Compensation Training and Lifestyle Modifications to promote healthy aging in persons at risk for Alzheimer's disease: a digital application supported intervention

补偿培训和生活方式改变以促进阿尔茨海默病风险人群的健康老龄化：数字应用支持的干预措施

• 批准号: 10324579
• 负责人: MAUREEN SCHMITTER-EDGECOMBE
• 金额: $ 74.44万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-15 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10324579
• 关键词: Activities of Daily Living; Adherence; Adoption; Age; Alzheimer' s Disease; Alzheimer' s disease risk; Behavior; Behavior Therapy; Behavior monitoring; Behavioral; Brain; Calendar; Caregiver Burden; Characteristics; Cognition; Cognitive; Collection; Competence; Control Groups; Data; Data Collection; Development; Disease; Education; Educational Intervention; Educational Materials; Elderly; Encapsulated; Ethnic Origin; Exercise; Exhibits; Feedback; Financial compensation; Future; Goals; Health; Health Care Costs; Health Status; Health behavior; Impaired cognition; Individual; Interdisciplinary Study; Intervention; Interview; Knowledge; Lead; Life Style; Life Style Modification; Machine Learning; Maintenance; Measures; Medical; Memory; Methods; Mission; Monitor; Motivation; Neuronal Plasticity; Neuropsychology; Outcome; Participant; Pattern; Personal Satisfaction; Persons; Physical Function; Physical activity; Pilot Projects; Population Heterogeneity; Prevalence; Public Health; Quality of life; Race; Randomized; Randomized Controlled Trials; Research; Research Design; Self Determination; Socioeconomic Status; Structure; Symptoms; System; Tablets; Technology; Testing; Time; Training; Translations; Treatment Effectiveness; Treatment Efficacy; Treatment outcome; United States National Institutes of Health; Work; aging population; base; brain health; cost; daily functioning; dementia risk; design; digital; disability; efficacy evaluation; evidence base; executive function; follow-up; functional disability; functional independence; health care delivery; health literacy; healthy aging; healthy lifestyle; improved; innovation; insight; instrumental activity of daily living; lifestyle intervention; machine learning algorithm; mild cognitive impairment; modifiable risk; novel; outcome prediction; post intervention; prevent; preventive intervention; primary outcome; racial and ethnic; resilience; secondary outcome; sex; stress management; success; support tools; technology development; theories; therapy development; tool; treatment adherence; treatment responders; uptake; user-friendly

The prevalence of Alzheimer's Disease and other disorders (ADRDs) is now a public health crisis. In the absence of effective medical treatment, there is a critical need for behavioral interventions to prevent or delay symptom onset. Multidomain interventions simultaneously targeting multiple modifiable risks for ADRD have shown promise, but additional innovative approaches that could be highly accessible by capitalizing on user- friendly digital applications to support and strengthen behavior modification are needed. Training in the use of compensatory aids (e.g., calendars and note taking systems) can improve daily independence. These same compensatory tools can be employed to facilitate the adoption of lifestyle changes that support brain health (e.g., exercise, cognitive engagement, stress management) through management of goal-setting, behavioral monitoring, tracking and feedback. The current project will test a 6-month intervention that provides training in both compensatory aids and lifestyle modification. A comprehensive suite of digital tools encapsulated in the Digital Memory Notebook (DMN), an easy to use, interactive application, will be used to facilitate behavioral change and enhance participant motivation. Further, the DMN allows collection of real-time data to track intervention adherence. The DMN has been successfully applied to improving compensation among individuals with mild cognitive impairment. The proposed work capitalizes on a critical window for building resilience by targeting individuals at risk for ADRD due to a subjective cognitive concern (SCC) but who remain cognitively normal. We will conduct a randomized controlled trial (RCT) among ethnoracially diverse older adults with SCC to compare our digital app supported compensation training and lifestyle modification intervention to an education only control group that will not use the DMN or be provided with guidance on how to implement the educational material into their daily lives. Specific aims of the project include: 1) evaluate intervention efficacy on primary outcomes (global cognition and everyday function); secondary outcomes focus on well-being, cognitive domains (memory and executive function), activities of daily living (IADLs), physical function, compensation, and health behaviors; 2) evaluate characteristics of treatment responders; 3) evaluate adherence and identify the effective components of the target intervention using a mixed-method approach; and 4) design machine learning algorithms that use patterns of change in real-time DMN data metrics to identify incipient declines in treatment adherence and changes in health status. The intervention under study is novel because it applies training in compensation to support lifestyle modifications and everyday functioning using a digital app that also monitors adherence to each component of the intervention in real-time. The project is expected to expand understanding of factors that may impact adherence to and outcomes of a preventative intervention leading to optimization of a scalable intervention to reduce dementia risk applicable to diverse populations.

阿尔茨海默病和其他疾病（ADRD）的流行现在是一个公共卫生危机。在 缺乏有效的医疗，迫切需要行为干预，以防止或延迟 症状发作。多领域干预同时针对ADRD的多种可改变风险， 显示出了希望，但更多的创新方法，可以通过利用用户， 需要友好的数字应用程序来支持和加强行为矫正。使用培训 补偿辅助（例如，日历和笔记系统）可以提高日常独立性。这些相同 可以采用补偿工具来促进生活方式的改变，以支持大脑健康 (e.g.,锻炼，认知参与，压力管理）通过管理目标设定，行为 监测、跟踪和反馈。目前的项目将测试一个为期6个月的干预， 在补偿性艾滋病和改变生活方式方面。一套全面的数字化工具， 数字记忆笔记本（DMN）是一个易于使用的交互式应用程序，将用于促进行为 改变和提高参与者的积极性。此外，DMN允许收集实时数据以跟踪 干预依从性。DMN已成功地应用于改善 有轻度认知障碍的人。拟议的工作利用了一个关键的窗口， 通过针对由于主观认知问题（SCC）而存在ADRD风险的个体， 认知正常。我们将在不同种族的老年人中进行一项随机对照试验（RCT）， 患有SCC的成年人比较我们的数字应用程序支持的补偿培训和生活方式改变 对仅接受教育的对照组进行干预，该对照组将不使用DMN或提供以下方面的指导 如何将教材融入到日常生活中。项目的具体目标包括：1） 评价干预对主要结局（总体认知和日常功能）的有效性;次要结局 结果侧重于福祉、认知领域（记忆和执行功能）、日常生活活动 （IADL），身体功能，补偿和健康行为; 2）评估治疗特征 3）评估依从性，并使用 混合方法; 4）设计实时使用变化模式的机器学习算法 DMN数据指标，用于识别治疗依从性的初期下降和健康状况的变化。的 正在研究的干预是新颖的，因为它应用了补偿培训来支持生活方式的改变 以及使用数字应用程序的日常功能，该应用程序还监控对 实时干预。预计该项目将扩大对可能影响的因素的了解 预防性干预的依从性和结果，导致可扩展干预的优化， 降低痴呆症风险适用于不同人群。