What Predicts a Clinical Discussion About PrEP? Results From Analysis of a U.S. National Cohort of HIV-Vulnerable Sexual and Gender Minorities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
HIV-outcome inequities remain prevalent in the U.S. Medical providers (MPs) are gatekeepers of PrEP, and understanding the dynamics of PrEP assessments is of major interest for public health. We analyzed data from Together 5000, an internet-based U.S. national cohort of sexual and gender minority (SGM) individuals aged 16-49 years and at risk for HIV. Among those eligible for PrEP uptake (n = 6264), we modeled predictors of discussing PrEP with an MP. A third (31%) of participants had spoken to a MP about PrEP. Among those who spoke to a MP, 45% suggested they would initiate PrEP; this outcome was more common among participants older than 24. With a persistent stagnant uptake nationwide, new opportunities to influence PrEP uptake must be explored. An attractive less targeted space is the medical office, specifically ways to support an initial and continued discussion about PrEP between MPs and their patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it