Paper Type
ERF
Abstract
The prevalence of diabetes and obesity has risen sharply in recent years. Traditional clinical interventions and existing technological solutions, such as chatbots, offer some promise but often lack a comprehensive, scalable approach to behavior change. This study develops an AI-driven solution that seamlessly integrates continuous health monitoring through behavioral tracking, personalized education via interactive question-answering and health quizzes, and gamified social support systems to enhance user motivation and engagement. Following a systematic process aligned with design science research guidelines, we demonstrate the feasibility of implementing an AI health coach and explore the potential for a soft launch followed by a randomized controlled trial the Middle East region. We believe that this approach offers a more effective and scalable solution for tackling obesity and diabetes compared to existing methods. Our study contributes to both academic research and practical applications in health IT and healthcare delivery processes.
Paper Number
2095
Recommended Citation
Jozani, Mohsen; Ebadi, Nima; Khan, Rubayat; and Zoughbie, Daniel, "ChatGPC: A Novel Interactive AI Health Coach for Obesity and Diabetes Prevention" (2025). AMCIS 2025 Proceedings. 9.
https://aisel.aisnet.org/amcis2025/health_it/sig_health/9
ChatGPC: A Novel Interactive AI Health Coach for Obesity and Diabetes Prevention
The prevalence of diabetes and obesity has risen sharply in recent years. Traditional clinical interventions and existing technological solutions, such as chatbots, offer some promise but often lack a comprehensive, scalable approach to behavior change. This study develops an AI-driven solution that seamlessly integrates continuous health monitoring through behavioral tracking, personalized education via interactive question-answering and health quizzes, and gamified social support systems to enhance user motivation and engagement. Following a systematic process aligned with design science research guidelines, we demonstrate the feasibility of implementing an AI health coach and explore the potential for a soft launch followed by a randomized controlled trial the Middle East region. We believe that this approach offers a more effective and scalable solution for tackling obesity and diabetes compared to existing methods. Our study contributes to both academic research and practical applications in health IT and healthcare delivery processes.
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