Evaluation of Alexithymia in Patients Admitted to the Dermatology Clinic
Bibliographic record
Abstract
Background and Aim: Alexithymia has been suggested to be an important symptom in psychodermatological patients.Our study aims to evaluate alexithymia by diseases groups in patients who were admitted at the dermatology clinic. Materials and Methods:The Toronto Alexithymia Scale was used on 150 patients, aged 15-75 years, who were admitted to the Dermatology Clinic and 100 age-sex matched controls, without any skin disease, among the admissions to general surgery clinic.The patients were divided into 5 groups based on diagnoses.A p<0.05 was considered significant in all tests.Results: While the overall alexithymic score in all patients was 51.27±10.71,these values were 45.30±7.50 in the healthy group, with the difference being statistically significant (p≤0.001).While 56.7% of the patients were not alexithymic, 23.3% were diagnosed to have borderline alexithymia, Original Research Articleand 20% alexithymia.And in the control group, alexithymia borderline was found in 11 out of 100 persons (11%).The patients were classified into Group 1 Acne vulgaris 28%, Group 2 papulosquamous diseases 10%, Group 3 infectious skin diseases 16.7%, Group 4 dermatitis 14.7%, and Group 5 other diseases 30.7%.While there was no statistically significant difference between these values, (TAS-B) difficulty identifying emotions was found to be statistically low (p=0.04) in the dermatitis group.Conclusion: Some skin diseases may increase alexithymia or some dermatological diseases may predispose to alexithymia.Further studies with larger patient profiles organized in more specific groups are needed in order to elucidate possible alexithymia in the etiopathogenesis of dermatological diseases.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".