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Richard J. E. James School of Psychology, University of Nottingham, University Park, Nottingham, UK

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Richard J. Tunney School of Psychology, University of Nottingham, University Park, Nottingham, UK

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In their position paper, Aarseth et al. (2016) bring to light several timely issues concerning the categorization of gaming disorder as a form of addiction and as a discrete mental disorder. In our commentary, we welcome their caution toward this move and their discussion of the equivocal scientific data in its support and the potential negative consequences for gamers. We suggest that a more heterogeneous approach is required for understanding any behavioral addiction, as concepts from gambling appear to be more relevant for aspects of mobile gaming than for video games more generally. In addition to a greater need for clinical research, we argue that studying gaming at a different level of analysis than the epidemiological study is required to gain a meaningful understanding of the harm video games may or may not entail.

Abstract

In their position paper, Aarseth et al. (2016) bring to light several timely issues concerning the categorization of gaming disorder as a form of addiction and as a discrete mental disorder. In our commentary, we welcome their caution toward this move and their discussion of the equivocal scientific data in its support and the potential negative consequences for gamers. We suggest that a more heterogeneous approach is required for understanding any behavioral addiction, as concepts from gambling appear to be more relevant for aspects of mobile gaming than for video games more generally. In addition to a greater need for clinical research, we argue that studying gaming at a different level of analysis than the epidemiological study is required to gain a meaningful understanding of the harm video games may or may not entail.

Introduction

The open debate paper by Aarseth et al. (2016) raises a number of important difficulties concerning the proposal for a gaming disorder category in the 11th Revision of the International Classification of Diseases (ICD-11), but are also relevant to the existing debate concerning the proposed Internet gaming disorder (IGD) in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). There is a substantial range of conceptual, epidemiological, and nosological concerns highlighted that lead to the compelling conclusion that the introduction of a category of gaming disorder in diagnostic manuals is premature and is liable to be detrimental in understanding the nature of any harm that might be caused by gaming. These concerns are relevant regardless of whether gaming is considered as a whole or for a subset of games, such as with the online/offline distinction in the ICD-11 drafts and ostensibly so in the DSM-5 (although the DSM includes the possibility that offline games could be included in IGD). The debate paper also highlights some of the wider effects that might result from codifying such a disorder, such as moral panics and stigmatization of video gamers, leading to the possibility of changes in public policy. Public concerns about the effects of video games, whether it be aggression, addiction, or other forms of harm are common, but the research is at best equivocal.

The purpose of this commentary is to focus on two issues that arise from the debate letter. Primarily, we argue that the study and diagnosis of behavioral addictions should be determined by a deeper unit of analysis than is currently used, such as the behavioral mechanics of games. We then challenge the assertion that it is problematic to translate concepts from gambling and addictions to the study of video games, discussing this further in relation to the introduction of gambling elements into mobile games. This is likely to be informative in broadening our collective understanding of the impact of video games on people and society, rather than a naïve conception of a behavioral addiction as being merely a compulsive behavior in the absence of a known mechanism for dependence.

A Greater Heterogeneity in Studying Problematic Gaming

The open letter highlights the predominance of gaming research that is (a) typically not substantiated against clinical samples, (b) liable to mischievous responding, and (c) based on potentially erroneous interpretation of large-scale survey data. Building on this, we feel that there is also an absence of research looking in depth at gaming at the product level, with a particular need for research that focuses on the structural and associative aspects of games. For these reasons, we question whether it makes sense to classify video games generally as addictive, and instead recommend that research should look at the problem at a more appropriate level of analysis.

The empirical literature is limited in trying to capture heterogeneity in the design and content of video games, often focusing on sociodemographic predictors of gaming addiction rather than the types of games played or how these are engaged with. Models of IGD (Lee, Lee, & Choo, 2017) have considered differences between genres alongside other outcomes, but these can belie differences in a game’s mechanics. Games within a genre may have substantially different mechanisms of play, either to suit the device the game is played upon or the business model underlying the game. The focus on mechanics and design elements rather than genres to an extent mirrors a similar distinction in the gambling literature between a type of product and its structural features (Griffiths & Auer, 2013), although a larger number of intra-genre differences might be expected. In some cases, there is room for translation from one to the other, as research has experimentally examined the role of near-misses, a feature typically associated with slot machines, in casual puzzle games (Larche, Musielak, & Dixon, 2017). In this case, the translation from gambling to gaming was appropriate, but there is also utility in studying the cognitive and behavioral features included within some gaming mechanics independently of their association with gambling.

