research questionnaire about online games addiction

Evaluating the Psychometric Properties and Measurement Invariance of the Addiction-Engagement Questionnaire Using a Longitudinal Sample

• Published: 25 June 2021
• Volume 43 , pages 757–765, ( 2021 )

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• Lukas Blinka   ORCID: orcid.org/0000-0003-0380-4744 1 ,
• Adam Ťápal 1 &
• Kateřina Škařupová 1  

To date, number of scales have been used to study online gaming addiction. Aside from their quantity, their uncertain psychometric properties are among the issues that this field of research faces. This study aims at a more detailed assessment of the frequently used Addiction-Engagement Questionnaire (Charlton & Danforth, 2010 ) that can uniquely discriminate pathological and non-pathological intensive gaming. An online questionnaire was administered thrice during a period of one year to a sample of online gamers ( N  = 5080). A series of factor analysis models was used to re-evaluate the original suggested models and formulate new models. Measurement invariance of the final selected model was evaluated in terms of preferred genres (MMORPG and MOBA), age groups, and waves of data collection. The original model did not exhibit a solid fit to data. Few changes were suggested as remedies to improve model fit. The revised model keeps the original two-factor solution, however, we found little support for the so-called peripheral components of addiction with the exception of tolerance. The revised model was found to be invariant over the selected groups. With only few modifications, the Addiction-Engagement Questionnaire was found to be usable for survey-type research purposes, showing a mid-high internal consistency and test-retest reliability.

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This research was supported by Czech Science Foundation (project GA21-30769S).

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Blinka, L., Ťápal, A. & Škařupová, K. Evaluating the Psychometric Properties and Measurement Invariance of the Addiction-Engagement Questionnaire Using a Longitudinal Sample. J Psychopathol Behav Assess 43 , 757–765 (2021). https://doi.org/10.1007/s10862-021-09907-x

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• Published: 10 December 2020

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

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

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

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

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Introduction.

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

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

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

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

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

Subject demographics

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

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

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

Internet use and academic performance

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

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

Electronic gaming and academic performance

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

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

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

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

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

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

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

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

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

Data description

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

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

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

Outcome variables

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

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

Independent variables

Internet use and electronic gaming.

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

Other covariates

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

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

Statistical analysis

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

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

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

Data availability

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

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Acknowledgements

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

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

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

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

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• v.19(5); 2022 May

Psychometric Assessment of the Motives for Online Gaming Questionnaire Among Iranian Gamers

Marziyeh hamzehzadeh.

1 Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran

2 Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran

Arshiya Sangchooli

3 School of Medicine, Tehran University of Medical Sciences, Tehran, Iran

Rabert Farnam

Hosein rafiemanesh.

4 Non-Communicable Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran

Behrang Shadloo

Kamyar ghani, maral mardaneh jobehdar, masoumeh amin-esmaeili, jamileh rahimi.

5 Department of Epidemiology and Biostatistics, School of Public Health, North Khorasan University of Medical Sciences, Bojnurd, Iran

Zsolt Demetrovics

6 Centre of Excellence in Responsible Gaming, University of Gibraltar, Gibraltar, Gibraltar

7 Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary

Orsolya Király

Afarin rahimi-movaghar.

Gaming motivations are crucial aspects of healthy and problematic video gaming behavior. The aim of this study was to assess the psychometric properties of the widely used Motives for Online Gaming Questionnaire (MOGQ).

Test-retest reliability was evaluated in a sample of 66 university students. Data from 791 participants in an online survey of Iranian online gamers were examined to assess convergent validity and construct validity using confirmatory factor analysis. Internal consistency of MOGQ factors was assessed in both samples.

The item content validity index (I-CVI) and the scale content validity index (S-CVI) were between 0.8 and 1.0 for clarity and relevancy. The test-retest reliability of the 27-item questionnaire was 0.85 and internal consistency was 0.94. After incorporating additional error paths, model fit improved to an acceptable level. The MOGQ factors had acceptable correlations with relevant motivational scales such as Gaming Motivation Scale and Player Experience of Need Satisfaction. Recreation motives had the highest average score in the sample and social ones had the lowest, and males scored higher than females across all motivation domains except escape.

