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Examining the antecedents and consequences of addiction to mobile games: an empirical study

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• Published: 18 December 2022

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• Sheshadri Chatterjee   ORCID: orcid.org/0000-0003-1075-5549 1 ,
• Ranjan Chaudhuri 2 &
• Demetris Vrontis 3  

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Mobile games are video games that are typically played on any portable devices including mobile phones, such as feature phones or smartphones; tablets; personal digital assistants, which are able to handle game consoles; and portable media players with internet connectivity. Increasingly, people are becoming addicted to such mobile gaming. Not many studies are available that have investigated the factors responsible for such addiction, especially social influence and motivation aspects. There is a huge interest among practitioners, researchers, and academicians to understand the antecedents and consequences of people’s addiction to mobile games. Therefore, the aim of this study is to investigate the antecedents and consequences of addiction to mobile games. With the help of social exchange theory, social networking theory, motivational theory and technology acceptance model, a theoretical model has been proposed, which is subsequently validated using partial least squares structural equation modelling on the feedback from 322 respondents who are mobile game players. The study finds that social influence has a significant positive impact on both hedonic and utilitarian attitudes of people towards playing mobile games. With different factors influencing them to play mobile games frequently, these players eventually become addicted to mobile games.

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Ahn D, Jeon S, Yoo B (2018) What’s your real age? An empirical analysis of identity fraud in online game. Inf Syst E-Bus Manage 16:775–789

Article   Google Scholar  

Ajzen I, Fishbein M (2005) The influence of attitudes on Behaviour. In: Albarracín D, Johnson BT, Zanna MP (eds) The handbook of attitudes. Lawrence Erlbaum Associates Publishers, pp 173–221

Alha K, Koskinen E, Paavilainen J, Hamari J, Kinnunen J (2014) Free-to-play games: professionals’ perspectives. Proceedings of 2014 International DiGRA Nordic Conference, Gotland, May 29–30

Al-Samarraie H, Bello K-A, Alzahrani AI, Smith AP, Emele C (2021) Young users’ social media addiction: causes, consequences and preventions. Inf Technol People. https://doi.org/10.1108/ITP-11-2020-0753

Al-Zyoud MF, Mert İS (2019) Does employees’ psychological capital buffer the negative effects of incivility? EuroMed J Bus 14(3):239–250

Armstrong JS, Overton TS (1977) Estimating nonresponse bias in mail surveys. J Mark Res 14(3):396–402

Ayandele O, Popoola OA, Oladiji TO (2020) Addictive use of smartphone, depression and anxiety among female undergraduates in Nigeria: a cross-sectional study. J Health Res 34(5):443–453

Bae J, Park H-H, Koo D-M (2019) Perceived CSR initiatives and intention to purchase game items: the motivational mechanism of self-esteem and compassion. Internet Res 29(2):329–348

Bouwman H, Carlsson C, Walden P (2009) Reconsidering the actual and future use of mobile services. Inf Syst E-Bus Manage 7:301–317

Boyd DM, Ellison NB (2008) Social network sites: definition, history, and scholarship. J Comput-Mediat Commun 13(1):210–230

Cameron P (1969) Age parameters of young adult, middle-aged, old, and aged. J Gerontol 24(2):201–202

Chang C-C, Chin Y-C (2011) Predicting the usage intention of social network games: an intrinsic-extrinsic motivation. Int J Online Market 1(13):29–37

Chatterjee S (2015) Security and privacy issues in E-Commerce: A proposed guidelines to mitigate the risk. IEEE International Advance Computing Conference (IACC). 393–396. https://doi.org/10.1109/IADCC.2015.7154737

Chatterjee S (2019) Is data privacy a fundamental right in India? An analysis and recommendations from policy and legal perspective. Int J Law Manage 61(1):170–190

Chatterjee S (2020) Antecedents of phubbing: from technological and psychological perspectives. J Syst Inf Technol 22(2):161–178

Chatterjee S (2021a) Dark side of online social games (OSG) using Facebook platform: effect of age, gender, and identity as moderators. Inf Technol People 34(7):1800–1818

Chatterjee S (2021b) Impact of addiction of online platforms on quality of life: age and gender as moderators. Australasian J Inf Syst 25. https://doi.org/10.3127/ajis.v25i0.2761

Chaudhuri R, Chatterjee S, Vrontis D (2022) Antecedents of privacy concerns and online information disclosure: Moderating role of government regulation. Euromed Journal of Business, In Press. https://doi.org/10.1108/EMJB-11-2021-0181

Chen A, Lu Y, Wang B (2016) Enhancing perceived enjoyment in social games through social and gaming factors. Inf Technol People 29(1):99–119

Chen A, Roberts N (2019) Connecting personality traits to social networking site addiction: the mediating role of motive. Inf Technol People 33(2):633–656

Chen J, Tang L, Tian H, Ou R, Wang J, Chen Q (2022) The effect of mobile business simulation games in entrepreneurship education: a quasi-experiment. Library Hi Tech, In Press. https://doi.org/10.1108/LHT-12-2021-0509

Chen PY, Chang CC (2010) The analysis of service acceptance framework for social games based on extensive technology acceptance model. Proceedings of 10th Technology Management for Global Economic Growth, IEEE, Phuket

Collier MR (1993) A mathematical model of habituation and addiction. Int J Addict 28(1):175–185

Davis FD (1989) Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Q 13(3):319–340

Deb M, Lomo-David E (2014) An empirical examination of customers’ adoption of -mbanking in India. J Market Intell Plan 32(4):475–494

Deci EL, Ryan RM (1985) Intrinsic motivation and self-determination in human behavior. Plenum, New York, NY

Book   Google Scholar  

Delistavrou A, Katrandjiev H, Sadeh H, Tilikidou I (2019) Exploring ethical consumption in different geographical places. EuroMed J Bus 14(3):221–238

Dwivedi YK, Rana NP (2020) Social media as a tool of knowledge sharing in academia: an empirical study using valance, instrumentality, and expectancy (VIE) approach. J Knowl Manage 24(10):2531–2552

Feijoo C, Gómez-Barroso J-L, Aguado JM, Ramos S (2012) Mobile gaming: industry challenges and policy implications. Telecommun Policy 36(3):212–221

Fishbein M, Ajzen I (1980) Understanding attitudes and predicting consumer behavior. Prentice Hall, Englewood Cliffs, NJ, pp 148–172

Google Scholar  

Fisher RJ, Price LL (1992) An investigation into the social context of early adoption behavior. J Consumer Re 19(3):477–486

Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Market Res 18(1):39–50

Galati A, Vrontis D, Giorlando B, Giacomarra M, Crescimanno M (2021) Exploring the common blockchain adoption enablers: the case of three italian wineries. Int J Wine Bus Res 33(4):578–596

Ghazali EM, Mutum DS, Woon MY (2019) Multiple sequential mediation in an extended uses and gratifications model of augmented reality game Pokemon Go. Internet Res 29(3):504–528

Gong M, Xu M, Luqman A, Yu, Masood A (2020a) Understanding the role of individual differences in mobile SNS addiction. Kybernetes 49(12):3069–3097

Gong X, Zhang KZK, Chen C, Cheung CMK, Lee MKO (2020b) Antecedents and consequences of excessive online social gaming: a social learning perspective. Inform Technol People 33(2):657–688

Gunter B (2019) Children and mobile phones: adoption, use, impact, and control. Emerald Publishing, Bingley

Hair JF, Howard MC, Nitzl C (2020) Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. J Bus Res 109:101–110

Handa M, Ahuja P (2020) Disconnect to detox: a study of smartphone addiction among young adults in India. Young Consumers 21(3):273–287

Heerink M, Kröse B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the Almere model. Int J Soc Robotics 2(4):361–375

Homans G (1961) Social behavior: its elementary forms. Harcourt Brace Jovanovich, New York, NY

Hsiao KL (2017) Compulsive mobile application usage and technostress: the role of personality traits. Online Inf Rev 41(2):272–295

Hu L, Bentler PM (1999) Fit indices in covariance structure modelling: sensitivity to under parameterized model misspecification. Psycholog Methods 3(4):424–453

Jimenez N, San-Martin S, Camarero C, San Jose Cabezudo R (2019) What kind of video gamer are you? J Consumer Mark 36(1):218–227

Jordan T (2019) Does online anonymity undermine the sense of personal responsibility? Media Cult Soc 41(4):572–577

Kar AK, Chatterjee S, Mustafa SZ (2019) Securing IoT devices in smart cities of India: from ethical and enterprise information system management perspective. J Enterp Inf Syst 15(4):585–615

Ketokivi MA, Schroeder RG (2004) Perceptual measures of performance: fact or fiction? J Oper Manag 22(3):247–264

Khan NF, Khan MN (2021) A bibliometric analysis of peer-reviewed literature on smartphone addiction and future research agenda. Asia-Pac J Bus Adm, In Press. https://doi.org/10.1108/APJBA-09-2021-0430

Kim E, Kim EJ, Cho CI (2017) Structural equation model of smartphone addiction based on adult attachment theory: mediating effects of loneliness and depression. Asian Nurs Res 11(2):92–97

Ko M, Yang S, Lee J, Heizmann C, Jeong J, Lee U (2015) NUGU: a group-based intervention app for improving self-regulation of limiting smartphone use. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work and Social Computing, ACM, Vancouver, BC, Pp. 1235–1245

Kock N, Hadaya P (2018) Minimum sample size estimation in PLS-SEM: the inverse square root and gamma-exponential methods. Inf Syst J 28(1):227–261

Lee J-y, Ko DW, Lee H (2019) Loneliness, regulatory focus, inter-personal competence, and online game addiction: a moderated mediation model. Internet Res 29(2):381–394

Lee Y-H, Wohn DY (2012) Are there cultural differences in how we play? Examining cultural effects on playing social network games. Comput Hum Behav 28(4):1307–1314

Liang T, Ho Y, Li Y, Turban E (2011) What drives social commerce: the role of social support and relationship quality. Int J Electron Commer 16(2):69–90

Lindell MK, Whitney DJ (2001) Accounting for common method variance in cross-sectional research designs. J Appl Psychol 86(1):114–121

Mishra A, Maheswarappa SS, Maity M, Samu S (2018) Adolescent’s eWOM intentions: an investigation into the roles of peers, the internet and gender. J Bus Res 86:394–405

Moon Y, Armstrong DJ (2020) Service quality factors affecting customer attitudes in online-to-offline commerce. Inf Syst E-Bus Manage 18:1–34

Muniz AM, O’Guinn TC (2001) Brand community. J Consumer Res 27(4):412–432

Oh Y, Oh J (2017) A critical incident approach to consumer response in the smartphone market: product, service, and contents. Inf Syst E-Bus Manage 15:577–597

Ortiz SM (2019) You can say I got desensitized to it: how men of colour cope with everyday racism in online gaming. Sociol Perspect 62(4):572–588

Paavilainen J, Hamari J, Stenros J, Kinnunen J (2013) Social network games: players’ perspectives. Simul Gaming 46(6):794–820

Park J, Ko D (2022) Catch me if you can: effects of AR-enhanced presence on the mobile game experience. Internet Res 32(4):1235–1263

Park WK (2014) An exploitative study on college students’ addiction: using psychological variables as predictors. Soc Psychol Res 27(1):95–125

Peng DX, Lai F (2012) Using partial least squares in operations management research: a practical guideline and summary of past research. J Oper Manage 30(6):467–480

Piccolo R, Chaudhuri R, Vrontis D (2021) Enterprise social network for knowledge sharing in MNCs: examining the role of knowledge contributors and knowledge seekers for cross-country collaboration. J Int Manag 27(1):100827

Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–881

Prochnow T, Patterson MS, Hartnell L (2020) Social support, depressive symptoms, and online gaming network communication. Mental Health Soc Inclusion 24(1):49–58

Rana NP, Dwivedi YK (2021) Assessing Consumers’ Co-production and Future Participation On Value Co‐creation and Business Benefit: an FPCB Model Perspective. Information Systems Frontiers. In Press. https://doi.org/10.1007/s10796-021-10104-0

Rigdon EE, Sarstedt M, Ringle M (2017) On comparing results from CB-SEM and PLS-SEM: five perspectives and five recommendations. Mark ZFP 39(3):4–16

