qualitative research about effects of online games

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

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

69k Accesses

23 Citations

32 Altmetric

Metrics details

• Human behaviour
• Risk factors

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.

Similar content being viewed by others

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

Julian Packheiser, Helena Hartmann, … Frédéric Michon

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

Federico Cavanna, Stephanie Muller, … Enzo Tagliazucchi

What colour are your eyes? Teaching the genetics of eye colour & colour vision. Edridge Green Lecture RCOphth Annual Congress Glasgow May 2019

David A. Mackey

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).

Download references

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.

Author information

Authors and affiliations.

Centre for Health Research and School of Commerce, University of Southern Queensland, Workstation 15, Room T450, Block T, Toowoomba, QLD, 4350, Australia

Md Irteja Islam & Rasheda Khanam

Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Mohakhali, Dhaka, 1212, Bangladesh

Md Irteja Islam

Transport and Road Safety (TARS) Research Centre, School of Aviation, University of New South Wales, Sydney, NSW, 2052, Australia

Raaj Kishore Biswas

You can also search for this author in PubMed   Google Scholar

Contributions

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.

Corresponding author

Correspondence to Md Irteja Islam .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

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

Rights and permissions

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

Reprints and permissions

About this article

Cite this article.

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

Download citation

Received : 28 August 2020

Accepted : 02 December 2020

Published : 10 December 2020

DOI : https://doi.org/10.1038/s41598-020-78916-9

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

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

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Positive effects of online games on the growth of college students: A qualitative study from China

Content maybe subject to  copyright     Report

103,789  citations

2,446  citations

1,546  citations

1,237  citations

1,199  citations

Related Papers (5)

Trending questions (3).

The provided paper discusses the positive effects of online games on college students, including satisfying the need for personal growth, meeting the requirement of social life, and promoting academic performance.

The paper states that playing online games can promote academic performance in college students.

The effect of online games on academic performance is mentioned in the paper. It states that promoting academic performance is one of the positive effects of playing online games.

Ask Copilot

Related papers

Related topics

College & Research Libraries ( C&RL ) is the official, bi-monthly, online-only scholarly research journal of the Association of College & Research Libraries, a division of the American Library Association.

C&RL is now on Instragram! Follow us today.

Shannon L. Farrell is Natural Resources Librarian in the Natural Resources Library at the University of Minnesota Twin Cities; e-mail: [email protected] . Amy E. Neeser is Assistant Librarian, Library Research—Science and Engineering in the University Library at the University of Michigan, Ann Arbor; e-mail: [email protected] . Carolyn Bishoff is Physics, Astronomy, and Earth Sciences Librarian in the Walter Library at the University of Minnesota Twin Cities; e-mail: [email protected] ).

C&RL News

ALA JobLIST

Advertising Information

• Research is an Activity and a Subject of Study: A Proposed Metaconcept and Its Practical Application (71455 views)
• Information Code-Switching: A Study of Language Preferences in Academic Libraries (38563 views)
• Three Perspectives on Information Literacy in Academia: Talking to Librarians, Faculty, and Students (27151 views)

Academic Uses of Video Games: A Qualitative Assessment of Research and Teaching Needs at a Large Research University

Shannon L. Farrell, Amy E. Neeser, and Carolyn Bishoff *

Academic libraries develop collections and services for scholars who use video games in teaching and research. However, there are no assessments of related information and technology needs. The authors conducted 30 semistructured interviews to gather data about these needs and understand how the University of Minnesota Libraries can facilitate access to games and technology. A total of 28 interviewees used games in research, and 23 used games in teaching. We identified a variety of information and technology needs; many showed strong disciplinary trends. The findings can inform needs-based multidisciplinary strategies to develop video game services and collections relevant to unique academic communities.

Introduction

Recent studies show that video games are ingrained in American culture and, increasingly, higher education. A 2015 Pew Research Center survey found that 49 percent of American adults and 67 percent of adults ages 18–29 play video games. 1 The New Media Consortium reported that games and gamification have several applications in higher education, as educational technology and components of blended learning. 2 A search for “video games” in major article indices finds game technology used in diverse research areas.

College and research libraries share a vision of exceptional services to motivate and facilitate cutting-edge research and student learning 3 and have proactively supported scholars using and experimenting with video games. Librarians frequently collaborate with faculty and students to create game collections and interactive spaces for research, teaching, game development, and play. Despite this, there are currently no multidisciplinary assessments that provide an overview of the information and technology needs required by scholars working with video games. Some disciplinary-specific needs are understood, such as the needs of game design programs and curricula, but most information on needs is based on anecdotal evidence.

The University of Minnesota (UMN) is a large, doctoral-granting research university. The Twin Cities campus includes more than 4,000 faculty and 52,000 students, 16 colleges, and more than 300 research, education, and outreach centers and institutes. There is no video game design program or department, but there are a number of research faculty, teaching faculty, and students who use video games for academic purposes. To understand the diverse uses of video games across disciplines, we conducted semistructured narrative interviews of faculty, staff, and graduate students who use games or gaming technology in their work. This paper explores the information and technology needs of scholars who use video games on the UMN campus, similarities and differences by discipline, and how college and research libraries can incorporate disciplinary needs into a strategic approach to video game services and collections.

Literature Review

Many academic libraries recognize that scholars using video games for research and instruction have unique information and technology needs. In 2008, Smith 4 called for a better understanding of game scholars’ information needs, research methods, and types of materials they require, but there are three challenges to understanding those needs on a large scale: lack of information on conducting a comprehensive needs assessment of academic video game users, scarce information about research and teaching needs related to video games, and little information about how unique disciplinary or institutional needs affect a game-related collection or service.

Most library literature on games focuses on recommended genres and equipment 5 or the specifics of acquiring, cataloging, and circulating games. 6 Descriptions of video game collections and services often include a process to gather input; but none of these articles go into detail about the methods or findings, nor do they share a specific plan for how faculty and students would be consulted as technology, research, and classroom needs change.

Laskowski and Ward provide the most thorough overview of classroom and research needs and areas the library can support. 7 They note three primary needs for game-related classes at the University of Illinois Urbana-Champaign (UIUC): access to labs with high-powered PCs, availability of course reserves, and access to discontinued games. They propose a variety of needs for game design classes and surmise that those classes would benefit from close liaison partnerships. The research needs they identify all relate to analyses of gameplay, and they propose archiving gameplay videos with player commentary. Since then, game technology has evolved and these recommendations are worth updating.

Many academic libraries have new game collections since the publication of these foundational articles, and descriptions of these collections provide the most up-to-date understanding of the evolving academic uses of video games. It is well recognized that researchers and instructors who use games come from many different disciplines, including education, economics, and the humanities. 8 Some libraries developed partnerships with one department or discipline, such as education 9 or the arts. 10 Librarians managing the game collection at the University of Chicago (UChicago) intend to serve a wide population, from music to media studies to computer science. 11 UChicago also has strong faculty advocates who identified many potential users on campus. 12 Game collections at the University of Michigan 13 and Carleton University 14 likewise support a range of courses and research interests from the sciences to the humanities.

Despite the variety of potential users, there is less documentation about how a library game collection reflects the disciplinary or departmental information and technology needs at a particular institution. The information available shows a surprising amount of consistency across academic game collections: most libraries collect commercially successful games to play on consoles, such as the Playstation 3 or XBox 360. UIUC, 15 the University of Michigan, 16 and the University of California Santa Cruz (UCSC) 17 have vintage games and game systems available. Though personal computer (PC) games are recognized as an important genre to collect, 18 it was difficult to determine if any academic libraries collected PC games or provided hardware to play them. Carleton University is one of the few that does. 19

There are similarities among the themes of many game collections. Collections at Virginia Commonwealth University (VCU), 20 UChicago, 21 and the University of Michigan 22 all represent the history of video game development and the evolution of games through time. Many academic game collections also focus on acquiring current releases. 23

Some libraries have unique aspects to their collections. For example, VCU collects games specifically for users in the arts. The arts librarian looks for “games that have certain aesthetics … have significant artistic direction, unique narrative or cerebral gameplay.” 24 Some libraries plan to expand beyond console games, including UChicago; a faculty member from English hopes that “computer and mobile games” are eventually added to the collection. 25 At least two libraries make game development software available: the University of Calgary game resources include “six high performance (liquid cooled) gaming PCs” with software packages including Unity and several Autodesk products; 26 and Carleton University had requests for software including Poser Pro. 27

As affordable game technology evolves, libraries take steps to stay up-to-date with new research and teaching applications. Commonly, academic libraries rely on subject librarians to stay aware of research and instruction trends, and that is no different when video games are involved. 28 Another strategy involves direct faculty and student input, which often happens during the initial development of video game collections. 29 However, some collections are built from donations and gifts like at the University of Calgary; 30 a for those, the relationship between the collection and local research and teaching needs is less clear. Some collections accept donations for a particular purpose: the University of Michigan Computer and Video Game Archive (CVGA) accepts donations and purchases games to create the most comprehensive collection possible, while also collecting in targeted ways to support faculty and student activities. 31

No literature to date provides a comprehensive overview of the information and technology needs of academic video game users. Many universities rely on a handful of faculty advisors to understand needs on campus; UIUC consulted a faculty member and hosted a game night for students to gather input; 32 Carleton University similarly “crowd-sourced” input for their game collection from faculty, students, and library staff, though they did not describe their methods. 33 At UChicago, faculty advocates assisted directly with the development of the collection. 34 The University of Michigan LibGuide for the CVGA provides the most comprehensive list of courses, research, and faculty who have used the CVGA on their campus, but the list is intended to inform students and potential users, not provide an overview of trends about research and teaching needs or inform collection and service development. 35

This paper explores the information and technology needs of games scholars at UMN Twin Cities and how libraries can accommodate disciplinary needs and help overcome barriers to academic work related to video games.

We formulated the following research questions:

• Which disciplines are represented among UMN scholars who use video games?
• Do UMN scholars who use video games collaborate outside their disciplines?
• What are the information and technology needs for game-related research and teaching at UMN?
• Are there similarities in the information and technology needs of researchers and instructors using video games, despite disciplinary differences?
• If obstacles are identified, how can libraries help researchers and instructors overcome them and enhance their work?

To answer these questions, we identified scholars at UMN who work with video games or video game technology. This was defined broadly and ranged from using games as an object of study to using the technology to study a separate problem. We excluded researchers studying “game theory” (a mathematical concept) or studying analog games such as board games or logic puzzles because our interest was in needs related to video game technology.

We used a number of methods to identify a population of faculty, staff, and students. SciVal Experts, a research profile system used at UMN, identified 62 people who had published on video games. The SciVal Experts system does not include all UMN scholars, and the database best represents disciplines that use journal articles as their primary means of scholarly communication, so we also conducted searches of the UMN website to find mentions of video games in biographies, research statements, or classes. Word-of-mouth also played an important role: we asked librarians at the UMN for recommendations and used snowball sampling to find additional names from those we interviewed. Through these combined methods, we obtained 92 total names, which we considered an exhaustive list.

A qualitative approach was most appropriate, as opposed to a survey, since it allowed participants to drive the conversation and focus on topics important to them. Since we did not have personal connections to those doing video game–related work at UMN, interviews had the additional advantage of building new relationships. We sent invitations to conduct hour-long, semistructured interviews to our sample of faculty, staff, and graduate students. Those who responded were interviewed at a location of their choice. Those who did not respond were sent a follow-up invitation two weeks later. Of the 92 names in the original population, 30 people agreed to be interviewed, 20 declined, and 42 did not respond.

Each interview was attended by two members of the research team and was audio recorded with the interviewee’s permission. We asked guiding questions, but the interviewee led the conversation. Instead of transcribing each interview, we used a Google form to code data from the audio (see appendix for codes and definitions). We used a controlled vocabulary to code most topics and captured quotes and observations with free-text responses. To make sure that different coders maintained a level of consistency, we reviewed the audio from the first 15 interviews in tandem and resolved disputes with the codes and analysis methodology. We then assigned a single reviewer to the final 15 subjects.

We took measures to ensure participants’ anonymity by assigning each participant a random number, coding participants by discipline instead of department, and using generic titles (such as untenured faculty) in place of official positions. These methods were approved by the UMN Institutional Review Board on October 17, 2014.

We identified 92 people from four broad disciplinary groups: arts and humanities, social sciences, science/technology/engineering/math (STEM), and health sciences (see table 1). We interviewed 30 people from this population, an overall response rate of 33 percent. The interview sample overrepresented the STEM population, which had a 52 percent response rate, and underrepresented health sciences, which had a 19 percent response rate (see figure 1). It also overrepresented graduate students, who had a 46 percent response rate overall. Participants were split almost evenly between graduate students (13) and faculty/staff (17). It was also noteworthy that the largest number of interviewed graduate students (in both frequency and percentage of total) occurred in arts and humanities (5).

Interdepartmental collaboration was defined as a relationship, formal or informal, between an interview participant and a member of another department. Both formal and informal collaboration were considered: formal collaboration was defined as a relationship based on an externally recognized partnership, such as a project, grant, coauthorship on a manuscript, or serving as an academic advisor or dissertation committee member; informal collaboration was defined as unofficial or casual partnerships based on consultations, conversations, and friendships that contribute to academic work. These data were used to determine whether an interviewee’s work was confined to a single department or discipline or whether he or she had potential connections outside the interviewee’s home department. We found high levels of interdepartmental collaboration in all disciplines (see figure 2). One third of interview participants (10) reported three or more interdepartmental relationships, including an untenured instructor in arts and humanities who collaborated with faculty and students across five different departments in arts and humanities, STEM, and social sciences. A total of 20 percent of participants (6) reported no collaboration or no collaboration outside their departments, including an untenured instructor in STEM who only collaborated with graduate teaching assistants in his department. Interviewees from arts and humanities were the only group where all interviewees reported collaborative partnerships.

The majority (21/30) of interview participants used video games in both research and teaching (see figure 3). Most participants conducted research with video games (28/30). About a quarter of interviewees (7), most from STEM and health sciences, used games solely in research, including a graduate student in STEM who received funding for research and did not teach. Five categories of game-related research emerged from the interviews (see figure 4). Interviewees who conducted research on the development of games or technology typically produced software or algorithms that could be used in games or developed games based on existing technology. Researchers who used games as instrumentation modified game technology to collect quantitative data or used video games as a cheaper alternative to another analogous instrument they could have purchased. When games were used as an object of study, researchers often applied critical analysis or theory to a video game as they would another text or primary source. When games were used to study influences on people or society, the researcher typically used qualitative methods to examine some societal impact of games. Finally, games were studied by some for their educational applications and impact on student outcomes. Some interviewees used games in more than one way, such as a graduate student in arts and humanities who studied video games as both a cultural object and a cultural influence. Similarly, an untenured faculty in STEM researched video games as an educational technology while also examining their social influence. Each discipline was represented in 3–4 research application categories. At the same time, strong disciplinary research trends were present and each category was dominated by a single discipline, with the exception of educational technology. Educational technology applications primarily included testing games and game-based learning principles in the classroom.

Fewer people used video games in teaching (23/30) than in research, but interviewees who taught with games most often used them in research as well. For example, a tenured faculty researched the effectiveness of a mobile game to create and grade assignments and used the same game in several of his courses. Only two individuals used video games solely in a teaching capacity, including an instructor in STEM who had no research responsibilities. Four categories of teaching applications emerged from the interviews (see figure 5). Some instructors designed games from scratch for students to use in the classroom. Other instructors taught game design principles sometimes using commercial games and sometimes requiring students to create their own games. Games were also used as course material, analogous to texts or other primary sources: instructors assigned games in the syllabus or had students watch videos of others playing through a game. Finally, instructors discussed games, game mechanics, or their own research on games in the classroom but may not have assigned games to students to play in the course. Similar to research applications, some interviewees used games in the classroom multiple ways, like an untenured faculty in STEM who taught game design and also used video games as course material. Every disciplinary group used video games as course material and as a discussion piece in class. Some teaching applications were more common in particular disciplines; 4 of 8 STEM interviewees designed a game for their classes and 5 of 6 from the social sciences used games as course material. Overall, disciplinary trends were far less distinct. Table 2 summarizes the data from figures 3–5.

