Peer-Assisted Lifestyle (PAL) intervention: a protocol of a cluster-randomised controlled trial of a health-coaching intervention delivered by veteran peers to improve obesity treatment in primary care

Sandra Wittleder, Shea Smith, Binhuan Wang, Jeannette M Beasley, Stephanie L Orstad, Victoria Sweat, Allison Squires, Laura Wong, Yixin Fang, Paula Doebrich, Damara Gutnick, Craig Tenner, Scott E Sherman, Melanie Jay, Sandra Wittleder, Shea Smith, Binhuan Wang, Jeannette M Beasley, Stephanie L Orstad, Victoria Sweat, Allison Squires, Laura Wong, Yixin Fang, Paula Doebrich, Damara Gutnick, Craig Tenner, Scott E Sherman, Melanie Jay

Abstract

Introduction: Among US veterans, more than 78% have a body mass index (BMI) in the overweight (≥25 kg/m2) or obese range (≥30 kg/m2). Clinical guidelines recommend multicomponent lifestyle programmes to promote modest, clinically significant body mass (BM) loss. Primary care providers (PCPs) often lack time to counsel and refer patients to intensive programmes (≥6 sessions over 3 months). Using peer coaches to deliver obesity counselling in primary care may increase patient motivation, promote behavioural change and address the specific needs of veterans. We describe the rationale and design of a cluster-randomised controlled trial to test the efficacy of the Peer-Assisted Lifestyle (PAL) intervention compared with enhanced usual care (EUC) to improve BM loss, clinical and behavioural outcomes (aim 1); identify BM-loss predictors (aim 2); and increase PCP counselling (aim 3).

Methods and analysis: We are recruiting 461 veterans aged 18-69 years with obesity or overweight with an obesity-associated condition under the care of a PCP at the Brooklyn campus of the Veterans Affairs NY Harbor Healthcare System. To deliver counselling, PAL uses in-person and telephone-based peer support, a tablet-delivered goal-setting tool and PCP training. Patients in the EUC arm receive non-tailored healthy living handouts. In-person data collection occurs at baseline, month 6 and month 12 for patients in both arms. Repeated measures modelling based on mixed models will compare mean BM loss (primary outcome) between study arms.

Ethics and dissemination: The protocol has been approved by the Institutional Review Board and the Research and Development Committee at the VA NY Harbor Health Systems (#01607). We will disseminate the results via peer-reviewed publications, conference presentations and meetings with stakeholders.

Trial registration number: NCT03163264; Pre-results.

Keywords: medical education & training; nutrition & dietetics; primary care.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
The Peer-Assisted Lifestyle (PAL) study design. EUC, enhanced usual care; PCP, primary care provider.
Figure 2
Figure 2
Integration of the Peer-Assisted Lifestyle (PAL) intervention components and the 5As (Assess, Advise, Agree, Assist, Arrange) counselling framework. PCP, primary care provider; SMART, Specific, Measurable, Attainable, Relevant, Timely.
Figure 3
Figure 3
Logic model of the clinical reminder to facilitate weight management counselling.