The MOGQ is a suitable instrument for the assessment of online gaming motivations in the Iranian population.

INTRODUCTION

Given the increasing popularity of video games, interest in understanding the underlying bases, associated behaviors and consequences of video game playing has been growing [ 1 ]. It has been estimated that by the end of 2017 there were 2.21 billion active gamers around the world [ 2 ], and more than 28 million Iranians reported playing for at least one hour per week in a recent national survey [ 3 ]. After decades of research, a consensus is emerging that players relate to video games in nuanced complex contexts, shaped by the characteristics of players, games, and the gaming environment [ 4 , 5 ]. Relatedly, while it appears that most players are not adversely impacted by their gaming behavior [ 6 , 7 ], a minority of players report potentially pathological patterns of gaming [ 8 ]. This has led to the recent formulation of the diagnostic entity of internet gaming disorder (IGD), and calls for its recognition as an important emerging public health issue globally [ 9 , 10 ]. While data is scarce, IGD is also considered a potential public health concern in Iran [ 11 , 12 ] and it has been estimated to impact about 3.7% of Iranian online gamers [ 13 ]. Thus, investigations of important aspects of gaming behavior seem warranted.

It is increasingly recognized that different individuals play online and offline games with a variety of different motives, and that these motives may constitute an important aspect of gaming behavior [ 14 ]. Besides general entertainment and enjoyment of the games they play, players may engage with games to form social connections, to feel a sense of progress, to modulate low mood, to detach from and escape daily life, to learn new skills, to compete and to feel competent, and to explore and sate their curiosity [ 15 ]. Among these diverse motivational profiles, some might be more strongly associated with problematic gaming than others [ 16 ]. For example, it has been demonstrated that individuals who engage in online games to compete [ 17 ], to escape life issues [ 18 - 20 ], and to stimulate fantasies [ 18 , 21 ] may be at greater risk of pathological gaming and associated psychiatric comorbidities [ 21 ]. Investigating and better theorizing about the motivations of players for online gaming may thus aid in understanding and distinguishing problematic patterns of play, and preventing or treating the problems associated with harmful online gaming [ 17 ].

Different theories of motivation have been applied to conceptualize online gaming behavior. Self-determination theory (SDT) proposes two general categories of intrinsic and extrinsic motivation for gaming; gamers who play for enjoyment, exploration and improve their skills would be intrinsically motivated, while those who play for game-related rewards, competition, or social connection are extrinsically motivated [ 22 ]. On the other hand, Bartle’s framework [ 23 ] would suggest four different motivations associated with the playing styles of achievers, explorers, socializers, and killers, and Yee [ 24 ] has developed this framework to propose the motivation categories of achievement (including advancement, mechanics, competition), social (socializing, relationship, teamwork), and immersion (discovery, role playing, customization, escapism). A number of instruments have been developed to assess gaming motives based on these theories, such as the 27-item Motivation for Online Games Questionnaire [ 25 , 26 ], the 18-item Gaming Motivation Scale (GAMS) [ 22 ] with a 15-item version proposed recently, the 12-item Online Gaming Motivations Scale [ 27 ], and the 10-item Player Experience of Need Satisfaction (PENS) Questionnaire [ 28 ].

Considering the increasing national and global popularity of online games and the importance of gaming motives to understand healthy and disordered gaming, this study is an attempt at translating the Motives for Online Gaming Questionnaire (MOGQ) into the Persian language, assessing its psychometric properties, and investigating the distribution of gaming motives based on the MOGQ in a sample of Iranian online gamers. We chose MOGQ since it is a comprehensive questionnaire that explores the aims of online gaming and can be used in a wide age range [ 25 ], and has been translated into a number of different languages and validated across different cultures [ 18 , 21 , 26 , 29 - 32 ].

