The Burden of Moderate to Severe Atopic Dermatitis in Canadian Children: A Cross-Sectional Survey
Bibliographic record
Abstract
OBJECTIVES: Although atopic dermatitis (AD) has significant impacts on quality of life, data from Canada on the subject are limited. This survey aims to assess the burden of moderate to severe AD on quality of life and disease management for pediatric patients and their caregivers in Canada. METHODS: The Eczema Society of Canada conducted an online national cross-sectional survey in English and French. We included children with self-reported moderate to severe AD. We present descriptive statistics from the survey. RESULTS: Of all initial respondents (n = 658), 70% (n = 458) were children or caregivers of children who have moderate or severe AD and were therefore eligible. Among them, 27% (123/451) are managed by a dermatologist, with 71% (174/244) waiting more than 3 months to see a dermatologist. Many respondents (85%, 279/330) feel that their child's AD is not well controlled, and 27% (75/275) have difficulty obtaining treatments for their child's AD. Impaired quality of life was found in 52% of families (200/381), with most reporting sleep disturbances in both the child (70%, 253/361) and the caregiver (55%, 199/361), as well as mental health issues. CONCLUSIONS: This survey demonstrates the medical and psychosocial burden of moderate to severe AD in Canadian children. Quality of life, access to care, and disease management are all areas of concern for patients and their families and warrant attention from individual clinicians and the health care system as a whole.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".