Abstract
BackgroundObservational learning plays an important role in surgical skills training, following the traditional model of learning from expertise. Recent findings have, however, highlighted the benefit of observing not only expert performance but also error-strewn performance. The aim of this study was to determine which model (novice vs. expert) would lead to the greatest benefits when learning robotically assisted surgical skills.Methods120 medical students with no prior experience of robotically-assisted surgery completed a ring-carrying training task on three occasions; baseline, post-intervention and at one-week follow-up. The observation intervention consisted of a video model performing the ring-carrying task, with participants randomly assigned to view an expert model, a novice model, a mixed expert/novice model or no observation (control group). Participants were assessed for task performance and surgical instrument control.ResultsThere were significant group differences post-intervention, with expert and novice observation groups outperforming the control group, but there were no clear group differences at a retention test one week later. There was no difference in performance between the expert-observing and error-observing groups.ConclusionsSimilar benefits were found when observing the traditional expert model or the error-strewn model, suggesting that viewing poor performance may be as beneficial as viewing expertise in the early acquisition of robotic surgical skills. Further work is required to understand, then inform, the optimal curriculum design when utilising observational learning in surgical training.
Highlights
Despite the shifting emphasis within surgical education towards competency-based training, current curricula still depend upon didactic learning, doing under guidance, and repetition [1], with observational learning—the process of passively watching another individual perform a task—maintaining a core role in developing surgical expertise [2]
Similar benefits were found when observing the traditional expert model or the error-strewn model, suggesting that viewing poor performance may be as beneficial as viewing expertise in the early acquisition of robotic surgical skills
Given the role of observational learning in effective and economical surgical training [2], this study aimed to determine the style of visual information leading to the most effective early acquisition of surgical skills on a robotic system
Summary
Despite the shifting emphasis within surgical education towards competency-based training, current curricula still depend upon didactic learning, doing under guidance, and repetition [1], with observational learning—the process of passively watching another individual perform a task—maintaining a core role in developing surgical expertise [2]. While observation is unlikely to lead to optimal learning on its own [3], it is effective as a supplement to physical practice [11]. This benefit is often attributed to the observer developing a model of the coordination patterns required, or a ‘perceptual blueprint’ [12,13], that serves as a standard of reference. The aim of this study was to determine which model (novice vs expert) would lead to the greatest benefits when learning robotically assisted surgical skills
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