Journal of acquired immune deficiency syndromes (1999)
October 1, 2026 · via Europe PMC
Preferences for HIV Testing Among Partners of Transgender Women in Lima, Peru: A Discrete Choice Experiment.
Tollefson D, Lankowski A, Dasgupta S, Kazmirak C, Sanchez H, Gonzales I, Duerr A.
AI summary — for doctors, generated from the abstract only
Among partners of transgender women in Lima, cost dominated HIV testing preferences, but many would pay for testing at a clinic known to be LGBTQ+ friendly.
What was studied
A discrete choice experiment conducted September-November 2023 with 292 HIV-negative partners of transgender women recruited by referral in Lima, Peru, evaluating six HIV testing attributes over 12 choice tasks, with conditional logit modelling, latent class analysis and willingness-to-pay estimates.
Key findings
- Cost carried 50% relative attribute importance and LGBTQ+ friendly clinic affiliation 36%
- Participants were willing to pay about 39 Soles (95% CI 31-47; about USD 10.70) for testing at LGBTQ+ affiliated clinics and 7 Soles (0.8-13; about USD 1.90) at private clinics
- Three latent classes: 52% with null preferences, 27% strongly preferring LGBTQ+ friendly clinics, 21% prioritizing free testing
Clinical relevance
Programmes may increase HIV testing uptake in this overlooked group by offering free testing at trusted LGBTQ+ affiliated clinics, though stated preferences in a referral sample may not match actual behaviour.
Who should care
Limitations
Hypothetical choice experiment in a referral-recruited convenience sample in one city, with half of participants showing no clear preferences.
Free testing matters most, but a trusted LGBTQ+ friendly setting carries real value to these men.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Background
Partners of transgender women (PTW) are a relatively overlooked population despite being at disproportionately high risk for HIV in Latin America. Understanding PTW preferences for HIV testing is crucial to inform the delivery of effective HIV testing and prevention services for this population.
Setting
Lima, Peru.
Methods
From September to November 2023, we recruited HIV-negative PTW for a discrete choice experiment (DCE) evaluating preferences for HIV testing services. PTW were recruited through referral from transgender women. The DCE considered 6 attributes for HIV testing, each with 2 to 3 levels. Participants were presented a total of 12 choice tasks. We used conditional logit modeling to estimate preferences and performed latent class analysis to explore heterogeneity. In addition, we evaluated willingness to pay for preferred HIV testing service attributes.
Results
Overall, 292 PTW completed the DCE. Attributes with the greatest influence on HIV testing preferences were cost (50% relative attribute importance) and affiliation with an LGBTQ+ friendly clinic (36%). Although participants strongly preferred free HIV testing, they were willing to pay an estimated 39 Soles (95% CI: 31 to 47 Soles) ($10.70 USD) for testing at LGTBQ+ affiliated clinics and 7 Soles (0.8-13 Soles) ($1.90) for testing at private clinics. Three latent classes were identified: 52% belonged to a class with null preferences, 27% to a class with strong preferences for testing at LGBTQ+ friendly clinics, and 21% with strongest preferences for free testing.
Conclusions
PTW were most concerned about cost of HIV testing but may be willing to pay for a service offered at clinics known and trusted by the LGTBQ+ community. To enhance uptake of HIV testing in this population, programs could prioritize LGTBQ+ affiliated clinics as sites of service provision.
DOI
10.1097/qai.0000000000003909
PMID
42358033
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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