Interrater Reliability of the Canadian Occupational Performance Measure (COPM) Within Geriatric Rehabilitation
Bibliographic record
Abstract
Background. The Canadian Occupational Performance Measure (COPM) is used by occupational therapists (OTs) to identify problems in the occupational performance of patients, and its use is currently expanding within geriatric rehabilitation (GR). However, due to the complexity of the target group concerns have been raised regarding consistency of administration between OTs. Purpose. To assess the interrater reliability of the COPM in routine GR practice. Method. In two GR wards with patients aged 65 years and older, two different OTs administered the COPM to the same patient. We calculated the overlap in prioritized occupational problems, as well as the intraclass correlation coefficients (ICC) of the COPM-Performance and COPM-Satisfaction scores. Findings. Twenty-six participants, mean age 79 (SD 7.6) with largely orthopaedic and neurological diagnoses, were assessed twice within 2–5 days (mean 3, SD 0.9). We identified a total of 355 problems, mostly in the domain selfcare ( N = 222). For the 112 prioritized problems, two OTs had a 65% overlap. ICC values for COPM-Performance and COPM-Satisfaction were 0.566 and 0.567, respectively. Conclusion. In GR, the COPM has moderate IRR and a moderate percentage of overlapping prioritized occupational performance problems. Therapists should be aware of the potential scoring problem within GR and should invest in training.
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 | 0.036 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".