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Record W3210126807 · doi:10.5737/23688076314463469

Synthèse des stratégies d’autogestion employées par de jeunes adultes ayant reçu une greffe de cellules hématopoïétiques : revue narrative

2021· article· fr· W3210126807 on OpenAlexaffvenue
Billy Vinette, Hazar Mrad, Ali El-Akhras, Karine Bilodeau

Bibliographic record

VenueCanadian Oncology Nursing Journal · 2021
Typearticle
Languagefr
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesMedicineGynecologyArt

Abstract

fetched live from OpenAlex

La greffe de cellules hématopoïétiques est couramment utilisée pour traiter de jeunes adultes atteints d’un cancer hématologique. Ce traitement peut occasionner de nombreux effets secondaires qui requièrent que les patients utilisent l’autogestion des symptômes. Toutefois, aucune étude ne semble recenser les stratégies d’autogestion mises en place par ce groupe. Le but de cet article est de répertorier les stratégies d’autogestion utilisées par de jeunes adultes (18-39 ans) ayant reçu une greffe de cellules hématopoïétiques lors d’une leucémie ou d’un lymphome. Une revue narrative effectuée dans CINAHL, MEDLINE et PsycINFO a permis de retenir 11 articles. L’analyse des données souligne que les jeunes adultes utilisent des stratégies d’autogestion, dont la gestion des émotions, l’appui sur les croyances spirituelles, l’appel à autrui et la modification de comportements. Les résultats accentuent l’importance des soins infirmiers quant au soutien des stratégies d’autogestion parmi les jeunes adultes affectés par une greffe de cellules hématopoïétiques.

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)0.007
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0020.002
Scholarly communication0.0060.006
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.031
GPT teacher head0.338
Teacher spread0.307 · 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 designSystematic review
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
Published2021
Admission routes2
Has abstractyes

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