US general population food allergy treatment preferences: a discrete choice experiment
Bibliographic record
Abstract
Objective To quantify treatment preferences for food allergy management options (oral immunotherapy, biologic therapy, and allergen avoidance), overall and by sociodemographic strata.Methods A US general population (≥13 years) discrete choice experiment (DCE) conducted comprised of 12 treatment-feature focused DCE choice sets; the Intolerance of Uncertainty─12 Scale (IUS-12); and clinical/demographic questions. Conditional logistic regression analyses were conducted overall and by age, income, urbanization, educational attainment, food and other sociodemographic factors, and presented as odds ratios (ORs) with 95% confidence intervals (CIs).Results Participants (n = 294) mean (standard deviation) age was 47 (19.7) years; 48.6% were male. Treatment features associated with statistically significant odds against preferring a treatment included: 1% reduction in risk of having an exposure resulting in a moderate-to-severe reaction (tested within a range of 0-10%; OR: 1.10 [CI:1.04-1.16] p < 0.01); treatment-related, severe anaphylaxis (0.85; 0.74-0.97 for a 1% risk); gastrointestinal symptoms (0.99; 0.99-0.99 per +1% risk); daily treatment (versus every 2-4 weeks; 0.81; 0.72-0.91); in-clinic administration (versus at-home; 0.76; 0.66-0.87); subcutaneous administration (versus oral; 0.69; 0.61-0.78); three-hour post-treatment physical activity limitation (0.84; 0.77-0.93); one-year reduction in life expectancy (0.87; 0.85-0.89). Preferences for at-home use and against activity limitations was stronger in rural versus urban dwellers; lower-income respondents strongly preferred convenience-related factors (oral, less frequent, at-home administration). Teens strongly preferred (2.75; 1.09–6.9) being bite-safe (versus fully allergic).Conclusion When making food allergy management decisions, US general population respondents had strong preferences for features related to safety and convenience; however, the magnitude of preferences varied by sociodemographic factors. These findings may be pertinent for population-level health decision makers.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".