical trial. 

Diabetologia. 2002 Sep;45(9):1231-9. 

PMID: 12242455.

306. Jaber LA, Halapy H, Fernet M, et al. 

Evaluation of a pharmaceutical care model 

on diabetes management. Ann 

Pharmacother. 1996 Mar;30(3):238-43. 

PMID: 8833557.

307. Kim HS, Oh JA. Adherence to diabetes 

control recommendations: impact of nurse 

telephone calls. J Adv Nurs. 2003 

Nov;44(3):256-61. PMID: 14641395.

308. Moher D, Pham B, Klassen TP, et al. What 

contributions do languages other than 

English make on the results of metaanalyses? J Clin Epidemiol. 2000 

Sep;53(9):964-72. PMID: 11004423.
108

Abbreviations and Acronyms

95% CIs 95 percent confidence intervals

AC active control

AHRQ Agency for Healthcare Research and Quality

BMI body mass index

CDC Centers for Disease Control and Prevention

DSME diabetes self-management education

DSMP Diabetes Self-Management Profile questionnaire

EOI end of intervention

EPC Evidence-based Practice Center

h hour

HbA1c hemoglobin A1c

HRQL health-related quality of life

I

2 I squared statistic (measure of statistical heterogeneity)

KIs Key Informants

KQ key question

m month

MD mean difference

n number

NA not applicable

NMA network meta-analysis

NR not reported

OR odds ratio

PAID Problem Areas in Diabetes questionnaire

PB “probability of being best”

PICOTS populations, interventions, comparators, outcomes, timing, settings

QOL quality of life

RCT randomized controlled trial

ROB risk of bias

RR risk ratios

SD standard deviation

SDSCA Summary of Diabetes Self-Care Activities

SMBG self-monitoring of blood glucose

SMD standardized mean differences

SOE strength of evidence

SRDR Systematic Review Data Repository

T1DM type 1 diabetes mellitus

T2DM type 2 diabetes mellitus

TEP Technical Expert Panel

TOO Task Order Officer

U.S. United States

UC usual care

UK United Kingdom

VO2max maximal oxygen uptake

yr year
A-1

Appendix A. Operational Definitions

Behavioral Program

An organized, multicomponent diabetes-specific program with repeated interactions by one or 

more trained individuals, with a duration of ≥4 weeks, to improve disease control and/or patient 

health outcomes, and consisting of at least one of: a) diabetes self-management education 

(DSME); b) a structured dietary intervention (related to any of weight loss, glycemic control, or 

reducing risk for complications) together with one or more additional components; or c) a 

structured exercise or physical activity intervention together with one or more additional 

components. Additional components for (b) and (c) above may include interventions related to: 

diet or physical activity; behavioral change (including but not limited to goal setting, problem 

solving, motivational interviewing, coping skills training, cognitive behavioral therapy 

strategies); relaxation or stress reduction; blood glucose regulation; medication adherence; or 

self-monitoring for diabetic complications (foot, eye and renal tests).

Interventions must include contact with those delivering the program, rather than sole reliance on 

“interactive behavior change technology” (e.g., patient-centered websites, automated telephone 

calls, DVDs, touch screen kiosks). While these tools show great promise for helping health 

systems meet the growing demand for diabetes management and support, they have been shown 

to be most effective when they support human contact.35

Below, we expand on specific elements of the above operational definition. They are presented 

in the order in which they appear in the definition. 

Trained Individual 

This can be an individual who has either received formal education and training in diabetes 

management and/or education, or has received some form of training to provide the specific 

program offered. There is no requirement to have a certain degree level or certification. This may 

include what is described as a lay health worker, “expert patient,” “promotores” (Spanish term), 

or peer, as long as training is provided.

Repeated Interaction 

There must be more than one interactive session―via face-to-face or indirect means―with the 

personnel providing the program. 

Duration of ≥4 Weeks 

The minimum duration of 4 weeks does not include post-intervention follow-up assessments for 

outcome ascertainment. 

Diabetes Self-Management Education 

A program will be considered DSME if the authors state that it meets the standards for DSME in 

the country in which the program is delivered (i.e., the program does not just cover a set of 

recommended topics of education). We also will include programs aiming to change patient (not 

provider) behaviors that are reported to: 1) include individualized assessment of needs/behaviors 

(performed by the provider and/or patient); 2) provide education on multiple selfcare/management behaviors using interactive approaches (these may be combined with didactic 

and/or collaborative approaches); and 3) incorporate some form of behavior change strategy
A-2

(e.g., goal setting) whereby patients are trained to make informed decisions to self-manage their 

disease.

Not all topics must be provided to all patients and not all patients will receive the same 

duration/number of sessions, that is, there may be some tailoring of topics and delivery based on 

the needs assessment. 

Structured Dietary Intervention

Dietary interventions may related to weight loss (e.g., caloric restriction), glycemic control (e.g., 

carbohydrate counting, controlling glycemic index of foods), and/or reducing risk for 

complications or comorbidities (e.g., reduced saturated and trans fats, increased fiber). The 

intervention must include interactive education/training methods (i.e., must be more than the 

provision of information or advice) on more than one occasion. The diet composition may either 

be personalized to the patient or follow a predetermined composition (e.g., low calorie diet with 

<30 percent fat). 

Structured Physical Activity Intervention

Physical activity interventions must include either 1) personalized programs based on patient 

assessment and/or a patient’s goals to train and facilitate behavior change, or 2) a structured 

intervention with a pre-determined program of activity (i.e., type, frequency, intensity and 

duration). The intervention must include interactive education/training methods (i.e., must be 

more than the provision of information or advice) on more than one occasion.

Activities that do not provide considerable energy expenditure (moderate intensity or more; goal 

to reach >40 percent aerobic capacity) or strength training potential will not be included (e.g., 

yoga, tai chi, stretching) but may be considered relaxation or stress reduction interventions. 

Blood Glucose Regulation

This includes self-regulation of medication, diet, physical activity and so forth, based on results 

of blood glucose monitoring or awareness training. The intervention must consist of more than 

didactic teaching of blood glucose monitoring, teaching how to use pumps or other diabetes 

treatment technology, or teaching how to inject insulin. It may, for example, include practicing 

skills and problem solving on how to use the test results or to increase self-awareness to improve 

control through behaviors. 

Relaxation or Stress Reduction

This includes interactive training or teaching related to meditation, yoga and other forms of nonaerobic or resistance training, or specific relaxation exercises or techniques (e.g., biofeedback). It 

may or may not include supervised practice.

Behavior Change Strategies

These include strategies to change behaviors but are not solely focused on emotional well-being. 

Strategies include, but are not limited to, motivational interviewing, coping skills training, 

cognitive behavioral therapy or techniques, problem-solving, goal setting, behavioral 

contracting, support groups, use of incentives or rewards, environmental change or barrier 

reduction, parent simulation, family therapy (related to problems with disease management 

behaviors), or anchored instruction. They must be directed at more than the single behavior in 
A-3

the structured diet or physical activity interventions. For example, a diet intervention with goal 

setting and motivational interviewing that are only related to diet will not be considered two 

separate interventions. The strategies do not have to be based on theory but, where they are, this 

will be noted during data extraction. They do not include interventions limited to screening or 

therapeutic counseling for mental health diagnoses or emotional issues, although general 

psychosocial aspects and adaptation to disease will be included. 

Medication Adherence

Any ongoing or intermittent intervention (i.e., not one-time provision of advice or information) 

that is intended to increase adherence to medication for hyperglycemia or risk factor reduction

(e.g., lipid-lowering medications). This can be technology-based (e.g., text reminders via cell 

phone).

Self-Monitoring for Diabetic Complications

Any ongoing or intermittent intervention (i.e., not one-time provision of advice or information) 

that is intended to increase self-monitoring or screening for micro- or macrovascular 

complications (e.g., training on home foot care, reminders to attend screening appointments). 

This can be technology-based (e.g., text reminders via cell phone).

Note on Classification During Data Synthesis

Because there were very few studies evaluating programs with dietary and another (non-physical 

activity) component, or physical activity and another (non-dietary) component, we collapsed all 

programs that were not DSME into a “lifestyle” category which largely contained programs 

focusing on diet and physical activity.

Community Health Setting

A clinical practice setting with the primary purpose of providing health care to communitydwelling individuals (i.e., not hospital inpatients). Community health settings include ambulatory 

care clinics, outpatient clinics, primary care clinics, family physician clinics, and federally 

qualified health centers (i.e., Community Health Centers and Rural Health Centers). Programs 

that will be excluded are those delivered in inpatient settings and those offered in the community 

but without a link to a health clinic or center.

Comparators

Usual (or Routine/Standard) Care 

These consist of usual medical management of study participants, whether this was provided by 

the study investigators or other health care professionals; because medical care is so diverse, 

these groups could receive a minimally intense intervention such as provision of pamphlets or 

one individual session with an educator. Interventions which are very minimal (e.g. delivery of 

pamphlets) will be included in this category.
A-4

Active Comparator

Controls that were beyond usual care but not meeting our operational definition of a behavioral 

program were considered active controls (e.g., stand-alone dietary intervention, basic education 

program of short duration or not including behavioral approaches). 

Other Intervention

Anything that meets our definition of behavioral health program will be categorized as an 

intervention.
B-1

Appendix B. Literature Search Strategies

MEDLINE

Database: Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations and Ovid 

MEDLINE(R) 1946 to Present 

Search Title: Behavioral Health Programs for Diabetes_1

Search Date: 28 May 2014

Results: 15064

1. exp Diabetes Mellitus/

2. exp hypoglycemia/

3. diabet*.mp.

4. (noninsulin depend* or non insulin depend* or insulin depend*).mp.

5. (T1DM or T2DM or IDDM or NIDDM).mp.

6. or/1-5

7. exp Diabetes Insipidus/

8. (diabet* adj3 (insipidus not mellitus)).mp.

9. or/7-8

10. 6 not 9 (473318)

11. Behavior Therapy/

12. Blood Glucose Self-Monitoring/

13. Cognitive Therapy/

14. Community Health Centers/

15. Disease Management/

16. exp Exercise/ and (counsel* or intervention* or program* or train*).mp.

17. exp Exercise Therapy/

18. exp Directive Counseling/

19. Health Behavior/ and (counsel* or intervention* or program* or train*).mp.

20. Health Education/

21. Health Promotion/

22. exp Nutrition Therapy/

23. "Outcome Assessment (Health Care)"/

24. exp Patient Care Team/

25. exp Patient Compliance/

26. Patient Education as Topic/

27. Program Evaluation/

28. Relaxation Therapy/

29. Self Administration/

30. Self Medication/

31. Self Care/

32. Weight Loss/

33. (behavio?r adj2 therap*).mp.

34. (blood glucose adj2 monitor*).mp.

35. (cognitive adj2 therap*).mp.

36. (communit* adj2 (center* or centre*)).mp.
B-2

37. disease management.mp.

38. directive counsel*.mp.

39. ((behavio* or exercis* or diet* or fitness or life style* or lifestyle* or nutrition or physical 

activit* or problem solving or relax*) adj3 (counsel* or intervention* or program* or therap* or 

train* or treat*)).mp.

40. motivation* interview*.mp.

41. (self manag* or selfmanag* or self car* or selfcar*).mp.

42. or/11-41 (655126)

43. 10 and 42 (43958)

44. randomized controlled trial.pt.

45. controlled clinical trial.pt.

46. randomi?ed.ab.

47. placebo.ab.

48. drug therapy.fs.

49. randomly.ab.

50. trial.ab.

51. groups.ab.

52. or/44-51

53. exp animals/ not humans.sh.

54. 52 not 53

55. 43 and 54 (16442)

56. cohort studies/

57. follow-up studies/

58. longitudinal studies/

59. prospective studies/

60. cohort analy*.tw.

61. (cohort adj (study or studies)).tw.

62. (control* adj5 (before adj2 after)).tw.

63. (control* adj5 (pre* adj2 post*)).tw.

64. (follow up adj (study or studies)).tw.

65. longitudinal.tw.

66. (observational adj (study or studies)).tw.

67. prospective.tw.

68. or/56-67 (1252385)

69. exp animals/ not humans.sh.

70. 68 not 69

71. 43 and 70 (5831)

72. 55 or 71 (19002)

73. limit 72 to yr=“1993-2014” (16423)

74. limit 73 to english language (15064)

CENTRAL

Database: CENTRAL via Cochrane Library

Search Title: Behavioral Health Programs for Diabetes

Date Searched: 30 May 2014

Results: 8010
B-3

1. MeSH descriptor: [Diabetes Mellitus] explode all trees

2. MeSH descriptor: [Hypoglycemia] explode all trees

3. diabet*:ti,ab,kw

4. ("noninsulin depend*" or "non insulin depend*" or "insulin depend*"):ti,ab,kw

5. (T1DM or T2DM or IDDM or NIDDM):ti,ab,kw

6. #1 or #2 or #3 or #4 or #5

7. exp Diabetes Insipidus/

8. (diabet* near/3 (insipidus not mellitus)):ti,ab,kw

9. #7 or #8

10. #6 not #9 (31905)

11. MeSH descriptor: [Behavior Therapy] this term only

12. MeSH descriptor: [Blood Glucose Self-Monitoring] this term only

13. MeSH descriptor: [Cognitive Therapy] this term only

14. MeSH descriptor: [Community Health Centers] this term only /

15. MeSH descriptor: [Disease Management] this term only

16. MeSH descriptor: [Exercise] explode all trees

17. (counsel* or intervention* or program* or train*):ti,ab,kw

18. #16 and #17

19. MeSH descriptor: [Exercise Therapy] explode all trees

20. MeSH descriptor: [Directive Counseling] explode all trees

21. MeSH descriptor: [Health Behavior] this term only

22. (counsel* or intervention* or program* or train*):ti,ab,kw

23. #21 and #22

24. MeSH descriptor: [Health Education] this term only

25. MeSH descriptor: [Health Promotion] this term only

26. MeSH descriptor: [Nutrition Therapy] explode all trees

27. MeSH descriptor: [Outcome Assessment (Health Care)] this term only

28. MeSH descriptor: [Patient Care Team] explode all trees 

29. MeSH descriptor: [Patient Compliance] explode all trees

30. MeSH descriptor: [Patient Education as Topic] this term only

31. MeSH descriptor: [Program Evaluation] this term only

32. MeSH descriptor: [Relaxation Therapy] this term only

33. MeSH descriptor: [Self Administration] this term only

34. MeSH descriptor: [Self Medication] this term only

35. MeSH descriptor: [Self Care] this term only

36. MeSH descriptor: [Weight Loss] this term only 

37. (behavio*r near/2 therap*):ti,ab,kw

38. (“blood glucose” near/2 monitor*):ti,ab,kw

39. (cognitive near/2 therap*):ti,ab,kw

40. (communit* near/2 (center* or centre*)):ti,ab,kw

41. “disease management”:ti,ab,kw

42. “directive counsel*”:ti,ab,kw

43. ((behavio* or exercis* or diet* or fitness or “life style*” or lifestyle* or nutrition or “physical 

activit*” or “problem solving” or relax*) near/3 (counsel* or intervention* or program* or 

therap* or train* or treat*)):ti,ab,kw

44. “motivation* interview*”:ti,ab,kw
B-4

45. (“self manag*” or selfmanag* or “self car*” or selfcar*):ti,ab,kw

46. #11 or #12 or #13 or 14 or #15 or #18 or #19 or #20 or #23 or #24 or #25 or #26 or #27 or 

#28 or #29 or #30 or #31 or #32 or #33 or #34 or #35 or #36 or #37 or #38 or #39 or #40 or #41 

or #42 or #43 or #44 or #45 (175091)

47. #10 and #46 (9944)

limit: Publication Date from 1993 to 2014, in Trials (8010)

CINAHL

Database: CINAHL

Search Title: Behavioral Health Programs for Diabetes

Date Searched: 30 May 2014

Results: 8881

1. (MH "Diabetes Mellitus+")

2. (MH "Hypoglycemia+")

3. diabet*

4. "noninsulin depend*" or "non insulin depend*" or "insulin depend*"

5. T1DM or T2DM or IDDM or NIDDM

6. S1 OR S2 OR S3 OR S4 OR S5

7. (MH "Diabetes Insipidus+")

8. diabet* N3 (insipidus not mellitus)

9. S7 OR S8

10. S6 not S9 (120,132)

11. (MH "Behavior Therapy")

12. (MH "Blood Glucose Self-Monitoring")

13. (MH "Cognitive Therapy")

14. (MH "Community Health Centers")

15. (MH "Diabetes Education") 

16. (MH "Diet Therapy+")

17. (MH "Disease Management")

18. (MH "Exercise+") AND (counsel* or intervention* or program* or train*)

19. (MH "Health Behavior") AND (counsel* or intervention* or program* or train*)

20. (MH "Health Education")

21. (MH "Health Promotion")

22. (MH "Motivational Interviewing")

23. (MH "Multidisciplinary Care Team+")

24. (MH "Outcome Assessment")

25. (MH "Patient Compliance+")

26. (MH "Patient Education")

27. (MH "Program Evaluation")

28. (MH "Self Administration")

29. (MH "Self Medication")

30. (MH "Self Care")

31. (MH "Therapeutic Exercise+")

32. (MH "Weight Loss")

33. behavio#r N2 therap*
B-5

35. “blood glucose” N2 monitor*

36. cognitive N2 therap*

36. communit* N2 (center* or centre*)

37. “disease management”

38. “directive counsel*”

39. (behavio* or exercis* or diet* or fitness or “life style*” or lifestyle* or nutrition or “physical 

activit*” or “problem solving” or relax*) N3 (counsel* or intervention* or program* or therap* 

or train* or treat*)

40. “motivation* interview*”

41. “self manag*” or selfmanag* or “self car*” or selfcar*

42. S7 OR S8 OR S9 OR S10 OR S11 OR S12 OR S13 OR S14 OR S15 OR S16 OR S17 OR 

S18 OR S19 OR S20 OR S21 OR S22 OR S23 OR S24 OR S25 OR S26 OR S27 OR S28 OR 

S29 OR S30 OR S31 OR S32 OR S33 OR S34 OR S35 OR S36 OR S37 OR S38 OR S39 OR 

S40 OR S41 (334531)

43. S10 AND S42 (27139)

44. (MH "Clinical Trials+")

45. PT Clinical trial

46. TX clinic* n1 trial*

47. TX ( (singl* n1 blind*) or (singl* n1 mask*) ) or TX ( (doubl* n1 blind*) or (doubl* n1 

mask*) ) or TX ( (tripl* n1 blind*) or (tripl* n1 mask*) ) or TX ( (trebl* n1 blind*) or (trebl* n1 

mask*) )

48. TX randomi* control* trial*

49. (MH "Random Assignment")

50. TX random* allocat*

51. TX placebo*

52. (MH "Placebos")

53. (MH "Quantitative Studies")

54. TX allocat* random*

53. (MH "Quantitative Studies")

54. TX allocat* random*

55. S44 OR S45 OR S46 OR S47 OR S48 OR S49 OR S50 OR S51 OR S52 OR S53 OR S54

56. (MH "Animals+") NOT (MH "Human")

57. S55 NOT S56

58. S43 AND S57 (7921)

59. (MH “Concurrent Prospective Studies”)

60. (MH “Nonexperimental Studies”)

61. (MH “Prospective Studies”)

62. “cohort analy*”

63. cohort N1 (study or studies)

64. control* N5 (before N2 after)

65. control* N5 (pre* N2 post*)

66. “follow up” N1 (study or studies)

67. longitudinal

68. observational N1 (study or studies)

69. prospective

70. S59 OR S60 OR S61 OR S62 OR S63 OR S64 OR S65 OR S66 OR S67 OR S68 OR S69
B-6

71. (MH "Animals+") NOT (MH "Human")

72. S70 not S71

73. S43 AND S72 (2627)

74. S58 OR S73 (9468)

75. S74 Limiters – English Language; Publication Date: 19930101-20141231 (8881)

Ovid Embase

Database: Ovid Embase 1988 to 2014 Week 21

Search Title: Behavioral Health Programs for Diabetes_2

Date Searched: May 29, 2014

Results: 24629

1. exp diabetes mellitus/

2. exp hypoglycemia/

3. diabet*.mp.

4. (noninsulin depend* or non insulin depend* or insulin depend*).mp.

5. (T1DM or T2DM or IDDM or NIDDM).mp.

6. or/1-5

7. exp diabetes insipidus/

8. (diabet* adj3 (insipidus not mellitus)).mp.

9. or/7-8

10. 6 not 9 (613880)

11. behavior therapy/

12. blood glucose monitoring/

13. cognitive therapy/

14. diabetes education/

15. exp diet therapy/

16. directive counseling/

17. disease management/

18. drug self administration/

19. exp Exercise/ and (counsel* or intervention* or program* or train*).mp.

20. Health Behavior/ and (counsel* or intervention* or program* or train*).mp.

21. health center/

22. health education/

23. health promotion/

24. exp kinesiotherapy/

25. nutrition education/

26. outcome assessment/

27. patient care/

28. exp patient compliance/

29. patient education/

30. exp program evaluation/

31. rapid response team/

32. relaxation training/

33. self care/

34. weight reduction/
B-7

35. (behavio?r adj2 therap*).mp.

36. (blood glucose adj2 monitor*).mp.

37. (cognitive adj2 therap*).mp.

38. (communit* adj2 (center* or centre*)).mp.

39. disease management.mp.

40. directive counsel*.mp.

41. ((behavio* or exercis* or diet* or fitness or life style* or lifestyle* or nutrition or physical 

activit* or problem solving or relax*) adj3 (counsel* or intervention* or program* or therap* or 

train* or treat*)).mp.

42. motivation* interview*.mp.

43. (self manag* or selfmanag* or self car* or selfcar*).mp.

44. or/11-43 (1217935)

45. 10 and 44 (121429)

46. random*.mp. 

47. animals/ not (animals/ and humans/)

48. 46 not 47

49. 45 and 48 (18450)

50. cohort analysis/

51. longitudinal study/

52. prospective study/

53. (cohort adj (study or studies)).tw.

54. (control* adj5 (before adj2 after)).tw.

55. (control* adj5 (pre* adj2 post*)).tw.

56. (follow up adj (study or studies)).tw.

57. (prospective adj (study or studies)).tw.

58. or/50-57

59. animals/ not (animals/ and humans/)

60. 58 not 59

61. 45 and 60 (9212)

62. 49 or 61 (25875)

63. limit 62 to yr=“1993-2014” (25632)

64. limit 63 to english language (24629)

Ovid PsycINFO

Database: Ovid PsycINFO 1987 to May Week 4 2014

Search Title: Behavioral Health Programs for Diabetes_3

Date Searched: 29 May 2014

Results: 4008

1. exp Diabetes/

2. Hypoglycemia/

3. diabet*.mp.

4. (noninsulin depend* or non insulin depend* or insulin depend*).mp.

5. (T1DM or T2DM or IDDM or NIDDM).mp.

6. or/1-5

7. Diabetes Insipidus/
B-8

8. (diabet* adj3 (insipidus not mellitus)).mp.

9. or/7-8

10. 6 not 9 (18569)

11. Behavior Therapy/

12. Client Centered Therapy/

13. Client Education/

14. Cognitive Therapy/

15. exp Community Services/

16. exp Compliance/

17. exp Counseling/

18. Disease Management/

19. Drug Self Administration/

20. exp Exercise/ and (counsel* or intervention* or program* or train*).mp.

21. Health Behavior/ and (counsel* or intervention* or program* or train*).mp.

22. exp Health Care Delivery/

23. Health Care Services/

24. Health Education/

25. Health Promotion/

26. Movement Therapy/

27. Motivational Interviewing/

28. Physical Activity/

29. exp Program Evaluation/

30. Recreation Therapy/

31. exp Relaxation Therapy/

32. Self Monitoring/

33. Self Care Skills/

34. Weight Control/

35. Weight Gain/

36. Weight Loss/

37. (behavio?r adj2 therap*).mp.

38. (blood glucose adj2 monitor*).mp.

39. (cognitive adj2 therap*).mp.

40. (communit* adj2 (center* or centre*)).mp.

41. disease management.mp.

42. directive counsel*.mp.

43. ((behavio* or exercis* or diet* or fitness or life style* or lifestyle* or nutrition or physical 

activit* or problem solving or relax*) adj3 (counsel* or intervention* or program* or therap* or 

train* or treat*)).mp.

44. motivation* interview*.mp.

45. (self manag* or selfmanag* or self car* or selfcar*).mp.

46. or/11-45 (258474)

47. 10 and 46 (5964)

48. control*.tw. 

49. random*.tw.

50. exp treatment/

51. or/ 48-50
B-9

52. exp animals/ not humans.sh.

53. 51 not 52

54. 47 and 53 (4248)

55. cohort analy*.tw.

56. (cohort adj (study or studies)).tw.

57. (control* adj5 (before adj2 after)).tw.

58. (control* adj5 (pre* adj2 post*)).tw.

59. (follow up adj (study or studies)).tw.

60. longitudinal.tw.

61. (observational adj (study or studies)).tw.

62. prospective.tw.

63. or/55-62 

64. exp animals/ not humans.sh.

65. 63 not 64

66. 47 and 65 (502)

67. 54 or 66 (4367)

68. limit 67 to yr=“1993-2014” (4103)

69. limit 68 to english language (4010)

70. remove duplicates from 69 (4008)

PubMed

Database: PubMed

Search Title: 

Date Searched: 30 May 2014

Results: 670

1. "Diabetes Mellitus"[Mesh]

2. "Hypoglycemia"[Mesh]

3. diabet*[tiab]

4. "noninsulin dependent"[tiab] OR "non insulin dependent"[tiab] OR "insulin dependent"[tiab]

5. T1DM[tiab] OR T2DM[tiab] OR IDDM[tiab] OR NIDDM[tiab]

6. #1 OR #2 OR #3 OR #4 OR #5

7. "Diabetes Insipidus"[Mesh] 

8. diabet*[tiab] AND (insipidus[tiab] NOT mellitus[tiab])

9. #7 OR #8

10. #6 NOT #9 (472248)

11. "Behavior Therapy"[Mesh:NoExp]

12. "Blood Glucose Self-Monitoring"[Mesh]

13. "Cognitive Therapy"[Mesh:NoExp]

14. "Community Health Centers"[Mesh:NoExp] 

15. "Disease Management"[Mesh:NoExp]

16. "Exercise"[Mesh] AND (counsel* or intervention* or program* or train*)

17. "Exercise Therapy"[Mesh]

18. "Directive Counseling"[Mesh]

19. “Health Behavior”[Mesh] AND (counsel* or intervention* or program* or train*)

20. "Health Education"[Mesh:NoExp]
B-10

21. "Health Promotion"[Mesh:NoExp]

22. "Nutrition Therapy"[Mesh]

23. "Outcome Assessment (Health Care)"[Mesh:NoExp]

24. "Patient Care Team"[Mesh]

25. "Patient Compliance"[Mesh]

26. "Patient Education as Topic"[Mesh:NoExp]

27. "Program Evaluation"[Mesh:NoExp]

28. "Relaxation Therapy"[Mesh:NoExp]

29. "Self Administration"[Mesh]

30. "Self Medication"[Mesh] /

31. "Self Care"[Mesh:NoExp]

32. "Weight Loss"[Mesh:NoExp]

33. "behavior therapy"[tiab] OR "behaviour therapy"[tiab] OR "behavior therapies"[tiab] OR 

"behaviour therapies"[tiab] OR "behavioral therapy"[tiab] OR "behavioural therapy"[tiab] OR 

"behavioral therapies"[tiab] OR "behavioural therapies"[tiab]

34. "blood glucose monitoring"[tiab]

35. "cognitive therapy"[tiab] OR "cognitive therapies"[tiab]

36. "community centre"[tiab] OR "community centres"[tiab] OR "community center"[tiab] OR 

"community centers"[tiab]

37. "disease management"[All Fields]

38. "directive counseling"[All Fields]

39. ((behavio*[tiab] or exercis*[tiab] or diet[tiab] or fitness[tiab] or "life style"[tiab] or "life 

styles"[tiab] or lifestyle*[tiab] or nutrition[tiab] or "physical activity"[tiab] or "problem 

solving"[tiab] or relax*[tiab]) AND (counsel*[tiab] or intervention*[tiab] or program*[tiab] or 

therap*[tiab] or train*[tiab] or treat*[tiab]))

40. "motivational interviewing"[tiab] OR "motivational interview"[tiab] OR "motivational 

interviews"[tiab]

41. "self manage"[tiab] OR "self managed"[tiab] OR selfmanag*[tiab] or "self care"[tiab] or 

selfcar*[tiab]

42. #11 OR #12 OR #13 OR #14 OR #15 OR #16 OR #17 OR #18 OR #19 OR #20 OR #21 OR 

#22 OR #23 OR #24 OR #25 OR #26 OR #27 OR #28 OR #29 OR #30 OR #31 OR #32 OR #33 

OR #34 OR #35 OR #36 OR #37 OR #38 OR #39 OR #40 OR #41 (965205)

43. #10 AND #42 (56413)

44. randomized controlled trial [pt] 

45. controlled clinical trial [pt]

46. randomized [tiab]

47. placebo [tiab]

48. drug therapy [sh]

49. randomly [tiab]

50. trial [tiab]

51. groups [tiab]

52. #44 OR #45 OR #46 OR #47 OR #48 OR #49 OR #50 OR #51

53. animals [mh] NOT humans [mh]

54. #52 NOT #53

55. #43 AND #54 (20350)

56. "Cohort Studies"[Mesh:NoExp]
B-11

57. "Follow-Up Studies"[Mesh]

58. "Longitudinal Studies"[Mesh:NoExp]

59. "Prospective Studies"[Mesh]

60. "cohort analysis"[tiab] OR "cohort analyses"[tiab]

61. "cohort study"[tiab] OR "cohort studies"[tiab]

62. "controlled before and after"[tiab] OR "controlled before after"[tiab]

63. control*[tiab] AND pre[tiab] AND post[tiab] AND (study[tiab] OR studies[tiab])

64. "follow up study"[tiab] OR "follow up studies"[tiab]

65. longitudinal[tiab]

66. "observational study"[tiab] OR "observational studies"[tiab]

67. prospective[tiab]

68. #56 OR #57 OR #58 OR #59 OR #60 OR #61 OR #62 OR #63 OR #64 OR #65 OR #66 OR 

#67

69. animals [mh] NOT humans [mh]

70. #68 NOT #69

71. #43 AND #70 (7284)

72. #55 OR #71 (23770)

73. #72 Filters activated: Publication date from 2014/01/01 to 2014/12/31 (685)

74. #73 Filters activated: English (670)

Single search string: 

Search: ((((("Diabetes Mellitus"[Mesh]) OR ("Hypoglycemia"[Mesh]) OR (diabet*[tiab]) OR 

("noninsulin dependent"[tiab] OR "non insulin dependent"[tiab] OR "insulin dependent"[tiab]) 

OR (T1DM[tiab] OR T2DM[tiab] OR IDDM[tiab] OR NIDDM[tiab])) NOT ((diabet*[tiab] 

AND (insipidus[tiab] NOT mellitus[tiab])) OR ("Diabetes Insipidus"[Mesh]))) AND (("self 

manage"[tiab] OR "self managed"[tiab] OR selfmanag*[tiab] OR "self care"[tiab] OR 

selfcar*[tiab]) OR ("motivational interviewing"[tiab] OR "motivational interview"[tiab] OR 

"motivational interviews"[tiab]) OR ((behavio*[tiab] OR exercis*[tiab] OR diet[tiab] OR 

fitness[tiab] OR "life style"[tiab] OR "life styles"[tiab] OR lifestyle*[tiab] OR nutrition[tiab] OR 

"physical activity"[tiab] OR "problem solving"[tiab] OR relax*[tiab]) AND (counsel*[tiab] OR 

intervention*[tiab] OR program*[tiab] OR therap*[tiab] OR train*[tiab] OR treat*[tiab])) OR 

("directive counseling"[All Fields]) OR ("disease management"[All Fields]) OR ("community 

centre"[tiab] OR "community centres"[tiab] OR "community center"[tiab] OR "community 

centers"[tiab]) OR ("cognitive therapy"[tiab] OR "cognitive therapies"[tiab]) OR ("blood glucose 

monitoring"[tiab]) OR ("behavior therapy"[tiab] OR "behaviour therapy"[tiab] OR "behavior 

therapies"[tiab] OR "behaviour therapies"[tiab] OR "behavioral therapy"[tiab] OR "behavioural 

therapy"[tiab] OR "behavioral therapies"[tiab] OR "behavioural therapies"[tiab]) OR ("Weight 

Loss"[Mesh:noexp]) OR ("Self Care"[Mesh:noexp]) OR ("Self Medication"[Mesh]) OR ("Self 

Administration"[Mesh]) OR ("Relaxation Therapy"[Mesh:noexp]) OR ("Program 

Evaluation"[Mesh:noexp]) OR ("Patient Education as Topic"[Mesh:noexp]) OR ("Patient 

Compliance"[Mesh]) OR ("Patient Care Team"[Mesh]) OR ("Outcome Assessment (Health 

Care)"[Mesh:noexp]) OR ("Nutrition Therapy"[Mesh]) OR ("Health Promotion"[Mesh:noexp]) 

OR ("Health Education"[Mesh:noexp]) OR ("Health Behavior"[Mesh] AND (counsel* OR 

intervention* OR program* OR train*)) OR ("Directive Counseling"[Mesh]) OR ("Exercise 

Therapy"[Mesh]) OR ("Exercise"[Mesh] AND (counsel* OR intervention* OR program* OR 

train*)) OR ("Disease Management"[Mesh:noexp]) OR ("Community Health 
B-12

Centers"[Mesh:noexp]) OR ("Cognitive Therapy"[Mesh:noexp]) OR ("Blood Glucose SelfMonitoring"[Mesh]) OR ("Behavior Therapy"[Mesh:noexp]))) AND (((randomized controlled 

trial[pt]) OR (controlled clinical trial[pt]) OR (randomized[tiab]) OR (placebo[tiab]) OR (drug 

therapy[sh]) OR (randomly[tiab]) OR (trial[tiab]) OR (groups[tiab])) NOT (animals[mh] NOT 

humans[mh]))) OR ((((("Diabetes Mellitus"[Mesh]) OR ("Hypoglycemia"[Mesh]) OR 

(diabet*[tiab]) OR ("noninsulin dependent"[tiab] OR "non insulin dependent"[tiab] OR "insulin 

dependent"[tiab]) OR (T1DM[tiab] OR T2DM[tiab] OR IDDM[tiab] OR NIDDM[tiab])) NOT 

((diabet*[tiab] AND (insipidus[tiab] NOT mellitus[tiab])) OR ("Diabetes Insipidus"[Mesh]))) 

AND (("self manage"[tiab] OR "self managed"[tiab] OR selfmanag*[tiab] OR "self care"[tiab] 

OR selfcar*[tiab]) OR ("motivational interviewing"[tiab] OR "motivational interview"[tiab] OR 

"motivational interviews"[tiab]) OR ((behavio*[tiab] OR exercis*[tiab] OR diet[tiab] OR 

fitness[tiab] OR "life style"[tiab] OR "life styles"[tiab] OR lifestyle*[tiab] OR nutrition[tiab] OR 

"physical activity"[tiab] OR "problem solving"[tiab] OR relax*[tiab]) AND (counsel*[tiab] OR 

intervention*[tiab] OR program*[tiab] OR therap*[tiab] OR train*[tiab] OR treat*[tiab])) OR 

("directive counseling"[All Fields]) OR ("disease management"[All Fields]) OR ("community 

centre"[tiab] OR "community centres"[tiab] OR "community center"[tiab] OR "community 

centers"[tiab]) OR ("cognitive therapy"[tiab] OR "cognitive therapies"[tiab]) OR ("blood glucose 

monitoring"[tiab]) OR ("behavior therapy"[tiab] OR "behaviour therapy"[tiab] OR "behavior 

therapies"[tiab] OR "behaviour therapies"[tiab] OR "behavioral therapy"[tiab] OR "behavioural 

therapy"[tiab] OR "behavioral therapies"[tiab] OR "behavioural therapies"[tiab]) OR ("Weight 

Loss"[Mesh:noexp]) OR ("Self Care"[Mesh:noexp]) OR ("Self Medication"[Mesh]) OR ("Self 

Administration"[Mesh]) OR ("Relaxation Therapy"[Mesh:noexp]) OR ("Program 

Evaluation"[Mesh:noexp]) OR ("Patient Education as Topic"[Mesh:noexp]) OR ("Patient 

Compliance"[Mesh]) OR ("Patient Care Team"[Mesh]) OR ("Outcome Assessment (Health 

Care)"[Mesh:noexp]) OR ("Nutrition Therapy"[Mesh]) OR ("Health Promotion"[Mesh:noexp]) 

OR ("Health Education"[Mesh:noexp]) OR ("Health Behavior"[Mesh] AND (counsel* OR 

intervention* OR program* OR train*)) OR ("Directive Counseling"[Mesh]) OR ("Exercise 

Therapy"[Mesh]) OR ("Exercise"[Mesh] AND (counsel* OR intervention* OR program* OR 

train*)) OR ("Disease Management"[Mesh:noexp]) OR ("Community Health 

Centers"[Mesh:noexp]) OR ("Cognitive Therapy"[Mesh:noexp]) OR ("Blood Glucose SelfMonitoring"[Mesh]) OR ("Behavior Therapy"[Mesh:noexp]))) AND ((("Cohort 

Studies"[Mesh:noexp]) OR ("Follow-Up Studies"[Mesh]) OR ("Longitudinal 

Studies"[Mesh:noexp]) OR ("Prospective Studies"[Mesh]) OR ("cohort analysis"[tiab] OR 

"cohort analyses"[tiab]) OR ("cohort study"[tiab] OR "cohort studies"[tiab]) OR ("controlled 

before and after"[tiab] OR "controlled before after"[tiab]) OR (control*[tiab] AND pre[tiab] 

AND post[tiab] AND (study[tiab] OR studies[tiab])) OR ("follow up study"[tiab] OR "follow up 

studies"[tiab]) OR (longitudinal[tiab]) OR ("observational study"[tiab] OR "observational

studies"[tiab]) OR (prospective[tiab])) NOT (animals[mh] NOT humans[mh])))

AADE Proceedings

Conference Proceeding: AADE Proceedings

Search Title: N/A

Date Searched: 27 June 2014

https://event.crowdcompass.com/aade14/custom-list/Schedule
B-13

URL provided by Michelle Crain, AADE Marketing and Communications Coordinator 

mcrain@aadenet.org

Note: No availability to abstracts from 2011-2013 meetings.

ADA Proceedings

Conference Proceeding: ADA Proceedings (via Embase)

Search Title: N/A

Date Searched: 26 June 2014

Results: 3 PDFs

1. american diabetes association.ti.

2. limit 1 to (yr=2011 –Current” and (conference abstract or conference paper or conference 

proceeding or “conference review”)) (3)

CDA Proceedings

Conference Proceeding: CDA Proceedings

Search Title: N/A

Date Searched: 27 June 2014

Results: 3 journal issues 

Hand searched issues of the Canadian Journal of Diabetes on ScienceDirect: 

http://www.sciencedirect.com/science/journal/14992671/

EASD Proceedings

Conference Proceeding: EASD (European Association for the Study of Diabetes) Proceedings

Search Title: N/A

Date Searched: 27 June 20143

Results: 3 links

Meeting abstracts available through the EASD website: 

http://www.easd.org/index.php?option=com_content&view=article&id=69&Itemid=509

IDF Proceedings

Conference Proceeding: IDF Proceedings

Search Title: N/A

Date Searched: 27 June 2014

Results: 2 links (2012 conference not available)

Meeting abstracts available through the IDF website: 

http://www.idf.org/final-programme

SMB Proceedings

Conference Proceeding: SBM Proceedings

Search Title: N/A
B-14

Date Searched: 27 June 2014

Results: 4 links to program PDFs

Meeting abstracts/programs available through the SBM website: 

http://www.sbm.org/meetings/past

ISBNPA Proceedings

Conference Proceeding: ISBNPA (International Society for Behavioral, Nutrition and Physical 

Activity) Proceedings

Search Title: N/A

Date Searched: 27 June 2014

Results: 4 links to programs/abstracts

Meeting abstracts/programs available through the ISBNPA website: 

https://secure.isbnpa.org/annual-meeting/index.cfm

ClinicalTrials.gov

Trial Registry: ClinicalTrials.gov

Date Searched: 25 – 26 June, 2014

Results: 2070

1. "Diabetes Mellitus" [DISEASE] AND ( life style OR lifestyle OR life styles OR lifestyles ) 

[TREATMENT] AND ( "01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] (291)

2. "Diabetes Mellitus" [DISEASE] AND ( self management ) [TREATMENT] AND ( 

"01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] (197)

3. "Diabetes Mellitus" [DISEASE] AND ( behavior OR behaviour OR behavioral OR 

behavioural ) [TREATMENT] AND ( "01/01/2009" : "12/31/2014" ) [FIRST-RECEIVEDDATE] (710)

4. "Diabetes Mellitus" [DISEASE] AND ( education OR educational ) [TREATMENT] AND ( 

"01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] (403)

5. "Diabetes Mellitus" [DISEASE] AND ( blood glucose regulation ) [TREATMENT] AND ( 

"01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] (14)

6. "Diabetes Mellitus" [DISEASE] AND ( medication adherence ) [TREATMENT] AND ( 

"01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] (61)

7. "Diabetes Mellitus" [DISEASE] AND ((exercise OR physical activity) AND (diet OR 

dietary)) [TREATMENT] AND ( "01/01/2009" : "12/31/2014" ) [FIRST-RECEIVED-DATE] 

(273)

8. "Diabetes Mellitus" [DISEASE] AND ( ( exercise OR physical activity ) AND ( relaxation OR 

biofeedback OR yoga OR meditation ) ) [TREATMENT] AND ( "01/01/2009" : "12/31/2014" ) 

[FIRST-RECEIVED-DATE] (10)

9. "Diabetes Mellitus" [DISEASE] AND ( ( diet OR dietary ) AND ( relaxation OR biofeedback 

OR yoga OR meditation ) ) [TREATMENT] AND ( "01/01/2009" : "12/31/2014" ) [FIRSTRECEIVED-DATE] (7)

10. "Diabetes Mellitus" [DISEASE] AND ( family ) [TREATMENT] AND ( "01/01/2009" : 

"12/31/2014" ) [FIRST-RECEIVED-DATE] (104)
B-15

WHO ICTRP

Trial Registry: WHO ICTRP

Date Searched: 26 June 2014

Results: 422

Advance search interface: http://apps.who.int/trialsearch/AdvSearch.aspx

> “Condition” field: diabetes

> “Intervention” field: lifestyle OR self management OR behavior OR education OR family

> “Recruitment status” field is: ALL

> Date of registration is between: 01/01/2009 and 31/12/2014 (422)
C-1

Appendix C. Very High Human Development Index 

Countries

These countries meet the category of Very-high Human Development Index status, as per the 

United Nations Development Program. (Human Development Report 2013 Team. Table 1. 

Human Development Index and its components. In: Human Development Report 2013. The Rise 

of the South: Human Progress in a Diverse World. United Nations Development Programme,

2013; pp 144-7. http://hdr.undp.org/en/content/human-development-report-2013. Accessed 

March 3, 2014.)

Andorra

Argentina

Australia

Austria

Barbados

Belgium

Brunei Darussalam

Canada

Chile

Croatia

Cyprus

Czech Republic

Denmark

Estonia

Finland

France

Germany

Greece

Hong Kong, China (SAR)

Hungary

Iceland

Ireland

Israel

Italy

Japan

Korea (Republic of)

Latvia

Liechtenstein

Lithuania

Luxembourg

Malta

Netherlands

New Zealand

Norway

Poland

Portugal

Qatar

Seychelles

Singapore

Slovakia

Slovenia

Spain

Sweden

Switzerland

United Arab Emirates

United Kingdom

United States
D-1

Appendix D. Studies Excluded After Full-Text Review

1. Aas AM, Bergstad I, Thorsby PM, et al. An 

intensified lifestyle intervention programme 

may be superior to insulin treatment in 

poorly controlled type 2 diabetic patients on 

oral hypoglycaemic agents: results of a 

feasibility study. Diabet Med. 2005 

Mar;22(3):316-22. PMID: 15717881. 

