Benzodiazepine receptor agonist dispensations in Alberta: a population-based descriptive study
Bibliographic record
Abstract
BACKGROUND: There is increasing concern over the use of benzodiazepine receptor agonists (BZRAs). The objective of this study was to describe BZRA dispensations in the province of Alberta in 2015 according to age, sex and appropriateness. METHODS: A population-based descriptive study of people 10 years of age or older with at least 1 BZRA dispensation in Alberta, Canada, between Jan. 1 and Dec. 31, 2015, was conducted. Prevalence of BZRA use, characteristics of BZRAs dispensations, use at the individual level and appropriateness were determined. RESULTS: value for trend < 0.001) and was consistently highest among females. Twenty percent of patients used both Z-drugs and benzodiazepines. BZRA users had an average of 7 dispensations (standard deviation [SD] 20), 137 days of use overall (SD 123) and a maximum period of consecutive use of 90 days (SD 95). Days of consecutive use were highest among those aged 65 years or older (126 d). A total of 62 795 (17%) people used more than 1 distinct BZRA ingredient concurrently and 10% had 3 or more distinct prescribers. INTERPRETATION: The prevalence of BZRA use was high and a substantial proportion of use appeared to be potentially inappropriate. This study supports the need for continued monitoring for the prescribing and use of these medications at the population level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".