The Scientific Rigor of the Objective Structured Examination for Competency Assessment in Health Sciences Education: A Systematic Review
Bibliographic record
Abstract
Background and Purpose. The objective structured clinical examination (OSCE) is widely used as an assessment of competency in health sciences education. The aim of our systematic review was to appraise the scientific rigor of the OSCE as a competency-based assessment in health sciences education, including physical therapy. Methods. Our search was performed in 6 databases—Ovid MEDLINE(R), CINAHL, EMBASE, APA PsycINFO, ERIC, and Web of Science—to identify original data evaluating the OSCE in programs of education in physical therapy and related health sciences disciplines. Data were extracted as per the Utility Model to evaluate the validity, educational impact, reliability, acceptability, and costs of the OSCE in these programs. Results. The search identified 106 records, with 13 studies meeting our eligibility criteria. The OSCE is distinct from traditional clinical assessments, with low-to-fair concurrent validity between the 2 assessment types. The OSCE was used for instructional design, namely, curriculum development and alignment, and for educational practice, namely, making decisions on students' readiness for practice. Limitations of the OSCE include poor-to-low validity to predict practice readiness and low-to-acceptable reliability, with student-specific, domain-specific, and examiner-specific effects on outcomes identified. Strategies were provided which could improve the scientific rigor of the OSCE. Discussion and Conclusion. Based on current evidence, the scientific rigor of the OSCE may be insufficient to support its use to make academic decisions on students' standing in health sciences programs, including physical therapy, and readiness for clinical practice, with confidence. However, the OSCE can play an important role in instructional design and in guiding student learning. Protocol registration: PROSPERO, ID 162338.
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 | 0.166 | 0.507 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".