The Role of Family Emotional Atmosphere and Attachment Styles in Alexithymia of Married People
Bibliographic record
Abstract
Background: The ability to create and maintain a satisfying relationship in the marital life requires an understanding of attachment styles, the family’s emotional atmosphere, recognizing and expressing mutual emotions, and understanding and accepting the spouse’s emotions. This study aimed to examine the role of family emotional atmosphere and attachment styles in predicting the alexithymia of married people. Methods: This predictive correlational study was conducted on a sample of married men and women with marital communication problems who were referred to counseling centers in District 2 of Tehran Municipality in 2021. The subjects included 400 married men and women who were selected by stratified proportional sampling. The data were collected by the Toronto Alexithymia Scale (TAS-20), the Family Emotional Climate Questionnaire, and the Adult Attachment Scale (AAS) and were analyzed using the correlation coefficient test and multiple regression analysis by SPSS software, version 22. Results: The results showed that secure and avoidant attachment styles were negatively correlated (r=0.38) with alexithymia. Furthermore, anxious/ambivalent attachment style was positively correlated with alexithymia (r=0.38). The family emotional atmosphere was negatively correlated with alexithymia (r=0.68) (P<0.01). Moreover, 46.6% of the variances in alexithymia were explained by family emotional atmosphere and attachment styles (R2=0.466). Conclusion: The findings revealed that alexithymia as a psychological construct could be predicted by the family’s emotional atmosphere and the attachment styles of married people. Thus, providing training on social skills and emotional expression helps married people to identify positive and negative emotions and the inability to recognize their partner’s feelings
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".