Work Productivity Loss and Health-Related Quality of Life in People Living with Atopic Dermatitis: A Canada-Wide Cross-Sectional Study
Bibliographic record
Abstract
Abstract: Background: As new therapies for atopic dermatitis (AD) are developed, it is increasingly important to assess how AD impacts patient-reported outcomes. Objective: To quantify productivity loss, work impairment, and health-related quality of life (HRQOL) among individuals with different levels of AD severity. Methods: Employed adults from across Canada with a history of AD completed a web-based questionnaire. AD severity was assessed using the Patient-Oriented Eczema Measure; productivity loss, work impairment, and HRQOL were evaluated by the Valuation of Lost Productivity, Work Productivity and Activity Impairment, and Veterans RAND 12-item Health Survey (VR-12) questionnaires, respectively. The association between outcomes and AD severity was evaluated using multiple linear regression. Results: Among the 200 participants, productivity loss increased with AD severity, but this was not statistically significant. Work impairment was greater in those with moderate (adjusted difference 13.6%[95% CI: 3.0, 24.1]) and severe to very severe AD (adjusted difference 20.5%[95% CI: 8.3, 32.7]) compared to those with no or mild AD. VR-12 health utility was lower for individuals with moderate (adjusted difference −0.08[95% CI: −0.16, −0.01]) and severe to very severe AD (adjusted difference −0.17[95% CI: −0.26, −0.08]) compared to those with mild or no AD. Conclusions: Greater AD severity was associated with greater work impairment and worse HRQOL.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".