Behavioral Programs for Diabetes Mellitus

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55. Revicki D, Hays RD, Cella D, et al. Recommended methods for determining responsiveness and minimally important differences for patient-reported outcomes. J Clin Epidemiol. 2008 Feb;61(2):102-9. PMID: 18177782. 56. Inthout J, Ioannidis JP, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard Dersimonian-Laird method. BMC Med Res Methodol. 2014;14:25. PMID: 24548571. 57. Sidik K, Jonkman JN. A simple confidence interval for meta-analysis. Stat Med. 2002 Nov 15;21(21):3153-9. PMID: 12375296. 58. Methods Guide for Effectiveness and Comparative Effectiveness Reviews. AHRQ Publication No. 10(14)-EHC063-EF. Rockville, MD: Agency for Healthcare Research and Quality. January 2014. Chapters available at www.effectivehealthcare.ahrq.gov. 59. Court JM, Cameron FJ, Berg-Kelly K, et al. Diabetes in adolescence. Pediatr Diabetes. 2009 Sep;10 Suppl 12:185-94. PMID: 19754629. 60. 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. 61. 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. 62. Peters A, Laffel L. Diabetes care for emerging adults: recommendations for transition from pediatric to adult diabetes care systems: a position statement of the American Diabetes Association, with representation by the American College of Osteopathic Family Physicians, the American Academy of Pediatrics, the American Association of Clinical Endocrinologists, the American Osteopathic Association, the Centers for Disease Control and Prevention, Children with Diabetes, the Endocrine Society, the International Society for Pediatric and Adolescent Diabetes, Juvenile Diabetes Research Foundation International, the National Diabetes Education Program, and the Pediatric Endocrine Society (formerly Lawson Wilkins Pediatric Endocrine Society). Diabetes Care. 2011 Nov;34(11):2477-85. PMID: 22025785. 63. 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. ES-31
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 A 1c (HbA 1c ) 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- 1
Page 1 and 2: Evidence Report/Technology Assessme
Page 3 and 4: This report is based on research co
Page 5 and 6: Key Informants In designing the stu
Page 7 and 8: Peer Reviewers Prior to publication
Page 9 and 10: HbA 1c reduction were more often de
Page 11 and 12: KQ 6. Subgroups for Factors Moderat
Page 13 and 14: Figure 13. Behavioral programs for
Page 15 and 16: glycemia in reducing the incidence
Page 17 and 18: together with one or more additiona
Page 19 and 20: Figure A. Analytic framework for be
Page 21 and 22: Methods Literature Search Strategy
Page 23 and 24: With input from our Technical Exper
Page 25 and 26: participants had suboptimal baselin
Page 27 and 28: duration of diabetes ranged from 2.
Page 29 and 30: Table B. Type 1 diabetes: summary o
Page 31 and 32: T2DM: Description and Risk of Bias
Page 33 and 34: Figure D. Plot of network meta-anal
Page 35 and 36: The positive findings for behaviora
Page 37 and 38: elated to the Human Development Ind
Page 39 and 40: Table D. Potential research needs b
Page 41 and 42: References 1. Renders CM, Valk GD,
Page 43: 37. Chodosh J, Morton SC, Mojica W,
Page 47 and 48: Factors other than blood glucose co
Page 49 and 50: may include interventions related t
Page 51 and 52: programs. The overarching boxes (co
Page 53 and 54: Figure 2. Analytic framework for be
Page 55 and 56: American Diabetes Association, Amer
Page 57 and 58: Table 1. Inclusion criteria for typ
Page 59 and 60: S1 in the Supplementary File). The
Page 61 and 62: clinically significant); we refer t
Page 63 and 64: Synthesis for T1DM (KQs 1-4) KQ 1:
Page 65 and 66: conducted for HbA 1c and body mass
Page 67 and 68: Applicability We followed the Metho
Page 69 and 70: Type 1 Diabetes Mellitus This secti
Page 71 and 72: therapy, 90,99,108 motivational enh
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Page 75 and 76: followup (low SOE for both); there
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Page 79 and 80: similar results were found for yout
Page 81 and 82: HbA 1c : Comparative Effectiveness
Page 83 and 84: Two trials reported on adherence to
Page 85 and 86: Table 4. Other clinical and behavio
Page 87 and 88: Figure 14. Behavioral programs for
Page 89 and 90: Health-Related Quality of Life: Beh
Page 91 and 92: estimated effects were imprecise an
Page 93 and 94: Table 8. Type 1 diabetes: summary o
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Summary of Key Findings and Strengt
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studies 82,94,95,105,109,112 were n
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studied a DSME program in patients
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I 2 =74%), 135,137,139,141,142,145,
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Aerobic Fitness Test which estimate
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Key Points: Body Mass Index • Lif
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Table 12. Network meta-analysis for
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Figure 20. Plot of network meta-ana
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active comparator (20 trials, 7,709
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Discussion Key Findings and Discuss
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to be tempered by the findings of n
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compared with usual care. There was
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Our finding that single-topic, non-
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In their systematic review and meta
