Investigating adaptive sport participation for adults aged 50 years or older with spinal cord injury or disease: A descriptive cross-sectional survey
Bibliographic record
Abstract
CONTEXT: Spinal cord injury or disease (SCI/D) can lead to health challenges that are exacerbated with aging. Adaptive sport is understood to provide health benefits for the SCI/D population. Prior literature investigating adaptive sport in this population pertains to adults with SCI/D who are <50 years of age. However, most Canadians with SCI/D are >50 years of age. OBJECTIVES: This study aimed to: (1) Compare demographics of those who do and do not participate in adaptive sport; (2) Describe the characteristics of adaptive sport that adults aged ≥50 years with SCI/D participate in; and (3) Identify barriers and facilitators to adaptive sport participation in this age group. METHODS: This descriptive, cross-sectional survey was carried out using an online survey. Analytical statistics were used to address objective one, while descriptive statistics were employed for objectives two and three. PARTICIPANTS: Responses from 72 adults aged ≥50 years, residing in Canada, living with a SCI/D for >6 months were included in the analysis. RESULTS: < 0.05). Adaptive sport participants most commonly played individual sports at the recreational level. Common barriers pertained to physical capacity, travel, and COVID-19; common facilitators included social support, desire to improve health, and having friends/peers who also participate. CONCLUSION: Future research should investigate strategies to enhance facilitators and mitigate barriers to adaptive sport participation in order to improve access.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".