Prescription Drug Insurance and Cost-Related Medication Nonadherence Among Lesbian, Gay, and Bisexual Individuals in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: This study estimates the frequency of uninsurance for prescription drugs and cost-related medication nonadherence (CRNA) among lesbian, gay, and bisexual (LGB) persons in Canada, compared with the heterosexual population. Methods: Logistic regression was used to quantify associations between sexual orientation, insurance status, and CRNA within the national probability-based Canadian Community Health Survey, 2015–2016. This sample included 98,413 individuals aged 15–80 years, including 2803 LGB individuals. Results: From our sample of Canadians, 22.2% of LGB respondents reported being uninsured for prescription drugs, compared with 20.0% of heterosexual persons (unadjusted odds ratio [UOR] 1.14, 95% confidence interval [CI] 0.97–1.35). LGB individuals had more than twice the odds of reporting CRNA compared with heterosexual individuals (UOR 2.48, 95% CI 1.99–3.10). This disparity was most pronounced among bisexual respondents, who had over three times the odds of reporting CRNA in comparison to heterosexual respondents (UOR 3.45, 95% CI 2.65–4.51). The odds ratio (OR) for CRNA comparing bisexual with heterosexual individuals remained statistically significant after adjustment for race/ethnicity, gender/sex, and age (OR 2.67, 95% CI 1.97–3.61) and was further attenuated with adjustment for partnership status, employment status, income, educational attainment, prescription drug insurance status, general health status, and immigration status (OR 2.09, 95% CI 1.51–2.89). Conclusion: LGB Canadians reported more CRNA but comparable prescription drug insurance frequencies to heterosexual persons. Factors pertaining to medication access (e.g., income, partnership status) and health needs appear to be the most important contributors to disparities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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 it