The Role of Dietitians in Providing Guidance: On the Use of Natural Health Products
Bibliographic record
Abstract
PURPOSE: Dietitians are experts on nutrition, and yet much uncertainty remains about their readiness and capacity to address a rapidly evolving marketplace of novel foods, nutrients, and nutrient-like substances (i.e., natural health products [NHPs]), which are available to consumers. In 2011, we conducted a qualitative examination of current thinking on the scope of practice, as well as barriers to and facilitators of dietitians' role as experts in providing guidance on NHP use. METHODS: We sought rich descriptions of existing and future dietetic competencies with NHPs. We therefore conducted six focus groups. Participants were 18 dietitians practising in rural settings and 21 practising in urban settings of Atlantic Canada. RESULTS: Themes identified included people, products, and information; future education and training underlay these themes. The "food first" philosophy of dietetics practice was a primary convergent theme, the consensus being that NHPs can be used for select populations, lifestyles, and health conditions. The less food-related the NHP, the more divergent opinions were on specific competencies and scope of practice; focus group participants often referred to the importance of "doing no harm" and evidence-based practice. CONCLUSIONS: Dietitians' achievement of competency in providing guidance on NHPs will require core, consistent, and cross-disciplinary information and competencies, as well as enhanced integrative practice models.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".