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

Abstract

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. 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. 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. 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.