References

    1. Rush T, LeardMann CA, Crum-Cianflone NF. Obesity and associated adverse health outcomes among US military members and veterans: findings from the millennium cohort study. Obesity 2016;24:1582–9. 10.1002/oby.21513
    1. Nelson KM. The burden of obesity among a national probability sample of Veterans. J Gen Intern Med 2006;21:915–9. 10.1111/j.1525-1497.2006.00526.x
    1. Noël PH, Copeland LA, Pugh MJ, et al. . Obesity diagnosis and care practices in the Veterans health administration. J Gen Intern Med 2010;25:510–6. 10.1007/s11606-010-1279-z
    1. Das SR, Kinsinger LS, Yancy WS, et al. . Obesity prevalence among Veterans at Veterans Affairs medical facilities. Am J Prev Med 2005;28:291–4. 10.1016/j.amepre.2004.12.007
    1. Breland JY, Phibbs CS, Hoggatt KJ, et al. . The obesity epidemic in the Veterans health administration: prevalence among key populations of women and men veterans. J Gen Intern Med 2017;32:11–17. 10.1007/s11606-016-3962-1
    1. Tsai AG, Wadden TA. Treatment of obesity in primary care practice in the United States: a systematic review. J Gen Intern Med 2009;24:1073–9. 10.1007/s11606-009-1042-5
    1. Martin PD, Dutton GR, Rhode PC, et al. . Weight loss maintenance following a primary care intervention for low-income minority women. Obesity 2008;16:2462–7. 10.1038/oby.2008.399
    1. Bennett GG, Warner ET, Glasgow RE, et al. . Obesity treatment for socioeconomically disadvantaged patients in primary care practice. Arch Intern Med 2012;172:565–74. 10.1001/archinternmed.2012.1
    1. Abid A, Galuska D, Khan LK, et al. . Are healthcare professionals advising obese patients to lose weight? A trend analysis. MedGenMed 2005;7:10.
    1. Galuska DA, Will JC, Serdula MK, et al. . Are health care professionals advising obese patients to lose weight? JAMA 1999;282:1576–8. 10.1001/jama.282.16.1576
    1. Yarnall KSH, Pollak KI, Østbye T, et al. . Primary care: is there enough time for prevention? Am J Public Health 2003;93:635–41. 10.2105/ajph.93.4.635
    1. Huang J, Yu H, Marin E, et al. . Physicians’ weight loss counseling in two public hospital primary care clinics. Acad Med 2004;79:156–61. 10.1097/00001888-200402000-00012
    1. National Institute for Health and Care Excellence (NICE) . The grants register 2020, 2019: 586–7.
    1. U.S. Department of Veteran Affairs and Department of Defense . Management of obesity and overweight (OBE), 2014.
    1. Moyer VA, U.S. Preventive Services Task Force . Screening for and management of obesity in adults: U.S. preventive services Task force recommendation statement. Ann Intern Med 2012;157:373–8. 10.7326/0003-4819-157-5-201209040-00475
    1. Goodwin S. The practical guide to the identification, evaluation and treatment of overweight and obesity in adults. Clin Nurse Spec 2002;16:164.
    1. Knowler WC, Barrett-Connor E, Fowler SE, et al. . Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393–403. 10.1056/NEJMoa012512
    1. Del Re AC, Maciejewski ML, Harris AHS. MOVE: weight management program across the Veterans health administration: patient- and facility-level predictors of utilization. BMC Health Serv Res 2013;13:511. 10.1186/1472-6963-13-511
    1. VHA National Center for Health Promotion and Disease Prevention . MOVE! weight management program for veterans fiscal year 2013 evaluation report: narrative summary, 2013.
    1. Viswanathan M, Kraschnewski JL, Nishikawa B, et al. . Outcomes and costs of community health worker interventions: a systematic review. Med Care 2010;48:792–808. 10.1097/MLR.0b013e3181e35b51
    1. Brace AM, Padilla HM, DeJoy DM, et al. . Applying RE-AIM to the evaluation of FUEL Your Life : a worksite translation of DPP. Health Promot Pract 2015;16:28–35. 10.1177/1524839914539329
    1. a KJ, Vitolins MZ, Rosenberger EL. One-Year results of a community-based translation of the diabetes prevention program. Diabetes Care 2011;34:1451–7.
    1. West DS, Bursac Z, Cornell CE, et al. . Lay health educators translate a weight-loss intervention in senior centers: a randomized controlled trial. Am J Prev Med 2011;41:385–91. 10.1016/j.amepre.2011.06.041
    1. Parikh P, Simon EP, Fei K, et al. . Results of a pilot diabetes prevention intervention in East Harlem, New York City: project HEED. Am J Public Health 2010;100:S232–9. 10.2105/AJPH.2009.170910
    1. Lynch EB, Liebman R, Ventrelle J, et al. . A self-management intervention for African Americans with comorbid diabetes and hypertension: a pilot randomized controlled trial. Prev Chronic Dis 2014;11:E90. 10.5888/pcd11.130349
    1. Dutton GR, Phillips JM, Kukkamalla M, et al. . Pilot study evaluating the feasibility and initial outcomes of a primary care weight loss intervention with peer coaches. Diabetes Educ 2015;41:361–8. 10.1177/0145721715575356
