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Adaptive Intervention Designs to Promote Behavioral Change in Adults: What Is the Evidence?

  • Psychosocial Aspects (SS Jaser, Section Editor)
  • Published:
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Abstract

Purpose of Review

Adaptive behavioral interventions tailor the type or dose of intervention strategies to individuals over time to improve saliency and intervention efficacy. This review describes the unique characteristics of adaptive intervention designs, summarizes recent diabetes-related prevention studies, which used adaptive designs, and offers recommendations for future research.

Recent Findings

Eight adaptive intervention studies were reported since 2013 to reduce sedentary behavior or improve weight management in overweight or obese adults. Primarily, feasibility studies were conducted. Preliminary results suggest that just-in-time adaptive interventions can reduce sedentary behavior or increase minutes of physical activity through repeated prompts. A stepped-down weight management intervention did not increase weight loss compared to a fixed intervention. Other adaptive interventions to promote weight management are underway and require further evaluation.

Summary

Additional research is needed to target a broader range of health-related behaviors, identify optimal decision points and dose for intervention, develop effective engagement strategies, and evaluate outcomes using randomized trials.

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References

Papers of particular interest, published recently, have been highlighted as: •• Of major importance

  1. Franz MJ, Van Wormer JJ, Crain AL, Boucher JL, Histon T, Caplan W, et al. Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc. 2007;107:1755–67.

    Article  Google Scholar 

  2. Ely EK, Gruss SM, Luman ET, Gregg EW, Ali MK, Nhim K, et al. A national effort to prevent type 2 diabetes: participant-level evaluation of CDC’s National Diabetes Prevention Program. Diabetes Care. 2017;40:1289–341.

    Article  Google Scholar 

  3. Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med. 2010;17:161–7.

    Article  Google Scholar 

  4. Unick JL, Hogan PE, Neiberg RH, Cheskin LJ, Dutton GR, Evans-Hudnall G, et al. Evaluation of early weight loss thresholds for identifying nonresponders to an intensive lifestyle intervention. Obesity. 2014;22:1608–16.

    Article  Google Scholar 

  5. Miller CK, Nagaraja HN, Weinhold KR. Early weight-loss success identifies nonresponders after a lifestyle intervention in a worksite diabetes prevention trial. J Acad Nutr Diet. 2015;115:1464–71.

    Article  Google Scholar 

  6. Lei H, Nahum-Shani I, Lynch K, Oslin D, Murphy SA. A “SMART” design for building individualized treatment sequences. Annu Rev Clin Psychol. 2012;8:21–48.

    Article  CAS  Google Scholar 

  7. Murphy SA, Lynch KG, Oslin D, McKay JR, TenHave T. Developing adaptive treatment strategies in substance abuse research. Drug Alcohol Depend. 2007;88S:S24–30.

    Article  Google Scholar 

  8. Lavori PW, Dawson R. Adaptive treatment strategies in chronic disease. Annu Rev Med. 2008;59:443–53.

    Article  CAS  Google Scholar 

  9. •• Almirall D, Nahum-Shani I, Sherwood NE, Murphy SA. Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research. Transl Behav Med. 2014;4:260–74 Explains the aims of SMART designs and provides an overview of data analyses for these trials.

    Article  Google Scholar 

  10. Jakicic JM, Tate DF, Lang W, Davis KK, Polzien K, Rickman AD, et al. Effect of a stepped-care intervention approach on weight loss in adults: a randomized clinical trial. JAMA. 2012;307:2617–26.

    Article  CAS  Google Scholar 

  11. Carels RA, Darby L, Cacciapaglia HM, Douglass OM, Harper J, Kaplar ME, et al. Applying a stepped-care approach to the treatment of obesity. J Psychosom Res. 2005;59:375–83.

    Article  Google Scholar 

  12. Carels RA, Young KM, Hinman N, Gumble A, Koball A, Oehlhof MW, et al. Stepped-care in obesity treatment: matching treatment intensity to participant performance. Eat Behav. 2012;13:112–8.

    Article  Google Scholar 

  13. Carels RA, Hoffmann DA, Hinman N, Burmeister JB, Koball A, Ashrafloun L, et al. Step-down approach to behavioral weight loss treatment: a pilot of a randomized clinical trial. Psychol Health. 2013;28:1121–34.

    Article  Google Scholar 

  14. Collins LM. Optimization of behavioral, biobehavioral, and biomedical interventions: the multiphase optimization strategy (MOST). Springer International Publishing: 2018. Doi: https://link.springer.com/book/10.1007%2F978-3-319-72206-1

  15. American Diabetes Association. Comprehensive medical evaluation and assessment of comorbidities: standards of medical care in diabetes-2018. Diabetes Care. 2018;41(suppl 1):S28–37.

