Do Motion Metrics Lead to Improved Skill Acquisition on Simulators?

Emphasizing the growing popularity of motion metrics are the majority of available virtual reality simulators and some newer hybrid models that offer motion tracking for performance assessment. A popular hybrid model (PROMIS) allows training with regular laparoscopic instruments in a box-trainer while automatically recording task duration and movement efficiency (pathlength and smoothness) that are immediately offered as feedback to trainees. Despite the increasing availability of simulators that track motion, our knowledge of the impact those metrics have on trainee learning is severely limited. We do not know if it is more important to use speed, accuracy, motion efficiency or a combination thereof for performance assessment and how these metrics impact skill transfer to the OR. Based on sound educational principles we have developed a proficiency-based laparoscopic suturing simulator curriculum. This curriculum focuses on deliberate and distributed practice, provides trainees with augmented feedback and sets expert-derived performance goals based on time and errors. We have previously demonstrated that this curriculum leads to improved operative performance of trainees compared to controls. To measure operative performance and determine transferability, we will use a live porcine Nissen fundoplication model. Instead of placing actual patients at risk, the porcine model is preferable for this purpose as it offers objective metrics (targets are established, distances measured, knots are disrupted for slippage scoring), complete standardization, and allows multiple individuals to be tested on the same day. We hypothesize that proficiency-based simulator training in laparoscopic suturing to expert-derived levels of speed and motion will result in better operative performance compared to participants training to levels of speed or motion alone. The study is powered to detect an at least 10% performance difference between the groups. Specific Aims 1. Compare whet