This study proposed an improved representation of the DASS-21 factor structure developed by Lovibond and Lovibond in , 335-342 (1995) using bifactor exploratory structural equation modeling (bifactor ESEM). This research was conducted by reference to 521 Turkish adults (45.3% females; = 27.86, = 8.23). The bifactor ESEM findings indicated a strong general factor of negative affect underlying responses to all DASS-21 items but also that despite the presence of three specific factors (depression, anxiety, and stress), the depression subscale explained a high degree of variance and could be considered to constitute a specific factor. The results obtained from this study show that there is a common factor associated with DASS-21 scales, the total score of DASS-21 can be identified as a measure of general negative affect, and the bifactor ESEM structure of DASS-21 ensures measurement invariance across genders.
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http://dx.doi.org/10.1007/s12144-022-03710-x | DOI Listing |
Acta Psychol (Amst)
November 2024
Department of Psychology, Sociology and Social Work, Faculty of Education, Psychology and Social Work, University of Lleida, Lleida, Spain. Electronic address:
Background: Teachers in demanding work environments are prone to anxiety, depression, and stress. Validated measures across different cultural contexts are required. The present study evaluated the psychometric properties of the 21-item Depression, Anxiety and Stress Scale (DASS-21) and DASS-12 and DASS-8 among Spanish and Chinese primary school teachers.
View Article and Find Full Text PDFBody Image
October 2023
Substantive-Methodological Synergy Research Laboratory, Department of Psychology, Concordia University, Montreal, Canada.
Traditionally, assessments of factor validity of body image instruments have relied on exploratory or confirmatory factor analysis. However, the emergence of exploratory structural equation modeling (ESEM), a resurgence of interest in bifactor models, and the ability to combine both models (bifactor-ESEM) is beginning to shape the future of body image research. For these analytic approaches to truly advance body image research, scholars will need to have a deep understanding of their use and application.
View Article and Find Full Text PDFJ Pers
November 2024
Department of Psychology, Faculty of Philosophy, University of Novi Sad, Novi Sad, Serbia.
Objective: The tripartite model of subjective well-being (SWB) posits three components: positive affect, negative affect, and life satisfaction. The fundamental issue regarding the structure of SWB and the meaning of the general SWB factor remains unresolved.
Methods: Across three studies and six samples (total N = 9304), we evaluated competing models of SWB and tested the criterion-related validity of SWB components operationalized within different models.
Acta Psychol (Amst)
October 2024
Department of English, Faculty of Languages and Translation, King Khalid University, Abha, Saudi Arabia. Electronic address:
This study tested the psychometric properties and factorial validity of the language domain-specific trait emotional intelligence (L2-TEI) scale among 415 language learners and assessed its criterion validity in predicting language engagement. The scale consistes of four factors-emotionality (EM), self-control (SC), wellbeing (WB), and sociability (SO). Four models we considered to validate the scale: confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), bifactor CFA, and bifactor ESEM were employed to evaluate the factorial validity of the L2-TEI scale.
View Article and Find Full Text PDFDigit Health
September 2024
School of Journalism and Communication, Wuhan University, Wuhan, Hubei, P.R. China.
Introduction: The need for privacy is a high-order psychological need of human, which is closely related to human mental health problems in the digital age. The Need for Privacy Scale (NFP-S) is a reliable measure of need for privacy. This study tested its psychometric characteristics among Chinese populations.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!