Validation of the Social Media Disorder Scale using network analysis in a large representative sample of Czech adolescents
| Authors | |
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| Year of publication | 2022 |
| Type | Article in Periodical |
| Magazine / Source | Frontiers in Public Health |
| MU Faculty or unit | |
| Citation | |
| Web | article - open access |
| Doi | http://dx.doi.org/10.3389/fpubh.2022.907522 |
| Keywords | problematic social media use (PSMU); social media addiction; validation; psychometrics; Network analysis; adolescents; Health Behavior in School-aged Children (HBSC) |
| Attached files | |
| Description | Background: The importance of studying the excessive use of social media in adolescents is increasing and so is the need for in-depth evaluations of the psychometric properties of the measurement tools. This study investigated the properties of the Social Media Disorder Scale (SMDS) in a large representative sample of Czech adolescents. Methods: We analyzed the representative sample of 13,377 Czech adolescents (50.9% boys), 11–16 years old, who participated in the Health Behavior in School-aged Children (HBSC) survey (2017–18), using confirmatory factor analysis (CFA) and network models. Furthermore, we evaluated the measurement invariance and constructed the validity of the SMDS. Results: We found support for a single dominant factor but not for strict unidimensionality. Several residual correlations were identified. The strongest were for: problems–conflicts–deceptions; persistence–escape; and preoccupation–tolerance–withdrawal. Girls, particularly 13- and 15-year-olds, scored higher than boys in the same age group, and 13- and 15-year-olds achieved higher scores than 11-year-olds, although some items were not invariant between the groups. The SMDS was positively related to other online activities, screen time, and falling asleep late, but negatively related to well-being and mental health. Discussion and conclusions: The SMDS showed solid psychometric properties and construct validity. However, small violations of measurement invariance were detected. Furthermore, the network analysis showed important residual relationships between the items. |
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