Insights From Caregivers on the Impact of Pediatric Atopic Dermatitis on Families: “I’m Tired, Overwhelmed, and Feel Like I’m Failing as a Mother”
Bibliographic record
Abstract
BACKGROUND: The impact of pediatric atopic dermatitis (AD) on families is largely hidden from view, and AD is commonly misunderstood as a minor skin condition. Few studies have examined the full burden of AD from the family perspective. OBJECTIVE: The aim of the study was to assess the burden of AD on children and families using a caregiver-centered survey. METHODS: A 72-item anonymous online survey was posted on social media sites targeted to or composed of parents of children with AD. It explored the following 9 domains of impact: sleep, social isolation, time requirements, life decisions, family relationship dynamics, energy/fatigue, mental health impacts, and unmet treatment needs. Atopic dermatitis severity was reported by respondents using the Patient-Oriented Eczema Measure. Statistical analyses were conducted using R 3.6.0. RESULTS: Two hundred thirty-five individuals completed the survey during the 1-month period that it was promoted via social media. Caregivers reported frequent sleep disturbance, exhaustion, worry, and social isolation related to their child's AD. CONCLUSIONS: Results highlight the need for psychosocial support and respite care for caregivers of children with AD.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".