Rogers EM (2003) Diffusion innov, 5th edn. The Free Press, New York, NY

Ryan RM, Deci EL (2000) Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp Educ Psychol 25(1):54–67

San-Martín S, Jiménez N (2021) What colour are you? Smartphone addiction traffic lights and user profiles. Eur J Manag Bus Econ, In Press. https://doi.org/10.1108/EJMBE-02-2021-0069

Sarstedt M, Ringle CM, Henseler J, Hair JF (2014) On the emancipation of PLS-SEM: a commentary on Rigdon (2012). Long Range Plann 47(3):154–160

Scott JP (2000) Social network analysis: a handbook, 2nd edn. Sage Publications, Thousand Oaks, CA

Shalvey K (2012) Zynga readies its own social network site keeps strong Facebook ties game maker first outside site to carry Facebook ads. ProQuest, Investor’s Business Daily, Los Angeles, CA

Shiau W-L, Luo MM (2012) Factors affecting online group buying intention and satisfaction: a social exchange theory perspective. Comput Hum Behav 28(6):2431–2444

Shin D-H, Kim W-Y (2008) Applying the technology acceptance model and flow theory to Cyworld user behavior: implication of the web 2.0 user acceptance. Cyber Psychol Behav 11(3):378–382

Tamilmani K, Rana NP, Sharma A (2021) The effect of AI-based CRM on organization performance and competitive advantage: an empirical analysis in the B2B context. Ind Mark Manage 97(8):205–219

Tseng FC, Huang HC, Teng CI (2015) How do online game communities retain gamers? Social presence and social capital perspectives. J Comput-Mediat Commun 20(6):601–614

Vallerand RJ (1997) Toward a hierarchical model of intrinsic and extrinsic motivation. Adv Exp Soc Psychol 29(3):271–360

Van der Heijden H (2003) Factors influencing the usage of websites: the case of a generic portal in the Netherlands. Inf Manage 40(6):541–549

Varshney U (2004) Group-oriented mobile services: requirements and solutions. Inf Syst E-Bus Manage 2(1):325–335

Vrontis D, Chatterjee S, Chaudhuri R (2022) Big data analytics in strategic sales performance: Mediating role of CRM capability and moderating role of leadership support. Euromed Journal of Business, In Press. https://doi.org/10.1108/EMJB-07-2021-0105

Wamba SF, Gunasekaran A, Akter S, Dubey R (2019) The performance effects of big data analytics and supply chain ambidexterity: the moderating effect of environmental dynamism. Int J Prod Econ 222(4):1–22

Wang C, Zhang J, Lee MKO (2021) Time flies when chatting online: a social structure and social learning model to understand excessive use of mobile instant messaging. Inf Technol People, In Press. https://doi.org/10.1108/ITP-09-2020-0624

Wang L (2022) Understanding peer recommendation in mobile social games: the role of needs–supplies fit and game identification. Info Tech People 35(2):677–702

Willaby HW, Costa DSJ, Burns BD, MacCann C, Roberts RD (2015) Testing complex models with small sample sizes: a historical overview and empirical demonstration of what partial least squares (PLS) can offer differential psychology. Pers Individ Differ 84:73–78

Xue Y, Dong Y, Luo M, Mo D, Dong W, Zhang Z, Liang H (2018) Investigating the impact of mobile SNS addiction on individual’s self-rated health. Internet Res 28(2):278–292

Yang H, Lee H (2019) Understanding user behavior of virtual personal assistant devices. Inf Syst E-Bus Manage 17:65–87

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Chatterjee, S., Chaudhuri, R. & Vrontis, D. Examining the antecedents and consequences of addiction to mobile games: an empirical study. Inf Syst E-Bus Manage (2022). https://doi.org/10.1007/s10257-022-00614-y

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Mobile gaming and problematic smartphone use: A comparative study between Belgium and Finland

Olatz lopez-fernandez.

1 International Gaming Research Unit, Psychology Department, Nottingham Trent University, Nottingham, UK

2 Laboratory for Experimental Psychopathology, Institut de recherche en sciences psychologiques, Université catholique de Louvain, Louvain-La-Neuve, Belgium

Niko Männikkö

3 Department of Social Services and Rehabilitation, Oulu University of Applied Sciences, Oulu, Finland

Maria Kääriäinen

4 Research Unit of Nursing Science and Health Management, Oulu University Hospital, University of Oulu, Oulu, Finland

5 Research Unit of Nursing Science and Health Management, Oulu University Hospital, Oulu, Finland

Mark D. Griffiths

Daria j. kuss, background and aims.

Gaming applications have become one of the main entertainment features on smartphones, and this could be potentially problematic in terms of dangerous, prohibited, and dependent use among a minority of individuals. A cross-national study was conducted in Belgium and Finland. The aim was to examine the relationship between gaming on smartphones and self-perceived problematic smartphone use via an online survey to ascertain potential predictors.

The Short Version of the Problematic Mobile Phone Use Questionnaire (PMPUQ-SV) was administered to a sample comprising 899 participants (30% male; age range: 18–67 years).

Good validity and adequate reliability were confirmed regarding the PMPUQ-SV, especially the dependence subscale, but low prevalence rates were reported in both countries using the scale. Regression analysis showed that downloading, using Facebook , and being stressed contributed to problematic smartphone use. Anxiety emerged as predictor for dependence. Mobile games were used by one-third of the respective populations, but their use did not predict problematic smartphone use. Very few cross-cultural differences were found in relation to gaming through smartphones.

Findings suggest mobile gaming does not appear to be problematic in Belgium and Finland.

Introduction

Interacting with mobile devices (e.g., smartphones and tablets) has now become strongly embedded in contemporary societies across the world as many different types of activity can now be engaged in (e.g., gaming, gambling, and social networking). Over the past two decades, the use of mobile technologies has evolved to comprise a set of behaviors that have become ubiquitous in people’s daily lives, especially for youth ( Hoffner, Lee, & Park, 2016 ; Okazaki, Skapa, & Grande, 2008 ). Smartphone gaming has been one form of popular mobile entertainment engaged in on a variety of devices, accounting for more than 42% (i.e., 32% for smartphones and 10% for tablets) of the global games market (i.e., 47% Asia-pacific, 25% North America, 24% Europe, Middle-East and Africa, and 4% Latin-America; Newzoo, 2017 ). Given rapid developments in mobile technology, smartphone gaming requires an in-depth exploration to ascertain factors that may contribute to problematic use.

Mobile games are video games played online via a mobile device, and are particularly popular when downloaded for free (e.g., “freemium game” – games played for free and where customers can pay for extra features), and can be single-player or multiplayer games ( Su, Chiang, Lee, & Chang, 2016 ). Moreover, the social elements of most mobile games are major features in current digital gaming because social networking sites (SNSs) are successfully integrated and used across many gaming platforms. Some studies have focused on gaming through smartphones, especially in Asia ( Lee, 2017 ; Su et al., 2016 ). In contrast, Europe represents a quarter of the global games market, according to the Global Games Market Report ( Newzoo, 2017 ), with 78% of European mobile gamers playing freemium games ( Deloitte, 2015 ). According to a Deloitte ( 2014 ) report, mobile games represent one of the fastest growing sectors of the mobile application industry in Europe. Europeans have adopted mobile games, which have become the most downloaded applications (“apps”) on smartphones. Similarly, a study conducted by the Entertainment Software Association ( ESA, 2015 ) stated gaming has partly shifted from being console and PC-based to being multiplatform and cross-platform (i.e., video games with an online component allowing gamers to use different hardware). This study uses data from the Tech Use Disorders ( TUD, 2017 ) project, a prospective study involving a panel of European adults followed since 2014 exploring problematic mobile phone use (PMPU) in Belgian and Finnish smartphone users, because these two countries had not been studied before in such a context ( Deloitte, 2015 ), despite having a couple of the highest prevalence rates in mobile phone technology usage ( International Telecommunication Union [ITU], 2015 ).

Belgium and Finland do not differ in mobile phone use. According to the ITU ( 2015 ), between 2007 and 2015, mobile-broadband subscriptions increased 12-fold from 4% to 47% globally. In 2014, the Belgian mobile-broadband penetration was 34%, and mobile social media 36% ( European Digital Landscape, 2014 ). Furthermore, the ITU has recently ranked Finland and Belgium among the higher scoring nations in the Information and communication technologies Development Index (IDI) in Europe, with Finland ranking 11th (IDI = 8.08) and Belgium 15th (IDI = 7.83) of 40 countries. In Europe, Finland and Belgium are among the countries with the highest active mobile-broadband subscriptions per 100 inhabitants, which refer to the sum of these types of standard and dedicated subscriptions through handset-based or computer-based (USB/dongle) devices covering actual subscribers. In 2015, Finland had 144.1 and Belgium 66.6 active mobile-broadband subscriptions (see ITU, 2016 , pp. 224–225, 255). Similarly, the Global Consumer Survey ( Deloitte, 2014 ) reported that 65% of the Finnish population had a smartphone, 29% of Finnish smartphone owners played games on their phone weekly, and the highest penetration was found among 18- to 24-year-old adults. According to the Finnish Player Barometer ( Mäyrä, Karvinen, & Ermi, 2016 ), the proportion of Finnish players playing mobile games at least once a month had increased significantly from 2011 to 2015 (from 21% to 37%). Another survey by the Interactive Software Federation of Europe [ISFE] ( 2012a ) reported that 53% of the Belgian online population aged between 16 and 64 years had played any video game in the past 12 months, with 26% playing weekly. In addition, Belgian respondents reported playing different types of games (e.g., downloaded games [23%], gaming apps [15%]) with one in five (19%) using mobile devices to play (i.e., 14% smartphones, 10% tablets, and 3% iPods). Similarly, the ISFE ( 2012b ) reported 60% of the Finnish online population aged 16–64 years had played video games last year, with 25% playing weekly. Furthermore, Finnish respondents reported playing downloaded games (31%), gaming apps (24%), with one in three (31%) using mobile devices to play (i.e., 25% smartphones, 13% tablets, and 2% iPods).

Despite the many benefits of mobile phones to users, it has been reported primarily by South Korean and Chinese researchers ( Bae, 2017 ; Jeong, Kim, Yum, & Hwang, 2016 ; Lee, Chang, Lin, & Cheng, 2014 ; Lee, Lee, & Lee, 2016 ; Liu, Lin, Pan, & Lin, 2016 ) that there can be a negative side of smartphone usage, arguing that compulsive use of smartphones can arise from a person’s individual characteristics and the device’s structural characteristics. First, related to users, specific psychological traits (e.g., social anxiety and lower self-control), higher stress and technostress (i.e., distress associated with problematic smartphone use), high frustration and impatience without a smartphone (e.g., irritation and fear of group exclusion) have shown to be associated with potential problematic smartphone use ( Lee et al., 2014 ). Structural characteristics, e.g., near-misses (i.e., where gamers just miss leveling up) in the smartphone game Candy Crush have been shown to be more arousing than losses (i.e., where gamers do not come close to leveling up), and are the most frustrating of all outcomes, triggering the highest urge to continue playing ( Larche, Musielak, & Dixon, 2017 ). Furthermore, smartphone content (i.e., SNS, gaming, or other information and entertainment-related apps) and patterns of use (i.e., frequency of smartphone use on weekdays and weekend days) have also been related to problematic smartphone use ( Bae, 2017 ; Jeong et al., 2016 ; Lee et al. 2016 ; Liu et al., 2016 ). Therefore, both internal and external factors appear to be associated with problematic smartphone use. To date, most studies in this area have assessed problematic smartphone use in adolescents rather than adults. However, problematic smartphone use among adults can include a wider range of activities that can be interfered with (e.g., driving, full-time work rather than education, and long-term relationships) because of the smartphone’s immersive properties. Consequently, further research is needed to study the effects of problematic smartphone uses by adults, such as gaming through smartphones.

