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Record W4312447706 · doi:10.2196/42496

A Logical Framework (MYGERYFS) for Hospital Foodservice to Prevent Malnutrition Among Geriatric Patients in Hospitals, Malaysia: Protocol for a Feasibility Study

2022· article· en· W4312447706 on OpenAlexvenueno aff
Noraida Omar, Shazli Illyani Shafiee, Siti Hazimah Nor'hisham, Zuriati Ibrahim, Rosita Jamaluddin, Syafiqah Rahamat, Barakatun Nisak Mohd Yusof, Halimatus Sakdiah Minhat, Hakimah Sallehuddin

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
FundersMinistry of Higher Education, Malaysia
KeywordsMalnutritionProtocol (science)MedicineGeriatric careGerontologyNursingAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Geriatric malnutrition in hospitals is common and can be affected by many things, including poor satisfaction toward hospital foodservice. Hospital foodservice plays an important role in a patient's recovery process by providing adequate nutrients. On top of that, patients' foodservice satisfaction can easily be afflicted by the quality of food served and the overall foodservice experience. Furthermore, malnutrition can occur from poor foodservice quality, especially among geriatric patients. OBJECTIVE: This study aims to assess the effectiveness of the Malaysian Geriatric Patients' Hospital Foodservice Protocol (MYGERYFS). METHODS: The protocol comprises 3 phases. Phase One is a cross-sectional study that took place at public hospitals with geriatric wards in the Klang Valley. Univariate data from Phase One were analyzed descriptively. Pearson correlation and chi-square were conducted to find factors associated with foodservice satisfaction. Phase Two involves the collaboration of health care professionals in the geriatric field. In Phase Three, a feasibility study will be conducted to determine the feasibility of the MYGERYFS protocol in a hospital among 60 geriatric patients. These patients will be randomized into control and intervention groups, respectively. Intervention care will be done to ensure the safety of the protocol. RESULTS: Data collection for Phase One of the study has been completed. A total of 233 geriatric respondents with the mean age of 71.39 (SD 7.99) years were gathered. Approximately 51.5% (n=120) of the respondents were female, while 48.5% (n=113) were male, with a mean BMI of 24.84 (SD 6.05) kg/m2. Their mean energy and protein intakes were 1006.20 kcal (SD 462.03 kcal) and 42.60 (SD 22.20) grams, respectively. Based on the Mini Nutritional Assessment, older patients who scored 12-14 (normal) were 27.9% (n=65), those who scored 8-11 (at risk) were 54.9% (n=128), and those who scored 0-7, which is the lowest (malnutrition), were 17.2% (n=40) of the study population. Hence, most patients were at risk of malnutrition. Although a majority of the patients claimed to have good foodservice satisfaction 26.2% (n=61), they also experienced at least 3 barriers during mealtimes. It was found that dietary intake and mealtime barriers were significantly associated with the respondent's foodservice satisfaction. Data for Phase Two and Phase Three are yet to be collected and analyzed. CONCLUSIONS: This study protocol could potentially benefit the hospital foodservice system and aid in improving geriatric nutritional status. TRIAL REGISTRATION: ClinicalTrials.gov NCT04858165; https://clinicaltrials.gov/ct2/show/NCT04858165. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/42496.

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)0.043
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.045
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.026
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0450.007

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 head0.236
GPT teacher head0.572
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations2
Published2022
Admission routes1
Has abstractyes

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