Association between Skin Conditions and Depressive Disorders in Community-Dwelling Older Adults
Bibliographic record
Abstract
BACKGROUND: Depression is frequently observed in dermatologic patients. However, the association between depressive disorders and skin conditions has rarely been explored through population-based studies, especially within older-adult populations. OBJECTIVE: To test this association in a representative sample of an older-adult population. METHODS: Data came from the Survey on the Health of the Elderly (Enquête sur la Santé des Aìnés [ESA]), a longitudinal survey conducted in Quebec among 2,811 older adults. Cross-lagged panel models were used to simultaneously examine cross-sectional and longitudinal relationships between the presence of skin conditions and depressive disorders. RESULTS: The prevalence of skin conditions was 13%, and the prevalence of depressive disorders among participants presenting with skin conditions was 11%. Our results indicated significant cross-sectional correlation (ζ = 0.20) between skin conditions and depressive disorders, but no longitudinal association was observed. CONCLUSION: Our results reinforce the hypothesis that skin conditions and depressive disorders are concurrently associated in older adults. However, no evidence of the predictive effect of skin problems on depression (and vice versa) was found in our community sample. Despite the deleterious effect of the coexistence of these problems in older adults, studies are lacking. This article highlights the importance of this issue and emphasizes the need for further research on this topic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".