Barriers to food intake in acute care hospitals: a report of the Canadian Malnutrition Task Force
Bibliographic record
Abstract
BACKGROUND: Poor food intake is common in acute care patients and can exacerbate or develop into malnutrition, influencing both recovery and outcome. Yet, research on barriers and how they can be alleviated is lacking. The present study aimed to (i) describe the prevalence of food intake barriers in diverse hospitals and (ii) determine whether patient, care or hospital characteristics are associated with the experience of these barriers. METHODS: Patients (n = 890; 87%) completed a validated questionnaire on barriers to food intake, including perceptions of food quality, just before their discharge from a medical or surgical unit in each of 18 hospitals across Canada. Scores were created for barrier domains. Associations between these barriers and selected patient characteristics collected at admission or throughout the hospital stay and site characteristics were determined using bivariate analyses. RESULTS: Common barriers were being interrupted at meals (41.8%), not being given food when a meal was missed (69.2%), not wanting ordered food (58%), loss of appetite (63.9%) and feeling too sick (42.7%) or tired (41.1%) to eat. Younger patients were more likely (P < 0.0001) to report being disturbed at meals (44.6%) than older patients (33.9%) and missing a meal for tests (39.0% versus 31.0%, P < 0.05). Patients who were malnourished, women, those with more comorbidity, and those who ate <50% of the meal reported several barriers across domains. CONCLUSIONS: The present study confirms that barriers to food intake are common in acute care hospitals. This analysis also identifies that specific patient subgroups are more likely to experience food intake barriers. Because self-reported low food intake in hospital was associated with several barriers, it is relevant to consider assessing, intervening and monitoring barriers to food intake during the hospital stay.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".