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Scaling Science-Based Approaches Beyond the Clinic

  • Alexis C. Wojtanowski
  • Gary D. Foster
Chapter

Abstract

The behavioral treatment of obesity, alone or in combination with pharmacotherapy or bariatric surgery, is the cornerstone of effective weight management and recommended as the first line of treatment. Expert panels, including the United States Preventive Services Task Force (USPSTF), the American Heart Association (AHA), the American College of Cardiology (ACC), and The Obesity Society (TOS), have developed a list of specific criteria for effective comprehensive behavioral weight management programs. These guidelines recommend that physicians offer such treatments or refer to programs that meet empirically based criteria. The reality, however, is that remarkably few providers or other healthcare professionals are able to overcome the barriers of lack of time, reimbursement, and training, to effectively provide the kind of empirically based treatment described by the panels. Specialized clinics and providers can help, but their number pales in comparison to the number of patients seeking effective solutions. Given the prevalence of overweight and obesity, the potential of commercial behavioral weight management programs lies in their scalability through standardized programs, multiple community locations, and costs that compare favorably to clinic-based approaches. Not all programs are created equal, however, and while many commercial weight management programs incorporate behavioral content, remarkably few have empirical support from randomized controlled trials. This chapter reviews widely available commercial behavioral weight management programs, both face-to-face and app-based, with an emphasis on those with empirical support. Such empirical evidence can help providers and patients make sense of countless programs that often overpromise and under deliver.

