An Evidence-based Approach to Developing the Collaborative, Client-Centred Nutrition Education (3CNE) Framework and Practice Points
Bibliographic record
Abstract
PURPOSE: The purpose of this, the third phase of a 3-phase research project, was to develop guidelines for client-centred nutrition education (NE). METHODS: A 3-phase study was conducted using a progressive development design, where each phase informed the subsequent phase. Phase 1 was a national online survey of dietitians' perceptions of consumers' NE needs and preferences; results informed the Phase 2 national online survey of consumers about their NE needs and preferences. Phase 3 involved national 2-part teleconference consultations with dietitians to discuss implications of the Phase 2 findings for NE practice. This paper is the report of Phase 3. RESULTS: Discussion group participants were 22 dietitians from around Canada who had been in practice for an average of 14.5 years. Discussions resulted in the development of the Collaborative Client-Centred Nutrition Education (3CNE) conceptual framework and related Practice Points that explicate the complexity of NE practice. CONCLUSION: The 3CNE framework and Practice Points provide a means to inform precepting students and interns, and for use in planning for the professional development of practicing dietitians on providing client-centred NE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.386 | 0.399 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.013 | 0.019 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".