Registered Dietitians’ Roles in Decision-making Processes For PEG Placement in the Elderly
Bibliographic record
Abstract
PURPOSE: The role of registered dietitians (RDs) in decision-making for percutaneous endoscopic gastrostomy (PEG) placement was explored. The ethical climate in their workplace and the relationship between decision-making and the ethical climate were examined. METHODS: The survey included 67 RDs in complex continuing care and long-term care settings in Ontario. Descriptive statistics were used to describe roles, ethical climate, and professional characteristics. Pearson's and nonparametric correlations were used to examine relationships between roles, ethical climate, and professional characteristics. RESULTS: Among the respondents, 97% thought RDs had a role in decision-making processes. The majority of RDs were usually or always involved in two roles: identifying relevant nutrition issues (91.2%) and discussing feeding options and alternatives (80.7%). Dietitians' roles in decision-making processes were more extensive when their relationship with physicians was positive (r=0.321, P=0.016), they had adequate knowledge (r=0.465, P<0.001) and adequate skills (r=0.520, P<0.001), and they were more satisfied with their role (r=0.554, P<0.001). CONCLUSIONS: Registered dietitians performed a variety of roles in decision-making processes concerning PEG placement in the elderly. A positive working relationship with physicians, knowledge, skills, and role satisfaction significantly increase RDs' involvement with patients and families.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".