Alexithymia prevalence among patients with chronicdermatological diseases in a tertiary hospital, Saudi Arabia
Bibliographic record
Abstract
Introduction: Alexithymia is a psychological condition characterized by difficulty in identifying and expressing one's emotions, and it has been associated with several physical and mental health disorders. Aim: To determine the prevalence of alexithymia among patients with a range of chronic dermatological diseases in a Saudi public hospital. Material and methods: 477 patients who were over 14 years old and affected by one of the following chronic skin conditions: psoriasis, atopic dermatitis, acne, alopecia areata, vitiligo, hidradenitis suppurativa, pemphigus vulgaris, chronic urticaria were included in this study. Alexithymia was assessed in these patients by using the Toronto Alexithymia Scale (TAS) which is a widely used, reliable and valid measure of this construct. Results: Prevalence of alexithymia among chronic dermatological disease patients ranges from 14.8% to 71.4%, with an overall occurrence of 43%. The highest prevalence of alexithymia was found in hidradenitis suppurativa (71.4%) and the lowest in acne (14.8%). Overall, the alexithymia cases were predominantly male (51.7%). The distribution of male and female cases with alexithymia varied among patients with different types of chronic skin diseases, with the highest male prevalence in psoriasis (58.7%) and the highest female prevalence in pemphigus vulgaris (66.7%). Conclusions: Alexithymia is prevalent among patients with chronic dermatological diseases and dermatologists' awareness of how to identify and address alexithymia among their patients can play a vital role in improving treatment adherence and outcomes.
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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".