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AI-empowered health coaching for university students: A mixed-method process evaluation.
Iva Bojic1, Qi Chwen Ong1, Sakura Ito1
1Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Rd, 308232, Singapore.
AI-empowered health coaching (HC) shows promise but faces challenges. Improving AI accuracy and usability is key for effective integration into health coaching workflows.
Area of Science:
- Digital Health
- Human-Computer Interaction
- Health Coaching Technologies
Background:
- Artificial Intelligence (AI)-empowered health coaching (HC) offers real-time, evidence-based support.
- Integration challenges include retrieval accuracy, usability, and engagement in live HC sessions.
- A pilot randomized controlled trial evaluated the feasibility of AI-empowered HC interventions.
Purpose of the Study:
- To examine health coaches' receptivity to AI-empowered HC.
- To assess engagement and acceptance of an AI-powered Question/Answer (Q/A) system during trials.
- To gather recommendations for improving AI-powered HC systems.
Main Methods:
- A mixed-methods process evaluation was employed.
- Focus group discussions and post-trial quantitative assessments were conducted.
- Health coaches' perspectives on AI integration were explored.
Main Results:
- Health coaches had positive attitudes, valuing AI's factual, evidence-based responses.
- Engagement was limited by irrelevant or incomplete AI answers, disrupting HC flow.
- Recommendations included enhanced retrieval accuracy, more answer options, session history, summaries, and a better UI.
Conclusions:
- AI-empowered HC is promising, but Q/A accuracy limitations hinder usability.
- Refining AI retrieval, personalization, and adaptability is crucial for future development.
- User-centered AI models are needed to support health coaches effectively.
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