Factor structure and measurement invariance of the Depression anxiety stress scale (DASS-21) in Chinese left-behind and non-left-behind children: an exploratory structural equation modeling approach.

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Title: Factor structure and measurement invariance of the Depression anxiety stress scale (DASS-21) in Chinese left-behind and non-left-behind children: an exploratory structural equation modeling approach.
Authors: Chen W; School of Psychology, Guizhou Normal University, Guiyang, China. chenweihb@yeah.net.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China. chenweihb@yeah.net., Peng K; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China., Gao M; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China., Meng Z; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China., Wang L; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China., Liao Y; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.
Source: BMC public health [BMC Public Health] 2024 Jun 21; Vol. 24 (1), pp. 1660. Date of Electronic Publication: 2024 Jun 21.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100968562 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2458 (Electronic) Linking ISSN: 14712458 NLM ISO Abbreviation: BMC Public Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Factor structure and measurement invariance of the Depression anxiety stress scale (DASS-21) in Chinese left-behind and non-left-behind children: an exploratory structural equation modeling approach.
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  Data: <searchLink fieldCode="AU" term="%22Chen+W%22">Chen W</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China. chenweihb@yeah.net.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China. chenweihb@yeah.net.<br /><searchLink fieldCode="AU" term="%22Peng+K%22">Peng K</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.<br /><searchLink fieldCode="AU" term="%22Gao+M%22">Gao M</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.<br /><searchLink fieldCode="AU" term="%22Meng+Z%22">Meng Z</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.<br /><searchLink fieldCode="AU" term="%22Wang+L%22">Wang L</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.<br /><searchLink fieldCode="AU" term="%22Liao+Y%22">Liao Y</searchLink>; School of Psychology, Guizhou Normal University, Guiyang, China.; Center for Big Data Research in Psychology, Guizhou Normal University, Guiyang, China.
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  Data: <searchLink fieldCode="JN" term="%22100968562%22">BMC public health</searchLink> [BMC Public Health] 2024 Jun 21; Vol. 24 (1), pp. 1660. <i>Date of Electronic Publication: </i>2024 Jun 21.
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