Maternal depression symptoms, child behavior problems, and their transactional relations: Probing the role of formal childcare
Bibliographic record
Abstract
Among children exposed to elevated maternal depression symptoms (MDS), recent studies have demonstrated reduced internalizing and externalizing problems for those who have attended formal childcare (i.e., center-based, family-based childcare). However, these studies did not consider whether childcare attendance is associated with benefits for the child only or also with reduced MDS. Using a four-wave longitudinal cross-lagged model, we evaluated whether formal childcare attendance was associated with MDS or child behavior problems and whether it moderated longitudinal associations between MDS and child behavior problems and between child behavior problems and MDS. The sample was drawn from a population-based cohort study and consisted of 908 biologically related mother-child dyads, followed from 5 months to 5 years. Attending formal childcare was not associated with MDS or child behavior problems but moderated the association between MDS at 3.5 years and child internalizing and externalizing problems at 5 years as well as between girls' externalizing problems at 3.5 years and MDS at 5 years. No other moderation of formal childcare was found. Findings suggest that attending formal childcare reduces the risks of behavior problems in the context of MDS but also the risk of MDS in the context of girls' externalizing 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 | 0.000 |
| 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) | 0.001 | 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".