Winnipeg-based elementary school teachers’ perspectives on food allergy management and practices: a qualitative investigation
Bibliographic record
Abstract
Introduction Food allergy affects approximately 7.0% of children worldwide. Children spend most of their waking hours at school, yet, teachers, who have the majority of contact with children during all school day, have variable food allergy-related knowledge. Objective We aimed to identify how Winnipeg-based elementary school teachers manage food allergic reactions in their classrooms and schools. Methods Winnipeg-based public and private school teachers who taught Kindergarten to Grade 6 were recruited via social media and word-of-mouth, and were interviewed virtually consent. Interviews were recorded and transcribed verbatim. The study followed a pragmatic framework. Data were analysed via thematic analysis. Member checking was done to enhance study rigour. Results We interviewed 16 teachers, who taught primarily public school and between Kindergarten Grade 3. The manuscript presents four identified themes. Theme 1 (“Each classroom is a case-by-case basis”) describes the minimal standardization and inconsistent policies and education between and within schools. Theme 2 (Food allergy-related knowledge, experience and supports shape teachers’ confidence) reflected teachers’ variable confidence/perceived food allergy knowledge. Theme 3 (Food allergy could be a more prominent conversation for teachers to “debunk the myths”) captured the lack of standardized food allergy education for teachers. Theme 4 (Communication between all parties is essential) described how teachers’ reliance on school staff, families and students to effectively communicate. The published paper presents two identified themes. Theme 1 (COVID-19 restrictions made mealtimes more manageable) depicted how pandemic-related restrictions, such as enhanced cleaning, handwashing, and emphasis on no food sharing, were deemed positively influencing food allergy management. Theme 2 (Food allergy management was indirectly adapted to fit changing COVID-19 restrictions) captured how food allergy management had to be adapted to pandemic restrictions. Teachers also had less nursing supports and virtual training. Conclusions Teachers’ food allergy management was informed by their knowledge and lived experience, guided by school policies, and students’ needs. Continuation of pandemic-related restrictions may enhance food allergy management in the classroom. Teachers unanimously wanted further food allergy education and training, and resources to improve communication gaps and language barriers. More training throughout the school year and multimedia resources may be beneficial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".