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      The links between healthy, problematic, and addicted Internet use regarding comorbidities and self-concept-related characteristics

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          Addicted Internet users present with higher rates of comorbidities, e.g., attention-deficit hyperactivity disorder (ADHD), depressive, and anxiety disorders. In addition, deficits in self-concept-related characteristics were found in addicted Internet gamers and social network users. The aim of this study was to examine the links between healthy, problematic, and addicted Internet use regarding comorbidities and self-concept-related characteristics. The association between recently developed ADHD-like symptoms without an underlying diagnosis and addictive Internet use was also examined.


          n = 79 healthy controls, n = 35 problematic, and n = 93 addicted Internet users were assessed for comorbidities, social and emotional competencies, body image, self-esteem, and perceived stress. Apart from an ADHD-diagnosis, recently developed ADHD-like symptoms were also assessed.


          Addicted users showed more self-concept-related deficits and higher rates of comorbidities with ADHD, depressive, and anxiety disorders. Addicted and problematic users showed similarities in the prevalence of cluster B personality disorders and decreased levels of characteristics related to emotional intelligence. Participants with recently developed ADHD-like symptoms scored higher in lifetime and current severity of Internet use compared with those without ADHD symptoms. Addicted participants with recently developed ADHD symptoms showed higher lifetime Internet use severity compared with those without any symptoms.


          Our findings indicate that cluster B personality disorders and premorbid problems in emotional intelligence might present a link between problematic and addictive Internet use. Furthermore, the findings provide a first indication that addictive Internet use is related to ADHD-like symptoms. Symptoms of ADHD should therefore be assessed against the background of possible addicted Internet use.

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          Most cited references 44

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          A cognitive-behavioral model of pathological Internet use

           R.A. Davis (2001)
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            Prevalence and correlates of adult attention-deficit hyperactivity disorder: meta-analysis.

            In spite of the growing literature about adult attention-deficit hyperactivity disorder (ADHD), relatively little is known about the prevalence and correlates of this disorder. To estimate the prevalence of adult ADHD and to identify its demographic correlates using meta-regression analysis. We used the MEDLINE, PsycLit and EMBASE databases as well as hand-searching to find relevant publications. The pooled prevalence of adult ADHD was 2.5% (95% CI 2.1-3.1). Gender and mean age, interacting with each other, were significantly related to prevalence of ADHD. Meta-regression analysis indicated that the proportion of participants with ADHD decreased with age when men and women were equally represented in the sample. Prevalence of ADHD in adults declines with age in the general population. We think, however, that the unclear validity of DSM-IV diagnostic criteria for this condition can lead to reduced prevalence rates by underestimation of the prevalence of adult ADHD.
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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.

                Author and article information

                Journal of Behavioral Addictions
                J Behav Addict
                Akadémiai Kiadó (Budapest )
                14 February 2018
                March 2018
                : 7
                : 1
                : 31-43
                [ 1 ]Medical Faculty Mannheim, Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Heidelberg University , Mannheim, Germany
                [ 2 ]Medical Faculty Mannheim, Department of Biostatistics, Central Institute of Mental Health, Heidelberg University , Mannheim, Germany
                Author notes
                [* ]Corresponding author: Tagrid Leménager, PhD; Medical Faculty Mannheim, Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Heidelberg University, J5 Mannheim D-68159, Germany; Phone: +49 621 1703 3907; Fax: +49 621 1703 3505; E-mail: Tagrid.Lemenager@
                © 2018 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

                Page count
                Figures: 4, Tables: 6, Equations: 0, References: 56, Pages: 13
                Funding sources: This study was supported by the Ministerium für Arbeit und Sozialordnung, Familie, Frauen und Senioren, Baden-Württemberg, Germany (reference number: 55-5072-7.1; PI: Prof. Dr. med. KM and Co-PI: Dr. TL).
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