The burden of food allergy on children and teens: A systematic review
Bibliographic record
Abstract
BACKGROUND: Over the last two decades, researchers have placed increasing attention on understanding how food allergy affects the health-related quality of life (HRQL) and psychosocial well-being of children and teens. In response, a number of reviews have been published that aim at synthesizing the literature. However, many of these papers focus narrowly on HRQL or suffer from methodological limitations. METHOD: The current review aims to fill this gap by providing a comprehensive overview of the burden of pediatric food allergy by synthesizing the quantitative and qualitative literature. RESULTS: Findings from the present review provide evidence of reduced HRQL among children and teens with food allergy, particularly older children and those with more severe manifestations of the condition. In comparison to HRQL, the link between food allergy and psychosocial functioning is less clear; however, some evidence can be cited linking food allergy to greater levels of psychological distress. Qualitative evidence suggests that the burden of pediatric food allergy largely stems from worries surrounding exposures outside of the home and the social consequences of the condition. The current review also highlights several gaps in the literature, including a paucity of longitudinal research, research focused on predictors of psychological distress among children and teens with food allergy as well as a dearth of studies comparing rates of bullying in food-allergic and non-food-allergic samples. CONCLUSION: More emphasis should be placed on not only alleviating the social and psychological consequences of food allergy, but also on identifying and assisting those most acutely burdened by the condition.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".