{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T19:02:31Z","timestamp":1790276551083,"version":"4.1.0"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universidade Federal De Ci\u00eancias Da Sa\u00fade De Porto Alegre","id":[{"id":"https:\/\/ror.org\/00x0nkm13","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Acad Psychiatry"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Four psychiatric patient personas (major depressive disorder, bipolar disorder\u2014manic 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s40596-026-02422-9","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T18:52:07Z","timestamp":1790275927000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LLM-Based Psychiatric Interview Simulation: Technical Development and Pilot Expert-Based Content Validation of a Voice Prototype"],"prefix":"10.1007","author":[{"given":"Vin\u00edcius Vicente","family":"Soares","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felipe Francisco de Castro","family":"Passos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fl\u00e1vio Milman","family":"Shansis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juliana Silva","family":"Herbert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"2422_CR1","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195062519.001.0001","volume-title":"The psychiatric mental status examination","author":"PT Trzepacz","year":"1993","unstructured":"Trzepacz PT, Baker RW. The psychiatric mental status examination. New York, NY: Oxford University Press; 1993."},{"key":"2422_CR2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2019.00077","volume":"10","author":"HG Rocha Neto","year":"2019","unstructured":"Rocha Neto HG, Estellita-Lins CE, Lessa JLM, Cavalcanti MT. Mental state examination and its procedures-narrative review of Brazilian descriptive psychopathology. Front Psychiatry. 2019;10:77.","journal-title":"Front Psychiatry"},{"key":"2422_CR3","doi-asserted-by":"publisher","first-page":"e68486","DOI":"10.2196\/68486","volume":"27","author":"DA Cook","year":"2025","unstructured":"Cook DA, Overgaard J, Pankratz VS, Del Fiol G, Aakre CA. Virtual patients using large language models: scalable, contextualized simulation of clinician-patient dialogue with feedback. J Med Internet Res. 2025;27:e68486. https:\/\/doi.org\/10.2196\/68486.","journal-title":"J Med Internet Res"},{"key":"2422_CR4","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1080\/09540261.2019.1648242","volume":"32","author":"JELU Keith Hariman","year":"2020","unstructured":"Keith Hariman JELU, da Costa MP. The future of psychiatric education. Int Rev Psych. 2020;32:178\u201385. https:\/\/doi.org\/10.1080\/09540261.2019.1648242.","journal-title":"Int Rev Psych"},{"key":"2422_CR5","doi-asserted-by":"publisher","first-page":"e49877","DOI":"10.2196\/49877","volume":"9","author":"R Scherr","year":"2023","unstructured":"Scherr R, Halaseh FF, Spina A, Andalib S, Rivera R. ChatGPT interactive medical simulations for early clinical education: case study. JMIR Med Educ. 2023;9:e49877. https:\/\/doi.org\/10.2196\/49877.","journal-title":"JMIR Med Educ"},{"key":"2422_CR6","unstructured":"Chu SN, Goodell AJ. Synthetic patients: simulating difficult conversations with multimodal generative AI for medical education. 2024. http:\/\/arxiv.org\/abs\/2405.19941. Accessed 26 Aug 2026."},{"key":"2422_CR7","doi-asserted-by":"publisher","DOI":"10.1136\/medethics-2020-106820","author":"JM Dur\u00e1n","year":"2021","unstructured":"Dur\u00e1n JM, Jongsma KR. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI. J Med Ethics. 2021. https:\/\/doi.org\/10.1136\/medethics-2020-106820.","journal-title":"J Med Ethics"},{"issue":"1","key":"2422_CR8","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1038\/s41746-025-01611-4","volume":"8","author":"Y Hua","year":"2025","unstructured":"Hua Y, et al. A scoping review of large language models for generative tasks in mental health care. npj Digit Med. 2025;8:230.","journal-title":"npj Digit Med"},{"key":"2422_CR9","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1126\/science.aax2342","volume":"366","author":"Z Obermeyer","year":"2019","unstructured":"Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366:447\u201353.","journal-title":"Science"},{"key":"2422_CR10","unstructured":"OpenAI. GPT-4o System Card. Tech Rep, OpenAI. 2024. https:\/\/openai.com\/index\/gpt-4o-system-card\/. Accessed 26 Aug 2026."},{"key":"2422_CR11","doi-asserted-by":"publisher","DOI":"10.3389\/frvir.2022.827312","author":"L Chaby","year":"2022","unstructured":"Chaby L. Embodied virtual patients as a simulation-based framework for training clinician-patient communication skills: an overview of their use in psychiatric and geriatric care. 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