Depression and Anxiety in Psoriatic Disease: Prevalence and Associated Factors
Bibliographic record
Abstract
OBJECTIVE: (1) To determine the prevalence of depression and anxiety in patients with psoriatic arthritis (PsA) and to identify associated demographic and disease-related factors. (2) To determine whether there is a difference in the prevalence of depression and anxiety between patients with PsA and those with psoriasis without PsA (PsC). METHODS: Consecutive patients attending PsA and dermatology clinics were assessed for depression and anxiety using the Hospital Anxiety and Depression Scale. Patients underwent a clinical assessment according to a standard protocol and completed questionnaires assessing their health and quality of life. T tests, ANOVA, and univariate and multivariate models were used to compare depression and anxiety prevalence between patient cohorts and to determine factors associated with depression and anxiety. RESULTS: We assessed 306 patients with PsA and 135 with PsC. There were significantly more men in the PsA group (61.4% vs 48% with PsC) and they were more likely to be unemployed. The prevalence of both anxiety and depression was higher in patients with PsA (36.6% and 22.2%, respectively) compared to those with PsC (24.4% and 9.6%; p = 0.012, 0.002). Depression and/or anxiety were associated with unemployment, female sex, and higher actively inflamed joint count as well as disability, pain, and fatigue. In the multivariate reduced model, employment was protective for depression (OR 0.36) and a 1-unit increase on the fatigue severity scale was associated with an increased risk of depression (OR 1.5). CONCLUSION: The rate of depression and anxiety is significantly higher in patients with PsA than in those with PsC. Depression and anxiety are associated with disease-related factors.
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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 | 0.001 | 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) | 0.001 | 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".