Currently, PMPU has been theoretically defined as a heterogenic potential behavioral disorder associated with a number of different problems, such as dangerous use (i.e., use in risky situations, such as driving), prohibited use (i.e., using smartphones in venues where they are banned, such as in public places like libraries or theaters), and dependent use (i.e., having an excessive need for using smartphones, such as constantly checking notifications). The latter can include addiction-like symptoms ( Billieux, 2012 , Billieux, Maurage, Lopez-Fernandez, Kuss, & Griffiths, 2015 ; Kanjo, Kuss, & Ang, 2017 ), which can include core components of addiction, including cognitive salience, loss of control, mood modification, tolerance, withdrawal, conflict, and relapse ( Griffiths, 1995 , 2005 ) as well as associated psychological and/or behavioral consequences (e.g., compulsion, negative consequences, and functional impairment; Lee et al., 2016 ; Liu et al., 2016 ). PMPU is a multifaceted condition requiring further research into users’ smartphone activities, including mobile games, as these may contribute to experiencing problems and addiction-like symptoms ( Griffiths & Szabo, 2014 ), highlighting another gap in knowledge that this study aims to address. It has also been demonstrated excessive smartphone gaming can lead to detrimental health effects for a small minority of users, including depression, anxiety, stress, worse mood, specific personality disorders, and low self-control ( Cheever, Rosen, Carrier, & Chavez, 2014 ; Jeong et al., 2016 ; Thomée, Härenstam, & Hagberg, 2011 ), as well as dependence-like symptoms ( Billieux, Van der Linden, & Rochat, 2008 ; Cheng & Leung, 2016 ; Km, Park, & Lee, 2011 ; Kwon et al., 2013 ).

A study by Roberts, Yaya, and Manolis ( 2014 ) surveyed a convenience sample of 164 North American undergraduates to investigate which mobile phone activities (e.g., playing games and social networking) were associated with mobile phone addiction, but did not find that playing mobile games was a predictor. Another study highlighted that high engagement across a wide range of video game genres (e.g., casual, shooter, and sport games), referred to as “gaming versatility” (e.g., the number of different video game genres engaged in), is one of the risk factors for gaming addiction ( Donati, Chiesi, Ammannato, & Primi, 2015 ). Game genres, such as the popular massively multiplayer online role-playing games (MMORPGs), are potentially considered more addictive than other gaming genres (e.g.,  Dauriat et al., 2011 ; Kuss, Louws, & Wiers, 2012 ), but these are the games that are usually played on PCs or gaming consoles rather than on smartphones. Therefore, the evidence regarding the addictive potential of smartphone gaming is currently scarce among adult populations in Western cultures, and no scale assesses this type of content, and therefore further studies are required.

From a psychological perspective, depression and anxiety are associated with gaming addiction ( Ferguson, Coulson, & Barnett, 2011 ; Gentile et al., 2011 ). Similar findings are reported regarding adults’ PMPU ( Thomée, Härenstam, & Hagberg, 2012 ). Anxiety can be triggered gradually in heavy users when their smartphones are unavailable (i.e., a symptom of substance withdrawal [ Cheever et al., 2014 ]). However, a recent study observed while depression and anxiety initially positively correlated with addictive technology use proneness, depression (positively) and anxiety (negatively) predicted addictive video game playing ( Andreassen et al., 2016 ). Regarding stress, problematic online gaming can be conceptualized as a response to preexisting life stress in the framework of the stress-coping theory ( Snodgrass et al., 2014 ), especially when playing MMORPGs. Moreover, Internet Gaming Disorder (IGD) recently included in Section 3 of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders ( American Psychiatric Association, 2013 ) was associated with stress reactivity ( Kaess et al., 2017 ). However, very few studies exist that assess the relationships between stress and anxiety in smartphone gaming, a gap in knowledge that this study aims to fill.

From a psychosociocultural perspective, few studies have assessed smartphone gaming factors and those that have were conducted in Asia. These include a study in India assessing internal factors ( Banerjee & Das, 2015 ), two in South Korea assessing external factors ( Jang & Ryu, 2016 ; Jin, Chee, & Kim, 2015 ), and one in China assessing external factors ( Liu & Li, 2011 ). The Indian study found several motivations for using mobile games, including convenience, fun, escapism, easy use, visual appeal, and perceived influence of being a positive tool (e.g., being able to stay alone to enjoy gaming or socializing). One of the South Korean studies ( Jin et al., 2015 ), focusing on a sociocultural analysis discussing how the emergence of smartphone use had shaped the development of mobile games, indicated the factors that contributed to increases in smartphone gaming (e.g., a community-based social environment based on technology use). Jang and Ryu ( 2016 ) took a developmental approach examining the relationship between parenting and adolescents’ problematic mobile game use, and suggested overexpectation regarding their children’s potential positively related to problematic mobile game use. Finally, Liu and Li ( 2011 ) reported context was the strongest predictor in mobile game adoption (e.g., affecting perceived usefulness and enjoyment).

There are a number of reasons for carrying out this study. First, there is little empirically known regarding potentially problematic smartphone gaming, especially in adulthood. Second, PMPU has almost exclusively been studied in relation to addictive use only rather than considering other potential problems, such as dangerous or prohibited use. To remedy this, this study investigates the multidimensional construct of PMPU across the three problematic smartphone uses. Third, while PMPU exists in Eastern cultures, little evidence has been found in Western cultures. Therefore, this study aims to explore this phenomenon in two European countries to assess smartphone gaming patterns, potential problems, and associated factors. Consequently, the objectives of this cross-national study were twofold. First, to investigate the extent to which Belgian and Finnish adults use mobile games, and second, to identify whether this is associated with problematic use (namely dangerous, prohibited, and dependent use), and to identify psychological predictors (namely depression, anxiety, and stress) and gaming patterns associated with problematic smartphone use.

Participants

The study surveyed two convenience online samples, at the Catholic University of Louvain (Belgium; n  = 397) and Oulu University of Applied Sciences (Oulu UAS, Finland; n  = 502) with 899 participants [30% male; age range: 18–67 years, mean ( M ) age 26.8 years, standard deviation ( SD ) = 9 years], sampled from student and staff members voluntarily agreeing to participate.

The online survey was developed using Qualtrics and comprised: (a) sociodemographics, (b) smartphone use patterns (e.g., mobile game genre), and (c) psychometric scales assessing problematic smartphone use, depression, anxiety, and stress.

Sociodemographics examined gender, age, relationship status [i.e., single, in a relationship, legally cohabitating, married, separated, divorced, or other (e.g., widowed)], education level (i.e., primary, secondary, and higher education), and profession (i.e., student, employed, unemployed, retired, housewife/husband, self-employed, or other).

Smartphone use patterns examined possessing a smartphone, mean use in minutes per week (including daily and weekly smartphone gaming) and usual use frequency (days/week), and online gaming activities on smartphones during the past year, i.e., downloading (e.g., apps), SNS use (i.e.,  Facebook use in general, gaming and posting and checking of received posts), or playing different mobile games by genre: casual games (e.g.,  Candy Crush ), solo video games (e.g.,  Grand Theft Auto ), vehicle simulation games (e.g.,  Farming Simulator 14 ,), strategy and management games (e.g.,  The Sims ,), sports games (e.g.,  FIFA 15 ), first person shooters (e.g.,  Call of Duty ), Multiplayer Online Battle Arena games (e.g.,  Heroes of Order & Chaos ), MMORPGs (e.g.,  Dawn of the Immortals ), and gaming versatility (i.e., playing more than one game genre during the past 12 months).

Psychometric tests: PMPU was assessed using the short version of the Problematic Mobile Phone Use Questionnaire (PMPUQ-SV; Billieux et al., 2008 ; Lopez-Fernandez et al., 2017 ). This assesses forbidden, dangerous, and self-perceived smartphone dependence, and was adapted to Finnish from French using the translation–back translation method ( Brislin, 1970 ). The response rate of the PMPUQ-SV was 79.4% in Belgium and 73.6% in Finland. The PMPUQ had good psychometric properties in previous studies, regarding its original longer version ( Billieux et al., 2008 ) and its dependence subscale ( Lopez-Fernandez et al., 2017 ). It comprises 15 items rated on a Likert scale (ranging from 1 “strongly agree” to 4 “strongly disagree”). The three subscales are: dependent use, e.g.,  It is hard for me to turn my mobile phone off ; dangerous use, e.g.,  While driving, I find myself in dangerous situations because of my mobile phone use , and prohibited use, e.g.,  I don’t use my mobile phone when it is completely forbidden to use it . Total scores range from 15 to 60, with higher scores representing increased presence of “problematic smartphone use”.

The Depression, Anxiety, and Stress Scale (DASS; Lovibond, & Lovibond, 1995a , 1995b ), which assesses these negative affective conditions was used in its shorter version (DASS-21; Antony, Bieling, Cox, Enns, & Swinson, 1998 ), translated into French and Finnish ( Lovibond, 2017 ). The short DASS was shown to have excellent psychometric properties, good factorial and concurrent validity, and Cronbach’s αs of .94 for depression, .87 for anxiety, and .91 for stress ( Antony et al., 1998 ). It comprises 21 items rated on a Likert scale (ranging from 0 “Did not apply to me at all” to 3 “Applied to me very much or most of the time”). The three subscales are: depression (assessing dysphoria, hopelessness, or anhedonia; e.g.,  I couldn’t seem to experience any positive feeling at all ), anxiety [assessing psychophysiological activation, and arousal, the subjective experience of anxious affect/skeletal musculature effects; e.g.,  I experienced trembling (e.g. in the hands) ], and stress (difficulty relaxing, being nervous, easily agitated/impatient; e.g.,  I found it hard to wind down ). Total scores range between 0 and 21 per subscale, with higher scores representing increased presence of these constructs.

The invitation to participate used three recruitment strategies: (a) inviting undergraduates during the Spring semester 2015 at both universities; inviting participants via (b) electronic invitations in academic online environments (e.g., Psychological Sciences Research Institute: https://www.uclouvain.be/364770.html ), and (c) SNSs (e.g., the TUD and Oulu UAS SNSs).

Statistical analysis

Comparisons of sociodemographic variables, use patterns, and mobile game genres across Belgium and Finland were tested with χ 2 , student t -tests, and non-parametric Mann–Whitney U tests. Exploratory Factor Analysis (EFA) with the principal components (PC) technique (using Promax rotation) was used to test the factor validity of the PMPUQ-SV. Student t -tests, multivariate analysis of variance, and Pearson’s correlation coefficient ( r ) were used to determine whether specific sociodemographic and usage patterns influenced problematic smartphone use. Additional Cronbach’s α and Pearson’s ( r ) coefficients were used to obtain internal reliabilities of the PMPUQ-SV and DASS-21 subscales and their degree of association. Finally, a set of multiple linear regressions with an entry method (i.e., forward type) was performed to identify potential predictors. SPSS 21 software was used.

The research team’s university ethics committee approved the study. All participants were informed about the study and all provided informed consent.

Sociodemographics and smartphone use in Belgium and Finland

Users from both countries were quite similar, as can be seen in Table  1 . However, some statistical differences in sociodemographics were observed [gender: χ 2 (1)  = 5.87, p  < .05; age: t (897)  = −4.15, p  < .001; relationship status: χ 2 (6)  = 175.1, p  < .001; profession: χ 2 (6)  = 24.84, p  < .001; educational level: χ 2 (6)  = 208.29, p  < .001], while their smartphone use showed no significant differences [e.g., time/weekday: Z  = −0.95, p  = .34; gaming behavior: χ 2 (1)  = 0.21, p  = .65; versatile gaming: χ 2 (1)  = 0.18, p  = .67].

Sociodemographic and patterns of using mobile phones/smartphones

Note. N  = 899; qualitative variables are shown with valid percentages and quantitative with mean ( M ) and standard deviation ( SD ).

Regarding gaming, Belgian and Finnish smartphone users were not prone to smartphone gaming, as the majority had not played any mobile game. However, when they played mobile games, they played quite often. More specifically, one-third of the Belgians and Finnish had played (Table  1 ), although only a few were categorized as versatile mobile gamers. The mobile game genres played were casual games, followed by strategy and solo mobile games (Table  2 ). Results also showed using Facebook and downloading apps were prevalent activities indirectly related to smartphone gaming. However, similar to smartphone gaming patterns described in Table  1 , there were no significant differences between countries in smartphone gaming activities [e.g., casual games: χ 2 (1)  = 0.02, p  = .88; strategy games: χ 2 (1)  = 1.53, p  = .22; downloading apps: χ 2 (1)  = 0.73, p  = .39]. However, there was a weak significant difference in SNS use [ Facebook : χ 2 (1)  = 4.13, p  < .05; Cramer’s V : 0.07, p  < .04].

