Just-in-Time Adaptive Interventions for Mental Health Promotion: incorporating Reinforcement Learning to Personalized Care

This grant proposal seeks to address key challenges in the integration of reinforcement learning (RL) into app-based mental health interventions, specifically for the creation of just-in-time adaptive interventions (JITAIs). The main obstacles include developing RL algorithms that don’t require large datasets, are resource-efficient on smartphones, and can balance between trying new intervention strategies and using proven ones. The proposal outlines a collaboration with the Behavioral Data Science Incubator (BDSI) and the BMSLab to overcome these challenges by leveraging the BDSI expertise to implement cutting-edge, innovative RL algorithms suitable for JITAIs within the constraints of existing app platforms.