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Record W3194774625

Strategies to improve hydration practices in residential care during COVID- 19

2021· article· en· W3194774625 on OpenAlexvenueaboutno aff
Christina Lengyel, H. Keller, Pedro Gaspar, George Heckman, Laura Carbajo Martín, Janet C. Mentes, Ashwini Namasivayam‐MacDonald, Sara Slaughter, Sifat E Syed, Chew Siew Wei, Me-Ok Yoon

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2021
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Coronavirus disease 2019 (COVID-19)MedicineFood preparationLong-term careNursingShowerResidential careApathyPsychologyEnvironmental healthFood safetyInfectious disease (medical specialty)DiseasePathology
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Older adults residing in residential care are at an increased risk for dehydration due to physiological changes related to aging (changes to body composition, decreased thirst sensation and kidney function), disease condition (medication use), and increased dependence on others (functional ability, access to fluid). A variety of hydration techniques are used in residential care, but there is no consensus on how to maintain hydration. Infection control measures aimed at limiting the spread of COVID-19 in residential care amplified the need for creative ways to ensure that residents are consuming adequate food and fluids. Effective practices that are also feasible during infectious outbreaks are needed. Objectives: To examine the perspectives of experts and providers in residential care on challenges and potential strategies to improve hydration practices during COVID-19. Methods: Twenty-seven research/academic experts (67%) and providers (33%) in residential care from Canada (78%) and outside of Canada (22% UK, US, & Germany) participated in an audio- recorded three-hour virtual discussion about hydration practices before and during COVID-19. The participants were from a variety of disciplines: nutrition (45%);nursing (19%);speech-language pathology (11%);administration (11%);food service (7%);and other (7%). Qualitative content analysis was conducted. Results: COVID-19 hydration-related challenges and potential solutions to mitigate them were identified and categorized into three levels: resident (e.g., reduced access to beverages due to COVID-19 restrictions, apathy);staff (e.g., limited staff, decreased beverage offerings, new staff and role changes, changes in hydration assessment);and home-related (e.g., changes in beverage availability, drinking cups, routines for social events/volunteer assistance and physical distancing in dining areas). Some potential strategies to mitigate the problems included: trolley beverage service between meals;physically distanced interactions;offerings of fluids at every contact by all staff;and, physically distanced events that encourage fluid intake. Conclusions: COVID-19 has impacted hydration practices in residential care at the resident, staff, and home levels. Significance: Creative strategies involving an interdisciplinary team approach are needed to change hydration practices during a pandemic to ensure resident fluid needs are being met in residential care. Funded by: University of Waterloo International Research Development Program, with matching funds from Adelphi University (startup funds for ANM), and University of California at Los Angeles (JM).

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)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0050.002
Scholarly communication0.0020.002
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.069
GPT teacher head0.434
Teacher spread0.365 · 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 designQualitative
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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