The Provision of Texture-Modified Foods in Long-term Care Facilities by Health Professionals: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Malnutrition among older adults with dysphagia is common. Texture-modified foods (TMFs) are an essential part of dysphagia management. In long-term care (LTC) facilities, health professionals have implemented TMFs, but their application has not been fully elucidated, making them heterogeneous. OBJECTIVE: We aim to explore the implementation of TMFs in LTC facilities, particularly focusing on the role of health professionals in nutritional care involving TMFs (eg, deciding the type of food, preparing and giving the food, and evaluating the outcomes). METHODS: A scoping review using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodological approach will be performed. A comprehensive search for published literature will be systematically performed in PubMed, CINAHL, MEDLINE, ProQuest, PsycINFO, and Science Citation Index (Web of Science). Data screening and extraction will be performed by 2 reviewers independently. The studies included will be synthesized, summarized, and reported, following the preferred reporting items of the Mixed Methods Appraisal Tool. Our review will consider the following study designs: mixed methods, quantitative, and qualitative. Studies with patients who are not older adults will be excluded. RESULTS: Data extraction will be completed by February 2023. Data presentation and analyses will be completed by April 2023, and the final outcomes will be completed by June 2023. The study findings will be published in a peer-reviewed journal. CONCLUSIONS: Our scoping review will consider studies related to TMF interventions for older adults in LTC residential facilities, with no exclusion restrictions based on country, gender, or comorbidities. Studies on interventions that address TMF-related issues, such as deciding the type of food, preparing and giving the food, and evaluating the outcomes, are qualified for inclusion. TRIAL REGISTRATION: OSF Registries 79AFZ; https://osf.io/79afz. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/44201.
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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 | 0.110 | 0.089 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.083 | 0.017 |
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".