Maternal Prenatal Anxiety and Children’s Externalizing and Internalizing Behavioral Problems: The Moderating Roles of Maternal-Child Attachment Security and Child Sex
Bibliographic record
Abstract
BACKGROUND: Prenatal anxiety is associated with child behavioral problems. Prenatal anxiety is predictive of postnatal anxiety which can interfere with the security of maternal-child attachment and further raise the risk of child behavior problems. Secure maternal-child attachment is essential for optimal emotional health. Sex influences the type of behavior problem experienced. There is a gap in understanding whether attachment security and the sex of the child can moderate association between prenatal anxiety and children's behavioral problems. PURPOSE: To examine the association between prenatal anxiety and child behavioral problems and to test the moderating effects of attachment security and child sex on the association between prenatal anxiety and child behavioral problems. METHODS: Secondary analysis of data from 182 mothers and their children, enrolled in the Alberta Pregnancy Outcomes and Nutrition Study using Hayes' (2013) conditional process modeling. RESULTS: = 0.01) behaviors only in children with an insecure style of attachment. Child sex did not moderate the association between prenatal anxiety and children's behavioral problems. CONCLUSIONS: Attachment security moderated the association between prenatal anxiety and children's externalizing and internalizing behavioral problems.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".