A longitudinal mediation analysis of relationship catastrophizing, perceived partner support, and sexual well-being in couples seeking medically assisted reproduction
Bibliographic record
Abstract
Couples navigating medically assisted reproduction (MAR) may respond to relationship stressors by catastrophizing. Catastrophizers may be more likely to seek support indirectly; partners may miss these cues such that their responses are seen as unsupportive, which may impact sexual desire and distress. We investigated whether relationship catastrophizing predicted lower sexual desire and greater sexual distress, via lower perceived partner support, across 1 year. Couples ( N = 314) seeking/undergoing MAR completed surveys at baseline, 6, and 12 months. Catastrophizing predicted decreases in both partners’ perceived support, and lower perceived support predicted decreases in one’s own downstream sexual distress, but there were no effects for sexual desire. Although we found no evidence of longitudinal mediation, at baseline, greater catastrophizing was associated with lower perceived support, which was in turn linked to lower desire and greater distress. Interventions targeting relationship catastrophizing and improving partner support may help couples navigate the challenges of MAR.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".