Journal Article

Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial

Fan, Ting-Ting, Zhu, Nin-Jun, Wang, Xiao-Chen, Li, Meng-Li, Wang, Zhen

2025

Overview

Backgrounds Traditional methods of teaching history-taking in medical education are limited by scalability and resource intensity. This study aims to assess the effectiveness of simulated patient interactions based on a custom-designed Generative Pre-trained Transformer (GPT) model, developed using OpenAI’s ChatGPT GPTs platform, in enhancing medical students’ history-taking skills compared to traditional role-playing methods. Methods A total of 56 medical students were randomly assigned into two groups: an GPT group using GPT-simulated patients and a control group using traditional role-playing. Pre- and post-training assessments were conducted using a structured clinical examination to measure students’ abilities in history collection, clinical reasoning, communication skills, and professional behavior. Additionally, students’ evaluations of the educational effectiveness, satisfaction, and recommendation likelihood were assessed. Results The GPT-simulation group showed significantly higher post-training scores in the structured clinical examination compared to the control group (86.79 ± 5.46,73.64 ± 4.76, respectively, P  < 0.001). Students in the GPT group exhibited higher enthusiasm for learning, greater self-directed learning motivation, and better communication feedback abilities compared to the control group ( P  < 0.05). Additionally, the student satisfaction survey revealed that the GPT group rated higher on the diversity of diseases encountered, ease of use, and likelihood of recommending the training compared to the control group ( P  < 0.05). Conclusions GPT-based history-taking training effectively enhances medical students’ history-taking skills, providing a solid foundation for the application of artificial intelligence (AI) in medical education. Clinical trial number NCT06766383.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adult / Artificial Intelligence / Artificial Speech / Automation / Chatbots / Clinical Competence / Clinical Skills / Clinical trials / Communication / Communication Skills / Competence / Computer Simulation / Computer Use / Control Groups / Education / Education, Medical - methods / Education, Medical, Undergraduate - methods / Educational Change / Educational Facilities Improvement / Educational Measurement / Educational Objectives / Educational Quality / Educational research / Educational Testing / Feasibility Studies / Feedback / Feedback (Response) / Female / Flow Charts / GPT Simulation / History education / History-taking Training / Humans / Independent study / Informed Consent / Internal Medicine / Interviews / Large language models / Learner Engagement / Learning / Logical Thinking / Male / Medical Education / Medical Evaluation / Medical history taking / Medical History Taking - methods / Medical students / Methods / Outcome Measures / Patient Simulation / Patients / Performance evaluation / Physician Patient Relationship / Realism / Role playing / Science Curriculum / Simulation / Skills / Students, Medical - psychology / Technology application / Theory of Medicine/Bioethics / Training / Young Adult