Assessing the Relationship Between Vitiligo and Major Depressive Disorder Severity: Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Vitiligo, a common dermatological disorder in Saudi Arabia, is associated with significant psychological impacts. This study explores the relationship between vitiligo and the severity of major depressive disorder (MDD), highlighting the broader implications on mental health among affected individuals. OBJECTIVE: We aim to assess the prevalence and predictors of depression among adult patients with vitiligo, and to examine the relationship between MDD severity and vitiligo. METHODS: Using a cross-sectional design, the research used the vitiligo area severity index and the Patient Health Questionnaire-9 to measure the extent of vitiligo and depression severity, respectively. This study involved 340 diagnosed patients with vitiligo from various health care settings. Logistic and ordinal regression analysis were applied to evaluate the impact of sociodemographic variables and vitiligo types on MDD severity. RESULTS: The prevalence of MDD was 58.8% (200/340) of participants. Depression severity varied notably: 18.2% (62/340) of patients experienced mild depression, 17.9% (61/340) moderate, 11.8% (40/340) moderately severe, and 10.9% (37/340) severe depression. Female patients had higher odds of severe depression than male patients (adjusted odds ratio [aOR] 3.14, 95% CI 1.93-5.1; P<.001). Age was inversely related to depression severity, with patients aged older than 60 years showing significantly lower odds (aOR 0.1, 95% CI 0.03-0.39; P<.001). Lower income was associated with higher depression severity (aOR 10.2, 95% CI 3.25-31.8; P<.001). Vitiligo types also influenced depression severity; vulgaris (aOR 5.3, 95% CI 2.6-10.9; P<.001) and acrofacial vitiligo (aOR 2.8, 95% CI 1.5-5.1; P<.001) were significantly associated with higher depression levels compared to focal vitiligo. CONCLUSIONS: The findings suggest that vitiligo contributes to an increased risk of severe depression, highlighting the need for integrated dermatological and psychological treatment approaches to address both the physical and mental health aspects of the disease.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".