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Measuring poststroke fatigue: The psychometric properties of the Chinese version of multidimensional fatigue
Ya Ting Li1, Ho Yu Cheng1, Ying Liao2
1The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Objective:
Poststroke fatigue (PSF) is a common and debilitating problem among stroke patients. Multidimensional fatigue inventory (MFI) has been recommended to assess fatigue related to acquired brain injury. This study aimed to examine the psychometric properties of the Chinese version of MFI among stroke patients.
Methods:
The study recruited 252 stroke patients in China. The internal consistency of the Chinese-version MFI was evaluated using Cronbach's α coefficients. The test-retest reliability was measured over a 5-day interval with intraclass correlation coefficient. Exploratory factor analysis was conducted to analyze the construct validity. The concurrent validity of MFI was examined by calculating the Pearson's correlation coefficient between the scores of MFI and the fatigue assessment scale (FAS).
Results:
The exploratory factor analysis of the Chinese-version of MFI showed that it captured three dimensions of PSF, namely, physical fatigue, mental fatigue, and level of activity. The Chinese-version MFI demonstrated satisfactory internal consistency with Cronbach's α ranging from 0.83 (mental fatigue) to 0.91 (total scale). The Chinese-version MFI showed adequate test-retest reliability with intraclass correlation coefficients of 0.70 for the total scale, 0.69 for physical fatigue, 0.66 for mental fatigue, and 0.62 for level of activity. The concurrent validity of the Chinese-version MFI was demonstrated by a significant positive correlation (r=0.49, p <0.001) with FAS.
Conclusion:
This study findings showed that Chinese-version MFI has adequate internal consistency and test-retest reliability, and demonstrated its concurrent validity with FAS. The findings provide preliminary evidence of the three-factor structure of Chinese-version MFI by exploratory factor analysis.
