Measurement Properties of the Canadian Occupational Performance Measure: A Systematic Review
Bibliographic record
Abstract
IMPORTANCE: The Canadian Occupational Performance Measure (COPM) is widely used in clinical practice and research. However, the measurement properties of the COPM were not reviewed using rigorous systematic methodology. OBJECTIVE: To evaluate the measurement properties of the COPM. DATA SOURCES: MEDLINE, Web of Science, Scopus, OTseeker, and Cochrane Library. Study Selection and Data Collection: We used the updated COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) Risk of Bias checklist to evaluate the measurement properties of the COPM reported in relevant studies. FINDINGS: Our search identified 35 articles that reported measurement properties for the COPM with samples that differed in age, country, diagnosis, and disease stage. For content validity, the evidence was inconsistent and of low quality; no studies assessed structural validity. For reliability, the internal consistency was indeterminate and of low quality. One study reported indeterminate and very low quality evidence for cross-cultural validity. According to the evidence reported in these studies, the COPM has inconsistent and moderate reliability, construct validity, and responsiveness and insufficient and high-quality evidence for criterion validity. CONCLUSIONS AND RELEVANCE: Our review of the evidence using the COSMIN Risk of Bias checklist indicates that the Canadian Occupational Performance Measure lacks high-quality validation. What This Article Adds: High-quality validation of the Canadian Occupational Performance Measure is lacking. Further examination of its measurement properties using updated relevant guidelines is required.
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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 | 0.056 | 0.258 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.023 | 0.029 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".