Comparison of the prevalence and impact of health problems of pre‐school children with and without cerebral palsy
Bibliographic record
Abstract
BACKGROUND: The range of health problems associated with children with cerebral palsy (CP) is well documented in the literature; however, the existing data are often either reported for samples of children with all types of CP, or stratified by typology of motor disorder, rather than using the Gross Motor Function Classification System (GMFCS), which has been shown to be the most reliable way of classifying children with CP. Furthermore, availability of research on pre-school-aged children (under 5 years) is sparse. The aim of this study is to compare the prevalence and impact of health problems in pre-school children with and without CP, stratified by the GMFCS. METHODS: Parents of 430 pre-school-aged children with CP (243 boys, 187 girls; mean age = 3 years 2 months, SD = 11 months) and 107 typically developing (TD) children (56 boys, 51 girls; mean age = 3 years 4 months, SD = 11 months) participated. Using the consensus definition of CP and the World Health Organization's International Classification of Functioning, Disability and Health, a parent survey was developed to assess the prevalence and impact of 16 health problems. The measure demonstrates good test-retest reliability (ICC > 0.80) and discriminant validity across GMFCS levels (P < 0.001). RESULTS: Both the prevalence and impact of health problems is greater in children with CP compared with TD children (P < 0.001). The number and impact of health problems increase with ascending GMFCS level (P ≤ 0.01), except for the impact of health problems between groups GMFCS I and GMFCS II/III (P= 0.19). Children with CP have an average of between 3.4 and 6.7 health problems, compared with fewer than one in TD children. CONCLUSIONS: Service providers working with pre-school-aged children with CP need to consider health problems and their impact when planning care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".