AI and inclusion in simulation education and leadership: a global cross-sectional evaluation of diversity.

Journal: Advances in simulation (London, England)
Published Date: May 4, 2025

Abstract

BACKGROUND: Simulation-based medical education (SBME) is a critical training tool in healthcare, shaping learners' skills, professional identities, and inclusivity. Leadership demographics in SBME, including age, gender, race/ethnicity, and medical specialties, influence program design and learner outcomes. Artificial intelligence (AI) platforms increasingly generate demographic data, but their biases may perpetuate inequities in representation. This study evaluated the demographic profiles of simulation instructors and heads of simulation labs generated by three AI platforms-ChatGPT, Gemini, and Claude-across nine global locations.

Authors

  • Joana Berger-Estilita
    Institute for Medical Education, University of Bern, Bern, Switzerland.
  • Mia Gisselbaek
    Division of Anesthesiology, Department of Anesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland. Mia.gisselbaek@gmail.com.
  • Arnout Devos
    ETH AI Center, Swiss Federal Institute of Technology Zurich (ETH Zurich), Zurich, Switzerland.
  • Albert Chan
    Department of Anaesthesia, Pain and Perioperative Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, Hong Kong.
  • Pier Luigi Ingrassia
    Centro di Simulazione (CeSi), Centro Professionale Sociosanitario Medico-Tecnico, Lugano, Switzerland.
  • Basak Ceyda Meco
    Department of Anesthesia and Intensive Care, , Ankara University Faculty of Medicine, Ankara, Turkey.
  • Odmara L Barreto Chang
    Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, CA, USA.
  • Georges L Savoldelli
    Division of Anesthesiology, Department of Anesthesiology, Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
  • Francisco Maio Matos
    Anesthesiology Department, Hospitais da Universidade de Coimbra, Coimbra, Portugal.
  • Peter Dieckmann
    Copenhagen Academy for Medical Education and Simulation (CAMES), Herlev, Copenhagen, Capital Region of Denmark, Denmark.
  • Doris Østergaard
    Copenhagen Academy for Medical Education and Simulation (CAMES), Herlev, Copenhagen, Capital Region of Denmark, Denmark.
  • Sarah Saxena
    Department of Anesthesiology, Helora, Mons, Belgium.

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