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Record W2755908614 · doi:10.1177/1049732317730568

Supporting Family Involvement in Long-Term Residential Care: Promising Practices for Relational Care

2017· article· en· W2755908614 on OpenAlexafffund
Rachel Barken, Ruth Lowndes

Bibliographic record

VenueQualitative Health Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsYork University
FundersYork UniversityLouisiana Transportation Research Center
KeywordsTeamworkEthnographyNursingWork (physics)Long-term carePsychologyAssisted livingCare workTerm (time)MedicineSociologyPolitical science

Abstract

fetched live from OpenAlex

Family members and friends provide significant support for older relatives in long-term residential care (LTRC). Yet, they occupy ambiguous positions in these settings, and their relationships with LTRC staff can involve conflicts and challenges. Based on an ethnographic project carried out in North America and Europe, this article identifies practices that promote meaningful family participation in care home life. We consider instances of rewarding family involvement upon admission to LTRC, throughout the time a relative is living in a care home, and during the final stages of life. Furthermore, we identify working conditions needed to support the well-being of family/friend carers as well as residents and staff. These include greater appreciation of relational care work, time for effective communication, teamwork, and appropriate, inclusive physical spaces. Findings make visible the importance of relational care and have implications for improving living and working conditions in LTRC.

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)0.024
metaresearch head score (Gemma)0.022
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 score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0130.012
Scholarly communication0.0090.008
Open science0.0030.010
Research integrity0.0020.003
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 head0.632
GPT teacher head0.706
Teacher spread0.074 · 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".

Quick stats

Citations91
Published2017
Admission routes2
Has abstractyes

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