The perceived impact of pediatric food allergy on mental health care needs and supports: A pilot study
Bibliographic record
Abstract
Background Evidence suggests a mental health impact of food allergy on affected children and their families; however, little is known about health care professionals' understanding of these impacts and the resources available to patients and their families. Objective Our aim was to conduct a pilot study examining health care professionals' perceptions of the psychosocial and financial burden of food allergy to identify gaps in education and resources and thus better support families with food allergy moving forward. Methods Between February 20 and November 19, 2020, we conducted audiorecorded interviews (n = 6) and profession-specific focus groups (n = 2 [representing 7 individuals]). The participants included pediatric allergists, allergy nurse educators, and clinical dietitians who were directly involved in pediatric food allergy care. The interviews were recorded and transcribed verbatim. Thematic analysis was subsequently applied to identify the main themes. Results Our study consisted of an interdisciplinary group of Manitoban health care providers (N = 13) who were directly involved with pediatric food allergy care. We identified 3 main themes from these interviews: anxiety among families with food allergy, which is a common comorbidity; limited resources available within current public infrastructure; and empowerment through education . These themes describe issues surrounding access to information and resources and how this can affect anxiety and parenting styles among families with food allergy. Conclusions Health care professionals perceive that many families experience anxiety as a result of their child's food allergy. They further advocate that access to information and suitability of public resources be considered when planning for related programs.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".