Feasibility of adapting the fundamentals of laparoscopic surgery trainer box to endoscopic skills training tool

The fundamentals of laparoscopic surgery (FLS) training box is a validated tool, already accessible to surgical trainees to hone their laparoscopic skills. We aim to investigate the feasibility of adapting the FLS box for the practice and assessment of endoscopic skills. This would allow for a highly available, reusable, low-cost, mechanical trainer. The design and development process was based on a user-centered design, which is a combination of the design thinking method and cognitive task analysis. The process comprises four phases: empathy, cognitive, prototyping/adaptation, and end user testing. The underlying idea was to utilize as many of the existing components of FLS training to maintain simplicity and cost effectiveness while allowing for the practice of clinically relevant endoscopic skills. A sample size of 18 participants was calculated to be sufficient to detect performance differences between experts and trainees using a two tailed t test with alpha set at 0.05, standard deviation of 5.5, and a power of 80%. Adaptation to the FLS box included two fundamental attachments: a front panel with an insertion point for an endoscope and a shaft which provides additional support and limits movement of the scope. The panel also allows for mounting of retroflexion tasks. Six endoscopic tasks inspired by FLS were designed (two of which utilize existing FLS components). Pilot testing with 38 participants showed high user's satisfaction and demonstrated that the trainer was robust and reliable. Task performance times was able to discriminate between trainees and experts for all six tasks. A mechanical, reusable, low-cost adaptation of the FLS training box for endoscopic skills is feasible and has high user satisfaction. Preliminary testing shows that the simulator is able to discriminate between trainees and experts. Following further validation, this adaptation may act as a supplement to the FES program.