Treatment for Type 2 Diabetes

In an effort to personalize medical care, novel approaches have been used to categorize sub-populations of patients with type 2 diabetes (T2D). These are based on biological and genetic variables, allowing identification of clusters with significantly different clinical characteristics and risks of complications that may be more amenable to targeted and precise therapeutic interventions. Increasingly, wearable and other digital health technologies have the potential to capture additional and objective information to support personalized medicine but at present underserved populations have largely been excluded from clinical trials incorporating digital health. With this study, the Investigators aim to build on prior work using specially trained community health workers ("Community Scientists") to support engagement with an underserved population and to encourage adherence to using wearables and other digital health technologies. In the US, this is especially imperative for the Hispanic/Latino population, which is at high risk for T2D and associated complications.