Nutrigenomics – perspectives from registered dietitians: a report from the Quebec‐wide e‐consultation on nutrigenomics among registered dietitians
Bibliographic record
Abstract
BACKGROUND: Not all healthcare professionals are familiar with nutrigenomics. However, they recognise that nutrigenomics has great potential for the development of preventive health approaches. The present study aimed to provide an overall picture of the current situation about nutrigenomics in the practice of registered dietitians (RDs) from the province of Quebec (Canada). METHODS: Three hundred and seventy-three RDs members of the Ordre professionnel des diététistes du Québec completed an online survey that included 34 questions, most of which were closed-ended questions. RESULTS: Overall, 76.9% of RDs knew about nutrigenomics. Among RDs with <5 years of experience, 49.2% knew about genetic testing related to nutrition compared to 11.7% for RDs with over 25 years of experience. Currently, 75.9% of RDs working in clinical nutrition in the public sector consider that they do not have the basic knowledge to integrate nutrigenomics in their practice compared to 62.9% for RDs in private practice. When asked about main limitations of genetic testing related to nutrition, RDs considered that genetic testing does not consider the other determinants of health, that genetic testing and their results have poor accuracy, and that there is a lack of scientific evidence. Concerns remained about ethical and legal aspects and its difficult application as a result of poor understanding and/or interpretation by professionals and/or customers. The high costs of these tests were also noted as a limitation. CONCLUSIONS: Registered dietitians know and are interested in nutrigenomics, especially those with less experience, although they do not feel adequately qualified to integrate findings from nutrigenomics into their practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".