Preliminary Face and Construct Validation Study of a Virtual Basic Laparoscopic Skill Trainer

Abstract

The Virtual Basic Laparoscopic Skill Trainer (VBLaST) is a developing virtual-reality-based surgical skill training system that incorporates several of the tasks of the Fundamentals of Laparoscopic Surgery (FLS) training system. This study aimed to evaluate the face and construct validity of the VBLaST system. Thirty-nine subjects were voluntarily recruited at the Beth Israel Deaconess Medical Center (Boston, MA) and classified into two groups: experts (PGY 5, fellow and practicing surgeons) and novice (PGY 1-4). They were then asked to perform three FLS tasks, consisting of peg transfer, pattern cutting, and endoloop, on both the VBLaST and FLS systems. The VBLaST performance scores were automatically computed, while the FLS scores were rated by a trained evaluator. Face validity was assessed using a 5-point Likert scale, varying from not realistic/useful (1) to very realistic/useful (5). Face-validity scores showed that the VBLaST system was significantly realistic in portraying the three FLS tasks (3.95 +/- 0.909), as well as the reality in trocar placement and tool movements (3.67 +/- 0.874). Construct-validity results show that VBLaST was able to differentiate between the expert and novice group (P = 0.015). However, of the two tasks used for evaluating VBLaST, only the peg-transfer task showed a significant difference between the expert and novice groups (P = 0.003). Spearman correlation coefficient analysis between the two scores showed significant correlation for the peg-transfer task (Spearman coefficient 0.364; P = 0.023). VBLaST demonstrated significant face and construct validity. A further set of studies, involving improvement to the current VBLaST system, is needed to thoroughly demonstrate face and construct validity for all the tasks.