Evaluation of an e-learning program for the diagnosis of rectosigmoid endometriosis with rectal water contrast transvaginal ultrasonography (rectosonography)

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This study evaluated the effectiveness of an e-learning program in training practitioners to diagnose rectosigmoid endometriosis using rectosonography.

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Abstract

This study aimed to evaluate the value of an e-learning program for the diagnosis of rectosigmoid endometriosis lesions using rectal water contrast transvaginal ultrasonography (rectosonography/RSG). Theoretical RSG training using videos with a commentary was offered online to healthcare professionals involved in ultrasound screening for endometriosis. A test (without correction) with 24 RSG video loops was used to assess the participants' baseline level before the training and their improvement afterwards. If the success rate post-training was below 80 %, the participant could start over with another series of 24 videos. Between February and June 2020, thirty participants took the training course (of which 80 % were obstetrics-gynaecology residents). The e-learning program resulted in a significant performance increase in the diagnosis of rectosigmoid endometriosis lesions, with a higher test success rate after the training compared to before (74.4 % and 63.6 % respectively; +10.8 %; 95 % CI [6,6; 15]; p < 0.001). Significant improvement was also observed regarding the overall skills involved in the ultrasound diagnosis of deep infiltrating endometriosis (+9.2 %; p < 0.001), the accurate diagnosis of the height of bowel lesions (+14.7 %; p < 0.001) and uterosacral ligament lesions (+8%; p < 0.005). In conclusion, our e-learning program led to a significant improvement of the diagnostic performance of digestive endometriosis using transvaginal ultrasound with intrarectal water contrast (rectosonography). Adding feedback to the post-test video loops could further increase the efficacy of the e-learning training.

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Condition tags

endometriosis

MeSH descriptors

Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction Computer-Assisted Instruction

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (38)

Source provenance

europepmc
last seen: 2026-08-11T06:11:44.160905+00:00
openalex
last seen: 2026-06-10T17:14:06.276822+00:00
pubmed
last seen: 2026-08-11T06:11:39.584961+00:00
License: CC0 · commercial use OK