Applying the COM-B model to creation of an IT-enabled health coaching and resource linkage program for low-income Latina moms with recent gestational diabetes: the STAR MAMA program

Margaret A Handley, Elizabeth Harleman, Enrique Gonzalez-Mendez, Naomi E Stotland, Priyanka Althavale, Lawrence Fisher, Diana Martinez, Jocelyn Ko, Isabel Sausjord, Christina Rios, Margaret A Handley, Elizabeth Harleman, Enrique Gonzalez-Mendez, Naomi E Stotland, Priyanka Althavale, Lawrence Fisher, Diana Martinez, Jocelyn Ko, Isabel Sausjord, Christina Rios

Abstract

Background: One of the fastest growing risk groups for early onset of diabetes is women with a recent pregnancy complicated by gestational diabetes, and for this group, Latinas are the largest at-risk group in the USA. Although evidence-based interventions, such as the Diabetes Prevention Program (DPP), which focuses on low-cost changes in eating, physical activity and weight management can lower diabetes risk and delay onset, these programs have yet to be tailored to postpartum Latina women. This study aims to tailor a IT-enabled health communication program to promote DPP-concordant behavior change among postpartum Latina women with recent gestational diabetes. The COM-B model (incorporating Capability, Opportunity, and Motivational behavioral barriers and enablers) and the Behavior Change Wheel (BCW) framework, convey a theoretically based approach for intervention development. We combined a health literacy-tailored health IT tool for reaching ethnic minority patients with diabetes with a BCW-based approach to develop a health coaching intervention targeted to postpartum Latina women with recent gestational diabetes. Current evidence, four focus groups (n = 22 participants), and input from a Regional Consortium of health care providers, diabetes experts, and health literacy practitioners informed the intervention development. Thematic analysis of focus group data used the COM-B model to determine content. Relevant cultural, theoretical, and technological components that underpin the design and development of the intervention were selected using the BCW framework.

Results: STAR MAMA delivers DPP content in Spanish and English using health communication strategies to: (1) validate the emotions and experiences postpartum women struggle with; (2) encourage integration of prevention strategies into family life through mothers becoming intergenerational custodians of health; and (3) increase social and material supports through referral to social networks, health coaches, and community resources. Feasibility, acceptability, and health-related outcomes (weight loss, physical activity, consumption of healthy foods, breastfeeding, and glucose screening) will be evaluated at 9 months postpartum using a randomized controlled trial design.

Conclusions: STAR MAMA provides a DPP-based intervention that integrates theory-based design steps. Through systematic use of behavioral theory to inform intervention development, STAR MAMA may represent a strategy to develop health IT intervention tools to meet the needs of diverse populations.

Trial registration: ClinicalTrials.gov NCT02240420.

Keywords: Behavior change theory; COM-B model; Diabetes Prevention Program; Diabetes prevention; Health disparities.

Figures

Fig. 1
Fig. 1
STAR MAMA intervention model for telephone-based diabetes prevention support plus supportive health coaching and linkages to resources

