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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
Abstract
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.
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“The supplementary search added studies from South Africa (Humphries et al., 2026), Nigeria (Das and Drolet, 2024), Thailand (Rivera, 2022), India (Mathupriya et al., 2025), and Japan (Skierś et al., 2025), but these remain few, and only one of them involved adolescents (Zanardi et al., 2026).”
From Artificial intelligence and immersive technologies for LGBTQ+ youth: a narrative review (2026) · cites this paper as Humphries et al., 2026
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“AI chatbots are acceptable to LGBTQ+ young people and valued for their anonymity, but current tools give generic responses and perform poorly outside North American and Western European contexts.”
From Artificial intelligence and immersive technologies for LGBTQ+ youth: a narrative review (2026) · cites this paper as Humphries et al., 2026
In the citing paper
“Humphries et al. (2026) piloted a multi-agent chatbot built on GPT-4-turbo to deliver introductory problemsolving support to 44 men who have sex with men and transgender women aged 18-29 in KwaZulu-Natal, South Africa, all with mild to moderate depressive symptoms.”
From Artificial intelligence and immersive technologies for LGBTQ+ youth: a narrative review (2026) · cites this paper as Humphries et al., 2026
In the citing paper
“Participants valued its privacy, its convenience, and the absence of judgement, but described slow and repetitive responses and a limited sense of rapport, and most saw the chatbot as an addition to in-person counseling rather than a substitute for it.”
From Artificial intelligence and immersive technologies for LGBTQ+ youth: a narrative review (2026) · cites this paper as Humphries et al., 2026
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Abd-Alrazaq, A. A., Alajlani, M., Ali, N., Denecke, K., Bewick, B. M., & Househ, M. (2021) · Journal of Medical Internet Research · doi:10.2196/17828 · Cited by 301
“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health
Siddals, S., Torous, J., & Coxon, A. (2024) · npj Mental Health Research · doi:10.1038/s44184-024-00097-4 · Cited by 241
Chatbots to Support Young Adults’ Mental Health: An Exploratory Study of Acceptability
Koulouri, T., Macredie, R. D., & Olakitan, D. (2022) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3485874 · Cited by 127
Operario, D., Sun, S., Bermudez, A. N., Masa, R., Shangani, S., van der Elst, E., & Sanders, E. (2022) · The Lancet HIV · doi:10.1016/s2352-3018(22)00076-5 · Cited by 99
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Artificial intelligence and immersive technologies for LGBTQ+ youth: a narrative review
Shekarchi, R., Eleuteri, S., Saladino, V., Calaresi, D., Giordano, F., & Prunas, A. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.2002054
Metadata
- Authors
- Humphries, H., Msimango, L., Tshawe, Z., Gcelu, N., Ferreira, K., Pienaar, J., van der Elst, E. M., Giovenco, D., Operario, D., Sanders, E. J., & van Heerden, A.
- Affiliations
- Centre for Community-Based Research, Human Science Research Council , Sweetwaters 3201 ,
- Worien , Hilton 3245 ,
- Aurum Institute , Johannesburg 2193 ,
- Faculty of Social and Behavioural Sciences, University Utrecht , Utrecht 3508 ,
- Rollins School of Public Health, Emory University Hubert Department of Global Health, , Atlanta, GA 30322 ,
- Emory University Department of Behavioral, Social, and Health Education Sciences, , Atlanta, GA 30322 ,
- Syndicate for Public Science and Emerging Technologies, Wits Health Consortium , Johannesburg 2193 ,
- ORCID
- Humphries, Hilton
- Venue
- Transactions of The Royal Society of Tropical Medicine and Hygiene
- Publisher
- Oxford University Press (OUP)
- Published
- 2026-01-13
- Volume
- 120
- Issue
- 2
- Pages
- 160-174
- ISSN
- 0035-9203
- 1878-3503
- PMC
- PMC12863077
- Cited by
- 6
- References
- 6
- Language
- en
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