Health Inquiry with AI: How Empathetic Expression and Conversational Contexts Shape Users' Communicative Acts

2026-08-17

AI Summary

研究探讨了聊天机器人的共情表达方式（言语、视觉、多模态）和对话情境（一般、敏感、心理健康）如何影响用户的交流行为，以促进构建能鼓励用户积极参与的情境敏感型AI健康咨询系统。

Abstract

As online health information-seeking shifts to conversational AI, high-quality information retrieval increasingly relies on users' ``communicative acts''(proactively sharing and seeking information)---similar to how effective diagnosis and personalized guidance are elicited in patient-clinician communication. Drawing on health communication research, this study examines how a chatbot's modality of empathetic expression (Verbal, Visual, Multimodal) and the conversational context (General, Sensitive, Mental Health) influence these acts through a 2 x 2 x 3 within-subjects experiment (N = 48). The results revealed that while verbal and multimodal empathy significantly increased reply length, communicative acts were largely shaped by conversational context, with Sensitive context triggering more question-asking and Mental Health context leading to heightened concerns, assertive responses, and unprompted information disclosure. Combined with qualitative findings, we discuss design implications for building context-sensitive AI health inquiry systems that can encourage active user participation.

Problem

• empathetic expression
• conversational context
• communicative acts

Innovation

• empathetic expression
• conversational context
• communicative acts
• context-sensitive AI
• health inquiry systems