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Record W2179197905 · doi:10.3406/oss.2003.942

Les caractéristiques de la consommation de psychotropes chez les personnes âgées en France et au Québec

2003· article· en· W2179197905 on OpenAlexaboutno aff
Joël Ankri, Johanne Collin, Guilhème Pérodeau, Béatrice Beaufils

Bibliographic record

VenueSanté Société et Solidarité · 2003
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialDistressPsychotropic drugMental healthPsychiatryPsychologyMedicinePolitical scienceDrugPsychotherapist

Abstract

fetched live from OpenAlex

The use of psychotropic drugs is considered to be a public health problem in all European and North American countries because of its frequency and the risks it poses for older persons in particular. The present article examines the characteristics of this psychotropic drug use based on a review of the French and Québec literature so as to identify common problems in both countries. There seems to be a number of common characteristics in the use of psychotropic drugs in France and Québec, but studies on the social and psychosocial factors that explain this use are more developed in Québec than in France. Questions about the appropriate use of these products persist: are these molecules prescribed to treat genuine mental pathologies or to try to relieve social distress? Nevertheless, to gain a better understanding of this use and for public health activities to be effective, it is necessary to understand the psychosocial processes involved and to analyze how these products, beyond the treatment of disease, influence the capacity of individuals to deal with life events and aging and, in a certain way, allow them to deny conflict or change.

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)0.002
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.033
GPT teacher head0.435
Teacher spread0.403 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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