More Than Just not Being Alone: The Number, Nature, and Complementarity of Meal-Time Social Interactions Influence Food Intake in Hospitalized Elderly Patients
Bibliographic record
Abstract
PURPOSE: This study evaluated the social facilitation of elderly patients' food intake beyond the presence of mealtime companions by assessing various relationships. The study examined the relationships between patients' intake and (a) the number of interpersonal exchanges with mealtime fellows, (b) the nature of behaviors expressed by the patients themselves and their fellows, and (c) the degree of complementarity between these. DESIGN AND METHODS: Interpersonal exchanges and intake were observed on repeated mealtime occasions (n = 1,477) nested within 32 geriatric patients (21 women, 11 men; age, M = 78.8 years). Participants' intake was estimated from plate leftovers. Interpersonal behaviors were examined for both participants and patients with whom they interacted in terms of agency and communion dimensions, following the interpersonal circumplex model of human interaction. With the use of multilevel regression analyses, the number, nature, and complementarity of behaviors that participants engaged in and were exposed to on a given meal were computed to test their impact on intake. RESULTS: The total amount of interaction between patients was positively related to intake. The effect was significant for both participants' own behaviors and those to which they were exposed, and it varied with the nature of the interaction; effects were significant in terms of frequency and complementarity for communal behaviors, and complementarity only for agentic behaviors. Effects could only partly be explained by meal duration effects. IMPLICATIONS: The results provide support for the effect of the number, nature, and complementarity of mealtime interpersonal behaviors on the food intake of elderly patients, and they may inspire new approaches to ensure adequate intake in this malnutrition-prone population.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".