Development of a GPT-4-Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: Multiphase Study.

Journal: JMIR formative research
PMID: 40246299

Abstract

BACKGROUND: Standardized patients (SPs) prepare medical students for difficult conversations with patients. Despite their value, SP-based simulation training is constrained by available resources and competing clinical demands. Researchers are turning to artificial intelligence and large language models, such as generative pretrained transformers, to create communication training that incorporates virtual simulated patients (VSPs). GPT-4 is a large language model advance allowing developers to design virtual simulation scenarios using text-based prompts instead of relying on branching path simulations with prescripted dialogue. These nascent developmental practices have not taken root in the literature to guide other researchers in developing their own simulations.

Authors

  • Dan Weisman
    UCLA Simulation Center, University of California, Los Angeles, Los Angeles, CA, United States.
  • Alanna Sugarman
    David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
  • Yue Ming Huang
    UCLA Simulation Center, University of California, Los Angeles, Los Angeles, CA, United States.
  • Lillian Gelberg
    Department of Family Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
  • Patricia A Ganz
    David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
  • Warren Scott Comulada
    Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.

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