Authors:
Chih-Hung Ko Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan
Department of Psychiatry, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan

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Orsolya Király Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary

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Zsolt Demetrovics Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
Centre of Excellence in Responsible Gaming, University of Gibraltar, Gibraltar, Gibraltar

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Mark D. Griffiths Psychology Department, Nottingham Trent University, Nottingham, United Kingdom

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Takahiro A. Kato Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

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Masaru Tateno Department of Neuropsychiatry, School of Medicine, Sapporo Medical University, Sapporo, Japan
Tokiwa Child Development Center, Tokiwa Hospital, Sapporo, Japan

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Ju-Yu Yen Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan
Department of Psychiatry, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung Medical University, Kaohsiung City, Taiwan

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Abstract

Background

The eleventh revision of the International Classification of Diseases (ICD-11) defines the three key diagnostic criteria for gaming disorder (GD). These are loss of control over gaming, gaming as a priority over daily activities, and impaired functioning due to gaming. While this definition has implications for the prevention and treatment of GD, there is significant heterogeneity in the symptoms and etiology of GD among individuals, which results in different treatment needs. Cognitive control, emotional regulation, and reward sensitivity are three critical dimensions in the etiology model for GD. Aspects such as gender, comorbidity, motivation for gaming, stage or severity of GD, and risk factors all contribute to the heterogeneity of etiology among individuals with the disorder.

Method

On the basis of clinical symptoms and comorbidity characteristics among approximately 400 patients with gaming disorder, the present paper proposes a clinical typology of patients with GD based on the authors' clinical experience in treating individuals with GD.

Results

The findings indicated three common types of patients with GD: (i) impulsive male patients with attention deficit hyperactivity disorder (ADHD), (ii) dysphoria patients with dysfunctional coping skills, and (iii) isolated patients with social anxiety. The paper also discusses the presentation and treatment priority for these patients.

Conclusion

Personalized treatments for patients with GD should be developed to fit their individual needs. Future studies should examine the heterogeneity of GD and confirm these types, as well as obtain evidence-based information that can help in the development of personalized treatment. Treatment resources should be developed, and professionals should be trained to provide integrated individualized treatment.

Abstract

Background

The eleventh revision of the International Classification of Diseases (ICD-11) defines the three key diagnostic criteria for gaming disorder (GD). These are loss of control over gaming, gaming as a priority over daily activities, and impaired functioning due to gaming. While this definition has implications for the prevention and treatment of GD, there is significant heterogeneity in the symptoms and etiology of GD among individuals, which results in different treatment needs. Cognitive control, emotional regulation, and reward sensitivity are three critical dimensions in the etiology model for GD. Aspects such as gender, comorbidity, motivation for gaming, stage or severity of GD, and risk factors all contribute to the heterogeneity of etiology among individuals with the disorder.

Method

On the basis of clinical symptoms and comorbidity characteristics among approximately 400 patients with gaming disorder, the present paper proposes a clinical typology of patients with GD based on the authors' clinical experience in treating individuals with GD.

Results

The findings indicated three common types of patients with GD: (i) impulsive male patients with attention deficit hyperactivity disorder (ADHD), (ii) dysphoria patients with dysfunctional coping skills, and (iii) isolated patients with social anxiety. The paper also discusses the presentation and treatment priority for these patients.

Conclusion

Personalized treatments for patients with GD should be developed to fit their individual needs. Future studies should examine the heterogeneity of GD and confirm these types, as well as obtain evidence-based information that can help in the development of personalized treatment. Treatment resources should be developed, and professionals should be trained to provide integrated individualized treatment.

Introduction

Emerging empirical evidence indicates that the worldwide mental health impact and treatment demand of gaming disorder (GD) are driving a need to establish practical diagnostic criteria for identifying individuals who require therapeutic help (Reed et al., 2022). The eleventh revision of the International Classification of Diseases (ICD-11) defines GD as a loss of control regarding gaming behavior, which takes precedence over essential daily activities and has negative consequences, including functional impairment (World Health Organization, 2019). The ICD-11 GD criteria provides a practical means of diagnosing GD so that effective treatments can be administered (Billieux et al., 2017; Ko, Lin, Lin, & Yen, 2020; Müller et al., 2022). Kuss, Pontes, and Griffiths (2018) and Dong and Potenza (2014) reported that cognitive control function (Heuer, Mennig, Schubö, & Barke, 2021), emotional regulation ability, and reward sensitivity (Wang et al., 2021; Zhou et al., 2021) are three domains that play important roles in the development of GD. However, Ko, Lin, Lin, and Yen (2020) highlighted the heterogeneity in the etiology of GD and suggested that this heterogeneity could mean that personalization is required in terms of interventions and treatment.

