Associations with food allergy‐related psychological distress in a global sample of adults, children and caregivers
Bibliographic record
Abstract
OBJECTIVE: Food allergy (FA) impacts health-related quality of life and mental health. Understanding what variables are associated with psychological distress can help healthcare providers direct patients to appropriate support. As part of the study, Global Access to Psychological Services (GAPS) for FA and associations with FA-related psychological distress were explored in adults with FA and caregivers of children with FA. METHODS: Participants completed online surveys in seven languages. Participants reported the types of FA-related distress they or their child experienced, along with demographic and FA-related information. Associations with distress were analysed using regression models. RESULTS: N = 1329 adults with FA and N = 1373 caregivers of children with FA from 27 countries participated. Of the 21 different types of distress selected, anxiety about an allergic reaction was the most common (62.5% adults; 72.6% caregivers). Females reported significantly more types of distress than males (p < 0.001). There were significant differences between countries (all p < 0.05-0.001); participants in Australia, Brazil, Canada, and the United Kingdom consistently reported more types of distress than European countries or the United States. In regression models, country of residence, number of FAs, and symptoms were significantly associated with distress. Additional associations included adrenaline autoinjector (AAI) prescription, being female, anaphylaxis and comorbidities in adults; in caregivers having a younger child, longer time elapsed since FA diagnosis, being female, AAI prescription and anaphylaxis; and in children being older and living longer with FA. CONCLUSIONS: FA-related distress is experienced differently across countries. Understanding associations with types of distress can help direct healthcare services and psychological support to where it is needed most.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".