Acquisition of flexible cystoscopy skills on a virtual reality simulator by experts and novices.
OBJECTIVE
To assess the construct validity of the URO Mentor (Simbionix Corp., Cleveland, OH, USA) virtual reality training model for several variables of skills training in cysto-urethroscopy, addressing two research questions: (i) Does training on the URO Mentor significantly improve novices' performance in terms of time, trauma, areas inspected and Global Rating Scale (GRS) score?; (ii) is discrimination between different levels of expertise possible using the URO Mentor?


METHODS
Thirty experts and 50 novices performed seven tasks on the URO Mentor during one training session. The first, fourth and seventh tasks were 'test tasks' to evaluate participants' performance. The simulator recorded procedure time and trauma; a supervisor scored which areas were inspected and gave scores on the GRS. A two-way analysis of variance with repeated-measures test was used to analyse experts' and novices' performances, with P < 0.05 considered to indicate statistical significance. Effect sizes (ES) were calculated to quantify the practical significance of the results; ES of 0.10, 0.30, and 0.50 were considered small, medium and large, respectively.


RESULTS
Novices' performances showed a significant improvement with large ES in time (linear trend of learning curve P < 0.001, ES 0.66) and mean GRS score (linear trend P < 0.001, ES 0.84, quadratic trend P = 0.018, ES 0.24). There was a medium improvement for trauma (linear trend P < 0.001, ES 0.40) and a small improvement in areas inspected (linear trend P = 0.032, ES 0.21). That the 95% confidence intervals of the measures on the first task of experts and novices did not coincide indicates that differentiation between experts and novices on the four variables measured can be achieved using the URO Mentor.


CONCLUSIONS
Training on the URO Mentor appears to result in a medium to large improvement of novices' performances for time, trauma, areas inspected and GRS scores. Moreover, discrimination between different levels of expertise is possible using this simulator.
Schout
Barbara M A
BM
VU University Medical Centre, Amsterdam, the Netherlands. barbara.schout@cze.nl
Muijtjens
Arno M M
AM
Hendrikx
Ad J M
AJ
Ananias
Hildo J K
HJ
Dolmans
Valérie E M G
VE
Scherpbier
Albert J J A
AJ
Bemelmans
Bart L H
BL
D002983:Clinical Competence / Q000592:standards*; D003198:Computer Simulation; D003194:Computer-Assisted Instruction / Q000379:methods* / Q000592:standards; D003558:Cystoscopy / Q000379:methods* / Q000592:standards; D004502:Education, Medical, Continuing / Q000379:methods*; D004521:Educational Measurement; D006801:Humans; D008505:Medical Staff, Hospital / Q000193:education*; D010865:Pilot Projects