Personalized treatment

The aim of personalized medicine is to identify the treatment with the best outcome for the individual (Cutter & Liu, 2012). Personalized treatment of psychiatric disorders is determined by individual factors, clinical characteristics, and biological markers (Simon & Perlis, 2010). Consequently, comprehensive data from research on the heterogeneity of a disorder are essential to implement relevant treatments that are bespoke to the individual. Because genetic data for GD are very limited (Yen et al., 2022), the optimal individualized treatment for GD may be dependent on clinical characteristics (Sharman, Roberts, Harris, Lockwood, & Bowden-Jones, 2022).

Factors affecting therapeutic treatment of gaming disorder

Impulsivity (Gentile, Swing, Lim, & Khoo, 2012), lack of deliberation, and risk-taking potential (Ko et al., 2017) may contribute to a person's loss of control during gaming, underlining the cognitive control impairment of individuals with GD (Dong & Potenza, 2014). This impairment prevents them from stopping gaming when they need to perform other tasks. Therefore, cognitive control impairment may be a critical factor in developing GD (Gentile et al., 2012).

High emotional vulnerability, impaired emotional regulation (Kuss et al., 2018), frustration intolerance (Lin, Yen, Lin, & Ko, 2021; Yu, Mao, & Wu, 2018), and inadequate coping ability or resilience (Lin, Yen, Lin, & Ko, 2021) can lead to depression, anxiety, or irritability among patients with GD, as negative consequences of excessive gaming. This impairment makes individuals continue their gaming. The bidirectional interaction between negative consequences and emotional difficulties may lead to a vicious cycle. Therefore, this aspect may form one of the key factors in the continuance of GD and relapse under stress.

The reward sensitivity for and expected reward from gaming may contribute to a weak reward response to daily activities other than gaming (Zhou et al., 2021). Consequently, individuals might prefer gaming rather than meeting their responsibilities in life, such as educational and/or occupational tasks, as well as other leisure time activities (Criterion 2 of the ICD-11-GD definition). This may result in anhedonia when not gaming (Yen et al., 2022), engaging in gaming to overcome boredom, and leading to procrastination of daily activities (Yeh et al., 2017), which may prevent individuals with GD from performing any alternative activities. This inadequate motivation in daily life could be a key issue underlying individuals' resistance to treatment, resulting in an isolated life. Restoring a rewarding response to daily life activities other than gaming is essential in helping an individual with GD recover from the disorder. Therefore, treatments should address these three aspects in the etiology of GD as well as the various stages of development and maintenance of GD.

From a clinical perspective, heterogeneity can arise from various factors including (but not limited to) gender (Dong & Potenza, 2022), comorbidity (González-Bueso et al., 2020; Ko et al., 2021), motivation for gaming (Király et al., 2022), stage or severity of the disorder (Granero et al., 2021), age, region (Kim et al., 2022), and other risk factors (such as impulsivity) (Jeong et al., 2021). For instance, males with GD are more likely to be impulsive compared to females with GD, whereas females with GD are more likely to be lonely, have mood problems (Dong & Potenza, 2022), and play videogames to avoid everyday problems (i.e., escape motive; Király et al., 2015, 2022). Comorbidity is perhaps the most familiar aspect that clinicians have to address regarding the heterogeneity of GD. The mechanisms underlying psychiatric comorbidities include self-medication (i.e., self-intervention for psychiatric symptoms; Khantzian, 1987), negative consequences (i.e., psychiatric symptoms resulting from GD), a shared mechanism (i.e., common mechanism underlying the association), and bi-direction (i.e., conditions affecting each other; Huang, Liu, Su, Lin, & Ko, 2016). These four mechanisms may determine which disorder should be treated with priority. For example, a self-medication model might suggest that a major depression episode should be treated prior to GD because of its primary role and clinical severity. An individual's motivation for gaming, such as immersion/escapism or habit/boredom, plays a role in the psychological mechanisms that lead to the development and maintenance of GD (Király et al., 2022). According to previous studies, depression (e.g., Gentile et al., 2012; Ostinelli et al., 2021) and impulsivity (e.g., Kim et al., 2019; Şalvarlı & Griffiths, 2021) are two of the most evaluated factors of GD. They have been associated with GD differently on the type of comorbid psychiatric disorder. For example, impulsivity appears more in the comorbidity with ADHD (Cabelguen et al., 2021) and depression is more severe among those individuals with GD who have a comorbid depressive and/or anxiety disorder (Ko et al., 2021). These factors are all essential in determining the heterogeneity of GD.

