A Safe Haven Through Attachment: A Dyadic Perspective on the Association Between Cumulative Childhood Trauma and Relationship Satisfaction
Bibliographic record
Abstract
Cumulative childhood trauma (CCT) increases the risk of experiencing interpersonal problems and relationship distress in adulthood. However, not all CCT survivors experience such difficulties, and little research has investigated protective factors against relationship dissatisfaction in CCT survivors and their partners. Romantic attachment might be one such factor that could reduce the harmful effects of a CCT history on relationship satisfaction for both survivors and their partners. Using a dyadic perspective, this study aimed to examine the association between CCT and relationship satisfaction and to test the moderating effect of attachment avoidance and anxiety on this association. A sample of 501 couples was recruited through a Canadian survey firm. Canadian couples who had provided their telephone number were randomly selected to complete the short form of the Dyadic Adjustment Scale, the Experiences in Close Relationships Scale, and the Childhood Cumulative Trauma Questionnaire. The actor-partner interdependence moderation model was used to guide the analyses. Results showed that individuals' and partners' higher CCT was correlated with both partners' lower relationship satisfaction. The analyses revealed a moderating effect of lower attachment avoidance on the link between individuals' CCT and their own relationship satisfaction. Specifically, individuals' CCT was significantly and negatively associated with relationship satisfaction at high levels of attachment avoidance, but unrelated to relationship satisfaction at low levels of attachment avoidance. The final model explained 31.4% of the variance in relationship satisfaction. Overall, the findings support the relevance of couple interventions that focus on romantic attachment to improve relationship well-being in couples where one or both partners have experienced CCT.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".