Psychosocial and productivity impact of caring for a child with peanut allergy
Bibliographic record
Abstract
BACKGROUND: Limited previous research has assessed the psychosocial burden and productivity impact of caring for a child with peanut allergy and factors associated with burden. The objective of this research was to explore caregiver burden in terms of psychosocial and productivity impact of caring for a child with peanut allergy, the influence of caregiver and child gender on caregiver burden, and factors predicting caregiver burden in peanut allergy. METHODS: A cross-sectional survey of caregivers of children with peanut allergy was conducted in the United Kingdom, and included sociodemographic and clinical questions, EQ-5D, Hospital Anxiety and Depression Scale, Food Allergy Quality of Life-Parental Burden, Food Allergy Independent Measure, and productivity questions. RESULTS: One hundred caregivers (55% female) of children with peanut allergy (aged 4-15 years) completed the survey. Male and female caregivers reported mean levels of anxiety significantly higher than United Kingdom population norms. Caregivers of children with severe peanut allergy reported significant impacts on their careers and health-related quality of life. Neither caregiver nor child gender impacted burden, indicating that male and female caregivers are equally anxious and suffer the same level of negative career, productivity, and health-related quality-of-life impact due to their child's peanut allergy. Caregivers' perceived risk of outcomes related to their child's peanut allergy (e.g., death or severe reaction) as measured by the Food Allergy Independent Measure independently predicted burden. CONCLUSIONS: Caregivers of children with peanut allergy in the United Kingdom experience health-related quality-of-life, psychosocial, and productivity burden; this study demonstrates the high levels of anxiety reported by both male and female caregivers.
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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 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".