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  • 1 Masaryk University, Czech Republic
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Background and aims

The present study explores the relationship between social motivations and addiction to online gaming and if that possible connection can be explained by the personality traits responsible for social functioning.

Methods

We employ Bernstein’s concept of interpersonal dependency to distinguish healthy dependency, dysfunctional detachment, and destructive overdependence, and Charlton and Danforth’s conceptualisation of online gaming addiction and high engagement. An online questionnaire was administered to a self-nominated sample of 4,074 online gamers. Two regression models were constructed to separately explain gaming addiction and high engagement using social motivations to play, while controlling for age, gender, and time spent online.

Results

High scores on subscales measuring dysfunctional detachment and destructive overdependence were positively associated with online gaming addiction, while healthy dependency was negatively correlated with addiction scores. In contrast, the overall role of social motivation was negligible.

Discussion

People with healthy relationship profiles are less likely to develop problematic patterns of online gaming. High in-game engagement, although sharing some factors with addiction, was only poorly explained by the study variables, suggesting the mutual exclusiveness of addiction and engagement.

Abstract

Background and aims

The present study explores the relationship between social motivations and addiction to online gaming and if that possible connection can be explained by the personality traits responsible for social functioning.

Methods

We employ Bernstein’s concept of interpersonal dependency to distinguish healthy dependency, dysfunctional detachment, and destructive overdependence, and Charlton and Danforth’s conceptualisation of online gaming addiction and high engagement. An online questionnaire was administered to a self-nominated sample of 4,074 online gamers. Two regression models were constructed to separately explain gaming addiction and high engagement using social motivations to play, while controlling for age, gender, and time spent online.

Results

High scores on subscales measuring dysfunctional detachment and destructive overdependence were positively associated with online gaming addiction, while healthy dependency was negatively correlated with addiction scores. In contrast, the overall role of social motivation was negligible.

Discussion

People with healthy relationship profiles are less likely to develop problematic patterns of online gaming. High in-game engagement, although sharing some factors with addiction, was only poorly explained by the study variables, suggesting the mutual exclusiveness of addiction and engagement.

Introduction

During the last decade and a half, Massive Multiplayer Online Games (MMOGs) have become a significant entertainment medium to which millions of young people devote a large portion of their leisure time (Williams, Yee, & Caplan, 2008). Although mere entertainment and leisure activity for most gamers, a certain proportion report that online gaming took over their lives and caused serious problems in their social or occupational functioning (Haagsma, Pieterse, Peters, & King, 2013). Health-related negative consequences are also among the symptoms of excessive patterns of online gaming and include low quality and quantity of sleep, neglecting meals or poor and unhealthy diet, repetitive strain injuries, etc. (c.f. Kalmus, Siibak, & Blinka, 2014 for an overview). The most excessive players may spend 40 hours or more per week online, which equals or exceeds the amount of time spent in a regular full-time job (Dauriat et al., 2011). Online gaming has been shown to be the riskiest online activity in terms of the development of Internet addiction and related problems (Blinka et al., 2015).

The American Psychiatric Association included Internet Gaming Disorder in Section 3 of its revised diagnostic manual, DSM-5, as a potential future diagnosis that requires further investigation (American Psychiatric Association, 2013). However, whether problematic patterns of online gaming represent a distinct psychiatric condition that belongs among behavioural addictions is not yet a matter of consensus within the scientific community (Griffiths, King, & Demetrovics, 2014). Although Griffiths’ criteria (2005) of behavioural addiction were generally accepted in the research of online gaming addiction, not all criteria were identified as similarly contributing to the increase of pathology. Peripheral criteria (euphoria, cognitive salience, and tolerance), especially when dominantly present without core criteria (behavioural salience, withdrawal symptoms, relapse, and conflict), seem to be signs of non-pathological gaming (Charlton & Danforth, 2004). Such high engagement in online gaming, although extensive at first glance but non-problematic at the second, is not connected to those personality traits which are associated with pathological gaming (Charlton & Danforth, 2007, 2010). This suggests that high engagement and addiction, although overlapping in some symptoms, are rather distinct categories and thus point toward the usefulness of differentiating approaches in measuring Internet gaming addiction. The addictive potential of online games is usually associated with the reward aspects of gaming (King, Delfabbro, & Griffiths, 2011). However, MMOGs are inherently social environments and thus the social aspects of games, the social motivations of gamers, and their sociability may play an important role. As shown by Ng and Wiemer-Hastings (2005), MMOGs are played much more intensively compared to non-MMOGs. The difference is the community – while offline video games are solitary or a small-group activity; thousands of people are online in MMOGs at the same time. MMOGs represent a rich and valued source of social contacts for gamers through in-game interactions, discussion forums, and also communication beyond the gaming tasks (Cole & Griffiths, 2007; Yee, 2006). It has also been reported that collective gaming, necessary for reaching advanced in-game content, leads to more time spent online and may contribute to the development of patterns of compulsive gaming (Haagsma et al., 2013). According to the Social Compensation Hypothesis (Caplan, 2003; Davis, 2001), lonely individuals are especially prone to compulsive Internet use as they seek social support, which they lack in their natural offline environment. Such gamers may then be caught in a vicious circle – with increasing time spent online for in-game social interactions and in-game group commitments, there may follow a negative effect on daily functioning and face-to-face interactions, and the sense of loneliness may worsen (Davis, 2001; Shen & Williams, 2011). From this point of view, the social motivation for gaming (i.e. the seeking of in-game social support) can be expected to contribute to increased addictive gaming. Nevertheless, such a direct relationship has not yet been confirmed. Several studies indicate that this relationship is rather negligible (Blinka & Mikuška, 2014; Caplan, Williams, & Yee, 2009; Dauriat et al., 2011; Kardefelt-Winther, 2014; Király et al., 2015). According to Blinka and Mikuška (2014), a gamer’s social skills and personality traits, such as lower interpersonal trust and lower social self-efficacy, contribute to the development of pathological gaming more than the actual social motivation for gaming. Gamers with schizoid personality traits and higher introversion are reported to be more at risk of problematic online gaming (Kuss & Griffiths, 2012). This finding indicates that the underlying psychological dispositions of individuals may be the key to the relationship between social motivations and online gaming addiction, and to the development of online gaming addiction.

