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Record W3014092078 · doi:10.1186/s40463-020-00411-y

Assessment of a virtual reality temporal bone surgical simulator: A national face and content validity study

2020· article· en· W3014092078 on OpenAlexafffundabout
Evan C. Compton, Sumit Agrawal, Hanif M. Ladak, Sonny Chan, Monica Hoy, Steven C. Nakoneshny, Lauren Siegel, Joseph C. Dort, Justin T. Lui

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of TorontoWestern UniversityUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsVirtual realityContent validityFace (sociological concept)Face validityContent (measure theory)Computer scienceSimulationHuman–computer interactionBone mineral contentPsychologyMedicineBone densityMathematicsPsychometricsSociologyDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Trainees in Otolaryngology-Head and Neck Surgery must gain proficiency in a variety of challenging temporal bone surgical techniques. Traditional teaching has relied on the use of cadavers; however, this method is resource-intensive and does not allow for repeated practice. Virtual reality surgical training is a growing field that is increasingly being adopted in Otolaryngology. CardinalSim is a virtual reality temporal bone surgical simulator that offers a high-quality, inexpensive adjunct to traditional teaching methods. The objective of this study was to establish the face and content validity of CardinalSim through a national study. METHODS: Otolaryngologists and resident trainees from across Canada were recruited to evaluate CardinalSim. Ethics approval and informed consent was obtained. A face and content validity questionnaire with questions categorized into 13 domains was distributed to participants following simulator use. Descriptive statistics were used to describe questionnaire results, and either Chi-square or Fishers exact tests were used to compare responses between junior residents, senior residents, and practising surgeons. RESULTS: Sixty-two participants from thirteen different Otolaryngology-Head and Neck Surgery programs were included in the study (32 practicing surgeons; 30 resident trainees). Face validity was achieved for 5 out of 7 domains, while content validity was achieved for 5 out of 6 domains. Significant differences between groups (p-value of < 0.05) were found for one face validity domain (realistic ergonomics, p = 0.002) and two content validity domains (teaching drilling technique, p = 0.011 and overall teaching utility, p = 0.006). The assessment scores, global rating scores, and overall attitudes towards CardinalSim, were universally positive. Open-ended questions identified limitations of the simulator. CONCLUSION: CardinalSim met acceptable criteria for face and content validity. This temporal bone virtual reality surgical simulation platform may enhance surgical training and be suitable for patient-specific surgical rehearsal for practicing Otolaryngologists.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.178
GPT teacher head0.372
Teacher spread0.194 · 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 designObservational
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

Citations29
Published2020
Admission routes3
Has abstractyes

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