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Insights Regarding Mealtime Assistance for Individuals in Long-term Care

2007· article· en· W2322138108 on OpenAlexaff
Catriona M. Steele, Tiziana Rivera, Laurie Bernick, Lyen Mortensen

Bibliographic record

VenueTopics in Geriatric Rehabilitation · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsBaycrest HospitalTrillium Health CentreToronto Rehabilitation InstituteYork UniversityToronto Metropolitan UniversityUniversity of TorontoHumber Polytechnic
Fundersnot available
KeywordsGratitudeNursingFiduciaryMedicineFocus groupLong-term carePsychologySocial psychologyDuty

Abstract

fetched live from OpenAlex

Focus groups were conducted with staff in a geriatric care facility who provided mealtime assistance during a quarantine that prevented family members from entering the facility. The volunteers' accounts reflected 3 primary themes that influenced their experience as mealtime assistants. First, the role of volunteer-recipient relationships emerged as paramount in facilitating optimal mealtime care. Strong reinforcement was derived from small signs of gratitude and awareness in the residents' nonverbal behaviors. This fostered the volunteers' sense of fiduciary responsibility toward the resident, thereby facilitating a meaningful and successful mealtime experience. Second, it was clear that the experience of being a mealtime assistant evolved over time, with changes in volunteer attitude mediated directly by the relationships that developed between volunteers and recipients. Lastly, the data reflect a strong awareness among volunteers of the challenges faced by nursing staff on a daily basis with respect to meeting the mealtime needs of residents in long-term care institutions, and a concern that nursing staff have insufficient time to develop intimate relationships with residents at the mealtime. These data strongly suggest that volunteer-assisted mealtime programs that focus primarily on social relationships can enhance the mealtime experience for residents in long-term care institutions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.385
Teacher spread0.360 · 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.

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

Citations10
Published2007
Admission routes1
Has abstractyes

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