Interpersonal dependency represents a useful concept to study the social traits of gamers in relation to potential pathological game play. The concept itself describes how people rely on others – how their cognition, motivation, affective responses, and actual behavioural patterns are affected by relationships to others (Bornstein, Porcerelli, Huprich, & Markova, 2009). The concept is, to some extent, similar to the concept of attachment; for instance, high levels of interpersonal dependency share some similarities with insecure attachment (Pincus & Wilson, 2001).

Bornstein et al. (2003) divided the idea of interpersonal dependency into a three-dimensional concept. The three dimensions of interpersonal dependency are healthy dependency (confidence and autonomy, desire for closeness, and situation-appropriate help seeking) representing healthy functioning; and two representing dysfunctional functioning – destructive overdependence (characterised by weak self, fear of negative evaluation, and reassurance seeking) and dysfunctional detachment (fear of being hurt, fear of being overwhelmed by others, and consequent need for control over social situations) (Bornstein et al., 2003). Individuals with unhealthy interpersonal dependency traits tend to be more sensitive to peer pressure, less stable in their attitudes and beliefs, and have a more pronounced need for acceptance by others (Bornstein, 2009). These characteristics may be associated with negative consequences and feelings in some social contexts and situations, but may be effective and useful in others.

Destructive overdependence and dysfunctional detachment may underlie the effect of dysregulation in individuals that may, subsequently and reportedly, put individuals at risk of psychological and physiological disease (Fiori, Consedine, & Magai, 2008). Individuals scoring high in interpersonal dependence face more psychological impairment through decreased lower self-esteem and increased depression, loneliness, and overall emotional dysregulation (Overholser, 1992). When observed, the association between interpersonal dependency traits and substance use disorders (e.g. smoking and alcoholism) was generally linked to orally dependent personality features (Greenberg & Bornstein, 1988). The link between dependency traits and the tendency to addictive behavioural patterns might, therefore, lead to the compensation of unsatisfying or imperilling social contacts in real life. Thus, as online games are inherently social environments, we assume that interpersonal dependency and the conceptualizing social orientation of the individual might be a significant factor explaining why some gamers tend to pathological gaming while others do not.

Research Focus and Hypotheses

In the present study we examine social motivations as conscious preferences and personal traits represented by the three dimensions of interpersonal dependency in relationship to highly engaged and addictive gaming.

Based on a literature review we expect the followings:

H1: Social motivations do not play an important role in online gaming addiction, and online gaming addiction is predicted by personality traits related to social functioning. Social situation was expected to contribute to problematic gaming by some researchers (Lemmens, Valkenburg, & Peter, 2011). However, the relationship between online gaming addiction and social motivations, which may be a conscious reflection of the lack of social contact, is not supported in literature.

H1a: Destructive overdependence is positively associated with online gaming addiction. We expect that personal traits associated with orientation towards social commitment and the need for positive feedback from the community may be an important factor that contributes to higher addictive potential in these gamers.

H1b: Dysfunctional detachment is positively associated with online gaming addiction. We expect that the MMOG environments, where it is easy to control social interactions and there is a lack of face-to-face interactions, attract gamers who score high in dysfunctional detachment.

H1c: Healthy dependency is negatively associated with online gaming addiction. We expect that the healthy dependency personality trait, usually associated with healthy social functioning, is negatively associated with online gaming addiction.

H2: High engagement in online gaming is not, in contrast to online gaming addiction, significantly associated with the social motives and psychological traits significant for social functioning. A large number of motives for online gaming has been identified (King et al., 2011; Koo, 2009; Yee, 2006). We assume that intensive yet non-pathological gamers enjoy the game for these various reasons and thus they are not a group with any unified gaming pattern nor psychological trait or distress.

Methods

Participants

The data come from the first wave of a three-wave longitudinal online survey of Internet gaming addiction. A total sample of 6,730 Czech and Slovak online gamers was recruited through advertisement in online gaming magazines, on gaming discussion forums, and on guild websites. The ads targeted the core of the Czech and Slovak gaming community, with heavy players expected to be the highest proportion. Incentives in the form of lottery prizes were used to solicit higher participation. The questionnaire was published in Czech on the Lime Survey platform in the spring of 2013. A subsample of 4,074 players (ages 10–68; M = 20.81, SD = 5.95; 93.50% male) of MMORPG and MOBA games was selected for the analysis, and measurement tools were developed specifically for these types of games. Participants spent between 2 and 92 hours per week playing online games (M = 32.85, SD = 16.72); League of Legends (MOBA, 35.22%) and World of Warcraft (MMORPG, 19.69%) were the most played games in the sample. Female players were significantly older compared to males (Females: M = 21.79, SD = 6.80; Males: M = 20.75, SD = 5.88; p < 0.05); and spent significantly less hours gaming per week (Females: M = 27.85, SD = 15.84; Males: M = 33.20, SD = 16.73; p < 0.001).

