online gaming research paper

Playing games: advancing research on online and mobile gaming consumption

Internet Research

ISSN : 1066-2243

Article publication date: 9 April 2019

Issue publication date: 9 April 2019

Seo, Y. , Dolan, R. and Buchanan-Oliver, M. (2019), "Playing games: advancing research on online and mobile gaming consumption", Internet Research , Vol. 29 No. 2, pp. 289-292. https://doi.org/10.1108/INTR-04-2019-542

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

Introduction

Computer games consistently generate more revenue than the movie and music industries and have become one of the most ubiquitous symbols of popular culture ( Takahashi, 2018 ). Recent technological developments are changing the ways in which consumers are able to engage with computer games as individuals – adult gamers, parents and children ( Christy and Kuncheva, 2018 ) – and as collectives, such as communities, networks and subcultures ( Hamari and Sjöblom, 2017 ; Seo, 2016 ). In particular, with the proliferation of online and mobile technologies, we have witnessed the emergence of newer forms of both computer games themselves (e.g. advertising games (advergames), virtual and augmented reality games and social media games) ( Rauschnabel et al. , 2017 ) and of gaming practices (e.g. serious gaming, hardcore gaming and eSports) ( Seo, 2016 ).

It is, therefore, not surprising that the issues concerning the ways computer games consumption is changing in light of these technological developments have received much attention across diverse disciplines of social sciences, such as marketing (e.g. Seo et al. , 2015 ), information systems (e.g. Liu et al. , 2013 ), media studies (e.g. Giddings, 2016 ) and internet research (e.g. Hamari and Sjöblom, 2017 ). The purpose of this introductory paper to the special issue “Online and mobile gaming” is to chart future research directions that are relevant to a rapidly changing postmodern digital gaming landscape. In this endeavor, this paper first provides an integrative summary of the six articles that comprise this special issue, and then draws the threads together in order to elicit the agenda for future research.

An integrative summary of the special issue

The six articles that were selected for this special issue advance research into online and mobile gaming in several ways. The opening article by Pappas, Mikalef, Giannakos and Kourouthanassis draws attention to the complex ecosystem of mobile applications in which multiple factors influence consumer behavior in mobile games. Pappas and his colleagues shed light on how price value, game content quality, positive and negative emotions, gender, and gameplay time interact with one another to predict the intention to download mobile games. This study offers useful insights by demonstrating how fuzzy set qualitative comparative analysis methodology can be applied to advance research into computer games consumption.

The study by Bae, Kim, Kim and Koo addresses the digital virtual consumption that occurs within computer games. This second paper explores the relationship between in-game items and mood management to determine the affective value of purchasing in-game items. The findings reveal that game users manage their levels of arousal and mood valence through the use of in-game purchases, suggesting that stressed users are more likely to purchase decorative items, whereas bored users tend to purchase functional items. This study offers an informative perspective of how mood management and selective exposure theories can be applied to understand the in-game purchases. Continuing this theme, the third study by Bae, Park and Koo investigates the effect of perceived corporate social responsibility (CSR) initiatives. Park and colleagues extend previous research by identifying important motivational mechanisms, such as self-esteem and compassion, which link CSR initiative perceptions with the intentions to purchase in-game items.

The fourth and fifth studies of this special issue draw our attention to the use of avatars and game characters. Liao, Cheng and Teng use social identity and flow theories to construct a novel model that explains how avatar attractiveness and customization impact loyalty among online game consumers. In the fifth study, Choi explores the importance of game character characteristics being congruent with product types in order to make advergames more persuasive.

The final study by Lee and Ko reviews the predictors of game addiction based on loneliness, motivation and inter-personal competence. The findings of these authors suggest that regulatory focus mediates the effect of loneliness on online game addiction, and that inter-personal competence significantly buffers the indirect effect of loneliness on online game addiction. This study advances our knowledge about online game addiction through an investigation of the important role played by loneliness.

Future directions for research

Taken together, our introductory commentary and the six empirical studies that make up this special issue deepen and broaden the current understanding of how online and mobile technologies augment the consumption of computer games. In this final section of our paper, we outline potential directions for future research.

First, this special issue highlights that computer games consumption is a diverse interdisciplinary phenomenon, where important issues range from establishing the factors that determine the adoption of particular computer games to what consumers do within these games; from whether computer games enhance consumer well-being (e.g. Howes et al. , 2017 ), to whether they engender addiction (e.g. Frölich et al. , 2016 ); and from establishing how computer gaming experiences are influenced by internal psychological mechanisms to querying the effects of broader social aspects of consumer lives on computer games consumption ( Kowert et al. , 2015 ). Informed by these findings, we assert that as computer games consumption becomes more complex and interactive, incorporating more technology brought about by the proliferation of online and mobile gaming, it is important that our theorizing follows by tracking the mutual imbrication of consumers, play, technology, culture, well-being and other salient issues.

Computer games consumption is a phenomenon of global significance, which is reflected by the international interest that we have received for this special issue. This prompts us to consider similarities and differences in the ways that computer games are consumed across cultures ( Elmezeny and Wimmer, 2018 ). Many computer games themselves now foster intercultural, multicultural and transcultural experiences ( Cruz et al. , 2018 ) by enabling consumers from different countries and regions to connect and build relationships within the shared virtual space. How do such experiences shape the consumption of computer games? This gap in the literature has been previously noted ( Seo et al. , 2015 ), but it has not been either sufficiently detailed or theorised. Future studies should explore the role of various transcultural experiences and practices within online and mobile games consumption.

Finally, one increasingly promising area for future research is the rise of virtual reality (VR) applications. Although the earliest references to VR date back to the 1990s (e.g. Gigante, 1993 ), it has been only recently that technological developments have allowed VR to evolve from a niche technology into an everyday phenomenon that is readily available to consumers ( Lamkin, 2017 ; Oleksy and Wnuk, 2017 ). Given that VR is an experientially distinct medium, how will it augment computer games consumption experiences and practices? Will it foster more diverse applications of computer games across various aspects of consumer lives (e.g. Tussyadiah et al. , 2018 ), or will it increase computer games addiction (e.g. Chou and Ting, 2003 )? What are the current and future intersections between VR technology, online and mobile games, and how are they likely to develop and affect consumers? We envision that these and many other questions related to the application and proliferation of VR technology in computer games consumption will be an exceptionally fruitful area for future research.

In summary, we hope that this paper and the special issue, with its emphasis on online and mobile gaming, will offer new insights for researchers and practitioners who are interested in the advancement of research on computer games consumption.

Chou , T.J. and Ting , C.C. ( 2003 ), “ The role of flow experience in cyber-game addiction ”, CyberPsychology and Behavior , Vol. 6 No. 6 , pp. 663 - 675 .

Christy , T. and Kuncheva , L.I. ( 2018 ), “ Technological advancements in affective gaming: a historical survey ”, GSTF Journal on Computing , Vol. 3 No. 4 , pp. 32 - 41 .

Cruz , A.G.B. , Seo , Y. and Buchanan-Oliver , M. ( 2018 ), “ Religion as a field of transcultural practices in multicultural marketplaces ”, Journal of Business Research , Vol. 91 , pp. 317 - 325 .

Elmezeny , A. and Wimmer , J. ( 2018 ), “ Games without frontiers: a framework for analyzing digital game cultures comparatively ”, Media and Communication , Vol. 6 No. 2 , pp. 80 - 89 .

Frölich , J. , Lehmkuhl , G. , Orawa , H. , Bromba , M. , Wolf , K. and Görtz-Dorten , A. ( 2016 ), “ Computer game misuse and addiction of adolescents in a clinically referred study sample ”, Computers in Human Behavior , Vol. 55 , pp. 9 - 15 .

Giddings , S. ( 2016 ), “ Pokémon Go as distributed imagination ”, Mobile Media and Communication , Vol. 5 No. 1 , pp. 59 - 62 .

Gigante , M.A. ( 1993 ), “ Virtual reality: definitions, history and applications ”, in Earnshaw , R.A. (Ed.), Virtual Reality Systems , Academic Press , New York, NY , pp. 3 - 14 .

Hamari , J. and Sjöblom , M. ( 2017 ), “ What is eSports and why do people watch it ”, Internet Research , Vol. 27 No. 2 , pp. 211 - 232 .

Howes , S.C. , Charles , D.K. , Marley , J. , Pedlow , K. and McDonough , S.M. ( 2017 ), “ Gaming for health: systematic review and meta-analysis of the physical and cognitive effects of active computer gaming in older adults ”, Physical Therapy , Vol. 97 No. 12 , pp. 1122 - 1137 .

Kowert , R. , Vogelgesang , J. , Festl , R. and Quandt , T. ( 2015 ), “ Psychosocial causes and consequences of online video game play ”, Computers in Human Behavior , Vol. 45 , pp. 51 - 58 .

Lamkin , P. ( 2017 ), “ Virtual reality headset sales hit 1 million ”, available at: www.forbes.com/sites/paullamkin/2017/11/30/virtual-reality-headset-sales-hit-1-million/#241697c42b61/ (accessed October 4, 2018 ).

Liu , D. , Li , X. and Santhanam , R. ( 2013 ), “ Digital games and beyond: what happens when players compete ”, MIS Quarterly , Vol. 37 No. 1 , pp. 111 - 124 .

Oleksy , T. and Wnuk , A. ( 2017 ), “ Catch them all and increase your place attachment! The role of location-based augmented reality games in changing people–place relations ”, Computers in Human Behavior , Vol. 76 , pp. 3 - 8 .

Rauschnabel , P.A. , Rossmann , A. and tom Dieck , M.C. ( 2017 ), “ An adoption framework for mobile augmented reality games: the case of Pokémon Go ”, Computers in Human Behavior , Vol. 76 , pp. 276 - 286 .

Seo , Y. ( 2016 ), “ Professionalized consumption and identity transformations in the field of eSports ”, Journal of Business Research , Vol. 69 No. 1 , pp. 264 - 272 .

Seo , Y. , Buchanan‐Oliver , M. and Fam , K.S. ( 2015 ), “ Advancing research on computer game consumption: a future research agenda ”, Journal of Consumer Behaviour , Vol. 14 No. 6 , pp. 353 - 356 .

Takahashi , D. ( 2018 ), “ Newzoo: games market expected to hit $180.1 billion in revenues in 2021 ”, available at: https://venturebeat.com/2018/04/30/newzoo-global-games-expected-to-hit-180-1-billion-in-revenues-2021/ (accessed October 4, 2018 ).

Tussyadiah , I.P. , Wang , D. , Jung , T.H. and tom Dieck , M.C. ( 2018 ), “ Virtual reality, presence and attitude change: empirical evidence from tourism ”, Tourism Management , Vol. 66 , pp. 140 - 154 .

Acknowledgements

The guest editors would like to offer special thanks to the Editor of Internet Research , Christy Cheung, for supporting the publication of this special issue. The guest editors would also like to thank all of the authors who contributed to this research for the “Online and mobile gaming” special issue. Finally, the guest editors gratefully acknowledge the contribution of reviewers, who generously spent their time in helping to review submissions: Luke Butcher, Curtin University, Australia; Hsiu-Hua Chang, Feng Chia University, Taiwan; I-Cheng Chang, National Dong Hwa University, Taiwan; Chi-Wen Chen, California State University, USA; Zifei Fay Chen, University of San Francisco, USA; Sujeong Choi, Chonnam National University, Korea; Diego Costa Pinto, New University of Lisbon, Portugal; Angela Cruz, Monash University, Australia; Robert Davis, Massey University, New Zealand; Julia Fehrer, University of Auckland, New Zealand; Tony Garry, University of Otago, New Zealand; Tracy Harwood, De Montfort University, UK; Mu Hu, Beihang University, China; Tseng-Lung Huang, Yuan Ze University, Taiwan; Kun-Huang Huang, Feng Chia University, Taiwan; Chelsea Hughes, Virginia Commonwealth University, USA; Euejung Hwang, Otago University, New Zealand; Sang-Uk Jung, Hankuk University of Foreign Studies, Korea; Kacy Kim, Bryant University, USA; Dong-Mo Koo, Kyungpook National University, Korea; Jun Bum Kwon, University of New South Wales, Australia; Chun-Chia Lee, National Chiao Tung University, Taiwan; Jacob Chaeho Lee, Ulsan National Institute of Science and Technology, Korea; Loic Li, University of Auckland, New Zealand; Marcel Martončik, University of Presov, Slovakia; Mike Molesworth, University of Reading, UK; Gavin Northey, University of Auckland, New Zealand; James Richard, Victoria University of Wellington, New Zealand; Ryan Rogers, University of Pennsylvania, USA; Felix Septianto, University of Auckland, New Zealand; Zhen Shao, Harbin Institute of Technology, China; Kai-Shuan Shen, Fo Guang University, Taiwan; Jungmin Son, Chungnam National University; Korea; Yang Sun, Zhejiang Sci-Tech University, China; Eva van Reijmersdal, University of Amsterdam, Netherlands; Ekant Veer, University of Canterbury, New Zealand; John Velez, Indiana University, USA; Wei-Tsong Wang, National Cheng Kung University, Taiwan; Ya-Ling Wu, Tamkang University, Taiwan; Sheau-Fen Yap, Auckland University of Technology, New Zealand; and Sukki Yoon, Bryant University, USA.

Corresponding author

About the authors.

Yuri Seo is Senior Lecturer at the University of Auckland of Business School, New Zealand. His research interests include digital technology and consumption, cultural branding and multicultural marketplaces.

Rebecca Dolan is Lecturer at the University of Adelaide School of Business, Australia. Her research focuses on understanding, facilitating and optimizing customer relationships, engagement, and online communication strategies. She has a specific interest in the role that digital and social media play in the modern marketing communications environment.

Margo Buchanan-Oliver is Professor in the Department of Marketing and the Co-Director of the Centre of Digital Enterprise (CODE) at the University of Auckland Business School. Her research concerns interdisciplinary consumption discourse and practice, particularly that occurring at the intersection of the digital and physical worlds.

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• Published: 10 December 2020

Effect of internet use and electronic game-play on academic performance of Australian children

• Md Irteja Islam 1 , 2 ,
• Raaj Kishore Biswas 3 &
• Rasheda Khanam 1  

Scientific Reports volume  10 , Article number:  21727 ( 2020 ) Cite this article

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This study examined the association of internet use, and electronic game-play with academic performance respectively on weekdays and weekends in Australian children. It also assessed whether addiction tendency to internet and game-play is associated with academic performance. Overall, 1704 children of 11–17-year-olds from young minds matter (YMM), a cross-sectional nationwide survey, were analysed. The generalized linear regression models adjusted for survey weights were applied to investigate the association between internet use, and electronic-gaming with academic performance (measured by NAPLAN–National standard score). About 70% of the sample spent > 2 h/day using the internet and nearly 30% played electronic-games for > 2 h/day. Internet users during weekdays (> 4 h/day) were less likely to get higher scores in reading and numeracy, and internet use on weekends (> 2–4 h/day) was positively associated with academic performance. In contrast, 16% of electronic gamers were more likely to get better reading scores on weekdays compared to those who did not. Addiction tendency to internet and electronic-gaming is found to be adversely associated with academic achievement. Further, results indicated the need for parental monitoring and/or self-regulation to limit the timing and duration of internet use/electronic-gaming to overcome the detrimental effects of internet use and electronic game-play on academic achievement.

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Introduction

Over the past two decades, with the proliferation of high-tech devices (e.g. Smartphone, tablets and computers), both the internet and electronic games have become increasingly popular with people of all ages, but particularly with children and adolescents 1 , 2 , 3 . Recent estimates have shown that one in three under-18-year-olds across the world uses the Internet, and 75% of adolescents play electronic games daily in developed countries 4 , 5 , 6 . Studies in the United States reported that adolescents are occupied with over 11 h a day with modern electronic media such as computer/Internet and electronic games, which is more than they spend in school or with friends 7 , 8 . In Australia, it is reported that about 98% of children aged 15–17 years are among Internet users and 98% of adolescents play electronic games, which is significantly higher than the USA and Europe 9 , 10 , 11 , 12 .

In recent times, the Internet and electronic games have been regarded as important, not just for better results at school, but also for self-expression, sociability, creativity and entertainment for children and adolescents 13 , 14 . For instance, 88% of 12–17 year-olds in the USA considered the Internet as a useful mechanism for making progress in school 15 , and similarly, electronic gaming in children and adolescents may assist in developing skills such as decision-making, smart-thinking and coordination 3 , 15 .

On the other hand, evidence points to the fact that the use of the Internet and electronic games is found to have detrimental effects such as reduced sleeping time, behavioural problems (e.g. low self-esteem, anxiety, depression), attention problems and poor academic performance in adolescents 1 , 5 , 12 , 16 . In addition, excessive Internet usage and increased electronic gaming are found to be addictive and may cause serious functional impairment in the daily life of children and adolescents 1 , 12 , 13 , 16 . For example, the AU Kids Online survey 17 reported that 50% of Australian children were more likely to experience behavioural problems associated with Internet use compared to children from 25 European countries (29%) surveyed in the EU Kids Online study 18 , which is alarming 12 . These mixed results require an urgent need of understanding the effect of the Internet use and electronic gaming on the development of children and adolescents, particularly on their academic performance.

Despite many international studies and a smaller number in Australia 12 , several systematic limitations remain in the existing literature, particularly regarding the association of academic performance with the use of Internet and electronic games in children and adolescents 13 , 16 , 19 . First, the majority of the earlier studies have either relied on school grades or children’s self assessments—which contain an innate subjectivity by the assessor; and have not considered the standardized tests of academic performance 16 , 20 , 21 , 22 . Second, most previous studies have tested the hypothesis in the school-based settings instead of canvassing the whole community, and cannot therefore adjust for sociodemographic confounders 9 , 16 . Third, most studies have been typically limited to smaller sample sizes, which might have reduced the reliability of the results 9 , 16 , 23 .

By considering these issues, this study aimed to investigate the association of internet usage and electronic gaming on a standardized test of academic performance—NAPLAN (The National Assessment Program—Literacy and Numeracy) among Australian adolescents aged 11–17 years using nationally representative data from the Second Australian Child and Adolescent Survey of Mental Health and Wellbeing—Young Minds Matter (YMM). It is hypothesized that the findings of this study will provide a population-wide, contextual view of excessive Internet use and electronic games played separately on weekdays and weekends by Australian adolescents, which may be beneficial for evidence-based policies.

Subject demographics

Respondents who attended gave NAPLAN in 2008 (N = 4) and 2009 (N = 29) were removed from the sample due to smaller sample size, as later years (2010–2015) had over 100 samples yearly. The NAPLAN scores from 2008 might not align with a survey conducted in 2013. Further missing cases were deleted with the assumption that data were missing at random for unbiased estimates, which is common for large-scale surveys 24 . From the initial survey of 2967 samples, 1704 adolescents were sampled for this study.

The sample characteristics were displayed in Table 1 . For example, distribution of daily average internet use was checked, showing that over 50% of the sampled adolescents spent 2–4 h on internet (Table 1 ). Although all respondents in the survey used internet, nearly 21% of them did not play any electronic games in a day and almost one in every three (33%) adolescents played electronic games beyond the recommended time of 2 h per day. Girls had more addictive tendency to internet/game-play in compare to boys.

The mean scores for the three NAPLAN tests scores (reading, writing and numeracy) ranged from 520 to 600. A gradual decline in average NAPLAN tests scores (reading, writing and numeracy) scores were observed for internet use over 4 h during weekdays, and over 3 h during weekends (Table 2 ). Table 2 also shows that adolescents who played no electronic games at all have better scores in writing compared to those who play electronic games. Moreover, Table 2 shows no particular pattern between time spent on gaming and NAPLAN reading and numeracy scores. Among the survey samples, 308 adolescents were below the national standard average.

Internet use and academic performance

Our results show that internet (non-academic use) use during weekdays, especially more than 4 h, is negatively associated with academic performance (Table 3 ). For internet use during weekdays, all three models showed a significant negative association between time spent on internet and NAPLAN reading and numeracy scores. For example, in Model 1, adolescents who spent over 4 h on internet during weekdays are 15% and 17% less likely to get higher reading and numeracy scores respectively compared to those who spend less than 2 h. Similar results were found in Model 2 and 3 (Table 3 ), when we adjusted other confounders. The variable addiction tendency to internet was found to be negatively associated with NAPLAN results. The adolescents who had internet addiction were 17% less and 14% less likely to score higher in reading and numeracy respectively than those without such problematic behaviour.

Internet use during weekends showed a positive association with academic performance (Table 4 ). For example, Model 1 in Table 4 shows that internet use during weekends was significant for reading, writing and national standard scores. Youths who spend around 2–4 h and over 4 h on the internet during weekends were 21% and 15% more likely to get a higher reading scores respectively compared to those who spend less than 2 h (Model 1, Table 4 ). Similarly, in model 3, where the internet addiction of adolescents was adjusted, adolescents who spent 2–4 h on internet were 1.59 times more likely to score above the national standard. All three models of Table 4 confirmed that adolescents who spent 2–4 h on the internet during weekends are more likely to achieve better reading and writing scores and be at or above national standard compared to those who used the internet for less than 2 h. Numeracy scores were unlikely to be affected by internet use. The results obtained from Model 3 should be treated as robust, as this is the most comprehensive model that accounts for unobserved characteristics. The addiction tendency to internet/game-play variable showed a negative association with academic performance, but this is only significant for numeracy scores.

Electronic gaming and academic performance

Time spent on electronic gaming during weekdays had no effect on the academic performance of writing and language but had significant association with reading scores (Model 2, Table 5 ). Model 2 of Table 5 shows that adolescents who spent 1–2 h on gaming during weekdays were 13% more likely to get higher reading scores compared to those who did not play at all. It was an interesting result that while electronic gaming during weekdays tended to show a positive effect on reading scores, internet use during weekdays showed a negative effect. Addiction tendency to internet/game-play had a negative effect; the adolescents who were addicted to the internet were 14% less likely to score more highly in reading than those without any such behaviour.

All three models from Table 6 confirm that time spent on electronic gaming over 2 h during weekends had a positive effect on readings scores. For example, the results of Model 3 (Table 6 ) showed that adolescents who spent more than 2 h on electronic gaming during weekdays were 16% more likely to have better reading scores compared to adolescents who did not play games at all. Playing electronic games during weekends was not found to be statistically significant for writing and numeracy scores and national standard scores, although the odds ratios were positive. The results from all tables confirm that addiction tendency to internet/gaming is negatively associated with academic performance, although the variable is not always statistically significant.

Building on past research on the effect of the internet use and electronic gaming in adolescents, this study examined whether Internet use and playing electronic games were associated with academic performance (i.e. reading, writing and numeracy) using a standardized test of academic performance (i.e. NAPLAN) in a nationally representative dataset in Australia. The findings of this study question the conventional belief 9 , 25 that academic performance is negatively associated with internet use and electronic games, particularly when the internet is used for non-academic purpose.

In the current hi-tech world, many developed countries (e.g. the USA, Canada and Australia) have recommended that 5–17 year-olds limit electronic media (e.g. internet, electronic games) to 2 h per day for entertainment purposes, with concerns about the possible negative consequences of excessive use of electronic media 14 , 26 . However, previous research has often reported that children and adolescents spent more than the recommended time 26 . The present study also found similar results, that is, that about 70% of the sampled adolescents aged 11–17 spent more than 2 h per day on the Internet and nearly 30% spent more than 2-h on electronic gaming in a day. This could be attributed to the increased availability of computers/smart-phones and the internet among under-18s 12 . For instance, 97% of Australian households with children aged less than 15 years accessed internet at home in 2016–2017 10 ; as a result, policymakers recommended that parents restrict access to screens (e.g. Internet and electronic games) in children’s bedrooms, monitor children using screens, share screen hours with their children, and to act as role models by reducing their own screen time 14 .

This research has drawn attention to the fact that the average time spent using the internet, which is often more than 4 h during weekdays tends to be negatively associated with academic performance, especially a lower reading and numeracy score, while internet use of more than 2 h during weekends is positively associated with academic performance, particularly having a better reading and writing score and above national standard score. By dividing internet use and gaming by weekdays and weekends, this study find an answer to the mixed evidence found in previous literature 9 . The results of this study clearly show that the non-academic use of internet during weekdays, particularly, spending more than 4 h on internet is harmful for academic performance, whereas, internet use on the weekends is likely to incur a positive effect on academic performance. This result is consistent with a USA study that reported that internet use is positively associated with improved reading skills and higher scores on standardized tests 13 , 27 . It is also reported in the literature that academic performance is better among moderate users of the internet compared to non-users or high level users 13 , 27 , which was in line with the findings of this study. This may be due to the fact that the internet is predominantly a text-based format in which the internet users need to type and read to access most websites effectively 13 . The results of this study indicated that internet use is not harmful to academic performance if it is used moderately, especially, if ensuring very limited use on weekdays. The results of this study further confirmed that timing (weekdays or weekends) of internet use is a factor that needs to be considered.

Regarding electronic gaming, interestingly, the study found that the average time of gaming either in weekdays or weekends is positively associated with academic performance especially for reading scores. These results contradicted previous literatures 1 , 13 , 19 , 27 that have reported negative correlation between electronic games and educational performance in high-school children. The results of this study were consistent with studies conducted in the USA, Europe and other countries that claimed a positive correlation between gaming and academic performance, especially in numeracy and reading skills 28 , 29 . This is may be due to the fact that the instructions for playing most of the electronic games are text-heavy and many electronic games require gamers to solve puzzles 9 , 30 . The literature also found that playing electronic games develops cognitive skills (e.g. mental rotation abilities, dexterity), which can be attributable to better academic achievement 31 , 32 .

Consistent with previous research findings 33 , 34 , 35 , 36 , the study also found that adolescents who had addiction tendency to internet usage and/or electronic gaming were less likely to achieve higher scores in reading and numeracy compared to those who had not problematic behaviour. Addiction tendency to Internet/gaming among adolescents was found to be negatively associated with overall academic performance compared to those who were not having addiction tendency, although the variables were not always statistically significant. This is mainly because adolescents’ skipped school and missed classes and tuitions, and provide less effort to do homework due to addictive internet usage and electronic gaming 19 , 35 . The results of this study indicated that parental monitoring and/ or self-regulation (by the users) regarding the timing and intensity of internet use/gaming are essential to outweigh any negative effect of internet use and gaming on academic performance.

Although the present study uses a large nationally representative sample and advances prior research on the academic performance among adolescents who reported using the internet and playing electronic games, the findings of this study also have some limitations that need to be addressed. Firstly, adolescents who reported on the internet use and electronic games relied on self-reported child data without any screening tests or any external validation and thus, results may be overestimated or underestimated. Second, the study primarily addresses the internet use and electronic games as distinct behaviours, as the YMM survey gathered information only on the amount of time spent on internet use and electronic gaming, and included only a few questions related to addiction due to resources and time constraints and did not provide enough information to medically diagnose internet/gaming addiction. Finally, the cross-sectional research design of the data outlawed evaluation of causality and temporality of the observed association of internet use and electronic gaming with the academic performance in adolescents.

This study found that the average time spent on the internet on weekends and electronic gaming (both in weekdays and weekends) is positively associated with academic performance (measured by NAPLAN) of Australian adolescents. However, it confirmed a negative association between addiction tendency (internet use or electronic gaming) and academic performance; nonetheless, most of the adolescents used the internet and played electronic games more than the recommended 2-h limit per day. The study also revealed that further research is required on the development and implementation of interventions aimed at improving parental monitoring and fostering users’ self-regulation to restrict the daily usage of the internet and/or electronic games.

