发表机构
Peking University（北京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本综述系统梳理了GenAI-MI聊天机器人在设计、安全、质量、用户感知及干预效果方面的证据，发现其能提供符合MI原则且用户感知良好的交互，但持续行为改变证据有限。
AI 中文摘要
动机性访谈（MI）是一种协作性方法，旨在激发个体对健康行为改变的自主动机。生成式人工智能（GenAI）为通过对话系统实施动机性访谈提供了新途径，但关于其设计、评估及向干预措施转化的证据仍较为零散。本范围综述从系统设计、安全性、动机性访谈质量、用户感知及干预效果等方面，对GenAI-MI聊天机器人的相关证据进行了系统梳理。我们遵循PRISMA-ScR范围综述指南开展研究。检索了九个数据库，纳入2015年1月1日至2026年6月2日期间发表或公开、使用GenAI生成MI聊天机器人回复或咨询师话语的研究。采用预设框架提取数据并进行描述性综合。共纳入47篇报告（48项研究）。其中20项（41.7%）聚焦于系统设计，未涉及直接用户使用；28项（58.3%）涉及直接交互。大多数系统基于文本且无实体形态；23项（47.9%）纳入了动态适应机制。安全措施的报道参差不齐。在涉及直接使用的研究中，21/28项（75.0%）报告了知情同意或用户教育。30项（62.5%）评估了MI质量，总体表明交互符合MI原则。用户感知总体积极，尤其在同理心、可用性、帮助性和使用意愿方面，但测量工具存在异质性。18项（37.5%）报告了干预效果，多数仅评估单次会话后的效果。短期动机方面的积极结果比持续行为或功能改变更为一致。GenAI-MI聊天机器人能够提供符合MI原则且用户感知良好的交互，但关于持续行为或功能改变的证据有限。未来研究应加强运行时安全监控，标准化MI质量评估，并采用包含行为和功能结局的长期比较设计。
英文摘要
Motivational interviewing (MI) is a collaborative approach to elicit autonomous motivation for health behavior change. Generative AI (GenAI) offers new ways to deliver MI via conversational systems, but evidence on their design, assessment, and translation into interventions remains fragmented. This scoping review characterized evidence on GenAI-MI chatbots across system design, safety, MI quality, user perceptions, and intervention outcomes. We conducted a PRISMA-ScR scoping review. Nine datasets were searched for studies published or publicly available from January 1, 2015 to June 2, 2026 that used GenAI to generate MI chatbot responses or counselor utterances. Data were extracted using a predefined framework and synthesized descriptively. Forty-seven reports (48 studies) were included. Twenty (41.7%) focused on system design without direct participant use; 28 (58.3%) involved direct interaction. Most systems were text based and disembodied; 23 (47.9%) incorporated dynamic adaptation. Safety measures were unevenly reported. Among studies with direct use, 21/28 (75.0%) reported informed consent or user education. Thirty (62.5%) assessed MI quality, generally suggesting MI-consistent interactions. User perceptions were favorable, especially empathy, usability, helpfulness, and intention to use, though measures were heterogeneous. Eighteen (37.5%) reported intervention outcomes, mostly after a single session. Positive findings were more consistent for short-term motivation than sustained behavioral or functional change. GenAI-MI chatbots can deliver MI-consistent interactions perceived favorably, but evidence for sustained behavioral or functional change is limited. Future research should strengthen runtime safety monitoring, standardize MI quality assessment, and use longer-term comparative designs with behavioral and functional outcomes.
