A qualitative exploration of barriers to HIV prevention, treatment and support: Perspectives of transgender women and service providers
Bibliographic record
Abstract
Transgender (trans) women experience barriers to access to HIV care, which result in their lower engagement in HIV prevention, treatment and support relative to cisgender people living with HIV. Studies of trans women's barriers to HIV care have predominantly focused on perspectives of trans women, while barriers are most often described at provider, organisation and/or systems levels. Comparing perspectives of trans women and service providers may promote a shared vision for achieving health equity. Thus, this qualitative study utilised focus groups and semi-structured interviews conducted 2018-2019 to understand barriers and facilitators to HIV care from the perspectives of trans women (n = 26) and service providers (n = 10). Barriers endorsed by both groups included: (a) anticipated and enacted stigma and discrimination in the provision of direct care, (b) lack of provider knowledge of HIV care needs for trans women, (c) absence of trans-specific services/organisations and (d) cisnormativity in sexual healthcare. Facilitators included: (a) provision of trans-positive trauma-informed care, (b) autonomy and choice for trans women in selecting sexual health services and (c) models for trans-affirming systems change. Each theme had significant overlap, yet nuanced perspective, between trans women and service providers. Specific recommendations to improve HIV care access for trans women are discussed. These recommendations can be used by administrators and service providers alike to work collaboratively with trans women to reduce barriers and facilitators to HIV care and ultimately to achieve health equity for trans women.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".