    1. Leahey TM, Fava JL, Seiden A. A randomized controlled trial testing an Internet delivered cost–benefit approach to weight loss maintenance. Prev Med 2016;92:51–7.
    1. Lehavot K, Der-Martirosian C, Simpson TL, et al. . The role of military social support in understanding the relationship between PTSD, physical health, and healthcare utilization in women veterans. J Trauma Stress 2013;26:772–5. 10.1002/jts.21859
    1. Goldstein KM, Zullig LL, Oddone EZ. Understanding women veterans’ preferences for peer support interventions to promote heart healthy behaviors: A qualitative study. Prev Med Reports 2018;10:353–8.
    1. Mosack KE, Wendorf AR, Brouwer AM, et al. . Veterans service organization engagement in ‘POWER,’ a peer-led hypertension intervention. Chronic Illn 2012;8:252–64. 10.1177/1742395312437978
    1. Jay M, Mateo KF, Squires AP, et al. . Military service and other socioecological factors influencing weight and health behavior change in overweight and obese veterans: a qualitative study to inform intervention development within primary care at the United States Veterans health administration. BMC Obes 2015;3:5. 10.1186/s40608-016-0087-3
    1. Long JA, Jahnle EC, Richardson DM, et al. . Peer mentoring and financial incentives to improve glucose control in African American veterans: a randomized trial. Ann Intern Med 2012;156:416–24. 10.7326/0003-4819-156-6-201203200-00004
    1. Heisler M, Vijan S, Makki F, et al. . Diabetes control with reciprocal peer support versus nurse care management: a randomized trial. Ann Intern Med 2010;153:507–15. 10.7326/0003-4819-153-8-201010190-00007
    1. Glasgow RE, Emont S, Miller DC. Assessing delivery of the five ‘As’ for patient-centered counseling. Health Promot Int 2006;21:245–55. 10.1093/heapro/dal017
    1. Wittleder S, Ajenikoko A, Bouwman D, et al. . Protocol for a cluster-randomized controlled trial of a technology-assisted health coaching intervention for weight management in primary care: the GEM (goals for eating and moving) study. Contemp Clin Trials 2019;83:37–45. 10.1016/j.cct.2019.06.005
    1. Viglione C, Bouwman D, Rahman N, et al. . A technology-assisted health coaching intervention vs. enhanced usual care for primary care-based obesity treatment: a randomized controlled trial. BMC Obes 2019;6:4. 10.1186/s40608-018-0226-0
    1. Jay MR, Gillespie CC, Schlair SL, et al. . The impact of primary care resident physician training on patient weight loss at 12 months. Obesity 2013;21:45–50. 10.1002/oby.20237
    1. Miller W, Rollnick S. Motivational interviewing: helping people change. Guilford Press, 2013.
    1. CCMI – Centre for Collaboration . Motivation and innovation. Available: [Accessed 14 Jul 2020].
    1. Damschroder LJ, Goodrich DE, Kim HM, et al. . Development and validation of the ASPIRE-VA coaching fidelity checklist (ACFC): a tool to help ensure delivery of high-quality weight management interventions. Transl Behav Med 2016;6:369–85. 10.1007/s13142-015-0336-x
    1. Mateo KF, Berner NB, Ricci NL. Development of a 5As-based technology-assisted weight management intervention for veterans in primary care. BMC Health Serv Res 2018;18:1–14.
    1. Doran G. There’s a S.M.A.R.T way to write management’s goals and objectives. Manage Rev 1981;70:35–6.
    1. Gutnick D, Reims K, Davis C. Brief action planning to facilitate behavior change and support patient self-management. J Clin Outcomes Manag 2014;21:17–29.
    1. MOVE! Coach . MOVE! weight management program. Available: [Accessed 14 Jul 2020].
    1. MyFitnessPal . Available: [Accessed 14 Jul 2020].
    1. Peterson ND, Middleton KR, Nackers LM, et al. . Dietary self-monitoring and long-term success with weight management. Obesity 2014;22:1962–7. 10.1002/oby.20807
    1. Damschroder LJ, Lutes LD, Kirsh S, et al. . Small-changes obesity treatment among veterans: 12-month outcomes. Am J Prev Med 2014;47:541–53. 10.1016/j.amepre.2014.06.016
    1. Lee PH, Macfarlane DJ, Lam TH, et al. . Validity of the international physical activity questionnaire short form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act 2011;8:115. 10.1186/1479-5868-8-115
    1. Banna JC, Townsend MS. Assessing factorial and convergent validity and reliability of a food behaviour checklist for Spanish-speaking participants in US department of agriculture nutrition education programmes. Public Health Nutr 2011;14:1165–76. 10.1017/S1368980010003058
    1. Gans KM, Risica PM, Wylie-Rosett J, et al. . Development and evaluation of the nutrition component of the rapid eating and activity assessment for patients (REAP): a new tool for primary care providers. J Nutr Educ Behav 2006;38:286–92. 10.1016/j.jneb.2005.12.002
