Evaluation of a paediatric gluten-free food guide by children and youth with coeliac disease, their parents and health care professionals
Bibliographic record
Abstract
Abstract There are currently no universal evidence-based nutrition guidelines that address the gluten-free (GF) diet for children/youth (4–18 years). A GF food guide was created to help children/youth with coeliac disease (CD) and their families navigate the complexities of following a GF diet. Guide formation was based on pre-guide stakeholder consultations and an evaluation of nutrient intake and dietary patterns. The study objective was to conduct an evaluation on guide content, layout, feasibility and dissemination strategies from end-stakeholder users (children/youth with CD, parents/caregivers and health care professionals). This is a cross-sectional study using a multi-method approach of virtual focus groups and an online survey to conduct stakeholder evaluations. Stakeholders included children/youth (4–18 years), their parents/caregivers in the coeliac community (n 273) and health care professionals (n 80) with both paediatric and CD experience from across Canada. Thematic analysis was performed on focus group responses and open-ended survey questions until thematic saturation was achieved. χ2 and Fisher’s exact statistical analyses were performed on demographic and close-ended survey questions. Stakeholders positively perceived the guide for content, layout, feasibility, ethnicity and usability. Stakeholders found the material visually appealing and engaging with belief that it could effectively be used in multi-ethnic community and clinical-based settings. Guide revisions were made in response to stakeholder consultations to improve food selection (e.g. child-friendly foods), language (e.g. clarity) and layout (e.g. organisation). The evaluation by end-stakeholders provided practical and patient-focused feedback on the guide to enable successful uptake in community and clinical-based settings.
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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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".