MétaCan
Menu
Back to cohort
Record W2146350554 · doi:10.12968/ijpn.2005.11.5.226

End-of-life care in a nursing home: a study of family, nurse and healthcare aide perspectives

2005· article· en· W2146350554 on OpenAlexaffabout
Donna Goodridge, John Bond, Cynthia Cameron, Elizabeth McKean

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2005
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of ManitobaRiverview HospitalUniversity of Saskatchewan
Fundersnot available
KeywordsNursingThematic analysisMedicineEnd-of-life careHealth careExploratory researchPalliative careAmbivalenceFamily medicinePsychologyQualitative research

Abstract

fetched live from OpenAlex

AIM: To examine the perspectives of family members, registered nurses and healthcare aides regarding the last 72 hours of Canadian nursing home residents' lives. STUDY DESIGN: Exploratory, descriptive design using semistructured interviews. SAMPLE: Consisted of 14 registered nurses and eight healthcare aides who had provided care within the last 72 hours before a resident's death and four family members who had visited within the same time frame. SETTING: A 220-bed nursing home located within a larger long-term care facility in Canada. METHODS: Thematic analysis was conducted independently and through consensus identified themes and subthemes emerging from the interviews. FINDINGS: Dyspnea was a more common end-of-life (EoL) symptom for nursing home residents in this sample than was pain. Caring behaviours of staff were central to the resident's dying process and involved assessment, coordination of care, physical care, family education and nurture. Family members' ambivalence about the resident's death and fear of the resident dying alone were frequently noted. CONCLUSIONS: Appropriate and timely symptom management and a range of caring behaviours of staff are critical elements in the dying experience of nursing home residents. Additional education and support for personnel involved with caring for this group will enhance end-of-life care.

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)0.000
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 score0.114
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.101
GPT teacher head0.474
Teacher spread0.374 · 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

Citations70
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Palliative NursingSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207