The effects of aquatic therapy on mobility of individuals with neurological diseases: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To summarize evidence on the effects of aquatic therapy on mobility in individuals with neurological diseases. DATA SOURCES: MEDLINE, EMBASE, PsycInfo, CENTRAL, CINAHL, SPORTDiscus, PEDro, PsycBITE and OT Seeker were searched from inception to 15 September 2014. Hand-searching of reference lists was performed in the selected studies. REVIEW METHODS: The search included randomized controlled trials and quasi-experimental studies that investigated the use of aquatic therapy and its effect on mobility of adults with neurological diseases. One reviewer screened titles and abstracts of retrieved studies from the search strategy. Two reviewers independently examined the full texts and conducted the study selection, data extraction and quality assessment. A narrative synthesis of data was applied to summarize information from included studies. The Downs and Black Scale was used to assess methodological quality. RESULTS: A total of 116 articles were obtained for full text eligibility. Twenty studies met the specified inclusion criteria: four Randomized Controlled Trials (RCTs), four non-randomized studies and 12 before-and-after tests. Two RCTs (30 patients with stroke in the aquatic therapy groups), three non-randomized studies and three before-and-after studies showed "fair" evidence that aquatic therapy increases dynamic balance in participants with some neurological disorders. One RCT (seven patients with stroke in the aquatic therapy group) and two before-and-after tests (20 patients with multiple sclerosis) demonstrated "fair" evidence on improvement of gait speed after aquatic therapy. CONCLUSION: Our synthesis showed "fair" evidence supporting the use of aquatic therapy to improve dynamic balance and gait speed in adults with certain neurological conditions.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".