MétaCan
Menu
Back to cohort
Record W2030017325 · doi:10.3406/sosan.2002.1544

Médicaments psychotropes et sujets âgés une problématique commune France-Québec ? (synthèse de la littérature)

2002· article· en· W2030017325 on OpenAlexaboutno aff
Joël Ankri, Johanne Collin, Guilhème Pérodeau, Béatrice Beaufils

Bibliographic record

VenueSciences sociales et santé · 2002
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPsychiatryPsychotropic medicationPsychotropic AgentElderly peopleMedicinePsychotropic drugPsychologyDrugMental healthGerontology

Abstract

fetched live from OpenAlex

Psychotropic drugs and elderly: a same problem in France and Quebec. Review of literature The use of psychotropic medication is seen as a major problem related to public health in Europe as well as in North America. The limits between therapeutic and social functions of psychotropic medication have produced many controversies. In this debate, the case of the elderly is seen as a major issue. The aim of this article is to review the literature related to psychotropic medication use among the elderly in two French speaking societies, France and Quebec. First, we will focus on social and psychosocial characteristics of the elderly users in both countries. Then we will summarize the results of studies about adverse effects, addiction and other risks related to the long term use of psychotropic drugs by older people. Finally we will provide an analysis of social and cultural determinants of psychotropic drug utilization among the elderly by emphasizing the importance of physician/patient relationship and the rationale underlying prescribing behaviors.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.110
GPT teacher head0.482
Teacher spread0.372 · 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 designNot applicable
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

Citations11
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueSciences sociales et santéSame topicHealth, Medicine and SocietyFrench-language works237,207