Predictors of Leisure Time Physical Activity Among People with Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Most studies of physical activity predictors in people with disability have lacked a guiding theoretical framework. Identifying theory-based predictors is important for developing activity-enhancing strategies. PURPOSE: To use the World Health Organization's International Classification of Functioning, Disability and Health (ICF) framework to identify predictors of leisure time physical activity among people with spinal cord injury (SCI). METHODS: Six hundred ninety-five persons with SCI (M age=47; 76% male) completed measures of Body Functions and Structures, Activities and Participation, Personal Factors, and Environmental Factors at baseline and 6-months. Activity was measured at 6 and 18 months. Logistic and linear regression models were computed to prospectively examine predictors of activity status and activity minutes per day. RESULTS: Models explained 19%-25% of variance in leisure time physical activity. Activities and Participation and Personal Factors were the strongest, most consistent predictors. CONCLUSIONS: The ICF framework shows promise for identifying and conceptualizing predictors of leisure time physical activity in persons with disability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".