Self-reported indications for antidepressant use in a population-based cohort of middle-aged and elderly
Bibliographic record
Abstract
Background Population-based studies investigating indications for antidepressant prescribing mostly rely on diagnoses from general practitioners. However, diagnostic codes might be incomplete and drugs may be prescribed 'off-label' for indications not investigated in clinical trials. Objective We aimed to study indications for antidepressant use based on self-report. Also, we studied the presence of depressive symptoms associated with the self-reported indications. Setting Our study population of antidepressant users was selected based on interview data between 1997 and 2013 from the prospective population-based Rotterdam Study cohort (age >45 years). Method Antidepressant use, self-reported indication for use, and presence of depressive symptoms (Center for Epidemiological Studies Depression Scale) were based on interview. Self-reported indications were categorized by the researchers into officially approved, clinically-accepted and commonly mentioned off-label indications. Main outcome measures A score of 16 and higher on the Center for Epidemiological Studies Depression Scale was considered as indicator for clinically-relevant depressive symptoms. Results The majority of 914 antidepressant users reported 'depression' (52.4 %) as indication for treatment. Furthermore, anxiety, stress and sleep disorders were reported in selective serotonin reuptake inhibitor and other antidepressant users (ranging from 5.9 to 13.3 %). The indication 'pain' was commonly mentioned by tricyclic antidepressant users (19.0 %). Indications were statistically significantly associated with higher depressive symptom scores when compared to non-users (n = 10,979). Conclusions Depression was the main indication for antidepressant treatment. However, our findings suggest that antidepressants are also used for off-label indications, subthreshold disorders and complex situations, which were all associated with clinically-relevant depressive symptoms in the middle-aged and elderly population.
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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 | 0.001 | 0.003 |
| 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".