essay about online gaming addiction

Addiction to Online Gaming: A Review of Literature Essay

Introduction.

The rapid development of technologies has led not only to numerous breakthroughs in various spheres of people’s lives but also to significant issues related to the inability of some individuals to limit their time spent on gadget use. Whereas the Internet has presented ample opportunity for communication and research, it has also become the reason why too many users have become dependent on it. The selected topic of research is the addiction to online gaming among adults. This specific kind of addiction does not produce such a devastating effect on one’s health as the excessive consumption of alcohol or drugs. However, online gaming addiction poses other threats, which are no less severe both for the addicts and their close ones.

Researchers have presented evidence on the severity of online gaming addiction (Marino & Spada, 2017). Still, too many people continue to neglect the issue’s potential adverse outcomes. Therefore, more research is needed to investigate the problem from different angles, which will suggest viable solutions to it. The present paper is an overview of scholarly sources on online gaming addiction and the analysis of narrative inquiry as the most suitable qualitative research method to use for the investigation of this problem.

The Problem of Interest

Despite the constant development and enhancement of community resources and entertainment opportunities, the number of individuals addicted to online gaming is growing annually. What previously used to be viewed merely as a leisure activity has now come to be considered as a serious threat due to its potential to provoke addiction in users. Online gaming is related to social and psychological problems by facilitating self-regulation deficiency (Gong et al., 2019). Furthermore, the age of gamers has increased considerably, and the activity is no longer regarded as a teenage male hobby (Pietersen et al., 2018). Whereas, in the past, playing video games online, was considered as a useless pastime, at present, it has become an important part of many people’s lifeworlds. The increasing popularity of online gaming is associated with the idea that video games are “richly expressive and creative,” and they grant people much more immersive experience than other media forms do (Pietersen et al., 2018, p. 123). Therefore, one of the core aims in performing current research is to enhance the understanding of people’s likelihood to become addicted to online gaming.

Another rationale for selecting the problem is the need to analyze the possible ways of mitigating a growing issue of online game addiction among the population. Typically, game addicts are male individuals who report unique experiences related to their gaming activity and a high rate of engagement as the triggers of addiction (Tang et al., 2017). However, it is evident that the problem affects not only those directly involved in it but also anyone they interact with within their personal, professional, social, and family lives. Specifically, as Tang et al. (2017) mention, addiction to online gaming can cause a range of social and family problems that present a significant public health concern.

With the increasing interest of researchers in the question of problematic use of the Internet by gamers, a new clinical definition has been suggested to characterize the issue: Internet gaming disorder (Marino & Spada, 2017). Other terms utilized to denote the problem include ‘online gaming addiction,’ ‘problematic online gaming,’ ‘pathological gaming,’ and ‘video gaming dependence’ (Marino & Spada, 2017). The prevalence of Internet gaming disorder is reported to vary from 1.6 to 8.5% among Western youths. Furthermore, the disorder is frequently accompanied by other psychological problems, such as depression, anxiety, attention deficit hyperactivity disorder, and social phobia (Marino & Spada, 2017). Thus, it is crucial to analyze the available research in order to synthesize what has already been found and single out questions for further detailed research.

The main focus of the study will be the development of online gaming addiction and individuals’ feelings about it. According to Monacis et al. (2017), excessive use of technology has become an emerging issue of concern in the past few decades. The most common symptoms of online gaming addiction are unpleasant feelings when there is no access to the Internet (emptiness and depression), excessive investment of time spent on playing online games, and the refusal to admit a problem (Monacis et al., 2017). One of the major motives for engaging in online gaming is seeking sensation (Hu et al., 2017).

Other common reasons for developing online gaming addiction are concerned with coping, escape, competition, fantasy, and social motives (Šporčić & Glavak-Tkalić, 2018). Hence, it is crucial to investigate why individuals develop an addiction to online gaming and how they feel about it at the stage when they are only starting to engage in excessive Internet use and at the point when online games begin to take up too much time and initiate psychological problems. Personal stories of online gamers will serve as a solid ground for identifying the principal problems and suggesting solutions to them.

The Qualitative Research Method to Be Used

Taking into consideration the nature of the problem under investigation, the most suitable qualitative research method to employ in the study is narrative inquiry. This method involves the process of collecting data from respondents through storytelling. The study of the narrative becomes the means of understanding the ways people perceive the world and various situations in their lives. The self-narrative construction is manifested both in the content and form of narratives (Androutsopoulou & Stefanoua, 2018). According to Lieblich et al., there are two core dimensions for interpreting and scrutinizing narratives: “holistic versus categorical” and “content versus form” (as cited in Androutsopoulou & Stefanoua, 2018, p. 130).

According to Androutsopoulou and Stefanoua (2018), the most beneficial approach to employing a narrative inquiry analysis is a holistic one. The holistic-content dimension implies that the researcher should use the whole life story of an individual, which allows focusing on emerging topics. Meanwhile, the holistic-content mode presupposes that researchers look inside the structure of a respondent’s life story (Androutsopoulou & Stefanoua, 2018). As a result, the use of narrative inquiry helps to understand people’s attitudes toward the events happening in their lives and the ways they feel about them.

The selected research method enables scholars to focus on respondents’ thoughts about their lives rather than on events happening. By using this holistic approach, an individual is able to construct a coherent story of their life with the past, present, and future (James, 2018; McAlpine, 2016). When one tells a researcher about their experiences, the latter becomes “narratives as part of inquiry” and makes the audience “vicarious” participants of these experiences (Chen, 2019, p. 382). Narrative inquiry is composed of three dimensions: temporality, sociality, and space (Kovinthan, 2016). These presuppose a transitional movement of people and places in the story, the revelation of the person’s emotions and feelings, and the possibility of the physical space of inquiry to change (Kovinthan, 2016). Overall, narrative inquiry allows for receiving valuable and reliable first-hand information about the researched issues and problems.

The Review of Literature

Benefits and limitations of the selected research design.

As a research design, a narrative inquiry has a number of advantages and disadvantages that should be considered before utilizing it. The major benefit is undoubtedly the possibility to receive information from the respondent openly, honestly, and without bias. Narrative inquiry is considered to be the most suitable way of uncovering and understanding people’s complex problems (James, 2018). The next advantage of the selected research design is placing the respondent’s self in the central part of the story (Gordon et al., 2015). As a result, the narrator is able to present and construct events, identities, and realities in close synergy with others (Gordon et al., 2015). With the help of narrative research, individuals find it easier to story and re-story their lives in various problematic contexts (Sheilds et al., 2015). Another strength of the narrative inquiry is the likelihood of improving people’s well-being by allowing them to express their thoughts and apprehensions (Ho et al., 2020). When an individual receives an opportunity to express their problems out loud, the chances of coping with these issues increase.

What is more, narrating personal experience equals making sense of it (Ho et al., 2020). In the case of online gamers, the use of narrative inquiry enables researchers to understand “what it means to be a gamer” (Pietersen et al., 2018, p. 123). With this information available, scholars can understand the mechanisms of addiction better since unique personal data allows for a thorough analysis of how people develop an addiction to online gaming and how they feel about it. The next benefit of the selected research design is that it incorporates not only inward but also outward analysis. According to Law and Chan (2015), narrative inquirers consider both the participants’ and researchers’ identities, feelings, hopes, moral tendencies, the environment, conditions, and people affecting the forces and factors from respondents’ contexts. Kovinthan (2016) reports that narrative inquiry helps researchers to cross the boundary between themselves and participants. Additionally, the selected research design enables scholars to investigate the issues faced by respondents and draw out the implicit beliefs and values of researchers (Kovinthan, 2016).

One more advantage of narrative inquiry is the possibility of this approach to unite not only participants and researchers but also the readers of results obtained. As Martinie et al. (2016) note, the audience is likely to reevaluate their own experiences and views on the problem investigated in a study. According to Clandinin and Murphy, narrative inquiry gives knowledge about the experiences of people “composing lives within complex storied landscapes” (as cited in Martinie et al., 2016, p. 659). Finally, as McAlpine (2016) notes, narrative research is a beneficial research design due to creating the opportunity to value different ways of learning about people’s problems and experiences. Therefore, narrative inquiry offers numerous advantages to researchers and, consequently, to research participants.

Disadvantages

What concerns the research design’s limitations is that it must be acknowledged that personal narratives cannot be void of subjectivity without the opportunity to check the information given by respondents (Bruce et al., 2016). Another problem is that the selected research design is not suitable for investigations involving a large number of participants. As James (2018) remarks, since narrative inquiry requires an in-depth and holistic approach to each participant, this method is not appropriate for the studies covering large samples. A limitation closely related to this one is the lack of the possibility to generalize findings due to the uniqueness of each participant’s story (Sheilds et al., 2015). One more difficulty is the fact that narrative inquiry is interpreted and implemented differently by various scholars (James, 2018). Due to this aspect, some researchers argue for the need to draw a firmer line between what narrative inquiry is and what it is not (James, 2018). A disadvantage is also presented by the potentially lacking understanding and trust between participants and researchers or researchers and ethics review boards (Bruce et al., 2016).

The next limitation is concerned with the fact that identity construction that is described in the narrative constitutes only one of the features presented by identity-in-action (McAlpine, 2016). Also, according to Taylor, the narratives’ innate structure frequently leads to the problem of overlooking the “overarching sense of indeterminacy, partiality, and complexity” (as cited in McAlpine, 2016, p. 46). Hence, researchers should be cautious of the information that is left out from respondents’ stories and mind the inconsistencies in narrations. Along with this difficulty, there is a challenge of the researcher’s wrong interpretation of the data given by respondents. Finally, there is a limitation concerned with narrowing the focus of research and ignoring the broader structural problems (McAlpine, 2016). Thus, despite the variety of benefits presented by narrative inquiry, researchers utilizing this approach should be highly attentive to avoid possible mistakes in the process of collecting and analyzing data.

The Evaluation of the Selected Software Analysis Program

Electronic analysis of research data has been commonly associated with quantitative methods. However, one must admit the presence of a sufficient amount of software for qualitative data analysis. Still, despite their availability, these tools are not favored by qualitative research specialists, and the most probable reason for it is the difficulty mastering the software (Zamawe, 2015). In the present study, the software analysis program to be utilized is NVivo. This program is aimed not so much at analyzing the collected data but at aiding the process of analysis (Zamawe, 2015). NVivo is a popular data management program that has such features as multimedia functions, rich text capabilities, and character-based coding. Furthermore, the program incorporates built-in facilities enabling individuals from different geographical areas to operate the same information files simultaneously via a network.

Another benefit of NVivo is in its high level of compatibility of the program with research designs. Since NVivo is not “methodological-specific,” it can be utilized with a variety of qualitative research designs and data analysis methods, including ethnography, grounded theory, literature reviews, discourse analysis, phenomenology, conversation analysis, and mixed methods (Zamawe, 2015, p. 13). NVivo has been available since the 1980s, but only a small amount of researchers have utilized it. Zamawe (2015) notes that despite some limitations, the program is rather useful, and, hence, underestimated. For instance, an evident advantage of NVivo is “easy, effective and efficient coding,” making the retrieval process easier (Zamawe, 2015, p. 14). The program also enables scholars to gather information across sources to group the material that is related (Dollah et al., 2017). Apart from easy data management, NVivo offers such advantages as simplicity in finding topics, the opportunity to save time, and the simplification of data classification.

At the same time, it is necessary to admit some drawbacks of the system. For instance, researchers admit that NVivo may present difficulty processing audio files (Zamawe, 2015). What is more, the program requires much time to master (Dollah et al., 2017). Also, NVivo may be expensive for researchers, as well as it may present complications when attempting to interpret data (Dollah et al., 2017). Still, taking into consideration all advantages and disadvantages of NVivo and bearing in mind the purpose of the present research, it is relevant to use the selected software for the simplification of data analysis in the process of work on the research problem.

Validity Threats in the Selected Qualitative Design

As with any qualitative research design, narrative inquiry meets threats to validity. There are two major dimensions in which the selected method’s validity may be undermined. Firstly, there may arise the problem of a disparity between individuals’ experiences and the stories they tell about these experiences (Wang & Geale, 2015). Secondly, there may emerge wrong connections between the stories told and the interpretations of these stories. In case any of these two issues appear, the validity of research will inevitably suffer. To avoid these common problems, the researcher has to make sure that participants understand the purpose of the study and are aware of the need to be precise and objective about their narratives. On the other hand, the researcher also should do their best to remain impartial and help respondents to uncover their stories in a logical and untwisted way.

Validity in qualitative research is established through such qualities as confirmability, credibility, trustworthiness, and dependability. Apart from that, rigorous data collection and analysis are required, as is member checking (Byrne, 2015). There may also emerge some validity threats of narrative inquiry as a research design in connection with these issues. Confirmability is related to the establishment of trustworthiness and the level of confidence that the study is based on respondents’ narratives rather than on the researcher’s biased opinions (Abkhezr et al., 2020; Heilmann, 2018). In order to make sure that the study focuses on participants’ narratives solely, the researcher has to reflect on their choice of the topic and the attitudes toward data collection and interpretation.

Another important aspect that can pose a threat to validity is credibility. According to Haydon et al. (2018), researchers have to consider whether narrative inquiry has the potential to answer the research question. One of the ways of overcoming this threat is long-term communication between the researcher and the participant, which allows for the confirmation of data collection, thus leading to a higher level of rigor and credibility (Haydon et al., 2018; Nolan et al., 2017).

To mitigate threats to dependability and trustworthiness, narrative inquirers need to be highly attentive when listening to individuals’ stories. Furthermore, as Nolan et al. (2017) mention, it is of utmost importance to respond to critics’ notes. Without a sober reaction to criticism, a researcher risks making the study biased, which can lead to a lack of trustworthiness and dependability. It is a good idea to let participants check the final interpretation of their narratives to evaluate whether it coincides with the experience they described in their stories (Nolan et al., 2017). Harfitt (2015) also emphasizes the significance of validating the field notes with participants as a crucial prerequisite of maintaining trustworthiness. The process of data analysis is no less essential than that of data collection when it comes to maintaining the study’s validity. As Wang and Geale (2015) remark, it is necessary to perform validation checks throughout collecting and analyzing data. Furthermore, the researcher should maintain a close connection with the participants at all stages of the study to ensure its dependability and trustworthiness.

Potential Ethical Issues

When considering narrative inquiry as a research design, ethical issues are probably the most significant ones to be addressed. The main problem that may arise is that sharing one’s experiences may turn into something more personal than mere information exchange (Caine et al., 2019). As a result, by the end of the study, investigators may develop too friendly relationship with their respondents. Another potential ethical issue is that researchers place the narratives of the participants within a larger narrative, which means that scholars are imposing meaning on respondents’ experiences. Consequently, there may arise the problem of the misinterpretation of data.

The next ambiguous issue is the subjectivity of the study on the part of a researcher (Caine et al., 2019). Because some of the personal narratives are ambiguous, it is impossible to rule out researchers’ personal assessment of the situations, through the prism of which respondents’ narrations may be altered from what they were meant to uncover initially. Narrative inquirers should also bear in mind that their relationships with the participants can affect the final result of the study (Law & Chan, 2015). Therefore, researchers should be cautious of their own interpretations of the respondents’ narratives, as well as they should make sure that their interactions do not influence the final result.

In order to minimize the risk of the mentioned ethical issues in the current research, the following steps will be taken. Firstly, the researchers will make it a rule not to become too close or friendly with the participants in order to remain as objective as possible throughout the whole process of the study. Secondly, the researcher will listen to the narratives attentively and ask clarifying questions if needed, which will enable avoiding misinterpretations. Finally, at all stages of the research project, the researcher will refrain from offering a personal assessment of situations described by participants. By following these steps, it will become possible to avoid the most viable ethical concerns.

Summary of Research

Research on the topic of online gaming addiction available so far is rich in directions of investigation. Scholars have analyzed individuals’ disposition toward engaging in online gaming (Balakrishnan & Griffiths, 2018; Pietersen et al., 2018; Tang et al., 2017), the desire for online group gaming (Gong et al., 2019), and dysfunctional cognitions associated with Internet gaming disorder (Marino & Spada, 2017). These and other topics of research allowed for an in-depth understanding of the research question, but they have not answered all the questions related to online gaming addiction.

A connection between individuals’ loyalty toward online gaming and developing online gaming addiction has been found. Research findings reveal that addiction to online mobile games is associated with game loyalty (Balakrishnan & Griffiths, 2018). Furthermore, scholars report a positive relationship between online gaming addiction and the tendency to purchase mobile in-game applications. Finally, researchers have investigated that online gaming loyalty boosts players’ desire to buy online game applications. However, researchers failed to provide a discussion of how these processes evolve.

A study by Gong et al. (2019) has resulted in finding a positive correlation between the desire for playing online games and addiction to this activity. Additionally, the authors have found that the desire for group gaming is connected with people’s social identities, expected enjoyment, and specific attitudes. However, the research lacks generalizability since Gong et al. (2019) have analyzed only one type of social game played online. Meanwhile, each online game has its own unique features aimed at supporting specific social ties, which can have different effects on players’ predisposition toward becoming addicted to playing.

Marino and Spada (2017) have examined the peculiarities of the gaming disorder with the help of a narrative review, which makes this study especially valuable in light of the selected topic and research design. Scholars report that online gaming-associated dysfunctional conditions are numerous, and their quantity increases with the growth of the industry. Marino and Spada (2017) remark that it is crucial to differentiate between dysfunctional cognitions and metacognitions in Internet gaming disorder. Implications for future research based on these findings include the comparison between dysfunctional cognitions and metacognitions with the aim of finding effective evidence-based treatment for online gaming addictive individuals.

Findings of Tang et al.’s (2017) research suggest that males are usually more addicted to online games than women, whereas females are more predisposed to online social networking addiction. Pietersen et al.’s (2018) study has resulted in valuable insights into what it is to be a gamer based on online gaming addicts’ personal narratives. Whereas these studies have addressed some of the aspects of online gaming and the development of addiction to it, more thorough research is needed in various dimensions of the research topic. Specifically, it is important to focus research on understanding the development of online gaming addiction and people’s feelings about it.

Abkhezr, P., McMahon, M., Campbell, M., & Glasheen, K. (2020). Exploring the boundary between narrative research and narrative intervention: Implications of participating in narrative inquiry for young people with refugee backgrounds. Narrative Inquiry, 30 (2), 316-342. Web.

Androutsopoulou, A., & Stefanoua, M. M. (2018). Seeking “home”: Personal narratives and turning points in the lives of adult homeless. The European Journal of Counselling Psychology , 7 (1), 126-147. Web.

Balakrishnan, J., & Griffiths, M. D. (2018). Loyalty towards online games, gaming addiction, and purchase intention toward online mobile in-game features. Computers in Human Behavior , 87 , 238-246. Web.

Bruce, A., Beuthin, R., Sheilds, L., Molzahn, A., & Schick-Makaroff, K. (2016). Narrative research evolving: Evolving through narrative research. International Journal of Qualitative Methods, 15 (1), 1-6. Web.

Byrne, G. (2015). Narrative inquiry and the problem of representation: “Giving voice”, making meaning. International Journal of Research & Method in Education, 40 (1), 36-52. Web.

Caine, V., Chung, S., Steeves, P., & Clandinin, D. J. (2019). The necessity of a relational ethics alongside Noddings’ ethics of care in narrative inquiry. Qualitative Research, 20 (3), 265-276. Web.

Chen, J. C. (2019). Restorying a “newbie” teacher’s 3d virtual teaching trajectory, resilience, and professional development through action research: A narrative case study. TESOL Quarterly, 54 (2), 375-403. Web.

Dollah, S., Abduh, A., & Rosmaladewi. (2017). Benefits and drawbacks of NVivo QSR application. Advances in Social Science, Education and Humanities Research, 149 , 61-63. Web.

Gong, X., Zhang, K. Z. K., Cheung, C. M., Chen, C., & Lee, M. K. O. (2019). Alone or together? Exploring the role of desire for online group gaming in players’ social game addiction. Information & Management , 56 (6). Web.

Gordon, L. J., Rees, C. E., Ker, J. S., & Cleland, J. (2015). Leadership and followership in the healthcare workplace: Exploring medical trainees’ experiences through narrative inquiry. BMJ Open, 5 , e008898. Web.

Harfitt, G. J. (2015). From attrition to retention: A narrative inquiry of why beginning teachers leave and then rejoin the profession. Asia-Pacific Journal of Teacher Education, 43 (1), 22-35. Web.

Haydon, G., Browne, G., & van der Riet, P. (2018). Narrative inquiry as a research methodology exploring person centred care in nursing. Collegian, 25 (1), 125-129. Web.

Heilmann, S. (2018). A scaffolding approach using interviews and narrative inquiry networks. An Online Journal for Teacher Research, 20 (2). Web.

Ho, I. K., Newton, T. L., & McCabe, A. (2020). The narrative structure of stressful interpersonal events. Narrative Inquiry , 30 (1), 1-17. Web.

Hu, J., Zhen, S., Yu, C., Zhang, Q., & Zhang, W. (2017). Sensation seeking and online gaming addiction in adolescents: A moderated mediation model of positive affective associations and impulsivity. Frontiers in Psychology, 8 . Web.

James, G. (2018). A narrative inquiry perspective into coping mechanisms of international postgraduate students’ transition experiences. American Journal of Qualitative Research , 2 (1), 41-56.

Kovinthan, T. (2016). Learning and teaching with loss: Meeting the needs of refugee children through narrative inquiry. Diaspora, Indigenous, and Minority Education, 19 (3), 141-155. Web.

Law, B. Y.-S., & Chan, E. A. (2015). The experience of learning to speak up: A narrative inquiry on newly graduated registered nurses. Journal of Clinical Nurses, 24 , 1837-1848. Web.

Marino, C., & Spada, M. M. (2017). Dysfunctional cognitions in online gaming and internet gaming disorder: A narrative review and a new classification. Current Addiction Reports , 4 (3), 308-316. Web.

Martinie, S. L., Kim, J.-H., & Abernathy, D. (2016). “Better to be a pessimist”: A narrative inquiry into mathematics teachers’ experience of the transition to the Common Core. The Journal of Educational Research, 109 (6), 658-665. Web.

McAlpine, L. (2016). Why might you use narrative methodology? A story about narrative. Eesti Haridusteaduste Ajakiri, 4 (1), 32-57. Web.

Monacis, L., de Palo, V., Griffiths, M. D., & Sinatra, M. (2017). Exploring individual differences in online addictions: The role of identity and attachment. International Journal of Mental Health and Addiction, 15 , 853-868. Web.

Nolan, S., Hendricks, J., Williamson, M., & Ferguson, S. (2017). Using narrative inquiry to listen to the voices of adolescent mothers in relation to their use of social networking sites (SNS). Journal of Advanced Nursing, 74 (3), 743-751. Web.

Pietersen, A. J., Coetzee, J. K., Byczkowska-Owczarek, D., Elliker, F., & Ackermann, L. (2018). Online gamers, lived experiences, and sense of belonging: Students at the University of the Free State, Bloemfontein. Qualitative Sociology Review , 14 (4), 122-137. Web.

Sheilds, L., Molzahn, A., Bruce, A., Schick Makaroff, K., Stajduhar, K., Beuthin, R., & Shermak, S. (2015). Contrasting stories of life-threatening illness: A narrative inquiry. International Journal of Nursing Studies, 52 (1), 207–215. Web.

Šporčić, B., & Glavak-Tkalić, R. (2018). The relationship between online gaming motivation, self-concept clarity and tendency toward problematic gaming. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 12 (1). Web.

Tang, C. S. K., Koh, Y. W., & Gan, Y. (2017). Addiction to Internet use, online gaming, and online social networking among young adults in China, Singapore, and the United States. Asia Pacific Journal of Public Health , 29 (8), 673-682. Web.

Wang, C. C., & Geale, S. K. (2015). The power of story: Narrative inquiry as a methodology in nursing research. International Journal of Nursing Sciences, 2 (2), 195-198. Web.

Zamawe, F. C. (2015). The implication of using NVivo software in qualitative data analysis: Evidence-based reflections. Malawi Medical Journal, 27 (1), 13-15. Web.

Chicago (A-D)
Chicago (N-B)

IvyPanda. (2022, September 27). Addiction to Online Gaming: A Review of Literature. https://ivypanda.com/essays/addiction-to-online-gaming-a-review-of-literature/

"Addiction to Online Gaming: A Review of Literature." IvyPanda , 27 Sept. 2022, ivypanda.com/essays/addiction-to-online-gaming-a-review-of-literature/.

IvyPanda . (2022) 'Addiction to Online Gaming: A Review of Literature'. 27 September.

IvyPanda . 2022. "Addiction to Online Gaming: A Review of Literature." September 27, 2022. https://ivypanda.com/essays/addiction-to-online-gaming-a-review-of-literature/.

1. IvyPanda . "Addiction to Online Gaming: A Review of Literature." September 27, 2022. https://ivypanda.com/essays/addiction-to-online-gaming-a-review-of-literature/.

Bibliography

IvyPanda . "Addiction to Online Gaming: A Review of Literature." September 27, 2022. https://ivypanda.com/essays/addiction-to-online-gaming-a-review-of-literature/.

Coding Using NVivo 9 in Research
Qualitative Data Analysis Recommendations
Qualitative Coding with Hands or Software
Online Gaming Addiction Intervention
Online Gaming Addiction Analysis
When Gaming Is Good for You?
Technology and Parenting: Gaming and Social Media
Gambling and Gaming Industry
Online gaming and behavior
The Gaming Industry in the USA
Playing Video Games Can Help to Control Dreams
Does Video Game Violence Lead to Aggression in Children?
Video Games as a Way to Fix Reality
The Impact of Video Games on the Human Psyche
Natural Law and Video Games

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

We're Hiring!
Help Center

Social Effects of Online Game Addiction in Adolescents: A Systematic Review

This study aimed to determine the social effects of online game addiction in adolescents and increase our knowledge of adolescents who experience online game addiction. This was a systematic review of the literature using the Scopus, Science Direct and SAGE Journals databases during five years with a randomized controlled trial. All the studies included online game addiction, focusing on the effect of social influence on online gaming addiction in adolescents. Based on the findings of 15 research articles used showed that there was a social influence on online gaming addiction experienced by adolescents. Social constraints proved to be an essential factor in the excessive internet use of adolescents. Other findings showed that associated internet gaming disorders and a lack of attention suggests that individualistic cultural orientations exacerbate these relationships without gender differences

Related Papers

Polish Journal of Public Health

Jolanta Szymańska

Introduction. Dependence on the Internet and online games is a growing problem worldwide. Aim. The aim of this study was to determine the differences between girls and boys as well as between adolescents living in urban vs. rural areas in regard to prevalence of playing online games, the amount of time devoted to playing games, the severity of symptoms of online gaming addiction, and preferences for game genres. Also, significant predictors of online game addiction in the studied group of young people were identified. Material and methods. The study involved 827 adolescents aged 14 to 19 years. When it comes to 488 (60.02%) of them, they lived in the countryside and 325 (39.98%) in a city. The following instruments were used: a sociodemographic questionnaire, the Online Gaming Addiction Questionnaire and the Disturbed Family Relations Questionnaire, all developed by Pawłowska and Potembska. Results. Statistically significant differences were found between girls and boys and between ...

