The Relationship Between Alexithymia and Coping Styles: The Mediator Roles of Anger and Anger Expression Styles
Bibliographic record
Abstract
The concept of alexithymia basically points to the various problems that individuals experience in defining and expressing their feelings. A review of the literature shows that alexithymic characteristics may cause various difficulties in anger and its expression. Furthermore, it is seen that alexithymia, anger and anger expression styles are important variables to predict coping styles. From this point of view, the aim of this study is to investigate the mediator roles of anger and anger expression styles in the relationship between alexithymia and coping styles in the university sample. The present study included 434 college students (244 women, 190 men). In addition to the Demographic Information Form, participants were administered the 20-item Toronto Alexithymia Scale (TAS-20), the State-Trait Anger Expression Inventory (STAXI) and the Ways of Coping Questionnaire (WCQ). The mediation analysis was conducted via using PROCESS macro model with 5000 bootstrapping samples (Hayes, 2013)The mediation analyses showed that the anger-in and anger-control mediated the relationship between alexithymia and problem-focused/emotion-focused coping styles. It is concluded that the relationship between alexithymia and coping styles is mediated by anger and anger expression styles. Therefore, current study emphasizes the benefit of addressing alexithymic characteristics, the frequency of anger experience, and healthy ways of anger expression simultaneously and as a whole rather than individually in psychotherapies aiming to strengthen the ways of coping with stress.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".