Validity, feasibility, and effectiveness of a voice‐recognition based digital cognitive screener for dementia and mild cognitive impairment in community‐dwelling older Chinese adults: A large‐scale implementation study

Author:

Zhao Xuhao12,Wen Haoxuan12,Xu Guohai3,Pang Ting12,Zhang Yaping12,He Xindi12,Hu Ruofei3,Yan Ming3,Chen Christopher4,Wu Xifeng12,Xu Xin124

Affiliation:

1. School of Public Health, The Second Affiliated Hospital of School of Medicine Zhejiang University Hangzhou Zhejiang P. R. China

2. Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province Hangzhou Zhejiang P. R. China

3. DAMO Academy, Alibaba Group Hangzhou Zhejiang P. R. China

4. Department of Pharmacology Yong Loo Lin School of Medicine Memory, Ageing, and Cognition Centre (MACC) National University of Singapore Singapore Singapore

Abstract

AbstractINTRODUCTIONWe investigated the validity, feasibility, and effectiveness of a voice recognition‐based digital cognitive screener (DCS), for detecting dementia and mild cognitive impairment (MCI) in a large‐scale community of elderly participants.METHODSEligible participants completed demographic, cognitive, functional assessments and the DCS. Neuropsychological tests were used to assess domain‐specific and global cognition, while the diagnosis of MCI and dementia relied on the Clinical Dementia Rating Scale.RESULTSAmong the 11,186 participants, the DCS showed high completion rates (97.5%) and a short administration time (5.9 min) across gender, age, and education groups. The DCS demonstrated areas under the receiver operating characteristics curve (AUCs) of 0.95 and 0.83 for dementia and MCI detection, respectively, among 328 participants in the validation phase. Furthermore, the DCS resulted in time savings of 16.2% to 36.0% compared to the Mini‐Mental State Examination (MMSE) and Montral Cognitive Assessment (MoCA).DISCUSSIONThis study suggests that the DCS is an effective and efficient tool for dementia and MCI case‐finding in large‐scale cognitive screening.Highlights To our best knowledge, this is the first cognitive screening tool based on voice recognition and utilizing conversational AI that has been assessed in a large population of Chinese community‐dwelling elderly. With the upgrading of a new multimodal understanding model, the DCS can accurately assess participants' responses, including different Chinese dialects, and provide automatic scores. The DCS not only exhibited good discriminant ability in detecting dementia and MCI cases, it also demonstrated a high completion rate and efficient administration regardless of gender, age, and education differences. The DCS is economically efficient, scalable, and had a better screening efficacy compared to the MMSE or MoCA, for wider implementation.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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