Socioemotional and behavioural difficulties in children with chronic physical conditions: analysis of the Longitudinal Study of Australian Children
Bibliographic record
Abstract
OBJECTIVES: To examine the prevalence of socioemotional and behavioural difficulties (SEBDs) in children with chronic physical conditions (CPCs) and to analyse how this prevalence varied with the type and number of CPCs and the age of the child. DESIGN: Cross-sectional study of a secondary data analysis of the Longitudinal Study of Australian Children. SETTING: An Australian nationally representative sample of general population of children. PARTICIPANTS: 15 610 children-waves aged 6-14 years. INTERVENTION/EXPOSURE: Children reported to have at least 1 of the 21 CPCs by their parents. MAIN OUTCOME MEASURES: Clinically relevant SEBDs were defined using standardised cut-offs of the parent-administered Strengths and Difficulties Questionnaire. RESULTS: Children with a CPC have significantly increased odds of total, internalising and externalising SEBDs than those without (total SEBDs, adjusted odds rartio or OR 3.13, 95% CI 2.52 to 3.89), controlling for sex, age, socioeconomic status and parental mental health status. The highest prevalence of total SEBDs was found in children with chronic fatigue (43.8%), epilepsy (33.8%) and day wetting (31.6%). An increasing number of comorbid CPCs was associated with a rising prevalence of SEBDs. On average, 24.2% of children with at least four CPCs had SEBDs. These children had 8.83-fold increased odds (95% CI 6.9 to 11.31) of total SEBDs compared with children without a CPC. Age was positively related to the odds of SEBDs. CONCLUSION: Children with a CPC have a significantly increased risk of having SEBDs than those without. These findings highlight the need for routine assessment and integrated intervention for SEBDs among children with CPCs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".