Mental illness remains one of the most critical public health issues of our time, due to the severe scarcity and accessibility limit of professionals. Psychotherapy requires high-level expertise to conduct deep, complex reasoning and analysis on the cognition modeling of the patients. In the era of Large Language Models, we believe it is the right time to develop AI assistance for computational psychotherapy. We study the task of cognitive distortion detection and propose the Diagnosis of Thought (DoT) prompting. DoT performs diagnosis on the patient's speech via three stages: subjectivity assessment to separate the facts and the thoughts; contrastive reasoning to elicit the reasoning processes supporting and contradicting the thoughts; and schema analysis to summarize the cognition schemas. The generated diagnosis rationales through the three stages are essential for assisting the professionals. Experiments demonstrate that DoT obtains significant improvements over ChatGPT for cognitive distortion detection, while generating high-quality rationales approved by human experts.

翻译：精神疾病仍然是当今最关键的公共卫生问题之一，原因是专业人员的严重稀缺和可及性限制。心理治疗需要高水平专业知识，对患者的认知建模进行深入、复杂的推理和分析。在大语言模型时代，我们相信是时候开发面向计算心理治疗的AI辅助工具了。我们研究认知扭曲检测任务，并提出思维诊断（DoT）提示方法。DoT通过三个阶段对患者言语进行诊断：主观性评估以区分事实与思维；对比推理以引出支持与反驳思维的推理过程；图式分析以总结认知图式。这三个阶段生成的诊断推理对于辅助专业人员至关重要。实验表明，DoT在认知扭曲检测上相较于ChatGPT取得显著提升，同时生成了经人类专家认可的高质量推理过程。