Assessing mental health for China's police: psychometric features of the Self-Rating Depression Scale and Symptom Checklist 90-Revised

Chen, I-H, Lin, C-Y, Zheng, X and Griffiths, MD ORCID: https://orcid.org/0000-0001-8880-6524, 2020. Assessing mental health for China's police: psychometric features of the Self-Rating Depression Scale and Symptom Checklist 90-Revised. International Journal of Environmental Research and Public Health, 17 (8): 2737.

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Abstract

Police mental health is important because police officers usually encounter stressors that cause high levels of stress. In order to better understand mental health for Chinese police, the Zung Self-Rating Depression Scale (SDS) and Symptom Checklist 90-Revised (SCL-90-R) are commonly used in mainland China. Unfortunately, both the SDS and SCL-90-R lack detailed information on their psychometric properties. More specifically, factor structures of the SDS and SCL-90-R have yet to be confirmed among the police population in mainland China. Therefore, the present study compared several factor structures of the SDS and SCL-90-R proposed by prior research and to determine an appropriate structure for the police population. Utilizing cluster sampling, 1151 traffic police officers (1047 males; mean age = 36.6 years [SD = 6.10]) from 49 traffic police units in Jiangxi Province (China) participated in this study. Confirmatory factor analysis (CFA) with Akaike information criterion (AIC) was used to decide the best fit structure. In the SDS, the three-factor model (first posited by Kitamura et al.) had the smallest AIC and outperformed other models. In the SCL-90-R, the eight-factor model had the smallest AIC and outperformed the one-factor and nine-factor models. CFA fit indices also showed that both the three-factor model in the SDS and the eight-factor model in the SCL-90-R had satisfactory fit. The present study's results support the use of both SDS and SCL-90-R for police officers in mainland China.

Item Type:	Journal article
Publication Title:	International Journal of Environmental Research and Public Health
Creators:	Chen, I.-H., Lin, C.-Y., Zheng, X. and Griffiths, M.D.
Publisher:	MDPI AG
Date:	2020
Volume:	17
Number:	8
Identifiers:	Number Type 10.3390/ijerph17082737 DOI 1316021 Other
Rights:	© 2020 by the authors. Licensee MDPI, Basel, Switzerland. © This is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Divisions:	Schools > School of Social Sciences
Record created by:	Linda Sullivan
Date Added:	20 Apr 2020 08:49
Last Modified:	20 Apr 2020 08:49
URI:	https://irep.ntu.ac.uk/id/eprint/39685

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