O53: SO YOU WANT TO BE A ROBOTIC SURGEON? THE EFFECT OF BASELINE PSYCHOMOTOR ABILITY AND VIDEO-GAME EXPERIENCE ON ROBOTIC SURGICAL SKILL: A RANDOMISED CONTROL TRIAL

Introduction We assessed whether expert mentoring improved the rate of uptake of robotic surgical skill and whether general advanced psychomotor ability (PMA), and specific video-game experience (VGE) had any impact on robotic surgical skill. Method Twenty robotically naive medical students were blinded and randomised to two cohorts; control (CC) and intervention (IC). Each student's initial performance on a variety of da Vinci Skills Simulator (dVSSim) exercises was measured and then reassessed following an independent practice (CC) or mentor guided practice session (IC). Outcome metrics were overall score, time to completion, economy of motion and master workspace range. Quantitative, questionnaire data was collected to evaluate the relationship between robotic surgical skill, PMA and VGE. Statistical analysis was performed with SPSS software utilising the independent t-test. Result On average, overall score for CC improved by 16.8% compared to 43.3% for the IC (p=0.04). Time to completion improved by 26.2% (CC) vs. 40% (IC), economy of motion by 16.5% vs. 25% and master workspace range by 8% vs. 11%. PMA correlated with better initial performances for all metrics, especially for overall score (p=0.003) and economy of motion (p=0.03). Students with more VGE had overall scores that were on average 20% better than those with little or no experience and this relationship was also seen for economy of motion and master workspace range. Conclusion Expert mentoring leads to a greater improvement in performance than independent practice alone. Advanced PMA correlates with greater innate robotic skill, as does VGE, but to a lesser extent. Take-home message 1) Expert mentoring leads to a greater improvement in performance than independent practice alone. 2) Advanced PMA correlates with greater innate robotic skill, as does VGE, but to a lesser extent.

Application of a Perception Neuron® System in Simulation-Based Surgical Training

While multiple studies show that simulation methods help in educating surgical trainees, few studies have focused on developing systems that help trainees to adopt the most effective body motions. This is the first study to use a Perception Neuron® system to evaluate the relationship between body motions and simulation scores. Ten medical students participated in this study. All completed two standard tasks with da Vinci Skills Simulator (dVSS) and five standard tasks with thyroidectomy training model. This was repeated. Thyroidectomy training was conducted while participants wore a perception neuron. Motion capture (MC) score that indicated how long the tasks took to complete and each participant’s economy-of-motion that was used was calculated. Correlations between the three scores were assessed by Pearson’s correlation analyses. The 20 trials were categorized as low, moderate, and high overall-proficiency by summing the training model, dVSS, and MC scores. The difference between the low and high overall-proficiency trials in terms of economy-of-motion of the left or right hand was assessed by two-tailed t-test. Relative to cycle 1, the training model, dVSS, and MC scores all increased significantly in cycle 2. Three scores correlated significantly with each other. Six, eight, and six trials were classified as low, moderate, and high overall-proficiency, respectively. Low- and high-scoring trials differed significantly in terms of right (dominant) hand economy-of-motion (675.2 mm and 369.4 mm, respectively) (p = 0.043). Perception Neuron® system can be applied to simulation-based training of surgical trainees. The motion analysis score is related to the traditional scoring system.