Sexual Health Needs Among Men Who Engage in Transactional Sex with Men in the UK
Bibliographic record
Abstract
Men who engage in transactional sex with men (MTSM) are a high-risk population for HIV and other sexually transmitted infections. Epidemiological data have so far included them in the broad category of men who have sex with men (MSM), while research on transactional sex typically focused on female sex workers. The internet has substantially changed sex work practices and earlier findings concerning the sexual health needs of MTSM may no longer be applicable. We analyzed quantitative data from MSM based in the UK (n = 11629) taking part in the European MSM Internet Survey (EMIS-2017). Compared to non-MTSM, MTSM (n = 230; 2%) were younger, more likely to self-identify as an ethnic minority, be single, have lower education levels, struggle financially, and-controlling for age-more likely to be living with diagnosed HIV. Commonly unmet needs among all MSM were a lack of confidence in accessing HIV post-exposure prophylaxis, uncertainty about HIV status, and ignorance of where to access hepatitis vaccinations. Compared with other MSM, MTSM were notably less satisfied with the safety of their sexual practices, less confident in their ability to maintain sexual boundaries, and more likely to engage in risk because of absent precautionary resources. Given their greater opportunity for sexual risk, as well as fewer resources for negotiating safety, our findings suggest that services should prioritize MTSM in HIV prevention and sexual health promotion, including assertiveness and social skills training, in addition to knowledge-based education.
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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 | 0.004 |
| 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) | 0.003 | 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".