Pathways of Intergenerational Risk: Examining the Association Between Maternal Adverse Childhood Experiences and Child Socio-Emotional and Behavioral Concerns at 8 Years of Age
Bibliographic record
Abstract
Support has been found for the intergenerational transmission of risk from maternal adverse childhood experiences (ACEs) to child outcomes. Less research has focused on longitudinal psychosocial pathways that account for this transmission. In the current study, path analysis examined mediating pathways (i.e., maternal adult attachment insecurity, romantic relationship functioning, and maternal anxiety and depression symptoms) in the association between maternal ACEs and internalizing and externalizing concerns among their child at eight years of age. Participants included 1,994 mother-child dyads from a prospective longitudinal cohort sample. Maternal ACEs were significantly associated directly with child internalizing concerns (β = .06, p = .025) and indirectly via both maternal attachment anxiety and avoidance, lower romantic relationship functioning, and depression, (β = .002, p = .006; β = .003, p = .005, respectively). Maternal ACEs were directly associated with child externalizing concerns (β = .06, p = .018) and indirectly via both maternal attachment anxiety and avoidance, lower romantic relationship functioning, and depression, (β = .001, p = .008; β = .002, p = .010, respectively). This study identified several maternal risk factors that have implications for downstream internalizing and externalizing concerns among their children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".