Water-based therapeutic exercise in stroke: a scoping review
Bibliographic record
Abstract
PURPOSE: To (1) describe the state of the literature on water-based therapeutic exercise (WBTE) for people living with stroke, (2) describe the content and structure of interventions, (3) summarize the effects of interventions described in the literature, and (4) identify gaps in the literature limiting application and implementation. MATERIALS AND METHODS: Scoping review methodology described by Arksey and O'Malley (2005) and Levac et al. (2010). Electronic databases were searched for articles with eligibility criteria including: (1) adult stroke survivors (18 years or older) of any type (ischemic/hemorrhagic) or stage (acute/chronic) in any setting, and (2) the study intervention involved WBTE to address a post-stroke deficit. RESULTS: 40 articles were included in this review. Five trials had a treatment control, 20 had an active comparison. Calculated intervention effect sizes demonstrated a strong effect of WBTE on balance and gait related outcomes in 80% of controlled and comparison trials. CONCLUSIONS: This scoping review highlights common parameters of WBTE interventions and provides an inventory of the differences in the treatment approaches utilized in this population. Opportunities for future work include the development of a standardized treatment protocol, qualitative or mixed methodology research, and greater inclusion of more individuals with more severe stroke-related impairments. IMPLICATIONS FOR REHABILITATIONWater-based therapeutic exercise is an approach that may allow stroke survivors to carry out challenging activities in a safe and accessible environment.Water-based interventions for stroke survivors appear to have a beneficial impact on walking and balance.Given that an aquatic environment offers an opportunity for individuals with more significant physical impairments to carry out early practice of walking and balance related tasks, clinicians should explore the feasibility and effectiveness for this subset of stroke survivors.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".