Among the interviewees, 18 types of information were used (see table 3). Arts and humanities participants used the most information sources (13), while STEM participants used the least (6). Video games were used as primary sources by interviewees in arts and humanities and social sciences, including a tenured faculty in the social sciences who studies game symbology. Interviewees from all disciplines used colleagues, web sources, journals and Google Scholar. Dominant information sources emerged from each discipline: arts and humanities, journals and web sources (see figure 6); social sciences, journals (see figure 7); STEM, colleagues, journals, and Google Scholar (see figure 8); and health sciences, colleagues (see figure 9).

Participants identified 17 unique technology needs (see table 4). The following technology categories emerged: equipment, games, programming languages, servers, software, and web applications. Equipment included any type of hardware, from game consoles like Xbox or PlayStations, to mobile phones or personal computers (PCs). PCs were the most common piece of equipment identified as required by the whole sample, but peripherals (accessories such as game controllers) were the predominant type of equipment mentioned by participants in the health sciences. For example, a Wii balance board was used to study involuntary bodily movements. Only five interviewees used console system equipment (see figure 10).

Games referred to all types of playable software, and four categories of video games emerged: PC games, played on a computer and often accessed through a platform like Steam, were the most common, followed by console games (played on a console) and web games (played through an Internet browser); mobile games (played on a phone) were the least common. Arts and humanities and social sciences participants had the strongest need for games, and they use the widest variety of platforms. For example, a graduate student in arts and humanities uses PC, console, and mobile games to study music, and a graduate student in the social sciences uses web, PC, and console games to study representations of bodies. Social sciences have the largest use of web-based games, used by 3 of 4 interviewees. Only 1 of 11 STEM participants used video games in his or her academic activities (see figure 11), a graduate student studying a prominent massively multiplayer online role-playing game (MMORPG).

Software as a category excluded video games but included almost any other type of digital application that a researcher or instructor identified as necessary to his or her work. The subcategories were chosen with collection development needs in mind; proprietary software would likely come at a cost and include access restrictions, while open source software would be more accessible for any library or user to install. Other categories of interest included custom software, which was usually designed by the researcher or instructor and might not be widely shared or available, and game design software. Game design software might overlap with one of the other categories: some interviewees used Unity, an open source game design software; some used the Unreal engine, which at the time of the interviews cost money to download and was not open source; and some built custom game design software of their own. STEM participants had the most software needs overall; and, as a group, both STEM and health sciences interviewees reported using some type of software from every category (see figure 12). However, the needs were diverse among individuals: a graduate student in STEM used proprietary robotics software and a tenured faculty member in STEM used open source software to teach programming. Arts and humanities interviewees overall did not report many software needs; only 1 of 7 interviewees described any software needs at all. However, members of every disciplinary grouping did report a need for proprietary software.

Some technology used by the interviewees in this study was free or provided by the university, like a personal computer, but many technology needs required some financial resources to fulfill. To determine how interviewees currently met their technology needs, we asked about the specific methods they used to acquire technology. We split the results on technology acquisition into two categories: graduate students and faculty/staff (see figures 13 and 14). Tenured and untenured faculty and staff were combined because the methods of technology acquisition were very similar for both groups. Graduate students used many strategies to acquire technology, including borrowing from others or using their own personal property. For example, one graduate student in the social sciences used free technology, borrowed games from others, made purchases, and still did not have all the technology he needed. On the other hand, faculty and staff primarily purchase technology. One faculty member in health sciences said, “I usually have a couple thousand bucks in my ICR [indirect cost recovery] account… that’s more than enough to pay for the kinds of things we’ve been talking about [plasma screen, Xbox 360, games].” This trend holds true regardless of tenure status. Faculty and staff in STEM are using more freely available technology when compared to the other disciplinary groups. If the faculty, staff, or students had not yet acquired the technology they planned to use, those responses appear as “other.” Faculty planned to either create the technology themselves or hire someone to create it, while graduate students were still considering their options.

Funding sources differed significantly by status, and untenured faculty and staff are shown separately from tenured faculty and graduate students (see figures 15–17). In general, graduate students and untenured faculty and staff relied on a variety of methods for funding compared to tenured faculty. In arts and humanities and social sciences, many graduate students paid out-of-pocket, such as a graduate student in arts and humanities who was unable to get funding for game skins (armor, clothing, and the like), which were required for his dissertation research. In STEM, graduate students received some funding from grants, but that was not the case for graduate students from other disciplines (see figure 15). Tenured faculty mostly got their funding from grants (10 out of 11 in our sample), with some additional support from ICR funds, departmental funds (funding providing by a researcher’s or instructor’s department), and new technology funds (funds provided by the department, college, or university to acquire technology) (see figure 16). Unlike graduate students, tenured faculty did not pay out-of-pocket costs. Health sciences’ tenured faculty illustrated a depth of funding sources. Although there were only three participants in our sample, they had six sources of funding. One example is a tenured faculty member who had both an external grant and used department funding. Untenured faculty and staff appear to be seeking multiple sources of funding (see figure 17). For example, in arts and humanities, an untenured instructor was funding his work with a grant, departmental funds, and his own money. Figures 18–21 summarize the data from figures 13–17 and organize it by discipline.

Research Limitations

This research had several limitations. If an eligible participant did not mention his or her work with video games on a staff profile page or in publications, or if the participant was not located through recommendations or snowball sampling, he or she was not included among the population of 92 UMN game scholars. The interview data was more limited in scope because some eligible participants were away on sabbatical, did not respond to invitations, or declined an interview.

The exploratory nature of this study limits the generalizability of the findings. However, despite being limited to this one research context, the size of the institution and broad range of disciplines and activities covered in this study provide a rich starting point for future research and the development of library services aimed at these types of researchers. Librarians serving game design or game development programs may observe different needs from those identified in this study because UMN does not have a dedicated game design program.

The open-ended, semistructured nature of the interviews resulted in rich and diverse data that posed some problems when categorizing findings and ensuring anonymity. We used broad codes and categories to capture as much data as possible while also maintaining anonymity, resulting in some loss in the granularity of the data. Additionally, determining how to assign disciplines to interviewees to maintain anonymity was challenging. For example, depending on the context, History can be considered a social science or part of the humanities as it is “multifaceted and diffuse.” 36 We chose to place it in arts and humanities because the researchers interviewed were primarily studying video games as cultural objects instead of the impact on society or human behavior.

Finally, some of the subjects discussed were sensitive (for example, institutional barriers to completing work or acquisition of funding) and some participants felt apprehensive about sharing information. Therefore, the data only represents what interviewees shared “on the record.” Occasionally, the interview location could have inhibited participants (for example, one interview occurred in a public location and two interviews occurred where interviewees’ colleagues were present). However, we have no reason to believe that interviewees concealed information or provided untruthful answers; in the cases where subjects spoke “off the record,” they were candid and honest about challenges with their work.

Demographics and Collaboration

Four disciplines were represented in both the larger population of game scholars and our sample of 30 interviewees. All but one interviewee identified strongly with a single area of study, usually the person’s department or area of research. No single department or discipline dominated; video games were used institutionwide.

Most interviewees had strong disciplinary ties and also had strong patterns of collaboration outside their departments. Collaboration was common for those we interviewed regardless of discipline. We anticipated a higher frequency of collaboration in STEM and health sciences because previous studies showed high levels of formal collaboration in these disciplines, 37 but this did not bear out in the interview sample. Collaborative partnerships took the form of coauthorships, collaborative conference presentations, and participation on doctoral committees, as well as many informal collaborations. Informal collaborations were also commonly described by interviewees and included professional friendships, relationships with advisors and committee members, pilot projects, and interest groups.

These data on collaboration are useful to keep in mind while discussing disciplinary trends around information and technology needs. Widespread collaboration on game-related projects and other projects suggests a need for cross-departmental and cross-disciplinary collaboration among librarians on collection development and the creation of services. Some libraries that invested in game technology do serve a range of users and disciplines, 38 but other prominent collections of games and game technology in academic libraries were driven by the needs of only one or two departments. 39 Awareness of the collaborative partnerships that exist could help libraries go beyond serving one student, class, or researcher at a time, and investments in game technology have the potential to support the work of whole networks of researchers and instructors. Explicit library support of collaborative work with video games could even give fringe projects and new collaborations a space to intersect and thrive. At UMN there is the potential for many departments and subject librarians to guide the development of a possible video game collection, and this would require a very collaborative approach to collection development.

Academic Use of Video Games: Research and Teaching

Video games were commonly used in research across all four disciplines represented in our sample. This confirmed a need for the collection development practices of universities such as UChicago, 40 University of Michigan, 41 and Carleton University, 42 which accommodated users from multiple disciplines.

We did not anticipate how common video games are in classrooms, since published information about game-related courses only identified a handful of classes at any comparable institution, unless they were focused on game design. Additionally, very few course descriptions in the UMN course catalog mentioned video games, and, of the game-related courses we found during our initial searching, most were in the social sciences or arts and humanities. We did not expect so many STEM and health science classes to integrate games as well. In fact, the use of video games in classes was present within all the disciplines, especially in introductory undergraduate courses and upper level seminars. The course descriptions were often vague enough to give the instructor leeway in how to develop his or her individual section, and those who wished to incorporate games could do so. Some departments even encouraged game-related classes due to consistently high enrollment.

Most people in our sample incorporated games into both their research and teaching. We suspect that having a research interest in games may make it more likely for them to incorporate video games into the classroom as well. This may explain why only two people in our sample were using video games exclusively in the classroom.

Overall, knowing how scholars are using video games and gaming technology on campus formed the backbone of this needs assessment. Any effort to provide library support for video game–related work will impact both research and classroom/student needs. Since we know that most scholars are using games in both research and teaching capacities, the support of this work may have double the impact.

Role of Video Games in Research and Teaching

There were clear disciplinary trends in the types of research done with video game technology. The development of video games primarily occurred in STEM, while video games were most often used as a text or an object of study in arts and humanities research. There were also some strong similarities among the disciplinary groups. At least one interviewee in every discipline conducted research that studies “educational technology” or “the influences on people and society.” Since video games were used by different disciplines in different ways, the type of support the library offers should not be done through the lens of a single department or discipline, and a variety of materials need to be available for many different applications including development, study, and experimental design.

Disciplinary differences were more difficult to discern when examining the role of games in teaching. Many classes were new or were only offered once; even so, teaching game design or designing games from scratch occurred not only in STEM but also in social science and arts and humanities classrooms. Incorporating game technology as course material was common, and interviewees identified a number of different ways in which games were used: readings, storytelling devices, and technology in labs. Students were impacted by these course requirements as well. Many interviewees described accommodations for students who did not own a console or a computer equipped to run graphics-intensive games, but some required students to figure out how to access the games on their own (such as via a personal account on the Steam game distribution system). 43

Game design was taught in four classes from three disciplines, which was unexpected because there is no game design program or certificate at UMN. Supporting classes that incorporate game design would be easier if they were all in one area of study, but a subject liaison might only be aware of the one class in his or her discipline. Regular environmental scans might be needed to uncover common technology and material requirements for classes across disciplines for courses that use video games and other emerging technologies.

Information Needs

The most commonly used information sources were Google Scholar, journals, and web sources. The interviewees in the social sciences and arts and humanities were the strongest users of “traditional” library materials such as books and journals. Several interviewees described having to acquire the majority of their texts through interlibrary loan (ILL) because their library did not have the journals or books they needed. Libraries need to review collections in this and other emerging areas to minimize the need for backchannels and shortcuts.

Colleagues were the single most common source of information for interviewees, especially in STEM and health sciences. In one case, a project in health sciences was developed entirely with information and skills contributed from existing relationships. The frequency with which interviewees in this sample collaborate outside their department emphasizes the importance of colleague networks in new and emerging areas. Libraries cross departmental and disciplinary borders and can cultivate a role as a connector for scholars doing similar work in different subject areas with events, experimental technology space, or other strategies.

Libraries should pursue partnerships with existing video game archives and other libraries or investigate shared collection development efforts to help researchers and the public overcome barriers to accessing game-related information sources. Interview participants identified video games as both a kind of technology and a type of information. Games are available in some academic libraries and public libraries, but it is unclear how accessible they are outside their immediate communities or institutions through ILL. Game manuals and trade magazines like Nintendo Power were also used by several interviewees. Public libraries typically collect trade magazines but, according to Worldcat, many often only keep the last 1–2 years. Locating game manuals is even more difficult, as they typically lie only in the hands of hobbyists and collectors. A search on Worldcat shows that relatively few libraries have holdings for either game magazines or manuals, raising the question of how libraries can facilitate access to these materials.

The depth and variety of sources used makes it clear that libraries cannot be the sole gatekeepers of information on this subject. The people in our sample used subscription journals but also ephemeral, noncurated materials (such as game manuals, gaming websites, and streaming games). Other library resources like subscription databases were not as valuable for most interviewees, possibly because they are too narrow in scope or interviewees are simply not aware of them. Rather than collect all of the sources scholars need, libraries can create guides to help scholars locate these materials elsewhere, akin to the University of Michigan CVGA LibGuide. 44

Technology Needs

Interviewees’ needs for devices, displays, and peripherals show no disciplinary trends. Investing in a range of equipment would benefit the largest range of users at UMN. Arts and humanities and social science scholars had a greater need for video games, while those in STEM and health sciences had more software needs. In fact, only one person in STEM identified games as a need, and only one interviewee in arts and humanities used software of any kind.

Disciplinary trends ought to factor into decisions related to purchasing and marketing game technology. For example, at UMN, subject librarians and users in the arts and humanities and social sciences disciplines might be primarily responsible for selecting game titles. Subject librarians for STEM and health sciences should weigh in on video game software selection, since usage would be most expected from STEM and health sciences disciplines.

Among our interviewees, the PC was the most common technology necessary to research and teaching. PCs are necessary to academic work, but there was some nuance to how interviewees used them. PC games are used almost as much as nearly all other types of games combined (console, mobile, and web-based). Mobile games are a growing industry, 45 but they are not used heavily on this campus for academic purposes. Other technology needs are tied to PC games as well; PC accessories, most often graphics cards, were the third highest need in the equipment category. PC games do not require much additional technology besides a computer (unless a powerful game requires faster processing or graphics cards), so they may be more attractive to the researchers and instructors from arts and humanities and social science, who make up the majority of game users. Guidance on collecting PC games is limited, since few academic libraries currently collect them. Most libraries with game collections and services collect console games almost exclusively, likely because console games do not have restrictive digital rights management (DRM) or require an account to play and are easier to collect and lend.

Peripherals were a common technology need, especially in health sciences. Interviewees shared a diverse range of applications for peripherals that have nothing to do with consoles: to control robotics, play PC games, and modify to use as instrumentation. Interviewees also preferred them for their low cost and ability to interface with a number of technologies. Since they are flexible and relatively cheap, libraries and makerspaces could provide a variety of peripherals (with or without consoles) for on-site use or rental.

Acquisition of and Funding for Games and Gaming Technology

In general, interviewees found they could purchase games or technology at stores or online but did not always have funding to do so. The acquisition of games and video game technology was intrinsically tied to funding, which was mentioned as the largest barrier to acquiring technology.

Graduate students used a variety of creative strategies to acquire technology (such as using their personal game collection, borrowing from friends, and other means), whereas faculty and staff simply purchased technology with grants or other funds as needed or used freely available games and technologies, such as online emulators. Graduate students may have less funding available, or they do not know how to access existing funding. The majority of graduate students, all from the social sciences and arts and humanities, were paying out-of-pocket.

Graduate students had the same technology needs as faculty and staff and conduct their own research, often independent of their faculty advisors and any associated funding. STEM graduate students were the only ones receiving grants or new technology funds. We argue that graduate students would be the primary beneficiaries of having video games and technology available, as this would break down disciplinary acquisition and funding barriers. Underfunded graduate students are probably not unique to UMN; and, if libraries made these games and technologies available, graduate students would have much more flexibility in their research. The arts and humanities students who purchased video games out-of-pocket likely used the games as primary research materials, analogous to texts. Since many libraries purchase books for research, it should be easy to purchase games for analogous reasons.

