The Chinese version of the Perceived Stress Questionnaire: development and validation amongst medical students and workers

• Authors: Runtang Meng, Wuhan University; Jingjing Li, Emory University; Zhenkun Wang, Huazhong University of Science & Technology; Di Zhang, Wuhan Asia Gen Hosp; Bing Liu, Hubei University of Medicine; Yi Luo, Ningbo Coll Hlth Sci; Ying Hu, Wuhan University; Chuanhua Yu, Wuhan University
• Journal Title: HEALTH AND QUALITY OF LIFE OUTCOMES
• Volume: Volume 18, Number 1
• Publisher: BMC | 2020-03-13, Pages 70-70
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1186/s12955-020-01307-1
• Subjects: Health Sciences, Public Health; Health Sciences, Nursing
• Keywords: Science & Technology; Life Sciences & Biomedicine; Health Care Sciences & Services; Health Policy & Services; Perceived stress; Instrument validation; Rasch analysis; Factor analysis; OF-FIT INDEXES; CULTURAL-ADAPTATION; ULCERATIVE-COLITIS; LIFE EVENTS; RELIABILITY; PSQ; DEPRESSION; ANXIETY; TRANSLATION; COEFFICIENT

Abstract

Background: A valid and efficient stress measure is important for clinical and community settings. The objectives of this study were to translate the English version of the Perceived Stress Questionnaire (PSQ) into Chinese and to assess the psychometric properties of the Chinese version of the PSQ (C-PSQ). The C-PSQ evaluates subjective experiences of stress instead of a specific and objective status. Methods: Forward translations and back translations were used to translate the PSQ into Chinese. We used the C-PSQ to survey 2798 medical students and workers at three study sites in China from 2015 to 2017. Applying Rasch analysis (RA) and factor analysis (FA), we examined the measurement properties of the C-PSQ. Data were analyzed using the Rasch model for item fit, local dependence (LD), differential item functioning (DIF), unidimensionality, separation and reliability, response forms and person-item map. We first optimized the item selection in the Chinese version to maximize its psychometric quality. Second, we used cross-validation, by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), to determine the best fitting model in comparison to the different variants. Measurement invariance (MI) was tested using multi-group CFA across subgroups (medical students vs. medical workers). We evaluated validity of the C-PSQ using the criterion instruments, such as the Chinese version of the Perceived Stress Scale (PSS-10), the Short Form-8 Health Survey (SF-8) and the Goldberg Anxiety and Depression Scale (GADS). Reliability was assessed using internal consistency (Cronbach's alpha, Guttman's lambda-2, and McDonald's omegas) and reproducibility (test-retest correlation and intraclass correlation coefficient, [ICC]). Results: Infit and/or outfit values indicated that all items fitted the Rasch model. Three item pairs presented local dependency (residual correlations > 0.30). Ten items showed DIF. Dimensionality instruction suggested that eight items should be deleted. One item showed low discrimination. Thirteen items from the original PSQ were retained in the C-PSQ adaptation (i.e. C-PSQ-13). We tested and verified four feasible models to perform EFA. Built on the EFA models, the optimal CFA model included two first-order factors (i.e. constraint and imbalance) and a second-order factor (i.e., perceived stress). The first-order model had acceptable goodness of fit (Normed Chi-square = 8.489, TLI = 0.957, CFI = 0.965, WRMR = 1.637, RMSEA [90% CI] = 0.078 [0.072, 0.084]). The second-order model showed identical model fit. Person separation index (PSI) and person reliability (PR) were 2.42 and 0.85, respectively. Response forms were adequate, item difficulty matched respondents' ability levels, and unidimensionality was found in the two factors. Multi-group CFA showed validity of the optimal model. Concurrent validity of the C-PSQ-13 was 0.777, - 0.595 and 0.584 (Spearman correlation, P < 0.001, the same hereinafter) for the Chinese version of the PSS-10, SF-8, and GADS. For reliability analyses, internal consistency of the C-PSQ-13 was 0.878 (Cronbach's alpha), 0.880 (Guttman's lambda-2), and 0.880 (McDonald's omegas); test-retest correlation and ICC were 0.782 and 0.805 in a 2-day interval, respectively. Conclusion: The C-PSQ-13 shows good metric characteristics for most indicators, which could contribute to stress research given its validity and economy. This study also contributes to the evidence based regarding between-group factorial structure analysis.