Effects of Dining-focused Life Enhancement Program in Welfare Facilities for Seniors in Japan
Bibliographic record
Abstract
This study evaluated the effectiveness of a life-enhancement program designed to focus on dining conditions in welfare facilities for seniors living in Japan. Effectiveness was specifically evaluated based on whether improvements were achieved in (1) nutritional status, (2) oral health, (3) frequency of fever, and (4) vitality of appetite across three sites. As part of a comprehensive-care initiative that began with dining support, the program consisted of two main components: (1) a 3-month intensive program comprised of (a) collective experiential learning for residents and staff (including nutritionists, nurses, and physiotherapists) and (b) a tailor-made individual program for residents followed by (2) a 3-month continuation program. Participants included 168 individuals (31 males and 137 females) from a total of three facilities (average age was 85.9 [60–104] years). Results showed that the intensive program significantly improved nutritional status (e.g., BMI, caloric intake, and water intake; P < 0.000–0.005) and tongue movement (P < 0.000) while significantly reducing dental-plaque and tongue-coating indices (P < 0.000). Significant improvements were also achieved for degree of appetite and vitality indices (P < 0.000–0.001). However, incidences of fever were not reduced. These findings indicate that the program effectively improved nutritional status, oral health, vitality, and appetite. However, these effects did not sufficiently remain once the program was finished, thus suggesting the need for a continuous intervention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".