Procedure and participants

The study was conducted in three stages: 1) translation and assessment of the content validity of the translated questionnaire, 2) assessment of the internal consistency and test-retest reliability, and 3) investigation of convergent and construct validity.

At the first step the questionnaire was translated from English to Persian, in compliance with World Health Organization guidelines [ 33 ] and using the forward-backward translation method. Content validity was assessed by a group of 15 experts which consisted of content experts, lay experts, and a psychometrist, for relevancy, clarity, and comprehensiveness. Relevancy and clarity indices were calculated using the universal agreement (UA) approach and the mean approach, for each item as well as the entire instrument. Content validity ratio (CVR) was also assessed. Values above 0.80 were regarded as acceptable for content validity indices.

To evaluate the test-retest reliability in the first stage, 120 undergraduate students were recruited from five classes of Allameh University in Tehran after providing informed consent to participate in the study. Of these, 96 had a history of online gaming in the past year. In the retest phase, all individuals who met the inclusion criteria were asked to retake the retest, and 66 completed the MOGQ for the second time after a 10- to 14- day interval. Convenience sampling was used without randomization. For all MOGQ factors, intraclass correlation coefficients (ICCs) were assessed to estimate test-retest reliability.

An online survey was carried out among 791 Iranian online gamers in 2016 to test convergent and construct validity [ 34 ]. The Persian versions of the instruments were uploaded to a website with open public access. The Iranian National Center for Addiction Studies (INCAS) advertised the URL and recruited participants in several rounds of announcements via the INCAS website. Calls for participation were also made on social media platforms popular in Iranian and flyers and pamphlets distributed in several universities. Upon clicking the questionnaire URL, participants were greeted and given a detailed description of the study objectives and criteria for inclusion, and assured that measures would be taken to anonymize their data which would only be used towards the study’s stated purposes. No sample size calculation or randomization was performed, with the objective of recruiting as large a convenience sample as possible.

The construct validity of the MOGQ was assessed using confirmatory factor analysis (CFA) for the data from this survey. For the CFA, chi-square values and fitness indices were calculated. To assess the convergent validity of the questionnaire, we calculated correlations between MOGQ factors and relevant domains from the PENS and GAMS instruments. The internal consistency of MOGQ (based on Cronbach’s alpha) was calculated in both samples. We have also provided the results of the MOGQ testing among the 791 online gamers based on gender and different age groups. The IBM SPSS Statistics 25 (IBM Co., Armonk, NY, USA) and the AMOS 24 (IBM Co.) software programs were used for the analyses.

The MOGQ [ 25 ] is a 27-item self-administered instrument assessing an individual’s motivations for gaming. The instrument consists of the following domains: escape, coping, fantasy, skill development, recreation, competition, and social motivation. Each item has a 5-point Likert scale, with higher scores showing greater motivation in that domain. The MOGQ has been assessed in several languages and shown to have acceptable to very good psychometric properties [ 25 , 26 , 29 ].

The PENS is a 10-item questionnaire assessing gamers’ experience across five dimensions: presence/immersion, autonomy, competence, relatedness, and intuitive controls. Items in the PENS are rated by on a 7-point Likert scale which shows participants agreement [ 28 ].

The GAMS is an 18-item questionnaire, designed to identify individuals’ motives for playing video games, measuring six domains of motivation using three questions for each domain with a 7-point Likert scale [ 22 ]. GAMS was constructed within the theoretical framework of SDT. Within SDT, behaviors depend on six types of motivations; namely intrinsic motivation, integrated regulation, identified regulation, introjected regulation, external regulation, and amotivation. The GAMS was developed and validated to measure the extent to which participants’ gaming behavior relies on each of the SDT’s six motivation domains [ 9 ].

