Alexithymia in depressive disorder and its correlation with mental symptoms and personality traits
Bibliographic record
Abstract
Aim:To explore the feature of Alexithymia in patients with depression and its correlation with personality traits and mental symptoms.Methods: 74 patients with depression were assessed with Toronto Alexithymia Scale-20(TAS-20),Self-rating Depression Scale(SDS),Symptom Checklist 90(SCL-90),and Eysenck personality questionnaire(EPQ).Results: The total score and factor scores of TAS-20 were positively related with the score of the SDS.Stepwise regression analysis showed that factors of TAS-20 were positively related with many symptom factors of SCL-90.The variance of symptom factors of SCL-90 explained by regression equations which consist of factors in TAS-20 varied from 8.7% to 23.4%.The total score and score of factor 2 in TAS-20 were negatively related with factor E in EPQ.There was positive correlation between factor 1 of TAS-20 and factor N as well as factor3 and factor P.Conclusion:Alexithymia is the vulnerable personality trait as well as a reactive state of depression,which interact with many mental symptoms of depressive disorder.Alexithymia is a relatively stable as a personality trait and variable as a reactive state of depression.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".