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      Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S. Adolescents After 2010 and Links to Increased New Media Screen Time

      1 , 2 , 2 , 1
      Clinical Psychological Science
      SAGE Publications

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          The need to belong: Desire for interpersonal attachments as a fundamental human motivation.

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            The interpersonal theory of suicide.

            Suicidal behavior is a major problem worldwide and, at the same time, has received relatively little empirical attention. This relative lack of empirical attention may be due in part to a relative absence of theory development regarding suicidal behavior. The current article presents the interpersonal theory of suicidal behavior. We propose that the most dangerous form of suicidal desire is caused by the simultaneous presence of two interpersonal constructs-thwarted belongingness and perceived burdensomeness (and hopelessness about these states)-and further that the capability to engage in suicidal behavior is separate from the desire to engage in suicidal behavior. According to the theory, the capability for suicidal behavior emerges, via habituation and opponent processes, in response to repeated exposure to physically painful and/or fear-inducing experiences. In the current article, the theory's hypotheses are more precisely delineated than in previous presentations (Joiner, 2005), with the aim of inviting scientific inquiry and potential falsification of the theory's hypotheses. PsycINFO Database Record (c) 2010 APA, all rights reserved.
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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
                Clinical Psychological Science
                Clinical Psychological Science
                SAGE Publications
                2167-7026
                2167-7034
                October 27 2017
                January 2018
                November 14 2017
                January 2018
                : 6
                : 1
                : 3-17
                Affiliations
                [1 ]San Diego State University
                [2 ]Florida State University
                Article
                10.1177/2167702617723376
                54429017-d516-4e4b-97d6-5cf96f1eb210
                © 2018

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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