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Survey of Current Surgical Competency Assessment and a Possible Role for Virtual Reality Simulation.

2007· article· en· W2315709551 on OpenAlexaboutno aff
Yousuf M. Khalifa, Nadeem Fatteh, David Bogorad, Julian J. Nussbaum

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2007
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsnot available
Fundersnot available
KeywordsRespondentVirtual realityCurriculumMedical educationMedicineCompetency assessmentPsychologyComputer sciencePedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: To survey Ophthalmology Residency program directors and chairmen regarding current surgical competency assessment trends and opinions on the role of virtual reality surgical simulation. METHODS: A 23 question survey was sent to the membership of the Association of University Professors of Ophthalmology (AUPO), which includes residency program directors and chairmen from 120 ophthalmology training programs in the United States and Canada. Questions encompassed current surgical assessment methods for residents, the respondent’s virtual reality experience, and the respondent’s opinions on virtual reality simulation RESULTS: A total of 106 responses (44.2%) from 83 different residency programs (69.2%) were received. 86.7% of programs had functional wetlabs with 87.7% of respondents believing that wetlabs were beneficial. Experience with virtual reality simulation was limited to only having heard of the technology in 76.4% of respondents, 59.4% have seen a VR simulator, 34.9% have hands-on experience with VR simulator, and 2.8% use VR simulation in training. Those with higher familiarity scores had a stepwise more favorable opinion of VR with regards to patient safety, surgical curriculum, and awareness/acceptance by residents and faculty. CONCLUSIONS The community of ophthalmology educators is grappling with the issue of ACGME-mandated competency-based assessment in general and surgical competency appraisal tools in particular. The selection of assessment methods varies widely from program to program. Two different programs may use a similar number of assessment methods but completely different methods of assessment. This lack of uniformity can be corrected by implementation of objective, efficacious methods that are used across the board and serve as a standard of assessment among residency programs. VR is one such possibility of standardized assessment. While VR is considered relatively advanced technology, it is a rather new tool and its efficacy as a method of assessment has not been adequately gauged. Furthermore, awareness of VR is low as is knowledge regarding its possible incorporation into surgical curriculum. Perception of VR, familiarity with usage of VR, obstacles faced in incorporating VR into curriculum, and the issue of whether or not it is even a valid assessment tool were addressed in this study. The results of this survey support virtual reality as a means of delivering a surgical curriculum that is safe for the patient and accepted by residents and faculty. Conversely, cost is viewed as a detractor from full implementation. The acquisition of surgical skills and transferability of surgical skills gained through virtual reality simulation has not been substantiated according to the opinions of those surveyed. The results of the survey shed some light on the residency programs’ current opinions of VR, but more definitive research is needed to prove the benefit of virtual reality in the operating room.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.130
GPT teacher head0.472
Teacher spread0.342 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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