Redefining simulator proficiency using automaticity theory

BackgroundAutomaticity is a characteristic of expertise defined by the ability to perform a task without significant demands on attention. Our objective was to assess whether a visual–spatial task that measures spare attentional capacity would distinguish among individuals with different levels of laparoscopic expertise.MethodsThe performance of novices (n = 10), surgery residents (n = 9), laparoscopy experts (n = 3), and individuals previously trained (n = 7) to proficiency in laparoscopic suturing on simulators but without operative experience (trained individuals) was measured under dual-task conditions. Participants performed laparoscopic suturing for 10 minutes on a video trainer simulator using the Fundamentals of Laparoscopic Surgery suturing model (primary task) while at the same time they responded to a visual–spatial secondary task.ResultsExperts and trained individuals outperformed both residents and novices on the suturing task (P < .001). Although the performance of experts and trained individuals did not differ significantly based on suturing scores, experts achieved higher secondary-task scores (P < .05).ConclusionsA visual–spatial secondary task that assesses spare attentional capacity may help distinguish among individuals of variable laparoscopic expertise when standard performance measures fail to do so. Such automaticity metrics may improve current simulator training and assessment methods and warrants further investigation.