Construct validity and assessment of the learning curve for the SIMENDO endoscopic simulator.
BACKGROUND
The SIMENDO is an affordable virtual reality simulator designed to train basic psychomotor skills for endoscopic surgery. This study aimed first to establish construct validity by determining which parameters can discriminate groups with different experience levels, and second to establish the extent to which training is useful by determining when inexperienced groups reach expert level.


METHODS
The study participants were divided into four groups according to their experience with endoscopic procedures: experienced group (group A, >50 procedures performed, n = 15), intermediate group (group B, 1-50 procedures performed, n = 18), endoscope navigation group (group C, endoscope navigation experience, n = 14), and novice group (group D, no endoscopic experience, n = 14). Each participant performed three repetitions of six consecutive exercises. The parameters studied were task time, path length of the instruments, and number of errors (collisions). Some participants continued training up to 10 repetitions to get insight in the learning curve.


RESULTS
Group A (expert) outperformed all the other groups (B, C, and D) in terms of total median task time (p < 0.05), groups C and D in terms of path length, and group D in terms of collision frequency in the first two repetitions. Group B (intermediate) outperformed group D (novice) in total time and endoscope path length for all repetitions, and group C (camera navigation) outperformed group D (novice) in the first repetition. Less experienced groups D and C did not reach expert level for the task time within 10 repetitions, and group B reached it after the eighth repetition (p < 0.05).


CONCLUSIONS
The study was able to establish construct validity for the training program with the simulator under study. The learning curve showed that training with this simulator is useful for subjects with or without limited endoscopic experience. Furthermore, previous endoscopic camera navigation already improves motor skills to more than the basic level.
Verdaasdonk
E G G
EG
Department of BioMechanical Engineering, Man Machine Systems Group, Delft University of Technology, Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg 2, 2628, CD, Delft, The Netherlands. e.g.g.verdaasdonk@3me.tudelft.nl
Stassen
L P S
LP
Schijven
M P
MP
Dankelman
J
J
D002983:Clinical Competence; D003198:Computer Simulation; D004724:Endoscopy / Q000193:education*; D006801:Humans; D007858:Learning; D013664:Teaching Materials; D014584:User-Computer Interface