Reasons for antidepressant prescriptions in Canada
Bibliographic record
Abstract
PURPOSE: To describe reasons reported by physicians making recommendations for treatment with antidepressant medications. METHODS: Data collected by IMS Health Canada in a database called the Canadian Disease and Therapeutic Index (CDTI) were used in this analysis. CDTI data are collected from a representative sample of office-based physicians who complete diaries in their practices during selected sampling periods. A drug recommendation is recorded each time a treatment is recommended. The data are weighted to produce national estimates of the frequency of such recommendations. RESULTS: The frequency of recommendations for antidepressant treatment increased between 2000 and 2004. However, there was a slight decrease in 2005. Two types of antidepressant medications, tricyclic antidepressants (TCAs) and trazodone showed distinct patterns of use. TCAs were more commonly used for non-psychiatric indications than for psychiatric indications, especially for sleep- and pain-related reasons. Trazodone was frequently recommended for sleep problems. The proportion of recommendations for depressive disorders for antidepressants as a group remained stable over the 5-year study period. CONCLUSIONS: About one-third of antidepressant recommendations are for reasons other than depression. It can no longer be assumed that the frequency of antidepressant use is a measure of the frequency of pharmacological depression treatment. However, prescription data may be useful for tracking trends.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".