用大模型打造能激励戒烟的聊天机器人，效果接近真人。
A Fully Generative Motivational Interviewing Counsellor Chatbot for Moving Smokers Towards the Decision to Quit
- 基于先进大模型与动机访谈法设计对话机器人。
- 参与者戒烟信心平均提升1.7分（0-10分制），一周后仍保持提升。
- 自动评估显示其符合动机访谈标准达98%，适合推广至心理辅导场景。
大型语言模型（LLMs）的对话能力表明它们可能胜任自动化心理治疗。本文提出一款专注于激励吸烟者戒烟的顾问聊天机器人，结合最先进的大模型与广泛使用的动机访谈（MI）疗法，并由具备MI专长的临床科学家共同开发。我们还描述并验证了一种自动化评估方法，用于衡量聊天机器人对MI的遵循程度及用户响应。在106名参与者中测试，其戒烟信心在对话前与一周后分别测量，平均提升1.7分（0-10分制）。自动化评估显示，聊天机器人在98%的发言中符合MI标准，高于人类咨询师。参与者反馈的共情感知得分良好，但低于典型人类咨询师。此外，参与者语言表现出较高水平的改变意愿，这是动机访谈的核心目标。结果表明，使用现代大模型实现谈话治疗自动化具有潜力。
原文摘要 · Abstract (English)
The conversational capabilities of Large Language Models (LLMs) suggest that they may be able to perform as automated talk therapists. It is crucial to know if these systems would be effective and adhere to known standards. We present a counsellor chatbot that focuses on motivating tobacco smokers to quit smoking. It uses a state-of-the-art LLM and a widely applied therapeutic approach called Motivational Interviewing (MI), and was evolved in collaboration with clinician-scientists with expertise in MI. We also describe and validate an automated assessment of both the chatbot's adherence to MI and client responses. The chatbot was tested on 106 participants, and their confidence that they could succeed in quitting smoking was measured before the conversation and one week later. Participants' confidence increased by an average of 1.7 on a 0-10 scale. The automated assessment of the chatbot showed adherence to MI standards in 98% of utterances, higher than human counsellors. The chatbot scored well on a participant-reported metric of perceived empathy but lower than typical human counsellors. Furthermore, participants' language indicated a good level of motivation to change, a key goal in MI. These results suggest that the automation of talk therapy with a modern LLM has promise.
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