OBJECTIVE: We developed an innovative, clinic-integrated smartphone app called JomPrEP, which provides a virtual platform for Malaysian MSM to engage in HIV prevention services. In collaboration with the local clinics in Malaysia, JomPrEP offers a range of HIV prevention (ie, HIV testing and pre-exposure prophylaxis [PrEP]) and other support services (eg, referral to mental health support) without having to interface face to face with clinicians. This study evaluated the usability and acceptability of JomPrEP to deliver HIV prevention services for MSM in Malaysia.
METHODS: In total, 50 PrEP-naive MSM without HIV in Greater Kuala Lumpur, Malaysia, were recruited between March and April 2022. Participants used JomPrEP for a month and completed a postuse survey. The usability of the app and its features were assessed using self-report and objective measures (eg, app analytics, clinic dashboard). Acceptability was evaluated using the System Usability Scale (SUS).
RESULTS: The participants' mean age was 27.9 (SD 5.3) years. Participants used JomPrEP for an average of 8 (SD 5.0) times during 30 days of testing, with each session lasting an average of 28 (SD 38.9) minutes. Of the 50 participants, 42 (84%) ordered an HIV self-testing (HIVST) kit using the app, of whom 18 (42%) ordered an HIVST more than once. Almost all participants (46/50, 92%) initiated PrEP using the app (same-day PrEP initiation: 30/46, 65%); of these, 16/46 (35%) participants chose PrEP e-consultation via the app (vs in-person consultation). Regarding PrEP dispensing, 18/46 (39%) participants chose to receive their PrEP via mail delivery (vs pharmacy pickup). The app was rated as having high acceptability with a mean score of 73.8 (SD 10.1) on the SUS.
CONCLUSIONS: JomPrEP was found to be a highly feasible and acceptable tool for MSM in Malaysia to access HIV prevention services quickly and conveniently. A broader, randomized controlled trial is warranted to evaluate its efficacy on HIV prevention outcomes among MSM in Malaysia.
TRIAL REGISTRATION: ClinicalTrials.gov NCT05052411; https://clinicaltrials.gov/ct2/show/NCT05052411.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/43318.
OBJECTIVE: This paper presents a protocol of a bibliometric analysis aimed at offering the public insights into the current state and emerging trends in research related to the use of chatbot technology for promoting health.
METHODS: In this bibliometric analysis, we will select published papers from the databases of CINAHL, IEEE Xplore, PubMed, Scopus, and Web of Science that pertain to chatbot technology and its applications in health care. Our search strategy includes keywords such as "chatbot," "virtual agent," "virtual assistant," "conversational agent," "conversational AI," "interactive agent," "health," and "healthcare." Five researchers who are AI engineers and clinicians will independently review the titles and abstracts of selected papers to determine their eligibility for a full-text review. The corresponding author (ZN) will serve as a mediator to address any discrepancies and disputes among the 5 reviewers. Our analysis will encompass various publication patterns of chatbot research, including the number of annual publications, their geographic or institutional distribution, and the number of annual grants supporting chatbot research, and further summarize the methodologies used in the development of health-related chatbots, along with their features and applications in health care settings. Software tool VOSViewer (version 1.6.19; Leiden University) will be used to construct and visualize bibliometric networks.
RESULTS: The preparation for the bibliometric analysis began on December 3, 2021, when the research team started the process of familiarizing themselves with the software tools that may be used in this analysis, VOSViewer and CiteSpace, during which they consulted 3 librarians at the Yale University regarding search terms and tentative results. Tentative searches on the aforementioned databases yielded a total of 2340 papers. The official search phase started on July 27, 2023. Our goal is to complete the screening of papers and the analysis by February 15, 2024.
CONCLUSIONS: Artificial intelligence chatbots, such as ChatGPT (OpenAI Inc), have sparked numerous discussions within the health care industry regarding their impact on human health. Chatbot technology holds substantial promise for advancing health care systems worldwide. However, developing a sophisticated chatbot capable of precise interaction with health care consumers, delivering personalized care, and providing accurate health-related information and knowledge remain considerable challenges. This bibliometric analysis seeks to fill the knowledge gap in the existing literature on health-related chatbots, entailing their applications, the software used in their development, and their preferred functionalities among users.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/54349.
