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Record W2041912042 · doi:10.1177/0269216307084612

Short Report: Preferences for location of death of seriously ill hospitalized patients: perspectives from Canadian patients and their family caregivers

2008· article· en· W2041912042 on OpenAlexafffundabout
Kelli Stajduhar, Diane Allan, S. Robin Cohen, Daren K. Heyland

Bibliographic record

VenuePalliative Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsQueen's UniversityMcGill UniversityUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsMedicinePreferencePalliative carePlace of deathFamily caregiversFamily medicineFamily memberQuality of life (healthcare)GerontologyNursing

Abstract

fetched live from OpenAlex

Previous studies involving palliative patients suggest a preference for dying at home. The purpose of this paper is to examine, prospectively, patient and family caregiver preferences for, and congruence with, location of death for hospitalized patients with cancer and end-stage medical conditions. Questionnaires were administered to 440 eligible in-patients and 160 family caregivers in five hospitals across Canada. This paper reports results of 138 patient/family caregiver dyads who answered a question about preference for location of death. The results suggest that only half of all patients and family caregivers report a preference for a home death. Furthermore, half of the patient/family caregiver dyads disagree on preferred location of death. If one of the primary goals of end of life care is to enhance the quality of life of dying patients and their family caregivers, policies directed towards ensuring that patients die in their location of choice ought to be a priority and resources should be allocated to promote the development of excellent care, not only in the home, but also within our institutional settings.

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)0.002
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 score0.064
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.073
GPT teacher head0.341
Teacher spread0.268 · 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

Citations89
Published2008
Admission routes3
Has abstractyes

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