Social differences associated with the use of psychotropic drugs among men and women aged 65 to 74 years living in the community: the international mobility in aging study (IMIAS)
Bibliographic record
Abstract
BACKGROUND: Elderly persons make greater use of psychotropic drugs, but there are few international studies on social differences in the use of these medications. The aim of this study is to examine social differences in the use of psychotropic drugs among persons aged 65-74 years in the International Mobility in Aging Study (IMIAS). METHODS: The sample consisted of 1,995 participants in the IMIAS 2012 baseline study in Saint-Hyacinthe (Canada), Kingston (Canada), Tirana (Albania), Manizales (Colombia), and Natal (Brazil). During home visits, all medication taken by the participants in the previous 15 days was recorded. We then used the Anatomical Therapeutic Chemical classification system to code psychotropic drugs as anxiolytics, sedatives, hypnotics (ASH); antidepressants (ADP); or analgesics, antiepileptics, or antiparkinsonians (AEP). Prevalence ratios for psychotropic drug use according to sex, education, income, and occupation were estimated by fitting a Poisson regression and controlling for demographic and health covariates. RESULTS: Psychotropic drug use was higher among Canadian participants than among those living outside Canada. Prevalence of AEP drug use was higher for women than men in the Canadian and Latin American sites. In Tirana, antidepressant drugs were rarely used. Socioeconomic differences varied among sites. In the Canadian cities, low socioeconomic standing was associated with higher frequency of psychotropic drug use. In the Latin American cities, elderly people with high education and income levels showed a higher level of antidepressant drug use, while people with manual occupations had a higher use of AEP drugs. In Tirana, ASH drug use was higher among those with low income. CONCLUSION: An inverse association was observed between socioeconomic standing and psychotropic drug use in Canada, while the opposite was true in Latin America. Albania was notable for an absence of antidepressant use and greater use of ASH drugs among low-income groups.
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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 | 0.001 |
| 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 | 0.001 |
| 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".