Latent class analysis on internet and smartphone addiction in college students
Mok JY, Choi SW, Kim DJ, Choi JS, Lee J, Ahn H, Choi EJ, Song WY
Neuropsychiatric disease and treatment · 125 citations
How it was studied
- Design
- Cross-sectional study (classified by our AI screen)
- Studied in
- People
- Main outcome
- Health markers and function
Who paid for it
- Funding
- Independent funding
Based on full-text disclosure statement.
Publication
- Published
- 2014-05-01 · Neuropsychiatr Dis Treat · vol. 10 · p. 817
- Publisher
- Dove Medical Press
- Cited
- 299 citations · more than 100% of similar papers · 52.5× the field average
- Impact
- Top 10% most cited in its field
- References
- 64 works
- Access
- Open access (journal) · CC-BY-NC
- Research areas
- Impact of Technology on Adolescents · Psychosocial Factors Impacting Youth
- Keywords
- internet addiction, smartphone addiction, university students, addiction severity, sex differences, psychosocial traits, anxiety, neurotic personality, mood, Big Five personality traits
8 authors
From KR
- Sam‐Wook ChoiEulji University
- Jung Yeon MokEulji University
- Dai‐Jin KimThe Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- Jung‐Seok ChoiSeoul National University; SNUH SMG-SNU Boramae Medical Center
- Jaewon LeeEulji University
- Heejune AhnSeoul National University of Science and Technology
Abstract
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.
Abstract via Europe PMC. Copyright remains with the authors or publisher (CC BY-NC).
Community trust
Loading…
How much do you trust this study's findings?
Comments
Sign in to rate, comment on or flag this study.Sign inSomething wrong here?
Flag this study if its information, labels or funding look wrong. An editor reviews every flag.
Sign in to rate, comment on or flag this study.Sign inEducational information about published research. Not medical advice, and not a recommendation to start or stop anything.