Food allergic teens: education, anaphylaxis and concerns
Bibliographic record
Abstract
Adolescents with food allergy are at particular risk for life threatening anaphylaxis. Management of food allergies includes preventing, recognizing and responding to reactions. Focus groups were held as a preliminary step in the planning and development of effective education for this group. Focus groups were held from January to April 2014. Semi structured interviews were conducted to gather information about what teens with food allergy needed to know and how they like to learn. Interviews were digitally recorded, transcribed and reviewed. 16 adolescents (M = 11, F = 5); age 12-19; 15/16 peanut allergic, 10/16 other food allergens All had epinephrine auto-injectors (EpiPen = 11; Allerject = 5) Teens believe they are well informed; often from parents; however they did identify important topics to incorporate into an education program for teens. Teens need/want to learn more about: cross-contamination, advisory statements on food labels, allergens in non-food products, recognizing a reaction, staying calm during a reaction, teaching friends – signs of a reaction and auto-injector use, communicating confidently with others – strategies for what to say in situations and hands on practice with the auto-injectors. Food allergy related topics teens would like to discuss: travelling, dating, partying, grocery shopping, cooking, symptoms of a reaction versus anxiety, new treatments and research. Concerning themes around anaphylaxis noted were: reactions are dealt with by “waiting it out” or “sleeping it off”; epinephrine is only used if you can’t breathe, can’t talk or think you’re dying); antihistamines can be used as first line treatment. This study highlights knowledge gaps that exist around anaphylaxis in this group and identifies important topics to incorporate into a program. An education program delivered in an effective manner for adolescents that addresses these gaps and provides strategies to help manage food allergy may be helpful and increase confidence for this high-risk group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".