Long-term sedative use among community-dwelling adults: a population-based analysis
Bibliographic record
Abstract
BACKGROUND: Chronic use of benzodiazepines and benzodiazepine-like sedatives (z-drugs) presents substantial risks to people of all ages. We sought to assess trends in long-term sedative use among community-dwelling adults in British Columbia. METHODS: Using population-based linked administrative databases, we examined longitudinal trends in age-standardized rates of sedative use among different age groups of community-dwelling adults (age ≥ 18 yr), from 2004 to 2013. For each calendar year, we classified adults as nonusers, short-term users, or long-term users of sedatives based on their patterns of sedative dispensation. For calendar year 2013, we applied cross-sectional analysis and estimated logistic regression models to identify health and socioeconomic risk factors associated with long-term sedative use. RESULTS: More than half (53.4%) of long-term users of sedatives in British Columbia are between ages 18 and 64 years (young and middle-aged adults). From 2004 to 2013, long-term sedative use remained stable among adults more than 65 years of age (older adults) and increased slightly among young and middle-aged adults. Although the use of benzodiazepines decreased during the study period, the trend was offset by equal or greater increases in long-term use of z-drugs. Being an older adult, sick, poor and single were associated with increased odds of long-term sedative use. INTERPRETATION: Despite efforts to stem such patterns of medication use, long-term use of sedatives increased in British Columbia between 2004 and 2013. This increase was driven largely by increased use among middle-aged adults. Future deprescribing efforts that target adults of all ages may help curb this trend.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".