Data description

Young minds matter (YMM) was an Australian nationwide cross-sectional survey, on children aged 4–17 years conducted in 2013–2014 37 . Out of the initial 76,606 households approached, a total of 6,310 parents/caregivers (eligible household response rate 55%) of 4–17 year-old children completed a structured questionnaire via face to face interview and 2967 children aged 11–17 years (eligible children response rate 89%) completed a computer-based self-reported questionnaire privately at home 37 .

Area based sampling was used for the survey. A total of 225 Statistical Area 1 (defined by Australian Bureau of Statistics) areas were selected based on the 2011 Census of Population and Housing. They were stratified by state/territory and by metropolitan versus non-metropolitan (rural/regional) to ensure proportional representation of geographic areas across Australia 38 . However, a small number of samples were excluded, based on most remote areas, homeless children, institutional care and children living in households where interviews could not be conducted in English. The details of the survey and methodology used in the survey can be found in Lawrence et al. 37 .

Following informed consent (both written and verbal) from the primary carers (parents/caregivers), information on the National Assessment Program—Literacy and Numeracy (NAPLAN) of the children and adolescents were also added to the YMM dataset. The YMM survey is ethically approved by the Human Research Ethics Committee of the University of Western Australia and by the Australian Government Department of Health. In addition, the authors of this study obtained a written approval from Australian Data Archive (ADA) Dataverse to access the YMM dataset. All the researches were done in accordance with relevant ADA Dataverse guidelines and policy/regulations in using YMM datasets.

Outcome variables

The NAPLAN, conducted annually since 2008, is a nationwide standardized test of academic performance for all Australian students in Years 3, 5, 7 and 9 to assess their skills in reading, writing numeracy, grammar and spelling 39 , 40 . NAPLAN scores from 2010 to 2015, reported by YMM, were used as outcome variables in the models; while NAPLAN data of 2008 (N = 4) and 2009 (N = 29) were excluded for this study in order to reduce the time lag between YMM survey and the NAPLAN test. The NAPLAN gives point-in-time standardized scores, which provide the scope to compare children’s academic performance over time 40 , 41 . The NAPLAN tests are one component of the evaluation and grading phase of each school, and do not substitute for the comprehensive, consistent evaluations provided by teachers on the performance of each student 39 , 41 . All four domains—reading, writing, numeracy and language conventions (grammar and spelling) are in continuous scales in the dataset. The scores are given based on a series of tests; details can be found in 42 . The current study uses only reading, writing and numeracy scores to measure academic performance.

In this study, the National standard score is a combination of three variables: whether the student meets the national standard in reading, writing and numeracy. Based on national average score, a binary outcome variable is also generated. One category is ‘below standard’ if a child scores at least one standard deviation (one below scores) from the national standard in reading, writing and numeracy, and the rest is ‘at/above standard’.

Independent variables

Internet use and electronic gaming.

In the YMM survey, owing to the scope of the survey itself, an extensive set of questions about internet usage and electronic gaming could not be included. Internet usage omitted the time spent in academic purposes and/or related activities. Playing electronic games included playing games on a gaming console (e.g. PlayStation, Xbox, or similar console ) online or using a computer, or mobile phone, or a handled device 12 . The primary independent covariates were average internet use per day and average electronic game-play in hours per day. A combination of hours on weekdays and weekends was separately used in the models. These variables were based on a self-assessed questionnaire where the youths were asked questions regarding daily time spent on the Internet and electronic game-play, specifically on either weekends or weekdays. Since, internet use/game-play for a maximum of 2 h/day is recommended for children and adolescents aged between 5 and 17 years in many developed countries including Australia 14 , 26 ; therefore, to be consistent with the recommended time we preferred to categorize both the time variables of internet use and gaming into three groups with an interval of 2 h each. Internet use was categorized into three groups: (a) ≤ 2 h), (b) 2–4 h, and (c) > 4 h. Similar questions were asked for game-play h. The sample distribution for electronic game-play was skewed; therefore, this variable was categorized into three groups: (a) no game-play (0 h), (b) 1–2 h, and (c) > 2 h.

Other covariates

Family structure and several sociodemographic variables were used in the models to adjust for the differences in individual characteristics, parental inputs and tastes, household characteristics and place of residence. Individual characteristics included age (continuous) and sex of the child (boys, girls) and addiction tendency to internet use and/or game-play of the adolescent. Addiction tendency to internet/game-play was a binary independent variable. It was a combination of five behavioural questions relating to: whether the respondent avoided eating/sleeping due to internet use or game-play; feels bothered when s/he cannot access internet or play electronic games; keeps using internet or playing electronic games even when s/he is not really interested; spends less time with family/friends or on school works due to internet use or game-play; and unsuccessfully tries to spend less time on the internet or playing electronic games. There were four options for each question: never/almost never; not very often; fairly often; and very often. A binary covariate was simulated, where if any four out of five behaviours were reported as for example, fairly often or very often, then it was considered that the respondent had addictive tendency.

Household characteristics included household income (low, medium, high), family type (original, step, blended, sole parent/primary carer, other) 43 and remoteness (major cities, inner regional, outer regional, remote/very remote). Parental inputs and taste included education of primary carer (bachelor, diploma, year 10/11), primary carer’s likelihood of serious mental illness (K6 score -likely; not likely); primary carer’s smoking status (no, yes); and risk of alcoholic related harm by the primary carer (risky, none).

Statistical analysis

Descriptive statistics of the sample and distributions of the outcome variables were initially assessed. Based on these distributions, the categorization of outcome variables was conducted, as mentioned above. For formal analysis, generalized linear regression models (GLMs) 44 were used, adjusting for the survey weights, which allowed for generalization of the findings. As NAPLAN scores of three areas—reading, writing and numeracy—were continuous variables, linear models were fitted to daily average internet time and electronic game play time. The scores were standardized (mean = 0, SD = 1) for model fitness. The binary logistic model was fitted for the dichotomized national standard outcome variable. Separate models were estimated for internet and electronic gaming on weekends and weekdays.

We estimated three different models, where models varied based on covariates used to adjust the GLMs. Model 1 was adjusted for common sociodemographic factors including age and sex of the child, household income, education of primary carer’s and family type 43 . However, the results of this model did not account for some unobserved household characteristics (e.g. taste, preferences) that are unobserved to the researcher and are arguably correlated with potential outcomes. The effects of unobserved characteristics were reduced by using a comprehensive set of observable characteristics 45 , 46 that were available in YMM data. The issue of unobserved characteristics was addressed by estimating two additional models that include variables by including household characteristics such as parental taste, preference and inputs, and child characteristics in the model. In addition to the variables in Model 1, Model 2 included remoteness, primary carer’s mental health status, smoking status and risk of alcoholic related harm by the primary carer. Model 3 further included internet/game addiction of the adolescent in addition to all the covariates in Model 2. Model 3 was expected to account for a child’s level of unobserved characteristics as the children who were addicted to internet/games were different from others. The model will further show how academic performance is affected by internet/game addiction. The correlation among the variables ‘internet/game addiction’ and ‘internet use’ and ‘gaming’ (during weekdays and weekends) were also assessed, and they were less than 0.5. Multicollinearity was assessed using the variance inflation factor (VIF), which was under 5 for all models, suggesting no multicollinearity 47 .

p value below the threshold of 0.05 was considered the threshold of significance. All analysis was conducted in R (version 3.6.1). R-package survey (version 3.37) was used for modelling which is suited for complex survey samples 48 .

Data availability

The authors declare that they do not have permission to share dataset. However, the datasets of Young Minds Matter (YMM) survey data is available at the Australian Data Archive (ADA) Dataverse on request ( https://doi.org/10.4225/87/LCVEU3 ).

Wang, C. -W., Chan, C. L., Mak, K. -K., Ho, S. -Y., Wong, P. W. & Ho, R. T. Prevalence and correlates of video and Internet gaming addiction among Hong Kong adolescents: a pilot study. Sci. World J . 2014 (2014).

Anderson, E. L., Steen, E. & Stavropoulos, V. Internet use and problematic internet use: a systematic review of longitudinal research trends in adolescence and emergent adulthood. Int. J. Adolesc. Youth 22 , 430–454 (2017).

Article   Google Scholar  

Oliveira, M. P. MTd. et al. Use of internet and electronic games by adolescents at high social risk. Trends Psychol. 25 , 1167–1183 (2017).

Google Scholar  

UNICEF. Children in a digital world. United Nations Children's Fund (UNICEF) (2017)

King, D. L. et al. The impact of prolonged violent video-gaming on adolescent sleep: an experimental study. J. Sleep Res. 22 , 137–143 (2013).

Byrne, J. & Burton, P. Children as Internet users: how can evidence better inform policy debate?. J. Cyber Policy. 2 , 39–52 (2017).

Council, O. Children, adolescents, and the media. Pediatrics 132 , 958 (2013).

Paulus, F. W., Ohmann, S., Von Gontard, A. & Popow, C. Internet gaming disorder in children and adolescents: a systematic review. Dev. Med. Child Neurol. 60 , 645–659 (2018).

Posso, A. Internet usage and educational outcomes among 15-year old Australian students. Int J Commun 10 , 26 (2016).

ABS. 8146.0—Household Use of Information Technology, Australia, 2016–2017 (2018).

Brand, J. E. Digital Australia 2018 (Interactive Games & Entertainment Association (IGEA), Eveleigh, 2017).

Rikkers, W., Lawrence, D., Hafekost, J. & Zubrick, S. R. Internet use and electronic gaming by children and adolescents with emotional and behavioural problems in Australia–results from the second Child and Adolescent Survey of Mental Health and Wellbeing. BMC Public Health 16 , 399 (2016).

Jackson, L. A., Von Eye, A., Witt, E. A., Zhao, Y. & Fitzgerald, H. E. A longitudinal study of the effects of Internet use and videogame playing on academic performance and the roles of gender, race and income in these relationships. Comput. Hum. Behav. 27 , 228–239 (2011).

Yu, M. & Baxter, J. Australian children’s screen time and participation in extracurricular activities. Ann. Stat. Rep. 2016 , 99 (2015).

Rainie, L. & Horrigan, J. A decade of adoption: How the Internet has woven itself into American life. Pew Internet and American Life Project . 25 (2005).

Drummond, A. & Sauer, J. D. Video-games do not negatively impact adolescent academic performance in science, mathematics or reading. PLoS ONE 9 , e87943 (2014).

Article   ADS   CAS   Google Scholar  

Green, L., Olafsson, K., Brady, D. & Smahel, D. Excessive Internet use among Australian children (2012).

Livingstone, S. EU kids online. The international encyclopedia of media literacy . 1–17 (2019).

Wright, J. The effects of video game play on academic performance. Mod. Psychol. Stud. 17 , 6 (2011).

Gentile, D. A., Lynch, P. J., Linder, J. R. & Walsh, D. A. The effects of violent video game habits on adolescent hostility, aggressive behaviors, and school performance. J. Adolesc. 27 , 5–22 (2004).

Rosenthal, R. & Jacobson, L. Pygmalion in the classroom. Urban Rev. 3 , 16–20 (1968).

Willoughby, T. A short-term longitudinal study of Internet and computer game use by adolescent boys and girls: prevalence, frequency of use, and psychosocial predictors. Dev. Psychol. 44 , 195 (2008).

Weis, R. & Cerankosky, B. C. Effects of video-game ownership on young boys’ academic and behavioral functioning: a randomized, controlled study. Psychol. Sci. 21 , 463–470 (2010).

Howell, D. C. The treatment of missing data. The Sage handbook of social science methodology . 208–224 (2007).

Terry, M. and Malik, A. Video gaming as a factor that affects academic performance in grade nine. Online Submission (2018).

Houghton, S. et al. Virtually impossible: limiting Australian children and adolescents daily screen based media use. BMC Public Health. 15 , 5 (2015).

Jackson, L. A., Von Eye, A., Fitzgerald, H. E., Witt, E. A. & Zhao, Y. Internet use, videogame playing and cell phone use as predictors of children’s body mass index (BMI), body weight, academic performance, and social and overall self-esteem. Comput. Hum. Behav. 27 , 599–604 (2011).

Bowers, A. J. & Berland, M. Does recreational computer use affect high school achievement?. Educ. Technol. Res. Dev. 61 , 51–69 (2013).

Wittwer, J. & Senkbeil, M. Is students’ computer use at home related to their mathematical performance at school?. Comput. Educ. 50 , 1558–1571 (2008).

Jackson, L. A. et al. Does home internet use influence the academic performance of low-income children?. Dev. Psychol. 42 , 429 (2006).

Barlett, C. P., Anderson, C. A. & Swing, E. L. Video game effects—confirmed, suspected, and speculative: a review of the evidence. Simul. Gaming 40 , 377–403 (2009).

Suziedelyte, A. Can video games affect children's cognitive and non-cognitive skills? UNSW Australian School of Business Research Paper (2012).

Chiu, S.-I., Lee, J.-Z. & Huang, D.-H. Video game addiction in children and teenagers in Taiwan. CyberPsychol. Behav. 7 , 571–581 (2004).

Skoric, M. M., Teo, L. L. C. & Neo, R. L. Children and video games: addiction, engagement, and scholastic achievement. Cyberpsychol. Behav. 12 , 567–572 (2009).

Leung, L. & Lee, P. S. Impact of internet literacy, internet addiction symptoms, and internet activities on academic performance. Soc. Sci. Comput. Rev. 30 , 403–418 (2012).

Xin, M. et al. Online activities, prevalence of Internet addiction and risk factors related to family and school among adolescents in China. Addict. Behav. Rep. 7 , 14–18 (2018).

PubMed   Google Scholar  

Lawrence, D., Johnson, S., Hafekost, J., et al. The mental health of children and adolescents: report on the second Australian child and adolescent survey of mental health and wellbeing (2015).

Hafekost, J. et al. Methodology of young minds matter: the second Australian child and adolescent survey of mental health and wellbeing. Aust. N. Z. J. Psychiatry 50 , 866–875 (2016).

Australian Curriculum ARAA. National Assessment Program Literacy and Numeracy: Achievement in Reading, Persuasive Writing, Language Conventions and Numeracy: National Report for 2011 . Australian Curriculum, Assessment and Reporting Authority (2011).

Daraganova, G., Edwards, B. & Sipthorp, M. Using National Assessment Program Literacy and Numeracy (NAPLAN) Data in the Longitudinal Study of Australian Children (LSAC) . Department of Families, Housing, Community Services and Indigenous Affairs (2013).

NAP. NAPLAN (2016).

Australian Curriculum ARAA. National report on schooling in Australia 2009. Ministerial Council for Education, Early Childhood Development and Youth… (2009).

Vu, X.-B.B., Biswas, R. K., Khanam, R. & Rahman, M. Mental health service use in Australia: the role of family structure and socio-economic status. Children Youth Serv. Rev. 93 , 378–389 (2018).

McCullagh, P. Generalized Linear Models (Routledge, Abingdon, 2019).

Book   Google Scholar  

Gregg, P., Washbrook, E., Propper, C. & Burgess, S. The effects of a mother’s return to work decision on child development in the UK. Econ. J. 115 , F48–F80 (2005).

Khanam, R. & Nghiem, S. Family income and child cognitive and noncognitive development in Australia: does money matter?. Demography 53 , 597–621 (2016).

Kutner, M. H., Nachtsheim, C. J., Neter, J. & Li, W. Applied Linear Statistical Models (McGraw-Hill Irwin, New York, 2005).

Lumley T. Package ‘survey’. 3 , 30–33 (2015).

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Acknowledgements

The authors would like to thank the University of Western Australia, Roy Morgan Research, the Australian Government Department of Health for conducting the survey, and the Australian Data Archive for giving access to the YMM survey dataset. The authors also would like to thank Dr Barbara Harmes for proofreading the manuscript.

This research did not receive any specific Grant from funding agencies in the public, commercial, or not-for-profit sectors.

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M.I.I.: Methodology, Validation, Visualization, Investigation, Writing—Original draft preparation, Writing—Reviewing and Editing. R.K.B.: Methodology, Software, Data curation, Formal Analysis, Writing—Original draft preparation. R.K.: Conceptualization, Methodology, Supervision, Writing- Reviewing and Editing.

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Islam, M.I., Biswas, R.K. & Khanam, R. Effect of internet use and electronic game-play on academic performance of Australian children. Sci Rep 10 , 21727 (2020). https://doi.org/10.1038/s41598-020-78916-9

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SYSTEMATIC REVIEW article

Massively multiplayer online games and well-being: a systematic literature review.

• 1 School of Health and Behavioural Sciences, University of the Sunshine Coast, Maroochydore, QLD, Australia
• 2 Institute of Health and Sports, Victoria University, Melbourne, VIC, Australia
• 3 School of Psychology, National and Kapodistrian University of Athens, Athens, Greece
• 4 Thompson Institute, University of the Sunshine Coast, Maroochydore, QLD, Australia

Background: Massively multiplayer online games (MMOs) evolve online, whilst engaging large numbers of participants who play concurrently. Their online socialization component is a primary reason for their high popularity. Interestingly, the adverse effects of MMOs have attracted significant attention compared to their potential benefits.

Methods: To address this deficit, employing PRISMA guidelines, this systematic review aimed to summarize empirical evidence regarding a range of interpersonal and intrapersonal MMO well-being outcomes for those older than 13.

Results: Three databases identified 18 relevant English language studies, 13 quantitative, 4 qualitative and 1 mixed method published between January 2012 and August 2020. A narrative synthesis methodology was employed, whilst validated tools appraised risk of bias and study quality.

Conclusions: A significant positive relationship between playing MMOs and social well-being was concluded, irrespective of one's age and/or their casual or immersed gaming patterns. This finding should be considered in the light of the limited: (a) game platforms investigated; (b) well-being constructs identified; and (c) research quality (i.e., modest). Nonetheless, conclusions are of relevance for game developers and health professionals, who should be cognizant of the significant MMOs-well-being association(s). Future research should focus on broadening the well-being constructs investigated, whilst enhancing the applied methodologies.

Introduction

Internet gaming is a popular activity enjoyed by people around the globe, and across ages and gender ( Internet World Stats, 2020 ). With the addition of Internet Gaming Disorder (IGD) in the 5th edition of the Diagnostic and Statistical Manual for Mental Health Disorders (DSM-5; American Psychiatric Association, 2013 ) as a condition requiring further study, followed by the introduction of Gaming Disorder (GD) as a formal diagnostic classification in the 11th edition of the International Classification of Diseases (ICD-11; World Health Organization, 2019 ), research concerning the associated adverse effects of gaming has increased ( Kircaburun et al., 2020 ; Teng et al., 2020 ). Accordingly, a series of potentially harmful aspects of internet gaming, such as reduced social skills, aggression, reduced family connection, interruptions to one's work and education have been cited ( Pontes et al., 2020 ).

Despite such likely aversive connotations, the uptake of internet gaming continues to increase. Recent statistics suggest that 64% of adults in the United States (U.S.) are gamers, 59% of those being male, with the average age range situated between 34 to 45 ( Entertainment Software Association, 2020 ). Of note is that 65% of those gamers are playing with others online or in person and they spend an average of 6.6 h playing per week with others online. Similarly, a survey of 801 New Zealand households (2,225 individuals) revealed that two-thirds play video games, with 34 years being the average age ( Brand et al., 2019 ).

Such high levels of game involvement have been interwoven with high reports of potential well-being benefits in the U.S. sample, including 80% for mental stimulation, 63% for problem solving, 55% for connecting with friends, 79% for relaxation and stress relief, 57% for enjoyment, and 50% for accommodating family quality time ( Entertainment Software Association, 2020 ). Interestingly, 30% of U.S. gamers met a good friend, spouse, or significant other through gaming ( Entertainment Software Association, 2020 ). Thus, video gaming does offer benefits, especially for one's socialization; indeed, gaming can simultaneously engage multiple online players ( Pierre-Louis, 2020 ; Pontes et al., 2020 ).

Multiplayer online games involve a broad genre of internet games, which entail participants playing with others in teams or competing within online virtual worlds ( Barnett and Coulson, 2010 ). A 2017 report of 1,234 Australian households (3,135 individuals) found 67% regularly played video games on computers, tablets, mobile phones, handheld devices, and gaming consoles, with 92% of those playing online with others ( Brand et al., 2017 ). When the “multiple-players” component allows the concurrent inclusion of large numbers (i.e., masses) of gamers, games are referred as massively multiplayer online games (MMOs; Stavropoulos et al., 2019 ). Such games employ the internet to simultaneously host millions of users globally. Participants tend to be organized in groups/teams/alliances competing with each other in the context of game worlds with progressively higher demands and challenges ( Adams et al., 2019 ). Massively multiplayer online role-playing games (MMORPG) expand on this format of play with the introduction of role-playing characteristics through the creation of an avatar. This involves the player establishing their own customizable character for their gameplay, providing an opportunity for gamers to experiment with their own identity in a safe environment ( Stavropoulos et al., 2020 ). Thus, MMORPGs constitute a distinct subgenre of MMOs.

A preponderance of recent research on MMOs has focused specifically on the negative effects of problematic gaming or IGD ( Kircaburun et al., 2020 ; Pontes et al., 2020 ). For instance, a systematic review conducted by Männikkö et al. (2017) focused on health-related outcomes of problematic gaming behavior. This review aligns with prior research that looked at the risk factors and adverse health outcomes of excessive internet usage, particularly among adolescents ( Lam, 2014 ; Goh et al., 2019 ). Despite these efforts, Sublette and Mullan (2012) suggested that the evidence regarding the negative health consequences of gaming is inconclusive (e.g., overall health, sleep, aggression). As Internet games, and especially MMOs, may be also played moderately, they can accommodate a series of beneficial effects for the users such as socialization, a sense of achievement, and positive emotion ( Halbrook et al., 2019 ; Zhonggen, 2019 ; Colder Carras et al., 2020 ). Accordingly, the systematic literature review of Scott and Porter-Armstrong (2013) aimed to offer a more balanced view of the whole range of the positive and the negative effects of participation in MMORPGs, including on the psychosocial well-being of adolescents and young adults. They studied six research articles, where both negative and positive outcomes were identified; for instance, they concluded that problematic/pathological gaming associated with the negative outcomes such as depression, disrupted sleep, and avoidance of unpleasant thoughts. However, they also suggested that the MMORPG context could often provide a refuge from real-world issues, where new friendships and cooperative play could provide enjoyment. Correspondingly, a review of videogame use and flourishing mental health employing Seligman's 2011 positive psychology model of well-being (i.e., positive emotion; engagement; relationships; meaning and purpose; and accomplishment) reported that moderate levels of play was associated with improved mood and emotional regulation, decreased stress and emotional distress, and relaxation. Decisively, Jones and colleagues ( Jones et al., 2014 ) asserted that “videogame research must move beyond a “good-bad” dichotomy and develop a more nuanced understanding about videogame play” (p. 7).

Despite the progress made, no systematic literature to date has synthesized the state of the empirical evidence considering the well-being influences of MMOs. This is important for three reasons: (a) MMOs have had significant advancements in the last 5 years, which may have radically altered their well-being potential (i.e., audio, visual, and augmented reality effects; Alha et al., 2019 ; Semanová, 2020 ); (b) the MMO players community has significantly expanded ( Statista, 2021 ) and; (c) growing empirical evidence has widened the available knowledge of the effects of multiplayer gaming ( Sourmelis et al., 2017 ; Cole et al., 2020 ). Consequently, this present systematic review will contribute to the niche research area referring to the MMOs and well-being association. To address this purpose, the notion of psychosocial well-being and its operationalization needs to be clarified. Scott and Porter-Armstrong (2013) conceived one's level of well-being as expressed through an individual's interpersonal and intrapersonal functioning. In that context, the complexity related to the assessment of one's well-being is acknowledged ( Burns, 2015 ; Linton et al., 2016 ). On that basis, this review utilized the six broad well-being themes as delineated by Linton et al. (2016) to inform the theoretical framework of synthesizing MMO well-being related effects and evidence. The six themes are: (a) mental well-being (e.g., a person's thoughts and emotions); (b) social well-being (e.g., interactions and relationships with others, social support); (c) activities and functioning (e.g., daily activities and behavior); (d) physical well-being (e.g., person's physical functioning and capacity); (e) spiritual well-being (e.g., connection to something greater, faith) and; (f) personal circumstances (e.g., environmental factors; Linton et al., 2016 ).

To enhance the utility of findings, the present review will focus on the most prevalent age range of MMO gamers. The entertainment software association reported that of those playing video games, 21% are under the age of 18 years, 38% between 18 and 34, 26% between 35 and 54 and 15% 55 and over ( Pierre-Louis, 2020 ). In addition, the currently most popular MMOs were identified and targeted. According to the entertainment software association, these involve World of Warcraft, RuneScape, and Guild Wars 2 among gamers older than 13 years ( BeStreamer, 2020 ; Entertainment Software Association, 2020 ). All the available empirical evidence derived by randomized, controlled trials, cross-sectional studies, and case studies with n > 1 that identified any MMOs linked well-being outcomes was included and examined across the six well-being domains identified (see Linton et al., 2016 ). Thus, all the range of interpersonal and intrapersonal well-being outcomes for MMO players over the age of 13 were considered. The ultimate aim of this review is to contribute to balancing the available knowledge surrounding the impact of the popular MMO genre, whilst concurrently illustrating directions for gamer-centered and beneficial future research and mental health practice initiatives.

Materials and Methods

This systematic review followed the methodology suggested in the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA; Moher et al., 2009 ; Shamseer et al., 2015 ). Research team discussion and perusal of related published reviews assisted the development of the initial research eligibility, search strategy, and related terms. Inclusion and exclusion criteria were further refined at the selection process stage, after exposure and familiarity with the research area; this review was limited to research obtained from database searches.

Eligibility Criteria

All research investigating massively multiplayer online gaming were eligible for review. The initial search eligibility criteria were (i) a publication date between 2012 to 2020; (ii) written in or translated into English language; and (iii) full-text, peer-reviewed primary research.

Information Sources and Search Strategy

Searches were conducted in August 2020 using online databases, JB searched PsycNET (APA), and PUBMED; whereas, LR searched Scopus (see Figure 1 ). In each case, the following search terms and protocol were used (massively multiplayer online OR multiplayer online OR MMORPG OR MMOG) to search abstracts and/or titles. Searches were limited by publication date, 2012 to the present. No specific terms for well-being outcomes were prescribed to ensure that the literature search remained expansive. Accordingly, potential well-being effects were assessed at the screening stage.

Figure 1 . PRISMA flow diagram for the present study.

Selection Process and Data Management

After the title search, abstracts were independently screened by two investigators (JB & LR) for positive outcome measures, fitting within the identified well-being parameters (i.e., Linton et al., 2016 ). Example terms included, but were not limited to, “well-being,” “quality of life,” “social support,” “belonging,” “positive affect,” and “cognitive ability.” Where abstracts contained insufficient/unclear information, the full-text was reviewed for accurate evaluation. The resultant items/studies/records were pooled, and duplicates were removed. The remaining, potentially relevant studies were divided equally between LR and JB, and the full studies were subsequently (and independently) assessed. Where uncertainty of inclusion was noted, articles were screened by the alternate investigator (i.e., JB or LR). Then, if uncertainty regarding inclusion still remained, investigator LK was the final arbitrator (see Figure 1 ).

