- Demonstrates technical feasibility of real-time GPT-4o voice simulations for psychiatric semiology, successfully simulating diverse patient personas.
- High pedagogical potential for practising interviewing mechanics, with SME noting useful feedback but presence of stereotyped presentations and content restrictions.
- Suitable primarily for formative practice due to limited multimodal realism and need for rigorous faculty supervision rather than high-stakes assessment.
Acad Psychiatry. 2026 Sep 24. doi: 10.1007/s40596-026-02422-9. Online ahead of print.
ABSTRACT
OBJECTIVE: This 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.
METHODS: Four 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.
RESULTS: GPT-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.
CONCLUSIONS: This 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.
PMID:42786409 | DOI:10.1007/s40596-026-02422-9
Share Evidence Blueprint
Save to Google Notes
Search Google Scholar
Save as PDF
⭐ My Revision List