Measures

Online gaming addiction was measured using the Addiction-Engagement Questionnaire (AEQ), a 24-item tool with response options on a four-point scale (1 – strongly disagree; 4 – strongly agree). The tool distinguishes between online gaming addiction (12 items) and high engagement in online games (12 items). The addiction subscale focuses on core addiction criteria, such as conflict, behavioural salience, and withdrawal, while the engagement subscale measures peripheral addiction criteria, such as cognitive salience, euphoria, and tolerance (Charlton & Danforth, 2007, 2010). Since the scale was not validated for discriminatory purposes, it is used as a continuum. Both subscales had sufficient internal consistency (Cronbach’s α = 0.79 for addiction and Cronbach’s α = 0.72 for high engagement). We created two new combined variables for addiction and engagement as mean scores of the respective subscales ranging from 1 to 4 (MADD = 1.82, SDADD = 0.49; MENG = 2.50, SDENG = 0.26).

The frequency of online gaming, expressed in weekly playing hours, was constructed as a combined measure using two open-ended questions: “In the last 3 months, how much time (in hours) did you usually spend gaming on a normal working day?” and “In the last 3 months, how much time (in hours) do you usually spend gaming on a day off?” Respondents who did not play in the last three months (i.e. obtained zero in the combined frequency variable) were excluded from the analysis.

To obtain information about game genre, respondents were asked to name a game they played most often in the last three months. Only players of MMORPG and MOBA games were included in the analysis, as the AEQ scale contained some items relevant only to these types of games (i.e. questions on virtual character, levelling, collecting armour, etc.).

Interpersonal dependency was measured using 30 items of the Relationship Profile Test (RPT) (Bornstein, Geiselman, Eisenhart, & Languirand, 2002). The scale distinguishes between destructive overdependence (Cronbach’s α = 0.81), healthy dependence (Cronbach’s α = 0.63), and dysfunctional detachment (Cronbach’s α = 0.67), with 10 items providing answer options ranging from “very true” to “not at all true” and representing each subscale. The three new variables, created as mean scores of each sub-scale, ranged between 1 and 5 (MDO = 2.95, SDDO = 0.75; MHD = 3.63, SDHD = 0.56; MDD = 3.22, SDDD = 0.60).

Social motivations for online gaming were measured using two subscales based on eight items selected from the pool of the most commonly used questionnaires on player’s motivations (Hsu, Wen, & Wu, 2009; Koo, 2009; Yee, 2006). Examples of the items are: “I like talking to other players”; “I enjoy being part of the gaming community”; “I sometimes share worries with other players”; and “I appreciate when fellow players offer support in my real-life situations.” The four-point response scale (strongly disagree – strongly agree) focused on respondents’ attitudes rather than actual behaviour. The exploratory factor analysis showed two factors – team play (five items) and social support (three items). Both scales had sufficient internal consistency (Cronbach’s α = 0.75 for team play and Cronbach’s α = 0.70 for social support). The final variables were created as mean scores of the respective items and ranged between 1 and 4.

Data analysis

Pearson’s correlation coefficients were calculated for addiction, engagement, and all predictors. Two separate regression models were constructed using a stepwise hierarchical linear regression to determine the association between online gaming addiction / engagement and social motivations / interpersonal dependency traits, while controlling for age, gender, frequency of online gaming, and game genre.

Ethics

According to rules of Masaryk University, the study did not require approval of ethical committee. In line with the university’s ethical guidelines (CTT, 2015), details about the study aims, procedures, and the data collected were provided on the first page of the questionnaire. As the participation was solicited via online advertisement and parents of the underage children could not be addressed directly, minors were requested to confirm that they would participate in the survey with parental approval.

Results

Pearson’s correlation coefficients indicate a statistically significant relationship between addiction and all predictors; addiction is negatively correlated with the healthy-dependency-personality trait (r = –0.18, p < 0.01) and age (r = –0.23, p < 0.01). There is no relationship between the motivations for in-game social support and high engagement (r = –0.03, p = 0.07). Time spent online is associated to both addiction (r = –0.34, p < 0.01) and engagement (r = –0.11, p < 0.01), although the effect is stronger for addiction. The association with the negative aspects of interpersonal dependency – destructive overdependence and dysfunctional detachment – is stronger for addiction than for engagement in online gaming. The two negative aspects correlate positively, while there is a negative association with healthy dependency. Healthy dependency is negatively correlated with addiction and positively with both types of social motivations, while there is either no or negligible association between social motivations and negative dependency traits. Team play is negatively associated with both addiction and engagement. The correlation between social support and healthy dependency indicates that these two concepts may be related. The need for in-game social support also increases with age. Table 1 summarizes the results of the correlational analysis.

Table 1.