Libraries can also help connect graduate students with funding. Many academic units at UMN provide grants to fund graduate research, and the UMN Libraries subscribe to grant databases and offer workshops on locating grant funding. Since graduate student research is highly valued, it makes sense to assist them in their efforts to acquire game technology by building their grant-seeking skills.

Even though faculty and staff theoretically have the same opportunities for funding, untenured faculty and staff seek more sources of funding to meet their needs, whereas tenured faculty receive most of their funding from grants. Startup packages supported three untenured faculty from STEM and the health sciences, and one staff member reported having to pay out-of-pocket to buy games for classroom use. Faculty and staff for the most part were successful in finding funding to purchase the required technology, but making materials available at the library would put less pressure on faculty and staff to acquire them in other ways and would give them an option to use their funding for other purposes.

Collections in the UMN Libraries are focused primarily on meeting faculty research and teaching needs, as faculty tend to stay at the university longer than students. We recognize that these data could suggest that faculty and staff do not have many barriers to accessing technology and that it is neither necessary nor urgent to include video games and video game technology in library collections. It could also be argued that grants and other funding sources already pay for research and classroom needs and that libraries are not in the business of directly funding research costs like instrumentation, experimental design, or technology development. However, many faculty we spoke to welcomed a chance to collaborate with librarians whether or not the library could directly support their research. Some faculty incorporate games into their outreach service, and many have classes that would benefit from the availability of game materials. We also argue that libraries have a great opportunity to engage with graduate and undergraduate students who want to experiment with games before personally investing in the technology.

By focusing our study on researchers and instructors, we have missed the opportunity to explore implications for students taking classes that incorporate games and gaming technology. What we know came solely from the instructors’ viewpoints; therefore, we do not have a comprehensive picture of how these technologies were made available to students or if they encountered barriers to accessing them. In some classes the game technology was provided, like a health sciences class where Wii balance boards were available to take measurements; but, in another case, students were expected to purchase World of Warcraft and install it on their PCs. Some instructors did note that requiring students to purchase video games may be prohibitive and not directly analogous to purchasing textbooks, as it requires students to own consoles or a high-powered PC that supports gaming. Some attempted to find alternative solutions such as asking the UMN Libraries to install games on library computers and investigating Steam licensing for computer labs. It would be worthwhile to interview students from some of these classes to uncover if they encountered any barriers in attempting to access these technologies.

There is little data available about the information and technology needs of researchers and instructors who use video games in higher education. This study attempted to fill that gap with interviews with faculty, staff, and graduate students from UMN. Scholars from all disciplinary groups were represented and demonstrated both a high level of collaborative activity and use of video games in both research and teaching. As libraries build new video game collections or expand existing collections, they should consider the following findings:

• Information used in game-related research and teaching includes nontraditional material such as trade magazines and game manuals. Journals were the most common source of information identified overall, but some essential titles may not be collected or indexed in library catalogs.
• Video games are most often researched as an influence on society and having a role in educational technology. This research is diverse and may have vastly different needs.
• Video games are commonly used as course material in courses from all disciplines, but console games may not be used as frequently as PC games.
• All of the interviewees needed game-related technology, though there was much variation among the disciplines: arts and humanities and social sciences required video games; STEM required software; health sciences required peripherals.
• Graduate students, especially those from arts and humanities, are at a major funding disadvantage compared to colleagues in the sciences. This impedes access to game technology required for research and teaching and often requires them to pay out-of-pocket.

This study found some consistency in video game applications between disciplines but even more differences, especially in technology and information use. This suggests that the support libraries provide should be done collaboratively through a multidisciplinary lens. We propose a strategic approach to video game services and collections focused on disciplinary needs. For UMN, this would mean building a collection focused on PC games, a few console games, cutting-edge equipment with game design software, and a collection of peripherals with or without consoles, perhaps associated with a makerspace. Each academic game collection should reflect its institution, based on an evaluation of the unique needs of its population.

Since this study was limited to the UMN campus, we would like to see similar studies undertaken at various institutions that look at how students use and acquire games for classroom use, as well as a large-scale multi-institution look at the use of games in higher education. As technology changes and moves away from physical media, academic institutions will benefit from studies looking at the impact of DRM on scholarship and libraries. Very few video game companies have partnerships with higher education, and more exploration of this issue is needed. These studies would provide a more complete understanding of scholarly video games–related work and scholars’ information and technology needs.

APPENDIX. Interview Themes, Codes, and Definitions

• Graduate student: both master’s and doctoral students
• Untenured faculty and staff: assistant professor, instructor, postdoc
• Tenured faculty: associate professor, full professor
• Arts and Humanities: includes any field where the human experience and expressions or explanations thereof are the primary objects of study. History is included here because the interviewees study video games and texts and consider the games as the object of study
• Health Sciences: medical, kinesiology, and related disciplines
• Social Sciences: includes any field where humans are the primary object of study
• STEM: includes disciplines from science, technology, engineering, and mathematics
• Formal collaborations: working on a project, publishing a paper, working on a grant together, serving as an academic advisor or member of a thesis or dissertation committee
• Informal collaborations: talking to/with people, sharing ideas
• Both: a combination of both formal and informal collaborations
• Intradepartmental: work alone or only collaborate within their own department
• Interdepartmental (1–2): between 1–2 collaborations outside their own department
• Interdepartmental (3+): 3+ collaborations outside their own department or split positions between departments
• Development of games/technology: researcher has created the video game or associated technology
• Instrumentation: using video games to gather quantitative data
• Object of study: using critical analysis or thematic study of video games
• Influences on people or society: researcher is examining the societal impact of video games
• Educational technology: using video games to facilitate learning and improve student outcomes
• Undergraduate: lower-level classes, primarily for those pursuing their bachelor’s (1xxx–4xxx)
• Graduate: upper level classes, marketed toward master’s and doctoral students (5xxx–8xxx)
• Instructor designed a game: instructor created a video game for use in the classroom
• Taught game design: instructor taught students how to design their own games
• Used games as course material: video games were studied in the classroom, as primary sources
• Discussed games: video games were used in the classroom as secondary sources
• Other: any other response that did not fall within the above categories
• Borrowed/given: the material was owned by someone else and the researcher or instructor acquired from them
• Purchased: the material had to be purchased by the researcher or instructor either out-of-pocket or with other funds
• Already owned: the instructor or researcher previously owned the material
• Freely available: available at no cost to consumers
• Grant (general): acquired funding via another organization to pursue their research or teaching projects
• New technology funds: funds provided for the explicit purpose of acquiring new technologies
• Seed grant: initial capital to start a project
• Department funds: funding provided by researcher’s or instructor’s department
• Dissertation fund: funding provided by graduate student’s department or graduate school to support dissertation research
• Startup package: new professor was provided with funding to set up a lab
• Indirect cost recovery (ICR) funds: funds that the university collects to cover overhead costs when grants are written. A portion is returned back to departments
• Out-of-pocket: the instructor or researcher had to use personal money to cover the cost
• MNDrive grant: grant allocated via partnership between the UMN and the state of Minnesota that provides funding in areas of interdisciplinary research that align with specific industries
• Not required: no funding was required for this research or teaching
• Equipment, console: consoles, such as Xbox 360, Xbox One, PS3, PS4, Wii, WiiU, or any other
• Equipment, controllers, and peripherals: secondary equipment for the gaming systems listed above, including controllers, Wiimotes, headsets, Xbox Kinects, Wii balance boards, steering wheels, and the like
• Equipment, mobile: smartphones, tablets, and other mobile devices, including iPhones, iPads, and such
• Equipment, display: equipment used to view video games, including television screens, computer monitors, or any other display equipment
• Equipment, personal computer: includes Mac, Windows, and Linux systems
• Equipment, personal computer accessories: secondary equipment for PC gaming, including joysticks, controllers, headsets, webcams, and other equipment
• Games, web: games that are available through a browser or browser-based emulator, or for download online
• Games, PC: games purchased to play on personal computers
• Games, console: games purchased to play on consoles
• Games, mobile: games that are available on smartphones or tablets
• Programming languages: computer language used to communicate instructions to a machine, including C, C++, Java, Javascript, Python, and other languages
• Servers: computers or programs that manages access to a network resource
• Software, proprietary: software that must be purchased from the individual or company that developed it; often includes major restrictions for adaptation and use
• Software, free or open source: software that is available for free, typically on the web; often allows users to modify or adapt as needed
• Software, custom: software written by the researcher or instructor from scratch
• Software, game design: software developed for the specific purpose to design video games
• Web applications: software application that is available and runs on the web, such as streaming video
• Archives: historical documents or records
• Books: written or printed works
• Colleagues: talking to people in their discipline
• Conferences: formal meetings for people in related disciplines
• Course readings: resources that were provided while taking a class
• Datasets: collection of related sets of information
• Game manuals: instructions on how to play video games
• Game reviews: evaluations of video games
• Games: console, PC, mobile, or web video games
• Google Scholar: freely accessible web search engine that indexes scholarly literature
• Interviews: information obtained by interviewing appropriate people
• Journals: collections of articles about specific subjects or disciplines
• Library databases: catalog of both full-text resources and indexed citations that are accessible electronically
• Newsletters: bulletins that are issued periodically
• News sources: includes both print and website-based news
• Students: people enrolled in either undergraduate or graduate programs
• Trade magazines: periodicals that contain news and items about a particular topic
• Web sources: materials found on the open web

1. Meave Duggan, “Gaming and Gamers” (Report, Pew Research Center, 2015), available online at www.pewinternet.org/2015/12/15/gaming-and-gamers/ [accessed 18 December 2015].

2. Laurence F. Johnson et al., “NMC Horizon Report: 2015 Higher Education Edition,” Horizon Report (Austin, Tex.: The New Media Consortium, 2015), 22, 35, available online at www.nmc.org/publication/nmc-horizon-report-2015-higher-education-edition/ [accessed 18 December 2015].

3. Association of College and Research Libraries, “ACRL Plan for Excellence,” 2015, available online at www.ala.org/acrl/aboutacrl/strategicplan/stratplan [accessed 11 January 2016].

4. Brena Smith, “Twenty-First Century Game Studies in the Academy: Libraries and an Emerging Discipline,” Reference Services Review 36, no. 2 (2008): 205–20, doi:10.1108/00907320810873066.

5. Examples include Mary Laskowski and David Ward, “Building Next Generation Video Game Collections in Academic Libraries,” Journal of Academic Librarianship 35, no. 3 (May 2009): 267–73, doi: 10.1016/j.acalib.2009.03.005 ; Kristen Mastel and Dave Huston, “Using Video Games to Teach Game Design: A Gaming Collection for Libraries,” Computers in Libraries 29, no. 3 (2009): 41–44, available online at http://eric.ed.gov/?id=EJ831241 [accessed 18 December 2015]; and Diane Robson and Patrick Durkee, “New Directions for Academic Video Game Collections: Strategies for Acquiring, Supporting, and Managing Online Materials,” Journal of Academic Librarianship 38, no. 2 (Mar. 2012): 79–84, doi: 10.1016/j.acalib.2012.01.003 .

6. Examples include Natalie Gick, “Making Book: Gaming in the Library: A Case Study,” in Gaming in Academic Libraries: Collections, Marketing, and Information Literacy (Chicago: American Library Association, 2008), 1–25; David Baker et al., “Lessons Learned from Starting a Circulating Videogame Collection at an Academic Library,” in Gaming in Academic Libraries: Collections, Marketing, and Information Literacy (Chicago: American Library Association, 2008), 26–38; Danielle Kane, Catherine Soehner, and Wei Wei, “Building a Collection of Video Games in Support of a Newly Created Degree Program at the University of California, Santa Cruz,” Science & Technology Libraries 27, no. 4 (Aug. 20, 2007): 77–87, doi:10.1300/J122v27n04_06; and Emma Cross, David Mould, and Robert Smith, “The Protean Challenge of Game Collections at Academic Libraries,” New Review of Academic Librarianship 21, no. 2 (May 4, 2015): 129–45, doi:10.1080/13614533.2015.1043467.

7. Mary Laskowski and David Ward, “Building Next Generation Video Game Collections in Academic Libraries,” Journal of Academic Librarianship 35, no. 3 (May 2009): 267–73, doi: 10.1016/j.acalib.2009.03.005 .

8. Andy Burkhardt, “Taking Games in Libraries Seriously,” The Academic Commons (blog), available online at www.academiccommons.org/2014/07/24/taking-games-in-libraries-seriously/ [accessed 5 November 2015].

9. Chris Nelson, “Gaming Reaches into Far Corners of Academic World as U of C Builds Huge Collection,” Calgary Herald (Mar. 16, 2015), available online at http://calgaryherald.com/news/local-news/gaming-reaches-into-far-corners-of-academic-world-as-u-of-c-builds-huge-collection [accessed 4 November 2015].

10. Brian McNeill, “VCU Libraries Launches Collection of Critically Acclaimed Video Games,” VCU News (blog) (Nov. 6, 2014), available online at http://news.vcu.edu/article/VCU_Libraries_launches_collection_of_critically_acclaimed_video [accessed 4 November 2015].

11. Sarah G. Wenzel, “New Library Videogame Collection,” The University of Chicago Library News (blog) (May 25, 2012), available online at http://news.lib.uchicago.edu/blog/2012/05/25/new-library-videogame-collection/ [accessed 30 November 2015].

12. Patrick Jagoda, “Videogame Collection Supports Scholarly Study,” The University of Chicago Library News (blog) (May 25, 2012), available online at http://news.lib.uchicago.edu/blog/2012/05/25/videogame -collection-supports-scholarly-study/ [accessed 30 November 2015].

13. An overview of classes and disciplinary uses is discussed in Mary Claire Morris, “Computer & Video Game Archive Celebrating Five Years of Growth,” The University Record (blog) (Nov. 5, 2013), available online at http://record.umich.edu //articles/computer-video-game-archive-celebrating-five-years-growth [accessed 2 December 2015]. A list of classes and research applications can be found in Valerie Waldron, “Computer & Video Game Archive: CVGA,” University of Michigan Research Guides (2015), available online at http://guides.lib.umich.edu/c.php?g=282987 [accessed 2 December 2015].

14. Emma Cross, David Mould, and Robert Smith, “The Protean Challenge of Game Collections at Academic Libraries,” New Review of Academic Librarianship 21, no. 2 (May 4, 2015): 135–37, doi: 10.1080/13614533.2015.1043467 .

15. David Ward, “Vintage Gaming Collection Development Policy and Description” (Urbana, Ill.: University of Illinois Urbana-Champaign, 2014), available online at www.library.illinois.edu/gaming/gamearchives.html [accessed 20 December 2015].

16. Valerie Waldron, “Computer & Video Game Archive: CVGA,” University of Michigan Research Guides (2015), available online at http://guides.lib.umich.edu/c.php?g=282987 [accessed 2 December 2015]

17. University of California Santa Cruz Library, “Video Games” (2015), available online at https://library.ucsc.edu/collections/video-games [accessed 18 December 2015].

18. Diane Robson and Patrick Durkee, “New Directions for Academic Video Game Collections: Strategies for Acquiring, Supporting, and Managing Online Materials,” Journal of Academic Librarianship 38, no. 2 (Mar. 2012): 82, doi: 10.1016/j.acalib.2012.01.003 .

19. Cross, Mould, and Smith, “The Protean Challenge of Game Collections,” 134.

20. McNeill, “VCU Libraries Launches Collection.”

21. Jagoda, “Videogame Collection Supports Scholarly Study.”

22. Adam DePollo, “Play On: Changing Gamer Culture at the ‘U,’” Michigan Daily (Oct. 22, 2014), available online at https://www.michigandaily.com/arts/10computer-video-game-archive22 [accessed 2 December 2015].

23. Laskowski and Ward, “Building next Generation Video Game Collections,” 268.

24. McNeill, “VCU Libraries Launches Collection.”

25. Jagoda, “Videogame Collection Supports Scholarly Study.”

26. University of Calgary Libraries and Cultural Resources, “Video Games,” available online at http://library.ucalgary.ca/dmc/video-games [accessed 4 November 2015].

27. Emma Cross and Robert Smith, “The Evolution of Gaming at Academic Libraries,” Canadian Library Association Conference (Winnepeg, Manitoba, 2013), available online at https://prezi.com/supsungb2uil/the-evolution-of-gaming-at-academic-libraries/ [accessed 4 November 2015].

