Factors Associated with Women's Medication Use
Bibliographic record
Abstract
HEALTH ISSUE: Research has consistently shown that while women generally live longer than men, they report more illness and use of health care services (including medication). In the literature, the reasons for women's elevated medication use are not clear. This paper investigates the associations between over-the-counter (OTC) and prescription (Rx) medication use and selected social and demographic variables in men and women. KEY FINDINGS: While a larger proportion of women than men used medication throughout the study, the proportion of people using medication did not increase. The use of OTC and Rx medication increased by number of physician visits for women and men.Medication use increased with age, chronic disease and number of physician visits, and decreased with the perception of good to excellent health. The relationship with other factors varied for women and men depending on their education level, income and social roles. For women, the social roles of being married or previously married, being employed or being a parent did not increase their likelihood of medication use. Reported income adequacy is not associated with the chances of mediation use among highly educated women, but for women with low levels, medication use increases as income adequacy decreases. DATA GAPS AND RECOMMENDATIONS: More complete data are needed about social roles and their relation to mediation use. Data that would allow an assessment of the appropriateness of OTC and Rx drug use or the reasons for such use need to be collected. More research is needed to better understand the distribution and determinants of specific medication use.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.008 | 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".