Open AccessA latent class analysis of adolescents' technology and interactive social media use: Associations with academics and substance use
Author(s) -
Tang Sandra,
Patrick Megan E.
Publication year - 2020
Publication title -
human behavior and emerging technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.823
H-Index - 8
ISSN - 2578-1863
DOI - 10.1002/hbe2.154
Subject(s) - latent class model , multinomial logistic regression , substance use , social media , psychology , logistic regression , class (philosophy) , media use , social class , clinical psychology , medicine , social psychology , computer science , world wide web , machine learning , artificial intelligence , political science , law
Latent class analysis was used to identify patterns of technology and social media use among adolescents in a national study ( n = 26,348). Multinomial logistic regression was used to examine associations between latent classes and academics and substance use. Results demonstrated four classes: Infrequent Users (55%), Interactive Users (21%), Television Watchers (14%), and Constant Users (10%). Compared to Infrequent Users , Interactive , and Constant Users had lower grades and higher alcohol and marijuana use. Television Watchers had lower grades and participated in fewer extracurricular activities compared to Infrequent Users , but there were no differences on substance use. Results show that adolescents with the most media‐intensive profiles were also at greater risk for poor academic outcomes and substance use.