Predictors of nutrition care process knowledge and use among dietitians internationally
Bibliographic record
Abstract
BACKGROUND: The nutrition care process (NCP) and its associated standardised terminology (NCPT, referred to collectively as NCP/T) forms a problem-solving framework fundamental to dietetic practice. Global implementation would assist in confirming outcomes from dietetic care, but implementation rates have varied between countries. We investigated which factors predict NCP/T knowledge and use among dietetic professionals in an international cohort, aiming to understand how implementation can be strengthened. METHODS: The validated International NCP Implementation Survey was disseminated to dietitians in 10 countries via professional networks. Implementation, attitudes and knowledge of the NCP/T along with workplace and educational data were assessed. Independent predictive factors associated with higher NCP/T knowledge and use were identified using backward stepwise logistic regression. RESULTS: Data from 6149 respondents was used for this analysis. Enablers that were independent predictors of both high knowledge and frequent use of NCP/T were peer support, recommendation from national dietetic association and workplace requirements (all p < 0.001). Country of residence and working in clinical settings (p < 0.001) were demographic characteristics that were independent predictors of high knowledge and frequent use of NCP/T. A high knowledge score was an independent predictor of frequent NCP/T use (p = 0.002). CONCLUSIONS: Important modifiable enablers for NCP knowledge and use rely on organisational management. National dietetic organisations and key stakeholders such as employers are encouraged to integrate active NCP/T support in their leadership initiatives. This could take the form of policies, formalised and structured training strategies, and informatics initiatives for the integration in electronic health records.
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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 | 0.000 |
| 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".