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      Evaluating the psychometric properties of the Chinese Depression Anxiety Stress Scale for Youth (DASS-Y) and DASS-21

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          Abstract

          Background

          In recognizing the need for a reliable and valid instrument to assess psychological distress among children and adolescents, the present study translated the newly developed Depression Anxiety Stress Scale for Youth (DASS-Y) into Chinese, while also comparing its psychometric properties with those of the well-established DASS-21 within a primary and middle school demographic.

          Methods

          Utilizing a combination of convenience sampling and purposive sampling, a cohort comprising 1,507 primary and 1,131 middle school students was recruited. Rasch analysis, confirmatory factor analysis (CFA), and structural equation modeling (SEM) were used in the data analysis.

          Results

          Significant differences were observed between the DASS-Y and the DASS-21, notably within the anxiety subscale. The proportions of individuals with clinical mood disorders identified by the two scales demonstrated a significant disparity. Both scales, following an adjustment of responses, exhibited satisfactory internal consistency and convergent validity, with the acceptance of a three-factor structure. Furthermore, the DASS-Y showed superior discriminant validity relative to the DASS-21, providing more compelling evidence regarding concurrent validity.

          Conclusion

          Overall, the Chinese version of the DASS-Y demonstrated superior robustness to the DASS-21 in terms of psychometric properties. The findings provide initial evidence for the psychometric properties of the DASS-Y from another culture.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13034-023-00655-2.

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          Most cited references67

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Comparison of Convenience Sampling and Purposive Sampling

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              Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares.

              In confirmatory factor analysis (CFA), the use of maximum likelihood (ML) assumes that the observed indicators follow a continuous and multivariate normal distribution, which is not appropriate for ordinal observed variables. Robust ML (MLR) has been introduced into CFA models when this normality assumption is slightly or moderately violated. Diagonally weighted least squares (WLSMV), on the other hand, is specifically designed for ordinal data. Although WLSMV makes no distributional assumptions about the observed variables, a normal latent distribution underlying each observed categorical variable is instead assumed. A Monte Carlo simulation was carried out to compare the effects of different configurations of latent response distributions, numbers of categories, and sample sizes on model parameter estimates, standard errors, and chi-square test statistics in a correlated two-factor model. The results showed that WLSMV was less biased and more accurate than MLR in estimating the factor loadings across nearly every condition. However, WLSMV yielded moderate overestimation of the interfactor correlations when the sample size was small or/and when the latent distributions were moderately nonnormal. With respect to standard error estimates of the factor loadings and the interfactor correlations, MLR outperformed WLSMV when the latent distributions were nonnormal with a small sample size of N = 200. Finally, the proposed model tended to be over-rejected by chi-square test statistics under both MLR and WLSMV in the condition of small sample size N = 200.
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                Author and article information

                Contributors
                27020@sdwu.edu.cn
                281770596@qq.com
                gamble@cc.ncue.edu.tw
                376658135@qq.com
                jiang3737@sina.com
                Lxd_73@163.com
                mark.griffiths@ntu.ac.uk
                aholechen@gmail.com
                cylin36933@gmail.com
                Journal
                Child Adolesc Psychiatry Ment Health
                Child Adolesc Psychiatry Ment Health
                Child and Adolescent Psychiatry and Mental Health
                BioMed Central (London )
                1753-2000
                7 September 2023
                7 September 2023
                2023
                : 17
                : 106
                Affiliations
                [1 ]GRID grid.495262.e, ISNI 0000 0004 1777 7369, School of Foreign Languages, , Shandong Women’s University, ; Jinan, 250300 China
                [2 ]GRID grid.412638.a, ISNI 0000 0001 0227 8151, Faculty of Education, , Qufu Normal University, ; Qufu, 273165 China
                [3 ]GRID grid.411864.e, ISNI 0000 0004 1761 3022, Faculty of Education, , Jiangxi Science and Technology Normal University, ; Nanchang, 330031 China
                [4 ]Department of English, National Changhua University, Changhua, 50007 Taiwan
                [5 ]Xinjian District of Nanchang City, No.1 Senior High School, Nanchang, 330100 China
                [6 ]Yangan Primary School of Qionglai City, Qionglai, 611535 China
                [7 ]Gaogeng Nine-year School, Qionglai, 611533 China
                [8 ]GRID grid.12361.37, ISNI 0000 0001 0727 0669, International Gaming Research Unit, Psychology Department, , Nottingham Trent University, ; Nottingham, UK
                [9 ]GRID grid.412638.a, ISNI 0000 0001 0227 8151, Chinese Academy of Education Big Data, Qufu Normal University, ; Qufu, 273165 China
                [10 ]GRID grid.64523.36, ISNI 0000 0004 0532 3255, Institute of Allied Health Sciences, College of Medicine, , National Cheng Kung University, ; Tainan, 701401 Taiwan
                [11 ]GRID grid.64523.36, ISNI 0000 0004 0532 3255, Department of Occupational Therapy, College of Medicine, , National Cheng Kung University, ; Tainan, 701401 Taiwan
                [12 ]GRID grid.64523.36, ISNI 0000 0004 0532 3255, Biostatistics Consulting Center, National Cheng Kung University Hospital, , College of Medicine, National Cheng Kung University, ; Tainan, 701401 Taiwan
                [13 ]GRID grid.64523.36, ISNI 0000 0004 0532 3255, Department of Public Health, College of Medicine, , National Cheng Kung University, ; Tainan, 701401 Taiwan
                Article
                655
                10.1186/s13034-023-00655-2
                10486035
                37679819
                47337827-c0db-4fa8-a4d5-0784a7c4ae96
                © BioMed Central Ltd., part of Springer Nature 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 7 June 2023
                : 30 August 2023
                Funding
                Funded by: Shandong Province Social Science Foundation Project
                Award ID: 22CJYJ16
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2023

                Clinical Psychology & Psychiatry
                psychometric properties,children,adolescents,dass-y,dass-21
                Clinical Psychology & Psychiatry
                psychometric properties, children, adolescents, dass-y, dass-21

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