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Record W2902682793 · doi:10.1080/10401334.2018.1503961

Comparison of the Ottawa Surgical Competency Operating Room Evaluation (O-SCORE) to a Single-Item Performance Score

2018· article· en· W2902682793 on OpenAlexafffundabout
David Saliken, Nancy Dudek, Timothy J. Wood, Matthew J MacEwan, Wade Gofton

Bibliographic record

VenueTeaching and Learning in Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsOrthopedic surgeryPhysical therapyMedicineCompetence (human resources)CorrelationPsychologySurgerySocial psychology

Abstract

fetched live from OpenAlex

Construct: We compared a single-item performance score with the Ottawa Surgical Competency Operating Room Evaluation (O-SCORE) for their ability in assessing surgical competency. BACKGROUND: Surgical programs are adopting competency-based frameworks. The adoption of these frameworks for assessment requires tools that produce accurate and valid assessments of knowledge and technical performance. An assessment tool that is quick to complete could improve feasibility, reduce delays, and result in a higher volume of assessments of learners. Previous work demonstrated that the 9-item O-SCORE can produce valid results; the goal of this study was to determine if a single-item performance rating (Is candidate competent to independently complete procedure: yes or no) completed at a separate viewing would correlate to the O-SCORE, thus increasing feasibility of procedural competence assessment. APPROACH: Nineteen residents and 2 staff orthopedic surgeons from the University of Ottawa volunteered for a 2-part OSCE-style station including a written questionnaire and videotaped simulated open reduction and internal fixation midshaft radius fracture. Each performance was rated independently by 3 orthopedic surgeons using a single-item performance score (Time 1). The performances were assessed again 6 weeks later by the 3 raters using the O-SCORE (Time 2). Correlation between the single-item performance score and the O-SCORE were evaluated. RESULTS: Three orthopedic surgeons completed 21 ratings each resulting in 63 orthopedic ratings. There was a high level of correlation and agreement between the single-item performance score at Time 1 and Time 2 (κ correlation =0.72-1.00; p < .001; percentage agreement =90%-100%). The reliability of the O-SCORE at Time 2 with three raters was 0.83 and the internal consistency was 0.89. There was a tendency for each rater to assign more yes responses to the more senior trainees. CONCLUSIONS: A single-item performance score correlated highly with the O-SCORE in an orthopedic setting. A single-item score could be used to supplement a multi-item score with similar results in orthopedics. There is still benefit in completing multi-item scores such as the O-SCORE evaluations to guide specific areas of improvement and direct feedback.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.086
GPT teacher head0.386
Teacher spread0.300 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2018
Admission routes3
Has abstractyes

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