Promoting Problem-Solving Among Low-Income Adults with Type 2 Diabetes: A Cluster-Randomized Controlled Trial of Mobile Diabetes Detective, an mHealth Intervention with Text Messaging
Abstract
Background. Problem-solving is essential to self-management of type 2 diabetes but challenging for underserved individuals. mHealth interventions can improve diabetes self-management but few focus on problem-solving.
Objectives. To evaluate the efficacy of Mobile Diabetes Detective (MoDD), a fully automated web-based intervention with SMS messaging that provides problem-solving support tailored with self-monitoring data, for improving glycemic control among medically underserved adults with type 2 diabetes.
Methods. This open-label, 1:1 cluster-randomized controlled trial was conducted in 2013–2018. Participants were adults with poorly controlled type 2 diabetes (HbA1c>7.5%) receiving care at eight Federally Qualified Health Centers serving medically underserved communities in the New York metropolitan area; the centers served as clusters and were randomized using computer-generated allocation. The recruitment and study sessions were either in-person or hybrid. The intervention arm used MoDD for 12 months; the control arm received standard diabetes education and routine care. The primary outcome was change in HbA1c, captured from medical chart, from baseline to 12 months; we hypothesized a greater improvement in the intervention arm compared to the control arm. Secondary outcomes included psychosocial measures. Outcomes were compared between groups using intention-to-treat analyses. This report includes the final analysis of the outcomes.
Results. This trial randomized 248 participants (intervention arm: n=126; control arm: n=122); of those, 219 were included in the final analysis (intervention arm: n=111; control arm: n=108). Participants were predominantly female (67%), ethnically and racially diverse (51% Hispanic, 42% African American), with mean HbA1c=9.9% at baseline. 40% of participants engaged with MoDD at least once weekly during the first 30 days, and 20% engaged weekly by 90 days. HbA1c did not differ significantly between groups at baseline (intervention 9.81%, 95% CI 9.42 to 10.20; control 9.95%, 95% CI 9.55 to10.34; difference 0.14%, p=0.63) or at 12 months (intervention 9.36%, 95% CI 8.95 to 9.78; control 9.58%, 95% CI 9.15 to 10.01; difference −0.22%, p=0.47). Both groups demonstrated reductions in HbA1c from baseline to 3 months. Sustained within-group improvement at 12 months was observed in the intervention group but not in the control group. No adverse events related to the intervention were reported.
Conclusions. This study evaluated the impact of an mHealth intervention for problem-solving in diabetes. MoDD is innovative because, unlike prior work, it operates autonomously and tailors support to individuals’ self-monitoring data. While there was no difference in HbA1c between arms, the intervention group showed sustained within-group improvement at 12 months. These results are significant because they highlight potential long-term benefits of fully automated mHealth interventions for problem-solving. The study observed an increase in diabetes distress, possibly reflecting heightened awareness of uncontrolled blood glucose levels. If implemented in clinical practice, MoDD could complement traditional diabetes education and help improve glycemic control.
Objectives. To evaluate the efficacy of Mobile Diabetes Detective (MoDD), a fully automated web-based intervention with SMS messaging that provides problem-solving support tailored with self-monitoring data, for improving glycemic control among medically underserved adults with type 2 diabetes.
Methods. This open-label, 1:1 cluster-randomized controlled trial was conducted in 2013–2018. Participants were adults with poorly controlled type 2 diabetes (HbA1c>7.5%) receiving care at eight Federally Qualified Health Centers serving medically underserved communities in the New York metropolitan area; the centers served as clusters and were randomized using computer-generated allocation. The recruitment and study sessions were either in-person or hybrid. The intervention arm used MoDD for 12 months; the control arm received standard diabetes education and routine care. The primary outcome was change in HbA1c, captured from medical chart, from baseline to 12 months; we hypothesized a greater improvement in the intervention arm compared to the control arm. Secondary outcomes included psychosocial measures. Outcomes were compared between groups using intention-to-treat analyses. This report includes the final analysis of the outcomes.
Results. This trial randomized 248 participants (intervention arm: n=126; control arm: n=122); of those, 219 were included in the final analysis (intervention arm: n=111; control arm: n=108). Participants were predominantly female (67%), ethnically and racially diverse (51% Hispanic, 42% African American), with mean HbA1c=9.9% at baseline. 40% of participants engaged with MoDD at least once weekly during the first 30 days, and 20% engaged weekly by 90 days. HbA1c did not differ significantly between groups at baseline (intervention 9.81%, 95% CI 9.42 to 10.20; control 9.95%, 95% CI 9.55 to10.34; difference 0.14%, p=0.63) or at 12 months (intervention 9.36%, 95% CI 8.95 to 9.78; control 9.58%, 95% CI 9.15 to 10.01; difference −0.22%, p=0.47). Both groups demonstrated reductions in HbA1c from baseline to 3 months. Sustained within-group improvement at 12 months was observed in the intervention group but not in the control group. No adverse events related to the intervention were reported.
Conclusions. This study evaluated the impact of an mHealth intervention for problem-solving in diabetes. MoDD is innovative because, unlike prior work, it operates autonomously and tailors support to individuals’ self-monitoring data. While there was no difference in HbA1c between arms, the intervention group showed sustained within-group improvement at 12 months. These results are significant because they highlight potential long-term benefits of fully automated mHealth interventions for problem-solving. The study observed an increase in diabetes distress, possibly reflecting heightened awareness of uncontrolled blood glucose levels. If implemented in clinical practice, MoDD could complement traditional diabetes education and help improve glycemic control.
