Accepted for/Published in: JMIR Medical Education
Date Submitted: Sep 22, 2025
Open Peer Review Period: Sep 28, 2025 - Nov 23, 2025
Date Accepted: Jan 30, 2026
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
AI Patients for Training CBT Therapists to Develop Clinical Competence: Pilot Study of CBT Trainer
ABSTRACT
Background:
Training challenges in Cognitive Behavioral Therapy (CBT) include limited supervised practice with diverse cases, inconsistent feedback, resource-intensive supervision, and difficulties standardising competence assessment.
Objective:
This study evaluated the acceptability and feasibility of CBT Trainer, a mobile application for training CBT practitioners through the use of standardized AI patient interactions and the evaluation of therapist responses against competence frameworks to enable structured skill development grounded in experiential learning and deliberate practice.
Methods:
This mixed-methods pilot study employed a two-stage approach. Stage 1 involved usability testing with four participants. Stage 2 included 59 participants from psychological practitioner training programs (a Low Intensity CBT Interventions Programme and a Doctorate in Clinical Psychology) who engaged with the CBT Trainer over one month. Measures of impact included the System Usability Scale (SUS), platform engagement, post-study questionnaire on perceived learning outcomes and qualitative feedback.
Results:
CBT Trainer performed well on all pre-specified outcome targets. Participants spent an average of 95.24 minutes (SD=134.58) in roleplays, completed an average of 4.15 role-play sessions (SD=3.55), with 49.69 interactions per session. Platform usability was rated as excellent (mean SUS=82.20, SD=12.93). Self-reported competence improvement was highest in assessment skills (96.7%), followed by information gathering (66.7%). Key advantages over traditional methods included immediate feedback (83.3%) and convenience (73.3%).
Conclusions:
This pilot study provides evidence that an AI-based patient simulation shows promise as a supplementary training tool for CBT therapists, particularly regarding accessibility and immediate feedback. Future research should employ randomized controlled designs with objective competence assessments. Clinical Trial: The study protocol was pre-registered with the Open Science Framework (https://osf.io/mskb7).
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