Turning Down, Tuning In: How Mindfulness Shapes Sexual Rejection, Relationship Satisfaction, and Sexual Satisfaction
Bibliographic record
Abstract
Sexual rejection is a challenging interpersonal experience in intimate relationships. The present research examined how mindfulness relates to the use of different sexual rejection strategies across three studies with complementary methodologies: cross-sectional (Study 1), experimental (Study 2) and longitudinal (Study 3). In Study 1 (N = 383; 49.87% women and 48.83% men; Mage = 39.25, SD = 11.97), greater trait mindfulness was associated with fewer hostile and deflecting, and more assertive, rejection strategies. Parallel mediation analyses revealed that fewer hostile and deflecting rejection strategies accounted for the positive links between mindfulness and both sexual and relationship satisfaction. In Study 2 (N = 409; 50.12% women and 49.39% men; Mage = 41.20, SD = 12.68), we replicated the indirect association between pre-manipulation state mindfulness and satisfaction via lower hostile rejection. In Study 3 (N = 193; 59.1% women and 39.4% men; Mage = 43.52, SD = 11.95), greater baseline trait mindfulness predicted less hostile rejection across eight weeks, which in turn was linked to greater weekly sexual and relationship satisfaction. Across studies, mindfulness was consistently linked to less hostile sexual rejection, which may support the maintenance of sexual and relationship satisfaction. The findings offer novel insight into how mindfulness relates to sexual communication and relationship well-being. Future research should examine whether mindfulness-based interventions can improve sexual rejection communication and relational outcomes in more diverse populations.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".