Relationship between Alexithymia and Coping Attitudes in Generalized Anxiety Disorder
Bibliographic record
Abstract
Among anxiety disorders, the incidence of alexithymic features is found in a wide range of 12.5-58%, and it is a personality trait that can also be seen in healthy individuals. Our study investigated the relationship between alexithymic features and coping attitudes in patients with generalized anxiety disorder. Forty patients diagnosed with Generalized Anxiety Disorder and 39 healthy volunteers participated in the study. Participants were divided into groups using the Toronto Alexithymia Scale, and the Hamilton Anxiety Scale and Coping Attitudes Scale were applied to all participants. Nineteen patients with alexithymia and Generalized anxiety disorder, 21 patients with Generalized anxiety disorder without alexithymia, and 39 healthy volunteers participated in this study. Statistically significant differences were observed between the problem-focused coping and emotion-focused coping subscale scores, but there was no difference in dysfunctional coping styles between the three groups. In the correlation analysis performed to determine the relationship between the total alexithymia and Coping attitudes subscale scores, there was a moderate negative correlation between the alexithymia scores and problem-focused (r=-0.442) and emotion-focused coping (r=-0.425) subscale scores. Alexithymia is often accompanied by generalized anxiety disorder and negatively affects coping attitudes.
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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 | 0.000 | 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) | 0.002 | 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".