The Indirect Costs of Avoidance in Food Allergy Management: A Scoping Review
Bibliographic record
Abstract
Background: Food allergy management requires avoidance of allergenic food. While the direct costs of food allergy management have been described, avoidance may also contribute to time and opportunity costs. We aimed to conduct a scoping review of the peer-reviewed literature on the indirect costs of food allergy, and to characterise these costs through a series of fictitious case studies. Methods: We performed a scoping review, guided by Arskey and O’Malley’s methodological framework, and reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews. Eligible studies included original, peer-reviewed, English language literature with no lower limits to publication dates, which addressed the indirect costs of food allergy, including time and opportunity costs. A search strategy was developed by content experts with experience performing multi-database scoping reviews. The search was performed on 10 July 2023, managed using Rayyan (Cambridge, USA), and screened for eligibility. Results: Searches yielded 104 articles. After deduplication, 96 articles were screened at the title and abstract level; 12 articles were included following full-text screening. Of these, three studies were performed on adults with food allergy, eight studies were based on data collected from caregivers of children with food allergy, and one study made use of data reflecting adults and caregivers of children with food allergy. Collectively, indirect costs were identified as higher amongst those with vs. without food allergy. The few studies on age and food allergy differences (e.g., type and number of food allergies, history of reaction) are equivocal. Conclusions: The limited body of peer-reviewed literature supports that food allergy commonly carries substantial indirect costs across diverse measurement tools, albeit with age-group differences.
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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 | 0.025 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".