BACKGROUND: The use of simulation for minimally invasive surgery (MIS) skills training has many advantages over current traditional methods. One advantage of simulation is that it enables an objective assessment of technical performance. The purpose of this study was to determine whether the ProMIS augmented reality simulator could objectively distinguish between levels of performance skills on a complex laparoscopic suturing task. METHODS: Ten subjects--five laparoscopic experts and five laparoscopic novices--were assessed for baseline perceptual, visio-spatial, and psychomotor abilities using validated tests. After three trials of a novel laparoscopic suturing task were performed on the simulator, measures for time, smoothness of movement, and path distance were analyzed for each trial. Accuracy and errors were evaluated separately by two blinded reviewers to an interrater reliability of >0.8. Comparisons of mean performance measures were made between the two groups using a Mann-Whitney U test. Internal consistency of ProMIS measures was assessed with coefficient alpha. RESULTS: The psychomotor performance of the experts was superior at baseline assessment (p < 0.001). On the laparoscopic suturing task, the experts performed significantly better than the novices across all three trials (p < 0.001). They performed the tasks between three and four times faster (p < 0.0001), had three times shorter instrument path length (p < 0.0001), and had four times greater smoothness of instrument movement (p < 0.009). Experts also showed greater consistency in their performance, as demonstrated by SDs across all measures, which were four times smaller than the novice group. Observed internal consistency of ProMIS measures was high (alpha = 0.95, p < 0.00001). CONCLUSIONS: Preliminary results of construct validation efforts of the ProMIS simulator show that it can distinguish between experts and novices and has promising psychometric properties. The attractive feature of ProMIS is that a wide variety of MIS tasks can be used to train and assess technical skills.
BACKGROUND: The use of simulation for minimally invasive surgery (MIS) skills training has many advantages over current traditional methods. One advantage of simulation is that it enables an objective assessment of technical performance. The purpose of this study was to determine whether the ProMIS augmented reality simulator could objectively distinguish between levels of performance skills on a complex laparoscopic suturing task. METHODS: Ten subjects--five laparoscopic experts and five laparoscopic novices--were assessed for baseline perceptual, visio-spatial, and psychomotor abilities using validated tests. After three trials of a novel laparoscopic suturing task were performed on the simulator, measures for time, smoothness of movement, and path distance were analyzed for each trial. Accuracy and errors were evaluated separately by two blinded reviewers to an interrater reliability of >0.8. Comparisons of mean performance measures were made between the two groups using a Mann-Whitney U test. Internal consistency of ProMIS measures was assessed with coefficient alpha. RESULTS: The psychomotor performance of the experts was superior at baseline assessment (p < 0.001). On the laparoscopic suturing task, the experts performed significantly better than the novices across all three trials (p < 0.001). They performed the tasks between three and four times faster (p < 0.0001), had three times shorter instrument path length (p < 0.0001), and had four times greater smoothness of instrument movement (p < 0.009). Experts also showed greater consistency in their performance, as demonstrated by SDs across all measures, which were four times smaller than the novice group. Observed internal consistency of ProMIS measures was high (alpha = 0.95, p < 0.00001). CONCLUSIONS: Preliminary results of construct validation efforts of the ProMIS simulator show that it can distinguish between experts and novices and has promising psychometric properties. The attractive feature of ProMIS is that a wide variety of MIS tasks can be used to train and assess technical skills.
Authors: Shanu N Kothari; Brian J Kaplan; Eric J DeMaria; Timothy J Broderick; Ronald C Merrell Journal: J Laparoendosc Adv Surg Tech A Date: 2002-06 Impact factor: 1.878
Authors: Neal E Seymour; Anthony G Gallagher; Sanziana A Roman; Michael K O'Brien; Vipin K Bansal; Dana K Andersen; Richard M Satava Journal: Ann Surg Date: 2002-10 Impact factor: 12.969
Authors: Vimal K Narula; William C Watson; S Scott Davis; Kristen Hinshaw; Bradley J Needleman; Dean J Mikami; Jeffrey W Hazey; John H Winston; P Muscarella; Mike Rubin; Vipul Patel; W Scott Melvin Journal: Surg Endosc Date: 2007-05-24 Impact factor: 4.584