Types of patients with gaming disorder

This paper presents a new clinical typology of disordered gaming by pooling clinical data from approximately 400 patients with GD over the past ten years from psychiatric outpatients' clinics in Taiwan and Japan. The diagnoses of GD were typically based on clinical interviews using the DSM-5 (American Psychiatric Association, 2013) as these were the only criteria available from 2013. Since 2019, the ICD-11 criteria (WHO, 2019) have also been incorporated into the clinical interviews. There are two studies that have demonstrated the similarity between the two sets of criteria (Higuchi, Nakayama, Matsuzaki, Mihara, & Kitayuguchi, 2021; Yen, Lin, Wu, & Ko, 2022). Approximately 80% of the patients were male, approximately three-quarters were under 18 years of age, and approximately two-thirds were high school students. Psychiatric comorbidities (i.e., ADHD, depressive or social anxiety disorder) among patients were assessed by psychiatrists using the DSM-5 criteria of the respective disorders. Based on these clinical evaluations, the present authors propose three types of patients with GD: (1) impulsive male patients with attention deficit hyperactivity disorder (ADHD); (2) dysphoria patients with dysfunctional coping skills; and (3) isolated patients with social anxiety. There appear to be other types as well, such as patients with psychotic disorders or autism spectrum disorder (Torres-Rodríguez, Griffiths, Carbonell, Farriols-Hernando, & Torres-Jimenez, 2019). Treatment regarding these latter types is determined predominantly by the nature of the psychotic or autistic disorder, and therefore it is not discussed here.

The first type involves impulsive male patients with ADHD. They are characterized by impulsivity and irritability (Ko et al., 2021; Torres-Rodríguez et al., 2019; Yen et al., 2017) and are partly similar to the impulsive/aggressive type of GD reported by Lee, Lee, and Choo (2017). The onset of ADHD before the age of 12 years (APA, 2013) usually precedes that of GD. The attention deficit usually impairs individuals' daily life functions but preserves their performance in gaming (Bioulac et al., 2012). Individuals with ADHD are prone to respond to small, immediate rewards over valuable, delayed incentives (Modesto-Lowe, Chaplin, Soovajian, & Meyer, 2013). Therefore, they are motivated by pleasure from achievement in gaming (Morsink et al., 2017). However, the accompanying impulsivity makes it difficult for them to control their gaming despite repeated negative consequences. Their risk-taking and inadequate deliberation attenuate their motivation to change (Pollak, Dekkers, Shoham, & Huizenga, 2019). Pharmacological or behavioral interventions in treating the attention deficit and promoting cognitive control and deliberation are required as an initial step before the patients' gaming symptoms can be alleviated. Improvement in impulse control and executive ability will benefit remission from addictive gaming. Fortunately, individuals with ADHD respond relatively positively to treatment (Martín-Fernández et al., 2016) because they are usually likely to pursue alternative activities suggested during the intervention process based on the authors' clinical experience.

The second type involves dysphoria patients with dysfunctional coping skills. Although research is not conclusive, it is most likely that the interaction between depression and GD is bidirectional (Huang et al., 2016; Teng, Pontes, Nie, Griffiths, & Guo, 2021). Individuals with GD will likely experience negative consequences in their occupation, education and/or personal relationships (Ko, Király, Demetrovics, Chang, & Yen, 2020). They have low frustration tolerance (Lin, Yen, Lin, & Ko, 2021), low resilience, and dysfunctional coping skills (Lin, Yen, Lin, & Ko, 2021) when facing these problems. Because gaming is usually the most readily available way of coping with stress for individuals with GD (Lin, Yen, Lin, Chou et al., 2021), an aggressive interruption of gaming could result in serious reactions, such as extreme irritability or self-harming behaviors, in the case of such individuals. If their mood is not sufficiently improved or they do not cope well with stress, they could experience a vicious cycle and remain caught in depression and GD. Therefore, if depression reaches clinical significance or is associated with suicidal risk, interventions for depression, such as antidepressants, should be provided as soon as possible. Psychotherapy, such as emotion regulation therapy, which promotes emotional regulation and offers functional coping strategies, could buffer stress regulation (Renna, Quintero, Fresco, & Mennin, 2017). These interventions could help the patient with GD manage their stress during abstinence from gaming (Yen et al., 2022).