Exclude: Intervention.

2. Abolfotouh MA, Kamal MM, El-Bourgy 

MD, et al. Quality of life and glycemic 

control in adolescents with type 1 diabetes 

and the impact of an education intervention. 

Int J Gen Med. 2011;4:141-52. PMID: 

21475630. Exclude: Setting/Country.

3. Adams KF, Sperl-Hillen JaM, Davis H, et 

al. Factors influencing patient completion of 

diabetes self-management education. 

Diabetes Spectrum. 2013;26(1):40-5. PMID: 

Not available. Exclude: Outcomes.

4. Adepoju OE, Bolin JN, Ohsfeldt RL, et al. 

Can chronic disease management programs 

for patients with type 2 diabetes reduce 

productivity-related indirect costs of the 

disease? Evidence from a randomized 

controlled trial. Popul Health Manag. 

2014;17(2):112-20. PMID: 24152055. 

Exclude: Intervention.

5. Adepoju OE, Bolin JN, Phillips CD, et al. 

Effects of diabetes self-management 

programs on time-to-hospitalization among 

patients with type 2 diabetes: a survival 

analysis model. Patient Educ Couns. 2014 

Apr;95(1):111-7. PMID: 24468198. 

Exclude: Intervention.

6. Adkins JW, Storch EA, Lewin AB, et al. 

Home-based behavioral health intervention: 

use of a telehealth model to address poor 

adherence to type-1 diabetes medical 

regimens. Telemed J E Health. 2006 

Jun;12(3):370-2. PMID: 16796506. 

Exclude: Design.

7. Agema P, Sherifali D. Determining the 

impact of an intervention to increase 

problem-solving skills in diabetes selfmanagement: the diabetes problem-solving 

passport pilot study. Can. 2012 

August;36(4):199-203. PMID: Not 

available. Exclude: Intervention.

8. Aikens JE, Rosland AM, Piette JD. 

Improvements in illness self-management 

and psychological distress associated with 

telemonitoring support for adults with 

diabetes. Prim Care Diabetes. 2014 Jul 22.

PMID: 25065270. Exclude: Design.

9. Al Mazroui NR, Kamal MM, Ghabash NM, 

et al. Influence of pharmaceutical care on 

health outcomes in patients with type 2 

diabetes mellitus. Br J Clin Pharmacol. 2009 

May;67(5):547-57. PMID: 19552750. 

Exclude: Intervention.

10. Ali M, Schifano F, Robinson P, et al. Impact 

of community pharmacy diabetes 

monitoring and education programme on 

diabetes management: a randomized 

controlled study. Diabet Med. 2012 

Sep;29(9):e326-33. PMID: 22672148. 

Exclude: Intervention.

11. Al-Jiffri O, Al-Sharif FM, Abd El-Kader 

SM, et al. Weight reduction improves 

markers of hepatic function and insulin 

resistance in type-2 diabetic patients with 

non-alcoholic fatty liver. Afr Health Sci. 

2013 Sep;13(3):667-72. PMID: 24250305. 

Exclude: Setting/Country.

12. Allen N, Whittemore R, Melkus G. A 

continuous glucose monitoring and problemsolving intervention to change physical 

activity behavior in women with type 2 

diabetes: a pilot study. Diabetes Technol 

Ther. 2011 Nov;13(11):1091-9. PMID: 

21919735. Exclude: Intervention.

13. Allen NA, Fain JA, Braun B, et al. 

Continuous glucose monitoring counseling 

improves physical activity behaviors of 

individuals with type 2 diabetes: a

randomized clinical trial. Diabetes Res Clin 

Pract. 2008 Jun;80(3):371-9. PMID: 

18304674. Exclude: Duration.

14. Ambrosino JM, Fennie K, Whittemore R, et 

al. Short-term effects of coping skills 

training in school-age children with type 1 

diabetes. Pediatr Diabetes. 2008 Jun;9(3 Pt 
D-2

2):74-82. PMID: 18540868. Exclude: 

Intervention.

15. Amoako E, Skelly AH. Managing 

uncertainty in diabetes: an intervention for 

older African American women. Ethn Dis. 

2007;17(3):515-21. PMID: 17985507. 

Exclude: Outcomes.

16. Anderson BJ, Brackett J, Ho J, et al. An 

intervention to promote family teamwork in 

diabetes management tasks: relationships 

among parental involvement, adherence to 

blood glucose monitoring, and glycemic 

control in young adolescents with type 1 

diabetes. Drotar Dennis [Ed]. 2000. PMID: 

Not available. Exclude: Publication type.

17. 'Behavior change' is centerpiece of new 

disease management approach for diabetics. 

Dis Manag Advis. 2001 Aug;7(8):118-21, 3. 

PMID: 11530657. Exclude: Publication 

type.

18. Culturally appropriate lifestyle interventions 

promote weight loss in rural dwelling people 

with type 2 diabetes. Evidence-Based 

Healthcare and Public Health. 2005 

June;9(3):231-2. PMID: Not available. 

Exclude: Publication type.

19. Ardigo D, Vaccaro O, Cavalot F, et al. 

Effectiveness of treat-to-target strategy for 

ldl-cholesterol control in type 2 diabetes: 

post-hoc analysis of data from the mind.it 

study. Eur J Prev Cardiolog. 2014; (4).

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/003/CN00992003/frame.html. Accessed March 20, 

2015. Exclude: Intervention.

20. Armstrong MJ, Campbell TS, Lewin AM, et 

al. Motivational interviewing-based exercise 

counselling promotes maintenance of 

physical activity in people with type 2 

diabetes. Can. 2013 October;37:S3. PMID: 

71210438. Exclude: Publication type.

21. Arseneau DL, Mason AC, Wood OB, et al. 

A comparison of learning activity packages 

and classroom instruction for diet 

management of patients with non-insulindependent diabetes mellitus. Diabetes Educ. 

1994 Nov-Dec;20(6):509-14. PMID: 

7851264. Exclude: Intervention.

22. Ash S, Reeves MM, Yeo S, et al. Effect of 

intensive dietetic interventions on weight 

and glycaemic control in overweight men 

with type ii diabetes: a randomised trial. Int 

J Obes Relat Metab Disord. 2003 

Jul;27(7):797-802. PMID: 12821964. 

Exclude: Intervention.

23. Audet CM. A comparison of quality of life 

in traditional face-to-face and internet-based 

diabetes social support group participants. 

Dissertation Abstracts International: Section 

B: The Sciences and Engineering. 

2014;74(8-B E). PMID: Not available. 

Exclude: Intervention.

24. Avdal E, Kizilci S, Demirel N. The effects

of web-based diabetes education on diabetes 

care results: a randomized control study. 

Comput Inform Nurs. 2011;29(2):101-6. 

PMID: 21372642. Exclude: Setting/Country.

25. Bacchi E, Negri C, Trombetta M, et al. 

Differences in the acute effects of aerobic 

and resistance exercise in subjects with type 

2 diabetes: results from the RAED2 

randomized trial. Diabetes Technol Ther. 

2014; (Suppl. 1).

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/183/CN00978183/frame.html. Accessed March 20, 

2015. Exclude: Intervention.

26. Balamurugan A, Hall-Barrow J, Blevins 

MA, et al. A pilot study of diabetes 

education via telemedicine in a rural 

underserved community-opportunities and 

challenges: a continuous quality 

improvement process. Diabetes Educ. 2009 

Jan-Feb;35(1):147-54. PMID: 19244570. 

Exclude: Intervention.

27. Balducci S, Zanuso S, Nicolucci A, et al. 

Effect of an intensive exercise intervention 

strategy on modifiable cardiovascular risk 

factors in subjects with type 2 diabetes 

mellitus: a randomized controlled trial: the 

Italian Diabetes and Exercise Study (IDES). 

Arch Intern Med. 2010 Nov 8;170(20):1794-

803. PMID: 21059972. Exclude: 

Intervention.

28. Baradaran HR, Knill-Jones RP, Wallia S, et 

al. A controlled trial of the effectiveness of a 

diabetes education programme in a multiethnic community in Glasgow. BMC Public 
D-3

Health. 2006;6:134. PMID: 16709243. 

Exclude: Outcomes.

29. Barrera M, Strycker LA, Mackinnon DP, et 

al. Social-ecological resources as mediators 

of two-year diet and physical activity 

outcomes in type 2 diabetes patients. Health 

Psychol. 2008 Mar;27(2 Suppl):S118-25. 

PMID: 18377153. Exclude: Outcomes.

30. Barrera M, Jr., Toobert DJ, Angell KL, et al. 

Social support and social-ecological 

resources as mediators of lifestyle 

intervention effects for type 2 diabetes. J 

Health Psychol. 2006 May;11(3):483-95. 

PMID: 16774900. Exclude: Outcomes.

31. Barrera MJ, Glasgow RE, Mckay HG, et al.

Do internet-based support interventions 

change perceptions of social support? an 

experimental trial of approaches for 

supporting diabetes self-management. Am J 

Community Psychol. 2002 Oct;30(5):637-

54. PMID: 12188054. Exclude: Outcomes.

32. Basch CE, Walker EA, Howard CJ, et al. 

The effect of health education on the rate of 

ophthalmic examinations among African 

Americans with diabetes mellitus. Am J 

Public Health. 1999 Dec;89(12):1878-82. 

PMID: 10589324. Exclude: Intervention.

33. Bastelaar K, Cuijpers P, Pouwer F, et al. 

Development and reach of a web-based 

cognitive behavioural therapy programme to 

reduce symptoms of depression and 

diabetes-specific distress. Patient Educ

Couns. 2011;84(1):49-55. PMID: 20619577. 

Exclude: Intervention.

34. Batik O, Phelan EA, Walwick JA, et al. 

Translating a community-based motivational 

support program to increase physical 

activity among older adults with diabetes at 

community clinics: a pilot study of Physical 

Activity for a Lifetime of Success (PALS). 

Prev Chronic Dis. 2008 Jan;5(1):A18. 

PMID: 18082007. Exclude: Intervention.

35. Bellary S, O'hare JP, Raymond NT, et al. 

Enhanced diabetes care to patients of south 

Asian ethnic origin (the United Kingdom 

Asian diabetes study): a cluster randomised 

controlled trial. Lancet. 2008 May 

24;371(9626):1769-76. PMID: 18502301. 

Exclude: Intervention.

36. Berger G, Brunmayr F, Muehlehner M, et al. 

Gender differences in the effect of 

motivational interviewing and cognitive 

behavioural therapy in Austrian adolescents 

with type 1 diabetes. Diabetologia. 2013 

September;56:S452. PMID: 71439545. 

Exclude: Publication type.

37. Berger M, Imershein SG, Jackson RA. Waitlist control study of a diabetes (dm) 

education program. Diabetes. 2013 

July;62:A621. PMID: 71288820. Exclude: 

Publication type.

38. Beverly EA, Fitzgerald S, Sitnikov L, et al. 

Do older adults aged 60-75 years benefit 

from diabetes behavioral interventions? 

Diabetes Care. 2013 Jun;36(6):1501-6. 

PMID: 23315603. Exclude: Outcomes.

39. Blackberry ID, Furler JS, Best JD, et al. 

Effectiveness of general practice based, 

practice nurse led telephone coaching on 

glycaemic control of type 2 diabetes: the 

patient engagement and coaching for health 

(PEACH) pragmatic cluster randomised 

controlled trial. BMJ (Online). 2013 28 

Sep;347(7926). PMID: 24048296. Exclude: 

Intervention.

40. Boehm S, Schlenk EA, Raleigh E, et al. 

Behavioral analysis and behavioral 

strategies to improve self-management of 

type ii diabetes. Clin Nurs Res. 1993 

Aug;2(3):327-44. PMID: 8401245. Exclude: 

Intervention.

41. Bradshaw BG. The efficacy of a resiliency 

training program in adults with type 2 

diabetes mellitus: University of Utah; 2006. 

Exclude: Publication type.

42. Braun AK, Kubiak T, Kuntsche J, et al. 

SGS: a structured treatment and teaching 

programme for older patients with diabetes 

mellitus--a prospective randomised 

controlled multi-centre trial. Age Ageing. 

2009 Jul;38(4):390-6. PMID: 19454403. 

Exclude: Population.

43. Brazeau A-S, Gingras V, Leroux C, et al. A 

pilot program for physical exercise 

promotion in adults with type 1 diabetes: the 

PEP-1 program. Appl Physiol Nutr Metab. 

2014;39(4):465-71. PMID: 24669988. 

Exclude: Intervention.
D-4

44. Brown SA, Harrist RB, Villagomez ET, et 

al. Gender and treatment differences in 

knowledge, health beliefs, and metabolic 

control in Mexican Americans with type 2 

diabetes. Diabetes Educ. 2000 MayJun;26(3):425-38. PMID: 11151290. 

Exclude: Outcomes.

45. Byrne M, Newell J, Coffey N, et al. 

Predictors of quality of life gains among 

people with type 1 diabetes participating in 

the dose adjustment for normal eating 

(DAFNE) structured education programme. 

Diabetes Res Clin Pract. 2012 

November;98(2):243-8. PMID: 23018180. 

Exclude: Design.

46. Cabrera-Pivaral CE, Gonzalez-Perez G, 

Vega-Lopez G, et al. Effects of behaviormodifying education in the metabolic profile 

of the type 2 diabetes mellitus patient. J 

Diabetes Complications. 2000 NovDec;14(6):322-6. PMID: 11120456. 

Exclude: Setting/Country.

47. Cade JE, Kirk SF, Nelson P, et al. Can peer 

educators influence healthy eating in people 

with diabetes? results of a randomized 

controlled trial. Diabet Med. 2009 

Oct;26(10):1048-54. PMID: 19900238. 

Exclude: Intervention.

48. Cakan N, Ellis DA, Templin T, et al. The 

effects of weight status on treatment 

outcomes in a randomized clinical trial of 

multisystemic therapy for adolescents with 

type 1 diabetes and chronically poor 

metabolic control. Pediatr Diabetes. 2007 

Aug;8(4):206-13. PMID: 17659062. 

Exclude: Outcomes.

49. Calderon JL, Shaheen M, Hays RD, et al. 

Improving diabetes health literacy by 

animation. Diabetes Educ. 2014;40(3):361-

72. PMID: 24676274 Exclude: Intervention.

50. Campbell EM, Redman S, Moffitt PS, et al. 

The relative effectiveness of educational and 

behavioral instruction programs for patients 

with NIDDM: a randomized trial. Diabetes 

Educ. 1996 Jul-Aug;22(4):379-86. PMID: 

8846745. Exclude: Population.

51. Carter EL, Nunlee-Bland G, Callender C. A 

patient-centric, provider-assisted diabetes 

telehealth self-management intervention for 

urban minorities. Perspect. 2011;8:1b. 

PMID: 21307985. Exclude: Intervention.

52. Castaneda C, Layne JE, Munoz-Orians L, et 

al. A randomized controlled trial of 

resistance exercise training to improve 

glycemic control in older adults with type 2 

diabetes. Diabetes Care. 2002 

Dec;25(12):2335-41. PMID: 12453982. 

Exclude: Intervention.

53. Castillo A, Giachello A, Bates R, et al. 

Community-based diabetes education for 

Latinos: the diabetes empowerment 

education program. Diabetes Educ. 2010 

Jul-Aug;36(4):586-94. PMID: 20538970. 

Exclude: Design.

54. Cavanaugh K, Wallston KA, Gebretsadik T, 

et al. Addressing literacy and numeracy to 

improve diabetes care: two randomized 

controlled trials. Diabetes Care. 2009 

Dec;32(12):2149-55. PMID: 19741187. 

Exclude: Intervention.

55. Chaney D, Coates V, Shevlin M. Running a 

complex educational intervention for 

adolescents with type 1 diabetes-lessons 

learnt. J Diabetes Nurs. 2010;14(10):370. 

PMID: Not available. Exclude: Publication 

type.

56. Channon SJ, Huws-Thomas MV, Rollnick 

S, et al. A multicenter randomized 

controlled trial of motivational interviewing 

in teenagers with diabetes. Diabetes Care.

2007 Jun;30(6):1390-5. PMID: 17351283. 

Exclude: Intervention.

57. Chao J, Yang L, Xu H, et al. The effect of 

integrated health management model on the 

health of older adults with diabetes in a 

randomized controlled trial. Arch Gerontol 

Geriatr. 2015 Jan-Feb;60(1):82-8. PMID: 

25456892. Exclude: Setting/Country.

58. Chesla CA, Kwan CML, Chun KM, et al. 

Gender differences in factors related to 

diabetes management in Chinese American 

immigrants. West J Nurs Res. 

2014;36(9):1074-90. PMID: 24558055. 

Exclude: Design.

59. Cheyette C. Weight no more: a randomised 

controlled trial for people with type 2 

diabetes on insulin therapy. Practical 

Diabetes International. 2007 
D-5

November/December;24(9):450-6. PMID: 

Not available. Exclude: Design.

60. Chiu CJ, Lu FH, Hu YH, et al. Can 

telephone-based minimal psychological 

intervention be an effective method for 

diabetes self-management? Diabetes. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/476/CN01009476/frame.html. Accessed March 20, 

2015. Exclude: Setting/Country.

61. Choe HM, Mitrovich S, Dubay D, et al. 

Proactive case management of high-risk 

patients with type 2 diabetes mellitus by a 

clinical pharmacist: a randomized controlled 

trial. Am J Manag Care. 2005 

Apr;11(4):253-60. PMID: 15839185. 

Exclude: Intervention.

62. Christian JG, Bessesen DH, Byers TE, et al. 

Clinic-based support to help overweight 

patients with type 2 diabetes increase 

physical activity and lose weight. Arch 

Intern Med. 2008 Jan 28;168(2):141-6. 

PMID: 18227359. Exclude: Intervention.

63. Cinar AB, Schou L. The role of self-efficacy 

in health coaching and health education for 

patients with type 2 diabetes. Int Dent J. 

2014 Jun;64(3):155-63. PMID: 24571189. 

Exclude: Setting/Country.

64. Cinar AB, Schou L. The role of self-efficacy 

in health coaching and health education for 

patients with type 2 diabetes. Int Dent J. 

2014;64(3):155-63. PMID: 24571189. 

Exclude: Setting/Country.

65. Clancy DE, Huang P, Okonofua E, et al. 

Group visits: promoting adherence to 

diabetes guidelines. J Gen Intern Med. 2007 

May;22(5):620-4. PMID: 17443369. 

Exclude: Intervention.

66. Clifford RM, Batty KT, Davis TME, et al. A 

randomised controlled trial of a 

pharmaceutical care programme in high-risk 

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Pharm Pract. 2002;10(2):85-9. PMID: Not 

available. Exclude: Intervention.

67. Clobes TA. Patient compliance with type 2 

diabetes using visual reminders and the 

transtheoretical model. Dissertation 

Abstracts International: Section B: The 

Sciences and Engineering. 2013;73(11-B E). 

PMID: Not available. Exclude: Intervention.

68. Cohn MA, Pietrucha ME, Saslow LR, et al. 

An online positive affect skills intervention 

reduces depression in adults with type 2 

diabetes. J Posit Psychol. 2014;9(6):523-34. 

PMID: 25214877. Exclude: Intervention.

69. Conget I, Jansa M, Vidal M, et al. Effects of 

an individual intensive educational control 

program for insulin-dependent diabetic 

subjects with poor metabolic control. 

Diabetes Res Clin Pract. 1995 

Mar;27(3):189-92. PMID: 7555600. 

Exclude: Design.

70. Couper JJ, Taylor J, Fotheringham MJ, et al. 

Failure to maintain the benefits of homebased intervention in adolescents with 

poorly controlled type 1 diabetes. Diabetes 

Care. 1999 Dec;22(12):1933-7. PMID: 

10587821. Exclude: Design.

71. Crasto W, Jarvis J, Khunti K, et al. 

Multifactorial intervention in individuals 

with type 2 diabetes and microalbuminuria: 

the Microalbuminuria Education and 

Medication Optimisation (MEMO) study. 

Diabetes Res Clin Pract. 2011 

Sep;93(3):328-36. PMID: 21640424. 

Exclude: Intervention.

72. Cummings DM, Lutes L, Littlewood K, et 

al. A small changes approach for lifestyle 

change is effective in non-insulin using 

African American women with uncontrolled 

type 2 diabetes: 12-month results from the 

empower trial. Diabetes. 2014.

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central/articles/471/CN01009471/frame.html. Accessed March 20, 

2015. Exclude: Publication Type.

73. Dale J, Caramlau I, Sturt J, et al. Telephone 

peer-delivered intervention for diabetes 

motivation and support: the telecare 

exploratory rct. Patient Educ Couns. 2009 

Apr;75(1):91-8. PMID: 19013741. Exclude: 

Intervention.

74. Daly KD. Test of a culturally sensitive 

health empowerment intervention on stress, 

health promoting behaviors, blood glucose 

and blood pressure among diverse adults 

with type 2 diabetes from low-income 

households. Dissertation Abstracts 
D-6

International: Section B: The Sciences and 

Engineering. 2012;73(5-B). PMID: Not 

available. Exclude: Duration.

75. Daniels EC, Powe BD, Metoyer T, et al. 

Increasing knowledge of cardiovascular risk 

factors among African Americans by use of 

community health workers: the abcd 

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Med Assoc. 2012;104(3-4):179-85. PMID: 

22774385. Exclude: Population.

76. Davidson MB, Castellanos M, Kain D, et al. 

The effect of self monitoring of blood 

glucose concentrations on glycated 

hemoglobin levels in diabetic patients not 

taking insulin: a blinded, randomized trial. 

Am J Med. 2005 Apr;118(4):422-5. PMID: 

15808142. Exclude: Intervention.

77. Davies MJ, Heller S, Skinner TC, et al. 

Effectiveness of the diabetes education and 

self management for ongoing and newly 

diagnosed (DESMOND) programme for 

people with newly diagnosed type 2 

diabetes: cluster randomised controlled trial. 

BMJ. 2008 Mar 1;336(7642):491-5. PMID: 

18276664. Exclude: Population.

78. De Greef K, Deforche B, Tudor-Locke C, et 

al. Increasing physical activity in Belgian 

type 2 diabetes patients: a three-arm 

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Med. 2011 Sep;18(3):188-98. PMID: 

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79. De Greef KP, Deforche BI, Ruige JB, et al. 

The effects of a pedometer-based behavioral 

modification program with telephone 

support on physical activity and sedentary 

behavior in type 2 diabetes patients. Patient 

Educ Couns. 2011 Aug;84(2):275-9. PMID: 

20732776. Exclude: Intervention.

80. Deakin TA, Cade JE, Williams DRR, et al. 

Empowered patients: better diabetes control, 

greater freedom to eat, no weight gain! 

Diabetologia. 2003. Exclude: Publication 

type.

81. Debussche X, Rollot O, Le Pommelet C, et 

al. Quarterly individual outpatients lifestyle 

counseling after initial inpatients education 

on type 2 diabetes: the redia prev-2 

randomized controlled trial in reunion 

island. Diabetes Metab. 2012 Feb;38(1):46-

53. PMID: 22030240. Exclude: 

Setting/Country.

82. Decoster VA, George L. An empowerment 

approach for elders living with diabetes: a

pilot study of a community-based self-help 

group-the diabetes club. Educ Gerontol. 

2005;31(9):699-713. 

WOS:000232104600003. Exclude: Design.

83. Denig P, Schuling J, Haaijer-Ruskamp FM, 

et al. Effects of a patient-oriented decision 

aid for prioritising treatment goals in 

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central/articles/251/CN01009251/frame.html. Accessed March 20, 

2015. Exclude: Intervention.

84. Di Loreto C, Fanelli C, Lucidi P, et al. 

Validation of a counseling strategy to 

promote the adoption and the maintenance 

of physical activity by type 2 diabetic 

subjects. Diabetes Care. 2003 

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Exclude: Intervention.

85. Didjurgeit U, Kruse J, Schmitz N, et al. A 

time-limited, problem-orientated 

psychotherapeutic intervention in type 1 

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2002 Oct;19(10):814-21. PMID: 12358867. 

Exclude: Intervention.

86. Diedrich A, Munroe DJ, Romano M. 

Promoting physical activity for persons with 

diabetes. Diabetes Educ. 2010 JanFeb;36(1):132-40. PMID: 20019197. 

Exclude: Intervention.

87. Dijkstra RF, Braspenning JC, Huijsmans Z, 

et al. Introduction of diabetes passports 

involving both patients and professionals to 

improve hospital outpatient diabetes care. 

Diabetes Res Clin Pract. 2005 

May;68(2):126-34. PMID: 15860240. 

Exclude: Intervention.

88. Dijkstra RF, Niessen LW, Braspenning JCC, 

et al. Patient-centred and professionaldirected implementation strategies for 

diabetes guidelines: a cluster-randomized 

trial-based cost-effectiveness analysis. 

Diabet Med. 2006 February;23(2):164-70. 

PMID: 16433714. Exclude: Intervention.
D-7

89. Dinneen SF, O'hara MC, Byrne M, et al. 

Group follow-up compared to individual 

clinic visits after structured education for 

type 1 diabetes: a cluster randomised 

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2013 Apr;100(1):29-38. PMID: 23398978. 

Exclude: Intervention.

90. Doucette WR, Witry MJ, Farris KB, et al. 

Community pharmacist-provided extended 

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May;43(5):882-9. PMID: 19401477. 

Exclude: Intervention.

91. Dunbar SB, Butts B, Reilly CM, et al. A 

pilot test of an integrated self-care 

intervention for persons with heart failure 

and concomitant diabetes. Nurs Outlook. 

2014;62(2):97-111. PMID: 24211112. 

Exclude: Setting/Country.

92. Dunbar SB, Reilly CM, Gary RA, et al. An 

integrated self care education and 

counseling intervention for persons with 

heart failure and diabetes improves quality 

of life and physical functioning. J Card Fail. 

2014;20(8):S118-S. PMID: Not available. 

Exclude: Setting/Country.

93. Dunstan DW, Mori TA, Puddey IB, et al. 

Exercise and fish intake: effects on serum 

lipids and glycemic control for type 2 

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1998;15(8):34-7. PMID: Not available. 

Exclude: Publication type.

94. Dunstan DW, Mori TA, Puddey IB, et al. A 

randomised, controlled study of the effects 

of aerobic exercise and dietary fish on 

coagulation and fibrinolytic factors in type 2 

diabetics. Thromb Haemost. 1999 

Mar;81(3):367-72. PMID: 10102462. 

Exclude: Outcomes.

95. Dunstan DW, Puddey IB, Beilin LJ, et al. 

Effects of a short-term circuit weight 

training program on glycaemic control in 

NIDDM. Diabetes Res Clin Pract. 1998 

Apr;40(1):53-61. PMID: 9699091. Exclude: 

Intervention.

96. Duran A, Martin P, Runkle I, et al. Benefits 

of self-monitoring blood glucose in the 

management of new-onset type 2 diabetes 

mellitus: the St Carlos study, a prospective 

randomized clinic-based interventional 

study with parallel groups. J Diabetes. 2010 

Sep;2(3):203-11. PMID: 20923485. 

Exclude: Population.

97. Dutton GR, Provost BC, Tan F, et al. A 

tailored print-based physical activity 

intervention for patients with type 2 

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PMID: 18652840. Exclude: Intervention.

98. Eakin E, Reeves M, Dunstan D, et al. Living 

well with diabetes: six-month randomised 

trial outcomes of a telephone-delivered 

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2012 December;15:S202. PMID: 70968590. 

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99. Eakin E, Reeves M, Lawler S, et al. 

Telephone counseling for physical activity 

and diet in primary care patients. Am J Prev 

Med. 2009 Feb;36(2):142-9. PMID: 

19062240. Exclude: Population.

100. Eakin E, Reeves M, Winkler E, et al. 

Maintenance of physical activity and dietary 

change following a telephone-delivered 

intervention. Health Psychol. 2010 

Nov;29(6):566-73. PMID: 20954778. 

Exclude: Population.

101. Eakin EG, Reeves MM, Lawler SP, et al. 

The logan healthy living program: a cluster 

randomized trial of a telephone-delivered 

physical activity and dietary behavior 

intervention for primary care patients with 

type 2 diabetes or hypertension from a 

socially disadvantaged community--

rationale, design and recruitment. Contemp 

Clin Trials. 2008 May;29(3):439-54. PMID: 

18055274. Exclude: Publication type.

102. Eakin EG, Reeves MM, Winkler E, et al. 

Six-month outcomes from living well with 

diabetes: a randomized trial of a telephonedelivered weight loss and physical activity 

intervention to improve glycemic control. 

Ann Behav Med. 2013 Oct;46(2):193-203. 

PMID: 23609340. Exclude: Outcomes.

103. Edelman D, Fredrickson SK, Melnyk SD, et 

al. Medical clinics versus usual care for 

patients with both diabetes and 

hypertension: a randomized trial. Ann Intern 

Med. 2010 Jun 1;152(11):689-96. PMID: 

20513826. Exclude: Intervention.
D-8

104. Elnour AA, El Mugammar IT, Jaber T, et al. 

Pharmaceutical care of patients with 

gestational diabetes mellitus. J Eval Clin 

Pract. 2008 Feb;14(1):131-40. PMID: 

18211656. Exclude: Intervention.

105. Engel L, Cummins R. Impact of dose 

adjustment for normal eating in Australia 

(ozdafne) on subjective wellbeing, coping 

resources and negative affects in adults with 

type 1 diabetes: a prospective comparison 

study. Diabetes Res Clin Pract. 2011 

Mar;91(3):271-9. PMID: 21146889. 

Exclude: Duration.

106. Engel L, Lindner H. Impact of using a 

pedometer on time spent walking in older 

adults with type 2 diabetes. Diabetes Educ. 

2006 Jan-Feb;32(1):98-107. PMID: 

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107. Eriksson KM, Westborg CJ, Eliasson MCE. 

A randomized trial of lifestyle intervention 

in primary healthcare for the modification of 

cardiovascular risk factors: the BJORKNAS

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October;34(5):453-61. PMID: 16990155 

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108. Esmatjes E, Jansà M, Roca D, et al. The 

efficiency of telemedicine to optimize 

metabolic control in patients with type 1 

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Technol Ther. 2014;16(7):435-41. PMID: 

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109. Espeland MA, Glick HA, Bertoni A, et al. 

Impact of an intensive lifestyle intervention 

on use and cost of medical services among 

overweight and obese adults with type 2 

diabetes: the action for health in diabetes. 

Diabetes Care. 2014; (9). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/149/CN01002149/frame.html. Accessed March 20, 

2015. Exclude: Outcomes.

110. Espeland MA, Rapp SR, Bray GA, et al. 

Long-term impact of behavioral weight loss 

intervention on cognitive function. J

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2014;69(9):1101-8. PMID: 24619151. 

Exclude: Outcomes.

111. Espeland MA, Rejeski WJ, West DS, et al. 

Intensive weight loss intervention in older 

individuals: results from the action for 

health in diabetes type 2 diabetes mellitus 

trial. J Am Geriatr Soc. 2013 Jun;61(6):912-

22. PMID: 23668423. Exclude: Outcomes.

112. Esposito K, Maiorino MI, Petrizzo M, et al. 

The effects of a Mediterranean diet on the 

need for diabetes drugs and remission of 

newly diagnosed type 2 diabetes: follow-up 

of a randomized trial. Diabetes Care. 

2014;37(7):1824-30. PMID: 24722497. 

Exclude: Population.

113. Estabrooks PA, Nelson CC, Xu S, et al. The 

frequency and behavioral outcomes of goal 

choices in the self-management of diabetes. 

Diabetes Educ. 2005 May-Jun;31(3):391-

400. PMID: 15919639. Exclude: 

Intervention.

114. Fabricatore AN, Wadden TA, Ebbeling CB, 

et al. Targeting dietary fat or glycemic load

in the treatment of obesity and type 2 

diabetes: a randomized controlled trial. 

Diabetes Res Clin Pract. 2011 Apr;92(1):37-

45. PMID: 21208675. Exclude: Intervention.

115. Faridi Z, Liberti L, Shuval K, et al. 

Evaluating the impact of mobile telephone 

technology on type 2 diabetic patients' selfmanagement: the niche pilot study. J Eval 

Clin Pract. 2008 Jun;14(3):465-9. PMID: 

18373577. Exclude: Intervention.

116. Farmer A, Wade A, Goyder E, et al. Impact 

of self monitoring of blood glucose in the 

management of patients with non-insulin 

treated diabetes: open parallel group 

randomised trial. BMJ. 2007 Jul 

21;335(7611):132. PMID: 17591623. 

Exclude: Intervention.

117. Farmer AJ, Wade AN, French DP, et al. 

Blood glucose self-monitoring in type 2 

diabetes: a randomised controlled trial. 

Health Technol Assess. 2009 Feb;13(15):iiiiv, ix-xi, 1-50. PMID: 19254484. Exclude: 

Intervention.

118. Faulconbridge LF, Wadden TA, Rubin RR, 

et al. One-year changes in symptoms of 

depression and weight in overweight/obese 

individuals with type 2 diabetes in the Look 

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Apr;20(4):783-93. PMID: 22016099. 

Exclude: Outcomes.
D-9

119. Fitzpatrick SL, Jeffery R, Johnson KC, et al. 

Baseline predictors of missed visits in the 

Look Ahead study. Obesity (Silver Spring). 

2014;22(1):131-40. PMID: 23996977. 

Exclude: Design.

120. Forjuoh SN, Bolin JN, Huber JCJ, et al. 

Behavioral and technological interventions 

targeting glycemic control in a 

racially/ethnically diverse population: a

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Exclude: Intervention.

121. Forjuoh SN, Ory MG, Jiang L, et al. Impact 

of chronic disease self-management 

programs on type 2 diabetes management in 

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2014;5(3):407-14. PMID: 24936263. 

Exclude: Intervention.

122. Fornos JA, Andres NF, Andres JC, et al. A 

pharmacotherapy follow-up program in 

patients with type-2 diabetes in community 

pharmacies in Spain. Pharm World Sci. 

2006 Apr;28(2):65-72. PMID: 16791717. 

Exclude: Intervention.

123. Foster GD, Borradaile KE, Sanders MH, et 

al. A randomized study on the effect of 

weight loss on obstructive sleep apnea 

among obese patients with type 2 diabetes: 

the sleep ahead study. Arch Intern Med. 

2009 Sep 28;169(17):1619-26. PMID: 

19786682. Exclude: Outcomes.

124. Foster GD, Wyatt HR, Hill JO, et al. Weight 

and metabolic outcomes after 2 years on a 

low-carbohydrate versus low-fat diet: a

randomized trial. Ann Intern Med. 2010 Aug 

3;153(3):147-57. PMID: 20679559. 

Exclude: Population.

125. Franciosi M, Lucisano G, Pellegrini F, et al. 

Roses: role of self-monitoring of blood 

glucose and intensive education in patients 

with type 2 diabetes not receiving insulin. A 

pilot randomized clinical trial. Diabet Med. 

2011 Jul;28(7):789-96. PMID: 21342243. 

Exclude: Intervention.

126. Freeman KA, Duke DC, Harris MA. 

Behavioral health care for adolescents with 

poorly controlled diabetes via skype: does 

working alliance remain intact? J Diabetes 

Sci Technol. 2014(3):727-35. PMID: 

23759406. Exclude: Publication type.

127. Gabbay RA, Lendel I, Saleem TM, et al. 

Nurse case management improves blood 

pressure, emotional distress and diabetes 

complication screening. Diabetes Res Clin 

Pract. 2006 Jan;71(1):28-35. PMID: 

16019102. Exclude: Intervention.

128. Gaede P, Beck M, Vedel P, et al. Limited 

impact of lifestyle education in patients with 

type 2 diabetes mellitus and 

microalbuminuria: results from a 

randomized intervention study. Diabet Med. 

2001 Feb;18(2):104-8. PMID: 11251672. 

Exclude: Intervention.

129. Gaede P, Lund-Andersen H, Parving HH, et 

al. Effect of a multifactorial intervention on 

mortality in type 2 diabetes. N Engl J Med. 

2008 Feb 7;358(6):580-91. PMID: 

18256393. Exclude: Intervention.

130. Gaede P, Vedel P, Larsen N, et al. 

Multifactorial intervention and 

cardiovascular disease in patients with type 

2 diabetes. N Engl J Med. 2003 Jan 

30;348(5):383-93. PMID: 12556541. 

Exclude: Intervention.

131. Gaede P, Vedel P, Parving HH, et al. 

Intensified multifactorial intervention in 

patients with type 2 diabetes mellitus and 

microalbuminuria: the steno type 2 

randomised study. Lancet. 1999 Feb 

20;353(9153):617-22. PMID: 10030326. 

Exclude: Intervention.

132. Gajewska KA, Pankowska E, Gajewski JA. 

The to become independent - educational 

program for young adolescents. The pilot 

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2012 October;13:28. PMID: 70932770. 

Exclude: Publication type.

133. Gallagher R, Kirkness A, Zelestis E, et al. A 

randomised trial of a weight loss 

intervention for overweight and obese 

people diagnosed with coronary heart 

disease and/or type 2 diabetes. Ann Behav 

Med. 2012 Aug;44(1):119-28. PMID: 

22552838. Exclude: Population.

134. Gallagher R, Zelestis E, Hollams D, et al. 

Impact of the healthy eating and exercise 

lifestyle programme on depressive 

symptoms in overweight people with heart 

disease and diabetes. Eur J Prev Cardiolog. 
D-10

2014; (9). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/286/CN01002286/frame.html. Accessed March 20, 

2015. Exclude: Population.

135. Ganz DA. Measuring the quality of chronic 

illness care for older adults. Dissertation 

Abstracts International: Section B: The 

Sciences and Engineering. 2008;68(9-B). 

PMID: Not available. Exclude: Intervention.

136. Garcia-Lopez M, Toledo E, Beunza JJ, et al. 

Mediterranean diet and heart rate: the 

predimed randomised trial. Int J Cardiol. 

2014;171(2):299-301. PMID: 24369792. 

Exclude: Population.

137. Gary TL, Batts-Turner M, Yeh HC, et al. 

The effects of a nurse case manager and a 

community health worker team on diabetic 

control, emergency department visits, and 

hospitalizations among urban African 

Americans with type 2 diabetes mellitus: a

randomized controlled trial. Arch Intern 

Med. 2009 Oct 26;169(19):1788-94. PMID: 

19858437. Exclude: Intervention.

138. Gary TL, Bone LR, Hill MN, et al. 

Randomized controlled trial of the effects of 

nurse case manager and community health 

worker interventions on risk factors for 

diabetes-related complications in urban 

African Americans. Prev Med. 2003 

Jul;37(1):23-32. PMID: 12799126. Exclude: 

Intervention.

139. Gibbs BB, Brancati FL, Chen H, et al. Effect 

of improved fitness beyond weight loss on 

cardiovascular risk factors in individuals 

with type 2 diabetes in the Look Ahead 

study. Eur J Prev Cardiolog. 

2014;21(5):608-17. PMID: 23012688. 

Exclude: Outcomes.

140. Gillespie P, Oshea E, O'hara MC, et al. Cost 

effectiveness of group follow-up after 

structured education for type 1 diabetes: a

cluster randomised controlled trial. Trials. 

2014; (1). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/470/CN00995470/frame.html. Accessed March 20, 

2015. Exlcude: Intervention.

141. Gillespie P, O'shea E, Paul G, et al. Cost 

effectiveness of peer support for type 2 

diabetes. Int J Technol Assess Health Care. 

2012 January;28(1):3-11. PMID: 22617733. 

Exclude: Intervention.

142. Glasgow RE, Boles SM, Mckay HG, et al. 

The d-net diabetes self-management 

program: long-term implementation, 

outcomes, and generalization results. Prev 

Med. 2003 Apr;36(4):410-9. PMID: 

12649049. Exclude: Intervention.

143. Glasgow RE, Christiansen SM, Kurz D, et 

al. Engagement in a diabetes selfmanagement website: usage patterns and 

generalizability of program use. J Med 

Internet Res. 2011;13(1):e9. PMID: 

21371992. Exclude: Outcomes.

144. Glasgow RE, Edwards LL, Whitesides H, et 

al. Reach and effectiveness of dvd and inperson diabetes self-management education. 

Chronic Illn. 2009 Dec;5(4):243-9. PMID: 

19933245. Exclude: Design.

145. Glasgow RE, La Chance PA, Toobert DJ, et 

al. Long-term effects and costs of brief 

behavioural dietary intervention for patients 

with diabetes delivered from the medical 

office. Patient Educ Couns. 1997 

Nov;32(3):175-84. PMID: 9423499. 

Exclude: Intervention.

146. Glasgow RE, Strycker LA, King DK, et al. 

Understanding who benefits at each step in 

an internet-based diabetes self-management 

program: application of a recursive 

partitioning approach. Med Decis Making. 

2014;34(2):180-91. PMID: 23913917. 

Exclude: Design.

147. Glasgow RE, Toobert DJ. Brief, computerassisted diabetes dietary self-management 

counseling: effects on behavior, physiologic 

outcomes, and quality of life. Med Care. 

2000 Nov;38(11):1062-73. PMID: 

11078048. Exclude: Intervention.

148. Glasgow RE, Toobert DJ, Barrera MJ, et al. 

Assessment of problem-solving: a key to 

successful diabetes self-management. J 

Behav Med. 2004 Oct;27(5):477-90. PMID: 

15675636. Exclude: Outcomes.

149. Glasgow RE, Toobert DJ, Hampson SE. 

Effects of a brief office-based intervention 

to facilitate diabetes dietary selfmanagement. Diabetes Care. 1996 
D-11

Aug;19(8):835-42. PMID: 8842601. 

Exclude: Intervention.

150. Glasgow RE, Toobert DJ, Hampson SE, et 

al. A brief office-based intervention to 

facilitate diabetes dietary self-management. 

Health Educ Res. 1995 Dec;10(4):467-78. 

PMID: 10159676. Exclude: Intervention.

151. Glasgow RE, Toobert DJ, Hampson SE, et 

al. Implementation, generalization and longterm results of the "choosing well" diabetes 

self-management intervention. Patient Educ 

Couns. 2002 Oct -Nov;48(2):115-22. PMID: 

12401414. Exclude: Intervention.

152. Goode AD, Winkler EA, Reeves MM, et al. 

Relationship between intervention dose and 

outcomes in living well with diabetes-a 

randomized trial of a telephone-delivered 

lifestyle-based weight loss intervention. Am 

J Health Promot. 2014 Nov 5. PMID: 

25372235. Exclude: Design.

153. Goode AD, Winkler EaH, Lawler SP, et al. 

A telephone-delivered physical activity and 

dietary intervention for type 2 diabetes and 

hypertension: does intervention dose 

influence outcomes? Am J Health Promot. 

2011 Mar-Apr;25(4):257-63. PMID: 

21361811. Exclude: Population.

154. Graue M, Wentzel-Larsen T, Hanestad BR, 

et al. Evaluation of a programme of group 

visits and computer-assisted consultations in 

the treatment of adolescents with type 1 

diabetes. Diabet Med. 2005 

Nov;22(11):1522-9. PMID: 16241917. 

Exclude: Intervention.

