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Record W4404998418 · doi:10.7202/1114806ar

Recours aux services psychosociaux en ligne avant et pendant la pandémie de la COVID-19 par les personnes utilisatrices de substances psychoactives

2024· article· fr· W4404998418 on OpenAlexaffvenue
Christophe Huỳnh, Nadine Blanchette-Martin, Alexis Beaulieu‐Thibodeau, Francine Ferland, Song Yuan, Mathieu Goyette, Vincent Wagner, Jacinthe Brisson, Jean‐Sébastien Fallu, Jorge Flores-Aranda, Thomas Gottin

Bibliographic record

VenueNouvelles pratiques sociales · 2024
Typearticle
Languagefr
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleCentre intégré de santé et de services sociaux de Chaudière-Appalaches
Fundersnot available
KeywordsHumanitiesPolitical scienceCoronavirus disease 2019 (COVID-19)MedicineArt

Abstract

fetched live from OpenAlex

Cette étude documente l’utilisation des services psychosociaux en ligne durant la pandémie de COVID-19 auprès de 1159 adultes qui consomment des substances psychoactives. Pendant cette période, 38 % ont utilisé ces services. En se basant sur le modèle d’Andersen, l’utilisation de ces services est associée 1) aux facteurs prédisposants du genre (s’identifier comme femme) et de l’âge (avoir 18 à 24 ans comparé à avoir 65 et plus), 2) au facteur facilitant du recours antérieur aux services psychosociaux en ligne et 3) aux facteurs de besoin, c’est-à-dire la détresse psychologique élevée, la consommation pour gérer son anxiété et l’augmentation de la fréquence de la consommation durant la pandémie. La complémentarité des modalités de services psychosociaux en présence et en ligne est nécessaire, car ces services répondent notamment aux besoins de s’informer et de développer des stratégies de gestion de soi.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.468
Teacher spread0.385 · 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 designObservational
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
Published2024
Admission routes2
Has abstractyes

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