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Evaluating the Usability of an HIV Prevention Artificial Intelligence Chatbot in Malaysia: National Observational
Zhao Ni1,2, Sunyoung Oh1, Rumana Saifi3,4
1School of Nursing, Yale University, 400 West Campus Drive, Orange, CT, 06477-3646, United States, 1 2037373039.
Background:
Malaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in men who have sex with men (MSM). MSM are the most vulnerable population for HIV in Malaysia. In 2022, our team developed a web-based artificial intelligence (AI) chatbot and tested its feasibility and acceptability among MSM in Malaysia to promote HIV testing. To enhance the usability of the AI chatbot, we made it accessible to the public through the website called MYHIV365 and tested it in an observational study.
Objective:
This study aimed to test the usability of an AI chatbot in promoting HIV testing among MSM living in Malaysia.
Methods:
This observational study was conducted from August 2023 to March 2024 among 334 MSM. Participants were recruited through community outreach and social-networking apps using flyers. The interactions between participants and the AI chatbot were documented and retrieved from the chatbot developer's platform. Data were analyzed following a predefined metrics using R software (Posit Software, PBC).
Results:
The AI chatbot interacted with 334 participants, assisting them in receiving free HIV self-testing kits, offering information on HIV, pre-exposure prophylaxis (PrEP), and mental health, and providing details of 220 MSM-friendly clinics, including their addresses, phone numbers, and operating hours. After the study, 393 human-chatbot interactions were documented on the chatbot developer's platform. Most participants (304/334, 91.0%) interacted with the AI chatbot once, 30 (9.0%) engaged 2 or more times at different intervals. Participants' interaction time with the chatbot varied, ranging from 1 to 31 minutes. The AI chatbot properly addressed most participants' questions (362/393, 92.1%) about HIV and PrEP. However, in 31 interactions, participants posed additional questions to the chatbot that were not programmed into the chatbot algorithms, resulting in unanswered interactions.
Conclusions:
The web-based AI chatbot demonstrated high usability in delivering HIV self-testing kits and providing clinical information on HIV testing, PrEP, and mental health services. To enhance its usability in community and clinical settings, the chatbot must offer personalized health information and precise interaction, powered by sophisticated machine learning algorithms. In addition, establishing an effective connection between the AI chatbot and health care systems to eliminate stigma and discrimination toward MSM is crucial for the future implementation of AI chatbots.
Insights
A web-based AI chatbot effectively promoted HIV testing among men who have sex with men (MSM) in Malaysia, providing self-testing kits and health information. Further development is needed for personalized interactions and integration with healthcare systems.
Area of Science:
- Digital Health
- Public Health
- Artificial Intelligence
Background:
- Malaysia faces an HIV epidemic primarily transmitted sexually among men who have sex with men (MSM).
- A web-based AI chatbot was developed to address HIV testing needs in this vulnerable population.
Purpose of the Study:
- To evaluate the usability of an AI chatbot in promoting HIV testing among MSM in Malaysia.
- To assess the chatbot's effectiveness in delivering health information and resources.
Main Methods:
- An observational study involving 334 MSM was conducted from August 2023 to March 2024.
- Participants were recruited via community outreach and social media; chatbot interactions were documented and analyzed.
- Data analysis utilized R software based on predefined metrics.
Main Results:
- The AI chatbot successfully assisted 334 participants, providing HIV self-testing kits, information on HIV and PrEP, and clinic details.
- Over 393 interactions, the chatbot accurately answered 92.1% of questions about HIV and PrEP.
- Some interactions (31) involved questions beyond the chatbot's programmed algorithms, leading to unanswered queries.
Conclusions:
- The AI chatbot demonstrated high usability for delivering HIV self-testing kits and clinical information.
- Enhancements for personalized health information and integration with healthcare systems are recommended for future AI chatbot implementation.
- Addressing stigma and discrimination is crucial for effective AI chatbot deployment in community and clinical settings.
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