Knowledge of Sugars Consumption and the WHO Sugars Guideline among Canadian Dietitians and Other Health Professionals
Bibliographic record
Abstract
Purpose: The objective was to assess knowledge related to sugars consumption and World Health Organization (WHO) sugars guideline among Canadian dietitians and other health professionals. Methods: A multiple-choice style survey was administered at Dietitians of Canada and Canadian Diabetes Association conferences in 2014. Results: The study showed that only 12% of the surveyed respondents (n = 335) in 2014 were able to correctly identify the amount of added sugars consumed by Canadians, whereas two-thirds overestimated this amount. About 10% of the respondents knew that the 10% guideline by WHO for free sugars was based on evidence related to dental caries. Registered dietitians had relatively better knowledge of Canadian sugars consumption (P = 0.003), but not of the WHO free sugars guideline compared with other surveyed health professionals such as medical doctors or nurses. Conclusions: Knowledge gaps existed among surveyed Canadian health professionals on topics related to sugars consumption and the WHO sugars guideline. Future research should focus on tools to support better communication of sugars guideline and consistent use of sugars terminology.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".