Social Cognition as Mediator of Romantic Breakup Adjustment in Young Adults Who Experienced Childhood Maltreatment.
Bibliographic record
Abstract
The current study investigated whether childhood maltreatment and social cognition (emotional regulation, mentalization, causal attributions) are associated with romantic breakup adjustment in youth (resilience, psychiatric symptoms, distress); and whether social cognition mediates the relationship between childhood maltreatment and adjustment to romantic breakup. We assessed childhood maltreatment, social cognition, and romantic breakup adjustment in a sample of 482 university students who experienced a romantic breakup recently. Linear regressions and mediation analyses were computed. Childhood maltreatment was associated with romantic breakup adjustment when mediators were considered (p < .01) and when they were not (p < .01). Only emotional regulation was linked with measures of breakup adjustment (p < .01), while mentalization and personal control demonstrated relationships with resilience (p < .01) and psychiatric symptoms (p < .01; p < .05). Childhood maltreatment was indirectly associated with romantic breakup adjustment through emotional regulation (p < .05). Childhood maltreatment was indirectly associated with psychiatric symptoms through mentalization (p < .05), while childhood maltreatment was indirectly associated with romantic breakup adjustment through self-related mentalization (p < .05). The current study provides further evidence that emotional regulation and mentalization may act as protective factors on romantic breakup adjustment in the context of childhood maltreatment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".