Skip to main content

Advertisement

SpringerLink
Log in

Initial engagement and attrition in a national weight management program: demographic and health predictors

  • Original Research
  • Published:
Translational Behavioral Medicine

Abstract

Inconsistent attendance and participant withdrawal limit the effectiveness of weight control programs, but little is known about predictors of initial and ongoing engagement. The purpose of this study was to identify these predictors with respect to the Veterans Affairs MOVE!® program, using medical record data. Logistic regression models were used to predict initial and ongoing engagement (n = 39,862 and 1985, respectively). Those who initially engaged in MOVE!® (vs. did not) were more likely to have high BMIs, to be female, live closer to the medical center, and receive health benefits from the VA; they also were less likely to use tobacco (ps < 0.02). Older veterans were more likely to continue to engage (p < 0.001), with trends toward continued engagement for those with (vs. without) benefits and higher BMIs (ps < 0.10). Findings highlight characteristics that may inform program improvements that promote ongoing engagement and prevent dropouts in a weight management programs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Moroshko I, Brennan L, O’Brien P. Predictors of dropout in weight loss interventions: a systematic review of the literature. Obes Rev. 2011; 12: 912-934.

    Article  CAS  PubMed  Google Scholar 

  2. Carels RA, Cacciapaglia HM, Douglass OM, et al. The early identification of poor treatment outcome in a women’s weight loss program. Eat Behav. 2003; 4: 265-282.

    Article  PubMed  Google Scholar 

  3. Kaplan RM, Atkins CJ. Selective continued attendance causes overestimates of treatment effects in studies of weight loss. Addict Behav. 1987; 12: 297-302.

    Article  CAS  PubMed  Google Scholar 

  4. Bautista-Castano I, Molina-Cabrillana J, Montoya-Aolonso JA, et al. Variables predictive of adherence to diet and physical activity recommendations in the treatment of obesity and overweight, in a group of Spanish subjects. Int J Obes Relat Metab Disord. 2004; 28: 697-705.

    Article  CAS  PubMed  Google Scholar 

  5. Honas JJ, Early JL, Frederickson DD, et al. Predictors of continued attendance in a large clinic-based weight-loss program. Obes Res. 2003; 11: 888-894.

    Article  PubMed  Google Scholar 

  6. Grossi E, Dalle Grave R, Mannucci E, et al. Complexity of continued attendance in the treatment of obesity: clues from a structured telephone interview. Int J Obes. 2006; 30: 1132-1137.

    Article  CAS  Google Scholar 

  7. Inelmen E, Toffanello ED, Enzi G, et al. Predictors of drop-out in overweight and obese outpatients. Int J Obes. 2004; 29: 122-128.

    Article  Google Scholar 

  8. Teixeira PJ, Going SB, Houtkooper LB, et al. Pretreatment predictors of continued attendance and successful weight management in women. Int J Obes Relat Metab Disord. 2004; 28: 1124-1133.

    Article  CAS  PubMed  Google Scholar 

  9. Dalle Grave R, Calugi S, Molinari E, et al. Weight loss expectations in obese patients and treatment continued attendance: an observational multicenter study. Obes Res. 2005; 13: 1961-1969.

    Article  PubMed  Google Scholar 

  10. Clark M, Niaura R, King T, Pera V. Depression, smoking, activity level, and predictors of continued attendance in obesity treatment. Addict Behav. 1996; 21: 509-513.

    Article  CAS  PubMed  Google Scholar 

  11. Davis MJ, Addis ME. Predictors of attrition from behavioral medicine treatments. Ann Behav Med. 1999; 21: 339-349.

    Article  CAS  PubMed  Google Scholar 

  12. Gorin AA, Raynor HA, Fava J, et al. Randomized controlled trial of a comprehensive home environment-focused weight-loss program for adults. Health Psychol. 2013; 32: 128-137.

    Article  PubMed  Google Scholar 

  13. Elfhag K, Rossner S. Initial weight loss is the best predictor for success in obesity treatment and sociodemographic liabilities increase risk for drop-out. Patient Educ Couns. 2010; 79: 361-366.

    Article  PubMed  Google Scholar 

  14. Kolotkin RL, Moore JM. Attrition in a behavioral weight‐control program: a comparison of dropouts and completers. Int J Eat Disord. 1983; 2: 93-100.

    Article  Google Scholar 

  15. Fabricatore AN, Wadden TA, Moore RH, et al. Predictors of continued attendance and weight loss success: results from a randomized controlled trial. Behav Res Ther. 2009; 47: 685-691.