OBJECTIVE: This study aims to adapt an existing app to create and test a clinic-integrated app (JomPrEP), a virtual platform to deliver HIV testing and PrEP services for MSM in Malaysia.
METHODS: The JomPrEP project involves developing and testing an app-based platform for HIV prevention among Malaysian MSM and will be conducted in 2 phases. In phase I (development phase), we will adapt an existing mHealth app (HealthMindr) to create a new clinic-integrated app called "JomPrEP" to deliver holistic HIV prevention services (eg, HIV testing, PrEP, support services for mental health and substance use) among MSM in Malaysia. During phase II (testing phase), we will use a type I hybrid implementation science trial design to test the efficacy of JomPrEP while gathering information on implementation factors to guide future scale-up in real-world settings.
RESULTS: As of September 2022, we have completed phase I of the proposed study. Based on a series of formative work completed during phase I, we developed a fully functional, clinic-integrated JomPrEP app, which provides a virtual platform for MSM in Malaysia to facilitate their engagement in HIV prevention in a fast and convenient manner. Based on participant feedback provided during phase I, we are currently optimizing JomPrEP and the research protocols for a large-scale efficacy trial (phase II), which will commence in January 2023.
CONCLUSIONS: Scant HIV prevention resources coupled with entrenched stigma, discrimination, and criminalization of same-sex sexual behavior and substance use hamper access to HIV prevention services in Malaysia. If found efficacious, JomPrEP can be easily adapted for a range of health outcomes and health care delivery services for MSM, including adaptation to other low- and middle-income countries.
TRIAL REGISTRATION: ClinicalTrials.gov NCT05325476; https://clinicaltrials.gov/ct2/show/NCT05325476.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43318.
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.
OBJECTIVE: This study aims to test the feasibility and acceptability of an AI chatbot in promoting the uptake of HIV testing and pre-exposure prophylaxis (PrEP) in MSM.
METHODS: We conducted beta testing with 14 MSM from February to April 2022 using Zoom (Zoom Video Communications, Inc). Beta testing involved 3 steps: a 45-minute human-chatbot interaction using the think-aloud method, a 35-minute semistructured interview, and a 10-minute web-based survey. The first 2 steps were recorded, transcribed verbatim, and analyzed using the Unified Theory of Acceptance and Use of Technology. Emerging themes from the qualitative data were mapped on the 4 domains of the Unified Theory of Acceptance and Use of Technology: performance expectancy, effort expectancy, facilitating conditions, and social influence.
RESULTS: Most participants (13/14, 93%) perceived the chatbot to be useful because it provided comprehensive information on HIV testing and PrEP (performance expectancy). All participants indicated that the chatbot was easy to use because of its simple, straightforward design and quick, friendly responses (effort expectancy). Moreover, 93% (13/14) of the participants rated the overall chatbot quality as high, and all participants perceived the chatbot as a helpful tool and would refer it to others. Approximately 79% (11/14) of the participants agreed they would continue using the chatbot. They suggested adding a local language (ie, Bahasa Malaysia) to customize the chatbot to the Malaysian context (facilitating condition) and suggested that the chatbot should also incorporate more information on mental health, HIV risk assessment, and consequences of HIV. In terms of social influence, all participants perceived the chatbot as helpful in avoiding stigma-inducing interactions and thus could increase the frequency of HIV testing and PrEP uptake among MSM.
CONCLUSIONS: The current AI chatbot is feasible and acceptable to promote the uptake of HIV testing and PrEP. To ensure the successful implementation and dissemination of AI chatbots in Malaysia, they should be customized to communicate in Bahasa Malaysia and upgraded to provide other HIV-related information to improve usability, such as mental health support, risk assessment for sexually transmitted infections, AIDS treatment, and the consequences of contracting HIV.