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Record W4386305991 · doi:10.1093/geront/gnad120

Filling In: Family Member Support for Nonrelative Residents in Long-Term Care Homes

2023· article· en· W4386305991 on OpenAlexafffundabout
Jennifer Baumbusch, Heather A. Cooke, Isabel Sloan Yip

Bibliographic record

VenueThe Gerontologist · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsTerm (time)Long-term careFamily memberGerontologyPsychologyNursingBusinessMedicineFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Past research about family involvement in long-term care (LTC) homes mainly focuses on family members' involvement with their own relative, interactions with staff, and collective activities such as Family Councils. Our research provides novel insights into family member's involvement in the care of residents who are not their relatives, an area that has not previously been explored. RESEARCH DESIGN AND METHODS: This critical ethnographic study examined ways that family members negotiate and navigate their roles within LTC homes. Data collection and analysis took place at 3 LTC homes in British Columbia, Canada, between 2014 and 2018. Data were collected through participant observation and semistructured interviews. Eleven family member participants shared experiences of caring for residents who were not their relatives. RESULTS: The umbrella theme was "filling in," which takes place in a care environment that is understaffed and underresourced. The subthemes reflect the various ways that families are "filling in": responding to resident's needs, supporting staff to respond to resident needs, and filling in for residents' families. DISCUSSION AND IMPLICATIONS: Caring for residents who are not their relatives is facet of family involvement in LTC homes that has not been previously explored. Many family members have expertise in providing person-centered care and they extend this expertise to residents who are not their relatives. Policies and legislation are needed to formalize family involvement in caring for nonrelative residents as it is a component of quality of care for all residents.

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)0.000
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 score0.090
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.115
GPT teacher head0.443
Teacher spread0.328 · 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

Citations1
Published2023
Admission routes3
Has abstractyes

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