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Effects of internet and Smartphone addictions on depression and anxiety based on propensity score matching analysis

Title
Effects of internet and Smartphone addictions on depression and anxiety based on propensity score matching analysis
Authors
Kim Y.-J.Jang H.M.Lee Y.Lee D.Kim D.-J.
Ewha Authors
이동환
SCOPUS Author ID
이동환scopus
Issue Date
2018
Journal Title
International Journal of Environmental Research and Public Health
ISSN
1661-7827JCR Link
Citation
International Journal of Environmental Research and Public Health vol. 15, no. 5
Keywords
AnxietyDepressionInternet addictionPropensity scoreSmartphone addiction
Publisher
MDPI AG
Indexed
SCOPUS WOS scopus
Document Type
Article
Abstract
The associations of Internet addiction (IA) and smartphone addiction (SA) with mental health problems have been widely studied. We investigated the effects of IA and SA on depression and anxiety while adjusting for sociodemographic variables. In this study, 4854 participants completed a cross-sectional web-based survey including socio-demographic items, the Korean Scale for Internet Addiction, the Smartphone Addiction Proneness Scale, and the subscales of the Symptom Checklist 90 Items-Revised. The participants were classified into IA, SA, and normal use (NU) groups. To reduce sampling bias, we applied the propensity score matching method based on genetics matching. The IA group showed an increased risk of depression (relative risk 1.207; p < 0.001) and anxiety (relative risk 1.264; p < 0.001) compared to NUs. The SA group also showed an increased risk of depression (relative risk 1.337; p < 0.001) and anxiety (relative risk 1.402; p < 0.001) compared to NCs. These findings show that both, IA and SA, exerted significant effects on depression and anxiety. Moreover, our findings showed that SA has a stronger relationship with depression and anxiety, stronger than IA, and emphasized the need for prevention and management policy of the excessive smartphone use. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
DOI
10.3390/ijerph15050859
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자연과학대학 > 통계학전공 > Journal papers
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