PDF(Pubmed)
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 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.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
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.
UNASSIGNED: PRR1-10.2196/59975.
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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.
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.
UNASSIGNED: PRR1-10.2196/59975.
摘要：
背景：HIV暴露前预防（PrEP）是预防顺性女性之间HIV传播的重要生物医学策略。尽管其有效性已被证明，在整个PrEP护理连续过程中，黑人女性的比例仍然严重不足，面临障碍，如获得护理的机会有限，医学上的不信任,以及交叉的种族或艾滋病毒耻辱。解决这些差异对于改善该社区的艾滋病毒预防成果至关重要。另一方面,护士从业人员(NPs)在PrEP利用中起着关键作用，但由于缺乏意识，代表性不足，缺乏人力资源，支持不足。配备人工智能（AI）和先进的大型语言模型的快速发展，聊天机器人有效地促进了医疗交流和与各个领域的医疗联系，包括艾滋病毒预防和PrEP护理。
目的：我们的研究通过自然语言处理算法利用NPs的整体护理能力和AI的力量，提供有针对性的,以患者为中心促进PrEP护理。我们的首要目标是创建一个护士主导的，利益相关者包容性，和人工智能驱动的计划，以促进顺性黑人女性的PrEP利用，最终分三个阶段加强这一弱势群体的艾滋病毒预防工作。该项目旨在缓解健康差距，推进创新，基于技术的解决方案。
方法：该研究使用混合方法设计，涉及与关键利益相关者的半结构化访谈，包括50名符合PrEP资格的黑人女性，10个NP,以及代表各种社会经济背景的社区顾问委员会。AI驱动的聊天机器人使用HumanX技术和SmartBot360的健康保险可移植性和责任法案兼容框架开发，以确保数据隐私和安全。这项研究历时18个月，包括3个阶段：探索，发展,和评价。
结果：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。我们计划在2024年9月开始招募黑人女性和NP，目的是收集信息以了解他们对聊天机器人开发的偏好。虽然机构审查委员会对第二阶段和第三阶段的批准仍在进行中，我们在参与者招募网络方面取得了重大进展。我们计划很快进行数据收集，随着研究的进展，将提供招聘和数据收集进展的进一步更新。
结论：AI驱动的聊天机器人提供了一种新颖的方法来改善黑人女性的PrEP护理利用率，有机会减少护理障碍，并促进无污名化的环境。然而,卫生公平和数字鸿沟方面的挑战仍然存在，强调需要有文化能力的设计和强大的数据隐私协议。这项研究的意义超出了PrEP护理，提出了一个可扩展的模型，可以解决更广泛的健康差距。
■PRR1-10.2196/59975。
目的：我们的研究通过自然语言处理算法利用NPs的整体护理能力和AI的力量，提供有针对性的,以患者为中心促进PrEP护理。我们的首要目标是创建一个护士主导的，利益相关者包容性，和人工智能驱动的计划，以促进顺性黑人女性的PrEP利用，最终分三个阶段加强这一弱势群体的艾滋病毒预防工作。该项目旨在缓解健康差距，推进创新，基于技术的解决方案。
方法：该研究使用混合方法设计，涉及与关键利益相关者的半结构化访谈，包括50名符合PrEP资格的黑人女性，10个NP,以及代表各种社会经济背景的社区顾问委员会。AI驱动的聊天机器人使用HumanX技术和SmartBot360的健康保险可移植性和责任法案兼容框架开发，以确保数据隐私和安全。这项研究历时18个月，包括3个阶段：探索，发展,和评价。
结果：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。我们计划在2024年9月开始招募黑人女性和NP，目的是收集信息以了解他们对聊天机器人开发的偏好。虽然机构审查委员会对第二阶段和第三阶段的批准仍在进行中，我们在参与者招募网络方面取得了重大进展。我们计划很快进行数据收集，随着研究的进展，将提供招聘和数据收集进展的进一步更新。
结论：AI驱动的聊天机器人提供了一种新颖的方法来改善黑人女性的PrEP护理利用率，有机会减少护理障碍，并促进无污名化的环境。然而,卫生公平和数字鸿沟方面的挑战仍然存在，强调需要有文化能力的设计和强大的数据隐私协议。这项研究的意义超出了PrEP护理，提出了一个可扩展的模型，可以解决更广泛的健康差距。
■PRR1-10.2196/59975。
