Engagements with Generative AI and Personal Health Informatics: Opportunities for Planning, Tracking, Reflecting, and...

Area of Science:

• Human-Computer Interaction
• Digital Health
• Artificial Intelligence

Background:

• Personal informatics and self-tracking for health present numerous challenges.
• Barriers arise from diverse data, goals, expertise, and contexts of individuals.

Purpose of the Study:

• Investigate Generative AI (GAI) potential to support health self-tracking.
• Examine how individuals interact with GAI concerning personal health data.

Main Methods:

• Conducted interview and observation sessions with 19 US-based participants who self-track for health.
• Analyzed participant interactions with GAI around personal health data.

Main Results:

• Participants formulated and refined queries, reflected on recommendations, and abandoned ineffective queries.
• Identified opportunities for GAI support in data selection, plan modification, and insight interpretation.

Conclusions:

• GAI can support diverse health goals and self-tracking processes (planning, reflection, action).
• Discussed limitations and opportunities for integrating GAI into health self-tracking tools.