Potential application of conversational agents in HIV testing uptake among high-risk populations

Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review

OBJECTIVES

To identify studies promoting the use of artificial intelligence (AI) or automation with HIV preexposure prophylaxis (PrEP) care and explore ways for AI to be used in PrEP interventions.

DESIGN

Systematic review.

METHODS

We searched in the US Centers for Disease Control and Prevention Research Synthesis database through November 2023; PROSPERO (CRD42023458870). We included studies published in English that reported using AI or automation in PrEP interventions. Two reviewers independently reviewed the full text and extracted data by using standard forms. Risk of bias was assessed using either the revised Cochrane risk-of-bias tool for randomized trials for randomized controlled trials or an adapted Newcastle-Ottawa Quality Assessment Scale for nonrandomized studies.

RESULTS

Our search identified 12 intervention studies (i.e., interventions that used AI/automation to improve PrEP care). Currently available intervention studies showed AI/automation interventions were acceptable and feasible in PrEP care while improving PrEP-related outcomes (i.e., knowledge, uptake, adherence, discussion with care providers). These interventions have used AI/automation to reduce workload (e.g., directly observed therapy) and helped non-HIV specialists prescribe PrEP with AI-generated clinical decision-support. Automated tools can also be developed with limited budget and staff experience.

CONCLUSIONS

AI and automation have high potential to improve PrEP care. Despite limitations of included studies (e.g., the small sample sizes and lack of rigorous study design), our review suggests that by using aspects of AI and automation appropriately and wisely, these technologies may accelerate PrEP use and reduce HIV infection.

Testing the Feasibility and Acceptability of Using an Artificial Intelligence Chatbot to Promote HIV Testing and Pre-Exposure Prophylaxis in Malaysia: Mixed Methods Study

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. Engaging MSM on the internet 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 that is now tested for feasibility and acceptability.

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.

Chatbots for HIV Prevention and Care: a Narrative Review

PURPOSE OF REVIEW

To explore the intersection of chatbots and HIV prevention and care. Current applications of chatbots in HIV services, the challenges faced, recent advancements, and future research directions are presented and discussed.

RECENT FINDINGS

Chatbots facilitate sensitive discussions about HIV thereby promoting prevention and care strategies. Trustworthiness and accuracy of information were identified as primary factors influencing user engagement with chatbots. Additionally, the integration of AI-driven models that process and generate human-like text into chatbots poses both breakthroughs and challenges in terms of privacy, bias, resources, and ethical issues. Chatbots in HIV prevention and care show potential; however, significant work remains in addressing associated ethical and practical concerns. The integration of large language models into chatbots is a promising future direction for their effective deployment in HIV services. Encouraging future research, collaboration among stakeholders, and bold innovative thinking will be pivotal in harnessing the full potential of chatbot interventions.

Chatbots to Improve Sexual and Reproductive Health: Realist Synthesis

BACKGROUND

Digital technologies may improve sexual and reproductive health (SRH) across diverse settings. Chatbots are computer programs designed to simulate human conversation, and there is a growing interest in the potential for chatbots to provide responsive and accurate information, counseling, linkages to products and services, or a companion on an SRH journey.

OBJECTIVE

This review aimed to identify assumptions about the value of chatbots for SRH and collate the evidence to support them.

METHODS

We used a realist approach that starts with an initial program theory and generates causal explanations in the form of context, mechanism, and outcome configurations to test and develop that theory. We generated our program theory, drawing on the expertise of the research team, and then searched the literature to add depth and develop this theory with evidence.

RESULTS

The evidence supports our program theory, which suggests that chatbots are a promising intervention for SRH information and service delivery. This is because chatbots offer anonymous and nonjudgmental interactions that encourage disclosure of personal information, provide complex information in a responsive and conversational tone that increases understanding, link to SRH conversations within web-based and offline social networks, provide immediate support or service provision 24/7 by automating some tasks, and provide the potential to develop long-term relationships with users who return over time. However, chatbots may be less valuable where people find any conversation about SRH (even with a chatbot) stigmatizing, for those who lack confidential access to digital devices, where conversations do not feel natural, and where chatbots are developed as stand-alone interventions without reference to service contexts.

CONCLUSIONS

Chatbots in SRH could be developed further to automate simple tasks and support service delivery. They should prioritize achieving an authentic conversational tone, which could be developed to facilitate content sharing in social networks, should support long-term relationship building with their users, and should be integrated into wider service networks.

