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.
Camerini, A., Gerosa, T., Marciano, L. (2021). Predicting problematic smartphone use over time in adolescence: A latent class regression analysis of online and offline activities. NEW MEDIA & SOCIETY, 23(11), 3229-3248 [10.1177/1461444820948809].
Predicting problematic smartphone use over time in adolescence: A latent class regression analysis of online and offline activities
Gerosa T.;
2021
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.