Dyadic Empathy Predicts Sexual and Relationship Well-Being in Couples Transitioning to Parenthood
Bibliographic record
Abstract
Becoming a new parent is typically a time of great joy, yet it is also marked by significant declines in sexual and relationship functioning. Dyadic empathy, a combination of perspective taking and empathic concern for one's romantic partner, may facilitate sexual and relationship quality for new parents. The purpose of this study was to examine the associations between dyadic empathy and sexual satisfaction, relationship adjustment, and sexual desire in a sample of first-time parents. Couples (N = 255) with an infant aged three to 12 months completed an online survey assessing dyadic empathy, sexual satisfaction, relationship adjustment, and sexual desire. Data were analyzed using multilevel analyses guided by the actor-partner interdependence model. When new mothers and fathers reported greater dyadic empathy, both they and their partners reported higher sexual satisfaction and relationship adjustment. New mothers who reported higher dyadic empathy also had higher sexual desire, although when they had more empathic partners new mothers reported lower sexual desire. Results remained significant after controlling for potential challenges unique to the postpartum period (e.g., fatigue, breastfeeding), as well as relationship duration. Targeting dyadic empathy in interventions aimed at helping couples transition to parenthood may promote the maintenance of sexual and relationship well-being.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".