Hostility, flooding, and relationship satisfaction: Predicting trajectories of psychological aggression across the transition to parenthood
Bibliographic record
Abstract
Psychological aggression has been shown to have harmful effects on both partners, sometimes above and beyond the effects of physical aggression. However, very little is known about psychological aggression during the transition to parenthood. The transition to parenthood is a time where relationship satisfaction often declines and stress increases, which may put the couples at higher risk for psychological aggression. The purpose of this study was to examine if prenatal risk factors related to interpersonal style (specifically, emotional flooding and hostility) predict changes in psychological aggression from pregnancy to 2 years postpartum. Ninety eight couples took part in this study. The couples completed self-report questionnaires during pregnancy, 1 year postpartum, and 2 years postpartum. Both partners were asked about perpetrating and experiencing psychological aggression in their current relationship. Two level Hierarchical Linear Models (HLMs) were used to examine longitudinal associations between hostility, flooding, and psychological aggression. For women, hostility during pregnancy was a significant longitudinal predictor of psychological aggression. For men, flooding was a significant longitudinal predictor of psychological aggression. For both men and women, relationship satisfaction partially mediated the relationship between flooding/hostility and psychological aggression, indicating that women's hostile attitudes and men's tendency to be flooded tend to erode relationship quality, leading to increases in psychological aggression. This may represent a classic demand-withdraw dynamic in couples. The results indicate hostility for women and flooding for men are potential prenatal risk factors for future psychological aggression. Implications and future research directions are discussed. Aggr. Behav. 42:134-148, 2015. © 2014 Wiley Periodicals, Inc.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".