Distribution of innate ability for surgery amongst medical students assessed by an advanced virtual reality surgical simulator.
BACKGROUND
Surgery is a craft profession requiring individuals with specific, well-documented innate aptitude for manipulative skills. Yet in most countries, the current selection process of surgical trainees does not include aptitude testing for the psychomotor and manipulative skills of candidates.


METHODS
A total of 125 participants (121 medical students and four expert surgeons) performed all 26 exercises of the da Vinci Skills Simulator, with six exercises being identified as metrics of aptitude for manipulative and psychomotor skills. The expert surgeons were enrolled as the control group to validate the performance of the most talented students.


RESULTS
Eight students (6.6%) significantly outperformed the remaining 113, obtaining a median value of the sum of weighted overall score on the six selected exercises of 52.7% versus 21.0% (p < 0.001). In contrast, 14 students (11.6%) performed significantly worse and well below the performance of the other 107, with a median value of overall score of 8.7% versus 24.1 (p < 0.001). There was no statistically significant difference between expert surgeons (control group) and the eight talented students (62.1% vs. 52.7%, respectively; p = 0.368). No significant correlation between exposure to video games and overall score (ρ = 0.330) was observed.


CONCLUSIONS
In terms of innate aptitude for manipulative and psychomotor abilities, the present investigation has documented two subpopulations that fall outside the norm for the group of medical students recruited for the study: (i) a small group (6.6%) with a high level and (ii) a larger cohort (11.6%) with low level (significantly below the norm) innate aptitude for surgery. Exposure to video game experience did not appear to influence performances on the da Vinci Skills Simulator.
EndoCAS, Center for Computer Assisted Surgery, University of Pisa, Edificio 102, via Paradisa 2, 56124, Pisa, Italy, andmog77@gmail.com.
Andrea
A
Moglia
Vincenzo
V
Ferrari
Luca
L
Morelli
Franca
F
Melfi
Mauro
M
Ferrari
Franco
F
Mosca
Alfred
A
Cuschieri
D000328:Adult; D000465:Algorithms; D015331:Cohort Studies; D003198:Computer Simulation; D003194:Computer-Assisted Instruction / Q000706:statistics & numerical data*; D004501:Education, Medical / Q000379:methods*; D004521:Educational Measurement; D005260:Female; D013502:General Surgery / Q000193:education*; D006801:Humans; D007323:Instinct; D008297:Male; D018579:Patient Selection; D011597:Psychomotor Performance; D012371:Robotics; D012737:Sex Factors; D018709:Statistics, Nonparametric; D013337:Students, Medical / Q000706:statistics & numerical data*; D014584:User-Computer Interface; D018910:Video Games