155. Greenhalgh T, Campbell-Richards D, 

Vijayaraghavan S, et al. New models of selfmanagement education for minority ethnic 

groups: pilot randomized trial of a storysharing intervention. J Health Serv Res 

Policy. 2011 Jan;16(1):28-36. PMID: 

20739577. Exclude: Intervention.

156. Greenwood DA, Kramer MK, Hankins AI, 

et al. Adapting the group lifestyle balanceTM 

program for weight management within a 

large health care system diabetes education 

program. Diabetes Educ. 2014;40(3):299-

307. PMID: 24562606. Exclude: Population.

157. Gregg JA, Callaghan GM, Hayes SC, et al. 

Improving diabetes self-management 

through acceptance, mindfulness, and 

values: a randomized controlled trial. J 

Consult Clin Psychol. 2007 Apr;75(2):336-

43. PMID: 17469891. Exclude: Duration.

158. Grey M, Boland EA, Davidson M, et al. 

Coping skills training for youth with 

diabetes mellitus has long-lasting effects on 

metabolic control and quality of life. J 

Pediatr. 2000 Jul;137(1):107-13. PMID: 

10891831. Exclude: Intervention.

159. Grey M, Boland EA, Davidson M, et al. 

Short-term effects of coping skills training 

as adjunct to intensive therapy in 

adolescents. Diabetes Care. 1998 

Jun;21(6):902-8. PMID: 9614605. Exclude: 

Intervention.

160. Grey M, Boland EA, Davidson M, et al. 

Coping skills training for youths with 

diabetes on intensive therapy. Appl Nurs 

Res. 1999 Feb;12(1):3-12. PMID: 

10048236. Exclude: Intervention.

161. Grey M, Davidson M, Boland EA, et al. 

Clinical and psychosocial factors associated 

with achievement of treatment goals in 

adolescents with diabetes mellitus. J 

Adolesc Health. 2001 May;28(5):377-85. 

PMID: 11336867. Exclude: Publication 

type.

162. Grey M, Whittemore R, Jaser S, et al. 

Effects of coping skills training in schoolage children with type 1 diabetes. Res Nurs 

Health. 2009 Aug;32(4):405-18. PMID: 

19488997. Exclude: Intervention.

163. Grey M, Whittemore R, Jeon S, et al. 

Internet psycho-education programs 

improve outcomes in youth with type 1 

diabetes. Diabetes Care. 2013 

Sep;36(9):2475-82. PMID: 23579179. 

Exclude: Intervention.

164. Group. CM-CS. Closing the gap: effect of 

diabetes case management on glycemic 

control among low-income ethnic minority 

populations: the California medi-cal type 2 

diabetes study. Diabetes Care. 2004 

Jan;27(1):95-103. PMID: 14693973. 

Exclude: Intervention.

165. Group. DS. Training in flexible, intensive 

insulin management to enable dietary 

freedom in people with type 1 diabetes: dose
D-12

adjustment for normal eating (DAFNE) 

randomised controlled trial. BMJ. 2002 Oct 

5;325(7367):746. PMID: 12364302. 

Exclude: Intervention.

166. Gucciardi E, Demelo M, Lee RN, et al. 

Assessment of two culturally competent 

diabetes education methods: individual 

versus individual plus group education in 

Canadian Portuguese adults with type 2 

diabetes. Ethn Health. 2007 Apr;12(2):163-

87. PMID: 17364900. Exclude: Duration.

167. Guerci B, Drouin P, Grange V, et al. Selfmonitoring of blood glucose significantly 

improves metabolic control in patients with 

type 2 diabetes mellitus: the autosurveillance intervention active (ASIA) 

study. Diabetes Metab. 2003 Dec;29(6):587-

94. PMID: 14707887. Exclude: Intervention.

168. Guldbrand H, Lindstrom T, Dizdar B, et al. 

Randomization to a low-carbohydrate diet 

advice improves health related quality of life 

compared with a low-fat diet at similar 

weight-loss in type 2 diabetes mellitus. 

Diabetes Res Clin Pract. 2014 

Nov;106(2):221-7. PMID: 25271116. 

Exclude: Intervention.

169. Ha M, Hu J, Petrini MA, et al. The effects of 

an educational self-efficacy intervention on 

osteoporosis prevention and diabetes selfmanagement among adults with type 2 

diabetes mellitus. Biol Res Nurs. 

2014;16(4):357-67. PMID: 24413898. 

Exclude: Setting/Country.

170. Hains AA, Davies WH, Parton E, et al. A 

stress management intervention for 

adolescents with type 1 diabetes. Diabetes 

Educ. 2000 May-Jun;26(3):417-24. PMID: 

11151289. Exclude: Intervention.

171. Halbron M, Sachon C, Simon D, et al. 

Evaluation of a 5-day education programme 

in type 1 diabetes: achieving individual 

targets with a patient-centred approach. 

Diabet Med. 2014;31(4):500-3. PMID: 

24299225. Exclude: Setting/Country.

172. Halford WK, Goodall TA, Nicholson JM. 

Diet and diabetes (ii): a controlled trial of 

problem solving to improve dietary selfmanagement in patients with insulin 

dependent diabetes. Psychol Health. 1997 

1997/03/01;12(2):231-8. 

WOS:A1997WL08900006. Exclude: 

Intervention.

173. Halle M, Berg A, Garwers U, et al. 

Influence of 4 weeks' intervention by 

exercise and diet on low-density lipoprotein 

subfractions in obese men with type 2 

diabetes. Metabolism. 1999 May;48(5):641-

4. PMID: 10337867. Exclude: Design.

174. Hamdy O, Carver C. The why wait program: 

improving clinical outcomes through weight 

management in type 2 diabetes. Curr Diab 

Rep. 2008;8(5):413-20. PMID: 18778592. 

Exclude: Design.

175. Hamid S, Dunsiger S, Seiden A, et al. 

Impact of a diabetes control and 

management intervention on health care 

utilization in American Samoa. Chronic Illn. 

2014;10(2):122-34. PMID: 24085749

Exclude: Setting/Country.

176. Hardeman W, Lamming L, Kellar I, et al. 

Implementation of a nurse-led behaviour 

change intervention to support medication 

taking in type 2 diabetes: beyond 

hypothesised active ingredients (sams 

consultation study). Implement Sci. 

2014;9(70). PMID: 24902481. Exclude: 

Duration.

177. Hare JL, Hordern MD, Leano R, et al. 

Application of an exercise intervention on 

the evolution of diastolic dysfunction in 

patients with diabetes mellitus: efficacy and 

effectiveness. Circ. 2011 Jul;4(4):441-9. 

PMID: 21576281. Exclude: Intervention.

178. Hargraves JL, Ferguson WJ, Lemay CA, et 

al. Community health workers assisting 

patients with diabetes in self-management. J 

Ambulatory Care Manage. 2012 JanMar;35(1):15-26. PMID: 22156952. 

Exclude: Intervention.

179. Harris MA, Freeman KA, Beers M. Family 

therapy for adolescents with poorly 

controlled diabetes: initial test of clinical 

significance. J Pediatr Psychol. 2009 NovDec;34(10):1097-107. PMID: 19264879.

Exclude: Intervention.

180. Harris MA, Freeman KA, Duke DC, et al. 

Skype-based family problem solving for 

youth with poorly controlled diabetes: 

relative effectiveness of improving 
D-13

adherence and metabolic control. Diabetes. 

2013 July;62:A198. PMID: 71287222. 

Exclude: Publication type.

181. Harris MA, Greco P, Wysocki T, et al. 

Family therapy with adolescents with 

diabetes: a litmus test for clinically 

meaningful change. Fam Syst Health. 

2001;19(2):159-68. PMID: Not available. 

Exclude: Intervention.

182. Hawthorne K. Effect of culturally 

appropriate health education on glycaemic 

control and knowledge of diabetes in British 

Pakistani women with type 2 diabetes 

mellitus. Health Educ Res. 2001 

Jun;16(3):373-81. PMID: 11497119. 

Exclude: Intervention.

183. Hawthorne K, Tomlinson S. One-to-one 

teaching with pictures--flashcard health 

education for British Asians with diabetes. 

Br J Gen Pract. 1997 May;47(418):301-4. 

PMID: 9219407. Exclude: Intervention.

184. Headley S, Germain M, Wood R, et al. 

Short-term aerobic exercise and vascular 

function in ckd stage 3: a randomized 

controlled trial. Am J Kidney Dis. 

2014;64(2):222-9. PMID: 24776325. 

Exclude: Intervention.

185. Hee-Sung K. Impact of web-based nurse's 

education on glycosylated haemoglobin in 

type 2 diabetic patients. J Clin Nurs. 2007 

Jul;16(7):1361-6. PMID: 17584355. 

Exclude: Intervention.

186. Heinrich E, Candel MJ, Schaper NC, et al. 

Effect evaluation of a motivational 

interviewing based counselling strategy in 

diabetes care. Diabetes Res Clin Pract. 2010 

Dec;90(3):270-8. PMID: 20950883. 

Exclude: Intervention.

187. Heinrich E, De Nooijer J, Schaper NC, et al. 

Evaluation of the web-based diabetes 

interactive education programme (DIEP) for 

patients with type 2 diabetes. Patient Educ 

Couns. 2012 Feb;86(2):172-8. PMID: 

21616626. Exclude: Duration.

188. Heisler M, Vijan S, Makki F, et al. Diabetes 

control with reciprocal peer support versus 

nurse care management: a randomized trial. 

Ann Intern Med. 2010 Oct 19;153(8):507-

15. PMID: 20956707. Exclude: Intervention.

189. Hellgren MI, Petzold M, Beteus-Forslund H, 

et al. Feasibility of a randomized controlled 

intervention with physical activity in 

participants with impaired glucose tolerance 

recruited by FINDRISC: a pilot study. 

Scand J Public Health. 2014;42(5):463-70. 

PMID: 24867622. Exclude: Population.

190. Henry JL, Wilson PH, Bruce DG, et al. 

Cognitive-behavioural stress management 

for patients with non-insulin dependent 

diabetes mellitus. Psychol Health Med. 

1997;2(2):109-18. PMID: Not available. 

Exclude: Intervention.

191. Hermanns N, Kulzer B, Kubiak T, et al. The 

effect of an education programme (HYPOS) 

to treat hypoglycaemia problems in patients 

with type 1 diabetes. Diabetes Metab Res 

Rev. 2007 Oct;23(7):528-38. PMID: 

17245692. Exclude: Intervention.

192. Hiss RG, Armbruster BA, Gillard ML, et al. 

Nurse care manager collaboration with 

community-based physicians providing 

diabetes care: a randomized controlled trial. 

Diabetes Educ. 2007 May-Jun;33(3):493-

502. PMID: 17570880. Exclude: 

Intervention.

193. Hiss RG, Gillard ML, Armbruster BA, et al. 

Comprehensive evaluation of communitybased diabetic patients: effect of feedback to 

patients and their physicians: a randomized 

controlled trial. Diabetes Care. 2001 

Apr;24(4):690-4. PMID: 11315832. 

Exclude: Intervention.

194. Daily text messages and nurse follow-up 

improve self-management in patients with 

diabetes. Home Healthc Nurse. 

2014;32(10):618. PMID: Not available. 

Exclude: Publication type.

195. Innovative diabetes self-management 

programs identified for urban patients who 

speak various languages. Home Healthc 

Nurse. 2014;32(8):455-. PMID: Not 

available. Exclude: Publication Type.

196. Hood KK, Weissberg-Benchell J. 

Supporting teen problem solving (STEPS): 

depression prevention for teens with t1d. 

Diabetes. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/469/CN-
D-14

01009469/frame.html. Accessed March 20, 

2015. Exclude: Publication Type.

197. Hornsten A, Lundman B, Stenlund H, et al. 

Metabolic improvement after intervention 

focusing on personal understanding in type 2 

diabetes. Diabetes Res Clin Pract. 2005 

Apr;68(1):65-74. PMID: 15811567. 

Exclude: Intervention.

198. Hornsten A, Stenlund H, Lundman B, et al. 

Improvements in hba1c remain after 5 yearsa follow up of an educational intervention 

focusing on patients' personal 

understandings of type 2 diabetes. Diabetes 

Res Clin Pract. 2008 Jul;81(1):50-5. PMID: 

18372074. Exclude: Intervention.

199. Houston DK, Leng X, Bray GA, et al. A 

long-term intensive lifestyle intervention 

and physical function: the Look Ahead 

movement and memory study. Obesity 

(Silver Spring). 2015 Jan;23(1):77-84. 

PMID: 25452229. Exclude: Outcomes.

200. Howe CJ, Jawad AF, Tuttle AK, et al. 

Education and telephone case management 

for children with type 1 diabetes: a

randomized controlled trial. J Pediatr Nurs. 

2005 Apr;20(2):83-95. PMID: 15815568. 

Exclude: Intervention.

201. Howells L, Wilson AC, Skinner TC, et al. A 

randomized control trial of the effect of 

negotiated telephone support on glycaemic 

control in young people with type 1 

diabetes. Diabet Med. 2002 Aug;19(8):643-

8. PMID: 12147144. Exclude: Intervention.

202. Howorka K, Pumprla J, Wagner-Nosiska D, 

et al. Empowering diabetes out-patients with 

structured education: short-term and longterm effects of functional insulin treatment 

on perceived control over diabetes. J 

Psychosom Res. 2000 Jan;48(1):37-44. 

PMID: 10750628. Exclude: Intervention.

203. Huizinga MM, Gebretsadik T, Garcia Ulen 

C, et al. Preventing glycaemic relapse in 

recently controlled type 2 diabetes patients: 

a randomised controlled trial. Diabetologia. 

2010 May;53(5):832-9. PMID: 20084363. 

Exclude: Intervention.

204. Hunt CW, Sanderson BK, Ellison KJ. 

Support for diabetes using technology: a

pilot study to improve self-management. 

Medsurg Nurs. 2014;23(4):231-7. PMID: 

25318336. Exclude: Intervention.

205. Iafusco D, Galderisi A, Nocerino I, et al. 

Chat line for adolescents with type 1 

diabetes: a useful tool to improve coping 

with diabetes: a 2-year follow-up study. 

Diabetes Technol Ther. 2011 

May;13(5):551-5. PMID: 21406010. 

Exclude: Intervention.

206. Izquierdo R, Lagua CT, Meyer S, et al. 

Telemedicine intervention effects on waist 

circumference and body mass index in the 

ideatel project. Diabetes Technol Ther. 2010 

Mar;12(3):213-20. PMID: 20151772. 

Exclude: Intervention.

207. Jaber LA, Halapy H, Fernet M, et al. 

Evaluation of a pharmaceutical care model 

on diabetes management. Ann 

Pharmacother. 1996 Mar;30(3):238-43. 

PMID: 8833557. Exclude: Intervention.

208. Jaber LA, Halapy H, Fernet M, et al. 

Evaluation of a pharmaceutical care model 

on diabetes management. Ann 

Pharmacother. 1996 Mar;30(3):238-43. 

PMID: 8833557. Exclude: Intervention.

209. Jablon SL, Naliboff BD, Gilmore SL, et al. 

Effects of relaxation training on glucose 

tolerance and diabetic control in type ii 

diabetes. Appl Psychophysiol Biofeedback. 

1997 Sep;22(3):155-69. PMID: 9428966. 

Exclude: Intervention.

210. Jackson R, Asimakopoulou K, Scammell A. 

Assessment of the transtheoretical model as 

used by dietitians in promoting physical 

activity in people with type 2 diabetes. J 

Hum Nutr Diet. 2007 Feb;20(1):27-36. 

PMID: 17241190. Exclude: Intervention.

211. Jahangard-Rafsanjani Z, Sarayani A, Nosrati 

M, et al. Effect of a community pharmacistdelivered diabetes support program for 

patients receiving specialty medical care: a

randomized controlled trial. Diabetes Educ. 

2014 Nov 24. PMID: 25420946. Exclude: 

Setting/Country.

212. Jakicic JM, Egan CM, Fabricatore AN, et al. 

Four-year change in cardiorespiratory fitness 

and influence on glycemic control in adults 

with type 2 diabetes in a randomized trial: 

the Look Ahead trial. Diabetes Care. 2013 
D-15

May;36(5):1297-303. PMID: 23223405. 

Exclude: Outcomes.

213. Jakicic JM, Jaramillo SA, Balasubramanyam 

A, et al. Effect of a lifestyle intervention on 

change in cardiorespiratory fitness in adults 

with type 2 diabetes: results from the Look 

Ahead study. Int J Obes (Lond). 2009

Mar;33(3):305-16. PMID: 19153582. 

Exclude: Outcomes.

214. Jalilian M, Moeini B, Hazavehei SMM, et 

al. Physical activity stage-matched 

intervention: promoting metabolic control in 

type 2 diabetes. J Educ Health Promot.

2013;2:18. PMID: 24083268. Exclude: 

Setting/Country.

215. Jansa M, Vidal M, Viaplana J, et al. 

Telecare in a structured therapeutic 

education programme addressed to patients 

with type 1 diabetes and poor metabolic 

control. Diabetes Res Clin Pract. 2006 

Oct;74(1):26-32. PMID: 16621113. 

Exclude: Intervention.

216. Jansink R, Braspenning J, Keizer E, et al. 

No identifiable hb1ac or lifestyle change 

after a comprehensive diabetes programme 

including motivational interviewing: a

cluster randomised trial. Scand J Prim 

Health Care. 2013 Jun;31(2):119-27. PMID: 

23659710. Exclude: Population.

217. Jaser SS, Patel N, Rothman RL, et al. A 

randomized pilot of a positive psychology 

intervention to improve adherence in 

adolescents with type 1 diabetes. Diabetes 

Educ. 2014;40(5):659-67. PMID: 24867917. 

Exclude: Intervention.

218. Jennings CA, Vandelanotte C, Caperchione 

CM, et al. Effectiveness of a web-based 

physical activity intervention for adults with 

type 2 diabetes-a randomised controlled 

trial. Prev Med. 2014;60:33-40. PMID: 

24345601. Exclude: Intervention.

219. Johannsen NM, Sparks LM, Zhang Z, et al. 

Determinants of the changes in glycemic 

control with exercise training in type 2 

diabetes: a randomized trial. Diabetes 

Technol Ther. 2014; (Suppl. 1). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/182/CN00978182/frame.html. Accessed March 20, 

2015. Exclude: Intervention.

220. Johansen OE, Gullestad L, Blaasaas KG, et 

al. Effects of structured hospital-based care 

compared with standard care for type 2 

diabetes-the asker and baerum 

cardiovascular diabetes study, a randomized 

trial. Diabet Med. 2007 Sep;24(9):1019-27. 

PMID: 17509068. Exclude: Intervention.

221. Johnson W, Shaya FT, Winston R, et al. 

Diabetes control through an educational 

intervention. Ethn Dis. 2014;24(2):182-8. 

PMID: 24804364. Exclude: Intervention.

222. Johnston CA, Moreno JP, Foreyt JP. 

Cardiovascular effects of intensive lifestyle 

intervention in type 2 diabetes. Curr 

Atheroscler Rep. 2014 Dec;16(12):457. 

PMID: 25288176. Exclude: Publication 

Type.

223. Joshi R, Joshi N, Helmuth A. Improving 

ambulatory diabetes care in high-risk racial 

minorities: use of culture-specific education 

and close follow-up. Endocr Pract. 2010 

Mar-Apr;16(2):171-7. PMID: 19833583. 

Exclude: Outcomes.

224. Kahleova H, Matoulek M, Malinska H, et al. 

Vegetarian diet improves insulin resistance 

and oxidative stress markers more than 

conventional diet in subjects with type 2 

diabetes. Diabet Med. 2011 May;28(5):549-

59. PMID: 21480966. Exclude: Intervention.

225. Kang CM, Chang SC, Chen PL, et al. 

Comparison of family partnership 

intervention care vs. conventional care in 

adult patients with poorly controlled type 2 

diabetes in a community hospital: a

randomized controlled trial. Int J Nurs Stud. 

2010 Nov;47(11):1363-73. PMID: 

20371056. Exclude: Setting/Country.

226. Karstoft K, Christensen CS, Pedersen BK, et 

al. The acute effects of interval vs 

continuous-walking exercise on glycemic 

control in subjects with type 2 diabetes: a

crossover, controlled study. J Clin 

Endocrinol Metab. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/419/CN01014419/frame.html. Accessed March 20, 

2015. Exclude: Setting/Country.

227. Kempf K, Schloot NC, Gärtner B, et al. 

Meal replacement reduces insulin 
D-16

requirement, hba1c and weight long-term in 

type 2 diabetes patients with >100 u insulin 

per day. J Hum Nutr Diet. 2014:21-7. 

PMID: 23909831. Exclude: Design.

228. Kenya S, Lebron C, Reyes Arrechea E, et al. 

Glucometer use and glycemic control among

Hispanic patients with diabetes in Southern

Florida. Clin Ther. 2014;36(4):485-93. 

PMID: 24731865. Exclude: Design.

229. Kerr D, Gillam E, Ryder J, et al. An eastern 

art form for a western disease: randomised 

controlled trial of yoga in patients with 

poorly controlled insulin-treated diabetes. 

Practical Diabetes International. 2002 

July/August;19(6):164-6. PMID: Not 

available. Exclude: Intervention.

230. Keyserling TC, Ammerman AS, SamuelHodge CD, et al. A diabetes management 

program for African American women with 

type 2 diabetes. Diabetes Educ. 2000 SepOct;26(5):796-805. PMID: 11140007. 

Exclude: Outcomes.

231. Khosravizade TH, Madarshahian F, 

Khoshniat NM, et al. Impact of family 

support improvement behaviors on anti 

diabetic medication adherence and cognition

in type 2 diabetic patients. J Diabetes Metab 

Disord. 2014;13(1):113. PMID: 25436202. 

Exclude: Setting/Country.

232. Kim HJ, Kang CK, Park H, et al. Effects of 

vitamin d supplementation and circuit 

training on indices of obesity and insulin 

resistance in t2d and vitamin d deficient 

elderly women. J Exerc Nutrition Biochem. 

2014;18(3):249-57. PMID: 25566461. 

Exclude: Design.

233. Kim HS, Oh JA. Adherence to diabetes 

control recommendations: impact of nurse 

telephone calls. J Adv Nurs. 2003 

Nov;44(3):256-61. PMID: 14641395. 

Exclude: Intervention.

234. Kim HS, Oh JA, Lee HO. Effects of nursecoordinated intervention on patients with 

type 2 diabetes in korea. J Nurs Care Qual. 

2005 Apr-Jun;20(2):154-60. PMID: 

15839295. Exclude: Intervention.

235. Kim SI, Kim HS. Effectiveness of mobile 

and internet intervention in patients with 

obese type 2 diabetes. Int J Med Inform. 

2008 Jun;77(6):399-404. PMID: 17881285. 

Exclude: Intervention.

236. King DK, Glasgow RE, Toobert DJ, et al. 

Self-efficacy, problem solving, and socialenvironmental support are associated with 

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PMID: 20150299. Exclude: Design.

237. Kirk A, Mutrie N, Macintyre P, et al. 

Increasing physical activity in people with 

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Exclude: Intervention.

238. Kirk A, Mutrie N, Macintyre P, et al. Effects 

of a 12-month physical activity counselling 

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2004 May;47(5):821-32. PMID: 15138687. 

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239. Kirkman MS, Weinberger M, Landsman PB, 

et al. A telephone-delivered intervention for 

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240. Ko GT, Li JK, Kan EC, et al. Effects of a 

structured health education programme by a 

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9. PMID: 15569128. Exclude: Intervention.

241. Kolbasovsky A. A pilot project to address 

the behavioral health needs of people with 

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Exclude: Design.

242. Kolbasovsky A, Reich L. Improving the 

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intervention. J Healthc Qual. 2010;32(2):43-

51. PMID: 20364650. Exclude: Design.

243. Koproski J, Pretto Z, Poretsky L. Effects of 

an intervention by a diabetes team in 

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D-17

244. Korytkowski MT, Koerbel GL, Kotagal L, 

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245. Kraemer DF, Kradjan WA, Bianco TM, et 

al. A randomized study to assess the impact 

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Exclude: Intervention.

246. Krakow D, Feulner-Krakow G. Linda. The 

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Exclude: Design.

247. Krein SL, Klamerus ML, Vijan S, et al. Case 

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248. Krein SL, Klamerus ML, Vijan S, et al. Case 

management for patients with poorly 

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249. Kroese FM, Adriaanse MA, Vinkers CDW, 

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Exclude: Design.

250. Krousel-Wood MA, Berger L, Jiang X, et al. 

Does home-based exercise improve body 

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Results of a feasibility trial. Diabetes Res 

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251. Kulzer B, Hermanns N, Ehrmann D, et al. 

The effect of a diabetes education 

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252. Kuznetsov L, Long GH, Griffin SJ, et al. 

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253. Lagger G, Golay A. A 5 dimension 

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254. Laitinen J, Uusitupa M, Ahola I, et al. 

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255. Lane JD, Mccaskill CC, Ross SL, et al. 

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256. Lawler SP, Winkler E, Reeves MM, et al. 

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257. Lawson ML, Cohen N, Richardson C, et al. 

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40. PMID: 15787899. Exclude: Intervention.

258. Legorreta AP, Peters AL, Ossorio RC, et al. 

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259. Levetan CS, Dawn KR, Robbins DC, et al. 

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260. Li X, Zhang H, Yuan B, et al. Study on 

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D-18

261. Ligtenberg PC, Hoekstra JB, Bol E, et al. 

Effects of physical training on metabolic 

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262. Lipkin EW, Schwartz AV, Anderson AM, et 

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263. Lo R, Lo B, Wells E, et al. The development 

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264. Look ARG, Pi-Sunyer X, Blackburn G, et 

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265. Look ARG, Wing RR. Long-term effects of 

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266. Lorig KR, Ritter PL, Gonzalez VM. 

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267. Lucotti P, Monti LD, Setola E, et al. Aerobic 

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268. Lukács A, Varga B, Kiss-Tóth E, et al. 

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269. Luley C, Blaik A, Reschke K, et al. Weight 

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270. Lynch EB, Liebman R, Ventrelle J, et al. 

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271. Macphail M, Mullan B, Sharpe L, et al. 

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272. Magee MF, Khan NH, Desale S, et al. 

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273. Maindal HT, Carlsen AH, Lauritzen T, et al. 

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274. Maislos M, Weisman D. Multidisciplinary 

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D-19

275. Maljanian R, Grey N, Staff I, et al. Intensive 

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276. Maloni HW. An intervention to effect 

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available. Exclude: Duration.

277. Mandalia PK, Stone MA, Davies MJ, et al. 

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278. Manning RM, Jung RT, Leese GP, et al. The 

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15. PMID: 7648803. Exclude: Intervention.

279. Manning RM, Jung RT, Leese GP, et al. The 

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280. Martinus R, Corban R, Wackerhage H, et al. 

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281. Matam P, Kumaraiah V, Munichoodappa C, 

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282. Mathis RA. The effect of exercise training 

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283. Mau MK, Glanz K, Severino R, et al. 

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Exclude: Design.

284. Mavros Y, Kay S, Simpson KA, et al. 

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285. Mayer-Davis EJ, D'antonio A, Martin M, et 

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35. PMID: 11373164. Exclude: Outcomes.

286. Mazzuca KB, Farris NA, Mendenhall J, et 

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287. Mccarrier KP, Ralston JD, Hirsch IB, et al. 

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288. Mcginnis RA, Mcgrady A, Cox SA, et al. 

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289. Mckay HG, Glasgow RE, Feil EG, et al. 

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Exclude: Outcomes.

290. Mckay HG, King D, Eakin EG, et al. The 

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D-20

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291. Mclean DL, Mcalister FA, Johnson JA, et al. 

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292. Mcmahon GT, Fonda SJ, Gomes HE, et al. 

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293. Mcmahon GT, Gomes HE, Hickson Hohne 

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294. Mehuys E, Van Bortel L, De Bolle L, et al. 

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295. Mendez FJ, Belendez M. Effects of a 

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296. Mengham LH, Morris BF, Palmer CR, et al. 

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available. Exclude: Intervention.

297. Middelkoop BJC, Geelhoed-Duijvestijn 

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298. Miller CK, Edwards L, Kissling G, et al. 

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299. Miller CK, Jensen GL, Achterberg CL. 

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300. Mitra A, Dewanjee D, Dey B. Mechanistic 

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301. Mollaoglu M, Beyazit E. Influence of 

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302. Mons U, Raum E, Kramer HU, et al. 

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303. Moskowitz D, Thom DH, Hessler D, et al. 

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304. Mulvaney SA, Rothman RL, Wallston KA, 

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305. Murphy HR, Wadham C, Hassler-Hurst J, et 

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D-21

306. Naccashian Z. The impact of diabetes selfmanagement education on glucose 

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307. Naik AD, Palmer N, Petersen NJ, et al. 

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308. Naik AD, Palmer N, Petersen NJ, et al. 

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309. Naik AD, White CD, Robertson SM, et al. 

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310. Nakamura N, Kanematsu Y. Coping in 

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311. Nebel IT, Klemm T, Fasshauer M, et al. 

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312. New NF. The development and outcomes of 

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313. Newton KT. Impact of an interactive health 

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314. Nicholas DB, Fellner KD, Frank M, et al. 

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315. Niswender K, Piletic M, Andersen H, et al. 

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316. Niswender K, Piletic M, Andersen H, et al. 

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317. Noda K, Zhang B, Iwata A, et al. Lifestyle 

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318. Noel PH, Larme AC, Meyer J, et al. Patient 

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319. Nothwehr FK, Guare J, Marrero DG, et al. 

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320. Nunn E, King B, Smart C, et al. A 

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321. O'connor PJ, Desai J, Solberg LI, et al. 

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D-22

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322. Ofstad AP, Johansen OE, Gullestad L, et al. 

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323. Oh JA, Kim HS, Yoon KH, et al. A 

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324. O'hare JP, Raymond NT, Mughal S, et al. 

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325. O'kane MJ, Bunting B, Copeland M, et al. 

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326. Orsama AL, Lahteenmaki J, Harno K, et al. 

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327. Osborn CY. Using the imb model of health 

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available. Exclude: Duration.

328. Palizgir M, Bakhtiyari M, Esteghamati A. 

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329. Panagiotopoulos C, Preston JM, Stewart LL, 

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330. Panagiotopoulos C, Stewart LL. Weekly 

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331. Pandit AU, Bailey SC, Curtis LM, et al. 

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332. Park SY, Lee IH. Effects on training and 

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Intervention.

333. Pascale RW, Wing RR, Butler BA, et al. 

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334. Patton SR, Odar C, Midyett LK, et al. Pilot 

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335. Pena-Purcell NC, Boggess MM. An 

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336. Perez-Escamilla R, Damio G, Chhabra J, et 

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D-23

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the dialbest trial. Diabetes Care. 2014 Aug 

14. PMID: 25125508. Exclude: Intervention.

337. Perez-Tortosa S, Roig L, Manresa JM, et al. 

Continued smoking abstinence in diabetic 

patients in primary care: a cluster 

randomized controlled multicenter study. 

Diabetes Res Clin Pract. 2014 Sep 30. 

PMID: 25444354. Exclude: Intervention.

338. Phumipamorn S, Pongwecharak J, Soorapan 

S, et al. Effects of the pharmacist's input on 

glycaemic control and cardiovascular risks 

in Muslim diabetes. Prim Care Diabetes. 

2008 Feb;2(1):31-7. PMID: 18684418. 

Exclude: Setting/Country.

339. Piatt GA, Orchard TJ, Emerson S, et al. 

Translating the chronic care model into the 

community: results from a randomized 

controlled trial of a multifaceted diabetes 

care intervention. Diabetes Care. 2006 

Apr;29(4):811-7. PMID: 16567820. 

Exclude: Intervention.

340. Pibernik-Okanovic M, Prasek M, PoljicaninFilipovic T, et al. Effects of an 

empowerment-based psychosocial 

intervention on quality of life and metabolic 

control in type 2 diabetic patients. Patient 

Educ Couns. 2004 Feb;52(2):193-9. PMID: 

15132525. Exclude: Design.

341. Piette JD, Mcphee SJ, Weinberger M, et al. 

Use of automated telephone disease 

management calls in an ethnically diverse 

sample of low-income patients with 

diabetes. Diabetes Care. 1999 

Aug;22(8):1302-9. PMID: 10480775. 

Exclude: Intervention.

342. Piette JD, Richardson C, Himle J, et al. A 

randomized trial of telephonic counseling 

plus walking for depressed diabetes patients. 

Med Care. 2011 Jul;49(7):641-8. PMID: 

21478777. Exclude: Intervention.

343. Piette JD, Weinberger M, Kraemer FB, et al. 

Impact of automated calls with nurse followup on diabetes treatment outcomes in a 

department of veterans affairs health care 

system: a randomized controlled trial. 

Diabetes Care. 2001 Feb;24(2):202-8. 

PMID: 11213866. Exclude: Intervention.

344. Piette JD, Weinberger M, Mcphee SJ. The 

effect of automated calls with telephone 

nurse follow-up on patient-centered 

outcomes of diabetes care: a randomized, 

controlled trial. Med Care. 2000 

Feb;38(2):218-30. PMID: 10659695. 

Exclude: Intervention.

345. Plotnikoff RC, Karunamuni N, Courneya 

KS, et al. The Alberta diabetes and physical 

activity trial (ADAPT): a randomized trial 

evaluating theory-based interventions to 

increase physical activity in adults with type 

2 diabetes. Ann Behav Med. 2013 

Feb;45(1):45-56. PMID: 22922954. 

Exclude: Intervention.

346. Polonsky WH, Earles J, Smith S, et al. 

Integrating medical management with 

diabetes self-management training: a

randomized control trial of the diabetes 

outpatient intensive treatment program. 

Diabetes Care. 2003 Nov;26(11):3048-53. 

PMID: 14578238. Exclude: Intervention.

347. Puffelen AL, Rijken M, Nijpels G, et al. 

Group-based self-management support leads 

to more adequate exercise behaviour in 

recently diagnosed type 2 diabetes patients. 

Diabetologia. 2014; (1 suppl. 1). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/229/CN01009229/frame.html. Accessed March 20, 

2015. Exclude: Publication Type.

348. Rachmani R, Slavacheski I, Berla M, et al. 

Treatment of high-risk patients with 

diabetes: motivation and teaching 

intervention: a randomized, prospective 8-

year follow-up study. J Am Soc Nephrol. 

2005 Mar;16 Suppl 1:S22-6. PMID: 

15938028. Exclude: Intervention.

349. Raji A, Gomes H, Beard JO, et al. A 

randomized trial comparing intensive and 

passive education in patients with diabetes 

mellitus. Arch Intern Med. 2002 Jun 

10;162(11):1301-4. PMID: 12038949. 

Exclude: Duration.

350. Rami B, Popow C, Horn W, et al. 

Telemedical support to improve glycemic 

control in adolescents with type 1 diabetes 

mellitus. Eur J Pediatr. 2006 

Oct;165(10):701-5. PMID: 16670859. 

Exclude: Intervention.
D-24

351. Raynor HA, Anderson AM, Miller GD, et 

al. Partial meal replacement plan and quality 

of the diet at 1 year: action for health in 

diabetes (Look Ahead) trial. J Acad Nutr 

Diet. 2015 Jan 6. PMID: 25573655. 

Exclude: Outcomes.

352. Reaney M, Zorzo EG, Golay A, et al. Impact 

of conversation map education tools versus 

regular care on diabetes-related knowledge 

of people with type 2 diabetes: a

randomized, controlled study. Diabetes 

Spectr. 2014(4):236-45. PMID: Not 

available. Exclude: Publication type.

353. Redmon JB, Raatz SK, Reck KP, et al. Oneyear outcome of a combination of weight 

loss therapies for subjects with type 2 

diabetes: a randomized trial. Diabetes Care. 

2003 Sep;26(9):2505-11. PMID: 12941710. 

Exclude: Intervention.

354. Reilly CM, Higgins M, Butler J, et al. Cost 

effectiveness of an integrated self care 

intervention for persons with heart failure 

and diabetes. J Card Fail. 2014;20(8):S5-S. 

PMID: Not available. Exclude: 

Setting/Country.

355. Rejeski WJ, Bray GA, Chen SH, et al. 

Aging and physical function in type 2 

diabetes: 8 years of an intensive lifestyle 

intervention. J Gerontol A Biol Sci Med Sci. 

2014 Jul 1. PMID: 24986062. Exclude: 

Outcomes.

356. Robertson JL. Evaluation of an andragogical 

intervention on the self-care behaviors of 

adults with non-insulin dependent diabetes 

mellitus. University of Arkansas; 2002. 

Exclude: Duration.

357. Robison FF. A training and support group 

for elderly diabetics: description and 

evaluation. Journal for Specialists in Group 

Work. 1993;18(3):127-36. PMID: Not 

available. Exclude: Outcomes.

358. Rosal MC, White MJ, Borg A, et al. 

Translational research at community health 

centers: challenges and successes in 

recruiting and retaining low-income Latino 

patients with type 2 diabetes into a 

randomized clinical trial. Diabetes Educ. 

2010 Sep-Oct;36(5):733-49. PMID: 

20729512. Exclude: Outcomes.

359. Rosenbek Minet LK, Wagner L, Lonvig 

EM, et al. The effect of motivational 

interviewing on glycaemic control and 

perceived competence of diabetes selfmanagement in patients with type 1 and type 

2 diabetes mellitus after attending a group 

education programme: a randomised 

controlled trial. Diabetologia. 2011 

Jul;54(7):1620-9. PMID: 21455729. 

Exclude: Intervention.

360. Rosenberg D, Lin E, Peterson D, et al. 

Integrated medical care management and 

behavioral risk factor reduction for 

multicondition patients: behavioral 

outcomes of the teamcare trial. Gen Hosp 

Psychiatry. 2014;36(2):129-34. PMID: 

24333157. Exclude: Intervention.

361. Rossi MC, Nicolucci A, Di Bartolo P, et al. 

Diabetes interactive diary: a new 

telemedicine system enabling flexible diet 

and insulin therapy while improving quality 

of life: an open-label, international, 

multicenter, randomized study. Diabetes 

Care. 2010 Jan;33(1):109-15. PMID: 

19808926. Exclude: Intervention.

362. Rothman RL, Dewalt DA, Malone R, et al. 

Influence of patient literacy on the 

effectiveness of a primary care-based 

diabetes disease management program. 

JAMA. 2004 Oct 13;292(14):1711-6. PMID: 

15479936. Exclude: Intervention.

363. 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. 2005 Mar;118(3):276-84. PMID: 

15745726. Exclude: Intervention.

364. Rubak S, Sandbaek A, Lauritzen T, et al. 

Effect of "motivational interviewing" on 

quality of care measures in screen detected 

type 2 diabetes patients: a one-year followup of an rct, addition Denmark. Scand J 

Prim Health Care. 2011 Jun;29(2):92-8. 

PMID: 21306296. Exclude: Intervention.

365. Rush TE. Assessing the efficacy of a 

culturally informed adherence intervention 

for rural African Americans with type 2 

diabetes. Dissertation Abstracts 

International: Section B: The Sciences and 
D-25

Engineering. 2014;75(1-B E). PMID: Not 

available. Exclude: Full text not available.

366. Ryabov I. The impact of community health 

workers on behavioral outcomes and 

glycemic control of diabetes patients on the 

U.S.-Mexico border. Int Q Community 

Health Educ. 2010;31(4):387-99. PMID: 

22192944. Exclude: Design.

367. Ryabov I. Cost-effectiveness of community 

health workers in controlling diabetes 

epidemic on the U.S.-Mexico border. Public 

Health. 2014;128(7):636-42. PMID: 

24999158. Exclude: Design.

368. Ryden O, Nevander L, Johnsson P, et al. 

Family therapy in poorly controlled juvenile 

IDDM: effects on diabetic control, selfevaluation and behavioural symptoms. Acta 

Paediatr. 1994 Mar;83(3):285-91. PMID: 

8038531. Exclude: Intervention.

369. Rygg LO, Rise MB, Gronning K, et al. 

Efficacy of ongoing group based diabetes 

self-management education for patients with 

type 2 diabetes mellitus. a randomised 

controlled trial. Patient Educ Couns. 2012 

Jan;86(1):98-105. PMID: 21592715. 

Exclude: Duration.

370. Sacco WP, Bykowski CA, Mayhew LL, et 

al. Educational attainment moderates the 

effect of a brief diabetes self-care 

intervention. Diabetes Res Clin Pract. 2012 

Jan;95(1):62-7. PMID: 21992869. Exclude: 

Outcomes.

371. Sacre JW, Jellis CL, Jenkins C, et al. A sixmonth exercise intervention in subclinical 

diabetic heart disease: effects on exercise 

capacity, autonomic and myocardial 

function. Metabolism. 2014;63(9):1104-14. 

PMID: 24997499. Exclude: Design.

372. Sadler GR, Ko, C.M., Wu, P., Ngai, P.

Lessons learned from the black 

cosmetologists promoting health program: a

randomized controlled trial testing a 

diabetes education program. J Commun

Healthc. 2014;7(2):117-27. PMID: Not 

available. Exclude: Population.

373. Sadur CN, Moline N, Costa M, et al. 

Diabetes management in a health 

maintenance organization. Efficacy of care 

management using cluster visits. Diabetes 

Care. 1999 Dec;22(12):2011-7. PMID: 

10587835. Exclude: Intervention.

374. Saengtipbovorn S, Taneepanichskul S. 

Effectiveness of lifestyle change plus dental 

care (LCDC) program on improving 

glycemic and periodontal status in the 

elderly with type 2 diabetes. BMC Oral 

Health. 2014;14(72). PMID: 24934646. 

Exclude: Setting/Country.

375. Safren SA, Gonzalez JS, Wexler DJ, et al. A 

randomized controlled trial of cognitive 

behavioral therapy for adherence and 

depression (CBT-AD) in patients with 

uncontrolled type 2 diabetes. Diabetes Care. 

2014 Mar;37(3):625-33. PMID: 24170758. 

Exclude: Population.

376. Saletsky RD, Trief PM, Anderson BJ, et al. 

Parenting style, parent-youth conflict, and 

medication adherence in youth with type 2 

diabetes participating in an intensive 

lifestyle change intervention. Fam Syst 

Health. 2014;32(2):176-85. PMID:

24548045. Exclude: Design.

377. Samaras K, Ashwell S, Mackintosh AM, et 

al. Will older sedentary people with noninsulin-dependent diabetes mellitus start 

exercising? A health promotion model. 

Diabetes Res Clin Pract. 1997 

Aug;37(2):121-8. PMID: 9279482. Exclude: 

Intervention.

378. Scain SF, Friedman R, Gross JL. A 

structured educational program improves 

metabolic control in patients with type 2 

diabetes: a randomized controlled trial. 

Diabetes Educ. 2009 Jul-Aug;35(4):603-11. 

PMID: 19451553. Exclude: Setting/Country.

379. Schillinger D, Handley M, Wang F, et al. 

Effects of self-management support on 

structure, process, and outcomes among 

vulnerable patients with diabetes: a threearm practical clinical trial. Diabetes Care. 

2009 Apr;32(4):559-66. PMID: 19131469. 

Exclude: Intervention.

380. Schneider KL, Pagoto SL, Handschin B, et 

al. Design and methods for a pilot 

randomized clinical trial involving exercise 

and behavioral activation to treat comorbid 

type 2 diabetes and major depressive 

disorder. Ment Health Phy Act. 2011 
D-26

June;4(1):13-21. PMID: 21765864. Exclude: 

Intervention.

381. Schwedes U, Siebolds M, Mertes G. Mealrelated structured self-monitoring of blood 

glucose: effect on diabetes control in noninsulin-treated type 2 diabetic patients. 

Diabetes Care. 2002 Nov;25(11):1928-32. 

PMID: 12401734. Exclude: Intervention.

382. Scott DM, Boyd ST, Stephan M, et al. 

Outcomes of pharmacist-managed diabetes 

care services in a community health center. 

Am J Health Syst Pharm. 2006 Nov 

1;63(21):2116-22. PMID: 17057049. 

Exclude: Intervention.

383. Sears B, Kahl P, Rapier G. The San Antonio 

type 2 diabetic study. International Journal 

of Applied Kinesiology & Kinesiologic 

Medicine. 2006(21):66-7. PMID: Not 

available. Exclude: Intervention.

