Hysteroscopic placement of tubal sterilization implants: virtual reality simulator training View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2012-07

AUTHORS

Pierre Panel, Michael Bajka, Arnaud Le Tohic, Alaa El Ghoneimi, Carmen Chis, Stéphane Cotin

ABSTRACT

STUDY OBJECTIVE: To assess face and construct validity of a new virtual reality (VR) training simulator for hysteroscopic placement of tubal sterilization implants. DESIGN: Nonrandomized, controlled trial comparing responses and performance of novices and experts on the simulator. DESIGN CLASSIFICATION: Canadian task force II-1. SETTING: Forty-six gynecologists were personally invited or recruited at the 33rd Conference of the French National College of Gynecologists and Obstetricians (CNGOF) from December 9 to 12, 2009, grouped as 20 experts and 26 novices. They all performed the defined sequence of virtual procedures on the simulator (case 1 for familiarization, case 4 for study assessment) and finally completed the study questionnaire. MEASUREMENTS AND MAIN RESULTS: Responses to realism, educational potential, and general opinion were excellent, proving face validity. Significant differences between novices and experts were assessed for 7 of the 15 metrics analyzed, proving construct validity. CONCLUSIONS: We established face and construct validity for EssureSim, an educational VR simulator for hysteroscopic tubal sterilization implant placement. The next steps are to investigate convergent and predictive validity to affirm the real capacity of transferring the skills learned on the training simulator to the patient in the operating room. More... »

PAGES

1986-1996

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00464-011-2139-6

DOI

http://dx.doi.org/10.1007/s00464-011-2139-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050150877

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22234594


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

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curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s00464-011-2139-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s00464-011-2139-6'

Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00464-011-2139-6'


 

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