Informed consent and confidentiality

Participants in both samples were informed that provided data would remain confidential. Only those involved in statistical analyses had access to complete participant information. Institutional review board approval was sought and the research protocol was approved by the Ethics Committee of Tehran University of Medical Sciences in Iran (no. IR.TUMS. VCR.REC.1395.800).

Content validity

For the Persian version of the MOGQ-27, the item content validity index (I-CVI) for clarity was 0.8 for question 5, 0.93 for question 13 and 27, and 1.0 for the rest of the questions. I-CVI for relevancy was 1.0 for all items. The scale content validity index (S-CVI) for clarity using the UA approach and the mean approach were 0.89 and 0.99, respectively. S-CVI for relevancy was 1.0 in both approaches. The CVR for all items and questionnaire comprehensiveness were 1.0. CVI values of 0.80 or more were interpreted as indicating acceptable validity, following the widely cited suggestion of Davis [ 35 ].

Reliability

Data from the sample of university students was used to assess test-retest reliability. Sixty-six individuals completed the questionnaire twice with a 10- to 14-day interval. Among these, 47 (71.2%) were females. Fifty-one (77.3%) were undergraduate students and the rest (22.7%) were graduate students. In terms of marital status, only three were married and the rest (95.5%) were single. The age distribution of 66 people was between 19 and 40 years and their age was 22.1±3.2 (mean± standard deviation [SD]) years.

Besides item 11 “…because it helps me get rid of stress” which had a test-retest reliability of 0.45, the test-retest reliability of MOGQ items ranged from 0.64 to 0.87. The reliability of all factors was between 0.79 (coping) and 0.87 (skill development), and the ICC of the entire questionnaire was 0.85 that considers good [ 36 ]. The internal consistency of the MOGQ factors was also assessed in this sample, and ranged from 0.68 (social) to 0.87 (recreation). The ICC between 0.50–0.75 and between 0.75–0.90 are indicated as moderate and good reliability, respectively ( Table 1 ) [ 36 ].

Internal consistency and test-retest reliability of the Motives for Online Gaming Questionnaire (N=66)

ICC, intraclass correlation coefficient; CI, confidence interval

Convergent validity and internal consistency

A total of 791 participants in the online survey, including 592 (75.4%) males. The age of participants ranged from 18 to 50 years, with a mean of 23.4±8.8 years. To investigate the validity of the Persian version of the MOGQ and its internal consistency, we used the data from 758 participants in the online survey who had no missing values. Correlations between the MOGQ factors ranged from 0.24 to 0.71, with the lowest correlation observed between the escape and recreation factors and the highest observed between escape and coping. The internal consistency of MOGQ factors based on Cronbach’s alpha ranged from 0.78 for the social motives factor to 0.91 for the recreation factor ( Table 2 ). Cronbach’s alpha for the entire questionnaire was 0.94.

Mean, SD, internal consistency of the Motives for Online Gaming Questionnaire factors (N=791)

All correlations are significant at least at p-value<0.05. SD, standard deviation

There were significant correlations between the social factor from the MOGQ and relatedness from the PENS (r=0.546, p<0.001), the competition factor from the MOGQ and competence from the PENS (r=0.494, p<0.001), the escape factor from the MOGQ and introjected regulation from the GAMS (r=0.567, p<0.001), the competition factor from the MOGQ and external regulation from the GAMS (r=0.482, p<0.001), and the skill development factor from the MOGQ and identified regulation from the GAMS (r=0.577, p<0.001). Regarding the other three MOGQ motivation factors, i.e., fantasy, coping, and recreation, we were not able to find corresponding domains in other instruments to assess convergent validity.

Construct validity

To explore the dimensionality of the MOGQ, we ran a CFA testing a first-order model with seven factors as suggested during the original development of the MOGQ [ 25 ]. Each of the seven factors consisted of three or four corresponding items. According to the CFA, the model had the following fit indices: chi-square=1,746.6 (df=303, n=758, p<0.001), comparative fit index (CFI)=0.897, incremental fit index (IFI)=0.897, normed fit index (NFI)=0.878, root-mean-square error of approximation (RMSEA)=0.079 (90% confidence interval [CI], 0.076–0.083), Akaike information criterion=1896.61, and Bayesian information criterion=2,243.91.

