Trends in the awareness, acceptability, and usage of HIV pre-exposure prophylaxis among at-risk men who have sex with men in Toronto
Bibliographic record
Abstract
OBJECTIVES: Pre-exposure prophylaxis (PrEP) with daily oral tenofovir/emtricitabine dramatically reduces HIV risk in men who have sex with men (MSM). However, uptake is slow worldwide. METHODS: We administered anonymous cross-sectional questionnaires to MSM presenting for anonymous HIV testing at a Toronto sexual health clinic at four successive time points during the period 2013-2016. We assessed trends in PrEP awareness, acceptability, and use over time using the Cochran-Armitage Trend Test, and identified barriers to using PrEP by constructing "PrEP cascades" using 2016 data. We assumed that to use PrEP, MSM must (a) be at risk for HIV, (b) be at objectively high risk (HIRI-MSM score ≥ 10), (c) perceive themselves to be at medium-to-high risk, (d) be aware of PrEP, (e) be willing to use PrEP, (f) have a family doctor, (g) be comfortable discussing sexual health with that doctor, and (h) have drug coverage/be willing to pay out of pocket. RESULTS: MSM participants were mostly white (54-59.5%), with median age 31 years (IQR = 26-38). PrEP awareness and use increased significantly over time (both p < 0.0001), reaching 91.3% and 5.0%, respectively, in the most recent wave. Willingness to use PrEP rose to 56.5%, but this increase did not reach statistical significance (p = 0.06). The full cascade, ABCDEFGH, suggested few could readily use PrEP under current conditions (11/400 = 2.8%). The largest barriers, in descending order, were low self-perceived HIV risk, unwillingness to use PrEP, and access to PrEP providers. CONCLUSION: To maximize its potential public health benefits, PrEP scale-up strategies must address self-perceived HIV risk and increase access to PrEP providers.
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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 | 0.002 |
| 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) | 0.002 | 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".