Area deprivation and child psychosocial problems. A national cross-sectional study among school-aged children:
Bibliographic record
Abstract
Background. We examined the association of area deprivation with the occurrence of psychosocial problems among children aged 4-16 in a representative national sample of children based on standardised measures of parent-reported problems and diagnoses made by doctors and nurses working in child healthcare (child health professionals, CHPs). Methods. The study comprised 4480 children aged 4-16 years, eligible for a routine health assessment (response: 90.1 %), in 19 Child Healthcare Services across the Netherlands that routinely provided preventive child healthcare to nearly all school-aged children. Parents completed the Child Behaviour Checklist (CBCL). CHPs examined the child and interviewed parents and child during their routine health assessments. Main outcome measures concerned psychosocial problems as reported by parents (i. e. a clinical score on the CBCL) and as identified by CHPs. Results. Prevalence rates of psychosocial problems were 8.6% for parent-reported problems and 10.1 % for CHP-identified problems. They were much higher in the most deprived third of the areas. Odds ratios (95 % confidence intervals) compared with the least deprived third were 1.93 (1.41-2.64) regarding parent-reported problems and 1.76 (1.30-2.38) regarding CHP-identified problems. Regarding parent reports, associations were slightly stronger for behavioural problems than for emotional problems. Less than a quarter of the area differences could be explained by individual and family characteristics. Conclusions. Child psychosocial problems occur more frequently in deprived areas. Both preventive and curative health services should be better equipped for this concentration of child and adolescent morbidity in deprived areas. © Steinkopff Verlag 2005.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".