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Record W2985469607 · doi:10.3148/cjdpr-2019-035

Effect of a Protected Mealtime Pilot on Energy and Protein Intake in a Canadian Hospital

2019· article· en· W2985469607 on OpenAlexaffvenueabout
Amanda Goarley, Dahlia Hassan, Latifeh Ahmadi

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2019
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsWestern University
Fundersnot available
KeywordsMalnutritionMedicineMealPolicy developmentEnvironmental healthEmergency medicineDemographyGerontologyInternal medicineBusiness

Abstract

fetched live from OpenAlex

Purpose: In Canada, approximately 45% of hospitalized patients are moderately or severely malnourished upon admission. The protected mealtime policy was designed to address malnutrition in institutions. This pilot study aimed to provide preliminary results examining the effect of this policy on patient energy and protein intake. Methods: A 1-group, pre–post observation design was conducted in a Canadian hospital. Pre- and post-observations included the frequency and type of interruptions, type of interrupter, and patient energy and protein intake at each meal. Results: The average number and length of interruptions decreased, and the average length of mealtime assistance provided to patients (n = 12) increased in the post-observation period. Energy and protein consumption showed a slight increase during the post-observation period. Conclusion: A protected mealtime policy may be an effective policy to address malnutrition among hospitalized Canadian adults. Further studies are warranted in Canada to determine the effects and feasibility of this policy implementation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.384
Teacher spread0.343 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2019
Admission routes3
Has abstractyes

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