Expanding Access to Care for Marginalized Caregivers through Innovative Methods for Multicultural and Multilingual Adaptation of AI-Based Health Technologies

通过基于人工智能的医疗技术的多文化和多语言适应创新方法，扩大边缘化护理人员获得护理的机会

• 批准号: 10741177
• 负责人: Magaly Ramirez
• 金额: $ 41.61万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-04 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10741177
• 关键词: Address; Adoption; Adult; Affect; Anxiety; Artificial Intelligence; Asthma; Attention; Caregiver Burden; Caregivers; Caring; Child; Child Care; Chronic; Clinical; Clinical Trials; Communication; Communities; Data; Data Analyses; Data Collection; Dementia caregivers; Development; Disparate; Ethnic Population; Event; Evidence based intervention; Family; Family Caregiver; Feeling; Financial Hardship; Foundations; Future; Health; Health Promotion; Health Services Accessibility; Health Technology; Healthcare; Hybrids; Inequity; Intention; Intervention; Interview; Label; Language; Latino; Latino Population; Linguistics; Literature; Machine Learning; Mental Depression; Methods; Minority Groups; Modeling; Monitor; Morbidity - disease rate; Multilingualism; Natural Language Processing; Nature; Not Hispanic or Latino; Nurses; Outcome; Parents; Positioning Attribute; Prevention; Program Appropriateness; Provider; Psyche structure; Reporting; Research; Research Priority; Resources; Risk; Self Management; Services; Side; Supportive care; Symptoms; System; Technology; Testing; Text; Training; Translations; Treatment Efficacy; United States; Work; Writing; archived data; autism spectrum disorder; burden of illness; care burden; care giving burden; care providers; care systems; caregiving; chatbot; community organizations; cost effective; cost efficient; design; digital health; efficacy clinical trial; evidence base; experience; family management; family support; handheld mobile device; health care service; health equity; human centered design; improved; innovation; intervention refinement; machine translation; marginalization; marginalized community; marginalized population; member; mobile application; mortality; novel; online delivery; pilot test; pilot trial; problem solving therapy; programs; prototype; racial population; recruit; skill acquisition; skills; social health determinants; technological innovation; tool

Project Summary and Relevance Care for children with chronic conditions impacts 10 million family caregivers, who provide an estimated $100 billion in unpaid care services in the U.S. annually. This is a significant burden for caregivers physically, mentally, and financially. The burden of care is particularly prevalent among Latino communities, the largest and fastest-growing minority population in the U.S. Despite the overwhelming and disproportionate need, the use of supportive healthcare services is lower among Latino caregivers due to barriers including the lack of accessible and culturally and linguistically appropriate programs. Those, if available, could reduce the multifaceted caregiving burden, and improve the overall health of the caregiver and child. Language translations and cultural adaptations have been resource-intensive, and recent technological advancements in machine learning and AI have the potential to automate labor-intensive work. However, machine translations, if used without careful intention, also may exacerbate biases and existing inequities for marginalized groups. This proposal will culturally and linguistically adapt, develop, and pilot test an innovative, accessible, and cost-effective artificial intelligence (AI)-based intervention currently available for English-speaking caregivers of children with chronic health conditions - “Caring of Caregivers Online” (COCO) - for Latino family caregivers in Spanish. COCO is an innovative mobile application with an embedded chatbot leveraging cutting-edge technologies to deliver evidence-based interventions that were previously limited in terms of their ability to reach caregivers due to resource-intensive requirements both on the caregiver side and provider side. Our preliminary work, in tandem with evidence from the research literature about specific intervention components COCO delivers (e.g., daily wellness check-in, symptom self-monitoring, and problem-solving therapy), point to COCO's potential as a high-impact and scalable tool for expanding access to care. The development of an accessible, and culturally and linguistically appropriate intervention has the potential to improve the health outcomes of Latino family caregivers caring for children with chronic conditions, as well as establish long-term self-management and caregiving skills. Results from this study will guide future intervention refinement, inform assessment and recruitment strategies, and provide preliminary efficacy for the design of a full-scale clinical trial. Latino COCO is an accessible and scalable intervention that addresses a critical clinical gap in supporting family caregivers in marginalized communities. Through adapting COCO, we will develop novel multicultural and multilingual methods that can be transferable and have the potential to be applied in adapting other dialog-based health interventions for use among other culturally and linguistically marginalized populations in a scalable and cost-efficient manner.

项目摘要和相关性 对患有慢性疾病的儿童的护理会影响1000万家庭护理人员，他们提供约1000亿美元 每年在美国无偿护理服务。对于护理人员在身体，精神和财务上来说，这是一次重大的燃烧。 在拉丁裔社区中，护理的燃烧尤其普遍，这是最大，增长最快的少数民族 尽管有压倒性和不成比例的需求，但在美国的人口，使用支持的医疗服务是 由于障碍，包括缺乏可访问和文化和语言的障碍，在拉丁裔护理人员中较低 程序。如果有的话，这些可以减少多方面的护理燃烧，并改善 照料者和孩子。语言翻译和文化改编已经是资源密集的，最近的技术 机器学习和AI的进步有可能自动化实验室密集型工作。但是，机器 如果不仔细意图使用翻译，也可能会加剧边缘化群体的偏见和现有的不平等现象。 该建议将在文化和语言上适应，开发和试点测试一种创新，易于访问和成本效益的 人工智能（AI）的干预措施目前可用于慢性儿童的英语护理人员 健康状况 - “在线照顾者”（可可） - 西班牙语的拉丁裔家庭护理人员。可可是一个 具有嵌入式聊天机器人的创新移动应用程序，利用尖端技术来提供基于证据的技术 由于资源密集型而导致的干预措施以前限制了其接触护理人员 护理人员方和提供商方的要求。我们的初步工作，与 有关特定干预组件可可递送的研究文献（例如，每日健康签到，症状 自我监控和解决问题的疗法）指出可可的潜力是一种高影响力和可扩展工具 扩大访问护理的机会。 在文化上和语言上适当的干预措施的发展有可能改善 拉丁裔家庭护理人员照顾患有慢性疾病的儿童的健康状况，并建立长期 自我管理和护理技能。这项研究的结果将指导将来的干预精致，告知 评估和招聘策略，并为全面临床试验的设计提供初步效率。拉丁裔 可可是一种易于访问且可扩展的干预措施，可以解决支持家庭护理人员的关键临床差距 边缘化社区。通过适应可可，我们将开发新颖的多元文化和多语言方法 可以转移并有可能应用于调整基于对话的其他健康干预措施的使用 在其他文化和语言上以可扩展和成本效益的方式进行边缘化的人群。