Maartje Boer

CHAPTER 1 20 the methodological approach (i.e., level of analysis). As such, more in-depth research, that systematically takes all these factors into account, is crucial to understand the relation between adolescents’ SMU intensity and wellbeing, which is typically lacking in the aforementioned studies on SMU effects. Insights from a detailed analysis provide researchers with specific directions for future research on SMU effects. Furthermore, it informs parents and health professionals who are concerned with the wellbeing of adolescents about the extent to which SMU could be beneficial or harmful to wellbeing. Aims of the Dissertation The overall aim of this dissertation is to improve our understanding of the association between SMU and wellbeing, with particular attention to the differences between SMU intensity and SMU problems in how they relate to specific domains of adolescent wellbeing. In all chapters of this dissertation, we focused on adolescents in high school (i.e., aged 11 to 16). Studying associations between adolescents’ SMU and wellbeing during this period of adolescence considered important, because in this period, social media are omnipresent and play an important role in their individual development (Granic et al., 2020). Given the prominent role of social media in adolescents’ daily lives and the possible effects on different aspects of their wellbeing, it is essential to study the relation between adolescents’ SMU and wellbeing both for science and possibly for the development of public health policies. In this dissertation, wellbeing often refers to mental health, indicated by positivemental health (e.g., life satisfaction) as well asmental health problems (e.g., ADHD-symptoms, depressive symptoms). In some chapters, wellbeing is also indicated by social wellbeing (e.g., friends support), school wellbeing (e.g., school satisfaction), and/or sleep (e.g., sleep duration). To study SMU behaviors and their relation with adolescent wellbeing, the chapters in this dissertation aim to answer the research questions highlighted above. More specifically, in response to the limited validation work on scales that measure problematic SMU, in Chapter 2 , we validated the Social Media Disorder (SMD)-scale (Van den Eijnden et al., 2016) among a cross-sectional representative sample of Dutch adolescents. Here, we investigated the structural validity, reliability, measurement invariance, itemscorepatterns, and criterion validity of the scale using (multigroup) Confirmatory Factor Analysis, Exploratory Factor analysis,