Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models

2025-07-27

AI Summary

Existing large language models (LLMs) lack domain-specific therapeutic simulation capabilities and fail to track longitudinal healing progress in mental health support. Method: We propose the first interactive LLM system designed specifically for narrative therapy, integrating treatment-stage planning, reflective-level scaffolding, context-aware response generation, and narrative transformation detection to form a closed-loop intervention framework. We further introduce a novel “Moment of Innovation” quantification model to dynamically monitor narrative reconstruction and deliver personalized feedback. Contribution/Results: Evaluated on 260 simulated dialogues and 230 human participants, the system significantly enhances dialogue depth and therapeutic quality (p < 0.01), generating more empowering and socially supportive responses. It overcomes key limitations of general-purpose LLMs—namely insufficient therapeutic depth, poor temporal continuity, and low clinical adaptability—thereby advancing AI’s role in evidence-informed, narrative-based mental health interventions.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior
• Natural Language Processing: Conversational AI/Dialog Systems

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

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.

Problem

• Simulating realistic specialized psychotherapy using LLMs
• Increasing access to narrative therapy despite social stigma
• Quantifying therapy progress through Innovative Moment Assessment

Innovation

• Simulates expert narrative therapists interactively
• Tracks Innovative Moments for therapy progress
• Outperforms standard LLMs in therapeutic quality