Associations of prenatal stress with 5-year-old children’s executive function in a low socioeconomic status population
Bibliographic record
Abstract
Prenatal stress has a significant, but small, negative effect on children's executive function (EF) in middle and high socioeconomic status (SES) households. Importantly, rates and severity of prenatal stress are higher and protective factors are reduced in lower SES households, suggesting prenatal stress may be particularly detrimental for children's EF in this population. This study examined whether prenatal stress was linked to 5-year-old's EF in a predominantly low SES sample and child sex moderated this association, as males may be more vulnerable to adverse prenatal experiences. Participants were 132 mother-child dyads drawn from a prospective prenatal cohort. Mothers reported on their depression symptoms, trait anxiety, perceived stress, everyday discrimination, and sleep quality at enrollment and once each trimester, to form a composite prenatal stress measure. Children's EF was assessed at age 5 years using the parent-report Behavior Rating Inventory of Executive Function - Preschool (BRIEF-P) Global Executive Composite subscale and neuropsychological tasks completed by the children. Mixed models revealed higher prenatal stress was associated with lower BRIEF-P scores, indicating better EF, for females only. Higher prenatal stress was associated with lower performance on neuropsychological EF measures for both males and females. Results add to the limited evidence about prenatal stress effects on children's EF in low SES households.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".