Construct and face validity and task workload for laparoscopic camera navigation: virtual reality versus videotrainer systems at the SAGES Learning Center
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Laparoscopic camera navigation (LCN) training on simulators has demonstrated transferability to actual operations, but no comparative data exist. The objective of this study was to compare the construct and face validity, as well as workload, of two previously validated virtual reality (VR) and videotrainer (VT) systems.
Attendees (n = 90) of the SAGES 2005 Learning Center performed two repetitions on both VR (EndoTower™) and VT (Tulane Trainer) LCN systems using 30° laparoscopes and completed a questionnaire regarding demographics, simulator characteristics, and task workload. Construct validity was determined by comparing the performance scores of subjects with various levels of experience according to five parameters and face validity according to eight. The validated NASA-TLX questionnaire that rates the mental, physical, and temporal demand of a task as well as the performance, effort, and frustration of the subject was used for workload measurement.
Construct validity was demonstrated for both simulators according to the number of basic laparoscopic cases (p = 0.005), number of advanced cases (p < 0.001), and frequency of angled scope use (p < 0.001), and only for VT according to training level (p < 0.001) and fellowship training (p = 0.008). Face validity ratings on a 1-20 scale averaged 15.4 ± 3 for VR vs. 16 ± 2.6 for VT (p = 0.04). Ninety-six percent of participants rated both simulators as valid educational tools. The NASA-TLX overall workload score was 69.5 ± 24 for VR vs. 68.8 ± 20.5 for VT (p = 0.31).
This is the largest study to date that compares two validated LCN simulators. While subtle differences exist, both VR and VT simulators demonstrated excellent construct validity, good face validity, and acceptable workload parameters. These systems thus represent useful training devices and should be widely used to improve surgical performance.
KeywordsSimulation Skills assessment Virtual reality Laparoscopic camera navigation Construct validity Face validity Workload
The authors gratefully acknowledge SAGES, Verefi Inc., and Karl Storz Endoscopy for equipment support.
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