Dulce Digital-Me: An Adaptive mHealth Intervention for Underserved Hispanics With Diabetes

Summary

Participation Requirements

Description

Individuals of low socioeconomic (SES) and ethnic minority status, including Hispanics, the largest U.S. ethnic minority group, are disproportionately affected by diabetes. Poor healthcare access and cultural barriers prevent optimal care, adherence, and clinical benefit, thus placing Hispanics at h...

Individuals of low socioeconomic (SES) and ethnic minority status, including Hispanics, the largest U.S. ethnic minority group, are disproportionately affected by diabetes. Poor healthcare access and cultural barriers prevent optimal care, adherence, and clinical benefit, thus placing Hispanics at high risk for costly diabetes complications. The investigators' established academic-healthcare-community partnership has unique experience in developing and testing innovative, cost-effective, and sustainable chronic care interventions to reduce disparities and improve health in underserved communities. The investigators recently developed Dulce Digital (i.e., "one-size-fits-all" educational text messages, with nurse monitoring of patient-transmitted blood glucose values), which improved glycemic control across 6 months, relative to usual care in a recent randomized controlled trial (RCT) of N=126 Hispanic patients with poorly controlled type 2 diabetes (T2DM). The process evaluation for this trial indicated that Dulce Digital was both feasible and acceptable from patient and provider perspectives; however, patients expressed a preference for a more individualized intervention, and providers requested an even greater focus on health behavior change. Thus, the proposed RCT will examine the comparative effectiveness of Dulce Digital versus "Dulce Digital-Me" (DD-Me) in N=414 Hispanic adults of low SES with poorly controlled T2DM from Neighborhood Healthcare, a San Diego Federally-Qualified Health Center. Guided by patient and provider feedback, DD-Me includes Dulce Digital components plus personalized goal-setting and feedback that is responsive to the individual's needs and preferences. The DD-Me adaptive feedback component will be informed by the Resources and Support for Self-Management Model and Operant Conditioning Theory, and based on the individual's progress on intermediate behavioral targets (i.e., medication adherence assessed by wireless sensor; brief mobile phone-based assessments of diet, physical activity, stress). Feedback will be delivered via algorithm-driven automated messaging in 50% of DD-Me participants and by the care team medical assistant in the remaining half to determine the feasibility and acceptability (given the purported cultural relevance of interpersonal relationships in the Hispanic culture), and the comparative effectiveness and cost of each delivery method. Changes in indicators of diabetes clinical control [i.e., glycosylated hemoglobin (HbA1c) low density lipoprotein cholesterol (LDL-C), systolic blood pressure (SBP)], patient-provider communication, and patient adherence (i.e., to medication and other diabetes self-management behaviors) will be evaluated across twelve months. Thorough process and cost-effectiveness analyses will evaluate the scalability and sustainability potential of DD-Me. This comparative evaluation of two mHealth approaches will elucidate how technology can be integrated most effectively and efficiently within existing nurse-led chronic care approaches to meet the complex needs of underserved individuals with poorly controlled T2DM.

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