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Record W4383619793 · doi:10.1186/s13223-023-00813-3

“There definitely should be some more help for families”: a call for federal support for families managing pediatric food allergy

2023· letter· en· W4383619793 on OpenAlexafffundvenueabout
Manvir Bhamra, Zoe Harbottle, Michael A. Golding, Moshe Ben‐Shoshan, Jennifer Gerdts, Jennifer L. P. Protudjer

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2023
Typeletter
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsPROTO Manufacturing (Canada)George & Fay Yee Centre for Healthcare InnovationResearch ManitobaAllerGenMcGill UniversityChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersCanadian Allergy, Asthma and Immunology Foundation
KeywordsFood allergyFamily medicineAllergyMedicineBusinessImmunology

Abstract

fetched live from OpenAlex

This study is part of an overarching, mixed methods, intervention study involving Winnipeg families with children age < 6 years, who have allergist-diagnosed cow’s milk allergy. Each family received a home-delivered, subsidy kit of milk allergy-friendly foods (valued at ~$50 per kit) every second week between March and August 2022. Approximately one month prior to the end of the study, a parent from each family completed an in-depth, semi-structured interview (Table 1 ) moderated by an experienced qualitative interviewer (MG) and supported by a research assistant (MB or ZH). Interviews were audio-recorded and transcribed verbatim. Data were analysed thematically [ 10 ] by two research assistants (MB and ZH) who worked independently, and who had regular discussions with two experienced qualitative researchers (MG and JP). Descriptive data, collected at baseline, were analysed using Stata® Version 17.0 (College Station, TX). This study was approved by the University of Manitoba Health Research Ethics Board HS25168 (H2021:340). Eight parents, all from different families, completed qualitative interviews. On average, families were composed of 4.38 ± 1.78 members, and had an average monthly household income of $3764.29. The median index child was age 2 years and with equal numbers of boys and girls represented. All index children had milk allergy; other reported allergies included peanut (4/8), egg (4/8) and soy (each n = 3/8). Parents were, on average, age 29.9 ± 4.4 years, most (n = 5) had post-secondary education and few (n = 2) had food allergy themselves. In our thematic analysis, we identified one theme: “There definitely should be some more help for families.” This theme, which was indeed a participant quote, captured what parents perceived to be the most meaningful type of support for families with young children managing food allergy. Within this theme, parents described various ways in which they would benefit from financial support to help offset the price of foods, ranging from “ gift cards ” to continued subsidies, such as that provided by our intervention. Interestingly, parents spoke against a tax credit. For example, one parent noted: [I] would prefer probably the subsidy like this portion of it rather than a tax credit . In contrast, others described how they would have preferred an enhanced ability to select their own foods, rather than being restricted to those provided by the subsidy, as the desire to select their own foods was important. This was captured in quotes from parents who succinctly expressed their sentiments: for people, like to pick, whatever they want like the difficulties of finding dairy-free items in Winnipeg . While food procurement was perceived as challenging for some families, a more frequently described concern was the cost of allergy-friendly foods, which was cost-prohibitive for some, particularly as the child may refuse the food. As one participant described: [Additional support] would be a huge relief for a lot of people especially if allergies are new, like you don’t really want to be spending $7 to $10 on one new product just for your child to say I am not eating it… that is the big stressful part of it Another parent also spoke to the high cost of allergy-friendly foods: How expensive things really are! There is nothing that has a label of allergy-friendly that is cheap in any way. So trying to, you know, bring in an income and also pay for food at the same time is horrible. So many people go through and I believe [additional support] can help so many people. While families in our study appreciated the subsidy, families spoke about what they perceived to be the best way to provide additional support to offset the cost of allergy-friendly foods. These perceptions were elegantly captured in the statement of one participant: I would say actually like helping with the cost of food items would be like the best.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.030
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.016
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0170.002
Scholarly communication0.0030.004
Open science0.0030.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.084
GPT teacher head0.363
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2023
Admission routes4
Has abstractyes

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