    1. Segal-Isaacson CJ, Wylie-Rosett J, Gans KM. Validation of a short dietary assessment questionnaire: the rapid eating and activity assessment for participants short version (REAP-S). Diabetes Educ 2004;30:774–81. 10.1177/014572170403000512
    1. Fernandez S, Olendzki B, Rosal MC. A dietary behaviors measure for use with low-income, Spanish-speaking Caribbean Latinos with type 2 diabetes: the Latino dietary behaviors questionnaire. J Am Diet Assoc 2011;111:589–99. 10.1016/j.jada.2011.01.015
    1. Linde JA, Rothman AJ, Baldwin AS. The impact of self-efficacy on behavior change and weight change among overweight participants in a weight loss trial. Heal Psychol 2006;25:282–91.
    1. Marcus BH, Selby VC, Niaura RS, et al. . Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport 1992;63:60–6. 10.1080/02701367.1992.10607557
    1. Ames GE, Heckman MG, Grothe KB, et al. . Eating self-efficacy: development of a short-form WEL. Eat Behav 2012;13:375–8. 10.1016/j.eatbeh.2012.03.013
    1. Prochaska JO, Velicer WF, Rossi JS. Multiple risk expert systems interventions: impact of simultaneous stage-matched expert system interventions for smoking, high-fat diet, and sun exposure in a population of parents. Heal Psychol 2004;23:503–16.
    1. Prochaska JO, Velicer WF, Redding C. Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Prev Med 2005;41:406–16.
    1. Sarkin JA, Johnson SS, Prochaska JO. Applying the transtheoretical model to regular moderate exercise in an overweight population: validation of a stages of change measure. Prev Med 2001;33:462–9.
    1. Wilcox S, Castro CM, King AC. Outcome expectations and physical activity participation in two samples of older women. J Health Psychol 2006;11:65–77. 10.1177/1359105306058850
    1. King AC, Taylor CB, Haskell WL, et al. . Influence of regular aerobic exercise on psychological health: a randomized, controlled trial of healthy middle-aged adults. Health Psychol 1989;8:305–24. 10.1037//0278-6133.8.3.305
    1. Williams GC, Grow VM, Freedman ZR, et al. . Motivational predictors of weight loss and weight-loss maintenance. J Pers Soc Psychol 1996;70:115–26. 10.1037//0022-3514.70.1.115
    1. Leahey TM, LaRose JG, Lanoye A, et al. . Secondary data analysis from a randomized trial examining the effects of small financial incentives on intrinsic and extrinsic motivation for weight loss. Health Psychol Behav Med 2017;5:129–44. 10.1080/21642850.2016.1276460
    1. Tyler T, Mentovich A, Satyavada S. What motivates adherence to medical recommendations? The procedural justice approach to gaining deference in the medical arena. Regul Gov 2014;8:350–70.
    1. Rueda-Clausen CF, Benterud E, Bond T, et al. . Effect of implementing the 5As of obesity management framework on provider-patient interactions in primary care. Clin Obes 2014;4:39–44. 10.1111/cob.12038
    1. Jay M, Kalet A, Ark T, et al. . Physicians’ attitudes about obesity and their associations with competency and specialty: a cross-sectional study. BMC Health Serv Res 2009;9:106. 10.1186/1472-6963-9-106
    1. van Breukelen GJP, Candel MJJM. Calculating sample sizes for cluster randomized trials: we can keep it simple and efficient! J Clin Epidemiol 2012;65:1212–8. 10.1016/j.jclinepi.2012.06.002
    1. Levine DM, Savarimuthu S, Squires A, et al. . Technology-assisted weight loss interventions in primary care: a systematic review. J Gen Intern Med 2015;30:107–17. 10.1007/s11606-014-2987-6
    1. Jay M, Chintapalli S, Squires A, et al. . Barriers and facilitators to providing primary care-based weight management services in a patient centered medical home for veterans: a qualitative study. BMC Fam Pract 2015;16:167. 10.1186/s12875-015-0383-x
    1. Patel ML, Wakayama LN, Bass MB, et al. . Motivational interviewing in eHealth and telehealth interventions for weight loss: a systematic review. Prev Med 2019;126:105738. 10.1016/j.ypmed.2019.05.026
    1. Bradley KA, DeBenedetti AF, Volk RJ, et al. . AUDIT-C as a brief screen for alcohol misuse in primary care. Alcohol Clin Exp Res 2007;31:1208–17. 10.1111/j.1530-0277.2007.00403.x
    1. Cella D, Choi SW, Condon DM. PROMIS® adult health profiles: efficient short-form measures of seven health domains. Value Heal 2019;22:537–44.
    1. Levine SZ. Evaluating the seven-item center for epidemiologic studies depression scale short-form: a longitudinal U.S. community study. Soc Psychiatry Psychiatr Epidemiol 2013;48:1519–26. 10.1007/s00127-012-0650-2

Source: PubMed

Szponzorok és közreműködők

Egészségi állapot

Kábítószer-beavatkozások

3
Iratkozz fel