High Levels of Psychological Distress, Sleep Disturbance, and Alcohol Use Disorder in Adults With Atopic Dermatitis
Bibliographic record
Abstract
BACKGROUND: The burden of illness associated with atopic dermatitis (AD) is significant and multidimensional, especially in those with moderate to severe disease. OBJECTIVE: Our objective was to evaluate the disease burden of patients with AD in relation to psychological distress, sleep disturbance, and alcohol misuse. METHODS: Patients with AD, attending 2 tertiary referral centers in Dublin, Ireland, were recruited. A series of validated questionnaires were used including the Patient-Oriented Eczema Measure, Dermatology Life Quality Index (DLQI), Center for Epidemiologic Studies-Depression Scale, Quality of Life in Atopic Dermatitis Questionnaire, Alcohol Use Disorders Identification Test, and Pittsburgh Sleep Quality Index. The Eczema Area and Severity Index was calculated contemporaneously with the questionnaire completion. RESULTS: One hundred patients completed the questionnaire, of whom 52% were female. Sixty-three percent of patients experienced impaired quality of life as measured by the DLQI. Higher DLQI scores correlated with decreasing age (r = 0.3277, P < 0.0009). Thirty percent were found to be at risk of clinical depression, and higher Center for Epidemiologic Studies-Depression Scale scores correlated with a younger age and eczema severity. Sleep disturbance was greater in those at risk of depression (mean = 10.40 vs 5.79, P < 0.0001). Patients with moderate to severe AD were more likely to score higher on the Alcohol Use Disorders Identification Test, and 25% met the criteria for alcohol use disorder. In relation to sleep, 73% of patients scored higher than 5 on the Pittsburgh Sleep Quality Index, which signifies poor sleep quality. CONCLUSIONS: Patients with AD endure a significant burden on health with regard to mental well-being, alcohol use, and sleep quality. Clinicians should consider screening patients for these comorbidities.
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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 | 0.002 |
| 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 | 0.000 |
| 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".