Access to a Simulator is Not Enough: The Benefits of Virtual Reality Training Based on Peer-Group-Derived Benchmarks—A Randomized Controlled Trial

von Websky, Martin ; Raptis, Dimitri ; Vitz, Martina ; Rosenthal, Rachel ; Clavien, P. ; Hahnloser, Dieter

In: World Journal of Surgery, 2013, vol. 37, no. 11, p. 2534-2541

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    Summary
    Background: Virtual reality (VR) simulators are widely used to familiarize surgical novices with laparoscopy, but VR training methods differ in efficacy. In the present trial, self-controlled basic VR training (SC-training) was tested against training based on peer-group-derived benchmarks (PGD-training). Methods: First, novice laparoscopic residents were randomized into a SC group (n=34), and a group using PGD-benchmarks (n=34) for basic laparoscopic training. After completing basic training, both groups performed 60 VR laparoscopic cholecystectomies for performance analysis. Primary endpoints were simulator metrics; secondary endpoints were program adherence, trainee motivation, and training efficacy. Results: Altogether, 66 residents completed basic training, and 3,837 of 3,960 (96.8%) cholecystectomies were available for analysis. Course adherence was good, with only two dropouts, both in the SC-group. The PGD-group spent more time and repetitions in basic training until the benchmarks were reached and subsequently showed better performance in the readout cholecystectomies: Median time (gallbladder extraction) showed significant differences of 520s (IQR 354-738s) in SC-training versus 390s (IQR 278-536s) in the PGD-group (p<0.001) and 215s (IQR 175-276s) in experts, respectively. Path length of the right instrument also showed significant differences, again with the PGD-training group being more efficient. Conclusions: Basic VR laparoscopic training based on PGD benchmarks with external assessment is superior to SC training, resulting in higher trainee motivation and better performance in simulated laparoscopic cholecystectomies. We recommend such a basic course based on PGD benchmarks before advancing to more elaborate VR training