Actual vs best practice for families post-stroke according to three rehabilitation disciplines
Bibliographic record
Abstract
OBJECTIVE: To investigate occupational therapists', physiotherapists' and speech language pathologists' family-related rehabilitation practice post-stroke and its association with clinician and environmental variables. METHODS: A Canadian cross-sectional telephone survey was conducted on 1755 clinicians. Three case studies describing typical patients after stroke receiving acute care, in-patient rehabilitation, or community rehabilitation, and including specific descriptors regarding family stress and concern, were used to elicit information on patient management. RESULTS: One-third of the sample identified a family-related problem and offered a related intervention, but only 12/1755 clinicians indicated that they would typically use a standardized assessment of family functioning. Working in the community out-patient setting was associated (OR 9.16), whereas working in a rehabilitation in-patient setting was negatively associated (OR 0.58) with being a problem identifier, the reference group being acute care. Being a PT (OR 0.53) or an SLP (OR 0.49) vs an OT was negatively associated with being a problem identifier, whereas being older (OR 1.02 ) or working in Ontario (OR 1.58) was associated with being a problem identifier. To work in a community out-patient setting (OR 2.43), being older clinicians (OR 1.02) or not perceiving their work environment being supportive of an on-going professional learning (OR 1.72) was associated with being an intervention user,whereas being a PT (OR 0.50) was negatively associated with being a user. CONCLUSION: For these 3 disciplines, the prevalence of a family-related focus is low post-stroke. Given the increasing evidence regarding the effectiveness of family-related interventions on stroke outcomes, it is imperative that best practice is implemented.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".