Construct validity of nine new inanimate exercises for robotic surgeon training using a standardized setup

As more surgeons choose to complete procedures robotically, validated training tools are needed so that they can acquire and maintain the technical skills required to proficiently use robotic systems. The purpose of this study was to show construct validity of nine new inanimate training exercises for robot-assisted surgery. The inanimate training exercises were designed to span several core technical skills required to use a robotic system.

New (n = 30) and experienced (n = 11) robotic surgeons participated in the study. New robotic surgeons had not yet completed their first robotic surgery case and participated in this study before attending their robotic certification course. Experienced robotic surgeons had completed more than 200 robotic surgery cases. The raw scores from the exercises were reported so that other research groups could easily define custom proficiency levels. Example normalized scores that could be used in proficiency-based curricula were computed. These normalized scores balanced efficiency (completion time) and accuracy (exercise-specific errors) to measure performance. Finally, the setup was standardized using a custom docking model, which enabled consistent and repeatable completion of the inanimate exercises across surgeons.

For all nine exercises, experienced robotic surgeons completed the exercises significantly faster than new robotic surgeons (p < 0.01). Similarly, experienced robotic surgeons achieved higher normalized scores than new robotic surgeons for all nine exercises (p < 0.01). Finally, consistent robot setup was achieved using the custom docking model based on an analysis of the robot kinematic data.

In summary, all nine inanimate exercises showed construct validity. The results suggest that the inanimate exercises along with the custom docking model can be used as part of proficiency-based curricula to improve robotic surgeon training.