AI 中文总结
该研究通过2×2×3被试内实验，发现对话语境对用户沟通行为的影响远大于共情表达模态，为构建语境感知的AI健康咨询系统提供设计依据。
AI 中文摘要
随着在线健康信息获取转向对话式AI，高质量信息检索越来越依赖用户的“沟通行为”（主动分享与寻求信息），这与医患沟通中获取有效诊断和个性化指导的方式类似。本研究借鉴健康传播研究，通过2×2×3被试内实验（N=48），探究聊天机器人的共情表达模态（语言、视觉、多模态）和对话语境（一般、敏感、心理健康）如何影响这些行为。结果显示，语言和多模态共情显著增加回复长度，但沟通行为主要受对话语境影响：敏感语境触发更多提问，心理健康语境引发更多担忧、更果断的回应及主动信息披露。结合定性发现，本文探讨构建语境感知的AI健康咨询系统的设计启示，以鼓励用户积极参与。
英文摘要
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.
Comments5 pages, 2 figures. To appear in UbiComp Companion 2026 (October 11-15, 2026, Shanghai, China)
