A qualitative study assessing the acceptability of a multi-agent AI Chatbot for providing HIV and mental health support among men who have sex with men and transgender women in KwaZulu-Natal, South Africa

Journal article

Background: Transgender women (TGW) and men who have sex with men (MSM) are disproportionately affected by human immunodeficiency virus (HIV) and mental health challenges. Mental well-being influences uptake and adherence to HIV prevention and treatment. However, gaps in mental health service delivery present challenges for scalability in public health systems. Artificial intelligence (AI)-driven chatbots may offer a novel, scalable solution to expand access to mental health support. Methods: This qualitative study was conducted at the Aurum POP INN clinic in Pietermaritzburg, KwaZulu-Natal. A multi-agent AI chatbot, designed to simulate supportive counselling based on the Inuka model, was piloted with TGW and MSM. Ten participants engaged in in-depth interviews after interacting with the chatbot. An additional 34 participants experienced both chatbot and in-person counselling through a randomised crossover design and then participated in four focus group discussions. The Unified Theory of Acceptance and Use of Technology and the Acceptability of Healthcare Interventions Framework guided the analysis. Results: The chatbot was generally acceptable, with participants valuing its privacy, convenience and human-like interaction. Acceptability was enhanced by associations with modernity and anonymity. Trust, usability and accessibility improved engagement. Key barriers included slow response times, limited rapport and repetitive messaging. Conclusions: AI chatbots offer a promising, scalable approach to supporting mental health among key populations in HIV care.

Authors: Humphries, H; Msimango, L; Tshawe, Z; Gcelu, N; Ferreira, K

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Oxford University Press
• Journal: Transactions of The Royal Society of Tropical Medicine and Hygiene
• Article number: traf143
• Publication date: 2026-01-13
• Acceptance date: 2025-12-01
• DOI: 10.1093/trstmh/traf143
• EISSN: 1878-3503
• ISSN: 0035-9203
• Language: English
• Keywords: transgender women; HIV treatment; HIV prevention; key populations; MSM; chatbots; South Africa; artificial intelligence; mental health