The use of aquatic therapy among rehabilitation professionals for individuals with spinal cord injury or disorder
Bibliographic record
Abstract
Context/Objective: Aquatic therapy (AT) has been used to enhance balance and mobility in people with disabilities; however, AT is reported to be underused among people with spinal cord injury or disorder (SCI/D). We aimed to understand the perceptions of AT use by physical therapists (PT), PT assistants (PTA) and kinesiologists (KIN) across Canada for clients with SCI/D.Design/Methods: Individual semi-structured interviews were completed with PT, PTA and KIN (phone or in-person). PT, PTA and KIN who had used AT with at least one client with SCI/D in the past year were eligible. Interview questions queried each participant’s AT setting, AT approaches, and perceived facilitators and barriers to AT implementation for clients with SCI/D. Interviews were audio recorded and transcribed verbatim. Thematic analysis was used to identify themes and subthemes.Results: Six PT (2 male, 4 female), three PTA (female) and 1 KIN (female) participated. The following four themes were identified: (1) multi-system benefits from AT (e.g. from impairment to function, confidence and enjoyment); (2) application of AT (e.g. based on principles of the water); (3) perceived barriers to implementing AT (e.g. pool accessibility, client comorbidities); and (4) water as an enabler to function on land.Conclusions: The participants reported AT was a unique and versatile approach that benefits the multi-dimensional aspects of the health of individuals with SCI/D. They successfully integrated AT into their clinical practice despite the barriers faced by professionals and clients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".