Delegation Opportunities for Malnutrition Care Activities to Dietitian Assistants—Findings of a Multi-Site Survey
Bibliographic record
Abstract
Approximately one-third of adult inpatients are malnourished with substantial associated healthcare burden. Delegation frameworks facilitate improved nutrition care delivery and high-value healthcare. This study aimed to explore knowledge, attitudes, and practices of dietitians and dietitian assistants regarding delegation of malnutrition care activities. This multi-site study was nested within a nutrition care implementation program, conducted across Queensland (Australia) hospitals. A quantitative questionnaire was conducted across eight sites; 87 dietitians and 37 dietitian assistants responded and descriptive analyses completed. Dietitians felt guidelines to support delegation were inadequate (agreement: <50% for assessment/diagnosis, care coordination, education, and monitoring and evaluation); dietitian assistants perceived knowledge and guidelines to undertake delegated tasks were adequate (agreement: >50% food and nutrient delivery, education, and monitoring and evaluation). Dietitians and dietitian assistants reported confidence to delegate/receive delegation (dietitian agreement: >50% across all care components; dietitian assistant agreement: >50% for assessment/diagnosis, food and nutrient delivery, education, monitoring and evaluation). Practice of select nutrition care activities were routinely performed by dietitians, rather than assistants (p < 0.001 across all nutrition care components). The process for care delegation needs to be improved. Clarity around barriers and enablers to delegation of care prior to implementing reforms to the current models of care is key.
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 | 0.005 | 0.012 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".