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      Passive and Active Social Media Use and Depressive Symptoms Among United States Adults

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          Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample

          Despite social media use being one of the most popular activities among adolescents, prevalence estimates among teenage samples of social media (problematic) use are lacking in the field. The present study surveyed a nationally representative Hungarian sample comprising 5,961 adolescents as part of the European School Survey Project on Alcohol and Other Drugs (ESPAD). Using the Bergen Social Media Addiction Scale (BSMAS) and based on latent profile analysis, 4.5% of the adolescents belonged to the at-risk group, and reported low self-esteem, high level of depression symptoms, and elevated social media use. Results also demonstrated that BSMAS has appropriate psychometric properties. It is concluded that adolescents at-risk of problematic social media use should be targeted by school-based prevention and intervention programs.
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            How to factor-analyze your data right: do’s, don’ts, and how-to’s.

            The current article provides a guideline for conducting factor analysis, a technique used to estimate the population-level factor structure underlying the given sample data. First, the distinction between exploratory and confirmatory factor analyses (EFA and CFA) is briefly discussed; along with this discussion, the notion of principal component analysis and why it does not provide a valid substitute of factor analysis is noted. Second, a step-by-step walk-through of conducting factor analysis is illustrated; through these walk-through instructions, various decisions that need to be made in factor analysis are discussed and recommendations provided. Specifically, suggestions for how to carry out preliminary procedures, EFA, and CFA are provided with SPSS and LISREL syntax examples. Finally, some critical issues concerning the appropriate (and not-so-appropriate) use of factor analysis are discussed along with the discussion of recommended practices.
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              Social Networking Sites, Depression, and Anxiety: A Systematic Review

              Background Social networking sites (SNSs) have become a pervasive part of modern culture, which may also affect mental health. Objective The aim of this systematic review was to identify and summarize research examining depression and anxiety in the context of SNSs. It also aimed to identify studies that complement the assessment of mental illness with measures of well-being and examine moderators and mediators that add to the complexity of this environment. Methods A multidatabase search was performed. Papers published between January 2005 and June 2016 relevant to mental illness (depression and anxiety only) were extracted and reviewed. Results Positive interactions, social support, and social connectedness on SNSs were consistently related to lower levels of depression and anxiety, whereas negative interaction and social comparisons on SNSs were related to higher levels of depression and anxiety. SNS use related to less loneliness and greater self-esteem and life satisfaction. Findings were mixed for frequency of SNS use and number of SNS friends. Different patterns in the way individuals with depression and individuals with social anxiety engage with SNSs are beginning to emerge. Conclusions The systematic review revealed many mixed findings between depression, anxiety, and SNS use. Methodology has predominantly focused on self-report cross-sectional approaches; future research will benefit from leveraging real-time SNS data over time. The evidence suggests that SNS use correlates with mental illness and well-being; however, whether this effect is beneficial or detrimental depends at least partly on the quality of social factors in the SNS environment. Understanding these relationships will lead to better utilization of SNSs in their potential to positively influence mental health.
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                Author and article information

                Journal
                Cyberpsychology, Behavior, and Social Networking
                Cyberpsychology, Behavior, and Social Networking
                Mary Ann Liebert Inc
                2152-2715
                2152-2723
                July 2018
                July 2018
                : 21
                : 7
                : 437-443
                Affiliations
                [1 ]Center for Research on Media, Technology, and Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
                [2 ]Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
                [3 ]Health Policy Institute, University of Pittsburgh, Pittsburgh, Pennsylvania.
                [4 ]Department of Communication Studies, West Virginia University, Morgantown, West Virginia.
                [5 ]Division of Adolescent Medicine, Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
                Article
                10.1089/cyber.2017.0668
                29995530
                23d0cc0a-e732-4986-818f-bff6afe286bd
                © 2018

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