When searching for partial misfits, modification indices (MI) suggested the addition of error paths between item 9 “…because it makes me forget real life” and item 16 “…because gaming helps me escape reality” (MI=82.28), between item 13 “…to feel as if I was somebody else” and item 20 “…to be somebody else for a while” (MI=38.61), and then between item 1 “…because I can get to know new people” and item 8 “…because I can meet many different people” (MI=19.96). Incorporating the proposed additional error paths improved the model fit to an acceptable level: chi-square=1,422.7 (df=300, n=758, p<0.001), CFI=0.920, IFI=0.920, NFI=0.901, RMSEA=0.070 (90% CI: 0.067–0.074). Standardized factor loadings for all items were higher than 0.6 and the highest correlation was between escape and coping motives ( Figure 1 ).

Estimates of standardized factor loadings and correlations among the factors of the Motives for Online Gaming Questionnaire.

Demographic correlates

Considering the distribution of MOGQ factor scores across genders and age groups, male online gamers scored significantly higher than female ones in all motivational dimensions (p<0.05) except for escape, in which males had an average score of 8.48±4.25 and females had an average score of 8.17± 4.13. Compared to other age groups, the 18–20 age group scored significantly higher in all motivational dimensions (p<0.05), again except for escape ( Table 3 ).

Motivation scores of the Motives for Online Gaming Questionnaire by sex and age

Values are presented as mean±standard deviation or number only. Different subscript letters (a, b, c) in the same row of age reflect significant (p<0.05) difference between the means while same subscript letters in one row reflect non-significant difference between the means according to Bonferroni post-hoc test

In this study, we translated and assessed the content validity, test-retest and internal reliability, and construct and convergent validity of the Persian version of the MOGQ and described the distribution of motivation domain scores in a population of Iranian online players. The results showed that the Persian MOGQ has very good content validity and suitable internal and external reliability (Cronbach’s alpha=0.94). Notably, we are not aware of any prior study on the test-retest reliability of the MOGQ and our study showed that it has good test-retest reliability for both the individual factors and the entire questionnaire. The MOGQ was originally developed in English, and has since been translated and validated in several other languages. The psychometric properties of the English version as well as the Chinese, Indonesian, Turkish, Korean, and Italian versions have also been assessed [ 18 , 25 , 26 , 29 , 32 ].

In the original English version, the internal consistency for all 7 dimensions ranged from 0.79 to 0.90 (Cronbach’s alpha=0.91) [ 25 ]. The internal consistency was between 0.83–0.90 in the Chinese version (Cronbach’s alpha=0.95) [ 26 ], between 0.80–0.87 for the Korean version [ 18 ] and between 0.88–0.92 for the Turkish version [ 32 ] for dimensions. In the Italian version, the internal consistency of all factors was observed to be appropriate [ 21 ]. Lastly, the Indonesian version of the MOGQ was reported to be valid and reliable and with a Cronbach’s alpha of 0.94 [ 29 ]. In both our samples, the social motives factor had the lowest internal consistency and recreation motives the highest, which diverges from the English [ 25 ] and Chinese questionnaires [ 26 ] and might reflect variations resulting from translation or sample differences. On the other hand, these results are consistent with a psychometric assessment of the Turkish version of MOGQ [ 32 ], potentially reflecting greater cultural similarities between Iranian and Turkish samples.

