Barriers and enablers in the implementation of a standardised process for nutrition care: findings from a multinational survey of dietetic professionals in 10 countries
Bibliographic record
Abstract
BACKGROUND: To explore the barriers and enablers experienced by nutrition and dietetic professionals in the implementation of the standardised Nutrition Care Process (NCP) across 10 different countries. NCP related beliefs, motivations and values were investigated and compared. METHODS: A validated online survey was disseminated to nutrition and dietetics professionals in 10 countries in the local language during 2017. Cross-sectional associations and differences between countries were explored for level of implementation, barriers/enablers and attitudes/motivation among the respondents. RESULTS: Higher NCP implementation was associated with greater occurrence of enabling aspects, as well as fewer occurrences of barriers. The most common enabler was 'recommendation by the national dietetic association' (69%) and the most common barrier was 'lack of time' (39%). A longer experience of NCP use was associated with a more positive attitude towards all NCP aspects. Differences between countries were identified, regarding both the occurrence of barriers/enablers and attitudes/motivations. CONCLUSIONS: Implementation efforts need to be tailored to country-specific contexts when implementing a new standard of care framework among nutrition and dietetic professionals. Additional research is needed to further assess the management and workplace strategies to support the development of nutrition and dietetics professionals in multidisciplinary healthcare organisations.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".