Examining the Feasibility and Predictive Validity of the SAGAT Tool to Assess Situation Awareness Among Medical Trainees

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12 Scopus citations

Abstract

INTRODUCTION: Situational awareness (SA) describes a teamʼs ability to perceive environmental elements, comprehend their meaning, and anticipate future events. Although SA is consistently described as a critical competency among surgical teams, there is a dearth of research identifying efficacious methods to assess and develop SA in such settings. The aim of this study was to investigate the feasibility of implementing an objective tool that has been used to measure SA in other intense and dynamic environments —the Situation Awareness Global Assessment Technique (SAGAT)—and to examine its ability to predict surgical trainee team performance. METHODS: Ten team-training sessions were conducted involving 2 standardized high-fidelity trauma simulation scenarios. Teams consisted of 4 or 5 participants, and roles were randomly assigned. Team situational awareness was assessed using the SAGAT method, which involves intermittent freezes to probe trainee awareness of the situation. Team performance was assessed using the Mayo High-Performance Teamwork Scale. Hierarchical regression was used to examine SA-performance relationships for each scenario. RESULTS: Forty-three third-year medical students participated in the training sessions. Team SA ranged from 45% to 79% and 46% to 97% for the first and second scenarios, respectively. Additionally, team SA significantly predicted team performance for both the first scenario (F(1, 42)=19.57; P<0.001; R=0.30) and second scenario (F(1,42)=26.18, P<0.001; R=0.38). CONCLUSIONS: The SAGAT is a valid, reliable tool for assessing surgical trainee SA. Information provided by the SAGAT can help diagnose team performance problems, inform debriefing discussion points, and inform curriculum development endeavors.

Original languageEnglish (US)
JournalSimulation in Healthcare
DOIs
StateAccepted/In press - Aug 8 2016

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Epidemiology
  • Education
  • Modeling and Simulation

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