The third type comprises isolated patients with social anxiety. These patients usually exhibit strong behavior inhibition and sensitivity to aversion (Wang et al., 2017). Because they experience less anxiety online than offline (Yen et al., 2012), they tend to withdraw from the real world and enjoy online gaming. This is similar to a phenomenon known as “hikikomori” (Kato, Shinfuku, & Tateno, 2020) that is associated with internet addiction in Japan (Tateno et al., 2019). These individuals usually have a cooperative attitude and have insight into their problems in the authors' clinical experience. However, they experience difficulty regarding change because of the anxiety associated with change itself, resulting in an unalterable course of GD. Moreover, both treatments for anxiety and a rehabilitation program, including social skills training or job coaching, are required to find alternative goals in their daily lives and eventually treat their GD.

Challenges and future directions in implementing personalized treatment

There are specific challenges in implementing personalized treatment for GD. The evidence-based information available for determining the appropriate treatment is very limited (King et al., 2017; King, Wölfling, & Potenza, 2020). Case studies (such as those outlined by Torres-Rodríguez et al., 2019) are necessary to demonstrate the clinical characteristics, such as the course of the disorder or gaming motivation of a specific type of patient (Tateno & Kato, 2022). Additionally, a classification analysis with large clinical and research samples is required to support the heterogeneity of GD. Case-control studies could examine the etiology, negative consequences, and treatment needs for specific types of patients with GD. Cross-cultural studies could identify the similarities and differences of each type of patient with GD in different cultures. For example, evaluating hikikomori (Tateno et al., 2019) among isolated patients experiencing GD with social anxiety (the third type) in Japan. Classification theories should be proposed based on clinical experience and empirical research evidence (Lee et al., 2017). Lastly and most importantly, individualized treatment studies for specific types of patients with GD should be conducted to provide the best solutions for identifying the best treatment.

An integrated team of multidisciplinary professionals is essential but usually unavailable to provide a personalized treatment plan. Mental health professionals, such as psychiatrists, psychologists, social workers, and occupational therapists, should participate in the work related to GD based on a reasonable referral system, such as Screening, Brief Intervention, and Referral to Treatment based on the ICD-11 GD criteria (Yen et al., 2022). They should collaboratively work with other health providers, educators, and volunteers in the community to address the functional impairment caused by GD. Therefore, training, communication, and collaborative work for multidisciplinary professionals should be developed. The services for medication, psychotherapy, family therapy, rehabilitation programs, and supportive systems should be integrated. Consequently, all these services could be provided to satisfy the individualized needs of patients with GD.

Conclusion

Despite the aforementioned limitations of personalized treatment, patients with GD require treatment that corresponds to their needs. The etiology of their GD, psychiatric comorbidities, stage of the disorder (severity, course, and insight of the patient), gaming motivations, and personal characteristics should be assessed to determine the optimal treatment. A treatment model and resources should be developed to satisfy the needs of individuals with GD. Future studies focusing on the heterogeneity of GD would contribute to the development of personalized treatment.

Funding sources

This study was supported by Taiwan's Ministry of Science and Technology (MOST109-2314-B-037-081-, MOST109-2629-B-037-001-MY3, and MOST110-2314-B-037-062-) and Kaohsiung Municipal Siaogang Hospital (H-109-004; H-110-006). ZD's and OK's contribution was supported by the Hungarian National Research, Development and Innovation Office (KKP126835).

Authors' contribution

Chih-Hung Ko wrote the original draft. All authors reviewed and revised the draft and provided further opinions.

