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

TL;DR

This study investigates the metacognitive challenges users face when seeking health information through off-the-shelf AI conversational agents and explores strategies to improve user experience.

Contribution

It identifies specific metacognitive demands and coping strategies, offering design considerations to enhance health information seeking with AI agents.

Findings

High monitoring and control demands identified

Users adopt specific coping strategies

Design recommendations proposed for better interfaces

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.