384. Shaya FT, Chirikov VV, Howard D, et al. 

Effect of social networks intervention in 

type 2 diabetes: a partial randomised study. J 

Epidemiol Community Health. 

2014;68(4):326-32. PMID: 24297971. 

Exclude: Design.

385. Shea S, Weinstock RS, Starren J, et al. A 

randomized trial comparing telemedicine 

case management with usual care in older, 

ethnically diverse, medically underserved 

patients with diabetes mellitus. J Am Med 

Inform Assoc. 2006 Jan-Feb;13(1):40-51. 

PMID: 16221935. Exclude: Intervention.

386. Shechter A, St-Onge MP, Kuna ST, et al. 

Sleep architecture following a weight loss 

intervention in overweight and obese 

patients with obstructive sleep apnea and 

type 2 diabetes: relationship to apneahypopnea index. J Clin Sleep Med. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/742/CN01015742/frame.html. Accessed March 20, 

2015. Exclude: Outcomes.

387. Shi Q, Ostwald SK, Wang S. Improving 

glycaemic control self-efficacy and 

glycaemic control behaviour in chinese 

patients with type 2 diabetes mellitus: 

randomised controlled trial. J Clin Nurs. 

2010 Feb;19(3-4):398-404. PMID: 

20500279. Exclude: Setting/Country.

388. Siebolds M, Gaedeke O, Schwedes U. Selfmonitoring of blood glucose-psychological 

aspects relevant to changes in hba1c in type 

2 diabetic patients treated with diet or diet 

plus oral antidiabetic medication. Patient 

Educ Couns. 2006 Jul;62(1):104-10. PMID: 

16159705. Exclude: Intervention.

389. Silverman JB, Krieger J, Kiefer MM, et al. 

The association of food insecurity and 

diabetes control among low-income 

individuals. J Gen Intern Med. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/120/CN01010120/frame.html. Accessed March 20, 

2015. Exclude: Design.

390. Siminerio L, Ruppert K, Huber K, et al. 

Telemedicine for reach, education, access, 

and treatment (TREAT): linking 

telemedicine with diabetes self-management 

education to improve care in rural 

communities. Diabetes Educ. 

2014;40(6):797-805. PMID: 25253624. 

Exclude: Design.

391. Siminerio LM, Ruppert K, Emerson S, et al. 

Delivering diabetes self-management 

education (DSME) in primary care: the 

Pittsburgh regional initiative for diabetes 

education (PRIDE). Disease Management & 

Health Outcomes. 2008;16(4):267-72. 

PMID: Not available. Exclude: Design.

392. Simmons D, Fleming C, Voyle J, et al. A 

pilot urban church-based programme to 

reduce risk factors for diabetes among 

Western Samoans in New Zealand. Diabet 

Med. 1998 Feb;15(2):136-42. PMID: 

9507914. Exclude: Intervention.

393. Simmons D, Gamble GD, Foote S, et al. The 

New Zealand diabetes passport study: a

randomized controlled trial of the impact of 

a diabetes passport on risk factors for 

diabetes-related complications. Diabet Med. 

2004 Mar;21(3):214-7. PMID: 15008829. 

Exclude: Intervention.

394. Sinclair AJ, Girling AJ, Gadsby R, et al. 

Diabetes in care homes: a cluster 

randomised controlled trial of resident 

education. British Journal of Diabetes and 

Vascular Disease. 2012 SeptemberOctober;12(5):238-42. PMID: Not available. 

Exclude: Intervention.
D-27

395. Skoro-Kondza L, Tai SS, Gadelrab R, et al. 

Community based yoga classes for type 2 

diabetes: an exploratory randomised 

controlled trial. BMC Health Serv Res. 

2009;9:33. PMID: 19228402. Exclude: 

Intervention.

396. Smith L, Weinert C. Telecommunication 

support for rural women with diabetes. 

Diabetes Educ. 2000 Jul-Aug;26(4):645-55. 

PMID: 11140073. Exclude: Intervention.

397. Smith SM, Paul G, Kelly A, et al. Peer 

support for patients with type 2 diabetes: 

cluster randomised controlled trial. BMJ. 

2011;342:d715. PMID: 21324992. Exclude: 

Intervention.

398. Snel M, Gastaldelli A, Ouwens DM, et al. 

Effects of adding exercise to a 16-week very 

low-calorie diet in obese, insulin-dependent 

type 2 diabetes mellitus patients. J Clin 

Endocrinol Metab. 2012 Jul;97(7):2512-20. 

PMID: 22569236. Exclude: Setting/Country.

399. Snoek FJ, Van Der Ven NCW, Twisk JWR, 

et al. Cognitive behavioural therapy (CBT) 

compared with blood glucose awareness 

training (BGAT) in poorly controlled type 1 

diabetic patients: long-term effects on hba 

moderated by depression: a randomized 

controlled trial. Diabet Med. 2008 

Nov;25(11):1337-42. PMID: 19046225. 

Exclude: Intervention.

400. Sone H, Katagiri A, Ishibashi S, et al. 

Effects of lifestyle modifications on patients 

with type 2 diabetes: the Japan diabetes 

complications study (JDCS) study design, 

baseline analysis and three year-interim 

report. Horm Metab Res. 2002 

Sep;34(9):509-15. PMID: 12384828. 

Exclude: Intervention.

401. Sone H, Tanaka S, Iimuro S, et al. Longterm lifestyle intervention lowers the 

incidence of stroke in Japanese patients with 

type 2 diabetes: a nationwide multicentre 

randomised controlled trial (the Japan 

diabetes complications study). Diabetologia. 

2010 Mar;53(3):419-28. PMID: 20054522. 

Exclude: Intervention.

402. Song M, Choe M, Kim KS, et al. An 

evaluation of web-based education as an 

alternative to group lectures for diabetes 

self-management. Nurs Health Sci. 2009 

Sep;11(3):277-84. PMID: 19689636. 

Exclude: Design.

403. Song M, Park Y, Song W, et al. Combined 

exercise training and self-management 

education for community-dwelling older 

adults with diabetes in Korea. J Gerontol 

Nurs. 2012 Oct;38(10):38-48. PMID: 

22998094. Exclude: Design.

404. Song MS, Kim HS. Effect of the diabetes 

outpatient intensive management 

programme on glycaemic control for type 2 

diabetic patients. J Clin Nurs. 2007 

Jul;16(7):1367-73. PMID: 17584356. 

Exclude: Design.

405. Souto DL, Zajdenverg L, Rodacki M, et al. 

Impact of advanced and basic carbohydrate 

counting methods on metabolic control in 

patients with type 1 diabetes. Nutrition. 

2014;30(3):286-90. PMID: 24360781. 

Exclude: Setting/Country.

406. Steed L, Barnard M, Hurel S, et al. How 

does change occur following a theoretically 

based self-management intervention for type 

2 diabetes. Psychol Health Med. 

2014;19(5):536-46. PMID: 24111492. 

Exclude: Outcomes.

407. Stuckey HL, Dellasega C, Graber NJ, et al. 

Diabetes nurse case management and 

motivational interviewing for change 

(dynamic): study design and baseline 

characteristics in the chronic care model for 

type 2 diabetes. Contemp Clin Trials. 2009 

Jul;30(4):366-74. PMID: 19328244. 

Exclude: Publication type.

408. Sturt JA, Whitlock S, Fox C, et al. Effects of 

the diabetes manual 1:1 structured education 

in primary care. Diabet Med. 2008 

Jun;25(6):722-31. PMID: 18435777. 

Exclude: Intervention.

409. Surwit RS, Van Tilburg MA, Zucker N, et 

al. Stress management improves long-term 

glycemic control in type 2 diabetes. 

Diabetes Care. 2002 Jan;25(1):30-4. PMID: 

11772897. Exclude: Intervention.

410. Svoren BM, Butler D, Levine BS, et al. 

Reducing acute adverse outcomes in youths 

with type 1 diabetes: a randomized, 

controlled trial. Pediatrics. 2003 
D-28

Oct;112(4):914-22. PMID: 14523186. 

Exclude: Intervention.

411. Tang PC, Overhage JM, Chan AS, et al. 

Online disease management of diabetes: 

engaging and motivating patients online 

with enhanced resources-diabetes 

(EMPOWER-D), a randomized controlled 

trial. J Am Med Inform Assoc. 2013 May 

1;20(3):526-34. PMID: 23171659. Exclude: 

Intervention.

412. Tao H, Sun XQ, He JH, et al. An interactive 

telemedicine system improves diabetes 

management for type 2 diabetic patients in 

China. Diabetes. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/451/CN01009451/frame.html. Accessed March 20, 

2015. Exclude: Setting/Country.

413. Tatti P, Lehmann ED. A prospective 

randomised-controlled pilot study for 

evaluating the teaching utility of interactive 

educational diabetes simulators. Diabetes 

Nutr Metab. 2003 Feb;16(1):7-23. PMID: 

12848301. Exclude: Intervention.

414. Taveira TH, Friedmann PD, Cohen LB, et 

al. Pharmacist-led group medical 

appointment model in type 2 diabetes. 

Diabetes Educ. 2010 Jan-Feb;36(1):109-17. 

PMID: 19966072. Exclude: Intervention.

415. Taylor CB, Miller NH, Reilly KR, et al. 

Evaluation of a nurse-care management 

system to improve outcomes in patients with 

complicated diabetes. Diabetes Care. 2003 

Apr;26(4):1058-63. PMID: 12663573. 

Exclude: Intervention.

416. Taylor DJ, Fletcher JP, Mathis RA, et al.

Effects of moderate- versus high- intensity 

exercise training on physical fitness and 

physical function in people with type 2 

diabetes: a randomized clinical trial. Phys 

Ther. 2014;94(12):1720-30. PMID: 

99778997. Exclude: Intervention.

417. Taylor KI, Oberle KM, Crutcher RA, et al. 

Promoting health in type 2 diabetes: nursephysician collaboration in primary care. Biol 

Res Nurs. 2005 Jan;6(3):207-15. PMID: 

15583361. Exclude: Intervention.

418. Thom D, Hessler D, Willard-Grace R, et al. 

Impact of health coaching on patient trust in 

their primary care provider: a randomized 

controlled trial. J Gen Intern Med. 2014. 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/128/CN01010128/frame.html. Accessed March 20, 

2015. Exclude: Outcomes.

419. Thom DH, Ghorob A, Hessler D, et al. 

Impact of peer health coaching on glycemic 

control in low-income patients with 

diabetes: a randomized controlled trial. Ann 

Fam Med. 2013 Mar-Apr;11(2):137-44. 

PMID: 23508600. Exclude: Intervention.

420. Thom DH, Hessler D, Willard-Grace R, et 

al. Does health coaching change patients' 

trust in their primary care provider? Patient 

Educ Couns. 2014;96(1):135-8. PMID:

24776175. Exclude: Population.

421. Thoolen B, De Ridder D, Bensing J, et al. 

Who participates in diabetes selfmanagement interventions? Issues of 

recruitment and retainment. Diabetes Educ. 

2007 May-Jun;33(3):465-74. PMID: 

17570877. Exclude: Outcomes.

422. Thoolen B, De Ridder D, Bensing J, et al. 

Beyond good intentions: the development 

and evaluation of a proactive selfmanagement course for patients recently 

diagnosed with type 2 diabetes. Health Educ 

Res. 2008 Feb;23(1):53-61. PMID: 

17289660. Exclude: Outcomes.

423. Tomar R, Hamdan M, Al-Qahtani MH. 

Effect of low to moderate intensity walking 

and cycling on glycaemic and metabolic 

control in type 1 diabetes mellitus 

adolescent males: a randomized controlled 

trial. Isokinet Exerc Sci. 2014;22(3):237-43. 

PMID: Not available. Exclude: Intervention.

424. Tomioka M, Braun KL, Ah Cook V, et al. 

Improving behavioral and clinical indicators 

in Asians and Pacific Islanders with 

diabetes: findings from a community clinicbased program. Diabetes Res Clin Pract. 

2014;104(2):220-5. PMID: 24636628. 

Exclude: Design.

425. Toobert DJ, Strycker LA, Barrera M, et al. 

Seven-year follow-up of a multiple-healthbehavior diabetes intervention. Am J Health

Behav. 2010 Nov-Dec;34(6):680-94. PMID: 

20604694. Exclude: Outcomes.
D-29

426. Torbjornsen A, Jenum AK, Smastuen MC, 

et al. A low-intensity mobile health 

intervention with and without health 

counseling for persons with type 2 diabetes, 

part 1: baseline and short-term results from a 

randomized controlled trial in the 

Norwegian part of renewing health. JMIR 

MHealth and UHealth. 2014;2(4). PMID: 

25499592. Exclude: Outcomes.

427. Tovote KA, Fleer J, Snippe E, et al. 

Individual mindfulness-based cognitive 

therapy and cognitive behavior therapy for 

treating depressive symptoms in patients 

with diabetes: results of a randomized 

controlled trial. Diabetes Care. 2014; (9).

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/152/CN01002152/frame.html. Accessed March 20, 

2015. Exclude: Intervention.

428. Trento M, Basile M, Borgo E, et al. A 

randomised controlled clinical trial of 

nurse-, dietitian- and pedagogist-led 

Group Care for the management of Type 2 

diabetes. J Endocrinol Invest. 2008 

Nov;31(11):1038-42. PMID: 19169063. 

Exclude: Intervention.

429. Trento M, Gamba S, Gentile L, et al. 

Rethink organization to improve education 

and outcomes (ROMEO): a multicenter 

randomized trial of lifestyle intervention by 

group care to manage type 2 diabetes. 

Diabetes Care. 2010 Apr;33(4):745-7. 

PMID: 20103547. Exclude: Intervention.

430. Trento M, Passera P, Bajardi M, et al. 

Lifestyle intervention by group care

prevents deterioration of type ii diabetes: a

4-year randomized controlled clinical trial. 

Diabetologia. 2002 Sep;45(9):1231-9. 

PMID: 12242455. Exclude: Intervention.

431. Trento M, Passera P, Borgo E, et al. A 3-

year prospective randomized controlled 

clinical trial of group care in type 1 diabetes. 

Nutr Metab Cardiovasc Dis. 2005 

Aug;15(4):293-301. PMID: 16054554. 

Exclude: Intervention.

432. Trento M, Passera P, Borgo E, et al. A 5-

year randomized controlled study of 

learning, problem solving ability, and 

quality of life modifications in people with 

type 2 diabetes managed by group care. 

Diabetes Care. 2004 Mar;27(3):670-5. 

PMID: 14988283. Exclude: Intervention.

433. Trento M, Passera P, Tomalino M, et al. 

Group visits improve metabolic control in 

type 2 diabetes: a 2-year follow-up. Diabetes 

Care. 2001 Jun;24(6):995-1000. PMID: 

11375359. Exclude: Intervention.

434. Trento M, Passera P, Tomalino M, et al. 

Therapeutic group education in the followup of patients with non-insulin treated, noninsulin dependent diabetes mellitus. 

Diabetes Nutr Metab. 1998;11(3):212-6. 

PMID: Not available. Exclude: Intervention.

435. Trento M, Trinetta A, Kucich C, et al. 

Carbohydrate counting improves coping 

ability and metabolic control in patients with 

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PMID: 20440106. Exclude: Intervention.

436. Trief PM, Izquierdo R, Eimicke JP, et al. 

Adherence to diabetes self care for white, 

African-American and Hispanic American 

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2013;18(1):83-96. PMID: 22762449. 

Exclude: Intervention.

437. Trief PM, Sandberg J, Fisher L, et al. 

Challenges and lessons learned in the 

development and implementation of a 

couples-focused telephone intervention for 

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September;1(3):461-7. PMID: 22003374. 

Exclude: Publication type.

438. Trief PM, Teresi JA, Izquierdo R, et al. 

Psychosocial outcomes of telemedicine case 

management for elderly patients with 

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Diabetes Care. 2007 May;30(5):1266-8. 

PMID: 17325261. Exclude: Intervention.

439. Tu KS, Mcdaniel G, Gay JT. Diabetes selfcare knowledge, behaviors, and metabolic 

control of older adults-the effect of a 

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Diabetes Educ. 1993 Jan-Feb;19(1):25-30. 

PMID: 8458295. Exclude: Intervention.

440. Tudor-Locke C, Bell RC, Myers AM, et al. 

Controlled outcome evaluation of the first 
D-30

step program: a daily physical activity 

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2004 Jan;28(1):113-9. PMID: 14569279. 

Exclude: Intervention.

441. Tudor-Locke C, Lauzon N, Myers AM, et 

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PMID: 19842459. Exclude: Design.

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2. PMID: 23410564. Exclude: Outcomes.

443. Unick JL, Beavers D, Jakicic JM, et al. 

Effectiveness of lifestyle interventions for 

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PMID: 21836103. Exclude: Outcomes.

444. Uusitupa MI. Early lifestyle intervention in 

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8949977. Exclude: Population.

445. Vadstrup ES, Frolich A, Perrild H, et al. 

Lifestyle intervention by group-based 

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PMID: 70263067. Exclude: Publication 

type.

446. Van Der Ven NCW, Hogenelst MHE, 

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PMID: 16241932. Exclude: Intervention.

447. Van Dyck D, De Greef K, Deforche B, et al. 

Mediators of physical activity change in a 

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21958233. Exclude: Intervention.

448. Van Son J, Nyklicek I, Pop VJ, et al. 

Mindfulness-based cognitive therapy for 

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PMID: 24913347. Exclude: Intervention.

449. Van Veldhuizen-Scott MK, Widmer LB, 

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Exclude: Intervention.

450. Vanninen E, Laitinen J, Uusitupa M. 

Physical activity and fibrinogen 

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Diabetes Care. 1994 Sep;17(9):1031-8. 

PMID: 7988302. Exclude: Design.

451. Vanninen E, Uusitupa M, Lansimies E, et al. 

Effect of metabolic control on autonomic 

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1993 Jan-Feb;10(1):66-73. PMID: 8435991. 

Exclude: Design.

452. Varroud-Vial M, Simon D, Attali J, et al. 

Improving glycaemic control of patients 

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15154945. Exclude: Intervention.

453. Venmans LMaJ, Gorter KJ, Hak E, et al. 

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Exclude: Intervention.

454. Verrotti A, Chiarelli F, Sabatino G, et al. 

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455. Viklund GE, Rudberg S, Wikblad KF. 

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456. Vincent D. Culturally tailored education to 

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D-31

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2015. Exclude: Intervention.

458. W Hutchison R. Treating diabetes in 

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460. Wadham C, Hassler Hurst J, Almond J, et al. 

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463. Walford GA, Ma Y, Christophi CA, et al. 

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Exclude: Population.

464. Walker EA, Stevens KA, Persaud S. 

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465. Wallace A, Perkhounkova Y, Tseng H, et al. 

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Exclude: Design.

466. Wang ML, Gellar L, Nathanson BH, et al. 

Decrease in glycemic index associated with 

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Dec 26. PMID: 25547339. Exclude: 

Outcomes.

467. Wang Y, Stewart SM, Mackenzie M, et al. 

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Exclude: Intervention.

468. Webb PM. The impact of parental 

involvement in goal setting on treatment

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University; 1999. Exclude: Intervention.

469. Weinberger M, Kirkman MS, Samsa GP, et 

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Intervention.

470. Weinstock RS, Brooks G, Palmas W, et al. 

Lessened decline in physical activity and 

impairment of older adults with diabetes 

with telemedicine and pedometer use: 

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2011 Jan;40(1):98-105. PMID: 21081539. 

Exclude: Intervention.

471. Weinstock RS, Teresi JA, Goland R, et al. 

Glycemic control and health disparities in 

older ethnically diverse underserved adults 

with diabetes: five-year results from the 

informatics for diabetes education and 
D-32

telemedicine (ideatel) study. Diabetes Care. 

2011 Feb;34(2):274-9. PMID: 21270184. 

Exclude: Intervention.

472. Welch G, Allen NA, Zagarins SE, et al. 

Comprehensive diabetes management

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PMID: 21918206. Exclude: Intervention.

473. West SP, Lagua C, Trief PM, et al. Goal 

setting using telemedicine in rural 

underserved older adults with diabetes: 

experiences from the informatics for 

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Telemed J E Health. 2010 May;16(4):405-

16. PMID: 20507198. Exclude: Design.

474. Westman EC. In overweight or obese 

patients with diabetes, a lifestyle 

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Ann Intern Med. 2014; (12).

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central/articles/621/CN00995621/frame.html. Accessed March 20, 

2015. Exclude: Publication Type.

475. Westrupp E, Northam E, Lee K, et al. 

Reducing and preventing internalizing and 

externalizing behavior problems in children 

with type 1 diabetes: a randomized 

controlled trial of the triple p-positive 

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Aug 29. PMID: 25168676. Exclude: 

Intervention.

476. Wheeler ML. Translation of successful 

diabetes-related lifestyle interventions from 

research to practice. Curr Diab Rep. 2005 

Oct;5(5):363-5. PMID: 16188171. Exclude: 

Publication type.

477. Whittemore R, Grey M, Lindemann E, et al. 

Development of an internet coping skills 

training program for teenagers with type 1 

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Exclude: Intervention.

478. Whittemore R, Melkus GD, Sullivan A, et 

al. A nurse-coaching intervention for women 

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Sep-Oct;30(5):795-804. PMID: 15510531. 

Exclude: Intervention.

479. Wildermuth SA. Cognitive behavioral group 

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Dissertation Abstracts International: Section 

B: The Sciences and Engineering. 

2008;69(5-B). PMID: Not available. 

Exclude: Design.

480. Williams GC, Mcgregor H, Zeldman A, et 

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diabetes self-management: evaluating a 

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15590220. Exclude: Intervention.

481. Williams IC, Utz SW, Hinton I, et al. 

Enhancing diabetes self-care among rural 

African Americans with diabetes: results of 

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PMID: 24478047. Exclude: Design.

482. Williamson DA, Rejeski J, Lang W, et al. 

Impact of a weight management program on 

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Med. 2009 Jan 26;169(2):163-71. PMID: 

19171813. Exclude: Outcomes.

483. Wing RR, Anglin K. Effectiveness of a 

behavioral weight control program for 

blacks and whites with NIDDM. Diabetes 

Care. 1996 May;19(5):409-13. PMID: 

8732700. Exclude: Intervention.

484. Wing RR, Blair E, Marcus M, et al. Yearlong weight loss treatment for obese patients 

with type ii diabetes: does including an 

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outcome? Am J Med. 1994 Oct;97(4):354-

62. PMID: 7942937. Exclude: Intervention.

485. Wing RR, Leahey T, Jeffery R, et al. Do 

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behavioral treatment groups? Obesity (Silver 

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23804576. Exclude: Design.

486. Wing RR, Shiffman S, Drapkin RG, et al. 

Moderate versus restrictive diets: 

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1995;26(1):5-24. PMID: Not available. 

Exclude: Outcomes.

487. Wisse W, Rookhuizen MB, De Kruif MD, et 

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sufficient to change sedentary behavior and 

improve glycemic control in type 2 diabetes 
D-33

patients. Diabetes Res Clin Pract. 2010 

May;88(2):e10-3. PMID: 20138384. 

Exclude: Intervention.

488. Woe SK, Sakano Y. Cognitive-behavioral 

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Japanese Journal of Psychosomatic 

Medicine. 1996; (1). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/253/CN00174253/frame.html. Accessed March 20, 

2015. Exclude: Language.

489. Wolf MS, Seligman H, Davis TC, et al. 

Clinic-based versus outsourced 

implementation of a diabetes health literacy 

intervention. J Gen Intern Med. 2014 

Jan;29(1):59-67. PMID: 24002623. Exclude: 

Intervention.

490. Wolf MS, Seligman H, Davis TC, et al. 

Clinic-based versus outsourced 

implementation of a diabetes health literacy 

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2014;29(1):59-67. PMID: 24002623. 

Exclude: Intervention.

491. Wylie-Rosett J. Weight-loss intervention by 

telephone: lessons learned. Diabetes Care. 

2014; (8). 

http://onlinelibrary.wiley.com/o/cochrane/cl

central/articles/973/CN00998973/frame.html. Accessed March 20, 

2015. Exclude: Publication Type.

492. Wysocki T, Greco P, Harris MA, et al. 

Behavior therapy for families of adolescents 

with diabetes: maintenance of treatment 

effects. Diabetes Care. 2001 Mar;24(3):441-

6. PMID: 11289465. Exclude: Intervention.

493. Wysocki T, Harris MA, Buckloh LM, et al. 

Randomized, controlled trial of behavioral 

family systems therapy for diabetes: 

maintenance and generalization of effects on 

parent-adolescent communication. Behav. 

2008 Mar;39(1):33-46. PMID: 18328868. 

Exclude: Outcomes.

494. Wysocki T, Harris MA, Greco P, et al. 

Randomized, controlled trial of behavior 

therapy for families of adolescents with 

insulin-dependent diabetes mellitus. J 

Pediatr Psychol. 2000 Jan-Feb;25(1):23-33. 

PMID: 10826241. Exclude: Intervention.

495. Wysocki T, Harris MA, Wilkinson K, et al. 

Self-management competence as a predictor 

of outcomes of intensive therapy or usual 

care in youth with type 1 diabetes. Diabetes 

Care. 2003 Jul;26(7):2043-7. PMID: 

12832310. Exclude: Intervention.

496. Yamada Y, Uchida J, Izumi H, et al. A noncalorie-restricted low-carbohydrate diet is 

effective as an alternative therapy for 

patients with type 2 diabetes. Intern Med. 

2014;53(1):13-9. PMID: 24390522. 

Exclude: Intervention.

497. Yamauchi K, Katayama T, Yamauchi T, et 

al. Efficacy of a 3-month lifestyle 

intervention program using a japanese-style 

healthy plate on body weight in overweight 

and obese diabetic Japanese subjects: a

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2014;13:108. PMID: 25418542. Exclude: 

Intervention.

498. Yannakoulia M, Poulia KA, Mylona E, et al. 

Effectiveness of an intensive nutritional 

intervention in patients with type 2 diabetes 

mellitus: results from a pilot study. Rev

Diabet Stud. 2007 Winter;4(4):226-30. 

PMID: 18338075. Exclude: Population.

499. Yoo HJ, Park MS, Kim TN, et al. A 

ubiquitous chronic disease care system using 

cellular phones and the internet. Diabet 

Med. 2009 Jun;26(6):628-35. PMID: 

19538239. Exclude: Intervention.

500. Yopp JM. The impact of family functioning 

on treatment adherence and metabolic 

control for adolescents with poorly 

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Abstracts International: Section B: The 

Sciences and Engineering. 2005;66(3-B). 

PMID: Not available. Exclude: Publication 

type.

501. Young H, Miyamoto S, Ward D, et al. 

Sustained effects of a nurse coaching 

intervention via telehealth to improve health 

behavior change in diabetes. Telemed J E 

Health. 2014 Sep;20(9):828-34. PMID: 

25061688. Exclude: Intervention.

502. Young RJ, Taylor J, Friede T, et al. Proactive call center treatment support 

(PACCTS) to improve glucose control in 

type 2 diabetes: a randomized controlled 
D-34

trial. Diabetes Care. 2005 Feb;28(2):278-82. 

PMID: 15677779. Exclude: Intervention.

503. Zapotoczky H, Semlitsch B, Herzog G, et al. 

A controlled study of weight reduction in 

type 2 diabetics treated by two reinforcers. 

Int J Behav Med. 2001/03/01;8(1):42-9. 

PMID: Not available. Exclude: Intervention.

504. Zolfaghari M, Mousavifar SA, Pedram S, et 

al. The impact of nurse short message 

services and telephone follow-ups on 

diabetic adherence: which one is more 

effective? J Clin Nurs. 2012 Jul;21(13-

14):1922-31. PMID: 22239205. Exclude: 

Setting/Country.
E-1

Appendix E. Risk of Bias 

Table E1. Risk of bias for studies on type 1 diabetes mellitus 

Table E2. Risk of bias for studies on type 2 diabetes mellitus
E-2

Table E1. Risk of bias for studies on type 1 diabetes mellitus

Author, Year SG AC Blinding of PP 

Subjective Objective

Blinding of OA 

Subjective Objective

IOD 

Subjective Objective

SOR Other Overall 

Subjective Objective

Amsberg, 2009 M M H M H L H H L L H H

Anderson, 1999 M M NA* M NA L NA L L L NA M

Boardway, 1993 M M H M H L H H L L H H

Christie, 2014 L L H M H L H M L L H M

Cook, 2002 M M H M H L H H L L H H

Ellis, 2007 M M NA M NA L NA M L L NA M

Ellis, 2012 L M M M M L M M M L M M

Franklin, 2006 L M H M H L M M L L H M

Freeman, 2013 M M M M M L H H L L H H

Hermanns, 2013 L L H M H L L L L L H M

Holmes, 2014 M M NA M NA L NA N L L NA H

Husted, 2014 L L H M H L H H L H H H

Ismail, 2008 L H H M H L H M M H H H

Karlsen, 2004 M M H M H L H H L L H H

Katz, 2014 M M H M H L L L L L H M

Kichler, 2013 M M H M H L H M L L H M

Laffel, 2003 M M H M H L L L L L H M

Lehmkuhl, 2010 L M NA M NA L NA H L L NA H

Mannucci, 2005 H H H M H L H H L H H H

Mayer-Davis, 2014 L M H M H L L L L L H M

McNabb, 1994 M M NA M NA L NA H L L NA H

Murphy, 2007 M M NA M NA L NA M M L NA M

Murphy, 2012 L L NA M NA L NA L M L NA M

Nansel, 2007 L M H M H L L L L L H M

Nansel, 2012 L M H M H L L L L L H M

Perry, 1997 M M H M H L H H L L H H

Serlachius, 2014 L M H M H L H L L M H M

Viklund, 2007 M M NA M NA L NA L L L NA M
E-3

Weinger, 2011 L M NA M NA L NA L L L NA M

Wysocki, 2007 M M H M H L M M L L H M

Zoffmann, 2006 H L H M H L H H L L H H

*These trials may have reported on subjective (i.e., patient reported) outcomes but they were either not of interest to the review or not included in the analysis because of lacking 

data.

AC = allocation concealment; Blinding of OA = blinding of outcome assessors; Blinding of PP = blinding of participants and personnel; H = high risk of bias; IOD = incomplete 

outcome data; L = low risk of bias; M = medium or unclear risk of bias; NA = not applicable; Other = other sources of bias; Overall = overall risk of bias assessment; SG = 

sequence generation; SOR = selective outcome reporting
E-4

Table E2. Risk of bias for studies on type 2 diabetes mellitus

Author, Year SG AC Blinding of PP 

Subjective Objective

Blinding of OA 

Subjective Objective

IOD 

Subjective Objective

SOR Other Overall 

Subjective Objective

Adachi, 2013 M M H M H L M M L L H M

Adolfsson, 2007 M L NA* M NA L NA H L H NA H

Agur-Collins, 

1997

M M H M H L H H L L H H

Amoako, 2008 H H H M H L M M L L H H

Anderson, 1995 M M H M H L H H L L H H

Anderson, 2005 M M H M H L L L L L H M

Anderson, 2009 L L H M H L H H L L H H

Anderson, 2010 M M NA M NA L NA H L H NA H

Anderson-Loftin, 

2005

L M H M H L H H L L H H

Baksi, 2008 L M NA M NA L NA H L L NA H

Barratt, 2008 L M NA M NA L NA L L L NA M

Beverly, 2013 L M M M M L H H L M H H

Bond, 2007 M M H M H L L L L L H M

Bozzetto, 2014 L M M M M L H H L L H H

Bradshaw, 2007 M M M M M L H H M L H H

Brown, 2002 M M NA M NA L NA H L L NA H

Brown, 2005 M M M M M L L L L L M M

Brown, 2011 M M NA M NA L NA L L L NA M

Castejon, 2013 M M NA M NA L NA H L L NA H

Chan, 2012 L M H M H L H H L L H H

Chan, 2014 L L M M M L L L L L M M

Cheong, 2009 M M M M M L H H L L H H

Chlebowy, 2014 M M H M H L H H L L H H

Clark, 2004 L M H M H L L L L L H M

Cooper, 2008 M M NA M NA L NA H H M NA H

Corkery, 1997 M M NA M NA L NA H L L NA H
E

-5

Cramer, 2007MMHMHLHHLMHH

Dasgupta, 2006MM NAM NAL NAHLL NAH

Davis, 2010MM NAM NAL NAMLL NAM

Deakin, 2006MMHMHLLLLLHM

D-Eramo Melkus, 

2010

LMMMMLMMLLMM

Dunstan, 1997MMHMHLHHLLHH

Dunstan, 2005MMMMMLHHLLHH

Eakin, 2014LMHMHLMMLLHM

Edelman, 2015MM NAM NAL NAMLL NAM

Fisher, 2013LMMMHLHHMLHH

Foster, 2009LMHMHLLLLLHM

Foster, 2013LM NAM NAL NALLL NAM

Frosch, 2011MMHMHLHHLLHH

Gagliardino, 

2013a

MMMMMLLLLLMM

Gagliardino, 

2013b

MM NAM NAL NAHLL NAH

Giannopoulou, 

2005

MM NAM NAL NAHLL NAH

Glasgow, 2006aMMHMHLMMLLHM

Glasgow, 2006bLMHMHLHHLLHH

Glasgow, 2012LMHMHLMMLLHM

Goudswaard, 

2004

LM NAM NAL NAHLL NAH

Hawkins, 2010LL NAM NAL NAHLL NAH

Hendricks, 2000MMMMMLHHLLHH

Hermanns, 2012LMMMMLHHLLHH

Hill-Briggs, 2011MM NAM NAL NALLL NAM

Holmen, 2014LMHMHLMMLMHM

Holtrop, 2002MM NAM NAL NAHLL NAH

Huisman, 2009MMHMHLHHLLHH

Izquierdo, 2003MMMMMLHHLHHH
E

-6

Johnson, 2009LMMMMLMMLLMM

Jones, 2003MM NAM NAL NAMLL NAM

Keyserling, 2002LMMMHLHHLHHH

Kim, 2006MM NAM NAL NALLL NAM

Kim, 2009LMHMHLLLLLHM

Kim, 2014MMHMHLHHLLHH

Koo, 2010MM NAM NAL NAMLL NAM

Kulzer, 2007MMHMHLMMLLHM

Lee, 2011MM NAM NAL NAHLL NAH

Lorig, 2008MMHMHLHHLLHH

Lorig, 2009LMHMHLMMLLHM

Lorig, 2010LMHMHLMMLLHM

Lujan, 2007MM NAM NAL NALLL NAM

Lynch, 2014MMMMMLHHLHHH

Mandel, 2013LLMMMLHHLLHH

Mayer-Davis, 

2004

MM NAM NAL NAMLL NAM

McGowan, 2011HLMMMLHHLLHH

Miller, 2014LMMMMLHHLLHH

Moncrieft, 2014MMHMHLMMLMHM

Moriyama, 2009HHHMHLHHLLHH

Muchmore, 1994MM NAM NAL NAHLL NAH

Murrock, 2009LM NAM NAL NAHLL NAH

Nashita, 2013MMHMHLHHLLHH

Palmas, 2014LL NAM NAL NAMLL NAM

Philis-Tsimikas, 

2011

LH NAM NAL NAHLL NAH

Plotnikoff, 2011LMMMMLMMLLMM

Prezio, 2013LM NAM NAL NAMLL NAM

Reaney, 2013LMHMHLLMLLHM

Rickheim, 2002HHHMHLHHLHHH
E

-7

Ridgeway, 1999MMHMHLHHMLHH

Rock, 2014LMHMHLMMLLHM

Rosal, 2005MMHMHLLLLLHM

Rosal, 2011MMHMHLMMLMHM

Rosal, 2014LMMMMLLLLHHH

Rothschild, 2014LMLLLLMMLHHH

Ruggiero, 2010MMHMHLHHLLHH

Ruggiero, 2014LMHMHLHHLLHH

Sacco, 2009HMHMHLHHLLHH

Salinero-Fort, 

2011

MM NAM NAL NALLL NAM

Samuel-Hodge, 

2009

LMHMHLHMMLHM

Sarkadi, 2004LLHMHLMMLLHM

Sevick, 2012LM NAM NAL NAHLL NAH

Shibayama, 2007MMHMHLMMLLHM

Sigurdardottir, 

2009

LLHMHLLLLLHM

Siminerio, 2013MMMMMLMMLLMM

Sinclair, 2013LMHMHLHHLLHH

Sixta, 2008LM NAM NAL NAHLL NAH

Skelly, 2005LMHMHLHHLLHH

Skelly, 2009MLMMMLLLLLMM

Smith, 1997MM NAM NAL NAHLL NAH

Sorkin, 2014MMHMHLLLLMHM

Spencer, 2011MMHMHLHHLLHH

Sperl-Hillen, 2013LMHMHLMLHLHH

Steed, 2005HHHMHLMMLLHH

Sung, 2012LMHMHLMMLLHM

Tang, 2014ML NAL NAL NAHML NAH

Thoolen, 2007LMHMHLHHLLHH

Toobert, 2003MMHMHLHHLLHH
E-8

Toobert, 2011 M M H M H L H H L L H H

Trief, 2011 M M NA M NA L NA H L L NA H

Tucker, 2014 M M H M H L H H L M H H

Utz, 2008 L M M M M L M M L L M M

Vadstrup, 2011 L M M M M L M M L L M M

Varney, 2014 L M H M H L H H L M H H

Vazquez, 1998 M M H M H L M M L L H M

Vincent, 2007 L M H M H L H H L L H H

Walker, 2011 L M M M M L M M L L M M

Weinger, 2011 L M M M M L M M L M M M

Welch, 2011 M M NA M NA L NA H L L NA H

Welschen, 2013 L L H M H L L L L H H H

West, 2007 M M NA M NA L NA L L L NA M

Wierenga, 1994 M M H M H L H H M L H H

Wing, 2013 M M H M H L L L L L H M

Wolever, 2010 M M H M H L H H L L H H

Wolf, 2004 L L H M H L M M L L H M

Yoo, 2007 L M NA M NA L NA H L L NA H

Yuan, 2014 M M NA M NA L NA H L M NA H

Zgibor, 2013 M M M M M L H H L L H H

*These trials may have reported on subjective (i.e., patient reported) outcomes but they were either not of interest to the review or not included in the analysis because of lacking 

data.

AC = allocation concealment; Blinding of OA = blinding of outcome assessors; Blinding of PP = blinding of participants and personnel; H = high risk of bias; IOD = incomplete 

outcome data; L = low risk of bias; M = medium or unclear risk of bias; NA = not applicable; Other = other sources of bias; Overall = overall risk of bias assessment; SG = 

sequence generation; SOR = selective outcome reporting
F-1

Appendix F. Description of Studies and Interventions

Table F1. Description of studies and interventions for T1DM in youth

Table F2. Description of studies and interventions for T1DM in adults

Table F3. Description of studies and interventions for T2DM 
F-2

Table F1. Description of studies and interventions for T1DM in youth Author, Year & Country Comparison & Sample Size Age, Males, Ethnic Minorities, HbA1c Intervention Category & Description Total Duration, # 

Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

Anderson, 

1999

U.S. (MA)

I= 30

UC= 28

AC= 31

I= 12.7±1.4y, 

50%, NR, 

8.3±1.1%

UC = 12.5±1.4y, 

52%, NR, 

8.6±0.9%

AC= 12.7±1.4y, 

50%, NR, 

8.7±1.2%

DSME; officebased Parent 

Adolescent 

Teamwork

intervention

12m, 4, 1.5-

2h

In-person Individual with 

family

Non-HCP

(research 

assistant)

Minimal –

Content & 

Delivery

None/NR

Boardway, 

1993

U.S. (MI)

I= 13

UC= 18

I= 15.4±1.2y, 

22%, 30%, 

13.9±2.4%

UC= 14.3±1.7y, 

60%, 33%, 

15.7±3.6%

DSME; stress 

management &

regime adherence 

training with active 

SMBG

6m, 13, NR In-person Group HCP (RN) Moderate-toHigh -

Content

None/NR

Christie, 

2014

United 

Kingdom

I= 182

UC= 183

I= 13.1±2.1y, 

42.8%, 13.2%, 

9.9±1.5%

UC= 13.2±2.1y, 

46.4%, 20.2%, 

10.0±1.5%

DSME; CASCADE 

intervention with MI 

& solution-focused 

brief therapy

4m, 4, 8h In-person Group with 

families

Multidisciplinary 

(DSN with any 

HCP)

Moderate-toHigh - 

Content 

Yes

Cook, 

2002

U.S. (IL, 

NY)

I= 26

UC= 27

I= 14.8±1.2y, 

50%, 12%, 

8.8±1.3%

UC= 14.4±1.4y, 

37%, 19%, 

9.2±2.0%

DSME; Choices 

Diabetes Program 

focus on problem 

solving

1.5m, 6, 12h In-person Group HCP (not 

specified)

Moderate-toHigh -

Content

None/NR

Ellis, 2007

U.S. (MI)

I= 64

UC= 63

I= 13.4±1.9y, 

59%, 80%, 

DSME; 

Multisystemic 

5.7m, 48±19, 

48h

In-person Individual with 

family

HCP 

(therapists)

Moderate-toHigh -Yes
F-3

Author, Year & 

Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cIntervention Category & DescriptionTotal Duration, # Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

11.4±2.2%

UC= 13.1±2.0y, 

38%, 68%, 

11.3±2.2%

Therapy (familycentered, home 

and communitybased 

psychotherapy)

Content & 

Delivery

Ellis, 2012

U.S. (MI)

I= 74

AC= 72

I= 14.2±2.2y, 

43%, 82%, 

11.6±2.5%

AC= 14.1±2.4y, 

44%, 78%, 

11.8±2.6%

I= DSME; 

Multisystemic 

Therapy (familycentered, home 

and communitybased 

psychotherapy)

AC= Telephone 

support

I= 5.6m, 

45.7±18.6, 

46h

AC= 4.9m, 

14.0±6.3, 7h

I= In-person

AC= 

Technology 

(telephone)

1= Individual 

with family

AC= 

Individual

HCP (Psych or

Social workers)

I= Moderateto-High -

Content & 

Delivery

AC= 

Moderate-toHigh -

Content & 

Delivery

I= Yes

AC= None

Franklin, 

2006

Scotland

I= 33

UC= 28

Not 

reporting 

on 

Intensive 

insulin 

therapy 

(IIT) plus 

Sweet 

Talk arm

I= 14.1 (11.7-

15.6)y, 45.5%, 

3%, 9.8 (8.6-

11.5) (Median 

IQR)

UC= 12.7 (10.5-

14.8)y, 63%, 

3.7%, 10.1 (9.2-

11.2) (Median, 

IQR)

DSME; Sweet Talk 

(automated weekly 

delivery of tailored 

text messages to 

reinforce/support 

goals made in 

clinics)

12m, 3-4, NR 

(during clinic 

visits)

Mixed Individual Multidisciplinary 

(RA & care 

team)

Minimal –

Content & 

Delivery

None/NR

Freeman, 

2013

U.S. (OR)

I1= 44

I2= 46

I1= 15.0±1.8y, 

47.3%, NR, 

11.2±1.7%

I2= 14.9±1.8y, 

52.7%, NR, 

11.0±1.7%

I1= DSME; BFST-D 

(Behavioral Family 

Systems Therapy 

for Diabetes)

delivered in-person

I2= DSME; BFST-D 

delivered via 

videoconferencing

I1= 3m, 7.56, 

8-12h 

I2= 3m, 7.03, 

7-10.5h

I1= In-person

I2= 

Technology

I1= Individual 

with family

I2= Individual 

with family

I1= HCP (Psych)

I2= HCP (Psych)

I1=Moderate 

to High –

Content & 

Delivery

I2= Moderate 

to High –

Content & 

Delivery

I1= Yes

I2= Yes
F-4

Author, Year & 

Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cIntervention Category & DescriptionTotal Duration, # Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

Holmes, 

2014

U.S.

