Utilisation des technologies de communications virtuelles pour les personnes ayant perdu un proche en fin de vie en temps de pandémie
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".