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Record W4285246830 · doi:10.7202/1089344ar

Utilisation des technologies de communications virtuelles pour les personnes ayant perdu un proche en fin de vie en temps de pandémie

2022· article· fr· W4285246830 on OpenAlexaffvenue
Julia Masella, Diane Tapp, Marie‐Pierre Gagnon

Bibliographic record

VenueFrontières · 2022
Typearticle
Languagefr
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Pour limiter la propagation de la COVID-19, diverses restrictions ont été mises en place, notamment lors des soins palliatifs et des cérémonies funéraires. Pour contrer ces restrictions et leurs effets, certaines familles ont eu recours à des technologies virtuelles de communication afin de rester en contact avec leur proche. Cet article a pour but de documenter les impacts de l’utilisation des technologies virtuelles sur l’expérience des proches de personnes décédées lors de la pandémie. Une revue de la littérature de type examen de la portée a été réalisée dans 4 bases de données. Les résultats suggèrent que l’utilisation de technologies virtuelles de communication lors des soins palliatifs a eu un impact positif sur l’état psychologique du patient et la satisfaction des proches. En revanche, ceux n’ayant pas eu accès à ces moyens ont ressenti de la frustration quant au fait de ne pas avoir pu dire au revoir à leur proche.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.325
Teacher spread0.284 · 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.

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
Published2022
Admission routes2
Has abstractyes

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