Poster (Knowledge Generation) ID 1985172
Bibliographic record
Abstract
Background Rehabilitation approaches after Spinal Cord Injury (SCI) differ across rehabilitation centres and between therapists. Differences may be influenced by factors such as therapeutic approaches, equipment availability, training provided for therapists, or demographics of admitted patients. A measure of physical function that is widely used within Canadian rehabilitation centres is the Standing and Walking Assessment Tool (SWAT). It is not clear what factors or therapeutic approaches lead to optimal standing and walking outcomes in the SCI population. Objectives To explore the perspectives of physio-therapists on factors that affect standing and walking outcomes in inpatient SCI rehabilitation. Methods Three focus groups were conducted with nine physiotherapists representing seven inpatient rehabilitation centres across Canada to provide their perspectives on current practices and to gain in-depth insights into centre-specific factors that may influence standing and walking outcomes. Thematic analysis was used to analyze the focus group data. Results Thematic analysis revealed that high treatment intensity and frequency are needed for optimal standing and walking outcomes. Physiotherapists emphasized that appropriate length of stay was essential to deliver an effective treatment plan. They noted, however, that there is pressure to discharge patients quickly leading to shorter length of stays and a perceived compromise in outcomes. Physiotherapists emphasized the importance of building rapport with patients, creating an exciting therapeutic environment, and the availability of enough staff for optimal recovery. Conclusions The findings of this qualitative study will inform the implementation and development of opportunities to optimize standing and walking outcomes across rehabilitation centres in Canada.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.890 | 0.559 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".