Optimization of Late Imagery Rescripting Research Using Generative Artificial Intelligence

Overview

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.

Detailed description

This pilot randomized controlled trial will explore the application of large language models (LLMs) in the development of personalized therapeutic interventions. The study will focus on the emotional and psychophysiological effects of listening to autobiographical scenarios based on participants' childhood experiences of parental criticism. All participants will be asked to recall and describe two critical and two neutral childhood memories. Based on this input, personalized scripts will be generated using Gemini, a large language model. Each script will be reviewed and, if necessary, modified by trained experimenters to ensure therapeutic coherence and alignment with imagery rescripting (ImRs) principles. On Day 1, all participants will listen to critical personalized scenarios during the laboratory session. The experimental group will listen to modified versions of the critical memory scripts, in which a therapist figure will intervene to address the child's unmet needs-an application of imagery rescripting. To assess physiological arousal, skin conductance will be continuously recorded throughout the session. After each scenario, participants will rate their emotional intensity and specific feelings (e.g., fear, sadness) on Likert scales. The group will receive the ImRs intervention after the initial scenario phase. One week later, all participants will complete follow-up questionnaires assessing generalized anxiety (GAD-7) and the frequency of intrusive thoughts related to the memories. In addition, a panel of licensed cognitive-behavioral therapists will evaluate the generated scenarios for therapeutic quality. Their feedback will be used to assess the acceptability and coherence of AI-assisted therapeutic scripts. The study will test the feasibility of using LLM-generated content in clinical settings and aims to determine whether such interventions can reduce distress and intrusiveness while eliciting measurable emotional and physiological responses

Hypotheses:

The criticism scenarios generated by the model will elicit fearful responses in all participants.

The level of fearful reaction evoked by the AI-generated criticism scenarios will correlate with participants' baseline fear of failure.

Participants in the ImRs group will report fewer intrusive thoughts and lower generalized anxiety levels one week after the intervention.

Magnitude of Prediction Error (operationalized as a difference in SCL response between hotspot and intervention parts of the scenario) will correlate positively with a decrease in the number of intrusive thoughts.

The magnitude of imagery difficulty during the rescripting part will correlate negatively with the magnitude of Prediction Error.

Subjective efficacy of intervention will be predicted by working alliance.

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

Primary outcome measures

• Generalized Anxiety Disorder DSM Scale (GAD) [Time frame: Screening, Pre-intervention (Day 1) and 1-week follow-up]
• The Performance Failure Appraisal Inventory [Time frame: Pre-intervention (Day 1)]
• Intrusive Thought Frequency (Rumination Inventory - adapted) [Time frame: Pre-intervention (Day 1) and 1-week follow-up]
• Skin Conductance Level (SCL) [Time frame: During experiment/intervention (Day 1)]
• Emotional Response Ratings (Subjective) [Time frame: During experiment/intervention (Day 1)]

Secondary outcome measures (5)

• Therapist Ratings of Script Quality [Time frame: Prior to intervention]
• Questionnaire on the Perceived Effectiveness and Appropriateness of Imagery-Based Intervention [Time frame: Post-intervention (Day 1)]
• TAPS Tool - Substance Use Screening [Time frame: Screening only]
• Post-Traumatic Stress Symptoms Scale (DSM) [Time frame: Screening only]
• Working Alliance Inventory - Short Revised [Time frame: Post-intervention (Day 1)]

Eligibility criteria

Inclusion criteria

• Age 18-35
• Score ≥ 8 on GAD-7 (Plummer et al., 2016)
• Ability to recall at least two childhood memories involving parental criticism

Exclusion criteria

• History of prolonged physical or sexual abuse
• Current psychotherapy or psychopharmacology
• PTSD diagnosis (DSM-5 screening)
• Substance abuse (TAPS tool)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

N/A

Model

Single group

Masking

Open label

Primary purpose

Basic science

Study locations

Poland · 2 centers

• SWPS University (University of Social Sciences and Humanities); Poznań Laboratory of Affec — Poznan
• SWPS University of Social Sciences and Humanities; Poznań Laboratory of Affective Neurosci — Poznan

Publications

• Bradley MM, Sambuco N, Lang PJ. Imagery, emotion, and bioinformational theory: From body to brain. Biol Psychol. 2023 Oct;183:108669. doi: 10.1016/j.biopsycho.2023.108669. Epub 2023 Aug 28. PMID 37648076
• McNeely J, Wu LT, Subramaniam G, Sharma G, Cathers LA, Svikis D, Sleiter L, Russell L, Nordeck C, Sharma A, O'Grady KE, Bouk LB, Cushing C, King J, Wahle A, Schwartz RP. Performance of the Tobacco, Alcohol, Prescription Medication, and Other Substance Use (TAPS) Tool for Substance Use Screening in Primary Care Patients. Ann Intern Med. 2016 Nov 15;165(10):690-699. doi: 10.7326/M16-0317. Epub 2016 PMID 27595276
• Mossman SA, Luft MJ, Schroeder HK, Varney ST, Fleck DE, Barzman DH, Gilman R, DelBello MP, Strawn JR. The Generalized Anxiety Disorder 7-item scale in adolescents with generalized anxiety disorder: Signal detection and validation. Ann Clin Psychiatry. 2017 Nov;29(4):227-234A. PMID 29069107
• Busseri MA, Tyler JD. Interchangeability of the Working Alliance Inventory and Working Alliance Inventory, Short Form. Psychol Assess. 2003 Jun;15(2):193-7. doi: 10.1037/1040-3590.15.2.193. PMID 12847779
• Cann A, Calhoun LG, Tedeschi RG, Triplett KN, Vishnevsky T, Lindstrom CM. Assessing posttraumatic cognitive processes: the Event Related Rumination Inventory. Anxiety Stress Coping. 2011 Mar;24(2):137-56. doi: 10.1080/10615806.2010.529901. PMID 21082446
• Arntz, A. (2012). Imagery rescripting as a therapeutic technique: Review of clinical trials, basic studies, and research agenda. Journal of Experimental Psychopathology, 3(2), 189-208.
• Conroy, D. E. (2001). Progress in the development of a multidimensional measure of fear of failure: The Performance Failure Appraisal Inventory (PFAI). Anxiety, Stress and Coping, 14(4), 431-452.
• Dibbets P, Arntz A. Imagery rescripting: Is incorporation of the most aversive scenes necessary? Memory. 2016;24(5):683-95. doi: 10.1080/09658211.2015.1043307. Epub 2015 Jun 15. PMID 26076101

Identifiers

NCT: NCT07565714 · ImRs_LLM_DeanGrant

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