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Record W2060631972 · doi:10.1177/1049909108331316

Nurses’ Perceptions of Factors Influencing Patient Decision Support for Place of Care at the End of Life

2009· article· en· W2060631972 on OpenAlexaff
Mary Murray, Keith G. Wilson, Jennifer Kryworuchko, Dawn Stacey, Annette M. O’Connor

Bibliographic record

VenueAmerican Journal of Hospice and Palliative Medicine® · 2009
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineNursingPerceptionDecision support systemHealth professionalsHealth careClinical decision support systemMEDLINESocial supportPsychologySocial psychology

Abstract

fetched live from OpenAlex

Although patients have more choices about where to receive care as death approaches, they often need help with decision making. This study identified factors that influence nurses' provision of decision support. A total of 22 nurses, from 3 health networks, participated in semistructured interviews. Overall, nurses held favorable attitudes toward providing decision support for place of care at end of life. Overlap between other professionals' roles and nurses' clinical experience affected nurses' decision support behaviors. Although nurses considered decision support to be part of patient-centered care, they report a lack of skills, confidence, and tools to help them provide it. These findings confirm the need to develop practical postlicensure education strategies and ways to embed patient decision support tools into systems of 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 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)0.005
metaresearch head score (Gemma)0.027
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.389
Teacher spread0.351 · 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

Citations21
Published2009
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Hospice and Palliative Medicine®Same topicPalliative Care and End-of-Life IssuesFrench-language works237,207