An associative-behavioral analysis of potential behavioral addictions is likely to be one of the most fruitful lines of enquiry (James & Tunney, 2017; Robbins & Clark, 2015). In gambling, there has been an effort to understand how the mechanics of gambling play affect behavior simultaneous to the survey-based work that tends to be dominant in the gaming disorder field. Even if the psychometric research is ultimately able to identify a valid construct of gaming disorder, it is intrinsically limited in the conclusions that can be drawn regarding the nature of the addiction or harm that video games may entail. Behavioral research is likely also to complement studies of clinical cases of gaming disorder. Much of the work, when applied to gambling (and in forms to other addictions) has identified differential responding, both in brain and behavior, between disordered and non-disordered individuals. However, a significant proportion of this work has been undertaken not only to understand the relationship between these events and addiction, but the nature of these events themselves.

Such work is also not a prerequisite for identifying video gaming as a potentially addictive behavior, and can be exploratory in studying the effects of mechanics or structural features on behavior. A similar line of thought has been applied to the “gamification” of activities to increase enjoyment of a tedious activity, or to encourage positive behaviors. Many of these include components derived from associative learning alongside an array of psychological techniques (Baranowski, Buday, Thompson, & Baranowski, 2008). Such work can be informative as much as the darker side of video gaming that has been more typically the object of study. From the perspective of the gambling researcher, understanding the behavioral features of games in more depth is useful as the convergence of gaming and gambling goes in both directions. Slot machines in casinos in America are starting to utilize skill-based elements as a means of attracting younger audiences (Parry, 2016). We recommend that research should focus more on different features or mechanics included in games instead of measuring the prevalence and predictors of disorder in the general population.

Mobile Gaming and Pathological Gambling Criteria

The recommendations of Aarseth et al.’s (2016) paper are important for determining the appropriate diagnostic criteria for a gaming disorder. Concerns about some addiction criteria, particularly tolerance and withdrawal, are relevant across analyses of behavioral addictions (Billieux, Schimmenti, Khazaal, Maurage, & Heeren, 2015) as well as gaming (Kaptsis, King, Delfabbro, & Gradisar, 2016). However, the call to move away from addiction and specifically gambling may be less beneficial for understanding some forms of play more than others. The increasing use of gambling mechanics and themes in mobile play leads itself toward a sustained, gambling-informed analysis that is less advisable in other domains of gaming or behavioral addiction.

It is important to emphasize that in referring to “mobile” gaming, we do not attempt to distinguish between modalities of play in the manner that has been common, for example, between “online” and “offline” games. This approach underlies both the DSM-5 and ICD-11 proposals for a gaming disorder, and is in our view, unhelpful. In the time between initial formulations of gaming in Internet addiction (Young, 1998) and its codification in the DSM (American Psychiatric Association, 2013), changes in the video gaming market have meant that a much wider spread of games are now online-focused, meaning whatever discriminant validity this term had is vestigial. We instead refer to a subset of games that have a common clustering of mechanisms and business models that have become prevalent on mobile devices. What appears to be common among these is a reliance on principles derived from behavioral psychology, including the use of random ratio schedules of reinforcement alongside gambling themes, different types of reinforcement (e.g., achievements/badges) and the use of stamina-style systems to affect how frequently reinforcement is delivered (James, O’Malley, & Tunney, 2017; Larche et al., 2017). These make heavy use of micro-transactions, often based on the premise that a small proportion of users, colloquially referred to as “whales” (Alha, Koskinen, Paavilainen, Hamari, & Kinnunen, 2014; Kimppa, Heimo, & Harviainen, 2016), engage in substantial spending (Garfield, 2016). These are not limited to mobile games, with similar mechanics being used in some console or PC games. Much of the criticism of these models comes from video gamers and developers themselves, with a focus on their exploitative nature, referring to these games as “Skinnerware” for their overt basis in conditioning and associative learning (Garfield, 2016).

