Use of Antidepressants Among Elderly Subjects: Trends and Contributing Factors
Bibliographic record
Abstract
OBJECTIVE: The authors assessed changes over time in antidepressant utilization among elderly subjects regarding the prevalence of antidepressant users, shifts in prescription patterns, and related financial implications. METHOD: The authors conducted a population-based study of more than 1.4 million Ontario residents aged 65 years or older. Cross-sectional data regarding annual antidepressant utilization were obtained from administrative databases for 1993 to 1997. Time series analysis was used to assess trends over time and to make future projections. RESULTS: The proportion of antidepressant users increased from 9.3% of the elderly population in 1993 to 11.5% in 1997. Prescriptions for selective serotonin reuptake inhibitors (SSRIs) accounted for 9.6% of antidepressant prescriptions dispensed in the first 30 days of 1993 and 45.1% of those dispensed by the last 30 days of 1997 and were projected to increase to approximately 56% by the end of 2000. Prescriptions for tricyclic antidepressants fell from 79.0% in the first 30 days of 1993 to 43.1% by the last 30 days of 1997 and were projected to decline to approximately 28% by the end of 2000. Annual antidepressant costs (in Canadian dollars) increased by 150%, from $10.8 million in 1993 to $27.0 million in 1997. Population shifts and an increase in the prevalence of antidepressant users accounted for at least 20% of this increase, whereas the prescribing transition from tricyclic antidepressants to SSRIs accounted for at least 61% of the increase. CONCLUSIONS: The introduction of SSRIs has had a substantial financial impact at the drug utilization level. Future research should address the appropriate balancing of the cost of newer agents versus their ostensible advantages.
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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 | 0.000 | 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) | 0.001 | 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 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".