Psychometric and diagnostic properties of the Taiwan version of the Quick Mild Cognitive Impairment screen

• Published in: PloS one 2018-12, Vol.13 (12), p.e0207851-e0207851
• Main Authors: Lee, Meng-Ta, Chang, Wan-Ying, Jang, Yuh
• Format: Article
• Language: English
• Subjects: Activities of daily living; Aged; Aged, 80 and over; Aging; Alzheimer's disease; Analysis; Biology and Life Sciences; Clinical medicine; Cognitive ability; Cognitive Dysfunction - diagnosis; Correlation; Correlation coefficient; Correlation coefficients; Cross-Sectional Studies; Dementia; Dementia - diagnosis; Dementia disorders; Diagnosis; Diagnosis, Differential; Diagnostic systems; Elderly; Female; Health aspects; Health screening; Hospitals; Humans; Impairment; Male; Medical diagnosis; Medicine and Health Sciences; Memory; Mental Status and Dementia Tests - statistics & numerical data; Multivariate Analysis; Neurology; Occupational therapy; Older people; People and Places; Predictive Value of Tests; Psychometrics; Psychometrics - statistics & numerical data; Quality of life; Quantitative psychology; Reliability analysis; Reproducibility of Results; Risk factors; ROC Curve; Screening; Social Sciences; Taiwan
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0207851

There is a need for a screening tool with capacities of accurate detection of early mild cognitive impairment (MCI) and dementia and is suitable for use in a range of languages and cultural contexts. This research aims to evaluate the psychometric and diagnostic properties of the Taiwan version of Qmci (Qmci-TW) screen and to explore the discriminating ability of the Qmci-TW in differentiating among normal controls (NCs), MCI and dementia. Thirty-one participants with dementia and 36 with MCI and 35 NCs were recruited from a neurology department of regional hospital in Taiwan. Their results on the Qmci-TW, Taiwanese version of the Montreal Cognitive Assessment (MoCA), and Traditional Chinese version of the Mini-Mental State Examination (MMSE) were compared. For analysis, we used Cronbach's α, intraclass correlation coefficient, Spearman's ρ, Kruskal-Wallis test, receiver operating characteristic curve analysis, and multivariate analysis, as appropriate. The Qmci-TW exhibited satisfactory test-retest reliability, internal consistency, and interrater reliability as well as a strong positive correlation with results from the MoCA and MMSE. The optimal cut-off score on the Qmci-TW for differentiating MCI from NC was ≤ 51.5/100 and dementia from MCI was ≤ 31/100. The MoCA exhibited the highest accuracy in differentiating MCI from NC, followed by the Qmci-TW and then MMSE; whereas, the Qmci-TW and MMSE exhibited the same accuracy in differentiating dementia from MCI, followed by the MoCA. The Qmci-TW may be a useful clinical screening tool for a spectrum of cognitive impairments.