Child maltreatment and mental health problems in adulthood: birth cohort study
Bibliographic record
Abstract
BACKGROUND: Retrospective studies have shown a high association between child abuse and subsequent psychiatric morbidity. Prospective studies are rarer.AimsTo examine, using a prospective record-linkage analysis, whether substantiated child maltreatment is associated with adverse psychological outcomes in early adulthood. METHOD: The participants were 3778 mother and child pairs enrolled in a population-based birth cohort study in Brisbane, Australia. Exposure to suspected child maltreatment was measured by linkage with state child protection agency data. The primary outcomes were the internalising and externalising scales of the Youth Self-Report and the Centre for Epidemiological Studies-Depression scales (CES-D) at approximately 21 years of age. A subset completed the Composite International Diagnostic Interview-Auto version (CIDI-Auto). RESULTS: In total, 171 (4.5%) participants had a history of substantiated child maltreatment, most commonly emotional abuse (n = 91), followed by physical abuse (n = 78), neglect (n = 73) and sexual abuse (n = 54). After adjustment for potential confounders, depressive symptoms on the CES-D, as well as internalising and externalising behaviours were strongly associated with substantiated abuse in all forms, except sexual abuse. The results for the subset of the sample who completed the CIDI-Auto were less clear. Anxiety, especially post-traumatic stress disorder, showed the strongest association whereas the findings for depressive disorder were equivocal. However, across all diagnostic categories, emotional abuse and neglect, as well as multiple forms of abuse, showed a consistent association. CONCLUSIONS: Child maltreatment, particularly neglect and emotional abuse, has serious adverse effects on early adult mental health. These two warrant the attention given to other forms of child maltreatment. Children experiencing more than one type of maltreatment are at particular risk.Declaration of interestNone.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".