Influence of Sport Participation on Community Integration and Quality of Life: A Comparison Between Sport Participants and Non-Sport Participants With Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: To determine whether community integration and/or quality of life (QoL) among people living with chronic spinal cord injury (SCI) are superior among sport participants vs non-sport participants. STUDY DESIGN: Cross-sectional study. PARTICIPANTS/METHODS: Persons (n=90) living in the community with SCI (ASIA Impairment Scale A-D), level C5 or below, > 15 years of age, >12 months postinjury, and requiring a wheelchair for >1 hours/day were divided into 2 groups based on their self-reported sport participation at interview: sport participants (n=45) and non-sport participants (n 5). RESULTS: Independent-sample t tests revealed that both Community Integration Questionnaire (CIQ) and Reintegration to Normal Living Index (RNL) total mean scores were higher among sport participants vs nonsport participants (P < 0.05). Significant correlation between CIQ and RNL total scores was found for all participants (Pearson correlation coefficients, P < 0.01). Logistic regression analysis revealed that the unadjusted odds ratio of a high CIQ mean score was 4.75 (95% CI 1.7, 13.5) among current sport participants. Similarly, the unadjusted odds ratio of a high RNL score was 7.00 (95% CI 2.3, 21.0) among current sport participants. Regression-adjusted odds ratios of high CIQ and high RNL scores were 1.36 (95% CI 0.09, 1.45) and 0.15 (95% CI 0.04, 0.55), respectively. The odds ratio for pre-SCI sport participation predicting post-SCI sport participation was 3.06 (95% CI 1.23, 7.65). CONCLUSIONS: CIQ and QoL scores were higher among sport participants compared to non-sport participants. There was an association between mean CIQ and RNL scores for both groups. Sport participants were 4.75 and 7.00 times as likely to have high CIQ and QoL scores. Both groups had a similar likelihood of high CIQ and RNL scores after adjusting for important confounders. Individuals who participated in sports prior to SCI were more likely to participate in sports post-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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".