Differences in HIV testing among sexual orientation subgroups in the United States: A national cross-sectional study

Understanding differences in HIV testing among US adults is a crucial step for HIV prevention. This study used cross-sectional data to assess whether HIV testing varies across sexual orientation subgroups and by important psychosocial factors. Data were from the National Epidemiological Survey on Alcohol and Related Conditions-III (NESARC-III; n = 36 309, response rate = 60.1%), a nationally representative survey of the US non-institutionalized adult population. Using logistic regression, we examined HIV testing among heterosexual concordant, heterosexual discordant, gay/lesbian, and bisexual adults. Psychosocial correlates included adverse childhood experiences (ACEs), discrimination, educational attainment, social support, and substance use disorders (SUDs). Bisexual (77.0%) and gay/lesbian (65.4%) women had a greater prevalence of HIV testing than concordant heterosexual women (51.6%), and bisexual women had a significantly higher testing prevalence than discordant heterosexual women (54.8%). Gay (84.0%) and bisexual (72.1%) men also had a significantly higher testing prevalence than discordant (48.2%) and concordant (49.4%) heterosexual men. In multivariable models, bisexual men and women (AOR = 1.8; 95% CI = 1.3-2.4) and gay men (AOR = 4.7; 95% CI = 3.2-7.1) had significantly greater odds of HIV testing than heterosexual concordant adults. A higher number of ACEs, greater social support, history of SUDs, and higher educational attainment were positively associated with HIV testing. HIV testing prevalence varied across sexual orientation subgroups; discordant heterosexual men had the lowest prevalence. Health care providers should consider a person's sexual orientation, ACEs, educational attainment, social support, and history of SUDs when evaluating HIV testing needs in the US.

Increasing Participation in a TelePrEP Program for Sexual and Gender Minority Adolescents and Young Adults in Louisiana: Protocol for an SMS Text Messaging-Based Chatbot

BACKGROUND

Sexual and gender minority (SGM) adolescents and young adults (AYAs) are at increased risk of HIV infection, particularly in the Southern United States. Despite the availability of effective biomedical prevention strategies, such as pre-exposure prophylaxis (PrEP), access and uptake remain low among SGM AYAs. In response, the Louisiana Department of Health initiated the LA TelePrEP Program, which leverages the power of telemedicine to connect Louisiana residents to PrEP. A virtual TelePrEP Navigator guides users through the enrollment process, answers questions, schedules appointments, and facilitates lab testing and medication delivery. To increase the participation of SGM AYAs in the program, the TelePrEP program partnered with researchers to develop a chatbot that would facilitate access to the program and support navigator functions. Chatbots are capable of carrying out many functions that reduce employee workload, and despite their successful use in health care and public health, they are relatively new to HIV prevention.

OBJECTIVE

In this paper, we describe the iterative and community-engaged process that we used to develop an SMS text messaging-based chatbot tailored to SGM AYAs that would support navigator functions and disseminate PrEP-related information.

METHODS

Our process was comprised of 2 phases: conceptualization and development. In the conceptualization phase, aspects of navigator responsibilities, program logistics, and user interactions to prioritize in chatbot programming (eg, scheduling appointments and answering questions) were identified. We also selected a commercially available chatbot platform that could execute these functions and could be programmed with minimal coding experience. In the development phase, we engaged Department of Health staff and SGM AYAs within our professional and personal networks. Five different rounds of testing were conducted with various groups to evaluate each iteration of the chatbot. After each iteration of the testing process, the research team met to discuss feedback, guide the programmer on incorporating modifications, and re-evaluate the chatbot's functionality.

RESULTS

Through our highly collaborative and community-engaged process, a rule-based chatbot with artificial intelligence components was successfully created. We gained important knowledge that could advance future chatbot development efforts for HIV prevention. Key to the PrEPBot's success was resolving issues that hampered the user experience, like asking unnecessary questions, responding too quickly, and misunderstanding user input.

CONCLUSIONS

HIV prevention researchers can feasibly and efficiently program a rule-based chatbot with the assistance of commercially available tools. Our iterative process of engaging researchers, program personnel, and different subgroups of SGM AYAs to obtain input was key to successful chatbot development. If the results of this pilot trial show that the chatbot is feasible and acceptable to SGM AYAs, future HIV researchers and practitioners could consider incorporating chatbots as part of their programs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/42983.

Potential Role of Conversational Agents in Encouraging PrEP Uptake

Approximately 1.2 million people are living with HIV, with many of them unaware of their infection. Pre-exposure prophylaxis (PrEP) is available to minimize transmission among those at high risk for infection, including men who have sex with men, people who inject drugs, and female sex workers. Despite its availability, there is low usage of PrEP. To address this problem, various digital tools have been examined in HIV research. Among those, conversational agents are still underused and their capacity warrants examination to reach at-risk populations. In this paper, we discuss the potential of conversational agents in increasing uptake of PrEP by addressing barriers experienced among those at high risk for infection.