大型语言模型是否有可能进行认知行为疗法？
Are Large Language Models Possible to Conduct Cognitive Behavioral Therapy?
AI总结：
本研究针对LLMs能否进行认知行为疗法（CBT）的疑问，收集真实CBT语料并设计自动评估框架，从情感倾向、结构化对话模式、主动提问能力及知识库整合四方面评估四种LLM变体，结果显示LLMs在心理咨询领域具巨大潜力。
摘要：
在当代社会，心理健康问题日益突出，表现为精神障碍的多样化、复杂化和普遍化。认知行为疗法（CBT）是目前最具影响力且临床有效、无副作用的心理治疗方法，但在大多数国家其覆盖面有限且质量不佳。近年来，利用大型语言模型（LLMs）进行情绪障碍识别和干预的研究已得到验证，为心理辅助治疗提供了新的可能性。然而，LLMs是否真的有可能进行认知行为疗法？心理健康专家对使用LLMs进行疗法提出了诸多担忧。为了回答这个问题，我们从在线视频网站收集了真实的CBT语料库，设计并实施了一个针对性的自动评估框架，涉及对生成文本的情感倾向、结构化对话模式和主动询问能力的评估。对于情感倾向，我们计算每个模型生成的CBT对话文本的情感倾向得分。对于结构化对话模式，我们使用多种自动评估指标来比较不同模型在说话风格、保持话题一致性以及CBT技术使用方面的表现。至于引导患者的询问，我们使用PQA（主动提问能力）指标。我们还评估了整合CBT知识库后LLM的CBT能力，以探索引入额外知识对增强模型CBT咨询能力的帮助。评估了四种在自然语言处理方面表现优异的LLM变体，实验结果显示了LLMs在心理咨询领域的巨大潜力，尤其是在结合其他技术手段之后。
英文摘要：
In contemporary society, the issue of psychological health has become increasingly prominent, characterized by the diversification, complexity, and universality of mental disorders. Cognitive Behavioral Therapy (CBT), currently the most influential and clinically effective psychological treatment method with no side effects, has limited coverage and poor quality in most countries. In recent years, researches on the recognition and intervention of emotional disorders using large language models (LLMs) have been validated, providing new possibilities for psychological assistance therapy. However, are LLMs truly possible to conduct cognitive behavioral therapy? Many concerns have been raised by mental health experts regarding the use of LLMs for therapy. Seeking to answer this question, we collected real CBT corpus from online video websites, designed and conducted a targeted automatic evaluation framework involving the evaluation of emotion tendency of generated text, structured dialogue pattern and proactive inquiry ability. For emotion tendency, we calculate the emotion tendency score of the CBT dialogue text generated by each model. For structured dialogue pattern, we use a diverse range of automatic evaluation metrics to compare speaking style, the ability to maintain consistency of topic and the use of technology in CBT between different models . As for inquiring to guide the patient, we utilize PQA (Proactive Questioning Ability) metric. We also evaluated the CBT ability of the LLM after integrating a CBT knowledge base to explore the help of introducing additional knowledge to enhance the model's CBT counseling ability. Four LLM variants with excellent performance on natural language processing are evaluated, and the experimental result shows the great potential of LLMs in psychological counseling realm, especially after combining with other technological means.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