These types of activity have been partially explored in the existing literature, which has looked at social gambling or social casino games (Gainsbury et al., 2015; Parke, Wardle, Rigbye, & Parke, 2012). However, this research has tended to focus on games that are primarily gambling-based (i.e., stand-alone casino apps or on social media) or contain an explicit gambling element that is ring-fenced from the primary content of the game (Gainsbury, Russell, & Hing, 2014) or a side game (Griffiths, King, & Delfabbro, 2012). What differentiates this emerging form of mobile gaming is that gambling mechanics are a core focus of the game itself. The term “games with gambling elements” has been used to describe this phenomenon alongside a number of commentaries identifying a convergence between gaming and gambling or the “gamblification” of games (Gainsbury, Russell, King, Delfabbro, & Hing, 2016; King, Delfabbro, & Griffiths, 2010; King, Gainsbury, Delfabbro, Hing, & Abarbanel, 2015; McBride & Derevensky, 2016), but again an examination of the literature shows that this has tended to focus more on console video games with a simulated gambling element using in-game currency (Gainsbury et al., 2015; Gainsbury, Hing, Delfabbro, & King, 2014). Griffiths and King (2015) have argued that gambling elements within games can constitute a gambling activity, using the example of simulated gambling games within RuneScape, the browser-based massively multiplayer online role-playing game. Plays on the games in question can be purchased using a secondary currency that can be obtained both in-game and using real money. This model is reasonably similar to the one that has proliferated among mobile gaming, although this example differs insofar as a maximum monthly spending limit is placed on this activity.

Although it has been argued these kinds of games could be classed as gambling (Griffiths & King, 2015), regulatory perspectives on this issue have tended to be more cautious (The Gambling Commission, 2015). Moreover, the existing questions appear to focus on whether these activities engender a risk of problem gambling/gambling-like problems (Parke et al., 2012), or whether their risk is in encouraging players to transition to real money gambling, where there is a growing research literature (Gainsbury et al., 2016; Kim, Wohl, Salmon, Gupta, & Derevensky, 2015; McBride & Derevensky, 2016). In addition, this behavior may not fall under the criteria for existing constructs of gaming disorder, which focus on excessive behavior and (in the case of the DSM-5) the lack of monetary risk involved. Mobile games are an example in which gambling style mechanics are becoming more common in video games. Although we agree comparisons from gambling are often inappropriate, we argue that a more nuanced approach is required.

Concluding Remarks

The primary theme underlying this commentary is the need for a greater heterogeneity in understanding the nature of the relationship between video gaming and disorder. Given the range of mechanics and business models within video gaming, it seems inadvisable to treat this as an unitary phenomenon, both in attempting to codify and measure a gaming disorder (both of which consider games as either “online” and “offline”) or in the psychometric scales employed to measure gaming disorders of various kinds. This commentary highlights an example of one increasingly common type of gaming that has the potential to substantially differ from other games in that regard. In discussing this, we identify a number of issues in the area that highlight different elements of an association with problematic gambling behavior that makes a gambling perspective on these products more informative than for other types of gaming. At one extreme it might be viable to consider some cases as instances of gambling disorder. Further research is required to understand the behavioral characteristics of video games, whether common or distinct from those observed in gambling.

We have previously argued for a greater heterogeneity in understanding potentially addictive behavior in behavioral addictions, including video games. Translating markers from drugs and gambling has proven of limited utility, overinflating estimates in epidemiologically inspired studies. Gambling may not be the most appropriate starting point to consider behavioral addictions. However, it is important to recognize the market for video games is being driven in multiple directions. One of the more prominent of these is in the growth of free to play or freemium models, particularly on mobile phones. Many of the mechanisms these games are designed around or involve mechanics or themes from gambling. While the debate paper cites mounting research that markers derived from substance use or gambling addictions are of limited utility in the study of video gaming generally, there are certain kinds of game where translations appear to be appropriate and proportional.

Authors’ contribution

RJEJ and RJT were directly involved in the writing of the manuscript; RJEJ wrote the initial draft.

Conflict of interest

No conflicts of interest have arisen from the production of this manuscript.

References

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  • Larche, C. J. , Musielak, N. , & Dixon, M. J. (2017). The candy crush sweet tooth: How ‘Near-misses’ in candy crush increase frustration, and the urge to continue gameplay. Journal of Gambling Studies, 33, 599615. doi:10.1007/s10899-016-9633-7

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    • Search Google Scholar
    • Export Citation
  • Alha, K. , Koskinen, E. , Paavilainen, J. , Hamari, J. , & Kinnunen, J. (2014). Free-to-play games: Professionals’ perspectives. Proceedings of Nordic DiGRA, Gotland, Sweden, May 29–30 (pp. 114).

