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

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Authors: Shri Harini Ramesh, Foroozan Daneshzand, Babak Rashidi, Shriti Raj, Hariharan Subramonyam, Fateme Rajabiyazdi
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Abstract

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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Information Retrieval and Search Behavior Innovative Human-Technology Interaction

Publication details

Journal / source
CHI Conference on Human Factors in Computing Systems
Pages
1–16
Publication date
13 April 2026