The long reach of adversity: Intermediary pathways from maternal adverse childhood experiences to child socio‐emotional and cognitive outcomes
Bibliographic record
Abstract
BACKGROUND: This longitudinal study with multi-informant (maternal, paternal, and experimenter) and multimethod (questionnaires, behavioral observations, and standardized assessments) data tests an intergenerational model from mothers' adverse childhood experiences (ACEs) to their children's socio-emotional and cognitive outcomes. METHODS: Participants were 501 children (50.7% male) and caregivers (56.5% white) followed from child age 2 months to 5 years. Mothers reported on their ACEs, as well as their postnatal socio-economic status (SES), marital conflict, and depressive symptoms. Observers rated maternal sensitivity using validated coding systems. Partners' history of childhood conduct problems and children's emotional and conduct problems were rated by mothers and fathers, and cognition was assessed by experimenters using standardized assessments. RESULTS: Maternal ACEs score was associated with children's socio-emotional and cognitive outcomes through unique intermediary pathways. Specifically, maternal ACEs were related to child emotion problems through SES, paternal history of conduct problems, and maternal depression. Maternal ACEs to child conduct problems operated via SES, paternal history of conduct problems, and marital conflict. Maternal ACEs to child cognitive skills operated through SES and maternal sensitivity. CONCLUSIONS: Maternal ACEs, economic stress, and paternal history of conduct problems may collectively strain families, diverting caregiver attention and resources, which may impact childrearing and children's development. To effectively address root causes of intergenerational risks, it is critical to advocate for resources and supports that mitigate these hardship conditions. In addition, interventions that target modifiable individual and family factors may hold the greatest promise for breaking cycles of generational risk and promoting healthier outcomes for children and families.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".