    Article  PubMed  PubMed Central  Google Scholar 

  16. De Panfilis C, Torre M, Cero S, et al. Personality and continued attendance from behavioral weight-loss for obesity. Gen Hosp Psychiatry. 2008; 30: 515-520.

    Article  PubMed  Google Scholar 

  17. Pekarik G, Blodgett C, Evans RG, et al. Variables related to continuance in a behavioral weight loss program. Addict Behav. 1984; 9: 413-416.

    Article  CAS  PubMed  Google Scholar 

  18. Lahti-Koski M, Pietinen P, Heliövaara M, Vartiainen E. Associations of body mass index and obesity with physical activity, food choices, alcohol intake, and smoking in the 1982–1997 FINRISK Studies. Am J Clin Nutr. 2002; 75: 809-817.

    CAS  PubMed  Google Scholar 

  19. Healton CG, Vallone D, McCausland KL, Xiao H, Green MP. Smoking, obesity, and their co-occurrence in the United States: cross sectional analysis. BMJ. 2006; 333: 25-26.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Douketis JD, Macie C, Thabane L, Williamson DF. Systematic review of long-term weight loss studies in obese adults: clinical significance and applicability to clinical practice. Int J Obes. 2005; 29: 1153-1167.

    Article  CAS  Google Scholar 

  21. Koepsell TD, Forsberg CW, Littman AJ. Obesity, overweight, and weight control practices in U.S. veterans. Prev Med. 2009; 48: 267-271.

    Article  PubMed  Google Scholar 

  22. Dahn JR, Fitzpatrick SL, Llabre MM, et al. Weight management for veterans: examining change in weight before and after MOVE®. Obesity. 2010; 19: 977-981.

    Article  PubMed  Google Scholar 

  23. Damschroder LJ, Goodrich DE, Robinson CH, Fletcher CE, Lowery JC. A systematic exploration of differences in contextual factors related to implementing the MOVE!® weight management program in VA: a mixed methods study. BMC Health Serv Res. 2011; 11: 248.

    Article  PubMed  Google Scholar 

  24. Arigo D, Hooker S, Funderburk JS, Dundon P, et al. (in press.) Provider and staff perceptions of veterans’ continued attendance from a national primary care weight management program. Prim Health Care Res Dev.

  25. Locatelli SM, Sohn MW, Spring B, Hadi S, Weaver FM. Peer reviewed: participant retention in the Veterans Health Administration’s MOVE!® weight management program. Prev Chronic Dis. 2012; 9.

  26. Littman AJ, Boyko EJ, McDonell MB, Fihn S. Evaluation of a weight management program for veterans. Prev Chronic Dis. 2012; 9, E99.

    PubMed  PubMed Central  Google Scholar 

  27. Cronin KA, Miglioretti DL, Krapcho M, et al. Bias associated with self-report of prior screening mammography. Cancer Epidemiol Biomark Prev. 2009; 18: 1699-1705.

    Article  Google Scholar 

  28. Bauhoff S. Systematic self-report bias in health data: impact on estimating cross-sectional and treatment effects. Health Serv Outcomes Res Methodol. 2011; 11: 44-53.

    Article  Google Scholar 

  29. Zivin K, Kim HM, McCarthy JF, et al. Suicide mortality among individuals receiving treatment for depression in the Veterans Affairs health system: associations with patient and treatment setting characteristics. Am J Public Health. 2007; 97: 2193-2198.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Noel PH, Copeland LA, Perrin RA, et al. VHA corporate data warehouse height and weight data: opportunities and challenges for health services research. J Rehabil Res Dev. 2010; 47: 739-750.

    Article  PubMed  Google Scholar 

  31. Kerr EA, Smith DM, Hogan MM, et al. Comparing clinical automated, medical record, and hybrid data sources for diabetes quality measures. Jt Comm J Qual Patient Saf. 2002; 28: 555-565.

    Google Scholar 

  32. Weaver FM, Collins EG, Kurichi J, et al. Prevalence of obesity and high blood pressure in veterans with spinal cord injuries and disorders: a retrospective review. Am J Phys Med Rehabil. 2007; 86: 22-29.

    Article  PubMed  Google Scholar 

  33. SAS Institute. SAS language reference: dictionary, version 8. SAS Institute. 2000.

  34. National Center for Veteran Analysis and Statistics. Available at http://www.va.gov/VETDATA/docs/SpecialReports/Profile_of_Veterans_2011.pdf. Accessibility verified March 13, 2014.

  35. Edens EL, Kasprow W, Tsai J, Rosenheck RA. Association of substance use and VA service‐connected disability benefits with risk of homelessness among veterans. Am J Addict. 2011; 20: 412-419.