Some versions of the questionnaire reduce the number of factors from 7 to 6. For example, the coping and escape dimensions are merged into one dimension in the Turkish MOGQ [ 32 ] and the coping factor was eliminated from the Korean after exploratory and confirmatory factor analyses favored a six-factor structure [ 18 ]. We observed a high correlation between the escape and coping factors (0.712), similar to the Turkish study [ 32 ], but decided to keep the original structure intact given factor analysis results. This high correlation may indicate that the coping and escape, although conceptually distinct, can be considered overlapping constructs. Indeed, some studies before the development of the MOGQ considered the escape factor a coping factor. Demetrovics et al. [ 25 ] also observed a strong correlation between the two factors (0.602) but proposed that the two factors be separated considering the results of their factor analysis. A discussion of the differences between coping and escape would be warranted given these results.

Escape indicates a desire to escape certain situations or environments and is thus focused on escaping real life, ultimately helping the player manage unwanted moods and emotions such as stress, aggression, and anxiety [ 37 ]. In many studies, this kind of escape is what is considered important as a motivation for seeking entertainment [ 38 ]. On the other hand, coping is often defined as a conscious, active effort to resolve or overcome personal and interpersonal problems [ 39 ]. Two notable differences emerge between escape and coping. First, coping refers to strategies aiming to reduce, eliminate, or manage the stressor, while escape implies disengagement, in which the main goal is to ignore, avoid, or withdraw from the stressor or its emotional consequences [ 37 ]. Second, escape is an emotion-focused strategy whereas coping is an action-focused one [ 40 ]. While further investigations are required to clarify this distinction, our factor analysis suggests that the 7-factor model is preferable after a few modifications, and a 6-factor model may result in notable information loss.

In terms of demographic correlates of gaming motivations, males in our sample scored significantly higher than females across all motivational dimensions except escape. This is consistent with the results of the Chinese version of the MOGQ and also a recent meta-analysis which suggests that males have greater motivation to play video games across a variety of motivation domains [ 26 , 41 ]. Interestingly, several other studies have also found that the score for the escape motive specifically is not higher in males than in females [ 42 ] or that females have higher scores on escapist motives [ 22 ]. Wu et al. [ 26 ] also reported that males generally scored higher on MOGQ motives, but not on the escape domain. Interestingly, the pattern was repeated for those in the 18–20 age group, who scored significantly higher than other in all motivational dimensions (p<0.05) except in the escape dimension. Since participant ages are truncated at 18 (based on our inclusion criteria), our results may suggest that gaming motivations decline with age. This may happen since cognitive maturity could render many major games less appealing and enjoyable [ 43 ], or since individuals take on increasing responsibilities and challenges as they age and enter the job market. It seems the only motivation that does not decrease significantly with age is the escape. This may be since some players increasingly use video games to escape routine tensions which increase with age and responsibility. However, this result has not been reported in any study so far and requires future studies [ 44 ].

We observed several significant correlations between certain motivational factors from the MOGQ and domains which appear to correspond to them from the PENS and GAMS measures. Ballabio et al. [ 21 ] similarly assessed the convergent validity of MOGQ, and have observed a close association between the social, competition, and fantasy factors in MOGQ and the social, achievement, and immersion factors in OGMS, respectively. The recreation and coping factors were developed in the MOGQ for the very first time, so they have not been compared with any other subscales to the best of our knowledge.

Conclusion and limitations

Overall, this study investigated multiple reliability and validity indices of the Persian version of the MOGQ questionnaire, and results indicate that it has appropriate psychometric properties for the assessment of online gaming motivations in our samples. However, the present study also had several major limitations. Firstly, we mainly sampled populations of university students, and even the online survey was advertised mainly on platforms which may be used more regularly by those with better education. We also utilized convenience samples which are not necessarily representative of the sampled populations, and future studies are needed to investigate the generalizability of our findings. Furthermore, the test-retest reliability of the questionnaire was investigated in the smaller of our two samples and after only a two-week interval, and studies of larger samples across longer follow-up periods are required to establish test-retest reliability with greater confidence. Lastly, we did not have access to data on a variety of demographic, socioeconomic and clinical variables, or objective measure of playing behavior that may be relevant to gaming motives and their relationship to problematic gaming. Longitudinal studies collecting data on multiple variables of interest across time would be necessary to further explore the dynamic relationships between gaming motives and such factors.

