# GPTCoach: Towards LLM-Based Physical Activity Coaching

arXiv: https://arxiv.org/abs/2405.06061 · HTML: https://mlsanity.com/paper/2405.06061/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 May 2024.

## Built on by (most cited first, 29 of 29)

- [Human Decision-making is Susceptible to AI-driven Manipulation](https://mlsanity.com/paper/2502.07663/) (2025)
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- [CALM-IT: Enhancing Synthetic Motivational Interviewing Dialogue Quality with Conversational Dynamics](https://mlsanity.com/paper/2601.10085/) (2026)
- [A Framework for Longitudinal Health AI Agents](https://mlsanity.com/paper/2604.12019/) (2026)
- [State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Living](https://mlsanity.com/paper/2510.14513/) (2025)
- [From Barriers to Tactics: A Behavioral Science-Informed Agentic Workflow for Personalized Nutrition Coaching](https://mlsanity.com/paper/2410.14041/) (2024)
- [Tailored Behavior-Change Messaging for Physical Activity: Integrating Contextual Bandits and Large Language Models](https://mlsanity.com/paper/2506.07275/) (2025)
- [SePA: A Search-enhanced Predictive Agent for Personalized Health Coaching](https://mlsanity.com/paper/2509.04752/) (2025)
- [From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Model](https://mlsanity.com/paper/2601.19053/) (2026)
- [Chaplains' Reflections on the Design and Usage of AI for Conversational Care](https://mlsanity.com/paper/2602.04017/) (2026)
- [CANINE: Coaching Visually Impaired Users for Interactive Navigation with a Robot Guide Dog](https://mlsanity.com/paper/2605.19501/) (2026)
- [HiMe: Real-Time Self-Hosted Personal Agent Platform for Health Insights with Wearable Devices](https://mlsanity.com/paper/2607.21019/) (2026)
- [Exposure to Content Written by Large Language Models Can Reduce Stigma Around Opioid Use Disorder in Online Communities](https://mlsanity.com/paper/2504.10501/) (2025)
- [Offline Policy Evaluation of Multi-Turn LLM Health Coaching with Real Users](https://mlsanity.com/paper/2510.17173/) (2025)
- [Lived Experience in Dialogue: Co-designing Personalization in Large Language Models to Support Youth Mental Well-being](https://mlsanity.com/paper/2511.05769/) (2025)
- [Can AI Chatbots Provide Coaching in Engineering? Beyond Information Processing Toward Mastery](https://mlsanity.com/paper/2601.03693/) (2026)
- [When Workout Buddies Are Virtual: AI Agents and Human Peers in a Longitudinal Physical Activity Study](https://mlsanity.com/paper/2602.01918/) (2026)
- [COACH meets QUORUM: A Framework and Pipeline for Aligning User, Expert and Developer Perspectives in LLM-generated Health Counselling](https://mlsanity.com/paper/2603.08392/) (2026)
- [ReLay: Personalized LLM-Generated Plain-Language Summaries for Better Understanding, but at What Cost?](https://mlsanity.com/paper/2605.00468/) (2026)
- ["What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Use](https://mlsanity.com/paper/2605.00497/) (2026)
- [SocialCoach: Personalized Social Skill Learning with Agentic Tutoring and Practice](https://mlsanity.com/paper/2606.04155/) (2026)
- [HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data](https://mlsanity.com/paper/2607.27635/) (2026)
- [A Survey of Large Models in Sports](https://mlsanity.com/paper/2608.14377/) (2026)
- [From Momentary Emotion Inference to Sustained Emotion Support: Evaluating a Companion Agent in a Longitudinal Study](https://mlsanity.com/paper/2609.16344/) (2026)
- [Eternal Sunshine of the Spotless Mind: Systematically Erasing LLM's Memories](https://mlsanity.com/paper/2609.36414/) (2026)

## Abstract (arXiv)

Mobile health applications show promise for scalable physical activity promotion but are often insufficiently personalized. In contrast, health coaching offers highly personalized support but can be prohibitively expensive and inaccessible. This study draws inspiration from health coaching to explore how large language models (LLMs) might address personalization challenges in mobile health. We conduct formative interviews with 12 health professionals and 10 potential coaching recipients to develop design principles for an LLM-based health coach. We then built GPTCoach, a chatbot that implements the onboarding conversation from an evidence-based coaching program, uses conversational strategies from motivational interviewing, and incorporates wearable data to create personalized physical activity plans. In a lab study with 16 participants using three months of historical data, we find promising evidence that GPTCoach gathers rich qualitative information to offer personalized support, with users feeling comfortable sharing concerns. We conclude with implications for future research on LLM-based physical activity support.