Empowering Dementia Caregivers using a Culturally Relevant Cyber-Human System

在美国，非裔美国人比其他群体更容易被诊断出患有痴呆症。尽管这种情况很普遍，但很少有研究针对使用技术来提高患有痴呆症的非裔美国人及其照顾者的功能。本研究利用一种新颖的方法来开发一种研究模型，该模型促进了非裔美国人社区痴呆症护理的网络-人类系统研究。该项目利用文化基础来探索用户的需求和偏好，以推动技术系统的发展，这些系统可以很容易地被非裔美国人社区采用。此外，这项研究将有助于提高对文化敏感研究方法的认识，以提高对技术在痴呆症中的应用的理解。最终，该项目将成为未来与文化相关的智能和互联健康技术进步的催化剂。该项目的总体目标是开发一个与文化相关的网络-人类系统，通过减少护理人员的负担，提高痴呆症患者以及其他不同人群的护理效率。这种网络-人类系统建模方法利用了来自痴呆症激动发作、自我报告的照顾者反应（例如情绪和感知压力）以及非裔美国人痴呆症社区的独特属性的信息。这些数据用于网络-人类系统来预测无偏见的躁动模型，以便护理人员可以得到最佳的反应，减轻他们的负担，并支持痴呆症患者的功能。本研究的结果将会促进网络人系统在家庭照护中的应用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

African Americans are more frequently diagnosed with dementia than other groups in the United States. Despite the prevalence, there is little research targeting technology use to enhance the functioning of African Americans living with dementia and their caregivers. This study utilizes a novel approach to develop a research model that advances cyber-human systems research on dementia caregiving in the African American community. The project uses a cultural foundation to explore the needs and preferences of users to drive the development of technological systems that can be readily adopted by the African American community. Moreover, this study will contribute to increasing awareness of culturally-sensitive research approaches to improve the understanding of the use of technology in dementia. Ultimately, this project will serve as the catalyst for future technological advances in culturally-relevant smart and connected health.The overarching goal of this project is to develop a culturally-relevant cyber-human system than can improve the effectiveness of caregivers of people with dementia -- and subsequently other diverse populations -- by reducing caregiver burden. This cyber-human system modeling approach utilizes information from dementia agitation episodes, self-reported caregiver response (e.g., mood and perceived stress), as well as unique attributes of the African American community with dementia. These data are used in a cyber-human system to predict unbiased agitation models so that caregivers and can be primed with an optimal response that reduces their burden and supports the functioning of the person with dementia. The results of this study will enhance the use of cyber-human systems for family caregiving.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.