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Development of a computerized tool for the chinese version of the montreal cognitive assessment for screening mild cognitive impairment

Published online by Cambridge University Press:  03 November 2014


Ke Yu
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Shangang Zhang
Affiliation:
Department of Rehabilitation, Wuhan General Hospital of Guangzhou Military Command, Wuhan 430070, Hubei, China
Qingsong Wang
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Xiaofei Wang
Affiliation:
Computer Networking Center, Chengdu Military General Hospital, Chengdu 610083, Sichuan, China
Yang Qin
Affiliation:
Department of Geriatrics, Chengdu Military General Hospital, Chengdu 610083, Sichuan, China
Jian Wang
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Congyang Li
Affiliation:
Department of Psychiatry, Chengdu Military General Hospital, Chengdu 610083, Sichuan, China
Yuxian Wu
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Weiwen Wang
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Hang Lin
Affiliation:
Department of Neurology, Chengdu Military General Hospital, No270, Rongdu Avenue, Jinniu District, Chengdu 610083, Sichuan, China
Corresponding
E-mail address:

Abstract

Background:

The Montreal Cognitive Assessment (MoCA) is used for screening mild cognitive impairment (MCI), and the Beijing version (MoCA-BJ) is widely used in China. We aimed to develop a computerized tool for MoCA-BJ (MoCA-CC).

Methods:

MoCA-CC used person-machine interaction instead of patient-to-physician interaction; other aspects such as the scoring system did not differ from the original test. MoCA-CC, MoCA-BJ and routine neuropsychological tests were administered to 181 elderly participants (MCI = 96, normal controls [NC] = 85).

Results:

A total of 176 (97.24%) participants were evaluated successfully by MoCA-CC. Cronbach's α for MoCA-CC was 0.72. The test–retest reliability (retesting after six weeks) was good (intraclass correlation coefficient = 0.82; P < 0.001). Significant differences were observed in total scores (t = 9.38, P < 0.001) and individual item scores (t = 2.18–8.62, P < 0.05) between the NC and MCI groups, except for the score for “Naming” (t = 0.24, P = 0.81). The MoCA-CC total scores were highly correlated with the MoCA-BJ total scores (r = 0.93, P < 0.001) in the MCI participants. The area under receiver–operator curve for the prediction of MCI was 0.97 (95% confidence interval = 0.95–1.00). At the optimal cut-off score of 25/26, MoCA-CC demonstrated 95.8% sensitivity and 87.1% specificity.

Conclusion:

The MoCA-CC tool developed here has several advantages over the paper-pencil method and is reliable for screening MCI in elderly Chinese individuals, especially in the primary clinical setting. It needs to be validated in other diverse and larger populations.


Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2014 

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