References

    1. Kim C, Newton KM, Knopp RH. Gestational diabetes and the incidence of type 2 diabetes: a systematic review. Diabetes Care. 2002;25(10):1862–8. doi: 10.2337/diacare.25.10.1862.
    1. Ferrara A. Increasing prevalence of gestational diabetes mellitus: a public health perspective, Diabetes Care. 30(Supplement 2), S141–S146. 2007. .
    1. Bellamy L, Casas J-P, Hingorani AD, Williams D. Type 2 diabetes mellitus after gestational diabetes: a systematic review and meta-analysis. Lancet. 2009;373(9677):1773–9. doi: 10.1016/S0140-6736(09)60731-5.
    1. Reece EA, Leguizamón G, Wiznitzer A. Gestational diabetes: the need for a common ground. Lancet. 2009;373(9677):1789–97. doi: 10.1016/S0140-6736(09)60515-8.
    1. Gunderson EP, Lewis CE, Tsai A-L, Chiang V, Carnethon M, Quesenberry CP, et al. A 20-year prospective study of childbearing and incidence of diabetes in young women, controlling for glycemia before conception: The Coronary Artery Risk Development in Young Adults (CARDIA) Study. Diabetes. 2007;56(12):2990–6. .
    1. Hod M, Hadar E, Cabero-Roura L. Prevention of type 2 diabetes among women with prior gestational diabetes mellitus. Int J Gynecol Obstet. 2015;131:S16–8. doi: 10.1016/j.ijgo.2015.02.010.
    1. DeSisto CL, Kim SY, Sharma AJ. Prevalence estimates of gestational diabetes mellitus in the United States, Pregnancy Risk Assessment Monitoring System (PRAMS), 2007-2010. Prev Chronic Dis. 2014;11(12)
    1. Bardenheier BH, Imperatore G, Gilboa SM, Geiss LS, Saydah SH, Devlin HM, Kim SY, Gregg EW. Trends in Gestational Diabetes Among Hospital Deliveries in 19 U.S. States, 2000-2010. Am J Prev Med. 2015 Jul;49(1):12-9. doi:.
    1. California Department of Public Health, Maternal, Child, and Adolescent Health Program. California Diabetes and Pregnancy Program – Calendar Year 2009, Data Report for deliveries between January 1, 2009 and by December 31, 2009 [Data Report]. Retrieved from the California Department of Public Health. 2011. Website: .
    1. DPP Research Group 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study. Lancet. 2009;374(9702):1677–86. doi: 10.1016/S0140-6736(09)61457-4.
    1. England LJ, Dietz PM, Njoroge T, Callaghan WM, Bruce C, Buus RM, et al. Preventing type 2 diabetes: public health implications for women with a history of gestational diabetes mellitus. Am J Obstet Gynecol. 2009;200(4):365.e1–8. .
    1. Verier-Mine O. Outcomes in women with a history of gestational diabetes: screening and prevention of type-2 diabetes. Diabetes Metab. 2010;36:596–616. doi: 10.1016/j.diabet.2010.11.011.
    1. Diabetes Prevention Program Research Group Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403. doi: 10.1056/NEJMoa012512.
    1. Ratner R, Christophi C, Metzger B, et al. Prevention of diabetes in women with a history of gestational diabetes: effects of metformin and lifestyle interventions. J Clin Endocrinol Metab. 2008;93(12):4774–9. doi: 10.1210/jc.2008-0772.
    1. Ferrara A, Hedderson MM, Albright CL. A pregnancy and postpartum lifestyle intervention in women with gestational. Diabetes Care. 2011;34(7):1519–25. doi: 10.2337/dc10-2221.
    1. Ferrara A, Ehrlich SF. Strategies for diabetes prevention before and after pregnancy in women with GDM. Curr Diabetes Rev. 2011;7(2):75–83. doi: 10.2174/157339911794940738.
    1. Ferrara A, Hedderson MM, Albright CL, Brown SD, Ehrlich SF, Caan BJ, Quesenberry CP. A pragmatic cluster randomized clinical trial of diabetes prevention strategies for women with gestational diabetes: design and rationale of the Gestational Diabetes’ Effects on Moms (GEM) study. BMC Pregnancy Childbirth. 2014; 14:21. .
    1. Gupta Y, Gupta A. Correspondence CgA in heart diseases: more than meets the eye post-partum screening. Lancet Diabetes Endocrinol. 2013;1(2):90–1. doi: 10.1016/S2213-8587(13)70066-4.
    1. Vesco KK, Dietz PM, Bulkley J, Bruce FC, Callaghan WM, England L, Hornbrook MC. A system-based intervention to improve postpartum diabetes screening among women with gestational diabetes. YMOB. 2012; 207(4):283.e1–283.e6. .
    1. Perrin A. Social media usage: 2005-2015: 65 % of adults now use social networking sites—a nearly tenfold jump in the past decade. Pew Research Center, (October), 2005–2015. 2015. Retrieved from .
    1. Schillinger D, Handley M, Wang F, Hammer H. Effects of self-management support on structure, process, and outcomes among vulnerable patients with diabetes: a three-arm practical clinical trial. Diabetes Care. 2009;32(4):559–66. doi: 10.2337/dc08-0787.
    1. Handley MA, Shumway M, Schillinger D. Cost-effectiveness of automated telephone. Ann Fam Med. 2008:1–7. .
    1. Handley MA, Hammer H, Schillinger D. Navigating the Terrain between Research and Practice: A CRN Case Study in Diabetes Research. J Am Board of Fam Med. 2006;19(1) 85-92.
    1. Schillinger D, Hammer H, Wang F, Palacios J, Mclean I, Tang A, Handley M. Seeing in 3-D: examining the reach of diabetes self-management support strategies in a public health care system. Health Educ Behav. 2006; 35(5):664–82. doi:10.1177/1090198106296772.
