Dharshini Suresh1, Michael Choti2, Alexander Eastman2, Ann Majewicz Fey1. 1University of Texas at Dallas, 2UT Southwestern Medical Center
INTRODUCTION: The purpose of this study is to examine the effects of different stressor conditions on performance in laparoscopic surgical training tasks under stress. The stressor conditions evaluated included: (1) environmental stressors (i.e., flickering video and sounds), (2) positive evaluative stressors (i.e., encouraging feedback), (3) negative evaluative stressors (i.e., negative feedback), and (4) clinical stressors (i.e., vitals of patient coding).
METHODS AND PROCEDURES: We developed a stress simulator testbed by integrating an FLS box trainer with a Linux computer, running custom C++ code. The code generated various stressor conditions, while recording sensor data from the trainer and human operator. We tested 3 groups of participants in an IRB approved trial including: novices (non-medical students), intermediates (medical students), and experts (PGY4 residents and fellows). The study consisted of subjects performing the peg transfer and the pattern cut six times (baseline, four randomized stressors, post-test). After each task, the NASA-TLX survey was administered to determine the overall workload of that stressor condition. An analysis of variance was conducted to identify significant trends in terms of stressor type.
RESULTS: When compared to baseline NASA-TLX scores, the intermediate group had the greatest changes in overall workload than novices and experts (p=0.0005). Additionally, the change between baseline and post-test workload was significantly lower than for the environmental, negative evaluative, and clinical stressors (p=0.0006). For pattern cutting, subjects reported a significantly lower perception of failure (p=0.0479) in both the positive evaluative (mean = 8.5556) and post-test conditions (mean = 8.222), yet, though not statistically significant (p = 0.0564), the measured accuracy in the task during the positive evaluative condition was actually worse (33.3%), second only to the pre-test accuracy (31.1%). The best accuracy for pattern cutting across all expertise levels was 62% for the post-test followed by 54.4% in the negative evaluative condition. These results are interesting as they show that despite perceived improvements in performance with a positive feedback condition, performance actually degrades and is better in the negative feedback condition, which is perceived to be more difficult. These results were not found in the peg transfer task, which is arguably an easier task.
CONCLUSION: From the evidence gathered in the study, it is clear that there is a correlation between distractors and performance. Further analysis is needed to identify the relationship between the type of stressor, and inherent difficulty of the tasks, in terms of which type of stressor best improves learning and outcomes.
Presented at the SAGES 2017 Annual Meeting in Houston, TX.
Abstract ID: 88576
Program Number: P349
Presentation Session: iPoster Session (Non CME)
Presentation Type: Poster
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