Mark D Griffiths

Research suggests that excessive online gaming may lead to symptoms commonly experienced by substance addicts. Since games are particularly appealing to children and adolescents, these individuals may be more at risk than other groups of developing gaming addiction. Given these potential concerns, a literature review was undertaken in order (i) to present the classification basis of online gaming addiction using official mental disorder frameworks, (ii) to identify empirical studies that assess online gaming addiction in children and adolescents, and (iii) to present and evaluate the findings against the background of related and established mental disorder criteria. Empirical evidence comprising 30 studies indicates that for some adolescents, gaming addiction exists and that as the addiction develops, online gaming addicts spend increasing amounts of time preparing for, organizing, and actually gaming. Further evidence suggests that problematic online gaming can be conceptualized as a behavioral addiction rather than a disorder of impulse control.

Selahattin Çavuş , Bünyamin AYHAN

This study carried out in order to analyze the characteristics of game addiction among the adolescents. The research was tackled within the frame of screening model and data was collected in accordance with it. The questionnaire used as a data collecting instrument was applied in a secondary school and a high school which are considered to have the capacity of representing the socioeconomic and cultural structure of Selçuklu district of Konya province. After the analysis, it was determined that the average of the boys as for game addiction were higher than those of girls. Moreover, the boys were observed to spend more money on games. The socioeconomic reasons such as educational status of parents, the number of siblings, having computers and having a private room weren't seen to be discriminative characteristics. However, a differentiation related to addiction was observed among genders and stages. The research suggests that it is necessary to activate the patterns of social communication networks such as friendly footing, taking more responsibilities, and highlighting social life to diminish game addiction.

Research suggests that excessive online gaming may lead to symptoms commonly experienced by substance addicts. Since games are particularly appealing to children and adolescents, these individuals may be more at risk than other groups of developing gaming addiction. Given these potential concerns, a literature review was undertaken in order (i) to present the classification basis of online gaming addiction using official mental disorder frameworks, (ii) to identify empirical studies that assess online gaming addiction in children and adolescents, and (iii) to present and evaluate the findings against the background of related and established mental disorder criteria. Empirical evidence comprising 30 studies indicates that for some adolescents, gaming addiction exists and that as the addiction develops, online gaming addicts spend increasing amounts of time preparing for, organizing, and actually gaming. Evidence suggests that problematic online gaming can be conceptualized as a behavioral addiction rather than a disorder of impulse control.

Research suggests that excessive online gaming may lead to symptoms commonly experienced by substance addicts. Since games are particularly appealing to children and adolescents, these groups may be more at risk than other groups of developing gaming addiction. Given these potential concerns, a literature review was undertaken in order (i) to present the classification basis of online gaming addiction using official mental disorder frameworks, (ii) to identify empirical studies that assess online gaming addiction in children and adolescents, and (iii) to present and evaluate the findings against the background of related and established mental disorder criteria. Empirical evidence comprising 30 studies indicates that for some adolescents, gaming addiction exists and that as the addiction develops, online gaming addicts spend increasing amounts of time preparing for, organizing, and actually gaming. Further evidence suggests that problematic online gaming can be conceptualized as a behavioral addiction rather than a disorder of impulse control.

Belitung Nursing Journal

Siripattra Juthamanee

Background: Understanding factors influencing Internet and game addiction in children and adolescents is very important to prevent negative consequences; however, the existing factors in the literature remain inconclusive.Objective: This study aims to systematically map the existing literature of factors related to Internet and game addiction in adolescents.Methods: A scoping review was completed using three databases - Science Direct, PROQUEST Dissertations and Theses, and Google Scholar, which covered the years between 2009 to July 2020. Quality appraisal and data extraction were presented. A content analysis was used to synthesize the results.Results: Ultimately, 62 studies met inclusion criteria. There were 82 associated factors identified and grouped into 11 categories, including (1) socio-demographic characteristics, (2) parental and family factors, (3) device ownership, Internet access and location, social media, and the game itself, (4) personality/traits, psychopathology fa...

International Journal of Advanced Computer Science and Applications

Maha A B D U L L A H AlDwehy

Open Access Macedonian Journal of Medical Sciences

ira nurmala

International Conference on Humanities, Social and Education Sciences

Mustafa Tevfik Hebebci

Digital games are tools where individuals from all ages have fun, socialize, and spend time. They have positive effects as well as negative effects. One of the most notable negative effects is addiction. In general terms, digital game addiction is playing games without control. To that end, this study examines adolescents' digital game addictions by their digital game tendencies, gender, and gaming spending. In this direction, the research sample consists of a total of 191 adolescents, 90 female and 101 male. Descriptive statistics and independent samples t-tests were used in the data analysis. When the digital game-playing tendencies of adolescents are analyzed, it is concluded that the games are generally played on the smartphone, are in the battle royale type, and are played for entertainment purposes. Another result collected in the study is that the mean addiction score is statistically significantly higher for males than for females and for those who spend money on games compared to those who do not. The research results were discussed in relation to the studies in the literature, and suggestions were made.

Patti Valkenburg

RELATED PAPERS

Texas Heart Institute journal / from the Texas Heart Institute of St. Luke's Episcopal Hospital, Texas Children's Hospital

Michael Reardon

European Heart Journal

South American Journal of Basic Education, Technical and Technological

Luciana Ogando

Charles Riedhauser

Biological Chemistry

Rolf Heumann

John Gribben

Hirofumi Daiguji

Orthopedic Research and Reviews

calogero foti

Educação, Gênero e Sexualidade: perspectiva crítica e decolonial no espaço escolar e não-escolar

John Jamerson da Silva Brito

Editorial ILAE

Alejandro Gómez Jaramillo

Journal of Differential Equations

Marius Tucsnak

Emmy Yuanita

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

hugo marques

Families in Society: The Journal of Contemporary Social Services

Julian Stallabrass

Proceedings of the National Academy of Sciences

Seung-Yong Seo

Trilita Apriani

Intus Legere Historia

Erwin Robertson

Journal of Computing in Civil Engineering

Magued Iskander

Remote Sensing

Riccardo Lanari

ihssan elfahssi

Ruben Florio

Merpati: Media Publikasi Pengabdian Kepada Masyarakat Politeknik Pos Indonesia

Irayanti Adriant

Vol. 8 No.2 NJNS

NJNS NUST , Momna Arooj Malik

Valorando el pluralsimo

Cristóbal Astorga

European Biophysics Journal

Eva Zerovnik

Expert advice on gaming addiction in young people and children

Jason Shiers Dip.Psyh MBACP is a Certified Transformative Coach & Certified Psychotherapist who is Creative Innovations Manager for UK Addiction Treatment.

In 2019, the global games market was worth $152 billion. With growing concerns about the amount of time children and teenagers spend playing online games and the impact it can have, Psychotherapist Jason Shiers, shares his insight on gaming addiction in children.

81% of under 18s regularly play online games and in moderation, gaming can be fun, sociable and interactive with opportunities for children and young people to learn and solve problems. Most will not experience any harm but there are known impacts of gaming addiction in children you need to be aware of:

Gaming addiction and financial concerns

Social relationships

Effects of gaming addiction on physical health

Effects of gaming addiction on education and personal growth
Gaming addiction effect on mental health

Tips to combat bad gaming habits in children

Gaming addiction and financial concerns
Effects of gaming on physical health

Tips to combat bad gaming habits in children

Games that have in-app purchases to buy ‘tokens’ or ‘passes’ could possibly lead to children running up unexpected credit card bills for parents and carers..

To access games, many platforms or developers require credit card details sometimes even for free downloads. Unless sufficient parental controls are set up – for example, password protection, spending restrictions, and alerts, separate accounts for children or unlinking credit cards from the child’s device – then parents can be stung with big bills for in-game purchases.

What are in-game and in-app purchases? Although many games are free-to-play, they also include premium features that you have to pay for to access. These could include certain characters, points or virtual currency. So children may use real money in the game to buy these items to enhance their gameplay or progress further in the game.
Can you get a refund for unauthorised in-game purchases? If your child accidentally spends too much on in-game purchases getting a refund depends on the terms and conditions of the gaming platform or game developer. It’s not always possible to claim the money back – including in cases where parental controls aren’t set up properly.
One of the biggest gaming sensations, Fortnite , does offer refunds for unauthorised purchases by children – but there’s a limit on how many times they will do this. Other platforms and developers are much less flexible.
What are loot boxes and what are the risks for children? Loot boxes unlock special features, characters or items in a game. However, they come with a fee and players do not know what’s inside until they have paid. So, you could receive items you really want or nothing of use. Loot boxes have been criticised globally for promoting underage gambling and encouraging multiple purchases. In the UK, there have been calls to ban the sale of loot boxes to children.
Getting into debt If parents can’t get a refund for unauthorised purchases, they can find themselves with a large debt that is accumulating interest. Sometimes parents insist that their child pays back the debt – including by docking pocket money, reducing spending on other treats or by asking teenagers for contributions from earnings. Children and young adults can also run up large debts from gaming – including students with first-time access to loans and credit cards.
Legal issues In extreme cases, parents have reported their children to the police for ‘friendly fraud’ . This is usually when they have been unsuccessful in getting a refund for in-game purchases. Although rare, this puts young people at risk of being questioned by the police and even criminalised.

Effects of gaming addiction on education and personal growth

Implications of excessive gaming may result in harmful effects on children’s education and wellbeing..

Interference with studies – One of the signs of gaming addiction is the impact on other areas of life. If school work is suffering – including boredom in lessons, difficulty concentrating or low motivation to complete homework – then their gaming habits should be assessed.
Exposure to violent, graphic or sexualised content – Ofcom found that increasing numbers of parents are concerned about the content of games they play. This includes 25% of parents of 3-4-year-old gamers (compared to 10% in 2017). Most major titles do come with age guidance but as with films or TV shows, many children access the content at a younger age. Fortnite, for example, is rated 12+ – yet many primary school-age children play.

Games with violent, sexualised or highly realistic content (including augmented reality and virtual reality games) can also have an emotional impact on children, especially the younger kids . It’s a controversial area with conflicting research but a study from Science Daily has linked violent video games to aggression in young people.

Social relationships

If gaming is at the expense of connection with friends in real life, then this withdrawal can affect relationship skills in everyday situations..

Gaming can be a social activity. Whether playing with siblings on a console or competing with friends online, there are benefits for social development in gameplay. Increasingly, children and young people are playing games online. In 2018, Ofcom found that three-quarters of 5-15-year-old gamers only ever play online – up from two-thirds in 2017.

Gaming addiction effect on mental health

All of the following elements can indicate gaming addiction. these symptoms tend to be more pronounced when children or young people are not gaming – including if they are prevented from playing..

Anger or rage – If a parent interrupts a gaming session or broadband goes down, what is the reaction? If children or young people respond with anger or rage – including shouting, screaming or physical attacks, then this is something worth noting.
Compulsivity – Is there a strong sense of urgency to get back to gaming? Is it difficult to pull yourself away? With children and young people, compulsive play can manifest in playing past switch-off times, late at night or secretively.
Isolation and loneliness – If children spend long periods of time playing games by themselves, this reduces interaction with relatives and friends in real life. Though many young gamers use online chat in multiplayer games, including to talk to friends in real life – this should be balanced with interactions in the same physical space.
Depression – In regular gamers, ongoing listlessness, sadness or lethargy can be signs of problem gaming. Depressive symptoms will be most apparent when they are not playing the game – i.e. in the withdrawal phase.

Effects of gaming addiction on physical health

Excessive gaming repeatedly over long periods can potentially cause physical strain on gamers..

Repetitive strain injury (RSI) Children and young people who play games for extended periods can be affected by RSI. Stiffness, aches, pain and numbness are signs to watch out for. For example, ‘nintendinitis’ refers to thumb, wrist and hand problems associated with playing on gaming consoles. Eye strain is also common if you look at screens for long periods without taking breaks. Screen glare can also affect vision.
Poor posture If you’re slouching in a chair or you’re hunched over your mobile, then it’s time to take a break. Whilst these positions won’t harm most children immediately, they can lead to serious problems in adulthood.
Headaches and migraines Headaches may be related to physical causes such as eye strain, bad posture or dehydration. Or they may be related to mental health issues – including anxiety and depression. Young gamers who get regular headaches should get checked out by a doctor.
Lack of physical activity Playing sedentary games for long periods can mean that people miss out on exercise. The World Health Organisation recommends that children and young people, aged 5 to 17, do at least 60 minutes of activity per day.
Poor nutrition or self-care When gaming addiction takes over, children and young people may skip meals, rely on junk food, resist taking toilet breaks or have poor hygiene.
Poor quality sleep Playing stimulating games for many hours at a time, particularly late at night, will make it harder to get to sleep.

It’s understandable to believe that if you can get your child’s gaming under control, then everything will return to normal. However, every addiction is best understood as a symptom rather than the problem. For this reason, telling your child to reduce their gaming, punishing them for breaking rules or restricting their access to devices, probably won’t solve their difficulties permanently.

The key to real change is this – what is so distressing or unsatisfactory about your child’s life when s/he is not gaming? To overcome gaming addiction, your son or daughter will need help to discover the answers to this question, as well as learning how to cope in healthier ways.

Of course, it’s an important step for your child to acknowledge the consequences of harmful gaming, including how health, relationships, education and finances are affected – but this is only the start. Lasting recovery from gaming disorder comes through awareness and emotional resilience . Your child needs to know how to recognise and handle emotional distress including when they crave game play.

More to Explore

See more resources and articles to support children online:

Advice for 11-13 years
Advice for 14+ year olds
Advice for 6-10 years
Online gaming resources
Support wellbeing with tech

On site links

Online gaming – the basics
Online safety issues
Just Jack – a positive experience in the digital world
Top 9 age-specific video games for children to play during holidays

Download Workbook

To receive personalised online safety guidance in the future, we’d like to ask for your name and email. Simply fill your details below. You can choose to skip, if you prefer.
First name *
Last name *
Email Address *
I am a * Parent/Carer Teacher Professional
Organisation name
Skip and download
Comments This field is for validation purposes and should be left unchanged.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List

Internet and Gaming Addiction: A Systematic Literature Review of Neuroimaging Studies

In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction. Internet addiction has been considered as a serious threat to mental health and the excessive use of the Internet has been linked to a variety of negative psychosocial consequences. The aim of this review is to identify all empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging studies offer an advantage over traditional survey and behavioral research because with this method, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. A systematic literature search was conducted, identifying 18 studies. These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction led to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains. The paper shows that understanding the neuronal correlates associated with the development of Internet and gaming addiction will promote future research and will pave the way for the development of addiction treatment approaches.

1. Introduction

In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction (e.g., [ 1 , 2 , 3 , 4 ]). Clinical evidence suggests that Internet addicts experience a number of biopsychosocial symptoms and consequences [ 5 ]. These include symptoms traditionally associated with substance-related addictions, namely salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse [ 6 ]. Internet addiction comprises a heterogeneous spectrum of Internet activities with a potential illness value, such as gaming, shopping, gambling, or social networking. Gaming represents a part of the postulated construct of Internet addiction, and gaming addiction appears to be the most widely studied specific form of Internet addiction to date [ 7 ]. Mental health professionals’ and researchers’ extensive proposals to include Internet addiction as mental disorder in the forthcoming fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) will come to fruition as the American Psychiatric Association accepted to include Internet use disorder as mental health problem worthy of further scientific investigation [ 8 ].

The excessive use of the Internet has been linked to a variety of negative psychosocial consequences. These include mental disorders such as somatization, obsessive-compulsive and other anxiety disorders, depression [ 9 ], and dissociation [ 10 ], as well as personality traits and pathology, such as introversion and psychoticism [ 11 ]. Prevalence estimates range from 2% [ 12 ] to 15% [ 13 ], depending on the respective sociocultural context, sample, and assessment criteria utilized. Internet addiction has been considered as serious threat to mental health in Asian countries with extensive broadband usage, particularly South Korea and China [ 14 ].

1.1. The Rise of Neuroimaging

In accordance with Cartesian dualism, the French philosopher Descartes advocated the view that the mind is an entity that is separate from the body [ 15 ]. However, the cognitive neurosciences have proved him wrong and reconcile the physical entity of the body with the rather elusive entity of the mind [ 16 ]. Modern neuroimaging techniques link cognitive processes ( i.e. , Descartes’ thinking mind ) to actual behavior ( i.e. , Descartes’ moving body ) by measuring and picturing brain structure and activity. Altered activity in brain areas associated with reward, motivation, memory, and cognitive control has been associated with addiction [ 17 ].

Research has addressed the neural correlates of drug addiction development via classical and operant conditioning [ 18 , 19 ]. It has been found that during the initial stages of the voluntary and controlled usage of a substance, the decision to use the drug is made by specific brain regions, namely the prefrontal cortex (PFC) and ventral striatum (VS). As habituation to use and compulsion develops, brain activity changes in that the dorsal regions of the striatum (DS) become increasingly activated via dopaminergic innervation ( i.e. , dopamine release) [ 20 ]. Long term drug use leads to changes in the brain dopaminergic pathways (specifically the anterior cingulate (AC), orbitofrontal cortex (OFC), and the nucleus accumbens (NAc) which may lead to a reduction of sensitivity to biological rewards and it decreases the individual’s control over seeking and eventually taking drugs. [ 21 , 22 ]. On a molecular level, the long-term depression (LTD; i.e. , the reduction) of synaptic activity has been linked to the adaptation of the brain as a result of substance-related addictions [ 23 ]. Drug addicts become sensitized to the drug because in the course of prolonged intake, the synaptic strength in the ventral tegmental area increases, and so does the LTD of glutamate in the nucleus accumbens, which will result in craving [ 24 ].

At the same time, the brain ( i.e. , NAc, OFC, DLPFC) becomes increasingly responsive to drug cues (e.g., availability, particular context) via craving [ 21 , 25 ]. Craving for drug use involves a complex interaction between a variety of brain regions. Activity in the nucleus accumbens following recurrent drug intake leads to learning associations between drug cues and the reinforcing effects of the drug [ 26 ]. In addition, the orbitofrontal cortex, important for the motivation to engage in behaviors, the amygdala (AMG) and the hippocampus (Hipp), as main brain regions associated with memory functions, play a role in intoxication and craving for a substance [ 17 ].

Natural rewards, such as food, praise, and/or success gradually lose their hedonic valence. Due to habituation to rewarding behaviors and intake of drugs, a characteristic addiction symptom develops ( i.e. , tolerance). Increasing amounts of the substance or increasing engagement in the respective behaviors are needed in order to produce the desired effect. As a result, the reward system becomes deficient. This leads to the activation of the antireward system that decreases the addict’s capacity for experiencing biological reinforcers as pleasurable. Instead, he requires stronger reinforcers, i.e. , their drug or behavior of choice, in larger amounts ( i.e. , tolerance develops) to experience reward [ 27 ]. In addition, the lack of dopamine in the mesocorticolimbic pathways during abstinence explains characteristic withdrawal symptoms. These will be countered with renewed drug intake [ 17 ]. Relapse and the development of a vicious behavioral cycle are the result [ 28 ]. Prolonged drug intake and/or engagement in a rewarding behavior leads to changes in the brain, including dysfunctions in prefrontal regions, such as the OFC and the cingulate gyrus (CG) [ 17 , 29 ].

Research indicates that brain activity alterations commonly associated with substance-related addictions occur following the compulsive engagement in behaviors, such as pathological gambling [ 30 ]. In line with this, it is conjectured that similar mechanisms and changes are involved in Internet and gaming addiction. The aim of this review is therefore to identify all peer-reviewed empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging broadly includes a number of distinct techniques. These are Electroencephalogram (EEG), Positron Emission Tomography (PET), SPECT Single Photon Emission Computed Tomography (SPECT), functional Magnetic Resonance Imaging (fMRI), and structural magnetic resonance imaging (sMRI), such as Voxel-based Morphometry (VBM), and Diffusion-Tensor Imaging (DTI). These are briefly explained in turn before examining the studies that have utilized these techniques for studies on Internet and gaming addiction.

1.2. Types of Neuroimaging Used to Study Addictive Brain Activity

Electroencephalogram (EEG): With an EEG, neural activity in the cerebral cortex can be measured. A number of electrodes are fixed to specific areas ( i.e. , anterior, posterior, left and right) of the participant’s head. These electrodes measure voltage fluctuations ( i.e. , current flow) between pairs of electrodes that are produced by the excitation of neuronal synapses [ 31 ]. With event-related potentials (ERPs), the relationships between the brain and behavior can be measured via an electrophysiological neuronal response to a stimulus [ 32 ].

Positron Emission Tomography (PET): PET is a neuroimaging method that allows for the study of brain function on a molecular level. In PET studies, metabolic activity in the brain is measured via photons from positron emissions ( i.e. , positively charged electrons). The subjected is injected with a radioactive 2-deoxyglucose (2-DG) solution that is taken up by active neurons in the brain. The amounts of 2-DG in neurons and positron emissions are used to quantify metabolic activity in the brain. Thus, neuronal activity can be mapped during the performance of a particular task. Individual neurotransmitters can be distinguished with PET, which makes the latter advantageous over MRI techniques. It can measure activity distribution in detail. Limitations to PET include relatively low spatial resolution, time needed to obtain a scan, as well as potential radiation risk [ 33 ].

Single Photon Emission Computed Tomography (SPECT): SPECT is a subform of PET. Similar to PET, a radioactive substance (a “tracer”) is injected into the blood stream that rapidly travels to the brain. The stronger the metabolic activity in specific brain regions, the stronger the enrichment of gamma rays. The emitted radiation is measured in accordance with brain layers, and metabolic activity is imaged using computerized techniques. Unlike PET, SPECT allows for counting individual photons, however, its resolution is poorer because with SPECT, resolution depends on the proximity of the gamma camera that measures neuronal radioactivity [ 34 ].

Functional Magnetic Resonance Imaging (fMRI): With fMRI, changes in the levels of blood oxygen in the brain are measured that are indicative of neuronal activity. Specifically, the ratio of oxyhemoglobin ( i.e. , hemoglobin that contains oxygen in the blood) to deoxyhemoglobin ( i.e. , hemoglobin that has released oxygen) in the brain is assessed because blood flow in “active” brain areas increases to transport more glucose, also bringing in more oxygenated hemoglobin molecules. The assessment of this metabolic activity in the brain allows for finer and more detailed imaging of the brain relative to structural MRI. In addition to this, the advantages of fMRI include speed of brain imaging, spatial resolution, and absence of potential health risk relative to PET scans [ 35 ].

Structural Magnetic Resonance Imaging (sMRI): sMRI uses a variety of techniques to image brain morphology [ 36 ]. One such technique is Voxel-Based Morphometry (VBM) . VBM is used to compare the volume of brain areas and the density of gray and white matter [ 37 ]. Another sMRI technique is Diffusion-Tensor Imaging (DTI) . DTI is a method used for picturing white matter. It assesses the diffusion of water molecules in the brain which helps to identify interconnected brain structures by using fractional anisotropy (FA). This measure is an indicator of fiber density, axonal diameter, and myelination in white matter [ 38 ].

A comprehensive literature search was conducted using the database Web of Knowledge . The following search terms (and their derivatives) were entered with regards to Internet use: “addiction”, “excess”, “problem”, and “compulsion”. Moreover, additional studies were identified from supplementary sources, such as Google Scholar , and these were added in order to generate a more inclusive literature review. Studies were selected in accordance with the following inclusion criteria. Studies had to (i) assess Internet or online gaming addiction or direct effects of gaming on neurological functioning, (ii) use neuroimaging techniques, (iii) be published in a peer-reviewed journal, and (iv) be available as full text in English language. No time period was specified for the literature search because neuroimaging techniques are relatively new, so that the studies were expected to be recent ( i.e. , almost all having been published between 2000 and 2012).

A total of 18 studies were identified that fulfilled the inclusion criteria. Of those, the method of data acquisition was fMRI in eight studies [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ] and sMRI in two studies [ 47 , 48 ], two studies used PET scans [ 49 , 50 ], one of which combined it with an MRI [ 49 ], one used SPECT [ 51 ], and six studies utilized EEG [ 52 , 53 , 54 , 55 , 56 , 57 ]. It should also be noted that two of these were actually the same study with one published as a letter [ 53 ] and one published as a full paper [ 54 ]. One study [ 57 ] met all the criteria but was excluded because the diagnosis details of Internet addiction were insufficient to make valid conclusions. Furthermore, two studies did not directly assess Internet and gaming addiction [ 43 , 50 ], but assessed the direct effects of gaming on neurological activity using an experimental paradigm, and were therefore retained in the review. Detailed information on the included studies are presented in Table 1 .

Included studies.

3.1. fMRI Studies

Hoeft et al . [ 43 ] investigated gender differences in the mesocorticolimbic system during computer-game play among 22 healthy students (age range = 19–23 years; 11 females). All participants underwent fMRI (3.0-T Signa scanner (General Electric, Milwaukee, WI, USA), completed the Symptom Checklist 90-R [ 58 ], and the NEO-Personality Inventory-R [ 59 ]. FMRI was carried out during 40 blocks of either a 24-s ball game with the goal being to gain space or a similar control condition that did not include a specific game goal (as based on its structural makeup). Results indicated that there was an activation of neural circuitries that are involved in reward and addiction in the experimental condition ( i.e. , insula, NAc, DLPFC, and OFC). Consequently, the presence of an actual game goal (a characteristic of most conventional online games that are rule-based rather than pure role-playing games), modified brain activity via behavior. Here, a clear cause and effect relationship is evident, which adds strength to the findings.

