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[학술저널]

  • 학술저널

Hyo-Jeong Kim(Sungkyunkwan University School of Medicine) Eun-Ho Lee(Sungkyunkwan University School of Medicine) Soon-Taeg Hwang(Chungbuk National University) Sang-Hwang Hong(Chinju National University of Education) Ji-Hae Kim(Sungkyunkwan University School of Medicine)

DOI : 10.15842/kjcp.2018.37.2.005

초록

Childhood depression is a disorder with negative and long-lasting effects through to adulthood. At present, the Children’s Depression Inventory is the most globally used tool for evaluating depression in a pediatric group, and the Children’s Depres¬sion Inventory-2 (CDI-2) was developed considering a birth-cohort effect. The current study has two main objectives: (a) to investigate the psychometric properties of the self-rated version of the CDI-2 and (b) to investigate its factorial structure in Korean nonclinical children and adolescent populations. A convenient sample considering age, sex, and area was used. The total sample comprised 1,036 children and adolescents aged 7 to 17 years living in 3 different areas. The psychometric prop¬erties of the CDI-2, including internal consistency, interrater reliability, and concurrent validity, were evaluated. Exploratory structural equation modeling (ESEM) analysis was also conducted to determine the internal structure of the CDI-2 for Ko¬rean children and adolescents. The gender difference was is significant, and age also affected the total score. The interaction effect of age and sex in the total score is statistically significant. The Korean CDI-2 appeared to have good internal consis¬tency. Correlations among the CDI-2 scores of self-report, parent-report, and teacher-report forms were statistically signifi¬cant and moderate in size. ESEM analysis demonstrated that a two-factor structure could be a best-fit model for our sample. The sample of the study consisted entirely of non-clinical children and adolescents, and therefore more researches targeting the clinical population are necessary to generalize these results. Future studies could identify a cut-off score or predictive va¬lidity.

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