    Article  Google Scholar 

  16. Davies MJ, D’Alessio DA, Fradkin J, Kernan WN, Mathiew C, Mingrone G, et al. Management of hyperglycemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2018. https://doi.org/10.2337/dc118-0033.

  17. van Dantzig S, Geleijnse G, van Halteren AT. Toward a persuasive mobile application to reduce sedentary behavior. Pers Ubiquitous Comput. 2013;17:1237–46.

    Article  Google Scholar 

  18. Bond DS, Thomas JG, Raynor HA, Moon J, Sieling J, Trautvetter J, et al. B-MOBILE – a smartphone-based intervention to reduce sedentary time in overweight/obese individuals: a within-subjects experimental trial. PLoS One. 2014;9:3100821.

    Google Scholar 

  19. •• Muller AM, Blandford A, Yardley L. The conceptualization of a just-in-time adaptive intervention (JITAI) for the reduction of sedentary behavior in older adults. mHealth. 2017;3:37. Explains in detail the theoretical and empirical evidence used during the development of a JITAI to reduce sedentary behavior.

    Article  Google Scholar 

  20. Goldstein SP, Evans BC, Flack D, Juarascio A, Manasse S, Zhang F, et al. Return of the JITAI: applying a just-in-time adaptive intervention framework to the development of mHealth solutions for addictive behaviors. Int J Behav Med. 2017;24:673–82.

    Article  Google Scholar 

  21. Rabbi M, Pfammatter A, Zhang M, Spring B, Choudhury T. Automated personalized feedback for physical activity and dietary behavior change with mobile phones: a randomized controlled trial on adults. JMIR mHealth uHeatlh. 2015;3:e42.

    Article  Google Scholar 

  22. Downs DS, Savage JS, Rivera DE, Smyth JM, Rolls BJ, Hohman EE, et al. Individually tailored, adaptive intervention to manage gestational weight gain: protocol for a randomized controlled trial in women with overweight and obesity. JMIR Res Protoc. 2018;7:e150.

    Article  Google Scholar 

  23. Sherwood NE, Butryn ML, Forman EM, Almirall D, Seburg EM, Crain AL, et al. The BestFIT trial: a SMART approach to developing individualized weight loss treatments. Control Clin Trials. 2016;47:209–16.

    Article  Google Scholar 

  24. Riley WT, Rivera DE, Atienza AA, Nilsen W, Allison SM, Mermelstein R. Health behavior models in the age of mobile interventions: are our theories up to the task? Transl Behav Med.. 2011;1:53–71.

    Article  Google Scholar 

  25. Nahum-Shani I, Hekler EB, Spruijt-Metz D. Building health behavior models to guide the development of just-in-time adaptive interventions: a pragmatic framework. Health Psychol. 2015;34:1209–19.

    Article  Google Scholar 

  26. •• Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, et al. Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support. Ann Behav Med. 2018;52:446–62 Discusses the motivation for developing JITAIs and design principles for these interventions.

    Article  Google Scholar 

  27. Collins LM, Murphy SA, Bierman KL. A conceptual framework for adaptive preventive interventions. Prev Sci. 2004;5:185–96.

    Article  Google Scholar 

  28. Kristal AR, Andrilla HA, Koepsell TD, Diehr PH, Cheadle A. Dietary assessment instruments are susceptible to intervention-associated response set bias. J Am Diet Assoc. 1998;98:40–3.

    Article  CAS  Google Scholar 

  29. Dwyer JT, Krall EA, Coleman KA. The problem of memory in nutritional epidemiology research. J Am Diet Assoc. 1987;87:1509–12.

    CAS  PubMed  Google Scholar 

  30. Fitipaldi H, McCarthy MI, Florez JC, Franks PW. A global overview of precision medicine in type 2 diabetes. Diabetes. 2018;67:1911–22.

    Article  CAS  Google Scholar 

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Acknowledgments

The author thanks Dr. Brian Focht for helpful comments on an earlier version of this manuscript.

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Authors and Affiliations

  1. Department of Human Sciences/Human Nutrition, Ohio State University, 1787 Neil Ave., 325 Campbell Hall, Columbus, OH, 43210, USA

    Carla K. Miller

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  1. Carla K. Miller
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Correspondence to Carla K. Miller.

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Carla K. Miller declares that she has no conflict of interest.

Human and Animal Rights and Informed Consent

All reported studies/experiments with human or animal subjects performed by the authors have been previously published and complied with all applicable ethical standards (including the Helsinki Declaration and its amendments, institutional/national research committee standards, and international/national/institutional guidelines).

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Miller, C.K. Adaptive Intervention Designs to Promote Behavioral Change in Adults: What Is the Evidence?. Curr Diab Rep 19, 7 (2019). https://doi.org/10.1007/s11892-019-1127-4

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