Economic Evidence in Occupational Therapy: A Rapid Review
Bibliographic record
Abstract
Background. Given the necessity to demonstrate that occupational therapy services are a good use of resources, understanding the state of economic evidence is essential. Purpose. This article presents a rapid review of this evidence. Method. Relevant articles were identified using SCOPUS. Eligible studies included economic analyses of interventions that included occupational therapy and were published in English or French after 1999. The findings were synthesized and then appraised using the Quality of Health Economic Studies (QHES) template. Results. The 135 studies identified were conducted in 23 countries and most commonly: with adults/older adults; in home, inpatient, outpatient, and rehabilitation centre settings; with individuals with cerebrovascular accident and orthopaedic conditions. The specific occupational therapy role was specified in 60% of the studies. Approximately 50% of the investigations used a randomized controlled trial and a cost effectiveness analysis, and 40% used a societal economic perspective. The average QHES score was 74.4/100 (reasonable quality). Implications. This review has revealed areas of relative strength, some important gaps, and potential directions for future action. Economic evidence that specifically identifies the occupational therapy contribution must continue to be gathered. The profession should consider the strategic alignment of its economic research (e.g., home care) to maximize its impact.
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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 | 0.016 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".