Refinement and Adaption of Reinforcement Learning to Personalize Behavioral Messaging for Healthy Habits

The goal of the proposed research is to refine, adapt and perform efficacy testing of a novel reinforcement learning-based text messaging intervention to support medication adherence for patients with type 2 diabetes within a community setting. Type 2 diabetes is an optimal condition in which to refine this program, as it is one of the most prevalent chronic conditions in the US adult population and requires most patients to be on daily or twice daily doses of medications. This study will be a parallel randomized pragmatic trial comparing medication adherence and clinical outcomes for adults in a community setting aged 18-84 with type 2 diabetes who are prescribed 1-3 daily oral medications for this disease. Participants will be randomized to one of two arms for the duration of the study period: (1) a reinforcement learning intervention arm with up to daily, tailored text messages based on time-varying treatment-response patterns; or (2) a control arm with up to daily, un-tailored text messages. Outcomes of interest will be medication adherence, as measured by electronic pill bottles, and HbA1c levels over 6 months.

Inclusion criteria

• Diagnosis of Type 2 Diabetes Mellitus (T2DM)
• Prescribed between 1-3 daily oral medications for diabetes
• Most recent HbA1c level of 7% or greater
• Suboptimal adherence, defined by proportion of days covered (PDC) < 0.90 based on chart review
• Must have a smartphone for which they are the sole user
• Must have a basic working knowledge of English or Spanish

Exclusion criteria

• Currently using a pillbox and/or not willing to use electronic pill bottles for 6 months
• Receive help at home on a daily basis with taking medications