Early childhood aetiology of mental health problems: a longitudinal population‐based study
Bibliographic record
Abstract
BACKGROUND: Mental health problems comprise an international public health issue affecting up to 20% of children and show considerable stability. We aimed to identify child, parenting, and family predictors from infancy in the development of externalising and internalising behaviour problems by age 3 years. METHODS: Design Longitudinal, population-based survey completed by primary caregivers when children were 7, 12, 18, 24 and 36 months old. Participants 733 children sequentially recruited at 6-7 months from routine well-child appointments (August-September 2004) across six socio-economically and culturally diverse government areas in Victoria, Australia; 589 (80%) retained at 3 years. Measures 7 months: sociodemographic characteristics, maternal mental health (Depression Anxiety Stress Scale (DASS)), substance misuse, home violence, social isolation, infant temperament; 12 months: partner relationship, parenting (Parent Behavior Checklist (PBC)); 18, 24 and 36 months: child behaviour (Child Behavior Checklist 1(1/2)-5 (CBCL)), PBC, DASS. RESULTS: Sixty-nine percent of all families attending well-child clinics took part. The consistent and cumulative predictors of externalising behaviours were parent stress and harsh discipline. Predictors of internalising behaviours included small family size, parent distress, and parenting. Twenty-five percent of variation in early externalising behaviour and 17% of variation in early internalising behaviour was explained. CONCLUSIONS: Effective and cost-efficient population approaches to preventing mental health problems early in childhood are urgently needed. Programmes must support parents in reducing personal stress as well as negative parenting practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".