Objectives• To evaluate three standardized robotic surgery training methods, inanimate, virtual reality and in vivo, for their construct validity.• To explore the concept of cross-method validity, where the relative performance of each method is compared.
Materials and Methods• Robotic surgical skills were prospectively assessed in 49 participating surgeons who were classified as follows: 'novice/trainee': urology residents, previous experience <30 cases (n = 38) and 'experts': faculty surgeons, previous experience Ն30 cases (n = 11).• Three standardized, validated training methods were used:(i) structured inanimate tasks; (ii) virtual reality exercises on the da Vinci Skills Simulator (Intuitive Surgical, Sunnyvale, CA, USA); and (iii) a standardized robotic surgical task in a live porcine model with performance graded by the Global Evaluative Assessment of Robotic Skills (GEARS) tool.• A Kruskal-Wallis test was used to evaluate performance differences between novices and experts (construct validity). • Spearman's correlation coefficient (r) was used to measure the association of performance across inanimate, simulation and in vivo methods (cross-method validity).
Results• Novice and expert surgeons had previously performed a median (range) of 0 (0-20) and 300 (30-2000) robotic cases, respectively (P < 0.001).• Construct validity: experts consistently outperformed residents with all three methods (P < 0.001).• Cross-method validity: overall performance of inanimate tasks significantly correlated with virtual reality robotic performance (r = -0.7, P < 0.001) and in vivo robotic performance based on GEARS (r = -0.8, P < 0.0001).• Virtual reality performance and in vivo tissue performance were also found to be strongly correlated (r = 0.6, P < 0.001).
Conclusions• We propose the novel concept of cross-method validity, which may provide a method of evaluating the relative value of various forms of skills education and assessment.• We externally confirmed the construct validity of each featured training tool.
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