Association between depression and alexithymia in adolescents with <i>Acne vulgaris</i>
Bibliographic record
Abstract
Introduction Acne vulgaris is a common skin disease that affects the majority of adolescents. The physical changes of acne may have negative effects on the psychological structure of adolescents such as anxiety and depression. Alexithymia has been suggested to be an important symptom in psychodermatological patients. Objective Our study aims to access depression in adolescents with A. vulgaris and to evaluate its relationship with alexithymia. Methods This is a descriptive cross-sectional study regarding 50 adolescents followed in the outpatient dermatology unit of Hédi Chaker University hospital in Sfax (Tunisia). To assess depression, we used a psychometric tool: Beck Depression Inventory (BDI). The Toronto Alexithymia Scale (TAS-20) was used to evaluate alexithymia. The severity of acne was evaluated with the Global Acne Evaluation (GEA) Scale. Results The mean age of adolescents was 15 years 9 months. Almost all of adolescents was female (82%), and live in urban area. The severity of A. vulgaris was mild in 50%, moderate in 32% and severe in 18%. The prevalence of depression was 48%. Twenty-four percent of them have a major depression. Forty-six percent of patients scored positive for alexithymia. The occurrence of depression was significantly associated to alexithymia (P = 0.003). Conclusion This study showed a positive correlation between alexithymia and depression. These results can be useful in treatment based on processing of emotional information and regulation of emotions. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 | 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".