Systematic review examines AI strategies for HIV prevention and care, indicating key facilitators and barriers.
This preprint presents a systematic review and qualitative evidence synthesis examining facilitators and barriers to user-facing artificial intelligence (AI) strategies in HIV prevention and care. Following PRISMA and ENTREQ guidelines, we searched four databases and identified 15 qualitative and mixed-methods studies across eight countries. Findings indicate that AI strategies, such as chatbots, risk prediction models, and mobile applications, can provide judgment-free spaces and support engagement, with anonymity facilitating uptake and confidentiality concerns acting as a barrier. Overall, AI is best positioned as a complementary tool to support, rather than replace, existing HIV care pathways.
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Abafita et al. (2026) studied this question.
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