Extradyadic stress as a barrier to sexual activity in couples? A dyadic response surface analysis
Bibliographic record
Abstract
Sexuality is integral to most romantic relationships. Through stress spillover, however, factors such as individually experienced stress outside of the relationship (i.e., extradyadic stress) can negatively impact sexuality. In this study, we explored how a possible (mis)matching of both partners' levels of extradyadic stress is related to sexual activity and tested for gender differences. Analyzing 316 mixed-gender couples from Switzerland, we employed Dyadic Response Surface Analysis to assess how extradyadic stress is associated with sexual activity. Our results showed that extradyadic stress was positively linked to sexual activity for women (in general) and men (in the case of matching stress levels). As this result was surprising, we conducted additional exploratory analyses and split the measure of sexual activity into (1) exchange of affection and (2) eroticism (petting, oral sex, and intercourse) and controlled for age. Results from this second set of analyses showed that for women, matching stress levels were associated with higher exchange of affection, whereas men's exchange of affection was higher if men reported higher stress levels than women. Notably, after accounting for age, the link between stress and eroticism dissipated. Our findings suggest that exchange of affection may serve as a coping mechanism for stress, with gender influencing this dynamic. However, future research investigating stress and sexual activity should consider additional factors such as age, relationship satisfaction, stressor type, and stress severity.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".