Psychiatric disorders in an urban sample of preschool children
Bibliographic record
Abstract
BACKGROUND: To increase limited epidemiological knowledge of early childhood psychopathology, a study of prevalence estimates and demographic correlates of psychiatric disorders was conducted in a sample of preschool children. METHODS: In a two-stage study, parents of 339 children aged 4-6 years who came for a medical check-up at three primary care centres in Reykjavik were invited to participate. First, the participants were screened with Brigance Screens and the Strengths and Difficulties Questionnaire (SDQ) for parents and teachers. Subsequently, the children were tested with a short version of Wechsler Preschool and Primary Scales of Intelligence - Revised and their parents were interviewed with the Schedule for Affective Disorders and Schizophrenia for School Aged Children Present and Lifetime Version. Weighted prevalence estimates were calculated and logistic regression was used to analyse the association between risk factors and psychiatric disorders. RESULTS: Of those invited to participate, 317 (93.5%) were included in the screening and of those, 131 received a full diagnostic assessment. The final study sample included 151 girls (47.6%) and 166 boys (52.4%) who represented 11.6% of the total birth cohort in Reykjavik. Weighted prevalence of DSM-IV psychiatric disorders was 10.1% (95% CI 6.7-13.5%) and 57/317 or 18.0% (95% CI 13.8-22.2%), including elimination disorders. Anxiety disorders (5.7%) and attention deficit hyperactivity disorder (3.8%) were the most common disorders in this preschool sample. Poor physical health of parents and higher education was associated with DSM-IV psychiatric disorders of the children. SDQ Total Difficulties score was associated with male gender and poor physical health of parents. CONCLUSIONS: This study indicates that psychiatric disorders in preschool children are common and may be correlated with parental health factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".