Nutrition Risk in Home-Bound Older Adults: Using Dietician-Trained and Supervised Nutrition Volunteers for Screening and Intervention
Bibliographic record
Abstract
Nutrition screening and early intervention in home-bound older adults are key to preventing unfavourable health outcomes and functional decline. This pilot study's objectives were (a) to test the reliability of the Elderly Nutrition Screening Tool (ENS) when administered by dietician-trained and supervised nutrition volunteers, and (b) to explore the feasibility of volunteers' doing nutrition screening and intervention for home-bound older adults receiving home care services. Both participating clients ( n = 29) and volunteers ( n = 15) were community-dwelling older adults. Volunteers met with participating clients, assessed nutritional risk with the ENS, provided nutritional education, and developed and helped implement intervention plans. To assess ENS (c) inter-rater reliability, we compared results obtained by nutrition volunteers and a dietician. Agreement was high (> or =80%) for most items but was higher among volunteers than between volunteers and the dietician. We conclude that nutrition volunteers can assist in screening and educating older adults regarding nutritional risks, but intervention is best left to professionals.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".