Psychotropic Medication Use in Canada
Bibliographic record
Abstract
BACKGROUND: Psychotropic medication use can be employed as an indicator of appropriate treatment for mental disorders. The Canadian Community Health Survey: Mental Health and Well-Being (CCHS 1.2) offers the first opportunity to characterize Canadian psychotropic medication use on a national level within diagnostic groups as assessed by a full version of the Composite International Diagnostic Interview (CIDI). METHOD: We assessed the prevalence of antidepressant, sedative-hypnotic, mood stabilizer, psychostimulant, and antipsychotic use over 2 days overall and in subgroups defined by CIDI-diagnosed disorders and demographics. We employed sampling weights and bootstrap methods. RESULTS: Overall psychotropic drug utilization was 7.2%. Utilization was higher for women and with increasing age. With any lifetime CIDI-diagnosed disorder assessed in the CCHS 1.2, utilization was 19.3%, whereas without such disorders, it was 4.1%. Selective serotonin reuptake inhibitors (SSRIs) were the most commonly used antidepressants for those with a past-year major depressive episode (17.8%), followed by venlafaxine (7.4%). Among people aged 15 to 19 years, antidepressant use was 1.8% overall and 11.7% among those with past-year depression; SSRIs made up the majority of use. Sedative-hypnotics were used by 3.1% overall, increasing with age to 11.1% over 75 years. CONCLUSIONS: International comparison is difficult because of different evaluation methods, but antidepressant use may be higher and antipsychotic use lower in Canada than in recent European and American reports. In light of the relative lack of contemporary evidence for antidepressant efficacy in adolescents, it is likely that antidepressant use among those aged 15 to 19 years will continue to decline. The increased use of sedative-hypnotics with age is of concern, given the associated risk of adverse effects among seniors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".