Didactic training vs. computer-based self-learning in the prediction of diminutive colon polyp histology by trainees: a randomized controlled study.

Background and study aim Experts can accurately predict diminutive polyp histology, but the ideal method to train nonexperts is not known. The aim of the study was to compare accuracy in diminutive polyp histology characterization using narrow-band imaging (NBI) between participants undergoing classroom didactic training vs. computer-based self-learning. Participants and methods Trainees at two institutions were randomized to classroom didactic training or computer-based self-learning. In didactic training, experienced endoscopists reviewed a presentation on NBI patterns for adenomatous and hyperplastic polyps and 40 NBI videos, along with interactive discussion. The self-learning group reviewed the same presentation of 40 teaching videos independently, without interactive discussion. A total of 40 testing videos of diminutive polyps under NBI were then evaluated by both groups. Performance characteristics were calculated by comparing predicted and actual histology. Fisher's exact test was used and P < 0.05 was considered significant. Results A total of 17 trainees participated (8 didactic training and 9 self-learning). A larger proportion of polyps were diagnosed with high confidence in the classroom group (66.5 % vs. 50.8 %; P < 0.01), although sensitivity (86.9 % vs. 95.0 %) and accuracy (85.7 % vs. 93.9 %) of high-confidence predictions were higher in the self-learning group. However, there was no difference in overall accuracy of histology characterization (83.4 % vs. 87.2 %; P = 0.19). Similar results were noted when comparing sensitivity and specificity between the groups. Conclusion The self-learning group showed results on a par with or, for high-confidence predictions, even slightly superior to classroom didactic training for predicting diminutive polyp histology. This approach can help in widespread training and clinical implementation of real-time polyp histology characterization. © Georg Thieme Verlag KG Stuttgart · New York.

RCT Entities:   Population Interventions Outcomes