Abstract

Although computerized cognitive training (CCT) is an effective digital intervention for cognitive impairment, its dose-response relationship is understudied. This retrospective cohort study explores the association between training dose and cognitive improvement to find the optimal CCT dose. From 2017 to 2022, 8,709 participants with subjective cognitive decline, mild cognitive impairment, and mild dementia were analyzed. CCT exposure varied in daily dose and frequency, with cognitive improvement measured weekly using Cognitive Index. A mixed-effects model revealed significant Cognitive Index increases across most dose groups before reaching the optimal dose. For participants under 60 years, the optimal dose was 25 to <30 min per day for 6 days a week. For those 60 years or older, it was 50 to <55 min per day for 6 days a week. These findings highlight a dose-dependent effect in CCT, suggesting age-specific optimal dosing for cognitive improvement.

Details

Title
Dose–response relationship between computerized cognitive training and cognitive improvement
Author
Liu, Liyang 1 ; Wang, Haibo 2   VIAFID ORCID Logo  ; Xing, Yi 1 ; Zhang, Ziheng 3 ; Zhang, Qingge 3 ; Dong, Ming 3 ; Ma, Zhujiang 3 ; Cai, Longjun 3 ; Wang, Xiaoyi 3 ; Tang, Yi 1   VIAFID ORCID Logo 

1  National Center for Neurological Disorders, Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, China (GRID:grid.24696.3f) (ISNI:0000 0004 0369 153X); Neurodegenerative Laboratory of Ministry of Education of the People’s Republic of China, Beijing, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X) 
2  Peking University, Clinical Research Institute, Institute of Advanced Clinical Medicine, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Haidian district, Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, 38 Xueyuan St, Beijing, China (GRID:grid.414252.4) (ISNI:0000 0004 1761 8894) 
3  Beijing Wispirit Technology Co., Ltd., Beijing, China (GRID:grid.419897.a) 
Pages
214
Publication year
2024
Publication date
Dec 2024
Publisher
Nature Publishing Group
e-ISSN
23986352
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41746-024-01210-9
ProQuest document ID
3093311301
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.