Examining Congruence Between Partners' Perceived Infertility‐Related Stress and Its Relationship to Marital Adjustment and Depression in Infertile Couples
Bibliographic record
Abstract
Because studies examining the emotional impact of infertility-related stress generally focus on individuals, there has been little research examining how relationship and individual variables are linked. The purpose of this study was to explore the impact of congruence (e.g., agreement) between partner's perceived infertility-related stress and its effects on depression and marital adjustment in infertile men and women. Couples referred for infertility treatments at a University-affiliated teaching hospital completed the Fertility Problem Inventory (FPI), the Beck Depression Inventory (BDI), and the Dyadic Adjustment Scale (DAS) 3 months prior to their first treatment cycle. Study findings show that men and women in couples who perceived equal levels of social infertility stress reported higher levels of marital adjustment when compared to men and women in couples who perceived the stress differently. In addition, women in couples who felt a similar need for parenthood reported significantly higher levels of marital satisfaction when compared to women in couples where the males reported a greater need for parenthood. While couple incongruence was unrelated to depression in males, incongruence over relationship concerns and the need for parenthood was related to female depression. These findings provide initial support for the theory that high levels of agreement between partners related to the stresses they experience help them successfully manage the impact of these stressful life events. Possibilities for future research examining the construct of couple congruence are discussed.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".