The Role of Alexithymia and Sexual Self-esteem in the Prediction of Marital Stress and Adjustment in Infertile Women
Bibliographic record
Abstract
Objective: Considering the negative impact of infertility on the level of adjustment and stress in women, the present study aimed to examine the role of sexual self-esteem and alexithymia in predicting marital stress and adjustment of infertile women. Methods: This research was a cross-sectional study. The study population consisted of all infertile women in Shiraz City, Iran (N=70000). A total of 400 women were selected through a non-random and purposeful sampling method, but the final sample consisted of 380 subjects. The study tools were a short form of sexual self-esteem scale for women, Locke-Wallace marital adjustment questionnaire, Stockholm-Tehran marital stress scale, and Toronto alexithymia scale. The obtained data were analyzed by the Pearson correlation and multivariate regression in the SPSS V. 26. Results: The results showed a significant negative relationship between sexual self-esteem and marital stress as well as alexithymia and marital adjustment (P<0.01). Besides, the positive relationships between sexual self-esteem and marital adjustment and alexithymia and marital stress were significant (P<0.01). The results of multiple regression analysis demonstrated that alexithymia and sexual self-esteem could significantly predict marital stress and marital adjustment with the standard coefficient of 0.44 and 0.22, respectively. Conclusion: Alexithymia and sexual self-esteem play essential roles in predicting adjustment and stress levels of infertile women, respectively. Accordingly, difficulty in emotional awareness at first, and then the low level of self-esteem in sexual function can decrease adjustment and increase stress in marital relationships.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".