Conflict of interest

The University of Gibraltar receives funding from the Gibraltar Gambling Care Foundation, an independent, not-for-profit charity. ELTE Eötvös Loránd University receives funding from Szerencsejáték Ltd. (the gambling operator of the Hungarian government) to maintain a telephone helpline service for problematic gambling. ZD is Editor-in-Chief of the Journal of Behavioral Addictions. MDG has received research funding from Norsk Tipping (the gambling operator owned by the Norwegian government). MDG has received funding for a number of research projects in the area of gambling education for young people, social responsibility in gambling and gambling treatment from Gamble Aware (formerly the Responsibility in Gambling Trust), a charitable body which funds its research program based on donations from the gambling industry. MDG undertakes consultancy for various gambling companies in the area of social responsibility in gambling. None of these funding sources are related to this study, and the funding institution had no role in the study design or the collection, analysis, and interpretation of the data, the writing of the manuscript, or the decision to submit the paper for publication.

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    • PubMed
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    • Export Citation
  • Reed, G. M., First, M. B., Billieux, J., Cloitre, M., Briken, P., Achab, S., … Bryant, R. A. (2022). Emerging experience with selected new categories in the ICD-11: Complex PTSD, prolonged grief disorder, gaming disorder, and compulsive sexual behaviour disorder. World Psychiatry, 21(2), 189213. https://doi.org/10.1002/wps.20960.

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    • Export Citation
  • Renna, M., Quintero, J., Fresco, D., & Mennin, D. (2017). Emotion regulation therapy: A mechanism-targeted treatment for disorders of distress. Frontiers in Psychology, 8, 98. https://doi.org/10.3389/fpsyg.2017.00098.

    • Search Google Scholar
    • Export Citation
  • Şalvarlı, Ş. İ., & Griffiths, M. D. (2021). Internet gaming disorder and its associated personality traits: A systematic review using PRISMA guidelines. International Journal of Mental Health and Addiction, 19(5), 14201442. https://doi.org/10.1007/s11469-019-00081-6.

    • Search Google Scholar
    • Export Citation
  • Sharman, S., Roberts, A., Harris, B., Lockwood, R., & Bowden-Jones, H. (2022). The national centre for gaming disorders (UK) – Who is accessing this service? Journal of Behavioral Addictions, 11(2), 147149. https://doi.org/10.1556/2006.2022.00010.

    • Search Google Scholar
    • Export Citation
  • Simon, G. E., & Perlis, R. H. (2010). Personalized medicine for depression: Can we match patients with treatments? American Journal of Psychiatry, 167(12), 14451455. https://doi.org/10.1176/appi.ajp.2010.09111680.

    • Search Google Scholar
    • Export Citation
  • Tateno, M., & Kato, T. A. (2022). Personality traits of female vocational school students in Japan with smartphone addiction with comorbid modern-type depression traits. Psychiatry and Clinical Neurosciences. Advance online publication. https://doi.org/10.1111/pcn.13475.

    • Search Google Scholar
    • Export Citation
  • Tateno, M., Teo, A. R., Ukai, W., Kanazawa, J., Katsuki, R., Kubo, H., & Kato, T. A. (2019). Internet addiction, smartphone addiction, and hikikomori trait in Japanese young adult: Social isolation and social network. Frontiers in Psychiatry, 10, 455. https://doi.org/10.3389/fpsyt.2019.00455.

    • Search Google Scholar
    • Export Citation
  • Teng, Z., Pontes, H. M., Nie, Q., Griffiths, M. D., & Guo, C. (2021). Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: A longitudinal study. Journal of Behavioral Addictions, 10(1), 169180. https://doi.org/10.1556/2006.2021.00016.

    • Search Google Scholar
    • Export Citation
  • Torres-Rodríguez, A., Griffiths, M. D., Carbonell, X., Farriols-Hernando, N., & Torres-Jimenez, E. (2019). Internet gaming disorder treatment: A case study evaluation of four different types of adolescent problematic gamers. International Journal of Mental Health and Addiction, 17(1), 112. https://doi.org/10.1007/s11469-017-9845-9.

    • Search Google Scholar
    • Export Citation
  • Wang, C. Y., Wu, Y. C., Su, C. H., Lin, P. C., Ko, C. H., & Yen, J. Y. (2017). Association between internet gaming disorder and generalized anxiety disorder. Journal of Behavioral Addictions, 6(4), 564571. https://doi.org/10.1556/2006.6.2017.088.

