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Record W2105184292 · doi:10.7202/008622ar

Utilisation des anxiolytiques, sédatifs et hypnotiques chez les personnes âgées vivant dans la communauté : construction d’un cadre conceptuel

2004· article· fr· W2105184292 on OpenAlexaffvenue
Michel Préville, Claire Ducharme, Dany Fortin, Réjean Hébert, Jean‐Pierre Grégoire, Anick Bérard, Jacques Allard

Bibliographic record

VenueSanté mentale au Québec · 2004
Typearticle
Languagefr
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de MontréalCentre hospitalier universitaire de QuébecHealth and Social Services Centre University Institute of Geriatrics of Sherbrooke
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

La consommation non appropriée d’anxiolytiques, de sédatifs et d’hypnotiques (ASH) chez les personnes âgées est un problème de santé publique important. Près de 35 % de la population âgée vivant à domicile consomment ces médicaments, en moyenne 206 jours par an. Selon les données québécoises, les personnes âgées de plus de 65 ans consomment cinq fois plus d’ASH que les individus âgés entre 18 et 64 ans. L’utilisation des ASH ne serait pas uniquement déterminée par la présence de symptômes, mais aussi par les caractéristiques psychosociales des sujets. En outre, plusieurs chercheurs ont suggéré que l’entourage et le système de soins étaient des facteurs environnementaux pouvant faciliter ou inhiber la consommation de ces médicaments chez les personnes âgées. Un cadre conceptuel est proposé pour aider à spécifier adéquatement les diverses hypothèses explicatives de ce comportement social de santé et, par conséquent, pour aider à mieux cibler les interventions visant à le modifier.

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)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.528

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.004
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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 designTheoretical or conceptual
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

Citations2
Published2004
Admission routes2
Has abstractyes

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