OBJECTIVE: The aim of this study was to identify the barriers to and facilitators of Malaysian MSM's acceptance of an AI chatbot designed to assist in HIV testing and prevention in relation to its perceived benefits, limitations, and preferred features among potential users.
METHODS: We conducted 5 structured web-based focus group interviews with 31 MSM in Malaysia between July 2021 and September 2021. The interviews were first recorded, transcribed, coded, and thematically analyzed using NVivo (version 9; QSR International). Subsequently, the unified theory of acceptance and use of technology was used to guide data analysis to map emerging themes related to the barriers to and facilitators of chatbot acceptance onto its 4 domains: performance expectancy, effort expectancy, facilitating conditions, and social influence.
RESULTS: Multiple barriers and facilitators influencing MSM's acceptance of an AI chatbot were identified for each domain. Performance expectancy (ie, the perceived usefulness of the AI chatbot) was influenced by MSM's concerns about the AI chatbot's ability to deliver accurate information, its effectiveness in information dissemination and problem-solving, and its ability to provide emotional support and raise health awareness. Convenience, cost, and technical errors influenced the AI chatbot's effort expectancy (ie, the perceived ease of use). Efficient linkage to health care professionals and HIV self-testing was reported as a facilitating condition of MSM's receptiveness to using an AI chatbot to access HIV testing. Participants stated that social influence (ie, sociopolitical climate) factors influencing the acceptance of mobile technology that addressed HIV in Malaysia included privacy concerns, pervasive stigma against homosexuality, and the criminalization of same-sex sexual behaviors. Key design strategies that could enhance MSM's acceptance of an HIV prevention AI chatbot included an anonymous user setting; embedding the chatbot in MSM-friendly web-based platforms; and providing user-guiding questions and options related to HIV testing, prevention, and treatment.
CONCLUSIONS: This study provides important insights into key features and potential implementation strategies central to designing an AI chatbot as a culturally sensitive digital health tool to prevent stigmatized health conditions in vulnerable and systematically marginalized populations. Such features not only are crucial to designing effective user-centered and culturally situated mobile health interventions for MSM in Malaysia but also illuminate the importance of incorporating social stigma considerations into health technology implementation strategies.
RESULTS: Women and girls comprise one-third of people who use and inject drugs globally. There is substantial variation in HIV prevalence in this population, between and within countries. There is a pronounced lack of data examining HIV risk among particularly vulnerable subpopulations of women who use and inject drugs, including women who have sex with women, transgender women, racial and ethnic minority women, and young women. Women who use and inject drugs experience stigma and discrimination that affect access to services, and high levels of sexual risk exposures.
CONCLUSIONS: There are significant gaps in our understanding of the epidemiology of drug use and injecting among women and girls and HIV risk and prevalence in this population. Women are frequently underrepresented in studies of drug use and HIV risk and prevalence among people who inject drugs, limiting our understanding of possible sex differences in this population. Most research originates from developed countries and may not be generalizable to other settings. A great deal of work is needed to improve understanding of HIV among particularly vulnerable subpopulations, such as transgender women who use drugs. Better data are critical to efforts to advocate for the needs of women and girls who use and inject drugs.