Maartje Boer

CHAPTER 9 288 explained by the countries’ mobile internet accessibility. Multilevel analysis on data from 154,981 adolescents from 29 countries in the European region and Canada showed that in countries where relatively few adolescents reported intense SMU, intense users report higher levels of psychological complaints, lower levels of life satisfaction, and lower levels of family support than non- intense users. However, in countries where relatively many adolescents reported intense SMU, intense and non-intense users reported equal levels of psychological complaints, and intense users reported higher levels of life satisfaction and family support than non-intense users. In all countries, intense users reported higher levels of friend support than non-intense users, and this association became stronger as the countries’ proportion of intense users increased. In some countries, intense users reported less school satisfaction and more schoolwork pressure than non-intense users, but this was not explained by the countries’ proportion of intense users. The association between problematic SMU and wellbeing was more robust than the one for intense SMU, because it was negative across all national contexts and this applied to all investigated indicators of wellbeing, although the strength of the negative associations varied across countries. The countries’ mobile internet accessibility did not explain the observed country-level differences in intense or problematic SMU. Overall, the findings suggest that intense SMU could be beneficial as well as detrimental to wellbeing, depending on the country context andwellbeing domain, whereas problematic SMU consistently poses a risk for impairments in multiple wellbeing domains. Most studies on the association between SMU behaviors and wellbeing are cross-sectional. Therefore, the next four chapters investigated the association between SMU intensity, SMU problems, and adolescent wellbeing in more detail using longitudinal data. Other than in Chapters 3 and 4, where SMU intensity was measured with the frequency of online communication, SMU intensity in the following chapters was indicated by the average frequency of diverse SMU activities, ranging frommore active tomore passive activities. Chapter 5 investigated whether changes in ADHD-symptoms (i.e., attention deficits, impulsivity, hyperactivity), preceded or followed from changes in SMU intensity and SMU problems using three waves of data from 543 Dutch adolescents. Findings from random intercept cross-lagged