<i>Nutritional Risk</i>in Vulnerable Community-Living Seniors
Bibliographic record
Abstract
The purpose of this study was to quantify nutritional risk in a convenience sample of vulnerable, community-living seniors, and to determine patterns of nutritional risk in these seniors. The sample consisted of 367 seniors who provided health, functional, and nutritional risk information during an interview in which the Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire was used. The majority (73.6%) of the sample was female, and the mean age was 79 years. Nutritional risk was identified in 68.7% of the sample, with 44.4% being at high nutritional risk. Common nutritional risk factors were weight change, restricting food, low fruit and vegetable intake, difficulty with chewing, cooking, or shopping, and poor appetite. Principal components analysis identified four independent components within the Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire; these components can be described as low food intake, poor appetite, physical and external challenges, and instrumental activity challenges. Data are sparse on nutritional risk in community-living Canadian seniors; despite methodologic limitations in the recruitment process, this study provides some indication of the level of nutrition problems. The patterns of nutritional risk identified in this vulnerable population may help providers identify useful strategies for ameliorating risk. The Seniors in the Community: Risk Evaluation for Eating and Nutrition questionnaire could be used to identify risk and patterns of risk in Canadian seniors, so that treatment could be individualized.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".