Impact of Student Pharmacist State Anxiety on Vasopressor Calculation Accuracy in Advanced Cardiac Life Support Simulations

Abstract

Objective: To assess the impact of student pharmacist state anxiety on vasopressor calculation accuracy in advanced cardiac life support (ACLS) simulations.

Methods: Third-year professional students participated in 2 ACLS-related simulation laboratory sessions. In week 1, students completed 3 calculations at their workstation with no stressors. Students were then randomized into teams for a bedside simulation where they independently completed 3 additional calculations either with or without stressors. Team assignments were maintained for week 2 where all participants completed a high-fidelity ACLS simulation that included a team vasopressor calculation. At both encounters, calculation accuracy was assessed as well as pre- and post-state anxiety using the Spielberger State-Trait Anxiety Inventory (STAI) survey tool.

Results: Students' (N = 145) trait anxiety aligned with normative data for similarly aged professional students. Post-simulation state anxiety in week 1 was found to be higher for those completing the activity with stressors than without (STAI score 44.7 vs 36.9) paired with lower bedside calculation accuracy, despite similar initial workstation calculation accuracy. In week 2, pre-simulation state anxiety score and calculation accuracy were not significantly different between the 2 groups. However, the state anxiety score significantly increased post-simulation for those exposed to stress in the previous week.

Conclusion: Stress negatively impacted student pharmacist vasopressor calculation accuracy. However, the repeated exposure to a stressed simulation did not result in a significant difference in pre- or post-simulation state anxiety score or calculation accuracy when compared to a non-stressed control. Consideration should be made whether to include more "real-life" simulations in student pharmacist education.

Keywords: ACLS; Simulation; State-trait anxiety inventory.