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John Rhodes Martin1, Nicholas Anton2, Lava Timsina1

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Reducing performance variability during surgical simulator training leads to better skills. Lower variability in laparoscopic suturing practice correlates with improved post-training scores and better skill transfer to live models.

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Area of Science:

  • Medical Education
  • Surgical Simulation
  • Skill Acquisition

Background:

  • Expert performance is defined by consistency.
  • Performance variability during simulator training may indicate expertise acquisition.
  • Hypothesis: Lower performance variability predicts better training outcomes and skill transfer.

Purpose of the Study:

  • To investigate the association between performance variability during simulator training and surgical skill acquisition.
  • To determine if reduced variability predicts improved post-training performance and skill transfer.

Main Methods:

  • Analyzed performance variability in 93 subjects (residents, medical students) during laparoscopic suturing training on the Fundamentals of Laparoscopic Surgery (FLS) simulator.
  • Assessed performance at baseline, post-training (simulator), and on a live porcine model (transfer test).
  • Used linear regression to correlate performance variability with posttest and transfer-test scores.

Main Results:

  • Decreased practice variability was significantly associated with higher posttest and transfer-test scores (P < .001 for both).
  • Each 1% decrease in variability correlated with a 3.8-point increase in posttest scores and a 3.0-point increase in transfer-test scores.
  • Higher mean practice scores also correlated with better transfer-test performance (P < .001).

Conclusions:

  • Reduced performance variability during simulator practice is linked to enhanced end-of-training performance and skill transfer.
  • Simulator performance variability may serve as a metric to track trainee progress and readiness for clinical settings.
  • Further research is needed to validate this potential new performance metric.