++Publication Alert++ Predicting smartphone addiction in adolescence: A latent class regression analysis of online and offline activities
12 August 2020
Despite today’s ubiquitous nature of smartphones among adolescents, little is known about behavioural online and offline longitudinal predictors of problematic smartphone use (PSU). Guided by Uses and Gratifications Theory, we applied latent class analysis on survey data collected in 2017 from a cohort of 1096 adolescents (Mage = 12.4, SDage = 0.56) and regressed PSU measured 1 year later on class membership, controlling for socio-demographic characteristics, social desirability and autoregressive effects. We extracted four distinct classes: social-recreational onliners (n = 228), weekend onliners (n = 331), balanced (n = 404) and noninvolved (n = 153). Characterised by significantly more time spent online for recreational and social networking activities, both during weekdays and weekend days, as well as less time for sleep, the social-recreational onliners class showed significantly higher levels of PSU over time. Future studies should assess not only duration but also the frequency of daily online activities to provide further insights into behavioural predictors of PSU.