“The Women’s PrEP Project,” a Clinic-Based, Socio-Structural Intervention to Improve the Provision of Preexposure Prophylaxis for Cisgender Women: Interrupted Time Series Pilot
Bibliographic record
Abstract
Background: Cisgender women account for 23% of new HIV diagnoses in the United States, but there are significant socio-structural barriers to engagement and retention in the preexposure prophylaxis (PrEP) cascade, particularly for women of color. Objective: In response to the lack of evidence-based interventions to improve PrEP initiation, adherence, and persistence among women in the United States, we developed and piloted a clinic-based, socio-structural intervention to measure (1) the feasibility of delivering the adapted intervention and (2) clinic team and patient perspectives on the intervention, in preparation for a future trial on engagement and retention in the PrEP cascade among women. Methods: We previously applied the ADAPT-ITT (Assessment, Decision, Adaptation, Production, Topical experts, Integration, Training, Testing) model to develop a culturally appropriate, evidence-based intervention, responsive to Black women's HIV prevention needs. In the present study, we set out to complete the Training and Testing phases: namely, to hire and train a PrEP navigator and to train clinic staff to deliver the adapted intervention. We completed a 4-month pilot to assess the feasibility of delivering the intervention and collecting outcomes of interest and initial outcome trends (compared to baseline). We further assessed the clinic team and patient perspectives on the intervention to understand the potential for future scale and delivery. Results: The clinic team participants found the adapted Women's PrEP project (W-PrEP) intervention both highly feasible and relevant to patients, with minimal impact on clinic flow. Patient participants reported that the W-PrEP intervention was highly relevant and appreciated the education and counseling from the PrEP navigator-many learning about PrEP for the first time from the navigator and health care provider. The outcome measures were both feasible to collect and appropriate to capture the primary outcomes of interest. Finally, the W-PrEP intervention increased the proportion of patients counseled about PrEP from 65% to 76% of patients seen (P<.001). Conclusions: The intervention and outcome data collection was feasible, and open-ended clinic team and patient perspectives showed positive feedback about the intervention and relevance. The associated increase in PrEP counseling is promising but necessitates further evaluation of the effects of the W-PrEP intervention on the PrEP cascade (eg, initiation, persistence, adherence) in a larger randomized trial.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".