Barriers and facilitators to HIV and sexually transmitted infections testing for gay, bisexual, and other transgender men who have sex with men
Bibliographic record
Abstract
Transgender men who have sex with men (trans MSM) may be at elevated risk for HIV and other sexually transmitted infections (STI), and therefore require access to HIV and STI testing services. However, trans people often face stigma, discrimination, and gaps in provider competence when attempting to access health care and may therefore postpone, avoid, or be refused care. In this context, quantitative data have indicated low access to, and uptake of, HIV testing among trans MSM. The present manuscript aimed to identify trans MSM's perspectives on barriers and facilitators to HIV and STI testing. As part of a community-based research project investigating HIV risk and resilience among trans MSM, 40 trans MSM aged 18 and above and living in Ontario, Canada participated in one-on-one qualitative interviews in 2013. Participants described a number of barriers to HIV and other STI testing. These included both trans-specific and general difficulties in accessing sexual health services, lack of trans health knowledge among testing providers, limited clinical capacity to meet STI testing needs, and a perceived gap between trans-inclusive policies and their implementation in practice. Two major facilitators were identified: access to trusted and flexible testing providers, and integration of testing with ongoing monitoring for hormone therapy. Based on these findings, we provide recommendations for enhancing access to HIV and STI testing for this key population.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".