JMIR Publications

ABSTRACT

Background:

Digital technology and media use is integral to adolescents’ lives and has been associated with both positive and negative health consequences. Previous studies have largely focused on understanding technology behaviors and outcomes within adolescent populations, which can promote assumptions about adolescent’ technology use as homogenous. Further, many studies of adolescent technology use have focused on risks and negative outcomes. To better understand adolescent digital technology use, we need new approaches that can assess distinct profiles within study populations and take a balanced approach to understanding risks and benefits of digital technology use.

Objective:

The purpose of this study was to identify profiles of adolescent technology use within a large study population, focusing on four evidence-based constructs: technology ownership and use, parental involvement, health outcomes and well-being indicators.

Methods:

Adolescent-parent dyads were recruited to a cross-sectional online survey using the Qualtrics platform and panels. Technology use measures included ownership of devices, social media use frequency and the Adolescents’ Digital Interactions and Importance (ADTI) scale. Parent involvement measures included household media rules, technology-related parenting practices, parent social media use frequency, and parent-child relationship. Health outcome measures included physical activity, sleep, problematic internet use (PIU) and mental health assessments. Well-being indicators included mental wellness, communication and empathy. We used latent class analysis (LCA) to identify distinct profile groups across these 4 critical constructs.

Results:

Among our 3981 adolescent-parent dyads recruited, adolescent participants had a mean age of 15.0 years (SD=1.43), a total of 46.3% (1842/3981) were female, 69.7% (2701/3981) were Caucasian and 75.4% (2986/3981) lived in a household with an income above the poverty line. The LCA identified two discrete classes: Class 1 was made up of 63% of participants. Class 1 participants were more likely than Class 2 to report family owned devices, to have lower technology importance scores, to have household technology rules-often centered on content, to have positive parent relationships and lower parental social media use, and to report better health outcomes and well-being indicators.

Conclusions:

Findings from this national cross-sectional survey utilizing LCA led to two distinct profile groups of adolescent media use and their association with technology use, parent involvement as well as health and well-being outcomes. The two classes included a larger Class 1 of Family-Engaged Adolescents and a smaller Class 2 of At-Risk Adolescents. Findings from this study can inform interventions to support positive technology use and family support.