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Four OSCE scenarios were tested under a standard clinical prompt, a context-enhanced prompt, and two variation prompts containing irrelevant or distracting information. The model was tasked with OSCE activities including history-taking, risk assessment, explanation, and management, then responses were scored with a structured rubric and analysed thematically.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/large-language-model-used-to-simulate-psychiatric-osce-scenarios-a-medical-student-perspective/317143/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/large-language-model-used-to-simulate-psychiatric-osce-scenarios-a-medical-student-perspective/317143.png","ImageObject",300,407,{"name":92,"@type":93},"Jake","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-20",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",15,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What was the main aim of the study?","Question",{"text":113,"@type":114},"To determine how different prompt conditions influence the quality and clinical coherence of GPT-4o mini responses in simulated psychiatric OSCE scenarios.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were the GPT-4o mini prompts varied in the experiments?",{"text":118,"@type":114},"Four psychiatric OSCE cases were presented under a standard clinical prompt, a context-enhanced prompt, and two prompts that added irrelevant or distracting information.",{"name":120,"@type":111,"acceptedAnswer":121},"What did the study find when irrelevant information was introduced?",{"text":122,"@type":114},"Clinically relevant responses were generated under standard and context-enhanced prompts, but performance declined when irrelevant information was added, with lower quantitative scores and reduced coherence.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},317143,1790450350,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146},962084928904,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Large language model used to simulate psychiatric OSCE scenarios: a medical student perspective  \nZhaochu Geng, 1 * Craig S. Webster,2,3 Yan Chen,2 Lillian Ng,4,5 Christian U. Krägeloh,6 Angel Li, 1 and Marcus A. Henning.2  \nAffiliations:  \n1 School of Medicine, University of Auckland, Auckland, New Zealand  \n2Centre for Medical and Health Sciences Education, School of Medicine, University of Auckland, Auckland, New Zealand  \n3Department of Anaesthesiology, School of Medicine, University of Auckland, Auckland, New Zealand  \n4Department of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand  \n5Auckland Regional Forensic Services, Health New Zealand, Te Whatu Ora, Auckland, New Zealand  \n6Department of Psychology, Auckland University of Technology, Auckland, New Zealand  \n*Correspondence to: [zgen174@acuklanduni.ac.nz](zgen174@acuklanduni.ac.nz)  \nLarge language model used to simulate psychiatric OSCE scenarios: a medical student perspective  \nAbstract  \nAIM: This study investigates how varying prompt conditions influence the quality and clinical coherence of responses generated by a large language model (GPT-4o mini) in simulated psychiatric OSCE scenarios.  \nMETHODS: Four psychiatric OSCE cases were presented to GPT-4o mini under four conditions with increasing details: a standard clinical prompt, a context-enhanced prompt, and two variation prompts incorporating irrelevant or distracting information. GPT-4o mini was asked to perform key OSCE tasks, history-taking, risk assessment, explanation, and management for each case. Responses were scored using a standardised, structured rubric and analysed thematically.  \nRESULTS: GPT-4o mini generated clinically relevant responses under standard and contextenhanced prompts. However, performance declined as irrelevant information was introduced.  \nQuantitative scores dropped significantly across the different conditions, and qualitative analysis revealed reduced coherence, increased verbosity, and difficulty prioritising clinical content.  \nCONCLUSIONS: LLMs like GPT-4o mini can generate useful responses when provided with clear and concise prompt instructions. However, in this study, we noted that clinical accuracy and coherence deteriorated in the presence of distracting or ambiguous input. This highlights the need for critical evaluation and unambiguous literacy when using LLMs in medical  \neducation.  \nKeywords: Artificial intelligence; Large language models; Medical education; Objective structured clinical examination; Psychiatry education; Generative AI  \nIntroduction  \nThe rapid development of artificial intelligence (AI), particularly large language models (LLMs), is transforming multiple sectors, including healthcare and medical education.1 The use of AI offers new opportunities for personalised learning, automated feedback, and simulated clinical experiences. Its potential to augment traditional teaching methods and support the training of future healthcare professionals is a growing area of academic and clinical interest.2 This study directly evaluates the performance of a large language model (GPT-4o mini) in a high-stakes clinical exam, i.e., the Objective Structured Clinical Examination (OSCE) . Understanding how LLMs perform in this context is crucial for their safe and effective integration into student learning.  \nOSCEs are a core component of medical education, designed to assess clinical skills in a standardised and objective manner.3 In psychiatry, OSCEs are particularly valuable for evaluating history-taking, risk assessment, communication skills, and treatment planning in simulated patient encounters.4 These assessments provide students with a structured environment to develop clinical reasoning and interpersonal skills through direct feedback.  \nGiven the growing accessibility of LLMs, there is a compelling rationale to investigate whether these models can produce clinically accurate responses to medical s","cbCaifFFg9RKYpy5","https://ap.wps.com/l/cbCaifFFg9RKYpy5","pdf",294980,22,"English","# Abstract\n## Aim\n## Methods\n## Results\n## Conclusions\n# Introduction\n# Materials and Methods","[{\"question\":\"What was the main aim of the study?\",\"answer\":\"To determine how different prompt conditions influence the quality and clinical coherence of GPT-4o mini responses in simulated psychiatric OSCE scenarios.\"},{\"question\":\"How were the GPT-4o mini prompts varied in the experiments?\",\"answer\":\"Four psychiatric OSCE cases were presented under a standard clinical prompt, a context-enhanced prompt, and two prompts that added irrelevant or distracting information.\"},{\"question\":\"What did the study find when irrelevant information was introduced?\",\"answer\":\"Clinically relevant responses were generated under standard and context-enhanced prompts, but performance declined when irrelevant information was added, with lower quantitative scores and reduced coherence.\"}]","Large language model used to simulate psychiatric OSCE scenarios - a medical student perspective | PDF",1789929119,55]