Accepted for/Published in: JMIR Human Factors
Date Submitted: Aug 21, 2023
Date Accepted: Dec 12, 2023
Testing the feasibility and acceptability of using an artificial intelligence chatbot to promote HIV testing and pre-exposure prophylaxis in Malaysia: a mixed-methods study
ABSTRACT
Background:
The HIV epidemic continues to grow fastest among men who have sex with men (MSM) in Malaysia in the presence of stigma and discrimination. Reaching MSM online using chatbots supported through artificial intelligence (AI) can potentially help HIV prevention efforts. We previously identified the benefits, limitations, and preferred features of HIV prevention AI chatbots and developed an AI chatbot prototype which is now tested for feasibility and acceptability.
Objective:
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 via Zoom. Beta testing involved three steps: 1) a 45-minute human-chatbot interaction using the think-aloud method, 2) a 35-minute semi-structured interview, and 3) a 10-minute online survey. The first two steps were recorded, transcribed verbatim, and analyzed using the Unified Theory of Acceptance and Use of Technology (UTAUT); emerging themes from the qualitative data were mapped on the four domains of the UTAUT: performance expectancy, effort expectancy, facilitating conditions, and social influence.
Results:
Most participants (13/14, 93%) perceived the chatbot useful as 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). Thirteen (93%) participants rated the overall chatbot quality as high, and all participants perceived the chatbot as a helpful tool, and they would refer it to others. Eleven (78.6%) participants agreed they would continue using the chatbot. They suggested adding a local language (i.e., 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. Clinical Trial: N/A
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