Games used on smartphones ( N  = 889)

PMPUQ-SV descriptive statistics, associations, and psychometrics

The PMPUQ-SV scores were not significantly different between samples [ U: Z  = −0.71, p  = .480; M Belgium ( n  =465) = 27.66, SD  = 7.62; M Finland ( n  = 443) = 27.18, SD  =6.37] and between subscales [e.g., dependent use: U: Z  = −0.40, p  = .689; M Belgium ( n  = 465) = 11.15, SD  = 4.43; M Finland ( n  = 449) = 11.14, SD  = 3.63]. The analysis was carried out merging both samples to observe potential internal and external predictors of problematic smartphone use.

The results obtained through an EFA with the PC technique were Kaiser–Meyer–Olkin = 0.83, Bartlett’s test: χ² (105)  = 3,615.94; p  < .001, and yielded three factors that explained 50.7% of the variance. Specifically, the sums of the squared loadings were 4.01, 2.18, and 1.42 for Factors 1 “dependent use” (26.72% variance), 2 “dangerous use” (14.53% variance), and 3 “prohibited use” (9.44% variance), respectively, as expected following the factorial structure described in the method section. The 15-item scale had an overall good reliability (α = 0.79), similar to its subscales (Table  3 ); only “prohibited use” obtained a modest alpha, which is acceptable as it was above 0.5 as this coefficient is sensitive to the number of items in the scale (i.e., five items per PMPUQ-SV subscale; Cortina, 1993 ; Helmstadter, 1964 ).

Reliability and correlation matrix of the PMPUQ-SV and the DASS-21 subscales (Cronbach’s α; Pearson’s r ) in both countries (Belgium and Finland)

Note. PMPUQ-SV-P: prohibited use; PMPUQ-SV-D: dangerous use; PMPUQ-SV-Dep: dependent use; DASS-21-D: depression; DASS-21-A: anxiety; DASS-21-S: stress.

* p  < .05. ** p  < .001.

Sociodemographics were associated with problematic smartphone use. Females were more likely to be dependent on using smartphones [ t (399)  = −2.30, p  < .05 (men: M  = 11.17, SD  = 3.87, women: M  = 12.21, SD  = 3.72)], whereas males used smartphones more dangerously [ t (399)  = 2.74, p  < .001 (men: M  = 8.42, SD  = 3.05, women: M  = 7.47, SD  = 3.87)]. PMPUQ-SV scores significantly correlated with age (dangerous use: r  = 0.11, p  < .05; prohibited use: r  = −0.17, p  < .01), and older users tended to use smartphones in dangerous situations, whereas younger people used it more often when use was banned. A MANOVA was computed to check the interaction between country and age (as reported in Table  1 ) on the PMPUQ-SV subscales. Age predicted dependent use [ F (2, 755) =11.52, p  < .001] and prohibited use [ F (2, 755) = 11.64, p  < .001]. Only a first-order interaction appeared between age and country in prohibited use [ F (2, 755) = 7.94, p  < .01], because while in Belgium, banned smartphone use was decreasing by age groups ( Erikson, 1968 ; young adults: M  = 8.86, SD  = 2.74; middle aged: M  = 6.77, SD  = 2.78; older adults: M  = 5, SD  = 0), the tendency of Finns was also decreasing but reversing the scores in middle adulthood and producing a cross-over interaction between young and middle adults (young adults: M  = 8.22, SD  = 2.33; middle adults: M  = 7.81, SD  = 2.17; no data for older adults were reported). The other sociodemographic variables did not significantly predict PMPU. However, time spent using mobile games was associated with PMPU: days/week (dependent: r  = .28, p  < .001; dangerous: r  = .15, p  < .01) and min/week (dependent: r  = .36, p  < 0.001; dangerous: r  = −.15, p  < .01; prohibited: r  = −.17, p  < .01), supporting the PMPUQ-SV’s construct validity. Casual gamers scored higher on the PMPUQ-SV dependence subscale than participants who did not play casual games [dependent use: t (399)  = −2.06, p  < .05 (yes: M  = 12.09, SD  = 3.74, no: M  = 10.65, SD  = 3.87)]. Finally, the DASS-21 had high internal consistency and positively correlated with the PMPUQ-SV.

Predictors of perceived problematic smartphone use

A multiple linear regression was computed using the whole sample (rather than the respective subsamples per country), as most variables related to gaming behavior were similar across countries, with the PMPUQ-SV as outcome variable and these predictors: patterns of smartphone use regarding gaming [i.e., being a mobile gamer, having versatile gaming behaviors, playing casual games, downloading apps, using Facebook , country (Finland and Belgium), depression, anxiety, and stress]. The rationale behind the selected factors is that these were the more common variables related to smartphone gaming in the TUD project that showed in the descriptive analysis that Belgian and Finnish smartphone users usually associated with. Results showed the variance inflation factor (VIF) and tolerance index supported the absence of multicollinearity (i.e., VIF max  < 2.07, tolerance min  = 0.48). The Durbin–Watson coefficient indicated a lack of autocorrelation between adjacent residuals (0 < 2.25 < 4). A significant model emerged [ F (8, 214)  = 3.29, p  < .01; R 2  = .11], explaining 11% of variance. PMPUQ-SV scores were predicted by downloading apps ( B  = 1.62, SE B  = 0.63, β  = 0.17, t  = 2.59, p  < .05), Facebook use ( B  = 1.27, SE B  = 0.53, β  = .16, t  = 2.39, p  < .05), and stress ( B  = 0.52, SE B  = 0.15, β  = 0.31, t  = 3.38, p  < .01).

However, dimensions of PMPU slightly changed the predictors when computing a regression per subscale. Regarding dependent smartphone use (VIF max  < 2.02, tolerance min  = 0.48, Durbin–Watson = 2.18), a significant model emerged [ F (8, 214)  = 2.55, p  < .05] explaining 9% of the variance, positively predicted by Facebook use ( B  = 0.82, SE B  = 0.33, β  = 0.17, t  = 2.47, p  < .05) and being stressed ( B  = 0.31, SE B  = 0.10, β  = 0.30, t  = 3.21, p  < .01), but negatively predicted by anxiety ( B  = −0.27, SE B  = 0.12, β  =−0.52, t  = −0.58, p  < .05). Regarding prohibited smartphone use (VIF max  < 2.08, tolerance min  = 0.48, Durbin–Watson =1.98), a significant model emerged [ F (8, 214)  = 2.7, p  < .01], explaining 9% of the variance, predicted by downloading apps ( B  = 0.47, SE B  = 0.23, β  = 0.13, t  = 2.04, p  < .05), and being a Belgian resident ( B  = −0.44, SE B  = 0.17, β  = 0.18, t  = −2.63, p  < .01).

Despite the increased popularity of mobile phones and smartphone gaming, gaps in current knowledge were identified. This is the first study to examine the influence of smartphone and smartphone gaming on users’ self-perceived problematic use in Belgian and Finnish adults. It also adds to the current knowledge base by investigating potentially problematic smartphone gaming from a cross-national perspective. Smartphones have features and apps that facilitate habitual usage with many benefits (i.e., increased connection, productivity, and entertainment; Pew Research Center, 2015 ). The online-enabled features allow users to download and play games and interact with others anywhere at any time. In the present European sample, respondents were smartphone users regularly engaged in online activities (i.e., approximately 1.5 hr/daily). Mobile games were used by one-third of the respective populations, as stated by Deloitte ( 2014 ) for Finnish individuals and the ISFE ( 2012a ) for Belgians. The present findings suggest smartphone gaming, specifically casual gaming, is one of the main activities engaged in in these two countries, but it is not the most popular activity because social networking (i.e., using Facebook ) was more prevalent.

The findings showed that the favorite type of gaming on smartphones was playing casual games rather than MMORPGs, which are considered more addictive games on PCs and consoles ( Kuss, 2013 ; Kuss et al., 2012 ). These results are in line with ESA findings ( 2015 ), indicating social games, puzzle games, action, and strategy games are the most commonly played mobile games. As Engl and Nacke ( 2013 ) suggested, mobile game players may engage in these activities for instant entertainment and to fill time between daily activities (e.g., playing games while commuting). According to Jin et al. ( 2015 ), the expansion of smartphone gaming has been driven by the compact screen and easy mobility of these devices. This has generated an increasing production of casual games, similar to puzzle games, which are characterized as a leisure activity that requires sporadic attention of up to 5 min.

The PMPUQ-SV demonstrated that it had a three-factor structure in both languages and an adequate reliability, as has been shown in previous literature ( Billieux et al., 2008 ; Lopez-Fernandez et al., 2017 ). The results regarding the PMPU dependence subscale were similar to those by Roberts et al. ( 2014 ) who used the short Manolis/Roberts Cell-phone Addiction Scale, indicating smartphone gaming did not predict cell phone addiction, which is in accordance with the findings here. However, this study demonstrated higher problem and dependence scores, which were positively correlated with time spent on leisure mobile activities. On the one hand, these associations provide evidence for construct validity and the relationship between time and dependent smartphone use ( Bae, 2017 ). However, as a number of studies make clear, time spent using these devices and engaging in online activities excessively is not always associated with addictive use ( Griffiths, 2010 ). Furthermore, Rosen, Whaling, Carrier, Cheever, and Rokkum ( 2013 ) noted at least two issues when discussing time perception and problematic technology uses. First, the assessment of time spent using the technology has been proven to be problematic (e.g., users are not accurate at estimating the time they spend on the computer; Junco, 2013 ). Second, an individual’s preference for task-switching or multitasking may explain use times (e.g., half of the time when users were online they were multitasking; especially young adults are texting or using SNS; Moreno et al., 2012 ). Moreover, while females scored significantly higher on dependence, concurring with the findings of Roberts et al. ( 2014 ), males were more likely to use their smartphones in a dangerous way, similar to studies reporting the use of smartphones while driving ( McEvoy, Stevenson, & Woodward, 2006 ) and distraction while walking ( Zhou, 2015 ). With respect to age and time, both were only weakly associated with slight problems and not related to dependency. Overall, the results showed that the potential predictors of problematic smartphone use were downloading apps, using Facebook , and being stressed. Dependence was predicted by low anxiety, and prohibited use was a problem in the Belgian sample.

Evidence from previous research indicated that social networking is associated with addictive mobile behaviors (e.g.,  Jeong et al., 2016 ; Roberts et al., 2014 ; Salehan & Negahban, 2013 ). Furthermore, some SNSs (e.g., Facebook ) contain games ( Griffiths, 2012 ), sometimes offered by gambling developers ( Griffiths, 2015 ; Jacques et al., 2016 ), that can be played on smartphones by downloading the apps and accessing them via SNSs, and completing the games using different hardware (e.g., smartphones, PCs, and tablets). According to Müller, Wölfing, and Dreier ( 2013 ), the social networking component of online games indicates that a successful gamer has the subliminal quest for socializing (e.g., to update personal knowledge about the game of choice), and this could be an alternative explanation about the interdependent use of gaming and SNS. Furthermore, Jeong et al. ( 2016 ) highlighted mobile SNS use was a stronger predictor than mobile gaming for smartphone addiction. On the other hand, downloading apps has usually been studied in relation to pirate behaviors, and mobile games are not exempt from this ( Phau & Liang, 2012 ), which may offer a partial explanation for why downloading apps predicted prohibited smartphone use. Another explanation may be the social element to downloading apps (e.g., sharing results with others; Kim, Oh, Yang, & Kim, 2010 ). These two motivations for downloading apps hold for free-to-play Facebook games, which are easy and convenient, playable with friends, and as single players ( Kuo-Hsiang, Shen, & Min-Yuan, 2012 ; Paavilainen, Hamari, Stenros, & Kinnunen, 2013 ). Consequently, the present findings did not show that problematic gaming was present in the samples studied, in addition to gaming predictors not explaining PMPU. This is contrary to findings from Asiatic research studies carried out among adolescent populations ( Jeong et al., 2016 ; Lee et al., 2016 ). It may be that the phenomenon of smartphone gaming is more prevalent in Eastern cultures compared with Western cultures, although comparability is unclear as methods, populations, and other contextual characteristics (e.g., parenting, educational, and work environments) are different in both cultures and external predictors have not usually been studied.

