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居民将构成