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RESEARCH ARTICLE

Confirmatory Factor Analysis of Center for Epidemiological Studies Depression 10-item Scale on Chinese International Students in Korea

Yang Eun Kim1 , * Open Modal iD Boram Lee1 , # Open Modal iD Authors Info & Affiliations
The Open Psychology Journal 17 Sept 2021 RESEARCH ARTICLE DOI: 10.2174/1874350102114010185

Abstract

Introduction:

Depression has become increasingly prevalent in Chinese international students in South Korea. For this population, therefore, accurate assessment of mood disorders, particularly depression, is critically important. The 10-item Center for Epidemiological Studies Depression Scale (CES-D 10) is commonly used to measure depression in both clinical and non-clinical populations. Thus, this study examined the CES-D 10’s factor structure and psychometric properties in Chinese international students.

Methods:

Study participants were 250 Chinese international students aged 18–23, attending a four-year university in Korea; they completed the Chinese version of the CES-D 10. Based on relevant theories and empirical research, confirmatory factor analysis was employed to examine the adequacy of three competing models’ factor structure. Internal consistency reliability was assessed using Cronbach’s alpha, and test-retest reliability using the Pearson correlation coefficient.

Results:

Confirmatory factor analysis suggested that the two-factor model comprised of depressive affect/somatic retardation and positive affect had the best fit. The CES-D 10 showed satisfactory internal consistency and test-retest reliability in Chinese international students.

Conclusion:

The CES-D 10 demonstrated strong psychometric properties in this Chinese international student sample, and results suggest that the CES-D scale is a useful screening tool for depressive symptoms. Therefore, the CES-D 10 could be used as a depression screen for international students at the population level and in health clinics.

Keywords: CES-D, Chinese international students, Confirmatory factor analysis, Depression, Factor structure, Health clinics.
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