Parent–child attachment and children’s experience and regulation of emotion: A meta-analytic review.
Bibliographic record
Abstract
Attachment relationships serve as contexts within which children develop emotional capacities. This meta-analytic review assessed the strength of associations of parent-child attachment patterns with the experience and regulation of emotion in children under age 18 years. In a series of meta-analyses (k = 72 studies, N's ranged from 87 to 9,167), we examined children's positive and negative affective experiences (assessed either globally or elicited in specific contexts), emotion regulation ability, and coping strategies. More securely attached children experienced more global positive affect and less global negative affect, expressed less elicited negative affect, were better able to regulate emotions, and more often used cognitive and social support coping strategies. More avoidantly attached children experienced less global positive affect, were less able to regulate emotions, and were less likely to use cognitive or social support coping strategies. By contrast, more ambivalently attached children experienced more global and more elicited negative affect, and were less able to regulate emotions. More disorganized children experienced less global positive affect and more global negative affect. These robust findings provide evidence that attachments to parents have implications for children's emotional development, although more research is needed on whether insecure attachment patterns are associated with distinct emotion profiles. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".