    • Search Google Scholar
    • Export Citation
  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association.

    • Search Google Scholar
    • Export Citation
  • Baranowski, T. , Buday, R. , Thompson, D. I. , & Baranowski, J. (2008). Playing for real: Video games and stories for health-related behavior change. American Journal of Preventive Medicine, 34(1), 7482.e10. doi:10.1016/j.amepre.2007.09.027

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Billieux, J. , Schimmenti, A. , Khazaal, Y. , Maurage, P. , & Heeren, A. (2015). Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. Journal of Behavioral Addictions, 4(3), 119123. doi:10.1556/2006.4.2015.009

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gainsbury, S. , King, D. , Delfabbro, P. , Hing, N. , Russell, A. , Blaszczynski, A. , & Derevensky, J. (2015). The use of social media in gambling. Melbourne, VIC: Gambling Research Australia.

    • Search Google Scholar
    • Export Citation
  • Gainsbury, S. M. , Hing, N. , Delfabbro, P. H. , & King, D. L. (2014). A taxonomy of gambling and casino games via social media and online technologies. International Gambling Studies, 14(2), 196213. doi:10.1080/14459795.2014.890634

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gainsbury, S. M. , Russell, A. , & Hing, N. (2014). An investigation of social casino gaming among land-based and Internet gamblers: A comparison of socio-demographic characteristics, gambling and co-morbidities. Computers in Human Behavior, 33, 126135. doi:10.1016/j.chb.2014.01.031

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gainsbury, S. M. , Russell, A. M. T. , King, D. L. , Delfabbro, P. , & Hing, N. (2016). Migration from social casino games to gambling: Motivations and characteristics of gamers who gamble. Computers in Human Behavior, 63, 5967. doi:10.1016/j.chb.2016.05.021

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garfield, R. (2016). A game player’s manifesto. Retrieved from https://www.facebook.com/notes/richard-garfield/a-game-players-manifesto/1049168888532667

    • Search Google Scholar
    • Export Citation
  • Griffiths, M. , King, D. , & Delfabbro, P. (2012). Simulated gambling in video gaming: What are the implications for adolescents? Education and Health, 30, 6870.

    • Search Google Scholar
    • Export Citation
  • Griffiths, M. , & King, R. (2015). Are mini-games within RuneScape gambling or gaming? Gaming Law Review and Economics, 19(9), 640643. doi:10.1089/glre.2015.1995

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Griffiths, M. D. , & Auer, M. (2013). The irrelevancy of game-type in the acquisition, development and maintenance of problem and pathological gambling [Opinion]. Frontiers in Psychology, 3, 621. doi:10.3389/fpsyg.2012.00621

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R. J. E. , O’Malley, C. , & Tunney, R. J. (2017). Understanding the psychology of mobile gambling: A behavioural synthesis. British Journal of Psychology, 108, 608625. doi:10.1111/bjop.12226

    • Crossref
    • Search Google Scholar
    • Export Citation
  • James, R. J. E. , & Tunney, R. J. (2017). The need for a behavioural analysis of behavioural addictions. Clinical Psychology Review, 52, 6976. doi:10.1016/j.cpr.2016.11.010

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kaptsis, D. , King, D. L. , Delfabbro, P. H. , & Gradisar, M. (2016). Withdrawal symptoms in Internet gaming disorder: A systematic review. Clinical Psychology Review, 43, 5866. doi:10.1016/j.cpr.2015.11.006

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, H. S. , Wohl, M. J. A. , Salmon, M. M. , Gupta, R. , & Derevensky, J. (2015). Do social casino gamers migrate to online gambling? An assessment of migration rate and potential predictors. Journal of Gambling Studies, 31(4), 18191831. doi:10.1007/s10899-014-9511-0

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kimppa, K. K. , Heimo, O. I. , & Harviainen, J. T. (2016). First dose is always freemium. ACM SIGCAS Computers and Society, 45(3), 132137. doi:10.1145/2874239.2874258

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, D. , Delfabbro, P. , & Griffiths, M. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26(2), 175187. doi:10.1007/s10899-009-9153-9

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, D. L. , Gainsbury, S. M. , Delfabbro, P. H. , Hing, N. , & Abarbanel, B. (2015). Distinguishing between gaming and gambling activities in addiction research. Journal of Behavioral Addictions, 4(4), 215220. doi:10.1556/2006.4.2015.045

