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Record W3016120602 · doi:10.1089/jpm.2019.0582

Congruence between Preferred and Actual Place of Death for Those in Receipt of Home-Based Palliative Care

2020· article· en· W3016120602 on OpenAlexaff
Jiaoli Cai, Li Zhang, Denise N. Guerriere, Peter C. Coyte

Bibliographic record

VenueJournal of Palliative Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPalliative careMedicineReceiptCongruence (geometry)Multivariate analysisPlace of deathNursingFamily medicinePsychologySocial psychology

Abstract

fetched live from OpenAlex

Background: Understanding the factors that affect the congruence between preferred and actual place of death may help providers offer clients customized end-of-life care settings. Little is known about this congruence for cancer patients in receipt of home-based palliative care. Objectives: This study aims to determine the congruence between preferred and actual place of death among cancer patients in home-based palliative care programs. Design: A longitudinal prospective cohort study was conducted. Congruence between preferred and actual place of death was measured. Both univariate and multivariate analyses were used to assess the determinants of achieving a preferred place of death. From July 2010 to August 2012, a total of 290 caregivers were interviewed biweekly over the course of their palliative care trajectory from entry to the program and death. Results: The overall congruence between preferred and actual place of death was 71.72%. Home was the most preferred place of death. The intensity of home-based nursing visits and hours of care from personal support workers (PSWs) increased the likelihood of achieving death in a preferred setting. Conclusions: The provision of care by home-based nurse visits and PSWs contributed to achieving a greater congruence between preferred and actual place of death. This finding highlights the importance of formal care providers in signaling and executing the preferences of clients in receipt of home-based palliative 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)0.001
metaresearch head score (Gemma)0.004
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 score0.120
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.216
GPT teacher head0.440
Teacher spread0.224 · 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

Citations52
Published2020
Admission routes1
Has abstractyes

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