Keywords

Commercial weight loss mHealth weight management apps 

References

  1. 1.
    National Center for Health Statistics. Health, United States, 2016: with chartbook on long-term trends in health, DHHS Publication No.: 2017-1232. Hyattsville, MD: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2017. 488 p.Google Scholar
  2. 2.
    ASMBS and NORC at the University of Chicago. Issue brief: new insights into Americans’ perceptions and misperceptions of obesity treatments, and the struggles many face. ASMBS and NORC at the University of Chicago; 2016. Available from: http://www.norc.org/PDFs/ASMBS%20Obesity/Issue%20Brief%20B_ASMBS%20NORC%20Obesity%20Poll.pdf.
  3. 3.
    Wadden TA, Webb VL, Moran CH, Bailer BA. Lifestyle modification for obesity: new developments in diet, physical activity, and behavior therapy. Circulation. 2012;125(9):1157–70.CrossRefGoogle Scholar
  4. 4.
    Moyer VA. Screening for and management of obesity in adults: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med. 2012;157(5):373–8.PubMedGoogle Scholar
  5. 5.
    Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2014;63(25 Part B):2985–3023.CrossRefGoogle Scholar
  6. 6.
    Foster GD, Wadden TA, Makris AP, Davidson D, Sanderson RS, Allison DB, Kessler A. Primary care physicians’ attitudes about obesity and its treatment. Obesity. 2003;11(10):1168–77.CrossRefGoogle Scholar
  7. 7.
    Gudzune KA, Doshi RS, Mehta AK, Chaudhry ZW, Jacobs DK, Vakil RM, Lee CJ, Bleich SN, Clark JM. Efficacy of commercial weight-loss programs: an updated systematic review. Ann Intern Med. 2015;162(7):501–12.CrossRefGoogle Scholar
  8. 8.
    Prevention D. Programme (DPP) Research Group. The Diabetes Prevention Program (DPP). Description of lifestyle intervention. Diabetes Care. 2002;25:2165–71.CrossRefGoogle Scholar
  9. 9.
    Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81–95.CrossRefGoogle Scholar
  10. 10.
    Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol. 2008;27(3):379.CrossRefGoogle Scholar
  11. 11.
    Doshi A, Patrick K, Sallis JF, Calfas K. Evaluation of physical activity web sites for use of behavior change theories. Ann Behav Med. 2003;25(2):105–11.CrossRefGoogle Scholar
  12. 12.
    O’Neil PM, Miller-Kovach K, Tuerk PW, Becker LE, Wadden TA, Fujioka K, Hollander PL, Kushner RF, Timothy Garvey W, Rubino DM, Malcolm RJ. Randomized controlled trial of a nationally available weight control program tailored for adults with type 2 diabetes. Obesity. 2016;24(11):2269–77.CrossRefGoogle Scholar
  13. 13.
    Marrero DG, Palmer KN, Phillips EO, Miller-Kovach K, Foster GD, Saha CK. Comparison of commercial and self-initiated weight loss programs in people with prediabetes: a randomized control trial. Am J Public Health. 2016;106(5):949–56.CrossRefGoogle Scholar
  14. 14.
    Ahern AL, Wheeler GM, Aveyard P, Boyland EJ, Halford JC, Mander AP, Woolston J, Thomson AM, Tsiountsioura M, Cole D, Mead BR. Extended and standard duration weight-loss programme referrals for adults in primary care (WRAP): a randomised controlled trial. Lancet. 2017;389(10085):2214–25.CrossRefGoogle Scholar
  15. 15.
    Cook CM, McCormick CN, Knowles M, Kaden VN. A commercially available portion controlled diet program is more effective for weight loss than a self-directed diet: results from a randomized clinical trial. Front Nutr. 2017;4:55.CrossRefGoogle Scholar
  16. 16.
    Pew Research Center, Internet & Technology. Mobile fact sheet. [Internet]. 2018. [2018 Feb; cited 2018 Mar 22]. Available from: http://www.pewinternet.org/fact-sheet/mobile/.
  17. 17.
    Research2guidance report. The mHealth app market is getting crowded reaching the 259,000 apps. [Internet]. 2016 [2016 Oct 13; cited 2018 Mar 22]. Available from: https://www.ticbiomed.org/2016/10/13/the-mhealth-app-market-is-getting-crowded-reaching-the-259-000-apps/.
  18. 18.
    Kasbo A, McLaughlin R. Mobile health applications: 2012 study. [Internet]. 2012. [2012 Aug 6; cited 2018 Mar 22]. Available from: https://verasoni.com/ahha3/mobile-health-applications-2012-study/.
  19. 19.
    Bardus M, van Beurden SB, Smith JR, Abraham C. A review and content analysis of engagement, functionality, aesthetics, information quality, and change techniques in the most popular commercial apps for weight management. Int J Behav Nutr Phys Act. 2016;13(1):35.CrossRefGoogle Scholar
  20. 20.
    Azar KM, Lesser LI, Laing BY, Stephens J, Aurora MS, Burke LE, Palaniappan LP. Mobile applications for weight management: theory-based content analysis. Am J Prev Med. 2013;45(5):583–9.CrossRefGoogle Scholar
  21. 21.
    Middelweerd A, Mollee JS, van der Wal CN, Brug J, Te Velde SJ. Apps to promote physical activity among adults: a review and content analysis. Int J Behav Nutr Phys Act. 2014;11(1):97.CrossRefGoogle Scholar
  22. 22.
    Conroy DE, Yang CH, Maher JP. Behavior change techniques in top-ranked mobile apps for physical activity. Am J Prev Med. 2014;46(6):649–52.CrossRefGoogle Scholar
  23. 23.
    Yang CH, Maher JP, Conroy DE. Implementation of behavior change techniques in mobile applications for physical activity. Am J Prev Med. 2015;48(4):452–5.CrossRefGoogle Scholar
  24. 24.
    Pagoto S, Schneider K, Jojic M, DeBiasse M, Mann D. Evidence-based strategies in weight-loss mobile apps. Am J Prev Med. 2013;45(5):576–82.CrossRefGoogle Scholar
  25. 25.
    Laing BY, Mangione CM, Tseng CH, Leng M, Vaisberg E, Mahida M, Bholat M, Glazier E, Morisky DE, Bell DS. Effectiveness of a smartphone application for weight loss compared with usual care in overweight primary care patients: a randomized, controlled trial. Ann Intern Med. 2014;161(10_Supplement):S5–12.CrossRefGoogle Scholar
  26. 26.
    Thomas JG, Raynor HA, Bond DS, Luke AK, Cardoso CC, Foster GD, Wing RR. Weight loss in Weight Watchers Online with and without an activity tracking device compared to control: a randomized trial. Obesity. 2017;25(6):1014–21.CrossRefGoogle Scholar
  27. 27.
    Thomas JG, Raynor HA, Bond DS, Luke AK, Cardoso CC, Wojtanowski AC, Vander Veur S, Tate D, Wing RR, Foster GD. Weight loss and frequency of body-weight self-monitoring in an online commercial weight management program with and without a cellular-connected ‘smart’ scale: a randomized pilot study. Obes Sci Pract. 2017;3(4):365–72.CrossRefGoogle Scholar
  28. 28.
    Foster GD, Makris A, Wojtanowski AC. The role of scalable, community-based weight management programs. In: Brownell KD, Walsh BT, editors. Eating disorders and obesity: a comprehensive handbook. 3rd ed. New York: Guildford Press; 2017. p. 538–45.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexis C. Wojtanowski
    • 1
  • Gary D. Foster
    • 1
    • 2
    • 3
  1. 1.WW International, Inc.New YorkUSA
  2. 2.Center for Weight and Eating DisordersPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaUSA
  3. 3.Center for Obesity Research and EducationTemple UniversityPhiladelphiaUSA

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