Alcohol consumption among Canadians taking benzodiazepines and related drugs
Bibliographic record
Abstract
PURPOSE: Benzodiazepines and related drugs (BZDs) are widely used for the treatment of anxiety, insomnia and other conditions. The combination of BZDs with alcohol increases risk for oversedation, abuse, dependence and accidents. This study examines drinking behaviour among Canadians taking BZDs. METHODS: We use data from cycle 1.2 of the Canadian Community Health Survey, a large (n = 36,984) population survey conducted in 2002 by Statistics Canada. We use bivariate methods and logistic regression to test the independent association between BZD use and 2 levels of recent drinking in the general population, and then examine associations between drinking and sociodemographic factors within the group of BZD users. RESULTS: Any drinking and heavy drinking are less common among users of BZDs than among other respondents, but these differences are small (any drinking, OR = 0.77, p = 0.02; heavy drinking, OR = 0.81, p = 0.13) when differences in respondent characteristics are controlled statistically. Among BZD users, any drinking is associated with male sex, younger age and not meeting criteria for a past-year anxiety disorder. Heavy drinking is associated only with younger age. CONCLUSIONS: Heavy alcohol use is uncommon among users of BZDs, and the combination of alcohol and BZD use is rare in the general population. Differences between BZD users and others are not large when other factors are taken into account, however, which may call into question the effectiveness of physician and pharmacist warnings against this combination. People treated for an anxiety disorder with BZDs may be less likely to use alcohol than those taking them for other indications.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".