Experiencing a first food allergic reaction: a survey of parent and caregiver perspectives
Bibliographic record
Abstract
Inadequate knowledge of food allergy and anaphylaxis has been identified by caregivers as an important barrier to coping, and a potential cause of fear and anxiety. This is especially true for those newly diagnosed with food allergy. The objectives of this research study were to better understand the experiences of caregivers of children with newly diagnosed food allergy (first allergic reaction within the last 12 months), and to identify the information gaps between what caregivers received at diagnosis and what they perceived they needed. An online survey was administered to members of Anaphylaxis Canada (a patient support group consisting of approximately 12,000 members). The sampling strategy included an email invitation, and posting of a URL link on the organization’s website. Of 293 respondents, 208 were eligible (newly diagnosed), and 184 consented. 83.5% of respondents reported being anxious to extremely anxious at first diagnosis, and only 38% stated that they had received enough information. Identified gaps included education on food allergy, anaphylaxis management, how to use epinephrine auto-injectors, and coping strategies. Actions taken by families in response to the diagnosis included avoidance of eating out at restaurants (85%), restriction of their child’s activities with other children (61%), limitation of travel (49%), termination of their job (11%), and a reduction in work hours (13%). Survey findings will be supplemented by a follow-up qualitative study to better understand gaps. These findings will then inform the development of educational strategies for patients newly diagnosed with food allergy.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".