Predicting emotional alexithymia based on emotional information processing with the mediation of emotional self-disclosure in married people
Bibliographic record
Abstract
Background: Alexithymia is a type of mood disorder that causes the inability to cognitively process emotional information and regulate emotions. Spouses' Alexithymia is one of the factors affecting couples' incompatibility and interaction, which has a negative effect on their interaction and compatibility. However, there is a research gap in the field of the ability to predict Alexithymia through the ability to process emotional information with the mediation of emotional self-disclosure in the target society, so in this research, the prediction of Alexithymia based on emotional processing with the mediation of emotional self-disclosure in married people is discussed. Aims: The aim of the present study was to provide a structural model for predicting Alexithymia based on emotional processing with the mediation of emotional self-disclosure. Methods: The method of descriptive research is correlation type using structural equations. The research population was all married women who referred to counseling and assistance clinics in Robat Karim city for consensual divorce in the year2019, and 200 people were selected by available sampling method. In order to collect data, Toronto Persian scale of emotional Alexithymia (Bashart, 2007), Emotional information processing questionnaire(Abolmaali,2019) and emotional self-disclosure scale (Snell, 2001) were used. In order to analyze the data, descriptive statistical methods and Also, structural equations and Spss, Lisrel software were used.. Results: The results showed that emotional self-disclosure plays a mediating role in the relationship between Alexithymia and emotional processing (p>0.05) and there is an indirect relationship between Alexithymia and emotional processing considering emotional self-disclosure as a mediating factor. Conclusion: The results of this research showed that there is a direct and meaningful relationship between emotional information processing and Alexithymia, so that among the variables of emotional processing, the variable of weakened and suppressed emotions predicts Alexithymia and in general, Alexithymia in couples can be predicted based on the mentioned variables. Therefore, these factors should be considered in prevention and treatment programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 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".