28. Burkhardt, “Taking Games in Libraries Seriously.”

29. Three examples of soliciting direct feedback from faculty and students are found in Kane, Soehner, and Wei, “Building a Collection of Video Games”; Laskowski and Ward, “Building Next Generation Video Game Collections”; and Cross, Mould, and Smith, “The Protean Challenge of Game Collections.”

30. Nelson, “Gaming Reaches into Far Corners of Academic World.”

31. DePollo, “Play On: Changing Gamer Culture at the ‘U.’”

32. Laskowski and Ward, “Building Next Generation Video Game Collections,” 268.

33. Cross, Mould, and Smith, “The Protean Challenge of Game Collections,” 133.

34. Jagoda, “Videogame Collection Supports Scholarly Study.”

35. Waldron, “Computer & Video Game Archive.”

36. Mark T. Gilderhus, History and Historians : A Historiographical Introduction , 7th ed. (Englewood Cliffs, N.J.: Prentice Hall, 2010), 41.

37. Vincent Larivière, Yves Gingras, and Éric Archambault, “Canadian Collaboration Networks: A Comparative Analysis of the Natural Sciences, Social Sciences and the Humanities,” Scientometrics 68, no. 3 (2006): 519–33, doi:10.1007/s11192-006-0127-8.

38. Nelson, “Gaming Reaches into Far Corners of Academic World.”

39. Kane, Soehner, and Wei, “Building a Collection of Video Games.”

40. Wenzel, “New Library Videogame Collection.”

41. Mary Claire Morris, “Computer & Video Game Archive Celebrating Five Years of Growth,” The University Record (blog) (Nov. 5, 2013), available online at http://record.umich.edu //articles/computer-video-game-archive-celebrating-five-years-growth [accessed 2 December 2015].

42. Cross, Mould, and Smith, “The Protean Challenge of Game Collections,” 144.

43. For more information, see http://store.steampowered.com/about /.

44. Waldron, “Computer & Video Game Archive.”

45. John Gaudiosi, “Mobile Game Revenues Set to Overtake Console Games in 2015,” Fortune , (Jan. 15, 2015), available online at http://fortune.com/2015/01/15/mobile -console-game-revenues-2015/ [accessed 15 January 2016].

* Shannon L. Farrell is Natural Resources Librarian in the Natural Resources Library at the University of Minnesota Twin Cities; e-mail: [email protected] . Amy E. Neeser is Assistant Librarian, Library Research—Science and Engineering in the University Library at the University of Michigan, Ann Arbor; e-mail: [email protected] . Carolyn Bishoff is Physics, Astronomy, and Earth Sciences Librarian in the Walter Library at the University of Minnesota Twin Cities; e-mail: [email protected] ). ©2017 Shannon L. Farrell, Amy E. Neeser, and Carolyn Bishoff, Attribution-NonCommercial ( http://creativecommons.org/licenses/by-nc/4.0/ ) CC BY-NC.

Article Views (Last 12 Months)

Contact ACRL for article usage statistics from 2010-April 2017.

Article Views (By Year/Month)

© 2024 Association of College and Research Libraries , a division of the American Library Association

Print ISSN: 0010-0870 | Online ISSN: 2150-6701

ALA Privacy Policy

ISSN: 2150-6701

ORIGINAL RESEARCH article

The effects of online game addiction on reduced academic achievement motivation among chinese college students: the mediating role of learning engagement.

• 1 BinZhou College of Science and Technology, Binzhou, China
• 2 Binzhou Polytechnic, Binzhou, China
• 3 Faculty of Education, Beijing Normal University, Beijing, China
• 4 National Institute of Vocational Education, Beijing Normal University, Beijing, China

Introduction: The present study aimed to examine the effects of online game addiction on reduced academic achievement motivation, and the mediating role of learning engagement among Chinese college students to investigate the relationships between the three variables.

Methods: The study used convenience sampling to recruit Chinese university students to participate voluntarily. A total of 443 valid questionnaires were collected through the Questionnaire Star application. The average age of the participants was 18.77 years old, with 157 males and 286 females. Statistical analysis was conducted using SPSS and AMOS.

Results: (1) Chinese college students’ online game addiction negatively affected their behavioral, emotional, and cognitive engagement (the three dimensions of learning engagement); (2) behavioral, emotional, and cognitive engagement negatively affected their reduced academic achievement motivation; (3) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

1. Introduction

Online games, along with improvements in technology, have entered the daily life of college students through the popularity of computers, smartphones, PSPs (PlayStation Portable), and other gaming devices. Online game addiction has recently become a critical problem affecting college students’ studies and lives. As early as 2018, online game addiction was officially included in the category of “addictive mental disorders” by the World Health Organization (WHO), and the International Classification of Diseases (ICD) was updated specifically to include the category of “Internet Gaming Disorder” (IGD). Prior research investigating Chinese college students’ online game addiction status mostly comprised regional small-scale studies. For example, a study on 394 college students in Chengde City, Hebei province, China showed that the rate of online game addiction was about 9% ( Cui et al., 2021 ). According to the results of an online game survey conducted by China Youth Network (2019) on 682 Chinese college students who played online games, nearly 60% of participants played games for more than 1 h a day, over 30% stayed up late because of playing games, over 40% thought that playing games had affected their physical health, over 70% claimed that games did not affect their studies, and over 60% had spent money on online games. This phenomenon has been exacerbated by the fact that smartphones and various portable gaming devices have become new vehicles for gaming with the development of technology. The increase in the frequency or time spent on daily gaming among adolescents implies a growth in the probability of gaming addiction, while an increase in the level of education decreases the probability of gaming addiction ( Esposito et al., 2020 ; Kesici, 2020 ). Moreover, during the COVID-19 pandemic, adolescents’ video game use and the severity of online gaming disorders increased significantly ( Teng et al., 2021 ).

A large body of literature on the relationship between problematic smartphone use and academic performance has illustrated the varying adverse effects of excessive smartphone obsession ( Durak, 2018 ; Mendoza et al., 2018 ; Rozgonjuk et al., 2018 ). These effects are manifested in three critical ways: first, the more frequently cell phones are used during study, the greater the negative impact on academic performance and achievement; second, students are required to master the basic skills and cognitive abilities to succeed academically, which are negatively affected by excessive cell phone use and addiction ( Sunday et al., 2021 ); third, online game addiction negatively affects students’ learning motivation ( Demir and Kutlu, 2018 ; Eliyani and Sari, 2021 ). However, there is currently a lack of scientifically objective means of effective data collection regarding online game addiction among college students in China, such as big data. Hong R. Z. et al. (2021) and Nong et al. (2023) suggested that the impact of addiction on students’ learning should be explored more deeply.

Since the 1990s, learning engagement has been regarded as a positive behavioral practice in learning in Europe and the United States, and plays an important role in the field of higher education research ( Axelson and Flick, 2010 ). Recently, studies on learning engagement among college students have also been a hot topic in various countries ( Guo et al., 2021 ). According to Fredricks et al. (2004) , learning engagement includes three dimensions: behavioral, emotional, and cognitive.

The concept of behavioral engagement encompasses three aspects: first, positive behavior in the classroom, such as following school rules and regulations and classroom norms; second, engagement in learning; and third, active participation in school activities ( Finn et al., 1995 ). Emotional engagement refers to students’ responses to their academic content and learning environment. The emotional responses to academic content include students’ emotional responses such as interest or disinterest in learning during academic activities ( Kahu and Nelson, 2018 ), while the emotional responses to the learning environment refer to students’ identification with their peers, teachers, and the school environment ( Stipek, 2002 ). Cognitive engagement is often associated with internal processes such as deep processing, using cognitive strategies, self-regulation, investment in learning, the ability to think reflectively, and making connections in daily life ( Khan et al., 2017 ). Cognitive engagement emphasizes the student’s investment in learning and self-regulation or strategies.

According to Yang X. et al. (2021) , learning engagement refers to students’ socialization, behavioral intensity, affective qualities, and use of cognitive strategies in performing learning activities. Besides, Kuh et al. (2007) argued that learning engagement was “the amount of time and effort students devote to instructional goals and meaningful educational practices.” Learning engagement is not only an important indicator of students’ learning process, but also a significant predictor of students’ academic achievement ( Zhang, 2012 ). It is also an essential factor in promoting college students’ academic success and improving education quality.

As one of the crucial components of students’ learning motivation ( Han and Lu, 2018 ), achievement motivation is the driving force behind an individual’s efforts to put energy into what he or she perceives to be valuable and meaningful to achieve a desired outcome ( Story et al., 2009 ). It can be considered as achievement motivation when an individual’s behavior involves “competing at a standard of excellence” ( Brunstein and Heckhausen, 2018 ). Students’ achievement motivation ensures the continuity of learning activities, achieving academic excellence and desired goals ( Sopiah, 2021 ). Based on the concept of achievement motivation, academic achievement motivation refers to the mental perceptions or intentions that students carry out regarding their academic achievement, a cognitive structure by which students perceive success or failure and determine their behavior ( Elliot and Church, 1997 ). Related research also suggests that motivation is one variable that significantly predicts learning engagement ( Xiong et al., 2015 ).

Therefore, it is worthwhile to investigate the internal influence mechanism of college students’ online game addiction on their reduced academic achievement motivation and the role of learning engagement, which is also an issue that cannot be ignored in higher education research. The present study explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation among college students by establishing a structural equation model (SEM) to shed light on the problem of online game addiction among college students.

2. Research model and hypotheses

2.1. research model.

Previous research usually regarded learning engagement as a variable of one or two dimensions, and scholars tend to favor the dimension of behavioral engagement. However, other ignored dimensions are inseparable parts of learning engagement ( Dincer et al., 2019 ). In a multi-dimensional model, the mutual terms of each dimension form a single composite structure. Therefore, the present study took the structure proposed by Fredricks et al. (2004) as a reference, divided learning engagement into behavioral, emotional, and cognitive dimensions as mediating variables, and explored the relationship between online game addiction, learning engagement, and reduced academic achievement motivation. The research frame diagram is shown in Figure 1 .

Figure 1 . The research model.

2.2. Research questions

2.2.1. the relationship between online game addiction and learning engagement.

Learning engagement has been viewed as a multidimensional concept in previous studies. Finn (1989) proposed the participation-identification model to make pioneering progress in learning engagement study. Schaufeli et al. (2002) suggested that learning engagement was an active, fulfilling mental state associated with learning. Chapman (2002) pointed out affective, behavioral, and cognitive criteria for assessing students’ learning engagement based on previous research. Fredricks et al. (2004) systematically outlined learning engagement as an integration of behavioral, emotional, and cognitive engagement. The updated International Classification of Diseases [ World Health Organization (WHO), 2018a , b ] specifies several diagnostic criteria for gaming addiction, including the abandonment of other activities, the loss of interest in other previous hobbies, and the loss or potential loss of work and social interaction because of gaming. Past studies have shown the adverse effects of excessive Internet usage on students’ learning. Short video addiction negatively affects intrinsic and extrinsic learning motivation ( Ye et al., 2022 ). Students’ cell phone addiction negatively affects academic commitment, academic performance, and relationship facilitation, all of which negatively affect their academic achievement ( Tian et al., 2021 ). The amount of time spent surfing the Internet and playing games has been identified to negatively affect students’ cognitive ability ( Pan et al., 2022 ). College students’ cell phone addiction, mainly reflected in cell phone social addiction and game entertainment addiction, has also been noted to impact learning engagement; specifically, the higher the level of addiction, the lower the learning engagement ( Qi et al., 2020 ). Gao et al. (2021) also showed that cell phone addiction among college students could negatively affect their learning engagement. Choi (2019) showed that excessive use of cell phones might contribute to smartphone addiction, which also affects students’ learning engagement. Accordingly, the following three research hypotheses were proposed.

H1 : Online game addiction negatively affects behavioral engagement.

H2 : Online game addiction negatively affects emotional engagement.

H3 : Online game addiction negatively affects cognitive engagement.

2.2.2. The relationship between learning engagement and reduced academic achievement motivation

Achievement motivation is people’s pursuit of maximizing individual value, which embodies an innate drive, including the need for achievement, and can be divided into two parts: the intention to succeed and the intention to avoid failure ( McClelland et al., 1976 ). On this basis, Weiner (1985) proposed the attributional theory of achievement motivation, suggesting that individuals’ personality differences, as well as the experience of success and failure, could influence their achievement attributions and that an individual’s previous achievement attributions would affect his or her expectations and emotions for the subsequent achievement behavior while expectations and emotions could guide motivated behavior. Birch and Ladd (1997) indicated that behavioral engagement involved positive behavioral attitudes such as hard work, persistence, concentration, willingness to ask questions, and active participation in class discussions to complete class assignments. Students’ attitudes toward learning are positively related to achievement motivation ( Bakar et al., 2010 ). Emotional engagement involves students’ sense of identity with their peers, teachers, and the school environment ( Stipek, 2002 ). Students’ perceptions of the school environment influence their achievement motivation ( Wang and Eccles, 2013 ). Cognitive engagement encompasses the ability to use cognitive strategies, self-regulation, investment in learning, and reflective thinking ( Khan et al., 2017 ). Learning independence and problem-solving abilities predict student motivation ( Saeid and Eslaminejad, 2017 ). Hu et al. (2021) indicated that cognitive engagement had the most significant effect on students’ academic achievement among the learning engagement dimensions, and that emotional engagement was also an important factor influencing students’ academic achievement. Therefore, the following three research hypotheses were proposed:

H4 : Behavioral engagement significantly and negatively affects the reduced academic achievement motivation.

H5 : Emotional engagement significantly and negatively affects the reduced academic achievement motivation.

H6 : Cognitive engagement significantly and negatively affects the reduced academic achievement motivation.

2.2.3. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation

Past studies have demonstrated the relationship between online game addiction and students’ achievement motivation. For example, a significant negative correlation between social network addiction and students’ motivation to progress has been reported ( Haji Anzehai, 2020 ), and a significant negative correlation between Internet addiction and students’ achievement motivation has been reported ( Cao et al., 2008 ). Students addicted to online games generally have lower academic achievement motivation because they lack precise academic planning and motivation ( Chen and Gu, 2019 ). Yayman and Bilgin (2020) pointed out a correlation between social media addiction and online game addiction. Accordingly, there might be a negative correlation between online game addiction and academic achievement motivation among college students.

Students addicted to online games generally have lower motivation for academic achievement because they lack precise academic planning and learning motivation ( Chen and Gu, 2019 ). Similarly, Haji Anzehai (2020) reported a significant negative correlation between social network addiction and students’ motivation to progress.

Learning engagement is often explored as a mediating variable in education research. Zhang et al. (2018) found that learning engagement was an essential mediator of the negative effect of internet addiction on academic achievement in late adolescence and is a key factor in the decline in academic achievement due to students’ internet addiction. Li et al. (2019) noted that college students’ social networking site addiction significantly negatively affected their learning engagement, and learning engagement mediated the relationship between social networking addiction and academic achievement. Accordingly, the following research hypothesis was proposed.

H7 : Learning engagement mediates the relationship between online game addiction and reduced academic achievement motivation.

3. Research methodology and design

3.1. survey implementation.

The present study employed the Questionnaire Star application for online questionnaire distribution. Convenience sampling was adopted to recruit Chinese college students to participate voluntarily. The data were collected from October 2021 to January 2022 from a higher vocational college in Shandong province, China. Participants were first-and second-year students. According to Shumacker and Lomax (2016) , the number of participants in SEM studies should be approximately between 100 and 500 or more. In the present study, 500 questionnaires were returned, and 443 were valid after excluding invalid responses. The mean age of the participants was 18.77 years. There were 157 male students, accounting for 35.4% of the total sample, and 286 female students, accounting for 64.6%.

3.2. Measurement instruments

The present empirical study employed quantitative research methods by collecting questionnaires for data analysis. The items of questionnaires were adapted from research findings based on corresponding theories and were reviewed by experts to confirm the content validity of the instruments. The distributed questionnaire was a Likert 5-point scale (1 for strongly disagree , 2 for disagree , 3 for average , 4 for agree , and 5 for strongly agree ). After the questionnaire was collected, item analysis was conducted first, followed by reliability and validity analysis of the questionnaire constructs using SPSS23 to test whether the scale met the criteria. Finally, research model validation was conducted.

