用大模型模拟心理叙事疗法，自动识别治疗关键进展
Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models
- 构建交互式叙事治疗框架，分阶段引导用户重构人生故事
- 通过创新时刻量化评估，准确捕捉治疗过程中的认知转变
- 适合心理健康应用、数字疗愈产品开发人员参考
大语言模型在心理健康支持方面取得进展，但现有方法缺乏专业心理治疗的真实模拟，且难以追踪治疗进程。叙事疗法能帮助个体将问题化的人生故事转化为赋能性叙述，却因资源有限和社交偏见而难普及。本文提出一个包含两个核心组件的综合框架：首先，INT（交互式叙事治疗师）通过规划治疗阶段、引导反思层次并生成符合语境的专家级回应，模拟专业叙事治疗师；其次，IMA（创新时刻评估）提供以治疗为中心的评估方法，通过量化“创新时刻”（IMs）——即客户话语中标志治疗进展的关键叙事转变——来衡量疗效。在260个模拟患者和230名真人参与者上的实验结果表明，INT在治疗质量与深度上持续优于标准大模型。此外，研究还验证了INT生成高质量支持对话的能力，可有效用于社交应用场景。
原文摘要 · Abstract (English)
Recent progress in large language models (LLMs) has opened new possibilities for mental health support, yet current approaches lack realism in simulating specialized psychotherapy and fail to capture therapeutic progression over time. Narrative therapy, which helps individuals transform problematic life stories into empowering alternatives, remains underutilized due to limited access and social stigma. We address these limitations through a comprehensive framework with two core components. First, INT (Interactive Narrative Therapist) simulates expert narrative therapists by planning therapeutic stages, guiding reflection levels, and generating contextually appropriate expert-like responses. Second, IMA (Innovative Moment Assessment) provides a therapy-centric evaluation method that quantifies effectiveness by tracking "Innovative Moments" (IMs), critical narrative shifts in client speech signaling therapy progress. Experimental results on 260 simulated clients and 230 human participants reveal that INT consistently outperforms standard LLMs in therapeutic quality and depth. We further demonstrate the effectiveness of INT in synthesizing high-quality support conversations to facilitate social applications.
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