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Record W3191585048 · doi:10.1371/journal.pone.0255696

A systematic review and meta-analysis of measurement properties of objective structured clinical examinations used in physical therapy licensure and a structured review of licensure practices in countries with well-developed regulation systems

2021· review· en· W3191585048 on OpenAlexafffundabout
Pavlos Bobos, Dimitra V Pouliopoulou, Alexandra Harriss, Jackie Sadi, Alison Rushton, Joy C. MacDermid

Bibliographic record

VenuePLoS ONE · 2021
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsMcMaster UniversitySt. Joseph's HospitalHand and Upper Limb ClinicPublic Health OntarioUniversity of TorontoSt. Michael's HospitalWestern University
FundersCanadian Institutes of Health ResearchArthritis Society
KeywordsLicensureCronbach's alphaMeta-analysisIntraclass correlationMedicineObjective structured clinical examinationMedical educationFamily medicinePsychologyClinical psychologyPsychometricsPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The Objective Structured Clinical Examination (OSCE) is a commonly used tool internationally to assess clinical competency. Physical therapy (PT) licensure processes vary internationally. The OSCE is the tool used in Canada to assess clinical competency for PT graduates seeking licensure. Previous studies that examined the measurement properties of OSCEs present contradictory results. OBJECTIVES: The first objective was to investigate the reliability and validity of OSCEs when administered to PTs during their education or as part of a licensure process. The second objective was to conduct a structured review to report PT educational and licensing components and policies in 17 countries with well-developed PT regulation systems. METHODS: An electronic search was performed in four databases from inception to 31st March 2021 to identify relevant articles. Two reviewers performed the critical appraisal of the included studies using a validated quality assessment tool. We deployed a random effects meta-analysis on reliability and validity estimates of OSCEs and examined sources of heterogeneity with univariate meta-regressions. We searched websites of professional regulatory bodies and associations for data on educational and licencing components and policies. Educational and licensing components across countries were synthesized descriptively. RESULTS: A pooled estimate of Cronbach's alpha of 0.55, (95% CI: 0.41, 0.67) was determined for OSCEs. The pooled estimate of Intraclass Correlation Coefficient (ICC) between assessors was 0.77 (95% CI: 0.70, 0.83). The pooled estimate of Pearson Correlation between multiple OSCE stations' scores was 0.27 (95% CI: 0.15, 0.39); and between each station score and the total score was 0.71 (95% CI: 0.61, 0.79). The pooled estimates for kappa Coefficients were 0.75 (95% CI: 0.58, 0.86) and 0.84, (95% CI: 0.72, 0.91) for intra-rater and inter-rater reliability of the standardised patient respectively. From the 17 included countries, Canada (excluding Quebec) was the only country that required both a clinical and written competency exam following graduation from an accredited PT program. Two countries (USA, UAE) required a written competency exam. The remaining 14 countries did not require an additional competency examination after completion of degree requirements from an accredited program. CONCLUSIONS: We found weak evidence that OSCE examinations items are internally consistent when used to assess PTs. Canada (excluding Quebec) is the only country out of 17 implementing a national clinical competency examination for their PT graduates to achieve licensure after completing professional degree requirements.

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)0.035
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.122
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.031
Bibliometrics0.0140.015
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.353
GPT teacher head0.415
Teacher spread0.062 · 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.

Study designSystematic review
DomainMethods
GenreReview

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

Citations30
Published2021
Admission routes3
Has abstractyes

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