Exploring Challenges Faced by Adults Living With Celiac Disease: A Food Literacy Perspective
Bibliographic record
Abstract
BACKGROUND: Coeliac disease (CD) is an autoimmune disorder treated with a gluten-free diet (GFD), requiring substantial changes in food choices and eating habits. This study explores the challenges faced by adults living with CD focusing on the theme of food literacy (FL), namely functional, relational, and system FL competencies. METHODOLOGY: A secondary analysis of data obtained through an online questionnaire was conducted. Adults living with CD in Québec, Canada and subscribed to Coeliaque Québec's newsletter were invited to complete a questionnaire. Using the critical incident method, respondents described a negative experience in their journey living with CD. Content analysis was done in a deductive and inductive manner, based on the 2022 Slater Food Literacy framework adapted to CD. RESULTS: A total of 743 patients were included in the analysis. The qualitative analysis resulted in 11 codes under the three themes of FL. Patients reported challenges in finding reliable nutrition and medical information, managing a GFD in social settings, explaining CD and preventing gluten contamination, preparing balanced gluten-free (GF) meals, and making informed food choices. Patients reported on the negative impact of the GFD on their relationship with food, and how CD inhibits conviviality. Finally, patients addressed the need to advocate for GF food access in grocery stores and restaurants. CONCLUSIONS: This study highlights the broad impacts of effectively managing CD and the GFD on patients' functional, relational and system FL competencies. Future research should explore how social and economic factors further interact with FL competencies of adults living with CD.
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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 | 0.003 | 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 | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".