Assessment of psychometric performance for the Chinese version of the Brief Inventory of Perceived Stress integrating exploratory graph analysis and confirmatory factor analysis

Abstract

Objective: This study was to evaluate measurement properties of the Chinese version of the Brief Inventory of Perceived Stress (BIPS-C) and confirm possible solutions for measuring the constructs underlying perceived stress. Methods: A total of 1356 community residents enrolled and were randomly split into two halves. The first half was used to explore the underlying constructs of the BIPS-C by exploratory graph analysis (EGA) and the second half was used to compare and confirm the constructs by confirmatory factor analysis (CFA). Results: The EGA identified a one-factor model of the BIPS-C with an accuracy of 99.3%. One-factor, three-factor, second-order, and bifactor models were compared by CFAs. The bifactor model with one general and three specific factors was found to be the most adequate [comparative fit index (CFI) = 0.990; Tucker-Lewis index (TLI) = 0.979; root mean square error of approximation (RMSEA) = 0.058] and was superior to the other models. The related bifactor indices showed a stronger existence of the general factor. The bifactor model of the BIPS-C also showed adequate internal consistency with McDonald’s omega and omega subscales ranging from moderate to strong (0.677–0.869). Conclusion: The BIPS-C demonstrates sufficient measurement properties for assessing general perceived stress.