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) 的流行现已成为一场公共卫生危机。在 由于缺乏有效的医疗治疗，迫切需要行为干预来预防或延迟 症状发作。同时针对 ADRD 的多种可改变风险的多领域干预措施 表现出了希望，但通过利用用户可以轻松获得其他创新方法 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 补偿性辅助工具（例如日历和笔记系统）可以提高日常独立性。这些相同的 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 （例如，锻炼、认知参与、压力管理）通过目标设定、行为管理 监控、跟踪和反馈。当前项目将测试为期 6 个月的干预措施，提供培训 在补偿性辅助和生活方式改变方面。封装在其中的一套全面的数字工具 数字记忆笔记本（DMN）是一种易于使用的交互式应用程序，将用于促进行为 改变并增强参与者的积极性。此外，DMN 允许收集实时数据来跟踪 干预依从性。 DMN 已成功应用于改善薪酬 患有轻度认知障碍的人。拟议的工作利用了建设的关键窗口 通过针对因主观认知问题 (SCC) 而处于 ADRD 风险但仍然存在的个人来恢复弹性 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 的成年人可以比较我们的数字应用程序支持的补偿训练和生活方式改变 对不使用 DMN 或不接受指导的仅教育对照组进行干预 如何将教育材料应用到他们的日常生活中。该项目的具体目标包括：1) 评估主要结局（整体认知和日常功能）的干预效果；中学 结果侧重于幸福感、认知领域（记忆和执行功能）、日常生活活动 (IADL)、身体机能、补偿和健康行为； 2) 评估治疗特征 响应者； 3) 使用以下方法评估依从性并确定目标干预措施的有效组成部分 混合方法； 4）设计使用实时变化模式的机器学习算法 DMN 数据指标可识别治疗依从性的初期下降和健康状况的变化。这 正在研究的干预措施是新颖的，因为它应用补偿培训来支持生活方式的改变 使用数字应用程序进行日常运作，该应用程序还可以监控对每个组件的遵守情况 实时干预。该项目预计将扩大对可能影响的因素的了解 预防性干预的坚持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。