Short-term educational interventions in surgical training: measuring the knowledge gain among surgeons in Ethiopia.

INTRODUCTION

Laparoscopic surgery offers significant benefits in modern healthcare, including reduced recovery times and fewer complications. However, mastering these techniques requires specialized training, which is often limited in resource-constrained settings like Ethiopia. Simulator-based training has been shown to be an effective method for improving surgeons' understanding of basic laparoscopic surgery concepts, particularly in resource-limited settings. By providing hands-on practice in a simulated environment, this approach enables participants to refine their skills and enhance their knowledge of key techniques. This study aims to assess the impact of a two-day simulator-based laparoscopy training program on Ethiopian surgeons' knowledge.

METHODS

This is a quasi-experimental study conducted in Ethiopia on April 20 and 21, 2024. Surgeons were randomly selected from those who registered for the study, after which the selected surgeons underwent a two-day simulator-based laparoscopy training. Structured pre-test and post-test questionnaires with a maximum score of 20 were administered. A paired sample t-test was performed to evaluate the effect of the intervention.

RESULTS

The study included 14 surgeons, 12 of whom were male. Only one surgeon had prior laparoscopy training, and 6 (42%) had experience either performing or assisting in laparoscopic procedures. Participants demonstrated significant improvement from the pre-test (M = 10.57, SD ± 4.54) to the post-test (M = 14.64, SD ± 2.47), indicating substantial improvements in surgical knowledge following the training (95% CI 1.88-6.26, p = 0.001).

CONCLUSION

The short-term simulator-based training significantly improved the knowledge of Ethiopian surgeons in laparoscopic surgery, as evidenced by the increase in post-test scores. These findings highlight the importance of simulator-based training in enhancing surgical knowledge, particularly in resource-limited settings.