Correlations of main study variables

(1)(2)(3)(4)(5)(6)(7)(8)(9)
Addiction (1).25**.29**.22**−.18**.10**.13**−.23**.34**
Engagement (2).12**.15**.07**.12**.03−.19**.11**
Destructive overdependence (3).28**−.20**.03.07**−.18**.07**
Dysfunctional detachment (4)−.18**−.19**−.08**.02−.01
Healthy dependency (5).27**.19**.00−.03
Team play (6).49**−.23**.19**
Social support (7)−.06**.15**
Age (8).21**
Frequency of gaming (9)

Note: **p < .01

Table 2 shows three linear regression models explaining online gaming addiction by using the main interpersonal dependency subscales and social motivations. It confirms that the negative aspects of interpersonal dependency are positive predictors for online gaming addiction (hypotheses H1a and H1b), while there is a significant negative association with healthy dependency (hypothesis H1c). The main effect of social motivation is small and has only a limited impact on the relationship between addiction and interpersonal dependency. Adding interpersonal dependency variables into the model reduces the effect of social motivations; team play, particularly, becomes non-significant in the third regression step. Overall, the final model explains 25% of the variance of online gaming addiction. Thus, we consider the whole hypothesis H1 as confirmed.

Table 2.

Linear regression models for online gaming addiction (method: stepwise)

Model 1Model 2Model 3
bβSig.bβSig.bβSig.
Constant1.81<.011.81<.011.14<.01
Gender (Female = 1, Male = 2)−0.04−0.020.17−0.03−0.020.28−0.010.000.79
Age−0.01−0.14<.01−0.01−0.15<.01−0.01−0.10<.01
Frequency of gaming0.010.30<.010.010.29<.010.010.27<.01
Genre (MMORPG = 0, MOBA = 1)0.080.08<.010.080.08<.010.080.09<.01
Team play (TP)−0.05−0.06<.010.020.020.26
Social support (SS)0.060.10<.010.060.09<.01
Destructive overdependence (DO)0.110.17<.01
Dysfunctional detachment (DD)0.140.17<.01
Healthy dependence (HD)−0.11−0.13<.01
F146.75104.12131.50
P<.001<.001<.001
R Square0.140.150.25

Table 3 shows similar models for engagement to online games as a dependent variable; the effect of the predictors is less pronounced and the final model explains only 8% of the variance of online gaming engagement. Contrary to online gaming addiction, adding dependency traits into the model slightly increased the effect of social motivations in the final model. The need for social support is a positive predictor for online gaming addiction patterns, but it is negatively associated with high engagement and this effect, although small, remains significant despite the interpersonal dependency traits in the final model. Thus, we cannot fully support hypothesis H2 – the associations are opposite in comparison to addiction; however, small but significant association with social motivation and interpersonal dependency traits still exist.

Table 3.

Linear regression models for high engagement in online gaming (method: stepwise)

Model 1Model 2Model 3
bβSig.bβSig.bβSig.
Constant2.59<.012.50<.012.01<.01
Gender (Female = 1, Male = 2)0.000.000.870.000.000.800.000.000.89
Age−0.01−0.16<.01−0.01−0.14<.01−0.01−0.13<.01
Frequency of gaming0.000.09<.010.000.08<.010.000.08<.01
Genre (MMORPG = 0, MOBA = 1)0.010.030.140.010.020.250.020.030.09
Team play (TP)0.040.09<.010.040.10<.01
Social support (SS)−0.01−0.040.03−0.02−0.06<.01
Destructive overdependence (DO)0.020.07<.01
Dysfunctional detachment (DD)0.070.17<.01
Healthy dependence (HD)0.040.10<.01
F37.0728.0136.38
P<0.001<0.001<0.001
R Square0.040.040.08

Discussion

The present study confirmed that interpersonal dependency traits are crucial in developing addictive behaviours discounting from the social motivation factors. Both, dysfunctional detachment and destructive overdependence increase the online gaming addiction score, while healthy dependency is associated with lower addiction scores. The relationship between various addictions and overdependence has been reported in literature (Loas et al., 2005) and our study extends the evidence of its relationship to online gaming addiction. It must be noted that dysfunctional detachment and destructive overdependence are not mutually distinct categories. On the contrary, they are often found together (Bornstein et al., 2003, 2009) and they were also mildly correlated in our research. In the case of online gaming, that means that some of the pathological gamers may use MMOGs as an escape to a more secure and controlled social environment and, at the same time, seek the social support and recognition of fellow gamers. A concept very closely related to healthy dependency is connectedness (Bornstein, 2009). Decreased connectedness has been reported to be associated with increased general problematic Internet use (McIntyre, Wiener, & Saliba, 2015). Our final model explaining the 25% variance of online gaming addiction is completed with demographic- and gaming-style variables – gender does not play a role, while younger gamers (those preferring the MOBA genre to MMORPG and those spending more time in the game) seem to be more susceptible. While the facts that younger gamers are more at risk of gaming addiction and that the gender effect is rather negligible have been shown in literature (Caplan et al., 2009), the change in the effect of the game genre is new information. Traditionally, MMORPGs like World of Warcraft were shown to be the environment which tended to attract or produce problematic gaming patterns. The fact that the newly emerging MOBA genre even surpasses the MMORPGs should be further investigated together with other possible emerging trends in the gaming industry.

High involvement in online gaming, on the other hand, is less connected to the psychological underpinning of impairments in interpersonal relationships and can be seen more as controlled, although time-consuming, behaviour. This suggests that highly engaged and addicted gamers are a qualitatively distinct category and that they differ not only in the mere quantity of the activity. Such a result is in line with the previous findings of Charlton and Danforth (2010) and gives support to the approach of measuring Internet gaming addiction that distinguishes types of involvement. Our model combines demographic variables, personality traits, and social motivation for gaming, and explained only 8% of the variance of engagement points to online gaming as an entertaining activity, which is not necessary to problematize. Similar results have been reported elsewhere, though different methods were used (e.g. Griffiths, 2010; Király et al., 2015).