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Larche, C. J. , Musielak, N. , & Dixon, M. J. (2017). The candy crush sweet tooth: How ‘Near-misses’ in candy crush increase frustration, and the urge to continue gameplay. Journal of Gambling Studies, 33, 599615. doi:10.1007/s10899-016-9633-7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S.-Y. , Lee, H. K. , & Choo, H. (2017). Typology of Internet gaming disorder and its clinical implications. Psychiatry and Clinical Neurosciences, 71, 479491. doi:10.1111/pcn.12457

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McBride, J. , & Derevensky, J. (2016). Gambling and video game playing among youth. Journal of Gambling Issues, 34, 156178. doi:10.4309/jgi.2016.34.9

    • Search Google Scholar
    • Export Citation
  • Parke, J. , Wardle, H. , Rigbye, J. , & Parke, A. (2012). Exploring social gambling: Scoping, classification and evidence review. London, UK: Gambling Commission.

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  • Parry, W. (2016). Firm hopes to be 1st with skill-based slot machines. Las Vegas Review Journal. Retrieved from http://www.reviewjournal.com/business/casinos-gaming/firm-hopes-be-1st-skill-based-slot-machines

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  • Robbins, T. W. , & Clark, L. (2015). Behavioral addictions. Current Opinion in Neurobiology, 30, 6672. doi:10.1016/j.conb.2014.09.005

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  • Young, K. S. (1998). Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior, 1(3), 237244. doi:10.1089/cpb.1998.1.237

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The author instruction is available in PDF.
Please, download the file from HERE

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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  • CABELLS Journalytics

2022  
Web of Science  
Total Cites
WoS
5713
Journal Impact Factor 7.8
Rank by Impact Factor

Psychiatry (SCIE) 18/155
Psychiatry (SSCI) 13/144

Impact Factor
without
Journal Self Cites
7.2
5 Year
Impact Factor
8.9
Journal Citation Indicator 1.42
Rank by Journal Citation Indicator

Psychiatry 35/264

Scimago  
Scimago
H-index
69
Scimago
Journal Rank
1.918
Scimago Quartile Score Clinical Psychology Q1
Medicine (miscellaneous) Q1
Psychiatry and Mental Health Q1
Scopus  
Scopus
Cite Score
11.1
Scopus
Cite Score Rank
Clinical Psychology 10/292 (96th PCTL)
Psychiatry and Mental Health 30/531 (94th PCTL)
Medicine (miscellaneous) 25/309 (92th PCTL)
Scopus
SNIP
1.966

 

 
2021  
Web of Science  
Total Cites
WoS
5223
Journal Impact Factor 7,772
Rank by Impact Factor Psychiatry SCIE 26/155
Psychiatry SSCI 19/142
Impact Factor
without
Journal Self Cites
7,130
5 Year
Impact Factor
9,026
Journal Citation Indicator 1,39
Rank by Journal Citation Indicator

Psychiatry 34/257

Scimago  
Scimago
H-index
56
Scimago
Journal Rank
1,951
Scimago Quartile Score Clinical Psychology (Q1)
Medicine (miscellaneous) (Q1)
Psychiatry and Mental Health (Q1)
Scopus  
Scopus
Cite Score
11,5
Scopus
CIte Score Rank
Clinical Psychology 5/292 (D1)
Psychiatry and Mental Health 20/529 (D1)
Medicine (miscellaneous) 17/276 (D1)
Scopus
SNIP
2,184

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
submission  
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 990 EUR/article for articles submitted after 30 April 2023 (850 EUR for articles submitted prior to this date)
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%.
Subscription Information Gold Open Access

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
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

  • Stephanie ANTONS (Universitat Duisburg-Essen, Germany)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Beáta BŐTHE (University of Montreal, Canada)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Ruth J. van HOLST (Amsterdam UMC, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Gyöngyi KÖKÖNYEI (ELTE Eötvös Loránd University, Hungary)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)

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)
  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • 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)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • 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 (Humboldt-Universität zu Berlin, Germany)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Astrid MÜLLER  (Hannover Medical School, Germany)
  • 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)
  • Róbert URBÁN  (ELTE Eötvös Loránd University, Hungary)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Aviv M. WEINSTEIN  (Ariel University, Israel)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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