The impact of sport participation for individuals with spinal cord injury: A scoping review
Bibliographic record
Abstract
BACKGROUND: Spinal cord injury (SCI) leads to various physical, psychological, and social challenges. Sport is a holistic physical activity that may target these challenges. No literature systematically summarizes the overall impact of sport participation for those with SCI. OBJECTIVE: To comprehensively report the findings of quantitative studies investigating the impact of sport on the physical, psychological, and social health of individuals with SCI. METHODS: Six databases were searched: APA PsycInfo, CINAHL, Embase, Emcare, Ovid Medline, and PubMed (non-Medline). Studies were included if (a) participants were adults with SCI for ≥12 months, (b) outcomes resulting from ≥3 months of sport participation were investigated, (c) sport occurred in the community setting, and (d) comparisons of sport and non-sport conditions were analyzed. Details regarding study characteristics, participants, sport(s), and outcomes were extracted. Methodological quality was assessed using the Modified Downs and Black checklist. RESULTS: Forty-nine studies were included. Study quality ranged from poor to moderate. Sport participation showed favourable results for outcomes including function, quality of life, and community integration. Mixed results were found for outcomes including cardiac function, depressive symptoms, and employment. No significant associations were found for postural control, resilience, and education. CONCLUSIONS: The review findings suggest sport may be a promising intervention for addressing some challenges associated with SCI.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".