Training of Registered Dietitian Nutritionists to Improve Culinary Skills and Food Literacy
Bibliographic record
Abstract
OBJECTIVE: To understand if a culinary medicine training program increases food literacy, culinary skills, and knowledge among practicing registered dietitian nutritionists (RDN). METHODS: Prepost study design evaluating pilot test of RDN train-the-trainer curriculum from September, 2019 to January, 2020. RESULTS: On average, results indicate an increase in culinary nutrition skills (mean difference, 6.7 ± 4.4; P < 0.001; range, 10-30) and a significant increase in 5 of the 8 food literacy factors. Through process evaluation, RDNs rated the training as extremely useful to their practice (mean, 4.4 ± 0.3). CONCLUSIONS AND IMPLICATIONS: Registered dietitian nutritionist participants increased culinary nutrition skills with statistically significant scores across all individual measures. This study describes an RDN training curriculum in culinary medicine across a diverse group of practicing RDNs from a large county health care system. Culinary medicine shows a promising impact on promoting nutrition skills and confidence; however, it warrants further assessment.
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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 | 0.001 | 0.003 |
| 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) | 0.005 | 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".