How much do we need experts during laparoscopic suturing training?

INTRODUCTION: Because of the complex nature of laparoscopic suturing, numerous curricula have been developed to overcome the steep learning curve in a patient-free environment. Distributed training leads to better acquisition and retention of skill compared with massed training. However, this requires considerable time commitment of experts that supervise these training sessions. This study investigates the possibility of replacing expert supervision by structured training with video demonstrations and peer feedback.
MATERIALS AND METHODS: The study population consisted of two balanced groups of ten senior medical students with minimal experience in laparoscopy. The control group trained with continuous expert feedback while for the experimental group only video demonstrations and external feedback from peers were available. Training was completed when a previously determined expert level was achieved on two consecutive attempts (proficiency criterion). Students were tested on their suturing skills 1 week after the training as well as after 4 months. A composite score assessing quality and quantity of suturing performance was used. Data are shown as median (interquartile range, IQR).
RESULTS: Students' performance improved more than 200% after training. Learning curves did not differ between groups (p = 0.28). One week after training, scores were 192 s (IQR 65 s) for the control and 190 s (IQR 27 s) for the experimental group (p = 0.63). After 4 months this was 223 s (IQR 88 s) and 220 s (IQR 37 s), respectively (p = 0.60).
CONCLUSIONS: Both training methods are very efficient at improving laparoscopic suturing skills and provide excellent skill retention. We therefore conclude that structured training with video demonstrations and peer feedback can replace expert supervision to teach laparoscopic suturing skills to novices. This will facilitate practical organization of skills training.

RCT Entities:   Population Interventions Outcomes