Artificially Intelligent Simulated Patients in Undergraduate Surgical Teaching: A Single Blinded Randomized Controlled Study
Open Access
- 30 July 2026
- journal article
- research article
- Published by Wiley in The Clinical Teacher
- Vol. 23 (5) , e70486
Abstract
Introduction: Self‐directed learning (SDL) and reflection are critically important for clinicians. There is limited evidence describing the utilization of artificial intelligence (AI) to support medical SDL. AI simulated patients (AISP) may allow for high‐fidelity, reflective educational interactions. We aimed to determine how SDL with AISP interaction compared to standard SDL in the development of clinical reasoning skills. Methods: This was a single‐institution randomized controlled study in early clinical years' undergraduate students, learning about gallstone disease. For 90% power and a 20% noninferiority margin, 36 participants were randomized either to an intervention group using an AISP or to a control group using current educational resources. Both groups underwent a standardized clinical skills assessment. Quantitative and qualitative data were collected. Results: Twenty‐seven participants completed the study. The intervention group demonstrated statistical noninferiority compared with the control group (assessment scores of 13.1 vs. 12.1, respectively, p = 0.11). In addition, there were fewer borderline grades, and significantly more distinction grades in the intervention group than control (6 vs. 1, respectively, p = 0.037), suggesting the AISP may have improved performance in clinical management. The qualitative data suggested widespread satisfaction and enthusiasm for AISPs. Conclusion: Our results suggest that AISPs are comparable to traditional resources in developing undergraduate clinical skills, and may contribute to improved academic performance in undergraduate surgery. Globally, there is an appetite for their introduction into the clinical curriculum. Real patient interaction is the standard. However, AISPs may have a supplementary role and are likely to become increasingly prominent in medical curricula.Keywords
This publication has 13 references indexed in Scilit:
- Generative Artificial Intelligence–Driven Clinical Case Simulation in Temporomandibular Disorder Education: ChatGPT Versus Real PatientsJournal of Dental Education, 2025
- AI Teaches Surgical Diagnostic Reasoning to Medical Students: Evidence from an Experiment Using a Fully Automated, Low-Cost Feedback SystemJournal of Surgical Education, 2025
- Effects of Elaboration and Instructor Feedback on Retention of Clinical Reasoning Competence Among Undergraduate Medical StudentsJAMA Network Open, 2022
- Artificial Intelligence in Undergraduate Medical Education: A Scoping ReviewAcademic Medicine, 2021
- Challenges and opportunities for undergraduate clinical teaching during and beyond the COVID-19 pandemicJournal of the Royal Society of Medicine, 2021
- Artificial intelligence and the adoption of new technology in medical educationMedical Education, 2020
- Effective virtual patient simulators for medical communication training: A systematic reviewMedical Education, 2020
- The REDCap consortium: Building an international community of software platform partnersJournal of Biomedical Informatics, 2019
- CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trialsBMJ, 2010
- A Qualitative Analysis of the Transition from Theory to Practice in Undergraduate Training in a PBL-Medical SchoolAdvances in Health Sciences Education, 2000