Pattern of Psychotropic Drug Use among Older Adults Having a Depression or an Anxiety Disorder: Results from the Longitudinal ESA Study
Bibliographic record
Abstract
OBJECTIVE: To document the use of psychotropic drugs in Quebec older adult population with a depressive or anxiety disorder. METHOD: Data from the Enquête sur la Santé des Aînés (ESA) study conducted between 2005 and 2008 using a representative sample (n = 1869) of community-dwelling adults aged 65 years and older were used to examine the use of psychotropic drugs in the Quebec older adult population. RESULTS: Our results indicate that only 46.9% of the older adults with a diagnosis of depression or anxiety during the 24-month period studied according to the Régie de l'assurance maladie du Quebec (RAMQ) register used antidepressants (AD) for 400 days (12.9 months) on average during this period. Also, 59% of the RAMQ's mental health disorder patients used a mean daily dose of 5 mg of a diazepam equivalent for 338 days (10.9 months) on average during the same period. However, 10.0% of the older adults without any symptoms (ESA) at T1 and at T2 and any RAMQ depression and anxiety diagnosis between T0 and T2 were AD users during the 24-month period studied. They represent 26.2% of the AD users and consumed them for 494 days (15.9 months) on average during the 24-month period studied. Finally, the number of days of AD and benzodiazepine use was not associated with partial or total remission. CONCLUSIONS: This result questions the population effectiveness of these drugs in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".