HIV prevention for women: Exploring the uptake of pre- and postexposure prophylaxis (PrEP and PEP) among cis and trans women accessing nurse-led HIV prevention services in Ottawa, Canada (PrEP-RN)
Bibliographic record
Abstract
In response to increased HIV prevention efforts (PEP and PrEP), HIV rates in Ontario have decreased among gay men. By extension, the proportion of first-time HIV diagnoses in cis and trans women has increased, prompting concern for ongoing HIV transmissions. Presently, uptake of HIV prevention services among women is limited, largely due to variability of HIV-specific risk factors. To explore HIV prevention use among women, a retrospective review was completed of participants in a nurse-led HIV prevention service (PEP-RN and PrEP-RN) in Ottawa, Canada. Results showed 10% uptake for PEP and 3% uptake for PrEP among women. For PEP, 32 women presented for assessment, and 25 were initiated. Most PEP initiations were made following a potential sexual exposure to HIV, and 36% involved a partner who was HIV positive and not virally suppressed. For PrEP, offers for referral were made to 59 women; 28 declined, and 31 accepted. Among women who declined PrEP, 32% were HIV contacts, and among those who accepted, 80% were due to reported sexual or substance use practices. The highest PrEP engagement occurred among women receiving services in a safer opiate supply program. The high uptake of PEP suggests this could be a useful strategy to reducing HIV transmission rates in women. In addition, women receiving PrEP could benefit from a more supportive approach to care, including assistance with mediation use and regular contact with nurses. In using a more collaborative and gender-based approach to HIV prevention care, progress can be made in addressing ongoing HIV inequities among women.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".