A national survey of evidence-based stroke rehabilitation intervention use in clinical practice among Canadian occupational therapists
Bibliographic record
Abstract
BACKGROUND: More than 1,000 randomized controlled trials have been published examining the effectiveness of stroke rehabilitation interventions. OBJECTIVE: The objective of this study was to explore the use and non-use of evidence-based stroke rehabilitation interventions in clinical practice among Occupational Therapists across various stroke rehabilitation settings in Canada. METHODS: Participants were recruited from medical centres providing rehabilitation to stroke patients in each of the ten provinces across Canada (January-July 2021). Adult (18 + years) Occupational Therapists who provide direct rehabilitative care to individuals after a stroke completed a survey in either English or French. Therapists rated their awareness, use, and reasons for non-use of stroke rehabilitation interventions. RESULTS: 127 therapists (female = 89.8%), largely from Ontario or Quebec (62.2%) were included; most worked full-time (80.3%) in moderate-large (86.1%) cities. The greatest use of interventions were those applied to the body peripherally, without a technological component. Few individuals were aware of interventions applied to the brain (priming or stimulating) with a technological component, and they were rarely, if ever, used. CONCLUSION: Significant efforts should be made to increase the awareness of interventions which are supported by strong evidence through knowledge translation and implementation initiatives, particularly for those with a technological component.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".