Effect of a 6-Month Chronic Disease Management Program on the Physical Literacy of Children With Congenital Heart Disease: A CHAMPS Cohort Study
Bibliographic record
Abstract
Background: Children with congenital heart disease (CHD) have sequelae related to their heart defect that can affect their lifelong health. Physical literacy development is one way to improve their health because it provides them the competence and confidence to engage in physical activity; however, it may be impaired in children with CHD. Therefore, we sought to determine the effect of a 6-month chronic disease management program on physical literacy development of children with CHD. Methods: Thirteen children with CHD participated in the program and were age and sex matched to 12 typically developing peers (TDPs) who served as the control population. All participants had their motor competence (PLAYfun), confidence (PLAYself), and parental perception of the child's physical literacy (PLAYparent) measured before and after the program. A 2 × 2 between-within factorial multivariate analysis of covariance measured the effectiveness of the program while controlling for age, sex, height, weight, maturity, and self-reported physical activity. Results: 0.05). Conclusions: Children with CHD had impaired motor competence at baseline, and although the program did result in an improvement in the locomotor domain, it was not able to mitigate all differences in physical literacy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".