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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Dove Medical Press
2014
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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. |
format | Online Article Text |
id | pubmed-4038421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
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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