Objective structured clinical examination in physiotherapy teaching: a systematic review
Bibliographic record
Abstract
Abstract Introduction: Problems related to the clinical abilities of physiotherapy students are not always identified throughout the educational process and might only be observed when these future professionals have to treat patients. The Objective Structured Clinical Examination (OSCE) includes a problematization approach and can be used in Health Sciences teaching to help this identification before internship practices. However, there are few studies on its use in Physiotherapy. Objective: To gather evidence of the OSCE use to evaluate clinical abilities in Physiotherapy teaching. Method: Articles published from 2000 to 2016 were surveyed in the Biblioteca Virtual em Saúde (BVS) (Virtual Health Library), Centro Latino-Americano e do Caribe de Informação em Ciências da Saúde (BIREME) (Latin-American and Caribbean Health Sciences Information Center), PubMed, Scielo and Web of Science, using the descriptors “educational assessment”, “assessment methods”, “objective structured clinical examination”, “clinical competence”, “professional competence”, “clinical skills”, “student competence”, “student skills”, “physiotherapy” and the Booleans “OR” and “AND”. Results: The initial number of identified publications was 3,242. From these, seven were included in this review. Two studies were developed in Brazil, four in Australia and one in Canada. The studies were scored 7 to 12 regarding methodologic quality, and 1B and 2B regarding scientific evidence. Conclusion: Students’ clinical abilities were grouped into three classes: cognitive, psychomotor and affective, and four studies described their use. There is very little evidence of the use of OSCE, but the instrument can be applied to evaluate skills and competences in Physiotherapy teaching.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".