Availability of Data and Material

The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Marziyeh Hamzehzadeh, Rabert Farnam, Hosein Rafiemanesh, Masoumeh Amin-Esmaeili, Zsolt Demetrovics, Orsolya Király, Afarin Rahimi-Movaghar. Data curation: Marziyeh Hamzehzadeh, Hosein Rafiemanesh, Kamyar Ghani, Maral Mardaneh Jobehdar, Jamileh Rahimi. Formal analysis: Marziyeh Hamzehzadeh, Hosein Rafiemanesh, Behrang Shadloo, Arshiya Sangchooli. Investigation: Marziyeh Hamzehzadeh, Rabert Farnam, Hosein Rafiemanesh, Behrang Shadloo, Arshiya Sangchooli, Masoumeh Amin-Esmaeili, Afarin Rahimi-Movaghar. Methodology: Rabert Farnam, Hosein Rafiemanesh, Zsolt Demetrovics, Orsolya Király, Afarin Rahimi-Movaghar. Project administration: Marziyeh Hamzehzadeh, Rabert Farnam, Hosein Rafiemanesh, Afarin Rahimi-Movaghar. Resources: Afarin Rahimi-Movaghar. Software: Hosein Rafiemanesh. Supervision: Rabert Farnam, Hosein Rafiemanesh, Masoumeh Amin-Esmaeili, Zsolt Demetrovics, Orsolya Király, Afarin Rahimi-Movaghar. Validation: Marziyeh Hamzehzadeh, Hosein Rafiemanesh, Afarin Rahimi-Movaghar. Visualization: Hosein Rafiemanesh. Writing—original draft: Marziyeh Hamzehzadeh, Hosein Rafiemanesh, Behrang Shadloo. Writing—review & editing: all authors.

Funding Statement

This study was supported financially by Tehran University of Medical Sciences (Grant number. 95-02-49-32102).

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Gender differences in the longitudinal linkages between fear of covid-19 and internet game addiction: a moderated multiple mediation model.

1. Introduction

1.1. fear of covid-19 and iga, 1.2. mediating role of loneliness, 1.3. mediating role of depression, 1.4. multiple mediating effects of loneliness and depression, 1.5. gender differences, 1.6. the present study, 2.1. participants and procedure, 2.2. measurements, 2.2.1. fear of covid-19, 2.2.2. loneliness, 2.2.3. the patient health questionnaire-9 (phq-9), 2.2.4. internet game addiction, 2.3. data analysis, 2.4. testing the common method bias (cmb), 3.1. preliminary analyses, 3.2. testing the measurement model, 3.3. testing the mediation model, 3.4. testing the moderated multiple mediation model, 4. discussion, 4.1. implications, 4.2. limitations and future research directions, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Liu, Q.; Gao, B.; Wu, Y.; Ning, B.; Xu, Y.; Zhang, F. Gender Differences in the Longitudinal Linkages between Fear of COVID-19 and Internet Game Addiction: A Moderated Multiple Mediation Model. Behav. Sci. 2024 , 14 , 675. https://doi.org/10.3390/bs14080675

Liu Q, Gao B, Wu Y, Ning B, Xu Y, Zhang F. Gender Differences in the Longitudinal Linkages between Fear of COVID-19 and Internet Game Addiction: A Moderated Multiple Mediation Model. Behavioral Sciences . 2024; 14(8):675. https://doi.org/10.3390/bs14080675

Liu, Qing, Bin Gao, Yuedong Wu, Bo Ning, Yufei Xu, and Fuyou Zhang. 2024. "Gender Differences in the Longitudinal Linkages between Fear of COVID-19 and Internet Game Addiction: A Moderated Multiple Mediation Model" Behavioral Sciences 14, no. 8: 675. https://doi.org/10.3390/bs14080675

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