Generation Z versus generative artificial intelligence: a cross-sectional study assessing medical students' confidence and over-reliance on artificial intelligence in perioperative clinical scenarios.
Saxena, Sarah; Tsobgnie, Marc Nkana; Südy, Robertaet al.
Saxena, Sarah ; From the Department of Surgery, UMons, Research Institute for Health Sciences and Technology, University of Mons, Mons, Belgium (SS, MNT, JRL), Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland (RS, MG), Department of Anesthesia and Intensive Care Medicine, Liege University Hospital, Liege, Belgium (MC), Centro di Simulazione (CeSi), Centro Professionale Sociosanitario Medico-Tecnico, Lugano, Switzerland (PLI), Copenhagen Academy for Medical Education and Simulation (CAMES), Capital Region of Denmark, Herlev, Denmark (PD) and Institute for Medical Education, University of Bern, Bern, Switzerland (JB-E
Tsobgnie, Marc Nkana
Südy, Roberta
Gisselbaek, Mia
Lechien, Jerome R
CARELLA, Michele ; Centre Hospitalier Universitaire de Liège - CHU > > Service d'anesthésie - réanimation
Ingrassia, Pierre Luigi
Dieckmann, Peter
Berger-Estilita, Joana
Language :
English
Title :
Generation Z versus generative artificial intelligence: a cross-sectional study assessing medical students' confidence and over-reliance on artificial intelligence in perioperative clinical scenarios.
Publication date :
18 September 2025
Journal title :
European Journal of Anaesthesiology
ISSN :
0265-0215
eISSN :
1365-2346
Publisher :
Ovid Technologies (Wolters Kluwer Health), England