The results regarding the mental health predictors were partially in line with Andreassen et al.’s ( 2016 ) recent findings relating to addictive video gaming, as in this study anxiety also negatively predicted smartphone dependence, but depression did not. Moreover, stress positively predicted problematic smartphone use and dependence (which had not been studied previously). Regarding depression, Andreassen et al. ( 2016 ) found there was a significant but weak correlation with addictive gaming. Concerning stress, an alternative explanation is required when using smartphone apps, such as games and SNSs, leading to more stress and increased self-perceived problematic smartphone use. However, Lee et al. ( 2014 ) found there is a type of stress associated with excessively using smartphones (e.g., checking notifications), which is an outcome, instead of a predictor, of problematic smartphone use. Finally, regarding anxiety, the relationship was indirect, because anxious adult smartphone users perceive themselves to be less dependent on smartphone use, possibly due to smartphone use providing a feeling of relief, especially from social anxiety, which usually emerges when encountering strangers in public settings ( Hoffner et al., 2016 ; Lee et al., 2014 ). In other words, anxiety decreases when using smartphones.

This suggests smartphone gaming is different from online gaming. As Jin et al. ( 2015 ) stated, the genre of gaming is platform-specific because online gaming is usually associated with PC games and requires a higher investment of time and effort relative to the playing of mobile games via smartphones. The psychosocial impact of mobile games may be different in comparison with non-mobile games, as are the behaviors engaged in and the online apps used across platforms, and the contexts of use (e.g., smartphones are frequently used when commuting). This could also have implications in relation to research related to IGD, because online gaming studies are usually based on gaming via consoles and PCs rather than gaming via smartphones. Furthermore, no game variables (i.e., playing casual games and gaming versatility) were related to problematic smartphone use. This makes intuitive sense because (a) smartphone gaming on a very small screen is much less immersive than gaming via consoles and PCs ( Hou, Nam, Peng, & Lee, 2012 ) and therefore less likely to be potentially problematic, and (b) the more addictive types of games (e.g., MMORPGs), at present, do not translate well on a small smartphone screen compared with simpler casual games that do not rely on sophisticated graphics and sound.

This study also explored gaming regarding smartphone use and problematic smartphone uses in two European countries. According to Jin et al. ( 2015 ), the increase of smartphone gaming is explained by sociocultural factors (e.g., mobility and environment), but people may play mobile games because they are entertaining and fun ( Banerjee & Das, 2015 ; ISFE 2012a , 2012b ), and they are an accepted pastime activity within Eastern and Western cultures. In this study, being Belgian predicted prohibited smartphone use, and although the literature is scarce regarding this technological use aspect across European cultures (e.g.,  ITU, 2016 ), it appears Belgians used smartphones when banned more than the Finnish sample in the case of young adults. One reason for this could be that younger age is related to higher smartphone use when prohibited, and in this study, the Belgian participants were younger than the Finnish participants (Table  1 ). According to Srivastava ( 2005 ), students and young adults appear to be the most avid users of mobile phones with little distinction between public and the private spheres (e.g., talking or texting on the phone when forbidden), despite countries attempting to regulate mobile phone usage in public (e.g., prohibiting or restricting use in restaurants, on public transport, in theatres, cinemas, and schools). However, there is not enough literature yet to ascertain why these few cross-cultural differences appeared in relation to prohibited use, and this could be due to different age groups instead of different cultures. In both countries, mobile phones are banned when driving (the penalty being double in Belgium compared with Finland; Jeanne Breen Consulting, 2009 ). Similarly, Campbell ( 2007 ) also had problems in interpreting why safety and security were cross-nationally differently perceived in relation to mobile phones between American and European countries. This component of PMPU requires more research.

Furthermore, cross-cultural differences in mobile phone use seem to have diminished in smartphones compared with traditional mobile phones ( Campbell, 2007 ), probably due to Internet access. This seems to suggest there is a common Internet culture that goes beyond geographical regions, languages, and other cultural behaviors, which can be considered to be an international culture of the smartphone, at least on the European continent. This similar culture has been observed in Internet activities through cross-country comparisons in other cross-cultural studies related to other behavioral problems (e.g., while differences in Internet use, innovation and perceived risk of Internet shopping have been found between Korean and American users, no differences were detected in online shopping experience and online buying intention in buying behavior; Park & Jong-Kun, 2003 ). Accordingly, technological features enable and constrain human behavior, producing consistencies and shared perceptions in uses and effects across people and cultures, specifically the younger users’ perceptions of the relevant dimensions of mobile gaming adoption, which could provide indirect evidence that different countries and cultures share common interests and motivations in terms of smartphone gaming (“mobile/global youth culture;” Okazaki et al., 2008 ; Van den Abeele, 2016 ). Castells ( 2002 ) argued the Internet is a cultural creation per se, with smartphones being the material expressions of this culture, containing a set of cognitions and behaviors that are shared among users. In other words, as Silver ( 2004 ) stated, the Internet could be considered a meta-field, even a culture, where smartphones have a space to facilitate behaviors like gaming. Consequently, mobile online gaming and other online apps are used and perceived in similar ways across different countries and cultures, which could explain why smartphone gaming patterns were similar in both countries.

The study is not without its limitations. First, self-selected convenience samples with a self-report methodology were used (which are open to social desirability and memory recall biases). However, the samples were large enough to generalize findings to similar academic populations in both countries. Moreover, as more females were recruited in both universities among social science schools, it is also possible that this gender difference explained part of the findings in this sample, as traditionally both genders appear to engage with SNSs and games differently. Females are more likely to use SNSs, while males are more likely to spend time gaming ( Andreassen et al., 2016 ; Ko, Yen, Chen, Chen, & Yen, 2005 ; Szell & Thurner, 2013 ; Winn & Heeter, 2009 ). Another limitation is that participants possibly overestimated or underestimated their true smartphone activities because of the retrospective nature of the survey, and previous research tracking mobile phone use has indicated that self-perception tends to underestimate time spent using smartphones ( Lin et al., 2015 ). Furthermore, the short PMPUQ, although generally internally consistent, had modest reliability for the prohibited subscale but this does not diminish its validity ( Schmitt, 1996 ). Finally, in future studies, other more specific predictors concerning personal characteristics of gamers (e.g., impulsivity traits, emotion regulation, and craving symptoms) and their smartphone behaviors (e.g., solely playing Facebook games, gaming-predominant vs. gaming using multiple applications) could be included ( Hormes, Kearns, & Timko, 2014 ; Liu et al. 2016 ). Furthermore, the smartphone gaming context should be studied (e.g., when commuting, when multitasking at home, when used for entertainment vs. working or study-related purposes; Jang & Ryu, 2016 ; Jeong et al., 2016 ; Lee et al., 2016 ).

The findings suggest that, at present, smartphone gaming does not appear to be problematic in terms of dangerous, prohibited, or dependent use in Belgium and Finland. Gamer characteristics (e.g., being a gamer, being a versatile gamer, or playing casual games) were not predictors of problematic smartphone use. However, when general problematic smartphone use is studied in adult European users, a few predictors appear to explain it (i.e., downloading apps, Facebook use, and stress). Furthermore, for those with a smartphone dependence, low anxiety emerged as predictor, as was using a smartphone when banned. These novel findings relating to gaming via smartphones demonstrated adult behaviors were similar cross-culturally, showing common characteristics, patterns, and perceptions in smartphone users, who did not perceive their smartphone use as problematic in general.

Funding Statement

Funding sources: This work was supported by the European Commission (“Tech Use Disorders;” FP7-PEOPLE-805-2013-IEF-627999) through a grant awarded to OL-F.

Authors’ contribution

OL-F was the principal investigator and oversaw the study concept and design, performed the statistical analysis, and initial interpretation of the data. Both OL-F and NM performed the initial literature search and wrote the first draft. DJK and MDG reviewed the manuscript adding comments and suggestions and oversaw the second draft. MK did last reviews, especially in relation to Finnish sample. All co-authors participated contributing in revising the subsequent versions until the final write-up of the manuscript.

Conflict of interest

The authors declare no conflict of interest.

