Racial Differences in Decision Making among Older Adults

项目概要/摘要 财务和健康事务的决策对于保持独立性和健康至关重要 老年人的幸福感，以及最近对主要是老年白人的研究表明，决策能力恶化 随着年龄的增长。虽然对老年黑人决策的了解很少，但初步 研究表明，不同种族的决策可能存在差异。决策可以被视为 外部影响的情境因素与两个内部系统的复杂相互作用：认知处理 系统和情感处理系统。尽管认知过程中的种族差异已经很明显 据记录，人们对决策其他部分的种族差异知之甚少，而这些可能 对各种老年人产生深远的经济和公共卫生影响。总体目标 这项研究的目的是阐明老年人决策中的种族差异，并确定老年人决策中的种族差异 情境因素、情感因素和驱动它们的神经生物学机制。背景因素，例如 由于所获得的金融和健康素养、社会经济地位 (SES) 以及感知到的歧视，因人而异 种族，在生命历程中经常受到不利的社会和环境经历的影响，并且可能 在种族和决策之间具有重要的中介作用。生命历程的经历也塑造 内部调节的情感过程。由于情感影响时会观察到决策的差异 过程与认知过程相互作用，信任、风险规避和孤独感等情感因素可能会影响认知过程。 对种族决策有重要的调节作用。情境因素和情感因素都有 最近被证明可以影响大脑网络的功能结构，揭示了重要的见解 参与决策的神经系统。遗憾的是，这些发现几乎完全是在 白人；因此，缺乏关于黑人决策的神经关联的知识 人。生命历程中经历的背景和情感因素的种族差异可能会导致 大脑功能系统组织的可变性。然而，尚不清楚如何或是否有任何推定的 功能神经网络架构的差异可能会导致决策中的种族差异。最后， 黑人成年人患阿尔茨海默病（AD）的风险更大。我们最近的工作表明了错误的决定 成为白人成人 AD 的潜在危险因素；然而，尚不清楚是否以及在多大程度上 决策失误是成年黑人患 AD 的一个风险。拟议的研究将利用现有的临床数据 来自参与少数族裔老龄化研究的非痴呆老年黑人和白人 (RF1AG022018)、Rush 临床核心 (P3010161) 以及正在进行的衰老决策研究 （R01AG033678）收集老年黑人的新行为决策和神经影像数据。 了解决策中的种族差异以及驱动这些差异的相关因素将提供 确定潜在可修改干预目标以解决健康差异的关键信息。

PROJECT SUMMARY/ABSTRACT Decision making in financial and health matters is of critical importance for maintaining independence and wellbeing in old age, and recent work in predominately older White adults suggests decision making worsens with age. While there is a paucity of knowledge regarding decision making in older Black adults, preliminary studies suggest there may be differences in decision making by race. Decision making can be viewed as a complex interaction of externally influenced contextual factors with two internal systems: a cognitive processing system and an affective processing system. Although racial differences in cognitive processing have been well documented, little is known about racial differences in other components of decision making, and these could have profound economic and public health consequences for a diverse range of older adults. The overall goal of this study is to elucidate racial differences in decision making among older adults and to identify the contextual factors, affective factors, and neurobiological mechanisms that drive them. Contextual factors, such as acquired financial and health literacy, socioeconomic status (SES), and perceived discrimination, vary by race, are often influenced by adverse social and environmental experiences over the life course, and could have important mediating effects between race and decision making. Life course experiences also shape internally modulated affective processes. Since differences in decision making are observed when affective processes interact with cognitive processes, affective factors such as trust, risk aversion, and loneliness could have important moderating effects on decision making by race. Both contextual and affective factors have recently been shown to impact the functional architecture of brain networks, revealing important insights into the neural systems involved in decision making. Regrettably, these findings have been almost exclusively in White persons; thus there is a dearth of knowledge regarding the neural correlates of decision making in Black persons. Racial differences in contextual and affective factors experienced over the life course may result in variability in the organization of functional brain systems. However, it is unknown how or whether any putative differences in functional neural network architecture may drive racial differences in decision making. Finally, Black adults are at greater risk for Alzheimer's disease (AD). Our recent work has implicated poor decision making as a potential risk factor for AD in White adults; however, it is unknown whether and to what extent poor decision making is a risk for AD in Black adults. The proposed study will leverage existing clinical data from nondemented older Blacks and Whites participating in the Minority Aging Research Study (RF1AG022018), the Rush Clinical Core (P3010161), and an ongoing study of decision making in aging (R01AG033678) to collect new behavioral decision making and neuroimaging data among older Black adults. Knowledge of racial differences in decision making and the associated factors that drive them will provide crucial information for identifying potentially modifiable targets for intervention to address health disparities.