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Record W4402881204 · doi:10.1111/all.16332

Development and acceptability of a decision‐aid for food allergy oral immunotherapy in children

2024· article· en· W4402881204 on OpenAlexafffund
Aikaterini Anagnostou, Elissa M. Abrams, Melanie Carver, Edmond S. Chan, Sanaz Eftekhari, Justin Greiwe, Hannah Jaffee, Phil Lieberman, Douglas P. Mack, S. Shahzad Mustafa, Marcus Shaker, David R. Stukus, Julie Wang, Matthew Greenhawt

Bibliographic record

VenueAllergy · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsMcMaster UniversityBC Children's HospitalUniversity of British ColumbiaUniversity of Manitoba
FundersNational Institute of Allergy and Infectious DiseasesGenentechNational Institutes of HealthBausch HealthSanofi GenzymeIncytePublic Health AgencyAsthma and Allergy Foundation of AmericaLEO PharmaPublic Health Agency of CanadaRegeneron PharmaceuticalsSanofiCSL BehringAimmune TherapeuticsAstraZenecaCelldex TherapeuticsAmgenPfizer
KeywordsMedicineDecision aidsReadabilityFood allergyOral immunotherapyFamily medicineAllergyAlternative medicineComputer scienceImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Limited decision-support tools are available to help shared decision-making (SDM) regarding food oral immunotherapy (OIT) initiation. No current tool covers all foods, forms, and pediatric ages for which OIT is offered. METHODS: In compliance with International Patient Decision Aid Standards criteria, this pediatric decision-aid comparing OIT versus avoidance was developed in three stages. Nested qualitative data assessing OIT decisional needs were supplemented with evidence-synthesis from the OIT literature to create the prototype decision-aid content. This underwent iterative development with food allergy experts and patient advocacy stakeholders until unanimous consensus was reached regarding content, bias, readability, and utility in making a choice. Lastly, the tool underwent validated assessment of decisional acceptability, decisional conflict, and decisional self-efficacy. RESULTS: The decision-aid underwent 5 iterations, resulting in a 4-page written aid (Flesch-Kincaid reading level 6.1) explaining therapy choices, risks and benefits, providing self-rating for attribute importance for the options and self-assessment regarding how adequate the information was in decision-making. A total of n = 135 caregivers of food-allergic children assessed the decision-aid, noting good acceptability, high decisional self-efficacy (mean score 85.9/100) and low decisional conflict (mean score 20.9/100). Information content was rated adequate and sufficient, the therapy choices wording balanced, and presented without bias for a "best choice." Lower decisional conflict was associated with caregiver-reported anaphylaxis. CONCLUSIONS: This first pediatric OIT decision-aid, agnostic to product, allergen, and age has good acceptability, limited bias, and is associated with low decisional conflict and high decisional self-efficacy. It supports SDM in navigating the decision to start OIT or continue allergen avoidance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.132
GPT teacher head0.414
Teacher spread0.283 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations9
Published2024
Admission routes2
Has abstractyes

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