<i>Nutrition in Primary Health Care: Using a Delphi Process</i> To Design New Interdisciplinary Services
Bibliographic record
Abstract
PURPOSE: A modified Delphi process was used to identify key features of interdisciplinary nutrition services, including provider roles and responsibilities for Ontario Family Health Networks (FHNs), a family physician-based type of primary care. METHODS: Twenty-three representatives from interested professional organizations, including three FHN demonstration sites, completed a modified Delphi process. Participants reviewed evidence from a systematic literature review, a patient survey, a costing analysis, and key informant interview results before undertaking the Delphi process. Statements describing various options for services were developed at an in-person meeting, which was followed by two rounds of e-mail questionnaires. Teleconference discussions were held between rounds. RESULTS: An interdisciplinary model with differing and complementary roles for health care providers emerged from the process. Additional key features addressing screening for nutrition problems, health promotion and disease prevention, team collaboration, planning and evaluation, administrative support, access to care, and medical directives/delegated acts were identified. Under the proposed model, the registered dietitian is the team member responsible for managing all aspects of nutrition services, from needs assessment to program delivery, as well as for supporting all providers' nutrition services. CONCLUSIONS: The proposed interdisciplinary nutrition services model merits evaluation of cost, effectiveness, applicability, and sustainability in team-based primary care service settings.
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 | 0.164 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".