Designing a model of tendency to domestic violence based on emotional deprivation with the mediation of alexithymia in women affected by marital infidelity
Bibliographic record
Abstract
Background: Domestic violence and marital infidelity are among the events that, while affecting the relationship of couples in a negatively way, can cause the breakup of the family and the separation of couples from each other. Previous studies have investigated the relationship between emotional deprivation and alexithymia with domestic violence and marital infidelity, but so far, there has been no research that investigates the tendency to domestic violence based on emotional deprivation with the mediation of alexithymia in women affected by marital infidelity. Aims: The purpose of this research was to design a model of the tendency to domestic violence based on emotional deprivation with the mediation of alexithymia in women affected by marital infidelity. Methods: The method of the present study was descriptive-correlation, which was done with path analysis method. The statistical population of the present study included all women involved in the issue of marital infidelity of their husbands who had referred to the counseling centers of District 5 of Tehran in 2023. The data collection tools included four questionnaires: The Infidelity Questionnaire (Yeniceri & Kökdemir, 2006), Toronto Alexithymia Scale (Bagby et al., 1994), Domestic Violence Questionnaire (Mohseni Tabrizi et al., 2013) and Emotional deprivation questionnaire (Young, 1998). Also, SPSS software version 26 and Smart PLS software version 3 were used to analyze the research data. Results: The results showed that there is a direct relationship between emotional deprivation and domestic violence in women affected by marital infidelity (P< 0.05). There is an indirect relationship between emotional deprivation and domestic violence in women affected by marital infidelity due to alexithymia (P< 0.05). The model of tendency to domestic violence based on emotional deprivation with the mediation of alexithymia has a good fit. Conclusion: According to the obtained findings, it is suggested that couple therapists use the necessary strategies to reduce the effects of emotional deprivation and adjust alexithymia to prevent domestic violence and subsequent marital infidelity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".