Results also showed that male participants had a larger activation (in rNAc, blOFC, rAMG) and functional connectivity (lNAc, rAMG) in the mesocorticolimbic reward system when compared to females. The results furthermore indicated that playing the game activated the right insula (rI; signals autonomic arousal), right dorso-lateral PFC (maximize reward or change behavior), bilateral premotor cortices (blPMC; preparation for reward) and the precuneus, lNAc, and the rOFC (areas involved in visual processing, visuo-spatial attention, motor function, and sensori-motor transformation) compared to the resting state [ 43 ]. The insula has been implicated in conscious craving for addictive substances by implicating decision-making processes involving risk and reward. Insula dysfunction may explain neurological activities indicative of relapse [ 60 ]. Due to its experimental nature, this study was able to provide insight into idiosyncratic brain activation as a consequence of gaming in a healthy ( i.e. , non-addicted) population.

Ko et al . [ 44 ] attempted to identify the neural substrates of online gaming addiction by assessing brain areas involved in urge to engage in online games among ten male online gaming addicts (playing World of Warcraft for more than 30 h a week) compared to ten male controls (whose online use was less than two hours a day). All participants completed the Diagnostic Criteria for Internet Addiction for College Students (DCIA-C; [ 74 ]), the Mini-International Neuropsychiatric Interview [ 75 ], the Chen Internet Addiction Scale (CIAS) [ 71 ], the Alcohol Use Disorder Identification Test (AUDIT) [ 76 ], and the Fagerstrom Test for Nicotine Dependence (FTND) [ 77 ]. The authors presented gaming-related and paired mosaic pictures during fMRI scanning (3T MRscanner), and contrasts in BOLD signals in both conditions were analyzed using a cue reactivity paradigm [ 25 ]. The results indicated cue induced craving that is common among those with substance dependence. There was a dissimilar brain activation among gaming addicts following the presentation of game relevant cues as compared to controls and compared to the presentation of mosaic pictures, including the rOFC, rNAc, blAC, mFC, rDLPFC, and the right caudate nucleus (rCN). This activation correlated with gaming urge and a recalling of gaming experience. It was argued that there is a similar biological basis of different addictions including online gaming addiction. The quasi-experimental nature of this study that artificially induced craving in an experimental and controlled setting allowed the authors to make conclusions as based on group differences, and thus linking online gaming addiction status to the activation of brain areas associated with symptoms of more traditional ( i.e. , substance-related) addictions.

Han et al . [ 42 ] assessed the differences in brain activity before and during video game play in university students playing over a seven-week period. All participants completed the Beck Depression Inventory [ 78 ], the Internet Addiction Scale [ 67 ], and a 7-point visual analogue scale (VAS) to assess craving for Internet video game play. The sample comprised 21 university students (14 male; mean age = 24.1 years, SD = 2.6; computer use = 3.6, SD = 1.6 h a day; mean IAS score = 38.6, SD = 8.3). These were further divided into two groups: the excessive Internet gaming group (who played Internet video games for more than 60 min a day over a 42-day period; n = 6), and general player group (who played less than 60 min a day over the same period; n = 15). The authors used 3T blood oxygen level dependent fMRI (using Philips Achieva 3.0 Tesla TX scanner) and reported that brain activity in the anterior cingulate and orbitofrontal cortex increased among the excessive Internet game playing group following exposure to Internet video game cues relative to general players. They also reported that increased craving for Internet video games correlated with increased activity in the anterior cingulate for all participants. This quasi-experimental study is insightful for it not only offered evidence for a dissimilar brain activity in online gaming addicts compared to a general player control group, but it also elucidated brain activation that occurs as a consequence of playing in both groups. This indicates that (i) craving for online games alters brain activity irrespective of addiction status and might therefore be seen as a (prodromal) symptom of addiction, and that (ii) addicted players can be distinguished from non-addicted online gamers by a different form of brain activation.

Liu et al . [ 45 ] administered the regional homogeneity (ReHo) method to analyze encephalic functional characteristics of Internet addicts under resting state. The sample comprised 19 college students with Internet addiction and 19 controls. Internet addiction was assessed using Beard and Wolf’s criteria [ 72 ]. FMRI using 3.0T Siemens Tesla Trio Tim scanner was performed. Regional homogeneity indicates temporal homogeneity of brain oxygen levels in brain regions of interest. It was reported that Internet addicts suffered from functional brain changes leading to abnormalities in regional homogeneity relative to the control group, particularly concerning the reward pathways traditionally associated with substance addictions. Among Internet addicts, brain regions in ReHo in resting state were increased (cerebellum, brainstem, rCG, bilateral parahippocampus (blPHipp), right frontal lobe, left superior frontal gyrus (lSFG), right inferior temporal gyrus (rITG), left superior temporal gyrus (lSTG) and middle temporal gyrus (mTG)), relative to the control group. The temporal regions are involved in auditory processing, comprehension and verbal memory, whereas the occipital regions take care of visual processing. The cerebellum regulates cognitive activity. The cingulate gyrus pertains to integrating sensory information, and monitoring conflict. The hippocampi are involved in the brain’s mesocorticolimbic system that is associated with reward pathways. Taken together, these findings provide evidence for a change in a variety of brain regions as a consequence of Internet addiction. As this study assessed regional homogeneity under a resting state, it is unclear whether the changes in the brain observed in Internet addicts are a cause or consequence of the addiction. Therefore, no causal inferences can be drawn.

Yuan et al . [ 46 ] investigated the effects of Internet addiction on the microstructural integrity of major neuronal fiber pathways and microstructural changes associated with the duration of Internet addiction. Their sample comprised 18 students with Internet addiction (12 males; mean age = 19.4, SD = 3.1 years; mean online gaming = 10.2 h per day, SD = 2.6; duration of Internet addiction = 34.8 months, SD = 8.5), and 18 non-Internet addicted control participants (mean age = 19.5 years, SD = 2.8). All participants completed the Modified Diagnostic Questionnaire for Internet Addiction [ 72 ], a Self-Rating Anxiety Scale (no details provided), and a Self-Rating Depression Scale (no details provided). The authors employed fMRI and used the optimized voxel-based morphometry (VBM) technique. They analyzed white matter fractional anisotropy (FA) changes by using diffusion tensor imaging (DTI) to discern brain structural changes as a consequence of Internet addiction length. The results showed that Internet addiction resulted in changes in brain structure, and that the brain changes found appear similar to those found in substance addicts.

Controlling for age, gender, and brain volume, it was found that among Internet addicts there was decreased gray matter volume in the bilateral dorsolateral prefrontal cortex (DLPFC), supplementary motor area (SMA), orbitofrontal cortex (OFC), cerebellum and the left rostral ACC (rACC), an increased FA of the left posterior limb of the internal capsule (PLIC), and reduced FA in white matter in the right parahippocampal gyrus (PHG). There was also a correlation between gray matter volumes in DLPFC, rACC, SMA, and white matter FA changes of PLIC with the length of time the person had been addicted to the Internet. This indicates that the longer a person is addicted to the Internet, the more severe brain atrophy becomes. In light of the method, it is unclear from the authors’ description in how far their sample included those who were addicted to the Internet per se , or to playing games online. The inclusion of a specific question asking about the frequency and duration of online gaming (rather than any potential other Internet activity) suggests that the group in question consisted of gamers. In addition to this, the presented findings cannot exclude any other factor that may be associated with Internet addiction (e.g., depressive symptomatology) that may have contributed to the increased severity of brain atrophy.

Dong et al . [ 39 ] examined reward and punishment processing in Internet addicts compared to healthy controls. Adult males ( n = 14) with Internet addiction (mean age = 23.4, SD = 3.3 years) were compared to 13 healthy adult males (mean age = 24.1 years, SD = 3.2). Participants completed a structured psychiatric interview [ 79 ], the Beck Depression Inventory [ 78 ], the Chinese Internet Addiction Test [ 62 , 63 ], and the Internet Addiction Test (IAT; [ 61 ]). The IAT measures psychological dependence, compulsive use, withdrawal, related problems in school, work, sleep, family, and time management. Participants had to score over 80 (out of 100) on the IAT to be classed as having Internet addiction. Furthermore, all those classed as Internet addicts spent more than six hours online every day (excluding work-related Internet use) and had done so for a period of more than three months.

All the participants engaged in a reality-simulated guessing task for money gain or loss situation using playing cards. The participants underwent fMRI with stimuli presented through a monitor in the head coil, and their blood oxygen level dependence (BOLD) activation was measured in relation to wins and losses on the task. The results showed that Internet addiction was associated with increased activation in the OFC in gain trials, and decreased anterior cingulate activation in loss trials compared to normal controls. Internet addicts showed enhanced reward sensitivity and decreased loss sensitivity when compared with the control group [ 39 ]. The quasi-experimental nature of this study allowed for an actual comparison of the two groups by exposing them to a gaming situation and thus artificially inducing a neuronal reaction that was a consequence of the engagement in the task. Therefore, this study allowed for the extrication of a causal relationship between exposure to gaming cues and the resulting brain activation. This may be considered as empirical proof for reward sensitivity in Internet addicts relative to healthy controls.

Han et al . [ 40 ] compared regional gray matter volumes in patients with online gaming addiction and professional gamers. The authors carried out fMRI using a 1.5 Tesla Espree scanner (Siemens, Erlangen) and carried out a voxel-wise comparison of gray matter volume. All participants completed the Structured Clinical Interview for DSM-IV [ 80 ], the Beck Depression Inventory [ 78 ], the Barratt Impulsiveness Scale-Korean version (BIS-K9) [ 81 , 82 ], and the Internet Addiction Scale (IAS) [ 67 ]. Those (i) scoring over 50 (out of 100) on the IAS, (ii) playing for more than four hours per day/30 h per week, and (iii) impaired behavior or distress as a consequence of online game play were classed as Internet gaming addicts. The sample comprised three groups. The first group included 20 patients with online gaming addiction (mean age = 20.9, SD = 2.0; mean illness duration = 4.9 years, SD = 0.9; mean playing time = 9.0, SD = 3.7 h/day; mean Internet use = 13.1, SD = 2.9 h/day; mean IAS scores = 81.2, SD = 9.8). The second group was comprised of 17 professional gamers (mean age = 20.8 years, SD = 1.5; mean playing time = 9.4, SD = 1.6 h/day; mean Internet use = 11.6, SD = 2.1 h/day; mean IAS score = 40.8, SD = 15.4). The third group included 18 healthy controls (mean age = 12.1, SD = 1.1 years; mean gaming = 1.0, SD = 0.7 h/day; mean Internet use = 2.8, SD = 1.1 h/day; mean IAS score = 41.6, SD = 10.6).

The results showed that gaming addicts had higher impulsiveness, perseverative errors, increased volume in left thalamus gray matter, and decreased gray matter volume in ITG, right middle occipital gyrus (rmOG), and left inferior occipital gyrus (lIOG) relative to the control group. Professional gamers had increased gray matter volume in lCG, and decreased gray matter in lmOG and rITG relative to the control group, increased gray matter in lCG, and decreased left thalamus gray matter relative to the problem online gamers. The main differences between the gaming addicts and the professional gamers lay in the professional gamers’ increased gray matter volumes in lCG (important for executive function, salience, and visuospatial attention) and gaming addicts’ left thalamus (important in reinforcement and alerting) [ 40 ]. Based on the non-experimental nature of the study, it is difficult to attribute the evinced dissimilarities in brain structure across groups to the actual addiction status. Possible confounding variables cannot be excluded that may have contributed to the differences found.

Han et al . [ 41 ] tested the effects of bupropion sustained release treatment on brain activity among Internet gaming addicts and healthy controls. All participants completed the Structured Clinical Interview for DSM-IV [ 80 ], the Beck Depression Inventory [ 78 ], the Internet Addiction Scale [ 61 ], and the Craving for Internet video game play was assessed with a 7-point visual analogue scale. Those participants who engaged in Internet gaming for more than four hours a day, scored more than 50 (out of 100) on the IAS, and had impaired behaviors and/or distress were classed as Internet gaming addicts. The sample comprised 11 Internet gaming addicts (mean age = 21.5, SD = 5.6 years; mean craving score = 5.5, SD = 1.0; mean playing time = 6.5, SD = 2.5 h/day; mean IAS score = 71.2, SD = 9.4), and 8 healthy controls (mean age = 11.8, SD = 2.1 years; mean craving score = 3.9, SD =1.1; mean Internet use = 1.9, SD = 0.6 h/day; mean IAS score = 27.1, SD = 5.3). During exposure to game cues, Internet gaming addicts had more brain activation in left occipital lobe cuneus, left dorsolateral prefrontal cortex, and left parahippocampal gyrus relative to the control group. Participants with Internet gaming addiction underwent six weeks of bupropion sustained release treatment (150 mg/day for first week, and 300 mg/day afterwards). Brain activity was measured at baseline and after treatment using a 1.5 Tesla Espree fMRI scanner. The authors reported that bupropion sustained release treatment works for Internet gaming addicts in a similar way as it works for patients with substance dependence. After treatment, craving, play time, and cue-induced brain activity decreased among Internet gaming addicts. The longitudinal nature of this study allows for a determination of cause and effect, which emphasizes the validity and reliability of the presented findings.

3.2. sMRI Studies

Lin et al . [ 48 ] investigated white matter integrity in adolescents with Internet addiction. All participants completed a modified version of the Internet Addiction Test [ 72 ], the Edinburgh handedness inventory [ 83 ], the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) [ 84 ], the Time Management Disposition Scale [ 85 ], the Barratt Impulsiveness Scale [ 86 ], the Screen for Child Anxiety Related Emotional Disorders (SCARED) [ 87 ], and the Family Assessment Device (FAD) [ 88 ]. The sample comprised 17 Internet addicts (14 males; age range = 14–24 years; IAS mean score = 37.0, SD = 10.6), and 16 healthy controls (14 males; age range = 16–24 years; IAS mean score = 64.7, SD = 12.6). The authors carried out a whole brain voxel-wise analysis of fractional anisotropy (FA) by tract-based spatial statistics (TBSS), and volume of interest analysis was performed using diffusion tensor imaging (DTI) via a 3.0-Tesla Phillips Achieva medical scanner.

The results indicated that the OFC was associated with emotional processing and addiction-related phenomena (e.g., craving, compulsive behaviors, maladaptive decision-making). Abnormal white matter integrity in the anterior cingulate cortex was linked to different addictions, and indicated an impairment in cognitive control. The authors also reported impaired fiber connectivity in the corpus callosum that is commonly found in those with substance dependence. Internet addicts showed lower FA throughout the brain (orbito-frontal white matter corpus callosum, cingulum, inferior fronto-occipital fasciculus, corona radiation, internal and external capsules) relative to controls, and there were negative correlations between FA in the left genu of corpus callosum and emotional disorders, and FA in the left external capsule and Internet addiction. Overall, Internet addicts had abnormal white matter integrity in brain regions linked to emotional processing, executive attention, decision-making and cognitive control compared to the control group. The authors highlighted similarities in brain structures between Internet addicts and substance addicts [ 48 ]. Given the non-experimental and cross-sectional nature of the study, alternative explanations for brain alterations other than addiction cannot be excluded.

Zhou et al . [ 47 ] investigated brain gray matter density (GMD) changes in adolescents with Internet addiction using voxel-based morphometry (VBM) analysis on high-resolution T1-weighted structural magnetic resonance images. Their sample comprised 18 adolescents with Internet addiction (16 males; mean age = 17.2 years, SD = 2.6), and 15 healthy control participants with no history of psychiatric illness (13 males; mean age = 17.8 years, SD = 2.6). All participants completed the modified Internet Addiction Test [ 72 ]. The authors used high-resolution T1-weighted MRIs performed on a 3T MR scanner (3T Achieva Philips), scanned MPRAGE pulse sequences for gray and white matter contrasts, and VBM analysis was used to compare GMD between groups. Results showed that Internet addicts had lower GMD in the lACC (necessary for motor control, cognition, motivation), lPCC (self-reference), left insula (specifically related to craving and motivation), and the left lingual gyrus ( i.e. , areas that are linked to emotional behavior regulation and thus linked to emotional problems of Internet addicts). The authors state that their study provided neurobiological proof for structural brain changes in adolescents with Internet addiction, and that their findings have implications for the development of addiction psychopathology. Despite the differences found between the groups, the findings cannot exclusively be attributed to the addiction status of one of the groups. Possible confounding variables may have had an influence on brain changes. Moreover, the directionality of the relationship cannot be explained with certainty in this case.

3.3. EEG Studies

Dong et al . [ 53 ] investigated response inhibition among Internet addicts neurologically. The recordings of event-related brain potentials (ERPs) via EEG were examined in 12 male Internet addicts (mean age = 20.5 years, SD = 4.1) and compared with 12 healthy control university students (mean age = 20.2, SD = 4.5) while undergoing a go/NoGo task. The participants completed psychological tests ( i.e. , Symptom Checklist-90 and 16 Personal Factors scale [ 89 ]) and the Internet Addiction Test [ 65 ]. The results showed that Internet addicts had lower NoGo-N2 amplitudes (representing response inhibition—conflict monitoring), higher NoGo-P3 amplitudes (inhibitory processes—response evaluation), and longer NoGo-P3 peak latency when compared to controls. The authors concluded that compared to the control group, Internet addicts (i) had lower activation in conflict detection stage, (ii) used more cognitive resources to complete the later stage of the inhibition task, (iii) were less efficient at information processing, and (iv) had lower impulse control.

Dong et al . [ 52 ] compared Internet addicts and healthy controls on event-related potentials (ERP) via EEG while they were performing a color-word Stroop task. Male participants ( n = 17; mean age = 21.1 years, SD = 3.1) and 17 male healthy university students (mean age = 20.8 years, SD = 3.5) completed psychological tests ( i.e. , the Symptom Checklist-90 and the 16 Personal Factors scale [ 89 ]) and the Internet Addiction Test [ 64 ]. This version of the IAT included eight items (preoccupation, tolerance, unsuccessful abstinence, withdrawal, loss of control, interests, deception, escapism motivation) and the items were scored dichotomously. Those participants who endorsed four or more items were classed as Internet addicts. Results showed that Internet addicts had a longer reaction time and more response errors in incongruent conditions compared to controls. The authors also reported reduced medial frontal negativity (MFN) deflection in incongruent conditions than controls. Their findings suggested that Internet addicts have impaired executive control ability compared to controls.

Ge et al . [ 55 ] investigated the association between the P300 component and Internet addiction disorder among 86 participants. Of these, 38 were Internet addiction patients (21 males; mean age = 32.5, SD = 3.2 years) and 48 were healthy college student controls (25 males; mean age = 31.3, SD = 10.5 years). In an EEG study, P300 ERP was measured using a standard auditory oddball task using the American Nicolet BRAVO instrument. All participants completed the Structured Clinical Diagnostic Interview for Mental Disorders [ 80 ], and the Internet Addiction Test [ 64 ]. Those who endorsed five or more (of the eight items) were classed as Internet addicts. The study found that Internet addicts had longer P300 latencies relative to the control group, and that Internet addicts had similar profiles as compared to other substance-related addicts ( i.e. , alcohol, opioid, cocaine) in similar studies. However, the results did not indicate that Internet addicts had a deficiency in perception speed and auditory stimuli processing. This appears to indicate that rather than being detrimental to perception speed and auditory stimuli processing, Internet addiction may have no effect on these specific brain functions. The authors also reported that the cognitive dysfunctions associated with Internet addiction can be improved via cognitive-behavioral therapy and that those who participated in cognitive-behavioral therapy for three months decreased their P300 latencies. The final longitudinal result is particularly insightful because it assessed the development over time that may be attributed to the beneficial effects of therapy.

Little et al . [ 56 ] investigated error-processing and response inhibition in excessive gamers. All participants completed the Videogame Addiction Test (VAT) [ 73 ], the Dutch version of the Eysenck Impulsiveness Questionnaire [ 90 , 91 ], and the Quantity-Frequency-Variability Index for alcohol consumption [ 92 ]. The sample comprised 52 students grouped into two groups of 25 excessive gamers (23 males; scoring more than 2.5 on VAT; mean age = 20.5, SD = 3.0 years; mean VAT score = 3.1, SD = 0.4; average gaming = 4.7 h a day, SD = 2.3) and 27 controls (10 males; mean age = 21.4, SD = 2.6; mean Vat score = 1.1, SD = 0.2; average gaming = 0.5 h a day, SD = 1.2). The authors used a Go/NoGo paradigm using EEG and ERP recordings. Their findings indicated similarities with substance dependence and impulse control disorders in relation to poor inhibition and high impulsivity in excessive gamers relative to the control group. They also reported that excessive gamers had reduced fronto-central ERN amplitudes following incorrect trials in comparison to correct trials and that this led to poor error-processing. Excessive gamers also displayed less inhibition on both self-report and behavioral measures. The strength of this study include its quasi-experimental nature as well as the verification of self-reports with behavioral data. Therefore, validity and reliability of the findings are increased.

3.4. SPECT Studies

Hou et al . [ 51 ] examined reward circuitry dopamine transporter levels in Internet addicts compared to a control group. The Internet addicts comprised five males (mean age = 20.4, SD = 2.3) whose mean daily Internet use was 10.2 h (SD = 1.5) and who had suffered from Internet addiction for more than six years. The age-matched control group comprised nine males (mean age = 20.4, SD = 1.1 years), whose mean daily use was 3.8 h (SD = 0.8 h). The authors performed 99mTc-TRODAT-1 single photon emission computed tomography (SPECT) brain scans using Siemens Diacam/e.cam/icon double detector SPECT. They reported that reduced dopamine transporters indicated addiction and that there were similar neurobiological abnormalities with other behavioral addictions. They also reported that striatal dopamine transporter (DAT) levels decreased among Internet addicts (necessary for regulation of striatal dopamine levels) and that volume, weight, and uptake ratio of the corpus striatum were reduced relative to controls. Dopamine levels were reported to be similar to people with substance addictions and that Internet addiction “may cause serious damages to the brain” ([ 51 ], p. 1). This conclusion cannot be seen as entirely accurate for the directionality of the reported effect cannot be established with the utilized method.

3.5. PET Studies

Koepp et al . [ 50 ] were the first research team to provide evidence for striatal dopamine release during video game play ( i.e. , a game navigating a tank for monetary incentive). In their study, eight male video game players (age range = 36–46 years) underwent positron emission tomography (PET) during video game play and under resting condition. The PET scans employed a 953B-Siemens/CTIPET camera, and a region-of-interest (ROI) analysis was performed. Extracellular dopamine levels were measured via differences in [ 11 C]RAC-binding potential to dopamine D 2 receptors in ventral and dorsal striata. The results showed that ventral and dorsal striata were associated with goal-directed behavior. The authors also reported that the change of binding potential during video game play was similar to that following amphetamine or methylphenidate injections. In light of this, the earliest study included in this review [ 50 ] was already able to highlight changes in neurochemical activity as a consequence of gaming relative to a resting control. This finding is of immense significance because it clearly indicates that the activity of gaming can in fact be compared to using psychoactive substances when viewed from a biochemical level.

Kim et al . [ 49 ] tested whether Internet addiction was associated with reduced levels of dopaminergic receptor availability in the striatum. All participants completed the Structured Clinical Interview for DSM-IV [ 80 ], the Beck Depression Inventory [ 93 ], the Korean Wechsler Adult Intelligence Scale [ 94 ], the Internet Addiction Test [ 69 ] and the Internet Addictive Disorder Diagnostic Criteria (IADDC; [ 68 ]). Internet addiction was defined as those participants who scored more than 50 (out of 100) on the IAT, and endorsed three or more of the seven criteria on the IADDC.

Their sample comprised five male Internet addicts (mean age = 22.6, SD = 1.2 years; IAT mean score = 68.2, SD = 3.7; mean daily Internet hours = 7.8, SD = 1.5) and seven male controls (mean age = 23.1, SD = 0.7 years; IAT mean score = 32.9, SD = 5.3; mean daily Internet hours = 2.1, SD = 0.5). The authors carried out a PET study and used a radiolabeled ligand [ 11 C]raclopride and positron emission tomography via ECAT EXACT scanner to test dopamine D 2 receptor binding potential. They also performed fMRI using a General Electric Signa version 1.5T MRI scanner. The method for assessing D 2 receptor availability examined regions of interest (ROI) analysis in ventral striatum, dorsal caudate, dorsal putamen. The authors reported that Internet addiction was found to be related to neurobiological abnormalities in the dopaminergic system as found in substance-related addictions. It was also reported that Internet addicts had reduced dopamine D 2 receptor availability in the striatum ( i.e. , bilateral dorsal caudate, right putamen) relative to the controls, and that there was a negative correlation of dopamine receptor availability with Internet addiction severity [ 49 ]. However, from this study it is unclear to what extent Internet addiction may have caused the differences in neurochemistry relative to any other confounding variable, and, similarly, whether it is the different neurochemistry that may have led to the pathogenesis.

4. Discussion

The results of the fMRI studies indicate that brain regions associated with reward, addiction, craving, and emotion are increasingly activated during game play and presentation of game cues, particularly for addicted Internet users and gamers, including the NAc, AMG, AC, DLPFC, IC, rCN, rOFC, insula, PMC, precuneus [ 42 , 43 ]. Gaming cues appeared as strong predictors of craving in male online gaming addicts [ 44 ]. Moreover, it was shown that associated symptoms, such as craving, gaming cue-induced brain activity, and cognitive dysfunctions can be reduced following psychopharmacological or cognitive-behavioral treatment [ 41 , 55 ].

In addition to this, structural changes have been demonstrated in Internet addicts relative to controls, including the cerebellum, brainstem, rCG, blPHipp, right frontal lobe, lSFG, rITG, lSTG, and mTG. Specifically, these regions appeared to be increased and calibrated, indicating that in Internet addicts, neuroadaptation occurs that synchronizes a variety of brain regions. These include, but are not limited to, the widely reported mesocorticolimbic system involved in reward and addiction. In addition, Internet addicts’ brains appear to be able to integrate sensorimotor and perceptual information better [ 45 ]. This may be explained by a frequent engagement with Internet applications such as games, which require a stronger connectivity between brain regions in order for learned behaviors and reactions to addiction-relevant cues to occur automatically.

