ArticleAcademic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry2026
LLM-Based Psychiatric Interview Simulation: Technical Development and Pilot Expert-Based Content Validation of a Voice Prototype.
Article in Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveThis study describes the technical development and a pilot expert-based content validation of an interactive voice prototype, using the GPT-4o model, for teaching psychiatric semiology. It explores the potential of large language models (LLMs) to generate real-time feedback and address challenges in acquiring complex clinical competencies.
methodsFour psychiatric patient personas (major depressive disorder, bipolar disorder-manic episode, schizophrenia, and attention-deficit/hyperactivity disorder) were developed through a structured iterative process. A subject matter expert (SME) conducted a structured heuristic evaluation to assess clinical fidelity, consistency, and vocal expressiveness across the four scenarios. Quantitative data (Likert scale scores) and qualitative feedback were mapped to identified technical and semiological challenges.
resultsGPT-4o simulated diverse personas with distinct profiles. The SME reported high potential pedagogical value for practicing interviewing mechanics. However, challenges included stereotyped clinical presentations and platform-imposed content restrictions.
conclusionsThis pilot study establishes the technical feasibility of voice-based LLM simulations. While offering a promising complementary tool, current limitations in multimodal realism and the need for rigorous faculty supervision suggest that the tool is best suited for formative practice rather than high-stakes assessment.
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