3.2.1. Online game addiction

In the present study, online game addiction referred to the addictive behavior of college students in online games, including mobile games and online games. The present study adopted a game addiction scale compiled by Wu et al. (2021) and adapted the items based on the definition of online game addiction. The adapted scale had 10 items. Two examples of the adapted items in the scale were: “I will put down what should be done and spend my time playing online games” and “My excitement or expectation of playing an online game is far better than other interpersonal interactions.”

3.2.2. Learning engagement

In the present study, learning engagement included students’ academic engagement in three dimensions: behavioral, emotional, and cognitive. The learning engagement scale compiled by Luan et al. (2020) was adapted based on its definition. The adapted scale had 26 questions in three dimensions: behavioral, emotional, and cognitive engagement. Two examples of the adapted items in the scale are: “I like to actively explore unfamiliar things when I am doing my homework” and “I will remind myself to double-check the places where I tend to make mistakes in my homework.”

3.2.3. Reduced academic achievement motivation

Reduced academic achievement motivation in the present study refers to the reduction in college students’ intrinsic tendency to enjoy challenges and achieve academic goals and academic success. The achievement motivation scale developed by Ye et al. (2020) was adapted to measure reduced academic achievement motivation. The adapted scale had 10 items. Two examples of the adapted items in the scale are: “Since playing online games, I do not believe that the effectiveness of learning is up to me, but that it depends on other people or the environment” and “Since I often play online games, I am satisfied with my current academic performance or achievement and do not seek higher academic challenges.”

4. Results and discussion

4.1. internal validity analysis of the measurement instruments.

In the present study, item analysis was conducted using first-order confirmatory factor analysis (CFA), which can reflect the degree of measured variables’ performance within a smaller construct ( Hafiz and Shaari, 2013 ). The first-order CFA is based on the streamlined model and the principle of independence of residuals. According to Hair et al. (2010) and Kenny et al. (2015) , it is recommended that the value of χ 2 / df in the model fitness indices should be less than 5; the root mean square error of approximation (RMSEA) value should be greater than 0.100; the values of the goodness of fit index (GFI) and adjusted goodness of fit index (AGFI) should not be lower than 0.800; the factor loading (FL) values of the constructs should also be greater than 0.500. Based on the criteria above, the items measuring the online game addiction construct were reduced from 10 to seven; the items measuring the behavioral engagement construct were reduced from nine to six; the items measuring the emotional engagement construct were reduced from nine to six; the items measuring the cognitive engagement construct were reduced from eight to six; and the items measuring the reduced academic achievement motivation construct was reduced from 10 to six, as shown in Table 1 .

Table 1 . First-order confirmatory factor analysis.

4.2. Construct reliability and validity analysis

In order to determine the internal consistency of the constructs, the reliability of the questionnaire was tested using Cronbach’ s α value. According to Hair et al. (2010) , a Cronbach’ s α value greater than 0.700 indicates an excellent internal consistency among the items, and the constructs’ composite reliability (CR) values should exceed 0.700 to meet the criteria. In the present study, the Cronbach’ s α values for the constructs ranged from 0.911 to 0.960, and the CR values ranged from 0.913 to 0.916, which met the criteria, as shown in Table 2 .

Table 2 . Construct reliability and validity of constructs.

In the present study, convergent validity was confirmed by two types of indicators, FL and average variance extracted (AVE). According to Hair et al. (2011) , an FL value should be greater than 0.500, and items with an FL value less than 0.500 should be removed; and AVE values should be greater than 0.500. In the present study, the FL values of the constructs ranged from 0.526 to 0.932, and the AVE values ranged from 0.600 to 0.805; all dimensions met the recommended criteria, as shown in Table 2 .

According to Awang (2015) and Hair et al. (2011) , the square root of the AVE of each construct (latent variable) should be greater than its correlation coefficient values with other constructs to indicate the ideal discriminant validity. The results of the present study showed that the three constructs of online game addiction, learning engagement, and reduced academic achievement motivation had good discriminant validity in the present study, as shown in Table 3 .

Table 3 . Discriminant validity analysis.

4.3. Correlation analysis

Pearson’s correlation coefficient is usually used to determine the closeness of the relationship between variables. A correlation coefficient greater than 0.8 indicates a high correlation between variables; a correlation coefficient between 0.3 and 0.8 indicates a moderate correlation between variables; while a correlation of less than 0.3 indicates a low correlation. Table 4 shows the Correlation Analysis results. Online game addiction was moderately negatively correlated with behavioral engagement ( r  = −0.402, p  < 0.001), moderately negatively correlated with emotional engagement ( r  = −0.352, p  < 0.001), slightly negatively correlated with cognitive engagement ( r  = −0.288, p  < 0.001), and slightly positively correlated with reduced academic achievement motivation ( r  = 0.295, p  < 0.001). Behavioral engagement was moderately positively correlated with emotional engagement ( r  = 0.696, p  < 0.001), moderately positively correlated with cognitive engagement ( r  = 0.601, p  < 0.001), and moderately negatively correlated with reduced academic achievement motivation ( r  = −0.497, p  < 0.001). Emotional engagement was moderately positively correlated with cognitive engagement ( r  = 0.787, p  < 0.001) and moderately negatively correlated with reduced academic achievement motivation ( r  = −0.528, p  < 0.001). Cognitive engagement was moderately negatively correlated with reduced motivation for academic achievement ( r  = −0.528, p  < 0.001).

Table 4 . Correlation analysis.

4.4. Analysis of fitness of the measurement model

According to Hair et al. (2010) and Abedi et al. (2015) , the following criteria should be met in the analysis for measurement model fitness: the ratio of chi-squared and degree of freedom ( χ 2 / df ) should be less than 5; the root mean square error of approximation (RMSEA) should not exceed 0.100; the goodness of fit index (GFI), adjusted goodness of fit index (AGFI), normed fit index (NFI), non-normed fit index (NNFI), comparative fit index (CFI), incremental fit index (IFI) and relative fit index (RFI) should be higher than 0.800; and the parsimonious normed fit index (PNFI) and the parsimonious fitness of fit index (PGFI) should be higher than 0.500. The model fitness indices in the present study were χ 2  = 1434.8, df  = 428, χ 2 / df  = 3.352, RMSEA = 0.073, GFI = 0.837, AGFI = 0.811, NFI = 0.899, NNFI = 0.920, CFI = 0.927, IFI = 0.927, RFI = 0.890, PNFI = 0.827, and PGFI = 0.722. The results were in accordance with the criteria, indicating a good fitness of the model in the present study ( Table 5 ).

Table 5 . Direct effects analysis.

4.5. Validation of the research model

Online game addiction had a negative effect on behavioral engagement ( β  = −0.486; t  = −9.143; p < 0.001). Online game addiction had a negative effect on emotional engagement ( β  = −0.430; t  = −8.054; p < 0.001). Online game addiction had a negative effect on cognitive engagement ( β  = −0.370; t  = −7.180; p < 0.001). Online game addiction had a positive effect on reduced academic achievement motivation ( β  = 0.19; t = −2.776; p < 0.01). Behavioral engagement had a negative effect on reduced academic achievement motivation ( β  = −0.238; t  = −3.759; p < 0.001). Emotional engagement had a negative effect on reduced academic achievement motivation ( β  = −0.221; t  = −2.687; p < 0.01), and cognitive engagement had a negative effect on reduced academic achievement motivation ( β  = −0.265; t  = −3.581; p < 0.01), as shown in Figure 2 Table 6 .

Figure 2 . Validation of the research model. *** p  < 0.001.

Table 6 . Indirect effects analysis.

Cohen’ s f 2 is an uncommon but valuable standardized effect size measure that can be used to assess the size of local effects ( Selya et al., 2012 ). When f 2 reaches 0.02 it represents a small effect size, 0.150 represents a medium effect size, and 0.350 represents a high effect size ( Hair et al., 2014 ). The explanatory power of online game addiction on behavioral engagement was 23.6%, and f 2 was 0.309. The explanatory power of online game addiction on emotional engagement was 18.5%, and f 2 was 0.227. The explanatory power of online game addiction on cognitive engagement was 13.7%, and f 2 was 0.159. The explanatory power of behavioral, emotional, and cognitive engagement on reduced academic achievement motivation was 23.9%, and f 2 was 0.314. Figure 2 illustrates the above findings.

4.6. Indirect effects analysis

Scholars are often interested in whether variables mediate the association between predicting and outcome variables. Therefore, mediating variables can partially or entirely explain the association ( Hwang et al., 2019 ). In research fields such as psychology and behavior, where the research situation is often more complex, multiple mediating variables are often required to clearly explain the effects of the independent variables on the dependent variables ( MacKinnon, 2012 ). Scientific quantitative research requires tests of confidence interval (CI; Thompson, 2002 ), and the standard value of the test numbers is often determined by 95% CI ( Altman and Bland, 2011 ). CI value not containing 0 indicates the statistical significance of the analysis results ( Nakagawa and Cuthill, 2007 ). According to the statistical results shown in Table 4 , behavioral engagement significantly positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.230 and 95% CI ranging from 0.150 to 0.300 (excluding 0), p < 0.01; emotional engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.209, 95% CI ranging from 0.130 to 0.292 (excluding 0), p < 0.01; cognitive engagement positively mediated the relationship between online game addiction and reduced academic achievement motivation with a path coefficient of 0.170, 95% CI ranging from 0.100 to 0.250 (excluding 0), p < 0.01, as shown in Table 6 .

4.7. Discussion

4.7.1. analysis of the relationship between online game addiction and learning engagement.

Online game addiction is often negatively associated with students’ learning. For example, the problematic use of short videos was reported as negatively affecting students’ behavioral engagement, while behavioral engagement positively affected students’ emotional and cognitive engagement ( Ye et al., 2023 ). Meral (2019) highlighted that students’ learning attitudes and academic performance had a negative relationship with students’ addiction to online games. Demir and Kutlu (2018) found that online game addiction negatively affects students’ learning motivation. As the level of students’ game addiction increased, the level of their communication skills decreased ( Kanat, 2019 ). Furthermore, Tsai et al. (2020) pointed out a negative correlation between online game addiction and peer relationships as well as students’ learning attitudes. According to the results of the research model validation, it can be observed that: online game addiction negatively affected behavioral engagement, emotional engagement, and cognitive engagement. Therefore, it can be stated that online game addiction had significant and negative effects on all dimensions of learning engagement.

Online game addiction in the present study included aspects of computer game addiction and mobile phone game addiction. The results of the present study are consistent with the findings of Gao et al. (2021) , Choi (2019) , and Qi et al. (2020) , who pointed out that college students’ addiction to cell phones negatively affected their learning engagement.

4.7.2. Analysis of the relationship between learning engagement and reduced academic achievement motivation

For technology education in higher education, students’ intrinsic motivation for academic study predicts their learning engagement ( Dunn and Kennedy, 2019 ). In addition, learning engagement is positively correlated with academic achievement ( Fredricks and McColskey, 2012 ). Based on the research model validation results, behavioral, emotional, and cognitive engagement all negatively affected reduced academic achievement motivation. The findings are consistent with Hu et al.’s (2021) study which pointed out that cognitive engagement in the learning engagement dimension had the most significant effect on students’ academic achievement, and that emotional engagement was also an essential factor influencing students’ academic achievement. Lau et al. (2008) showed that achievement motivation positively predicted cognitive engagement in the learning engagement dimension. Mih et al. (2015) noted that achievement motivation positively predicted behavioral and emotional engagement in the learning engagement dimension. The present study supported the above discussion by confirming the association between learning engagement and reduced academic achievement motivation.

4.7.3. Analysis of the mediating role of learning engagement

According to the indirect effects analysis results of the present study, learning engagement negatively mediated the relationship between online game addiction and reduced academic achievement motivation. The findings support Haji Anzehai’s (2020) conclusion that social network addiction negatively correlated with students’ motivation to progress ( Haji Anzehai, 2020 ). It is also consistent with the findings of Chen and Gu (2019) that students addicted to online games generally had lower academic achievement motivation due to a lack of precise academic planning and motivation. Cao et al. (2008) found a significant negative correlation between Internet addiction and students’ achievement motivation. Similarly, Zhang et al. (2018) explored the intrinsic influencing mechanism of students’ Internet addiction on academic achievement decline in their late adolescence by identifying learning engagement as the important mediating variable. Li et al. (2019) proposed that social networking site addiction among college students significantly negatively affected learning engagement and that learning engagement mediated the relationship between social network addiction and students’ academic achievement. The present study findings also support the discussion above.

5. Conclusion and suggestions

5.1. conclusion.

Currently, the problem of online game addiction among college students is increasing. The relationship between online game addiction, learning engagement, and reduced academic achievement motivation still needs to be explored. The present study explored the relationships between the three aforementioned variables by performing SEM. The results of the study indicated that: (1) online game addiction negatively affected behavioral engagement; (2) online game addiction negatively affected emotional engagement; (3) online game addiction negatively affected cognitive engagement; (4) behavioral engagement negatively affected reduced academic achievement motivation; (5) emotional engagement negatively affected reduced academic achievement motivation; (6) cognitive behavioral engagement negatively affected reduced academic achievement motivation; (7) learning engagement mediated the relationship between online game addiction and reduced academic achievement motivation.

According to the research results, when college students are addicted to online games, their learning engagement can be affected, which may decrease their behavioral, emotional, and cognitive engagement; their academic achievement motivation may be further reduced and affect their academic success or even prevent them from completing their studies. The mediating role of learning engagement between online game addiction and reduced academic achievement motivation indicates that reduced academic achievement motivation influenced by online game addiction could be prevented or weakened by enhancing learning engagement.

5.2. Suggestions

Universities and families play a crucial role in preventing online game addiction among college students. One of the main reasons college students play online games may be that they lack an understanding of other leisure methods and can only relieve their psychological pressure through online games ( Fan and Gai, 2022 ). Therefore, universities should enrich college students’ after-school leisure life and help them cultivate healthy hobbies and interests. Besides, a harmonious parent–child relationship positively affects children’s learning engagement ( Shao and Kang, 2022 ). Parents’ stricter demands may aggravate children’s game addiction ( Baturay and Toker, 2019 ). Therefore, parents should assume a proper perspective on the rationality of gaming and adopt the right approach to guide their children.

One key factor influencing the quality of higher education is students’ learning engagement. The integration of educational information technology has disrupted traditional teaching methods. This trend has accelerated in the context of COVID-19. College students’ growth mindset can impact their learning engagement through the role of the perceived COVID-19 event strength and perceived stress ( Zhao et al., 2021 ). Moreover, students’ self-regulated learning and social presence positively affect their learning engagement in online contexts ( Miao and Ma, 2022 ). Students’ liking of the teacher positively affects their learning engagement ( Lu et al., 2022 ). Their perceived teacher support also positively affects their learning engagement ( An et al., 2022 ). Hence, educators should focus on teacher support and care in the teaching and learning process.

Students’ motivation for academic achievement can often be influenced by active interventions. Cheng et al. (2022) noted that the cumulative process of students gaining successful experiences contributed to an increased sense of self-efficacy, motivating them to learn. Zhou (2009) illustrated that cooperative learning motivated students’ academic achievement. In addition, Hong J. C. et al. (2021) showed that poor parent–child relationships (such as the behavior of “mama’ s boy” in adults) had a negative impact on students’ academic achievement motivation, and they concluded that cell phone addiction was more pronounced among students with low academic achievement motivation. Hence, enhancing students’ academic achievement motivation also requires family support.

5.3. Research limitations and suggestions for future research

Most of the past studies on the impact of online game addiction on academics have used quantitative research as the research method. The qualitative research approach regarding students’ online game addiction should not be neglected. By collecting objective factual materials in the form of qualitative research such as interviews a greater understanding of students’ actual views on games and the psychological factors of addiction can be achieved. Therefore, future studies could introduce more qualitative research to study online game addiction.