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For studies targeting adults, the m
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environmental contextual factors—
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assessors was also rarely reported,
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Tailoring programs to ethnic minori
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17. Centers for Disease Control and
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53. Medical Advisory Secretariat. B
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88. Ellis DA, Templin T, Naar-King
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122. Nansel TR, Iannotti RJ, Simons
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158. Cooper H, Booth K, Gill G. A t
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191. Koo BK, Han KA, Ahn HJ, et al.
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224. Sevick MA, Korytkowski M, Ston
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260. Yuan C, Lai CW, Chan LW, et al
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295. Ayling K, Brierley S, Johnson
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Appendix A. Operational Definitions
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the structured diet or physical act
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Appendix B. Literature Search Strat
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1. MeSH descriptor: [Diabetes Melli
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35. “blood glucose” N2 monitor*
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35. (behavio?r adj2 therap*).mp. 36
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52. exp animals/ not humans.sh. 53.
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57. "Follow-Up Studies"[Mesh] 58. "
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URL provided by Michelle Crain, AAD
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WHO ICTRP Trial Registry: WHO ICTRP
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Appendix D. Studies Excluded After
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Health. 2006;6:134. PMID: 16709243.
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November/December;24(9):450-6. PMID
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89. Dinneen SF, O'hara MC, Byrne M,
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119. Fitzpatrick SL, Jeffery R, Joh
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Aug;19(8):835-42. PMID: 8842601. Ex
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adherence and metabolic control. Di
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May;36(5):1297-303. PMID: 23223405.
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244. Korytkowski MT, Koerbel GL, Ko
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275. Maljanian R, Grey N, Staff I,
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306. Naccashian Z. The impact of di
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led structured program on blood glu
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Engineering. 2014;75(1-B E). PMID:
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395. Skoro-Kondza L, Tai SS, Gadelr
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426. Torbjornsen A, Jenum AK, Smast
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Americans with type 2 diabetes. J A
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patients. Diabetes Res Clin Pract.
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Table E1. Risk of bias for studies
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Weinger, 2011 L M NA M NA L NA L L
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Cramer, 2007 M M H M H L H H L M H
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Ridgeway, 1999 M M H M H L H H M L
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Appendix F. Description of Studies
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Author, Year & Country Comparison &
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Table F3. Description of studies an
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Appendix H. Strength of Evidence Ta
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Outcome # Trials (# Subjects); Tool
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Table H3. Behavioral programs compa
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16. Mayer-Davis EJ, Seid M, Crandel
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Table I1. Effectiveness of behavior
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Category Health Outcomes Outcomes A
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Table I2. Effectiveness of behavior
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Category Outcomes Timepoint Health
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Outcome Change in Body Composition
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Outcome Change in Physical Activity
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References for Appendix I 1. Adachi
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32. Rock CL, Flatt SW, Pakiz B, et
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follow-up study. Diabetes Res Clin
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98. Johnson ST, Bell GJ, Mccargar L
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Appendix J. Network Meta-Analysis R
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5 11-26h In person Group only NA -0
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9 11-26h In person Group only NA -0
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