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Automated summative feedback improves performance and retention in simulation training of mastoidectomy: a randomised controlled trial

2021; Cambridge University Press; Volume: 136; Issue: 1 Linguagem: Inglês

10.1017/s0022215121003352

1748-5460

Andreas Frithioff, Martin Frendø, Josefine Hastrup von Buchwald, Peter Trier Mikkelsen, Mads Sølvsten Sørensen, Steven Arild Wuyts Andersen,

Anatomy and Medical Technology

Abstract Objective This study aimed to investigate the effects of automated metrics-based summative feedback on performance, retention and cognitive load in distributed virtual reality simulation training of mastoidectomy. Method Twenty-four medical students were randomised in two groups and performed 15 mastoidectomies on a distributed virtual reality simulator as practice. The intervention group received additional summative metrics-based feedback; the control group followed standard instructions. Two to three months after training, participants performed a retention test without learning supports. Results The intervention group had a better final-product score (mean difference = 1.0 points; p = 0.001) and metrics-based score (mean difference = 12.7; p < 0.001). At retention, the metrics-based score for the intervention group remained superior (mean difference = 6.9 per cent; p = 0.02). Also at the retention, cognitive load was higher in the intervention group (mean difference = 10.0 per cent; p < 0.001). Conclusion Summative metrics-based feedback improved performance and lead to a safer and faster performance compared with standard instructions and seems a valuable educational tool in the early acquisition of temporal bone skills.