This detailed screening process utilized the following inclusion criteria: (i) qualitative or quantitative research of any design; (ii) written in or translated into English language; (iii) a primary study aim was psychological well-being (or a component of psychological well-being; Linton et al., 2016 ); and (iv) it was clearly indicated that participants were aged 13 years or over [according to Entertainment Software Association (2020) age ranges of high gaming prevalence]. Studies were excluded if: (i) they were single case studies, reviews of any kind (e.g., systematic reviews or meta-analyses), dissertations or theses, or opinions or discussion papers; (ii) the focus was IGD, problematic gaming or addiction; (iii) they involved online gambling, sexual foci (e.g., cybersex), exergaming, or e-sports; (iv) the game was not generally available to the wider community or was an educational tool; (v) they focused on motivations for engaging in online gaming or on learning English language; or (vi) gaming was not played on computers. Once articles were pooled, each reviewer independently recorded the reasons for excluding the articles in a shared file.

Data Extraction Process

The final studies were summarized according to the following characteristics: (1) study design (e.g., cross-sectional survey); (2) sample characteristics (i.e., size, source of recruitment); (3) the specific MMORPG(s) emphasized; (4) variables (i.e., types of social capital, types of networks); (5) instruments for assessing key variables (e.g., time in game, social capital); (6) the type of analysis used; (7) main findings in relation to well-being (e.g., relationship between game and well-being or with belongingness); and (8) limitations. Investigators SR and LR each independently reviewed half of the studies, with joint discussion to resolve any uncertainties. Table 1 summarizes the reviewed studies.

Table 1 . Main characteristics of reviewed studies ( N = 18).

Data Analysis Procedures and Quality

Given the diversity of study objectives and well-being outcomes reviewed, meta-analysis was not plausible. Therefore, a narrative synthesis methodology was adopted, as it involves a textual summation and explanation of the data which was considered appropriate considering the focus of this review ( Greenhalgh et al., 2005 ; Popay et al., 2006 ). Following the goals of this review, the analysis aimed to identify the key positive or well-being outcomes of playing MMORPGs. Consequently, comparable studies/results were grouped together categorizing the data into themes (and subthemes) that drew on the six well-being themes identified by Linton et al. (2016) . A narrative account of these results is presented under relevant thematic headings, along with any pertinent moderating factors ( Greenhalgh et al., 2005 ).

Risk of bias and quality of evidence evaluations were undertaken using the Appraisal tool for Cross-Sectional Studies ( Downes et al., 2016 ) for the quantitative studies, and the Critical Appraisal Checklist for Qualitative Research ( Joanna Briggs Institute, 2020 ) for the studies that used a qualitative methodology. The Mixed Methods Appraisal Tool ( Hong et al., 2018 ) was used by JB and LR to conduct their independent appraisals of each study. These were then compared and discussed across each item/study/record to conclude agreement.

Study Selection

As per the flow of information and studies is shown in Figure 1 , a total of 1695 studies (PsycNET n = 524, PubMed n = 500, Scopus n = 671) were identified through the initial search. After abstracts were reviewed, 1,431 studies were excluded due to not being suitable for the present review. A further 64 studies were removed for duplication. A full-text review was done on the remaining 200 studies. Of these 182 studies were excluded due to age of participants ( n = 8), focus on IGD or addiction ( n = 32), focus on motivations/predictors of play ( n = 24), not being in English ( n = 4), not being primary research ( n = 30), focused on education ( n = 16), full-text unable to be accessed ( n = 4), not exclusively MMO ( n = 8), only measuring in-game behaviors ( n = 29), or not meeting well-being criteria ( n = 27). Following this screening process, 18 studies were included in the final narrative synthesis (see Figure 1 ).

Study Characteristics

The main characteristics, including the aims and purpose of each study, the well-being measures used, and the results of each of the final 18 studies are noted Table 1 . For those studies which reported the gender of their participants, males accounted for the majority, ranging from 65 to 100% [the latter being the case in the qualitative study of Gallup et al. (2016) ]. One study was equally represented gender-wise ( Cole et al., 2020 ) and one had slightly more females (51%) than males ( Doh and Whang, 2014 ). Participants were from North America, China, Korea, Greece, and Australia. For those studies that reported the game platform, World of Warcraft was the most common ( n = 10). Twelve studies measured time spent gaming with variable time measures, such as hours weekly, per week-day, and weekend. Averages of hours per week ranged from 11 to 36.7, while daily hours were estimated to vary between 2 and 5.

Risk of Bias and Quality of Studies

Quality of reporting, study design quality and risk of bias was assessed for each of the 13 cross-sectional studies. All the cross-sectional studies had a moderate level of risk of bias [studies: 1–4, 8–10, 12, 13, 15-18]. This included sample issues [studies, 1-4, 8-10, 12, 13, 15, 17, 18]. Only one study provided information to justify their sample size, and this was through pragmatic rather than statistical reasons ( Zhang and Kaufman, 2015 ). Although seven studies [studies, 1, 4, 8, 10, 12, 13, 17] had sample sizes over 300, sample size was deemed to be an issue of concern given the millions of MMOG players globally ( Internet World Stats, 2020 ). Sampling methods raised concerns regarding risk of bias and study design quality, as most studies relied on self-selection, and one MMOG was the primary data collection source [six studies used this MMOG alone (studies 2, 9, 11, 16–18), while four studies (studies 1, 4, 14, 15) included this MMOG], although conclusions were often made with reference to MMOGs as a whole. Only six studies [studies, 2, 3, 10, 13, 15, 16] acknowledged or raised concerns regarding response rates, but did not provide clear information on this or expected response rates due to the impossibility of determining sampling frames. Furthermore, due to participant self-selection, the majority of studies did not compare responders and non-responders. Of the two studies [4, 15] that did consider response bias, one ( Cole et al., 2020 ) found no difference between non-completers and completers, while the other ( Xanthopoulou and Papagiannidis, 2012 ) found differences on four demographic characteristics (age, gender, occupational, and marital status). Considering the quality of design, the majority of the 13 cross-sectional studies were deemed to fall into a fair category, with a major concern being the omission of whether ethical approval or participant consent was obtained [studies 2, 3, 8–10, 12, 13, 15] and only three studies reporting that there were no funding or other conflicts [studies 2, 12, 17].

The Joanna Briggs Institute (JBI) critical appraisal checklist for qualitative research was used to assess risk of bias for the qualitative studies ( Joanna Briggs Institute, 2020 ). Overall, the quality of these four studies [5, 6, 7, 11] was assessed as quite good. The JBI checklist highlighted two key concerns: adequate reporting of the positioning and of the research influence of the investigators. Only two of the four studies provided details as to the role or possible influence of the investigators on the research [studies 5, 7], and only one study [7] provided a statement showing the cultural and or theoretical perspective of the investigator.

Of the 18 studies, four were qualitative [5, 6, 7, 11] one was a mixed method design [14] and the others were all cross-sectional by design [1–4, 8–10, 12, 13, 15–18]. This led to all results showing exclusively correlational and/or regression links/effects, with unclear direction of causality regarding the MMO gaming and well-being experiences association. Only one study ( Xanthopoulou and Papagiannidis, 2012 ) was longitudinal in design with the second measurement being obtained 1 month after the first responses were collected, allowing for stronger predictive inference.

The well-being outcomes assessed in all the studies were operationalized similarly to authors' expectations aligning with the framework provided by Linton et al. (2016) . Two predominant types of positive outcomes were addressed by the included studies: social well-being and mental well-being. Additionally, one study ( Shen and Chen, 2015 ) [13] considered physical well-being. Several game attributes were considered as predictors across the studies reviewed. The most common attribute was the social aspect as examined by 15 studies [2–4, 6–14, 16–18]. This referred to modes of communication (e.g., in-game talk, game bulletin boards, online comms outside the game), “who” the gamers play with (e.g., real-world friends, on-line friends, family), and time spent gaming. The synthesized results are presented through the lenses of the 2 main well-being outcomes identified.

Social Well-Being

Of the 18 studies, 15 included some form of measurement of social well-being. O'Connor et al. (2015) [study 11] reported that participants of WoW game received social support from others within this gaming community. Gallup et al. (2016) [study 6] and Gallup et al. (2017) [study 7] found that using the online game environment was beneficial for secondary and tertiary students with an Autism Spectrum Disorder (ASD) diagnosis, to develop social connections as well as communication and relationship skills. This skill development also led to improved post-secondary education transitioning. Cole et al. (2020) [study 4] also looked at whether social support increased in the gaming environment, finding that more time spent in playing in guilds as related to higher levels of social support, and that this was correlated with cognitive-emotional outcomes. Additionally, they compared on-line and in-person social support and outcomes, finding differential effects. Cole et al. (2020) [study 4] concluded that MMOGs represent different social support environments, and as such, online worlds could be used as a new and different source of social support. These findings are echoed by Voulgari et al. (2014) [study 14], whose mixed methods research across more than 10 MMOGs found that gaming developed collaborative skills and social bonds additional to real-life relationships. Moreover, gaming constituted a part of the gamers' existing real-world social life.

Social capital effects investigated by the reviewed studies included bonding and bridging aspects. Bonding related social capital implies a deeper form of social support, experienced by those with whom one maintains emotional intimacy, such as their family and friends ( Meng et al., 2015 ) [study 10]. In the game context, bonding social capital refers to the support networks within a specific online gaming group or community, such as one's guild (i.e., group of in-game allies) or group within a particular game ( Claridge, 2020 ). Bridging social capital refers to the support, mainly by sharing information and resources, one may experience from broader and less intimate social groups they belong into, such as their social class, race, and religion ( Perry et al., 2018 ) [study 12]. Castillo (2019) [study 2] found greater bridging social capital experienced when gamers presented more motivated to form relationships with others, compared to gaming for competitive reasons. Moreover, Meng et al. (2015) [study 10] found that playing frequently in the online gaming environment with existing offline friends was positively correlated with both higher bridging and higher bonding social capital. This aligned with Kaye et al. (2017) findings, that playing with online and real-world friends, as well as online interactions in-game and outside, was positively related to both higher bridging and higher bonding social capital.

The study by Perry et al. (2018) [study 12] reported that harmonious passion for playing MMOGs helped build social capital; however, when this passion was obsessive, the outcomes were negative. Their study further found that playing with real-life friends was positively associated with higher bonding social capital experienced by gamers. Interestingly, playing with strangers, and possible new friends, was positively associated with increased bridging social capital. Choi (2019) [study 3] extended such findings by focusing on the link between a gamer's social interactions, avatar identification, and social capital. Higher avatar (i.e., in-game figure representing the gamer) identification was related to increased real-life social capital, with one's greater perception of in-game social interactions linked to higher levels of avatar identification and subsequently elevated social capital.

Three of the articles reviewed [Studies 16, 17, & 18] focused specifically on social well-being among older populations, with all participants exceeding 55 years. These studies by Zhang and Kaufman (2015) [study 16], Zhang and Kaufman (2016) [study 17], and Zhang and Kaufman (2017) [study 18] all looked at the social interactions of older adults in MMORPGs. It was found that enjoyment of relationships in the online game was positively related to both bridging and bonding social capital, and this was partly associated to a gamer's amount of game play, active participation in guilds, and their reported enjoyment of the game. The same three studies also suggested that gaming contributed to maintaining existing family and friend relationships, as well as the development of new meaningful friendships. One of the studies, did imply, however, that new online friends did not easily integrate into the older gamers' real lives ( Zhang and Kaufman, 2017 ) [study 18]. They explained that as the result of older adults' lesser need for large networks, as well as geographical limitations.

Lastly, one article looked at social well-being through the lens of marital satisfaction ( Ahlstrom et al., 2012 ) [study 1]. They reported that compared to couples where only one member is a gamer, couples who game together experience higher levels of marital satisfaction. Higher marital satisfaction was related to more time spent in in-game interaction and higher satisfaction of playing together. They supported that gaming is a leisure activity, where when only one person is immersed, disruption to marital harmony may be caused. Indeed, this was confirmed by both types of couples (e. g., only one gaming vs. both gaming), when considering their different or similar bedtimes and their arguments over the time spent in gaming compared to the time spent together.

Mental Well-Being

A smaller proportion of studies looked at the effects of MMOG on components of mental well-being such as self-esteem, depression, stress, general affect, and skill acquisition. Self-esteem was specifically identified in three articles [Studies 3, 4, & 8] and was related to social support received in the game and with positive gamer identities in an MMORPG ( Kaye et al., 2017 ; Choi, 2019 ; Cole et al., 2020 ). In their study investigating MMO involvement, gamer identity, and social capital, Kaye et al. (2017) [study 8] found that higher MMO involvement increased with higher bonding and bridging social capital and solidified gamers' identity, which in turn increased their self-esteem and decreased their loneliness. Similarly, Choi's 2019 [study 3] study into the effects of avatar self-identification indicated that perceptions of social support from MMORPG increased avatar identification alongside the gamers' real-life self-esteem. In their examination of a Compensatory Social Interaction Model, Cole et al. (2020) [study 2] investigated the associations between one's MMORPG guild play, social support, peer victimization, self-esteem, depression and stress. Gamers who engaged more in guild play, experienced higher levels of social support (compared to levels of peer victimization), which resulted in improved self-esteem, lower depression, and stress symptoms. Martončik and Lokša (2016) [study 9] directly looked at the social effects of WoW's (i.e., guild affiliation, communication used) on individual's mental well-being. Their study revealed that gamers perceived their level of loneliness as significantly lower in the online world than in the real world. Additionally, gaming with others already known to the player in their real-life decreased perceptions of real-world loneliness. Martončik and Lokša (2016) [study 9] also found that levels of anxiety were lower in the online world, when gamers perceived themselves as less lonely. Similarly, lower levels of loneliness and depression among gamers aged over 55 years were predicted by higher quality of guild play [study 18]. This suggested that for older adults, being an active member of an in-game guild, may improve their emotional well-being ( Zhang and Kaufman, 2017 ).

The mixed methods study by Voulgari et al. (2014) [study 14] contributed information across a combination of different social, cognitive, and emotional well-being outcomes of gaming. Their study found that playing MMOGs had positive impacts on gaining social skills and improving cognitive skills, as well as a positive affective impact. The cognitive skills they identified to have been improved included procedural knowledge and problem-solving skills. The acquisition of such cognitive and social skills was reported to be transferable into their offline world. The authors also reported that for some gamers, positive affective impacts, such as enjoyment and satisfaction, were the most important outcomes. In-game and work leadership skills were looked at by Xanthopoulou and Papagiannidis (2012) [study 15] in their examination on the effects of gaming on real-life employment. They found that in-game active learning was reflected in active learning at work, but only for high game performers. Moreover, transformational leadership was shown to spill over into a player's work life, although this appears to be enhanced by higher game performance.

In that line, Doh and Whang (2014) focused on the development of behavioral statements to establish the gaming environment as a different pathway to use in identity development. They reported that a player's motivation to participate in online gaming could progressively lead to an alternated identity. Lastly, Shen and Chen (2015) explored the effect of gaming related social capital into health-related outcomes. This study found that bonding and not bridging social capital occurring while playing online related to reduced health disruption in one's daily lives.

The increasing preference for MMO gaming for leisure and e-sport has led to a large body of research investigating the possible adverse outcomes related to their excessive usage ( Stavropoulos et al., 2019 , 2020 ). However, less is known about the possible benefits of moderate MMO gaming for one's individual psychosocial well-being. The aim of this review was two-fold: (a) to identify and summarize the empirical evidence for the potential interpersonal and intrapersonal positive well-being outcomes for non-excessive MMO players over the age of 13; and (b) to identify possible research priorities in relation to better understanding the beneficial effects of MMO gaming. Overall, a positive relationship between playing MMOs and social well-being was found.

This systematic review identified 18 studies that were published between 2012 and 2020, and which investigated the adaptive well-being outcomes of MMOG for adolescent and adult players. These studies examined two key aspects of psychosocial well-being, as defined by Linton et al. (2016) . Firstly, one's social well-being, encompassing individuals' connections with others—their interactions, their depth of relationships, and the social support their connections provided, was emphasized by the reviewed empirical evidence. This was the dominant topic of interest, while the gamers' mental well-being (e.g., individual psychological, emotional, and cognitive aspects) followed. In order to investigate these outcomes, gaming attributes such as gaming time, game performance, gamer identity, types of communication one is engaged in, type of co-players (e.g., online or offline friends, family, strangers), and guild membership were examined.

In that context, a commonly used measure of social well-being employed in the studies reviewed was social capital. The significant positive relationship found between MMOG engagement and bridging and bonding social capital in those studies appears promising. Specifically, reviewed findings in studies 2, 10, 12, and 16 suggest there is strong support for the notion that MMO gaming may foster one's social well-being in both virtual worlds and in their off-line lives ( Meng et al., 2015 ; Zhang and Kaufman, 2015 ; Perry et al., 2018 ; Castillo, 2019 ). Moreover, such evidence is strengthened by studies 1, 3, 4, 6, & 18, which utilized more discrete measures of social well-being, such as one's perceptions of social support, social interactions, and marital satisfaction, showing that MMO gaming bolstered these too ( Ahlstrom et al., 2012 ; Gallup et al., 2016 ; Zhang and Kaufman, 2017 ; Choi, 2019 ; Cole et al., 2020 ). These overall positive conclusive impacts on one's social well-being seem to be reasonably robust given (a) the diverse game attributes considered in these studies (e.g., time spent in play, gamer identity, frequency of play with different types of co-players, avatar identification); and (b) the diverse age and ethnicities of gamers that these impacts were found with-including a small and unique group of gamers with ASD. Moreover, the impacts of MMORPG on social well-being were apparent in both quantitative and qualitative research. Nevertheless, and in line with the current PRISMA systematic literature review's study eligibility criteria, it should be reiterated that the majority of the gamers in the studies reviewed were classified as non-problematic gamers, with study 5 actively excluding those who fit criteria for addiction (e.g., Doh and Whang, 2014 ). Similarly, reviewed studies 12 and 18 included gamers who could be classified as experienced and/or as heavy users, yet they had received no formal diagnosis ( Zhang and Kaufman, 2017 ; Perry et al., 2018 ). Thus, due to the wide range of time participants spent gaming, the findings are applicable to both the more casual and immersed gamer populations, solidifying the positive effects of MMO gaming on one's social well-being.

Further, the reviewed studies examined the mental well-being effects of one's MMO gaming. Self-esteem, loneliness, depression, and positive affect were the main psychological outcomes investigated, while studies 7 and 14 looked at cognitive skill acquisition ( Voulgari et al., 2014 ; Gallup et al., 2017 ). Overall, these studies found that gaming bolstered self-esteem, and reduced depression, stress, and loneliness, whilst fostering cognitive and social skills. However, these positive findings should be treated with some caution, as these variables were only considered in a handful of the studies and such revealed effects may be interwoven with one's concurrently experienced positive social well-being outcomes. More studies need to be conducted among MMO gamers, in which mental well-being outcomes are of primary focus, and social variables are controlled for.

Taken together, this review provides validation to game developers, educators, health professionals, and policy makers, that despite evidence regarding the adverse outcomes of excessive MMO gaming and problematic gaming behavior, there are important psychosocial benefits to be gained from moderate and adaptive gaming. This information is relevant to game developers as they should be encouraged to find ways to enhance social contact opportunities. Moreover, it is important that health professionals and educators are aware that MMO gaming is an avenue for social connection and support, similar to other real-world leisure and sporting pursuits. Pathologizing gaming could well undermine the identity, social, and psychological well-being of those who actively benefit by their moderate and adaptive gaming engagement.

Strengths and Limitations

The validity of these results is restricted due to the heterogeneity of methodologies used in the studies reviewed. Although qualitative and quantitative empirical evidence was included, most studies used a descriptive design to assess the self-reported effects of MMO gaming on well-being. Moreover, although many of the studies controlled for some covariates, such as demographic variables or gaming time, variables of interest were narrow, and other unmeasured variables might account for some of the observed effects. Additionally, although many of the predictor measures had solid theoretical bases, others have not been fully trialed (e.g., intensity of interaction, multimodal connectedness), contributing to possible validity issues. Furthermore, the value of the findings is impacted by a lack of generalizable results. For example, self-selection bias was reported by several studies, where heavy gamers or an overly well-educated sample was used, and some studies looked at specific populations (e.g., 55+ years, those with ASD; Zhang and Kaufman, 2015 ; Gallup et al., 2017 ) [See studies 7 & 16]. The sample of MMO games examined was also narrow, with WoW dominating. Finally, only a limited number of well-being constructs were examined by the 18 studies, thus the conclusions regarding well-being have limited generalizability/need to be treated with caution due to narrow constructs covered. Of note was a lack of variety in the well-being outcomes being studied. While social well-being is an important part of MMO gaming, little is known about other aspects of well-being such as mental well-being, spiritual well-being, and physical well-being. The fact that no randomized control trials have been undertaken to contribute to the research on well-being outcomes and MMO participation is an important omission in this field of study.

This review was limited to peer-reviewed studies published in three academic databases between 2012 and August 2020, at one particular point in time. Therefore, the review may be subject to English-language and publication bias, and the studies included may not be a representative sample. Relevant research may also have been missed due to including the use of selected search terms, and this review did not include non-peer-reviewed literature (e.g., theses, conference proceedings), which may have omitted important data. Finally, well-being is a broad concept, and other reviews may generate different empirical evidence dependent on the operationalizations followed.

Despite the noted review-level limitations, this study has several strengths. First, this review used rigorous methodology, following PRISMA guidelines and assessing quality and risk of bias using validated tools. Additionally, the inclusivity of study design has meant we have captured data through diverse approaches with similar outcomes. Finally, the broad search parameters with regards well-being ensured that we did not limit the construct to narrow conceptualizations of well-being outcomes related to MMO gaming.

This review has offered a valuable examination of the current research on the psychosocial benefits of multiplayer online gaming. It is important to note the number of reviewed studies that reported significant positive outcomes regarding social well-being. The major limitation of the review relates to the modest quality of research in the area, and the limited aspects of well-being investigated to date. While social well-being is an important part of MMO gaming, there is very little known about other aspects of well-being such as mental well-being, spiritual well-being, and physical well-being.

Recommendations for future research include broadening the well-being constructs that are investigated in relation to gaming. Clear and consistent operationalization of commonly used variables and measures and standardized demographic information would provide greater validity and comparability of results. Longitudinal research in which baseline measurements of well-being and other variables are taken to assess changes in this outcome, to determine causation and not merely correlational effects is also required. Finally, using a greater variety of gaming platforms, instead of mostly WoW, would provide increased robustness for positive well-being outcomes related to MMOGs.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.

Author Contributions

LR and JB performed the bibliographic search, participated in the selection of included studies, resolved methodological doubts of possible studies, and helped in the all versions of this manuscript. LK-D and VS were senior authors and were involved in the review design and review aim, also the above processes conducted by LR and JB, and manuscript revision and submission. PM, AA, HS, JM, TD, and AW contributed in the interpretation of the results and the improvement of the manuscript. PM also contributed to mentoring in the PRISMA process. All authors contributed to the article and approved the submitted version.

VS has received the Australian Research Council, Discovery Early Career Researcher Award (DE210101107).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Adams, B. L., Stavropoulos, V., Burleigh, T. L., Liew, L. W., Beard, C. L., and Griffiths, M. D. (2019). Internet gaming disorder behaviors in emergent adulthood: a pilot study examining the interplay between anxiety and family cohesion. Int. J. Ment. Health Addict. 17, 828–844. doi: 10.1007/s11469-018-9873-0

CrossRef Full Text | Google Scholar

Ahlstrom, M., Lundberg, N. R., Zabriskie, R., Eggett, D., and Lindsay, G. B. (2012). Me, my spouse, and my avatar: the relationship between marital satisfaction and playing massively multiplayer online role playing games (MMORPGs). J. Leisure Res. 44, 1–22. doi: 10.1080/00222216.2012.11950252

Alha, K., Koskinen, E., Paavilainen, J., and Hamari, J. (2019). Why do people play location-based augmented reality games: a study on Pokémon GO. Comput. Hum. Behav. 93, 114–122. doi: 10.1016/j.chb.2018.12.008

American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Health Disorders, 5th Edn. Washington, DC: American Psychiatric Publishing. doi: 10.1176/appi.books.9780890425596

Barnett, J., and Coulson, M. (2010). Virtually real: a psychological perspective on massively multiplayer online games. Rev. Gen. Psychol. 14, 167–179. doi: 10.1037/a0019442

BeStreamer. (2020). 10 most played MMORPGS of 2020 . Available online at: https://bestreamer.com/gaming/most-played-mmorpg-2019/

Google Scholar

Brand, J. E., Jervis, J., Huggins, P. M., and Wilson, T. W. (2019). Digital New Zealand 2020. IGEA . Available online at: https://igea.net/wp-content/uploads/2019/09/DNZ20-Final-Report-2019.pdf

Brand, J. E., Todhunter, S., and Jervis, J. (2017). “Digital Australia Report 2018.” IGEA https://www.igea.net/wp-content/uploads/2017/07/Digital-Australia-2018-DA18-Final-1.pdf

Burns, R. (2015). “Psychosocial well-being,” in Encyclopedia of Geropsychology , eds N. A. Pachana (Singapore: Springer), 1–8. doi: 10.1007/978-981-287-080-3_251-1

Castillo, R. P. (2019). Exploring the differential effects of social and individualistic gameplay motivations on bridging social capital for users of a massively multiplayer online game. Comput. Hum. Behav. 91, 263–270. doi: 10.1016/j.chb.2018.10.016

Choi, J. W. (2019). An influence of game avatar on real world. Int. J. Innovat. Technol. Explo. Eng. 8, 2935–2940. doi: 10.35940/ijitee.K1906.1081219

Claridge, T. (2020). What is the difference between bonding and bridging social capital? Social Capital Research and Training . Available online at: https://www.socialcapitalresearch.com/difference-bonding-bridging-social-capital/#:~:text=Bonding%20social%20capital%20is%20within,important%20socio

Colder Carras, M., Shi, J., Hard, G., and Saldanha, I. J. (2020). Evaluating the quality of evidence for gaming disorder: a summary of systematic reviews of associations between gaming disorder and depression or anxiety. PLoS ONE 15:e0240032. doi: 10.1371/journal.pone.0240032

PubMed Abstract | CrossRef Full Text | Google Scholar

Cole, D. A., Nick, E. A., and Pulliam, K. A. (2020). Are massively multiplayer online role-playing games healthy or not and why? Preliminary support for a compensatory social interaction model. Comput. Hum. Behav. 102, 57–66. doi: 10.1016/j.chb.2019.08.012

Doh, Y. Y., and Whang, S.-M. L. (2014). From separation to integration: identity development of Korean adult players in online game world. Games Cult. J. Interact. Media 9, 30–57. doi: 10.1177/1555412013498301

Downes, M. J., Brennan, M. L., Williams, H. C., and Dean, R. S. (2016). Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS). BMJ Open 6:e011458. doi: 10.1136/bmjopen-2016-011458

Entertainment Software Association (2020). 2020 Essential Facts About the Video Game Industry . Available online at: https://www.theesa.com/esa-research/2020-essential-facts-about-the-video-game-industry/

Gallup, J., Little, M. E., Serianni, B., and Kocaoz, O. (2017). The potential of virtual environments to support soft-skill acquisition for individuals with autism. Quali. Rep. 22, 2509–2532. Available online at: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030689806&partnerID=40&md5=b92a6ae657d5b91f2e2749cdb8196c1b

Gallup, J., Serianni, B., Duff, C., and Gallup, A. (2016). An exploration of friendships and socialization for adolescents with autism engaged in massively multiplayer online role-playing games (MMORPG). Educ. Train. Autism Dev. Disabil . 51, 223–237. Available online at: https://www.jstor.org/stable/24827520

Goh, C., Jones, C., and Copello, A. (2019). A further test of the impact of online gaming on psychological wellbeing and the role of play motivations and problematic use. Psychiatr. Q. 90, 747–760. doi: 10.1007/s11126-019-09656-x

Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., Kyriakidou, O., and Peacock, R. (2005). Storylines of research in diffusion of innovation: A meta-narrative approach to systematic review. Soc. Sci. Med. 61, 417–430. doi: 10.1016/j.socscimed.2004.12.001

Halbrook, Y. J., O'Donnell, A. T., and Msetfi, R. M. (2019). When and how video games can be good: a review of the positive effects of video games on well-being. Perspect. Psychol. Sci. 14, 1096–1104. doi: 10.1177/1745691619863807

Hong, Q. N., Fàbregues, S., Bartlett, G., Boardman, F., Cargo, M., Dagenais, P., et al. (2018). The mixed methods appraisal tool (MMAT) version 2018 for information professionals and researchers. Educ. Informat. 34, 285–291. doi: 10.3233/EFI-180221

Internet World Stats. (2020). Internet World Stats: Usuage and Population Statistics.” Available online at: https://www.internetworldstats.com/

Joanna Briggs Institute. (2020). JBI Critical Appraisal Checklist for Qualitative Research . Available online at: https://joannabriggs.org/critical-appraisal-tools

Jones, C., Scholes, L., Johnson, D., Katsikitis, M., and Carras, M. C. (2014). Gaming well: Links between videogames and flourishing mental health. Front. Psychol. 5:260. doi: 10.3389/fpsyg.2014.00260

Kaye, L. K., Kowert, R., and Quinn, S. (2017). The role of social identity and online social capital on psychosocial outcomes in MMO players. Comput. Hum. Behav. 74, 215–223. doi: 10.1016/j.chb.2017.04.030

Kircaburun, K., Pontes, H. M., Stavropoulos, V., and Griffiths, M. D. (2020). A brief psychological overview of disordered gaming. Curr. Opin. Psychol. 36, 38–43. doi: 10.1016/j.copsyc.2020.03.004

Lam, L. (2014). Risk factors of internet addiction and the health effect of internet addiction on adolescents: a systematic review of longitudinal and prospective studies. Curr. Psychiatry Rep. 16, 1–9. doi: 10.1007/s11920-014-0508-2

Linton, M. J., Dieppe, P., and Medina-Lara, A. (2016). Review of 99 self-report measures for assessing well-being in adults: exploring dimensions of well-being and developments over time. BMJ Open . 6:e010641. doi: 10.1136/bmjopen-2015-010641

Liu, M., and Peng, W. (2008). “A cognitive mode for understanding online gaming addiction: a preliminary test in China,” in Paper Presented at the Annual Conference of the International Communication Association (Montreal, QC).

