Exposure to FLS Task Outweighs Video Gaming Experience for the VBLaST PT(c) Simulator

Charlotte Kaplan, MPH, Alexander Lanigan, MS, Henry Lin, MD, Ganesh Sankaranarayanan, PhD, Matt E Ritter, MD, Steven Schwaitzberg, MD, Daniel B Jones, MD, Suvranu De, ScD

Uniformed Services University, Rensselaer Polytechnic Institute, Harvard Medical School

Video gaming experience has shown to improve performance in minimally invasive surgical simulators. The VBLaST PT© is a virtual reality simulator that simulates the Peg Transfer task of the FLS. The aim of our study was to see the effect of video gaming experience compared to exposure to the Peg Transfer task in the performance of the novice subjects on the VBLaST.

Methods and Procedures
In this IRB approved study, first and second year Medical students were recruited at the Uniformed Services University, Bethesda, MD. Each subjects filled in a questionnaire about their FLS and video gaming experience. After viewing an instructional video subjects were randomly assigned to perform three repetitions of the peg transfer task on both FLS and VBLaST. Statistical analysis on their computed scores was performed using Pearson’s correlation and multivariate linear regression.

A total of 30 subjects participated in this study. 28 subjects had video game experience (mean = 15.8 years, frequency of playing in a year, mean = 47.3 days) and 20 subjects had performed the peg transfer task within the last year (number of repetitions, mean = 5.4 times and duration, mean = 24.8 minutes). Correlation analysis showed that the FLS and VBLaST PT© scores were highly correlated (0.427, P = 0.001). High correlation was also shown for FLS score and number of repetitions of FLS (0.324, p = 0.01), duration of practice (0.324, p = 0.017), duration from last training (-0.674, p < 0.001). VBLaST PT© score didn’t show a significant correlation for video gaming experience but showed correlation for duration from last training in FLS (-0.494, p < 0.001). Significant results from linear multivariate regression analysis on the relationship between the two scores and their 6 predictors (FLS number of repetitions, days of training , time since last training and number of years of gaming, frequency of gaming and time since last gaming session) are shown in Table 1. A significant model for FLS ( R2 = 0.5, F(6,47) = 9.84, p < 0.001) was achieved with frequency of video gaming having a significant positive weight and the time since last training in FLS a significant negative weights respectively. For the VBLaST (R2 = 0.37, F (6,47) = 6.26, p < 0.001), the model showed significant negative weights for time since last training in FLS and the number of years of gaming experience.

Our analysis showed that the frequency of gaming was a predictor for the performance on the FLS but prior gaming experience did not influence the performance of novice subjects on the VBLaST PT©. Time since last FLS practice session was a dominant factor for both FLS and VBLaST, indicating the importance of practice.

Table 1. Multiple Regression Results

Simulator Predictor Beta p Value
FLS Time sine last FLS practice session -0.599 p < 0.0001
FLS Fequency of gaming 0.297 p = 0.018
VBLaST PT© Time since last FLS practice session -0.722 p < 0.0001
VBLaST PT© Years of gaming -0.569 p = 0.015

Session: Poster Presentation

Program Number: P177

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