Accepted for/Published in: JMIR Research Protocols
Date Submitted: Apr 27, 2024
Date Accepted: Jul 18, 2024
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Ameliorating Racial Disparities in HIV Prevention: A Nurse-Led, AI-Enhanced Program for PrEP Utilization Among Black Cisgender Women
ABSTRACT
Background:
HIV pre-exposure prophylaxis (PrEP) is a critical biomedical strategy to prevent HIV transmission among cisgender women. Despite its proven effectiveness, Black cisgender women remain significantly underrepresented throughout the PrEP care continuum, facing barriers such as limited access to care, medical mistrust, and intersectional race/HIV stigma. Addressing these disparities is vital to improve HIV prevention outcomes within this community.
Objective:
This study aims to explore the development of a nurse-led, stakeholder-inclusive, and AI-powered program for PrEP utilization among Black cisgender women. The research question focuses on understanding how an AI-powered chatbot, integrated with a nurse-led approach, can enhance PrEP care, encourage adherence, and improve overall HIV prevention efforts within this group.
Methods:
The study employs a mixed-methods design involving semi-structured interviews with key stakeholders, including PrEP-eligible Black women, nurse practitioners (NPs), and a community advisory board (CAB) representing various socioeconomic backgrounds. The AI-powered chatbot is developed using HumanX technology and SmartBot360's HIPAA-compliant framework to ensure data privacy and security. The study spans 18 months and consists of three phases: exploration, development, and evaluation.
Results:
Preliminary groundwork for the project has begun, with IRB protocol submitted and under review. Participant recruitment is underway through a combination of community outreach and snowball sampling. The initial findings suggest a high level of acceptability for the AI-powered chatbot among Black cisgender women, indicating its potential in addressing PrEP disparities.
Conclusions:
The AI-powered chatbot offers a novel approach to improving PrEP care utilization among Black cisgender women, with opportunities to reduce barriers to care and facilitate a stigma-free environment. However, challenges remain regarding health equity and the digital divide, emphasizing the need for culturally competent design and robust data privacy protocols. The implications of this study extend beyond PrEP care, presenting a scalable model that can address broader health disparities. This study is innovative in its combination of nurse-led care and AI technology to address racial disparities in HIV prevention. By engaging stakeholders through a participatory design approach, the study aims to develop a culturally responsive chatbot that integrates biomedical, psychological, and sociocultural factors. The approach's scalability and adaptability have the potential to influence future healthcare interventions, with a vision to expand the model to other marginalized populations. Clinical Trial: n/a
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Copyright
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