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. 2025 Dec;57(1):2470976.
doi: 10.1080/07853890.2025.2470976. Epub 2025 Mar 3.

Elucidating cognitive processes in cardiac arrest team leaders: a virtual reality-based cued-recall study of experts and novices

Vitaliy Popov  1   2 , Bryan Harmer  1 , Sophie Raphael  1 , Isabella Scott  1 , Alanson P Sample  3 , James M Cooke  1   4 , Michael Cole  5
Affiliations

Elucidating cognitive processes in cardiac arrest team leaders: a virtual reality-based cued-recall study of experts and novices

Vitaliy Popov et al. Ann Med. 2025 Dec.

Abstract

Background: Team leadership during medical emergencies like cardiac arrest resuscitation is cognitively demanding, especially for trainees. These cognitive processes remain poorly characterized due to measurement challenges. Using virtual reality simulation, this study aimed to elucidate and compare communication and cognitive processes-such as decision-making, cognitive load, perceived pitfalls, and strategies-between expert and novice code team leaders to inform strategies for accelerating proficiency development.

Methods: A simulation-based mixed methods approach was utilized within a single large academic medical center, involving twelve standardized virtual reality cardiac arrest simulations. These 10- to 15-minutes simulation sessions were performed by seven experts and five novices. Following the simulations, a cognitive task analysis was conducted using a cued-recall protocol to identify the challenges, decision-making processes, and cognitive load experienced across the seven stages of each simulation.

Results: The analysis revealed 250 unique cognitive processes. In terms of reasoning patterns, experts used inductive reasoning, while novices tended to use deductive reasoning, considering treatments before assessments. Experts also demonstrated earlier consideration of potential reversible causes of cardiac arrest. Regarding team communication, experts reported more critical communications, with no shared subthemes between groups. Experts identified more teamwork pitfalls, and suggested more strategies compared to novices. For cognitive load, experts reported lower median cognitive load (53) compared to novices (80) across all stages, with the exception of the initial presentation phase.

Conclusions: The identified patterns of expert performance - superior teamwork skills, inductive clinical reasoning, and distributed cognitive strategiesn - can inform training programs aimed at accelerating expertise development.

Keywords: Cognitive load; clinical simulation; emergency medicine; medical education; virtual reality.

Plain language summary

Novel combination of virtual reality simulation and cognitive task analysis provides a promising educational tool for identifying and addressing gaps in resuscitation team leadership skills, offering a valuable approach to competency-based medical education in critical care scenarios.The consistently high cognitive load reported by team leaders, regardless of experience level, suggests a need for guidance on strategies to better distribute cognitive demands among team members during cardiac arrest resuscitations.Experts demonstrate more advanced teamwork skills, inductive reasoning, and distributed cognition during cardiac arrest management, highlighting areas for focused skill development in novice leaders.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
Methodological steps and procedures used in this study.
Figure 2.
Figure 2.
A screenshot of the virtual reality cardiac arrest simulation environment used in this study.
Figure 3.
Figure 3.
Heatmap of self-reported cognitive load median values according to the experts per stage.
Figure 4.
Figure 4.
Heatmap of self-reported cognitive load median values according to the novices per stage.
Figure 5.
Figure 5.
Line graph comparison of total team reported median cognitive load across all stages.
See this image and copyright information in PMC

References

    1. Qazi AH, Chan PS, Zhou Y, et al. . Trajectory of risk-standardized survival rates for in-hospital cardiac arrest. Circ Cardiovasc Qual Outcomes. 2020;13(9):e006514. doi: 10.1161/CIRCOUTCOMES.120.006514. - DOI - PMC - PubMed
    1. Nallamothu BK, Guetterman TC, Harrod M, et al. . How do resuscitation teams at top-performing hospitals for in-hospital cardiac arrest succeed? Circulation. 2018;138(2):154–163. doi: 10.1161/CIRCULATIONAHA.118.033674. - DOI - PMC - PubMed
    1. Andersen LW, Holmberg MJ, Berg KM, et al. . In-hospital cardiac arrest. JAMA. 2019;321(12):1200–1210. doi: 10.1001/jama.2019.1696. - DOI - PMC - PubMed
    1. Anderson TM, Secrest K, Krein SL, et al. . Best practices for education and training of resuscitation teams for in-hospital cardiac arrest. Circ Cardiovasc Qual Outcomes. 2021;14(12):e008587. doi: 10.1161/CIRCOUTCOMES.121.008587. - DOI - PMC - PubMed
    1. Jayaram N, Spertus JA, Nadkarni V, et al. . Hospital variation in survival after pediatric in-hospital cardiac arrest. Circ Cardiovasc Qual Outcomes. 2014;7(4):517–523. doi: 10.1161/CIRCOUTCOMES.113.000691. - DOI - PMC - PubMed