Männikkö, N., Ruotsalainen, H., Miettunen, J., Pontes, H. M., and Kääriäinen, M. (2017). Problematic gaming behaviour and health-related outcomes: a systematic review and meta-analysis. J. Health Psychol. 25, 67–81. doi: 10.1177/1359105317740414

Martončik, M., and Lokša, J. (2016). 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. 56, 127–134. doi: 10.1016/j.chb.2015.11.035

Meng, J., Williams, D., and Shen, C. (2015). Channels matter: multimodal connectedness, types of co-players and social capital for multiplayer online battle arena gamers. Comput. Hum. Behav. 52, 190–199. doi: 10.1016/j.chb.2015.06.007

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

O'Connor, E. L., Longman, H., White, K. M., and Obst, P. L. (2015). Sense of community, social identity and social support among players of massively multiplayer online games (mmogs): a qualitative analysis. J. Commun. Appl. Soc. Psychol. 25, 459–473. doi: 10.1002/casp.2224

Perry, R., Drachen, A., Kearney, A., Kriglstein, S., Nacke, L. E., Sifa, R., et al. (2018). Online-only friends, real-life friends or strangers? Differential associations with passion and social capital in video game play. Comput. Hum. Behav. 79, 202–210. doi: 10.1016/j.chb.2017.10.032

Pierre-Louis, S. (2020). 2020 Essential Facts About the Video Game Industry . Available online at: https://www.theesa.com/esa-research/2020-essential-facts-about-the-video-game-industry/

Pontes, H. M., Stavropoulos, V., and Griffiths, M. D. (2020). Emerging insights on internet gaming disorder: conceptual and measurement issues. Addict. Behav. Rep. 11:100242. doi: 10.1016/j.abrep.2019.100242

Popay, J., Roberts, H., Sowden, A., Petticrew, M., Arai, L., Rodgers, M., et al (2006). Guidance on the Conduct of Narrative Synthesis in Systematic Reviews: A Product From the ESRC Methods Programme . Available online at: https://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/fhm/dhr/chir/NSsynthesisguidanceVersion1-April2006.pdf

Scott, J., and Porter-Armstrong, A. P. (2013). Impact of multiplayer online role-playing games upon the psychosocial well-being of adolescents and young adults: reviewing the evidence. Psychiatry J. 2013:464685. doi: 10.1155/2013/464685

Seligman, M. E. (2011). Flourish: The New Positive Psychology and the Search for Well-Being . New York, NY: Free Press.

Semanová, M. (2020). Emerging Technologies and Video Game Industry: Anticipation of Future Changes . [Bachelor's thesis], JAMK University of Applied Sciences. Available online at: https://www.theseus.fi/bitstream/handle/10024/343752/Semanov%C3%A1%20Martina.pdf?sequence=2

Shamseer, L., Moher, D., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., et al. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 350:g7647. doi: 10.1136/bmj.g7647

Shen, C., and Chen, W. (2015). Social capital, coplaying patterns, and health disruptions: a survey of massively multiplayer online game participants in China. Comput. Hum. Behav. 52, 243–249. doi: 10.1016/j.chb.2015.05.053

Sourmelis, T., Ioannou, A., and Zaphiris, P. (2017). Massively Multiplayer Online Role Playing Games (MMORPGs) and the 21st century skills: a comprehensive research review from 2010 to 2016. Comput. Hum. Behav. 67, 41–48. doi: 10.1016/j.chb.2016.10.020

Statista (2021). Massively Multiplayer Online (MMO) and Multiplayer Online Battle Arena (MOBA) Games Market Size Worldwide in 2017 and 2021 . Available online at: https://www.statista.com/statistics/830090/mmo-moba-market-revenue/

Stavropoulos, V., Gomez, R., and Motti-Stefanidi, F. (2019). Internet gaming disorder: a pathway towards assessment consensus. Front. Psychol. 10:1822. doi: 10.3389/fpsyg.2019.01822

Stavropoulos, V., Gomez, R., Mueller, A., Yucel, M., and Griffiths, M. (2020). User-avatar bond profiles: How do they associate with disordered gaming? Addict. Behav. 103:106245. doi: 10.1016/j.addbeh.2019.106245

Sublette, V., and Mullan, B. (2012). Consequences of play: a systematic review of the effects of online gaming. Int. J. Ment. Health Addict. 10, 3–23. doi: 10.1007/s11469-010-9304-3

Teng, Z., Pontes, H. M., Nie, Q., Xiang, G., Griffiths, M. D., and Guo, C. (2020). Internet gaming disorder and psychosocial well-being: a longitudinal study of older-aged adolescents and emerging adults. Addict. Behav. 110:106530. doi: 10.1016/j.addbeh.2020.106530

Voulgari, I., Komis, V., and Sampson, D. G. (2014). Learning outcomes and processes in massively multiplayer online games: exploring the perceptions of players. Educ. Technol. Res. Dev. 62, 245–270. doi: 10.1007/s11423-013-9312-7

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

Xanthopoulou, D., and Papagiannidis, S. (2012). Play online, work better? Examining the spillover of active learning and transformational leadership. Technol. Forecast. Soc. Change 79, 1328–1339. doi: 10.1016/j.techfore.2012.03.006

Zhang, F., and Kaufman, D. (2015). The impacts of social interactions in MMORPGs on older adults' social capital. Comput. Hum. Behav. 51, 495–503. doi: 10.1016/j.chb.2015.05.034

Zhang, F., and Kaufman, D. (2017). Massively multiplayer online role-playing games (MMORPGs) and socio-emotional wellbeing. Comput. Hum. Behav. 73, 451–458. doi: 10.1016/j.chb.2017.04.008

Zhang, F., and Kaufman, D. P. (2016). Older adults' social interactions in massively multiplayer online role-playing games (MMORPGs). Games Cult. 11, 150–169. doi: 10.1177/1555412015601757

Zhonggen, Y. (2019). A meta-analysis of use of serious games in education over a decade. Int. J. Comput. Games Technol. 2019:4797032. doi: 10.1155/2019/4797032

Keywords: MMOs, internet gaming, systematic literature review, PRISMA, well-being, massively multiplayer online

Citation: Raith L, Bignill J, Stavropoulos V, Millear P, Allen A, Stallman HM, Mason J, De Regt T, Wood A and Kannis-Dymand L (2021) Massively Multiplayer Online Games and Well-Being: A Systematic Literature Review. Front. Psychol. 12:698799. doi: 10.3389/fpsyg.2021.698799

Received: 22 April 2021; Accepted: 25 May 2021; Published: 30 June 2021.

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Copyright © 2021 Raith, Bignill, Stavropoulos, Millear, Allen, Stallman, Mason, De Regt, Wood and Kannis-Dymand. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Vasileios Stavropoulos, Vasileios.Stavropoulos@vu.edu.au

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

The Role of Virtual Communities in Gambling and Gaming Behaviors: A Systematic Review

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• Open access
• Published: 18 April 2020
• Volume 37 , pages 165–187, ( 2021 )

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• Anu Sirola   ORCID: orcid.org/0000-0003-2195-8114 1 ,
• Nina Savela   ORCID: orcid.org/0000-0002-7042-6889 1 ,
• Iina Savolainen   ORCID: orcid.org/0000-0002-8811-965X 1 ,
• Markus Kaakinen   ORCID: orcid.org/0000-0002-7067-1665 2 &
• Atte Oksanen   ORCID: orcid.org/0000-0003-4143-5580 1  

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Gambling opportunities are facilitated by the growth of the Internet and social media platforms. Digital games also increasingly include monetary features, such as microtransactions, blurring the line between gambling and gaming. The Internet provides a variety of virtual communities for gamblers and gamers, but comprehensive research on these communities and their relevance in gambling and monetary gaming behaviors remains scarce. This paper summarizes research of online gambling and monetary gaming communities based on a systematic literature review. A systematic literature search was conducted from five databases: Scopus, Web of Science, PsycINFO, Social Science Premium Collection, and EBSCOhost. The search was limited to empirical articles that focused on gambling or gaming involving money and examined online interaction between gamblers or gamers. Preliminary search resulted in 1056 articles, from which 55 were selected for the analyses based on pre-determined criteria. According to results, online communities serve different functions in gambling and gaming behaviors. Gambling communities are typically forums for discussing and sharing gambling experiences, strategies, and tips as well as gambling problems, while gaming communities are inherently embedded inside a game being an essential part of the gaming experience. Identification with virtual communities influences gambling behavior and monetary gaming behavior through mechanisms of perceived norms, social influence, and community feedback. Whereas some gambling communities may provide protection from excessive gambling habits, gaming communities seem to solely motivate gaming behavior and purchase intentions. The role of online communities should be acknowledged in prevention and treatment of gambling and gaming problems.

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Introduction

The Internet and social media have facilitated and extended gambling opportunities via exponential growth of online gambling platforms. Consequently, social media users are increasingly exposed to gambling content and gambling-like activities in social media (King and Delfabbro 2016 ). At the same time, gambling problems are growing globally (Calado and Griffiths 2016 ). Online games and video games increasingly include gambling-like and monetary features, such as microtransactions (Jacques et al. 2016 ; H. S. Kim et al. 2017 ; King et al. 2015 ), blurring the line between gambling and gaming. Gambling and gambling-like behaviors can be detrimental particularly when excessive, and lead to severe and long-lasting problems, such as economic difficulties (Oksanen et al. 2018 ).

In addition to gambling and gaming platforms, the Internet also offers social environments for gamblers and gamers, such as discussion forums and in-game interaction tools. These kinds of consumption-related online communities (Kozinets 1999 ) and their social aspects may have an important role in gambling and monetary gaming behaviors, but comprehensive research on these communities and their relevance to users remains scarce. In this systematic literature review, we aim to summarize earlier research on online gambling and gaming communities and their role in gambling and monetary gaming behaviors.

The Blurring Line Between Gambling and Gaming

Gambling and gaming have been traditionally perceived as distinct activities. King et al. ( 2015 ) roughly distinguish gambling and gaming based on their central features: gambling is characterized by its risk-involving, chance-determined outcomes and monetary features, such as wagering and betting mechanisms, whereas gaming is characterized by interactive, skill-based play and contextual relevance in game progress and success. However, these boundaries have become more and more blurred, partly due to technological divergence.

Digital games increasingly utilize monetary features, typically microtransactions, as revenue models. Microtransactions are needed, for example, to get additional features or better equipment in a game. Also, so called “loot boxes” have become common particularly in video games, sharing the chance-determined features of gambling. Loot boxes are virtual entities that contain randomized items (e.g., weapons or other equipment) and can be paid with real-world money. Recent research found that spending on loot boxes was associated with problematic gambling (Zendle and Cairns 2018 ). It has also been suggested that due to many similarities between gambling and gaming, playing video games would increase a desire to gamble; but recent research has not fully supported this (Forrest et al. 2016 ; Macey and Hamari 2018 ).

In addition to video games, online games increasingly include gambling-like features. For example, social media sites, such as Facebook, include social games that simulate gambling activities like poker, roulette, or slot machines (Calado et al. 2018 ; Jacques et al. 2016 ; King et al. 2014 ). Although these types of games are often perceived as harmless and safe alternatives for real-money gambling, their gambling-like characteristics may also trigger motivation for real gambling (King et al. 2014 ) and teach mechanisms of gambling to children and adolescents (King et al. 2010 ). Moreover, while “free-to-play” games do not initially require real-money use, they typically encourage players to make in-game purchases (i.e., microtransactions) to get access to additional features (H. S. Kim et al. 2017 ; Paavilainen et al. 2013 ). The aforementioned studies demonstrate that gambling and gaming can no longer be perceived as fully distinct activities. Rather, they increasingly share common characteristics related to gambling-like mechanisms.

Online Communities: Social Dimension of Gambling and Gaming

Humans have a basic need for social belonging and relatedness (Baumeister and Leary 1995 ; Deci and Ryan 2000 ), which is one of the reasons behind the success of online communities and social media (Keipi and Oksanen 2014 ; McKenna and Bargh 1999 ; Reich and Vorderer 2013 ; William et al. 2000 ). Following Kozinets’ ( 1999 ) fundamental definition, virtual communities (i.e., online communities) consist of groups of people sharing social interactions, social ties, and virtual spaces for interactions. Communities are characterized by shared interests, goals, and norms that unite like-minded individuals (Preece 2000 ; Rheingold 1993 ). Indeed, in a virtual environment people have a tendency toward homophily, that is, to seek for and interact with similar others (Centola and van de Rijt 2015 ; McPherson et al. 2001 ).

Identifying with a virtual community consisting of like-minded people may have important consequences for a user (Kaakinen et al. 2020 ). Identifying with the community’s shared social identity and internalizing its group norms affect user behavior (Zhou 2011 ). Moreover, social media research shows that people often rely on information and content provided by their in-group members (Flanagin et al. 2014 ). Particularly when talking about potentially addictive behaviors, identifying with an online community can influence intentions and attitudes toward harmful direction and normalize maladaptive behavior (Oksanen et al. 2016 ). However, online communities and shared identity may also be beneficial in overcoming an addiction (McNamara and Parsons 2016 ).

In terms of gambling and gaming, online communities cover various kinds of virtual spaces, such as discussion forums and social network sites, where gamblers and gamers can interact with other gamblers and gamers. However, social interaction is not limited to distinct online platforms, as games often also include in-game interactive tools. Video games, in particular, are typically formed around interactive elements, such as communicating with one’s team members during the game, which are not essentially the case in traditional forms of gambling activities (Cole and Griffiths 2007 ; King et al. 2015 ). In particular, Massively Multiplayer Online Role-Playing Games (MMORPGs) are characterized by their community aspects and joint playing. In MMORPGs, gaming typically takes place in “guilds” that can be defined as long-lasting social structures where players are interdependent on each other’s contribution (Zhong 2011 ). Guild playing is also important in terms of a player’s game-related social identity (Guegan et al. 2015 ). In this review, we examine these different virtual spaces and their role in gambling and monetary gaming behaviors in more depth.

Current Study

The aim of this study is to bring additional insight into the gambling and gaming phenomena by investigating the role of online communities in gambling and monetary gaming behaviors. In this review, we adopt a loose definition of online communities (see Kozinets 1999 ; Preece 2000 ; Rheingold 1993 ) to cover various kinds of interactive online platforms for gamblers and gamers.

Some systematic reviews close to our topic have been conducted, for example in terms of online game communities (Warmelink and Siitonen 2013 ) and user participation in different online communities (Malinen 2015 ). However, our focus lies in the social aspects of the online gambling and monetary gaming phenomena. Thus, we aim to synthesize empirical evidence of the key characteristics and the roles of virtual gambling and gaming communities in gambling and monetary gaming behaviors. Since we are specifically interested in the role of virtual communities in gambling and gambling-like behaviors, we narrow our perspective of gaming to cover only gaming involving money. We believe this is reasonable when examining gaming alongside gambling. As we argued earlier, it is meaningful to include both gambling and gaming phenomena because of their combined monetary features; but, as such, we are also able to compare possible differences among these communities. Consequently, the more general role of online communities in gaming is out of our focus.

Our research questions are as follows:

RQ1 What is the role of virtual gambling communities in gambling behavior?

RQ2 What is the role of virtual gaming communities in monetary gaming behavior?

RQ3 Are there notable qualitative differences between virtual gambling and gaming communities?

Data Collection

To answer our research questions, we conducted a conceptual review with a systematic data collection process (e.g., Petticrew and Roberts 2006 , p. 39). The data were collected in two phases: The original search was conducted in July 2018 from five comprehensive databases: Scopus (Elsevier), Web of Science (Clarivate), PsycINFO (APA), Social Science Premium Collection (ProQuest), and EBSCOhost (EBSCO) with all databases selected. The search engines were set to search hits from abstracts, titles, and keywords using the same search phrase in each database: (gambl* OR gaming OR gamer) AND (internet OR online OR virtual OR digital) AND (“online communit*” OR “virtual communit*” OR “online group*” OR “virtual group*” OR “online discuss*” OR “chat room*” OR “online social network*” OR “forum*”). In addition to author keywords, the database keyword indexes were included in the search fields when applicable. Due to the vast amount of magazines and other irrelevant sources in Social Science Premium Collection and EBSCOhost, only scholarly or academic journals were selected using the filtering options within the search engines. We used no other limits in the search engines, for example, year or language. After removing duplicates, the database search resulted in 885 articles.

In order to keep the data up-to-date, we conducted an additional literature search in February 2020, following the same steps and guidelines established in 2018. The search was conducted from the same five databases: Scopus (Elsevier), Web of Science (Clarivate), PsycINFO (APA), Social Science Premium Collection (ProQuest), and EBSCOhost (EBSCO). In databases, the publication time was limited to cover years 2018-2020. After removing duplicates and overlaps with data gathered in 2018, the additional database search resulted in 171 articles.

In both data collection phases, studies were included based on the following criteria. (1) The article empirically examines participation or social interaction in online communities or networks related to gambling or gaming involving money. Participation or interaction can include aspects such as participation frequency, motivation, level of identification, or shared content between users. (2) The article empirically examines behavioral factors associated with participation or social interaction in online community or networks related to gambling or gaming involving money. Behavioral factors can include aspects such as virtual purchase behavior, frequency of gambling or gaming behaviors or other kinds of gambling and gaming behaviors involving money. Consequently, studies were excluded if they did not mention gambling, monetary gaming, or social interaction between gamblers and gamers; if they were theoretical articles or literature reviews; book or conference introductions; or were not published in English.

In the first data collection phase in 2018, two coders independently checked the 885 articles with pre-determined inclusion criteria. An inter-rater reliability test revealed that the average inter-rater agreement was 87.39% (Cohen’s kappa = .61). After this, the first author (not involved in the previous inclusion check) checked the articles that previous coders classified as included by reading the articles thoroughly. Disagreements and borderline cases were discussed within the research team. The final selection check of this first phase resulted in 44 articles (see Fig.  1 ).

Data collection and selection process accomplished in two phases in 2018 and 2020

In the second data collection phase in 2020, two coders independently checked the 171 articles using the same pre-determined inclusion criteria defined in 2018. The average inter-rater agreement was 94.34% (Cohen’s kappa = .58). Disagreements and borderline cases were discussed with the research team. The final selection check of this additional phase resulted in 11 articles. After additional data collection, we obtained a final dataset consisting of 55 articles (see Fig.  1 ).

Method of Analysis

Our aim was to summarize evidence of the role of online gambling and gaming communities in gambling and monetary gaming behaviors. We categorized the articles by characteristics relevant to our research: research type (quantitative or qualitative), sample characteristics, study context, topic (gambling, gaming, or both), and type of virtual community (e.g., discussion forum or in-game community). We used content analysis to summarize the main findings of the studies relevant to our research questions. Due to heterogeneity in terms of study design, participants, measures, and methods, we did not conduct a meta-analysis of the results.

General Details About Published Studies

Studies included in the data ( n  = 55) were published between 2003 and 2020. Out of all the studies, over half (60%) were quantitative, 31% qualitative, and 9% mixed method, utilizing both quantitative and qualitative methods. Over half (60%) of the studies were gaming studies, while 35% were gambling studies, and 5% examined both gambling and gaming. In about half of the studies (48%), respondents were either from multiple countries or the study context was not explicitly mentioned. One reason for this is many of the studies utilized online surveys gathered via international online websites and forums or ethnographic data from online platforms. Regarding specific country locations, most research was conducted in Taiwan (15%), followed by Australia (7%), Finland (5%), and the United States (5%) (see Table  1 ). Main characteristics of the included studies are reported in Table 2 .

Online Gambling Communities

According to the reviewed studies, online gambling communities exist typically outside the game, for example, in the form of discussion forums that are created around gambling discussions. There are gambling forums for mutual gambling discussions, such as sharing gambling tips, strategies, and experiences (Howe et al. 2019 ; O’Leary and Carroll 2013 ; Parke and Griffiths 2011 ; Schüll 2016 ; Sirola et al. 2018 , 2019 ), and also forums for sharing gambling problem experiences and discussing the downsides and related problems of gambling (Caputo 2015 ; Hing et al. 2015 ; Järvinen-Tassopoulos 2016 ; McGowan 2003 ; Mudry and Strong 2013 ; Rantala and Sulkunen 2012 ; Rodda et al. 2018 ; Sirola et al. 2018 , 2019 ; Wood and Wood 2009 ). In addition, there are also some in-game interactional tools, such as chat opportunities, for gamblers, particularly in online poker (Khazaal et al. 2017 ; Schüll 2016 ; Smith et al. 2012 ) and in online social casino games (Gainsbury et al. 2015 ).

Participation in online communities with positive gambling attitudes is a risk factor for excessive gambling (Howe et al. 2019 ; Sirola et al. 2018 , 2019 ). A study by Sirola et al. ( 2019 ) found that sense of loneliness moderated the association between excessive gambling and daily online gambling community participation in Finland, indicating that lonely problem gamblers are most likely to actively participate in such communities. Online poker communities are mostly used for sharing poker experiences and seeking social reinforcement for gambling successes; these kinds of communities may also increase poker playing and help develop cognitive biases concerning gambling (Parke and Griffiths 2011 ). However, there was also some evidence that actively participating in mutual discussion in a gambling community and actively consuming money in online gambling are mutually exclusive activities (Kaptein et al. 2015 ; Lindholm et al. 2012 ). Using longitudinal data of online poker players, it was noticed that when consumers increased their community activity, they also reduced their poker-related consumption (Lindholm et al. 2012 ). In addition, when relatively inactive community members increased their community activity, it was related to increased money consumption, while already active members’ increase in community engagement was related to decreased spending (Kaptein et al. 2015 ).

Online poker players share their poker data and experiences of former games with other poker players in online forums, chat threads, and message boards to get feedback and help to identify flaws in performance; this may also protect from overvaluing one’s poker skills (Schüll 2016 ). Feedback from the community members is considered helpful in developing one’s poker skills, and it may even reduce the risk of problematic gambling, as long as the information provided is accurate (Parke and Griffiths 2011 ). In addition, socializing with other players during online gambling by utilizing in-game interaction tools is associated with less problematic forms of gambling (Khazaal et al. 2017 ; Smith et al. 2012 ). A study by Khazaal et al. ( 2017 ) found that gambling problems were more severe among lonely online gamblers who did not utilize social interaction tools in a game or preferred to gamble against the computer. Thus, it seems that in online poker, utilizing poker communities both in- and outside the game may protect the player from developing excessive poker gambling habits.

Although communities may offer safeguards for poker players, research shows that gambling-related social networks and exposure to the gambling activities of peers may normalize gambling and make it attractive. Gambling-related activities of Facebook friends, such as “liking” social casino games and inviting friends to play, influence users’ intentions to try these gambling or gambling-like activities (Gainsbury et al. 2015 ). In mobile social-network games, the perceived number of users and friends increases the jackpot and purchase intentions of probability-based items (Lee et al. 2018 ). In online sports betting communities, users prefer sharing personal betting results and wagering opinions and predictions with others (Wen et al. 2016 ). Users can also extend their gambling-related networks to share wagering tips and celebrate wins with others; these kinds of gambling-positive discussions may contribute to the normalization of gambling (Deans et al. 2017 ).

Communities focusing on gambling problems have essential roles for those coping with problematic gambling; they may even help with overcoming problems. Discussions on gambling problem forums are grounded in sharing gambling problem experiences and related problems (Caputo 2015 ; Järvinen-Tassopoulos 2016 ; Rantala and Sulkunen 2012 ), and also strategies for getting rid of gambling problems (Rodda et al. 2018 ). From a user’s perspective, these kinds of communities are important sources of mutual support, by helping him or her to better cope with gambling problems and to feel less alone with his or her problems (Wood and Wood 2009 ). However, a survey study from Finland on young respondents aged 15–25 found that the main motivation for respondents to engage in online gambling communities was to share gambling tips and general gambling information, while only a few mentioned discussing gambling problems and recovery (Sirola et al. 2018 ). Also, a study by Hing et al. ( 2015 ) found that online problem gamblers were more reluctant to utilize online support groups or discussion boards compared to land-based problem gamblers.