• American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Association. [ Google Scholar ]
• Andreassen C. S., Billieux J., Griffiths M. D., Kuss D. J., Demetrovics Z., Mazzoni E., Pallesen S. (2016). The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study . Psychology of Addictive Behaviors, 30 ( 2 ), 252–262. doi: 10.1037/adb0000160 [ PubMed ] [ Google Scholar ]
• Antony M. M., Bieling P. J., Cox B. J., Enns M. W., Swinson R. P. (1998). Psychometric properties of the 42-item and 21-item versions of the Depression Anxiety Stress Scales (DASS) in clinical groups and a community sample . Psychological Assessment, 10 ( 2 ), 176–181. doi: 10.1037/1040-3590.10.2.176 [ Google Scholar ]
• Bae S. (2017). The relationship between the type of smartphone use and smartphone dependence of Korean adolescents: National survey study . Children and Youth Services Review, 81, 207–211. doi: 10.1016/j.childyouth.2017.08.012 [ Google Scholar ]
• Banerjee D., Das K. (2015). Smartphone gaming in Indian generation Y: An exploration . Romanian Journal of Marketing, 2, 54–66. [ Google Scholar ]
• Billieux J. (2012). Problematic use of the mobile phone: A literature review and a pathways model . Current Psychiatry Reviews, 8 ( 4 ), 299–307. doi: 10.2174/157340012803520522 [ Google Scholar ]
• Billieux J., Maurage P., Lopez-Fernandez O., Kuss D. J., Griffiths M. D. (2015). Can disordered mobile phone use be considered a behavioral addiction? An update on current evidence and a comprehensive model for future research . Current Addiction Reports, 2, 156–162. doi: 10.1007/s40429-015-0054-y [ Google Scholar ]
• Billieux J., Van der Linden M., Rochat L. (2008). The role of impulsivity in actual and problematic use of the mobile phone . Applied Cognitive Psychology, 22 ( 9 ), 1195–1210. doi: 10.1002/acp.1429 [ Google Scholar ]
• Brislin E. W. (1970). Back-translation for cross-cultural research . Journal of Cross-Cultural Psychology, 1 ( 3 ), 185–216. doi: 10.1177/135910457000100301 [ Google Scholar ]
• Campbell S. W. (2007). A cross-cultural comparison of perceptions and uses of mobile telephony . New Media & Society, 9 ( 2 ), 343–363. doi: 10.1177/1461444807075016 [ Google Scholar ]
• Castells M. (2002, Fall). The cultures of the Internet . Queen’s Quarterly, 109, 333–344. [ Google Scholar ]
• Cheever N. A., Rosen L. D., Carrier L. M., Chavez A. (2014). Out of sight is not out of mind: The impact of restricting wireless mobile device use on anxiety levels among low, moderate and high users . Computers in Human Behavior, 37, 290–297. doi: 10.1016/j.chb.2014.05.002 [ Google Scholar ]
• Cheng C., Leung L. (2016). Are you addicted to Candy Crush Saga? An exploratory study linking psychological factors to mobile social game addiction . Telematics and Informatics, 33 ( 4 ), 1155–1166. doi: 10.1016/j.tele.2015.11.005 [ Google Scholar ]
• Cortina J. M. (1993). What is coefficient alpha? An examination of theory and applications . Journal of Applied Psychology, 78 ( 1 ), 98–104. doi: 10.1037/0021-9010.78.1.98 [ Google Scholar ]
• Dauriat F. Z., Zermatten A., Billieux J., Thorens G., Bondolfi G., Zullino D., Khazaal Y. (2011). Motivations to play specifically predict excessive involvement in massively multiplayer online role-playing games: Evidence from an online survey . European Addiction Research, 17 ( 4 ), 185–189. doi: 10.1159/000326070 [ PubMed ] [ Google Scholar ]
• Deloitte. (2014). Mobile consumer 2014: The Finnish perspective. The pulse of the mobile nation . Retrieved February 7, 2017, from https://www2.deloitte.com/content/dam/Deloitte/fi/Documents/technology-media-telecommunications/Global%20Mobile%20Consumer%20Survey%202014_medium.pdf
• Deloitte. (2015). Mobile games in Europe: Innovation in European digital economy . Retrieved July 14, 2017, from https://www.euipo.europa.eu/ohimportal/delegate/webcontent-services/admindocs/wsdocumentdl/VZIUDXOSFQUIJ5OEO6HWWAPID2NVL7U276HVLNGG5TAW5S2Y3VPR253LWZXGPJ64CJQZWA27DVWD2
• Donati M. A., Chiesi F., Ammannato G., Primi C. (2015). Versatility and addiction in gaming: The number of video-game genres played is associated with pathological gaming in male adolescents . Cyberpsychology, Behavior, and Social Networking, 18 ( 2 ), 129–132. doi: 10.1089/cyber.2014.0342 [ PubMed ] [ Google Scholar ]
• Engl S., Nacke L. E. (2013). Contextual influences on mobile player experience – A game user experience model . Entertainment Computing, 4 ( 1 ), 83–91. doi: 10.1016/j.entcom.2012.06.001 [ Google Scholar ]
• Entertainment Software Association [ESA]. (2015). Essential facts about the computer and video game industry . Retrieved February 7, 2017, from http://www.theesa.com/wp-content/uploads/2015/04/ESA-Essential-Facts-2015.pdf
• Erikson E. H. (1968). Identity, youth, and crisis . New York, NY: Norton. [ Google Scholar ]
• European Digital Landscape. (2014). We are social . Retrieved November 4, 2017, from http://147.102.16.219/demo1/attachments/124_european%20digital%20landscape%202014.pdf
• Ferguson C. J., Coulson M., Barnett J. (2011). A meta-analysis of pathological gaming prevalence and comorbidity with mental health, academic and social problems . Journal of Psychiatric Research, 45 ( 12 ), 1573–1578. doi: 10.1016/j.jpsychires.2011.09.005 [ PubMed ] [ Google Scholar ]
• Gentile D. A., Choo H., Liau A., Sim T., Li D., Fung D., Khoo A. (2011). Pathological video game use among youths: A two-year longitudinal study . Pediatrics, 127 ( 2 ), e319–e329. doi: 10.1542/peds.2010-1353 [ PubMed ] [ Google Scholar ]
• Griffiths M. D. (1995). Technological addictions . Clinical Psychology Forum, 76, 14–19. [ Google Scholar ]
• Griffiths M. D. (2005). A “components” model of addiction within a biopsychosocial framework . Journal of Substance Use, 10 ( 4 ), 191–197. doi: 10.1080/14659890500114359 [ Google Scholar ]
• 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 ( 1 ), 119–125. doi: 10.1007/s11469-009-9229-x [ Google Scholar ]
• Griffiths M. D. (2012). Facebook addiction: Concerns, criticism, and recommendations – A response to Andreassen and colleagues . Psychological Reports, 110 ( 2 ), 518–520. doi: 10.2466/01.07.18.PR0.110.2.518-520 [ PubMed ] [ Google Scholar ]
• Griffiths M. D. (2015). Adolescent gambling and gambling-type games on social networking sites: Issues, concerns, and recommendations . Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33 ( 2 ), 31–37. [ Google Scholar ]
• Griffiths M. D., Szabo A. (2014). Is excessive online usage a function of medium or activity? An empirical pilot study . Journal of Behavioral Addictions, 3 ( 1 ), 74–77. doi: 10.1556/JBA.2.2013.016 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Helmstadter G. C. (1964). Principles of psychological measurement . New York, NY: Appleton-Century-Crofts. [ Google Scholar ]
• Hoffner C. A., Lee S., Park S. J. (2016). “I miss my mobile phone!”: Self-expansion via mobile phone and responses to phone loss . New Media & Society, 18 ( 11 ), 2452–2468. doi: 10.1177/1461444815592665 [ Google Scholar ]
• Hormes J. M., Kearns B., Timko C. A. (2014). Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits . Addiction, 109 ( 12 ), 2079–2088. doi: 10.1111/add.12713 [ PubMed ] [ Google Scholar ]
• Hou J., Nam Y., Peng W., Lee K. M. (2012). Effects of screen size, viewing angle, and players’ immersion tendencies on game experience . Computers in Human Behavior, 28 ( 2 ), 617–623. doi: 10.1016/j.chb.2011.11.007 [ Google Scholar ]
• Interactive Software Federation of Europe [ISFE]. (2012a). Videogames in Europe: consumer study, Belgium November 2012 . Brussels, Belgium: ISFE; Retrieved February 7, 2017, from http://www.isfe.eu/sites/isfe.eu/files/attachments/belgium_-_isfe_consumer_study_0.pdf [ Google Scholar ]
• Interactive Software Federation of Europe [ISFE]. (2012b). Videogames in Europe: consumer study, Finland November 2012 . Brussels, Belgium: ISFE; Retrieved February 7, 2017, from http://www.isfe.eu/sites/isfe.eu/files/attachments/finland_-_isfe_consumer_study.pdf [ Google Scholar ]
• International Telecommunication Union [ITU]. (2015). The World in 2015: ICT facts and figures . Geneva, Switzerland: ITU; Retrieved February 7, 2017, from http://www.itu.int/en/ITU-D/Statistics/Pages/facts/default.aspx [ Google Scholar ]
• International Telecommunication Union [ITU]. (2016). Measuring the information society report 2016 . Geneva, Switzerland: ITU; Retrieved February 7, 2017, from https://www.itu.int/en/ITU-D/Statistics/Documents/publications/misr2016/MISR2016-w4.pdf [ Google Scholar ]
• Jacques C., Fortin-Guichard D., Bergeron P., Boudreault C., Lévesque D., Giroux I. (2016). Gambling content in Facebook games: A common phenomenon? Computers in Human Behavior, 57, 48–53. doi: 10.1016/j.chb.2015.12.010 [ Google Scholar ]
• Jang Y., Ryu S. (2016). The role of parenting behavior in adolescents’ problematic mobile game use . Social Behavior and Personality, 44 ( 2 ), 269–282. doi: 10.2224/sbp.2016.44.2.269 [ Google Scholar ]
• Jeanne Breen Consulting. (2009). Car telephone use and road safety: Final report an overview prepared for the European Commission . Retrieved November 4, 2017, from https://ec.europa.eu/transport/road_safety/sites/roadsafety/files/pdf/car_telephone_use_and_road_safety.pdf
• Jeong S., Kim H., Yum J., Hwang Y. (2016). What type of content are smartphone users addicted to?: SNS vs. games . Computers in Human Behavior, 54, 10–17. doi: 10.1016/j.chb.2015.07.035 [ Google Scholar ]
• Jin D., Chee F., Kim S. (2015). Transformative mobile game culture: A sociocultural analysis of Korean smartphone gaming in the era of smartphones . International Journal of Cultural Studies, 18 ( 4 ), 413–429. doi: 10.1177/1367877913507473 [ Google Scholar ]
• Junco R. (2013). Comparing actual and self-reported measures of Facebook use . Computers in Human Behavior, 29 ( 3 ), 626–631. doi: 10.1016/j.chb.2012.11.007 [ Google Scholar ]
• Kaess M., Parzer P., Mehl L., Weil L., Strittmatter E., Resch F., Koenig J. (2017). Stress vulnerability in male youth with Internet gaming disorder . Psychoneuroendocrinology, 77, 244–251. doi: 10.1016/j.psyneuen.2017.01.008 [ PubMed ] [ Google Scholar ]
• Kanjo E., Kuss D. J., Ang C. S. (2017). NotiMind: Responses to smartphone notifications as affective sensors . IEEE Access . Advance online publication. doi: 10.1109/ACCESS.2017.2755661 [ Google Scholar ]
• Kim C., Oh E., Yang K. H., Kim J. K. (2010). The appealing characteristics of download type mobile games . Service Business, 4 ( 3–4 ), 253–269. doi: 10.1007/s11628-009-0088-0 [ Google Scholar ]
• Km W., Park B.-W., Lee K. C. (2011). Measuring smartphone dependence: A first step with emphasis on factor analytic evidence . Information – An International Interdisciplinary Journal, 14, 3031–3047. [ Google Scholar ]
• Ko C., Yen J., Chen C., Chen S., Yen C. (2005). Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents . Journal of Nervous and Mental Disease, 193 ( 4 ), 273–277. doi: 10.1097/01.nmd.0000158373.85150.57 [ PubMed ] [ Google Scholar ]
• Kuo-Hsiang C., Shen K., Min-Yuan M. (2012). The functional and usable appeal of Facebook SNS games . Internet Research, 22 ( 4 ), 467–481. doi: 10.1108/10662241211250999 [ Google Scholar ]
• Kuss D. J. (2013). Internet gaming addiction: Current perspectives . Psychology Research and Behavior Management, 6, 125–137. doi: 10.2147/PRBM.S39476 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kuss D. J., Louws J., Wiers R. W. (2012). Online gaming addiction? Motives predict addictive play behavior in massively multiplayer online role-playing games . Cyberpsychology, Behavior, and Social Networking, 15 ( 9 ), 480–485. doi: 10.1089/cyber.2012.0034 [ PubMed ] [ Google Scholar ]
• Kwon M., Lee J., Won W., Park J., Min J., Hahn C., Gu X., Choi J., Kim D. (2013). Development and validation of a Smartphone Addiction Scale (SAS) . PLoS One, 8 ( 2 ), e56936. doi: 10.1371/journal.pone.0056936 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Larche C. J., Musielak N., Dixon M. J. (2017). The Candy Crush Sweet Tooth: How ‘near-misses’ in Candy Crush increase frustration, and the urge to continue gameplay . Journal of Gambling Studies, 33 ( 2 ), 599–615. doi: 10.1007/s10899-016-9633-7 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lee C. (2017). Comparison of Korean and Chinese adolescents’ online games use including mobile games . In Jin D. (Eds.), Smartphone gaming in Asia. Mobile communication in Asia: Local insights, global implications (pp. 227–241). Dordrecht, The Netherlands: Springer. [ Google Scholar ]
• Lee S., Lee C., Lee C. (2016). Smartphone addiction and application usage in Korean adolescents: Effects of mediation strategies . Social Behavior and Personality, 44 ( 9 ), 1525–1534. doi: 10.2224/sbp.2016.44.9.1525 [ Google Scholar ]
• Lee Y., Chang C., Lin Y., Cheng Z. (2014). The dark side of smartphone usage: Psychological traits, compulsive behavior and technostress . Computers in Human Behavior, 31, 373–383. doi: 10.1016/j.chb.2013.10.047 [ Google Scholar ]
• Lin Y.-H., Lin Y.-C., Lee Y.-H., Lin P.-H., Lin S.-H., Chang L. R., Tseng H. W., Yen L. Y., Yang C. C., Kuo T. B. J. (2015). Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App) . Journal of Psychiatric Research, 65, 139–145. doi: 10.1016/j.jpsychires.2015.04.003 [ PubMed ] [ Google Scholar ]
• Liu C.-H., Lin S.-H., Pan Y.-C., Lin Y.-H. (2016). Smartphone gaming and frequent use pattern associated with smartphone addiction . Medicine, 95 ( 28 ), e4068. doi: 10.1097/MD.0000000000004068 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Liu Y., Li H. (2011). Exploring the impact of use context on mobile hedonic services adoption: An empirical study on smartphone gaming in China . Computers in Human Behavior, 27 ( 2 ), 890–898. doi: 10.1016/j.chb.2010.11.014 [ Google Scholar ]
• Lopez-Fernandez O., Kuss D. J., Romo L., Morvan Y., Kern L., Graziani P., Rousseau A., Rumpf H. J., Bischof A., Gässler A. K., Schimmenti A., Passanisi A., Männikkö N., Kääriänen M., Demetrovics Z., Király O., Chóliz M., Zacarés J. J., Serra E., Griffiths M. D., Pontes H. M., Lelonek-Kuleta B., Chwaszcz J., Zullino D., Rochat L., Achab S., Billieux J. (2017). Self-reported dependence on mobile phones in young adults: A European cross-cultural empirical survey . Journal of Behavioral Addictions, 6 ( 2 ), 168–177. doi: 10.1556/2006.6.2017.020 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Lovibond P. F. (2017). Depression Anxiety Stress Scales [DASS Translations]. Retrieved May 16, 2017, from http://www2.psy.unsw.edu.au/dass/translations.htm
• Lovibond S. H., Lovibond P. F. (1995a). Manual for the Depression Anxiety & Stress Scales (2nd ed.). Sydney, Australia: Psychology Foundation. [ Google Scholar ]
• Lovibond P. F., Lovibond S. H. (1995b). The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories . Behaviour Research and Therapy, 33 ( 3 ), 335–343. doi: 10.1016/0005-7967(94)00075-U [ PubMed ] [ Google Scholar ]
• Mäyrä F., Karvinen J., Ermi L. (2016). The Finnish player barometer 2015 [Pelaajabarometri 2015] . Tampere, Finland: University of Tampere. [ Google Scholar ]
• McEvoy S. P., Stevenson M. R., Woodward M. (2006). Phone use and crashes while driving: A representative survey of drivers in two Australian states . Medical Journal of Australia, 185 ( 11 ), 630–634. [ PubMed ] [ Google Scholar ]
• Moreno M. A., Jelenchick L., Koff R., Eikoff J., Diermyer C., Christakis D. A. (2012). Internet use and multitasking among older adolescents: An experience sampling approach . Computers in Human Behavior, 28 ( 4 ), 1097–1102. doi: 10.1016/j.chb.2012.01.016 [ Google Scholar ]
• Müller K. W., Wöffling K., Dreier M. (2013). Risks of developing Internet addictive behaviors: Scope and extent of Internet sites used . International Journal of Child and Adolescent Health, 6 ( 4 ), 399–409. doi: 10.1007/s11920-014-0508-2 [ Google Scholar ]
• Newzoo. (2017). The global market will reach $108.9 billion in 2017 with mobile taking 42%, April 20 . Retrieved July 13, 2017, from https://newzoo.com/insights/articles/the-global-games-market-will-reach-108-9-billion-in-2017-with-mobile-taking-42/
• Okazaki S., Skapa R., Grande I. (2008). Capturing global youth: Smartphone gaming in the U.S., Spain, and the Czech Republic . Journal of Computer-Mediated Communication, 13 ( 4 ), 827–855. doi: 10.1111/j.1083-6101.2008.00421.x [ Google Scholar ]
• Paavilainen J., Hamari J., Stenros J., Kinnunen J. (2013). Social network games: Players’ perspectives . Simulation and Gaming, 44 ( 6 ), 794–820. doi: 10.1177/1046878113514808 [ Google Scholar ]
• Park C., Jong-Kun J. (2003). A cross-cultural comparison of Internet buying behavior: Effects of internet usage, perceived risks, and innovativeness . International Marketing Review, 20 ( 5 ), 534–553. doi: 10.1108/02651330310498771 [ Google Scholar ]
• Pew Research Center. (2015). U.S. smartphone use in 2015 . Retrieved February 7, 2017, from http://www.pewinternet.org/2015/04/01/us-smartphone-use-in-2015/ [ Google Scholar ]
• Phau I., Liang J. (2012). Downloading digital video games: Predictors, moderators and consequences . Marketing Intelligence & Planning, 30 ( 7 ), 740–756. doi: 10.1108/02634501211273832 [ Google Scholar ]
• Roberts J. A., YaYa L. H. P., Manolis C. (2014). The invisible addiction: Cell-phone activities and addiction among male and female college students . Journal of Behavioral Addictions, 3 ( 4 ), 254–265. doi: 10.1037/t39752-00010.1556/JBA.3.2014.015 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rosen L. D., Whaling K., Carrier L. M., Cheever N. A., Rokkum J. (2013). The media and technology usage and attitudes scale: An empirical investigation . Computers in Human Behavior, 29 ( 6 ), 2501–2511. doi: 10.1016/j.chb.2013.06.006 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Salehan M., Negahban A. (2013). Social networking on smartphones: When mobile phones become addictive . Computers in Human Behavior, 29 ( 6 ), 2632–2639. doi: 10.1016/j.chb.2013.07.003 [ Google Scholar ]
• Schmitt N. (1996). Uses and abuses of coefficient alpha . Psychological Assessment, 8 ( 4 ), 350–353. doi: 10.1037/1040-3590.8.4.350 [ Google Scholar ]
• Silver D. (2004). Internet/cyberculture/digital culture/new media/fill-in-the-blank studies . New Media & Society, 6 ( 1 ), 55–64. doi: 10.1177/1461444804039915 [ Google Scholar ]
• Snodgrass J. G., Lacy M. G., Dengah H. J. F., Eisenhauer S., Batchelder G., Cookson R. J. (2014). A vacation from your mind: Problematic online gaming is a stress response . Computers in Human Behavior, 38, 248–260. doi: 10.1016/j.chb.2014.06.004 [ Google Scholar ]
• Srivastava L. (2005). Mobile phones and the evolution of social behavior . Behaviour & Information Technology, 24 ( 2 ), 111–129. doi: 10.1080/01449290512331321910 [ Google Scholar ]
• Su Y. S., Chiang W. L., Lee C. T. J., Chang H. C. (2016). The effect of flow experience on player loyalty in mobile game application . Computers in Human Behavior, 63, 240–248. doi: 10.1016/j.chb.2016.05.049 [ Google Scholar ]
• Szell M., Thurner S. (2013). How women organize social networks different from men . Scientific Reports, 3 ( 1 ), 1214. doi: 10.1038/srep01214 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Tech Use Disorders [TUD]. (2017). Technological use disorders: European cross-cultural longitudinal and experimental studies for Internet and smartphone problem uses, July 12 . Retrieved July 14, 2017, from http://cordis.europa.eu/project/rcn/189961_en.html
• Thomée S., Härenstam A., Hagberg M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults – A prospective cohort study . BMC Public Health, 11 ( 1 ), 66. doi: 10.1186/1471-2458-11-66 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Thomée S., Härenstam A., Hagberg M. (2012). Computer use and stress, sleep disturbances, and symptoms of depression among young adults – A prospective cohort study . BMC Psychiatry, 12 ( 1 ), 176. doi: 10.1186/1471-244X-12-176 [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Van den Abeele M. M. P. (2016). Mobile lifestyles: Conceptualizing heterogeneity in mobile youth culture . New Media & Society, 18 ( 6 ), 908–926. doi: 10.1177/1461444814551349 [ Google Scholar ]
• Winn J., Heeter C. (2009). Gaming, gender, and time: Who makes time to play? Sex Roles, 61 ( 1–2 ), 1–13. doi: 10.1007/s11199-009-9595-7 [ Google Scholar ]
• Zhou Z. (2015). Heads up: Keeping pedestrian phone addicts from dangers using mobile phone sensors . International Journal of Distributed Sensor Networks, 11 ( 5 ), 279846–279849. doi: 10.1155/2015/279846 [ Google Scholar ]

