Maternal Anxiety, Parenting Stress, and Preschoolers' Behavior Problems: The Role of Child Self-Regulation
Bibliographic record
Abstract
OBJECTIVE: Maternal anxiety is a well-known risk factor for early childhood behavior problems. In this study, we explore (1) whether parenting stress mediates this relation and also (2) whether child factors, namely self-regulation, modify the influence of maternal well-being on child externalizing and internalizing problems at 4 years of age. METHOD: Mothers taking part in the Growing Up in Singapore Towards Healthy Outcomes cohort completed the Spielberger State-Trait Anxiety Inventory when their children were 24 months of age. At 42 months of age, children performed a self-regulation task (n = 391), and mothers completed the Parenting Stress Index. When children were 48 months old, both parents completed the Child Behavior Checklist. RESULTS: As predicted, parenting stress mediated the relation between maternal trait anxiety and child externalizing and internalizing problems. This mediating effect was further moderated by child self-regulation. The indirect effect of maternal trait anxiety through parenting stress on child externalizing problems was stronger among children with low self-regulation. CONCLUSION: Parenting stress is an additional pathway connecting maternal trait anxiety and children's externalizing and internalizing behavior problems. The risk for child externalizing problems conveyed by elevated maternal trait anxiety and parenting stress may be buffered by better self-regulation in 4-year-olds. These results suggest that interventions that include decreasing parenting stress and enhancing child self-regulation may be important to limiting the transgenerational impact of maternal trait anxiety.
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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".