Factors associated with eating assistance among long-term care residents: A making the most of mealtimes (M3) analysis
Bibliographic record
Abstract
Introduction: Long-term care (LTC) residents requiring eating assistance are at nutritional risk. Objectives: To identify characteristics of LTC residents requiring eating assistance and examine factors associated with eating challenges. Methods: Secondary data from the Making the Most of Mealtimes study was analyzed including a Mini Nutritional Assessment–Short Form, Patient-Generated Subjective Global Assessment, energy intake, Edinburgh Feeding Evaluation in Dementia, knee height, ulna length, weight and Cognitive Performance Scale. Descriptive statistics, analyses of variance and linear regressions were conducted. Results: 23% of participants required some form of eating assistance. Energy intake was highest for residents requiring eating assistance “Often”. More eating challenges were associated with higher energy intake, lower Body Mass Index, poor nutritional status, and increased cognitive impairment. Conclusion: Residents requiring any eating assistance were more likely to be malnourished and have more eating challenges. Interventions are needed to improve the nutritional status of residents with varying assistance requirements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".