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The Capital Region of Denmark - a part of Copenhagen University Hospital
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Design and validation of a cross-specialty simulation-based training course in basic robotic surgical skills

Research output: Contribution to journalJournal articleResearchpeer-review

DOI

  1. Identifying curriculum content for a cross-specialty robotic-assisted surgery training program: a Delphi study

    Research output: Contribution to journalJournal articleResearchpeer-review

  2. Viral and Genomic Drivers of Squamous Cell Neoplasms Arising in the Lacrimal Drainage System

    Research output: Contribution to journalJournal articleResearchpeer-review

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BACKGROUND: The aim of this study was to design and validate a cross-specialty basic robotic surgical skills training program on the RobotiX Mentor virtual reality simulator.

METHODS: A Delphi panel reached consensus on six modules to include in the training program. Validity evidence was collected according to Messick's framework with three performances in each simulator module by 11 experienced robotic surgeons and 11 residents without robotic surgical experience.

RESULTS: For five of the six modules, a compound metrics-based score could significantly discriminate between the performances of novices and experienced robotic surgeons. Pass/fail levels were established, resulting in very few novices passing in their first attempt.

CONCLUSIONS: This validated course can be used for structured simulation-based basic robotic surgical skills training within a mastery learning framework where the individual trainee can practice each module until they achieve proficiency and can continue training on other modalities and more specific to their specialty.

Original languageEnglish
JournalThe international journal of medical robotics + computer assisted surgery : MRCAS
Volume16
Issue number5
Pages (from-to)1-10
Number of pages10
ISSN1478-5951
DOIs
Publication statusPublished - 2020

    Research areas

  • evidence-based medical education, robotic surgery, simulation-based training, validity, virtual reality simulation

ID: 60708290