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Record W4401013846 · doi:10.1186/s12909-024-05774-8

Conducting an objective structured clinical examination under COVID-restricted conditions

2024· article· en· W4401013846 on OpenAlexaffabout
Andrea Gotzmann, John R. Boulet, Yichi Zhang, Judy McCormick, Mathieu Wojcik, Ilona Bartman, Debra Pugh

Bibliographic record

VenueBMC Medical Education · 2024
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMedical Council of Canada
Fundersnot available
KeywordsObjective structured clinical examinationCronbach's alphaMedicineLicensurePhysical examinationUnited States Medical Licensing ExaminationIMGFamily medicineCertificationCoronavirus disease 2019 (COVID-19)Reliability (semiconductor)Clinical psychologyPsychologyPsychometricsMedical educationMedical schoolDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The administration of performance assessments during the coronavirus disease of 2019 (COVID-19) pandemic posed many challenges, especially for examinations employed as part of certification and licensure. The National Assessment Collaboration (NAC) Examination, an Objective Structured Clinical Examination (OSCE), was modified during the pandemic. The purpose of this study was to gather evidence to support the reliability and validity of the modified NAC Examination. METHODS: The modified NAC Examination was delivered to 2,433 candidates in 2020 and 2021. Cronbach's alpha, decision consistency, and accuracy values were calculated. Validity evidence includes comparisons of scores and sub-scores for demographic groups: gender (male vs. female), type of International Medical Graduate (IMG) (Canadians Studying Abroad (CSA) vs. non-CSA), postgraduate training (PGT) (no PGT vs. PGT), and language of examination (English vs. French). Criterion relationships were summarized using correlations within and between the NAC Examination and the Medical Council of Canada Qualifying Examination (MCCQE) Part I scores. RESULTS: Reliability estimates were consistent with other OSCEs similar in length and previous NAC Examination administrations. Both total score and sub-score differences for gender were statistically significant. Total score differences by type of IMG and PGT were not statistically significant, but sub-score differences were statistically significant. Administration language was not statistically significant for either the total scores or sub-scores. Correlations were all statistically significant with some relationships being small or moderate (0.20 to 0.40) or large (> 0.40). CONCLUSIONS: The NAC Examination yields reliable total scores and pass/fail decisions. Expected differences in total scores and sub-scores for defined groups were consistent with previous literature, and internal relationships amongst NAC Examination sub-scores and their external relationships with the MCCQE Part I supported both discriminant and criterion-related validity arguments. Modifications to OSCEs to address health restrictions can be implemented without compromising the overall quality of the assessment. This study outlines some of the validity and reliability analyses for OSCEs that required modifications due to COVID.

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)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.111
GPT teacher head0.483
Teacher spread0.372 · 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.

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

Citations3
Published2024
Admission routes2
Has abstractyes

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