Factors associated with antidepressant, anxiolytic and hypnotic use over 17 years in a national cohort
Bibliographic record
Abstract
BACKGROUND: In the general population, most individuals with mental disorders are not treated with psychotropic medications. The objective of this study was to identify factors associated with psychotropic medication use over a 17 year period in a birth cohort. METHOD: Members of the 1946 British birth cohort (n=2,928 in 1999) reported psychotropic medication use in 1982 at age 36, in 1989 at age 43, and in 1999 at age 53. At each of the three time points, several factors were investigated for their association with antidepressant, anxiolytic or hypnotic medication use. RESULTS: After adjusting for severity of symptoms of depression and anxiety, clinical factors such as suicidal ideation, sleep difficulty and poor physical health were strongly associated with antidepressant, anxiolytic or hypnotic medication use in 1982 and 1989, but not in 1999. Non-clinical factors were infrequently associated with antidepressant, anxiolytic or hypnotic medication use in 1982 and 1989 after adjusting for severity of symptoms, however several non-clinical factors were associated with antidepressant, anxiolytic or hypnotic medication use in 1999 including being female (OR=1.4, 95% CI: 1.0, 1.9), unemployment (OR=2.9, 95% CI: 2.1, 4.1), living alone (OR=2.6, 95% CI: 1.7, 3.9), and being divorced, separated or widowed (OR=1.5, 95% CI: 1.1, 2.3). LIMITATIONS: Data were not available on help-seeking behaviour. CONCLUSIONS: Treatment of mental disorder with psychotropic medications is strongly associated with clinical factors. However, non-clinical factors continue to be significant, and may influence both treatment-seeking and prescribing behaviour.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".