Gambling communities are grounded on mutual norms, where it is important to conform in order to be accepted as a legitimate member of the community (Mudry and Strong 2013 ; O’Leary and Carroll 2013 ). Communities are also important for a gambler’s identity; poker forums are spaces to construct poker player identities (O’Leary and Carroll 2013 ), but online communities focused on problem gambling can also be utilized in negotiating and (re)constructing problem gambler identities (Järvinen-Tassopoulos 2016 ; Mudry and Strong 2013 ).

There was also some evidence of gender-specific differences in the use of online gambling communities. In a study by Khazaal et al. ( 2017 ), women were less prone to utilize in-game interaction tools; this could be at least partly explained by the male-dominance typically associated with gambling. Since gambling problems have traditionally been more common among males than females, online forums offer a space for female problem gamblers to anonymously share their gambling problem experiences (Järvinen-Tassopoulos 2016 ; McGowan 2003 ; Wood and Wood 2009 ), which can be challenging or intimidating in male-dominated face-to-face groups (McGowan 2003 ). Also, in a study by Wood and Wood ( 2009 ), significantly more women than men found gambling problem forums helpful in coping with their gambling problem.

Online Gaming Communities

According to reviewed studies, online gaming communities inherently exist inside the game. This is especially true with MMORPGs (Badrinarayanan et al. 2014 , 2015 ; Ben-Ur et al. 2015 ; Fang et al. 2009 ; Gui 2018 ; Hota and Derbaix 2016 ; Jin et al. 2017 ; Park et al. 2018 ; Pinto et al. 2015 ). MMORPG playing typically takes place in guilds, that is, long-lasting social groups where players collaborate in order to better game success. In guilds, players share their skills, knowledge, and virtual resources, such as money, with each other (Gui 2018 ; Pinto et al. 2015 ). The player roles in guilds are important in terms of teamwork contributions. An example of this type of contribution would be taking care of a guild bank that is used for sharing common resources, like items and money (Rapp 2018 ). Social interaction with other players is one of the motivating factors in playing (Fang et al. 2009 ), and it may also have positive outcomes for a player’s social capital. Indeed, a study by Hickerson and Mowen ( 2012 ) found that gamers who utilized social bonding in video games reported positive social outcomes, such as friend-based social support.

Perceived group cohesion is an important determinant in a user’s preference for participating in an online game community, and a community’s social norms can affect a customer’s loyalty towards the community (Hsu and Lu 2007 ). Ben-Ur et al. ( 2015 ) suggested that a strong virtual game community intensifies hedonic consumption experience and satisfaction among its members. Lin et al. ( 2008 ) found that women are more likely than men to commit to a game if it utilizes interactional tools to create and maintain social relationships with other gamers; this was also associated with consumer satisfaction and loyalty. According to  M. Kim and J. Kim ( 2018 ), financial incentives (e.g. special price offerings or rewards) in an online game community, alongside with social and structural bonds, play an important role in users’ online community engagement.

Various studies indicated that a game community, either in-game or out-game, has an important role in terms of purchase intentions and consumption behavior within a game. Huang et al. ( 2018 ) found that gamers’ interdependence (i.e. depending on other players’ opinions) and network convergence (i.e. shared friends with other players) were positively related to continuance intention. A study by Zhang et al. ( 2018 ) found that players’ sense of community in game communities is positively associated with purchase behavior. In a study of Pokémon Go users by Ghazali et al. ( 2019 ), discussing the game and sharing experiences in a virtual game community enhanced gaming experience, and online community involvement mediated the relationship between network externality and continuance intention. In terms of MMORPG communities, studies utilizing structural equation modeling illustrated that identifying with a specific MMORPG community drives purchase intention and consumption behavior (Badrinarayanan et al. 2014 , 2015 ). Sierra et al. ( 2016 ) found that becoming attached to a MMORPG community intensifies a player’s tribal psyche associated with the MMORPG, which in turn enhances self-esteem. Further, self-esteem positively influences virtual purchase intentions within the MMORPG. A study by Canossa et al. ( 2019 ) indicated that game networks have a social contagion effect in a way that certain active players serve as influencers in a gaming network. These influencers then impact other players’ gaming habits, such as time and money invested in a game, and social play with others (Canossa et al. 2019 ).

Studies also examined the role of social influence in gaming communities in terms of virtual purchases. According to Hsieh and Tseng ( 2018 ), online informational influence (i.e., relying on online peers’ knowledge of online games and virtual items) directly affects intentions to buy virtual items, and this relationship was also mediated by happiness. In a study by Shukla and Drennan ( 2018 ), it was found that normative interpersonal influence (i.e., conformity in order to be approved by peers) and community identity within the MMORPG community influence virtual purchase intentions. In a study by Chang et al. ( 2014 ), peer-influence was positively associated with subjective norm, and subjective norm was further positively related to continuance intention to play online games. Park et al. ( 2018 ) found that social interaction between users in a MMORPG community positively affects both hedonic and functional product purchases, but social influence has a stronger impact on consumption of hedonic rather than functional products. Hota and Derbaix ( 2016 ) found that even 8–12-year-old children utilize teamwork aspects in their gaming and are susceptible to peer influence in virtual consumption. Observed gaming behavior and social norms of other players may influence excessive gaming behavior through social learning mechanisms (Gong et al. 2019 ). A study by King et al. ( 2020 ) found that in a highly popular online game Fortnite, spending on microtransactions was influenced by in-game friends’ purchase behavior. In addition, those who belonged to a larger online social network of Fortnite players were likely to spend money on microtransactions.

The motives for buying virtual items in online games are functional, hedonistic, and social; virtual items have social value, for example, in terms of social distinction and status (Lehdonvirta 2009 ). Interviews with 8–12-year-old children revealed that boys prefer buying virtual items for better game performance, while girls buy items for social status (Hota and Derbaix 2016 ). According to Gong et al. ( 2019 ), young gamers who play excessively spend lots of money on in-game purchases, which can lead to conflicts with family members.

Players help each other in virtual game communities by giving tips to better game performance (Ben-Ur et al. 2015 ; Hota and Derbaix 2016 ), sharing knowledge of the virtual products (Hota and Derbaix 2016 ), and recommending suitable and discounted games for others (Ben-Ur et al. 2015 ; Vella et al. 2019 ). Symbolic customer value, such as group membership in a game community, positively affects purchase intentions and likelihood to recommend products or services in online word-of-mouth communications (Liao et al. 2012 ). In a study by Huang et al. ( 2012 ), a sense of virtual community moderated the influence of other users’ comments on attitudes and purchase intentions.

Membership of a guild becomes an important and extended part of the identity, which becomes manifested in game-related consumption (Pinto et al. 2015 ). Both technological (i.e., interactivity, social presence) and user factors (i.e., social ties, social identity) have strong positive relationships with the users’ purchase intentions; further, social ties and social identities affect user engagement and community satisfaction (Jin et al. 2017 ).

MMORPGs and their guild-systems are characterized by shared roles (Rapp 2018 ) and mutual norms and policies concerning acceptable gaming behaviors. Malicious and grief (i.e., impolite and unethical) players are perceived as threatening to the community and its playing policies (Hsu and Lu 2007 ). Cheating and scamming in order to gain monetary benefits and virtual items are seen as norm-breaking and are socially sanctioned behaviors within game communities (Blackburn et al. 2014 ; Goodfellow 2015 ). However, in some game communities, such as in Habbo Hotel, scamming and cheating are regarded as normal and harmless activities despite their antisocial nature (Griffiths and Light 2008 ).

In addition to in-game communities, there are also game-related discussion forums where gamers can interact (Ben-Ur et al. 2015 ; Goodfellow 2015 ; Gui 2018 ; Huang et al. 2012 ; Y. B. Kim et al. 2015 , 2017 ). Game forums are important platforms for gamers to share experiences of games, and this kind of word-of-mouth communication may also affect game purchase intentions (Huang et al. 2012 ). In game review forums, gamers give recommendations of games for other players (Ben-Ur et al. 2015 ). In game-specific discussion forums, gamers can discuss all the things related to a specific game and, for example, criticize other players’ playing strategies and habits (Goodfellow 2015 ). Gamers also share their opinions of in-game virtual currencies in game-specific discussion forums, and even currency value fluctuations can be predicted based on these user opinions (Y. B. Kim et al. 2015 ,  2017 ).

Similarities and Differences Between Online Gambling and Gaming Communities

Online gambling and gaming communities have both differences and similarities regarding characteristics, reasons of use, and outcomes of use (see Table  3 ). In gambling studies, online communities are typically discussion forums and other virtual spaces that exist outside a game (Caputo 2015 ; Hing et al. 2015 ; Howe et al. 2019 ; Järvinen-Tassopoulos 2016 ; McGowan 2003 ; Mudry and Strong 2013 ; O’Leary and Carroll 2013 ; Parke and Griffiths 2011 ; Rantala and Sulkunen 2012 ; Rodda et al. 2018 ; Schüll 2016 ; Sirola et al. 2018 , 2019 ; Wood and Wood 2009 ), but also some in-game interaction tools exist particularly in online poker (Khazaal et al. 2017 ; Schüll 2016 ; Smith et al. 2012 ) and in social casino games (Gainsbury et al. 2015 ). Gaming communities, on the other hand, exist inherently embedded inside the game, as is the case particularly in MMORPGs and their guild-based systems (Badrinarayanan et al. 2014 , 2015 ; Ben-Ur et al. 2015 ; Fang et al. 2009 ; Gui 2018 ; Hota and Derbaix 2016 ; Jin et al. 2017 ; Park et al. 2018 ; Pinto et al. 2015 ), but also external communities such as discussion forums exist for gamers (Ben-Ur et al. 2015 ; Y. B. Kim et al. 2015 , 2017 ). Strikingly, at least within this data, no gaming problem forums or communities were identified, as was the case with gambling.

Mutual for both gambling and gaming communities is the importance of their community-specific norm system; being accepted as a legitimate member of the community requires following and conforming to the community’s norms (Blackburn et al. 2014 ; Goodfellow 2015 ; Griffiths and Light 2008 ; Gui 2018 ; Mudry and Strong 2013 ; O’Leary and Carroll 2013 ). Both gambling and gaming communities are also important in gambling- and gaming-related identity constructions (Järvinen-Tassopoulos 2016 ; Mudry and Strong 2013 ; O’Leary and Carroll 2013 ; Pinto et al. 2015 ).

According to the studies reviewed, utilizing in-game interaction and socializing with other players during the game have different functions and outcomes in online gambling and gaming. In gaming studies, there is strong evidence that identifying with in-game communities has a great potential to influence gaming behavior and in-game purchase intentions (Badrinarayanan et al. 2014 , 2015 ; Canossa et al. 2019 ; Ghazali et al. 2019 ; Gong et al. 2019 ; Hota and Derbaix 2016 ; Hsieh and Tseng 2018 ; Huang et al. 2018 ; King et al. 2020 ; Park et al. 2018 ; Shukla and Drennan 2018 ; Sierra et al. 2016 ; Zhang et al. 2018 ). In gambling studies, on the contrary, there is evidence that socializing with other players during a game, particularly in online poker, might be a protective factor, as this kind of social playing was associated with less severe and non-problematic forms of gambling (Khazaal et al. 2017 ; Smith et al. 2012 ). In general, it seems that social motives are more inherently embedded in video gaming compared to online gambling. For example, when interviewing players of social casino games (i.e., gambling-like online games), few of the interviewees mentioned playing for social motives, despite the interactional opportunities of the game (Gainsbury et al. 2015 ); while in video gaming, social interaction with other players is considered an important motive for playing (Fang et al. 2009 ; Hickerson and Mowen 2012 ).

Studies also indicate differences concerning a community’s potential protective role and feedback in terms of excessive gambling or gaming habits. In gambling studies, there was evidence that feedback from an online gambling community could influence gambling behavior to a more moderate direction and protect from overvaluing one’s poker skills (Parke and Griffiths 2011 ; Schüll 2016 ). There was also some evidence that actively contributing in an online gambling community could decrease gambling-related consumption (Kaptein et al. 2015 ; Lindholm et al. 2012 ). On the contrary, there were no studies or results indicating a gaming community’s protective role or critical feedback concerning excessive gaming or in-game purchase behaviors. Instead, studies consistently showed the motivating effect of a gaming community in terms of gaming continuation and purchase intentions.

There was also some evidence concerning gender differences in the use of virtual gambling and gaming communities. In online poker, females did not prefer using in-game interaction tools, while men did (Khazaal et al. 2017 ). Instead, women with a gambling problem found discussion forums important in coping with their gambling-related problems (Järvinen-Tassopoulos 2016 ; Wood and Wood 2009 ). In gaming studies, Lin et al. ( 2008 ) found that women were more likely than men to commit to a game if it provided tools to create and maintain social relationships. However, since the proportion of female participants in the reviewed studies was significantly smaller compared to males, evidence of potential gender differences remains weak.

The aim of this review was to summarize research on online gambling and gaming communities and their role in gambling and monetary gaming behaviors. In total, 55 articles filled the criteria; 60% of them were quantitative, and the rest were either qualitative or mixed method. Out of the articles, 33 were on gaming, 19 on gambling, and only three studies investigated both gambling and gaming. Despite a relatively limited number of studies on this area, the results show that identification with virtual communities has an influential role in gambling and monetary gaming behaviors, but there were also some notable differences in community types and possible outcomes of the community use between gambling and gaming communities.

In line with research on online identity formation (Kaakinen et al. 2020 ; McNamara and Parsons 2016 ), results show that virtual communities are important spaces for gamblers and gamers to construct and extend their identities concerning gambling and gaming with like-minded others. In MMORPGs, virtual game communities are grounded on collaboration, teamwork, and mutual goals, and the communities can become an extended part of the identity. In gambling, poker communities are important spaces for poker players to enhance their poker player identities via social reinforcement and community feedback. For problem gamblers, there are virtual communities to share their experiences with other problem gamblers and receive socio-emotional peer support for dealing with problems. Various studies of this review also pointed out the role of social influence in both gambling and gaming communities, for example, in terms of purchase intentions and trying out new gambling activities. Normalizing and promoting gambling and gambling-like activities in social media can make gambling attractive and encourage excessive gambling habits via social influence and perceived norms (e.g., Cialdini and Goldstein 2004 ).

One notable difference of gambling and gaming communities concerned the communities’ roles in game-related money use and purchase intentions. Whereas studies suggested that feedback from gambling communities can also protect from developing excessive gambling habits, gaming communities seem to solely motivate gaming behaviors and purchase intentions. A possible explanation for the differences is the fundamentally different nature of gambling compared to gaming. Succeeding in gambling, in terms of winning money, is highly individual by nature. Thus, members of a gambling community may be more prone to notice and criticize potentially problematic gambling behavior, as no one else of the community shares the benefits of the gambling success or money invested in gambling other than the gambler. In video gaming, in contrast, success in game and money invested for it could also benefit the community teammates, particularly in MMORPGs where gaming is typically formed around guilds. In other words, if committed to teamwork play, purchasing virtual items are for the community’s good and not solely for the individual’s. Thus, even excessive gaming and money use within the game can be important in terms of a team’s performance and success in the game. This makes it unlikely that members of the community would try to restrain their team players’ gaming activity because it would mean poorer game performance for the team.

Differences also existed concerning the role of in-game interaction. Although both digital games and online gambling games include in-game interaction tools, the role of in-game socialization in gambling and gaming proved to be inherently different. Indeed, it can be suggested based on the results that in online gambling lonely gamblers who do not socialize with other gamblers are more prone to use more money and to develop more severe gambling problems; in other words, social playing was associated with non-problematic forms of gambling. In video gaming, on the other hand, playing in isolation may result in less purchase intention within a game, since identifying with a game community was consistently and positively associated with in-game purchase intentions. Thus, the roles of social interaction and social influence should be taken into consideration when screening for potentially problematic forms of gaming behavior.

It is also noteworthy that while in gambling studies, there were forums for those seeking help for and sharing experiences of gambling problems, there were no studies on communities of problematic gaming in our data. A plausible explanation for the lack or scarcity of these communities is that there is a general lack of consensus on the phenomenon and definition of problematic gaming and whether it can be qualified as an addiction (Griffiths et al. 2015 ). Recently, “gaming disorder” has been included in the latest International Classification of Diseases (ICD-11), and in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V), it is recognized as a condition that requires more research before including it into mental disorders. The proposal of gaming disorder as a diagnosis has aroused a great deal of criticism among scholars due to, for example, low quality of the research base and problems in operationalization (Aarseth et al. 2017 ). However, it may be that if gaming disorder becomes established in general discourses and addiction treatments, gaming problem forums and online self-help groups will become more common.

From a theoretical perspective of virtual communities, the results of this systematic review show that virtual communities in gambling and gaming are grounded on mutual goals, shared interests, and norms. These aspects have been previously noted in studies on online communities (Boellstorff 2015 ; Preece 2000 ; Oksanen et al. 2014 ), and these communities play an important yet different role for gamblers and gamers. Despite some notable differences between gambling and gaming communities, it is clear that both types of communities provide their users virtual spaces to fulfill a fundamental need to belong and form social ties (Baumeister and Leary 1995 ; Deci and Ryan’s 2000 ). Virtual social ties may be valuable for those who have deficient offline relationships, and socialization with online friends is also a significant part of the fun, particularly in video gaming, and may have positive outcomes for a player’s social capital. However, this systematic literature review emphasizes the risks involved. It particularly recognizes the impact communities have, through social mechanisms, on monetary behavior and other potentially harmful consequences. Based on the results, we highlight that more emphasis should be placed in examining online communities’ roles in problematic gambling and gaming habits, particularly in terms of excessive money consumption.

Limitations

This study is not without its limitations. First, it is possible that some relevant articles have been excluded in the search phase due to the search words used. Second, in terms of gaming phenomena, we limited our focus on studies examining gaming with explicitly mentioned monetary behavior. Although microtransactions and gambling-like mechanisms are common business models in the majority of digital games, we did not include studies where monetary behavior was not explicitly mentioned. Online gaming communities and social interactions within them may play various important roles for gamers in general, but this review only focused on a community’s role on monetary gaming behavior, such as virtual purchase intentions. Finally, in this review we studied virtual gambling and gaming communities as factors in gambling and monetary gaming behaviors. Thus, this review does not cover those forms of gambling- or gaming-related virtual interactions and communities whose relationship to actual gambling or gaming behavior remains unstudied.

Although online gambling and gaming are isolated activities in the sense that the player is often physically alone, related virtual communities are an essential part of both activities. Online gambling and gaming communities normalize gambling and gaming behaviors and influence purchase intentions; but at least in gambling, communities may also support moderate forms of gambling, provide socio-emotional support for recovery of addiction and help to cope with a gambling problem. Even though the line between gambling and gaming has become blurred due to increased use of gambling-like mechanisms in digital games, the results of this review indicate that social interactions in these two activities have different functions, and also motives for and outcomes of the interaction differ in terms of monetary behavior.

The role of virtual communities should be acknowledged in prevention and treatment of gambling and gaming problems. In particular, it would be crucial to understand social mechanisms, such as social influence and social learning, taking place in virtual gambling and gaming environments. Raising awareness of social underpinnings and influential mechanisms behind gambling and monetary gaming would be important for players, parents and health care professionals when aiming to reduce excessive behavior and money consumption. Limiting players’ in-game social interaction would be required to reduce excessive money spending, particularly in group- and guild-based gaming, where purchase intention often follows strong belonging or attachment to the community. In gambling, utilizing recovery-oriented virtual communities for problem gamblers would be useful given that such communities are proven to be useful in implementing beneficial aspects of peer-influence, support and anonymity. Finally, improving gamblers’ and gamers’ offline relationships and healthy activities would be crucial in risk-prevention. Meaningful offline relationships and social activities would decrease the need for spending lots of time gambling and gaming online, but also diminish the need for belonging to virtual communities and searching for social contacts online.

References marked with an asterisk (*) indicate studies included in the data

Aarseth, E., Bean, A. M., Boonen, H., Colder Carras, M., Coulson, M., Das, D., et al. (2017). Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal. Journal of Behavioral Addictions, 6 (3), 267–270.

PubMed   PubMed Central   Google Scholar  

*Badrinarayanan, V. A., Sierra, J. J., & Martin, K. M. (2015). A dual identification framework of online multiplayer video games: The case of massively multiplayer online role playing games (MMORPGs). Journal of Business Research, 68 (5), 1045–1052.

Google Scholar  

*Badrinarayanan, V. A., Sierra, J. J., & Taute, H. A. (2014). Determinants and outcomes of online brand tribalism: Exploring communities of massively multiplayer online role playing games (MMORPGs). Psychology and Marketing, 31 (10), 853–870.

Baumeister, R. F., & Leary, M. R. (1995). The need to belong: desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin, 117 (3), 497.

CAS   PubMed   Google Scholar  

*Ben-Ur, J., Mai, E., & Yang, J. (2015). Hedonic consumption in virtual reality. Journal of Internet Commerce, 14 (3), 406–423.

*Blackburn, J., Kourtellis, N., Skvoretz, J., Ripeanu, M., & Iamnitchi, A. (2014). Cheating in online games: A social network perspective. ACM Transactions on Internet Technology (TOIT), 13 (3), 9.

Boellstorff, T. (2015). Coming of age in Second Life: An anthropologist explores the virtually human . Princeton: University Press.

Calado, F., Alexandre, J., & Griffiths, M. D. (2018). Gambling among adolescents and emerging adults: A cross-cultural study between Portuguese and English youth. International Journal of Mental Health and Addiction . https://doi.org/10.1007/s11469-018-9980-y .

Article   Google Scholar  

Calado, F., & Griffiths, M. D. (2016). Problem gambling worldwide: An update and systematic review of empirical research (2000–2015). Journal of Behavioral Addictions, 5 (4), 592–613.

*Canossa, A., Azadvar, A., Harteveld, C., Drachen, A., & Deterding, S. (2019). Influencers in multiplayer online shooters: Evidence of social contagion in playtime and social play. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1–12).

*Caputo, A. (2015). Sharing problem gamblers’ experiences: a text analysis of gambling stories via online forum. Mediterranean Journal of Clinical Psychology, 3 (1), 1–26.

Centola, D., & van de Rijt, A. (2015). Choosing your network: Social preferences in an online health community. Social Science and Medicine, 125, 19–31.

PubMed   Google Scholar  

*Chang, I. C., Liu, C. C., & Chen, K. (2014). The effects of hedonic/utilitarian expectations and social influence on continuance intention to play online games. Internet Research, 24 (1), 21–45.

Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621.

Cole, H., & Griffiths, M. D. (2007). Social interactions in massively multiplayer online role-playing gamers. Cyberpsychology and Behavior, 10 (4), 575–583.

*Deans, E. G., Thomas, S. L., Daube, M., & Derevensky, J. (2017). The role of peer influences on the normalisation of sports wagering: A qualitative study of Australian men. Addiction Research and Theory, 25 (2), 103–113.

Deci, E. L., & Ryan, R. M. (2000). The ‘what’ and ‘why’ of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227–268.

*Fang, K., Lin, Y. C., & Chuang, T. L. (2009). Why do internet users play massively multiplayer online role-playing games? A mixed method. Management Decision, 47 (8), 1245–1260.

Flanagin, A. J., Hocevar, K. P., & Samahito, S. N. (2014). Connecting with the user-generated Web: how group identification impacts online information sharing and evaluation. Information, Communication and Society, 17 (6), 683–694.

Forrest, C. J., King, D. L., & Delfabbro, P. H. (2016). The gambling preferences and behaviors of a community sample of Australian regular video game players. Journal of Gambling Studies, 32 (2), 409–420.

*Gainsbury, S. M., Hing, N., Delfabbro, P., Dewar, G., & King, D. L. (2015). An exploratory study of interrelationships between social casino gaming, gambling, and problem gambling. International Journal of Mental Health and Addiction, 13 (1), 136–153.

*Ghazali, E. M., Mutum, D. S., & Woon, M. Y. (2019). Multiple sequential mediation in an extended uses and gratifications model of augmented reality game Pokémon Go. Internet Research, 29 (3), 504–528.

*Gong, X., Zhang, K. Z., Chen, C., Cheung, C. M., & Lee, M. K. (2019). Antecedents and consequences of excessive online social gaming: A social learning perspective. Information Technology and People, 33 (2), 657–688.

*Goodfellow, C. (2015). Russian overlords, Vodka, and Logoffski: Russian-and English-language discourse about anti-Russian Xenophobia in the EVE Online community. Games and Culture, 10 (4), 343–364.

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.

*Griffiths, M., & Light, B. (2008). Social networking and digital gaming media convergence: Classification and its consequences for appropriation. Information Systems Frontiers, 10 (4), 447–459.

Guegan, J., Moliner, P., & Buisine, S. (2015). Why are online games so self-involving: A social identity analysis of massively multiplayer online role-playing games. European Journal of Social Psychology, 45 (3), 349–355.

*Gui, D. A. F. (2018). Virtual sense of community in a world of Warcraft ® storytelling open forum thread. Journal for Virtual Worlds Research , 11 (2), 1–17.

CAS   Google Scholar  

*Hickerson, B., & Mowen, A. J. (2012). Behavioral and psychological involvement of online video gamers: Building blocks or building walls to socialization. Loisir et Société/Society and Leisure, 35 (1), 79–103.

*Hing, N., Russell, A. M. T., Gainsbury, S. M., & Blaszczynski, A. (2015). Characteristics and help-seeking behaviors of internet gamblers based on most problematic mode of gambling. Journal of Medical Internet Research, 17 (1), e13.

*Hota, M., & Derbaix, M. (2016). A real child in a virtual world: Exploring whether children’s participation in MMORPGs transforms them into virtual retail shoppers. International Journal of Retail and Distribution Management, 44 (11), 1132–1148.

*Howe, P. D., Vargas-Sáenz, A., Hulbert, C. A., & Boldero, J. M. (2019). Predictors of gambling and problem gambling in Victoria, Australia. PLoS ONE, 14 (1), e0209277.

CAS   PubMed   PubMed Central   Google Scholar  

*Hsieh, J. K., & Tseng, C. Y. (2018). Exploring social influence on hedonic buying of digital goods: Online games’ virtual items. Journal of Electronic Commerce Research, 19 (2), 164–185.

*Hsu, C. L., & Lu, H. P. (2007). Consumer behavior in online game communities: A motivational factor perspective. Computers in Human Behavior, 23 (3), 1642–1659.

*Huang, H. C., Cheng, T. C. E., Huang, W. F., & Teng, C. I. (2018). Impact of online gamers’ personality traits on interdependence, network convergence, and continuance intention: Perspective of social exchange theory. International Journal of Information Management, 38 (1), 232–242.

*Huang, J. H., Hsiao, T. T., & Chen, Y. F. (2012). The effects of electronic word of mouth on product judgment and choice: The moderating role of the sense of virtual community. Journal of Applied Social Psychology, 42 (9), 2326–2347.

Jacques, C., Fortin-Guichard, D., Bergeron, P. Y., Boudreault, C., Lévesque, D., & Giroux, I. (2016). Gambling content in Facebook games: A common phenomenon? Computers in Human Behavior, 57, 48–53.