    • Search Google Scholar
    • Export Citation
  • Wang, L., Yang, G., Zheng, Y., Li, Z., Qi, Y., Li, Q., & Liu, X. (2021). Enhanced neural responses in specific phases of reward processing in individuals with Internet gaming disorder. Journal of Behavioral Addictions, 10(1), 99111. https://doi.org/10.1556/2006.2021.00003.

    • Search Google Scholar
    • Export Citation
  • World Health Organization (2019). International classification of diseases for mortality and morbidity statistics (11th Revision). Retrieved August 26, 2023, from: https://icd.who.int/.

    • Search Google Scholar
    • Export Citation
  • Yeh, Y. C., Wang, P. W., Huang, M. F., Lin, P. C., Chen, C. S., & Ko, C. H. (2017). The procrastination of Internet gaming disorder in young adults: The clinical severity. Psychiatry Research, 254, 258262. https://doi.org/10.1016/j.psychres.2017.04.055.

    • Search Google Scholar
    • Export Citation
  • Yen, J. Y., Higuchi, S., Ko, C. H., & Su, S. F. (2022). Screening, brief intervention, and referral to treatment model based on ICD-11 criteria of gaming disorder and hazardous gaming during the COVID-19 pandemic. Current Addiction Reports, 9, 571574. https://doi.org/10.1007/s40429-022-00444-5.

    • Search Google Scholar
    • Export Citation
  • Yen, J. Y., Higuchi, S., Lin, P. Y., Lin, P. C., Chou, W. P., & Ko, C. H. (2022). Functional impairment, insight, and comparison between criteria for gaming disorder in the international classification of diseases, 11 edition and internet gaming disorder in diagnostic and statistical manual of mental disorders, fifth edition. Journal of Behavioral Addictions, 11(4), 10121023. https://doi.org/10.1556/2006.2022.00079.

    • Search Google Scholar
    • Export Citation
  • Yen, J. Y., Lin, P. C., Lin, H. C., Lin, P. Y., Chou, W. P., & Ko, C. H. (2022). Association of internet gaming disorder with catechol-o-methyltransferase: Role of impulsivity and fun-seeking. Kaohsiung Journal of Medical Science, 38(1), 7076. https://doi.org/10.1002/kjm2.12454.

    • Search Google Scholar
    • Export Citation
  • Yen, J. Y., Lin, P. C., Wu, H. C., & Ko, C. H. (2022). The withdrawal-related affective, gaming urge, and anhedonia symptoms of internet gaming disorder during abstinence. Journal of Behavioral Addictions, 11(2), 481491. https://doi.org/10.1556/2006.2022.00008.

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  • Yen, J. Y., Liu, T. L., Wang, P. W., Chen, C. S., Yen, C. F., & Ko, C. H. (2017). Association between Internet gaming disorder and adult attention deficit and hyperactivity disorder and their correlates: Impulsivity and hostility. Addictive Behaviors, 64, 308313. https://doi.org/10.1016/j.addbeh.2016.04.024.

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  • Yen, J.-Y., Yen, C.-F., Chen, C.-S., Wang, P.-W., Chang, Y.-H., & Ko, C.-H. (2012). Social anxiety in online and real-life interaction and their associated factors. Cyberpsychology, Behavior and Sociial Networking, 15(1), 712. https://doi.org/10.1089/cyber.2011.0015.

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  • Yu, S., Mao, S., & Wu, A. M. S. (2018). The interplay among stress, frustration tolerance, mindfulness, and social support in internet gaming disorder symptoms among Chinese working adults. Asia Pacific Psychiatry, 10(4), e12319. https://doi.org/10.1111/appy.12319.

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  • Zhou, W. R., Wang, M., Dong, H. H., Zhang, Z., Du, X., Potenza, M. N., & Dong, G. H. (2021). Imbalanced sensitivities to primary and secondary rewards in internet gaming disorder. Journal of Behavioral Addictions, 10(4), 9901004. https://doi.org/10.1556/2006.2021.00072.

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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

Indexing and Abstracting Services:

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  • Journal Citation Reports/Science Edition
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  • Current Contents®/Social and Behavioral Sciences
  • EBSCO
  • GoogleScholar
  • PsycINFO
  • PubMed Central
  • SCOPUS
  • Medline
  • CABI
  • 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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