School of Nursing, University of Rochester, Rochester, NY, United States.
School of Dentistry and Medicine, University of Rochester, Rochester, NY, United States.
JMIR Res Protoc. 2024 Aug 13;13:e59975. doi: 10.2196/59975.
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 racial or HIV stigma. Addressing these disparities is vital to improving HIV prevention outcomes within this community. On the other hand, nurse practitioners (NPs) play a pivotal role in PrEP utilization but are underrepresented due to a lack of awareness, a lack of human resources, and insufficient support. Equipped with the rapid evolution of artificial intelligence (AI) and advanced large language models, chatbots effectively facilitate health care communication and linkage to care in various domains, including HIV prevention and PrEP care.
Our study harnesses NPs' holistic care capabilities and the power of AI through natural language processing algorithms, providing targeted, patient-centered facilitation for PrEP care. Our overarching goal is to create a nurse-led, stakeholder-inclusive, and AI-powered program to facilitate PrEP utilization among Black cisgender women, ultimately enhancing HIV prevention efforts in this vulnerable group in 3 phases. This project aims to mitigate health disparities and advance innovative, technology-based solutions.
The study uses a mixed methods design involving semistructured interviews with key stakeholders, including 50 PrEP-eligible Black women, 10 NPs, and a community advisory board representing various socioeconomic backgrounds. The AI-powered chatbot is developed using HumanX technology and SmartBot360's Health Insurance Portability and Accountability Act-compliant framework to ensure data privacy and security. The study spans 18 months and consists of 3 phases: exploration, development, and evaluation.
As of May 2024, the institutional review board protocol for phase 1 has been approved. We plan to start recruitment for Black cisgender women and NPs in September 2024, with the aim to collect information to understand their preferences regarding chatbot development. While institutional review board approval for phases 2 and 3 is still in progress, we have made significant strides in networking for participant recruitment. We plan to conduct data collection soon, and further updates on the recruitment and data collection progress will be provided as the study advances.
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.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/59975.
HIV 暴露前预防 (PrEP) 是预防 cisgender 女性 HIV 传播的重要生物医学策略。尽管 PrEP 已被证明有效，但 Black cisgender 女性在整个 PrEP 护理连续体中仍然严重代表性不足，面临着诸如获取护理机会有限、医疗不信任以及交叉的种族或 HIV 污名等障碍。解决这些差异对于改善该社区的 HIV 预防结果至关重要。另一方面，护士从业者 (NPs) 在 PrEP 的利用中发挥着关键作用，但由于缺乏意识、人力资源不足和支持不足，代表性不足。人工智能 (AI) 和先进的大型语言模型的快速发展，使得聊天机器人能够在包括 HIV 预防和 PrEP 护理在内的各个领域有效地促进医疗保健沟通和链接到护理。
我们的研究利用 NPs 的整体护理能力和自然语言处理算法的 AI 力量，为 PrEP 护理提供有针对性、以患者为中心的促进。我们的总体目标是创建一个由护士主导、利益相关者参与和 AI 驱动的计划，以促进 Black cisgender 女性使用 PrEP，最终分三个阶段加强该脆弱群体的 HIV 预防工作。该项目旨在减轻健康差距并推进创新的基于技术的解决方案。
该研究采用混合方法设计，包括与关键利益相关者（包括 50 名符合 PrEP 条件的 Black 女性、10 名 NPs 和代表各种社会经济背景的社区咨询委员会）进行半结构化访谈。使用 HumanX 技术和 SmartBot360 的符合《健康保险流通与责任法案》的框架开发人工智能驱动的聊天机器人，以确保数据隐私和安全。该研究跨越 18 个月，分为三个阶段：探索、开发和评估。
截至 2024 年 5 月，第一阶段的机构审查委员会方案已获得批准。我们计划于 2024 年 9 月开始招募 cisgender 女性和 NPs，旨在收集信息以了解他们对聊天机器人开发的偏好。虽然第二和第三阶段的机构审查委员会批准仍在进行中，但我们在参与者招募方面取得了重大进展。我们计划很快进行数据收集，并在研究进展时提供有关招募和数据收集进展的进一步更新。
人工智能驱动的聊天机器人为提高 Black cisgender 女性的 PrEP 护理利用率提供了一种新方法，有机会减少护理障碍并促进无污名环境。然而，在健康公平和数字鸿沟方面仍然存在挑战，这强调了需要进行文化上有能力的设计和稳健的数据隐私协议。该研究的影响超出了 PrEP 护理范围，提出了一个可扩展的模型，可以解决更广泛的健康差距。
