Representational and questionnaire measures of attachment: A meta-analysis of relations to child internalizing and externalizing problems.
Bibliographic record
Abstract
Although the quality of the attachment relationship is often cited as an important determinant of development, the extent of impact of this environmental influence in shaping behavioral outcomes has been a matter of considerable debate. This may, in part, be because of the variability in methodologies used for assessing attachment across infancy, childhood, and adolescence, including behavioral, representational, and questionnaire measures of attachment. Previous meta-analyses of the relations between attachment and internalizing and externalizing problems have focused on the behavioral measures of attachment used primarily in infancy. The current meta-analysis is a comprehensive examination of the literature on attachment and behavioral problems in children aged 3-18 years, focusing on the representational and questionnaire measures most commonly used in this age range. When secure attachment was compared with insecure attachment, modest associations with internalizing behavior (165 studies; 48,224 families; d = .58; 95% confidence interval [CI] [.52-.64]) were found. Multivariate moderator analyses were used to disentangle the unique influence of each significant univariate moderator more precisely, and results revealed that effect sizes decreased as the child aged, and were larger in studies in which the participants were ethnically White, where the child was the problem informant, and when the internalizing measure was depressive symptoms. Attachment and externalizing behavior were also associated (116 studies; 24,689 families; d = .49; 95% CI [42-.56]), and effect sizes were larger in ethnically White samples, and in those where the child was the problem informant. Avoidant, ambivalent, and disorganized attachment classifications were associated with internalizing behavior, but only disorganized attachment was associated with externalizing behavior.
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.038 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".