Latent class analysis on internet and smartphone addiction in college students

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 male...

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Autores principales: Mok, Jung-Yeon, Choi, Sam-Wook, Kim, Dai-Jin, Choi, Jung-Seok, Lee, Jaewon, Ahn, Heejune, Choi, Eun-Jeung, Song, Won-Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038421/
https://www.ncbi.nlm.nih.gov/pubmed/24899806
http://dx.doi.org/10.2147/NDT.S59293
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author Mok, Jung-Yeon
Choi, Sam-Wook
Kim, Dai-Jin
Choi, Jung-Seok
Lee, Jaewon
Ahn, Heejune
Choi, Eun-Jeung
Song, Won-Young
author_facet Mok, Jung-Yeon
Choi, Sam-Wook
Kim, Dai-Jin
Choi, Jung-Seok
Lee, Jaewon
Ahn, Heejune
Choi, Eun-Jeung
Song, Won-Young
author_sort Mok, Jung-Yeon
collection PubMed
description 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 <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.
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spelling pubmed-40384212014-06-04 Latent class analysis on internet and smartphone addiction in college students Mok, Jung-Yeon Choi, Sam-Wook Kim, Dai-Jin Choi, Jung-Seok Lee, Jaewon Ahn, Heejune Choi, Eun-Jeung Song, Won-Young Neuropsychiatr Dis Treat Original Research 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 <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. Dove Medical Press 2014-05-20 /pmc/articles/PMC4038421/ /pubmed/24899806 http://dx.doi.org/10.2147/NDT.S59293 Text en © 2014 Mok et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Mok, Jung-Yeon
Choi, Sam-Wook
Kim, Dai-Jin
Choi, Jung-Seok
Lee, Jaewon
Ahn, Heejune
Choi, Eun-Jeung
Song, Won-Young
Latent class analysis on internet and smartphone addiction in college students
title Latent class analysis on internet and smartphone addiction in college students
title_full Latent class analysis on internet and smartphone addiction in college students
title_fullStr Latent class analysis on internet and smartphone addiction in college students
title_full_unstemmed Latent class analysis on internet and smartphone addiction in college students
title_short Latent class analysis on internet and smartphone addiction in college students
title_sort latent class analysis on internet and smartphone addiction in college students
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038421/
https://www.ncbi.nlm.nih.gov/pubmed/24899806
http://dx.doi.org/10.2147/NDT.S59293
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