Ergonomics in Laparoscopic Box Training and Virtual Reality (VR) Simulations: A Systematic Review

Laparoscopic surgery has now become the gold standard in managing most surgical cases. Despite its advantages, working hours and in-theatre training restrictions have prompted trainees to explore alternatives like virtual reality (VR) simulations and box training. Furthermore, given the increased frequency of minimally invasive surgery and the prevalence of musculoskeletal issues among surgeons, there's a growing effort to optimize ergonomics. There is currently a lack of focus on ergonomics in training, prompting our study to inspect VR and box training's ergonomic outcomes and their impact on task performance. This systematic review was conducted at Barts Cancer Institute, Queen Mary University, from January 27, 2024, to April 22, 2024. Multiple databases were searched electronically from January 1980 to March 2024, including only articles that utilized electromyography (EMG) or the NASA Task Load Index (NASA-TLX) to measure ergonomics. Two reviewers independently conducted eligibility assessment, data extraction, and risk of bias evaluation, with discrepancies resolved through consensus discussions. Ultimately, 12 studies were selected. EMG results indicated a higher %MVC (maximum voluntary contraction) in box training in poor ergonomic settings and a negative correlation between skills and muscle activity. Both modalities showed a significant decrease in NASA-TLX scores after training on the simulators and when comparing novice and experienced surgeons. Furthermore, a reduction in physical demand and improved task performance was observed, with significant differences found between experts and novices in a VR appendicectomy scenario. This systematic review reveals reduced muscle activity and physical demand among trained individuals in laparoscopic surgery with both box trainers and VR simulators, emphasizing the importance of addressing ergonomic considerations. To advance our understanding of surgical ergonomics, the standardization of measurement methods and higher-quality evidence, particularly through randomized controlled trials, are recommended.