Negative Partner Attributions Moderate the Association between Heart Rate Reactivity During Relationship Conflict and Relationship Satisfaction
Why this work is in the frame
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Bibliographic record
Abstract
Numerous theoretical models of relationship distress suggest that strong, negative reactions to conflict are directly associated with lower levels of relationship satisfaction. Consistent with this supposition, substantial evidence links higher levels of subjective negative emotion, more pronounced and frequent expressions of negative affect, and higher levels of negative communication behaviors to lower levels of relationship satisfaction (e.g., Bradbury, Fincham, & Beach, 2000, Journal of Marriage and Family, 62(4), 964). However, the evidence linking stress-related physiological responding during relationship conflict and relationship satisfaction is less compelling than would be anticipated based on theory. We propose that these theoretically unexpected but empirically well-replicated findings may be the result of different patterns in association between physiological reactivity and relationship satisfaction for couples with varying styles in how they typically perceive unwanted behavior in one another. The present study tests negative attributions for undesirable partner behaviors as a moderator of the association between heart rate reactivity (HRR) during relationship conflict and relationship satisfaction in a sample of 60 married couples. A significant interaction emerged between HRR and negative attributions of partner behavior in predicting relationship satisfaction such that higher levels of HRR were associated with lower levels of relationship satisfaction for individuals who typically made more negative attributions for undesirable partner behaviors, but with higher levels of relationship satisfaction for individuals who typically made fewer negative attributions for undesirable partner behaviors. Implications for conceptualizing reactivity during relationship conflict and couple interventions are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it