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      Relationship of Smartphone Use Severity with Sleep Quality, Depression, and Anxiety in University Students

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          Abstract

          Background and Aims

          The usage of smartphones has increased rapidly in recent years, and this has brought about addiction. The aim of the current study was to investigate the relationship between smartphone use severity and sleep quality, depression, and anxiety in university students.

          Methods

          In total, 319 university students (203 females and 116 males; mean age = 20.5 ± 2.45) were included in the study. Participants were divided into the following three groups: a smartphone non-user group (n = 71, 22.3%), a low smartphone use group (n = 121, 37.9%), and a high smartphone use group (n = 127, 39.8%). All participants were evaluated using the Pittsburgh Sleep Quality Index, Beck Depression Inventory, Beck Anxiety Inventory; moreover, participants other than those in the smartphone non-user group were also assessed with the Smartphone Addiction Scale.

          Results

          The findings revealed that the Smartphone Addiction Scale scores of females were significantly higher than those of males. Depression, anxiety, and daytime dysfunction scores were higher in the high smartphone use group than in the low smartphone use group. Positive correlations were found between the Smartphone Addiction Scale scores and depression levels, anxiety levels, and some sleep quality scores.

          Conclusion

          The results indicate that depression, anxiety, and sleep quality may be associated with smartphone overuse. Such overuse may lead to depression and/or anxiety, which can in turn result in sleep problems. University students with high depression and anxiety scores should be carefully monitored for smartphone addiction.

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          Most cited references33

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          Is Open Access

          The Smartphone Addiction Scale: Development and Validation of a Short Version for Adolescents

          Objective This study was designed to investigate the revised and short version of the smartphone addiction scale and the proof of its validity in adolescents. In addition, it suggested cutting off the values by gender in order to determine smartphone addiction and elaborate the characteristics of smartphone usage in adolescents. Method A set of questionnaires were provided to a total of 540 selected participants from April to May of 2013. The participants consisted of 343 boys and 197 girls, and their average age was 14.5 years old. The content validity was performed on a selection of shortened items, while an internal-consistency test was conducted for the verification of its reliability. The concurrent validity was confirmed using SAS, SAPS and KS-scale. Receiver operating characteristics analysis was conducted to suggest cut-off. Results The 10 final questions were selected using content validity. The internal consistency and concurrent validity of SAS were verified with a Cronbach's alpha of 0.911. The SAS-SV was significantly correlated with the SAS, SAPS and KS-scale. The SAS-SV scores of gender (p<.001) and self-evaluation of smartphone addiction (p<.001) showed significant difference. The ROC analysis results showed an area under a curve (AUC) value of 0.963(0.888–1.000), a cut-off value of 31, sensitivity value of 0.867 and specificity value of 0.893 in boys while an AUC value of 0.947(0.887–1.000), a cut-off value of 33, sensitivity value of 0.875, and a specificity value of 0.886 in girls. Conclusions The SAS-SV showed good reliability and validity for the assessment of smartphone addiction. The smartphone addiction scale short version, which was developed and validated in this study, could be used efficiently for the evaluation of smartphone addiction in community and research areas.
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            Development and Validation of a Smartphone Addiction Scale (SAS)

            Objective The aim of this study was to develop a self-diagnostic scale that could distinguish smartphone addicts based on the Korean self-diagnostic program for Internet addiction (K-scale) and the smartphone's own features. In addition, the reliability and validity of the smartphone addiction scale (SAS) was demonstrated. Methods A total of 197 participants were selected from Nov. 2011 to Jan. 2012 to accomplish a set of questionnaires, including SAS, K-scale, modified Kimberly Young Internet addiction test (Y-scale), visual analogue scale (VAS), and substance dependence and abuse diagnosis of DSM-IV. There were 64 males and 133 females, with ages ranging from 18 to 53 years (M = 26.06; SD = 5.96). Factor analysis, internal-consistency test, t-test, ANOVA, and correlation analysis were conducted to verify the reliability and validity of SAS. Results Based on the factor analysis results, the subscale “disturbance of reality testing” was removed, and six factors were left. The internal consistency and concurrent validity of SAS were verified (Cronbach's alpha = 0.967). SAS and its subscales were significantly correlated with K-scale and Y-scale. The VAS of each factor also showed a significant correlation with each subscale. In addition, differences were found in the job (p<0.05), education (p<0.05), and self-reported smartphone addiction scores (p<0.001) in SAS. Conclusions This study developed the first scale of the smartphone addiction aspect of the diagnostic manual. This scale was proven to be relatively reliable and valid.
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              Electronic media use and sleep in school-aged children and adolescents: A review.

              Electronic media have often been considered to have a negative impact on the sleep of children and adolescents, but there are no comprehensive reviews of research in this area. The present study identified 36 papers that have investigated the relationship between sleep and electronic media in school-aged children and adolescents, including television viewing, use of computers, electronic gaming, and/or the internet, mobile telephones, and music. Many variables have been investigated across these studies, although delayed bedtime and shorter total sleep time have been found to be most consistently related to media use. A model of the mechanisms by which media use may affect sleep is presented and discussed as a vehicle for future research. Copyright 2010 Elsevier B.V. All rights reserved.
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                Author and article information

                Journal
                J Behav Addict
                J Behav Addict
                jba
                JBA
                Journal of Behavioral Addictions
                Akadémiai Kiadó
                2062-5871
                2063-5303
                June 2015
                1 July 2015
                : 4
                : 2
                : 85-92
                Affiliations
                [1 ]Department of Psychiatry, School of Medicine, Süleyman Demirel University , Isparta, Turkey
                Author notes
                * Corresponding author: Kadir Demirci, MD, Assist. Prof. Dr. of Psychiatry; Department of Psychiatry, Research and Training Hospital, School of Medicine, Süleyman Demirel University, Isparta, Turkey, 32200; Phone: +902462119336; Fax: +902462112830; E-mail: kdrdmrc@ 123456yahoo.com
                Article
                10.1556/2006.4.2015.010
                4500888
                26132913
                993f626c-ec88-42ff-a309-ce6b42ef2ce4
                © 2015 Akadémiai Kiadó, Budapest

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.

                History
                : 27 December 2014
                : 26 April 2015
                : 26 April 2015
                Page count
                Figures: 0, Tables: 6, References: 45, Pages: 8
                Funding
                Nothing declared.
                Categories
                Full-Length Report

                smartphone,addiction,sleep quality,depression,anxiety
                smartphone, addiction, sleep quality, depression, anxiety

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