Minimally invasive surgery training using multiple port sites to improve performance.

BACKGROUND

Structural learning theory suggests that experiencing motor task variation enables the central nervous system to extract general rules regarding tasks with a similar structure - rules that can subsequently be applied to novel situations. Complex minimally invasive surgery (MIS) requires different port sites, but switching ports alters the limb movements required to produce the same endpoint control of the surgical instrument. The purpose of the present study was to determine if structural learning theory can be applied to MIS to inform training methods.

METHODS

A tablet laptop running bespoke software was placed within a laparoscopic box trainer and connected to a monitor situated at eye level. Participants (right-handed, non-surgeons, mean age = 23.2 years) used a standard laparoscopic grasper to move between locations on the screen. There were two training groups: the M group (n = 10) who trained using multiple port sites, and the S group (n = 10) who trained using a single port site. A novel port site was used as a test of generalization. Performance metrics were a composite of speed and accuracy (SACF) and normalized jerk (NJ; a measure of movement 'smoothness').

RESULTS

The M group showed a statistically significant performance advantage over the S group at test, as indexed by improved SACF (p < 0.05) and NJ (p < 0.05).

CONCLUSIONS

This study has demonstrated the potential benefits of incorporating a structural learning approach within MIS training. This may have practical applications when training junior surgeons and developing surgical simulation devices.