Individualized Outcome Measures: A Review of the Literature
Bibliographic record
Abstract
The client-centred nature of occupational therapy acknowledges the individual as the central element of treatment. This philosophy, however, challenges the therapist to choose an outcome measure that is capable of reflecting this individualized perspective. Recent papers published in the rehabilitation literature have reported on the increased responsiveness of such measures over traditional self-report questionnaires. Although the need for a comprehensive review of individualized outcome measures has been identified in the literature, none exists to date. The purpose of this paper is to review six individualized outcome measures that have been identified in the rehabilitation and psychology literature. The measures include: the Canadian Occupational Performance Measure, the Assessment of Motor and Process Skills, McMaster (MAC) Toronto Arthritis, Goal Attainment Scaling, Target Complaints and the Patient Specific Functional Scale. The reliability, validity, responsiveness and clinical utility of each outcome measure was examined and critiqued. Each tool, to a varying degree, met the description of a standardized, client-centred outcome measure.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".