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Long‐Term Continuous Use of Benzodiazepines by Older Adults in Quebec: Prevalence, Incidence and Risk Factors

2000· article· en· W2018685660 on OpenAlexafffundabout
Mary Egan, Yola Moride, Christina Wolfson, Johanne Monette

Bibliographic record

VenueJournal of the American Geriatrics Society · 2000
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité de MontréalMcGill UniversityJewish General HospitalUniversity of Ottawa
FundersHealth CanadaAustralian Government
KeywordsMedicineIncidence (geometry)BenzodiazepineAnxietyCumulative incidenceCohort studyCohortPopulationGerontologyPediatricsPsychiatryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence and incidence of long-term use of benzodiazepines and to assess patient-, prescriber-, and drug-related risk factors. DESIGN: Cohort study. PARTICIPANTS: 1,423 community-dwelling older adults in Quebec who participated in the Canadian Study of Health and Aging (CSHA1). MEASUREMENTS: Patient characteristics were obtained from the CSHA1 database. These were linked to provincial health insurance data to ascertain benzodiazepine use and prescriber characteristics. MAIN OUTCOME MEASURE: Use of benzodiazepines for at least 135 of the first 180 days following initiation of use. RESULTS: Twelve-month prevalence of long-term continuous use, standardized by age and gender to the Quebec population, was 19.8%. Twelve-month cumulative incidence of long-term continuous use was 1.9%. Older patients were more likely to proceed to long-term continuous use. CONCLUSIONS: Risk of long-term continuous use of benzodiazepines seems to increase with age. This association was found to be independent of gender, health status, anxiety, cognitive status, benzodiazepine type, and physician characteristics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.042
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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.

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

Citations109
Published2000
Admission routes3
Has abstractyes

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