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Record W4212886262 · doi:10.3917/rsi.147.0067

De l’aide médicale à mourir au Québec : une analyse du contexte et de la pratique infirmière en soins palliatifs

2022· review· fr· W4212886262 on OpenAlexaffabout
Paweł Król, Malek Amiri, Nicolas Vonarx

Bibliographic record

VenueRecherche en soins infirmiers · 2022
Typereview
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Context : Quebec's "medical aid in dying" (MAID) is a medical intervention mostly practiced in palliative care units. MAID results from a deep revolution within Quebec's ethics regarding end-of-life care. However, there is a lack of empirical studies regarding nursing practice within the context of MAID.Aim : To conduct a literature review of legal and scientific data, as well as data from the media, related to the patient experience of nursing practices in palliative care for patients in Quebec who have requested MAID.Methodology : Burn, Grove, and Sutherland's methodology allowed us to extract and analyze six empirical studies from the CINAHL database. We also analyzed 17 media articles and one legal paper that documents the legalization of MAID in Quebec.Results : There has been a strict law governing MAID since 2015, but some major social events and issues have recently allowed for the expansion of the practice. The literature review allowed us to identify two themes : 1). the nature of nursing practice within MAID, and 2). the need for nursing education that addresses the complex aspects of MAID.Discussion and conclusion : We discuss the effects of the domination of the biomedical narrative on MAID and the collapse of Quebec's health system, which both negatively impact nursing practice in the context of MAID.

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)0.083
metaresearch head score (Gemma)0.054
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.867
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0830.054
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0140.045
Insufficient payload (model declined to judge)0.0050.001

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 head0.303
GPT teacher head0.534
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2022
Admission routes2
Has abstractyes

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