Factors Affecting Standing and Walking Outcomes for Individuals With Spinal Cord Injury During In-Patient Rehabilitation: A Qualitative Study on the Perspectives of Physiotherapists
Bibliographic record
Abstract
Purpose: Standing and walking outcomes following spinal cord injury (SCI) vary across rehabilitation centres and therapists. Much of this variation has been attributed to individual patient characteristics. However, insight from frontline health care providers, as well as exploration of comprehensive contributing factors, have been under-investigated. This study aimed to explore the perspectives of physiotherapists on factors affecting standing and walking recovery and outcomes during in-patient SCI rehabilitation. Method: An exploratory qualitative study was conducted using semi-structured focus group interviews. Our qualitative approach was grounded in interpretive description and used reflexive thematic analysis. Results: Ten physiotherapy representatives of seven different in-patient SCI rehabilitation sites across Canada participated. Dosage, organizational culture, length of stay, staffing, equipment, relationships, atmosphere, and mindset were the key factors identified. Our findings also highlight that how factors impact a site may differ, but perspectives on which factors influence standing and walking outcomes were similar. Factors beyond the individual and the relationship of these factors on training dosage were emphasized. Conclusion: Future work is needed to better understand the role of institutional culture, to design and implement potential ways to address key contributing factors, and to evaluate if such initiatives lead to improvements in standing and walking outcomes.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".