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ID07565714

Using Artificial Intelligence to Enhance Imagery Rescripting Therapy for Adults with Anxiety and Fear of Failure A Study on Personalized Audio Scripts Based on Childhood Memories

Led by University of Social Sciences and Humanities, Warsaw · Updated on 2026-05-07

40

Participants Needed

2

Research Sites

4 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are studying how imagery rescripting ImRs, a therapeutic technique, can be enhanced using large language models LLMs like Gemini. The focus is on emotional and physiological effects when participants listen to personalized audio scripts based on their childhood memories of parental criticism and neutral events. This pilot randomized controlled trial compares traditional ImRs methods with AI-generated versions to better understand their impact on anxiety, fear of failure, and rumination. Participants listen to audio scripts created from their own childhood memories. The experimental group hears a modified version of a critical memory script where a therapist figure intervenes in the scene to address unmet needs, applying ImRs. Skin conductance levels are recorded during sessions to measure physiological arousal. One week later, participants complete questionnaires on generalized anxiety and intrusive thoughts. Licensed therapists also evaluate the AI-generated scripts for therapeutic quality. During the study, participants recall and describe memories, listen to scenarios, rate their emotional responses, and have continuous skin conductance monitoring. Follow-up questionnaires assess anxiety and intrusive thoughts after one week. The study measures include anxiety scales, fear of failure, thought frequency, physiological responses, and therapist ratings. This research aims to test the feasibility of using AI-generated personalized therapies and their emotional and physiological effects over about one week of participation.

CONDITIONS

Brief Title

Optimization of Late Imagery Rescripting Research Using Generative Artificial Intelligence

Research Team

S

Stanisław Karkosz, MA

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