ArticleJMIR medical education2025
Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study.
Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Application of AI-based virtual standardized patients in physician-patient communication training: a study based on the SEGUE framework.Frontiers in public health · 2026Trial
- Feasibility of AI and Human Standardized Patients to Enhance Customer Discovery Communication Skills in Medical Students: Preliminary Evaluation of an Observational Cohort Study.JMIR formative research · 2026Observational
- Digital Standardized Patients: Conceptual Framework for Generative AI-Empowered Medical Education.JMIR medical education · 2026Article
- Enhancing Psychiatry Training Using an Agentic AI Simulated Consultation Tool: Prospective Cohort Study.JMIR medical education · 2026Article
- Feasibility of Large Language Model-Based Standardized Virtual Patients to Support Clinical Decision-Making Training in Operative Dentistry: Mixed Methods Study.JMIR formative research · 2026Article
- The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.Journal of orthopaedic surgery and research · 2026Review
- Trust Analysis Canvas for Teaching in the Field of Digital Public Health and Medicine: Tutorial.JMIR medical education · 2026Article
- Medical students perceptions and attitudes toward the use of generative artificial intelligence in clinical decision-making: a nationwide cross-sectional survey in China.BMC medical education · 2026Article
- AI-Driven Objective Structured Clinical Examination Generation in Digital Health Education: Comparative Analysis of Three GPT-4o Configurations.JMIR medical education · 2026Article
- Artificial intelligence in undergraduate medical education clinical skills curricula: a scoping review of implementations since 2022.Frontiers in digital health · 2026Review
- A primer on artificial intelligence for palliative care educators.Palliative care and social practice · 2026Review
- Using AI-Based Virtual Simulated Patients for Training in Psychopathological Interviewing: Cross-Sectional Observational Study.JMIR medical education · 2025Observational
- Perceptions, Usage, and Educational Impact of ChatGPT Among Medical Students in Germany: Cross-Sectional Mixed Methods Survey.JMIR formative research · 2025Article
- Technologies, opportunities, challenges, and future directions for integrating generative artificial intelligence into medical education: a narrative review.Ewha medical journal · 2025Article
- A guide to prompt design: foundations and applications for healthcare simulationists.Frontiers in medicine · 2024Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Standardized patients (SPs) have been crucial in medical education, offering realistic patient interactions to students. Despite their benefits, SP training is resource-intensive and access can be limited. Advances in artificial intelligence (AI), particularly with large language models such as ChatGPT, present new opportunities for virtual SPs, potentially addressing these limitations. objectives: This study aims to assess medical students' perceptions and experiences of using ChatGPT as an SP and to evaluate ChatGPT's effectiveness in performing as a virtual SP in a medical school setting. Methods: This qualitative study, approved by the American University of Antigua Institutional Review Board, involved 9 students (5 females and 4 males, aged 22-48 years) from the American University of Antigua College of Medicine. Students were observed during a live role-play, interacting with ChatGPT as an SP using a predetermined prompt. A structured 15-question survey was administered before and after the interaction. Thematic analysis was conducted on the transcribed and coded responses, with inductive category formation. Results: Thematic analysis identified key themes preinteraction including technology limitations (eg, prompt engineering difficulties), learning efficacy (eg, potential for personalized learning and reduced interview stress), verisimilitude (eg, absence of visual cues), and trust (eg, concerns about AI accuracy). Postinteraction, students noted improvements in prompt engineering, some alignment issues (eg, limited responses on sensitive topics), maintained learning efficacy (eg, convenience and repetition), and continued verisimilitude challenges (eg, lack of empathy and nonverbal cues). No significant trust issues were reported postinteraction. Despite some limitations, students found ChatGPT as a valuable supplement to traditional SPs, enhancing practice flexibility and diagnostic skills. Conclusions: ChatGPT can effectively augment traditional SPs in medical education, offering accessible, flexible practice opportunities. However, it cannot fully replace human SPs due to limitations in verisimilitude and prompt engineering challenges. Integrating prompt engineering into medical curricula and continuous advancements in AI are recommended to enhance the use of virtual SPs.
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