![]() ![]() Importantly, it explores how mobile data donations can be used as add-ons or substitutes for conventional media exposure measures. The study investigates the feasibility of the method, sample biases, and accuracy of smartphone usage self-reports on a general population sample of Dutch citizens (n=404). The iOS Screen Time function is used as a test case for gathering log data with the help of screenshots. This study presents a new methodological approach, mobile data donations, in which smartphone usage data is collected unobtrusively with the help of mobile log data. With digital communication increasingly shifting to mobile devices, communication research needs to explore ways to retrieve, process, and analyze digital trace data on people’s most personal devices. Overall this suggests that the disruptiveness of smartphones is rooted within learned user behaviours, not devices. Importantly, we find that 89% of smartphone interactions are initiated by users, not by notifications. We furthermore observe that while the duration of interactions varies, the intervals between interactions remain largely invariant across different activity and location contexts, and for being alone or in the company of others. We show how smartphone interactions are driven by a complex set of routines and habits users develop over time. This paper presents evidence from a mixed-methods study using first-person wearable video cameras, comprising 200 h of audio-visual first-person, and self-confrontation interview footage with 1130 unique smartphone interactions (N = 37 users), to situate and analyse the disruptiveness of notifications in real-world contexts. Previous research suggests they can be a major disruption to the professional and private lives of users. Notifications are one of the core functionalities of smartphones. We discuss the implications of our findings in light of recent debates about the impact of screen time and formulate suggestions for future research based on important limitations of the current study, revolving among others around appropriate control groups as well as the combined use of both subjective and objective (i.e., behavioral) measures. Participants also self-reported a decrease in negative emotions, but no increase in positive emotions. Interestingly, across all participants behavioral performance on sustained attention tasks remained stable over time, while perceived attentional performance improved. We also found no support for a moderating role of self-control, impulsivity or Fear of Missing Out. Neither analyses revealed an effect on the outcome measures. treatment-as-intended), and the effect of participants’ relative reduction in screen time irrespective of their condition (i.e. Hence, we analyzed both the effect of the original manipulation (i.e. Unexpectedly, several participants in the control group pro-actively reduced their screen time significantly beyond the intended 10%, dismantling our intended screen time manipulation. This study explores whether a social media restriction, implemented via screen time apps, has a positive effect on emotional well-being and sustained attention performance.Ī randomized controlled trial (N= 76) was performed, exploring whether a week-long 50% reduction in time spent on mobile Facebook, Instagram, Snapchat and YouTube is beneficial to attentional performance and well-being as compared to a 10% reduction. Screen time apps that allow smartphone users to manage their screen time are assumed to combat negative effects of smartphone use. The between- and within-person convergent validity of ESM estimates decreased over time (i.e., fatigue effect). The within-person convergent validity of adolescents’ ESM estimates of their time spent on social media was unacceptable (r =. The between-person convergent validity of adolescents’ time estimates according to retrospective surveys and ESM reached the threshold for minimum acceptable convergent validity (r ranged from. They more accurately estimated their time spent on platforms that are used in a less fragmented way (Instagram) than on platforms that are used in a more fragmented way (Snapchat). In both retrospective surveys and ESM, adolescents overestimated their time spent on social media. The sample consisted of 125 adolescents (48% girls Mage = 14.1) with Android smartphones. The aim of this preregistered study was to examine the accuracy and convergent validity of retrospective surveys and experience sampling method (ESM) surveys, by comparing adolescents’ responses to these self-report measures with their digital trace data. ![]() To establish the effects of social media use, we need accurate and valid instruments to measure adolescents’ time spent with these media. A growing number of studies have tried to assess the effects of social media on adolescents, who are among the most avid social media users.
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