Gross Motor Capability and Performance of Mobility in Children With Cerebral Palsy: A Comparison Across Home, School, and Outdoors/Community Settings
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Mobility of children with cerebral palsy (CP) has generally been examined in terms of capability (what a child can do) in a controlled environment, rather than performance (what a child does do) in everyday settings. The purpose of this study was to compare gross motor capability and performance across environmental settings in children with CP. SUBJECTS: The subjects were 307 children with CP, aged 6 to 12 years, who were randomly selected across Ontario, Canada. METHODS: Children were grouped by capability (the highest of 3 items achieved on the Gross Motor Function Measure). Performance was measured via a parent-completed questionnaire on usual mobility methods in the home, at school, and in the outdoors or community. RESULTS: There were statistically significant differences in performance across settings for children in all capability groups. Children who were capable of crawling performed crawling more at home than at school or in the outdoors or community. Children who were capable of walking with support performed walking with support more at school than in the outdoors or community. Children who were capable of walking alone performed walking alone more at home than at school or in the outdoors or community, and more at school than in the outdoors or community. DISCUSSION AND CONCLUSION: The results provide evidence that children with CP with similar capability demonstrate differences in performance across settings. The results suggest that physical therapists should examine performance in the settings that are important to the child's daily life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".