Analyzing Surgical Competency Development through Robotic and Laparoscopic Simulation-Based Training
DOI:
https://doi.org/10.56294/mw2023107Keywords:
Laparoscopic Techniques, Surgical Competency, Surgical Trainees, Medical Students, Robotic Training, Cadaveric SpecimensAbstract
Minimally invasive surgery is becoming increasingly common, yet laparoscopic techniques often present a steep learning curve. Robotic surgical systems can offer a more efficient training pathway. The research compared robotic and laparoscopic simulation-based training in developing surgical competency among surgical trainees and medical students. A total of 230 participants were randomly assigned to two groups: surgical trainees (Group 1, n=115) and medical students (Group 2, n=115). Group 1 received 6 hours of laparoscopic or robotic simulation training before completing three surgical tasks with cadaveric varieties. Group 2 underwent 3 hours of training on either platform and completed a single surgical task. Performance was assessed using the Surgical Competency Assessment Tool (SCAT, maximum score of 30), the time taken to complete each task and the number of suture errors. The results showed that Group 1 demonstrated significantly better performance after robotic training, with a median SCAT score of 27.00 for the robotic group compared to 18.00 for the laparoscopic group (P < 0.001). The robotic group also made fewer errors in both continuous and interrupted sutures (P < 0.001). Similarly, Group 2 completed more interrupted sutures with fewer errors and less time when trained on the robotic platform (P < 0.001). Additionally, both groups reported reduced fatigue and greater physical comfort with robotic training (P < 0.001). Using SPSS (version 25), data were analyzed by applying descriptive statistics, Mann-Whitney U tests for non-parametric data, and independent t-tests for continuous variables. These findings suggest that robotic simulation-based training enhances the development of surgical competency more effectively than laparoscopic training.
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Copyright (c) 2023 Sujayaraj Samuel Jayakumar, Harsh Bhati, Jitendra Narayan Senapati (Author)
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