To pay attention to the problem of students’ online game addiction, universities and families should not wait until they become addicted and try to remedy it, but should start to prevent it before it gets to that stage. In terms of developing students’ personal psychological qualities, students’ sensation-seeking and loneliness can significantly affect their tendency to become addicted to online games ( Batmaz and Çelik, 2021 ). Adolescents’ pain intolerance problems can also contribute to Internet overuse ( Gu, 2022 ). Emotion-regulation methods affect the emotional experience and play a vital role in Internet addiction ( Liang et al., 2021 ). In this regard, it is necessary to pay attention to students’ mental health status and to guide them to establish correct values and pursue goals through psychological guidance and other means.

In addition to individual factors, different parenting can considerably impact adolescents. Adolescents who tend to experience more developmental assets are less likely to develop IGD ( Xiang et al., 2022a ), and external resources can facilitate the development of internal resources, discouraging adolescents from engaging in IGD ( Xiang et al., 2022b ). Relevant research indicates that the most critical factor in adolescents’ game addiction tendency comes from society or their parents rather than being the adolescents’ fault ( Choi et al., 2018 ). Adolescents who tend to be addicted to online games may have discordant parent–child relationships ( Eliseeva and Krieger, 2021 ). Better father-child and mother–child relationships predict lower initial levels of Internet addiction in adolescents ( Shek et al., 2019 ). Family-based approaches such as improved parent–child relationships and increased communication and understanding among family members can be a direction for adolescent Internet addiction prevention ( Yu and Shek, 2013 ).

At the school level, a close teacher-student relationship is one of the main factors influencing students’ psychological state. Students’ participation in and control over the teaching and learning process as well as their closeness to teachers can increase their satisfaction and thus enhance their learning-related well-being ( Yang J. et al., 2021 ). More school resources can lead to higher adolescent self-control, attenuating students’ online gaming disorders ( Xiang et al., 2022c ).

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author contributions

R-QS, and J-HY: concept and design and drafting of the manuscript. R-QS, and J-HY: acquisition of data and statistical analysis. G-FS, and J-HY: critical revision of the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by Beijing Normal University First-Class Discipline Cultivation Project for Educational Science (Grant number: YLXKPY-XSDW202211). The Project Name is “Research on Theoretical Innovation and Institutional System of Promoting the Modernization of Vocational Education with Modern Chinese Characteristics”.

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.

Publisher’s note

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.

Abedi, G., Rostami, F., and Nadi, A. (2015). Analyzing the dimensions of the quality of life in hepatitis B patients using confirmatory factor analysis. Global J. Health Sci. 7, 22–31. doi: 10.5539/gjhs.v7n7p22

PubMed Abstract | CrossRef Full Text | Google Scholar

Altman, D. G., and Bland, J. M. (2011). How to obtain the confidence interval from a p value. Br. Med. J. 2011:343. doi: 10.1136/bmj.d2090

CrossRef Full Text | Google Scholar

An, F., Yu, J., and Xi, L. (2022). Relationship between perceived teacher support and learning engagement among adolescents: mediation role of technology acceptance and learning motivation. Front. Psychol. 13:992464. doi: 10.3389/fpsyg.2022.992464

Awang, Z. (2015). SEM made simple, a gentle approach to learning structural equation modeling . MPWS Rich Publication. Bangi.

Google Scholar

Axelson, R. D., and Flick, A. (2010). Defining student engagement. Change 43, 38–43. doi: 10.1080/00091383.2011.533096

Bakar, K. A., Tarmizi, R. A., Mahyuddin, R., Elias, H., Luan, W. S., and Ayub, A. F. M. (2010). Relationships between university students’ achievement motivation, attitude and academic performance in Malaysia. Procedia Soc. Behav. Sci. 2, 4906–4910. doi: 10.1016/j.sbspro.2010.03.793

Batmaz, H., and Çelik, E. (2021). Examining the online game addiction level in terms of sensation seeking and loneliness in university students. Addicta 8, 126–130. doi: 10.5152/ADDICTA.2021.21017

Baturay, M. H., and Toker, S. (2019). Internet addiction among college students: some causes and effects. Educ. Inf. Technol. 24, 2863–2885. doi: 10.1007/s10639-019-09894-3

Birch, S., and Ladd, G. (1997). The teacher-child relationship and children’s early school adjustment. Journal of School Psychology 35, 61–79. doi: 10.1016/S0022-4405(96)00029-5

Brunstein, J. C., and Heckhausen, H. (2018). “Achievement motivation,” in Motivation and action . eds. J. Heckhausen and H. Heckhausen (New York, NY: Springer), 221–304.

Cao, H., Cao, P., Wang, P., and Wang, X. H. (2008). An exploration of the interrelationship between internet addiction and achievement motivation among middle school students. J. Beijing Youth Polit. College 2008, 31–38.

Chapman, E. (2002). Alternative approaches to assessing student engagement rates. Pract. Assess. Res. Eval. 8:13. doi: 10.7275/3e6e-8353

Chen, C. G., and Gu, X. Q. (2019). The impact of online games on students’ subject literacy and social inclusion - an analysis based on PISA 2015 test data from four Chinese provinces and cities. Open Educat. Res. 25, 73–87. doi: 10.13966/j.cnki.kfjyyj.2019.05.008

Cheng, B. J., Chen, P., and Chen, Y. S. (2022). The influence of academic achievement motivation on technical learning engagement of students with specialization in physical education faculty: the mediating role of self-efficacy. J. Southwest Univ. 47, 96–106. doi: 10.13718/j.cnki.xsxb.2022.04.014

China Youth Network (2019). Survey on online hames for college students . Available at: http://edu.youth.cn/jyzx/jyxw/201904/t20190415_11926323.htm

Choi, S. (2019). Relationships between smartphone usage, sleep patterns and nursing students’ learning engagement. J. Korean Biol. Nurs. Sci. 21, 231–238. doi: 10.7586/jkbns.2019.21.3.231

Choi, C., Hums, M. A., and Bum, C. H. (2018). Impact of the family environment on juvenile mental health: eSports online game addiction and delinquency. Int. J. Environ. Res. Public Health 15:2850. doi: 10.3390/ijerph15122850

Cui, J., Yang, K. B., Yang, Q. Y., Liu, Y., Zhao, R. J., Wu, W., et al. (2021). Psychological influences of online game addiction among college students in Chengde City. Chin. J. Drug Depend 30, 296–300+305. doi: 10.13936/j.cnki.cjdd1992.2021.04.011

Demir, Y., and Kutlu, M. (2018). Relationships among Internet addiction, academic motivation, academic procrastination and school attachment in adolescents. Int. Online J. Educat. Sci. 10, 315–332. doi: 10.15345/iojes.2018.05.020

Dincer, A., Yeşilyurt, S., Noels, K. A., and Vargas Lascano, D. I. (2019). Self-determination and classroom engagement of EFL Learners: a mixed-methods study of the self-system model of motivational development. SAGE Open 9:215824401985391. doi: 10.1177/2158244019853913

Dunn, T. J., and Kennedy, M. (2019). Technology enhanced learning in higher education; motivations, engagement and academic achievement. Comput. Educ. 137, 104–113. doi: 10.1016/j.compedu.2019.04.004

Durak, H. Y. (2018). Investigation of nomophobia and smartphone addiction predictors among adolescents in Turkey: demographic variables and academic performance. Soc. Sci. J. 56, 492–517. doi: 10.1016/j.soscij.2018.09.003

Eliseeva, M. I., and Krieger, E. E. (2021). The peculiarities of parent-child relationship among teenagers who are addicted to online games. Psychol. Educat. Stud. 13, 51–67. doi: 10.17759/psyedu.2021130304

Eliyani, E., and Sari, N. F. (2021). The effect of online game activities on student learn motivation. Jurnal Pelita Pendidikan 9, 65–70. doi: 10.24114/jpp.v9i2.23843

Elliot, A. J., and Church, M. A. (1997). A hierarchical model of approach and avoidance achievement motivation. J. Pers. Soc. Psychol. 72, 218–232. doi: 10.1037/0022-3514.72.1.218

Esposito, M. R., Serra, N., Guillari, A., Simeone, S., Sarracino, F., Continisio, G. I., et al. (2020). An investigation into video game addiction in pre-adolescents and adolescents: a cross-sectional study. Medicina 56:221. doi: 10.3390/medicina56050221

Fan, H., and Gai, X. Y. (2022). A survey study on contemporary college students’ leisure activities and online gaming behavior. Campus Life Mental Health 20, 12–16. doi: 10.19521/j.cnki.1673-1662.2022.01.002

Finn, J. D. (1989). Withdrawing from school. Rev. Educ. Res. 59, 117–142. doi: 10.3102/00346543059002117

Finn, J. D., Pannozzo, G. M., and Voelkl, K. E. (1995). Disruptive and inattentive-withdrawn behavior and achievement among fourth graders. Elem. Sch. J. 95, 421–434. doi: 10.1086/461853

Fredricks, J. A., Blumenfeld, P. C., and Paris, A. H. (2004). School engagement: potential of the concept, state of the evidence. Rev. Educ. Res. 74, 59–109. doi: 10.3102/00346543074001059

Fredricks, J. A., and McColskey, W. (2012). “The measurement of student engagement: a comparative analysis of various methods and student self-report instruments,” in Handbook of research on student engagement (New York, NY: Springer), 763–782.

Gao, B., Zhu, S. J., and Wu, J. L. (2021). The relationship between cell phone addiction and learning engagement among college students: the mediating role of self-control and the moderating role of core self-evaluation. Psychol. Dev. Educ. 37, 400–406. doi: 10.16187/j.cnki.issn1001-4918.2021.03.11

Gu, M. (2022). Understanding the relationship between distress intolerance and problematic internet use: the mediating role of coping motives and the moderating role of need frustration. J. Adolesc. 94, 497–512. doi: 10.1002/jad.12032

Guo, J. P., Liu, G. Y., and Yang, L. Y. (2021). Mechanisms and models influencing college students’ learning engagement – a survey based on 311 undergraduate higher education schools. Educ. Res. 42, 104–115.

Hafiz, B., and Shaari, J. A. N. (2013). “Confirmatory factor analysis (CFA) of first order factor measurement model-ICT empowerment in Nigeria,” in International Journal of Business Management and Administration . 2, 81–88.

Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate data analysis (7th. New York Pearson Prentice Hall.

Hair, J. F., Hult, T. M., Ringle, C. M., and Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM) . Thousand Oaks, CA SAGE.

Hair, J. F., Ringle, C. M., and Sarstedt, M. (2011). PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19, 139–152. doi: 10.2753/MTP1069-6679190202

Haji Anzehai, Z. (2020). Correlation between self-efficacy and addiction to social networks with the motivation of academic achievement in high school students in Tehran. J. Health Promot. Manag. 9, 72–86.

Han, J., and Lu, Q. (2018). “A correlation study among achievement motivation, goal-setting and L2 learning strategy in EFL context,” in English Language Teaching . 11, 5–14.

Hong, J. C., Ye, J. N., Ye, J. H., Wang, C. M., and Cui, Y. T. (2021). Perceived helicopter parenting related to vocational senior high school students’ academic achievement and smartphone addiction. J. Res. Educat. Sci. 66, 1–33. doi: 10.6209/JORIES.202112_66(4).0001

Hong, R. Z., Ye, J. N., Ye, J. H., Wang, C. M., and Cui, Y. T. (2021). A study on the correlation between “mummy’s boys” behavior awareness, academic achievement motivation and cell phone addiction among technology-based high school students. J. Educat. Sci. Res. 66, 1–33. doi: 10.6209/JORIES.202112_66(4).0001

Hu, Q. Z., Wang, L. Y., and Gao, S. B. (2021). The effect of physics teacher trainees’ learning engagement on academic achievement. Higher Educat. Sci. 2021, 53–60.

Hwang, M. Y., Hong, J. C., Ye, J. H., Wu, Y. F., Tai, K. H., and Kiu, M. C. (2019). Practicing abductive reasoning: the correlations between cognitive factors and learning effects. Comput. Educ. 138, 33–45. doi: 10.1016/j.compedu.2019.04.014

Kahu, E. R., and Nelson, K. (2018). Student engagement in the educational interface: understanding the mechanisms of student success. High. Educ. Res. Dev. 37, 58–71. doi: 10.1080/07294360.2017.1344197

Kanat, S. (2019). The relationship between digital game addiction, communication skills and loneliness perception levels of university students. Int. Educ. Stud. 12, 80–93. doi: 10.5539/ies.v12n11p80

Kenny, D. A., Kaniskan, B., and McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociol. Methods Res. 44, 486–507. doi: 10.1177/0049124114543236

Kesici, A. (2020). The effect of conscientiousness and gender on digital game addiction in high school students. J. Educ. Fut. 18, 43–53. doi: 10.30786/jef.543339

Khan, A., Ahmad, F. H., and Malik, M. M. (2017). Use of digital game based learning and gamification in secondary school science: the effect on student engagement, learning and gender difference. Educ. Inf. Technol. 22, 2767–2804. doi: 10.1007/s10639-017-9622-1

Kuh, G. D., Kinzie, J., Cruce, T., Shoup, R., and Gonyea, R. M. (2007). Connecting the dots: multi-faceted analyses of the relationships between student engagement results from the NSSE, and the institutional practices and conditions that foster student success . Bloomington, IN: Indiana University Center for Postsecondary Research.

Lau, S., Liem, A. D., and Nie, Y. (2008). Task-and self-related pathways to deep learning: the mediating role of achievement goals, classroom attentiveness, and group participation. Br. J. Educ. Psychol. 78, 639–662. doi: 10.1348/000709907X270261

Li, Y., Yao, C., Zeng, S., Wang, X., Lu, T., Li, C., et al. (2019). How social networking site addiction drives university students’ academic achievement: the mediating role of learning engagement. J. Pac. Rim Psychol. 13:e19. doi: 10.1017/prp.2019.12

Liang, L., Zhu, M., Dai, J., Li, M., and Zheng, Y. (2021). The mediating roles of emotional regulation on negative emotion and internet addiction among Chinese adolescents from a development perspective. Front. Psych. 12:608317. doi: 10.3389/fpsyt.2021.608317

Lu, L., Zhang, L., and Wang, L. (2022). The relationship between vocational college students’ liking of teachers and learning engagement: a moderated mediation model. Front. Psychol. 13:998806. doi: 10.3389/fpsyg.2022.998806

Luan, L., Hong, J. C., Cao, M., Dong, Y., and Hou, X. (2020). Exploring the role of online EFL learners’ perceived social support in their learning engagement: a structural equation model. Interact. Learn. Environ. 31, 1703–1714. doi: 10.1080/10494820.2020.1855211

MacKinnon, D. P. (2012). Introduction to statistical mediation analysis . New York Routledge.

McClelland, D. C., Atkinson, J. W., Clark, R. A., and Lowell, E. L. (1976). The achievement motive . Appleton-Century-Crofts, New York.

