Maartje Boer

CHAPTER 9 312 step could be to investigate which individual characteristics reinforce these particular patterns of positive and negative online experiences, thereby identifying adolescents engaging in healthy and unhealthy SMU. Strengths and Limitations A main strength of this dissertation is the use of nationally representative and internationally comparative cross-sectional data as well as longitudinal data. These different samples point towards comparable conclusions, namely that problematic SMU, and often not high SMU intensity, is detrimental to wellbeing, supporting the robustness of our conclusions. Also, the use of a variety of analytical methods allowed us to examine the psychometric properties of the SMD-scale in detail and to shed light on the association between SMU behaviors and wellbeing in different ways. The studies in this dissertation also have limitations, of which some have already been acknowledged above. First, findings of the longitudinal studies should be interpreted in light of the yearly time intervals that were used in the data collection. The observed dynamics between SMU behaviors and wellbeing may be different when collecting data in shorter time intervals, as effects are likely contingent on the time intervals used to study associations (Keijsers & Roekel, 2018). Second, in our studies, we focused on particularly early and middle adolescents from 11 to 16 years old. The results of our studies may not be generalized to, for example, older adolescents, as the effects may be specific to the developmental period that we studied. Third, the conclusions from our longitudinal chapters are based on the same sample of Dutch adolescents (Chapters 5-8). Replication in other (inter)national samples is necessary to investigate the robustness and of our findings and generalizability to adolescents in other national contexts. After all, our study shows that SMU effects are sensitive to country contexts (Chapter 4). Fourth, the studies in this dissertation relied on self-report measures. The use of such measures to indicate SMU intensity is controversial, as adolescents may over- or underestimate their use because it may be difficult to recall their frequency of use (Junco, 2013; Parry et al., 2020). More objective measurements of SMU intensity, such as tracked time spent on particular SMU activities via smartphone apps, overcome the limitation of recall bias. However, many available time tracking facilities have practical challenges in recording time