The Burden of Disease in Alopecia Areata: Canadian Online Survey of Patients and Caregivers
Bibliographic record
Abstract
BACKGROUND: Alopecia areata (AA) is associated with negative impacts on the quality of life (QoL). Data on this impact are lacking for Canadian patients and their caregivers. OBJECTIVE: This study aims to investigate the burden of AA on Canadian patients and their caregivers. METHODS: We created 4 online surveys for patients 5-11 years old, 12-17 years old, and ≥18 years old and for caregivers of children (<18 years old) with AA. These were disseminated through the Canadian Alopecia Areata Foundation (CANAAF) website and to dermatologists across Canada. RESULTS: In total, 115 adult patients (n=100, 87%, female), 14 pediatric patients (n=13, 92.9%, female), and 15 caregivers completed the surveys online. The majority (n=123, 95%) of patients felt uncomfortable or self-conscious about their appearance. Camouflaging hair loss with hats, scarves, and hairpieces was a common practice for 11 (78.6%) pediatric and 84 (73%) adult patients. Avoidance of social situations was reported by 8 (57.1%) pediatric and 75 (65.2%) adult patients. Constant worry about losing the achieved hair growth was a concern for 8 (57.1%) pediatric and 75 (65.2%) adult patients. On a scale of 1-5, the mean score of caregivers' own feelings of sadness or depression about their child's AA was 4.0 (SD 0.9) and of their feelings of guilt or helplessness was 4.2 (SD 1.2). The impact on the QoL was moderate for both children and adults. Based on the Adjustment Disorder New Module-20 (ADNM-20), 71 (61.7%) of 115 patients were at high risk of an adjustment disorder. Abnormal anxiety scores were recorded in 40 (34.8%) patients compared to abnormal depression scores in 20 (17.4%) patients. CONCLUSIONS: This study confirmed a significant burden of AA on Canadian patients' and caregivers' QoL.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".