I= 137

AC= 89

I= 13.0±1.2y, 

44.5%, 32.1%, 

8.8%

AC= 12.7±1.2y, 

53.9%, 24.7%, 

8.9%

I= DSME; clinicintegrated lowintensity coping 

skills training, 

conflict resolution & 

communication

AC= Non-DSME 

education

I= 12m, 4 + 

telephone 

contacts, 3h + 

telephone 

contact time

AC= 12m; 4, 

1h

I= Mixed 

AC= Inperson

I= Individual 

with parent

AC= 

Individual with 

parent

I= Non-HCP 

(graduate-level 

interventionists)

AC= Non-HCP 

(bachelor-level 

facilitators)

I= Moderateto-High –

Content & 

Delivery

AC= None

I= 

None/NR

AC= 

None/NR

Husted, 

2014

Denmark

I= 37

UC= 34

I= 14.9±1.5y, 

38%, NR, 

9.5±3.7%

UC= 14.6±1.3y, 

40%, NR, 

8.8±3.0%

DSME; Guided 

Self-DeterminationYouth (clinic-based 

intervention 

focused on life 

skills to facilitate 

empowerment)

20m, 12 (8-

16), 8-12h

In-person Individual with 

family

Multidisciplinary 

(RN or 

Physician and 

RD)

Moderate-toHigh –

Content & 

Delivery

None/NR

Katz, 2014

U.S. (MA)

I= 50

UC= 51

NR on 

active 

control 

I= 12.7±2.2y, 

42%, 10%, 

8.4±1.4%

UC= 12.5±2.3y, 

55%, 2%, 

8.4±1.3%

DSME; clinicintegrated familybased 

psychoeducation &

Care Ambassador

25m, 9.4±1.5

+ 25 Care 

Ambassador 

contacts, 

4.75h + Care 

Ambassador

contacts 

(4+h)

Mixed Individual with 

family

Non-HCP 

(research 

assistant)

Moderate-toHigh –

Content & 

Delivery

None/NR

Kichler, 

2013

U.S. (MI)

I= 16

UC= 15

NR by arm; 

15.2±1.3y, 47%, 

23%, 10±2.1%

DSME; Diabetes 

Adjustment and 

Coping Group 

Therapy Program -

K.I.D.S. Project 

intervention with 

behavioral and 

family system 

strategies

1.5m, 6, 6h In-person Group with 

families

Non-HCP 

(trainee) & HCP 

(Pysch)

Moderate-toHigh –

Content & 

Delivery

None/NR

Laffel, 

2003

U.S. (MA)

I= 50

UC= 50

I= 11.9±2.4y, 

47%, NR, 

8.4±1.7% (all 

DSME; clinic 

integrated CBTbased family12m, 4, NR In-person Individual with family

Non-HCP 

(research 

assistant) 

Minimal –

Content & 

Delivery 

None/NR
F-5

Author, Year & 

Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cIntervention Category & DescriptionTotal Duration, # Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

participants)

UC= 12.2±2.2y, 

NR

focused teamwork 

intervention 

Lehmkuhl, 

2010

U.S. (FL)

I= 18

UC= 14

I= 13.7±2.7y, 

39%, NR, 

10.8±2.1%

UC= 13.4±2.2y, 

14%, NR, 

10.4±1.9%

DSME; Telehealth 

Behavioral Therapy 

(utilized some of 

the principles of 

BFST intervention)

2.8m, 36, 11h Technology Individual with 

family

Non-HCP 

(therapist 

interns)

Moderate-toHigh –

Content & 

Delivery

None/NR

MayerDavis, 

2014 

U.S. (CO, 

OH, NC)

I = 31

UC = 30

All 13.9±1.4y, 

NR, NR

HbA1c

I= 9.8±1.6%

UC= 9.5±1.3% 

DSME; Flexible 

Lifestyles for Youth 

(FL3X) combining 

MI, problemsolving, and family 

systems therapy

3m, 5, 2.5h

Plus short 

additional 

contacts

Mixed 

(In-person 

sessions 

with 

automated 

telephone 

reminders/ 

motivational 

boosters)

Individual with 

a family 

member

HCP (diabetes 

clinicians/educa

tors)

Moderate-toHigh –

Content & 

Delivery

None/NR

McNabb, 

1994

U.S. (IL)

I= 12

UC= 12

I= 9.7y, NR, 

NR, 10.5±2.9%

UC= 10y, NR, 

NR, 12.9±3.8%

DSME; In Control 

program for 

children to gain 

self-care 

independence

1.5m, 6, 6h In-person Group with 

families

HCP (NR) Minimal-toHigh –

Content

None/NR

Murphy, 

2007

United 

Kingdom

I= 37

UC= 41

I= 12.6±2.3y, 

55%, NR, 

9.1±1.0%

UC= 13.1±2.0y, 

56%, NR, 

9.1±1.5%

DSME; clinicintegrated group 

family sessions 

focused on family 

teamwork 

(Families, 

Adolescents and 

Children’s 

Teamwork Study 

(FACTS))

12m, 4, 4h In-person Group with 

families

Multidisciplinary 

(DSN, RD, 

Physician)

Minimal -

Delivery

None/NR
F-6

Author, Year & 

Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cIntervention Category & DescriptionTotal Duration, # Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

Murphy, 

2012

United 

Kingdom

I= 158

UC= 147

I= 13.1±1.9y, 

47%, 7%, 

9.2±1.7%

UC= 13.2±2.0y, 

49%, 9%, 

9.4±2.1%

DSME; clinicintegrated group 

family sessions 

focused on family 

teamwork (FACTS)

6m, 6, 9h In-person Group with 

families

Multidisciplinary 

(DSN, RD, 

Physician)

Minimal -

Delivery

None/NR

Nansel, 

2007

U.S. (MD)

I= 40

UC= 41

I= 13.6±1.9, 

42.5%, 17.5%, 

46.3±34.1 (% 

above upper 

limit)

UC= 13.9±1.6, 

46.3%, 12.2%, 

42.2±28.6 (% 

above upper 

limit)

DSME; Selfregulation and MI 

intervention using 

Diabetes Personal 

Trainers for selfmonitoring, goalsetting and problem 

solving sessions

2m, 6 + 

telephone 

calls, NR

Mixed Individual Non-HCP 

(health field 

students) 

Moderate-toHigh –

Content & 

Delivery

None/NR

Nansel, 

2012

U.S. (MA, 

IL, FL, TX)

I= 201

UC= 189

I= 12.5±1.8y, 

49.3%, 24%, 

8.4±1.2%

UC= 12.4±1.7y, 

49,2%, 26%, 

8.3±1.1%

DSME; WE*CAN 

Manage Diabetes

program focusing 

on problem solving 

approach

21m, 6 + 12 

telephone 

calls, 3h + 

telephone 

contact time

Mixed Individual with 

family

Non-HCP 

(trained health 

advisors)

Moderate-toHigh –

Content & 

Delivery

None/NR

Serlachius 

2014

Australia

I = 73

UC = 74

I= 14.4±1.1y, 

42.5%, NR, 

8.5±1.5%

UC= 14.3±1.1y, 

50%, NR, 

8.6±1.4%

DSME; DM-specific 

CBT-based Best 

Coping programme 

with coping skills 

and problemsolving training, 

and cognitive 

restructuring

1.2m, 5, 10h

Plus CD-ROM 

for 

maintenance

In-person Group HCP (health 

psychologist)

Minimal -

Content

None/NR

ThomasDobersen, 

1993

I= 11

UC= 9

I= 13.9y (12-17, 

range), 9.1%, 

NR, 12.2 (9-

Lifestyle; 

SHAPEDOWN 

(family-based 

3m, 14, 21h 

(Each contact 

In-person Group 

(sessions for 

adolescents 

Multidisciplinary 

(RD, Psych & 

child health 

Minimal -

Content 

None/NR
F-7

Author, Year & 

Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cIntervention Category & DescriptionTotal Duration, # Contacts, 

Contact 

TimeMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (NonHCP, Single HCP, Multidisciplinary)Degree of Tailoring CommunityEngagement

U.S. (CO)

Observ.

15.8)%

UC= 15.2y (12-

18, range), 0%, 

NR, 13.1 (9.9-

16.9)%

multidisciplinary 

behavior

modification 

program)

had separate 

sessions for 

adolescents 

and parents) 

and parent 

separate)

associate)

Viklund, 

2007

Sweden

I= 28

UC= 27

I= 14.3±1.6y, 

43%, NR,

7.4±1.2%

UC= 14.1±0.8y, 

39%, NR, 

8.1±1.8%

DSME; 

empowerment 

program with 

problem-based 

learning

1.5m, 6, 12h In-person Group HCP (DSN) Moderate-toHigh –

Content

None/NR

Viner, 

2003

United 

Kingdom

Observ.

I= 21

UC= 20

I= 13.0, 28%, 

NR, 10.2 (SE 

0.3)

UC= 13.3, 60%, 

NR, 10.0 (SE 

0.3)

DSME; 

motivational/solutio

ns-focused group 

intervention

1.5m, 6 + 1 

for parents, 

NR

In-person Group 

(sessions for 

adolescents 

and parents 

separate)

NR Moderate-toHigh –

Content & 

Delivery

None/NR

Wysocki,

2007

U.S. (MO, 

FL)

I= 36

AC= 36

UC= 32

I= 13.9±.9y, 

58%, 39%, 

9.6±1.6%

AC= 14.4±1.9y, 

56%, 25%, 

9.7±1.6%

UC= 14.2±1.9y, 

50%, 47%, 

9.5±1.5%

I= DSME; BFST-D 

AC= Non-DSME 

education 

I= 6m, 12, 

18h

AC= 6m, 12, 

18h

I= In-person

AC= Inperson

I= Individual 

with family

AC= Group 

with families

I= 

Multidisciplinary

AC= 

Multidisciplinary

I= Moderateto-High –

Content & 

Delivery

AC= None

I= 

None/NR

AC= 

None/NR

AC= active control; CBT= cognitive behavioral therapy; DSME= diabetes self-management education; DSN= diabetes specialist nurse; HCP= health care professional; I= 

Intervention; MI= motivational interviewing; NA= not applicable; NR= not reported; Observ.= observational study design; Pysch= psychologist; RA= research assistant; RD= 

registered dietitian; RN= registered nurse; SMBG= self-monitoring blood glucose; UC= usual care 
F-8

Table F2. Description of studies and interventions for T1DM in adults Author, Year & Country Comparison & Sample Size Age, Males, Ethnic Minorities, HbA1c Intervention Category & Description Total Duration, # Contacts, Contact Time 

Method of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (Non-HCP, Single HCP, Multidisciplinary)Degree of Tailoring Community Engagement

Amsberg, 

2009

Sweden

I= 46

UC= 48

I= 41.1±11.7y, 

56%, NR, 

8.5±0.9%

C= 41.4±12.9y, 

42%, NR, 

8.5±0.8%

DSME + Support; 

CBT-based with 

CGMS (“Power to 

Choose Your 

Direction”)

11, 12 + 5 

telephone 

contacts, 

18.25h + 

telephone 

contact time

(Maintenance 

phase = 9m)

Mixed Mixed Multidisciplinary 

(RN, Pysch) 

Moderateto-High –

Content & 

Delivery

None/NR

Forlani, 

2006

Italy 

Observ.

I= 54

UC= 36

I= 43 (18–65)y 

(Median, 

Range), 33%, 

NR, 8.2±1.6%

UC= 41 (26–

65)y (Median, 

Range), 66%, 

NR, 8.1±1.2%

DSME; 

empowerment 

group teaching & 

situation 

simulation 

4m, 8, 16h In-person Group HCP (Physician 

or RD)

Moderateto-High -

Content

None/NR

Hermanns, 

2013

Germany

I= 81

AC= 79

I= 45.9±13.8y, 

61.7%, NR, 

8.3±1.1%

AC= 

45.1±13.4y, 

50.6%, NR, 

8.0±0.9%

I= DSME; 

PRIMAS 

empowerment 

approach

AC= Non-DSME 

education; 

standard in 

Germany

I= 1.5m, 12, 18h

AC= 1.5m, 12, 

18

I= In-person

AC= Inperson

I= Group

AC= Group

I= HCP (CDE)

AC= HCP 

(CDE)

I= 

Moderateto-High –

Content

AC= None

I= 

None/NR

AC= 

None/NR

Ismail, 

2008

United 

Kingdom

I= 106

UC= 121

NR on 

Active 

control 

I= 37.2±9.9y, 

37.7%, 21%, 

9.6±1.3%

UC=36.4±11.3y, 

45,4%, 14%, 

9.7±1.2%

DSME; 

Motivational 

Enhancement 

Therapy & CBT

6m, 12, 10h In-person Individual HCP (DSN) Moderateto-High -

Content

None/NR
F

-9

Author, Year & Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cInterventionCategory & DescriptionTotal Duration, # Contacts, Contact Time Method of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (Non-HCP, Single HCP, Multidisciplinary)Degree of Tailoring Community Engagement

Karlsen, 

2004

Norway

I= 47

UC= 45

I= 49.2±14.7y, 

52%, NR, 

7.9±1.2%

UC= 

48.6±10.3y, 

53%, NR, 

8.4±1.2%

DSME; CBT-

based program

6m, 6, 9h In-person Group Non-HCP 

(peers) & HCP 

(DSN)

Moderate-

to-High –

Content & 

Delivery

Yes

Mannucci, 

2005

Italy

(Non-RCT)

I= 96

UC= 37

I= 30.7±8.4y, 

44%, NR, 

7.7±1.4%

UC= 

30.3±12.2y, 

43%, NR, 

7.9±1.6%

DSME; Interactive 

Educational and 

Support Group 

(IESG), physician-

led long-term 

open group 

education 

program

12m, 26, 52h In-person Group HCP 

(Physicians)

Moderate-

to-High –

Content & 

Delivery

None/NR

Perry, 

1997

New 

Zealand

I= 31

UC= 30

I= 41.5±11.6y, 

66.7%, NR, 

8.9±2.6%

UC= 

42.8±12.6y, 

48.4%, NR, 

8.7±2.0%

Lifestyle; multiple 

topics with 

individualized diet 

and physical 

activity 

prescriptions

6m, 6 + 

additional 

sessions or 

telephone calls, 

NR

In-person Individual Multidisciplinary 

(RD & others in 

research team)

Moderate-

to-High –

Content & 

Delivery

None/NR

Weinger, 

2011

U.S. (MA) 

I=74

AC

1= 75

AC

2= 73

I= 51.8 (23.7-

74.2)y

54%, 12%

9.0 (7.6-12.6)%, 

50%

AC

1= 54.7 

(25.0-75.1)y

52%, 11%

8.8 (7.6-13.6)%, 

50%

I= DSME; CBT-

based group 

education 

program

AC

1= Non

-DSME 

(didactic group 

sessions)

AC

2= Non

-DSME 

(individual RN & 

I= 1.5m, 5, 10h

AC

1= 1.5, 5, 

10h

AC

2= 6m, NR, 

NR

I= In-person

AC

1= In

-

person

AC

2= In

-

person

I= Group

AC

1= Group

AC

2= 

Individual 

I= 

Multidisciplinary 

(RN, RD)

AC

1= RN

AC

2= 

Multidisciplinary 

(RN, RD)

I= 

Moderate-

to-High –

Content

AC

1= 

Minimal –

Content

AC

2= 

Minimal –

I= 

None/NR

AC

1= 

None/NR

AC

2= 

None/NR
F-10

Author, Year & Country

Comparison & Sample SizeAge, Males, Ethnic Minorities, HbA1cInterventionCategory & DescriptionTotal Duration, # Contacts, Contact Time Method of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) Delivery Personnel (Non-HCP, Single HCP, Multidisciplinary)Degree of Tailoring Community Engagement

AC2= 56.2 

(21.6-74.8)y

42%, 15%

8.6 (7.6-13.1)%, 

49%

RD consults 

offered)

Content & 

Delivery

Zoffmann, 

2006

Denmark

I= 36

UC= 25

I= 36.8±1.7y, 

46.5%, NR, 

9.0±0.2%

UC= 35.7±2.1y, 

50%, NR, 

9.1±0.2%

DSME; Guided 

Self-Determination 

Group Training

2m, 8, 16h In-person Group Multidisciplinary 

(RN & 

researcher)

Moderateto-High –

Content & 

Delivery

None/NR

AC= active control; CBT= cognitive behavioral therapy; CDE= certified diabetes educator; CGMG= continuous glucose monitoring system; DSME= diabetes self-management 

education; DSN= diabetes specialist nurse; HCP= health care professional; I= Intervention; NA= not applicable; NR= not reported; Observ.= observational design; Psych= 

psychologist; RD= registered dietitian; RN= registered nurse; SMBG= self-monitoring blood glucose; UC= usual care 
F-11

Table F3. Description of studies and interventions for T2DM 

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Adachi, 2013

Japan

I= 100

UC= 93

I= 60.4±11.4y

45%, NR

26.3±4.6kg/m2

7.6±1.4%, 11%

UC= 62.3±10.1y

42%, NR

24.9±4.6kg/m2

7.3±1.1%, 13%

DSME; SILE 

(Structured 

Individual-based 

Lifestyle 

Education), focus 

on diet but also 

self-management 

through activity 

and stress 

management

6m; 3.5; NR; NA In-person Individual HCP (RD) Moderate-toHigh –

Content

None/NR

Adolfsson, 

2007

Sweden

I= 50

UC= 51

I= 62.4±8.9y

57%, NR

30.4±4.3

7.4±1.0%, 0%

UC= 63.7±9.0y

61%, NR

29.6±3.3kg/m2

7.1±0.8%, 0%

DSME; 

empowerment 

group education

7m; 4.7, 12h; NA In-person Group Multidisciplinary 

(DSN, Physician)

Moderate-toHigh –

Content & 

Delivery

None/NR

Agurs-Collins,

1997

U.S. (DC)

I= 32

UC= 32

I= 62.4±5.9y

34%, 100%

33.9±5.1kg/m2

11.0±1.7%, 

40%

UC= 61.0±5.7y

12%, 100%

34.9±6.8kg/m2

10.0±1.9%, 

50%

Lifestyle; hospitalbased lifestyle 

program (Diabetic 

Exchange Lists) to 

achieve ≤0.9kg wt 

loss/wk & 

moderate physical 

activity ≥3 x/wk 

with weekly group 

exercises for 3m) 

tailored to older 

African Americans

6m; 19, 28h; 3m In-person Mixed with 

supports

HCP (RD)

Minimal from 

exercise 

physiologist

Moderate-toHigh –

Content & 

Delivery

None/NR
F

-12

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Amoako, 2008

U.S. (NC)

I= 34

UC= 34

All= 61±9.5y

0%, 100%

NR, 0%

DSME; psycho-

educational 

uncertainty 

management 

intervention (DU-

UMI) for older 

African American 

women

1m; 4, 1h; NA Technology Individual HCP (NP) Moderate-to-

High –

Content & 

Delivery

Yes

Anderson D, 

2010

U.S. (CT)

I= 146

UC= 149

I= NR

41%, 72.6%

35.4±8.6

7.6±1.8%, NR

UC= NR

43%, 73.8%

33.7±6.6

8.4±2.3%, NR

DSME; telephonic 

disease 

management in a 

community health 

center for 

medically 

underserved,

predominantly 

Hispanic 

population

12m; 18, NR; NA Technology Individual HCP (RN) Moderate-to-

High –

Content & 

Delivery

None/NR

Anderson R, 

1995

U.S. (MI)

I= 23

UC= 23

All= 50y

30%, NR

54% using 

insulin

HbA1c

I=11.75±3.0%

UC= 10.8±2.9%

DSME; 

"Empowerment: 

Facilitating a Path 

to Personal Self-

Care"

1.5m; 6, 12h; NA In-person Group with 

supports

HCP (CDE) Moderate-to-

High –

Content & 

Delivery 

None/NR

Anderson R, 

2005

U.S. (MI)

I= 125

UC= 114

All= 61.0±11.4y

18%, 96%

91.3±20.6kg 

HbA1c

DSME; problem-

based 

empowerment 

program for

African Americans

1.5m; 6, 12h; NA In-person Group with 

supports

Multidisciplinary 

(RD, RN)

Moderate-to-

High –

Content & 

Delivery

Yes
F

-13

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

I= 8.7±2.13%

UC= 8.4±2.2%

Anderson R, 

2009

U.S. (MI)

I= 156

UC= 154

I= 55.5±11.3y

43.6%, 40.9%

34.9±9.0kg/m

2

7.7±2.1%, 

27.7%

UC= 55.7±11.5y

39%, 50%

33.8±7.8kg/m

2

7.5±1.8%, 

26.3%

DSME; Diabetes 

Self-Management 

Consultant 

(DSMC) manager 

intervention based 

on empowerment 

approach

24m; 24; NR; NA Mixed Individual HCP (RD or RN 

both CDE)

Moderate-to-

High –

Content & 

Delivery

None/NR

Anderson-

Loftin, 2005

U.S. (SC)

I= 49

UC= 48

I= 58.9±10.1y

22%, 100%

35.4±8.1kg/m

2

7.5±1.6%, 17%

UC= 55.7±12.1y

25%, 100%

34±8.3kg/m

2

8.3±2.6%, 13%

Lifestyle; Soul Food Light: 

culturally 

competent 

diabetes diet 

education and 

peer-professional 

support groups for 

rural black 

southerners

5m; 8+16 

telephone 

followup calls, 

10h + call 

duration; NA 

Mixed Mixed with 

supports

Multidisciplinary 

(RD, RN)

Moderate-to-

High –

Content & 

Delivery

Yes

Baksi, 2008

England

I

1= 43

I

2= 40

I

1= 59.3±13y

57.6%, NR

28.7±5.5kg/m

2

7.4±1.3%, 

21.4% I2= 60.5±11y

47.1%, NR

32.5±5.3kg/m

2

I

1= DSME; 

delivered by 

health 

professionals I2= DSME; 

delivered by peers

I

1= 6m; 6, 9h; NA

I

2= 6m; 6, 9h; NA

I

1= In

-person

I

2= In

-person

I

1= Group

I

2= Group

I

1= HCP (DSN)

I

2= Non

-HCP 

(peer) & HCP 

(DSN)

I

1= Minimal 

–

Content & 

Delivery I2= Minimal 

–

Content & 

Delivery

I

1= 

None/NR I2= Yes
F-14

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

7.6±1.6%, 

33.3%

Barratt, 2008

England

I= 27

UC= 26

I= 55.8±11.3y

44%, NR

33.8±5.3kg/m2

9.6±1.7%, 

100%

UC= 55.8±11.3y

46%, NR

32.1±4.3kg/m2

9.7±1.2%, 

100%

Lifestyle; weight 

loss and lifestyle 

program (500kcal 

deficit and 

150mins/wk PA) 

with MI to prevent 

weight gain 

following initiation 

of insulin

6m; 6, 4h; NA In-person Individual HCP (RD) Minimal –

Content & 

Delivery

None/NR

Beverly, 2013

U.S. (MA)

I= 68

AC= 67

I= 59.9±8.5y

52.2%, 26.9%

34.6±7.0kg/m2

8.5±1.4%, NR

AC= 58.4±9.0y

44.7%, 29.8%

33.7±7.1kg/m2

8.3±1.0%, NR

I= DSME; 

reinforcement of 

education using 

conversation map 

tools 

AC= Non-DSME 

education; Heart 

Healthy sessions 

I= 1m; 4, 4h; NA

AC= 1m; 2, 4h; 

NA

I= In-person

AC= Inperson

I= Group 

AC= Group

I= 

Multidisciplinary 

(RD, RN)

AC= 

Multidisciplinary 

(RD, RN)

I= Minimal –

Content

AC= Minimal 

– Content

I= 

None/NR

AC= 

None/NR

Bond, 2007

U.S. (WA)

I= 31

UC= 31

I= 66.2±5.7y

58%, 13%

90.7±16.3kg

7.0±1.1%, 94%

UC= 68.2±6.2y

52%, 14%

92.5±18.1kg

7.1±0.9%, 94%

DSME; webbased DSME with 

self-management 

tracking, online 

education and 

support sessions 

and MSN 

communication for 

older adults

6m; 26+, NR; NA

(Plus instant 

messaging, email 

& chats)

Technology Mixed HCP (RN) Moderate-toHigh –

Content & 

Delivery

Yes
F-15

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

(T1DM 13%)

Bozzetto, 2014

Italy

I1= 11

I2= 8

AC1= 10

AC2= 9

I1= 63±5y

72.8%, NR

31±3kg/m2

6.7±0.9%, 0%

I2= 59±8y

100%, NR

29±2.0kg/m2

6.9±0.6%, 0%

AC1= 58±4y

70%, NR

30±2.0kg/m2

6.3±0.3%, 0%

AC2= 56±7y

77.8%, NR

28±3kg/m2

6.6±0.8%, 0%

I1= Lifestyle; highcarbohydrate, 

high-fibre diet (no 

caloric restriction) 

plus supervised 

PA

I2= Lifestyle; highMUFA diet (no 

caloric restriction) 

plus supervised 

PA

AC1= Diet; highcarbohydrate, 

high-fibre diet

AC2= Diet; highMUFA diet

I1= 1.8m; 16, NR; 

NA

I2= 1.8m; 16, NR; 

NA

AC1= 1.8m; 8, 

NR; NA

AC2= 1.8m; 8, 

NR, NA

(Plus twice 

weekly telephone 

calls to check 

adherence)

I1= Mixed

I2= Mixed

AC1= Mixed

AC2= Mixed

I1= Individual

I2= Individual

AC1= 

Individual

AC2= 

Individual

I1= 

Multidisciplinary 

(RD, exercise 

physiologist)

I2= 

Multidisciplinary 

(RD, exercise 

physiologist)

AC1=HCP (RD)

AC2= HCP (RD)

I1= Minimal – 

Delivery

I2= Minimal – 

Delivery

AC1= Minimal 

& Delivery

AC2= Minimal 

– Delivery

I1= 

None/NR

I2= 

None/NR

AC1= 

None/NR

AC2= 

None/NR

Bradshaw, 

2007

U.S. (UT)

I= 30

UC= 37

I= 60.8±11.0y

32%, 0%

NR

6.7±1.2%, 23%

UC= 57.5±11.0y

38%, 17%

NR

6.9±1.1%, 23%

DSME; DSME 

meeting standards 

with RTAD

(Resiliency 

Training Approach 

for Diabetes)

1.2m; 10, 15h; 

NA

In-person Group Multidisciplinary 

(CDE, RD)

Minimal –

Content

None/NR

Brown, 2002

U.S. (TX)

I= 128

UC= 128

I= 54.7±8.2y

40%, 100%

DSME + Support; 

culturally 

12m; 27, 54h; 9m In-person Group with 

supports

Non-HCP (CHW) 

& 

Moderate-toHigh –Yes
F

-16

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

32.3±6.0kg/m

2

11.8±3.0%, 

26%

UC= 53.3±8.3y

32%, 100%

32.1±6.4kg/m

2

11.8±3.0%, 

27%

competent, 

community-based 

self-management 

intervention for

Mexican 

Americans

Multidisciplinary 

(RN, RD)

Content & 

Delivery

Brown, 2005

U.S. (TX)

I

1= 114

I

2= 102

I

1= 49.6±7.6y

39.5%, 100%

32.2±5.8kg/m

2

11.8±3.4%,

9.6% I2= 49.6±8.2y

40.2%, 100%

32.9±8.3kg/m

2

11.5±3.5%, 

7.4%

I

1= DSME + 

Support; 

compressed 

version of culturally 

competent, 

community-based 

DSME for

Mexican 

Americans I2= DSME + 

Support; intense 

version of DSME 

+ Support

I

1= 12m; 11, 22h; 

10m I2= 12m; 26, 52h; 

9m 

I

1= In

-person

I

2= In

-person

I

1= Group 

with 

supports I2= Group 

with 

supports

I

1= Non

-HCP 

(CHW) & 

Multidisciplinary 

(RN, RD) I2= Non-HCP 

(CHW) & 

Multidisciplinary 

(RN, RD)

I

1= Moderate

-

to-High –

Content & 

Delivery I2= Moderate

-

to-High –

Content & 

Delivery

I

1= Yes

I

2= Yes

Brown, 2011 

U.S. (TX)

I

1= 48

I

2= 35

I

1= 49.7±9.2y

25.7%, 100%

32.2±5.4kg/m

2

10.6±3.0%, 

21.3% I2= 49.0±7.8y

35.4%, 100%

I

1= DSME + 

Support; culturally 

tailored group 

DSME for 

Mexican 

Americans I2= DSME + 

I

1= 6m; 10; 20h; 

4mI2= 6m; 15; 20h+; 

4m

I

1= In

-person 

I

2= Mixed

I

1= Group 

with 

supports I2= Mixed 

with 

supports

I

1= 

Multidisciplinary 

(RN, RD) I2= 

Multidisciplinary 

(RN, RD)

I

1= Moderate

-

to-High –

Content & 

Delivery I2= Moderate

-

to-High –

Content & 

I

1= Yes

I

2= Yes
F-17

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

34.6±7.6kg/m2

9.2±2.7%, 

16.7% 

Support; addition 

of case manager 

to coordinate care 

Delivery

Castejon, 2013

U.S. (FL)

I= 19

UC= 24

I= 54±9y

42%, 100%

31.2±1.9kg/m2

8.3±0.4%, NR

UC= 55±10y

21%, 100%

31.5±1.3kg/m2

8.2±0.4%, NR

DSME; 

Pharmacistcentered 

Assessment and 

Reinforcement of 

Diabetes Selfefficacy (PARDS), 

community-based

pharmacist 

intervention for 

Latinos

1.5m; 4, 4.5h; NA In-person Mixed with 

supports

Non-HCP 

(graduate 

student) & HCP 

(Pharmacist)

Moderate-toHigh -

Content 

Yes

Chan, 2014

Hong Kong

I= 312

AC= 312

I= 54.5±9.9y

57.1%, NA

26.6±4.3kg/m2

8.2±1.7%, 

37.7%

AC= 54.8±8.6y

56%, NA

27.1±4.6kg/m2

8.2±1.6%, 32%

I= DSME; 

empowerment DM 

class followed by 

peer telephone 

support

AC= Non-DSME 

education; 

empowerment DM 

class

I= 12m; 14; 7h; 

NA

AC= 12m; 1, 2h; 

NA

I= In-person

AC= Inperson

I= Mixed

AC= Group

I= Non-HCP 

(peer) & HCP 

(RN)

AC=RN

I= Moderateto-High –

Content & 

Delivery

AC= Minimal 

- Content 

I= Yes

AC= 

None/NR

Chan, 2012

Hong Kong

I= 107

UC= 101

I= 71.7±8.0y

34.3%, NA

24.8±3.6kg/m2

7.4±1.5%, 

22.2%

UC= 72.0±7.9y

25.3%, NA

DSME; problemsolving group 

education with PA 

practice for older 

adults

2m; 8, 16h; NA In-person Group HCP (allied HCP) Minimal –

Content & 

Delivery

Yes
F

-18

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

24.6±3.8kg/m

2

7.0±1.2%, 

25.3%

Cheong, 2009

Canada

I= 22

AC= 22

I= 55.4±2.2y

58%, NR

32.6±1.3kg/m

2

7.2±0.3%, 0%

AC= 54.8±1.4y

53, NR

35.5±1.4kg/m

2

7.2±0.2%, 0%

(SEM used)

I= Lifestyle; First 

Step First Bite 

Program focused 

on walking more 

and low GI foods

AC= PA portion of 

Lifestyle 

I= 1m; 4, 4-6h; 

NA

AC= 1m; 4, 4-6h; 

NA

I= In-person

AC= In-

person

I= Group

AC= Group

I= Non-HCP 

(graduate 

student)

AC=Non- HCP 

(graduate 

student)

I= Minimal –

Content

AC= Minimal - Content

I= 

None/NR

AC= 

None/NR

Chlebowy, 

2014

U.S. (KY)

I = 26

UC = 36

I= 55.8±2.1y

NR, 100%

36.3±7.8 kg/m

2

7.8±0.2%, NR

UC= 53.0±2.3y

NR, 100%

33.0±7.6 kg/m

2

8.1±0.2%, NR

DSME; MI-based 

intervention 

focused on 

medication 

adherence, self-

monitoring, and 

PA

3m; 6, 5h; NA In-person Individual HCP (RN) Moderate-to-

High -

Content

None/NR

Clark, 2004

United 

Kingdom

I= 50

UC= 50

All= 59.5y

58%, NR

31±4kg/m

2

8.4±1.6%, 21%

Lifestyle; 

individualized diet 

and PA goals with 

brief MI based on 

assessment of 

stage of change 

and barrier 

identification

6m; 12, 3h; NA Mixed Individual HCP 

(interventionist)

Moderate-to-

High- Content 

& Delivery

None/NR

Cooper, 2008 I= 53 All= 58.6 (35- DSME; Looking 2m; 8, 16h; NA In-person Group HCP (DSN) Minimal – None/NR
F-19

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

United 

Kingdom

UC= 36 73)y

56% male

HbA1C

I= 8.5±2.3%

UC= 7.8±2.2%

After Yourself, 

empowermentbased education 

program with 

focus on systems 

of motivation and 

relaxation training

Content 

Corkery, 1997

U.A. (NY)

I1= 34

I2= 30

All= 52.±11.7y

26%, 100%

NR

11.7±3.7%, NR

I1= DSME; ADA 

standards for lowincome and 

literacy Hispanics

I2= DSME; 

addition of CHW 

for support and 

care coordination

I1= 3.4m

I2= 3.4m

I1= In-person

I2= In-person

I1= Individual 

(30% with 

supports)

I2= Individual 

(30% with 

supports)

I1= HCP 

(RN/CDE)

I2= Non-HCP 

(CHW) & HCP 

(RN/CDE)

I1= Moderateto-High –

Content & 

Delivery

I2= Moderateto-High –

Content & 

Delivery

I1= 

None/NR

I2= Yes

Cramer, 2007

U.S. (NY)

I= 27

UC= 24

I= HbA1c ≥8%

UC= HbA1c 

≥8%

Lifestyle; Modified 

Diabetes 

Prevention 

Program (DPP) 

teaching plan

9m; 16, NR; NA Mixed Individual HCP (RN) Moderate-toHigh –

Content 

None/NR

Dasgupta, 

2006

Canada

I= 21

AC= 21

I= 54 (47-58)y

57%, NR

36.6(31.6-39.8)

kg/m2

7.2(6.1-7.7)%, 

0%

AC= 49 (46-

55)y

43%, NR

I= Lifestyle; diet 

counseling and 

supervised 

aerobic moderateintensity exercise 

3x/wk tapering

AC= Diet portion 

of Lifestyle

I= 6m; 54, 50.5h; 

NA

AC= 6m; 6, 2.5h; 

NA

I= In-person

AC= Inperson

I= Mixed

AC= Mixed

I= 

Multidisciplinary 

(RD, exercise 

physiologist)

AC= HCP (RD)

I= Minimal –

Content

AC= Minimal 

- Content 

I= 

None/NR

AC= 

None/NR
F-20

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

36.4 (32.8-41.8) 

kg/m2

7.1 (6.3-7.4)%, 

0%

(Median, IQR)

Davis, 2010 I= 85

UC= 80

I= 59.9±9.4y

27.1%, 75.3%

37.1±8.1kg/m2

9.3±1.9%, 

16.3%

UC= 59.2±9.3y

23.7%, 72.5%

35.9±7.6 kg/m2

8.9±1.8%, 

22.8%

DSME; Diabetes 

TeleCare for 

underserved 

communities

12m; 13, NR; NA Mixed Mixed Multidisciplinary 

(RN/CDE, RD, 

LPN)

Moderate-toHigh –

Content & 

Delivery

Yes

Deakin, 2006 I= 157

Att. C= 

157

I= 61.3±9.7y

52%, NR

30.8±5.3kg/m2

7.7±1.6%, 17%

Att. C= 

61.8±11.0y

52%, NR

30.6±5.7kg/m2

7.7±1.6%, 17%

I= DSME; X-PERT 

Programme

focused on 

empowerment and 

discovery learning

Att. C= 3 booked 

contacts for RD, 

RN and GP 

I= 1.5m; 6, 12h; 

NA

Att. C= 1.5m; 1-

3, 1h; NA

I= In-person

Att. C= Inperson

I= Group 

with 

supports

Att. C= Inperson

I= HCP (RD)

Att. C= 

Multidisciplinary 

(RD, RN, GP)

I= Moderateto-High –

Content & 

Delivery

Att. C= 

Minimal -

Content

I= Yes

Att. C= 

None/NR

D’EramoMelkus, 2010

U.S. (CT)

I= 52

AC= 57

I= 45±10y

0%, 100%

96±18kg

8.3±2.2%, 0%

I= DSME + 

Support; culturally 

relevant CBTbased behavioral 

DSMT plus coping 

I= 12m; 13, 

12.5h+3 NP 

support visits; 9m

AC= 12m; 14, 

I= In-person

AC= Inperson

I= Mixed

AC= Mixed

I= 

Multidisciplinary 

(NP, Psych)

AC= HCP (NP)

I= Moderateto-High –

Content 

AC= None

I= 

None/NR

AC= 

None/NR
F

-21

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

AC= 45±10y

0%, 100%

96±18kg

8.3±2.2%, 0%

skills training and 

followup support

AC= Non-DSME 

education and 

support

17+3 NP support 

visits; 9m

Dunstan, 1997

Australia

I= 11

AC= 12

I= 52.3±8.3y

73%, NR

29.1±2.4kg/m

2

8.8±2.7%, 0%

AC= 53.0±7.0y

75%, NR

29.7±4.3kg/m

2

8.1±1.4%, 0%

I= Lifestyle; low-

fat diet with 

supervised 

moderate intensity 

stationary cycling 

3x/wk for older 

adults

AC= Diet; low fat 

diet with 

supervised 

stretching 3x/wk

I= 1.8m; 24, 

16h+weekly RD 

interview 

duration; NA

AC= 1.8m; 24, 

16h+weekly RD 

interview 

duration; NA

I= In-person

AC= In-

person

I= Individual

AC= 

Individual

(NR for PA 

component)

I= 

Multidisciplinary 

(RD, Exercise 

physiologist)

AC= 

Multidisciplinary 

(RD, Exercise 

physiologist)

I= Minimal –

Content

AC= Minimal - Content

I= 

None/NR

AC= 

None/NR

Dunstan, 2005

Australia

I= 19

AC= 17

I= 67.6±5.2y

63%, NR

31.5±3.4kg/m

2

8.1±1.1%, 0%

AC= 66.9±5.3y

46%, NR

32.5±3.8kg/m

2

7.5±1.1%, 0%

I= Lifestyle; moderate weight 

loss diet plus 

supervised and 

home-based high 

intensity (75-85% 

1-RM) progressive 

resistance training AC= Diet; 

moderate weight 

loss diet with 

supervised and 

home-based 

I= 12m; 86, 72h+ 

time for 14 calls; 

6m

AC=12m; 86, 

72h+ time for 14 

calls; 6m

I= Mixed

AC= Mixed

I= Individual

AC= 

Individual

I= 

Multidisciplinary 

(RD, Exercise 

physiologist)

AC= 

Multidisciplinary 

(RD, Exercise 

physiologist)

I= Minimal –

Content & 

Delivery

AC= Minimal – Content & 

Delivery

I= 

None/NR

AC= 

None/NR
F-22

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

stretching 

Eakin, 2014

Australia

I= 151

UC= 151

I= 57.7±8.1y

56%, 13.1%

33.1±6.3kg/m2

7.6 (6.3-8.1)%, 

15.2%

UC= 58.3±9.0y

57%, 11.9%

33.2±6.0kg/m2

7.0 (6.4-7.9)%, 

13.2%

(Median, IQR)

Lifestyle; Living 

Well with 

Diabetes, 

telephonedelivered program 

with MI for weight 

loss (5-10% initial 

weight) and PA 

(≥210min/wk & 2-

3 resistance/wk)

18; 27, 11.25h; 

12m

Technology Individual Non-HCP 

(telephone 

counselors)

Moderate-toHigh –

Content & 

Delivery

None/NR

Edelman, 2015

U.S. (NC)

I = 193

Att. C = 

184

I= 57.8±10.9y

46%, 51%

36.2±7.9 kg/m2

9.2±1.5%, NR

Att. C= 

59.6±10.7y

45%, 50%

36.4±7.5kg/m2

9.0±1.4%, NR

I = DSME; 

telephonic 

behavioral nurse 

intervention 

(TEACH-DM) for 

DM and 

hypertension 

Att. C = General 

health information 

at same frequency

I = 24m; 12, NR; 

NA

Att. C = 24m; 12, 

2hr; NA

I = 

Technology

Att. C = 

Technology

I = Individual

Att. C = 

Individual

I = HCP (RN)

Att. C = HCP 

(RN)

I = Moderateto-High –

Content & 

Delivery

Att. C = None

I = 

None/NR

Att. C = 

None/NR

Fisher, 2013

U.S. (CA)

I1= 150

I2= 146

AC= 96

I1= 57±8.8y

52%, 58.7%

32.1±7.2kg/m2

7.4±1.6% 

15.3%

I2= 55.9±9.4y

I1= DSME; My 

Path to Healthy 

Life, bilingual 

computer-assisted 

self-management 

program (CASM) 

focused on diet, 

I1= 12m; 10, 3h 

;8m

I2= 12m; 10, 

3.5h; 8m

AC= 12m; 8, 2h; 

I1= Mixed

I2= Mixed

AC= 

Technology 

I1= Individual

I2= Individual

AC= 

Individual

I1= Non-HCP 

(nonprofessional 

college 

graduates)

I2= Non-HCP 

(nonprofessional 

I1= Moderateto-High –

Content & 

Delivery

I2= Moderateto-High –

I1= 

None/NR

I2= 

None/NR

AC= 
F-23

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

44%, 58.2%

33.9±7.9kg/m2

7.4±1.6%, 

19.2%

AC= 55.2±9.6y

41%, 64.6%

33.3±8.4kg/m2

7.4±1.6%, 

19.8%

PA and 

medication taking 

with followup calls 

I2= DSME; CAPS 

(CASM plus 

problem solving 

therapy)

AC= Non-DSME 

education; 

Computer health 

risk assessment, 

DM DVD and 

telephone 

contacts

NA college 

graduates)

AC= Non-HCP 

(nonprofessional 

college 

graduates)

Content & 

Delivery

AC= None

None/NR 

Foster, 2009

U.S. (PA)

I= 35

AC= 34

I= 52.1±7.7y

25.7%, 63%

39.1±5.5kg/m2

7.6±1.6%, 0%

AC= 52.8±11.2y

32.2%, 56%

38.9±6.1kg/m2

7.5±1.7%, 0%

I= Lifestyle; 

portion-controlled 

diet, prescribed 

PA regime (1250-

1550 kcal/d; 20-

25% fat & 20-25% 

protein), ≥200 

mins PA/wk) and 

CBT-based 

behavioral weight 

loss treatment

AC= Non-DSME 

education; didactic 

group sessions

I= 2.8m; 12, NR; 

NA

AC= 2.8m; 3, 

NR, NA

I= In-person

AC= Inperson

I= Group

AC= Group

I= HCP (not 

specified)

AC= HCP (not 

specified)

I= Minimal –

Content

AC= None

I= 

None/NR

AC= 

None/NR

Foster, 2013 I1=50 I1= 55.5±10.3y I1= Lifestyle; I1= 6m; 9, 13.5h; I1= In-person I1= Group I1= Non-HCP I1= Minimal - I1= 
F

-24

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

U.S. (PA)I

2=50 58%, 68%

35.3±4.6kg/m

2

7.6±1.3%, NR I2= 55.7±11.0y

60%, 60%

36.2±5.8kg/m

2

7.9±1.3%, NR 

behavioral lifestyle 

program with 

portion-controlled 

pre-packaged diet

(1250-1550kcal/d; 

