Trial to Examine Text-based mHealth for Emergency Department Patients With Diabetes With Family And Friend Network Supporter
Trial to Examine Text-based mHealth for Emergency Department Patients With Diabetes With Family And Friend Network Supporter
In this study, an existing mobile health intervention to improve diabetes self-management will be combined with a social support module and tested for feasibility. The investigators hypothesize that this combination will be feasible and acceptable to both patients and their loved ones.
This will be the first ever evaluation of a highly scalable and low-cost social support intervention for patients with diabetes delivered entirely via mobile phones. TExT-MED FANS (Trial to Examine Text-based mHealth for Emergency Department Patients With Diabetes With Family And Friend Network Supporter) will unite the benefits of mHealth (scalability, ease of access) and social support interventions (personalized motivation, emotional support). The Diabetes FANS text message based curriculum will make it easier for friends and family to become supporters. Additionally, augmenting TExT-MED with the FANS social support module will be more effective than TExT-MED alone. The personalized support of TExT-MED FANS will also be more effective than providing TExT-MED in combination with a community health worker supporter who lacks a pre-existing relationship with the patient. Through this innovative combination, I can create a more cost-effective and diffusible mHealth solution that maintains the personal connection of social support interventions. To date there has only been one study evaluating social support interventions for patients with diabetes using mHealth, but in this study participants were paired with other subjects with diabetes (not friends or family) and it required intensive face-to-face support group time. TExT-MED FANS will provide key insights into the utility of combining social support interventions delivered solely via mHealth in low-income Latino patients. These insights will help future interventions achieve maximal impact on diabetes and other chronic disease management.
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