Maternal Adverse Childhood Experiences and Infant Development
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To examine the prenatal and postnatal mechanisms by which maternal adverse childhood experiences (ACEs) predict the early development of their offspring, specifically via biological (maternal health risk in pregnancy, infant health risk at birth) and psychosocial risk (maternal stress during and after pregnancy, as well as hostile behavior in early infancy). METHODS: Participants were 1994 women (mean age = 31 years) and their infants, who were recruited in pregnancy as part of a prospective longitudinal cohort from 2008 to 2010. Pregnant women completed self-report questionnaires in pregnancy and postpartum related to psychosocial risk and a questionnaire about hostile behavior when their infant was 4 months of age. Health risk in pregnancy and infant health risk at birth were obtained from health records. Mothers completed the Ages and Stages Questionnaire when infants were 12 months of age. RESULTS: Path analysis revealed that the association between maternal ACEs and infant development outcomes at 12 months operated through 2 indirect pathways: biological health risk (pregnancy health risk and infant health risk at birth) and psychosocial risk (maternal psychosocial risk in pregnancy and maternal hostile behavior in infancy). CONCLUSIONS: Psychosocial risks in pregnancy, but not in early infancy, contribute to the transmission of vulnerability from maternal ACEs to child development outcomes in infancy via maternal behavior. Maternal health risk in pregnancy indirectly confers risk from maternal ACEs to child development outcomes at 12 months of age through infant health risk. Maternal health and psychosocial well-being in pregnancy may be key targets for intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 it