The correlation between alexithymia and anxiety, depression in asthma
Bibliographic record
Abstract
Background: Alexithymia is a personality trait characterized by the inability to identify and describe emotions. Only few researches have studied the correlation between alexithymia and health factors in psychosomatic disorders. This study aimed to determine the correlation between alexithymia and anxiety, depression in asthmatic patients. \nMaterials and Methods: This cross-sectional study was conducted on all asthmatic patients referred to Khorram Abad medical centers. Among them 100 cases were chosen using the convenience sampling. The tools were Alexithymia Scale )TAS-20( along with Hospital Anxiety and Depression Scale )HADS(. The data were analyzed using Pearson correlation and Multivariate Regression. \nResults: A significant positive relationship was seen between aalexithymia, its factors and anxiety/depression. In addition, multiple multivariate regression analysis showed that difficulty in identifying feelings and describing feelings can predict the anxiety and depression. \nConclusion: Findings showed that difficulty in identifying and describing emotions as two factors of Alexithymia in asthmatic patients can predict the depression and anxiety. So, considering the emotional aspects of asthma, effective approaches should be taken into account in the treatment of these patients' mental health problems.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".