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      Effects of Internet and Smartphone Addictions on Depression and Anxiety Based on Propensity Score Matching Analysis

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          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.

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          SOME PRACTICAL GUIDANCE FOR THE IMPLEMENTATION OF PROPENSITY SCORE MATCHING

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            Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model.

            Within the last two decades, many studies have addressed the clinical phenomenon of Internet-use disorders, with a particular focus on Internet-gaming disorder. Based on previous theoretical considerations and empirical findings, we suggest an Interaction of Person-Affect-Cognition-Execution (I-PACE) model of specific Internet-use disorders. The I-PACE model is a theoretical framework for the processes underlying the development and maintenance of an addictive use of certain Internet applications or sites promoting gaming, gambling, pornography viewing, shopping, or communication. The model is composed as a process model. Specific Internet-use disorders are considered to be the consequence of interactions between predisposing factors, such as neurobiological and psychological constitutions, moderators, such as coping styles and Internet-related cognitive biases, and mediators, such as affective and cognitive responses to situational triggers in combination with reduced executive functioning. Conditioning processes may strengthen these associations within an addiction process. Although the hypotheses regarding the mechanisms underlying the development and maintenance of specific Internet-use disorders, summarized in the I-PACE model, must be further tested empirically, implications for treatment interventions are suggested.
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              The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study.

              Over the last decade, research into "addictive technological behaviors" has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the weak interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11 and 12% of the variance in addictive technology use. The mental health variables explained between 7 and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology, and suggests that the concept of Internet use disorder (i.e., "Internet addiction") as a unified construct is not warranted.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                25 April 2018
                May 2018
                : 15
                : 5
                : 859
                Affiliations
                [1 ]Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul 07061, Korea; loveaj1220@ 123456gmail.com
                [2 ]Department of Statistics, Ewha Womans University, Seoul 03760, Korea; janghyemin23@ 123456naver.com
                [3 ]Department of Statistics, Seoul National University, Seoul 08826, Korea; youngjo@ 123456snu.ac.kr
                [4 ]Department of Psychiatry, Seoul St. Mary’s Hospital, The Catholic University of Korea College of Medicine, Seoul 06591, Korea
                Author notes
                [* ]Correspondence: donghwan.lee@ 123456ewha.ac.kr (D.L.); Kdj922@ 123456catholic.ac.kr (D.-J.K.); Tel.: +82-2-3277-2300 (D.L.); +82-2-2258-7546 (D.-J.K.)
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-3878-6876
                Article
                ijerph-15-00859
                10.3390/ijerph15050859
                5981898
                29693641
                dde29f8f-3ef2-4dc5-a48d-07930ee222cf
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 February 2018
                : 21 April 2018
                Categories
                Article

                Public health
                anxiety,depression,internet addiction,smartphone addiction,propensity score
                Public health
                anxiety, depression, internet addiction, smartphone addiction, propensity score

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