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 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 | 0.001 |
| 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) | 0.001 | 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 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".