Enhancing a Client-Centred Practice with the Canadian Occupational Performance Measure
Bibliographic record
Abstract
Background . The active participation of clients is an important aspect of rehabilitation quality as conceptualized in client-centred practice (CCP). A recommended outcome measure for enhancing CCP is the Canadian Occupational Performance Measure (COPM). However, the relationship between COPM use and CCP enhancement has not been documented. Aim . The aim of this study was to examine whether the use of the COPM enhanced CCP. Methods . We performed a scoping review in five steps: (1) identifying a search strategy with inclusion and exclusion criteria; (2) screening relevant databases for published and unpublished studies by using selected keywords and by manually scrutinizing reference lists; (3) agreeing on eligible papers between authors in terms of inclusion and exclusion criteria; (4) charting included data; and (5) analysing data using qualitative content analysis. Results . Twelve studies were included in the review. The results indicated enhanced CCP in two themes when using the COPM. These themes appeared to influence each other; therefore, the first theme, Conditions for enhancing CCP when using the COPM , represented the circumstances needed for the second theme, Enhancing CCP when using the COPM , to be fulfilled. Conclusion. The use of the COPM seems to enhance CCP if certain conditions are present.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".