Improving life after stroke needs global efforts to implement evidence-based physical activity pathways
Bibliographic record
Abstract
There is an urgent need to improve life after stroke across the world-especially in low-income countries-through methods that are effective, equitable and sustainable. This paper highlights physical activity (PA) as a prime candidate for implementation. PA reduces modifiable risk factors for first and recurrent stroke and improves function and activity during rehabilitation and following discharge. Preliminary evidence also indicates PA is cost-effective. This compelling evidence urgently needs to be translated into seamless pathways to enable stroke survivors across the world to engage in a more active lifestyle. Although more quality research is needed-particularly on how to optimize uptake and maintenance of PA-this should not delay implementation of high-quality evidence already available. This paper shares examples of best practice service models from low-, middle-, and high-income countries around the world. The authors call for a concerted effort to implement high-quality PA services to improve life after stroke for all.
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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 | 0.044 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".