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Record W4318931884 · doi:10.1097/njh.0000000000000928

“We're Cancer Care Nurses”

2023· article· en· W4318931884 on OpenAlexaff
David Wright, X. Grace, Kathleen Charlebois, Karine Gimmig, Lyndsay Hodgson

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCARE CanadaDouglas CollegeMcGill UniversityMcGill University Health CentreUniversity of OttawaHealth Canada
Fundersnot available
KeywordsPalliative careMedicineNursingMeaning (existential)Family medicineIdentity (music)CancerFocus groupPsychologyInternal medicinePsychotherapistSociology

Abstract

fetched live from OpenAlex

Nurses play a key role in integrating palliative care into oncology. This project sought to better understand oncology nurses' perspectives about palliative care. Nurses from a community hospital were presented with a series of clinical scenarios and asked to comment on the appropriateness of palliative care in each case. A series of focus groups were held, inviting nurses' reflections about palliative care in relation to their practice. Nurses commenting on the clinical scenarios were unanimous that palliative care was appropriate in the most straightforward case: older adult, approaching the terminal phase of a cancer, having exhausted all curative treatment options, accepting death, wanting comfort, and contending with difficult symptoms. However, opinions on appropriateness varied in less straightforward cases, such as when patients did not accept death or when their cancer diagnosis was recent. In focus groups, nurses described a hybrid professional identity that integrates both oncology and palliative care. To them, this integration constituted the meaning of "cancer care." They further reflected on tensions they experience between their proximity to patients in everyday care and their (in)abilities to meet palliative care needs. Results suggest the need for stronger institutional supports of cancer nurses' palliative practice.

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 score0.174
Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.148
GPT teacher head0.485
Teacher spread0.337 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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