Furthermore, compared to controls, Internet addicts were found to have decreased gray matter volume in the blDLPFC, SMA, OFC, cerebellum, ACC, lPCC, increased FA lPLIC, and decreased FA in white matter in the PHG [ 46 ]. The lACC is necessary for motor control, cognition, and motivation, and its decreased activation has been linked to cocaine addiction [ 95 ]. The OFC is involved in processing emotions and it plays a role in craving, maladaptive decision-making processes, as well as the engagement in compulsive behaviors, each of which are integral to addiction [ 96 ]. Moreover, the length of Internet addiction correlated with changes in DLPFC, rACC, SMA, and PLIC, testifying to the increase of brain atrophy severity over time [ 46 ]. The DLPFC, rACC, ACC, and PHG have been linked to self-control [ 22 , 25 , 44 ], whereas the SMA mediates cognitive control [ 97 ]. Atrophy in these regions can explain the loss of control an addict experiences in regards to his drug or activity of choice. The PCC, on the other hand, is important in mediating emotional processes and memory [ 98 ], and a decrease in its gray matter density may be indicative of abnormalities associated with these functions.

The increase of the internal capsule has been linked to motor hand function and motor imagery [ 99 , 100 ], and can possibly be explained by the frequent engagement in computer games, that requires and significantly improves eye-hand coordination [ 101 ]. Moreover, decreased fiber density and white matter myelination as measured with FA were found in the anterior limb of the internal capsule, external capsule, corona radiation, inferior fronto-occipital fasciculus and precentral gyrus in Internet addicts relative to healthy controls [ 48 ]. Similar white matter abnormalities have been reported in other substance-related addictions [ 102 , 103 ]. Similarly, fiber connectivity in the corpus callosum was found to be decreased in Internet addicts relative to healthy controls, which indicates that Internet addiction may have similar degenerative consequences with regards to links between the hemispheres. These findings are in accordance with those reported in substance-related addictions [ 104 ].

Moreover, there appeared gender differences in activation in such a way that for males, the activation and connectivity of brain regions associated with the mesocorticolimbic reward system were stronger relative to females. This may explain the significantly higher vulnerability for males to develop an addiction to gaming and the Internet that has been reported in reviews of the empirical literature ( i.e. , [ 7 , 105 ]).

In addition to the MRI findings, the EEG studies assessing Internet and gaming addiction to date offer a variety of important findings that may help in understanding behavioral and functional correlates of this emergent psychopathology. In addition to this, the experimental nature of all of the included EEG studies allows for the determination of a causal relationship between the assessed variables. It has been shown that compared to controls, Internet addicts had decreased P300 amplitudes and an increased P300 latency. Typically, this amplitude reflects attention allocation. The differences in amplitude between Internet addicts and controls indicate that either Internet addicts have an impaired capacity for attention or they are not able to allocate attention adequately [ 55 , 57 ]. Small P300 amplitudes have been associated with genetic vulnerability for alcoholism in a meta-analysis [ 106 ]. Decreased P300 latency furthermore was found to distinguish heavy social drinkers from low social drinkers [ 107 ]. Accordingly, there appears to be a common change in neuronal voltage fluctuations in persons addicted to substances and the engagement in Internet use relative to people who are not addicted. Accordingly, Internet addiction appears to have an effect on neuroelectric functioning that is similar to substance addictions. Generally, Internet addicts’ brains appeared to be less efficient with regards to information processing and response inhibition relative to healthy control participants’ brains [ 54 , 56 ]. This indicates that Internet addiction is associated with low impulse control, and the use of an increased amount of cognitive resources in order to complete specific tasks [ 53 ]. Furthermore, Internet addicts appear to have an impaired executive control ability relative to controls [ 56 , 53 ]. These results are in accordance with reduced executive control ability found in cocaine addicts, implicating decreased activity in pre- and midfrontal brain regions that would allow for impulse-driven actions [ 108 ].

From a biochemical point of view, the results of PET studies provide evidence for striatal dopamine release during gaming [ 50 ]. Frequent gaming and Internet use were shown to decrease dopamine levels (due to decreased dopamine transporter availability) and lead to neurobiological dysfunctions in the dopaminergic system in Internet addicts [ 49 , 51 ]. The decreased availability was linked with the severity of Internet addiction [ 49 ]. Reduced dopamine levels have been reported in addictions time and again [ 26 , 109 , 110 ]. Furthermore, structural abnormalities of the corpus striatum have been reported [ 51 ]. Damages to the corpus striatum have been associated with heroin addiction [ 111 ].

The studies included in this literature review appear to provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet addiction, on a variety of levels. On the molecular level, it has been shown that Internet addiction is characterized by an overall reward deficiency that is characterized by decreased dopaminergic activity. The direction of this relationship is yet to be explored. Most studies could not exclude that an addiction develops as a consequence of a deficient reward system rather than vice versa. The possibility that deficits in the reward system predispose certain individuals to develop a drug or a behavioral addiction such as Internet addiction may put an individual at greater risk for psychopathology. In Internet addicts, negative affectivity can be considered the baseline state, where the addict is preoccupied with using the Internet and gaming to modify his mood. This is brought about by the activation of the antireward system. Due to the excessive use of the Internet and online gaming, opponent processes appear to be set in motion that quickly habituate the addict to the engagement with the Internet, leading to tolerance, and, if use is discontinued, withdrawal [ 27 ]. Accordingly, decreased neuronal dopamine as evinced in Internet addiction may be linked to commonly reported comorbidities with affective disorders, such as depression [ 112 ], bipolar disorder [ 113 ], and borderline personality disorder [ 10 ].

On the level of neural circuitry, neuroadaptation occurs as a consequence of increased brain activity in brain areas associated with addiction and structural changes as a consequence of Internet and gaming addiction. The cited studies provide a clear picture of Internet and gaming addiction pathogenesis and stress how maladaptive behavioral patterns indicative of addiction are maintained. The brain adapts to frequent use of drugs or engagement in addictive behaviors so that it becomes desensitized to natural reinforcers. Importantly, functioning and structure of the OFC and cingulate gyrus are altered, leading to increased drug or behavior salience and loss of control over behaviors. Learning mechanisms and increased motivation for consumption/engagement result in compulsive behaviors [ 114 ].

On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their impulse control, behavioral inhibition, executive functioning control, attentional capabilities, and overall cognitive functioning. In turn, certain skills are developed and improved as a consequence of frequent engagement with the technology, such as the integration of perceptual information into the brain via the senses, and hand-eye coordination. It appears that the excessive engagement with the technology results in a number of advantages for players and Internet users, however to the detriment of fundamental cognitive functioning.

Taken together, the research presented in this review substantiates a syndrome model of addictions for there appear to be neurobiological commonalities in different addictions [ 115 ]. According to this model, neurobiology and psychosocial context increase the risk to become addicted. The exposure to the addictive drug or behavior and specific negative events and/or the continued use of the substance and engagement in the behavior leads to behavioral modification. The consequence is the development of full-blown addictions, that are different in expression (e.g., cocaine, the Internet and gaming), but similar in symptomatology [ 115 ], i.e. , mood modification, salience, tolerance, withdrawal, conflict, and relapse [ 6 ].

Notwithstanding the insightful results reported, a number of limitations need to be addressed. First, there appear methodological problems that may decrease the strength of the reported empirical findings. The reported brain changes associated with Internet and online gaming addiction described in this review may be explained in two different ways. On the one hand, one could argue that Internet addiction leads to brain alterations relative to controls. On the other hand, people with unusual brain structures (as the ones observed in the present study) may be particularly predisposed to developing addictive behaviors. Only experimental studies will allow a determination of cause and effect relationships. Given the sensitive nature of this research that essentially assesses potential psychopathology, ethical considerations will limit the possibilities of experimental research in the field. In order to overcome this problem, future researchers should assess brain activity and brain alterations on a number of occasions during a person’s life longitudinally. This would allow for the extrication of invaluable information with regards to the relationships of pathogenesis and related brain changes in a more elaborate and, importantly, causal fashion.

Secondly, this review included neuroimaging studies of both Internet addicts and online gaming addicts. Based on the collected evidence, it appears difficult to make any deductions as regards the specific activities the addicts engaged in online, other than some authors specifically addressing online gaming addiction. Others, on the other hand, used the categories Internet addiction and Internet gaming addiction almost interchangeably, which does not allow for any conclusions with regards to differences and similarities between the two. In light of this, researchers are advised to clearly assess the actual behaviors engaged in online, and, if appropriate, extend the notion of gaming to other potentially problematic online behaviors. Ultimately, people do not become addicted to the medium of the Internet per sé, but it is rather the activities that they engage in that may be potentially problematic and could lead to addictive online behavior.

5. Conclusions

This review aimed to identify all empirical studies to date that have used neuroimaging techniques in order to discern the neuronal correlates of Internet and gaming addiction. There are relatively few studies ( n = 19), and therefore it is crucial to conduct additional studies to replicate the findings of those already carried out. The studies to date have used both structural and functional paradigms. The use of each of these paradigms allows for the extrication of information that is crucial for establishing altered neuronal activity and morphology as precipitated by Internet and gaming addiction. Overall, the studies indicate that Internet and gaming addiction is associated with both changes in function as well as structure of the brain. Therefore, not only does this behavioral addiction increase the activity in brain regions commonly associated with substance-related addictions, but it appears to lead to neuroadaptation in such a way that the brain itself actually changes as a consequence of excessive engagement with the Internet and gaming.

In terms of the method, neuroimaging studies offer an advantage over traditional survey and behavioral research because, using these techniques, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. Measurements of increased glutamatergic and electrical activity give insight into brain functioning, whereas measures of brain morphometry and water diffusion provide an indication of brain structure. It has been shown that each of these undergoes significant changes as a consequence of Internet and gaming addiction.

To conclude, understanding the neuronal correlates associated with the development of addictive behaviors related to using the Internet and playing online games will promote future research and will pave the way for the development of addiction treatment approaches. In terms of clinical practice, increasing our knowledge regarding the pathogenesis and maintenance of Internet and gaming addiction is essential for the development of specific and effective treatments. These include psychopharmacological approaches that target Internet and gaming addiction specifically on the level of biochemistry and neurocircuitry, as well as psychological strategies, that aim to modify learned maladaptive cognitive and behavioral patterns.

Conflict of Interest

The authors declare no conflict of interest.

Evidence on Problematic Online Gaming and Social Anxiety over the Past Ten Years: a Systematic Literature Review

Internet Use Disorders (H Rumpf & J Billieux, Section Editors)
Open access
Published: 05 January 2022
Volume 9 , pages 32–47, ( 2022 )

Cite this article

You have full access to this open access article

Francesca Gioia 1 ,
Gianluca Mariano Colella 1 &
Valentina Boursier ORCID: orcid.org/0000-0003-0899-8090 1

16k Accesses

16 Citations

2 Altmetric

Explore all metrics

Purpose of Review

The present study aimed to review the literature concerning the relationship between problematic online gaming (POG) and social anxiety, taking into account the variables implicated in this relationship. This review included studies published between 2010 and 2020 that were indexed in major databases with the following keywords: Internet gaming, disorder, addiction, problematic, social phobia, and social anxiety.

Recent Findings

In recent years, scientific interest in POG has grown dramatically. Within this prolific research field, difficulties associated with social anxiety have been increasingly explored in relation to POG. Indeed, evidence showed that individuals who experience social anxiety are more exposed to the risk of developing an excessive or addictive gaming behavior.

A total of 30 studies satisfied the initial inclusion criteria and were included in the present literature review. Several reviewed studies found a strong association between social anxiety and online gaming disorder. Furthermore, the relationships among social anxiety, POG, age, and psychosocial and comorbid factors were largely explored. Overall, the present review showed that socially anxious individuals might perceive online video games as safer social environments than face-to-face interactions, predisposing individuals to the POG. However, in a mutually reinforcing relationship, individuals with higher POG seem to show higher social anxiety. Therefore, despite online gaming might represent an activity able to alleviate psychopathological symptoms and/or negative emotional states, people might use online gaming to counterbalance distress or negative situations in everyday life, carrying out a maladaptive coping strategy.

Online Gaming Addiction and Basic Psychological Needs Among Adolescents: The Mediating Roles of Meaning in Life and Responsibility

The positive aspects of attention deficit hyperactivity disorder: a qualitative investigation of successful adults with ADHD

Social Media and Youth Mental Health

Avoid common mistakes on your manuscript.

Introduction

The social anxiety disorder (SAD), also known as social phobia, is an anxiety disorder characterized by fear in one or more social situations, leading to considerable distress, over-estimation of possible consequences of negative social evaluation, and impaired ability to face feared social situations [ 1 , 2 ]. As several previous studies highlighted [ 3 , 4 , 5 ], socially anxious individuals might consider Internet as a safer social context than face-to-face interactions due to the lack of physical and auditory contacts, frequently developing a preference for online social interactions [ 6 , 7 , 8 , 9 ]. Later studies found that problematic Internet-related activities were strongly associated with individuals’ social anxiety, especially if younger [ 10 , 11 , 12 , 13 , 14 ]. Among the Internet-related activities, specific structural characteristics of gaming (such as design and narrative, achievements, online social interactions, and motivations) appeared particularly fascinating for individuals who attempt to escape the boredom of common life [ 15 ]. Indeed, videogames seem to help individuals to escape real life and reduce stress, problems, and isolation also through online social interactions [ 16 , 17 , 18 , 19 ]. In this regard, according to the compensatory Internet use model [ 20 ••], online videogames might offer other alternative virtual environments where highly socially anxious individuals transfer most of their social activities (such as the formation of strong friendships), alleviate their stressful life event-related negative feelings, and feel safer and more comfortable than in face-to-face socialization [ 21 ]. However, as Lo et al. [ 22 ] stated, online games reduce social anxiety only temporarily, dangerously reducing social experiences in face-to-face contexts [ 23 ]. Furthermore, several recent studies explored the association between problematic online gaming and social anxiety as well as depressive symptoms, self-esteem, and loneliness [ 24 , 25 , 26 , 27 , 28 , 29 ]. Indeed, despite online gaming might offer an alternative context in which individuals can reduce emotional distress, psychosocial problems, and isolation through online social interactions [ 16 , 17 , 18 , 19 , 30 ], the excessive engagement in online gaming might represent a maladaptive coping strategy leading to negative outcomes [ 31 , 32 , 33 ].

Concerning the online gaming, in the last decade, it has been described as a social and not problematic activity for the majority of gamers [ 34 ] and concerns regarding the potential overpathologization of casual gamers have been raised [ 31 , 33 , 35 , 36 ••, 37 , 38 ••, 39 , 40 ]. However, scientific research increasingly focused on problematic and potentially pathological Internet gaming [ 41 , 42 , 43 ]. In this regard, already in 2013, the American Psychiatric Association (APA) [ 44 ] provisionally included the Internet Gaming Disorder (IGD) in the Section III of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5), as condition that requires further research to be definitely included in the manual [ 44 ], adopting the substance use diagnostic criteria (i.e., preoccupation, withdrawal, tolerance) [ 45 , 46 ]. Then, only more recently, the World Health Assembly officially declared Gaming Disorder (GD) as a diagnostic category to be included in the International Classification of Diseases, 11th Revision (ICD-11) [ 47 ]. Nevertheless, a theoretical and methodological classification of the Internet gaming disorder is still lacking due to uncertainty in conceptualization, measurement, and clinical assessment [i.e., 35, 40, [ 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 ]. Furthermore, evidence suggested to address attention toward comorbidity factors associated with problematic gaming, since it may be present along with other pathologies [ 38 ••]. In addition to social anxiety, deficient self-regulation, negative mood, and affective disorders (e.g. anxiety and panic, distress, depression), psychosocial difficulties such as isolation, intense shyness, and consistent preference for online social interactions have been frequently associated with problematic online gaming [ 51 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 ], especially among young individuals. Indeed, young people have been found typically engaged in high sensation-seeking and risky behaviors [ 68 , 69 ] and they have been defined as a vulnerable population for problematic online gaming, with potential negative outcomes for their psychological, social, and physical health [ 61 , 70 ].

In summary, in the past decade, the Internet gaming has dramatically grown becoming a widespread and often daily activity. However, individuals who experience social anxiety have been found more exposed to the risk of developing problematic online gaming because this online activity may help them to avoid and escape from difficulties and anxieties related to face-to-face social interactions [ 1 , 71 , 72 ]. A better understanding of the social anxiety-problematic online gaming relationship (and the possible related psychosocial difficulties) might provide several practical implications, especially considering the recent evidence about the association between social isolation and problematic gaming [ 73 , 74 ]. Therefore, in light of this evidence, the present study aimed at reviewing the scientific studies published in the last ten years specifically focusing on the relation between problematic online gaming and social anxiety.

Materials and Methods

The review has been conducted using Web of Science , Scopus , and ScienceDirect as the main research databases, entering the following keywords: internet gaming* problematic* social anxiety*/ internet gaming* disorder* social anxiety*/ internet gaming* addict* social anxiety*/ internet gaming* problematic* social phobia*/ internet gaming* disorder* social phobia*/ internet gaming* addict* social phobia. The present literature review is in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [ 75 ]. Progressive exclusion was performed by reading the abstract and, finally, the full text. The inclusion criteria for the present review were (i) studies containing quantitative empirical data, (ii) studies concerning Internet Gaming, (iii) studies published from 2010 to 2020, and (iv) studies providing a full-text article published in English. For comparison purposes, exclusion criteria were (i) studies focusing on the general Internet use, (ii) reviews, conference abstracts, letters, or editorials, and (iii) doctoral dissertations. Strong heterogeneity in reported studies’ findings and statistical information lead us to adopt a systematic narrative approach to report key outcomes.

A total of 784 papers were initially identified. Subsequently, 754 papers that did not meet the inclusion criteria were excluded. Thus, 30 studies that met the initial inclusion criteria were included in the present literature review (Fig. 1 ).

Flow chart of the search strategy and selection procedure

Different Perspectives on Problematic Online Gaming Research: Frameworks and Measures

Concerning the diagnostic instruments used to assess problematic video gaming (Table 1 ), several assessment tools based on DSM-5 diagnostic criteria for IGD and focused on traditional online gaming addiction on desktop computers have been used. More specifically, two studies administered the Gaming Addiction Scale (GAS) [ 76 , 77 , 78 ] and two studies adapted the GAS for mobile gaming [ 79 , 80 ]. Four studies used the Internet Gaming Disorder Scale (IGDS) [ 28 , 72 , 81 , 82 , 83 ] and Starcevic et al. [ 84 ] developed a semi-structured diagnostic interview consisting of nine items corresponding to the nine criteria for IGD. Moreover, Müller et al. [ 85 ] used the Scale for the Assessment of Internet and Computer game Addiction (AICA-S) [ 86 ] and Wei et al. [ 15 ] utilized the Chen’s Internet Addiction Scale (CIAS) [ 87 ]. Furthermore, Lopez-Fernandez et al. [ 88 ], Marino et al. [ 89 ], Severo et al. [ 90 ], and Wang and Cheng [ 91 ] tested the 9-item short form of IGDS (IGDS9-SF) [ 29 ]. Kircaburun et al. [ 92 ] used the 10-item Internet Gaming Disorder Test (IGDT-10) [ 93 ]. Finally, Van Rooij et al. [ 94 ] used the Compulsive Internet Use Scale (CIUS) [ 95 ] to evaluate the adolescents’ online video game addiction, and later, other studies employed the Video game Addiction Test (VAT) [ 43 , 96 , 97 , 98 ], a modified version of CIUS referred specifically to gaming.

Four studies adapted the DSM-IV diagnostic criteria for substance dependence or pathological gambling to the online game addiction. In particular, according to previous studies [ 99 ], Hyun et al. [ 100 ] and Park et al. [ 101 ] employed 5 criteria: (i) online game playing for more than 4 h per day or 30 h per week; (ii) scores higher than 50 in the Internet Addiction Scale score [ 102 ]; (iii) irritability, anxiety, and aggressive behaviors when forced to stop online gaming; (iv) impaired behaviors or distress, economic problems, or maladaptive patterns of regular life due to excessive online gaming; and (v) altered diurnal rhythms and consequent outcomes in life patterns (i.e., online gaming at night and sleeping during the day, irregular meals, failure in personal hygiene, school truancy, or loss of job). Moreover, Karaca et al. [ 103 ] utilized the Computer Game Addiction Scale for Children (CGASC) [ 104 ]. Finally, following Gentile [ 105 ], Gentile et al. [ 106 ] evaluated the pathological video game use.

According to the cognitive behavioral model of problematic Internet use [ 6 , 107 , 108 ], Cole and Hooley [ 10 ] and Lee and Leeson [ 1 ] tested the Generalized Problematic Internet Use Scale (GPIUS) [ 107 ] on MMOs and MMORPGs players, respectively.

In an alternative conceptualization termed compensatory internet use , Kardefelt-Winther [ 20 ••, 109 ] problematized the common research methodology in studies on excessive internet use developing the Excessive Online Gaming Scale (EOGS) [ 109 ]. As well, Sheng and Wang [ 79 ] employed the EOGS.

Three studies developed ad hoc measures to explore gaming habits [ 110 ], game experience and game behaviors [ 71 ], and engagement and addiction to World of Warcraft [ 111 , 112 ].

Measures of Social Phobia and Social Anxiety

Concerning the social phobia and social anxiety, the most employed self-report measure was the Social Phobia Inventory (SPIN) [ 15 , 71 , 83 , 106 , 110 , 111 , 113 ] and two studies used the SPIN short form (MINI SPIN) [ 85 , 90 , 114 , 115 ] to evaluate the social phobic symptoms such as social situations fear, avoidance of social situations or performances, and physiological discomfort in social contexts. Marino et al. [ 89 ] used the Italian version of the Social Phobia Inventory (I-SPIN) [ 116 ]. Five studies used the Social Anxiety Scale for children (CSAS) [ 43 , 80 , 94 , 97 , 98 , 117 , 118 , 119 ] aiming to explore how children deal with social avoidance and distress in new and known situations. Six studies [ 10 , 72 , 82 , 84 , 91 , 109 ] utilized the Social Interaction Anxiety Scale and Social Phobia Scale measures (SIAS/SPS) or its short form [ 120 , 121 ], and two companion scales aimed at measuring two related facets of social fears/anxiety. Furthermore, three studies utilized the Liebowitz Social Anxiety Scale (LSAS) [ 1 , 77 , 78 , 122 ] to assess social anxiety disorder and two Korean studies [ 100 , 101 ] employed the Social Avoidance and Distress Scale (SADS) [ 123 ] to explore the fear of negative evaluation by others and the tendency to avoid social situations due to distress in the presence of others. Karaca et al. [ 103 ] and Sheng and Wang [ 79 ] used two different measures for children: the Social Anxiety Scale for Children (SASC) [ 124 ] and the Child Social Anxiety Scale [ 125 ], respectively. Finally, Kircaburun et al. [ 92 ] utilized the Social Anxiety Scale for adolescents short form (SAS-A) [ 126 ], Lopez-Fernandez et al. [ 88 ] the social phobia items of the Symptom Checklist-27-Plus (SCL-27-Plus) [ 127 ], and Khalil et al. [ 81 ] employed the Social Anxiety subscale of the MINI International Neuropsychiatry Interview for children and adolescents (MINI KID) [ 128 ].

Problematic Online Gaming and Social Anxiety

Several reviewed studies found a strong association between social anxiety and problematic online gaming [ 1 , 15 , 43 , 71 , 72 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 88 , 89 , 90 , 94 , 97 , 98 , 100 , 101 , 103 , 106 , 110 , 111 ] among both young and adult individuals. More specifically, some studies highlighted significant differences between at-risk/problematic online gamers and no problematic/engaged video games users [ 43 , 77 , 81 , 83 , 85 , 94 , 100 , 101 , 111 ]. Indeed, problematic users, especially males [ 80 ], scored significantly higher in social anxiety compared with no problematic peers. Colder Carras et al. [ 97 ] used the latent class analysis to identify distinct classes of gamers (normative, problematic, at-risk, social at-risk, extensive, and social engaged gamers) and explored the association between social and non-social video gaming and social anxiety in both male and female adolescents. Interestingly, they found that while male social gamers had no significant associations with social anxiety, females’ engagement in social games reduced social anxiety, whereas non-social at-risk and extensive male gamers reported high social anxiety. Recently, Starcevic et al. [ 84 ] compared IGD patient group and general gamer group highlighting that patient group reported significantly higher social anxiety compared to general gamers. Finally, findings suggested that individuals with high level of social phobia spent more hours and played online video games during the weekends more than participants with lower social phobia [ 15 ].

Some correlational studies reported significant positive co-occurrence between social anxiety and problematic online gaming [ 79 , 81 , 82 , 90 , 98 ]. Kardefelt-Winther [ 109 ] suggested that social anxiety might be correlated with problematic video game use and that excessive use might be more usefully framed and considered as a coping strategy instead of as a compulsive behavior. Accordingly, Wei et al. [ 15 ] stated that socially anxious individuals might use games as an escape mechanism, avoiding face-to-face contact but significantly increasing online relationships.

Several studies explored the predictive effect of social anxiety on problematic online gaming, highlighting that gamers affected by social phobic symptoms were more prone to be engaged in virtual reality of online games, likely to avoid face-to-face social distress [ 1 , 15 , 72 , 78 , 88 , 89 ]. Accordingly, Cole and Hooley [ 10 ] identified trait anxiety and social phobia as best predictors of problematic Internet use among online gamers, suggesting that generally anxious individuals who have difficulties in social situations are the people most likely to have problems online gaming. Similarly, Karaca et al. [ 103 ] reported that high social anxiety was a pivotal risk factor for both problematic gaming and online gaming addiction. On the contrary, only Kircaburun et al. [ 92 ] failed to identify social anxiety as a risk factor for IGD.

Inversely, two studies tested the predictive role of problematic online gaming on social anxiety [ 80 , 106 ]. In a longitudinal growth model, Gentile et al. [ 106 ] found that the weekly amount of video game play significantly predicted the number of pathological gaming symptoms and that children who began with more pathological gaming symptoms demonstrated higher levels of social phobia. Similarly, the recent Wang et al.’s [ 80 ] findings reported that males addicted to mobile games tended to suffer more social anxiety. In addition, Wang and Cheng [ 91 ] found that gaming disorder measure did not explain a significant proportion of social anxiety. In a study focused on the MMORPG World of Warcraft (WoW), Martončik and Lokša [ 71 ] found that WoW players experienced less social anxiety in online world, especially in presence of and playing with known people. Similarly, Sauter et al. [ 110 ] found that individuals who played with known friends were less susceptible toward social anxiety. In Kardefelt-Winther’s [ 109 ] study, social anxiety did not predict WoW-related negative outcomes.

