Parenting Correlates of Children's Emotion Regulation: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Emotion regulation is central to adjustment and research suggests that parenting is critically influential in socializing children's emotion regulation skills. However, substantial limitations and inconsistencies exist in this literature, including conceptual challenges in defining emotion regulation, poor convergent validity among emotion regulation measures, inconsistencies regarding the relationship between parenting and children's emotion regulation and the lack of a systematic approach to assessing moderation. This meta-analysis consists of 61 independent effect sizes, including 8,854 children in the middle childhood period. The analyses revealed a significant overall effect of r = .13 (validated by two imputation methods yielding comparable effects), indicating that supportive parenting styles and practices are significantly and positively associated with adaptive child emotion regulation. Several moderators (e.g., demographic and methodological features) were examined. The sole moderator to emerge was the informant (i.e., parent, child) for emotion regulation and parenting constructs in a given study. Specifically, the effect was moderated by whether the informants were the same for both constructs (e.g., parent reporting on both child emotion regulation and parenting variables) or different (e.g., parent reporting on child emotion regulation and child reporting on parenting), such that the association was significantly stronger when the informant for both constructs was the same (r = .19) as compared to when informants were different (r = .10). Controlling for study informants, no additional moderators emerged reliably in meta-regression analyses. Findings highlight the need for more rigorous assessment of these constructs, with consideration of common-method variance, reporting biases, discrepancies in children’s and parents’ perspectives, and the extent to which emotion regulation measures, in particular, align with the intended definitions of the variables and with other unintended constructs. In light of the multidimensional and transactional influences on children’s emotion regulation, continued exploration of proximal and distal moderators, both theoretical and methodological, is strongly recommended across empirical and clinical intervention literatures.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.020 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".