Bibliographic record
Abstract
OBJECTIVE: The somatic component of depression is an important clinical phenomenon. The role of somatic amplification, alexithymia, anger and symptom attribution has been investigated in the genesis of the somatic symptoms of depression. METHOD: The study was carried out with 32 patients attending the outpatient psychiatry clinics of Karadeniz Technical University Medical School, meeting the diagnosis of depression according to DSM-IV, and 34 healthy subjects. The subjects were assessed with the Beck Depression Scale, the Beck Anxiety Scale, the Hamilton Depression Scale, the Hamilton Anxiety Scale, the Somatosensory Amplification Scale, the 20-item Toronto Alexithymia Scale the Spielberger State-Trait Anger Expression Inventory, the Symptom Interpretation Questionnaire and a data form for recording sociodemographic characteristics. RESULTS: The sociodemographic characteristics of the sample were similar. The anxiety, alexithymia, and anger-in scores were significantly higher, while anger-control scores were significantly lower in the depressive subjects. Psychologizing attributes were positively correlated with depression and anxiety. Normalizing was negatively correlated with anxiety. Somatizating was correlated with the difficulty in identifying feelings subscale of alexithymia. DISCUSSION: These findings show that depressive patients are more alexithymic, have more difficulty in controlling their anger and introject their anger more compared to the healthy controls. Depressed and anxious subjects psychologize, and subjects with difficulty in identifying emotions somatize their symptoms.
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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 | 0.000 | 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) | 0.011 | 0.002 |
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".