Identifying occupational therapy outcome measures supportive of recovery-orientated mental health services in Ireland
Bibliographic record
Abstract
Purpose No occupational therapy outcome measures have been designed specifically for recovery-orientated services.This paper aims to identify occupational therapy outcome measures relevant to mental health practice and assess them against recovery principles adopted by Irish Mental Health Services. Design/methodology/approach A narrative review methodology was used to appraise outcome measures against CHIME recovery principles. Findings A systematic search across 13 databases identified eight well-established outcome measures commonly used within occupational therapy mental health literature. The included outcome measures were appraised using a recovery alignment tool. Practical implications All outcome measures connected to some recovery processes. Those using semi-structured interview formats and notably the Canadian Occupational Performance Measure (COPM) had the strongest alignment to recovery processes. Originality/value This is the first known review which provides some validation that the included outcome measures support recovery processes, yet the measures rely heavily on therapist’s skills for processes to be facilitated. It recommends that ways to better support the process of partnership in occupational therapy mental health outcome measures be explored and further research be undertaken.
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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 | 0.062 | 0.164 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".