Development and Validation of Cognitive Status Assessments in Older Adults Utilizing Conversational Agent Technology (CAT) Delivered on Smart Displays - the CAUCAT Study

利用智能显示器上提供的会话代理技术 (CAT) 开发和验证老年人认知状态评估 - CAUCAT 研究

• 批准号: 10383284
• 负责人: Randall Williams
• 金额: $ 49.89万
• 依托单位: WELLSAID.AI, LLC
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-15 至 2024-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10383284
• 关键词: Acute; Address; Administrator; Affect; Age; Alzheimer' s Disease; Alzheimer' s disease related dementia; Artificial Intelligence; Assessment tool; COVID-19; Caregivers; Cellular Phone; Clinical; Cognitive; Companions; Computer Literacy; Consumption; Data; Dementia; Dependence; Detection; Development; Device or Instrument Development; Devices; Diagnosis; Early Diagnosis; Elderly; Emotional; Environment; Exhibits; Feedback; Future; Health Insurance Portability and Accountability Act; Home; Impaired cognition; Impairment; Individual; Link; Methods; Monitor; National Institute on Aging; Needs Assessment; Paper; Patient Recruitments; Patients; Persons; Phase; Physicians; Population; Property; Provider; Psychometrics; Public Health; Reporting; Review Literature; Risk; Sampling; Screening procedure; Secure; Small Business Innovation Research Grant; Societies; Techniques; Technology; Technology Assessment; Testing; Time; Training; United States National Institutes of Health; Validation; Voice; Work; aging in place; analog; base; clinical care; cognitive function; cognitive testing; cohort; commercialization; computerized; experience; financial incentive; informant; instrument; machine learning algorithm; mild cognitive impairment; novel; programs; prospective; recruit; response; screening; screening guidelines; skills; smartphone Application; social; statistics; technology training; usability; validation studies

PROJECT SUMMARY: Mild Cognitive Impairment (MCI), as well as Alzheimer’s Dementia and Related Dementias (ADRD) remain woefully under diagnosed. This is despite the availability of numerous scientifically validated screening instruments and recent financial incentives to physicians. This “evidence-practice” gap is at least in large part because available screening techniques are cumbersome to administer, expensive or too time consuming for regular use in daily clinical care. Additionally, current instruments often require trained docent administration, and/or caregiver confirmation, and typically are administered in the artificial clinical setting rather than monitored in the setting where impairment affects daily living, introducing potential recall bias. Conversely, attempts to digitize assessments typically are not form and function optimized for the target demographic, requiring additional computer literacy and skills or extensive user technology training, and limiting user acceptance. We have developed and demonstrated the potential utility of conversational agent technology (CAT) delivered on smart speakers and smart displays for serially monitoring the cognitive and daily living status of older adults in the home. Preliminary data on 760 older adults (age 60-95) suggests the ability to deploy cognitive screening tools enabled by voice and screen administration, without the potential limitations of unfamiliar technology interfaces or dependency on a clinical administrator, all in the comfort of the subject’s living environment. A companion smart phone app allows caregiver assessment where needed. Following literature review and expert panel input, we have determined that cognitive assessment tests from the well- validated NIH Toolbox Cognitive Battery (NIHTCB) are the best target for adaptation and potential broad scale clinical and commercial use. The present study has two objectives: 1) Create an in-home conversational agent administered comprehensive cognitive assessment platform utilizing assessment tests from the NIHTCB; and 2) Define the psychometric properties of CAT adapted cognitive assessments and compare them to standard assessments. In our Stage 1A study, the specific aim is proving feasibility and usability in a cohort of 30 patients recruited from our current commercial user base. Upon satisfactory evidence of technology viability, we will undertake a Stage 1B study with the specific aim of defining the psychometric properties of the adapted cognitive assessment instruments in 100 patient-caregiver dyads. CAT administered assessments will be evaluated for concurrent criterion validity compared to current standard assessments. We hypothesize Intraclass Correlation Coefficient (ICC) >0.9 compared to current standard assessments. Intra-rater reliability will be assessed with test-retest methods and we hypothesize r >0.8. Results from this study will inform a Phase II project assessing the clinical utility of longitudinal assessments and machine learning algorithms as predictors of the trajectory of cognitive decline. 1

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