Brief Report:Availability of and Interest in Gender-Affirming Care, PrEP, and HIV Prevention Services in a Global Sample of Transmasculine Persons
Bibliographic record
Abstract
BACKGROUND: We assessed access to pre-exposure prophylaxis (PrEP) and interest in integration of PrEP with gender-affirmative care in a global sample of transmasculine persons. METHODS: Transmasculine persons (N = 590) aged 18 years and above from 57 countries completed a brief online survey from April to July 2022 about sexual behavior, knowledge, and interest in PrEP, current access to PrEP and gender-affirmative care, and preferred context for accessing PrEP. Descriptive analyses were stratified by country income group. RESULTS: Most participants (54.4%) lived near a health center offering care to trans people. Overall, 1.9% of respondents reported ever receiving a positive HIV test result. Among those who had not (n = 579), more than a third reported engaging in receptive sex in the past year (35.2%) or anticipated doing so in the next year (41.5%), 86.9% had never received information about HIV prevention specific to transmasculine people, and 76.3% had heard of PrEP. Among those who had heard of PrEP (n = 440), only 18.9% had discussed or been offered it by a provider, and only 3.6% were currently taking it-yet 67.9% who had heard of it but were not using it would "definitely" (28.5%) or "maybe" (39.4%) be interested in taking it were it available for free. Out of these participants, the majority (60.5%) preferred the idea of accessing PrEP from the same clinic where they received gender-affirming care. CONCLUSIONS: Interventions are needed to improve PrEP access for transmasculine people globally. Clinics already providing gender-affirming care to trans people are acceptable clinical contexts to integrate such interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".