    Article  PubMed  Google Scholar 

  36. Gill T. Importance of preventing weight gain in adulthood. Asia Pac J Clin Nutr. 2002; 11: S632-S636.

    Article  Google Scholar 

  37. Ford ES, Moriarty DG, Zack MM, Mokdad AH, Chapman DP. Self-reported body mass index and health-related quality of life: findings from the behavioral risk factor surveillance system. Obes Res. 2012; 9: 21-31.

    Article  Google Scholar 

  38. Derraik JGB, de Bock M, Hofman PL, Cutfield WS. Increasing BMI is associated with a progressive reduction in physical quality of life among overweight middle-aged men. Sci Rep. 2013; 4: 1-4.

    Google Scholar 

  39. Mauro M, Taylor V, Wharton S, Sharma AM. Barriers to obesity treatment. Eur J Intern Med. 2008; 19: 173-180.

    Article  PubMed  Google Scholar 

  40. Emmons KM, Marcus BH, Linnan L, Rossi JS, Abrams DB. Mechanisms in multiple risk factor interventions: smoking, physical activity, and dietary-fat intake among manufacturing workers. Prev Med. 1994; 23: 481-489.

    Article  CAS  PubMed  Google Scholar 

  41. Abood D, Conway T. Smoking status, body composition, exercise and diet among navy men. Health Values. 1994; 18: 51-62.

    Google Scholar 

  42. Brouwer RJ, Pomerleau CS. “Prequit continued attendance” among weight-concerned women smokers. Eat Behav. 2000; 1: 145-151.

    Article  CAS  PubMed  Google Scholar 

  43. Copeland AL, Martin PD, Geiselman PJ, Rash CJ, Kendzor DE. Predictors of pretreatment continued attendance from smoking cessation among pre- and postmenopausal, weight-concerned women. Eat Behav. 2000; 7: 243-251.

    Article  Google Scholar 

  44. Klesges RC, Brown K, Pascale RW, et al. Factors associated with participation, continued attendance and outcome in a smoking cessation program in the workplace. Health Psychol. 1988; 7(6): 575-589.

    Article  CAS  PubMed  Google Scholar 

  45. Glasgow RE, Nelson CC, Kearney KA, et al. Reach, engagement and retention in an internet-based weight loss program in a multi-site randomized controlled trial. J Med Internet Res. 2007; 9, e11.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Kinsinger LS, Jones KR, Kahwati L, et al. Peer reviewed: design and dissemination of the MOVE! weight management program for veterans. Prev Chronic Dis. 2009; 6(3): A98.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The views expressed in this article are those of the authors and do not reflect the official policy of the Department of Veterans Affairs or other departments of the US government. This material is based upon work supported by the VA Center for Integrated Healthcare.

Conflict of interest

The authors declare that they have no competing interests.

Compliance with ethical standards

All procedures were conducted in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.

Author information

Authors and Affiliations

  1. VA Center for Integrated Healthcare, Syracuse VA Medical Center, 800 Irving Ave., Syracuse, NY, 13210, USA

    J. S. Funderburk Ph.D., D. Arigo Ph.D. & A. Kenneson Ph.D., M.S.

  2. Department of Clinical Psychology, Syracuse University, Syracuse, NY, USA

    J. S. Funderburk Ph.D.

  3. Department of Psychiatry, University of Rochester, Rochester, NY, USA

    J. S. Funderburk Ph.D.

  4. Department of Psychology, University of Scranton, Scranton, PA, USA

    D. Arigo Ph.D.

Authors
  1. J. S. Funderburk Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. Arigo Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Kenneson Ph.D., M.S.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. S. Funderburk Ph.D..

Additional information

Implications

Practice: To increase initial engagement in any weight management program, staff can provide additional encouragement to patients with a lower body mass index (albeit categorized as overweight/obese), live farther from the medical center, and who smoke tobacco.

Policy: Policy makers need to ensure that weight loss programs have identified ways to examine factors that predict initial and continued engagement and develop targeted ways to increase engagement rates.

Research: Additional investigation into factors associated with initial and continued engagement using a more diverse sample, and different types of interventions can be used to increase engagement and attendance.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Funderburk, J.S., Arigo, D. & Kenneson, A. Initial engagement and attrition in a national weight management program: demographic and health predictors. Behav. Med. Pract. Policy Res. 6, 358–368 (2016). https://doi.org/10.1007/s13142-015-0335-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13142-015-0335-y

Keywords

Search

Navigation