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Record W2005589297 · doi:10.1080/21551197.2013.809673

Dietary, Food Service, and Mealtime Interventions to Promote Food Intake in Acute Care Adult Patients

2013· review· en· W2005589297 on OpenAlexaff
Grace Cheung, Lisa Pizzola, Heather Keller

Bibliographic record

VenueJournal of Nutrition in Gerontology and Geriatrics · 2013
Typereview
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsUniversity of WaterlooUniversity of Guelph
Fundersnot available
KeywordsMedicineMalnutritionPsychological interventionEnvironmental healthFood serviceFood intakeIntervention (counseling)Randomized controlled trialAppetiteGerontologyNursingSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Malnutrition is common in acute care hospitals. During hospitalization, poor appetite, medical interventions, and food access issues can impair food intake leading to iatrogenic malnutrition. Nutritional support is a common intervention with demonstrated effectiveness. "Food first" approaches have also been developed and evaluated. This scoping review identified and summarized 35 studies (41 citations) that described and/or evaluated dietary, foodservice, or mealtime interventions with a food first focus. There were few randomized control trials. Individualized dietary treatment leads to improved food intake and other positive outcomes. Foodservices that promote point-of-care food selection are promising, but further research with food intake and nutritional outcomes is needed. Protected mealtimes have had insufficient implementation, leading to mixed results, while mealtime assistance, particularly provided by volunteers or dietary staff, appears to promote food intake. A few innovative strategies were identified but further research to develop and evaluate food first approaches is needed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.087
GPT teacher head0.388
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2013
Admission routes1
Has abstractyes

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