Association Between Attachment Styles and Shame Proneness: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: The present review aimed to examine the association between different styles of attachment and proneness to shame. METHOD: A systematic literature search was conducted across databases including PubMed, Scopus, Web of Science, and Google Scholar which led to the inclusion of 18 studies in the analysis. The meta-analysis incorporated studies involving diverse populations, ensuring a comprehensive understanding of the attachment-shame relationship across various demographic contexts. Four correlational meta-analyses were conducted to investigate the relationship between secure, insecure styles- dismissive, preoccupied, and fearful attachment styles and proneness to shame. Random-effect models in R were employed and the quality of the studies was assessed using the Newcastle-Ottawa Scale. RESULTS: Study findings revealed a significant small to moderate negative association between secure attachment and shame (Effect Size [ES] = -0.29); moderate positive associations were found between fearful (ES = 0.39) and preoccupied attachment styles (ES = 0.33) with shame; small but significant positive association was found between dismissing attachment and shame (ES = 0.13). Subgroup analysis revealed that the association between all three insecure attachment styles and shame was more pronounced among LGBTQ+ individuals. Meta-regression analysis showed that gender significantly influenced the associations for preoccupied and dismissing attachment styles. CONCLUSION: These results demonstrate that the strength of association with shame varies by type of attachment style. The results also point to the moderating influence of gender and sexual orientation. These insights have important clinical implications and suggest directions for future research on tailoring interventions based on attachment styles.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.023 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".