Objective measurement of clinicians’ cognitive load during high fidelity trauma simulations
Sandra Park1,2, Abdulrahman Alballa1, Scott Goldberg2, Baraa Tayeb6, Mohammed Bassurah1, Egide Abahuje7, Charles Pozner1,2, Steven Yule3,4,5, Roger Dias1,2
1STRATUS Center for Medical Simulation, Brigham and Women's Hospital, Boston, MA 2Department of Emergency Medicine, Harvard Medical School, Boston, MA 3Department of Clinical Surgery, University of Edinburgh, Scotland 4Department of Surgery, Harvard Medical School, Boston, MA 5Center for Surgery and Public Health, Brigham and Women's Hospital, Boston, MA 6Department of Anesthesia and Critical Care, King Abdulaziz University, Jeddah, Saudi Arabia 7Feinburg School of Medicine, Chicago, IL
Background: Previous literature has shown that cognitive overload can negatively impact both learning and clinical performance in surgery. We investigated learners’ cognitive load during trauma team training (TTT) using an objective digital biomarker. Methods: A 3-hour simulation-based interprofessional TTT program was conducted. Each session included 3 scenarios each followed by a debriefing session. One scenario involved multiple patients. Each learner wore a heart rate sensor that detects continuous interbeat intervals. Low frequency/high frequency ratio (LF/HF ratio) was used as a validated proxy for cognitive load. A mixed model analysis was used.
Results: Ten subjects (2 nurses, 2 surgery and 6 EM residents) participated in 12 simulations. Seven participants were female (70%); mean age: 31.4 + 5.2 years. There was a statistically significant difference in LF/HF ratio between scenario and debriefing: 1.91; 95% CI = [1.28 – 2.53]; p < 0.001. Compared to single-patient scenarios, multiple-patient scenarios posed a higher cognitive load to learners: mean difference = 1.34; 95% CI = [0.35 – 2.32]; p = 0.008 (Fig.1).
Conclusion: We used an objective digital biomarker to measure cognitive load during TTT. Cognitive load during simulation activities were higher than the average normal. Cognitive load was increased during all three scenarios compared to debriefings, and the highest in a multiple-patient scenario, suggesting that HRV is a sensitive tool to detect cognitive load in varying simulation phases and scenario difficulty.
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