Mendoza, J. S., Pody, B. C., Lee, S., Kim, M., and McDonough, I. M. (2018). The effects of cellphones on attention and learning: the influence of time, distraction, and nomophobia. Comput. Hum. Behav. 86, 52–60. doi: 10.1016/j.chb.2018.04.027

Meral, S. A. (2019). Students’ attitudes towards learning, a study on their academic achievement and internet addiction. World J. Educat. 9, 109–122. doi: 10.5430/wje.v9n4p109

Miao, J., and Ma, L. (2022). Students’ online interaction, self-regulation, and learning engagement in higher education: the importance of social presence to online learning. Front. Psychol. 13:815220. doi: 10.3389/fpsyg.2022.815220

Mih, V., Mih, C., and Dragoş, V. (2015). Achievement goals and behavioral and emotional engagement as precursors of academic adjusting. Procedia Soc. Behav. Sci. 209, 329–336. doi: 10.1016/j.sbspro.2015.11.243

Nakagawa, S., and Cuthill, I. C. (2007). Effect size, confidence interval and statistical significance: a practical guide for biologists. Biol. Rev. 82, 591–605. doi: 10.1111/j.1469-185X.2007.00027.x

Nong, W., He, Z., Ye, J.-H., Wu, Y.-F., Wu, Y.-T., Ye, J. N., et al. (2023). The relationship between short video flow, addiction, serendipity, and achievement motivation among Chinese vocational school students: the post-epidemic era context. Healthcare 11:462. doi: 10.3390/healthcare11040462

Pan, Y., Zhou, D., and Shek, D. T. L. (2022). Participation in after-school extracurricular activities and cognitive ability among early adolescents in China: moderating effects of gender and family economic status. Front. Pediatr. 10:839473. doi: 10.3389/fped.2022.839473

Qi, H. Y., Liu, J. H., Hou, Y. H., Fan, W. F., Hou, J. P., and Wang, X. Y. (2020). The effect of cell phone addiction types on college students’ learning engagement. Health Prot. Promot. 2020, 88–91. doi: 10.3969/j.issn.1671-0223(x).2020.05.023

Rozgonjuk, D., Saal, K., and That, K. (2018). Problematic smartphone use, deep and surface approaches to learning, and social media use in lectures. Int. J. Environ. Res. Public Health 15:92. doi: 10.3390/ijerph15010092

Saeid, N., and Eslaminejad, T. (2017). Relationship between student’s self-directed-learning readiness and academic self-efficacy and achievement motivation in students. Int. Educ. Stud. 10, 225–232. doi: 10.5539/ies.v10n1p225

Schaufeli, W. B., Martinez, I. M., Pinto, A. M., Salanova, M., and Bakker, A. B. (2002). Burnout and engagement in university students: a cross-national study. J. Cross-Cult. Psychol. 33, 464–481. doi: 10.1177/0022022102033005003

Selya, A. S., Rose, J. S., Dierker, L. C., Hedeker, D., and Mermelstein, R. J. (2012). A practical guide to calculating Cohen’s f 2 , a measure of local effect size, from PROC MIXED. Front. Psychol. 3:111. doi: 10.3389/fpsyg.2012.00111

Shao, Y., and Kang, S. (2022). The link between parent-child relationship and learning engagement among adolescents: the chain mediating roles of learning motivation and academic self-efficacy. Front. Educat. 7:854549. doi: 10.3389/feduc.2022.854549

Shek, D. T., Zhu, X., and Dou, D. (2019). Influence of family processes on internet addiction among late adolescents in Hong Kong. Front. Psych. 10:113. doi: 10.3389/fpsyt.2019.00113

Shumacker, R. E., and Lomax, R. G. (2016). A beginner’s guide to structural equation modeling (4th) New York, NY: Routledge.

Sopiah, C. (2021). The influence of parenting style, achievement motivation and self-regulation on academic achievement. Turk. J. Comput. Math. Educ. 12, 1730–1742. doi: 10.17762/turcomat.v12i10.4635

Stipek, D. (2002). “Good instruction is motivating” in Development of achievement motivation . eds. A. Wigfield and J. Eccles (San Diego, CA: Academic Press)

Story, P. A., Hart, J. W., Stasson, M. F., and Mahoney, J. M. (2009). Using a two-factor theory of achievement motivation to examine performance-based outcomes and self-regulatory processes. Personal. Individ. Differ. 46, 391–395. doi: 10.1016/j.paid.2008.10.023

Sunday, O. J., Adesope, O. O., and Maarhuis, P. L. (2021). The effects of smartphone addiction on learning: a meta-analysis. Comput. Hum. Behav. Rep. 4:100114. doi: 10.1016/j.chbr.2021.100114

Teng, Z., Pontes, H. M., Nie, Q., Griffiths, M. D., and Guo, C. (2021). Depression and anxiety symptoms associated with internet gaming disorder before and during the COVID-19 pandemic: a longitudinal study. J. Behav. Addict. 10, 169–180. doi: 10.1556/2006.2021.00016

Thompson, B. (2002). What future quantitative social science research could look like: confidence intervals for effect sizes. Educ. Res. 31, 25–32. doi: 10.3102/0013189X031003025

Tian, J., Zhao, J. Y., Xu, J. M., Li, Q. L., Sun, T., Zhao, C. X., et al. (2021). Mobile phone addiction and academic procrastination negatively impact academic achievement among Chinese medical students. Front. Psychol. 12:758303. doi: 10.3389/fpsyg.2021.758303

Tsai, S. M., Wang, Y. Y., and Weng, C. M. (2020). A study on digital games internet addiction, peer relationships and learning attitude of senior grade of children in elementary school of Chiayi county. J. Educat. Learn. 9, 13–26. doi: 10.5539/jel.v9n3p13

Wang, M. T., and Eccles, J. S. (2013). School context, achievement motivation, and academic engagement: a longitudinal study of school engagement using a multidimensional perspective. Learn. Instr. 28, 12–23. doi: 10.1016/j.learninstruc.2013.04.002

Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychol. Rev. 92, 548–573. doi: 10.1037/0033-295X.92.4.548

World Health Organization (WHO) (2018a). Inclusion of “gaming disorder” in ICD-11 . Available at: https://www.who.int/news/item/14-09-2018-inclusion-of-gaming-disorder-in-icd-11

World Health Organization (WHO) (2018b). WHO releases new international classification of diseases (ICD11) . Available at: https://www.who.int/news/item/18-06-2018-who-releases-new-international-classification-of-diseases-(icd-11)

Wu, Y.-T., Hong, J.-C., Wu, Y.-F., and Ye, J.-H. (2021). eSport addiction, purchasing motivation and continuous purchasing intention on eSport peripheral products. Int. J. e-Education e-Business e-Management e-Learning 11, 21–33. doi: 10.17706/ijeeee.2021.11.1.21-33

Xiang, G. X., Gan, X., Jin, X., and Zhang, Y. H. (2022a). The more developmental assets, the less internet gaming disorder? Testing the cumulative effect and longitudinal mechanism during the COVID-19 pandemic. Curr. Psychol. 1–12, 1–12. doi: 10.1007/s12144-022-03790-9

Xiang, G. X., Gan, X., Jin, X., Zhang, Y. H., and Zhu, C. S. (2022b). Developmental assets, self-control and internet gaming disorder in adolescence: testing a moderated mediation model in a longitudinal study. Front. Public Health 10:808264. doi: 10.3389/fpubh.2022.808264

Xiang, G. X., Li, H., Gan, X., Qin, K. N., Jin, X., and Wang, P. Y. (2022c). School resources, self-control and problem behaviors in Chinese adolescents: a longitudinal study in the post-pandemic era. Curr. Psychol. 1-13, 1–13. doi: 10.1007/s12144-022-04178-5

Xiong, Y., Li, H., Kornhaber, M. L., Suen, H. K., Pursel, B., and Goins, D. D. (2015). Examining the relations among student motivation, engagement, and retention in a MOOC: a structural equation modeling approach. Glob. Educ. Rev. 2, 23–33.

Yang, J., Peng, M. Y. P., Wong, S., and Chong, W. (2021). How E-learning environmental stimuli influence determinates of learning engagement in the context of COVID-19? SOR model perspective. Front. Psychol. 12:584976. doi: 10.3389/fpsyg.2021.584976

Yang, X., Zhang, M., Kong, L., Wang, Q., and Hong, J. C. (2021). The effects of scientific self-efficacy and cognitive anxiety on science engagement with the “question-observation-doing-explanation” model during school disruption in COVID-19 pandemic. J. Sci. Educ. Technol. 30, 380–393. doi: 10.30773/pi.2020.0034

Yayman, E., and Bilgin, O. (2020). Relationship between social media addiction, game addiction and family functions. Int. J. Evaluat. Res. Educat. 9, 979–986. doi: 10.11591/ijere.v9i4.20680

Ye, J. H., Wang, C. M., and Ye, J. N. (2020). An analysis of the relationship between achievement motivation, learning engagement and continuous improvement attitudes of technical vocational college students. J. Natl. Taichung Univ. Sci. Technol. 7, 1–20. doi: 10.6902/JNTUST.202012_7(2).0001

Ye, J. H., Wu, Y. F., Nong, W., Wu, Y. T., Ye, J. N., and Sun, Y. (2023). The association of short-video problematic use, learning engagement, and perceived learning ineffectiveness among Chinese vocational students. Healthcare 11:161. doi: 10.3390/healthcare11020161

Ye, J. H., Wu, Y. T., Wu, Y. F., Chen, M. Y., and Ye, J. N. (2022). Effects of short video addiction on the motivation and well-being of Chinese vocational college students. Front. Public Health 10:847672. doi: 10.3389/fpubh.2022.847672

Yu, L., and Shek, D. T. L. (2013). Internet addiction in Hong Kong adolescents: a three-year longitudinal study. J. Pediatr. Adolesc. Gynecol. 26, S10–S17. doi: 10.1016/j.jpag.2013.03.010

Zhang, N. (2012). A review of Chinese domestic and international research on learning engagement and its school influences. Psychol. Res. 5, 83–92.

Zhang, Y., Qin, X., and Ren, P. (2018). Adolescents’ academic engagement mediates the association between internet addiction and academic achievement: the moderating effect of classroom achievement norm. Comput. Hum. Behav. 89, 299–307. doi: 10.1016/j.chb.2018.08.018

Zhao, H., Xiong, J., Zhang, Z., and Qi, C. (2021). Growth mindset and college students’ learning engagement during the COVID-19 pandemic: a serial mediation model. Front. Psychol. 12:621094. doi: 10.3389/fpsyg.2021.621094

Zhou, H. (2009). The effect of cooperative learning in basketball teaching on social behavior and academic achievement motivation. Zhejiang Sport Sci. 31, 109–112.

Keywords: college students, online game addiction, learning engagement, reduced academic achievement motivation, online games

Citation: Sun R-Q, Sun G-F and Ye J-H (2023) The effects of online game addiction on reduced academic achievement motivation among Chinese college students: the mediating role of learning engagement. Front. Psychol . 14:1185353. doi: 10.3389/fpsyg.2023.1185353

Received: 13 March 2023; Accepted: 08 June 2023; Published: 13 July 2023.

Reviewed by:

Copyright © 2023 Sun, Sun and Ye. 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: Jian-Hong Ye, [email protected]

† 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.

An official website of the United States government

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

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

• Publications
• Account settings

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

• Advanced Search
• Journal List
• Front Psychol

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

Julie Bignill

Vasileios stavropoulos.

2 Institute of Health and Sports, Victoria University, Melbourne, VIC, Australia

3 School of Psychology, National and Kapodistrian University of Athens, Athens, Greece

Prudence Millear

Andrew allen, helen m. stallman.

4 Thompson Institute, University of the Sunshine Coast, Maroochydore, QLD, Australia

Jonathan Mason

Tamara de regt, andrew wood, lee kannis-dymand, associated data.

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

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.

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.

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

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.

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.

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

• Adams B. L., Stavropoulos V., Burleigh T. L., Liew L. W., Beard C. L., 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. 10.1007/s11469-018-9873-0 [ CrossRef ] [ Google Scholar ]
• Ahlstrom M., Lundberg N. R., Zabriskie R., Eggett D., 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. 10.1080/00222216.2012.11950252 [ CrossRef ] [ Google Scholar ]
• Alha K., Koskinen E., Paavilainen J., Hamari J. (2019). Why do people play location-based augmented reality games: a study on Pokémon GO . Comput. Hum. Behav. 93 , 114–122. 10.1016/j.chb.2018.12.008 [ CrossRef ] [ Google Scholar ]
• American Psychiatric Association . (2013). Diagnostic and Statistical Manual of Mental Health Disorders, 5th Edn. Washington, DC: American Psychiatric Publishing. 10.1176/appi.books.9780890425596 [ CrossRef ] [ Google Scholar ]
• Barnett J., Coulson M. (2010). Virtually real: a psychological perspective on massively multiplayer online games . Rev. Gen. Psychol. 14 , 167–179. 10.1037/a0019442 [ CrossRef ] [ Google Scholar ]
• BeStreamer. (2020). 10 most played MMORPGS of 2020 . Available online at: https://bestreamer.com/gaming/most-played-mmorpg-2019/
• Brand J. E., Jervis J., Huggins P. M., 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., 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 Pachana N. A. (Singapore: Springer; ), 1–8. 10.1007/978-981-287-080-3_251-1 [ CrossRef ] [ Google Scholar ]
• 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. 10.1016/j.chb.2018.10.016 [ CrossRef ] [ Google Scholar ]
• Choi J. W. (2019). An influence of game avatar on real world . Int. J. Innovat. Technol. Explo. Eng. 8 , 2935–2940. 10.35940/ijitee.K1906.1081219 [ CrossRef ] [ Google Scholar ]
• 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., 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. 10.1371/journal.pone.0240032 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cole D. A., Nick E. A., 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. 10.1016/j.chb.2019.08.012 [ CrossRef ] [ Google Scholar ]
• Doh Y. Y., 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. 10.1177/1555412013498301 [ CrossRef ] [ Google Scholar ]
• Downes M. J., Brennan M. L., Williams H. C., Dean R. S. (2016). Development of a critical appraisal tool to assess the quality of cross-sectional studies (AXIS) . BMJ Open 6 :e011458. 10.1136/bmjopen-2016-011458 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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., 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 [ Google Scholar ]
• Gallup J., Serianni B., Duff C., 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 [ Google Scholar ]
• Goh C., Jones C., 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. 10.1007/s11126-019-09656-x [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Greenhalgh T., Robert G., Macfarlane F., Bate P., Kyriakidou O., Peacock R. (2005). Storylines of research in diffusion of innovation: A meta-narrative approach to systematic review . Soc. Sci. Med. 61 , 417–430. 10.1016/j.socscimed.2004.12.001 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Halbrook Y. J., O'Donnell A. T., 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. 10.1177/1745691619863807 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. 10.3233/EFI-180221 [ CrossRef ] [ Google Scholar ]
• 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., Carras M. C. (2014). Gaming well: Links between videogames and flourishing mental health . Front. Psychol. 5 :260. 10.3389/fpsyg.2014.00260 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kaye L. K., Kowert R., Quinn S. (2017). The role of social identity and online social capital on psychosocial outcomes in MMO players . Comput. Hum. Behav. 74 , 215–223. 10.1016/j.chb.2017.04.030 [ CrossRef ] [ Google Scholar ]
• Kircaburun K., Pontes H. M., Stavropoulos V., Griffiths M. D. (2020). A brief psychological overview of disordered gaming . Curr. Opin. Psychol. 36 , 38–43. 10.1016/j.copsyc.2020.03.004 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. 10.1007/s11920-014-0508-2 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Linton M. J., Dieppe P., 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. 10.1136/bmjopen-2015-010641 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Liu M., 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: ). [ Google Scholar ]
• Männikkö N., Ruotsalainen H., Miettunen J., Pontes H. M., Kääriäinen M. (2017). Problematic gaming behaviour and health-related outcomes: a systematic review and meta-analysis . J. Health Psychol. 25 , 67–81. 10.1177/1359105317740414 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Martončik M., 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. 10.1016/j.chb.2015.11.035 [ CrossRef ] [ Google Scholar ]
• Meng J., Williams D., 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. 10.1016/j.chb.2015.06.007 [ CrossRef ] [ Google Scholar ]
• Moher D., Liberati A., Tetzlaff J., Altman D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement . PLoS Med. 6 :e1000097. 10.1371/journal.pmed.1000097 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• O'Connor E. L., Longman H., White K. M., 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. 10.1002/casp.2224 [ CrossRef ] [ Google Scholar ]
• 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. 10.1016/j.chb.2017.10.032 [ CrossRef ] [ Google Scholar ]
• 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., Griffiths M. D. (2020). Emerging insights on internet gaming disorder: conceptual and measurement issues . Addict. Behav. Rep. 11 :100242. 10.1016/j.abrep.2019.100242 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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., 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. 10.1155/2013/464685 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Seligman M. E. (2011). Flourish: The New Positive Psychology and the Search for Well-Being . New York, NY: Free Press. [ Google Scholar ]
• 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. 10.1136/bmj.g7647 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Shen C., 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. 10.1016/j.chb.2015.05.053 [ CrossRef ] [ Google Scholar ]
• Sourmelis T., Ioannou A., 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. 10.1016/j.chb.2016.10.020 [ CrossRef ] [ Google Scholar ]
• 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., Motti-Stefanidi F. (2019). Internet gaming disorder: a pathway towards assessment consensus . Front. Psychol. 10 :1822. 10.3389/fpsyg.2019.01822 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stavropoulos V., Gomez R., Mueller A., Yucel M., Griffiths M. (2020). User-avatar bond profiles: How do they associate with disordered gaming? Addict. Behav. 103 :106245. 10.1016/j.addbeh.2019.106245 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sublette V., Mullan B. (2012). Consequences of play: a systematic review of the effects of online gaming . Int. J. Ment. Health Addict. 10 , 3–23. 10.1007/s11469-010-9304-3 [ CrossRef ] [ Google Scholar ]
• Teng Z., Pontes H. M., Nie Q., Xiang G., Griffiths M. D., Guo C. (2020). Internet gaming disorder and psychosocial well-being: a longitudinal study of older-aged adolescents and emerging adults . Addict. Behav. 110 :106530. 10.1016/j.addbeh.2020.106530 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Voulgari I., Komis V., 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. 10.1007/s11423-013-9312-7 [ CrossRef ] [ Google Scholar ]
• World Health Organization . (2019). International Statistical Classification of Diseases and Related Health Problems, 11th Edn . Geneva: World Health Organization. [ Google Scholar ]
• Xanthopoulou D., Papagiannidis S. (2012). Play online, work better? Examining the spillover of active learning and transformational leadership . Technol. Forecast. Soc. Change 79 , 1328–1339. 10.1016/j.techfore.2012.03.006 [ CrossRef ] [ Google Scholar ]
• Zhang F., Kaufman D. (2015). The impacts of social interactions in MMORPGs on older adults' social capital . Comput. Hum. Behav. 51 , 495–503. 10.1016/j.chb.2015.05.034 [ CrossRef ] [ Google Scholar ]
• Zhang F., Kaufman D. (2017). Massively multiplayer online role-playing games (MMORPGs) and socio-emotional wellbeing . Comput. Hum. Behav. 73 , 451–458. 10.1016/j.chb.2017.04.008 [ CrossRef ] [ Google Scholar ]
• Zhang F., Kaufman D. P. (2016). Older adults' social interactions in massively multiplayer online role-playing games (MMORPGs) . Games Cult. 11 , 150–169. 10.1177/1555412015601757 [ CrossRef ] [ Google Scholar ]
• Zhonggen Y. (2019). A meta-analysis of use of serious games in education over a decade . Int. J. Comput. Games Technol. 2019 :4797032. 10.1155/2019/4797032 [ CrossRef ] [ Google Scholar ]