20-25% fat & 20-

25% protein), PA 

target ≥200 

mins/wk and CBT-

based behavioral 

training I2= DSME; DSME 

meeting standards 

plus diet and 

exercise goals (as 

lifestyle arm) and 

meal plan

NAI2= 6m; 9, 13.5h; 

NA

I

2= In

-person

I

2= Group (lifestyle 

counselor) I2= HCP (CDE)

Content I2= Minimal 

-

Content

None/NR I2= 

None/NR

Frosch, 2011

U.S. (CA)

I= 100

UC= 101

I= 56.7±8.3y

46%, 78.8%

33.3±8.0kg/m

2

9.4±1.1%, NR

UC= 54.3±8.9y

57%, 92%

32.8±7.4kg/m

2

9.8±2.1%, NR

DSME; DVD 

program with 

health coaching 

via telephone for 

poorly controlled 

diabetes

5m; 5; 2.5h; NA Technology Individual HCP (RN) Moderate-to-

High –

Content & 

Delivery

None/NR

Gagliardino, 

2013a

Argentina

I

1= 105

I

2= 93

I

1= 60±10y

50%, NA

33±6kg/m

2

7.3±1.5%, NR

I

1= DSME; 

Diabetes 

Structured 

Education 

Courses for 

I

1= 6m; 5, 7.5h+; 

NAI2= 12m; 46, 

7.5h+peer 

I

1= In

-person

I

2= Mixed

I

1= Group

I

2

= Mixed

I

1= HCP 

(diabetes 

educator) I2= Non-HCP 

I

1= Minimal 

–

Content I2= Moderate – Content & 

I

1= 

None/NR I2= Yes
F-25

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

I2= 62±9y

47%, NA

32±7kg/m2

7.1±1.5%, NR

People with

Type 2 Diabetes

including low 

calorie (1000kcal) 

diet and SMBG 

delivered by 

educators

I2= DSME + 

Support; same 

program delivered 

by peers with 

ongoing support

support contact 

time; 11m

(peer) Delivery

Gagliardino, 

2013b

Argentina

I= 117

UC= 117

(Not 

reporting 

on arms 

with 

physician 

education) 

I= 62.2±8.4y

NR, NA

29.0kg/m2

7.8±1.4%, NR

UC= 62±8.4y

NR, NA

29.3kg/m2

7.8±1.2%, NR

DSME; Diabetes 

Structured 

Education 

Courses for 

People with

Type 2 Diabetes

including low 

calorie (1000kcal) 

diet and SMBG

6m; 5, 7.5h+; NA In-person Group HCP (diabetes 

educators)

Minimal –

Content 

None/NR

Giannopoulou, 

2005

U.S. (NY)

I= 11

AC1= 11

AC2= 11

(Analyzed)

I= 57.4±1.7y

0%, NR

33.7±1.9kg/m2

6.8±0.5%, 0% 

AC1= 55.5±1.7y

0%, NR 

35.9±1.9kg/m2

6.4±0.8%, 0%

I= Lifestyle 

intervention with 

nutritional 

consulting (high 

monounsaturated 

fat and 600kcal 

energy deficit) and 

supervised 

walking program 

(60mins 3-4x/wk) 

I= 3.2; 42+, 42h+ 

nutritional 

counseling time; 

NA

AC1= 3.2m; 42+, 

42h+; NA 

AC2= 3.2m; 15, 

NR; NA

I= In-person

AC1= Inperson

AC2= Inperson 

I= NR

AC1= NR

AC2= 

Individual

I= HCP (non 

specific)

AC1= HCP (non 

specific)

AC2= HCP (non 

specific)

I= Minimal –

Content 

AC1= Minimal 

– Content 

AC2= Minimal 

– Content 

I= 

None/NR

AC1= 

None/NR

AC2= 

None/NR 
F

-26

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

AC

2= 58.5±1.7y

0%, NR

34.3±1.9kg/m

2

7.3±0.5%, 0%

AC

1= PA control

AC

2= Diet control 

Glasgow, 

2006a

U.S. (CO)

I= 174

Att. C= 

161

I= 62.0±11.7y

49.7%, 25.9%

31.3±7.0kg/m

2

7.4±1.6%, 

24.2%

Att. C= 

61.0±11.0y

50%, 20.4%

31.9±7.2kg/m

2

7.5±1.6%, 

19.2%

I= DSME; CBT-

based computer-

assisted tailored 

intervention 

focused on 

healthy eating and 

PA with followup

Att. C= computer-

generated general 

health risk 

appraisal with 

brief followup and 

counseling 

I= 2m; 3, 1h+; 

NA

(Plus tailored 

mail out)

Att. C= NR

I= Mixed

Att. C= Mixed

I= Individual

Att. C= 

Individual

I= Non-HCP 

(health 

educators)

Att. C= Non-HCP 

(health 

educators)

I= Minimal –

Content & 

Delivery

Att. C= NA

I= 

None/NR

Att. C= 

NA

Glasgow, 

2006b

U.S. (CO)

I= 167

UC= 160

I= 61.1±11.4y

50%, 34%

32.1±7.0kg/m

2

7.3±1.5%, 27%

UC= 61.1±11.4y

60%, 27%

33.3±8.0kg/m

2

7.2±1.3%, 22%

DSME; computer-

assisted and 

tailored DSM 

intervention 

focused on diet 

and aerobic and 

strength PA 

2m; 4, 1.5h; NA Mixed Individual Non-HCP 

(graduates of 

health degrees)

Moderate-to-

High –

Content 

None/NR

Glasgow, 2012

U.S. (CO)

I= 162

AC= 169

Att. C=

132

I= 57.8±9.3y

46.3%, 29.3%

35.3±0.5kg/m

2

8.3±0.1%, NR

I= DSME; My Path 

to Healthy Life, 

bilingual 

computer-assisted 

I= 12m; 3+, 1h+; 

NA 

(Plus computer 

I= Mixed

AC= NA

I= Mixed

AC= 

Individual

I= Non-HCP 

(research staff 

member) & HCP 

(RD)

I= Moderate-

to-High –

Content & 

Delivery

I= Yes

AC= Yes
F-27

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

AC= 58.7±9.3y

55.4%, 25.9%

34.4±0.5kg/m2

8.0±0.1%, NR

Att. C= 

58.7±9.1y

48.5%, 29.4%

34.8±0.6kg/m2

8.2±0.2%, NR

self-management 

program (CASM) 

focused on diet, 

PA and 

medication taking 

with followup calls 

and group 

sessions

AC= Non-DSME 

education via 

(CASM) with 

periodic 

automated 

motivational calls

Att. C= Tailored 

health risk 

assessment and 

brief contacts

use and invitation 

to 3- 2h group 

sessions but only 

36% attended 

one)

AC= 12m; NA 

(Computer use 

only)

Att. C= 12m; NR

Att. C= 

Technology Att. C= 

Individual

AC= NA

Att. C= NR

AC= 

Moderate-toHigh –

Content & 

Delivery

Att. C= NA

Att. C= 

NA

Goudswaard, 

2004

The 

Netherlands

I= 28

UC= 30

I= 62.6±9.0y

52%, NR

30.2±4.4

8.2±1.1%, 0%

UC= 58.7±11.4y

44%, NR

29.8±5.5

8.8±1.5%, 0%

DSME; 

collaborative 

education with 

emphasis on 

SMBG 

interpretation for 

patients on 

maximal oral 

hypoglycemic 

agents

6m; 6, 2.5h; NA In-person Individual HCP (RN) Minimal -

Content

None/NR

Hawkins, 2010

U.S. (CT)

I= 40

Att. C= 36

I= 64y

14.7%, 82.4%

I= DSME; 

videophone 

I= 6m; 16, 4.5h; 

NA 

I= 

Technology

I= Individual I= HCP (NP) I= Moderateto-High –I= 

None/NR
F

-28

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

37.7±8.5kg/m

2

9.0±2.3%, NR

Att. C= 

65.8±10.4y

12.5%, 84.4%

38.6±6.9kg/m

2

8.9±3.1%, NR

motivational 

program based on 

Life With 

Diabetes: A Series 

of Teaching 

Outlines and MI 

for older adults

Att. C= handouts 

on general healthy 

living and monthly 

videophone calls

(Plus reminder 

calls)

Att. C= 6m; 6, 

0.5h; NA

Att. C= 

Technology

Att. C= 

Individual

Att. C= HCP 

(RN)

Content & 

Delivery

Att. C= NA

Att. C= 

NA

Hendricks, 

2000

U.S. (MD)

I

1= 15

I

2= 15

I

1= 57.4±13.0y

100%, 100%

25-29kg/m

2

(33%); 

>30kg/m

2 (54%)

8.3±2.0%, NR I2= 58.9±10.5y

100%, 100%

25-29kg/m

2

(40%); 

>30kg/m

2 (60%)

7.8±1.9%, NR

I

1= DSME + 

Support; Lifeskills 

Diabetes Self-

Management 

Training Program 

with 

empowerment 

approach and 

quarterly 

telephone support 

for African 

American men I2= DSME + 

Support; Lifeskills 

Diabetes Self-

Management 

Training Program 

with 

empowerment 

I

1= 7m; 6, 8.5h; 

6mI2= 7m; 8, 9h; 6m

I

1= Mixed

I

2= Mixed

I

1= Mixed

I

2= Mixed

I

1= 

Multidisciplinary 

(NP, Psych both 

CDE) I2= 

Multidisciplinary 

(NP, Psych both 

CDE)

I

1= Moderate

-

to-High –

Content I2= Moderate

-

to-High –

Content & 

Delivery

I

1= 

None/NR I2= 

None/NR
F

-29

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

approach and 

monthly 

telephone support 

for African 

American men

Hermanns, 

2012

I= 94

AC= 92

I= 62.0±8.7y

47.9%, NR

33.3±5.6kg/m

2

8.4±1.5%, 

100% (4.2±3.2 

injections/day)

AC= 63.9±7.8y

63%, NR

33.4±6.2kg/m

2

8.3±1.2%, 

100% (3.7±1.2 

injections/day)

I= DSME; 

MEDIAS 2 ICT for 

initiation of 

intensive insulin 

therapy using 

empowerment 

approach and 

focus on 

metabolic risk 

factors

AC= Non-DSME 

education; didactic 

education

I= 1.25m; 10, 

15h; NA

AC= 1.25m; 10, 

15h; NA

I= In-person

AC= In-

person

I= Group 

with 

supports for 

1 session

AC= Group

I= HCP (CDE)

AC= HCP (CDE)

I= Minimal –

Content

AC= None 

I= 

None/NR

AC= 

None/NR

Hill-Briggs, 

2011

U.S. (MD)

I= 29

AC= 27

I= 61.1±11.0y

48.3%, 100%

NR

8.5%, 35.2%

AC= 61.5±10.9y

33.3%, 100%

NR

8.3%, 33.3%

I= DSME; Project 

DECIDE 

(Decision-making 

Education for 

Choices In

Diabetes 

Everyday), 

problem-solving-

based diabetes 

self-management 

training for low 

income and 

literacy patients

I= 4.5m; 9, NR; 

NA

AC= 0.5m; 2, 

NR; NA

I= In-person

AC= In-

person

I= Group

AC= Group

I= HCP 

(interventionist)

AC= HCP 

(interventionist)

I= Moderate-

to-High –

Content

AC= 

Moderate-to-

High-

Content

I= 

None/NR

AC= 

None/NR
F-30

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

AC= Non-DSME; 

condensed 2-

sessions of 

education and 

problem solving

Holmen, 2014

Norway

I = 50

AC = 51

UC = 50

I= 57.4±12.2y

50%, NR

30.7±5.6kg/m2

8.2±1.1%, 38%

AC= 58.6±11.8y

67%, NR

32.4±6.5 kg/m2

8.1±1.1%, 50%

UC= 55.9±12.2y

60%, NR

32.0±6.0kg/m2

8.3±1.2%, 48%

I = DSME; mobilephone selfmanagement 

system with 

telephone 

counseling

AC = Non-DSME; 

mobile-phone selfmanagement 

system

I = 12m; 5, 1.5h; 

NA

I = 

Technology

AC = NA

I = Individual

AC = 

Individual

I = 

Multidisciplinary 

(RN, RD)

AC= NA

I = Moderateto-High -

Delivery

I = 

None/NR

AC = 

None/NR

Holtrop, 2002

U.S. (MI)

I= 67

UC= 65

I= 58y

0%, 5%

35.4±5.8kg/m2

8.0%, 25.4%

UC= 65y

0%, 5%

37.9±8.1kg/m2

7.7%, 34%

DSME; Sticking to 

it- Diabetes 

Mellitus, 

behavioral 

education 

program focused 

on diet and 

exercise

1.5; 6+6 

supportive 

telephone 

contacts, 

9h+telephone 

duration; NA

(Plus supportive 

telephone 

contacts between 

sessions)

Mixed Mixed Non-HCP (lay 

health advisors 

from the 

community)

Minimal –

Content & 

Delivery

Yes

Huisman, 2009 I= 53 I= 60.1±6.8y I= Lifestyle; self- I= 6m; 9, 17h; I= In-person I= Mixed I= HCP (Psych) I= Minimal – I= 
F-31

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

The 

Netherlands

AC= 38

UC= 38

52%, 0%

36.0±6.8kg/m2

7.3±1.3%, NR

AC= 56.7±10.3y

42%, 0%

35.7±6.1kg/m2

7.6±1.5%, NR 

UC= 56.7±9.9y

46%, 0%

35.0±5.3kg/m2

7.2±1.1%, NR

regulation 

program for 

weight reduction 

via MI to select 

personalized 

goals

AC= Non-DSME 

education; selfhelp book with 12-

week program 

with 1 in-person 

and 3 telephone 

consultations 

NA

AC= 6m; 4, NR; 

NA

AC= Mixed

with 

supports for 

1 session

AC= 

Individual

AC= HCP (RN)

Content & 

Delivery

AC= Minimal 

– Content & 

Delivery

None/NR

AC= 

None/NR

Izquierdo, 2003

U.S. (NY)

I1= 27

I2= 29

I1= 61.4±8.9y

59%, 5%

31.3±6.2kg/m2

8.3±1.6%, NR 

(9% T1DM)

I2= 53.9±10.1y

33%, 5%

35.9±9.2kg/m2

8.7±2.2%, NR 

(12% T1DM)

I1= DSME; in-clinic 

delivery of DSME 

meeting standards 

and including 

coping skills and 

empowerment 

approach

I2= DSME; 

telemedicine 

delivery of DSME 

meeting standards 

and including 

coping skills and 

empowerment 

approach

I1= 3m; 3, 4h; NA

I2= 3m; 3, 4h; NA

I1= In-person

I2= 

Technology

I1= Individual

I2= Individual

I1= Multidisciplinary (RD, RN)

I2= Multidisciplinary (RD, RN)

I1= Minimal –

Content & 

Delivery

I2= Moderateto-High –

Content & 

Delivery 

I1= 

None/NR

I2= 

None/NR

Johnson, 2009 I= 22 I= 56.2y I= Lifestyle; I= 3m; 8, NR; NA I= In-person I= Group I= Non-HCP I= Minimal – I= 
F

-32

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Canada AC= 19 42%, NR

32.7±5.9kg/m

2

6.5±1.3%, 0%

AC= 56.2y

42%, NR

32.0±6.2kg/m

2

6.4±1.3%, 0%

walking program 

with supervised 

walking 1x/wk and 

goal to increase 

intensity by 10% 

and diet training to 

exchange foods 

having low for 

high glycemic 

index 

AC= basic walking 

program (no 

defined targets) 

and basic dietary 

education on 

glycemic load 

AC= 3m; 8, NR

(All participants 

received 12-

week basic 

walking program 

in early phase) 

AC= In-

person

AC = Group (health field 

graduate 

students) 

AC= non-HCP

Content

AC= Minimal - Content

None/NR

AC= 

None/NR

Jones, 2003

Canada

I= 250

UC= 250

(Not 

reporting 

on groups 

receiving 

free 

glucose 

testing 

strips)

I= 55.1y

56.4%, NR

32.2kg/m

2

8.43%, 32%

UC= 54.6y

50%, NR

31.6kg/m

2

8.48%, 34.4%

DSME; Pathways 

to Change, stage-

matched 

personalized 

assessment and 

counseling for 

SMBG, healthy 

eating and 

smoking cessation

12m; 5, NR; NA

(Plus 

newsletters)

Technology Individual NR Moderate-to-

High –

Content & 

Delivery

None/NR

Keyserling, 

2002

U.S. (NC)

I

1= 66

I

2= 67

UC= 67

I

1= 59.8y

0%, 100%

34.6kg/m

2

11.1%, 40.9%

I

1= Lifestyle; clinic

-

based with diet 

(reduced fat), PA 

(30mins/ day)

I

1= 6m; 4, 3h; NA

I

2= 12m; 19, 

9.5h; 6m

I

1= Individual

I

2= Mixed

I

1= Individual

I

2= Mixed

I

1= HCP (RD)

I

2= Non

-HCP 

(peer) & HCP 

I

1= Minimal 

–

Content & 

Delivery

I

1= 

None/NR I2= Yes
F

-33

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

I

2= 58.5y

0%, 100%

36.2kg/m

2

10.8%, 43.3%

UC= 59.2y

0%, 100%

36.5kg/m

2

11.3%. 41.8%

I

2= Lifestyle; clinic 

and community-

based A New

Leaf . Choices for 

Healthy Living 

with Diabetes for 

African American 

Women 

incorporating 

social support

(RD)I

2= Moderate

-

to-High –

Content & 

Delivery

Kim, 2006

Korea

I= 32

UC= 26

I= 55.0±8.1y

19%, NR

25.8±3.8kg/m

2

8.5±1.4%, NR

UC= 53.8±9.0y

31%, NR

26.2±4.0kg/m

2

8.6±1.3%, NR

Lifestyle; 

education and 

counseling for 5% 

weight loss 

including 

individualized diet 

and ≥150mins/wk 

moderate PA

6m; 18, NR; 2m In-person Individual Non-HCP 

(exercise trainer) 

& HCP (RN)

Minimal –

Content & 

Delivery

None/NR

Kim, 2009

U.S. (MD, DC)

I= 41

UC= 42

I= 56.2±8.4y

62.5%, 100%

25.9±3.4kg/m

2

9.4±1.5%, NR

UC= 56.6±7.6y

48.7%, 100%

25.7±3.1kg/m

2

9.1±1.3%, NR

DSME + Support; 

community-based 

SHIP-DM (self-

help intervention 

program for type 2 

diabetes 

management) for 

Korean American 

immigrants

7m; 12, 13-15h; 

5.6m

(Plus reminder 

calls and 

newsletters)

Mixed Mixed Multidisciplinary 

(RD, RN)

Moderate-to-

High -

Delivery

Yes

Kim, 2014

Korea

I = 18

UC = 17

I= 48.8±8.6y

50%, NA

28.3±3.4kg/m

2

Lifestyle; diet and 

PA prescription 

with supervised 

3m; 36, 36h+; NA In-person Individual Multidisciplinary 

(RD, exercise 

physiologist)

Minimal -

Content

None/NR
F-34

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

7.5±0.7%, 0%

UC= 48.3±8.2y

59%, NA

28.1±3.4kg/m2

7.7±0.7%, 0%

resistance training 

3x/wk and selfperformed aerobic 

exercise & 

educational 

sessions

Koo, 2010

Korea

I= 14

AC1= 19

AC2= 13

UC= 18

I= 53±8y

0%, NR

29.4 (25.9-37.8) 

kg/m2

8.0±1.8%, NR

AC1= 57±8y

0%, NR

27.1 (24.0-31.5) 

kg/m2

7.5±1.1%, NR

AC2= 59±4y

0%, NR

25.5 (23.5-34.4) 

kg/m2

7.8±1.0%, NR

UC= 57±8y

0%, NR

28.5 (24.0-31.5) 

kg/m2

7.5±1.1%, NR

I= Lifestyle; diet 

and PA 

prescriptions and 

education

AC1= Diet 

prescription 

(1200kcal) with 

education

AC2= PA 

prescription 

(120mins brisk 

walking /day) with 

monitoring

I= 3m; 13, NR; 

NA

AC1= 3m; 7, NR; 

NA

AC2= 3m; 7, NR, 

NA

I= In-person

AC1= Inperson

AC2= Inperson

I= Individual

AC1= 

Individual

AC2= 

Individual

I= HCP (exercise 

therapist)

AC1= NR

AC2= HCP 

(exercise 

therapist)

I= Minimal –

Content

AC1= Minimal 

– Content

AC2= None

I= 

None/NR

AC1= 

None/NR

AC2= 

None/NR

Kulzer, 2007

Germany

I1= 63

I2= 66

AC= 64

I1= 56.6±6.7y

53.6%, NR

31.8±3.3kg/m2

I1= DSME; 

empowerment 

group DSME

I1= 3m; 12, 18h; 

NA

I1= In-person

I2= In-person

I1= Group

I2= Mixed

AC= Group

I1= HCP (Psych)

I2= HCP (Pscyh)

I1= Minimal –

Content 

I1= 

None/NR
F

-35

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

8.2±0.5%, 0% I2= 55.4±6.5y

51.6%, NR

32.63±4.2kg/m

2

7.7±0.4%, 0%

AC= 55.2±5.6y

45.9%, NR

32.1±3.9kg/m

2

7.6±0.5%, 0%

I

2= DSME; 

empowerment 

group & Individual 

DSME

AC= Non-DSME 

education in 

groups

I

2= 3m; 12, 18h; 

NA

AC= 3m; 4, 6h; 

NA

AC= In-

person

AC= HCP 

(Psych)

I

2= Minimal 

–

Content & 

Delivery

AC= None

I

2= 

None/NR

AC= 

None/NR

Lee, 2011

Hong Kong

I= 84

UC= 73

I= NR

39%, NR

25.1

8.18%, NR

UC= NR

37%, NR

25.6

8.0%, NR

DSME; self-

management 

training focused 

on self-efficacy

1.5m; 6, 15h; NA In-person Group HCP (social 

worker)

Minimal -

Content

None/NR

Lorig, 2008

U.S. (CA)

I= 219

UC= 198

Not 

considerin

g 6-month 

RCT 

portion 

without 

reinforcem

ent by 

automated 

I= 52.9±13.2y

42.9%, 100%

80.0±18.5kg

7.4±2.0%, 8.7%

UC= 52.8±13.4y

32.8%, 100%

77.9±13.4kg

7.4±1.9%, 

12.1%

DSME; Spanish 

Diabetes Self-

Management 

Program 

(SDSMP)

delivered by peers 

for Spanish-

speaking adults

1.5m; 6, 15h; NA In-person Group with 

supports

Non-HCP 

(Spanish-

speaking peer)

Moderate-to-

High –

Content & 

Delivery

Yes
F-36

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

telephone)

Lorig, 2009

U.S. (CA)

I= 186

UC= 159

I= 67.7±11.9y

37.6%, 36%

87.0±24.0kg

6.7±1.5%, 

17.7%

UC= 65.4±11.4y

33.8%, 29.4%

88.9±24.6kg

6.7±1.4%, 17%

DSME; 

community-based, 

peer-led DSMP

using self-efficacy 

approach

1.5m; 6, 15h; NA In-Person Group with 

supports

Non-HCP (peers) Minimal –

Content 

Yes

Lorig, 2010

U.S. (CA)

I= 491

UC= 270

(Interventi

on group 

includes 

IDSMP 

with+witho

ut listserve 

reinforcem

ent) 

I= 54.2±9.9y

26.3%, 22%

NR

6.5±1.2%, NR

UC= 

54.4±10.6y

28.9%, 28.9%

NR

6.4±1.3%, NR

DSME; Internet 

DSMP with 

discussion boards 

and facilitator 

support 

1.5m; 6, NR; NA Technology Individual Non-HCP (peers) Moderate-toHigh –

Content & 

Delivery

Yes

Lujan, 2007

U.S. (TX)

I= 75

UC= 75

I= 57.0±9.8y

19%, 100%

NR

8.2±2.2%, 4%

UC= 59.6±10.3y

22%, 100%

NR

7.7±1.5%, 5%

DSME; culturally 

specific diabetes 

intervention 

delivered by 

promotores for 

Mexican 

Americans

6m; 12, 

16h+biweekly 

telephone 

support duration; 

NA 

(Plus 8 mailed 

postcards) 

Mixed Mixed Non-HCP 

(Promotores)

Moderate-toHigh –

Content & 

Delivery

Yes

Lynch, 2014 I= 30 I= 53.4±11.4y I= DSME; Lifestyle I= 6m; 42, I= Mixed I= Mixed I= Non-HCP I= Moderate- I= Yes
F-37

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

U.S. (IL) AC= 31 40%, 100%

35.3±6.5kg/m2

7.9±1.6%, 

43.3%

AC= 54.8±8.5y

25.8%, 100%

35.9±6.3kg/m2

7.4±1.6%, 

41.9%

Improvement 

Through Food and 

Exercise (LIFE), 

CBT-based

intervention for 

African Americans 

with comorbid 

diabetes and 

hypertension plus 

telephone support 

calls from peers

AC= minimal 

education classes 

36+telephone 

support duration; 

NA

AC= 6m; 2, 6h; 

NA

AC= InpersonAC= Group

(African 

American peers) 

& HCP (RD)

AC= Non-HCP 

(CHW)

to-High –

Content & 

Delivery

AC= Minimal 

- Content

AC= 

None/NR

Mandel, 2013

U.S. (OH)

I1= 64

I2= 67

I1= 57.1±9.7y

23.4%, NR

36.8±8.2kg/m2

7.7±1.8%, NR

I2= 58.0±11.3y

31.3%, NR

34.5±8.5kg/m2

7.4±1.6%, NR

I1= DSME

I2= DSME (Music 

Therapy)

I1= 1m; 4, 8h; NA

I2= 2m; 8, 14h; 

NA

I1= In-person

I2= In-person

I1= Group

I2= Group

I1= HCP (CDE or 

RD)

I2= 

Multidisciplinary 

(CDE or RD, 

music therapist) 

I1= Minimal –

Content

I2= Moderateto-High –

Content & 

Deivery

I1= 

None/NR

I2= 

None/NR

Mayer-Davis, 

2004

U.S. (SC)

I1= 58

I2= 67

UC= 64

I1= 58.9±7.8y

15%, 89.4%

37.5±6.7kg/m2

9.7±3.1%, 

42.5%

I2= 59.7±8.6y

22%, 85.7%

37.6±6.5kg/m2

I1= Lifestyle; 

reimbursable 

intensive lifestyle 

program tailored 

to medically 

underserved

I2= Lifestyle; 

reimbursable 

I1= 12m; 4, 4h; 

NA

I2= 12m; 26, 26h; 

8m

I1= In-person

I2= In-person

I1= Mixed

I2= Mixed

I1= HCP (RD)

I2= HCP (RD)

I1= Moderateto-High –

Content & 

Delivery

I2= Moderateto-High –

Content and 

Delivery

I1= 

None/NR

I2= 

None/NR
F-38

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

10.2±2.5%, 

51%

UC= 62.4±9.5y

21%, 73.2%

35.2±7.5kg/m2

9.6±2.9%, 41%

intensive lifestyle 

program modeled 

after Diabetes 

Prevention 

Program tailored 

to medically 

underserved

McGowan, 

2011

Canada

I= 169

AC= 152

I= 55±12y

46%, 22%

80±15kg

6.8±1.2%, NR

AC= 59±12y

45%, 18%

83±19kg

7.1±1.5%, NR

I= DSME; 2-day 

DM education and 

Stanford Chronic 

Disease Selfmanagement 

Program

AC= 2-day DM 

education

I= 1.5m; 8, 27+h; 

NA

AC= 0.06m; 2, 

6+h; NA

I= In-person

AC= Inperson

I= Group

AC= Group

I= Non-HCP (lay 

program leaders) 

& 

Multidisciplinary 

(RN, RD)

AC= 

Multidisciplinary 

(RN, RD)

I= Minimal –

Content & 

Delivery

AC= Minimal 

– Content 

I= Yes 

AC= 

None/NR

Miller, 2014

U.S. (OH)

I= 32

AC= 36

I= 54.0±7.0y

36%, 28%

36.2±1.2kg/m2

8.3±0.3%, 0%

AC= 53.9±8.2y

37%, 18.5%

36.2±1.2kg/m2

8.5±0.2%, 0%

I= DSME; Smart 

Choices

AC= Mindfulnessbased Eating 

Awareness 

Program with 

guided meditation

I= 6m; 12, 28h; 

NA

AC= 6m; 12, 

28h; NA

I= In-person

AC= Inperson

I= Group

AC= Group

I= HCP (RD)

AC= 

Multidisciplinary 

(RD, social 

worker)

I= Minimal –

Content & 

Delivery

AC= Minimal 

– Content & 

Delivery

I= 

None/NR

AC= 

None/NR

Moncrieft, 2013 

(Fl)

I = 54

UC = 57

I= 54.8±8.3y

35.1%, 100%

32.2±3.7kg/m2

7.7±1.4%, NR

UC= 54.8±6.3y

Lifestyle; 

Community 

Approach to 

Lifestyle 

Modification for 

Diabetes (CALM12m; 17; 26+h; 

9m

Plus brief 

telephone 

contact between 

Mixed Mixed Non-HCP 

(psychologist 

trainee)

I= Minimal –

Content

I = 

None/NR
F

-39

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

22.2%, 91%

32.9±5.4kg/m

2

7.8±1.2%, NR

D) with diet, PA 

and stress 

management 

training

sessions

Moriyama, 

2009

Japan

I= 50

UC= 25

I= 66.4±9.2y

40%, NR

60.0±11.0kg

7.5±1.5%, 7%

UC= 65.2±8.5y

57%, NR

60.7±11.2kg

7.4±1.7%, 17%

DSME; Cognitive-

behavior theory-

based program 

focused on diet, 

PA and family 

support

12m; 12+24 

telephone 

followups, 

6h+telephone 

call duration; NA

Mixed Individual

(Plus family 

provided 

information)

HCP (RN) Moderate-to-

High –

Content & 

Delivery

None/NR

Muchmore, 

1994

U.S. (CA)

I

1= 12

I

2= 11

I

1= 57.3±2.3y

33%, NR

89.5±5kg

10.3±0.3%, 0% I2= 60.1±2.2y

45%, NR

99±5kg

10.45±.04%, 

0%

I

1= Lifestyle; 

behavioral weight 

loss program plus 

basic DM diet 

education

 I

2= Lifestyle; 

behavioral weight 

loss program plus 

diet and blood 

glucose regulation 

intervention 

I

1= 6.5m; 23, 

22+; 3.7m I2= 6.5; 23, 22+; 

3.7m

I

1= In

-person

I

2= In

-person

I

1= Mixed

I

2= Mixed

I

1= 

Multidisciplinary 

(RN, RD) I2= 

Multidisciplinary 

(RN, RD)

I

1= Minimal 

–

Content I2= Moderate

-

to-High -

Content

I

1= 

None/NR I2= 

None/NR

Murrock, 2009

U.S. (OH)

I= 36

UC= 34

I= 58.5±12.2y

0%, 100%

94.8±26.9kg

7.7±1.2%, 21%

UC= 67.1±7.9y

0%, 100%

Lifestyle; dance 

and peer support 

for African 

American women

2.8m; 24, 

24+social 

support activity 

duration; NA

In-person Group Non-HCP 

(African 

American dance 

instructor) & HCP 

(RN)

Moderate-to-

High –

Content & 

Delivery

Yes
F-40

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

96.5±20.8kg

7.4±0.1%, 21%

Nishita, 2013

U.S. (HI)

I= 128

UC= 62

I= 47.6±.09y

34.4%, 68.7%

32.4±0.7kg/m2

7.8±0.2%, NR

UC= 50.±1.2y

43.6%, 74.2%

34.2±1.1kg/m2

7.7±0.2%, NR

DSME; life 

coaching and 

pharmacist 

counseling using 

empowerment 

approach for 

employed adults

12m; 14.0, 13h; 

NA

(Plus nutritional 

counseling as 

appropriate)

In-person Individual Non-HCP 

(graduates of 

social sciences 

degrees) & HCP 

(Pharmacist)

Moderate-toHigh –

Content & 

Delivery

Yes

Palmas, 2014

U.S. (NY)

I= 181

Att. C= 

179

I= 57.1±7.7y

39.2%, 100%

NR

8.8±1.7%, NR

Att. C= 

58.1±7.8y

37.4%, 100%

NR

8.5±1.6%, NR

I= DSME + 

Support; CHW-led 

intervention 

focused on 

problem solving 

and negotiating 

healthcare

Att. C= mailed 

information and 4 

telephone 

contacts

I= 12m; 13, 4.6h; 

9m

Att. C= 12m; 4+4 

mail-outs, 0.7h; 

NA

I= Mixed

Att. C= 

Technology

I= Mixed

Att. C= 

Individual

I= Non-HCP 

(CHW)

Att. C= Non-HCP 

(research 

assistant)

I= Moderateto-High –

Content & 

Delivery

Att. C= None

I= Yes

Att. C= 

None

PhilisTsimikas, 2011

U.S. (CA)

I= 104

UC= 103

I= 49.2±11.8y

25.2%, 98.1%

32.1±5.9kg/m2

10.3±1.7%, NR

UC= 52.2±9.6y

33.7%, 94.2%

I= DSME + 

Support; Project 

Dulce, peer-led 

diabetes 

education 

program for highrisk Mexican 

10m; 12, 16h; 8m In-person 

(Plus 

telephone 

reminders)

Group Non-HCP 

(Promotores)

Moderate-toHigh –

Content & 

Delivery

Yes
F-41

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

30.9±6.3kg/m2

10.5±1.7%, NR

Americans

Plotnikoff, 2011

Canada

I1= 49

I2= 47

I1= 60 (25-75)y

40%, NR

34.3±5.7kg/m2

7.8±2.2%, NR

I2= 60 (25-75)y

40%, NR

34.8±9.0kg/m2

7.3±1.3%, NR

(Mean, Range)

I1= DSME + 

Support; 

I2= DSME + 

Support; addition 

of individualized 

PA counseling 

with continual 

telephone support

I1= 12m; 11, 

16.5h+; 11m

I2= 12m; 32, 

17.5h+time for 

telephone 

counseling; 10m

I1= In-person

I2= Mixed

I1= Group 

I2= Mixed

I1= HCP (CDE)

I2= Non-HCP 

(certified 

personal trainers) 

& HCP (CDE)

I1= Minimal –

Content

I2= Moderateto-High –

Content & 

Delivery

I1= 

None/NR

I2= Yes

Prezio, 2013

U.S. (TX)

I= 90

UC= 90

I= 47.9±11.0y

33.3%, 77.8%

32.7±7.8kg/m2

8.9±2.2%, NR

UC= 45.7±10.7y

45.6%, 70%

33.9±8.2kg/m2

8.7±2.3%, NR

DSME + Support; 

Community 

Diabetes 

Education (CoDE)

for uninsured 

Mexican 

Americans

12m; 7, 7h; 10m In-person Individual Non-HCP (CHW) Moderate-toHigh –

Content & 

Delivery

Yes

Reaney, 2013

Germany & 

Spain (33 

sites)

I= 330

UC= 351

I= 62±9.6y

54.2%, NR

31.2±5.4

7.2 (6.5-8.0)%, 

47%

UC= 61.9±8.7y

52.4%, NR

31.7±5.9kg/m2

7.0 (6.4-7.8)%, 

I= DSME; group 

DSME using 

Conversation 

Maps tools EU 

version

1.5m; 4, 8-12h; 

NA

In-person Group HCP (trained 

diabetes 

educator as per 

usual care at 

sites)

Minimal -

Content

None/NR
F-42

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

41.9%

(Mean, IQR) 

Rickheim, 2002

U.S. (MN)

I1= 87

I2= 83

I1= 51.6±9.2y

35.6%, 3.6%

33.8±6.1kg/m2

8.9±1.9%, 0%

I2= 52.9±12.8y

32.5%, 10.5%

34.9±6.5kg/m2

8.0±1.9%, 0%

I1= DSME; group 

education meeting 

National 

Standards and 

informed by an 

integrated data 

evaluation system

I2= DSME; 

individual 

education meeting 

National 

Standards and 

informed by an 

integrated data 

evaluation system

I1= 6m; 4, 7h; NA

I2= 6m; 4, 5h; NA

I1= In-person

I2= In-person

I1= Group

I2= Individual

I1= 

Multidisciplinary 

(RD, RN)

I2= 

Multidisciplinary 

(RD, RN)

I1= Minimal –

Content 

I2= Minimal –

Content 

I1= 

None/NR

I2= 

None/NR

Ridgeway, 

1999

U.S. (TN)

I= 28

UC= 28

I= 62y

33%, NR

88±16kg

12.3±2.2%, 

17%

UC= 65y

25%, NR

84.8±17kg

12.3±3.0%, 

15%

DSME; Life Skills 

program with 

behavioral training

12m; 7, 10.5h; 

NA

(Plus telephone 

reminders)

In-person Mixed Multidisciplinary 

(RD, RN CDEs 

with some 

physician contact 

)

Minimal –

Content & 

Delivery

None/NR

Rock, 2014 I1= 74 I1= 55.5±9.2y I1= Lifestyle; I1 & I2= 12m; 41, I1 & I2= In- I1 & I2= I1 & I2= Non-HCP I1 & I2= I1 & I2= 
F-43

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

U.S. (CA, MN) I2= 77

Att. C= 76

52.7%, 20.3%

36.2±4.3kg/m2

7.4±1.1%, 18%

I2= 57.3±8.6y

52.0%, 18.2%

36.2±4.7kg/m2

7.3±1.4%, 18%

Att. C= 

56.8±9.3y

42.1%, 22.4%

36.3±4.4kg/m2

7.4±1.1%, 18%

weight loss 

program 

incorporating lowfat diet with meal 

replacements

I2= Lifestyle; 

weight loss 

program 

incorporating lowcarbohydrate diet 

with meal 

replacements

Att. C= two oneto-one weight loss 

sessions with 

materials, tracking 

program and 

monthly check-in

NR; 3m 

(Plus telephone 

availability)

Att. C= 12m; 2, 

2h; NA

(Plus monthly 

telephone checkins)

person 

(Plus 

telephone 

availability 

but use NR)

Att. C= 

Individual 

(Plus 

telephone 

check-ins)

Individual

Att. C=

Individual

(weight loss 

counselors)

Att. C= HCP 

(RD)

Minimal –

Content & 

Delivery

Att. C= None

None/NR

Att. C=

None/NR

Rosal, 2005

U.S. (MA)

I= 15

UC= 10

I= 62.7±8.1y

20%, 100%

32.4±4.5kg/m2

7.7±1.2%, 40%

UC= 62.4±9.7y

20%, 100%

32.7±7.4kg/m2

9.3±1.8%, 70%

DSME; 

community-based, 

literacy and 

culturally tailored 

program for lowincome Spanishspeaking 

individuals of 

Puerto Rican 

heritage

3m; 13, 26.5-

31.5h; NA

In-person Mixed Multidisciplinary 

(RN, RD)

Moderate-toHigh –

Content & 

Delivery

Yes
F-44

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Rosal, 2011

U.S. (MA)

I= 124

UC= 128

I= 18 - >65y

21.8%, 100%

34.5±6.5kg/m2

8.9±1.8%, 

42.8%

UC= 18 - >65y

25%, 100%

34.5±6.5kg/m2

9.1±2.0%, 

54.7%

DSME + Support; 

Latinos en 

Control, 

community-based, 

culturally tailored 

self-management 

intervention for 

low-income, 

Spanish-speaking 

Latinos

12m; 21, 51h; 8m

(Plus telephone 

reminders) 

In-person Mixed with 

supports

Non-HCP 

(trained lay 

person) & HCP 

(RD, health 

educator) 

Moderate-toHigh –

Content & 

Delivery

Yes

Rosal, 2014

U.S. (MA)

I1 = 43

 I2 = 46

I1= 52±11y

0%, 100%

34.4±8.0kg/m2

9.4±2%, 53.5%

I2= 53±10y

0%, 100%

36.4±8kg/m2

9.6±2%, 45.7

I1 = DSME; 

Adaptation of 

Power to Prevent

I2 = DSME; 

Virtual adaptation 

of Power to 

Prevent

I1 = 2m; 8, 12h; 

NA 

I2 = 2m; 8, 12h; 

NA

I1 = Inperson

I2 = 

Technology

I1 = Group 

I2 = Group

I1 = 

Multidisciplinary 

(RD [CDE], NP)

I2 = 

Multidisciplinary 

(RD [CDE], NP)

I1 = Moderateto-high -

Content, 

I2 = Moderateto-high –

Content and 

Delivery

I1 = 

None/NR

I2 = 

None/NR

Rothschild, 

2014

U.S. (IL)

I= 73

Att. C= 71

I= 53.7±11.7y

35.6%, 100%

32.7±7.4kg/m2

8.5±2.2%, 

19.2%

Att. C= 

53.6±12.7y

29.6%%, 100%

34.2±9.5kg/m2

8.1±1.6%, 

12.7%

I= DSME + 

Support; Mexican 

Americans Trial of 

Community Health 

Workers (MATCH)

providing in-home 

self-management 

training

Att. C; 36 mailed 

bilingual diabetes 

self-management 

I= 24m; 36, 54h; 

12m

Att. C = 24m; 36, 

Oh; NA

I= In-person

Att. C= mail 

only

I= Individual

Att. C= NA

I= Non-HCP 

(CHW)

Att. C= NA

I= Moderateto-High –

Content & 

Delivery

Att. C= 

Minimal -

Content

I= Yes

Att. C= 

None/NR
F-45

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

newsletters

Ruggerio, 2010

U.S. (IL)

I= 25

UC= 25

All participants=

65.8±9.4y

34%, 100%

32.4±6.6kg/m2

HbA1c:

I= 8.5±1.7%

UC= 8.9±1.6%

Insulin use NR

DSME; Medical 

assistant self-care 

coaching 

intervention using 

empowerment 

approach for lowincome 

racial/ethnic 

minorities

6m; 6, 2h; NA

(Plus telephone 

reminders)

Mixed Individual Non-HCP 

(certified medical 

assistants)

Moderate-toHigh –

Content & 

Delivery

Yes

Ruggerio, 2014

U.S. (IL)

I= 136

UC= 134

I= 53.2±11.7y

32.1%, 100%

33.0±6.4kg/m2

8.7±2.4%, NR

UC= 53.1±13.0y

30.3%, 100%

33.4±6.4kg/m2

8.5±2.3%, NR

DSME; Medical 

assistant self-care 

coaching 

intervention using 

empowerment 

approach for lowincome 

racial/ethnic 

minorities

12m; 12, 4h; NA Mixed Individual Non-HCP 

(certified medical 

assistants)

Moderate-toHigh –

Content & 

Delivery

Yes

Sacco, 2009

U.S. (FL)

I= 31

UC= 31

All participants 

=

52±8.6y

42%, 22.6%

35.8±7.7kg/m2

8.5±1.7%, 53%

DSME; brief CBTbased coaching 

telephone 

intervention 

delivered by 

paraprofessional 

for T2DM ≥1 

cardiovascular risk 

factors

6m; 16, 6h; NA Mixed (1 inperson 

session)

Individual Non-HCP 

(undergraduate 

psychology 

students)

Minimal –

Content & 

Delivery

None/NR

Salinero-Fort, 

2011

Spain

I1= 304

I2= 304

I1= 67.3±19y

51%, NR

30.5±5.2kg/m2

I1= DSME; 

Conventional 

Health Promotion 

I1= 24m; 10, 

6.7h; NA

I1= In-person

I2= In-person

I1= Individual

I2= Individual

I1= HCP (RN)

I2= HCP (RN)

I1= Minimal –

Content & 

Delivery

I1= 

None/NR
F

-46

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

7.4±1.2%, 

14.4% I2= 66.1±8y

46%, NR

29.6±4.6kg/m

2

7.1±1.3%, 

14.2% 

Education as per 

Spanish 

recommendation I2 = DSME; PRECEDE model 

focusing on 

predisposing, 

enabling and 

reinforcing factors 

for behaviors 

identified via 

assessment

I

2= 24m; 10, 

6.7h; NAI

2

= Moderate-

to-High –

Content & 

Delivery

I

2= 

None/NR

Samuel-

Hodge, 2009

U.S. (NC)

