Integration of a Trained Language Model to Improve Glycemic Control Through Increased Physical Activity: a Fully Digital My Heart Counts Smartphone App Randomized Trial

"Aim 1: In preliminary data, the investigators have pre-trained an open-source language model, LLAMA, with expert-created coaching prompts based on the stages of change model for physical activity. Seven different prompts (for each day of an intervention week) will be generated, accounting for race/ethnicity, age, gender, and stage of change, to improve personalization. Using the existing MHC app, the investigators will perform a randomized crossover trial on mean daily steps across each intervention. The investigators will compare the interventions of a daily reminder to reach 10,000 steps (a neutral control) and AI-personalized interventions based on an individual's stage of change."

"Aim 2: Using social accountability and the trained language model generating personalized coaching interventions, the investigators will conduct a long-term follow-up randomized, unblinded trial. Over a 24-week intervention period, participants will receive either a generic daily reminder to reach 10,000 steps or an AI-generated coaching prompt, with the AI group also being able to chat with the language model to ask for advice on maintaining their physical activity. The outcomes of this long-term trial will be change in: 1) daily steps over the intervention period, 2) weight (via HealthKit link to MHC), and 3) HbA1c (as derived from EMR records linked to the HIPAA-compliant MHC app)."