Problematic Online Gaming, Social Anxiety, and the Associated Factors

Three main orders of factors have been found to be associated with problematic online gaming and social anxiety: online gaming-related variables, psychosocial factors, and comorbid symptoms.

Concerning the online gaming-related variables, some studies reported a significant relationship between problematic online gaming and time spent video gaming [ 1 , 43 , 79 , 82 , 94 , 103 ]. More specifically, findings stated that an increase in young individuals’ online gaming time raised the risk of addiction [ 90 , 103 ], which in turn might gradually increase the time spent on video gaming [ 103 ]. On the contrary, according to Kardefelt-Winther [ 109 ], Lee and Leeson [ 1 ] showed that time spent playing was not indicative of problematic MMORPG usage. Other studies explored the motivations for online gaming using the Online Game Motivation Scale [ 129 ]. In this regard, assuming a compensatory view on MMO play, Kardefelt-Winther [ 109 ] evaluated the predictive effect of escapism, achievement, and social interactions motives underlying WoW-related negative outcomes and found that only escapism and achievement had significant effect. Furthermore, entering motivations in the regression model, the social anxiety lost the significant predictive effect on negative outcomes related to WoW play. Lehenbauer-Baum et al. [ 111 ] compared addicted and engaged players and showed that addicted gamers displayed higher achievement and immersion scores than engaged gamers. In a recent study focused on female gamers [ 88 ], the achievement and social motivations were detected as unique predictors of IGD, as well as strictly related to the identification with the avatar when playing videogames. Furthermore, Marino et al. [ 89 ] highlighted that social anxiety was directly associated with four escape, coping, fantasy, and recreation motives, but only escapism mediated the relationship between social anxiety and IGD. Finally, Sioni et al. [ 72 ] found that higher level of social phobia promoted stronger identification with gamers’ own avatar, which in turn exacerbated IGD symptoms.

The second order of factors refers to the psychosocial factors, including personality characteristics as well as social and family variables. More specifically, among the internal and personality factors, loneliness has been frequently explored [ 43 , 71 , 79 , 80 , 92 , 94 , 98 , 109 ]. A strong association between loneliness, social anxiety, and problematic online gaming has been confirmed [ 43 , 79 , 80 , 94 , 98 , 109 ]. Kardefelt-Winther [ 109 ] and Kircaburun et al. [ 92 ] failed to identify the predictive effect of loneliness on problematic online gaming, whereas this latter emerged as a pivotal predictive factor of loneliness in the Wang et al.’s [ 80 ] study. Martončik and Lokša [ 71 ] indicated that online gamers might experience less loneliness and social discomfort in virtual contexts. Other several psychosocial factors have been explored, such as perceived quality of life and life satisfaction [ 77 , 83 , 98 , 110 , 111 ], loneliness, stress [ 109 ], impulsivity [ 100 , 101 , 106 ], metacognitions [ 89 ], self-esteem [ 43 , 92 , 94 , 98 , 100 , 101 ], the true self [ 1 ], and personality traits [ 10 , 111 ]. Among the social variables, perceived social support [ 1 ], friendship quality [ 97 ], and social competence and skills [ 106 ] have been explored. Furthermore, the quality of parent–child relationship has been considered [ 100 , 101 , 106 ]. Also, cognitive factors have been explored [ 100 , 101 ].

Finally, concerning the comorbid symptoms, the association among depression, anxiety, social anxiety, and problematic online gaming has been the most explored [ 10 , 15 , 43 , 77 , 78 , 79 , 80 , 81 , 82 , 84 , 85 , 88 , 90 , 91 , 92 , 94 , 97 , 98 , 100 , 101 , 106 , 110 , 111 ]. In particular, depression symptoms as well as social anxiety have been found positively co-occurred with problematic online gaming [ 15 , 79 , 82 ] and problematic or addicted online gamers showed higher level of depression than engaged or non-problematic gamers [ 43 , 85 , 90 , 94 , 111 ], especially female gamers [ 77 ] and arcades games, sports online games, and casual games players [ 101 ]. Furthermore, depression has been reported also as a pivotal risk and predictive factor of problematic online gaming [ 15 , 78 , 92 , 97 , 98 , 100 ], whereas, inversely, Gentile et al. [ 106 ] and Wang et al. [ 80 ] found that young individuals who became pathological gamers ended up with increased levels of depression, anxiety, loneliness, and social phobia. Wang and Cheng [ 91 ] found that gaming disorder measure did not explain a significant proportion of depression. Finally, only in two studies [ 84 , 88 ], the depressive symptoms did not emerge as a predictor of problematic online gaming. According to Gentile et al. [ 106 ], also Müller et al. [ 85 ] found a strict relationship between problematic online gaming and anxiety and other studies showed the predictive role of anxious symptoms on problematic online gaming [ 10 , 100 ]. Only Starcevic et al. [ 84 ] did not found confirmed this predictive role and Sauter et al. [ 110 ] found that gaming habits significantly predicted generalized anxiety but with negligible practical relevance. Finally, other studies explored comorbid symptoms including obsessive–compulsive disorder [ 84 ], ADHD [ 84 , 100 , 101 ], sleep quality and suicidal ideation [ 90 ], psychoactive substance use [ 43 ], Internet addiction [ 81 , 84 ], problematic social media use [ 81 , 89 ], and mobile phone addiction [ 79 ].

Problematic Online Gaming and Social Anxiety at Different Ages

Among the reviewed studies, some age-related differences emerged in the relationship between social anxiety and problematic online gaming, showing mixed findings. Only two studies focused on children’s problematic online gaming [ 103 , 106 ]. More specifically, Karaka et al. [ 103 ] identified older age as a risk factor for online gaming addiction and Gentile et al. [ 106 ] confirmed that children with lower social competence and greater impulsivity showed increased pathological gaming symptoms, which in turn, over time, lead to higher levels of depression, anxiety, and social phobia. Several studies focused on adolescent samples. Phan et al. [ 77 ] highlighted that the incidence of IGD symptoms was similar before and after the age of 15 among both male and female adolescents, whereas Khalil et al. [ 81 ] found that gaming addicted adolescents had statistically significantly higher age and male sex. Other studies did not discuss their findings according to the adolescent age [ 43 , 80 , 94 , 97 , 98 ]. Six studies involved samples composed by adolescents and young adults. More specifically, Müller et al. [ 85 ] found that late adolescents sought treatment for online gaming more than for other Internet-based activities, whereas Kircaburun et al. [ 92 ], Severo et al. [ 90 ], and Wei et al. [ 15 ] reported that age was not significantly associated with Internet Gaming Disorder. Differently, Sheng and Wang [ 79 ] and Starcevic et al. [ 84 ] did not discuss the role of age in the problematic online gaming. Furthermore, some studies focused their research on emerging adult samples [ 10 , 88 , 101 ], but only two studies discussed their findings according to age, showing that there were no differences between problematic and non-problematic online gamers [ 10 ] and among different kind of games players, respectively [ 101 ]. Seven studies involved young adult and adult participants. Vanzoelen and Caltabiano [ 78 ] found that, as age increased, levels of social anxiety, behavioral inhibition, depression, and gaming addiction decreased, Sigerson et al. [ 82 ] tested and confirmed the strict measurement invariance of IGD scale for age, whereas in Sioni et al.’s study [ 72 ], age was not a significant factor. Similarly, Marino et al. [ 89 ] highlighted that age was not significantly associated with IGD. Lee and Leeson [ 1 ], Sauter et al. [ 110 ], and Wang and Cheng [ 91 ] did not explore age-based differences in association with problematic online gaming. Finally, other studies focused on a large range of age, including adolescents, young adults, and adults. In particular, despite findings did not highlight significant age-related differences between problematic and non-problematic gamers [ 100 , 111 ] and 109 found that age was not significantly associated with online gaming-related negative outcomes, Subramaniam et al. [ 83 ] reported that increasing age was a significant risk factor for IGD. Martončik and Lokša [ 71 ] did not discuss their findings according to age.

The present study reviewed the scientific literature published in the last ten years exploring the relationship between problematic online gaming, social anxiety, and other variables potentially implicated in this relationship. First, a large number of conceptual, theoretical, and/or methodological mixed approaches about problematic online gaming have been confirmed, thus showing the heterogeneity of conceptual and psychometric properties of the assessment tools largely used to measure problematic online gaming. According to recent findings by King et al. [ 38 ••], the IGD criteria have been found as privileged by the largest part of the studies [ 15 , 72 , 77 , 78 , 79 , 80 , 82 , 83 , 84 , 85 , 88 , 90 , 92 , 100 , 101 , 103 , 106 ], but other studies assumed different perspectives [ 1 , 10 , 43 , 60 , 71 , 79 , 94 , 97 , 98 , 109 , 111 ]. Concerning the frequency of use of online games, despite several reviewed studies reported a significant relationship between problematic online gaming and time spent video gaming [ 1 , 43 , 79 , 82 , 90 , 94 , 103 ], according to Kardefelt-Winther [ 109 ] and Lee and Leeson [ 1 ], the playing time variable should be used as a screening, rather than a diagnostic tool. Furthermore, mixed findings emerged concerning the relationship between age and problematic online gaming. As previous studies highlighted [ 49 , 70 , 78 , 130 , 131 ], the problematic online gaming has been found consistently associated with gamers’ younger age. On the contrary, among the reviewed studies, several studies found no significant age-related differences among problematic online (and offline) gamers [ 10 , 15 , 77 , 82 , 90 , 92 , 100 , 101 , 109 , 111 ] and other studies showed that, as age increased, levels of problematic online gaming also increased [ 83 , 85 , 103 ]. Likely, according to Kardefelt-Winther [ 109 ], online gaming is increasingly becoming common across the age groups, and therefore also the correlated risks. Further research on this issue is needed.

Overall, despite the several different frameworks concerning the problematic online gaming, the association between problematic online gaming and social anxiety has been largely confirmed [ 1 , 15 , 43 , 71 , 72 , 77 , 78 , 79 , 80 , 82 , 83 , 84 , 85 , 88 , 90 , 94 , 97 , 98 , 100 , 101 , 103 , 106 , 111 ].

Previous research suggested that socially anxious individuals might perceive the Internet as a safer social environment than face-to-face interactions [ 3 , 4 , 5 , 6 , 8 ], often developing a preference for online socialization [ 9 , 132 , 133 , 134 , 135 ]. Subsequently, this psychosocial vulnerability [ 108 ] might predispose individuals to the online gaming. In this regard, the literature of the last ten years largely showed that individuals with a serious tendency for problematic or addicted online gaming reported significantly higher social anxiety levels than non-problematic or engaged gamers [ 43 , 77 , 80 , 83 , 84 , 85 , 94 , 97 , 100 , 101 , 111 ]. Furthermore, in a possible bidirectional relationship [ 136 ], problematic online gaming and levels of social anxiety might mutually affect and reinforce each other. Indeed, as Lo et al. [ 22 ] found that the amount of social anxiety might increase when individuals spent more time playing online games, Wang et al. [ 80 ] and the longitudinal findings of Gentile et al. [ 106 ] showed the predictive role of the problematic (mobile) online gaming on social anxiety, especially among younger individuals. Nevertheless, overall, social anxious symptoms emerged as a pivotal risk and predictive factor of problematic online gaming [ 1 , 10 , 15 , 72 , 78 , 88 , 103 ]. In this regard, online gamers who suffer from social phobic symptoms appeared more likely to indulge in the virtual reality and more prone to develop a problematic online gaming, likely to avoid real life face-to-face social distress [ 73 ]. Therefore, the mutual predictive effect of social anxiety and problematic online gaming has been largely explored and frequently found in both young and adult individuals.

Several studies have defined social anxiety, depressive symptoms, self-esteem, and loneliness as strongly inter-related constructs [ 137 ] that have been extensively treated as risk factors for or of problematic Internet-related activities [ 7 , 9 , 22 , 138 , 139 , 140 , 141 ]. More specifically, in addition to social anxiety, the problematic online gaming has been explored in association with depression, self-esteem, and loneliness [ 24 , 25 , 26 , 27 , 28 , 131 ]. Similarly, the reviewed studies confirmed a strong association and a mutual relationship between these psychosocial and comorbid factors (especially depression and loneliness) and problematic online gaming [ 15 , 43 , 78 , 79 , 80 , 94 , 97 , 98 , 100 , 106 ]. Furthermore, interestingly, Martončik & Lokša [ 71 ] reported a reduction of social anxiety and loneliness among the WoW gamers, suggesting that likely online players who do not feel accepted in offline world might turn to the video games’ worlds where they might perceive less threat to their social status. These controversial findings seem to reflect the complexity of the relationship between problematic online gaming and psychosocial/comorbidity issues [ 94 ]. Overall, the problematic online gaming might be defined as a complex psychological health condition which involves a feature of everyday life activities with potential negative outcomes. Indeed, although online gaming might offer an alternative context in which individuals can experiment personal social competences, reducing stress, problems, and isolation through online social interactions [ 16 , 17 , 18 , 19 , 30 ], it might concurrently limit social experiences in face-to-face contexts when the online life starts to overshadow the offline one [ 23 , 80 , 94 , 106 ]. Consequently, following the theoretical work of Caplan [ 7 ], some gamers might find refuge in online games with decreasing depressive symptoms, social anxiety, and loneliness, whereas, in other gamers’ experiences, these correlates might increase, ensuring online socialization but failing in providing the needed face-to-face interactions.

Finally, in a compensatory Internet use model [ 20 ••, 98 ] by which addictive Internet-related activities might represent coping mechanisms to alleviate psychopathological symptoms and/or negative emotional states, people might use online gaming to counterbalance distress or negative situations in everyday life, carrying out a maladaptive coping strategy [ 31 , 32 , 33 ]. In this regard, according to the Yee’s [ 129 ] construct of motivations to play, the escapism has been identified as motivation to play that strongly predicts problematic gaming [ 16 , 31 , 32 , 142 , 143 , 144 ], especially in interaction with negative affects [ 111 , 143 , 145 , 146 , 147 , 148 ]. Overall, in line with previous studies [ 36 ••, 37 , 74 , 112 ], a new conceptualization of problematic online gaming and its related screening and assessment tools distinguishing between high engagement and pathological involvement in online videogames appear crucial.

Limitations and Conclusions

The results of the present review should be considered in view of the examined studies’ limitations. Firstly, the cross-sectional nature of the data limits the formal test of causality between social anxiety and problematic online gaming; thus, more longitudinal studies are needed to clarify the direction of their relationship. Secondly, studies largely used self-report methods which might be influenced by well-known bias, such as the lack of answer accuracy and social desirability. Furthermore, future studies should evaluate the relationship between social anxiety and problematic online gaming in interactions with other variables, contributing to the research field concerning the protective and predictive factors of problematic videogames use. Finally, the problematic online gaming among female users and gender-related differences in gaming habits are still understudied issues. However, the specific limitations of the present review should be considered. Firstly, the problematic online gaming research field is extremely prolific and largely explored and only studies published within the last ten years have been included in the present study. Consequently, this review might have excluded some relevant studies published more than ten years ago. Secondly, due to the electronic search of the studies, some not non-indexed papers into in the involved databases might have been missed. Finally, this review was based on English-language studies which excluded a significant proportion of the literature (especially East Asian).

Despite the limitations, the present review examined the literature of the last ten years concerning the association between problematic online gaming and social anxiety. According to King et al. [ 38 ••], studies on gaming behavior should include measures of comorbidity, thus addressing questions regarding the presence of other mental disorders. The current review of the literature confirmed a strong relationship among online gaming disorder and other psychosocial and comorbid factors, especially social anxiety, depression, and loneliness, thus reinforcing that great attention should be paid to the problematic or excessive online gaming as a maladaptive coping strategy for the psychopathological symptoms and/or negative emotional states regulation.

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

Lee BW, Leeson PRC. Online gaming in the context of social anxiety. Psychol Addict Behav. 2016;29(2):473–82. https://doi.org/10.1037/adb0000070 .

Article Google Scholar

Rapee RM, Heimberg RG. A cognitive-behavioral model of anxiety in social phobia. Behav Res Ther. 1997;35(8):741–56. https://doi.org/10.1016/S0005-7967[97]00022-3 .

Article CAS PubMed Google Scholar

McKenna KY, Bargh JA. Causes and consequences of social interaction on the Internet: a conceptual framework. Media Psychol. 1999;1(3):249–69. https://doi.org/10.1207/s1532785xmep0103_4 .

Ng BD, Wiemer-Hastings P. Addiction to the internet and online gaming. Cyberpsychol Behav. 2005;8(2):110–3. https://doi.org/10.1089/cpb.2005.8.110 .

Article PubMed Google Scholar

Peters CS, Malesky LA Jr. Problematic usage among highly-engaged players of massively multiplayer online role playing games. Cyberpsychol Behav. 2008;11(4):481–4. https://doi.org/10.1089/cpb.2007.0140 .

Caplan SE. Preference for online social interaction: a theory of problematic Internet use and psychosocial well-being. Commun Res. 2003;30(6):625–48. https://doi.org/10.1177/0093650203257842 .

Caplan SE. Relations among loneliness, social anxiety, and problematic Internet use. Cyberpsychol Behav. 2007;10(2):234–42. https://doi.org/10.1089/cpb.2006.9963 .

Caplan SE. Theory and measurement of generalized problematic Internet use: a two-step approach. Comput Hum Behav. 2010;26(5):1089–97. https://doi.org/10.1016/j.chb.2010.03.012 .

Lee BW, Stapinski LA. Seeking safety on the internet: relationship between social anxiety and problematic internet use. J Anxiety Disord. 2012;26(1):197–205. https://doi.org/10.1016/j.janxdis.2011.11.001 .

Cole SH, Hooley JM. Clinical and personality correlates of MMO gaming: anxiety and absorption in problematic internet use. Soc Sci Comput Rev. 2013;31(4):424–36. https://doi.org/10.1177/0894439312475280 .

Dalbudak E, Evren C, Aldemir S, Evren B. The severity of Internet addiction risk and its relationship with the severity of borderline personality features, childhood traumas, dissociative experiences, depression and anxiety symptoms among Turkish university students. Psychiatry Res. 2014;219(3):577–82. https://doi.org/10.1016/j.psychres.2014.02.032 .

Fayazi M, Hasani J. Structural relations between brain-behavioral systems, social anxiety, depression and internet addiction: with regard to revised Reinforcement Sensitivity Theory (r-RST). Comput Hum Behav. 2017;72:441–8. https://doi.org/10.1016/j.chb.2017.02.068 .

Harman JP, Hansen CE, Cochran ME, Lindsey CR. Liar, liar: Internet faking but not frequency of use affects social skills, self-esteem, social anxiety, and aggression. Cyberpsychol Behav. 2005;8(1):1–6. https://doi.org/10.1089/cpb.2005.8.1 .

Pilling S, Mayo-Wilson E, Mavranezouli I, Kew K, Taylor C, Clark DM. Recognition, assessment and treatment of social anxiety disorder: summary of NICE guidance. BMJ. 2013;346: f2541. https://doi.org/10.1136/bmj.f2541 .

Wei HT, Chen MH, Huang PC, Bai YM. The association between online gaming, social phobia, and depression: an internet survey. BMC Psychiatry. 2012;12(1):92. https://doi.org/10.1186/1471-244X-12-92 .

Article PubMed PubMed Central Google Scholar

Billieux J, Van der Linden M, Achab S, Khazaal Y, Paraskevopoulos L, Zullino D, Thorens G. Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth. Comput Hum Behav. 2013;29(1):103–9. https://doi.org/10.1016/j.chb.2012.07.021 .

Demetrovics Z, Urbán R, Nagygyörgy K, Farkas J, Zilahy D, Mervó B, Harmath E. Why do you play? The development of the motives for online gaming questionnaire (MOGQ). Behav Res Methods. 2011;43(3):814–25. https://doi.org/10.3758/s13428-011-0091-y .

Mills, D. J., Li, W., & Marchica, L. (2019). Original paper negative affect, life satisfaction, and internet gaming disorder: exploring the mediating effect of coping and the moderating effect of passion. World, 6 (1). https://doi.org/10.22158/wjssr.v6n1p45

Schneider LA, King DL, Delfabbro PH. Maladaptive coping styles in adolescents with Internet gaming disorder symptoms. Int J Ment Heal Addict. 2018;16(4):905–16. https://doi.org/10.1007/s11469-017-9756-9 .

•• Kardefelt-Winther, D. (2014a). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31 (1) , 351–354. https://doi.org/10.1016/j.chb.2013.10.059 [Not done in the last 3 years—but the article is important since it proposed a new conceptualization of Internet and its applications use, by suggesting that people might use Internet to counterbalance distress or negative situations in real-life experiences].

Giardina, A., Di Blasi, M., Schimmenti, A., King, D. L., Starcevic, V., & Billieux, J. (2021). Online gaming and prolonged self-isolation: evidence from Italian gamers during the COVID-19 outbreak. https://doi.org/10.36131/cnfioritieditore20210106

Lo VH, Wei R. Exposure to Internet pornography and Taiwanese adolescents’ sexual attitudes and behavior. J Broadcast Electron Media. 2005;49(2):221–37. https://doi.org/10.1207/s15506878jobem4902_5 .

Hussain Z, Griffiths MD. Excessive use of massively multi-player online role-playing games: a pilot study. Int J Ment Heal Addict. 2009;7(4):563. https://doi.org/10.1007/s11469-009-9202-8 .

Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, Pallesen S. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav. 2016;30(2):252. https://doi.org/10.1037/adb0000160 .

Bargeron AH, Hormes JM. Psychosocial correlates of internet gaming disorder: psychopathology, life satisfaction, and impulsivity. Comput Hum Behav. 2017;68:388–94. https://doi.org/10.1016/j.chb.2016.11.029 .

Beard CL, Wickham RE. Gaming-contingent self-worth, gaming motivation, and internet gaming disorder. Comput Hum Behav. 2016;61:507–15. https://doi.org/10.1016/j.chb.2016.03.046 .

Laconi S, Pirès S, Chabrol H. Internet gaming disorder, motives, game genres and psychopathology. Comput Hum Behav. 2017;75:652–9. https://doi.org/10.1016/j.chb.2017.06.012 .

Lemmens JS, Valkenburg PM, Gentile DA. The Internet gaming disorder scale. Psychological Assessment. 2015;27(2):567. https://doi.org/10.1037/pas0000062 .

Pontes HM, Griffiths MD. Measuring DSM-5 Internet gaming disorder: development and validation of a short psychometric scale. Comput Hum Behav. 2015;45:137–43. https://doi.org/10.1016/j.chb.2014.12.006 .

Jansz J, Martens L. Gaming at a LAN event: the social context of playing video games. New media & Society. 2005;7(3):333–55. https://doi.org/10.1177/2F1461444805052280 .

Di Blasi M, Giardina A, Giordano C, Lo Coco G, Tosto C, Billieux J, Schimmenti A. Problematic video game use as an emotional coping strategy: evidence from a sample of MMORPG gamers. Journal of Behavioural Addictions. 2019;8(1):25–34. https://doi.org/10.1556/2006.8.2019.02 .

Di Blasi M, Giardina A, Coco GL, Giordano C, Billieux J, Schimmenti A. A compensatory model to understand dysfunctional personality traits in problematic gaming: the role of vulnerable narcissism. Personality Individ Differ. 2020;160: 109921. https://doi.org/10.1016/j.paid.2020.109921 .

Schimmenti A, Guglielmucci F, Barbasio CP, Granieri A. Attachment disorganization and dissociation in virtual worlds: a study on problematic Internet use among players of online role playing games. Clin Neuropsychiatry. 2012;9(5):195–202.

Google Scholar

Bean AM, Nielsen RK, Van Rooij AJ, Ferguson CJ. Video game addiction: the push to pathologize video games. Prof Psychol Res Pract. 2017;48(5):378. https://doi.org/10.1037/pro0000150 .

Aarseth, E., Bean, A. M., Boonen, H., Colder Carras, M., Coulson, M., Das, D., … & Van Rooij, A. (2017). Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal. Journal of Behavioral Addictions . Advance online publication. https://doi.org/10.1556/2006.5.2016.088 .

•• Billieux, J., Flayelle, M., Rumpf, H. J., & Stein, D. J. (2019). High involvement versus pathological involvement in video games: a crucial distinction for ensuring the validity and utility of gaming disorder . Current Addiction Reports, 6(3), 323–330. https://doi.org/10.1007/s40429-019-00259-x [The paper highlighted the crucial distinction between high engagement and pathological involvement in online videogames].

Billieux J, King DL, Achab S, Bowden-Jones H. Functional impairment matters in the screening and diagnosis of gaming disorder. Journal of Behavioural Addictions. 2017;6(3):285–9. https://doi.org/10.1556/2006.6.2017.036 .

King, D. L., Chamberlain, S. R., Carragher, N., Billieux, J., Stein, D., Mueller, K., ... & Delfabbro, P. H. (2020b). Screening and assessment tools for gaming disorder: a comprehensive systematic review. Clinical Psychology Review , 77 , 101831. https://doi.org/10.1016/j.cpr.2020.101831 [The review of the several measures used to assess the problematic gaming suggested that the gaming disorder research field would benefit from a standard international tool].

Van Rooij AJ, Van Looy J, Billieux J. Internet Gaming Disorder as a formative construct: Implications for conceptualization and measurement. Psychiatry Clin Neurosci. 2017;71(7):445–58. https://doi.org/10.1111/pcn.12404 .

Van Rooij, A.J., Ferguson, C.J., Colder Carras, M., Bean, A. M., Helmersson, B., Etchells, P. J., ... & Przybylski, A. K. et al. (2018) A weak scientific basis for gaming disorder: let us err on the side of caution. Journal of Behavioral Addictions, 7, 1–9. https://akjournals.com/view/journals/2006/7/1/article-p1.xml . Accessed March 2021.

Hoff RA, Howell JC, Wampler J, Krishnan-Sarin S, Potenza MN. Differences in associations between problematic video-gaming, video-gaming duration, and weapon-related and physically violent behaviors in adolescents. J Psychiatr Res. 2020;121:47–55. https://doi.org/10.1016/j.jpsychires.2019.11.005 .

