Psychiatric Symptoms in Patients with Alopecia Areata
Bibliographic record
Abstract
Background and Design: Alopecia areata is a chronic inflammatory disease characterized by sudden hair loss. Existing evidence suggests that alopecia areata may be associated with personality traits altering the susceptibility to stress and psychiatric conditions associated with stress. The aim of this study was to compare the intensity of depressive and anxiety symptoms and the level of alexithymia in patients with alopecia areata and healthy control subjects.Materials and methods: Fifty patients with the diagnosis of alopecia areata and 30 healthy volunteers were compared in terms of scores of Beck depression inventory, Beck anxiety inventory, and Toronto alexithymia scale.Results: There were no statistically significant differences between alopecia areata cases and healthy controls regarding intensity of anxiety and level of alexythimia (p=0.053 and p=0.120, respectively). The intensity of depressive symptoms exhibited by alopecia areata patients was found to be significantly higher than that in healthy controls (p=0.010) and there was no statistically significant relationship between intensity of depressive symptoms and duration of the current alopecia areata episode (p=0.873).Conclusion: It is suggested that psychiatric evaluation should also be performed in all alopecia areata cases during the clinical follow-up period. (Turkderm 2011; 45: 203-5)
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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 | 0.000 |
| 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) | 0.002 | 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".