    1. Piette JD, Aikens JE, Trivedi R, Parrish D, Standiford C, Marinec NS, Bernstein SJ. Depression self-management assistance using automated telephonic assessments and social support. Am J Manag Care. 2013; 19(11):892–900.
    1. Brodey BB, Rosen CS, Brodey IS, Sheetz B, Unutzer J. Reliability and acceptability of automated telephone surveys among Spanish- and English-speaking mental health services recipients. Ment Health Serv Res. 2005;7(3):181–4. doi: 10.1007/s11020-005-5786-1.
    1. Mastrogiannis DS, Igwe E, Homko CJ. The role of telemedicine in the management of the pregnancy complicated by diabetes. Curr Diab Rep. 2013 Feb;13(1):1-5. doi:
    1. Michie S, Johnston M, Francis J, Hardeman W, Eccles M. From theory to intervention: mapping theoretically derived behavioural determinants to behaviour change techniques. Appl Psychol. 2008;57(4):660–80. doi: 10.1111/j.1464-0597.2008.00341.x.
    1. Curtis KE, Lahiri S, Brown KE. Targeting parents for childhood weight management: development of a theory-driven and user-centered healthy eating app. JMIR mHealth uHealth. 2015;3(2):e69. doi: 10.2196/mhealth.3857.
    1. Michie S, Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6(1):42. doi: 10.1186/1748-5908-6-42.
    1. Michie S. Making psychological theory useful for implementing evidence based practice: a consensus approach. Qual Saf Health Care. 2005;14(1):26–33. doi: 10.1136/qshc.2004.011155.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, 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. doi:10.1007/s12160-013-9486-6.
    1. Michie S, Atkins L, West R. The behaviour change wheel: a guide to designing Interventions. Silverback Publishing 2014.
    1. Francis J, Tinmouth A, Stanworth S, Grimshaw J, Johnston M, Hyde C, Fergusson D. Using theories of behaviour to understand transfusion prescribing in three clinical contexts in two countries: development work for an implementation trial. Implement Sci. 2009; 70(4): .
    1. French SD, Green SE, McKenzie J, Francis JJ, Michie S, et al. Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework Implementation Science. 2012;7:38.
    1. Shafer A, Cates JR, Diehl SJ, Hartmann M. Asking Mom: formative research for an HPV vaccine campaign targeting mothers of adolescent girls. J Health Commun Int Perspect. 2011;16(10). .
    1. Keller C, Records K, Ainsworth B, Belyea M, Pernmana P. Madres para la salud: Design of a theory-based intervention for post-partum Latinas. Contemp Clin Trials. 2011. doi:10.1016/j.cct.2011.01.003.
    1. Lie ML, Hayes L, May C, White M, Bell R. Research: care delivery preventing type 2 diabetes after gestational diabetes: women’s experiences and implications for diabetes prevention interventions. Diabet Med. 2013 Aug;30(8):986-93. doi:.
    1. Strauss AL, Corbin JM. Basics of qualitative research: techniques and procedures for developing grounded theory. Thousand Oaks: Sage Publications; 1998.
    1. Sandelowski M. Using qualitative research. Qual Health Res. 2004;14(10):1366–86. .
    1. Handley MA, Robles M, Sanford E, Collins N, Seligman H, Defries T, Perez R, Grieshop J. Navigating changing food environments - Transnational perspectives on dietary behaviours and implications for nutrition counselling. Glob Public Health. 2013;8(3):245–257. doi: 10.1080/17441692.2012.729218.
    1. American College of Obstetricians and Gynecologists. Stark AR, Riley L. Guidelines for Perinatal Care. 7. Washington D. C.: American Academy of Pediatrics; 2012.
    1. Blenning C, Paladine H. An approach to the postpartum office visit. Am Fam Physician. 2005;72:2491–2496.
    1. Hagan JF, Shaw JS, Duncan PE. Bright futures: guidelines for health supervision of infants, children, and adolescents. Elk Grove Village: American Academy of Pediatrics; 2008.
    1. Ryswyk EV, Middleton P, Shute E, Hague W, Crowther C. Women’s views and knowledge regarding healthcare seeking for gestational diabetes in the postpartum period: a systematic review of qualitative/survey studies. Diabetes Res Clin Pract. 2015;110(2):109–122. doi: 10.1016/j.diabres.2015.09.010.
    1. Jones EJ, Peercy M, Woods JC, Parker SP, Jackson T, Mata SA, Seely EW. Identifying postpartum intervention approaches to reduce cardiometabolic risk among American Indian women with prior gestational diabetes, Oklahoma, 2012-2013. Prev Chronic Dis. 2015;12(5):E45. .
    1. Greenhalgh T, Clinch M, Afsar N, Choudhury Y, Sudra R, Campbell-Richards D, et al. Socio-cultural influences on the behaviour of South Asian women with diabetes in pregnancy: qualitative study using a multi-level theoretical approach. BMC Med. 2015.
    1. Defries, T., Rodrigues, M., Ghorob, A., & Handley, M. (2015). Health Communication and Action Planningwith Immigrant Patients: Aligning Clinician and Community Perspectives. MedEdPORTAL Publications MEP. doi:10.15766/mep_2374-8265.10050.
    1. Tabak RG, Sinclair KA, Baumann AA, Racette SB, Sebert Kuhlmann A, Johnson-Jennings MD, Brownson RC. A review of diabetes prevention programtranslations: use of cultural adaptationand implementation research. Transl Behav Med. 2015;5(4):401–14. doi: 10.1007/s13142-015-0341-0.

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