Healthy dependency is positively associated with both types of social motivation, while there is a negligible relationship between social motives and destructive overdependence, and a negative relationship between social motives and dysfunctional detachment. Social motives, therefore, prevail in people who show a healthy need for social contact, and online games are efficient sources for social interaction. For some authors, motivations to play represent conscious choices that are key to understanding the etiology of excessive patterns of online gaming (Kardelfelt-Winther, 2014). In this view, the problematic patterns of online gaming are not understood as addiction but rather as maladaptive coping strategies. This approach, however, does not explain why only a few of those who report similar motivations to online gaming find themselves hooked on the game, and why some develop extreme symptoms of addiction that lead to neglecting basic drives. Our analysis indicates that this view may be correct in terms of high involvement in online gaming, but when it comes to loss of control, psychological factors play a role in the subsequent development of the pathology. Billieux et al. (2015) report similar results when demonstrating that social motivations are more typical for regulated role-play gamers than for hard-core and unregulated players. Indeed, online gaming addiction has been repeatedly shown to be associated with motives for immersion and escapism and with achieving better in-game content and rewards (e.g. King et al., 2011; Király et al., 2015; Kirby, Jones, & Copello, 2014).

A stronger relationship also exists between the time spent playing and online gaming addiction than with time spent playing and high engagement. This finding suggests that highly engaged gamers may have a sense for balance and can effectively control the impact of gaming on their real-life affairs. Psychological dispositions, then, are the underlying cause for reduced self-control and, subsequently, of disproportionate time spent online. This would be in line with research showing that disinhibition may manifest itself only in certain contexts, while in other situations individuals may perform normally and show sufficient levels of self-control (Hofmann, Friese, & Strack, 2009). The lack of self-control in online gaming might piggyback on unrelated psychological discomfort, in this case as unsatisfying social contacts as a result of unhealthy interpersonal dependency traits.

The limitations of this study are associated with the fact that, unlike interpersonal dependency traits, motivations to play and the level of involvement in online gaming may vary over time. The cross-sectional nature of the present study, therefore, cannot capture the whole complexity of the relationships delineated earlier in this text. It should also be acknowledged that our data come from a non-representative, self-selected sample of Czech and Slovak online gamers. However, this fact should not compromise the correlational analysis (Gosling, Vazire, Srivastava, & John, 2004).

Online gaming addiction, distinguished here from high engagement in online gaming, is not a medical diagnosis and should be interpreted with regard to the respective measurement instrument. The addiction subscale of the AEQ stresses those symptoms of addictive behaviours that either represent various types of present conflict or factors that may directly lead to one (i.e. behavioural salience, relapse, and reinstatement) (Charlton & Danforth, 2007). We, therefore, cannot claim that negative interpersonal dependency traits are predictors of addiction, but they certainly are associated with such patterns of online gaming that put an individual at risk of adverse consequences in many areas of life. People with healthy relationship profiles are less likely to develop these problematic patterns of online gaming.

Authors’ contribution

Drafting paper (KS, LB), study concept and design (LB), data preparation (KS), statistical analysis (KS), interpretation of data (LB, KS). All authors had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Conflict of interest

The authors declare no conflict of interest.

References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

  • Billieux, J., Thorens, G., Khazaal, Y., Zullino, D., Achab, S., & Van der Linden, M. (2015). Problematic involvement in online games: A cluster analytic approach. Computers in Human Behavior, 43, 242250. doi: 10.1016/j.chb.2014.10.055

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blinka, L., & Mikuška, J. (2014). The role of social motivation and sociability of gamers in online game addiction. Cyberpsychology, 8(2), Article 6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blinka, L., Škařupová, K., Ševčíková, A., Wölfling, K., Müller, K. W., & Dreier, M. (2015). Excessive Internet use in European adolescents: What determines differences in severity? International Journal of Public Health, 60, 249256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F. (2009). Interpersonal dependency. In Leary, M. R., & Hoyle, R. H. (Eds.), Handbook of individual differences in social behavior (pp. 8292). New York: Guilford Press.

    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Geiselman, K. J., Eisenhart, E. A., & Languirand, M. A. (2002). Construct validity of the Relationship Profile Test: Links with attachment, identity, relatedness, and affect. Assessment, 9(4), 373381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Languirand, M. A., Geiselman, K. J., Creighton, J. A., West, M. A., Gallagher, H. A., & Eisenhart, E. A. (2003). Construct validity of the Relationship Profile Test: A self-report measure of dependency-detachment. Journal of Personality Assessment, 80(1), 6474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Porcerelli, J. H., Huprich, S. K., & Markova, T.(2009). Construct validity of the relationship profile test: Correlates of overdependence, detachment, and healthy dependency in low income urban women seeking medical services. Journal of Personality Assessment, 91(6), 537544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and psychosocial well-being among MMO players. Computers in Human Behavior, 25(6), 13121319.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caplan, S. E. (2003). Preference for online social interaction: A theory of problematic Internet use and psychosocial well-being. Communication Research, 30(6), 625648.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2004). Differentiating computer-related addictions and high engagement. Human Perspectives in the Internet Society: Culture, Psychology and Gender, 4, 5968.

    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behavior, 23(3), 15311548.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2010). Validating the distinction between computer addiction and engagement: Online game playing and personality. Behaviour & Information Technology, 29(6), 601613.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers. CyberPsychology & Behavior, 10(4), 575583.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CTT. (2015). Nakládání s výzkumnými daty na Masarykově univerzitě: Centrum pro transfer technologií, Masarykova univerzita.

