Longitudinal Trajectories and Reference Percentiles for Participation in Family and Recreational Activities of Children with Cerebral Palsy
Bibliographic record
Abstract
AIM: To create longitudinal trajectories and reference percentiles for frequency of participation in family and recreational activities for children with cerebral palsy (CP) by Gross Motor Function Classification System (GMFCS) level. METHODS: 708 children with CP 18-months to 12-years of age and their families participated in two to five assessments using the GMFCS and Child Engagement in Daily Life Measure. Data were analyzed using mixed-effects models and quantile regression. RESULTS: Longitudinal trajectories depict the relatively stable level of frequency of participation with considerable individual variability. Average change in the frequency of participation scores of children from 2-12 years of age by GMFCS level varied from 3.7 (GMFCS level I) to - 9.0 points (GMFCS level V). A system to interpret the magnitude of change in percentiles over time is presented. CONCLUSIONS: Longitudinal trajectories and reference percentiles can inform therapists and families for collaboratively designing services and monitoring performance to support children's participation in family and recreational activities.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".