Playing games: advancing research on online and mobile gaming consumption

Internet Research

ISSN : 1066-2243

Article publication date: 9 April 2019

Issue publication date: 9 April 2019

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

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

Introduction

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

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

An integrative summary of the special issue

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

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

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

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

Future directions for research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Acknowledgements

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

Corresponding author

About the authors.

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

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

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

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Effects of Mobile Gaming to the Performance of the Students in Palahanan National High School

• Ericka Canarias

INTRODUCTION

Mobile games are always associated with poor academic performance. They largely influence the participation of students during class. Mobile Legends, Clash of Clans, and Clash Royale are some of the examples of these mobile games. However, some research studies have been proven that mobile games can bring positive learning outcomes. This study will give significance to mobile gaming which took part in the classroom environment and surprisingly made students actively engage with learning.

The descriptive method was used with the questionnaire as the main data gathering instrument that sought to identify the influences of mobile games to the cognitive development of the students. It was conducted to the STEM students of Palahanan National High School. Frequency, percentage, ranking and weighted mean were used to quantify data to look forward for the positive benefits of games in academic performance of the students.

Mobile gaming is one of the factors which affect academic performance of students. Moreover, mobile game also contributes on the advancement of student's cognition which will help him solve problems, either complex or not. Mobile gaming brings negative impacts on students' academic performance. Despite of this, it is proven that mobile games have the potential to increase participation of students. This can be done through applying this activity in the learning process inside the classroom. Teachers can use mobile gaming as incentives for students. Aside from this, several mobile games enhance vocabulary and mathematical intellect of students. Additionally, cognitive ability can be developed through mobile gaming since game apps are technologically developed to test the critical thinking and analytical skills of a person. Mobile games are brain-challenging in nature which can help a person solve more complex problems.

DISCUSSIONS

Students should be aware of the negative effects of mobile gaming andhow they can cope up with it. Teachers can use mobile gaming as an incentive for students. They can apply gaming in the learning process to be able to increase participation inside the classroom.

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©2017 by Ascendens Asia Pte. Ltd. | NLB Singapore-Registered Publisher.

BRIEF RESEARCH REPORT article

The association between mobile game addiction and depression, social anxiety, and loneliness.

• 1 Center for Mental Health Education, School of Psychology, Southwest University, Chongqing, China
• 2 Chongqing Youth and Vocational Technical College, Chongqing, China

As a new type of addictive behaviors and distinct from traditional internet game addiction on desktop computers, mobile game addiction has attracted researchers' attention due to its possible negative effects on mental health issues. However, very few studies have particularly examined the relationship between mobile game addiction and mental health outcomes, due to a lack of specified instrument for measuring this new type of behavioral addiction. In this study, we examined the relationship between mobile game addition and social anxiety, depression, and loneliness among adolescents. We found that mobile game addiction was positively associated with social anxiety, depression, and loneliness. A further analysis on gender difference in the paths from mobile game addiction to these mental health outcomes was examined, and results revealed that male adolescents tend to report more social anxiety when they use mobile game addictively. We also discussed limitations and implications for mental health practice.

With the fast development of mobile technology, many functions of desktop computers have been transferred to mobile devices like ipad and smartphone, which is especially the case for game applications. Mobile video games refer to games played by either single or multi players via online mobile devices. These games are particularly popular when they can be downloaded for free (e.g., “freemium games,” which are free but customers pay for extra features) ( 1 ). The latest China Internet Network Information Center's (CNNIC) report revealed that the growth rate of mobile online game has reached 9.6% and adolescents are the main user group ( 2 ). In comparison with most segments of society, adolescents are more vulnerable to Internet-related addiction because of their psychological and developmental characteristics, the easy access to Internet with a portable device, and the positive expectation of mobile gaming ( 3 ). It has been demonstrated that video game addicts suffered poorer mental health and cognitive functioning, and increased emotional difficulties, such as enhanced depression and anxiety, as well as more social isolation ( 4 ).

Despite this, relatively few studies have examined the relationship between mobile game addiction and mental health outcomes. This is because, so far, no measurement especially designed for mobile game addiction has been developed. In literature, problematic mobile video gaming has been defined as a phenomenon in which users strongly rely on mobile games and cannot help playing them repeatedly over a comparatively long period ( 5 ). Previous studies of Internet gaming disorder (IGD) have mainly focused on traditional online gaming addiction based on a desktop computer. However, recent research has suggested that there were only moderate correlations between the different forms of Internet addiction ( 6 ). In addition, although mobile game addiction has some similarity with traditional desktop computer online game addiction, there are still obvious differences. Specifically, mobile video games are characterized by portability, immediacy, and accessibility ( 7 ), which may increase the risk for addictive behavioral patterns and, thus, more severe mental health problems.

Additionally, most prior studies have treated social anxiety, depression, and loneliness as risk factors for Internet-relevant addiction ( 8 , 9 ), whereas, few studies have examined the alternative direction ( 10 ). A relevant study found that the relative risk for depression in students with Internet addiction after months was 1.5 times higher than that of non-Internet addiction participants, after controlling for potential confounding variables (gender, study burden, age, rural, or urban school). This indicated that Internet relevant addiction may also lead to depression and loneliness ( 11 ). Another reason for conducting the current study was because the relationship between playing video games and psychological adjustment during adolescence is relatively scarce, which is especially true for investigating the association between playing video games and social anxiety among adolescents ( 12 ). Therefore, an investigation on this issue can help us understand how mobile game addiction may hinder adolescents' social development and would provide some guidance for mental health education practice.

Theoretical Framework

Mobile game addiction and depression.

Internet game addiction is characterized by cognitive and emotional deficits. Previous studies have reported the co-occurrence of Internet addition and depression ( 13 , 14 ). In addition, a longitudinal study found that Internet game addition/depression severity at an earlier time positively predicted the depression/Internet game addition severity at a later time, which indicated that a possible bidirectional relationship existed between online gamers' depression symptoms and addiction. People cope with their emotional distress by playing online games, but the excessive use of online games for a long time may separate individuals from real-life relationships, thus causing severer mental health problems, such as depression ( 15 ). Therefore, in this study, we would expect a positive relationship between mobile game addition and depression.

