Factors Related to Physical Activity in Adults with Cerebral Palsy May Differ for Walkers and Nonwalkers
Bibliographic record
Abstract
OBJECTIVE: To explore what factors besides walking ability, e.g., additional health problems or complications, general health, and sociodemographic status, may be related to physical activity in adults with cerebral palsy. DESIGN: We administered a questionnaire regarding sociodemographic and health-related factors of potential relevance to physical activity to 66 men (20-41 yrs) and 66 women (18-39 yrs) with various types of cerebral palsy. Data were analyzed using logistic regression. RESULTS: Use of walking as the primary means of self-transport (walking ability) was associated with a higher odds of being physically active (odds ratio = 3.75; P = 0.002). Among those who could walk, being younger and having a positive perception of health were also associated with a higher odds of being active (odds ratios of 2.6 and 3.0, respectively). This was not true among nonwalkers. For individuals who walked, inactivity was associated with an increase in the severity (during the past 3 yrs) of several additional health problems or complications. For the nonwalkers, inactivity was most clearly associated with perceived range-of-motion limitations. CONCLUSIONS: Among adults with cerebral palsy, the ability to walk, as expected, is associated with being physically active. The factors additionally related to physical activity differ between walkers and nonwalkers.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".