Hypnotic use in a population-based sample of over thirty-five thousand interviewed Canadians
Bibliographic record
Abstract
BACKGROUND: As with most medications, benzodiazepine and similar sedative hypnotics (BDZ/SSH) can produce both beneficial and adverse effects. Pharmacoepidemiological studies have been limited in their capacity to evaluate the relationship between these medications and psychiatric diagnoses in non-clinical populations. The objective of this study was to provide a description of the pattern of use of BDZ/SSH medications in relation to both demographic and diagnostic data in a community population. METHODS: The source of data for this study was the Canadian Community Health Survey (CCHS 1.2), also known as the Canadian National Study of Mental Health and Well-being. This study was based on a nationally representative sample that included over 35 thousand subjects with a response rate of 77%. The survey interview included the latest version of the Composite International Diagnostic Interview (CIDI), which was developed for the World Health Organization's WHO Mental Health 2000 project. Current medication use was also recorded. RESULTS: As expected, BDZ/SSH use was more common in women than in men (4.2%, 95% CI 3.9 to 4.6 vs. 2.5%, 95% CI 2.2 to 2.8) and its frequency increased with age, 8.5% (95% CI 7.7 to 9.4) of those over the age of 65 compared to 2.4% (95% CI 2.2 to 2.7) of those aged 18 to 64 years. These medications were more frequently used in subjects with low levels of education (4.8%, 95% CI% 4.3 to 5.2) vs. high levels of education (2.4%, 95% CI 2.1 to 2.6) and low personal incomes (5.7%, 95% CI 5.2 to 6.3) vs. high personal incomes (2.3%, 95% CI 2.0 to 2.6). BDZ/SSH use was strongly associated with the presence of mood or anxiety disorders, but not with substance use disorders. Demographic differences persisted after statistical adjustment for diagnosis. CONCLUSION: The observation that benzodiazepine use is more frequent in women, increases with age and is higher in low income and education groups supports previous findings. These results help to confirm that these differences are not accounted for by psychiatric diagnoses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".