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Record W2109264648 · doi:10.12968/ijpn.2010.16.1.46181

Advance care planning among Asian Americans and Native Hawaiians receiving haemodialysis

2010· article· en· W2109264648 on OpenAlexaff
Merle Kataoka‐Yahiro, Francisco Conde, Rachael S. Wong, Victoria Page, Bernice Peller

Bibliographic record

VenueInternational Journal of Palliative Nursing · 2010
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsQueen's University
Fundersnot available
KeywordsAdvance care planningPsychological interventionMedicineNative HawaiiansFamily medicineGerontologyNursingPalliative careEnvironmental health

Abstract

fetched live from OpenAlex

AIM: To explore the attitudes about death and dying, advance care planning (ACP), and completion of ACP among Asian Americans (AAs) and Native Hawaiians (NHs) receiving haemodialysis. This study was a descriptive, cross-sectional survey design. METHOD: A convenience sample of 50 participants aged 30-82 years was recruited from four outpatient dialysis centers in Honolulu, Hawaii and interviewed face-to-face using a 43-item end-of-life community survey. A majority of participants perceived dying as an important part of life and were comfortable talking about death, but expressed concerns and fears about end-of-life issues. Aspects of ACP, such as planning a funeral service, getting finances in order, and completing the will were important. While most participants' attitudes about ACP were positive, less than half (40%) had completed ACP. Most participants preferred initiating end-of-life conversations with family. CONCLUSIONS: The main conclusions drawn from this study are that there is a need for ACP and secondly that AAs and NHs would prefer to discuss ACP with family members rather than health or legal professionals. Findings from this preliminary study build on the need to use a theoretical framework in which to develop sound instruments and effective interventions to promote ACP completion among AAs and NHs receiving haemodialysis.

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)0.001
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 score0.086
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.060
GPT teacher head0.444
Teacher spread0.384 · 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

Citations24
Published2010
Admission routes1
Has abstractyes

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