I= 117

UC= 84

I= 57.0y

36%, 100%

34.6kg/m

2

7.7%, 51%

UC= 61.3y

37%, 100%

35.1kg/m

2

7.9%, 38%

DSME + Support; 

church-based 

diabetes self-

management 

program for 

African Americans

12m; 25, 

19h+telephone 

call time;4m 

Mixed Mixed Non-HCP 

(church health 

advisor) & 

Multidisciplinary 

(RD, other HCP)

Moderate-to-

High –

Content & 

Delivery

Yes

Sarkadi, 2004

Sweden

I= 39

UC= 38

I= 66.4±7.9y

NR, NR

27.2±3.6kg/m

2

6.5+_0.5%, NR

UC= 66.5±10.7y

NR, NR

28.6±5.8kg/m

2

6.5±0.5%, NR

DSME; 

pharmacist-led, 

experience and 

empowerment-

based group 

education

12m; 12, NR; NA In-person Group HCP 

(Pharmacist)

Moderate-to-

High -

Content

None/NR

Sevick, 2012 I= 147 I= 25 - >75y I=DSME; SCT- I= 6m; 14, NR; I= In-person I= Group I= I= Moderate- I= 
F-47

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

U.S. (PA) Att. C= 

149

29.0%, 31.3%

34.0±7.3kg/m2

7.7±2.2%, NR

Att. C= 25 -

>75y

34.8%%, 28.8%

35.1±7.7kg/m2

7.5±1.7%, NR

based intervention 

with technologybased selfmonitoring of 

SNBG, diet and 

PA

Att. C= basic 

group education 

and mailed 

magazines; also 

received meter 

and pedometer

NA

Att. C= 6m; 3, 

NR:NA

Att. C= Inperson Att. C= 

Group

Multidisciplinary 

(RD, RN)

Att. C= HCP 

(RN)

to-High –

Content

Att. C= None

None/NR

Att. C= 

None/NR

Shibayama, 

2007

Japan

I= 67

UC= 67

I= 61±8y

65.2%, NR

26±5kg/m2

7.4±0.7%, 0%

UC= 62±7y

65.2%, NR

26±5kg/m2

7.4±0.7%, 0%

DSME; nurse-led 

DSME

12m; 12, 5.5h; 

NA

In-person Individual HCP (RN) Moderate-toHigh –

Content & 

Delivery

None/NR

Sigurdardottir, 

2009

Iceland

I= 30

UC= 28

I= 57.8±10.9y

64%, NR

31.5±5.1kg/m2

8.1±0.9%, 39%

UC= 63.5±9.3y

72%, NR

32.7±5.0kg/m2

7.9±8.9%, 20%

DSME; nurse-led 

empowerment 

approach using 

self-completed 

instruments on 

self-care and 

quality of life

1.5m; 6, 2.3-

3.7h; NA

Mixed Individual HCP (RN) Moderate-toHigh –

Content & 

Delivery

None/NR

Siminerio, I1= 32 I1= 60±12y I1= DSME; I1= 6m; NR, NR; I1= In-person I1= Individual I1= HCP (CDE) I1= Moderate- I1= 
F

-48

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

2013

U.S. (PA)

I

2= 35

I

3= 36

I

4= 38

47%, 22%

34.6±6.1

8.7±1.9%, NR I2= 60±13.4y

40%, 20%

36.2±8.2kg/m

2

9.0±2.1%, NR I3= 64±10y

47%, 14%

34±8.7kg/m

2

8.6±2.4%, NR I4= 60±10y

42%, 13%

35.7±8.8kg/m

2

8.3±1.8%, NR

empowerment 

based DSME, 

PRISM (Program 

Reinforcement 

Impacts Self-

Management) I2= DSME + 

Support; DSMS by 

practice staff I3= DSME + 

Support; DSMS by 

peer I4= DSME + 

Support; DSMS 

support by 

educator

NAI2= 6m; 

1.2+DSME, 

0.25h+DSME; 

4.5m I3= 6m; 

5.0+DSME, 

2.25h+DSME; 

4.5m I4= 6m; 

5.1+DSME, 

1.5h+DSME; 

4.5m

I

2= Mixed

I

3= Mixed

I

4= Mixed

I

2= Individual

I

3= Individual

I

4= Individual

I

2= Non

-HCP 

(medical 

assistant or LPN) 

& HCP (CDE) I3= Non-HCP 

(peer) & HCP 

(CDE) I4= HCP (CDE)

to-High –

Content & 

Delivery I2= Moderate

-

to-High –

Content & 

Delivery I3= Moderate

-

to-High –

Content & 

Delivery I4= Moderate

-

to-High –

Content & 

Delivery

None/NR I2= 

None/NR I3= Yes I4= 

None/NR

Sinclair, 2013

U.S. (HI)

I= 48

UC= 34

I= 53±12y

37%, 100%

36±12kg/m

2

9.9±2.0%, 56%

UC= 55±10y

38%, 100%

38±8kg/m

2

9.8±2.2%, 46%

DSME; Partners in 

Care; community-

based, culturally 

adapted CBT-

based DSME 

delivered by peers

for Hawi'i Natives 

and Pacific 

Islanders

3m; 12, 12h; NA In-person Group Non-HCP (peer) Moderate-to-

High –

Content & 

Delivery

Yes

Sixta, 2008

U.S. (TX)

I= 68

UC= 63

I= 54.5 (30-77)y

29%, 100%

NR

DSME; 

promotores-led 

culturally sensitive 

2.3m; 10, 15h; 

NA

In-person Group Non-HCP 

(Promotores)

Moderate-to-

High –

Content & 

Yes
F-49

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

7.32%, NR

UC= 52.8 (26-

81)y

29%, 100%

NR

7.65%, NR

(Mean, Range)

DSME for 

underserved 

Hispanic 

Americans

Delivery

Skelly, 2005

U.S. (NC)

I= 23

UC= 18

(Analyzed)

I= 60.5±9.0y

0%, 100%

NR

9.2±2.5%, 

26.1%

UC= 63.7±10.8y

0%, 100%

NR

9.0±2.8%, 

16.7%

DSME; symptomfocused teaching 

and counseling 

intervention for 

rural older African 

American women

2m; 4, 4h; NA In-person Individual HCP (RN) Moderate-toHigh –

Content & 

Delivery

None/NR

Skelly, 2009

U.S. (NC)

I1= 60

I2= 60

AC= 60

I1= 65y 

(Median)

0%, 100%

NR

8.3±1.6%, 18%

I2= 68.5y 

(Median)

0%, 100%

NR

8.4±1.6%, 17%

I1= DSME; 

symptom-focused 

teaching and 

counseling 

intervention for 

rural older African 

American women

I2= DSME + 

Support; 

symptom-focused 

teaching and 

I1= 2.8m; 4, 4h; 

NA

I2= 8.6m; 8, 5h; 

5.8m

AC= 2.8m; 4, 4h; 

NA

I1= In-person

I2= Mixed

AC= Inperson

I1= Individual 

with family

I2= Individual 

with family

AC= 

Individual

I1= HCP (RN)

I2= HCP (RN)

AC= HCP (RN)

I1= Moderateto-High –

Content & 

Delivery

I2= Moderateto-High –

Content & 

Delivery

AC= Minimal 

– Content & 

I1= 

None/NR

I2= 

None/NR

AC= 

None/NR
F-50

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

AC= 68y 

(Median)

0%, 100%

NR

8.1±1.6%, 17%

counseling 

intervention for 

rural older African 

American women 

with telephone 

booster sessions

AC= skills-based 

weight 

management 

program focused 

on diet education 

Delivery

Smith, 1997

U.S. (AL)

I1= 10

I2= 6

(Analyzed)

All participants: 

62.4±7.0y

0%, 41%

34.7±4.9kg/m2

10.25±2.2%, 

0% 

I1= Lifestyle; 

behavioral weightcontrol program 

for older obese 

women

I2= Lifestyle; 

behavioral weightcontrol program 

for older obese 

women with MI

I1= 4m; 16, NR; 

NA

I2= 4m; 19, NR; 

NA

I1= In-person

I2= In-person

I1= Group

I2= Mixed

I1= 

Multidisciplinary 

(RD, Psych, 

exercise 

physiologist)

I2= 

Multidisciplinary 

(RD, Psych, 

exercise 

physiologist) –

Psych for MI

I1= Minimal –

Content

I2= Moderateto-High –

Content & 

Delivery

I1= 

None/NR

I2= 

None/NR

Sorkin, 2014

U.S. (CA, 

I = 53

UC = 36

All participants:

52.7±6.9y

0%, 100%

NR, NR, NR

I = Lifestyle; 

United for Life 

(Unidas por la 

vida) modeled 

after DPP but 

community-based 

for Latino women 

(Mothers with 

I = 4m; 16, NR; 

NA

Mixed Mixed with 

supports

Non-HCP (CHW 

“Community 

Lifestyle 

Coaches”)

I = Moderateto-high –

Conent and 

Delivery

I = 

Present
F-51

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

T2DM and their 

daughters) 

Spencer, 2011

U.S. (MI)

I= 84

UC= 84

I= 50 (47, 52)y

25%, 100%

34 (32, 

36)kg/m2

8.6 (8.0, 9.1)%, 

27%

UC= 55 (53, 

57)y 33%, 

100%

35 (33, 

37)kg/m2

8.5 (8.0, 8.9)%, 

29%

(95% CI)

DSME; culturally 

tailored, 

behavioral theorybased CHW 

intervention for 

African Americans 

and Latinos

6m; 14 & 

biweekly 

telephone calls, 

24h plus 

telephone 

contact time; NA

Mixed Mixed Non-HCP (CHW) Moderate-toHigh –

Content & 

Delivery

Yes

Sperl-Hillen, 

2013

U.S. (NM, MN)

I1= 246

I2= 243

UC= 134

I1= 61.6±10.9y

50.4%, 37.3%

34.4±8.0 kg/m2

8.1%, NR

I2= 61.2±11.8y

49%, 33.5%

34.4±7.0 kg/m2

8.1%, NR

UC= 63.3±1.5y

53.7%, 32.6

34.7±7.7 kg/m2

8.0%, NR

I1= DSME; 

individual DSME

I2= DSME; group 

DSME using U.S. 

Conversation 

Maps

I1= 3m; 3, 3h; NA

I2= 2.5m; 4, 8h; 

NA

I1= In-person

I2= In-person

I1= Individual

I2= Group 

with 

supports

I1= HCP (RN or 

RD CDE)

I2= HCP (RN or 

RD CDE)

I1= Minimal –

Content

I2= Moderateto-High –

Content & 

Delivery

I1= 

None/NR

I2= 

None/NR
F

-52

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Steed, 2005

United 

Kingdom

I= 65

UC= 59

I= 59.2±8.8y

67.7%, 47.7%

NR

8.2±1.3%, NR

UC= 60.3

±8.6y

74.6%, 56.2%

NR

8.6±1.8%, NR

DSME; University 

College London 

diabetes self-

management 

programme (UCL-

DSMP)

3m; 6, 15h; NA In-person Group HCP (DSN) Minimal -

Content

None/NR

Sung, 2012

Korea

I= 22

UC= 18

I= 70.2±4.7y

31.8%, NR

23.9kg/m

2

7.6±1.1%, 

31.8%

UC= 70.1

±3.6y

38.9%, NR

25.5kg/m

2

7.6±1.4%, 

44.4%

Lifestyle; 

Supervised 

walking program 

with basic 

education for the 

elderly

6m; 34, 24h; NA In-person Mixed NR Moderate-to-

High–

Content

None/NR

Tang, 2014

U.S. (MI)

I

1= 56

I

2= 60

I

1= 48.4

±10.0y

35.7%, 100%

32.0±4.6kg/m

2

7.8±1.7%, 25%

I

2= 50.2±11.2y

46.7%, 100%

33.0+/-7.6kg/m

2

8.2±2.2%, 20%

I

1= DSME + 

Support; CHW-led

Partners in Care &

DSMS led by 

CHWs for Latinos I2= DSME + 

Support; CHW-led

Partners in Care &

DSMS led by peer 

leaders for Latinos

I

1= 18m; 16.9, 

25.5h; 12m I2= 18m; 17.7, 

26h; 12m

(Per protocol had 

many more contacts in 

DSMS phase) 

I

1= Mixed 

I

2= Mixed 

I

1= Mixed 

with 

supports I2= Mixed 

with 

supports 

I

1= Non

-HCP 

(CHW) I2= Non

-HCP 

(CHW & peers)

I

1= Moderate

-

to-High –

Content & 

Delivery I2= Moderate

-

to-High –

Content & 

Delivery

I

1= Yes

I

2= Yes 
F-53

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Thoolen, 2007

The 

Netherlands

I= 89

UC= 108

I= 62.0±4.9y

64%, NR

NR

NR, NR

UC= 61.9±5.6y

55%, NR

NR

NR, NR

DSME; Beyond 

Good Intentions, 

focused on coping 

and self-regulation 

around diet, 

exercise and 

medications

3m; 6, 10h; NA In-person Mixed HCP (RN) Minimal –

Content & 

Delivery

None/NR

Toobert, 2003

U.S. (OR)

I= 163

UC= 116

I= 61.6±8.0y

0%, 8%

35.1±7.75kg/m2

7.4±1.3%, 

20.4%

UC= 60.7±7.8y

0%, 5.3%

35.6±8.85kg/m2

7.4±1.5%, 

21.6%

Lifestyle; 

Mediterranean 

Lifestyle Program 

(multicomponent

program focusing 

on reduction of 

behavioral CHD 

risk factors of diet, 

PA, social 

support, stress 

management and 

smoking 

cessation)

6m; 29, 124h; NA In-person 

(telephone 

followup for 

missed 

sessions) 

Group Non-HCP (>75%; 

lay leaders & 

RAs) & 

Multidisciplinary 

(RD, Exercise 

physiologist)

Minimal –

Content & 

Delivery

Yes

Toobert, 2011 I= 142

UC= 138

I= 55.6±9.7y

0%, 100%

35.3±7.05kg/m2

8.4±1.9%, 

29.1%

UC= 58.7±10.3y

0%, 100%

33.2±6.75kg/m2

Lifestyle; Viva 

Bien (adaptation 

of Mediterranean 

Lifestyle Program 

for Latinos)

24m; 52, 208h; 

18m

In-person Group with 

supports 

during 

maintenance 

phase

Non-HCP (>75% 

trained bilingual 

facilitators) & 

Multidisciplinary 

(RD, Physician)

Moderate-toHigh –

Content & 

Delivery

Yes
F-54

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

8.2±1.7%, 

32.1%

Trief, 2011

U.S. (NY)

I1= 12

I2= 12

UC= 13

(Analyzed)

I1= 61.1±9.3y

50%, NR

33.0±5.4kg/m2

8.1±1.2%, NR

I2= 60.3±8.6y

41.7%, NR

35.3±7.3kg/m2

8.4±1.4%, NR

UC= 61.1±11.1y

38.5%, NR

35.1±7.2kg/m2

8.2±1.1%, NR

I1= DSME; 

problem-solving 

approach 

delivered via 

telephone to 

individuals

I2= DSME; 

problem-solving 

approach 

delivered via 

telephone for 

couples

I1= 3m; 9, NR; 

NA

I2= 3m; 9, NR; 

NA

I1= 

Technology

I2= 

Technology

I1= Individual

I2= Individual 

with spouse

I1= HCP (CDE)

I2= 

Multidisciplinary 

(CDE, therapist)

I1= Moderateto-High –

Content & 

Delivery

I2= Moderateto-High –

Content & 

Delivery 

I1= 

None/NR

I2= 

None/NR 

Tucker, 2014

U.S. (FL)

I= 64

UC= 

I= NR

27%, 70%

36.1(SE0.3)kg/

m2

NR, NR

UC= NR

25%, 77%

36.2(SE0.3)kg/

m2

NR, NR

DSME; culturally 

sensitive,

empowermentfocused, 

community-based 

health promotion 

program provided 

to racial/ethnic 

minorities

2m; 4, 12h+ 

telephone 

contact time; NA

Mixed Mixed Non-HCP 

(community 

leaders) & 

Multidisciplinary 

(RN, RD, Psych) 

Moderate-toHigh –

Content & 

Delivery

Yes

Utz, 2008

U.S. (VA)

I1= 8

I2= 13

I1= 56.6±14.7y

37.5%, 100%

NR

8.1±1.6%, 25%

I1= DSME; 

Individual DSME

I2= DSME; groupbased, culturally 

I1= 2m; 3, 1h; NA

I2= 2m; 8, 16h; 

NA

I1= In-person

I2= In-person

I1= Individual

I2= Group

I1= HCP (CDE)

I2= HCP (CDE)

I1= Minimal –

Content

I2= Moderateto-High –

I1= Yes

I2= Yes 
F-55

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

I2= 62.4±14.7y

23.1, 100%

NR

8.1±1.4%, 

46.2%

tailored DSME for 

rural African 

Americans 

Content & 

Delivery

Vadstrup, 2011

Denmark

I1= 73

I2= 70 

I1= 58.0±10.3y

60%, NR

98.2 +/- 24.8kg

7.8±0.9%, 14%

I2= 58.5±10.3y

59%, NR

96.2 +/- 15.2kg

7.9±0.8%, 19%

I1= DSME; 

individualized 

counseling 

program with MI

I2= DSME; groupbased 

rehabilitation 

program using an 

empowerment 

approach & 

supervised group 

aerobic exercise 

and resistance 

training

I1= 6m; 8, 6.75h; 

NA

I2= 6m; 33, 53h; 

NA

I1= In-person

I2= In-person

I1= Individual

I2= Group 

with some 

spouse 

involvement

I1= 

Multidisciplinary 

(RN, RD, 

Podiatrist)

I2= 

Multidisciplinary 

(RN, RD, 

Podiatrist, 

Physiotherapist)

I1= Moderateto-High –

Content & 

Delivery

I2= Minimal -

Content

I1= 

None/NR

I2= 

None/NR

Varney, 2014

Australia

I = 47

UC = 47

I= 59 (56-62)y

72%, 2%

32.1 (30.3-33.9) 

kg/m2

8.2 (8.0-9.7)%, 

53%

UC= 64 (61-

66)y

64%, 21%

30.9 (29.1-32.6) 

DSME; telephonic 

health coaching

6m; 6, 2.5h; NA Technology Individual HCP (RD) Moderate-toHigh –

Content & 

Delivery

None/NR
F-56

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

kg/m2

8.5 (8.1-8.9)%, 

62%

All 95% CI

Vazquez, 1998

U.S. (MA)

I= 18

UC= 20

All participants

32-70y

55%, 100%

27-40kg/m2

NR, NR

DSME; Buena 

Alimentacion, 

Buena Salud

(Good Eating, 

Good Health) for 

Caribbean Latinos

3m; 12, NR; NA In-person Group Multidisciplinary 

(RD, Psych)

Moderate-toHigh –

Content & 

Delivery

Yes

Vincent, 2007

U.S. (AZ)

I= 10

UC= 10

I= 56.7±10.6y

11%, 100%

30.6±2.7kg/m2

6.6±1.2%, NR

UC= 55.3±8.2y

50%, 100%

29.8±4.2kg/m2

6.7±1.2%, NR

DSME; culturally 

tailored for 

Mexican 

Americans

2m; 8, 16h; NA

(Plus telephone 

reminders)

In-person 

(with 

telephone 

reminders)

Group with 

supports

Non-HCP 

(Promotores) & 

HCP (not 

specified)

Moderate-toHigh –

Content & 

Delivery

Yes

Walker, 2011

U.S. (NY)

I= 262

UC= 265

I= 55.7±7.4y

31.7%, 94.3%

31.8±6.2kg/m2

8.6 (8.0-9.6)%, 

21%

UC= 55.4±7.2y

34.1%, 93.9%

30.7±6.0kg/m2

8.7 (8.0, 

10.2)%, 25%

DSME; telephonic 

intervention 

focused on 

medication 

adherence and 

lifestyle behaviors 

with socioecological 

approach for lowincome, insured 

urban diabetics 

12m; 7.9±2.1, 2h; 

NA

Technology Individual Non-HCP (health 

educators) 

Moderate-toHigh -

Delivery

None/NR
F-57

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

(Mean, IQR)

Weinger, 2011

U.S. (MA) both 

T1DM & T2DM 

50:50%

I=74

AC1= 75

AC2= 73

I= 51.8 (23.7-

74.2)y

54%, 12%

29.4 (18.6-

51.5)kg/m2

9.0 (7.6-12.6)%, 

55.3%

AC1= 54.7 

(25.0-75.1)y

52%, 11%

29.4 (20.3-57.8)

kg/m2

8.8 (7.6-13.6)%, 

55.3%

AC2= 56.2 

(21.6-74.8)y

42%, 15%

29.0 (17.8-50.4)

kg/m2

8.6 (7.6-13.1)%, 

55.3%

(Median, 

Range)

I= DSME; CBTbased group 

education 

program

AC1= Non-DSME 

(didactic group 

sessions)

AC2= Non-DSME 

(individual RN & 

RD consults 

offered)

I= 1.5m; 5, 10h; 

NA

AC1= 1.5; 5, 10h; 

NA

AC2= 6m; NR, 

NR; NA

I= In-person

AC1= Inperson

AC2= Inperson

I= Group

AC1= Group

AC2= 

Individual 

I= 

Multidisciplinary 

(RN, RD)

AC1= RN

AC2= 

Multidisciplinary 

(RN, RD)

I= Minimal –

Content

AC1= Minimal 

– Content

AC2= Minimal 

– Content & 

Delivery

I= 

None/NR

AC1= 

None/NR

AC2= 

None/NR

Welch, 2011

U.S. (MA)

I1=58

I2=57

Only 2 of 

4 arms –

not 

I1= 54.4±10.3y

37.9%, 21%

34.9±6.7kg/m2

8.8±1.3%, 

40.4%

I1= DSME; 

standard

I2= DSME; 

standard with MI 

I1= 6m; 4, 2.5h; 

NA

I2= 6m; 4, 2.5h; 

NA

I1= In-person

I2= In-person

I1= Individual

I2= Individual

I1= HCP (CDE)

I2= HCP (CDE)

I1= Minimal –

Content &

Delivery 

I2= ModerateI1=

None/NR

I2= 

None/NR
F

-58

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

reporting 

on arms 

adding 

computer 

summary 

of 

barriers)

I

2= 54.9±9.3y

42.1%, 14%

34.1±5.6kg/m

2

9.1±1.5%, 

31.6%

counseling and 

tools by CDEs

to-High –

Content & 

Delivery

Welschen, 

2013

Netherlands

I= 78

UC= 76

I= 60.5±9.4y

59.5%, 2.7%

31.6±5.7kg/m

2

6.8±1.0, NR

UC= 61.2±8.8y

64.2%, 5.1%

31.5±5.2kg/m

2

6.8±1.0%, NR

Lifestyle; CBT-

based intervention 

with problem-

solving training for 

diet, PA, smoking 

cessation

6m; 3±1.7, 1.5h; 

NA

In-person Individual Multidisciplinary 

(RN, RD)

Moderate-to-

High- Content 

& Delivery 

None/NR

West, 2007

U.S. (AL)

I

1= 108

I

2= 109

I

1= 52±10y

0%, 38% 

36.5±5.4kg/m

2

7.6±1.4%, 0% I2= 54±10y

0%, 39%

36.5±5.5kg/m

2

7.5±1.4%, 0%

I

1= Lifestyle; 

behavioral weight 

control program I2= Lifestyle: 

behavioral weight 

control program + 

MI

I

1= 18m; 47, NR; 

12m I2= 18m; 47, NR; 

12m

I

1= In

-person

I

2= In

-person

I

1= Mixed

I

2= Mixed

I

1= 

Multidisciplinary 

(RD, CDE, 

behaviorist, 

exercise 

physiologist)

I

2

=

Multidisciplinary 

(RD, CDE, 

behaviorist, 

exercise 

physiologist , 

psychologist)

I

1= Minimal 

–

Content I2= Moderate

-

to-High –

Content & 

Delivery

I

1= 

None/NR I2= 

None/NR

Wierenga, 

1994

I= 35

UC= 31

I= 30-86y

NR, 6.1%

Lifestyle; 

behavioral 

1.25m; 5, 7.5h; 

NA

In-person Group HCP (RN) Minimal –

Content

None/NR
F-59

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

U.S. (WI) 28.7±6.9kg/m2

NR, NR

UC=30-86y

NR, 6.1%

28.7±6.9kg/m2

NR, NR

(All except BMI 

for all 

participants)

modification 

program to 

promote gradual 

change

Wing & 

LookAhead 

Study Group, 

2013

U.S. (16 Sites)

I= 2570

AC= 2575

I= 58.6±6.8y

40.6%, 36.9%

35.3±5.7kg/m2

(Male), 36.3±6.2

kg/m2 (Female)

7.2±1.1%, 

15.5% 

AC= 58.9±6.9y

40.3%, 36.7%

35.1± 5.2kg/m2

(Male), 36.6±

6.0kg/m2

(Female)

7.3±1.2%, 

16.5%

I= Lifestyle; 3-

phase intense 

lifestyle 

intervention for 

sustained weight 

loss including 

group and 

individual 

contacts, 

supportive 

sessions, and 

behavioral training

AC= Non-DSME; 

diabetes support 

and education

I= 96+m; 202+, 

86+h; 84m

AC= 96+m; 16+, 

NR; 48+m

I= Mixed

AC= Inperson

I= Mixed

AC= Group

I= Non-HCP (RA) 

& HCP (lifestyle 

counselors of 

various 

disciplines)

AC= HCP 

(educator with 

background in 

DM education, 

exercise or 

nutiriton)

I= Moderateto-High –

Content & 

Deli very

AC= Minimal 

– Content & 

Delivery 

I= 

None/NR

AC= 

None/NR

Wolever, 2010

U.S. (NC)

I= 30

UC= 26

I= 53.1±8.3y

27%, 66%

NR

7.7±1.9%, NR

DSME; integrative 

health coaching 

using Wheel of 

Health

6m; 14, 7h Technology Individual Non-HCP 

(trainees in social 

work or 

psychology)

Moderate-toHigh - 

Content & 

Delivery

None/NR
F

-60

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

UC= 52.8±7.6y

19%, 54%

NR

8.2±1.9%, NR 

Wolf, 2004

U.S. (VA)

I= 74

UC= 73

I= 53.5±8.6y

38%, 15%

37.6±7.7kg/m

2

7.9±1.6%, 26%

UC= 53.4±8.0y

42%, 26%

37.5±6.4kg/m

2

7.5 ±1.5%, 22%

Lifestyle; 

Dietician-led 

lifestyle case 

management with 

structured medical 

nutrition therapy 

and basic 

education on diet 

and PA

12m; 12 + 

monthly 

telephone 

contacts, 10h + 

monthly 

telephone 

support

Mixed Group HCP (RD) Minimal –

Content and 

Delivery

None/NR

Yoo, 2007

Korea

I= 30

UC= 30

I= 55.3±7.6y

32%, NR

26.1±4.1kg/m

2

8.7±1.3%, 0%

UC= 55.3±7.6y

35%, NR

26.1±4.1kg/m

2

8.7±1.3%, 0%

Lifestyle; lifestyle 

modification 

program using 

self-efficacy 

approach with 

stress 

management 

training

13m; 25, 25h; 9m In-person Group HCP (RN) Minimal-

Content

None/NR

Yuan, 2014

Hong Kong

I = 36

UC = 40

I= 58.9±8.4y

39%, NA

23.8±4.6kg/m

2

6.97±0.9%, NR

UC= 57.8±8.2y

30%, NA

25.4±4.7kg/m

2

7.04±1.0%, NR

DSME; meeting 

standards but no 

identified 

behavioral 

approach 

2m; 8, 16h; NA In-person Group HCP (RD) Minimal-

Content

None/NR
F-61

Author, Year & Country

Comparison & Sample Size(Number randomized unless NR then # analyzed)Age, Male, Non-White, 

BMI/KG, HbA1c, Insulin 

TreatmentIntervention Category & DescriptionTotal Duration Including all Phases (m); Intensity (# contacts, total contact time); Maintenance/Support Phase DurationMethod of Communication (In-person, Mixed, Technology)Method of Delivery (Individual, Group, Mixed) & Presence of Supports

Delivery Personnel (NonHCP, Single HCP,Multidisciplinary)Degree of Tailoring Community Engagement

Zgibor, 2014 I1= 102

I2= 119

I1= 64.5y

33.3%, 3.9%

34.3kg/m2

7.4%, 35.0%

I2= 61.7y

38.7%, 2.5%

35.3kg/m2

7.6%, 30.0%

I1= DSME + 

Support; 

traditional DSME 

and support by 

CDE

I2= DSME + 

Support; DSME 

and support with 

peer leader 

I1= 13.5m; 16, 

NR; 12m

I2= 13.5m; 16, 

NR; 12m

I1= Mixed

I2= Mixed

I1= Mixed

I2= Mixed

I1= HCP (RN 

CDE)

I2= Non-HCP 

(peer) & HCP 

(RN CDE)

I1= Minimal - 

Content & 

Delivery

I2= Moderateto-High - 

Content & 

Delivery

I1= 

None/NR

I2= Yes

AC=active control; Att. C=attention control; CDE=certified diabetes educator; CHW=Community health worker; DSME=diabetes self-management education; DSMS=diabetes 

self-management support; DSN=diabetes specialist nurse; EU=European Union; GP=general practitioner; h=hour; HCP=health care professional; I=intervention (behavioral 

program); LPN=Licensed practical nurse; m=month; MI=motivational interviewing; NA=not applicable; NP=Nurse practitioner; NR=not reported; PA = physical activity; 

Psych=Psychologist; RD=registered dietitian; RN-registered nurse; SE=standard error; UC=usual care
G-1

Appendix G. Type 1 Diabetes Mellitus: Summary of 

Results From Observational Studies

Table G1. Summary of results from observational studies

Study, Year (#

Subjects)

Outcome Timepoint Results Conclusion

Thomas-Dobersen, 

1993 (20 youth)

HbA1c EOI MD, -0.50; 95% CI -1.84 to 0.84 No difference

Thomas-Dobersen, 

1993 (20 youth)

HbA1c 12m followup MD, 0.67; 95% CI -1.47 to 2.81 No difference

Thomas-Dobersen, 

1993 (20 youth)

Depression EOI SMD, -.43; 95% CI -0.84 to 0.75 No difference

Thomas-Dobersen, 

1993 (20 youth)

Depression 12m followup SMD, 0.05; 95% CI -0.86 to 0.96 No difference

Thomas-Dobersen, 

1993 (20 youth)

BMI EOI MD, 0.29; 95% CI -1.06 to 0.48 No difference

Thomas-Dobersen, 

1993 (20 youth)

12m followup MD, -0.27; 95% CI -1.87 to 1.36 No difference

Thomas-Dobersen, 

1993 (20 youth)

Weight EOI MD, -1.13; 95% CI -2.72 to 0.46 No difference

Thomas-Dobersen, 

1993 (20 youth)

12m followup MD, -0.40; 95% CI -4.54 to 3.74 No difference

Thomas-Dobersen, 

1993 (20 youth)

Participant 

attrition

12m RR, 1.64; 95% CI 0.16, 2.46 Increased risk of 

attrition for those 

receiving usual care

Viner, 2003 (41 youth) HbA1c 12m followup MD, -1.20; 95% CI -2.24 to -0.16 Improved for those 

receiving behavioral 

program

Forlani, 2006 (90 

adults)

HbA1c 12m followup MD, -0.70; 95% CI -1.31 to -0.09 Improved for those 

receiving behavioral 

program

Forlani, 2006 (90 

adults)

HRQL 12m followup SMD, 0.31; 95% CI -0.11 to 0.74 No difference

Forlani, 2006 (90 

adults)

HRQLdiabetes 

specific

12m followup SMD, 0.03; 95% CI -0.39 to 0.45 No difference

BMI = body mass index; EOI = end of intervention; m = month; MD = mean difference; QOL = quality of life; RR = risk ratio; 

SMD = standardized mean difference

1. Thomas-Dobersen DA, Butler-Simon N, 

Fleshner M. Evaluation of a weight 

management intervention program in 

adolescents with insulin-dependent diabetes 

mellitus. J Am Diet Assoc. 1993 

May;93(5):535-40. PMID: 8315162.

2. Viner RM, Christie D, Taylor V, et al. 

Motivational/solution-focused intervention 

improves HbA1c in adolescents with type 1 

diabetes: A pilot study. Diabet Med. 2003 

Sep;20(9):739-42. PMID: 12925054.

3. Forlani G, Zannoni C, Tarrini G, et al. An 

empowerment-based educational program 

improves psychological well-being and 

health-related quality of life in type 1 

diabetes. J Endocrinol Invest. 2006 

May;29(5):405-12. PMID: 16794363.
H-1

Appendix H. Strength of Evidence Tables for Type 1 Diabetes Mellitus

Table H1. Behavioral programs compared with usual care: strength of evidence for Key Question 1

Table H2. Behavioral programs compared with an active control: strength of evidence for Key Question 1

Table H3. Behavioral programs compared with usual care: strength of evidence for Key Question 2 (age subgroups)

Table H4. Behavioral programs compared with an active control: strength of evidence for Key Question 2 (age subgroups)
H-2

Table H1. Behavioral programs compared with usual care: strength of evidence for Key Question 1

Outcome # Trials (#

Subjects); Tool if 

Applicable

Risk of 

Bias

Consistency Directness Precision Reporting

Bias

Findings and Direction of Effects Strength of 

Evidence

HbA1c (EOI) 16 (1,155)1-16 Medium Inconsistent Direct Precise UnsuspectedMD, -0.11; 95% CI -0.33 to 0.11 Low

HbA1c (6m) 12 (1,463) 3, 5, 6, 15, 

17-24 Medium Consistent Direct Precise Unsuspected

MD, -0.31; 95% CI -0.47 to -0.15

Favors behavioral programs

Moderate

HbA1c (12m) 7 (1,333) 2, 15, 20-22, 

24, 25

Medium Consistent Direct Imprecise UnsuspectedMD, -0.22; 95% CI -0.49 to 0.05 Low

HbA1c (>12m) 4 (1,138)6, 21, 22, 25 Medium Consistent Direct Imprecise UnsuspectedMD, -0.40; 95% CI -0.92 to 0.12 

(>12m, <24m)

MD, -0.08; 95% CI -1.96 to 1.8 

(≥24m)

Low

Adherence to 

diabetes selfmanagement 

(EOI)

4 (282);3, 5, 8, 18

SMBG

1(74);1 SDSCA

1 (54);15 DSMP

High Consistent Direct Imprecise UnsuspectedMD, 0.15; 95% CI -0.54 to 0.84

MD, 1.4 days; 95% CI 0.35 to 2.43

MD, 5.00; 95% CI 0.60 to 9.40

Low

Adherence to 

diabetes selfmanagement 

(6m)

5 (252);3, 5, 17, 18, 23

SMBG

1 (244);6 SDSCA

2 (471);21, 22

DSMP

High Consistent Direct Imprecise UnsuspectedMD, 0.40; 95% CI -0.36 to 1.16

MD, -0.06; 95% CI -0.60 to 0.48

No difference (different summary 

measures)

Low

Adherence to 

diabetes selfmanagement 

(12m)

1 (54);15 DSMP

1 (180);25 skipping 

one or more 

doses in past 

month 

High Consistent Direct Imprecise UnsuspectedMD, 4.00; 95% CI -1.69 to 9.69

OR, 0.82; 95% CI, 0.48 to 0.1.38

Insufficient

Adherence to 

diabetes selfmanagement 

(≥12m)

1 (390); SMBG

1 (190);25 skipping 

one or more 

doses in past 

month 

High Inconsistent Direct Imprecise UnsuspectedMD, -0.36; 95% CI -0.69 to -0.03 

(≥24m)

OR, 1.30; 95% CI, 0.78 to 2.17 

(24m)

Insufficient

Change in body 

composition 

(BMI) (EOI)(6m)

1 (60)4 Medium Unknown Direct Imprecise UnsuspectedMD, 0.08; 95% CI, -0.35 to 0.51 Insufficient

Change in body 

composition 

(BMI)

1 (227)6 High Unknown Direct Imprecise UnsuspectedMD, -0.21; 95% CI, -0.62 to 0.20 Insufficient

Change in body 

composition (kg)

1 (61)13 High Unknown Direct Imprecise UnsuspectedMD, -0.50; 95% CI, -5.69 to 4.69 Insufficient

Change in 1 (43)13 High Unknown Direct Imprecise Un- MD, 0.59; 95% CI 0.22 to 0.96 Insufficient
H-3

Outcome # Trials (#

Subjects); Tool if 

Applicable

Risk of 

Bias

Consistency Directness Precision Reporting

Bias

Findings and Direction of Effects Strength of 

Evidence

physical activity 

(fitness–VO2

max) (EOI)

suspected Favors behavioral programs

Change in 

physical activity 

(intensity/ 

duration) (EOI)

2 (91)1, 3 High Consistent Direct Imprecise UnsuspectedSMD, 0.16; 95% CI -0.25 to 0.57 Insufficient

Change in 

physical activity 

(intensity/ 

duration) (6m)

2 (272)3, 6 High Inconsistent Direct Imprecise UnsuspectedSMD, -0.26; 95% CI -1.0 to 0.49 Insufficient

Change in 

nutrient intake 

(kcal/day) (EOI)

1 (61)13 High Unknown Direct Imprecise UnsuspectedMD, -247.10; 95% CI -281.7 to -

212.5

Favors behavioral programs

Insufficient

Change in 

nutrient intake 

(saturated fat) 

(EOI)

1 (61)13 High Unknown Direct Imprecise UnsuspectedMD, -1.80; 95% CI -3.53 to -0.07; 

favors behavioral programs

Insufficient

Generic HRQL 

(EOI)

7 (474)1, 5, 7-9, 16, 26 High Consistent Direct Precise UnsuspectedSMD, 0.10; 95% CI -0.18 to 0.38 Moderate 

Generic HRQL 

(6m)

1 (53)5 High Unknown Direct Imprecise UnsuspectedSMD, -0.29; 95% CI -0.83 to 0.26 Insufficient

Generic HRQL 

(12m)

2 (405)9, 25 High Unknown Direct Imprecise UnsuspectedSMD, 0.02; 95% CI -0.11 to 0.15 Insufficient

Generic HRQL 

(≥12m)

1 (291)25 High Unknown Direct Imprecise UnsuspectedSMD, -0.04; 95% CI -0.27 to 0.19 Insufficient

Diabetesspecific quality 

of life (EOI)

3 (212)11, 16, 26 High Inconsistent Direct Imprecise UnsuspectedSMD, 0.08; 95% CI, -1.44 to 1.60 Insufficient

Diabetes 

Distress (EOI)

4 (209)1, 3, 5, 7 High Consistent Direct Imprecise UnsuspectedSMD, -0.31; 95% CI, -0.83 to 0.21 Low

Diabetes 

Distress (6m)

4 (236)3, 5, 23, 24 High Consistent Direct Imprecise UnsuspectedSMD, -0.28; 95% CI, -0.94 to 0.38 Low

Note: No study reported on complications or all-cause mortality. Only clinical trials were included in strength of evidence assessments. Lower scores beneficial for HbA1c, 

Diabetes Distress, Change in Nutrient Intake, and Change in Body Composition; higher scores beneficial for Adherence to Diabetes Self-management, Change in Physical 

Activity, and Generic and Diabetes-specific Quality of Life.

CI = confidence interval; DSMP = Diabetes Self-Management Profile; EOI = end of intervention; HbA1c = hemoglobin A1c; HRQL = health-related quality of life; M = month; MD 

= mean difference; SDSCA = Summary of Diabetes Self-Care Activities; SMBG = self-monitoring of blood glucose
H-4

Table H2. Behavioral programs compared with an active control: strength of evidence for Key Question 1

Outcome # Trials (# 

Subjects); Tool 

if Applicable

Risk of 

Bias

Consistency Directness Precision Reporting 

Bias

Findings and Direction of Effects Strength of 

Evidence

HbA1c (EOI) 4 (529) 15, 27-29 Medium Consistent Direct Imprecise UnsuspectedMD, -0.32; 95% CI -0.97 to 0.33 Low 

HbA1c (6m) 4 (467)15, 28-30 Medium Consistent Direct Precise UnsuspectedMD, -0.44; 95% CI -0.69 to -0.19

Favors behavioral programs

Moderate

HbA1c (12m) 3 (305)15, 28, 29 Medium Consistent Direct Imprecise UnsuspectedMD, -0.44; 95% CI -1.04 to 0.16 Low

Adherence to 

diabetes selfmanagement 

(EOI)

1 (54);15 DSMP

1 (149);28 DBRS

High Inconsistent Direct Imprecise UnsuspectedMD, 2.40; 95% CI -2.46 to 7.26

No data reported; those in 

behavioral program did more poorly 

Insufficient

Adherence to 

diabetes selfmanagement 

(6m)

1 (149);30 SMBG

1 (149);28 DBRS

High Inconsistent Direct Imprecise UnsuspectedMD, -0.20; 95% CI -0.76 to 0.36

No data reported; those in 

behavioral program did more poorly

Insufficient

Adherence to 

diabetes selfmanagement 

(12m)

1 (54);15 DSMP

1 (149);28 DBRS

High Inconsistent Direct Imprecise UnsuspectedMD, 2.00; 95% CI -3.78 to 7.78

No data reported; those in 

behavioral program did more poorly

Insufficient

Note: Only clinical trials were included in strength of evidence assessments. Lower scores beneficial for HbA1c; higher scores beneficial for adherence to diabetes selfmanagement. 

CI = confidence interval; DBRS = Diabetes Behavior Rating Scale; DSMP = Diabetes Self-Management Profile; EOI = end of intervention; HbA1c = hemoglobin A1c; M = month; 

MD = mean difference; SDSCA = Summary of Diabetes Self-Care Activities; SMBG = self-monitoring of blood glucose
H-5

Table H3. Behavioral programs compared with usual care: strength of evidence for Key Question 2 (age subgroups)

Outcome # Trials (# 

Subjects); Tool 

if Applicable

Risk of 

Bias

Consistency Directness Precision Reporting 

Bias

Findings and Direction of Effects Strength of 

Evidence

Youth

HbA1c (EOI) 11 (653)2-5, 8-10, 12, 

14-16 Medium Inconsistent Direct Precise Unsuspected

MD, 0.00; 95% CI -0.33 to 0.33 Low 

HbA1c (6m) 10 (1,213)3, 5, 15, 

17-22, 24

Medium Consistent Direct Precise UnsuspectedMD, -0.28; 95% CI -0.51 to -0.05

Favors behavioral programs

Moderate

HbA1c (12m) 7 (1,333)2, 15, 20-22, 

24, 25

Medium Consistent Direct Imprecise UnsuspectedMD, -0.22; 95% CI -0.49 to 0.05 Low

Adults

HbA1c (EOI) 5 (502)1, 6, 7, 11, 13 High Consistent Direct Imprecise UnsuspectedMD, -0.28; 95% CI -0.57 to 0.01 Low

HbA1c (6m) 2 (250)6, 23 High Consistent Direct Imprecise UnsuspectedMD, -0.38; 95% CI -0.82 to 0.06 Low

HbA1c (12m) NR Insufficient

CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; M = month; MD = mean difference

Table H4. Behavioral programs compared with active controls: strength of evidence for Key Question 2 (age subgroups)

Outcome # Trials (# 

Subjects); Tool 

if Applicable

Risk of 

Bias

Consistency Directness Precision Reporting 

Bias

Findings and Direction of Effects Strength of 

Evidence

Youth

HbA1c (EOI) 3 (419)15, 27, 28 Medium Consistent Direct Imprecise UnsuspectedMD, -0.33; 95% CI -1.65 to 0.99 Insufficient 

HbA1c (6m) 2 (208)15, 28 Medium Consistent Direct Imprecise UnsuspectedMD, -0.60; 95% CI -2.56 to 1.36 Insufficient

HbA1c (12m) 2 (195)15, 28 Medium Consistent Direct Imprecise UnsuspectedMD, -0.52; 95% CI -1.04 to 0.00 Low

Adults

HbA1c (EOI) 1 (147)29 Medium Unknown Direct Imprecise UnsuspectedMD, -0.35; 95% CI -0.81 to 0.11 Insufficient

HbA1c (6m) 2 (259)29, 30 Medium Consistent Direct Imprecise UnsuspectedMD, -0.38; 95% CI -0.93 to 0.17 Low

HbA1c (12m) 1 (110)29 Medium Unknown Direct Imprecise UnsuspectedMD, -0.14; 95% CI -0.61 to 0.33 Insufficient

CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; M = month; MD = mean difference
H-6

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H-7

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24. Serlachius AS, Scratch SE, Northam EA, et 

al. A randomized controlled trial of 

cognitive behaviour therapy to improve 

glycaemic control and psychosocial 

wellbeing in adolescents with type 1 

diabetes. J Health Psychol. 2014 Sep 10. 

