Nutrition and food literacy among young Canadian adults living with type 1 diabetes
Bibliographic record
Abstract
AIM: Nutrition and food literacy encompasses knowledge, skills and confidence to prepare healthy meals. This project aimed to assess and compare the proportion of young Canadian adults (18-29 years old) living with type 1 diabetes and without diabetes (controls) who demonstrated adequate nutritional health literacy. METHODS: This cross-sectional study involved participants completing an online survey that included questions on socio-economic status, nutrition knowledge, confidence and skills in meal preparation and the Short Food Literacy Questionnaire (SFLQ). Proportion of participants with adequate SFLQ score (i.e. ≥34/52) was compared between the groups (two-sample t-test). RESULTS: Among the 236 people living with type 1 diabetes and 191 controls (81.5% women), mean age was 24 ± 3 years for people living with type 1 diabetes and 22 ± 3 years for controls (p < 0.001). More people living with type 1 diabetes reported adequate SFLQ score (people living with type 1 diabetes 88.0% vs. Controls 68.0%; p < 0.001). Similarly, majority of people living with type 1 diabetes prepared their own meals compared to the controls (74.5% vs. 47.6%; p < 0.001). Enhanced SFLQ score was associated with higher cooking skills (p = 0.02) and confidence (p < 0.01) in preparing healthy meals. CONCLUSIONS: Living with type 1 diabetes was associated with greater SFLQ scores among young Canadian adults. Having the independence, the confidence and skills in meal preparation were contributing factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".