*Järvinen-Tassopoulos, J. (2016). Problem gambling and drinking among Finnish women. Nordic Studies on Alcohol and Drugs, 33 (1), 27–42.

*Jin, W., Sun, Y., Wang, N., & Zhang, X. (2017). Why users purchase virtual products in MMORPG? An integrative perspective of social presence and user engagement. Internet Research, 27 (2), 408–427.

Kaakinen, M., Sirola, A., Savolainen, I., & Oksanen, A. (2020). Shared identity and shared information in social media: Development and validation of the identity bubble reinforcement scale. Media Psychology , 23 (1), 25–51.

*Kaptein, M., Parvinen, P., & Pöyry, E. (2015). The danger of engagement: Behavioral observations of online community activity and service spending in the online gaming context. International Journal of Electronic Commerce, 20 (1), 50–75.

Keipi, T., & Oksanen, A. (2014). Self-exploration, anonymity and risks in the online setting: Analysis of narratives by 14–18-year olds. Journal of Youth Studies, 17 (8), 1097–1113.

*Khazaal, Y., Chatton, A., Achab, S., Monney, G., Thorens, G., Dufour, M., et al. (2017). Internet gamblers differ on social variables: A latent class analysis. Journal of Gambling Studies, 33 (3), 881–897.

Kim, H. S., Hollingshead, S., & Wohl, M. J. (2017). Who spends money to play for free? Identifying who makes micro-transactions on social casino games (and why). Journal of Gambling Studies, 33 (2), 525–538.

*Kim, Y. B., Kang, K., Choo, J., Kang, S. J., Kim, T., Im, J., et al. (2017). Predicting the currency market in online gaming via lexicon-based analysis on its online forum. Complexity , 2017 , article ID 4152705.

*Kim, M., & Kim, J. (2018). The effects of perceived online justice on relational bonds and engagement intention: Evidence from an online game community. Computers in Human Behavior, 84, 410–419.

*Kim, Y. B., Lee, S. H., Kang, S. J., Choi, M. J., Lee, J., & Kim, C. H. (2015). Virtual world currency value fluctuation prediction system based on user sentiment analysis. PLoS ONE, 10 (8), e0132944.

King, D. L., & Delfabbro, P. H. (2016). Early exposure to digital simulated gambling: A review and conceptual model. Computers in Human Behavior, 55, 198–206.

King, D., Delfabbro, P., & Griffiths, M. (2010). The convergence of gambling and digital media: Implications for gambling in young people. Journal of Gambling Studies, 26 (2), 175–187.

King, D. L., Delfabbro, P. H., Kaptsis, D., & Zwaans, T. (2014). Adolescent simulated gambling via digital and social media: An emerging problem. Computers in Human Behavior, 31, 305–313.

King, D. L., Gainsbury, S. M., Delfabbro, P. H., Hing, N., & Abarbanel, B. (2015). Distinguishing between gaming and gambling activities in addiction research. Journal of Behavioral Addictions, 4 (4), 215–220.

*King, D. L., Russell, A. M., Delfabbro, P. H., & Polisena, D. (2020). Fortnite microtransaction spending was associated with peers’ purchasing behaviors but not gaming disorder symptoms. Addictive Behaviors, 104, 106311.

Kozinets, R. V. (1999). E-tribalized marketing? The strategic implications of virtual communities of consumption. European Management Journal, 17 (3), 252–264.

*Lee, J., Suh, E., Park, H., & Lee, S. (2018). Determinants of users’ intention to purchase probability-based items in mobile social network games: A case of South Korea. IEEE Access, 6, 12425–12437.

*Lehdonvirta, V. (2009). Virtual item sales as a revenue model: Identifying attributes that drive purchase decisions. Electronic Commerce Research, 9 (1–2), 97–113.

*Liao, S. H., Wu, C. C., Widowati, R., & Chen, M. Y. (2012). Relationships between brand awareness and online word-of-mouth: An example of online gaming community. International Journal of Web Based Communities, 8 (2), 177–195.

*Lin, W. K., Chiu, C. K., & Tsai, Y. H. (2008). Modeling relationship quality and consumer loyalty in virtual communities. Cyberpsychology and Behavior, 11 (5), 561–564.

*Lindholm, J., Kaptein, M., & Parvinen, P. (2012). The tradeoff between online community activity and consumption: evidence from online poker. In 2012 45th Hawaii international conference on system sciences (pp. 3238–3246). IEEE.

Macey, J., & Hamari, J. (2018). Investigating relationships between video gaming, spectating esports, and gambling. Computers in Human Behavior, 80, 344–353.

Malinen, S. (2015). Understanding user participation in online communities: A systematic literature review of empirical studies. Computers in Human Behavior, 46, 228–238.

*McGowan, V. (2003). Counter-story, resistance and reconciliation in online narratives of women in recovery from problem gambling. International Gambling Studies, 3 (2), 115–131.

McKenna, K. Y., & Bargh, J. A. (1999). Causes and consequences of social interaction on the Internet: A conceptual framework. Media Psychology, 1 (3), 249–269.

McNamara, N., & Parsons, H. (2016). ‘Everyone here wants everyone else to get better’: The role of social identity in eating disorder recovery. British Journal of Social Psychology, 55 (4), 662–680.

McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27 (1), 415–444.

*Mudry, T. E., & Strong, T. (2013). Doing recovery online. Qualitative Health Research, 23 (3), 313–325.

*O’Leary, K., & Carroll, C. (2013). The online poker sub-culture: Dialogues, interactions and networks. Journal of Gambling Studies, 29 (4), 613–630.

Oksanen, A., Garcia, D., & Räsänen, P. (2016). Proanorexia communities on social media. Pediatrics, 137 (1), e20153372.

Oksanen, A., Hawdon, J., & Räsänen, P. (2014). Glamorizing rampage online: School shooting fan communities on YouTube. Technology in Society, 39, 55–67.

Oksanen, A., Savolainen, I., Sirola, A., & Kaakinen, M. (2018). Problem gambling and psychological distress: A cross-national perspective on the mediating effect of consumer debt and debt problems among emerging adults. Harm Reduction Journal, 15 (1), 45.

Paavilainen, J., Hamari, J., Stenros, J., & Kinnunen, J. (2013). Social network games: Players’ perspectives. Simulation and Gaming, 44 (6), 794–820.

*Park, E., Rishika, R., Janakiraman, R., Houston, M. B., & Yoo, B. (2018). Social dollars in online communities: The effect of product, user, and network characteristics. Journal of Marketing, 82 (1), 93–114.

*Parke, A., & Griffiths, M. D. (2011). Poker gambling virtual communities: The use of Computer-Mediated Communication to develop cognitive poker gambling skills. International Journal of Cyber Behavior, Psychology and Learning (IJCBPL), 1 (2), 31–44.

Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide . Oxford: Wiley.

*Pinto, D. C., Reale, G., Segabinazzi, R., & Vargas Rossi, C. A. (2015). Online identity construction: How gamers redefine their identity in experiential communities. Journal of Consumer Behaviour, 14 (6), 399–409.

Preece, J. (2000). Online communities: Designing usability and supporting sociability . New York: Wiley.

*Rantala, V., & Sulkunen, P. (2012). Is pathological gambling just a big problem or also an addiction? Addiction Research and Theory, 20 (1), 1–10.

*Rapp, A. (2018). Social game elements in world of warcraft: Interpersonal relations, groups, and organizations for gamification design. International Journal of Human-Computer Interaction, 34 (8), 759–773.

Reich, S., & Vorderer, P. (2013). Individual differences in need to belong in users of social networking sites. In P. Moy (Ed.), Communication and community (pp. 129–148). New York: Hampton Press.

Rheingold, H. (1993). The virtual community: Finding connection in a computerized world . Reading: Addison-Wesley Longman Publishing Co., Inc.

*Rodda, S. N., Hing, N., Hodgins, D. C., Cheetham, A., Dickins, M., & Lubman, D. I. (2018). Behaviour change strategies for problem gambling: An analysis of online posts. International Gambling Studies, 18 (3), 420–438.

*Schüll, N. D. (2016). Abiding chance: Online poker and the software of self-discipline. Public Culture, 28 (3 (80)), 563–592.

*Shukla, P., & Drennan, J. (2018). Interactive effects of individual-and group-level variables on virtual purchase behavior in online communities. Information and Management, 55 (5), 598–607.

*Sierra, J. J., Badrinarayanan, V. A., & Taute, H. A. (2016). Explaining behavior in brand communities: A sequential model of attachment, tribalism, and self-esteem. Computers in Human Behavior, 55, 626–632.

*Sirola, A., Kaakinen, M., & Oksanen, A. (2018). Excessive gambling and online gambling communities. Journal of Gambling Studies, 34 (4), 1313–1325.

*Sirola, A., Kaakinen, M., Savolainen, I., & Oksanen, A. (2019). Loneliness and online gambling-community participation of young social media users. Computers in Human Behavior, 95, 136–145.

*Smith, M. D., Rousu, M. C., & Dion, P. (2012). Internet poker: examining motivations, behaviors, outcomes, and player traits using structural equations analysis. Journal of Gambling Issues, 27, 1–23.

*Vella, K., Klarkowski, M., Turkay, S., & Johnson, D. (2019). Making friends in online games: Gender differences and designing for greater social connectedness. Behaviour and Information Technology . https://doi.org/10.1080/0144929X.2019.1625442 .

Warmelink, H., & Siitonen, M. (2013). A decade of research into player communities in online games. Journal of Gaming and Virtual Worlds, 5 (3), 271–293.

*Wen, Y. F., Hung, K. Y., Hwang, Y. T., & Lin, Y. S. F. (2016). Sports lottery game prediction system development and evaluation on social networks. Internet Research, 26 (3), 758–788.

Williams, K. D., Cheung, C. K., & Choi, W. (2000). Cyberostracism: Effects of being ignored over the Internet. Journal of Personality and Social Psychology, 79 (5), 748–762.

*Wood, R. T., & Wood, S. A. (2009). An evaluation of two United Kingdom online support forums designed to help people with gambling issues. Journal of Gambling Issues, 23, 5–30.

Zendle, D., & Cairns, P. (2018). Video game loot boxes are linked to problem gambling: Results of a large-scale survey. PLoS ONE, 13 (11), e0206767.

*Zhang, Y., Wang, J., Wang, Y., & He, Y. (2018). Research on effect of virtual community internet interaction to online purchasing behavior. In 2018 4th international conference on information management (ICIM) (pp. 66–70). IEEE.

Zhong, Z. J. (2011). The effects of collective MMORPG (Massively Multiplayer Online Role-Playing Games) play on gamers’ online and offline social capital. Computers in Human Behavior, 27 (6), 2352–2363.

Zhou, T. (2011). Understanding online community user participation: A social influence perspective. Internet Research, 21 (1), 67–81.

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Sirola, A., Savela, N., Savolainen, I. et al. The Role of Virtual Communities in Gambling and Gaming Behaviors: A Systematic Review. J Gambl Stud 37 , 165–187 (2021). https://doi.org/10.1007/s10899-020-09946-1

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Published on 23.4.2024 in Vol 26 (2024)

Electronic Media Use and Sleep Quality: Updated Systematic Review and Meta-Analysis

Authors of this article:

• Xiaoning Han * , PhD   ; 
• Enze Zhou * , MA   ; 
• Dong Liu * , PhD  

School of Journalism and Communication, Renmin University of China, Beijing, China

*all authors contributed equally

Corresponding Author:

Dong Liu, PhD

School of Journalism and Communication

Renmin University of China

No. 59 Zhongguancun Street, Haidian District

Beijing, 100872

Phone: 86 13693388506

Email: [email protected]

Background: This paper explores the widely discussed relationship between electronic media use and sleep quality, indicating negative effects due to various factors. However, existing meta-analyses on the topic have some limitations.

Objective: The study aims to analyze and compare the impacts of different digital media types, such as smartphones, online games, and social media, on sleep quality.

Methods: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the study performed a systematic meta-analysis of literature across multiple databases, including Web of Science, MEDLINE, PsycINFO, PubMed, Science Direct, Scopus, and Google Scholar, from January 2018 to October 2023. Two trained coders coded the study characteristics independently. The effect sizes were calculated using the correlation coefficient as a standardized measure of the relationship between electronic media use and sleep quality across studies. The Comprehensive Meta-Analysis software (version 3.0) was used to perform the meta-analysis. Statistical methods such as funnel plots were used to assess the presence of asymmetry and a p -curve test to test the p -hacking problem, which can indicate publication bias.

Results: Following a thorough screening process, the study involved 55 papers (56 items) with 41,716 participants from over 20 countries, classifying electronic media use into “general use” and “problematic use.” The meta-analysis revealed that electronic media use was significantly linked with decreased sleep quality and increased sleep problems with varying effect sizes across subgroups. A significant cultural difference was also observed in these effects. General use was associated with a significant decrease in sleep quality ( P <.001). The pooled effect size was 0.28 (95% CI 0.21-0.35; k =20). Problematic use was associated with a significant increase in sleep problems ( P ≤.001). The pooled effect size was 0.33 (95% CI 0.28-0.38; k =36). The subgroup analysis indicated that the effect of general smartphone use and sleep problems was r =0.33 (95% CI 0.27-0.40), which was the highest among the general group. The effect of problematic internet use and sleep problems was r =0.51 (95% CI 0.43-0.59), which was the highest among the problematic groups. There were significant differences among these subgroups (general: Q between =14.46, P =.001; problematic: Q between =27.37, P <.001). The results of the meta-regression analysis using age, gender, and culture as moderators indicated that only cultural difference in the relationship between Eastern and Western culture was significant ( Q between =6.69; P =.01). All funnel plots and p -curve analyses showed no evidence of publication and selection bias.

Conclusions: Despite some variability, the study overall confirms the correlation between increased electronic media use and poorer sleep outcomes, which is notably more significant in Eastern cultures.

Introduction

Sleep is vital to our health. Research has shown that high sleep quality can lead to improvements in a series of health outcomes, such as an improved immune system, better mood and mental health, enhanced physical performance, lower risk of chronic diseases, and a longer life span [ 1 - 5 ].

Electronic media refers to forms of media or communication that use electronic devices or technology to create, distribute, and display content. This can include various forms of digital media such as smartphones, tablets, instant messaging, phone calls, social media, online games, short video platforms, etc. Electronic media has permeated every aspect of our lives [ 6 ]. Many prefer to use smartphones or tablets before sleep, which can negatively affect sleep in many aspects, including delayed sleep onset, disrupted sleep patterns, shortened sleep duration, and poor sleep quality [ 7 - 10 ]. Furthermore, problematic use occurs when the behavior surpasses a certain limit. In this study, problematic use of electronic media is not solely determined by the amount of time spent on these platforms, but rather by behavioral indicators that suggest an unhealthy or harmful relationship with them.

Smartphones or tablet use can affect sleep quality in many ways. At first, the use of these devices may directly displace, delay, or interrupt sleep time, resulting in inadequate sleep quantity [ 11 ]. The sound of notifications and vibrations of these devices may interrupt sleep. Second, the screens of smartphones and tablets emit blue light, which can suppress the production of melatonin, the hormone responsible for regulating sleep-wake cycles [ 12 ]. Third, consuming emotionally charged content, such as news, suspenseful movies, or engaging in online arguments, can increase emotional arousal, making it harder to relax and fall asleep. This emotional arousal can also lead to disrupted sleep and nightmares [ 13 ]. Finally, the use of electronic devices before bedtime can lead to a delay in bedtime and a shortened sleep duration, as individuals may lose track of time while engaging with their devices. This can result in a disrupted sleep routine and decreased sleep quality [ 14 ].

Some studies have conducted meta-analyses on screen media use and sleep outcomes in 2016, 2019, and 2021 [ 15 - 17 ]. However, these studies had their own limitations. First, the sample size included in their meta-analyses was small (around 10). Second, these studies only focused on 1 aspect of the effect of digital media on sleep quality. For example, Carter et al [ 16 ] focused only on adolescents, and both Alimoradi et al [ 15 ] and Kristensen et al [ 17 ] only reviewed the relationship between problematic use of digital media or devices and sleep quality. Despite of the high heterogeneity found in the meta-analyses, none have compared the effects of different digital media or devices. This study aims to clarify and compare the effects of these different channels.

Literature Search

The research adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines ( Multimedia Appendix 1 ) and followed a predetermined protocol [ 18 , 19 ]. As the idea and scope of this study evolved over time, the meta-analysis was not preregistered. However, the methodology was defined a priori and strictly followed to reduce biases, and the possible influence of post hoc decisions was minimized. All relevant studies in English, published from January 1, 2018, to October 9, 2023, were searched. We searched the following databases: Web of Science, MEDLINE, PsycINFO, PubMed, Science Direct, Scopus, and Google Scholar. The abstracts were examined manually. The keywords used to search were the combination of the following words: “sleep” OR “sleep duration” OR “sleep quality” OR “sleep problems” AND “electronic media” OR “smartphone” OR “tablet” OR “social media” OR “Facebook” OR “Twitter” OR “online gaming” OR “internet” OR “addiction” OR “problematic” ( Multimedia Appendix 2 ). Additionally, the reference lists of relevant studies were examined.

Two trained coders independently screened the titles and abstracts of the identified papers for eligibility, followed by a full-text review of the selected studies. Discrepancies between the coders were resolved through discussion until a consensus was reached. The reference lists of the included studies were also manually screened to identify any additional relevant studies. Through this rigorous process, we ensured a comprehensive and replicable literature search that could contribute to the robustness of our meta-analysis findings.

Inclusion or Exclusion Criteria

Titles and abstracts from search results were scrutinized for relevance, with duplicates removed. Full texts of pertinent papers were obtained, and their eligibility for inclusion was evaluated. We mainly included correlational studies that used both continuous measures of time spent using electronic media use and sleep quality. Studies must have been available in English. Four criteria were used to screen studies: (1) only peer-reviewed empirical studies, published in English, were considered for inclusion in the meta-analysis; (2) the studies should report quantitative statistics on electronic media use and sleep quality, including sample size and essential information to calculate the effect size, and review papers, qualitative studies, case studies, and conference abstracts were excluded; (3) studies on both general use and problematic use of electronic media or devices should be included; and (4) only studies that used correlation, regression, or odds ratio were included to ensure consistency.

Study Coding

Two trained coders were used to code the characteristics of the studies independently. Discrepancies were discussed with the first author of the paper to resolve. Sample size and characteristics of participants were coded: country, female ratio, average age, publication year, and electronic types. Effect sizes were either extracted directly from the original publications or manually calculated. If a study reported multiple dependent effects, the effects were merged into one. If a study reported multiple independent effects from different samples, the effects were included separately. Additionally, to evaluate the study quality, the papers were classified into 3 tiers (high, middle, and low) according to Journal Citation Reports 2022 , a ranking of journals based on their impact factor as reported in the Web of Science. The few unindexed papers were rated based on their citation counts as reported in Google Scholar.

Meta-Analysis and Moderator Analyses

The effect sizes were calculated using the correlation coefficient ( r ) as a standardized measure of the relationship between electronic media or device use and sleep quality across studies. When studies reported multiple effect sizes, we selected the one that best represented the overall association between electronic media use and sleep quality. If studies did not provide correlation coefficients, we converted other reported statistics (eg, standardized regression coefficients) into correlation coefficients using established formulas. Once calculated, the correlation coefficients were transformed into Fisher z scores to stabilize the variance and normalize the distribution.

Previous meta-studies have shown high levels of heterogeneity. Hence, the random effects model was adopted for all analyses. To explore potential factors contributing to the heterogeneity and to further understand the relationship between electronic media use and sleep quality, we conducted moderator analyses. The following categorical and continuous moderators were examined: media types (online gaming, social media, smartphone, or intent), participants’ average age, culture, female ratio, and sleep quality assessment method. For categorical moderators, subgroup analyses were performed, while for continuous moderators, meta-regression analyses were conducted. All analyses were completed in the Comprehensive Meta-Analysis software (version 3.0; Biostat, Inc).

Publication Bias

We used statistical methods such as funnel plots to assess the presence of asymmetry and a p -curve test to test the p -hacking problem, which may indicate publication bias. In case of detected asymmetry, we applied techniques such as the trim-and-fill method to adjust the effect size estimates.

By addressing publication bias, we aimed to provide a more accurate and reliable synthesis of the available evidence, enhancing the validity and generalizability of our meta-analytic findings. Nevertheless, it is essential for readers to interpret the results cautiously, considering the potential limitations imposed by publication bias and other methodological concerns.

Search Findings

A total of 98,806 studies were identified from databases, especially Scopus (n=49,643), Google Scholar (n=18,600), Science Direct (n=15,084), and Web of Science (n=11,689). Upon removing duplicate records and excluding studies that did not meet the inclusion criteria, 754 studies remained for the screening phase. After screening titles, abstracts, and full texts, 703 studies were excluded. A total of 4 additional studies were identified from the references of relevant reviews. Finally, 55 studies [ 20 - 74 ] were included in the meta-analysis. The flow diagram of the selection is shown in Figure 1 .

Characteristics of Included Studies

In 20 studies, 21,594 participants were included in the analysis of the general use of electronic media and sleep quality. The average age of the sample ranged from 9.9 to 44 years. The category of general online gaming and sleep quality included 4 studies, with 14,837 participants; the category of general smartphone use and sleep quality included 10 studies, with 5011 participants; and the category of general social media use and sleep quality included 6 studies, with 1746 participants.

These studies came from the following countries or areas: Germany, Serbia, Indonesia, India, China, Italy, Saudi Arabia, New Zealand, the United Kingdom, the United States, Spain, Qatar, Egypt, Argentina, and Portugal. The most frequently used measure of electronic media use was the time spent on it. The most frequently used measure of sleep was the Pittsburgh Sleep Quality Index.

In 35 studies, 20,122 participants were included in the analysis of the problematic use of electronic media and sleep quality. The average age of the sample ranged from 14.76 to 65.62 years. The category of problematic online gaming and sleep quality included 5 studies, with 1874 participants; the category of problematic internet use and sleep quality included 2 studies, with 774 participants; the category of problematic smartphone use and sleep quality included 18 studies, with 12,204 participants; and the category of problematic social media use and sleep quality included 11 studies, with 5270 participants. There was a study that focused on both social media and online gaming, which led to its inclusion in the analysis. These studies came from 14 countries or areas: Turkey, the United States, Indonesia, China, France, Taiwan, India, South Korea, Hong Kong, Iran, Poland, Israel, Hungary, and Saudi Arabia. The most frequently used measures of problematic electronic media use were the Internet Gaming Disorder Scale-Short Form, Smartphone Addiction Scale-Short Form, and Bergen Social Media Addiction Scale.

With respect to study quality, the 56 papers were published in 50 journals, 41 of which were indexed in Journal Citation Reports 2022 , while the remaining 9 journals were rated based on their citation counts as reported in Google Scholar. As a result, of the 56 papers included in the study, 22 papers were assigned a high rating, 18 papers were assigned a middle rating, and 16 papers were assigned a low rating. More information about the included studies is listed in Multimedia Appendix 3 [ 20 - 74 ].

Meta-Analysis

The results of the meta-analysis of the relationship between general electronic media use and sleep quality showed that electronic media use was associated with a significant decrease in sleep quality ( P <.001). The pooled effect size was 0.28 (95% CI 0.21-0.35; k =20), indicating that individuals who used electronic media more frequently were generally associated with more sleeping problems.

The second meta-analysis showed that problematic electronic media use was associated with a significant increase in sleep problems ( P ≤.001). The pooled effect size was 0.33 (95% CI 0.28-0.38; k =36), indicating that participants who used electronic media more frequently were more likely to have more sleep problems.

Moderator Analyses

At first, we conducted subgroup analyses for different media or devices. The results are shown in Tables 1 and 2 . The effect of the relationship between general online gaming and sleep problems was r =0.14 (95% CI 0.06-0.22); the effect of the relationship between general smartphone use and sleep problems was r =0.33 (95% CI 0.27-0.40); and the effect of the relationship between general social media use and sleep problems was r =0.28 (95% CI 0.21-0.34). There are significant differences among these groups ( Q between =14.46; P =.001).

The effect of the relationship between problematic gaming and sleep problems was r =0.49, 95% CI 0.23-0.69; the effect of the relationship between problematic internet use and sleep problems was r =0.51 (95% CI 0.43-0.59); the effect of the relationship between problematic smartphone use and sleep problems was r =0.25 (95% CI 0.20-0.30); and the effect of the relationship between problematic social media use and sleep problems was r =0.35 (95% CI 0.29-0.40). There are significant differences among these groups ( Q between =27.37; P <.001).

We also used age, gender, and culture as moderators to conduct meta-regression analyses. The results are shown in Tables 3 and 4 . Only cultural difference in the relationship between Eastern and Western culture was significant ( Q between =6.694; P =.01). All other analyses were not significant.

a Not applicable.

All funnel plots of the analyses were symmetrical, showing no evidence of publication bias ( Figures 2 - 5 ). We also conducted p -curve analyses to see whether there were any selection biases. The results also showed that there were no biases.

Principal Findings

This study indicated that electronic media use was significantly linked with decreased sleep quality and increased sleep problems with varying effect sizes across subgroups. General use was associated with a significant decrease in sleep quality. Problematic use was associated with a significant increase in sleep problems. A significant cultural difference was also observed by the meta-regression analysis.

First, there is a distinction in the impact on sleep quality between problematic use and general use, with the former exhibiting a higher correlation strength. However, both have a positive correlation, suggesting that the deeper the level of use, the more sleep-related issues are observed. In addressing this research question, the way in which electronic media use is conceptualized and operationalized may have a bearing on the ultimate outcomes. Problematic use is measured through addiction scales, while general use is predominantly assessed by duration of use (time), leading to divergent results stemming from these distinct approaches. The key takeaway is that each measurement possesses unique strengths and weaknesses, and the pathways affecting sleep quality differ. Consequently, the selection of a measurement approach should be tailored to the specific research question at hand. The duration of general use reflects an individual’s comprehensive involvement with electronic media, and its impact on sleep quality is evident in factors such as an extended time to fall asleep and reduced sleep duration. The addiction scale for problematic use illuminates an individual’s preferences, dependencies, and other associations with electronic media. Its impact on sleep quality is evident through physiological and psychological responses, including anxiety, stress, and emotional reactions.

Second, notable variations exist in how different types of electronic media affect sleep quality. In general, the positive predictive effects of smartphone, social media, and online gaming use durations on sleep problems gradually decrease. In the problematic context, the intensity of addiction to the internet and online gaming has the most significant positive impact on sleep problems, followed by social media, while smartphones exert the least influence. On one hand, longitudinal comparisons within the same context reveal that the content and format of electronic media can have varying degrees of negative impact on sleep quality, irrespective of whether it involves general or problematic use. On the other hand, cross-context comparisons suggest that both general and problematic use play a role in moderating the impact of electronic media types on sleep quality. As an illustration, problematic use reinforces the positive impact of online gaming and social media on sleep problems, while mitigating the influence of smartphones. Considering smartphones as electronic media, an extended duration of general use is associated with lower sleep quality. However, during problematic use, smartphones serve as the platform for other electronic media such as games and social media, resulting in a weakened predictive effect on sleep quality. Put differently, in the context of problematic use, the specific type of electronic media an individual consumes on their smartphones becomes increasingly pivotal in shaping sleep quality.

