At-home computerized assessment of normal cognitive aging and age-related cognitive decline in older African Americans, Hispanics, and rural non-Hispanic whites

对老年非裔美国人、西班牙裔和农村非西班牙裔白人的正常认知衰老和与年龄相关的认知衰退进行家庭计算机化评估

• 批准号: 10606447
• 负责人: Peter Pebler
• 金额: $ 49.71万
• 依托单位: NEUROBEHAVIORAL SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10606447
• 关键词: Address; Adult; Affect; African American; African American population; Age; Age-associated memory impairment; Alzheimer' s Disease; American; Benchmarking; Black American; Black race; COVID-19; California; Clinical Trials; Cognition; Cognitive; Cognitive aging; Consensus; Country; Data; Data Set; Dementia; Diagnosis; Diagnostic; Diagnostic and Statistical Manual of Mental Disorders; Disease; Disease Progression; Domiciles; Education; Elderly; Enrollment; Ensure; Ethnic Origin; Factor Analysis; Future; Gender; Genetic Transcription; Healthcare; Hispanic; Hispanic Americans; Hispanic Populations; Home; Impaired cognition; Individual; International; Interruption; Language; Language Tests; Learning; Manuals; Materials Testing; Measures; Medical; Methodology; Minority; Minority Access; Minority Groups; Modernization; National Institute on Aging; Neighborhoods; Neuropsychology; Not Hispanic or Latino; Participant; Patients; Pattern; Performance; Phase; Population; Population Heterogeneity; Psychometrics; Quality of Care; Questionnaires; Research; Risk; Rural; Rural Community; Sampling; Small Business Innovation Research Grant; South Texas; Speech; Statistical Methods; Statutes and Laws; Technology; Testing; Text; Training; Translations; Transportation; Underserved Population; United States; Voice; automated speech recognition; base; care burden; clinical development; cognitive function; cognitive testing; cohort; comparison group; computerized; cost; design; digital; ethnoracial minority; health disparity; hispanic community; improved; indexing; innovation; minority communities; neglect; novel therapeutics; peer; performance tests; racial and ethnic; racial and ethnic disparities; recruit; research study; response; rural dwellers; sex; suburb; symposium; testing access; theories; underserved community

Although by 2060 African Americans, Hispanics, and residents of rural communities will constitute the majority of US patients with Alzheimer’s disease (AD), these populations have long been neglected in AD research studies and clinical trials. In this large scale fast-track SBIR application, we propose to gather normative longitudinal California Cognitive Assessment Battery (CCAB) data from 300 healthy older (ages 60 to 89) individuals in each of four underserved populations: (1) African Americans: (2) English-speaking US Hispanics; (2) Spanish-speaking US Hispanics; and (4) non-Hispanic white (nHW) residents of rural communities. Participants will be recruited in California and South Texas. We will compare the results from each group with existing normative data from a primarily suburban white population. The CCAB includes 34 innovative computerized cognitive tests and questionnaires that utilize cellphone networks to enable telemedical testing in patients’ homes. CCAB test introductions and test materials are delivered with AI-enhanced text-to-speech voices and verbal responses are analyzed with consensus automatic speech recognition (CASR) with unexcelled transcription accuracy. Recruitment is facilitated and testing throughput is increased because CCAB tests are administered in participants’ homes. The CCAB has been designed to facilitate translation into other languages. Here, we will test Spanish-speaking US residents with CCAB-Español, a Spanish version of the CCAB optimized for US Spanish dialects. During Phase I, we will recruit African American and Hispanic examiners, assure that the Spanish translation of the CCAB is adapted for the US Hispanic population, and begin testing. During Phase II we will continue enrollment testing and thereafter test participants at one-year intervals to gather longitudinal norms and identify performance patterns that predict subsequent cognitive decline. Ethnoracial norms for each CCAB test will be developed using traditional analysis and supplemented with Item response theory factor analysis to improve scoring sensitivity and eliminate score bias. The acquisition of normative CCAB data will lower access barriers to neuropsychological assessment among ethnoracial minorities for six reasons: (1) At-home CCAB Testing will not be interrupted by COVID-19 lockdowns; (2) At-home CCAB testing minimizes mobility and transportation challenges; (3) CCAB-Español will address the lack of well-normed, scalable Spanish-language tests for the US Hispanic population and facilitate access to Spanish-speaking examiners; (4) CCAB telemedical testing will provide access to cognitive assessments in neglected urban and rural neighborhoods; (5) CCAB testing can reduce cost barriers to cognitive assessment by more than 70%; (6) The CCAB will reduce cultural barriers to research participation by testing participants in their familiar home surroundings and by using ethnoracially sensitive African American and Hispanic examiners.

尽管到2060年，非洲裔美国人、西班牙裔美国人和农村社区的居民将构成美国的人口， 大多数美国阿尔茨海默病（AD）患者，这些人群在AD中长期被忽视 研究和临床试验。在这个大规模的快速SBIR应用中，我们建议收集 来自300名健康老年人（年龄60岁）的规范性纵向加州认知评估成套测验（CCAB）数据 四个服务不足人群中的每一个人：（1）非洲裔美国人;（2）讲英语的美国人 西班牙裔;（2）讲西班牙语的美国西班牙裔;和（4）农村的非西班牙裔白色（nHW）居民 社区.参与者将在加州和南德克萨斯州招募。我们将比较 每个组都有来自主要是郊区白色人群的现有标准数据。 CCAB包括34项创新的计算机化认知测试和问卷， 网络，使远程医疗测试在病人的家中。CCAB测试介绍和测试材料 通过人工智能增强的文本到语音的语音和口头回应进行分析， 自动语音识别（CASR），具有无与伦比的转录准确性。促进了征聘工作， 因为CCAB测试是在参与者的家中进行的，所以测试吞吐量增加。CCAB已 旨在方便翻译成其他语言。在这里，我们将测试说西班牙语的美国居民 CCAB-Español是针对美国西班牙语方言优化的CCAB西班牙语版本。 在第一阶段，我们将招募非洲裔美国人和西班牙裔考官，确保西班牙人 CCAB的翻译适用于美国西班牙裔人群，并开始测试。在第二阶段，我们将 继续进行登记测试，然后每隔一年对参与者进行测试，以收集纵向规范 并确定预测随后认知能力下降的表现模式。每个CCAB的种族规范 本测验将采用传统的分析方法，并辅以项目反应理论的因素分析， 提高评分灵敏度和消除评分偏差。获得规范的CCAB数据将降低获得 少数民族神经心理学评估的障碍有六个原因：（1）在家CCAB 测试不会因COVID-19封锁而中断;（2）在家CCAB测试最大限度地减少了流动性， 交通挑战;（3）CCAB-Español将解决缺乏规范，可扩展的西班牙语 为美国西班牙裔人口提供测试，并方便使用西班牙语考官;（4）CCAB 远程医疗测试将为被忽视的城市和农村社区提供认知评估; (5)CCAB测试可以将认知评估的成本障碍降低70%以上;（6）CCAB将 通过在参与者熟悉的家庭环境中进行测试，减少参与研究的文化障碍， 通过使用种族敏感的非裔美国人和西班牙裔考官。