Acceptability of HIV Pre-Exposure Prophylaxis Among Transgender Women in India: A Qualitative Investigation
Bibliographic record
Abstract
Despite high HIV prevalence among transgender women (TGW) in India, there is limited exploration of pre-exposure prophylaxis (PrEP) acceptability. With PrEP licensure pending, we conducted six focus group discussions (FGDs) with diverse TGW (n = 36), and eight key informant interviews with community leaders and physicians, in Mumbai and Chennai. Data were explored using framework analysis guided by the Theoretical Framework of Acceptability. FGD participants' mean age was 26.1 years (SD = 4.8); two-thirds engaged in sex work. TGW reported low PrEP awareness, with moderate acceptability once PrEP was explained. Population-specific facilitators of PrEP acceptability included its perceived effectiveness in the context of challenges to condom use in serodiscordant relationships and forced sex encounters. PrEP was considered especially appropriate for TGW sex workers; however, barriers were anticipated in the context of hierarchical hijra (indigenous trans identity) kinship networks and gurus' (masters) potential negative reactions to PrEP use by their chelas (disciples). Positive attitudes toward high efficacy and potential covert use were tempered by TGW's concerns about high costs and adherence challenges living with parents or primary partners, and TGW sex workers' unpredictable schedules. Anticipated interactions with feminizing hormones, visible side effects, and PrEP-related stigma within TGW communities emerged as opportunity costs. PrEP implementation for TGW in India should promote comprehensive information on side effects and potential interactions with feminizing hormones, provide free or subsidized PrEP, and highlight the advantages of added protection in sex work and forced sexual encounters. Meaningful engagement with TGW kinship networks can encourage positive transgender community norms on PrEP use and mitigate multifaceted stigma.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".