Latent class analysis on internet and smartphone addiction in college students
Authors Mok JY, Choi S, Kim D, Choi J, Lee J, Ahn H, Choi E, Song W
Received 16 December 2013
Accepted for publication 29 January 2014
Published 20 May 2014 Volume 2014:10 Pages 817—828
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Jung-Yeon Mok,1 Sam-Wook Choi,1,2 Dai-Jin Kim,3 Jung-Seok Choi,4 Jaewon Lee,2 Heejune Ahn,5 Eun-Jeung Choi,6 Won-Young Song7
1Eulji Addiction Institute, Eulji University, Seoul, South Korea; 2Department of Psychiatry, Gangnam Eulji Hospital, Eulji University, Seoul, South Korea; 3Department of Psychiatry, Seoul St Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, South Korea; 4Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, South Korea; 5Department of Electrical and Information Engineering, SeoulTech, Seoul, South Korea; 6Department of Social Welfare, Dongshin University, Naju, South Korea; 7Department of Counseling and Psychotherapy, Konyang University, Nonsan, South Korea
Purpose: This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined.
Methods: A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used.
Results: Significant differences between males and females were found for most of the variables (all P<0.05). Specifically, in terms of internet usage, males were more addicted than females (P<0.05); however, regarding smartphone, this pattern was reversed (P<0.001). Due to these observed differences, classifications of the subjects into subgroups based on internet and smartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (P<0.001). A common trend for psychosocial trait factors was found for both sexes: anxiety levels and neurotic personality traits increased with addiction severity levels (all P<0.001). However, Lie dimension was inversely related to the addiction severity levels (all P<0.01).
Conclusion: Through the latent classification process, this study identified three distinct internet and smartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field.
Keywords: sex difference, Eysenck personality type, psychosocial traits
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Download Article [PDF] View Full Text [HTML][Machine readable]