A qualitative study exploring parents’ experiences with epinephrine use for their child’s anaphylactic reaction
Bibliographic record
Abstract
BACKGROUND: Children with life threatening food allergies live with the constant threat of a fatal reaction, and caregivers must always be prepared to treat with an epinephrine auto-injector (EAI). This interpretive phenomenological study explored parents' perceptions and lived experiences with prescribed EAI use for their child. METHODS: The purposive sample included ten parents of five children under 12 years of age, diagnosed with a food allergy and prescribed with an EAI who recently experienced anaphylaxis. Data sources included digitally-recorded semi-structured interviews and a reflexive journal. RESULTS: Eight main themes emerged: perception of anaphylaxis, life challenges, isolation, anxiety, hesitation, guilt, influence of health care professionals, and lessons learned. Parents uniformly described multiple life challenges and feelings of isolation, anxiety and hesitation during a reaction that lead to subsequent guilt. CONCLUSIONS: Handling reactions correctly provided parents with confidence to treat subsequent reactions. Witnessing the effects of an EAI and receiving positive feedback from health care providers further strengthened their confidence to quickly and competently intervene in future reactions.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".