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Treatment matching for obesity: identifying mediators of psychosocial and behavioral intervention components

International Journal of Obesity Supplements volume 2, pages S23–S25 (2012)Cite this article

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Abstract

In light of the limited long-term success of obesity treatments, it is tempting to consider the elusive goal of ‘treatment matching’, in which characteristics of individuals are optimally matched to targeted treatments to improve success. Previous frameworks for treatment matching in obesity have primarily focused on basic physiological characteristics, such as initial degree of overweight, and on treatment intensity, such as stepped-care alternatives (self-help manuals, group support, medication and surgery). Few studies have empirically evaluated the success of these frameworks. Given recent advances in genomics, neuroscience and other fields, both the breadth of domains and combinations of individuals’ characteristics that could be used for treatment matching have increased markedly. Although the obesity field seems poised to build on these advances, a crucial challenge remains regarding the treatments themselves. Ultimately, the success of treatment matching will rely on identifying treatment intervention components with well-differentiated and empirically supported mediators, that is, clear insights into how intervention components work. Here we examine the scope of this challenge specifically for the design of efficacious psychosocial and behavioral intervention components, and identify areas for future research.

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References

  1. Brownell KD, Wadden TA . The heterogeneity of obesity: fitting treatments to individuals. Behav Ther 1991; 22: 153–177.

    Article  Google Scholar 

  2. Teixeira PJ, Going SB, Sardinha LB, Lohman TG . A review of psychosocial pre-treatment predictors of weight control. Obes Rev 2005; 6: 43–65.

    Article  CAS  Google Scholar 

  3. King AC, Ahn DF, Atienza AA, Kraemer HC . Exploring refinements in targeted behavioral medicine intervention to advance public health. Ann Behav Med 2008; 35: 251–260.

    Article  Google Scholar 

  4. Thomas PR . Weighing the Options: Criteria for Evaluating Weight-Management Programs. The National Academies Press: Washington, DC, 1995.

    Book  Google Scholar 

  5. Kraemer HC, Kiernan M, Essex M, Kupfer DJ . How and why criteria defining moderators and mediators differ between the Baron & Kenny and MacArthur approaches. Health Psychol 2008; 27: S101–S108.

    Article  Google Scholar 

  6. Kiernan M, King AC, Kraemer HC, Stefanick ML, Killen JD . Characteristics of successful and unsuccessful dieters: an application of signal detection methodology. Ann Behav Med 1998; 20: 1–6.

    Article  CAS  Google Scholar 

  7. Kent DM, Rothwell PM, Ioannidis JPA, Altman DG, Hayward RA . Assessing and reporting heterogeneity in treatment effects in clinical trials: A proposal. Trials 2010; 11: 85.

    Article  Google Scholar 

  8. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346: 393–403.

    Article  Google Scholar 

  9. Diabetes Prevention Program Research Group. The Diabetes Prevention Program (DPP): description of lifestyle intervention. Diabetes Care 2002; 25: 2165–2171.

    Article  Google Scholar 

  10. Brownell KD, Marlatt GA, Lichtenstein E, Wilson GT . Understanding and preventing relapse. Am Psychol 1986; 41: 765–782.

    Article  CAS  Google Scholar 

  11. Perri MG, Limacher MC, Durning PE, Janicke DM, Lutes LD, Bobroff LB et al. Extended-care programs for weight management in rural communities. Arch Intern Med 2008; 168: 2347–2354.

    Article  Google Scholar 

  12. Tate DF . Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: A randomized trial. JAMA 2003; 289: 1833–1836.

    Article  Google Scholar 

  13. Harvey-Berino J, Pintauro S, Buzzell P, Gold BC . Effect of internet support on the long-term maintenance of weight loss. Obes Res 2004; 12: 320–329.

    Article  Google Scholar 

  14. Perri MG, Nezu AM, McKelvey WF, Shermer RL, Renjilian DA, Viegener BJ . Relapse prevention training and problem-solving therapy in the long-term management of obesity. J Consult Clin Psychol 2001; 69: 722–726.

    Article  CAS  Google Scholar 

  15. Nezu AM, Ronan GF . Life stress, current problems, problem solving, and depressive symptomatology: An integrative model. J Consult Clin Psychol 1985; 53: 693–697.

    Article  CAS  Google Scholar 

  16. Kraemer HC, Wilson GT, Fairburn CG, Agras WS . Mediators and moderators of treatment effects in randomized clinicial trials. Arch Gen Psychiatry 2002; 59: 877–883.

    Article  Google Scholar 

  17. Wing RR, Jeffery RW . Benefits of recruiting participants with friends and increasing social support for weight loss and maintenance. J Consult Clin Psychol 1999; 67: 132–138.

    Article  CAS  Google Scholar 

  18. Moyer A, Finney JW, Elworth JT, Kraemer HC . Can methodological findings account for patient-treatment matching findings in the alcohol field? J Stud Alcohol 2001; 62: 62–73.

    Article  CAS  Google Scholar 

  19. Foster NE, Hill JC, Hay EM . Subgrouping patients with low back pain in primary care: Are we getting any better at it? Man Ther 2011; 16: 3–8.

    Article  Google Scholar 

  20. Kiernan M, Moore SD, Schoffman D, Lee K, King AC, Taylor CB et al. Social support for healthy behaviors: Scale psychometrics and prediction of weight loss among women in a behavioral program. Obesity 2011; 20: 756–764.

    Article  Google Scholar 

  21. Wadden TA, Crerand CE, Brock J . Behavioral treatment of obesity. Psychiatr Clin N Am 2005; 28: 151–170.

    Article  Google Scholar 

  22. Stunkard AJ, Messick S . The three-factor eating questionnaire to measure dietary restraint, disinhibition, and hunger. J Psychosom Res 1985; 29: 71–83.

    Article  CAS  Google Scholar 

  23. Cohen S, Kamarck T, Mermelstein R . A global measure of perceived stress. J Health Soc Behav 1983; 24: 385–396.

    Article  CAS  Google Scholar 

  24. Kiernan M, Lee K, Schoffman DE, Brown SD, Fair J, Taylor-Piliae RE et al. Using the Stanford Leisure-Time Activity Categorical Item (L-Cat) to assess changes in leisure-time activity among obese women. Ann Behav Med 2011; 41: S187.

    Google Scholar 

Download references

Acknowledgements

Publication of this supplement was partially supported by Nutrilite Health Institute with an unrestricted educational contribution to Stanford Prevention Research Center.

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  1. Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA

    M Kiernan

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  1. M Kiernan
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Correspondence to M Kiernan.

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Kiernan, M. Treatment matching for obesity: identifying mediators of psychosocial and behavioral intervention components. Int J Obes Supp 2 (Suppl 1), S23–S25 (2012). https://doi.org/10.1038/ijosup.2012.6

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