2020
DOI: 10.1007/s10353-020-00651-2
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COVID-19: an opportunity to restructure surgical education

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Cited by 2 publications
(6 citation statements)
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“…Three studies reported an increase in simulated training in Argentinian 41 , Chilean 9 , and Mexican 35 programs. Simulated training was suggested as a strategy to adapt residency programs to the pandemic with the objective of improving surgical skills in a safe and standardized environment 61 .…”
Section: Resultsmentioning
confidence: 99%
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“…Three studies reported an increase in simulated training in Argentinian 41 , Chilean 9 , and Mexican 35 programs. Simulated training was suggested as a strategy to adapt residency programs to the pandemic with the objective of improving surgical skills in a safe and standardized environment 61 .…”
Section: Resultsmentioning
confidence: 99%
“…Studies from LA pointed out the need to suspend elective surgeries during COVID-19 outbreaks 29 , 30 , which caused a significant decrease in the total number of surgeries performed 35 , 42 . Consequently, the number of surgeries performed by residents decreased by 56–90% 21 , 22 , 30 .…”
Section: Introductionmentioning
confidence: 99%
“…2,3 Simulation-based training (SBT) has been proposed as an alternative to facilitate residents' ongoing surgical skill development where hands-on training in the OR is not feasible. 3,4 The paradigm shift towards SBT in surgery began years ago, in response to reduced training opportunities resulting from duty hour restrictions, concerns for patient safety, and increasing surgical subspecialization. 5 The rationale for SBT is compelling: simulation provides a 'risk-free' environment for trainees to develop surgical skills at their own pace and learn from mistakes without putting patients at risk.…”
mentioning
confidence: 99%
“…6,7 In this issue, Mirchi et al advocate for high-fidelity, virtual-reality (VR) simulation augmented by intelligent tutoring systems (ITS) to close the training gap created by COVID-19. 4 The automated feedback generated through ITS reduces the need for a live instructor, increasing the flexibility and feasibility of SBT. Machine learning facilitates individualization of this feedback (particularly in reference to a pre-defined proficiency criterion), which educators could use to adapt simulations 'on the fly' based on identified learning needs.…”
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confidence: 99%
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