Optimization of Late Imagery Rescripting Research Using Generative Artificial Intelligence
NCT07565714 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 40
Last updated 2026-05-07
Summary
The aim of the study is to examine the effect of imagery rescripting (ImRs) in the context of utilizing large language models (LLMs). Intervention will involve the prior presentation of the most aversive fragment of the memory, the so-called 'hotspot.' This intervention will allow for the replication of the effect described by Dibbets and Arntz (2016), according to which the prior activation of the most emotional element of a memory enhances the effectiveness of ImRs.
The study is also significant due to another ongoing study in which a substantial number of participants have already been examined; however, due to the exhaustion of funds, it was not possible to utilize the remainder of the recruited sample. Investigating an additional condition will allow for a more complete utilization of the available participant pool and significantly increase the project's scientific value by comparing the traditional ImRs mechanism with its AI-generated version.
Conditions
- Generalized Anxiety
- Fear of Failure
- Rumination
Interventions
- BEHAVIORAL
-
Imagery Rescripting Intervention
Participants listened to a series of personalized audio scenarios based on their childhood memories of parental criticism and neutral events. At the end of the session, one critical scenario was presented in a modified version that included a therapeutic imagery rescripting (ImRs) intervention. In this script, a therapist figure entered the scene and addressed the child's unmet needs, following the standard rescripting format. The scripts were generated using the Gemini large language model and reviewed by trained experimenters to ensure coherence and therapeutic validity. The intervention aimed to reduce distress and intrusive thoughts related to the memory.
Sponsors & Collaborators
-
University of Social Sciences and Humanities, Warsaw
lead OTHER
Principal Investigators
-
Stanisław Karkosz, MA · SWPS University
Study Design
- Allocation
- NA
- Purpose
- BASIC_SCIENCE
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 18 Years
- Max Age
- 35 Years
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2026-04-30
- Primary Completion
- 2026-06-30
- Completion
- 2026-07-31
Countries
- Poland
Study Locations
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