ArticleJMIR medical education2026
An AI-Driven Virtual Patient Platform (CBT Trainer) for Training Cognitive Behavioral Therapy Practitioners Against Competencies: Mixed Methods Pilot Study.
Article in JMIR medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Catch My Drift: Building Scalable and Sustainable Models for Promoting Clinician Adherence to Evidence-Based Treatments for Eating Disorders.Journal of medical Internet research · 2026Article
- [Therapist augmentation by generative AI: concept and implementation of the GAINED feedback system at Osnabrück University].Psychotherapie (Heidelberg, Germany) · 2026Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Cognitive behavioral therapy (CBT) training faces significant challenges, including supervised practice with diverse cases, inconsistent feedback, resource-intensive supervision, and difficulties standardizing competence assessment. Objective: This study evaluated the acceptability and feasibility of CBT Trainer (TTZ), the first virtual patient platform to provide real-time feedback aligned with established competence frameworks. The mobile app trains psychological practitioners using standardized artificial intelligence patient interactions and the evaluation of therapist responses against competence frameworks to enable structured skill development in a controlled, repeatable environment that complements traditional training methods. Methods: This mixed methods pilot study used a 2-stage approach. Stage 1 involved usability testing with 4 participants. Stage 2 included 59 participants from psychological practitioner training programs (a Low Intensity CBT Interventions Program and a Doctorate in Clinical Psychology) who engaged with the CBT Trainer voluntarily for over 1 month. Measures of impact included the System Usability Scale (SUS), platform naturalistic engagement, poststudy questionnaire on perceived competency development, comparative evaluation against traditional role-play, and qualitative feedback. Results: Participants engaged voluntarily with the platform for an average of 95.24 (SD 134.58; median 45.34, IQR 11.57-105.15) minutes of active role-play. Platform usability was rated as excellent (mean SUS 82.20, SD 12.93). Self-reported competence improvement improved most in assessment skills (96.7%) and information gathering (66.7%). When compared to traditional peer role-play exercises, participants rated CBT Trainer moderately favorably (mean 5.90/10, SD 1.94). Qualitative feedback highlighted strengths in competency-aligned feedback, on-demand accessibility, and a psychologically safe practice space. Conclusions: This pilot study provides evidence that an artificial intelligence-based patient simulation shows promise as a supplementary training tool for psychological therapists who use CBT in their practice, particularly regarding accessibility and immediate feedback. Future research should use randomized controlled designs with objective competence assessments.
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