Third, cultural differences were found to be significant moderators of the relationship between electronic media use and sleep problems in both our study and Carter et al [ 16 ]. Kristensen et al [ 17 ], however, did not specifically address the role of cultural differences but revealed that there was a strong and consistent association between bedtime media device use and sleep outcomes across the studies included. Our findings showed that the association between problematic social media use was significantly larger in Eastern culture. We speculate that the difference may be attributed to cultural differences in social media use patterns, perceptions of social norms and expectations, variations in bedtime routines and habits, and diverse coping mechanisms for stress. These speculations warrant further investigation to understand better the underlying factors contributing to the observed cultural differences in the relationship between social media use and sleep quality.

Fourth, it was observed that gender and age had no significant impact on sleep quality. The negative effects of electronic media use are not only confined to the sleep quality of adults, and the association with gender differences remains unclear. Recent studies point out that electronic media use among preschoolers may result in a “time-shifting” process, disrupting their sleep patterns [ 75 ]. Similarly, children and adolescent sleep patterns have been reported to be adversely affected by electronic media use [ 76 - 78 ]. These findings underscore the necessity of considering age group variations in future research, as electronic media use may differently impact sleep quality across age demographics.

In conclusion, our study, Carter et al [ 16 ], and Kristensen et al [ 17 ] collectively emphasize the importance of understanding and addressing the negative impact of electronic media use, particularly problematic online gaming and smartphone use, on sleep quality and related issues. Further research is warranted to explore the underlying mechanisms and specific factors contributing to the relationship between electronic media use and sleep problems.

Strengths and Limitations

Our study, supplemented with research by Carter et al [ 16 ] and Kristensen et al [ 17 ], contributes to the growing evidence supporting a connection between electronic media use and sleep quality. We found that both general and problematic use of electronic media correlates with sleep issues, with the strength of the correlation varying based on the type of electronic media and cultural factors, with no significant relationship observed with age or gender.

Despite the vast amount of research on the relationship between electronic media use and sleep, several gaps and limitations still exist.

First, the inclusion criteria were restricted to English-language, peer-reviewed empirical studies published between January 2018 and October 2023. This may have led to the exclusion of relevant studies published in other languages or before 2018, potentially limiting the generalizability of our findings. Furthermore, the exclusion of non–peer-reviewed studies and conference abstracts may have introduced publication bias, as significant results are more likely to be published in peer-reviewed journals.

Second, although we used a comprehensive search strategy, the possibility remains that some relevant studies may have been missed. Additionally, the search strategies were not linked with Medical Subject Headings headers and may not have captured all possible electronic media types, resulting in an incomplete representation of the effects of electronic media use on sleep quality.

Third, the studies included in our meta-analysis exhibited considerable heterogeneity in sample characteristics, electronic media types, and measures of sleep quality. This heterogeneity might have contributed to the variability in effect sizes observed across studies. Although we conducted moderator analyses to explore potential sources of heterogeneity, other unexamined factors may still have influenced the relationship between electronic media use and sleep quality.

Fourth, our meta-analysis relied on the correlation coefficient ( r ) as the primary effect size measure, which may not fully capture the complex relationships between electronic media use and sleep quality. Moreover, the conversion of other reported statistics into correlation coefficients could introduce additional sources of error. The correlational nature of the included studies limited our ability to draw causal inferences between electronic media use and sleep quality. Experimental and longitudinal research designs would provide stronger evidence for the directionality of this relationship.

Given these limitations, future research should aim to include a more diverse range of studies, examine additional potential moderators, and use more robust research designs to better understand the complex relationship between electronic media use and sleep quality.

Conclusions

In conclusion, our updated meta-analysis affirms the consistent negative impact of electronic media use on sleep outcomes, with problematic online gaming and smartphone use being particularly impactful. Notably, the negative effect of problematic social media use on sleep quality appears more pronounced in Eastern cultures. This research emphasizes the need for public health initiatives to increase awareness of these impacts, particularly for adolescents. Further research, including experimental and longitudinal studies, is necessary to delve deeper into the complex relationship between electronic media use and sleep quality, considering potential moderators like cultural differences.

Acknowledgments

This research was supported by the Journalism and Marxism Research Center, Renmin University of China (MXG202215), and by funds for building world-class universities (disciplines) of Renmin University of China (23RXW195).

A statement on the use of ChatGPT in the process of writing this paper can be found in Multimedia Appendix 4.

Data Availability

The data sets analyzed during this study are available from the corresponding author on reasonable request.

Conflicts of Interest

None declared.

PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 checklist.

Search strategies.

Characteristics of included studies.

Large language model statement.

• Brink-Kjaer A, Leary EB, Sun H, Westover MB, Stone KL, Peppard PE, et al. Age estimation from sleep studies using deep learning predicts life expectancy. NPJ Digit Med. 2022;5(1):103. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Killgore WDS. Effects of sleep deprivation on cognition. Prog Brain Res. 2010;185:105-129. [ CrossRef ] [ Medline ]
• Lee S, Mu CX, Wallace ML, Andel R, Almeida DM, Buxton OM, et al. Sleep health composites are associated with the risk of heart disease across sex and race. Sci Rep. 2022;12(1):2023. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Prather AA. Sleep, stress, and immunity. In: Grandner MA, editor. Sleep and Health, 1st Edition. Cambridge. Academic Press; 2019;319-330.
• Scott AJ, Webb TL, Martyn-St James M, Rowse G, Weich S. Improving sleep quality leads to better mental health: a meta-analysis of randomised controlled trials. Sleep Med Rev. Dec 2021;60:101556. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Guttmann A. Statista. 2023. URL: https://www.statista.com/topics/1536/media-use/#topicOverview [accessed 2023-06-10]
• Hysing M, Pallesen S, Stormark KM, Jakobsen R, Lundervold AJ, Sivertsen B. Sleep and use of electronic devices in adolescence: results from a large population-based study. BMJ Open. Feb 02, 2015;5(1):e006748. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Lavender RM. Electronic media use and sleep quality. Undergrad J Psychol. 2015;28(1):55-62. [ FREE Full text ]
• Exelmans L, Van den Bulck J. Bedtime mobile phone use and sleep in adults. Soc Sci Med. 2016;148:93-101. [ CrossRef ] [ Medline ]
• Twenge JM, Krizan Z, Hisler G. Decreases in self-reported sleep duration among U.S. adolescents 2009-2015 and association with new media screen time. Sleep Med. 2017;39:47-53. [ CrossRef ] [ Medline ]
• Exelmans L. Electronic media use and sleep: a self-control perspective. Curr Sleep Med Rep. 2019;5:135-140. [ CrossRef ]
• Jniene A, Errguig L, El Hangouche AJ, Rkain H, Aboudrar S, El Ftouh M, et al. Perception of sleep disturbances due to bedtime use of blue light-emitting devices and its impact on habits and sleep quality among young medical students. Biomed Res Int. 2019;2019:7012350. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Munezawa T, Kaneita Y, Osaki Y, Kanda H, Minowa M, Suzuki K, et al. The association between use of mobile phones after lights out and sleep disturbances among Japanese adolescents: a nationwide cross-sectional survey. Sleep. 2011;34(8):1013-1020. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Smith LJ, Gradisar M, King DL, Short M. Intrinsic and extrinsic predictors of video-gaming behaviour and adolescent bedtimes: the relationship between flow states, self-perceived risk-taking, device accessibility, parental regulation of media and bedtime. Sleep Med. 2017;30:64-70. [ CrossRef ] [ Medline ]
• Alimoradi Z, Lin CY, Broström A, Bülow PH, Bajalan Z, Griffiths MD, et al. Internet addiction and sleep problems: a systematic review and meta-analysis. Sleep Med Rev. 2019;47:51-61. [ CrossRef ] [ Medline ]
• Carter B, Rees P, Hale L, Bhattacharjee D, Paradkar MS. Association between portable screen-based media device access or use and sleep outcomes: a systematic review and meta-analysis. JAMA Pediatr. 2016;170(12):1202-1208. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kristensen JH, Pallesen S, King DL, Hysing M, Erevik EK. Problematic gaming and sleep: a systematic review and meta-analysis. Front Psychiatry. 2021;12:675237. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Akçay D, Akçay BD. The effect of computer game playing habits of university students on their sleep states. Perspect Psychiatr Care. 2020;56(4):820-826. [ CrossRef ] [ Medline ]
• Alahdal WM, Alsaedi AA, Garrni AS, Alharbi FS. The impact of smartphone addiction on sleep quality among high school students in Makkah, Saudi Arabia. Cureus. 2023;15(6):e40759. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alam A, Alshakhsi S, Al-Thani D, Ali R. The role of objectively recorded smartphone usage and personality traits in sleep quality. PeerJ Comput Sci. 2023;9:e1261. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Almeida F, Marques DR, Gomes AA. A preliminary study on the association between social media at night and sleep quality: the relevance of FOMO, cognitive pre-sleep arousal, and maladaptive cognitive emotion regulation. Scand J Psychol. 2023;64(2):123-132. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alshobaili FA, AlYousefi NA. The effect of smartphone usage at bedtime on sleep quality among Saudi non-medical staff at King Saud University Medical City. J Family Med Prim Care. 2019;8(6):1953-1957. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Alsulami A, Bakhsh D, Baik M, Merdad M, Aboalfaraj N. Assessment of sleep quality and its relationship to social media use among medical students. Med Sci Educ. 2019;29(1):157-161. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Altintas E, Karaca Y, Hullaert T, Tassi P. Sleep quality and video game playing: effect of intensity of video game playing and mental health. Psychiatry Res. 2019;273:487-492. [ CrossRef ] [ Medline ]
• Asbee J, Slavish D, Taylor DJ, Dietch JR. Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students. J Sleep Res. 2023;32(4):e13844. [ CrossRef ] [ Medline ]
• Bae ES, Kang HS, Lee HN. The mediating effect of sleep quality in the relationship between academic stress and social network service addiction tendency among adolescents. J Korean Acad Community Health Nurs. 2020;31(3):290-299. [ FREE Full text ] [ CrossRef ]
• Chatterjee S, Kar SK. Smartphone addiction and quality of sleep among Indian medical students. Psychiatry. 2021;84(2):182-191. [ CrossRef ] [ Medline ]
• Chung JE, Choi SA, Kim KT, Yee J, Kim JH, Seong JW, et al. Smartphone addiction risk and daytime sleepiness in Korean adolescents. J Paediatr Child Health. 2018;54(7):800-806. [ CrossRef ] [ Medline ]
• Demir YP, Sumer MM. Effects of smartphone overuse on headache, sleep and quality of life in migraine patients. Neurosciences (Riyadh). 2019;24(2):115-121. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Dewi RK, Efendi F, Has EMM, Gunawan J. Adolescents' smartphone use at night, sleep disturbance and depressive symptoms. Int J Adolesc Med Health. 2018;33(2):20180095. [ CrossRef ] [ Medline ]
• Eden A, Ellithorpe ME, Meshi D, Ulusoy E, Grady SM. All night long: problematic media use is differentially associated with sleep quality and depression by medium. Commun Res Rep. 2021;38(3):143-149. [ CrossRef ]
• Ellithorpe ME, Meshi D, Tham SM. Problematic video gaming is associated with poor sleep quality, diet quality, and personal hygiene. Psychol Pop Media. 2023;12(2):248-253. [ CrossRef ]
• Elsheikh AA, Elsharkawy SA, Ahmed DS. Impact of smartphone use at bedtime on sleep quality and academic activities among medical students at Al -Azhar University at Cairo. J Public Health (Berl.). Jun 15, 2023.:1-10. [ FREE Full text ] [ CrossRef ]
• Gaya AR, Brum R, Brites K, Gaya A, de Borba Schneiders L, Duarte Junior MA, et al. Electronic device and social network use and sleep outcomes among adolescents: the EHDLA study. BMC Public Health. 2023;23(1):919. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Gezgin DM. Understanding patterns for smartphone addiction: age, sleep duration, social network use and fear of missing out. Cypriot J Educ Sci. 2018;13(2):166-177. [ CrossRef ]
• Graham S, Mason A, Riordan B, Winter T, Scarf D. Taking a break from social media improves wellbeing through sleep quality. Cyberpsychol Behav Soc Netw. 2021;24(6):421-425. [ CrossRef ] [ Medline ]
• Guerrero MD, Barnes JD, Chaput JP, Tremblay MS. Screen time and problem behaviors in children: exploring the mediating role of sleep duration. Int J Behav Nutr Phys Act. 2019;16(1):105. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hamvai C, Kiss H, Vörös H, Fitzpatrick KM, Vargha A, Pikó BF. Association between impulsivity and cognitive capacity decrease is mediated by smartphone addiction, academic procrastination, bedtime procrastination, sleep insufficiency and daytime fatigue among medical students: a path analysis. BMC Med Educ. 2023;23(1):537. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Herlache AD, Lang KM, Krizan Z. Withdrawn and wired: problematic internet use accounts for the link of neurotic withdrawal to sleep disturbances. Sleep Sci. 2018;11(2):69-73. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Huang Q, Li Y, Huang S, Qi J, Shao T, Chen X, et al. Smartphone use and sleep quality in chinese college students: a preliminary study. Front Psychiatry. 2020;11:352. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hussain Z, Griffiths MD. The associations between problematic social networking site use and sleep quality, attention-deficit hyperactivity disorder, depression, anxiety and stress. Int J Ment Health Addict. 2021;19:686-700. [ FREE Full text ] [ CrossRef ]
• Imani V, Ahorsu DK, Taghizadeh N, Parsapour Z, Nejati B, Chen HP, et al. The mediating roles of anxiety, depression, sleepiness, insomnia, and sleep quality in the association between problematic social media use and quality of life among patients with cancer. Healthcare (Basel). 2022;10(9):1745. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Jeong CY, Seo YS, Cho EH. The effect of SNS addiction tendency on trait-anxiety and quality of sleep in university students'. J Korean Clin Health Sci. 2018;6(2):1147-1155. [ CrossRef ]
• Karaş H, Küçükparlak İ, Özbek MG, Yılmaz T. Addictive smartphone use in the elderly: relationship with depression, anxiety and sleep quality. Psychogeriatrics. 2023;23(1):116-125. [ CrossRef ] [ Medline ]
• Kater MJ, Schlarb AA. Smartphone usage in adolescents: motives and link to sleep disturbances, stress and sleep reactivity. Somnologie. 2020;24(4):245-252. [ CrossRef ]
• Kharisma AC, Fitryasari R, Rahmawati PD. Online games addiction and the decline in sleep quality of college student gamers in the online game communities in Surabaya, Indonesia. Int J Psychosoc Rehabil. 2020;24(7):8987-8993. [ FREE Full text ] [ CrossRef ]
• Kumar VA, Chandrasekaran V, Brahadeeswari H. Prevalence of smartphone addiction and its effects on sleep quality: a cross-sectional study among medical students. Ind Psychiatry J. 2019;28(1):82-85. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Lee Y, Blebea J, Janssen F, Domoff SE. The impact of smartphone and social media use on adolescent sleep quality and mental health during the COVID-19 pandemic. Hum Behav Emerg Technol. 2023;2023:3277040. [ FREE Full text ] [ CrossRef ]
• Li L, Griffiths MD, Mei S, Niu Z. Fear of missing out and smartphone addiction mediates the relationship between positive and negative affect and sleep quality among Chinese university students. Front Psychiatry. 2020;11:877. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Li Y, Mu W, Sun C, Kwok SYCL. Surrounded by smartphones: relationship between peer phubbing, psychological distress, problematic smartphone use, daytime sleepiness, and subjective sleep quality. Appl Res Qual Life. 2023;18:1099-1114. [ CrossRef ]
• Luo X, Hu C. Loneliness and sleep disturbance among first-year college students: the sequential mediating effect of attachment anxiety and mobile social media dependence. Psychol Sch. 2022;59(9):1776-1789. [ CrossRef ]
• Luqman A, Masood A, Shahzad F, Shahbaz M, Feng Y. Untangling the adverse effects of late-night usage of smartphone-based SNS among university students. Behav Inf Technol. 2021;40(15):1671-1687. [ CrossRef ]
• Makhfudli, Aulia A, Pratiwi A. Relationship intensity of social media use with quality of sleep, social interaction, and self-esteem in urban adolescents in Surabaya. Sys Rev Pharm. 2020;11(5):783-788. [ CrossRef ]
• Ozcan B, Acimis NM. Sleep quality in Pamukkale university students and its relationship with smartphone addiction. Pak J Med Sci. 2021;37(1):206-211. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Peltz JS, Bodenlos JS, Kingery JN, Abar C. Psychological processes linking problematic smartphone use to sleep disturbance in young adults. Sleep Health. 2023;9(4):524-531. [ CrossRef ] [ Medline ]
• Pérez-Chada D, Bioch SA, Schönfeld D, Gozal D, Perez-Lloret S, Sleep in Adolescents Collaborative Study Group. Screen use, sleep duration, daytime somnolence, and academic failure in school-aged adolescents. PLoS One. 2023;18(2):e0281379. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Przepiorka A, Blachnio A. The role of Facebook intrusion, depression, and future time perspective in sleep problems among adolescents. J Res Adolesc. 2020;30(2):559-569. [ CrossRef ] [ Medline ]
• Rudolf K, Bickmann P, Froböse I, Tholl C, Wechsler K, Grieben C. Demographics and health behavior of video game and eSports players in Germany: the eSports study 2019. Int J Environ Res Public Health. 2020;17(6):1870. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Sami H, Danielle L, Lihi D, Elena S. The effect of sleep disturbances and internet addiction on suicidal ideation among adolescents in the presence of depressive symptoms. Psychiatry Res. 2018;267:327-332. [ CrossRef ] [ Medline ]
• Scott H, Woods HC. Fear of missing out and sleep: cognitive behavioural factors in adolescents' nighttime social media use. J Adolesc. 2018;68:61-65. [ CrossRef ] [ Medline ]
• Spagnoli P, Balducci C, Fabbri M, Molinaro D, Barbato G. Workaholism, intensive smartphone use, and the sleep-wake cycle: a multiple mediation analysis. Int J Environ Res Public Health. 2019;16(19):3517. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Stanković M, Nešić M, Čičević S, Shi Z. Association of smartphone use with depression, anxiety, stress, sleep quality, and internet addiction. empirical evidence from a smartphone application. Pers Individ Differ. Jan 2021;168:110342. [ CrossRef ]
• Tandon A, Kaur P, Dhir A, Mäntymäki M. Sleepless due to social media? investigating problematic sleep due to social media and social media sleep hygiene. Comput Hum Behav. Dec 2020;113:106487. [ FREE Full text ] [ CrossRef ]
• Wang PY, Chen KL, Yang SY, Lin PH. Relationship of sleep quality, smartphone dependence, and health-related behaviors in female junior college students. PLoS One. 2019;14(4):e0214769. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wang Q, Zhong Y, Zhao G, Song R, Zeng C. Relationship among content type of smartphone use, technostress, and sleep difficulty: a study of university students in China. Educ Inf Technol. Aug 02, 2022;28(2):1697-1714. [ CrossRef ]
• Wong HY, Mo HY, Potenza MN, Chan MNM, Lau WM, Chui TK, et al. Relationships between severity of internet gaming disorder, severity of problematic social media use, sleep quality and psychological distress. Int J Environ Res Public Health. 2020;17(6):1879. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Xie X, Dong Y, Wang J. Sleep quality as a mediator of problematic smartphone use and clinical health symptoms. J Behav Addict. 2018;7(2):466-472. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Yang SY, Chen KL, Lin PH, Wang PY. Relationships among health-related behaviors, smartphone dependence, and sleep duration in female junior college students. Soc Health Behav. 2019;2(1):26-31. [ FREE Full text ] [ CrossRef ]
• Yıldırım M, Öztürk A, Solmaz F. Fear of COVID-19 and sleep problems in Turkish young adults: mediating roles of happiness and problematic social networking sites use. Psihologija. 2023;56(4):497-515. [ FREE Full text ] [ CrossRef ]
• Zhai X, Ye M, Wang C, Gu Q, Huang T, Wang K, et al. Associations among physical activity and smartphone use with perceived stress and sleep quality of Chinese college students. Mental Health and Physical Activity. Mar 2020;18:100323. [ CrossRef ]
• Zhang MX, Wu AMS. Effects of smartphone addiction on sleep quality among Chinese university students: the mediating role of self-regulation and bedtime procrastination. Addict Behav. 2020;111:106552. [ CrossRef ] [ Medline ]
• Zhang MX, Zhou H, Yang HM, Wu AMS. The prospective effect of problematic smartphone use and fear of missing out on sleep among Chinese adolescents. Curr Psychol. May 24, 2021;42(7):5297-5305. [ CrossRef ]
• Beyens I, Nathanson AI. Electronic media use and sleep among preschoolers: evidence for time-shifted and less consolidated sleep. Health Commun. 2019;34(5):537-544. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Mazurek MO, Engelhardt CR, Hilgard J, Sohl K. Bedtime electronic media use and sleep in children with autism spectrum disorder. J Dev Behav Pediatr. 2016;37(7):525-531. [ CrossRef ] [ Medline ]
• King DL, Delfabbro PH, Zwaans T, Kaptsis D. Sleep interference effects of pathological electronic media use during adolescence. Int J Ment Health Addict. 2014;12:21-35. [ CrossRef ]
• Kubiszewski V, Fontaine R, Rusch E, Hazouard E. Association between electronic media use and sleep habits: an eight-day follow-up study. Int J Adolesc Youth. 2013;19(3):395-407. [ FREE Full text ] [ CrossRef ]

Abbreviations

Edited by G Eysenbach, T Leung; submitted 20.04.23; peer-reviewed by M Behzadifar, F Estévez-López, R Prieto-Moreno; comments to author 18.05.23; revised version received 15.06.23; accepted 26.03.24; published 23.04.24.

©Xiaoning Han, Enze Zhou, Dong Liu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Does Video Gaming Have Impacts on the Brain: Evidence from a Systematic Review

Denilson brilliant t..

1 Department of Biomedicine, Indonesia International Institute for Life Sciences (i3L), East Jakarta 13210, Indonesia

2 Smart Ageing Research Center (SARC), Tohoku University, Sendai 980-8575, Japan; pj.ca.ukohot@iur (R.N.); pj.ca.ukohot@atuyr (R.K.)

3 Department of Cognitive Health Science, Institute of Development, Aging and Cancer (IDAC), Tohoku University, Sendai 980-8575, Japan

Ryuta Kawashima

4 Department of Functional Brain Imaging, Institute of Development, Aging and Cancer (IDAC), Tohoku University, Sendai 980-8575, Japan

Video gaming, the experience of playing electronic games, has shown several benefits for human health. Recently, numerous video gaming studies showed beneficial effects on cognition and the brain. A systematic review of video gaming has been published. However, the previous systematic review has several differences to this systematic review. This systematic review evaluates the beneficial effects of video gaming on neuroplasticity specifically on intervention studies. Literature research was conducted from randomized controlled trials in PubMed and Google Scholar published after 2000. A systematic review was written instead of a meta-analytic review because of variations among participants, video games, and outcomes. Nine scientific articles were eligible for the review. Overall, the eligible articles showed fair quality according to Delphi Criteria. Video gaming affects the brain structure and function depending on how the game is played. The game genres examined were 3D adventure, first-person shooting (FPS), puzzle, rhythm dance, and strategy. The total training durations were 16–90 h. Results of this systematic review demonstrated that video gaming can be beneficial to the brain. However, the beneficial effects vary among video game types.

1. Introduction

Video gaming refers to the experience of playing electronic games, which vary from action to passive games, presenting a player with physical and mental challenges. The motivation to play video games might derive from the experience of autonomy or competing with others, which can explain why video gaming is pleasurable and addictive [ 1 ].

Video games can act as “teachers” depending on the game purpose [ 2 ]. Video gaming has varying effects depending on the game genre. For instance, an active video game can improve physical fitness [ 3 , 4 , 5 , 6 ], whereas social video games can improve social behavior [ 7 , 8 , 9 ]. The most interesting results show that playing video games can change cognition and the brain [ 10 , 11 , 12 , 13 ].

Earlier studies have demonstrated that playing video games can benefit cognition. Cross-sectional and longitudinal studies have demonstrated that the experience of video gaming is associated with better cognitive function, specifically in terms of visual attention and short-term memory [ 14 ], reaction time [ 15 ], and working memory [ 16 ]. Additionally, some randomized controlled studies show positive effects of video gaming interventions on cognition [ 17 , 18 ]. Recent meta-analytical studies have also supported the positive effects of video gaming on cognition [ 10 , 11 , 12 , 13 ]. These studies demonstrate that playing video games does provide cognitive benefits.

The effects of video gaming intervention are ever more widely discussed among scientists [ 13 ]. A review of the results and methodological quality of recently published intervention studies must be done. One systematic review of video gaming and neural correlates has been reported [ 19 ]. However, the technique of neuroimaging of the reviewed studies was not specific. This systematic review reviewed only magnetic resonance imaging (MRI) studies in contrast to the previous systematic review to focus on neuroplasticity effect. Neuroplasticity is capability of the brain that accommodates adaptation for learning, memorizing, and recovery purposes [ 19 ]. In normal adaptation, the brain is adapting to learn, remember, forget, and repair itself. Recent studies using MRI for brain imaging techniques have demonstrated neuroplasticity effects after an intervention, which include cognitive, exercise, and music training on the grey matter [ 20 , 21 , 22 , 23 , 24 ] and white matter [ 25 , 26 , 27 , 28 , 29 ]. However, the molecular mechanisms of the grey and white matter change remain inconclusive. The proposed mechanisms for the grey matter change are neurogenesis, gliogenesis, synaptogenesis, and angiogenesis, whereas those for white matter change are myelin modeling and formation, fiber organization, and angiogenesis [ 30 ]. Recent studies using MRI technique for brain imaging have demonstrated video gaming effects on neuroplasticity. Earlier imaging studies using cross-sectional and longitudinal methods have shown that playing video games affects the brain structure by changing the grey matter [ 31 , 32 , 33 ], white matter [ 34 , 35 ], and functional connectivity [ 36 , 37 , 38 , 39 ]. Additionally, a few intervention studies have demonstrated that playing video games changed brain structure and functions [ 40 , 41 , 42 , 43 ].

The earlier review also found a link between neural correlates of video gaming and cognitive function [ 19 ]. However, that review used both experimental and correlational studies and included non-healthy participants, which contrasts to this review. The differences between this and the previous review are presented in Table 1 . This review assesses only experimental studies conducted of healthy participants. Additionally, the cross-sectional and longitudinal studies merely showed an association between video gaming experiences and the brain, showing direct effects of playing video games in the brain is difficult. Therefore, this systematic review specifically examined intervention studies. This review is more specific as it reviews intervention and MRI studies on healthy participants. The purposes of this systematic review are therefore to evaluate the beneficial effects of video gaming and to assess the methodological quality of recent video gaming intervention studies.

Differences between previous review and current review.

CT, computed tomography; fMRI, functional magnetic resonance imaging; MEG, magnetoencephalography MRI, magnetic resonance imaging; PET, positron emission tomography; SPECT, single photon emission computed tomography; tDCS, transcranial direct current stimulation; EEG, electroencephalography; NIRS, near-infrared spectroscopy.

2. Materials and Methods

2.1. search strategy.

