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Record W2008508310 · doi:10.1097/sih.0000000000000076

Queen’s Simulation Assessment Tool

2015· article· en· W2008508310 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2015
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsQueen's UniversityUniversity of Ottawa
Fundersnot available
KeywordsGeneralizability theoryInter-rater reliabilityObjective structured clinical examinationIntraclass correlationMedicinePsychologyMedical educationCompetence (human resources)Medical physicsPsychometricsClinical psychology

Abstract

fetched live from OpenAlex

INTRODUCTION: The use of high-fidelity simulation is emerging as an effective approach to competency-based assessment in medical education. We aimed to develop and validate a modifiable anchored global assessment scoring tool for simulation-based Objective Structured Clinical Examinations (OSCEs) of resuscitation competence in postgraduate emergency medicine (EM) trainees. METHODS: The Queen's Simulation Assessment Tool was developed using a modified Delphi technique with a panel of EM physicians. Ten standardized resuscitation OSCE scenarios were administered to EM trainees, and their video-recorded performances were scored by 3 independent and blinded EM attending physicians using the Queen's Simulation Assessment Tool. Correlational analyses and analysis of variance were applied to measure the discriminatory capabilities and interrater reliability of each scenario. A fully crossed generalizability study was conducted for each examination. RESULTS: Emergency medicine postgraduate trainees at Queen's University (n = 19-25 per station) participated in the study over 3 years. Interrater reliability showed acceptable levels of agreement for each scenario (mean Spearman ρ = 0.75 [0.63-0.87]; mean interclass correlation coefficient, 0.69 [0.58-0.87]). Discriminatory validity was strong, with senior residents outperforming junior residents in all but 1 of the 10 scenarios. Generalizability studies found the trainee and trainee by scenario interactions as the largest contributors to variance, with G coefficients ranging from 0.67 to 0.84. Resident trainees reported comfort being assessed in the simulation environment (3.8/5) and found the simulation-based examination valuable to their learning (4.6/5). CONCLUSIONS: This study describes the development and validation of a novel modifiable anchored global assessment scoring tool for simulation-based OSCE assessment of resuscitation competence in postgraduate EM trainees.

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.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.087
GPT teacher head0.450
Teacher spread0.364 · 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