Holtz P, Appel M. Internet use and video gaming predict problem behavior in early adolescence. J Adolesc. 2011;34(1):49–58. https://doi.org/10.1016/j.adolescence.2010.02.004 .

Van Rooij AJ, Kuss DJ, Griffiths MD, Shorter GW, Schoenmakers TM, Van De Mheen D. The (co-) occurrence of problematic video gaming, substance use, and psychosocial problems in adolescents. J Behav Addict. 2014;3(3):157–65. https://doi.org/10.1556/jba.3.2014.013 .

American Psychiatric Association (APA). Diagnostic and Statistic Manual of Mental Disorders (5th ed) (DSM). Washington, DC: Author; 2013.

Book Google Scholar

King DL, Delfabbro PH. Internet gaming disorder treatment: a review of definitions of diagnosis and treatment outcome. Journal of Clinical Psychology. 2014;70(10):942–55. https://doi.org/10.1002/jclp.22097 .

Zajac K, Ginley MK, Chang R, Petry NM. Treatments for Internet gaming disorder and Internet addiction: a systematic review. Psychology of Addictive Behaviors. 2017;31(8):979. https://doi.org/10.1037/adb0000315 .

World Health Organization (2019) Addictive behaviours: Gaming disorder. Available at https://www.who.int/news-room/q-a-detail/addictive-behaviours-gaming-disorder . Accessed March 2021.

Billieux J, Schimmenti A, Khazaal Y, Maurage P, Heeren A. Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. J Behav Addict. 2015;4(3):119–23. https://doi.org/10.1556/2006.4.2015.009 .

Griffiths MD, Kuss DJ, Billieux J, Pontes HM. The evolution of Internet addiction: a global perspective. Addict Behav. 2016;53:193–5. https://doi.org/10.1016/j.addbeh.2015.11.001 .

Kardefelt‐Winther, D., Heeren, A., Schimmenti, A., van Rooij, A., Maurage, P., Carras, M., ... & Billieux, J. (2017). How can we conceptualize behavioural addiction without pathologizing common behaviours?. Addiction, 112(10), 1709-1715. https://doi.org/10.1111/add.13763

King DL, Delfabbro PH. Issues for DSM-V: Video-gaming disorder? Australian and New Zealand Journal of Psychiatry. 2013;47:20–2. https://doi.org/10.1177/2F0004867412464065 .

King DL, Billieux J, Carragher N, Delfabbro PH. Face validity evaluation of screening tools for gaming disorder: scope, language, and overpathologizing issues. J Behav Addict. 2020;9(1):1–13. https://doi.org/10.1556/2006.2020.00001 .

Ko CH, Lin HC, Lin PC, Yen JY. Validity, functional impairment and complications related to Internet gaming disorder in the DSM-5 and gaming disorder in the ICD-11. Australian & New Zealand Journal of Psychiatry. 2020;54(7):707–18. https://doi.org/10.1177/2F0004867419881499 .

Kuss DJ, Griffiths MD, Pontes HM. Chaos and confusion in DSM-5 diagnosis of Internet Gaming Disorder: issues, concerns, and recommendations for clarity in the field. J Behav Addict. 2017;6(2):103–9. https://doi.org/10.1556/2006.5.2016.062 .

Kuss DJ, Griffiths MD, Pontes HM. DSM-5 Diagnosis of Internet Gaming Disorder: some ways forward in overcoming issues and concerns in the gaming studies field. Response to the commentaries. Journal of Behavioural Addictions. 2017;6(2):133–41. https://doi.org/10.1556/2006.6.2017.032 .

Griffiths MD, Kuss DJ, Lopez-Fernandez O, Pontes HM. Problematic gaming exists and is an example of disordered gaming: commentary on: Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal (Aarseth et al.). Journal of Behavioral Addictions. 2017;6(3):296–301. https://doi.org/10.1556/2006.6.2017.037 .

Pontes HM. Investigating the differential effects of social networking site addiction and Internet gaming disorder on psychological health. J Behav Addict. 2017;6(4):601–10. https://doi.org/10.1556/2006.6.2017.075 .

Starcevic V, Billieux J. Does the construct of Internet addiction reflect a single entity or a spectrum of disorders? Clin Neuropsychiatry. 2017;14(1):5–10.

Haagsma MC, Caplan SE, Peters O, Pieterse ME. A cognitive-behavioral model of problematic online gaming in adolescents aged 12–22 years. Comput Hum Behav. 2013;29(1):202–9. https://doi.org/10.1016/j.chb.2012.08.006 .

Lemos IL, Cardoso A, Sougey EB. Cross-cultural adaptation and evaluation of the psychometric properties of the Brazilian version of the Video Game Addiction Test. Computers in Human Behaviour. 2016;55:207–13. https://doi.org/10.1016/j.chb.2015.09.019 .

Männikkö N, Billieux J, Kääriäinen M. Problematic digital gaming behavior and its relation to the psychological, social and physical health of Finnish adolescents and young adults. J Behav Addict. 2015;4(4):281–8. https://doi.org/10.1556/2006.4.2015.040 .

Milani, L., Camisasca, E., Ionio, C., Miragoli, S., & Di Blasio, P. (2019). Video games use in childhood and adolescence: social phobia and differential susceptibility to media effects. Clinical Child Psychology and Psychiatry , 1359104519882754. https://doi.org/10.1177/2F1359104519882754

Kashdan TB, Herbert JD. Social anxiety disorder in childhood and adolescence: current status and future directions. Clin Child Fam Psychol Rev. 2001;4(1):37–61. https://doi.org/10.1023/A:1009576610507 .

King DL, Delfabbro PH, Griffiths MD, Gradisar M. Assessing clinical trials of Internet addiction treatment: a systematic review and CONSORT evaluation. Clin Psychol Rev. 2011;31:1110–6. https://doi.org/10.1016/j.cpr.2011.06.009 .

Kuss DJ, Griffiths MD. Internet gaming addiction: a systematic review of empirical research. Int J Ment Heal Addict. 2012;10:278–96. https://doi.org/10.1007/s11469-011-9318-5 .

Peng W, Liu M. Online gaming dependency: a preliminary study in China. Cyberpsychol Behav Soc Netw. 2010;13(3):329–33. https://doi.org/10.1089/cyber.2009.0082 .

Thomas NJ, Martin FH. Video-arcade game, computer game and Internet activities of Australian students: participation habits and prevalence of addiction. Aust J Psychol. 2010;62:59–66. https://doi.org/10.1080/00049530902748283 .

American Psychological Association. (2021). Developing adolescents: A reference for professionals . http://www.apa.org/topics/teens/developing-adolescents-professionals-reference .

Vannucci A, Simpson EG, Gagnon S, Ohannessian CM. Social media use and risky behaviors in adolescents: a meta-analysis. J Adolesc. 2020;79:258–74. https://doi.org/10.1016/j.adolescence.2020.01.014 .

Fam JY. Prevalence of internet gaming disorder in adolescents: a meta-analysis across three decades. Scand J Psychol. 2018;59:524–31. https://doi.org/10.1111/sjop.12459 .

Martončik M, Lokša J. Do World of Warcraft (MMORPG) players experience less loneliness and social anxiety in online world (virtual environment) than in real world (offline)? Comput Hum Behav. 2016;56:127–34. https://doi.org/10.1016/j.chb.2015.11.035 .

Sioni SR, Burleson MH, Bekerian DA. Internet gaming disorder: social phobia and identifying with your virtual self. Computers in Human Behaviour. 2017;71:11–5. https://doi.org/10.1016/j.chb.2017.01.044 .

Rosliana, L., & Widiandari, A. (2020). Online Game and the Hikikomori Phenomenon in Japan. In E3S Web of Conferences (Vol. 202, p. 07080). EDP Sciences. https://doi.org/10.1051/e3sconf/202020207080

Stavropoulos V, Anderson EE, Beard C, Latifi MQ, Kuss D, Griffiths M. A preliminary cross-cultural study of Hikikomori and Internet Gaming Disorder: the moderating effects of game-playing time and living with parents Addictive Behaviors Reports. 2019;9: 100137. https://doi.org/10.1016/j.abrep.2018.10.001 .

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Prisma Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7): e1000097. https://doi.org/10.1371/journal.pmed.1000097 .

Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol. 2009;12(1):77–95. https://doi.org/10.1080/15213260802669458 .

Phan O, Prieur C, Bonnaire C, Obradovic I. Internet gaming disorder: exploring its impact on satisfaction in life in PELLEAS adolescent sample. Int J Environ Res Public Health. 2020;17(1):3. https://doi.org/10.3390/ijerph17010003 .

Vanzoelen D, Caltabiano ML. The role of social anxiety, the behavioural inhibition system and depression in online gaming addiction in adults. Journal of Gaming & Virtual Worlds. 2016;8(3):231–45. https://doi.org/10.1386/jgvw.8.3.231_1 .

Sheng, J. R., & Wang, J. L. (2019). Development and psychometric properties of the problematic mobile video gaming scale. Current Psychology , 1-11. https://doi.org/10.1007/s12144-019-00415-6

Wang HZ, Sheng JR, Wang JL. The association between mobile game addiction and depression, social anxiety, and loneliness. Front Public Health. 2019;7:247. https://doi.org/10.3389/fpubh.2019.00247 .

Khalil, S. A., Kamal, H., & Elkouly, H. (2020). The prevalence of problematic internet use among a sample of Egyptian adolescents and its psychiatric comorbidities. International Journal of Social Psychiatry , 0020764020983841. https://doi.org/10.1177/0020764020983841

Sigerson L, Li AYL, Cheung MWL, Luk JW, Cheng C. Psychometric properties of the Chinese internet gaming disorder scale. Addict Behav. 2017;74:20–6. https://doi.org/10.1016/j.addbeh.2017.05.031 .

Subramaniam M, Chua BY, Abdin E, Pang S, Satghare P, Vaingankar JA, Chong SA. Prevalence and correlates of Internet gaming problem among Internet users: results from an Internet survey. Ann Acad Med Singapore. 2016;45(5):174–83.

Starcevic V, Choi TY, Kim TH, Yoo SK, Bae S, Choi BS, Han DH. Internet gaming disorder and gaming disorder in the context of seeking and not seeking treatment for video-gaming. J Psychiatr Res. 2020. https://doi.org/10.1016/j.jpsychires.2020.06.007 .

Müller KW, Beutel ME, Dreier M, Wölfling K. A clinical evaluation of the DSM-5 criteria for Internet Gaming Disorder and a pilot study on their applicability to further Internet-related disorders. J Behav Addict. 2019;8(1):16–24. https://doi.org/10.1556/2006.7.2018.140 .

Wölfling, K., Beutel, M. E., & Müller, K. W. (2016). OSV-S–skala zum onlinesuchtverhalten [AICA-S–Scale for the assessment of internet and computer game addiction]. Diagnostische Verfahren in der Psychotherapie [Diagnostic Measures in Psychotherapy] , 362–366.

Chen SH, Weng LJ, Su YJ, Wu HM, Yang PF. Development of a Chinese Internet addiction scale and its psychometric study. Chinese Journal of Psychology. 2003;45(3):279–94.

Lopez-Fernandez O, Williams AJ, Kuss DJ. Measuring female gaming: gamer profile, predictors, prevalence, and characteristics from psychological and gender perspectives. Front Psychol. 2019;10:898. https://doi.org/10.3389/fpsyg.2019.00898 .

Marino C, Canale N, Vieno A, Caselli G, Scacchi L, Spada MM. Social anxiety and Internet gaming disorder: the role of motives and metacognitions. J Behav Addict. 2020;9(3):617–28. https://doi.org/10.1556/2006.2020.00044 .

Severo, R. B., Soares, J. M., Affonso, J. P., Giusti, D. A., de Souza Junior, A. A., de Figueiredo, V. L., ... & Pontes, H. M. (2020). Prevalence and risk factors for internet gaming disorder. Brazilian Journal of Psychiatry , 42 (5), 532-535. doi: https://doi.org/10.1590/1516-4446-2019-0760

Wang HY, Cheng C. Psychometric evaluation and comparison of two gaming disorder measures derived from the DSM-5 and ICD-11 frameworks. Front Psych. 2020;11:1490. https://doi.org/10.3389/fpsyt.2020.577366 .

Kircaburun K, Griffiths MD, Billieux J. Psychosocial factors mediating the relationship between childhood emotional trauma and internet gaming disorder: a pilot study. Eur J Psychotraumatol. 2019;10(1):1565031. https://doi.org/10.1080/20008198.2018.1565031 .

Bányai, F., Zsila, Á., Király, O., Maraz, A., Elekes, Z., Griffiths, M. D., ... & Demetrovics, Z. (2017). Problematic social media use: results from a large-scale nationally representative adolescent sample. PLoS One , 12 (1), e0169839. https://doi.org/10.1371/journal.pone.0169839

Van Rooij AJ, Schoenmakers TM, Van de Eijnden RJ, Van de Mheen D. Compulsive internet use: the role of online gaming and other internet applications. J Adolesc Health. 2010;47(1):51–7. https://doi.org/10.1016/j.jadohealth.2009.12.021 .

Meerkerk GJ, Van Den Eijnden RJ, Vermulst AA, Garretsen HF. The compulsive internet use scale (CIUS): some psychometric properties. Cyberpsychol Behav. 2009;12(1):1–6. https://doi.org/10.1089/cpb.2008.0181 .

Van Rooij AJ, Schoenmakers TM, Van den Eijnden RJ, Vermulst AA, van de Mheen D. Video game addiction test: validity and psychometric characteristics. Cyberpsychol Behav Soc Netw. 2012;15(9):507–11. https://doi.org/10.1089/cyber.2012.0007 .

Colder Carras M, Van Rooij AJ, Van de Mheen D, Musci R, Xue QL, Mendelson T. Video gaming in a hyperconnected world: a cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents. Comput Hum Behav. 2017;68:472–9. https://doi.org/10.1016/j.chb.2016.11.060 .

Van Rooij AJ, Ferguson CJ, Van de Mheen D, Schoenmakers TM. Time to abandon Internet Addiction? Predicting problematic Internet, game, and social media use from psychosocial well-being and application use. Clin Neuropsychiatry. 2017;14(1):113–21.

Ko CH, Liu GC, Hsiao S, Yen JY, Yang MJ, Lin WC, et al. Brain activities associated with gaming urge of online gaming addiction. J Psychiatr Res. 2009;43:739–47. https://doi.org/10.1016/j.jpsychires.2008.09.012 .

Hyun GJ, Han DH, Lee YS, Kang KD, Yoo SK, Chung US, Renshaw PF. Risk factors associated with online game addiction: a hierarchical model. Comput Hum Behav. 2015;48:706–13. https://doi.org/10.1016/j.chb.2015.02.008 .

Park JH, Han DH, Kim BN, Cheong JH, Lee YS. Correlations among social anxiety, self-esteem, impulsivity, and game genre in patients with problematic online game playing. Psychiatry Investig. 2016;13(3):297. https://doi.org/10.4306/pi.2016.13.3.297 .

Young KS. Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychological Reports. 1996;79(3):899–902. https://doi.org/10.2466/2Fpr0.1996.79.3.899 .

Karaca, S., Karakoc, A., Gurkan, O. C., Onan, N., & Barlas, G. U. (2020). Investigation of the online game addiction level, sociodemographic characteristics and social anxiety as risk factors for online game addiction in middle school students. Community Mental Health Journal , 1-9. https://doi.org/10.1007/s10597-019-00544-z

Horzum, M. B., Tuncay, A. R. A. S., & BALTA, Ö. Ç. (2008). Computer game addiction scale for children. Türk Psikolojik Danışma ve Rehberlik Dergisi , 3 (30), 76–88. Retrieved from https://dergipark.org.tr/en/pub/tpdrd/issue/21450/229637 . Accessed March 2021.

Gentile D. Pathological video-game use among youth ages 8 to 18: A national study. Psychological Science. 2009;20(5):594–602. https://doi.org/10.1111/2Fj.1467-9280.2009.02340.x .

Gentile DA, Choo H, Liau A, Sim T, Li D, Fung D, Khoo A. Pathological video game use among youths: a two-year longitudinal study. Pediatrics. 2011;127(2):e319–29. https://doi.org/10.1542/peds.2010-1353 .

Caplan SE. Problematic Internet use and psychosocial well-being: development of a theory-based cognitive-behavioural measurement instrument. Computers in Human Behaviour. 2002;18:553–75. https://doi.org/10.1016/S0747-5632(02)00004-3 .

Davis RA. A cognitive-behavioural model of pathological Internet use. Computers in Human Behaviour. 2001;17:187–95. https://doi.org/10.1016/S0747-5632(00)00041-8 .

Kardefelt-Winther D. Problematizing excessive online gaming and its psychological predictors. Comput Hum Behav. 2014;31:118–22. https://doi.org/10.1016/j.chb.2013.10.017 .

Sauter M, Braun T, Mack W. Social context and gaming motives predict mental health better than time played: an exploratory regression analysis with over 13,000 video game players. Cyberpsychol Behav Soc Netw. 2021;24(2):94–100. https://doi.org/10.1089/cyber.2020.0234 .

Lehenbauer-Baum M, Klaps A, Kovacovsky Z, Witzmann K, Zahlbruckner R, Stetina BU. Addiction and engagement: an explorative study toward classification criteria for internet gaming disorder. Cyberpsychol Behav Soc Netw. 2015;18(6):343–9. https://doi.org/10.1089/cyber.2015.0063 .

Charlton, D. P., & Danforth, I. D. W. (2007). Distinguishing addiction and high engagement in the context of online game playing. Psychology: Journal Articles (Peer-Reviewed). Paper 3. http://digitalcommons.bolton.ac.uk/psych_journalspr/3 . Accessed March 2021.

Connor KM, Davidson JR, Churchill LE, Sherwood A, Weisler RH, Foa E. Psychometric properties of the Social Phobia Inventory (SPIN): new self-rating scale. Br J Psychiatry. 2000;176(4):379–86. https://doi.org/10.1192/bjp.176.4.379 .

D’El Rey GJF, Lacava JPL, Cardoso R. Internal consistency of the Portuguese version of the Mini-Social Phobia Inventory (Mini-SPIN). Archives of Clinical Psychiatry (São Paulo). 2007;34(6):266–9. https://doi.org/10.1590/S0101-60832007000600002 .

Weeks JW, Spokas ME, Heimberg RG. Psychometric evaluation of the mini-social phobia inventory (Mini-SPIN) in a treatment-seeking sample. Depress Anxiety. 2007;24(6):382–91. https://doi.org/10.1002/da.20250 .

Gori, A., Giannini, M., Socci, S., Luca, M., Dewey, D. E., Schuldberg, D., et al. (2013). Assessing social anxiety disorder: psychometric properties of the Italian social phobia inventory (ISPIN). Clinical Neuropsychiatry, 10 (1), 37. https://scholarworks.umt.edu/psych_pubs/11

La Greca AM, Lopez N. Social anxiety among adolescents: linkages with peer relations and friendships. J Abnorm Child Psychol. 1998;26(2):83–94. https://doi.org/10.1023/A:1022684520514 .

La Greca AM, Stone WL. Social anxiety scale for children-revised: factor structure and concurrent validity. J Clin Child Psychol. 1993;22(1):17–27. https://doi.org/10.1207/s15374424jccp2201_2 .

La Greca AM, Dandes SK, Wick P, Shaw K, Stone WL. Development of the Social Anxiety Scale for Children: reliability and concurrent validity. J Clin Child Psychol. 1988;17(1):84–91. https://doi.org/10.1207/s15374424jccp1701_11 .

Mattick RP, Clarke JC. Development and validation of measures of social phobia scrutiny fear and social interaction anxiety. Behav Res Ther. 1998;36(4):455–70. https://doi.org/10.1016/S0005-7967[97]10031-6 .

Peters L, Sunderland M, Andrews G, Rapee RM, Mattick RP. Development of a short form Social Interaction Anxiety (SIAS) and Social Phobia Scale (SPS) using nonparametric item response theory: the SIAS-6 and the SPS-6. Psychol Assess. 2012;24(1):66. https://doi.org/10.1037/a0024544 .

Heimberg RG, Horner KJ, Juster HR, Safren SA, Brown EJ, Schneier FR, Liebowitz MR. Psychometric properties of the Liebowitz social anxiety scale. Psychol Med. 1999;29(1):199–212.

Article CAS Google Scholar

Watson D, Friend R. Measurement of social-evaluative anxiety. J Consult Clin Psychol. 1969;33(4):448. https://doi.org/10.1037/h0027806 .

Demir T, Eralp-Demir D, Türksoy N, Özmen E, Uysal Ö. Çocuklar için sosyal anksiyete ölçeğinin geçerlilik ve güvenilirliği. Düşünen Adam. 2000;13(1):42–8.

Wang, X. D.,Wang, X. L., & Ma, H. (1999). Handbook of mental health assessment scales (updated version). Chinese Journal of Mental Health , 244–246.

Nelemans SA, Meeus WH, Branje SJ, Van Leeuwen K, Colpin H, Verschueren K, Goossens L. Social Anxiety Scale for Adolescents (SAS-A) Short Form: longitudinal measurement invariance in two community samples of youth. Assessment. 2017. https://doi.org/10.1177/1073191116685808 .

Hardt, J. (2008). The symptom checklist-27-plus (SCL-27-plus): a modern conceptualization of a traditional screening instrument. GMS Psycho-Social Medicine , 5 .

Sheehan DV, Sheehan KH, Shytle RD, Janavs J, Bannon Y, Rogers JE, Wilkinson B. Reliability and validity of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). J Clin Psychiatry. 2010;71(3):313–26. https://doi.org/10.4088/JCP.09m05305whi .

Yee N. Motivations for play in online games. Cyberpsychol Behav. 2006;9:772–5. https://doi.org/10.1089/cpb.2006.9.772 .

Gentile, D. A., Bailey, K., Bavelier, D., Brockmyer, J. F., Cash, H., Coyne, S. M., ... & Young, K. (2017). Internet gaming disorder in children and adolescents. Pediatrics , 140 (Supplement 2), S81-S85. https://doi.org/10.1542/peds.2016-1758H

Griffiths, M. D., Király, O., Pontes, H. M., & Demetrovics, Z. (2015). An overview of problematic gaming. In E. Aboujaoude & V. Starcevic (Eds.), Mental health in the digital age: Grave dangers, great promise (pp. 27–45). Oxford University Press. https://doi.org/10.1093/med/9780199380183.003.0002 .

Bonetti L, Campbell MA, Gilmore L. The relationship of loneliness and social anxiety with children’s and adolescents’ online communication. Cyberpsychol Behav Soc Netw. 2010;13(3):279–85. https://doi.org/10.1089/cyber.2009.0215 .

Casale S, Tella L, Fioravanti G. Preference for online social interactions among young people: direct and indirect effects of emotional intelligence. Personality Individ Differ. 2013;54(4):524–9. https://doi.org/10.1016/j.paid.2012.10.023 .

Valkenburg PM, Peter J. Social consequences of the Internet for adolescents: a decade of research. Curr Dir Psychol Sci. 2009;18(1):1–5. https://doi.org/10.1111/j.1467-8721.2009.01595.x .

Valkenburg PM, Peter J. Online communication among adolescents: an integrated model of its attraction, opportunities, and risks. J Adolesc Health. 2011;48(2):121–7. https://doi.org/10.1016/j.jadohealth.2010.08.020 .

Slater MD. Reinforcing spirals: the mutual influence of media selectivity and media effects and their impact on individual behavior and social identity. Commun Theory. 2007;17(3):281–303. https://doi.org/10.1111/j.1468-2885.2007.00296.x .

Leary MR. Responses to social exclusion: social anxiety, jealousy, loneliness, depression, and low self-esteem. J Soc Clin Psychol. 1990;9(2):221–9. https://doi.org/10.1521/jscp.1990.9.2.221 .

Boursier, V., Gioia, F., Musetti, A., & Schimmenti, A. (2020). Facing loneliness and anxiety during the COVID-19 isolation: the role of excessive social media use in a sample of Italian adults. Frontiers in psychiatry , 11 . doi: https://doi.org/10.3389/fpsyt.2020.586222

Boursier V, Musetti A, Gioia F, Flayelle M, Billieux J, Schimmenti A. Is watching TV series an adaptive coping strategy during the COVID-19 pandemic? Insights from an Italian community sample. Front Psych. 2021;12:554. https://doi.org/10.3389/fpsyt.2021.599859 .

Gioia F, Fioravanti G, Casale S, Boursier V. The effects of the fear of missing out on people’s social networking sites use during the COVID-19 pandemic: the mediating role of online relational closeness and individuals’ online communication attitude. Front Psych. 2021;12:146. https://doi.org/10.3389/fpsyt.2021.620442 .

Bozoglan B, Demirer V, Sahin I. Loneliness, self-esteem, and life satisfaction as predictors of Internet addiction: a cross-sectional study among Turkish university students. Scand J Psychol. 2013;54(4):313–9. https://doi.org/10.1111/sjop.12049 .

Ballabio M, Griffiths MD, Urbán R, Quartiroli A, Demetrovics Z, Király O. Do gaming motives mediate between psychiatric symptoms and problematic gaming? An empirical survey study. Addiction Research & Theory. 2017;25(5):397–408. https://doi.org/10.1080/16066359.2017.1305360 .

Bowditch L, Chapman J, Naweed A. Do coping strategies moderate the relationship between escapism and negative gaming outcomes in World of Warcraft (MMORPG) players? Comput Hum Behav. 2018;86:69–76. https://doi.org/10.1016/j.chb.2018.04.030 .

Schimmenti A, Infanti A, Badoud D, Laloyaux J, Billieux J. Schizotypal personality traits and problematic use of massively-multiplayer online role-playing games (MMORPGs). Comput Hum Behav. 2017;74:286–93. https://doi.org/10.1016/j.chb.2017.04.048 .

Billieux, J., Deleuze, J., Griffiths, M. D., & Kuss, D. J. (2015a). Internet gaming addiction: the case of massively multiplayer online role-playing games. Textbook of Addiction Treatment: International perspectives, 1515-1525. doi: https://doi.org/10.1007/978-88-470-5322-9_105

Chang SM, Hsieh GM, Lin SS. The mediation effects of gaming motives between game involvement and problematic Internet use: escapism, advancement and socializing. Comput Educ. 2018;122:43–53. https://doi.org/10.1016/j.compedu.2018.03.007 .

