Ndenkeh Jackson Jr Nforbewing, Aidoo-Frimpong Gloria A, Nelson LaRon E, Peng Mary L, Balakrishnan Vimala, Barnhart Victoria, Davis Bernard, Prayer James Donté, Quamina Alvan, Ni Zhao
School of Nursing, Yale University, New Haven, Connecticut, United States of America.
Center for Interdisciplinary Research on AIDS (CIRA), School of Public Health, Yale University, New Haven, Connecticut, United States of America.
PLOS Digit Health. 2025 Jun 4;4(6):e0000891. doi: 10.1371/journal.pdig.0000891. eCollection 2025 Jun.
Gay, bisexual, and other men who have sex with men (MSM) account for 60% of new HIV infections among Black Americans in the Southern United States (U.S.). Despite recommendations for frequent HIV testing and daily pre-exposure prophylaxis (PrEP) uptake, there remains a gap in PrEP uptake among these Black MSM in the Southern U.S. Artificial Intelligence (AI) chatbots have the potential to boost users' health awareness and medication adherence. This study aims to evaluate Black MSM' perspectives on the challenges to the uptake of PrEP and identify Black MSM-preferred chatbot functionalities and platforms for embedding AI chatbots. Five focus group discussions were conducted (February - March 2024) among 21 Black MSM in the Southern U.S. Interview transcripts were thematically analyzed according to challenges to PrEP uptake and the four domains of the Unified Theory of Acceptance and Use of Technology (UTAUT): performance expectancy, effort expectancy, facilitating conditions, and social influence. Black MSM identified lack of awareness or insufficient information, stigmatizations of sexuality, HIV, and PrEP, as well as concerns with side effects, and low self-perceived HIV vulnerability as the major challenges they faced in PrEP uptake. Moreover, chatbots were perceived as an acceptable option for delivering PrEP education (performance expectancy), especially with accessible, user-friendly interfaces (effort expectancy). Other desired features included simplifying access to PrEP information, incorporating culturally sensitive algorithms, upholding anonymity (social influence), and linking users to healthcare providers and resources (facilitating condition). The study highlights the multifaceted considerations for the adoption of AI chatbots as an HIV-prevention intervention among Black MSM in the Southern U.S.
男同性恋者、双性恋者以及其他与男性发生性行为的男性（MSM）占美国南部非裔美国人新增艾滋病毒感染病例的60%。尽管有建议要经常进行艾滋病毒检测并每日服用暴露前预防药物（PrEP），但美国南部的这些黑人男男性行为者在PrEP的服用方面仍存在差距。人工智能（AI）聊天机器人有潜力提高用户的健康意识和药物依从性。本研究旨在评估黑人男男性行为者对PrEP服用面临的挑战的看法，并确定黑人男男性行为者偏爱的聊天机器人功能以及嵌入人工智能聊天机器人的平台。在美国南部的21名黑人男男性行为者中进行了五次焦点小组讨论（2024年2月至3月）。根据PrEP服用面临的挑战以及技术接受与使用统一理论（UTAUT）的四个领域：绩效期望、努力期望、促进条件和社会影响，对访谈记录进行了主题分析。黑人男男性行为者认为缺乏认识或信息不足、对性取向、艾滋病毒和PrEP的污名化，以及对副作用的担忧和自我感知的低艾滋病毒易感性是他们在服用PrEP时面临的主要挑战。此外，聊天机器人被视为提供PrEP教育的可接受选择（绩效期望），尤其是具有易于使用的用户友好界面时（努力期望）。其他期望的功能包括简化获取PrEP信息的途径、纳入具有文化敏感性的算法、维护匿名性（社会影响）以及将用户与医疗保健提供者和资源联系起来（促进条件）。该研究强调了在美国南部黑人男男性行为者中采用人工智能聊天机器人作为艾滋病毒预防干预措施时需要多方面考虑。
