Active-Offer Nurse-Led PrEP (PrEP-RN) Referrals: Analysis of Uptake Rates and Reasons for Declining
Bibliographic record
Abstract
While pre-exposure prophylaxis (PrEP) is an effective HIV prevention strategy, its uptake is limited. To address barriers, we piloted a nurse-led PrEP clinic in an STI clinic and had public health nurses refer patients during STI follow-up. We recorded the number of PrEP offers and declines and clinic uptake. We conducted a thematic analysis of patients' responses from nursing notes written at the time patients declined PrEP. From August 6, 2018 to August 5, 2019, nurses offered a PrEP referral to 261 patients who met our criteria; only 47.5% accepted. Qualitative analysis identified four themes: (1) perceptions of risk, (2) lack of interest, (3) inability to manage, and (4) concerns about PrEP. Our patients did not feel sufficiently at-risk for HIV to use PrEP and maintained that PrEP was for a reckless "other". This analysis sheds light on how assumptions about risk affect PrEP uptake, particularly among those at-risk for HIV.
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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 | 0.014 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".