Preferences Among Physicians and Men Who Have Sex with Men (MSM) for a Long-Acting, Removable Implant for HIV Prevention: A Discrete Choice Study
Bibliographic record
Abstract
A longer acting, removable implant for HIV prevention has the potential to improve uptake of HIV pre-exposure prophylaxis (PrEP) by removing the need for daily adherence to an oral tablet, reducing potential side effects, and eliminating concerns about residual drug following injections. To end the HIV epidemic, we must understand the needs and preferences of groups most affected by HIV (e.g., men who have sex with men; MSM), and the physicians who prescribe PrEP to them. This article describes a discrete choice experiment to estimate the preference share for the implant within a competitive context of other PrEP products (including the oral tablet, dissolvable implant, and injection) and evaluate the impact of potential implant attributes. Physicians who had prescribed oral PrEP ( n = 75) and MSM at risk for HIV ( n = 175) completed a web-based survey that prompted decision-making about PrEP product preferences. The findings from both physicians and MSM demonstrated that the removable implant could capture a meaningful portion of the preference share, making it feasible to advance in the development pipeline as an important addition to the biomedical HIV prevention toolkit. Among MSM, specifically, the cost of treatment was the most important attribute impacting product preference. Our findings inform implant developers and future payers (e.g., commercial manufacturers, insurance companies) about specific device attributes that will likely affect MSM's willingness to use and physicians' willingness to prescribe this HIV prevention strategy.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".