Practice distribution in procedural skills training: a randomized controlled trial.
BACKGROUND
"Massed" and "distributed" practice are important concepts in the acquisition of fine motor skills, and may be important in training in procedural skills.


METHODS
A total of 41 novice subjects were recruited and randomized to three groups to receive training on the MIST VR surgical trainer. There were 14 subjects in each of groups A and B and 13 subjects in group C. Training comprised 20 min of massed practice for group A, 20 min of distributed practice in 5 min blocks for group B, and 15 min of distributed practice in 5-min blocks for group C. Following the training period, all groups had a 5-min rest period, followed by a 5-min retention test. Comparisons were made between groups A and B, and groups A and C.


RESULTS
There was a statistically significant difference between groups A and B (p = 0.023) on the retention test, with group B performing better. The increment between the groups was 19% for the overall score on MIST VR. There were also significant differences in the time taken to complete the task during the training phase (p = 0.023, training blocks 3 and 4). Graphical representation suggests no effect between groups A and C, and statistical analysis confirms that the observed difference in median score is not significant.


CONCLUSIONS
This study demonstrates a benefit for distributed practice over massed practice in learning laparoscopic surgical skills on the MIST VR surgical trainer. This finding has potential implications for skills training in all areas of medicine.
Mackay
S
S
Faculty of Medicine, Imperial College of Science, Technology, and Medicine, St. Mary's Hospital, Norfolk Place, London WZ 1PG, United Kingdom. s.mackay@ic.ac.uk
Morgan
P
P
Datta
V
V
Chang
A
A
Darzi
A
A
D000328:Adult; D002983:Clinical Competence / Q000706:statistics & numerical data*; D003194:Computer-Assisted Instruction; D013502:General Surgery / Q000193:education; D006801:Humans; D010535:Laparoscopy / Q000706:statistics & numerical data*; D016011:Normal Distribution; D013647:Task Performance and Analysis; D014584:User-Computer Interface