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Core Symptom Index (CSI): testing for bifactor model and differential item functioning

Published online by Cambridge University Press:  27 March 2019

Nahathai Wongpakaran Open the ORCID record for Nahathai Wongpakaran [Opens in a new window] ,
Tinakon Wongpakaran ,
Surang Lertkachatarn ,
Thanitha Sirirak  and
Pimolpun Kuntawong
Nahathai Wongpakaran*
Affiliation:
Chiang Mai University, Department of Psychiatry, Faculty of Medicine, Chiang Mai, Thailand
Tinakon Wongpakaran
Affiliation:
Chiang Mai University, Department of Psychiatry, Faculty of Medicine, Chiang Mai, Thailand
Surang Lertkachatarn
Affiliation:
Prasat Neurological Institute, Department of Psychiatry, Bangkok, Thailand
Thanitha Sirirak
Affiliation:
Prince of Songkla University, Department of Preventive Medicine, Faculty of Medicine, Songkhla, Thailand
Pimolpun Kuntawong
Affiliation:
Chiang Mai University, Department of Psychiatry, Faculty of Medicine, Chiang Mai, Thailand
*
Correspondence should be addressed to: Nahathai Wongpakaran, MD, FRCPsychT, Professor of Psychiatry, Geriatric Psychiatry Unit, Department of Psychiatry, Faculty of Medicine, Chiang Mai University 110 Intawaroros Rd., T. Sriphum, A. Muang, Chiang Mai, Kingdom of Thailand. 50200. Phone: +66 53 935422 ext 320; Fax: +66 53 935426. Email: nahathai.wongpakaran@cmu.ac.th.
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Abstract

Objectives:

The Core Symptom Index (CSI) is designed to measure anxiety, depression and somatization symptoms. This study examined the construct validity of CSI using confirmatory factor analysis (CFA) including a bifactor model and explored differential item functioning (DIF) of the CSI. The criterion and concurrent validity were evaluated.

Methods:

In all, 803 elderly patients, average age 69.24 years, 70% female, were assessed for depressive disorders and completed the CSI and the geriatric depression scale (GDS). A series involving CFA for ordinal scale was applied. Factor loadings and explained common variance were analyzed for general and specific factors; and Omega was calculated for model-based reliability. DIF was analyzed using the Multiple-Indicator Multiple-Cause model. Pearson’s correlation, ANOVA, and ROC analysis were used for associations and to compare CSI and GDS in predicting major depressive disorders (MDD).

Results:

The bifactor model provided the best fit to the data. Most items loaded on general rather than specific factors. The explained common variance was acceptable, while Omega hierarchical for the subscale and explained common variance for the subscales were low. Two DIF items were identified; ‘crying’ for sex items and ‘self-blaming’ for education items. Correlation among CSI and clinical disorders and the GDS were found. AUC for the GDS was 0.83, and for the CSI was 0.81.

Conclusion:

CSI appears sufficiently unidimensional. Its total score reflected a single general factor, permitting users to interpret the total score as a sufficient reliable measure of the general factors. CSI could serve as a screening tool for MDD.

Keywords

Core Symptom Index (CSI)confirmatory factor analysisdifferential item functioningMIMIC modelbifactor model

Information

Type
Original Research Article
Information
International Psychogeriatrics , Volume 31 , Issue 12: Issue Theme: Assessment of Cognitive Impairment in East Asia , December 2019 , pp. 1769 - 1779
Copyright
© International Psychogeriatric Association 2019 

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