Designing a Large Language Model-Based Coaching Intervention for Lifestyle Behavior Change

Adopting and maintaining healthy lifestyle behaviors such as regular exercise and balanced nutrition remain challenging despite their well-documented benefits for preventing chronic diseases and promoting overall well-being. Motivational Interviewing (MI) has emerged as a promising technique to address ambivalence and facilitate behavior change. However, traditional face-to-face delivery of MI interventions is limited by scalability and accessibility issues. Leveraging recent advancements in LLMs, this paper proposes an innovative approach to deliver MI-based coaching for lifestyle behavior change digitally. Following a problem-centered DSR approach, we created an initial prototype based on MI theory and qualitative user interviews using ChatGPT (GPT-3.5). We evaluated our prototype in a qualitative study. Our research outcomes include five design principles and thirteen system requirements. This research enhances the design knowledge base in LLM-based health coaching. It marks an essential first step towards designing LLM-based MI interventions, contributing valuable insights for future research in this emerging field.