Psychometric properties of the Chalder Fatigue Scale revisited: an exploratory structural equation modeling approach

Abstract

Objective Previous validation studies of the Chalder Fatigue Scale (CFS) suffer methodological shortcomings. The present study aimed to re-evaluate its psychometric properties using exploratory structural equation modeling (ESEM). Methods A Chinese sample of 1259 community-dwelling residents completed the 11-item Chinese CFS and a variety of health measures (anxiety, depression, exhaustion, sleep disturbance, and quality of life). In addition to traditional confirmatory factor analysis, ESEM was performed to assess the fit of two- and three-factor models using robust maximum likelihood estimation and oblique geomin rotation. Convergent validity of the CFS was examined via associations with five covariates (gender, age, exercise, perceived health, and life event) and the health measures in the ESEM model. Results The ESEM models displayed a superior fit to confirmatory factor models. The three-factor ESEM model showed a satisfactory model fit to the data but not for the two-factor model. The three factors were physical fatigue (three items, a = .800), low energy (four items, a = .821), and mental fatigue (four items, a = .861). The factors exhibited convergent validity with the model covariates and health measures. Conclusion The results demonstrate the satisfactory reliability and convergent validity for the three-factor structure of the CFS as a valid measure of fatigue symptoms in the general population. Future psychometric studies could adopt the ESEM approach as a practical alternative to traditional confirmatory factor analysis.