HIV Risk among Transgender Women: A Systematic Review of the Global Literature
Bibliographic record
Abstract
This review examines the global literature concerning HIV/STI risk factors among transgender women (TGW). The effects of marginalization intersecting with sex work, stigma, and abuse as well as sex- and drug-related risk behaviors merit a systematic review to enable a better understanding of how these factors impact HIV/STI transmission among TGW. The current paper synthesizes the results of 36 studies conducted in multiple cultural settings. Though the selected studies similarly found heightened HIV risks faced by TGW, the focuses varied concerning the impacts of HIV-related dynamics. These variances included the effect of sex work, social stigma, various forms of abuse/violence, sex- and substance risk behaviors, mental health, housing, employment, and the relationship between HIV and other STIs. While focus and results varied, the findings are in consensus that a lack of safe-sex knowledge, various forms of abuse/violence, and diminished autonomy accelerate the TGW’s risks of HIV/STIs. Variations in findings may be attributed to specific sociocultural settings and various research methods as well as differences in the risk factors being studied. This points to the need for more empirical studies – particularly those that specifically target TGW and the mechanisms of HIV/STI transmissions among the highly vulnerable 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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".