The Costs Associated with Antidepressant Use in Depression and Anxiety in Community-Living Older Adults
Bibliographic record
Abstract
OBJECTIVE: To determine the costs associated with antidepressant (AD) use by depression and anxiety status in a public-managed health care system. METHODS: Data were obtained from a population-based health survey of 1869 older adults. Depression and anxiety were based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria and measured at 2 time points 1 year apart. AD and health service use and costs were identified from provincial administrative databases and included hospitalizations, physician fees, outpatient medications, and ambulatory visits. Patient costs considered were related to drug copayments, transportation, and time spent seeking medical care. Annual costs associated with AD use were studied as a function of mental health status at baseline and follow-up interviews (persistence, incidence, remission, or no illness). Generalized linear models with a gamma distribution were used to control for individual factors. RESULTS: The costs incurred by participants using ADs as a whole (17.8%) reached $6678 (95% CI $5449 to $8182), significantly more than in participants not using ADs ($4698; 95% CI $3710 to $5949). AD use was associated with greater total adjusted costs among respondents with no depression (adjusted difference = $1769; 95% CI $236 to $3702) and no anxiety (adjusted difference = $1845; 95% CI $203 to $3486). CONCLUSION: The results showed that AD use was not associated with cost savings in any group, and indeed with greater costs among participants who were neither depressed nor anxious at any time point. Future cost studies may consider the analyses of different AD classes regarding the different clinical mental health profiles in older adults.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".