Király O, Griffiths MD, Demetrovics Z. Internet gaming disorder and the DSM-5: conceptualization, debates, and controversies. Curr Addict Rep. 2015;2(3):254–62. https://doi.org/10.1007/s40429-015-0066-7 .

Maroney N, Williams BJ, Thomas A, Skues J, Moulding R. A stress-coping model of problem online video game use. Int J Ment Heal Addict. 2019;17(4):845–58. https://doi.org/10.1007/s11469-018-9887-7 .

Download references

Author information

Authors and affiliations.

University of Naples Federico II, Corso Umberto I, 40, 80138, Naples, Italy

Francesca Gioia, Gianluca Mariano Colella & Valentina Boursier

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Valentina Boursier .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Gioia, F., Colella, G.M. & Boursier, V. Evidence on Problematic Online Gaming and Social Anxiety over the Past Ten Years: a Systematic Literature Review. Curr Addict Rep 9 , 32–47 (2022). https://doi.org/10.1007/s40429-021-00406-3

Download citation

Accepted : 23 November 2021

Published : 05 January 2022

Issue Date : March 2022

DOI : https://doi.org/10.1007/s40429-021-00406-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Online problematic gaming
Online gaming addiction
Internet gaming
Social anxiety
Social phobia
Find a journal
Publish with us
Track your research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
My Account Login
Explore content
About the journal
Publish with us
Sign up for alerts
Open access
Published: 28 November 2022

Psychological treatments for excessive gaming: a systematic review and meta-analysis

Jueun Kim 1 ,
Sunmin Lee 1 ,
Dojin Lee 1 ,
Sungryul Shim 2 ,
Daniel Balva 3 ,
Kee-Hong Choi 4 ,
Jeanyung Chey 5 ,
Suk-Ho Shin 6 &
Woo-Young Ahn 5

Scientific Reports volume 12 , Article number: 20485 ( 2022 ) Cite this article

4044 Accesses

1 Citations

4 Altmetric

Metrics details

Human behaviour

Despite widespread public interest in problematic gaming interventions, questions regarding the empirical status of treatment efficacy persist. We conducted pairwise and network meta-analyses based on 17 psychological intervention studies on excessive gaming ( n = 745 participants). The pairwise meta-analysis showed that psychological interventions reduce excessive gaming more than the inactive control (standardized mean difference [SMD] = 1.70, 95% confidence interval [CI] 1.27 to 2.12) and active control (SMD = 0.88, 95% CI 0.21 to 1.56). The network meta-analysis showed that a combined treatment of Cognitive Behavioral Therapy (CBT) and Mindfulness was the most effective intervention in reducing excessive gaming, followed by a combined CBT and Family intervention, Mindfulness, and then CBT as a standalone treatment. Due to the limited number of included studies and resulting identified methodological concerns, the current results should be interpreted as preliminary to help support future research focused on excessive gaming interventions. Recommendations for improving the methodological rigor are also discussed.

Microdosing with psilocybin mushrooms: a double-blind placebo-controlled study

A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions

Adults who microdose psychedelics report health related motivations and lower levels of anxiety and depression compared to non-microdosers

Introduction.

Excessive gaming refers to an inability to control one’s gaming habits due to a significant immersion in games. Such an immersion may result in experienced difficulties in one’s daily life 1 , including health problems 2 , poor academic or job performance 3 , 4 , and poor social relationships 5 . Although there is debate regarding whether excessive gaming is a mental disorder, the 11th revision of the International Classification of Diseases (ICD-11) included Gaming Disorder as a disorder in 2019 6 . While there is no formal diagnosis for Gaming Disorder listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), the DSM-5 included Internet Gaming Disorder (IGD) as a condition for further study 7 . In the time since the DSM-5’s publication, research on excessive gaming has widely continued. Although gaming disorder’s prevalence appears to be considerably heterogeneous by country, results from a systematic review of 53 studies conducted between 2009 and 2019 indicated a global prevalence of excessive gaming of 3.05% 8 . More specifically, a recent study found that Egypt had the highest IGD prevalence rate of 10.9%, followed by Saudi Arabia (8.8%), Indonesia (6.1%), and India (3.8%) among medical students 9 .

While the demand for treatment of excessive gaming has increased in several countries 10 , standard treatment guidelines for problematic gaming are still lacking. For example, a survey in Australia and New Zealand revealed that psychiatrics— particularly child psychiatrists, reported greater frequency of excessive gaming in their practice, yet 43% of the 289 surveyed psychiatrists reported that they were not well informed of treatment modalities for managing excessive gaming 11 . Similarly, 87% of mental health professionals working in addiction-related institutions in Switzerland reported a significant need for professional training in excessive gaming interventions 12 . However, established services for the treatment of gaming remain scarce and disjointed.

Literature has identified a variety of treatments for excessive gaming, but no meta-analysis has yet been conducted on effectiveness of the indicated interventions. The only meta-analysis to date has focused on CBT 13 , and while results demonstrated excellent efficacy in reducing excessive gaming. However, the study did not compare the intervention with other treatment options. Given that gaming behavior is commonly affected by cognitive and behavioral factors as well as social and familial factors 14 , 15 , 16 , it would also be important to examine the effectiveness of treatment approaches that reflect social and familial influences. While two systematic reviews examined diverse therapeutic approaches, they primarily reported methodological concerns of the current literature and did not assess the weight of evidence 17 , 18 . Given that studies in this area are rapidly evolving and studies employing rigorous methodological approaches have since emerged 19 , 20 , a meta-analytic study that analyzes and synthesizes the current stage of methodological limitations while also providing a comprehensive comparison of intervention options is warranted.

In conducting such a study, undertaking a traditional pairwise meta-analysis is vital to assess overall effectiveness of diverse interventions. Particularly, moderator and subgroup analyses in pairwise meta-analysis provide necessary information as to whether effect sizes vary as a function of study characteristics. Furthermore, to obtain a better understanding of the superiority and inferiority of all clinical trials in excessive gaming psychological interventions, it is useful to employ a network meta-analysis, which allows for a ranking and hierarchy of the included interventions. While a traditional pair-wise analysis synthesizes direct evidence of one intervention compared with one control condition, a network meta-analysis incorporates multiple comparisons in one analysis regardless of whether the original studies used them as control groups. It enters all treatment and control arms of each study, and makes estimates of the differences in interventions by using direct evidence (e.g., direct estimates where two interventions were compared) and indirect evidence (e.g., generated comparisons between interventions from evidence loops in a network 21 . Recent meta-analytic studies on treatments for other health concerns and disorders have used this analysis to optimize all available evidence and build treatment hierarchies 22 , 23 , 24 .

In this study, the authors used a traditional pairwise meta-analysis and network meta-analysis to clarify the overall and relative effectiveness of psychological treatments for excessive gaming. The authors also conducted a moderator analysis to examine potential differences in treatment efficacy between Randomized Controlled Trials (RCTs) and non-RCTs, age groups, regions, and research qualities. Finally, the authors examined follow-up treatment efficacy and treatment effectiveness on common comorbid symptoms and characteristics (e.g., depression, anxiety, and impulsivity).

The protocol for this review has been registered in the International Prospective Register of Systematic Review (PROSPERO 2021: CRD 42021231205) and is available for review via the following link: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=231205 . Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) network meta-analysis checklist 25 is included in Supplementary Material 1 .

Identification and selection of studies

The authors searched seven databases, which included ProQuest, PubMed, Scopus, Web of Science, PsycINFO, Research Information Sharing Service (RISS), and DBpia. Given that a substantial number of studies have been published particularly in East Asia and exclusion of literature from the area in languages other than English has been discussed as a major limitation in previous reviews 17 , 18 , the authors gave special attention to gaming treatment studies in English and other languages from that geographical area. Additionally, the authors searched Google Scholar to ensure that no studies were accidentally excluded. The authors conducted extensive searches for studies published in peer-reviewed journals between the first available year (year 2002) and October 31, 2022, using the following search terms: “internet”, or “video”, or “online”, or “computer”, and “game”, or “games”, or “gaming”, and “addiction”, or “addictions”, or “disorder”, “disorders”, or “problem”, or “problems”, or “problematic”, or “disease”, or “diseases”, or “excessive”, or “pathological”, or “addicted”, and “treatment”, or “treatments”, or “intervention”, or “interventions”, or “efficacy”, or “effectiveness”, or “effective”, or “clinical”, or “therapy”, or “therapies”. Search strategies applied to each database is provided in Supplementary Material 2 .

The authors included studies that recruited individuals who were excessively engaging in gaming, according to cutoff scores for different game addiction scales. Since there is not yet an existing consensus on operational definitions for excessive gaming, the authors included studies that recruited individuals who met high-risk cutoff score according to the scales used in each respective study (e.g., Internet Addiction Test [modified in game environments] > 70). The authors also sought studies that provided pretest and posttest scores from the game addiction scales in both the intervention and control groups. Studies meeting the following criteria were excluded: (a) the study targeted excessive Internet use but did not exactly target excessive gaming; (b) the study provided a prevention program rather than an intervention program; (c) the study provided insufficient data to perform an analysis of the effect sizes and follow-up contact to the authors of such studies did not yield the information necessary for inclusion within this paper; and (d) the study conducted undefinable types of intervention with unclear psychological orientations (e.g., art therapy with an undefined psychological intervention, fitness programs, etc.).

Two authors (D.L. and S.L.) independently screened the titles and abstracts of articles identified by the electronic searches and excluded irrelevant studies. A content expert (J.K.) examined the intervention descriptions to determine intervention types that were eligible for this review. All treatments were primarily classified based on the treatment theory, protocol, and descriptions about the procedures presented in each paper. D.L. and S.L.—both of whom have been in clinical training for 2 years categorized treatment type, to which J.K., a licensed psychologist, cross-checked and confirmed the categorization. The authors resolved disagreements through discussion. The specific example of intervention type classification is provided in Supplementary Material 3 .

Risk of bias and data extraction

Three independent authors assessed the following risks of bias among the included studies. The authors used the Risk of Bias 2.0 (RoB 2) tool for RCT studies and the Risk Of Bias In Non-Randomized Studies of Intervention (ROBINS-I) tool for non-RCT studies. The RoB 2 evaluates biases of (a) randomization processes; (b) deviations from intended interventions; (c) missing outcome data; (d) measurement of the outcome; and (e) selection of the reported result, and it categorizes the risk of bias in each dimension into three levels (low risk, moderate risk, and high risk). The ROBINS-I evaluates biases of (a) confounding variables; (b) selection of participants; (c) classification of interventions; (d) deviations from intended interventions; (e) missing data; (f) measurement of outcomes; and (g) selection of the reported result, and it categorizes the risk of bias in each dimension into five levels (low risk, moderate risk, serious risk, critical risk, and no information). After two authors (D.L. and S.L.) assessed each study, another author (J.K.) cross-checked the assessment.

For each study, the authors collected descriptive data, which included the sample size as well as participants’ ages, and regions where the studies were conducted. The authors also collected clinical data, including whether the study design was a RCT, types of treatment and control, treatment duration, and the number of treatment sessions. Finally, the authors collected data on the follow-up periods and the measurement tools used in each study.

Data analysis

The authors employed separate pairwise meta-analyses in active control and inactive control studies using R-package “meta” 26 and employed a random-effects model due to expected heterogeneity among studies. A random-effects model assumes that included studies comprise random samples from the larger population and attempt to generalize findings 27 . The authors categorized inactive control groups including no treatment and wait-list control and categorized active control groups including pseudo training (e.g., a classic stimulus-control compatibility training) and other types of psychological interventions (e.g., Behavioral Therapy, CBT, etc.). The authors also used the bias-corrected standardized mean change score (Hedges’ g ) due to small sample sizes with the corresponding 95% confidence interval 28 . The authors’ primary effectiveness outcome was a mean score change on game addiction scales from pre-treatment to post-treatment. Hedges’ g effect sizes were interpreted as small ( g = 0.15), medium ( g = 0.40) and large ( g = 0.75), as suggested by Cohen 29 . The authors used a conservative estimate of r = 0.70 for the correlation between pre-and post-treatment measures 30 , and to test heterogeneity, the authors calculated Higgins’ I 2 , which is the percentage of variability in effect estimates due to heterogeneity among studies rather than chance. I 2 > 75% is considered substantial heterogeneity 31 .

The authors conducted moderator analyses as a function of RCT status (RCT versus non-RCT), age group (adolescents versus adults), region (Eastern versus Western), and research quality (high versus low). The authors divided high versus low quality studies using median values of research quality scores (RCT: low [0–2] versus high [3–5], non-RCT: low [0–4] versus high [5]). The authors calculated Cochran’s Q for heterogeneity: A significant Q value indicates a potentially important moderator variable. For the subgroup analyses of follow-up periods and other outcomes, the authors conducted separate pairwise analyses in 1- to 3-month follow-up studies and in 4- to 6-month follow-up studies and separate analyses in depression, anxiety, and impulsivity outcome studies.

The authors sought to further explore relative effectiveness of treatment types and performed a frequentist network meta-analysis using the R-package “netmeta” 4.0.4 version 26 . To examine whether transitivity and consistency assumptions for network meta-analysis were met, the authors assessed global and local inconsistency. To test network heterogeneity, the authors calculated Cochran’s Q to compare the effect of a single study with the pooled effect of the entire study. The authors drew the geometry plot of the network meta-analysis through the netgraph function in “netmeta”, and the thicker lines between the treatments indicated a greater number of studies.

The authors presented the treatment rankings based on estimates using the surface area under the cumulative ranking curve (SUCRA) 32 . The SUCRA ranged from 0 to 100%, with higher scores indicating greater probability of more optimal treatment. The authors also generated a league table to present relative effectiveness between all possible comparisons between treatments. When weighted mean difference for pairwise comparisons is bigger than 0, it favors the column-defining treatment. Finally, funnel plots and Egger’s test were used to examine publication bias.

Included studies and their characteristics

Figure 1 presents the flow diagram of the study selection process. The authors identified 1471 abstracts in electronic searches and identified an additional seven abstracts through secondary/manual searches (total n = 1478). After excluding duplicates ( n = 765) and studies that did not meet the inclusion criteria based on the study abstract ( n = 550), the authors retrieved studies with potential to meet the inclusion criteria for full review ( n = 163). Of these, 144 studies were excluded due to not meeting inclusion criteria based on full-text articles, leaving 19 remaining studies. Of the 19, two studies did meet this paper’s inclusion criteria but were excluded from this network meta-analysis 33 , 34 because the consistency assumption between direct and indirect estimates was not met at the time of this study's consideration based on previous studies 35 , 36 . Therefore, a total of 17 studies were included in this network meta-analysis, covering a total of 745 participants 36 .

Flow diagram of the study selection process.

Table 1 lists the characteristics of the 17 included studies. CBT ( n = 4), Behavioral Treatment (BT) + Mindfulness ( n = 4), and BT only ( n = 4) were most frequently studied, followed by CBT + Family Intervention ( n = 1), CBT + Mindfulness ( n = 1), virtual reality BT ( n = 1), Mindfulness ( n = 1), and Motivational Interviewing (MI) + BT ( n = 1). Seven studies were conducted in Korea and six were conducted in China, followed by Germany and Austria ( n = 1), Spain ( n = 1), the United States ( n = 1), and the Philippines ( n = 1). Twelve articles were written in English, and five articles were written in a language other than English. Nine studies conducted a follow-up assessment with periods ranging from one to three months, and two studies conducted a follow-up assessment with periods ranging four to six months. In one study 20 , the authors described their 6-month follow-up but did not present their outcome value, and thus only two studies were included in the four- to six-month follow-up analysis. Among the 17 included studies, eight had no treatment control group, five had an active control group (e.g., pseudo training, BT, and CBT), and four had a wait-list control group. Seven of the studies were RCT studies, and 10 were non-RCT studies.

Pairwise meta-analysis

The results of meta-analyses showed a large effect of all psychological treatments when compared to any type of comparison groups ( n = 17, g = 1.47, 95% CI [1.07, 1.86]). The treatment effects were separately provided according to active versus inactive comparison groups in Fig. 2 . The effects of psychological treatments were large when compared to the active control ( n = 5, g = 0.88, 95% CI [0.21, 1.56]) or inactive control ( n = 12, g = 1.70, 95% CI: [1.27, 2.12]). Substantial heterogeneity was evident in studies that were compared to both the active controls (I 2 = 72%, < 0.01) and inactive controls at p -value level of 0.05 (I 2 = 69%, p < 0.001).

Pairwise Meta-analysis. Psychological treatment effects on excessive gaming by comparison group type (active and inactive controls). SMD standardized mean difference, SD standard deviation, CI confidence interval, I 2 = Higgins' I 2 .

Moderator analysis

As shown in Table 2 , the moderator analysis suggested that effect sizes were larger in non-RCT studies ( n = 10, g = 1.60, 95% CI [1.36, 1.84]) than RCT studies ( n = 7, g = 1.26, 95% CI [0.30, 2.23]). However, the results of a Q-test for heterogeneity yielded insignificant results (Q = 0.44, df[Q] = 1, p = 0.51), indicating that no statistically significant difference in treatment efficacy at p level of 0.05 between RCT and non-RCT studies.

The results of Q-test for heterogeneity did not yield any significant results, indicating no significant differences in treatment efficacy between adults and adolescents (Q = 2.39, df[Q] = 1, p = 0.12), Western and Eastern regions (Q = 0.40, df[Q] = 1, p = 0.53), or low and high research qualities among RCT studies (Q = 2.25, df[Q] = 1, p = 0.13) and non-RCT studies (Q = 3.06, df[Q] = 1, p = 0.08).

Subgroup analysis

The results demonstrated that the treatment effect was Hedges’ g = 1.54 (95% CI [0.87, 2.21]) at 1-to-3-month follow-up and Hedges’ g = 1.23 (95% CI [0.77, 1.68]) 4- to-6-month follow-up. The results also showed that the treatment for excessive gaming was also effective on depression and anxiety. Specifically, treatment on depression was Hedges’ g = 0.52 (95% CI: [0.22, 0.81], p < 0.001), and anxiety was Hedges’ g = 0.60 (95% CI [0.11, 1.08], p = 0.02), which are medium and significant effects. However, the effect on impulsivity was insignificant, Hedges’ g = 0.26 (95% CI [− 0.14, 0.67], p = 0.20).

Network meta-analysis

As shown in Fig. 3 , a network plot represents a connected network of eight intervention types (CBT, BT + Mindfulness, BT, Virtual Reality BT, CBT + Mindfulness, CBT + Family, MI + BT, and Mindfulness) and three control group types (wait-list control, no treatment, treatment as usual). The widest width of nodes was observed when comparing BT + Mindfulness and no treatment, indicating that those two modules were most frequently compared. No evidence of global inconsistency based on a random effects design-by-treatment interaction model was found (Q = 8.5, df[Q] = 7, p = 0.29). Further, local tests of loop-specific inconsistency did not demonstrate inconsistency, indicating that the results from the direct and indirect estimates were largely in agreement ( p = 0.12- 0.78).

Network plot for excessive gaming interventions. Width of lines and size of circles are proportional to the number of studies in each comparison. BT behavioral therapy, CBT cognitive behavioral therapy, Family family intervention, MI motivational interviewing, TAU treatment as usual.

As shown in Fig. 4 , according to SUCRA, a combined intervention of CBT and Mindfulness ranked as the most optimal treatment (SUCRA = 97.1%) and demonstrated the largest probability of effectiveness when compared to and averaged over all competing treatments. A combined treatment of CBT and Family intervention ranked second (SUCRA = 90.2%), and Mindfulness intervention ranked third (SUCRA = 82.1%). As shown in Table 3 , according to league table, CBT + Mindfulness intervention showed positive weighted mean difference values in the lower diagonal, indicating greater effectiveness over all other interventions. The CBT + Mindfulness intervention was more effective than CBT + Family or Mindfulness interventions, but their differences were not significant (weighted mean differences = 0.23–1.11, 95% CI [− 1.39 to 2.68]). The top three ranked interventions (e.g., CBT + Mindfulness, CBT + Family intervention, and Mindfulness in a row) were statistically significantly superior to CBT as a standalone treatment as well as the rest of treatments.

Surface under the cumulative ranking curve (SUCRA) rankogram of excessive gaming. BT behavioral therapy, CBT cognitive behavioral therapy, Family family intervention, MI motivational interviewing, TAU treatment as usual.

Risk of bias

Figure 5 displays an overview of the risk of bias across all included studies. Of note was that in the RCT studies, bias due to missing outcome data was least problematic, indicating a low dropout rate (six out of seven studies). In contrast, bias due to deviations from intended interventions was most problematic, indicating that, in some studies, participants and trial personnel were not blinded and/or there was no information provided as to whether treatments adhered to intervention protocols (six out of seven studies). In the non-RCT studies, bias in the selection of participants in the study was least problematic, indicating that researchers did not select participants based on participant characteristics after the start of intervention (10 out of 10 studies). In contrast, bias in the measurement of outcomes was most problematic, indicating that participants and outcome assessors were not blinded and/or studies used self-reported measures without clinical interviews (10 out of 10 studies).

Overview of risk of bias results across all included studies. Cl bias in classification of interventions, Co bias due to confounding, De bias due to deviations from intended interventions, Me bias in measurement of the outcome, Mi bias due to missing outcome data, R bias arising from the randomization process, RoB risk of bias, ROBINS-I risk of bias in non-randomized studies of intervention, Sp bias in selection of participants in the study, Sr bias in selection of the reported result.

Funnel plots and Egger’s test showed no evidence of publication in network meta-analyses. Funnel plots were reasonably symmetric and the result from Egger’s test for sample bias were not significant ( p = 0.22; see Supplementary Material 4 ).

In this pairwise and network meta-analyses, the authors assessed data from 17 trials and analyzed the overall and relative effectiveness of eight types of psychological treatments for reducing excessive gaming. The pairwise meta-analysis results indicated large overall effectiveness of psychological treatments in reducing excessive gaming. Although the effectiveness was smaller when compared to the active controls than when compared to the inactive controls, both effect sizes were still large. However, this result needs to be interpreted with caution because there are only seven existing RCT studies and several existing low-quality studies. Network meta-analysis results indicated that a combined treatment of CBT and Mindfulness was the most effective, followed by a combined therapy of CBT and Family intervention, Mindfulness, and then CBT as a standalone treatment, however, this finding was based on a limited number of studies. Overall, the findings suggest that psychological treatments for excessive gaming is promising, but replications are warranted, with additional attention being placed on addressing methodological concerns.

The large effect of psychological treatments in reducing excessive gaming seems encouraging but the stability and robustness of the results need to be confirmed. These authors’ moderator analysis indicated that the effect size of non-RCT studies was not significantly different from that of RCT studies. The authors conducted a moderator analysis using the research quality score (high vs low) and found that research quality did not moderate the treatment effect. The authors also examined publication bias using both funnel plots and Egger’s test and found no evidence of publication bias in network meta-analysis. Because most of the studies included in the review were from Asian countries, the authors examined the generalizability of the finding by testing moderator analysis by regions and found no significant difference of treatment effect sizes between Eastern and Western countries. Finally, although limited studies exist, treatment benefits did not greatly diminish after 1–6 months of follow-ups, indicating possible lasting effects.

Network meta-analysis findings provide some preliminary support for the notion that a combined treatment of CBT and Mindfulness and a combined treatment of CBT and Family intervention are most effective in addressing individuals’ gaming behaviors. These combined therapies were significantly more effective than the CBT standalone approach. CBT has been studied and found to be highly effective in addiction treatment—particularly in reducing excessive gaming due to its attention to stimulus control and cognitive restructuring 13 . However, adding Mindfulness and family intervention may have been more effective than CBT alone, given that gaming is affected not only by individual characteristics, but also external stress or family factors.

Mindfulness generally focuses on helping individuals to cope with negative affective states through mindful reappraisal and aims to reduce stress through mindful relaxation training. The effectiveness of Mindfulness has been validated in other substance and behavioral addiction studies such as alcohol 37 , gambling 38 , and Internet 39 addiction treatments. Indulging in excessive gaming is often associated with the motivation to escape from a stressful reality 40 , and mindful exercises are likely to help gamers not depend on gaming as a coping strategy.

Because excessive gaming is often entangled with family environments or parenting-related concerns—particularly with adolescents, addressing appropriate parent–adolescent communication and parenting styles within excessive gaming interventions are likely to increase treatment efficacy 41 , 42 , 43 . Based on a qualitative study focused on interviews with excessive gamers 43 , and per reports from interviewed gamers, parental guidance to support regulatory control and encouragement to participate in other activities are important factors to reduce excessive gaming. However, at the same time, if parents excessively restrict their children’s behavior, children will feel increased stress and may further escape into the online world through gaming 44 as a means of coping with their stress. Our study indicates that appropriate communication among parents and adolescents in addition to parenting styles with respect to game control must be discussed in treatment. However, because only two studies examined the top two ranked combined interventions within this paper, such findings warrant replication.

Limitations and future directions

These authors identified methodological limitations and future directions in the reviewed studies, which include the following. The authors included non-RCTs to capture data on emerging treatments, but a lack of RCT studies contributes to this paper’s identified methodological concerns. Of 17 studies included, seven were RCT studies and 10 were non-RCT studies. The lack of RCT studies has been repeatedly mentioned in previous review studies 17 , 18 . In fact, one of the two identified reviews 17 made the criticism that even CBT (the most widely studied treatment for excessive gaming) was mostly conducted in non-RCT studies, which was commensurate with this paper’s data (only one out of four CBT studies included in this review is a RCT). Including non-RCTs may be likely to increase selection bias by employing easily accessible samples and assigning participants with more willingness (which is an indicator of better treatment outcome) to intervention groups. Selection bias may have increased the effect size of treatments than what is represented in reality and may limit the generalizability of this finding. Thus, more rigorous evaluation through RCTs is necessary in future studies.

While there are concerns surrounding assessment tools, given that all included studies used self-report measures without clinical interviews, this may lead to inaccurate results due to perceived stigma. Additionally, 11 self-reported measurement tools were employed in the included studies—and some of those tools may have poor sensitivity or specificity. A previous narrative review 45 and a recent meta-analytic review 46 suggested that the Game Addiction Scale-7, Assessment of Internet and Computer Addiction Scale-Gaming, Lemmens Internet Gaming Disorder Scale-9, Internet Gaming Disorder Scale 9- Short Form, and Internet Gaming Disorder Test-10 have good internal consistency and test–retest reliability. Thus, there is a need for studies to employ clinical interviews and self-report measures with good psychometric features.