This systematic review was designed in accordance with the PRISMA checklist [ 44 ] shown in Appendix Table A1 . A literature search was conducted using PubMed and Google Scholar to identify relevant studies. The keywords used for the literature search were combinations of “video game”, “video gaming”, “game”, “action video game”, “video game training”, “training”, “play”, “playing”, “MRI”, “cognitive”, “cognition”, “executive function”, and “randomized control trial”.

2.2. Inclusion and Exclusion Criteria

The primary inclusion criteria were randomized controlled trial study, video game interaction, and MRI/fMRI analysis. Studies that qualified with only one or two primary inclusions were not included. Review papers and experimental protocols were also not included. The secondary inclusion criteria were publishing after 2000 and published in English. Excluded were duration of less than 4 weeks or unspecified length intervention or combination intervention. Also excluded were studies of cognition-based games, and studies of participants with psychiatric, cognitive, neurological, and medical disorders.

2.3. Quality Assessment

Each of the quality studies was assessed using Delphi criteria [ 45 ] with several additional elements [ 46 ]: details of allocation methods, adequate descriptions of control and training groups, statistical comparisons between control and training groups, and dropout reports. The respective total scores (max = 12) are shown in Table 3. The quality assessment also includes assessment for risk of bias, which is shown in criteria numbers 1, 2, 5, 6, 7, 9, and 12.

2.4. Statistical Analysis

Instead of a meta-analysis study, a systematic review of the video game training/video gaming and the effects was conducted because of the variation in ranges of participant age, video game genre, control type, MRI and statistical analysis, and training outcomes. Therefore, the quality, inclusion and exclusion, control, treatment, game title, participants, training period, and MRI analysis and specification of the studies were recorded for the respective games.

The literature search made of the databases yielded 140 scientific articles. All scientific articles were screened based on inclusion and exclusion criteria. Of those 140 scientific articles, nine were eligible for the review [ 40 , 41 , 42 , 43 , 47 , 48 , 49 , 50 , 51 ]. Video gaming effects are listed in Table 2 .

Summary of beneficial effect of video gaming.

Duration was converted into weeks (1 month = 4 weeks); DLPFC, dorsolateral prefrontal cortex; GM, grey matter; FPS, first person shooting. * Participants were categorized based on how they played during the video gaming intervention.

We excluded 121 articles: 46 were not MRI studies, 16 were not controlled studies, 38 were not intervention studies, 13 were review articles, and eight were miscellaneous, including study protocols, non-video gaming studies, and non-brain studies. Of 18 included scientific articles, nine were excluded. Of those nine excluded articles, two were cognitive-based game studies, three were shorter than 4 weeks in duration or were without a specified length intervention, two studies used a non-healthy participant treatment, and one was a combination intervention study. A screening flowchart is portrayed in Figure 1 .

Flowchart of literature search.

3.1. Quality Assessment

The assessment methodology based on Delphi criteria [ 45 ] for the quality of eligible studies is presented in Table 3 . The quality scores assigned to the studies were 3–9 (mean = 6.10; S.D. = 1.69). Overall, the studies showed fair methodological quality according to the Delphi criteria. The highest quality score of the nine eligible articles was assigned to “Playing Super Mario 64 increases hippocampal grey matter in older adult” published by West et al. in 2017, which scored 9 of 12. The scores assigned for criteria 6 (blinded care provider) and 7 (blinded patient) were lowest because of unspecified information related to blinding for those criteria. Additionally, criteria 2 (concealed allocation) and 5 (blinding assessor) were low because only two articles specified that information. All articles met criteria 3 and 4 adequately.

Methodological quality of eligible studies.

Q1, Random allocation; Q2, Concealed allocation; Q3, Similar baselines among groups; Q4, Eligibility specified; Q5, Blinded assessor outcome; Q6, Blinded care provider; Q7, Blinded patient; Q8, Intention-to-treat analysis; Q9, Detail of allocation method; Q10, Adequate description of each group; Q11, Statistical comparison between groups; Q12, Dropout report (1, specified; 0, unspecified).

3.2. Inclusion and Exclusion

Most studies included participants with little or no experience with gaming and excluded participants with psychiatric/mental, neurological, and medical illness. Four studies specified handedness of the participants and excluded participants with game training experience. The inclusion and exclusion criteria are presented in Table 4 .

Inclusion and exclusion criteria for eligible studies.

i1, Little/no experience in video gaming; i2, Right-handed; i3, Sex-specific; e1, Psychiatric/mental illness; e2, Neurological illness; e3, Medical illness; e4, MRI contraindication; e5, experience in game training.

3.3. Control Group

Nine eligible studies were categorized as three types based on the control type. Two studies used active control, five studies used passive control, and two studies used both active and passive control. A summary of the control group is presented in Table 5 .

Control group examined eligible studies.

3.4. Game Title and Genre

Of the nine eligible studies, four used the same 3D adventure game with different game platforms, which were “Super Mario 64” original and the DS version. One study used first-person shooting (FPS) shooting games with many different game titles: “Call of Duty” is one title. Two studies used puzzle games: “Tetris” and “Professor Layton and The Pandora’s Box.” One study used a rhythm dance game: Dance Revolution. One study used a strategy game: “Space Fortress.” Game genres are presented in Table 6 .

Genres and game titles of video gaming intervention.

* West et al. used multiple games; other games are Call of Duty 2, 3, Black Ops, and World at War, Killzone 2 and 3, Battlefield 2, 3, and 4, Resistance 2 and Fall of Man, and Medal of Honor.

3.5. Participants and Sample Size

Among the nine studies, one study examined teenage participants, six studies included young adult participants, and two studies assessed older adult participants. Participant information is shown in Table 7 . Numbers of participants were 20–75 participants (mean = 43.67; S.D. = 15.63). Three studies examined female-only participants, whereas six others used male and female participants. Six studies with female and male participants had more female than male participants.

Participant details of eligible studies.

3.6. Training Period and Intensity

The training period was 4–24 weeks (mean = 11.49; S.D. = 6.88). One study by Lee et al. had two length periods and total hours because the study examined video game training of two types. The total training hours were 16–90 h (mean = 40.63; S.D. = 26.22), whereas the training intensity was 1.5–10.68 h/week (mean = 4.96; S.D. = 3.00). One study did not specify total training hours. Two studies did not specify the training intensity. The training periods and intensities are in Table 8 .

Periods and intensities of video gaming intervention.

The training length was converted into weeks (1 month = 4 weeks). ns, not specified; n/a, not available; * exact length is not available.

3.7. MRI Analysis and Specifications

Of nine eligible studies, one study used resting-state MRI analysis, three studies (excluding that by Haier et al. [ 40 ]) used structural MRI analysis, and five studies used task-based MRI analysis. A study by Haier et al. used MRI analyses of two types [ 40 ]. A summary of MRI analyses is presented in Table 9 . The related resting-state, structural, and task-based MRI specifications are presented in Table 10 , Table 11 and Table 12 respectively.

MRI analysis details of eligible studies.

* Haier et al. conducted structural and task analyses. + Compared pre-training and post-training between groups without using contrast. TFCE, Threshold Free Cluster Enhancement; FEW, familywise error rate; FDR, false discovery rate.

Resting-State MRI specifications of eligible studies.

Structural MRI specifications of eligible studies.

Task-Based MRI specifications of eligible studies.

All analyses used 3 Tesla magnetic force; TR = repetition time; TE = echo time, ns = not specified.

4. Discussion

This literature review evaluated the effect of noncognitive-based video game intervention on the cognitive function of healthy people. Comparison of studies is difficult because of the heterogeneities of participant ages, beneficial effects, and durations. Comparisons are limited to studies sharing factors.

4.1. Participant Age

Video gaming intervention affects all age categories except for the children category. The exception derives from a lack of intervention studies using children as participants. The underlying reason for this exception is that the brain is still developing until age 10–12 [ 52 , 53 ]. Among the eligible studies were a study investigating adolescents [ 40 ], six studies investigating young adults [ 41 , 42 , 43 , 47 , 49 , 51 ] and two studies investigating older adults [ 48 , 50 ].

Differences among study purposes underlie the differences in participant age categories. The study by Haier et al. was intended to study adolescents because the category shows the most potential brain changes. The human brain is more sensitive to synaptic reorganization during the adolescent period [ 54 ]. Generally, grey matter decreases whereas white matter increases during the adolescent period [ 55 , 56 ]. By contrast, the cortical surface of the brain increases despite reduction of grey matter [ 55 , 57 ]. Six studies were investigating young adults with the intention of studying brain changes after the brain reaches maturity. The human brain reaches maturity during the young adult period [ 58 ]. Two studies were investigating older adults with the intention of combating difficulties caused by aging. The human brain shrinks as age increases [ 56 , 59 ], which almost invariably leads to declining cognitive function [ 59 , 60 ].

4.2. Beneficial Effects

Three beneficial outcomes were observed using MRI method: grey matter change [ 40 , 42 , 50 ], brain activity change [ 40 , 43 , 47 , 48 , 49 ], and functional connectivity change [ 41 ]. The affected brain area corresponds to how the respective games were played.

Four studies of 3D video gaming showed effects on the structure of hippocampus, dorsolateral prefrontal cortex (DLPFC), cerebellum [ 42 , 43 , 50 ], and DLPFC [ 43 ] and ventral striatum activity [ 49 ]. In this case, the hippocampus is used for memory [ 61 ] and scene recognition [ 62 ], whereas the DLPFC and cerebellum are used for working memory function for information manipulation and problem-solving processes [ 63 ]. The grey matter of the corresponding brain region has been shown to increase during training [ 20 , 64 ]. The increased grey matter of the hippocampus, DLPFC, and cerebellum are associated with better performance in reference and working memory [ 64 , 65 ].

The reduced activity of DLPFC found in the study by Gleich et al. corresponds to studies that showed reduced brain activity associated with brain training [ 66 , 67 , 68 , 69 ]. Decreased activity of the DLPFC after training is associated with efficiency in divergent thinking [ 70 ]. 3D video gaming also preserved reward systems by protecting the activity of the ventral striatum [ 71 ].

Two studies of puzzle gaming showed effects on the structure of the visual–spatial processing area, activity of the frontal area, and functional connectivity change. The increased grey matter of the visual–spatial area and decreased activity of the frontal area are similar to training-associated grey matter increase [ 20 , 64 ] and activity decrease [ 66 , 67 , 68 , 69 ]. In this case, visual–spatial processing and frontal area are used constantly for spatial prediction and problem-solving of Tetris. Functional connectivity of the multimodal integration and the higher-order executive system in the puzzle solving-based gaming of Professor Layton game corresponds to studies which demonstrated training-associated functional connectivity change [ 72 , 73 ]. Good functional connectivity implies better performance [ 73 ].

Strategy gaming affects the DLPFC activity, whereas rhythm gaming affects the activity of visuospatial working memory, emotional, and attention area. FPS gaming affects the structure of the hippocampus and amygdala. Decreased DLPFC activity is similar to training-associated activity decrease [ 66 , 67 , 68 , 69 ]. A study by Roush demonstrated increased activity of visuospatial working memory, emotion, and attention area, which might occur because of exercise and gaming in the Dance Revolution game. Results suggest that positive activations indicate altered functional areas by complex exercise [ 48 ]. The increased grey matter of the hippocampus and amygdala are similar to the training-associated grey matter increase [ 20 , 64 ]. The hippocampus is used for 3D navigation purposes in the FPS world [ 61 ], whereas the amygdala is used to stay alert during gaming [ 74 ].

4.3. Duration

Change of the brain structure and function was observed after 16 h of video gaming. The total durations of video gaming were 16–90 h. However, the gaming intensity must be noted because the gaming intensity varied: 1.5–10.68 h per week. The different intensities might affect the change of cognitive function. Cognitive intervention studies demonstrated intensity effects on the cortical thickness of the brain [ 75 , 76 ]. A similar effect might be observed in video gaming studies. More studies must be conducted to resolve how the intensity can be expected to affect cognitive function.

4.4. Criteria

Almost all studies used inclusion criteria “little/no experience with video games.” The criterion was used to reduce the factor of gaming-related experience on the effects of video gaming. Some of the studies also used specific handedness and specific sex of participants to reduce the variation of brain effects. Expertise and sex are shown to affect brain activity and structure [ 77 , 78 , 79 , 80 ]. The exclusion criterion of “MRI contraindication” is used for participant safety for the MRI protocol, whereas exclusion criteria of “psychiatric/mental illness”, “neurological illness”, and “medical illness” are used to standardize the participants.

4.5. Limitations and Recommendations

Some concern might be raised about the quality of methodology, assessed using Delphi criteria [ 45 ]. The quality was 3–9 (mean = 6.10; S.D. = 1.69). Low quality in most papers resulted from unspecified information corresponding to the criteria. Quality improvements for the studies must be performed related to the low quality of methodology. Allocation concealment, assessor blinding, care provider blinding, participant blinding, intention-to-treat analysis, and allocation method details must be improved in future studies.

Another concern is blinding and control. This type of study differs from medical studies in which patients can be blinded easily. In studies of these types, the participants were tasked to do either training as an active control group or to do nothing as a passive control group. The participants can expect something from the task. The expectation might affect the outcomes of the studies [ 81 , 82 , 83 ]. Additionally, the waiting-list control group might overestimate the outcome of training [ 84 ].

Considering the sample size, which was 20–75 (mean = 43.67; S.D. = 15.63), the studies must be upscaled to emphasize video gaming effects. There are four phases of clinical trials that start from the early stage and small-scale phase 1 to late stage and large-scale phase 3 and end in post-marketing observation phase 4. These four phases are used for drug clinical trials, according to the food and drug administration (FDA) [ 85 ]. Phase 1 has the purpose of revealing the safety of treatment with around 20–100 participants. Phase 2 has the purpose of elucidating the efficacy of the treatment with up to several hundred participants. Phase 3 has the purpose of revealing both efficacy and safety among 300–3000 participants. The final phase 4 has the purpose of finding unprecedented adverse effects of treatment after marketing. However, because medical studies and video gaming intervention studies differ in terms of experimental methods, slight modifications can be done for adaptation to video gaming studies.

Several unresolved issues persist in relation to video gaming intervention. First, no studies assessed chronic/long-term video gaming. The participants might lose their motivation to play the same game over a long time, which might affect the study outcomes [ 86 ]. Second, meta-analyses could not be done because the game genres are heterogeneous. To ensure homogeneity of the study, stricter criteria must be set. However, this step would engender a third limitation. Third, randomized controlled trial video gaming studies that use MRI analysis are few. More studies must be conducted to assess the effects of video gaming. Fourth, the eligible studies lacked cognitive tests to validate the cognitive change effects for training. Studies of video gaming intervention should also include a cognitive test to ascertain the relation between cognitive function and brain change.

5. Conclusions

The systematic review has several conclusions related to beneficial effects of noncognitive-based video games. First, noncognitive-based video gaming can be used in all age categories as a means to improve the brain. However, effects on children remain unclear. Second, noncognitive-based video gaming affects both structural and functional aspects of the brain. Third, video gaming effects were observed after a minimum of 16 h of training. Fourth, some methodology criteria must be improved for better methodological quality. In conclusion, acute video gaming of a minimum of 16 h is beneficial for brain function and structure. However, video gaming effects on the brain area vary depending on the video game type.

Acknowledgments

We would like to thank all our other colleagues in IDAC, Tohoku University for their support.

PRISMA Checklist of the literature review.

For more information, visit: www.prisma-statement.org .

Author Contributions

D.B.T., R.N., and R.K. designed the systematic review. D.B.T. and R.N. searched and selected the papers. D.B.T. and R.N. wrote the manuscript with R.K. All authors read and approved the final manuscript. D.B.T. and R.N. contributed equally to this work.

Study is supported by JSPS KAKENHI Grant Number 17H06046 (Grant-in-Aid for Scientific Research on Innovative Areas) and 16KT0002 (Grant-in-Aid for Scientific Research (B)).

Conflicts of Interest

None of the other authors has any conflict of interest to declare. Funding sources are not involved in the study design, collection, analysis, interpretation of data, or writing of the study report.

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Partisan divides over K-12 education in 8 charts

K-12 education is shaping up to be a key issue in the 2024 election cycle. Several prominent Republican leaders, including GOP presidential candidates, have sought to limit discussion of gender identity and race in schools , while the Biden administration has called for expanded protections for transgender students . The coronavirus pandemic also brought out partisan divides on many issues related to K-12 schools .

Today, the public is sharply divided along partisan lines on topics ranging from what should be taught in schools to how much influence parents should have over the curriculum. Here are eight charts that highlight partisan differences over K-12 education, based on recent surveys by Pew Research Center and external data.

Pew Research Center conducted this analysis to provide a snapshot of partisan divides in K-12 education in the run-up to the 2024 election. The analysis is based on data from various Center surveys and analyses conducted from 2021 to 2023, as well as survey data from Education Next, a research journal about education policy. Links to the methodology and questions for each survey or analysis can be found in the text of this analysis.

Most Democrats say K-12 schools are having a positive effect on the country , but a majority of Republicans say schools are having a negative effect, according to a Pew Research Center survey from October 2022. About seven-in-ten Democrats and Democratic-leaning independents (72%) said K-12 public schools were having a positive effect on the way things were going in the United States. About six-in-ten Republicans and GOP leaners (61%) said K-12 schools were having a negative effect.

About six-in-ten Democrats (62%) have a favorable opinion of the U.S. Department of Education , while a similar share of Republicans (65%) see it negatively, according to a March 2023 survey by the Center. Democrats and Republicans were more divided over the Department of Education than most of the other 15 federal departments and agencies the Center asked about.

In May 2023, after the survey was conducted, Republican lawmakers scrutinized the Department of Education’s priorities during a House Committee on Education and the Workforce hearing. The lawmakers pressed U.S. Secretary of Education Miguel Cardona on topics including transgender students’ participation in sports and how race-related concepts are taught in schools, while Democratic lawmakers focused on school shootings.

Partisan opinions of K-12 principals have become more divided. In a December 2021 Center survey, about three-quarters of Democrats (76%) expressed a great deal or fair amount of confidence in K-12 principals to act in the best interests of the public. A much smaller share of Republicans (52%) said the same. And nearly half of Republicans (47%) had not too much or no confidence at all in principals, compared with about a quarter of Democrats (24%).

This divide grew between April 2020 and December 2021. While confidence in K-12 principals declined significantly among people in both parties during that span, it fell by 27 percentage points among Republicans, compared with an 11-point decline among Democrats.

Democrats are much more likely than Republicans to say teachers’ unions are having a positive effect on schools. In a May 2022 survey by Education Next , 60% of Democrats said this, compared with 22% of Republicans. Meanwhile, 53% of Republicans and 17% of Democrats said that teachers’ unions were having a negative effect on schools. (In this survey, too, Democrats and Republicans include independents who lean toward each party.)

The 38-point difference between Democrats and Republicans on this question was the widest since Education Next first asked it in 2013. However, the gap has exceeded 30 points in four of the last five years for which data is available.

Republican and Democratic parents differ over how much influence they think governments, school boards and others should have on what K-12 schools teach. About half of Republican parents of K-12 students (52%) said in a fall 2022 Center survey that the federal government has too much influence on what their local public schools are teaching, compared with two-in-ten Democratic parents. Republican K-12 parents were also significantly more likely than their Democratic counterparts to say their state government (41% vs. 28%) and their local school board (30% vs. 17%) have too much influence.

On the other hand, more than four-in-ten Republican parents (44%) said parents themselves don’t have enough influence on what their local K-12 schools teach, compared with roughly a quarter of Democratic parents (23%). A larger share of Democratic parents – about a third (35%) – said teachers don’t have enough influence on what their local schools teach, compared with a quarter of Republican parents who held this view.

Republican and Democratic parents don’t agree on what their children should learn in school about certain topics. Take slavery, for example: While about nine-in-ten parents of K-12 students overall agreed in the fall 2022 survey that their children should learn about it in school, they differed by party over the specifics. About two-thirds of Republican K-12 parents said they would prefer that their children learn that slavery is part of American history but does not affect the position of Black people in American society today. On the other hand, 70% of Democratic parents said they would prefer for their children to learn that the legacy of slavery still affects the position of Black people in American society today.

Parents are also divided along partisan lines on the topics of gender identity, sex education and America’s position relative to other countries. Notably, 46% of Republican K-12 parents said their children should not learn about gender identity at all in school, compared with 28% of Democratic parents. Those shares were much larger than the shares of Republican and Democratic parents who said that their children should not learn about the other two topics in school.

Many Republican parents see a place for religion in public schools , whereas a majority of Democratic parents do not. About six-in-ten Republican parents of K-12 students (59%) said in the same survey that public school teachers should be allowed to lead students in Christian prayers, including 29% who said this should be the case even if prayers from other religions are not offered. In contrast, 63% of Democratic parents said that public school teachers should not be allowed to lead students in any type of prayers.

In June 2022, before the Center conducted the survey, the Supreme Court ruled in favor of a football coach at a public high school who had prayed with players at midfield after games. More recently, Texas lawmakers introduced several bills in the 2023 legislative session that would expand the role of religion in K-12 public schools in the state. Those proposals included a bill that would require the Ten Commandments to be displayed in every classroom, a bill that would allow schools to replace guidance counselors with chaplains, and a bill that would allow districts to mandate time during the school day for staff and students to pray and study religious materials.

Mentions of diversity, social-emotional learning and related topics in school mission statements are more common in Democratic areas than in Republican areas. K-12 mission statements from public schools in areas where the majority of residents voted Democratic in the 2020 general election are at least twice as likely as those in Republican-voting areas to include the words “diversity,” “equity” or “inclusion,” according to an April 2023 Pew Research Center analysis .

Also, about a third of mission statements in Democratic-voting areas (34%) use the word “social,” compared with a quarter of those in Republican-voting areas, and a similar gap exists for the word “emotional.” Like diversity, equity and inclusion, social-emotional learning is a contentious issue between Democrats and Republicans, even though most K-12 parents think it’s important for their children’s schools to teach these skills . Supporters argue that social-emotional learning helps address mental health needs and student well-being, but some critics consider it emotional manipulation and want it banned.

In contrast, there are broad similarities in school mission statements outside of these hot-button topics. Similar shares of mission statements in Democratic and Republican areas mention students’ future readiness, parent and community involvement, and providing a safe and healthy educational environment for students.

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About 1 in 4 U.S. teachers say their school went into a gun-related lockdown in the last school year

About half of americans say public k-12 education is going in the wrong direction, what public k-12 teachers want americans to know about teaching, what’s it like to be a teacher in america today, race and lgbtq issues in k-12 schools, most popular.

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‘An epidemic of loneliness’: How the pandemic changed life for aging adults

Stock image of a sign at a park in 2020, calling for social distancing. Four years later, a new study shows many are still keeping to themselves more than they did pre-pandemic.  

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Years after the U.S. began to slowly emerge from mandatory COVID-19 lockdowns, more than half of older adults still spend more time at home and less time socializing in public spaces than they did pre-pandemic, according to new CU Boulder research. 

Participants cited fear of infection and “more uncomfortable and hostile” social dynamics as key reasons for their retreat from civic life.

“The pandemic is not over for a lot of folks,” said Jessica Finlay, an assistant professor of geography whose findings are revealed in a series of new papers . “Some people feel left behind.”

The study comes amid what the U.S. Surgeon General recently called an “ epidemic of loneliness ” in which older adults—especially those who are immune compromised or have disabilities—are particularly vulnerable.

“We found that the pandemic fundamentally altered neighborhoods, communities and everyday routines among aging Americans, and these changes have long-term consequences for their physical, mental, social and cognitive health,” said Finlay.

‘I just can’t go back’

As a health geographer and environmental gerontologist, Finlay studies how social and built environments impact health as we age.

In March 2020 as restaurants, gyms, grocery stores and other gathering places shuttered amid shelter-in-place orders, she immediately wondered what the lasting impacts would be. Shortly thereafter, she launched the COVID-19 Coping Study with University of Michigan epidemiologist Lindsay Kobayashi. They began their research with a baseline and monthly survey. Since then, nearly 7,000 people over age 55 from all 50 states have participated.

The researchers check in annually, asking open-ended questions about how neighborhoods and relationships have changed, how people spend their time, opinions and experiences of the COVID-19 pandemic, and their physical and mental health.

By the numbers

How aging adults spend their time

• 59% spend more time at home than before pandemic
• 41% go to the grocery less often
• 75% eat out less often 
• 57% exercise indoors less often
• 62% visit an arts or cultural site less often
• 53% attend religious services less often
• 10% exercise outdoors more often

Source: Data from COVID-19 Coping Study survey results from May 2022. A more recent survey found that more than half still had not returned to pre-pandemic social routines.

“We’ve been in the field for some incredibly pivotal moments,” said Finlay, noting that surveys went out shortly after George Floyd was murdered in May 2020 and again after the attack on the U.S. Capitol on Jan. 6, 2021.

Collectively, the results paint a troubling picture in which a substantial portion of the older population remains isolated even after others have moved on. 

In one paper published in February in the journal Wellbeing, Space and Society , 60% of respondents said they spend more time in their home while 75% said they dine out less. Some 62% said they visit cultural and arts venues less, and more than half said they attend church or the gym less than before the pandemic.

The most recent survey, taken in spring 2023, showed similar trends, with more than half of respondents still reporting that their socialization and entertainment routines were different than they were pre-pandemic. 

In another paper titled “ I just can’t go back ,” 80% of respondents reported there are some places they are reluctant to visit in person anymore.

“The thought of going inside a gym with lots of people breathing heavily and sweating is not something I can see myself ever doing again,” said one 72-year-old male.

Those who said they still go to public places like grocery stores reported that they ducked in and out quickly and skipped casual chitchat. 

“It’s been tough,” said one 68-year-old female. “You don’t stop and talk to people anymore.”

Many respondents reported they were afraid of getting infected with a virus or infecting young or immune-compromised loved ones, and said they felt “irresponsible” for being around a lot of people.

Some reported getting dirty looks or rude comments when wearing masks or asking others to keep their distance—interpersonal exchanges that reinforced their inclination to stay home.

Revitalizing human connection

Jessica Finlay, a health geographer and environmental gerontologist, studies how built environments impact aging.

The news is not all bad, stresses Finlay.

At least 10% of older adults report exercising outdoors more frequently since the pandemic. And a small but vocal minority said that their worlds had actually opened up, as more meetings, concerts and classes became available online.

Still, Finlay worries that the loss of spontaneous interactions in what sociologists call “third places” could have serious health consequences.

Previous research shows that a lack of social connection can increase risk of premature death as much as smoking 15 cigarettes a day and exacerbate mental illness and dementia.

“For some older adults who live alone, that brief, unplanned exchange with the butcher or the cashier may be the only friendly smile they see in the day, and they have lost that,” Finlay said.

Societal health is also at risk.

“It is increasingly rare for Americans with differing sociopolitical perspectives to collectively hang out and respectfully converse,” she writes. 

Finlay hopes that her work can encourage policymakers to create spaces more amenable to people of all ages who are now more cautious about getting sick—things like outdoor dining spaces, ventilated concert halls or masked or hybrid events.

She also hopes that people will give those still wearing masks or keeping distance some grace.

“It is a privilege to be able to ‘just get over’ the pandemic and many people, for a multitude of reasons, just don’t have that privilege. The world looks different to them now,” she said. “How can we make it easier for them to re-engage?”

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