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Updated: Sep 26, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Reliability and Validity of the Traditional Chinese Version of the Mild Behavioral Impairment - Checklist Among
Rose Sy Lin1, Doris Sf Yu1, Pui H Chau1
1School of Nursing, Li Ka Shing Faculty of Medicine, 71020University of Hong Kong, Hong Kong.
Objective:
To evaluate the reliability and validity of the traditional Chinese version of the Mild Behavioral Impairment Checklist (MBI-C) among Hong Kong Chinese with mild cognitive impairment (MCI).
Methods:
A total of 172 participants were recruited from 2 community facilities. Cronbach's alpha (α) was calculated to evaluate internal consistency. Intra-class correlation coefficient (ICC) was used to measure 2-week test-retest reliability. Construct validity was evaluated by conducting exploratory factor analysis to identify the internal structure of MBI-C, and assessing the correlation between theoretically related constructs, including objective and subjective cognitive impairment, neurotic personality, social supports, and maladaptive coping. Concurrent validity was assessed by its correlation with Neuropsychiatric Inventory Questionnaire (NPI-Q).
Results:
The results revealed good internal consistency and test-retest reliability of the MBI-C. Item analysis identified 4 items with low item-to-total correlations. The EFA identified a seven-factor structure. Hypothesis testing identified its significant correlations with subjective cognitive impairment, neurotic personality, social supports, and maladaptive coping. Concurrent validity was supported by its significant correlation with the NPI-Q.
Conclusions:
The traditional Chinese version of MBI-C is a valid and reliable outcome measure to assess the severity of neuropsychiatric symptoms of the MCI population.