  • Dauriat, F. Z., Zermatten, A., Billieux, J., Thorens, G., Bondolfi, G., Zullino, D., & Khazaal, Y. (2011). Motivations to play specifically predict excessive involvement in massively multiplayer online role-playing games: Evidence from an online survey. European Addiction Research, 17(4), 185189.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187195.

  • Fiori, K., Consedine, N., & Magai, C. (2008). The adaptive and maladaptive faces of dependency in later life: Links to physical and psychological health outcomes. Aging and Mental Health, 12(6), 700712.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gosling, S. D., Vazire, S., Srivastava, S., & John, O. P. (2004). Should we trust web-based studies? A comparative analysis of six preconceptions about Internet questionnaires. American Psychologist, 59(2), 93.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Greenberg, R. P., & Bornstein, R. F. (1988). The dependent personality: II. Risk for psychological disorders. Journal of Personality Disorders, 2(2), 136143.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191197. doi: 10.1080/14659890500114359

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D. (2010). The role of context in online gaming excess and addiction: Some case study evidence. International Journal of Mental Health and Addiction, 8(1), 119125.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D., King, D. L., & Demetrovics, Z. (2014). DSM-5 Internet gaming disorder needs a unified approach to assessment. Neuropsychiatry, 4(1), 14. doi: 10.2217/npy.13.82

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haagsma, M. C., Pieterse, M. E., Peters, O., & King, D. L. (2013). How gaming may become a problem: A qualitative analysis of the role of gaming related experiences and cognitions in the development of problematic game behavior. International Journal of Mental Health and Addiction, 11(4), 441452.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162176.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, S. H., Wen, M.-H., & Wu, M.-C. (2009). Exploring user experiences as predictors of MMORPG addiction. Computers & Education, 53(3), 990999.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalmus, V., Siibak, A., & Blinka, L. (2014). Internet and child well-being. In Ben-Arieh, A., Frønes, I., Casas, F., & Korbin, J. E. (Eds.), Handbook of Child Well-Being (pp. 20932133). Dordrech: Springer.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kardefelt-Winther, D. (2014). A conceptual and methodological critique of Internet addiction research: Towards a model of compensatory Internet use. Computers in Human Behavior, 31, 351354.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2011). The role of structural characteristics in problematic video game play: An empirical study. International Journal of Mental Health and Addiction, 9(3), 320333.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Király, O., Urbán, R., Griffiths, M. D., Ágoston, C., Nagygyörgy, K., Kökönyei, G., & Demetrovics, Z. (2015). The mediating effect of gaming motivation between psychiatric symptoms and problematic online gaming: An online survey. Journal of Medical Internet Research, 17(4), e88.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirby, A., Jones, C., & Copello, A. (2014). The impact of massively multiplayer online role playing games (MMORPGs) on psychological wellbeing and the role of play motivations and problematic use. International Journal of Mental Health and Addiction, 12(1), 3651.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koo, D.-M. (2009). The moderating role of locus of control on the links between experiential motives and intention to play online games. Computers in Human Behavior, 25(2), 466474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuss, D., & Griffiths, M. (2012). Internet gaming addiction: A systematic review of empirical research. International Journal of Mental Health & Addiction, 10(2), 278296. doi: 10.1007/s11469-011-9318-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and consequences of pathological gaming. Computers in Human Behavior, 27(1), 144152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loas, G., Guilbaud, O., Perez-Diaz, F., Verrier, A., Stephan, P., Lang, F., Bizouard, P., Venisse, J. L., Corcos, M., Flament, M. F., & Jeammet, P. (2005). Dependency and suicidality in addictive disorders. Psychiatry Research, 137(1), 103111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McIntyre, E., Wiener, K. K., & Saliba, A. J. (2015). Compulsive Internet use and relations between social connectedness, and introversion. Computers in Human Behavior, 48, 569574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ng, B. D., & Wiemer-Hastings, P. (2005). Addiction to the Internet and online gaming. CyberPsychology & Behavior, 8(2), 110113.

  • Overholser, J. C. (1992). Interpersonal dependency and social loss. Personality and Individual Differences, 13(1), 1723.

  • Pincus, A. L., & Wilson, K. R. (2001). Interpersonal variability in dependent personality. Journal of Personality, 69(2), 223251.

  • Shen, C., & Williams, D. (2011). Unpacking time online: Connecting Internet and massively multiplayer online game use with psychosocial well-being. Communication Research, 38(1), 123149.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, D., Yee, N., & Caplan, S. E. (2008). Who plays, how much, and why? Debunking the stereotypical gamer profile. Journal of Computer Mediated Communication, 13(4), 9931018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6), 772775.

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.

  • Billieux, J., Thorens, G., Khazaal, Y., Zullino, D., Achab, S., & Van der Linden, M. (2015). Problematic involvement in online games: A cluster analytic approach. Computers in Human Behavior, 43, 242250. doi: 10.1016/j.chb.2014.10.055

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blinka, L., & Mikuška, J. (2014). The role of social motivation and sociability of gamers in online game addiction. Cyberpsychology, 8(2), Article 6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blinka, L., Škařupová, K., Ševčíková, A., Wölfling, K., Müller, K. W., & Dreier, M. (2015). Excessive Internet use in European adolescents: What determines differences in severity? International Journal of Public Health, 60, 249256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F. (2009). Interpersonal dependency. In Leary, M. R., & Hoyle, R. H. (Eds.), Handbook of individual differences in social behavior (pp. 8292). New York: Guilford Press.

