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Record W4413214291 · doi:10.5737/23688076352368

Détresse morale des proches aidants de personnes atteintes de cancer en soins palliatifs : une étude qualitative

2025· article· fr· W4413214291 on OpenAlexvenueno aff
Ana Lucía Oliveros Rozo, Milena Schneiders, Mateus Rodrigo Palombit, Kassiano Carlos Sinski, Rafael Augusto Ferreira do Carmo, Ana Isabel García García, Jeferson Santos Araújo, Júlia Valéria de Oliveira Vargas Bitencourt, Rosana Aparecida Spadoti Dantas, Vander Monteiro da Conceição

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2025
Typearticle
Languagefr
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

La présente étude visait à comprendre les causes de la détresse morale chez les proches aidants de personnes atteintes de cancer recevant des soins palliatifs. Pour cette étude qualitative longitudinale où le concept de détresse morale sert de référence interprétative, dix proches aidants se sont livrés à des entrevues approfondies. Les données ont été analysées à l’aide d’une technique thématique inductive, qui a permis de faire ressortir deux grands thèmes. Pour le premier thème, « Les répercussions du diagnostic », les participants ont parlé des incertitudes qu’ils ont ressenties après qu’un membre de leur famille ait reçu un diagnostic de cancer. Avec le deuxième thème, « Bouleversement de la vie quotidienne », les participants ont exprimé combien le fait de s’occuper d’un membre de leur famille atteint de cancer a transformé leur vie de tous les jours. Il ne faut pas oublier que les proches aidants vivent eux aussi des dilemmes et des incertitudes qui génèrent une certaine détresse morale pendant tout le parcours avec la maladie.

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)0.014
metaresearch head score (Gemma)0.021
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.021
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.137
GPT teacher head0.511
Teacher spread0.375 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueCanadian Oncology Nursing JournalSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207