Baby, it's cold outside: The influence of season on participation in leisure time physical activity for people with spinal cord injury (SCI)
Bibliographic record
Abstract
Seasonal variation affects participation in leisure time physical activity (LTPA). Among people with spinal cord injury, extreme weather conditions present additional environmental barriers to LTPA. The objective of this study is to estimate the influence of season on the number of minutes people with SCI spend engaged in specific types of LTPA. Participants included 696 individuals (76% men, M age =46.81±13.41, M years-post-injury =15.19±11.10) with SCI interviewed about time spent in LTPA at two time points, which spanned two seasons. Between group differences for the baseline level of LTPA were assessed in a regression analysis. Season marginally predicted the total moderate/heavy intensity LTPA, ?=0.12, p=0.06. Season was a significant predictor of moderate/heavy intensity exercise, ?=0.14, p=0.03, but not sport, ? s =0.01, p=0.86. Individuals interviewed in the summer exercised more than those interviewed in the winter, even when controlling for age, sex, and injury status. Within person differences across seasons were assessed using a repeated-measures ANCOVA controlling for age, sex, and injury status. The main effect of season was significant for total LTPA, F(3,695)=3.00; p=0.03 and specifically exercise, F(3,695)=3.85; p=0.01, but not sport, F(3,695)=0.59; p=0.63. Participants exercised more in the summer than in the winter. Evidently, effort should be placed on promoting sport and providing support for exercise during winter months.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".