    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Geiselman, K. J., Eisenhart, E. A., & Languirand, M. A. (2002). Construct validity of the Relationship Profile Test: Links with attachment, identity, relatedness, and affect. Assessment, 9(4), 373381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Languirand, M. A., Geiselman, K. J., Creighton, J. A., West, M. A., Gallagher, H. A., & Eisenhart, E. A. (2003). Construct validity of the Relationship Profile Test: A self-report measure of dependency-detachment. Journal of Personality Assessment, 80(1), 6474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bornstein, R. F., Porcerelli, J. H., Huprich, S. K., & Markova, T.(2009). Construct validity of the relationship profile test: Correlates of overdependence, detachment, and healthy dependency in low income urban women seeking medical services. Journal of Personality Assessment, 91(6), 537544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caplan, S., Williams, D., & Yee, N. (2009). Problematic Internet use and psychosocial well-being among MMO players. Computers in Human Behavior, 25(6), 13121319.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caplan, S. E. (2003). Preference for online social interaction: A theory of problematic Internet use and psychosocial well-being. Communication Research, 30(6), 625648.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2004). Differentiating computer-related addictions and high engagement. Human Perspectives in the Internet Society: Culture, Psychology and Gender, 4, 5968.

    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2007). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behavior, 23(3), 15311548.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton, J. P., & Danforth, I. D. (2010). Validating the distinction between computer addiction and engagement: Online game playing and personality. Behaviour & Information Technology, 29(6), 601613.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers. CyberPsychology & Behavior, 10(4), 575583.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CTT. (2015). Nakládání s výzkumnými daty na Masarykově univerzitě: Centrum pro transfer technologií, Masarykova univerzita.

  • Dauriat, F. Z., Zermatten, A., Billieux, J., Thorens, G., Bondolfi, G., Zullino, D., & Khazaal, Y. (2011). Motivations to play specifically predict excessive involvement in massively multiplayer online role-playing games: Evidence from an online survey. European Addiction Research, 17(4), 185189.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human Behavior, 17(2), 187195.

  • Fiori, K., Consedine, N., & Magai, C. (2008). The adaptive and maladaptive faces of dependency in later life: Links to physical and psychological health outcomes. Aging and Mental Health, 12(6), 700712.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gosling, S. D., Vazire, S., Srivastava, S., & John, O. P. (2004). Should we trust web-based studies? A comparative analysis of six preconceptions about Internet questionnaires. American Psychologist, 59(2), 93.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Greenberg, R. P., & Bornstein, R. F. (1988). The dependent personality: II. Risk for psychological disorders. Journal of Personality Disorders, 2(2), 136143.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. (2005). A ‘components’ model of addiction within a biopsychosocial framework. Journal of Substance Use, 10(4), 191197. doi: 10.1080/14659890500114359

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D. (2010). The role of context in online gaming excess and addiction: Some case study evidence. International Journal of Mental Health and Addiction, 8(1), 119125.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D., King, D. L., & Demetrovics, Z. (2014). DSM-5 Internet gaming disorder needs a unified approach to assessment. Neuropsychiatry, 4(1), 14. doi: 10.2217/npy.13.82

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haagsma, M. C., Pieterse, M. E., Peters, O., & King, D. L. (2013). How gaming may become a problem: A qualitative analysis of the role of gaming related experiences and cognitions in the development of problematic game behavior. International Journal of Mental Health and Addiction, 11(4), 441452.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162176.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, S. H., Wen, M.-H., & Wu, M.-C. (2009). Exploring user experiences as predictors of MMORPG addiction. Computers & Education, 53(3), 990999.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalmus, V., Siibak, A., & Blinka, L. (2014). Internet and child well-being. In Ben-Arieh, A., Frønes, I., Casas, F., & Korbin, J. E. (Eds.), Handbook of Child Well-Being (pp. 20932133). Dordrech: Springer.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kardefelt-Winther, D. (2014). A conceptual and methodological critique of Internet addiction research: Towards a model of compensatory Internet use. Computers in Human Behavior, 31, 351354.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2011). The role of structural characteristics in problematic video game play: An empirical study. International Journal of Mental Health and Addiction, 9(3), 320333.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Király, O., Urbán, R., Griffiths, M. D., Ágoston, C., Nagygyörgy, K., Kökönyei, G., & Demetrovics, Z. (2015). The mediating effect of gaming motivation between psychiatric symptoms and problematic online gaming: An online survey. Journal of Medical Internet Research, 17(4), e88.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirby, A., Jones, C., & Copello, A. (2014). The impact of massively multiplayer online role playing games (MMORPGs) on psychological wellbeing and the role of play motivations and problematic use. International Journal of Mental Health and Addiction, 12(1), 3651.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koo, D.-M. (2009). The moderating role of locus of control on the links between experiential motives and intention to play online games. Computers in Human Behavior, 25(2), 466474.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuss, D., & Griffiths, M. (2012). Internet gaming addiction: A systematic review of empirical research. International Journal of Mental Health & Addiction, 10(2), 278296. doi: 10.1007/s11469-011-9318-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lemmens, J. S., Valkenburg, P. M., & Peter, J. (2011). Psychosocial causes and consequences of pathological gaming. Computers in Human Behavior, 27(1), 144152.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loas, G., Guilbaud, O., Perez-Diaz, F., Verrier, A., Stephan, P., Lang, F., Bizouard, P., Venisse, J. L., Corcos, M., Flament, M. F., & Jeammet, P. (2005). Dependency and suicidality in addictive disorders. Psychiatry Research, 137(1), 103111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McIntyre, E., Wiener, K. K., & Saliba, A. J. (2015). Compulsive Internet use and relations between social connectedness, and introversion. Computers in Human Behavior, 48, 569574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ng, B. D., & Wiemer-Hastings, P. (2005). Addiction to the Internet and online gaming. CyberPsychology & Behavior, 8(2), 110113.

