Measuring Professional Behaviour in Canadian Physical Therapy Students' Objective Structured Clinical Examinations: An Environmental Scan
Bibliographic record
Abstract
PURPOSE: To identify professional behaviours measured in objective structured clinical examinations (OSCEs) by Canadian university physical therapy (PT) programs. METHOD: A cross-sectional telephone survey was conducted to review current practice and determine which OSCE items Canadian PT programs are using to measure PT students' professional behaviours. Telephone interviews using semi-structured questions were conducted with individual instructors responsible for courses that included an OSCE as part of the assessment component. RESULTS: Nine PT programmes agreed to take part in the study, and all reported conducting at least one OSCE. The number and characteristics of OSCEs varied both within and across programs. Participants identified 31 professional behaviour items for use in an OSCE; these items clustered into four categories: communication (n=14), respect (n=10), patient safety (n=4), and physical therapists' characteristics (n=3). CONCLUSIONS: All Canadian entry-level PT programmes surveyed assess professional behaviours in OSCE-type examinations; however, the content and style of assessment is variable. The local environment should be considered when determining what professional behaviours are appropriate to assess in the OSCE context in individual programmes.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".