Abstract

Background: Emotions significantly influence decision-making and performance in critical care settings. In situ simulation (ISS) has emerged as an educational tool that replicates real scenarios in clinical environments, potentially evoking authentic emotional responses. This scoping review examined how emotions have been studied in critical care ISS and their impact on learning and performance. Methods: Following PRISMA-ScR guidelines, we conducted a comprehensive search across SCOPUS, PubMed, Web of Science, and CINAHL databases for articles published between January 2014 and June 2024. Studies examining emotional responses during ISS among healthcare professionals in critical care settings were included. Data were extracted using a standardized form and analyzed through narrative synthesis. Results: Nine studies met the inclusion criteria. Analysis revealed that ISS evokes both positive and negative emotions comparable to real clinical scenarios, demonstrating psychological fidelity measured through standardized scales and physiological variables. While negative emotions like stress and anxiety were most extensively studied, positive emotions showed a significant correlation with enhanced performance. The concept of affective bonding emerged as a key component for knowledge retention and skill transfer. Conclusions: ISS can recreate both technical and certain emotional aspects of clinical environments, particularly stress responses. The dual presence of positive and negative emotions contributes to learning effectiveness, with positive emotions enhancing performance and negative emotions building resilience when properly managed. The reported equivalence between emotional responses in simulated and real clinical scenarios validates ISS as an effective preparatory tool for critical care practice through the mechanism of affective bonding. C 2025 Societe Franc & cedil;aise d'Anesthesie et de Reanimation (SFAR). Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.