  • Overholser, J. C. (1992). Interpersonal dependency and social loss. Personality and Individual Differences, 13(1), 1723.

  • Pincus, A. L., & Wilson, K. R. (2001). Interpersonal variability in dependent personality. Journal of Personality, 69(2), 223251.

  • Shen, C., & Williams, D. (2011). Unpacking time online: Connecting Internet and massively multiplayer online game use with psychosocial well-being. Communication Research, 38(1), 123149.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, D., Yee, N., & Caplan, S. E. (2008). Who plays, how much, and why? Debunking the stereotypical gamer profile. Journal of Computer Mediated Communication, 13(4), 9931018.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6), 772775.

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Dr. Zsolt Demetrovics
Institute of Psychology, ELTE Eötvös Loránd University
Address: Izabella u. 46. H-1064 Budapest, Hungary
Phone: +36-1-461-2681
E-mail: jba@ppk.elte.hu

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2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
Citation Indicator   
Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
Journal Rank
Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
Scite Score  
Scopus Clinical Psychology 7/283 (Q1)
Scite Score Rank Psychiatry and Mental Health 22/502 (Q1)
Scopus 2,026
SNIP  
Days from  38
sumbission  
to 1st decision  
Days from  37
acceptance  
to publication  
Acceptance 31%
Rate  

2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 850 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
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Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
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Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Publication
Programme
2021 Volume 10
Volumes
per Year
1
Issues
per Year
4
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • Anikó MARÁZ (Humboldt University of Berlin, Germany)
  • Astrid MÜLLER (Hannover Medical School, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)
  • Attila SZABÓ (ELTE Eötvös Loránd University, Hungary)
  • Róbert URBÁN (ELTE Eötvös Loránd University, Hungary)
  • Aviv M. WEINSTEIN (Ariel University, Israel)

Editorial Board

  • Max W. ABBOTT (Auckland University of Technology, New Zealand)
  • Elias N. ABOUJAOUDE (Stanford University School of Medicine, USA)
  • Hojjat ADELI (Ohio State University, USA)
  • Alex BALDACCHINO (University of Dundee, United Kingdom)
  • Alex BLASZCZYNSKI (University of Sidney, Australia)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Beáta BÖTHE (University of Montreal, Canada)
  • Wim VAN DEN BRINK (University of Amsterdam, The Netherlands)
  • Gerhard BÜHRINGER (Technische Universität Dresden, Germany)
  • Sam-Wook CHOI (Eulji University, Republic of Korea)
  • Damiaan DENYS (University of Amsterdam, The Netherlands)
  • Jeffrey L. DEREVENSKY (McGill University, Canada)
  • Naomi FINEBERG (University of Hertfordshire, United Kingdom)
  • Marie GRALL-BRONNEC (University Hospital of Nantes, France)
  • Jon E. GRANT (University of Minnesota, USA)
  • Mark GRIFFITHS (Nottingham Trent University, United Kingdom)
  • Heather HAUSENBLAS (Jacksonville University, USA)
  • Tobias HAYER (University of Bremen, Germany)
  • Susumu HIGUCHI (National Hospital Organization Kurihama Medical and Addiction Center, Japan)
  • David HODGINS (University of Calgary, Canada)
  • Eric HOLLANDER (Albert Einstein College of Medicine, USA)
  • Jaeseung JEONG (Korea Advanced Institute of Science and Technology, Republic of Korea)
  • Yasser KHAZAAL (Geneva University Hospital, Switzerland)
  • Orsolya KIRÁLY (Eötvös Loránd University, Hungary)
  • Emmanuel KUNTSCHE (La Trobe University, Australia)
  • Hae Kook LEE (The Catholic University of Korea, Republic of Korea)
  • Michel LEJOXEUX (Paris University, France)
  • Anikó MARÁZ (Eötvös Loránd University, Hungary)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Frederick GERARD MOELLER (University of Texas, USA)
  • Daniel Thor OLASON (University of Iceland, Iceland)
  • Nancy PETRY (University of Connecticut, USA)
  • Bettina PIKÓ (University of Szeged, Hungary)
  • Afarin RAHIMI-MOVAGHAR (Teheran University of Medical Sciences, Iran)
  • József RÁCZ (Hungarian Academy of Sciences, Hungary)
  • Rory C. REID (University of California Los Angeles, USA)
  • Marcantanio M. SPADA (London South Bank University, United Kingdom)
  • Daniel SPRITZER (Study Group on Technological Addictions, Brazil)
  • Dan J. STEIN (University of Cape Town, South Africa)
  • Sherry H. STEWART (Dalhousie University, Canada)
  • Attila SZABÓ (Eötvös Loránd University, Hungary)
  • Ferenc TÚRY (Semmelweis University, Hungary)
  • Alfred UHL (Austrian Federal Health Institute, Austria)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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