The Relationship between Texture-Modified Diets, Mealtime Duration, and Dysphagia Risk in Long-Term Care
Bibliographic record
Abstract
Many long-term care (LTC) residents have an increased risk for dysphagia and receive texture-modified diets. Dysphagia has been shown to be associated with longer mealtime duration, and the use of texture-modified diets has been associated with reduced nutritional intake. The current study aimed to determine if the degree of diet modification affected mealtime duration and to examine the correlation between texture-modified diets and dysphagia risk. Data were collected from 639 LTC residents, aged 62–102 years. Nine meal observations per resident provided measures of meal duration, consistencies consumed, coughing and choking, and assistance provided. Dysphagia risk was determined by identifying residents who coughed/choked at meals, were prescribed thickened fluids, and/or failed a formal screening protocol. Degree of texture modification was derived using the International Dysphagia Diet Standardization Initiative Functional Diet Scale. There was a significant association between degree of diet modification and dysphagia risk (P < 0.001). However, there was no association between diet modifications and mealtime duration, even when the provision of physical assistance was considered. Some residents who presented with signs of swallowing difficulties were not prescribed a texture-modified diet. Swallowing screening should be performed routinely in LTC to monitor swallowing status and appropriateness of diet prescription. Physical assistance during meals should be increased.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".