V Datta1, M Mandalia, S Mackay, A Darzi. 1. Department of Surgical Oncology and Technology, Imperial College School of Medicine at St. Mary's, London, United Kingdom. v.datta@ic.ac.uk
Abstract
AIM: To demonstrate face and construct validity of a computer based flexible sigmoidoscopy trainer. METHODS: The PreOp (Immersion Medical, USA) system is a virtual reality based flexible sigmoidoscopy simulator. The system records several performance parameters, such as percentage of colonic mucosa visualized, time taken, and pathlength of endoscope travel. Forty-five subjects were divided into three groups: novice (never performed a lower GI endoscopy), intermediate (5-50 examinations), and trained (greater than 200 examinations). After initial familiarization subjects were assessed three times on a case module. Results showed a nonparametric distribution. RESULTS: There was a significant difference between all three groups with respect to percentage of mucosa visualized (novice 71.0 +/- 3.7%, intermediate 77.3 +/- 5.6%, expert 84.8 +/- 4.6%, Kruskal-Wallis p <0.001) and efficiency ratio (%mucosa/time, novice 0.163 +/- 0.055, intermediate 0.259 +/- 0.07, expert 0.306 +/- 0.058, p <0.001). The novice group was also slower and had a lower pathlength of instrument travel compared to the others. CONCLUSION: PreOp virtual reality simulator is a valid discriminator of flexible sigmoidoscopic experience. Its effect on training needs to be explored.
AIM: To demonstrate face and construct validity of a computer based flexible sigmoidoscopy trainer. METHODS: The PreOp (Immersion Medical, USA) system is a virtual reality based flexible sigmoidoscopy simulator. The system records several performance parameters, such as percentage of colonic mucosa visualized, time taken, and pathlength of endoscope travel. Forty-five subjects were divided into three groups: novice (never performed a lower GI endoscopy), intermediate (5-50 examinations), and trained (greater than 200 examinations). After initial familiarization subjects were assessed three times on a case module. Results showed a nonparametric distribution. RESULTS: There was a significant difference between all three groups with respect to percentage of mucosa visualized (novice 71.0 +/- 3.7%, intermediate 77.3 +/- 5.6%, expert 84.8 +/- 4.6%, Kruskal-Wallis p <0.001) and efficiency ratio (%mucosa/time, novice 0.163 +/- 0.055, intermediate 0.259 +/- 0.07, expert 0.306 +/- 0.058, p <0.001). The novice group was also slower and had a lower pathlength of instrument travel compared to the others. CONCLUSION: PreOp virtual reality simulator is a valid discriminator of flexible sigmoidoscopic experience. Its effect on training needs to be explored.
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