Psychopathology and Alexithymia in Patients with Moderate-to-Severe Psoriasis: Development of a Novel Index with Prognostic Value
Bibliographic record
Abstract
BACKGROUND: Psoriasis is a chronic, relapsing, inflammatory disease with a high risk of developing mental health difficulties. OBJECTIVE: The purposes of the study were to evaluate in moderate-to-severe psoriasis (a) the prevalence of depression and psychopathology, (b) the relationship between depression, psychopathology symptoms, and alexithymia, including its three dimensions, difficulty in identifying feelings (DIF), difficulty in describing feelings (DDF), and externally oriented thinking (EOT), and (c) to establish a novel index for the development of depression according to patients' psychopathological profile. METHODS: In 104 patients, alexithymia was evaluated with the Toronto Alexithymia Scale (TAS-20), depression with the Beck Depression Inventory (BDI), and psychopathology with the Brief Symptom Inventory SCL-90 (SCL90). A psychopathology index that combines information from the BDI and SCL90 scales was constructed and the performance of the index with alexithymia was examined. RESULTS: Female patients and active smokers score higher on BDI and SCL90 scales. Overweight patients tend to score arithmetically higher. The psychopathology index developed correlates significantly with age, DIF, DDF, and TAS-20. DIF, DDF, and TAS-20 are significant predictors of the psychopathology index. Patients with alexithymia/possible alexithymia are six times as likely to score higher in one of the psychopathology scales. CONCLUSIONS: Alexithymia is a significant factor in the development of psychopathology in psoriasis patients. The use of the proposed novel psychopathology index could be essential in order to identify patients with moderate-to-severe psoriasis who are more likely to experience depression and psychopathology. This could have an impact on the decision-making of psoriasis treatment and monitoring of the patient.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".