Blenderized Tube Feeding: A Survey of Dietitians’ Perspectives, Education, and Perceived Competence
Bibliographic record
Abstract
Increasingly, patients and their caregivers desire blenderized tube feeding (BTF) as an alternative or adjunct to commercial enteral formula. Although dietitians are central in the care of tube fed patients, they do not necessarily have training or experience with BTF and may therefore find it challenging to manage the nutrition of patients who opt for this enteral nutrition approach. To describe dietitians' perspectives, perceived competence, and education on BTF, a cross-sectional survey was conducted by use of an original questionnaire. Dietitians with the authority to practice enteral nutrition in the province of British Columbia, Canada, were included in the study (n = 715). Of the 221 respondents (31% response rate), 28% reported being knowledgeable about BTF, and 24% reported confidence managing patients on BTF. Few agreed they had the expertise to design, administer, or teach administration of BTF (29%, 15%, and 24%, respectively). In regards to education, 27% of respondents did not have BTF education of any kind, and those with BTF education reported it to be primarily derived from informal sources such as self-directed study and learning from colleagues or patients. These results indicate that among dietitians, formal BTF education is uncommon, and there is limited perceived competence on BTF practice.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| 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".