PMID: 25213114.

25. Christie D, Thompson R, Sawtell M, et al. 

Structured, intensive education maximising 

engagement, motivation and long-term 

change for children and young people with 

diabetes: a cluster randomised controlled 

trial with integral process and economic 

evaluation - the cascade study. Health 

Technol Assess. 2014 Mar;18(20):1-202. 

PMID: 24690402.

26. Kichler JC, Kaugars AS, Marik P, et al. 

Effectiveness of groups for adolescents with 

type 1 diabetes mellitus and their parents. 

Fam Syst Health. 2013 Sep;31(3):280-93. 

PMID: 23957874.

27. Ellis DA, Naar-King S, Chen X, et al. 

Multisystemic therapy compared to 

telephone support for youth with poorly 

controlled diabetes: findings from a 

randomized controlled trial. Ann Behav 

Med. 2012 Oct;44(2):207-15. PMID: 

22644587.

28. Holmes CS, Chen R, Mackey E, et al. 

Randomized clinical trial of clinicintegrated, low-intensity treatment to 

prevent deterioration of disease care in 

adolescents with type 1 diabetes. Diabetes 

Care. 2014 Jun;37(6):1535-43. PMID: 

24623027.

29. Weinger K, Beverly EA, Lee Y, et al. The 

effect of a structured behavioral intervention 

on poorly controlled diabetes: a randomized 

controlled trial. Arch Intern Med. 2011 Dec 

12;171(22):1990-9. PMID: 21986346.

30. Hermanns N, Kulzer B, Ehrmann D, et al. 

The effect of a diabetes education 

programme (PRIMAS) for people with type 

1 diabetes: results of a randomized trial. 

Diabetes Res Clin Pract. 2013 

Dec;102(3):149-57. PMID: 24210673.
I-1

Appendix I. Effectiveness Across Outcomes for Type 2 Diabetes Mellitus

Table I1. Effectiveness of behavioral programs compared with usual care for type 2 diabetes mellitus

Table I2. Effectiveness of behavioral programs compared with active control for type 2 diabetes mellitus

Table I3. Comparative effectiveness of behavioral programs for type 2 diabetes mellitus

Notes: Bold text represents statistically significant findings. 
I-2

Table I1. Effectiveness of behavioral programs compared with usual care for type 2 diabetes 

Category Outcomes

Timepoint

EOI 6m 12m

# 

Comparisons

(# Subjects)

Study 

Effect

# 

Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects) Study Effect

Clinical 

Outcomes

Glycemic 

Control 

(HbA1c)

66 (8,715)1-63

MD, -0.35; 

95% CI -

0.56 to -

0.14; I2=74%

23 (4,138)14, 33, 45, 

51, 53, 62, 64-78

MD, -0.16; 

95% CI -0.36 

to 0.04; 

I

2

=61%

9 (1,494)14, 40, 67-69, 

71, 78, 79

MD, -0.14; 95% 

CI -0.4 to 0.12; 

I

2

=59%

Change in 

Body 

Composition 

(BMI)

36 (4,280)1-3, 6, 8-

10, 12, 13, 15, 18, 19, 21, 

22, 27, 29, 30, 32, 33, 41, 

43, 47, 49-51, 53, 56, 57, 

60, 62, 63, 77, 80, 81

MD, -0.51; 

95% CI -

0.66 to -

0.36; I2

=54%

14 (1,840)33, 51, 53, 

62, 64, 66-68, 70, 71, 75, 

77, 81

MD, -0.21;

95% CI -0.32 

to -0.1; I2

=0%

5 (867)67, 68, 71, 82, 

83

MD, -0.92; 95% 

CI -1.44 to -0.4; 

I

2

=0%

Weight (kg)

37 (4,070)2, 4, 6, 7, 

9, 11, 17, 19, 20, 22, 23, 

25, 26, 31, 32, 35, 39, 41-

43, 49, 53, 55, 58-63, 69, 

77, 84-86

MD, -1.68; 

95% CI -

2.06 to -

1.30; I2

=53%

8 (1,714)53, 62, 68, 

74, 77, 78, 84

MD, -0.22; 

95% CI -0.56 

to 0.12; I2=0%

1 (291)68 MD, -1.60; 95% CI -5.41 to 2.21; 

I

2

=NA

Change in 

Body 

Composition 

(% body fat)

2 (73)26, 60

MD, -3.34; 

95% CI -

4.57 to -

2.11; I2=0%

NA NA NA NA

Change in 

Body 

Composition 

(waist 

circumference 

[cm])

17 (1,521)6, 9, 12, 

22, 25, 32, 33, 41, 43, 51, 

55, 56, 60, 62, 84

MD, -3.17; 

95% CI -

4.36 to -

1.98; I2

=64%

6 (690)33, 51, 62, 68, 

84

MD, -1.09; 

95% CI -2.7 

to 0.52; 

I

2

=10%

2 (385)68, 82

MD, -2.92; 95% 

CI -11.3 to 5.46; 

I

2

=0%

Total 

Cholesterol 

(mmol/l)

27 (2,633)2, 6-9, 16-

18, 20-22, 25, 29, 31-33, 

42, 48, 49, 51, 55, 60, 62, 

63

MD, -0.1; 

95% CI -

0.11 to -

0.09; I2=0%

7 (686)33, 51, 53, 62, 

66, 68

MD, -0.24; 

95% CI -0.39 

to -0.09; 

I

2

=0%

1 (291)68 MD, -0.10; 95% CI -0.34 to 0.14; 

I

2

=NA

HDL 

Cholesterol 

(mmol/l)

25 (2,733)1, 2, 6, 7, 

9, 16-18, 20-22, 29-33, 

41, 48, 49, 55, 60, 62, 63

MD, 0.02; 

95% CI 0.02 

to 0.02; 

I

2

=7%

4 (563)33, 53, 62, 68

MD, -0.09; 

95% CI -0.12 

to -0.06; 

I

2

=0%

1 (291)68 MD, 0.00; 95% CI -0.20 to 0.20; 

I

2

=NA

LDL 

Cholesterol 

(mmol/l)

27 (3,063)1-3, 6, 9, 

12, 13, 18, 21, 22, 28-33, 

41, 47-49, 51, 55, 60, 62, 

63

MD, -0.03; 

95% CI -

0.03 to -

0.03; I2=59%

5 (457)33, 51, 62, 68

MD, -0.19; 

95% CI -0.47 

to 0.09; 

I

2

=49%

1 (291)68 MD, 0.00; 95% CI -0.09 to 0.09; 

I

2

=NA

Triglycerides 24 (2,561)1, 2, 6, 9, MD, -0.17; 5 (712)14, 33, 53, 62, MD, -0.18; 1 (291)68 MD, -0.20; 95% 
I-3

Category Outcomes

Timepoint

EOI 6m 12m

# 

Comparisons

(# Subjects)

Study 

Effect

# 

Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects) Study Effect

(mmol/l) 14, 18, 21, 22, 25, 29-33, 

41, 42, 48, 49, 55, 60, 62, 

63

95% CI -

0.24 to -0.1; 

I

2

=36%

68 95% CI -0.37 

to 0.01; I2=6%

CI -0.45 to 0.05; 

I

2

=NA

Systolic Blood 

Pressure 

(mmHg)

36 (4,776)1-4, 6, 7, 

9, 10, 12-14, 18, 21, 22, 

25, 26, 28-30, 32, 33, 39, 

41, 42, 47, 49, 51, 53, 58, 

60, 62, 63, 80, 84

MD, -0.78; 

95% CI -1.3 

to -0.26; 

I

2

=23%

10 (1,613)14, 33, 51, 

53, 62, 68, 78, 84

MD, -1.08; 

95% CI -2.9 

to 0.74; I2

=0%

1 (291)68 MD, -2.80; 95% 

CI -7.69 to 2.09; 

I

2

=NA

Diastolic 

Blood 

Pressure 

(mmHg)

33 (4,583)1-4, 6, 7, 

9, 10, 12, 13, 18, 21, 22, 

25, 26, 28-30, 32, 39, 41, 

42, 47, 49, 53, 58, 60, 62, 

63, 80, 84

MD, -0.94; 

95% CI -

1.32 to -

0.56; I2

=32%

7 (1,424)33, 53, 62, 

68, 78, 84

MD, -1.26; 

95% CI -1.97 

to -0.55; 

I

2

=0%

1 (291)68 MD, -2.20; 95% 

CI -4.73 to 0.33; 

I

2

=NA

Depression 

Symptoms

13 (1,751)5, 7, 17, 

21, 32-34, 38, 49, 53, 61, 

62

SMD, -0.16; 

95% CI -

0.32 to 0; 

I

2

=45%

5 (1,189)33, 53, 62, 

72, 74

SMD, -0.09; 

95% CI -0.57 

to 0.39; 

I

2

=80%

NA NA

Anxiety 

Symptoms NA NA NA NA NA NA

Behavioral 

Outcomes

Change in 

Physical 

Activity -

Duration/ 

Intensity 

(Subjective 

[days/week])

7 (1,176)19, 37, 43, 

49, 50, 54, 83

MD, 0.56; 

95% CI -0.1 

to 1.22; 

I

2

=79%

2 (270)68, 87

MD, 1.73; 

95% CI -8.82 

to 12.28; 

I

2

=91%

2 (382)68, 83

MD, 0.90; 95% 

CI 0.9 to 0.9; 

I

2

=0%

Change in 

Physical 

Activity -

Duration/ 

Intensity 

(Objective)

5 (373)20, 23, 39, 48

SMD, 0.49; 

95% CI -

0.24 to 1.22; 

I

2

=74%

NA NA NA NA

Change in 

Physical 

Activity –

Fitness

2 (329)15, 60

SMD, 0.67; 

95% CI -

7.37 to 8.71; 

I

2

=90%

1 (134)67 SMD, 0.03; 95% CI -0.30 

to 0.37; I2=NA

1 (134)67 SMD, 0.11; 95% CI -0.23 to 0.44; 

I

2

=NA

Change in 

Physical NA NA NA NA NA NA
I-4

Category Outcomes

Timepoint

EOI 6m 12m

# 

Comparisons

(# Subjects)

Study 

Effect

# 

Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects) Study Effect

Activity –

Strength

Change in 

Dietary Intake 

– Energy 

Intake 

(kcal/day)

11 (1,164)1, 2, 10, 

20, 23, 33, 34, 60, 84, 88

MD, -

149.62; 95% 

CI -243.01 

to -56.23; 

I

2

=68%

3 (469)33, 68, 84

MD, -64.05; 

95% CI -

96.44 to -

31.66; I2

=0%

1 (191)68

MD, 114.00; 

95% CI -308.19 

to 536.19; 

I

2

=NA

Change in 

Dietary Intake 

– Saturated 

Fat Intake (% 

of daily kcal)

10 (1,208)2, 10, 20, 

33, 34, 49, 50, 60, 88

MD, -0.24; 

95% CI -

0.73 to 0.25; 

I

2

=44%

2 (232)33, 68

MD, -0.40; 

95% CI -8.82 

to 8.02; 

I

2

=23%

1 (191)68 MD, -1.10; 95% CI -2.22 to 0.02; 

I

2

=NA

Adherence to 

Medication 

(higher 

scores 

desirable)

4 (742)13, 15, 54, 83

SMD, -0.17; 

95% CI -0.7 

to 0.36; 

I

2

=75%

1 (54)87 SMD, 0.42; 

95% CI -0.12 

to 0.96; I2=NA

1 (191)83 SMD, -0.50; 

95% CI -0.79 to 

-0.21; I2

=NA

Health 

Outcomes

Quality of Life 

– SF-36 

Physical

(higher score 

desirable)

5 (787)10, 32, 39, 49

MD, 0.45; 

95% CI -

0.05 to 0.95; 

I

2

=0%

NA NA NA NA

Quality of Life 

– SF-36 

Mental

(higher score 

desirable)

5 (787)10, 32, 39, 49

MD, 1.60; 

95% CI -

1.96 to 5.16; 

I

2

=86%

NA NA NA NA

Quality of Life 

– Other 

(higher score 

desirable)

4 (447)27, 43, 53, 54

SMD, 0.12; 

95% CI -

0.26 to 0.5; 

I

2

=40%

3 (789)53, 73, 74

SMD, 0.08; 

95% CI -0.11 

to 0.27; I2

=0%

NA NA

Diabetesspecific 

Quality of Life 

– Diabetes 

Distress 

(PAID)

(lower scores 

8 (1,384)5, 7, 36, 42-

44, 47, 75

MD, -1.82; 

95% CI -

3.43 to -

0.21; I2

=0%

4 (1,382)67, 75, 78

MD, -1.89; 

95% CI -4.37 

to 0.59; I2

=0%

3 (757)67, 78

MD, -1.30; 95% 

CI -5.84 to 3.24; 

I

2

=0%
I-5

Category Outcomes

Timepoint

EOI 6m 12m

# 

Comparisons

(# Subjects)

Study 

Effect

# 

Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects) Study Effect

desirable)

Diabetesspecific 

Quality of Life 

– Other 

(lower scores 

desirable)

5 (753)15, 17, 20, 21, 

33, 54

SMD, -0.21; 

95% CI -

0.55 to 0.13; 

I

2

=51%

3 (366)33, 67, 68

SMD, -0.04; 

95% CI -0.38 

to 0.3; I2

=0%

2 (325)67, 68

SMD, -0.09; 

95% CI -1.15 to 

0.97; I2

=0%

Mortality – All 

cause 

(longest 

followup)

25 (4,659)

5, 14, 20, 

28, 35, 39-43, 53, 64, 68, 

69, 78, 79, 82-84

RR, 1.28; 

95% CI 0.84

to 1.94; 

I

2

=1%

NA NA NA NA

Health Care 

Utilization

Emergency 

Department 

Visits 

(previous 6 

months)

NA NA 2 (762)73, 74

MD, -0.07; 

95% CI -0.7 

to 0.56

NA NA

Days of 

Hospital Stay 

(previous 6 

months)

NA NA 2 (646)73, 74

MD, 0.24; 

95% CI -1.52 

to 2.0

NA NA

Program 

Acceptability

Participant 

Attrition 

(longest 

followup)

81 (14,154)

1-6, 8, 

10-22, 24, 26-34, 36-44, 

47, 49, 52-70, 72-87, 89

RR, 1.11; 

95% CI 0.82 

to 1.49; 

I

2

=43%

NA NA NA NA

BMI = body mass index; CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; I2 = statistical heterogeneity; kg = kilograms; m = month; MD = mean 

difference; NA = not applicable; RR = risk ratio; SMD = standardized mean difference 
I-6

Table I2. Effectiveness of behavioral programs compared with active control for type 2 diabetes

Category Outcomes Timepoint

EOI 6m followup 12m followup

# Comparisons

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study Effect

Clinical 

Outcomes

Glycemic 

Control (HbA1c)

25(7,518)15, 19, 23, 

59, 90-104

MD, -0.24; 

95% CI -

0.41 to -

0.07; I2=70%

6 (595)103, 105-108 MD, -0.19; 

95% CI -

0.37 to -

0.01; I2=0%

6 (486)92, 99, 103, 108 MD, -1.10; 95% 

CI -2.56 to 0.36; 

I

2

=98%

Change in Body 

Composition 

(BMI)

10 (1,323)15, 19, 90, 

96-99, 101

MD, -0.52; 

95% CI -

1.08 to 0.04; 

I

2

=66%

1 (38)105 MD, -2.20; 

95% CI -

6.80 to 

2.40; I2=NA

2 (181)99 MD, -0.30; 95% 

CI -0.3 to -0.3; 

I

2

=0%

Weight (kg) 15 (6,212)19, 23, 59, 

90, 93, 94, 96-98, 100, 101, 

104, 109

MD, -1.30; 

95% CI -

2.48 to -

0.12; I2

=78%

3 (439)105, 106, 108 MD, 0.14; 

95% CI -

3.41 to 

3.69; 

I

2

=67%

1 (95)108 MD, 3.70; 95% 

CI 1.67 to 5.73; 

I

2

=NA

Change in Body 

Composition (% 

body fat)

NA NA NA NA NA NA

Change in Body 

Composition 

(waist 

circumference 

[cm])

5 (5,332)94, 96, 98, 

101, 104

MD, -2.54; 

95% CI -

5.78 to 0.7; 

I

2

=79%

1 (38)105 MD, -5.70; 

95% CI -

6.54 to -

4.86; I2

=NA

NA NA

Total 

Cholesterol 

(mmol/l)

8 (928)90, 93, 96, 97, 

99, 109

MD, -0.26; 

95% CI -

0.46 to -

0.06; I2=50%

1 (167)106 MD, 0.08; 

95% CI -

0.15 to 

0.30; I2=NA

2 (181)99 MD, -0.15; 95% 

CI -0.79 to 0.49; 

I

2

=0%

HDL 

Cholesterol 

(mmol/l)

8 (6,005)90, 93, 97, 99, 

104, 109

MD, 0.02; 

95% CI 0.0 

to 0.04; 

I

2

=0%

2 (401)106, 108 MD, 0.03; 

95% CI -

0.84 to 0.9; 

I

2

=54%

2 (181)99 MD, 0.1; 95% 

CI -0.22 to 0.02; 

I

2

=0%

LDL Cholesterol 

(mmol/l)

6 (5,824)90, 93, 97, 

104, 109

MD, 0.02; 

95% CI -

0.03 to 0.07; 

I

2

=0%

2 (401)106, 108 MD, 0.13; 

95% CI -

1.52 to 

1.78; 

I

2

=75%

NA NA

Triglycerides 

(mmol/l)

9 (6,073)90, 93, 96, 97, 

99, 104, 109

MD, -0.16; 

95% CI -

0.41 to 0.09; 

I

2

=72%

1 (167)106 MD, -0.05; 

95% CI -

0.40 to 

0.30; I2=NA

2 (181)99 MD, -0.36; 95% 

CI -0.99 to 0.27; 

I

2

=0%
I-7

Category Outcomes Timepoint

EOI 6m followup 12m followup

# Comparisons

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study Effect

Systolic Blood 

Pressure 

(mmHg)

5 (5,895)90, 96, 98, 

100, 104

MD, -0.63; 

95% CI -

3.13 to 1.87; 

I

2

=19%

2 (205)105, 106 MD, 2.49; 

95% CI -

10.46 to 

15.44; 

I

2

=0%

NA NA

Diastolic Blood 

Pressure 

(mmHg)

5 (5,895)90, 96, 98, 

100, 104

MD, -0.36; 

95% CI -

3.03 to 2.31; 

I

2

=54%

2 (205)105, 106 MD, 0.06; 

95% CI -8.6 

to 8.72; 

I

2

=0%

NA NA

Depression 

Symptoms

3 (4,982)90, 101, 104 SMD, -0.00; 

95% CI -

0.08 to 0.08; 

I

2

=0%

NA NA NA NA

Anxiety 

Symptoms

3 (233)99, 101 MD, -1.49; 

95% CI -2.1 

to -0.88; 

I

2

=0%

NA NA 2 (181)99 MD, -1.80; 95% 

CI -3.07 to -

0.53; I2

=0%

Behavioral 

Outcomes

Change in 

Physical Activity 

- Duration/ 

Intensity 

(Subjective 

[days/week])

1 (40)19 MD, -1.06; 

95% CI -

1.82 to -

0.31; I2

=NA

NA NA NA NA

Change in 

Physical Activity 

- Duration/ 

Intensity 

(Objective)

2 (46)23 SMD, 1.24; 

95% CI -

12.99 to 

15.47; 

I

2

=89% 

NA NA NA NA

Change in 

Physical Activity 

– Fitness

3 (102)91, 93, 109 SMD, 0.55; 

95% CI -

0.92 to 2.02; 

I

2

=55% 

NA NA NA NA

Change in 

Physical Activity 

– Strength

NA NA NA NA NA NA
I-8

Category Outcomes Timepoint

EOI 6m followup 12m followup

# Comparisons

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study Effect

Change in 

Dietary Intake –

Energy Intake 

(kcal/day)

7 (242)23, 93, 94, 98, 

100, 101

MD, -158.94; 

95% CI -

333.73 to 

15.85; 

I

2

=38%

1 (38)105 MD, -70.00; 

95% CI -

847.59 to 

707.59; 

I

2

=NA

NA NA

Change in 

Dietary Intake –

Saturated Fat 

Intake (% of 

daily kcal)

2 (74)93, 101 MD, -1.40; 

95% CI -

10.64 to 

7.84; I2

=22%

1 (38)105 MD, 2.00; 

95% CI -

0.77 to 

4.77; I2

=NA

NA NA

Adherence to 

Medication

4 (1,309)15, 90, 95 SMD, -0.05; 

95% CI -

0.17 to 0.07; 

I

2

=0%

NA NA NA NA

Health 

Outcomes

Quality of Life –

SF-36 Physical

(higher score 

desirable)

2 (4,432)96, 104 MD, 5.00; 

95% CI -

50.92 to 

60.92; 

I

2

=85%

1 (167)106 MD, 1.60; 

95% CI -

1.18 to 

4.38; I2

=NA

NA NA

Quality of Life –

SF-36 Mental

(higher score 

desirable)

2 (4,432)96, 104 MD, -2.59; 

95% CI -

48.65 to 

43.47; 

I

2

=74%

1 (167)106 MD, -1.00; 

95% CI -

3.82 to 

1.82; I2

=NA

NA NA

Quality of Life –

Other (lower 

score desirable)

2 (767)90, 99 SMD, -0.08; 

95% CI -

0.47 to 0.31; 

I

2

=11%

NA NA 2 (181)99 SMD, -0.06; 

95% CI -0.57 to 

0.45; I2

=0%

Diabetesspecific Quality 

of Life –

Diabetes 

Distress (PAID)

NA NA 1 (167)106 MD, 1.10; 

95% CI -

2.08 to 

4.28; I2

=NA

NA NA

Diabetesspecific Quality 

of Life – Other 

(lower score 

desirable)

4 (1,309)15, 90, 95 SMD, 0.04; 

95% CI -

0.16 to 0.24; 

I

2

=17%

NA NA NA NA
I-9

Category Outcomes Timepoint

EOI 6m followup 12m followup

# Comparisons

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study 

Effect

# Comparisons 

(# Subjects)

Study Effect

Mortality – All 

cause (longest 

followup)

5 (6,050)

90, 102, 104 RR, 0.86; 

95% CI, 0.77 

to 0.96; 

I

2

=0%

NA NA NA NA

Program 

Acceptability

Participant 

Attrition

21 (7,603)

15, 19, 59, 

90-92, 94, 96, 98-107

RR, 0.87; 

95% CI 0.78 

to 0.97; 

I

2

=0%

BMI = body mass index; CI = confidence interval; EOI = end of intervention; HbA1c = hemoglobin A1c; I2 = statistical heterogeneity; kg = kilograms; m = month; MD = mean 

difference; NA = not applicable; RR = risk ratio; SMD = standardized mean difference 

Table I3. Comparative effectiveness of behavioral programs for type 2 diabetes mellitus

Outcome Category of 

Comparative 

Effectiveness 

# Trials (# 

Subjects)

Study Effect at Longest 

Followup

Conclusion

HbA1c Addition of Support to 

DSME

3 (387)102, 110, 

111 MD, -0.07; 95% CI -0.35 to 0.22 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Addition of Support to 

Lifestyle Program

1 (114)20 MD, 0.20; 95% CI -0.94 to 1.34 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Addition of Another 

Component to DSME

4 (547)95, 112-

114 MD, 0.86; 95% CI -0.03 to 1.76 No difference when adding care coordination,112

PST,95 MT,113 or PA114 to DSME 95, 113or DSME + 

Support112, 114

Addition of Another 

Component to Lifestyle 

Program

3 (241)115-117 MD, -0.05; 95% CI -0.34 to 0.25 No difference when adding MI116, 117 or blood glucose 

regulation115 interventions to a lifestyle program

High vs. Low Intensity 2 (209)118, 119 MD, -0.41; 95% CI -1.22 to 0.41 No difference between high and low intensity DSME 

and support programs

Delivery of DSME via 

technology vs. in person

2 (126)

120, 121 MD, 0.07; 95% CI -0.61 to 0.75 No difference when delivery of empowerment DSME 

with CST via telemedicine vs. in person at clinic,

120 or 

when social-cognitive theory-guided group DSME for 

African Americans delivered via virtual world online vs 

in person121

Delivery of DSME to groups 

vs. individuals

3 (701)78, 99, 

122

MD, -0.36; 95% CI -0.63 to -0.08 Improved using group compared with individual 

delivery of DSME
I-10

Outcome Category of 

Comparative 

Effectiveness 

# Trials (# 

Subjects)

Study Effect at Longest 

Followup

Conclusion

Delivery by Peers vs. HCP 4 (575)110, 111, 

123, 124

MD, 0.00; 95% CI -0.23 to 0.23 No difference when delivery of DSME110, 123 or support 

phase111, 124 by peer compared with HCP

Delivery by non-HCPs vs. 

HCP

1 (72)111 MD, 0.02; 95% CI -0.60 to 0.64 No difference when support after DSME is provided by 

clinic staff vs. DM educators

Addition of peers to CHWled DSME + Support 

1 (116)125 MD, -0.30; 95% CI -0.90 to 0.30 No difference when adding peer leaders to support 

phase of CHW-led DSME + Support (Partners in Care) 

Others 1 (99)126 MD, -0.30; 95% CI -0.72 to 0.12 No difference between CBT-based lifestyle program 

with portion-controlled diet and DSME with meal plan

1 (600)127 MD, -0.07; 95% CI -0.22 to 0.08 No difference between DSME using PRECEDE model 

vs. conventional health promotion model 

1 (24)51 MD, 0.19; 95% CI -0.76 to 1.14 No difference between DSME with problem-solving 

approach using telephone delivery to couples vs. 

individuals

1 (21)128 MD, 0.13; 95% CI -1.18 to 1.44 No difference between group-based culturally tailored 

DSME to individual DSME for rural African Americans

1 (143)129 MD, -0.30; 95% CI -0.58 to -0.02 Improved with individual DSME with MI vs. groupbased empowerment DSME with supervised group 

exercise 

Change in Body 

Composition 

(BMI)

Addition of Support to 

DSME

2 (259)110, 111 MD, -0.08; 95% CI -0.58 to 0.41 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Addition of Another 

Component to DSME

3 (255)112-114 MD, 0.08; 95% CI -0.48 to 0.64 No difference when adding care coordination,112 

MT,113 or PA114 to DSME or DSME + Support

Delivery of DSME to groups 

vs. individuals

2 (212)99, 122 MD, 0.16; 95% CI -1.12 to 1.44 No difference using group delivery compared with 

individual delivery of DSME

Delivery by Peers vs. HCP 2 (263)110, 111 MD, 0.47; 95% CI -0.32 to 1.26 No difference when delivery of DSME110 or support 

phase111 by peer compared with HCP

Delivery by non-HCPs vs. 

HCP

1 (73)111 MD, 0.31; 95% CI -0.72 to 1.34 No difference when support after DSME is provided by 

clinic staff vs. DM educators111

Addition of peers to CHWled DSME + Support 

1 (116)125 MD, 0.50; 95% CI -0.24 to 1.24 No difference when adding peer leaders to support 

phase of CHW-led DSME + Support (Partners in Care)

Other 1 (99)126 MD, -1.80; 95% CI -2.51 to -1.09 Improved with CBT-based lifestyle program with 

portion-controlled diet compared with DSME with 

meal plan

1 (600)127 MD, 0.06; 95% CI -0.19 to 0.31 No difference between DSME using PRECEDE model 

vs. conventional health promotion model 

1 (24)51 MD, -0.04; 95% CI -5.27 to 5.19 No difference between DSME with problem-solving 

approach using telephone delivery to couples vs. 

individuals
I-11

Outcome Category of 

Comparative 

Effectiveness 

# Trials (# 

Subjects)

Study Effect at Longest 

Followup

Conclusion

Change in Body 

Composition 

(Weight [kg])

Addition of Support to 

Lifestyle Program

1 (112)20 MD, 0.41; 95% CI -7.21 to 8.03 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Addition of Another 

Component to Lifestyle 

Program

3 (241)115-117 MD, -1.14; 95% CI -2.80 to 0.52 No difference when adding MI116, 117 or blood glucose 

regulation115 interventions to a lifestyle program

High vs. Low Intensity 1 (96)85 MD, -1.30; 95% CI -2.90 to 0.30 No difference between high and low intensity lifestyle 

program tailored to medically underserved

Delivery of DSME to groups 

vs. individuals

2 (581)78, 122 MD, -0.15; 95% CI -0.87 to 0.58 No difference using group compared with individual 

delivery of DSME

Other 1 (99)78, 126 MD, -5.10; 95% CI -7.22 to -2.98 Improved with CBT-based lifestyle program with 

portion-controlled diet compared with DSME with 

meal plan

1 (121)129 MD, -0.10; 95% CI -1.30 to 1.10 No difference between individual DSME with MI and. 

group-based empowerment DSME with supervised 

group exercise

Change in Body 

Composition 

(waist 

circumference)

Addition of Another 

Component to DSME + 

Support

1 (88)114 MD -2.00; 95% CI -5.75 to 1.75 No difference when adding PA to DSME + Support

Addition of peers to CHWled DSME + Support 

1 (116)125 MD, 0.25; 95% CI -2.44 to 2.95 No difference when adding peer leaders to support 

phase of CHW-led DSME + Support (Partners in Care)

Others 1 (99)126 MD, -3.60; 95% CI -5.33 to -1.87 Improved with CBT-based lifestyle program with 

portion-controlled diet compared with DSME with 

meal plan

1 (24)51 MD, -1.22; 95% CI -10.32 to 7.88 No difference between DSME with problem-solving 

approach using telephone delivery to couples vs. 

individuals

1 (121)129 MD, -0.20; 95% CI -1.51 to 1.11 No difference between individual DSME with MI and. 

group-based empowerment DSME with supervised 

group exercise

Change in 

Dietary Intake 

(kcal/d) 

Addition of Support to 

Lifestyle Program

1 (102)20 MD, -65.00; 95% CI -195.23 to 

65.23

No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Change in 

Dietary Intake 

(% saturated 

fat/kcal)

Addition of Support to 

Lifestyle Program 

1 (102)20 MD, 0.14; 95% CI -0.25 to 0.53 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Medication 

Adherence

Addition of Another 

Component to DSME

1 (296)95 SMD, 0.05; 95% CI -0.18 to 0.28 No difference when adding PST to DSME
I-12

Outcome Category of 

Comparative 

Effectiveness 

# Trials (# 

Subjects)

Study Effect at Longest 

Followup

Conclusion

Change in 

Physical Activity 

– Intensity/ 

Duration 

(subjective; 

days per week)

Delivery of DSME to groups 

vs. individuals

1 (92)122 MD, 1.30; 95% CI -0.70 to 0.90 No difference in group compared with individual 

delivery of DSME

Delivery by non-HCPs vs. 

HCP

1 (73)111 MD, 0.56; 95% CI -1.11 to 1.80 No difference when support after DSME is provided by 

clinic staff vs. DM educators

Others 1 (121)129 MD, 1.30; 95% CI 0.80 to 1.80 Improved between individual DSME with MI and

group-based empowerment DSME with supervised 

group exercise

Change in 

Physical Activity 

– Intensity/ 

Duration 

(objective)

Addition of Support to 

Lifestyle Program

1 (111)20 SMD, 0.23; 95% CI -0.15 to 0.60 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Change in 

Physical Activity 

– Fitness

Addition of Another 

Component to DSME + 

Support

1 (88)114 SMD, 0.62; 95% CI 0.19 to 1.05 Improved when adding a PA component to DSME + 

Support

Quality of LifeOtherDelivery of DSME to groups 

vs. individuals

1 (120)99 SMD, -0.08; 95% CI -0.44 to 0.28 No difference using group compared with individual 

delivery of DSME

Quality of Life –

SF-36 Physical

Delivery of DSME to groups 

vs. individuals

1 (92)122 MD, -0.80; 95% CI -4.04 to 2.44 No difference in group compared with individual 

delivery of DSME

Quality of Life –

SF-36 Mental

Delivery by Peers vs. HCP 1 (221)124 MD, -0.20; 95% CI -2.21 to 1.81 No difference when delivery of support phase by peer 

compared with HCP

Diabetesrelated Quality 

of Life

(higher score 

desirable)

Addition of Another 

Component to DSME

1 (196)95 MD, 0.14; 95% CI -0.09 to 0.37 No difference when adding PST to DSME

Delivery by Peers vs. HCP 1 (198)110 SMD, 0.11; 95% CI -0.17 to 0.38 No difference when delivery of DSME by peer 

compared with HCP

Delivery of DSME via 

telemedicine vs. in person

1 (35)120 SMD, -0.06; 95% CI -0.72 to 0.61 No difference when delivery of empowerment DSME 

with CST via telemedicine vs. in person at clinic

Addition of Support to 

Lifestyle Program

1 (119)20 SMD, 0.04; 95% CI -0.32 to 0.40 No difference when adding tailoring (African American 

women) and social support in community to clinicbased lifestyle program

Other 1 (121)129 SMD, 0.15; 95% CI -0.20 to 0.51 Improved between individual DSME with MI and. 

group-based empowerment DSME with supervised 

group exercise

Diabetes 

Distress

(lower score 

desirable)

Delivery of DSME via 

telemedicine vs. in person

1 (31)120 MD, 3.60; 95% CI -12.05 to 19.25 No difference when delivery of empowerment DSME 

with CST via telemedicine vs. in person at clinic

Delivery by non-HCPs vs. 

HCP

1 (73)111 MD, 2.40; 95% CI -5.65 to 10.45 No difference when support after DSME is provided by 

clinic staff vs. DM educators

Delivery by Peers vs. HCP 1 (74)111 MD, 24.70; 95% CI 15.02 to 

34.38

Increased distress with delivery of support phase 

by peers compared with HCP
I-13

BMI = body mass index; CBT = cognitive-behavioral theory; CHW = community health worker; CI = confidence interval; CST = coping skills therapy; DM = diabetes mellitus; 

EOI = end of intervention; HbA1c = hemoglobin A1c; HCP = health care professional; m = month; MD = mean difference; MI = motivational interviewing; MT = music therapy; 

NA = not applicable; PA = physical activity; PST = problem-solving training; SMD = standardized mean difference 
I-14

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I-20

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J-1 

Appendix J. Network Meta-Analysis Results for Glycemic Control and Age 

Subgroup Analyses

Table J1. Network meta-analysis results for HbA1c for suboptimal glycemic control subgroup (HbA1c ≥7%) 

Table J2. Network meta-analysis results for HbA1c for participants under 65 years of age 
J-2 

Table J1. Network meta-analysis results for HbA1c for suboptimal glycemic control subgroup (HbA1c ≥7%)

Arm Description Rank 

Order of 

Effect & 

Studies 

(only 

those 

removed 

from 

original 

analysis) 

Intensity Method of 

Communication

Delivery Method Delivery 

Personnel

MD, 95% Credibility 

Interval

Probability of 

Being Best

Usual care NA1-6 NA NA NA NA 0 [NA, NA] 0.0%

Active comparator 

(non-DSME)

287 NA NA NA NA -0.10 [-0.34, 0.15] 0.0%

Active comparator 

(other)

248, 9 NA NA NA NA -0.14 [-0.55, 0.26] 0.0%

DSME 22 ≤10h In person Individual & mixed HCP -0.17 [-0.40, 0.07] 0.0%

20 ≤10h In person Group only HCP -0.20 [-0.47, 0.07] 0.0%

29 ≤10h In person Group only Non-HCP -0.03 [-0.96, 0.90] 0.4%

26 ≤10h Some technology Individual & mixed HCP -0.11 [-0.41, 0.18] 0.0%

211 ≤10h Some technology Individual & mixed Non-HCP -0.18 [-0.48, 0.11] 0.0%

17 11-26h In person Individual & mixed HCP -0.26 [-0.72, 0.20] 0.0%

183, 6 11-26h In person Group only HCP -0.26 [-0.48, -0.04] 0.0%

152, 4 11-26h In person Group only Non-HCP -0.34 [-0.78, 0.10] 0.0%

25 11-26h Some technology Individual & mixed HCP -0.12 [-0.47, 0.22] 0.0%

4 11-26h Some technology Individual & mixed Non-HCP -0.78 [-1.37, -0.18] 5.3%a

27 11-26h Some technology Group only HCP -0.11 [-1.16, 0.93] 1.3%

7 ≥27h In person Individual & mixed HCP -0.73 [-1.61, 0.14] 10.1%a

317 ≥27h In person Group only HCP 0.09 [-0.49, 0.68] 0.0%

9 ≥27h Some technology Individual & mixed HCP -0.70 [-1.60, 0.21] 9.3%a

DSME + Support 8 ≤10h In person Individual & mixed NA -0.70 [-1.52, 0.12] 7.7%a

34 ≤10h In person Group only NA 2.83 [1.48, 4.20] 0.0%

16 ≤10h Some technology Individual & mixed NA -0.30 [-0.74, 0.13] 0.0%

10 11-26h In person Individual & mixed NA -0.64 [-1.70, 0.43] 10.5%a

6 11-26h In person Group only NA -0.73 [-1.38, -0.10] 4.0%a

13 11-26h Some technology Individual & mixed NA -0.36 [-0.86, 0.12] 0.0%

11 ≥27h In person Individual & mixed NA -0.55 [-1.08, -0.02] 0.6%a

3 ≥27h In person Group only NA -0.88 [-1.66, -0.10] 14.4%a

Lifestyle 335 ≤10h In person Individual & mixed NA 0.50 [-0.35, 1.34] 0.0%

239 ≤10h In person Group only NA -0.15 [-1.16, 0.88] 1.4%

35 ≤10h Some technology Individual & mixed NA 0.40 [-0.83, 1.62] 0.4%

12 11-26h In person Individual & mixed NA -0.41 [-0.82, 0.01] 0.0%a
J-3 

5 11-26h In person Group only NA -0.76 [-1.19, -0.33] 1.8%a

1 11-26h Some technology Individual & mixed NA -1.01 [-1.61, -0.40] 19.4%a

19 11-26h Some technology Group only NA -0.20 [-0.99, 0.59] 0.4%

28 ≥27h In person Individual & mixed NA -0.98 [-1.47, -0.50] 12.9%a

30 ≥27h In person Group only NA 0.02 [-0.51, 0.57] 0.0%

25 ≥27h Some technology Individual & mixed NA -0.34 [-0.80, 0.11] 1.3%

DSME = diabetes self-management education; h = hour(s); HCP = health care professional; MD = mean difference; NA = not applicable

aHighlighted rows represent those nodes having effect sizes meeting or exceeding our criteria for clinical importance. 
J-4 

Table J2. Network meta-analysis results for HbA1c for participants under 65 years of age 

Arm Description Rank 

Order of 

Effect & 

Studies(

only 

those 

removed 

from 

original 

analysis)

Intensity Method of 

Communication

Delivery Method Delivery 

Personnel

MD, 95% Credibility 

IntervaI

Probability of 

Being Best

Usual care NA2, 3, 10-

14 NA NA NA NA 0 [NA, NA] 0.0%

Active comparator 

(non-DSME)

31 NA NA NA NA 0.12 [-0.23, 0.46] 0.0%

Active comparator 

(other)

1215, 16 NA NA NA NA -0.54 [-1.19, 0.10] 0.0%a

DSME 1816 ≤10h In person Individual & mixed HCP -0.33 [-0.68, 0.02] 0.0%

21 ≤10h In person Group only HCP -0.22 [-0.63, 0.19] 0.0%

29 ≤10h In person Group only Non-HCP -0.05 [-1.31, 1.21] 0.8%

2712 ≤10h Some technology Individual & mixed HCP -0.09 [-0.51, 0.32] 0.0%

2513 ≤10h Some technology Individual & mixed Non-HCP -0.15 [-0.55, 0.24] 0.0%

23 11-26h In person Individual & mixed HCP -0.17 [-0.83, 0.50] 0.0%

203, 11 11-26h In person Group only HCP -0.26 [-0.58, 0.06] 0.0%

172 11-26h In person Group only Non-HCP -0.38 [-0.97, 0.20] 0.0%

2810 11-26h Some technology Individual & mixed HCP -0.06 [-0.63, 0.50] 0.0%

5 11-26h Some technology Individual & mixed Non-HCP -0.78 [-1.60, 0.04] 3.4%a

26 11-26h Some technology Group only HCP -0.11 [-1.46, 1.22] 1.6%

7 ≥27h In person Individual & mixed HCP -0.73 [-1.92, 0.45] 7.7%a

1 ≥27h In person Group only HCP -1.42 [-2.12, -0.72] 37.3%a

13 ≥27h Some technology Individual & mixed HCP -0.49 [-1.72, 0.75] 3.8%a

DSME + Support 8 ≤10h In person Individual & mixed NA -0.71 [-1.85, 0.44] 6.5%a

34 ≤10h In person Group only NA 2.82 [1.14, 4.48] 0.0%

1916 ≤10h Some technology Individual & mixed NA -0.27 [-1.05, 0.51] 0.1%

15 11-26h In person Individual & mixed NA -0.43 [-1.77, 0.93] 4.2%a

6 11-26h In person Group only NA -0.74 [-1.58, 0.10] 2.4%a

16 11-26h Some technology Individual & mixed NA -0.39 [-1.09, 0.31] 0.1%

11 ≥27h In person Individual & mixed NA -0.54 [-1.32, 0.23] 0.8%a

4 ≥27h In person Group only NA -0.88 [-1.89, 0.12] 8.5%a

Lifestyle 32 ≤10h In person Individual & mixed NA 0.21 [-0.51, 0.95] 0.0%

10 ≤10h In person Group only NA -0.60 [-1.62, 0.41] 2.3%a

33 ≤10h Some technology Individual & mixed NA 0.26 [-1.13, 1.65] 0.5%

1414 11-26h In person Individual & mixed NA -0.45 [-1.06, 0.16] 0.0%a
J-5 

9 11-26h In person Group only NA -0.68 [-1.27, -0.09] 0.4%a

3 11-26h Some technology Individual & mixed NA -0.91 [-1.75, -0.06] 6.6%a

22 11-26h Some technology Group only NA -0.20 [-1.32, 0.92] 0.9%

2 ≥27h In person Individual & mixed NA -1.17 [-1.81, -0.55] 11.7%a

30 ≥27h In person Group only NA 0.08 [-0.70, 0.86] 0.0%

2415 ≥27h Some technology Individual & mixed NA -0.16 [-0.94, 0.62] 0.1%

DSME = diabetes self-management education; h = hour(s); HCP = health care professional; MD = mean difference; NA = not applicable

aHighlighted rows represent those nodes having effect sizes meeting or exceeding our criteria for clinical importance. 
J-6

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