Advertisement

A Qualitative Analysis of Online Gaming Addicts in Treatment

• Published: 27 October 2012
• Volume 11 , pages 149–161, ( 2013 )

Cite this article

• Marta Beranuy 1 ,
• Xavier Carbonell 1 , 3 &
• Mark D. Griffiths 2  

5171 Accesses

87 Citations

44 Altmetric

Explore all metrics

Online gaming addiction is a relatively under-researched area and there have been few studies examining online gamers in treatment. This paper reports the findings from a qualitative interview study of nine players undergoing treatment for their addictive playing of Massively Multiplayer Online Role Playing Games (MMORPGs). A face-to-face interview study with nine online gaming addicts was carried out using Grounded Theory. The six most reported phenomena by the participants were: (i) entertainment search, (ii) virtual friendship, (iii) escapism and/or dissociation, (iv) game context, (v) control versus no control, and (vi) conflict. The findings suggest that players’ initial gaming motivation is because of three factors: (i) entertainment, (ii) escapism, and/or (iii) virtual friendship. MMORPG addiction appears once the playing time significantly increases, coupled with a loss of control and a narrow behavior focus. These factors lead to problems and result in psychological dependence and serious life conflicts. The consequences of MMORPG addiction are similar to the consequences of more established substance addictions including salience, mood modification, loss of control, craving, and serious adverse effects. Additionally, in some cases, tolerance and relapse may also be present.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Motivation and Cognitive-Behavioral Factors in Problematic Online Gaming

Why do adults seek treatment for gaming (disorder)? A qualitative study

Veli-Matti Karhulahti, Sanni Behm & Lauri Lukka

Gaming Motivations as a Guide to Treating Problematic Gaming Behaviors

Jason L. Steadman

Allison, S. E., von Wahlde, L., Shockley, T., & Gabbard, G. O. (2006). The development of the self in the era of the Internet and role-playing fantasy games. The American Journal of Psychiatry, 163 , 381–385.

Article   PubMed   Google Scholar  

Beard, K. W. (2005). Internet addiction: a review of current assessment techniques and potential assessment questions. CyberPsychology & Behavior, 8 , 7–14.

Article   Google Scholar  

Bessière, K., Seay, A. F., & Kiesler, S. (2007). The ideal elf: identity exploration in World of Warcraft. Cyberpsychology & Behavior, 10 , 530–535.

Block, J. (2007). Pathological computer game use. Psychiatric Times , 24 (3). Located at: http://www.psychiatrictimes.com/display/article/10168/55406?pageNumber=2 (last accessed: 01.10.12).

Camí, J., & Farré, M. (2003). Drug addiction. The New England Journal of Medicine, 349 , 975–986.

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

Echeburúa, E., & de Corral, P. (1994). Adicciones psicológicas: Más allá de la metáfora. Clínica y Salud, 5 , 251–258.

Google Scholar  

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory . Chicago: Aldine Publishing Company.

Goodman, A. (1990). Addiction, definition and implications. British Journal of Addictions, 85 , 1403–1408.

Article   CAS   Google Scholar  

Griffiths, M. (2000). Does internet and computer “addiction” exist? Some case study evidence. CyberPsychology & Behavior, 3 , 211–218.

Griffiths, M. D. (2005). A “components” model of addiction within a biopsychosocial framework. Journal of Substance Use, 10 , 191–197.

Griffiths, M. D. (2010). The role of context in online gaming excess and addiction: some case study evidence. International Journal of Mental Health and Addiction, 8 , 119–125.

Griffiths, M. D., & Beranuy, M. (2009). Adicción a los videojuegos: Una breve revisión psicológica. Revista de psicoterapia, 73 , 33–49.

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2003). Breaking the stereotype: the case of online gaming. CyberPsychology & Behavior, 6 , 81–91.

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004a). Online computer gaming: a comparison of adolescent and adult gamers. Journal of Adolescence, 27 , 87–96.

Article   PubMed   CAS   Google Scholar  

Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2004b). Demographic factors and playing variables in online computer gaming. CyberPsychology & Behavior, 7 , 479–487.

King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M. (2011). Assessing clinical trials of Internet addiction treatment: a systematic review and CONSORT evaluation. Clinical Psychology Review, 31 , 1110–1116.

Klimmt, C., Schmid, H., & Orthmann, J. (2009). Exploring the enjoyment of playing browser games. CyberPsychology & Behavior, 12 , 231–234.

Kuss, D. J., & Griffiths, M. D. (2012). Online gaming addiction: a systematic review. International Journal of Mental Health and Addiction, 10 , 278–296.

Lafrenière, M. A., Vallerand, R. J., Donahue, E. G., & Lavigne, G. L. (2009). On the costs and benefits of gaming: the role of passion. Cyberpsychology & Behavior, 12 , 285–290.

Lawson, K. D. (2000). Beyond corporeality: the virtual self in postmodern times. Journal of Psychological Practice, 6 (1), 35–43.

McKenna, K. Y. A., & Bargh, J. A. (2000). Plan 9 from cyberspace: the implications of the internet for personality and social psychology. Personality and Social Psychology Review, 4 (1), 57–75.

Reid, E. (1998). The self and the Internet: Variations on the illusion of one self. In J. Gackenbach (Ed.), Psychology and the Internet: Intrapersonal, interpersonal, and transpersonal implications (pp. 29–42). San Diego, CA USA: Academic.

Sánchez-Carbonell, X. (2000). Conductas Adictivas. In A. Jarne & A. Talarn (Eds.), Manual de psicopatología clínica (pp. 597–632). Barcelona: Fundació Vidal i Barraquer i Ediciones Paidós Ibérica.

Sánchez-Carbonell, X., Beranuy, M., Castellana, M., Chamarro, A., & Oberst, U. (2008). La adicción a Internet y al móvil, ¿moda o trastorno? Adicciones, 20 (2), 149–160.

PubMed   Google Scholar  

Smyth, J. (2007). Beyond self-selection in video game play: an experimental examination of the consequences of Massively Multiplayer Online Role-Playing Game Play. CyberPsychology & Behavior, 10 , 717–721.

Smahel, D., Blinka, L., & Ledabyl, O. (2008). Playing MMORPGs: connections between addiction and identifying with a character. CyberPsychology & Behavior, 11 , 715–718.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques . London: Sage.

Talarn, A., & Carbonell, X. (2009). Algunas reflexiones a propósito de los juegos (y los jugadores) de rol online. Identidad y adicción. Revista de Psicoterapia, 19 (73), 51–67.

Turkle, S. (1997). Multiple subjectivity and virtual community at the end of the end of the Freudian century. Sociological Inquiry, 67 , 72–84.

Wan, C., & Chiou, W. (2006a). Psychological motives and online games addiction: a test of flow theory and humanistic needs theory for Taiwanese adolescents. CyberPsychology & Behavior, 9 , 317–324.

Wan, C., & Chiou, B. (2006b). Why are adolescents addicted to online gaming? An Interview Study in Taiwan. Cyberpsychology & Behavior, 9 , 762–766.

Washton, A. M., & Boundy, D. (1990). Willpower’s not enough: Understanding and overcoming addiction and compulsion . New York: Harper Trade.

Widyanto, L., & Griffiths, M. D. (2006). Internet addiction: a critical review. International Journal of Mental Health and Addiction, 4 , 31–51.

Wood, R. T. A., Griffiths, M. D., & Parke, A. (2007). Experiences of time loss among videogame players: an empirical study. CyberPsychology & Behavior, 10 , 45–56.

Download references

Acknowledgments

We thank Josep Cañete and Àngels González (Hospital of Mataró, Spain), Rosa Díaz (Hospital Clínic of Barcelona, Spain), Susanna Petri and Núria Aragay (Hospital of Terrassa, Spain) and Felix Cova and Maruzella Valdivia (Clínica de Atención Psicológica of University of Concepción, Chile).

Part of this study was carried out thanks to grant no. AP2005-2426 (Ministerio de Educación y Ciencia, Spanish Government) and FPCCE Blanquerna grant no. CER05/08-105C06.

Author information

Authors and affiliations.

Faculty of Psychology, Education and Sport Sciences, Universitat Ramon Llull, Barcelona, Spain

Marta Beranuy & Xavier Carbonell

Department of Social Sciences, Nottingham Trent University, Nottingham, UK

Mark D. Griffiths

Facultat de Psicologia, Ciències de l’Educació i de l’Esport Blanquerna, C/Císter, 34, 08022, Barcelona, Spain

Xavier Carbonell

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Xavier Carbonell .

Rights and permissions

Reprints and permissions

About this article

Beranuy, M., Carbonell, X. & Griffiths, M.D. A Qualitative Analysis of Online Gaming Addicts in Treatment. Int J Ment Health Addiction 11 , 149–161 (2013). https://doi.org/10.1007/s11469-012-9405-2

Download citation

Published : 27 October 2012

Issue Date : April 2013

DOI : https://doi.org/10.1007/s11469-012-9405-2

Share this article

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

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

Provided by the Springer Nature SharedIt content-sharing initiative

• Qualitative study
• Internet addiction
• Gaming addiction
• Massively Multiplayer Online Role Playing Games
• MMORPG addiction
• Gaming addiction treatment
• Find a journal
• Publish with us
• Track your research

Academia.edu no longer supports Internet Explorer.

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

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

• We're Hiring!
• Help Center

A Qualitative Analysis of Online Gaming: Social Interaction, Community and Game Design

The popularity of Massively Multi-Player Online Role-Playing Games (MMORPGs) has risen dramatically over the last decade. Some gamers spend many hours a day in these virtual environments interacting with other gamers, completing quests, and forming social groups. The present study set out to explore the experiences and feelings of online gamers. The study comprised 71 interviews with online gamers (52 males and 19 females) from 11 different countries. Many themes emerged from the analyses of the interview transcripts including (i) engaging in social interaction, (ii) being part of a community, (iii) learning real-life skills, (iv) gaining in-game rewards, (v) playing never-ending games (vi) escaping from real life, (vii) playing longer than intended, and (viii) being obligated towards other gamers in-game. These findings specifically showed the many positives of online gaming (including the social interaction and the community aspects of belonging) as well as the in-game features within MMORPGs that in some cases can lead to excessive online gaming. The implications of these findings are discussed in relation to previous qualitative and quantitative research in the area.

Related Papers

International Journal of Cyber Behavior, Psychology and Learning

Zaheer Hussain

The popularity of Massively Multi-Player Online Role-Playing Games (MMORPGs) has risen dramatically over the last decade. Some gamers spend many hours a day in these virtual environments interacting with other gamers, completing quests, and forming social groups. The present study set out to explore the experiences and feelings of online gamers. The study comprised 71 interviews with online gamers (52 males and 19 females) from 11 different countries. Many themes emerged from the analyses of the interview transcripts including (i) engaging in social interaction, (ii) being part of a community, (iii) learning real-life skills, (iv) gaining in-game rewards, (v) playing never-ending games (vi) escaping from real life, (vii) playing longer than intended, and (viii) being obligated towards other gamers in-game. These findings specifically showed the many positives of online gaming (including the social interaction and the community aspects of belonging) as well as the in-game features wi...

CyberPsychology & Behavior

Online Communities and Social Computing

Jacqui Taylor

International Journal of Games-Based Learning, 1, (4), 20-36.

This paper briefly overviews five studies examining massively multiplayer online role-playing games (MMORPGs). The first study surveyed 540 gamers and showed that the social aspects of the game were the most important factor for many gamers. The second study explored the social interactions of 912 MMORPG players and showed they created strong friendships and emotional relationships. A third study examined the effect of online socializing in the lives of 119 online gamers. Significantly more male gamers than female gamers said that they found it easier to converse online than offline, and 57% of gamers had engaged in gender swapping. A fourth study surveyed 7,069 gamers and found that 12% of gamers fulfilled at least three diagnostic criteria of addiction. Finally, an interview study of 71 gamers explored attitudes, experiences, and feelings about online gaming. They provided detailed descriptions of personal problems that had arisen due to playing MMORPGs.

Adler James W

The games industry has grown faster than any other entertainment sector and has recently surpassed global revenues of the music and film industries. Although there are bountiful studies regarding adolescents and young adults’ involvement in online gaming, much of these tackled on psychological correlates, academic, physical and social notion of gamers and not the experiences of the online gamers as a whole. Thus with this gap in knowledge this study aimed at exploring the online gamers’ lived experiences.

Helena Lefever (nee Cole)

To date, most research into massively multiplayer online role-playing games (MMORPGs) has examined the demographics of play. This study explored the social interactions that occur both within and outside of MMORPGs. The sample consisted of 912 self-selected MMORPG players from 45 countries. MMORPGs were found to be highly socially interactive environments providing the opportunity to create strong friendships and emotional relationships. The study demonstrated that the social interactions in online gaming form a considerable element in the enjoyment of playing. The study showed MMORPGs can be extremely social games, with high percentages of gamers making life-long friends and partners. It was concluded that virtual gaming may allow players to express themselves in ways they may not feel comfortable doing in real life because of their appearance, gender, sexuality, and/or age. MMORPGs also offer a place where teamwork, encouragement, and fun can be experienced.

Spanish Journal of Psychology

Hector Fuster

Technology Lifecycle and Workflow Analysis

Vivian Hsueh Hua Chen

Entertainment Computing-ICEC 2006

Henry B.L. Duh

Michael Perez

This study examines the social organization of Gaiscíoch, a large online gaming community that exists within the simulated world of a massively multiplayer online role playing game (MMORPG). It provides an ethnographic account of an online gaming community that is open to any player without skill or time commitment requirements, but still maintains high status within the game world. This project identifies eight elements that make this inclusive, friendly, and casual community successful in virtual worlds that tend to be dominated by communities that have a competitive, strict, and exclusive approach to online gaming (social interaction, code of values, leadership, rank system, events, community building, population size, gameplay). Lastly, this project briefly inquires about the nature of the border between the virtual and the physical and establishes that gamers can be considered pseudo-border-inhabitants that are in control of the community they place adjacent to them in the cyber world.

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024