Supplementary Material for: Disease Severity Is Associated with Alexithymia in Patients with Atopic Dermatitis
Bibliographic record
Abstract
Background: Atopic dermatitis (AD) is a chronic inflammatory skin disorder that is associated with higher rates of psychological disorders, but limited evidence supported the association with alexithymia, a psychoaffective dysfunction. Objectives: This study was aimed to investigate the occurrence of alexithymia in AD patients, compared to healthy subjects. Methods: This cross-sectional study assessed AD severity by the Eczema Area and Severity Index (EASI) score, sleeplessness and itch by a numeric rating scale (NRS), and alexithymia by the 20-item Toronto Alexithymia Scale (TAS-20) score. The association between disease characteristics and alexithymia was evaluated through several logistic regression models. Results: 202 AD patients and 240 healthy subjects were included in this study. The alexithymic personality trait (TAS-20 ≥51) was more frequently observed among AD patients compared to the control group (62.4% [126/202] vs. 29.2% [70/240], p < 0.0001). In particular, alexithymia (TAS-20 score ≥61) was detected in a significantly higher number of AD patients than in the controls (27.7% [56/202] vs. 7.5% [18/240]; p < 0.0001), whereas borderline alexithymia was detected in 34.6% (70/202) of AD patients compared to 21.7% of healthy controls. Alexithymia was more common among severe AD patients (43.6%) compared to mild AD patients (15.6%) and correlated with itch intensity and sleep disturbances. Among clinical variables, ordered logistic regression analyses revealed disease severity as predictor of alexithymia. Indeed, univariate analysis showed EASI score, sleep NRS, and itch NRS being significantly associated with alexithymia, while a multivariate model identified increased EASI score values as predicting factor. Conclusion:This study described alexithymia in AD patients correlating its occurrence with clinical AD severity markers (EASI score, itch, and sleeplessness) and identifying the increase in EASI score as predicting factor.
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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 | 0.001 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.796 | 0.176 |
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".