Many studies in this included review did not describe whether participants and experimenters were blinded and there was no information about whether treatments adhered to intervention protocols. Although blinding of participants and personnel may be impossible in most psychotherapy studies, it is crucial to evaluate possible performance biases such as social desirability. Also, a fidelity check by content experts is needed to confirm whether treatments adhered to intervention protocols.

Finally, future studies need to examine treatment efficacy in treating both excessive gaming and its comorbid psychiatric symptoms. Internet/gaming addiction has been reported to have a high comorbidity with attention deficit hyperactivity disorder, depression, anxiety, and other substance abuse 47 , 48 . Our results showed that CBT, BT, and BT + Mindfulness may be effective in reducing depression or anxiety symptoms of excessive gamers. However, other psychological and/or pharmacological treatments such as CBT + Bupropion or Bupropion as a standalone treatment have been also reported as potentially effective treatments for excessive gamers with major depressive disorder 49 , 50 . Thus, it would be worthwile to examine efficacy of treatments on excessive gamers with dual diagnoses.

TO the best of the authors’ knowledge, this is the first pairwise meta-analytic and network meta-analytic study that examined the overall effectiveness of psychological treatments and compared the relative effectiveness of diverse treatment options for excessive gaming. Although the authors intentionally used network meta-analysis because of its usefulness in comparing relative effectiveness of currently existing literature, this finding should be interpreted with caution due to the small number of studies. However, as previously indicated, the global prevalence of excessive gaming highlights the need for greater attention to this topic. Studies focused on the effectiveness of diverse gaming interventions help meet the call for further inquiry and study on this topic placed by the DSM-5 7 , and allow greater advances to be made in treating individuals who may have difficulty controlling excessive gaming habits. As such, this study can provide preliminary support for beneficial treatment interventions for excessive gaming as well as recommendations for more rigorous studies to be directed at helping those who have excessive gaming habits.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

•Indicates studies used in the meta-analysis

Griffiths, M. D., Király, O., Pontes, H. M. & Demetrovics, Z. Mental Health in the Digital Age: Grave Dangers, Great Promise (Oxford University Press, 2015).

Google Scholar

Wong, H. Y. et al. Relationships between severity of internet gaming disorder, severity of problematic social media use, sleep quality and psychological distress. Int. J. Environ. Health Res. 17 , 1879 (2020).

Article Google Scholar

Brandtner, A., Wegmann, E. & Brand, M. Desire thinking promotes decisions to game: The mediating role between gaming urges and everyday decision-making in recreational gamers. Addict. Behav. Rep. 12 , 100295 (2020).

PubMed PubMed Central Google Scholar

Ferguson, C. J., Coulson, M. & Barnett, J. A meta-analysis of pathological gaming prevalence and comorbidity with mental health, academic and social problems. J. Psychiatr. Res. 45 , 1573–1578 (2011).

Article PubMed Google Scholar

King, D. L. & Delfabbro, P. H. The concept of “harm” in Internet gaming disorder. J. Behav. Addict. 7 , 562–564 (2018).

Article PubMed PubMed Central Google Scholar

World Health Organization. International Statistical Classification of Diseases and Related Health Problems 11th edn. (World Health Organization, 2019).

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) (American Psychiatric Publishing, 2013).

Book Google Scholar

Stevens, M. W., Dorstyn, D., Delfabbro, P. H. & King, D. L. Global prevalence of gaming disorder: A systematic review and meta-analysis. Aust. N. Z. J. Psychiatry 55 , 553–568 (2020).

Chiang, C. L., Zhang, M. W. & Ho, R. C. Prevalence of internet gaming disorder in medical students: A meta-analysis. Front. Psychiatry 12 , 760911 (2021).

Rumpf, H.-J. et al. Including gaming disorder in the ICD-11: The need to do so from a clinical and public health perspective: Commentary on: A weak scientific basis for gaming disorder: Let us err on the side of caution (van Rooij et al. 2018). J. Behav. Addict. 7 , 556–561 (2018).

Dullur, P. & Hay, P. Problem internet use and internet gaming disorder: A survey of health literacy among psychiatrists from Australia and New Zealand. Australas. Psychiatry. 25 , 140–145 (2017).

Knocks, S., Sager, P. & Perissinotto, C. “Onlinesucht” in der Schweiz [“Online-addiction” in Switzerland] (2018).

Stevens, M. W., King, D. L., Dorstyn, D. & Delfabbro, P. H. Cognitive–behavioral therapy for Internet gaming disorder: A systematic review and meta-analysis. Clin. Psychol. Psychother. 26 , 191–203 (2019).

Mihara, S. & Higuchi, S. Cross-sectional and longitudinal epidemiological studies of I nternet gaming disorder: A systematic review of the literature. Psychiatry. Clin. Neurosci. 71 , 425–444 (2017).

Rehbein, F. & Baier, D. Family-, media-, and school-related risk factors of video game addiction. J. Media Psychol. 15 , 118–128 (2013).

Yu, C., Li, X. & Zhang, W. Predicting adolescent problematic online game use from teacher autonomy support, basic psychological needs satisfaction, and school engagement: A 2-year longitudinal study. Cyberpsychol. Behav. Soc. Netw. 18 , 228–233 (2015).

Zajac, K., Ginley, M. K. & Chang, R. Treatments of internet gaming disorder: A systematic review of the evidence. Expert. Rev. Neurother. 20 , 85–93 (2020).

Article CAS PubMed Google Scholar

King, D. L. et al. Treatment of Internet gaming disorder: An international systematic review and CONSORT evaluation. Clin. Psychol. Rev. 54 , 123–133 (2017).

•He, J., Pan, T., Nie, Y., Zheng, Y. & Chen, S. Behavioral modification decreases approach bias in young adults with internet gaming disorder. Addict. Behav. 113 , 106686 (2021).

•Wölfling, K. et al. Efficacy of short-term treatment of internet and computer game addiction: A randomized clinical trial. JAMA Psychiatry 76 , 1018–1025 (2019).

Mavridis, D., Giannatsi, M., Cipriani, A. & Salanti, G. A primer on network meta-analysis with emphasis on mental health. Evid. Based Ment. Health. 18 , 40–46 (2015).

Benz, F. et al. The efficacy of cognitive and behavior therapies for insomnia on daytime symptoms: A systematic review and network meta-analysis. Clin. Psychol. Rev. 80 , 101873 (2020).

Cuijpers, P. et al. A network meta-analysis of the effects of psychotherapies, pharmacotherapies and their combination in the treatment of adult depression. World Psychiatry 19 , 92–107 (2020).

Ha, A., Kim, S. J., Shim, S. R., Kim, Y. K. & Jung, J. H. Efficacy and safety of 8 atropine concentrations for myopia control in children: A network meta-analysis. Ophthalmology 129 , 322–333 (2021).

Hutton, B. et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: Checklist and explanations. Ann. Intern. Med. 162 , 777–784 (2015).

Team, R. C. R: A Language and Environment for Statistical Computing (2013).

Cheung, M. W. L., Ho, R. C., Lim, Y. & Mak, A. Conducting a meta-analysis: Basics and good practices. Int. J. Rheum. Dis. 15 , 129–135 (2012).

Hedges, L. V. & Olkin, I. Statistical Methods for Meta-analysis (Academic Press, 1985).

MATH Google Scholar

Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum Associates, 1988).

Rosenthal, R. Meta-Analytic Procedures for Social Science Research Vol. 15, 148 (Sage Publications, 1991).

Higgins, J. P. & Thompson, S. G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21 , 1539–1558 (2002).

Salanti, G., Ades, A. & Ioannidis, J. P. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: An overview and tutorial. J. Clin. Epidemiol. 64 , 163–171 (2011).

Nielsen, P. et al. Multidimensional family therapy reduces problematic gaming in adolescents: A randomised controlled trial. J. Behav. Addict. 10 , 234–243 (2021).

Pornnoppadol, C. et al. A comparative study of psychosocial interventions for internet gaming disorder among adolescents aged 13–17 years. Int. J. Ment. Health Addict. 18 , 932–948 (2020).

Shim, S., Yoon, B.-H., Shin, I.-S. & Bae, J.-M. Network meta-analysis: Application and practice using Stata. Epidemiol. Health 39 , e2017047 (2017).

Dias, S. et al. Evidence synthesis for decision making 4: Inconsistency in networks of evidence based on randomized controlled trials. Med. Decis. Mak. 33 , 641–656 (2013).

Cavicchioli, M., Movalli, M. & Maffei, C. The clinical efficacy of mindfulness-based treatments for alcohol and drugs use disorders: A meta-analytic review of randomized and nonrandomized controlled trials. Eur. Addict. Res. 24 , 137–162 (2018).

Maynard, B. R., Wilson, A. N., Labuzienski, E. & Whiting, S. W. Mindfulness-based approaches in the treatment of disordered gambling: A systematic review and meta-analysis. Res. Soc. Work. Pract. 28 , 348–362 (2018).

•Liu, L. et al. Altered intrinsic connectivity distribution in internet gaming disorder and its associations with psychotherapy treatment outcomes. Addict. Biol. 26 , e12917 (2021).

Bowditch, L., Chapman, J. & Naweed, A. Do coping strategies moderate the relationship between escapism and negative gaming outcomes in World of Warcraft (MMORPG) players? Comput. Hum. Behav. 86 , 69–76 (2018).

Bonnaire, C. & Phan, O. Relationships between parental attitudes, family functioning and Internet gaming disorder in adolescents attending school. Psychiatry Res. 255 , 104–110 (2017).

Schneider, L. A., King, D. L. & Delfabbro, P. H. Family factors in adolescent problematic Internet gaming: A systematic review. J. Behav. Addict. 6 , 321–333 (2017).

Shi, J., Renwick, R., Turner, N. E. & Kirsh, B. Understanding the lives of problem gamers: The meaning, purpose, and influences of video gaming. Comput. Hum. Behav. 97 , 291–303 (2019).

Siste, K. et al. Gaming disorder and parenting style: A case series. Addict. Disord. Their. Treat. 19 , 185–190 (2020).

King, D. L., Haagsma, M. C., Delfabbro, P. H., Gradisar, M. & Griffiths, M. D. Toward a consensus definition of pathological video-gaming: A systematic review of psychometric assessment tools. Clin. Psychol. Rev. 33 , 331–342 (2013).

Yoon, S. et al. Reliability, and convergent and discriminant validity of gaming disorder scales: a meta-analysis. Front. Psychol. 12 , 5659 (2021).

Ho, R. C. et al. The association between internet addiction and psychiatric co-morbidity: A meta-analysis. BMC Psychiatry 14 , 1–10 (2014).

González-Bueso, V. et al. Association between internet gaming disorder or pathological video-game use and comorbid psychopathology: A comprehensive review. Int. J. Environ. Health Res. 15 , 668 (2018).

Kim, S. M., Han, D. H., Lee, Y. S. & Renshaw, P. F. Combined cognitive behavioral therapy and bupropion for the treatment of problematic on-line game play in adolescents with major depressive disorder. Comput. Hum. Behav. 28 , 1954–1959 (2012).

Han, D. H. & Renshaw, P. F. Bupropion in the treatment of problematic online game play in patients with major depressive disorder. J. Psychopharmacol. 26 , 689–696 (2012).

•Kuriala, G. K. & Reyes, M. E. S. Efficacy of the acceptance and cognitive restructuring intervention program (ACRIP) on the internet gaming disorder symptoms of selected Asian adolescents. J. Technol. Behav. Sci. 5 , 238–244 (2020).

•Li, W. et al. Mindfulness-oriented recovery enhancement for internet gaming disorder in US adults: A stage I randomized controlled trial. Psychol. Addict. Behav. 31 , 393 (2017).

•Park, S. Y. et al. The effects of a virtual reality treatment program for online gaming addiction. Comput. Methods. Progr. Biomed. 129 , 99–108 (2016).

•Zheng, Y., He, J., Fan, L. & Qiu, Y. Reduction of symptom after a combined behavioral intervention for reward sensitivity and rash impulsiveness in internet gaming disorder: A comparative study. J. Psychiatr. Res. 153 , 159–166 (2022).

•Choi, O. Y. & Son, C. N. Effects of the self-control training program on relief of online game addiction level, aggression, and impulsivity of college students with online game addiction. Korean J. Clin. Psychol. 30 , 723–745 (2011).

•Torres-Rodriguez, A., Griffiths, M. D., Carbonell, X. & Oberst, U. Treatment efficacy of a specialized psychotherapy program for Internet Gaming Disorder. J. Behav. Addict. 7 , 939–952 (2018).

•Kang, H. Y. & Son, C. N. The effects of self-esteem enhancement cognitive behavioral therapy for adolescents’ internet addiction and game addiction. Korean J. Psychol. Health 15 , 143–159 (2010).

•Lee, H. C. & An, C. Y. A study on the development and effectiveness of cognitive-behavioral therapy for internet addiction. Korean J. Psychol. Health. 7 , 463–486 (2002).

•Lee, J. H. & Son, C. N. The effects of the group cognitive behavioral therapy on game addiction level, depression and self-control of the high school students with internet game addiction. Korean Soc. Stress. Med. 16 , 409–417 (2008).

•Deng, L.-Y. et al. Craving behavior intervention in ameliorating college students’ internet game disorder: A longitudinal study. Front. Psychol. 8 , 526 (2017).

•Zhang, J.-T. et al. Altered resting-state neural activity and changes following a craving behavioral intervention for Internet gaming disorder. Sci. Rep. 6 , 1–8 (2016a).

•Zhang, J.-T. et al. Effects of craving behavioral intervention on neural substrates of cue-induced craving in Internet gaming disorder. NeuroImage Clin. 12 , 591–599 (2016b).

•Ju, H. W., Hyun, M. H. & Park, J. S. Effects of the transtheoretical model-based intervention in game-addicted adolescents. Korean J. Youth. Stud. 18 , 227–246 (2011).

•Pyo, M. H. & Lee, Y. M. The effects of game control program on the mitigation of internet game addiction and self-efficacy. Kor. Elem. Cnslr. Edu. Assoc. 105–118 (2004).

Download references

This research was supported by the project investigating scientific evidence for registering gaming disorder on Korean Standard Classification of Disease and Cause of Death funded by the Ministry of Health and Welfare and Korea Creative Content Agency.

Author information

Authors and affiliations.

Department of Psychology, Chungnam National University, W12-1, Daejeon, 34134, South Korea

Jueun Kim, Sunmin Lee & Dojin Lee

Department of Health and Medical Informatics, College of Health Sciences, Kyungnam University, Changwon, South Korea

Sungryul Shim

Department of Counseling Psychology, University of Georgia, Athens, GA, USA

Daniel Balva

School of Psychology, Korea University, Seoul, South Korea

Kee-Hong Choi

Department of Psychology, Seoul National University, Seoul, South Korea

Jeanyung Chey & Woo-Young Ahn

Dr. Shin’s Neuropsychiatric Clinic, Seoul, South Korea

Suk-Ho Shin

You can also search for this author in PubMed Google Scholar

Contributions

J.K., K.-H.C., J.C., S.-H.S., and W.-Y.A. contributed to the conception and design of the study. J.K. wrote the draft of the manuscript and D.B. reviewed and edited the draft. D.L., S.L., and S.S. extracted the data and performed the analyses.

Corresponding author

Correspondence to Jueun Kim .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary information., rights and permissions.

Reprints and permissions

About this article

Cite this article.

Kim, J., Lee, S., Lee, D. et al. Psychological treatments for excessive gaming: a systematic review and meta-analysis. Sci Rep 12 , 20485 (2022). https://doi.org/10.1038/s41598-022-24523-9

Download citation

Received : 06 October 2022

Accepted : 16 November 2022

Published : 28 November 2022

DOI : https://doi.org/10.1038/s41598-022-24523-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Essay on Online Games Addiction

Students are often asked to write an essay on Online Games Addiction in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Online Games Addiction

Understanding online games addiction.

Online games addiction means playing games on the internet too much. This happens when someone spends more time playing games than doing other important things. This can cause problems like poor grades in school, less time with friends and family, and even health issues.

Reasons for Addiction

There are many reasons why people get addicted to online games. Some people play to escape from real-world problems. Others find the games exciting and challenging. Some people even play to feel a sense of achievement.

Effects of Addiction

Playing games too much can cause many problems. It can lead to poor performance in school or at work. It can also cause health problems like eye strain and lack of sleep. It can even hurt relationships with friends and family.

Overcoming Addiction

Overcoming online games addiction can be tough, but it’s possible. It’s important to set limits on how much time you spend playing games. It can also help to find other hobbies or activities to do instead of playing games. It might also be helpful to talk to a counselor or therapist.

Online games can be fun, but it’s important not to let them take over your life. If you think you might be addicted, it’s important to seek help. Remember, there’s a lot more to life than just playing games!

Also check:

Speech on Online Games Addiction

250 Words Essay on Online Games Addiction

What is online games addiction.

Online games addiction is when a person cannot stop playing games on the internet. They spend too much time playing these games and ignore other important things in life. This can harm their studies, health, and relationships.

Why Do People Get Addicted?

People get addicted to online games for many reasons. Some find these games fun and exciting. They enjoy the challenges and rewards that these games offer. Others use these games to escape from stress or problems in real life.

Effects of Online Games Addiction

Online games addiction can have many bad effects. It can cause poor grades in school because students spend too much time playing games instead of studying. It can also lead to health problems like eye strain and lack of sleep. Moreover, it can harm relationships with family and friends because the person is always busy with the games.

How to Overcome Online Games Addiction

Overcoming online games addiction is not easy, but it is possible. One way is to set a limit on how much time you can spend on games each day. Another way is to find other fun activities to do, like playing sports or reading books. It can also help to talk to a trusted adult about the problem.

In conclusion, online games addiction is a serious issue. It can harm a person’s studies, health, and relationships. But with the right help and effort, it can be overcome. It is important to balance online gaming with other activities and responsibilities in life.

500 Words Essay on Online Games Addiction

Online games addiction is when a person spends too much time playing games on the internet and finds it hard to stop. This can lead to problems in other parts of life like school, work, or relationships. It’s a bit like when someone can’t stop eating sweets, even though they know it’s bad for them. They might want to stop, but they find it very hard to do so.

There are many reasons why people get addicted to online games. Some people play games to escape from real-life problems or to feel good about themselves. Games can make people feel like they’re winning or achieving something, which can be very satisfying. Other people might get addicted because the games are so much fun and they lose track of time. Sometimes, people get addicted because they’re trying to be the best at the game and can’t stop until they are.

The Impact of Online Games Addiction

Online games addiction can cause many problems. Firstly, it can lead to poor performance in school or work. This is because people who are addicted to games often spend so much time playing that they don’t have time for anything else. They might also lose sleep because they stay up late to play games.

Secondly, addiction can harm relationships. If a person spends too much time playing games, they might not spend enough time with their friends and family. This can make people feel lonely and isolated.

Lastly, spending too much time playing games can also be bad for health. It can lead to problems like poor posture, eye strain, and lack of physical activity.

How to Prevent and Overcome Online Games Addiction

Preventing online games addiction starts with setting limits. It’s fine to play games, but it’s important to have a balance. This means making time for other activities like studying, playing sports, or spending time with friends and family.

If someone is already addicted to online games, it might be hard for them to stop on their own. In this case, it can be helpful to seek help from a professional, like a counselor or a psychologist. They can provide guidance and support to help the person overcome their addiction.

In conclusion, online games addiction is a serious problem that can affect a person’s school, work, relationships, and health. It’s important to balance time spent on gaming with other activities and seek professional help if needed. Remember, games are meant to be fun, not something that takes over your life.

That’s it! I hope the essay helped you.

If you’re looking for more, here are essays on other interesting topics:

Essay on Online Shopping Boon Or Bane
Essay on Open Campus Lunch
Essay on Operation Geronimo

Apart from these, you can look at all the essays by clicking here .

Happy studying!

Online Gaming Essay | Advantages and Disadvantages of Online Gaming

Online gaming is the most talked about fun topic among the teenagers of the 21st century. At the same time, it is the most talked about serious topic among the parents and teachers. Everyone has their own reasons to discuss online gaming. Our reason today is to help you write an Essay on Online Gaming so that you are exposed to the unseen side of online gaming addiction.

Long Essay on Online Gaming Addiction in 500 words | Argumentative Essay on Online Games Good or Bad

How online gaming started.

The Internet has changed the way we live, we eat, we dress, we work and we play. It has become a preferred and comfortable mode which has made our lives way too easy. Today almost everything is available at the click of a button. You ask for a thing and it reaches your doorstep within days. Amidst these gratifying moments, when we are saved from the daily hustle-bustle, another trend of online gaming has emerged.

Advantages of Online Games

Online gaming is a huge platform today. A platform that has broken all barriers and boundaries amidst countries around the world. In online gaming, you can connect to anyone anywhere in the world and play. Sometimes you don’t even know with whom you are playing and this mystery makes the experience even more thrilling. It also gives the player an opportunity to make new friends from other countries and get a chance to showcase their talent worldwide.

Nowadays, many online gaming championships are organized where gamers get a platform to compete with the best of the best and enhance their skills. It has gained much popularity over the years because one can play an online game on even a basic smartphone. What one requires is a consistent internet connection. Developing, designing and marketing online games has turned into a full-fledged profession and many are earning their bread and butter through it.

Disadvantages of Online Gaming

But then there is always the other side of a coin which is often dark and dingy. The other side of online gaming is not only dark but dreadful too. Many tend to become addicted to online gaming and it takes away all of their productive time. When money gets involved in it through betting, families are ruined. It pulls an individual into isolation as mostly online gamers play alone. Their social interaction becomes nil which leads to depression and loneliness.

Online harassment through many gaming sites is not a new thing. Children can easily be trapped in this way. Long hours spent in front of the computer can harm their posture and eyes too. These games, through their catchy visuals, entice young children and they become addicted to them to such an extent that they forget to eat or sleep and prefer to sit in front of the screen all the time. Such addiction not only harms the individual but the whole family suffers due to it. Besides social effects, there are many psychological symptoms like anxiety, irritability and uncontrollable mood swings which take a toll on the health of an individual due to addiction.

Ways to Control Online Gaming Addiction

Self-control, time management and focus can serve as the three pillars for fighting the addiction to online gaming. The external prohibitions from the government in the form of laws, certain regulations and even a ban on a few of them are not going to solve the problem. Good parenting, positive family time and socializing with friends can prove to be helpful. In some severe cases, guidance from a counsellor could become necessary. Positive reinforcement & support from loved ones is required for an individual to come out of this addiction.

‘Nothing can be more exciting and thrilling than a victory in real life’. So, let’s look forward to a win in real life than online.

Nurture Nature and Save the Future Impact of War on the Modern World Essay Importance of Cleanliness and Swacch Bharat Campaign Changing Role of Women in India My First Online Class Experience Essay How to Write an Essay on Myself with Examples Solar Energy Meaning Advantages Disadvantages Essay Academic Dishonesty Essay | Demerits of Online Exams Essay on Effects of Population on Environment Essay on Why is Education Important

Share With Your Friends

Click to share on WhatsApp (Opens in new window)
Click to share on Telegram (Opens in new window)
Click to share on Facebook (Opens in new window)
Click to share on LinkedIn (Opens in new window)
Click to print (Opens in new window)
Click to share on Pinterest (Opens in new window)
Click to share on Twitter (Opens in new window)

Addiction to Online Gaming: A Review of Literature Essay

The Problem of Interest

The Qualitative Research Method to Be Used

The Review of Literature

Disadvantages

The Evaluation of the Selected Software Analysis Program

Validity Threats in the Selected Qualitative Design

Potential Ethical Issues

Summary of Research

Social Effects of Online Game Addiction in Adolescents: A Systematic Review

Related Papers

RELATED PAPERS

RELATED TOPICS

Expert advice on gaming addiction in young people and children

Gaming addiction and financial concerns

Tips to combat bad gaming habits in children

Effects of gaming addiction on education and personal growth

Social relationships

Gaming addiction effect on mental health

Effects of gaming addiction on physical health

More to Explore

On site links

Related Web Links

Recent posts

Download Workbook

Internet and Gaming Addiction: A Systematic Literature Review of Neuroimaging Studies

1. Introduction

1.1. The Rise of Neuroimaging

1.2. Types of Neuroimaging Used to Study Addictive Brain Activity

3.1. fMRI Studies

3.2. sMRI Studies

3.3. EEG Studies

3.4. SPECT Studies

3.5. PET Studies

4. Discussion

5. Conclusions

Conflict of Interest

Evidence on Problematic Online Gaming and Social Anxiety over the Past Ten Years: a Systematic Literature Review

Cite this article

Purpose of Review

Recent Findings

Similar content being viewed by others

Online Gaming Addiction and Basic Psychological Needs Among Adolescents: The Mediating Roles of Meaning in Life and Responsibility

The positive aspects of attention deficit hyperactivity disorder: a qualitative investigation of successful adults with ADHD

Social Media and Youth Mental Health

Introduction

Materials and Methods

Different Perspectives on Problematic Online Gaming Research: Frameworks and Measures

Measures of Social Phobia and Social Anxiety

Problematic Online Gaming and Social Anxiety

Problematic Online Gaming, Social Anxiety, and the Associated Factors

Problematic Online Gaming and Social Anxiety at Different Ages

Limitations and Conclusions

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

Author information

Corresponding author

Additional information

Rights and permissions

About this article

Share this article

Psychological treatments for excessive gaming: a systematic review and meta-analysis

Similar content being viewed by others

Microdosing with psilocybin mushrooms: a double-blind placebo-controlled study

A systematic review and multivariate meta-analysis of the physical and mental health benefits of touch interventions

Adults who microdose psychedelics report health related motivations and lower levels of anxiety and depression compared to non-microdosers

Identification and selection of studies

Risk of bias and data extraction

Data analysis

Included studies and their characteristics

Pairwise meta-analysis

Moderator analysis

Subgroup analysis

Network meta-analysis

Risk of bias

Limitations and future directions

Data availability

•Indicates studies used in the meta-analysis

Author information

Contributions

Corresponding author