Measuring occupational performance and client priorities in the community: The COPM
Bibliographic record
Abstract
The primary aim of this study was to examine changes in clients' occupational performance and satisfaction with their performance within a community trust setting, using the Canadian Occupational Performance Measure (COPM). Given the rapid throughput of clients and the pressure of limited resources, the authors postulated that occupational therapy interventions were focusing on clients' self-care needs as a matter of priority for clients to be independent at home. Therefore, at a time when services are seeking to be increasingly client-focused, the authors' secondary aim was to explore whether self-care needs were also the clients' highest priorities. Fourteen occupational therapists and 62 clients took part in the study. The therapists used the COPM to assess the client; the clients completed the COPM at initial interview and at the end of the intervention. Inferential statistics were then used to ascertain any change over the intervention period. The findings showed a statistically significant change in clients' occupational performance and satisfaction with their performance, in all settings, following occupational therapy. There were notable differences in occupational performance goals between men and women, in that a higher percentage of self-care goals were identified by the men. Self-care goals were the most frequently cited goals in all of the settings.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".