Metacognitive Demands and Strategies While Using Off-The-Shelf AI Conversational Agents for Health Information Seeking

要旨

As Artificial Intelligence (AI) conversational agents become widespread, people are increasingly using them for health information seeking. The use of off-the-shelf conversational agents for health information seeking could place high metacognitive demands (the need for extensive monitoring and control of one's own thought process) on individuals, which could compromise their experience of seeking health information. However, currently, the specific demands that arise while using conversational agents for health information seeking, and the strategies people use to cope with those demands, remain unknown. To address these gaps, we conducted a think-aloud study with 15 participants as they sought health information using our off-the-shelf AI conversational agent. We identified the metacognitive demands such systems impose, the strategies people adopt in response, and propose considerations for designing beyond off-the-shelf interfaces to reduce these demands and support better user experiences and affordances in health information seeking.

受賞
Honorable Mention
著者
Shri Harini Ramesh
University of Calgary, Calgary, Alberta, Canada
Foroozan Daneshzand
Simon fraser university, Burnaby, British Columbia, Canada
Babak Rashidi
Ottawa General Campus, Ottawa, Ontario, Canada
Shriti Raj
Stanford University , Palo Alto, California, United States
Hariharan Subramonyam
Stanford University, Stanford, California, United States
Fateme Rajabiyazdi
University of Calgary, Calgary, Alberta, Canada

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI Explanations and Decision Support in Healthcare

Auditorium
7 件の発表
2026-04-13 20:15:00
2026-04-13 21:45:00