Factors associated with interest in and knowledge of pre-exposure prophylaxis (PrEP) among gay, bisexual, and other men who have sex with men (GBMSM) in the Region of Waterloo, Ontario, Canada: Insights from the OutLook Study
Bibliographic record
Abstract
Pre-exposure prophylaxis (PrEP) is an effective HIV-prevention tool for gay, bisexual, and other men who have sex with men (GBMSM), a group known to be disproportionately affected by HIV/AIDS. We aimed to identify sociodemographic, psychosocial, and health factors associated with awareness of PrEP or interest in PrEP among GBMSM in a mid-sized Canadian city, where PrEP availability is arguably more scarce compared to larger metropolitan regions. The OutLook Study was a comprehensive online survey of LGBTQ health and well-being that collected data from sexual minorities aged 16+ in the Region of Waterloo, Ontario, Canada. Participants were cisgender MSM with an unknown or negative HIV status (n = 203). Bivariate logistic regression was performed to analyze factors associated with both awareness of PrEP and interest in PrEP. Multivariate logistic regression explored sexual behaviours in the past 12 months while controlling for sociodemographic and psychosocial variables. Increasing number of sexual partners (OR: 1.10; 95% CI: 1.03–1.53) was significantly associated with interest in PrEP and lifetime experiences of homophobia remained significant from the bivariate model (ORs ranged from 1.11–1.12). Since GBMSM with low educational attainment were shown to have less knowledge about PrEP, educational campaigns could be targeted in high schools rather than colleges, universities, and trade schools. Prevention initiatives should be aimed at places where single or non-monogamous GBMSM frequent due to these men being disproportionately affected by HIV/AIDS. These findings provide insights for potential interventions targeting MSM from mid-sized cities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".