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      Predictors and patterns of problematic Internet game use using a decision tree model

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          Abstract

          Background and aims

          Problematic Internet game use is an important social issue that increases social expenditures for both individuals and nations. This study identified predictors and patterns of problematic Internet game use.

          Methods

          Data were collected from online surveys between November 26 and December 26, 2014. We identified 3,881 Internet game users from a total of 5,003 respondents. A total of 511 participants were assigned to the problematic Internet game user group according to the Diagnostic and Statistical Manual of Mental Disorders Internet gaming disorder criteria. From the remaining 3,370 participants, we used propensity score matching to develop a normal comparison group of 511 participants. In all, 1,022 participants were analyzed using the chi-square automatic interaction detector (CHAID) algorithm.

          Results

          According to the CHAID algorithm, six important predictors were found: gaming costs (50%), average weekday gaming time (23%), offline Internet gaming community meeting attendance (13%), average weekend and holiday gaming time (7%), marital status (4%), and self-perceptions of addiction to Internet game use (3%). In addition, three patterns out of six classification rules were explored: cost-consuming, socializing, and solitary gamers.

          Conclusion

          This study provides direction for future work on the screening of problematic Internet game use in adults.

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          Most cited references 48

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          An international consensus for assessing internet gaming disorder using the new DSM-5 approach.

          For the first time, the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) introduces non-substance addictions as psychiatric diagnoses. The aims of this paper are to (i) present the main controversies surrounding the decision to include internet gaming disorder, but not internet addiction more globally, as a non-substance addiction in the research appendix of the DSM-5, and (ii) discuss the meaning behind the DSM-5 criteria for internet gaming disorder. The paper also proposes a common method for assessing internet gaming disorder. Although the need for common diagnostic criteria is not debated, the existence of multiple instruments reflect the divergence of opinions in the field regarding how best to diagnose this condition. We convened international experts from European, North and South American, Asian and Australasian countries to discuss and achieve consensus about assessing internet gaming disorder as defined within DSM-5. We describe the intended meaning behind each of the nine DSM-5 criteria for internet gaming disorder and present a single item that best reflects each criterion, translated into the 10 main languages of countries in which research on this condition has been conducted. Using results from this cross-cultural collaboration, we outline important research directions for understanding and assessing internet gaming disorder. As this field moves forward, it is critical that researchers and clinicians around the world begin to apply a common methodology; this report is the first to achieve an international consensus related to the assessment of internet gaming disorder. © 2014 Society for the Study of Addiction.
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            The association between internet addiction and psychiatric co-morbidity: a meta-analysis

            Background This study evaluates the association between Internal Addiction (IA) and psychiatric co-morbidity in the literature. Methods Meta-analyses were conducted on cross-sectional, case–control and cohort studies which examined the relationship between IA and psychiatric co-morbidity. Selected studies were extracted from major online databases. The inclusion criteria are as follows: 1) studies conducted on human subjects; 2) IA and psychiatric co-morbidity were assessed by standardised questionnaires; and 3) availability of adequate information to calculate the effect size. Random-effects models were used to calculate the aggregate prevalence and the pooled odds ratios (OR). Results Eight studies comprising 1641 patients suffering from IA and 11210 controls were included. Our analyses demonstrated a significant and positive association between IA and alcohol abuse (OR = 3.05, 95% CI = 2.14-4.37, z = 6.12, P < 0.001), attention deficit and hyperactivity (OR = 2.85, 95% CI = 2.15-3.77, z = 7.27, P < 0.001), depression (OR = 2.77, 95% CI = 2.04-3.75, z = 6.55, P < 0.001) and anxiety (OR = 2.70, 95% CI = 1.46-4.97, z = 3.18, P = 0.001). Conclusions IA is significantly associated with alcohol abuse, attention deficit and hyperactivity, depression and anxiety.
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              Psychosocial causes and consequences of pathological gaming

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                Author and article information

                Journal
                jba
                JBA
                Journal of Behavioral Addictions
                J Behav Addict
                Akadémiai Kiadó (Budapest )
                2062-5871
                2063-5303
                05 August 2016
                September 2016
                : 5
                : 3
                : 500-509
                Affiliations
                [ 1 ]Department of Medical Informatics, College of Medicine, The Catholic University of Korea , Seoul, Republic of Korea
                [ 2 ]Catholic Institute for Healthcare Management and Graduate School of Healthcare Management and Policy, The Catholic University of Korea , Seoul, Republic of Korea
                [ 3 ]Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea , Seoul, Republic of Korea
                Author notes
                [* ]Corresponding authors: Dai-Jin Kim, PhD; Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; Phone: +82 2 2258 6086; Fax: +82 2 594 3870; E-mail: kdj922@ 123456catholic.ac.kr ; In Young Choi, PhD; Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; Phone: +82 2 2258 7870; Fax: +82 2 2258 8257; E-mail: iychoi@ 123456catholic.ac.kr
                Article
                10.1556/2006.5.2016.051
                5264417
                27499227
                © 2016 The Author(s)

                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.

                Page count
                Figures: 2, Tables: 5, Equations: 0, References: 52, Pages: 10
                Funding
                Funding sources: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014M3C7A1062893).
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