The effect of structured self-assessment in virtual reality simulation training of mastoidectomy.

Purpose: Virtual reality (VR) simulation surgical skills training is well established, but self-directed practice is often associated with a learning curve plateau. In this study, we investigate the effects of structured self-assessment as a means to improve performance in mastoidectomy training.

Methods: The study was a prospective, educational study. Two cohorts of novices (medical students) were recruited for practice of anatomical mastoidectomy in a training program with five distributed training blocks. Fifteen participants performed structured self-assessment after each procedure (intervention cohort). A reference cohort of another 14 participants served as controls. Performances were assessed by two blinded raters using a modified Welling Scale and simulator-recorded metrics.

Results: The self-assessment cohort performed superiorly to the reference cohort (mean difference of final product score 0.87 points, p = 0.001) and substantially reduced the number of repetitions needed. The self-assessment cohort also had more passing performances for the combined metrics-based score reflecting increased efficiency. Finally, the self-assessment cohort made fewer collisions compared with the reference cohort especially with the chorda tympani, the facial nerve, the incus, and the malleus.

Conclusions: VR simulation training of surgical skills benefits from having learners perform structured self-assessment following each procedure as this increases performance, accelerates the learning curve thereby reducing time needed for training, and induces a safer performance with fewer collisions with critical structures. Structured self-assessment was in itself not sufficient to counter the learning curve plateau and for continued skills development additional supports for deliberate practice are needed.