Alexithymia and Somatization in Depressed Patients: The Role of the Type of Somatic Symptom Attribution
Bibliographic record
Abstract
INTRODUCTION: This study aimed to establish the association between alexithymia and various factors, mainly somatization, and to determine the predictors of alexithymia in depressed patients. METHODS: A total of 90 patients with major depressive disorder who met The Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV) diagnostic criteria were administered the Toronto Alexithymia Scale (TAS), Beck Depression Inventory, Symptom Checklist-90 (SCL-90), Somatosensory Amplification Scale, and Symptom Interpretation Questionnaire. The patients were classified into two groups as alexithymic and non-alexithymic with respect to the TAS cut-off points (≥59=alexithymic). Predictors of alexithymia were tested by multiple linear regression analysis. RESULTS: Of all patients, 36 (40%) were in the alexithymic group. The percentage of women, depression severity, level of general psychopathology and distress, and somatic symptom reporting (SCL-90), as well as the tendency to somatosensory amplification and three forms of somatic symptom attributions, were significantly higher in alexithymic patients than in non-alexithymic patients. Furthermore, age, depression severity, somatic symptom reporting, and the tendency to attribute physical symptoms to somatic causes were predictors of alexithymia. CONCLUSION: The results indicated an intimate association between alexithymia and somatization in depressed patients. Therefore, when evaluating depressed patients with alexithymia, their tendency for somatization should be considered, and alexithymic individuals should be assessed with particular attention, considering that somatization can mask the underlying depressive condition.
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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".