Mobile Game Addition and Loneliness

Loneliness is defined as an unpleasant experience that derives from important deficiencies in a person's network of social relationships ( 16 ). Previous studies have consistently confirmed the connection between loneliness and online game addiction ( 17 , 18 ). Furthermore, loneliness is not only the cause of online gaming addiction but also the consequence; there is a possible reciprocal relationship ( 19 ). Prior research has indicated that, although playing online games may temporarily provide an escape from the negative feelings associated with social deficiencies, excessive gaming does little to facilitate the development or maintenance of real-life relationships. Instead, the substitution for interpersonal interactions in real life may exacerbate the deterioration of existing social relationships, thereby increasing loneliness ( 19 ). Thus, we would expect a positive association between mobile game addiction and loneliness in this study.

Social Anxiety

Social anxiety, which is the most common anxiety disorder in adolescence, is the state of tension or discomfort experienced by individuals in social situations ( 20 ). The investigation on the potential effects of mobile game addiction and adolescence social anxiety is of importance considering that approximately one third of adolescents meet the criteria for an anxiety disorder ( 21 , 22 ). Some literature indicates that Internet addiction, smartphone addiction, and online game addiction were all associated with an individual's social anxiety [e.g., ( 23 )]. Individuals with a serious tendency for online gaming addiction have significantly higher social anxiety levels than those who use online games normally. Lo et al. ( 24 ) investigated the potential effects of online games on the quality of interpersonal relationships and levels of social anxiety. The results indicated that the quality of interpersonal relationships may be undermined and the amount of social anxiety may increase when teenagers spend more time playing online games ( 24 ). In the current study, we would expect a positive association between mobile game addiction and social anxiety.

Gender Difference

Gender has been proposed as an important factor in influencing Internet use and its outcomes regarding mental health (e.g., 8). Evidence has suggested that males have a predilection toward activities that involve explosive action and combat, while females are drawn toward activities that are more social and communication focused ( 25 ). Females received more family supervision, which may prevent them from developing Internet addiction ( 26 ). In a more recent study, female video game addicts displayed significantly more somatic difficulties than male addicts ( 4 ). They further argued that female addicts may be uniquely at risk for negative physical health outcomes and sleep disturbances ( 4 ). Significant gender difference was also revealed on the association between family function and Internet addiction among adolescence ( 27 ). Females showed more negative consequences of its maladaptive mobile phone use ( 28 ). These studies highlighted the need to explore gender differences in mobile game addition and mental health problems further.

Participants and Data Collection Procedure

Data of this study was from the students ( n = 600) enrolled in the seventh, eighth, and ninth grades of a junior high school in Guizhou Province. Letters describing the project were sent home to parents with a consent form inviting participation. Children whose parents provided written informed consent and who themselves gave assent completed the questionnaire in classroom settings. Prior to answering the items, participants read information about the implications of participation and data protection. The information emphasized that participation was completely voluntary and anonymous. Excluding missing or incomplete data, 578 survey responses were collected (mean age = 15 years, SD = 1.05). 56.7% ( n = 328) participants were self-identified as males.

Mobile Game Addiction Scale

This scale was specially developed for the measurement of mobile game addiction and included 11 items ( 29 ). Each item was rated on a Likert-type scale from 1 = completely disagree to 5 = completely agree, with the total scores ranging from 11 to 55. A higher score indicated a severer addition tendency. This scale has shown good construct validity, with χ 2 /df = 2.835, RMSEA = 0.056, 90% CI (0.044, 0.069), SRMR = 0.037, CLI = 0.970, TLI = 0.959, the Cronbach alpha coefficient in the current study was 0.84. Sample items included: “ During the last year, have you felt miserable when you were unable to play mobile video games or played less than usual? ” and “ During the last year, have you played mobile video games so that you would not have to think about annoying things? ”

Depression Scale

The depression subscale from the Brief Symptom Inventory (BSI) was used to assess the depression symptoms ( 30 ). The scale contains 6 items and each item was rated on a 5-point Likert scale, ranging from 1 (not at all) to 5 (extremely serious). Higher scores indicate severe depressive symptoms. We did a measurement model analysis, and the scale showed good construct validity, with χ 2 /df = 1.931,RMSEA = 0.040,90% CI(0.000, 0.070),SRMR = 0.020,CFI = 0.994, TLI = 0.989. The Cronbach alpha coefficient in the current study was 0.84. Sample items included: “ You feel sad ” and “ You find everything dull .”

Child Loneliness Scale

The revised version of the Child Loneliness Scale was adopted to evaluate individuals' loneliness ( 31 ). The scale contains 16 items, which were answered using a 5-point Likert scale ranging from 1 (always) to 5 (never); higher scores indicate elevated loneliness. Good construct validity was exhibited in the current sample, with χ 2 /df = 2.833, RMSEA = 0.056, 9 % CI(0.048, 0.065), SRMR = 0.0461, CFI = 0.940, TLI = 0.918. The Cronbach alpha coefficient in our sample was 0.86. Sample items included: “ I don't have any friends ” and “ I feel lonely .”

Child Social Anxiety Scale

The modified version of the Child Social Anxiety Scale was used to assess participants' social anxiety ( 32 ). The term “children” in the original scale was changed to “classmate” in the current version. The scale contains 10 items and each item was rated using a 3-point Likert scale, ranging from 1 = never to 3 = always. Higher scores indicate higher levels of social anxiety. The scale has been proved to have good construct validity in the current study, with χ 2 / df = 2.872, RMSEA = 0.057, 90% CI(0.044, 0.071), SRMR = 0.041, CFI = 0.951, TLI = 0.931, and the Cronbach alpha coefficient in our sample was 0.80. Sample items included: “ I think my classmates make fun of me ” and “ I'm afraid other students won't like me .”

Descriptive Statistics and Zero-Order Correlations Among the Study Variables

Table 1 shows the descriptive results and zero-order correlations among the study variables. Mobile addiction was positively correlated with depression, loneliness, and social anxiety, with the correlations ranging from 0.18 to 0.46 ( p s < 0.01).

Table 1 . Descriptive results and zero-order correlations among the study variables.

Structural Equation Modeling on the Relationship Between Mobile Game Addiction, Depression, Social Anxiety, and Loneliness

Using Amos 22.0, we conducted a structural equation analysis to examine the association between mobile game addiction, depression, social anxiety, and loneliness.

Several underlying statistical assumptions for multiple regression analysis were examined before running the structural modeling. The assumption of homoscedasticity was checked using the Levene's Test for Equality of Variances ( 33 ). The test ensured no significant differences in the variance of the three dependent variables of social anxiety, depression, and loneliness across groups defined by mobile gaming addiction ( p > 0.05 for all cases). Thus, the assumption of homoscedasticity was not violated ( 34 ). Second, the skewness values for all variables ranged from 0.25 to 0.82 and the kurtosis values ranged from 0.27 to 0.30, which are within the acceptable range of −1 to +1 for normality ( 35 ). Thus, the violation of the normality assumption was not present in the sample data. Thirdly, the assumption of independence of residuals was confirmed by the calculation of the Durbin–Watson statistics for the dependent variables of depression (= 1.36), social anxiety (= 1.76), and loneliness (= 1.71), which are within the acceptable range of 1.5–2.5 for independence ( 36 ). Lastly, multi-collinearity was evaluated through the assessment of zero-order correlations among selected measured constructs, as calculated in Table 1 . Harris and Hagger ( 37 ) noted that multicolline arity is not a serious issue if none of the correlation coefficients between variables exceeds 0.70. It is apparent that pair-wise bivariate associations between the study variables were not highly correlated with each other. Accordingly, multi-collinearity was dismissed from being a major concern in the present study ( 38 ). To conclude, the sample data were judged to meet the criteria for further analysis.

Model fit was assessed by considering multiple criteria: a Chi-square/df < 5 a root mean square error of approximation (RMSEA) of <0.08 and a comparative fit index (CFI) and a Tucker-Lewis index (TLI) of >0.90 ( 39 ). The model fit was considered acceptable when most abovementioned criteria were satisfied. Our results showed that the model fit to the data well, with χ 2 /df = 3.475, RMSEA = 0.065, 90% CI (0.06, 0.07), CLI = 0.937, TLI = 0.921. Mobile game addiction can explain 10% variance of depression, 6% variance of social anxiety, and 4% variance of loneliness. The standardized beta coefficients are shown in Figure 1 . Mobile game addiction was positively related to depression, social anxiety, and loneliness, with β = 0.31, p < 0.001, β = 0.25, p < 0.001, and β = 0.21, p < 0.001, respectively.

Figure 1 . The Structural Modeling on the relation between mobile game addiction and depression, social anxiety, and loneliness. *** p < 0.01.

Considering that gender was proposed as a variable that may moderate the relationship between mobile game addiction and mental health outcomes, the moderating effect of gender was tested. We created a multi-group model in AMOS to test the differences between males and females on the paths between mobile game addiction and its outcomes. The results show that significant gender differences exist considering the relationship between mobile game addiction and social anxiety. Male adolescents who used mobile game additively reported higher levels of social anxiety (β = 0.118, p < 0.001), depression (β = 0.280, p < 0.001), and loneliness (β = 0.311, p < 0.001), compared with female adolescents (β = 0.077, p < 0.001; β = 0.17, p < 0.01; and β = 0.16, p < 0.05, respectively; see Table 2 for details).

Table 2 . Multi-group (male and female) analysis on the relationship among mobile game addiction and depression, social anxiety, and loneliness.

The goal of this study was to examine the associations between mobile game addiction and depression, loneliness, social anxiety, and the potential gender difference in these associations were also investigated. The results revealed that adolescent with mobile game addiction had higher self-reported depression, social anxiety and loneliness, which have supported our three hypotheses regarding the association between mobile game addiction and depression, social anxiety, and loneliness. Further, gender difference was observed in the path between mobile game addiction and social anxiety, with male adolescents having a stronger association between mobile game addiction and social anxiety. This indicates that male adolescents may experience more social anxieties if they use mobile game addictively, compared with female adolescents.

As we expected, mobile game addiction was positively associated with depression, anxiety, and loneliness, which have supported all of our three hypotheses and are in line with prior findings. Literature has consistently shown that video game addicts reported more anxiety, depression, lower positive affect and psychological well-being. Literature has also shown that Internet addictions are related to poorer emotional health, in particular depression and anxiety ( 40 , 41 ). For instance, Whang et al. ( 41 ) found a significant association between degree of Internet addiction and loneliness and depression. Adolescents with high Internet use exhibited more psychopathology, as revealed by the Brief Symptoms Inventory (BSI, a reduced version of the Symptoms Checklist, SCL-90) compared with those with low those use ( 42 ). In a recent study, ( 4 ) reported that young adults addicted to video games showed increased depression and anxiety, and felt more socially isolated. The link between mobile game addiction and mental health may be due to the social isolation resulting from spending too much time gaming, which in turn leads to undermined psychological well-being ( 43 ). Our results regarding the association between mobile game addiction and loneliness are also in line with the displacement hypothesis in terms of Internet use, which argues that digital device users have spent most time in online settings, rather than offline, and their existing relationships have suffered as a result ( 44 ).

We also expected a gender difference considering the association between mobile game addiction and mental health outcomes. We found that males who were addicted to mobile games tended to suffer more social anxiety, loneliness, and social anxiety, compared with females. This finding is line with prior research (e.g., 24). Gender difference on social anxiety and loneliness has been widely reported in literature. Compared with female adolescents, male adolescents tended to lack social skills, were more socially withdrawn and disclosed less about themselves in offline communication settings ( 45 ). This is also a reason why males are more likely to be attracted to a virtual world like computer games since the online world is more comfortable and can offer more sense of security ( 46 ). This would further lead them to be more social isolated and experience more social anxiety, loneliness, and depression due to the lack of social bond in offline settings.

Limitations and future directions

The results of this study should be viewed in light of its limitations. First, this study is a cross-sectional design. Thus, we could not determine a causal link between study variables. Future investigations should adopt an experimental design to establish the causal relationship between variables, or a longitudinal design to examine the prospective relationship among the variables. As prior studies indicated, the association between mobile game addiction and mental health problems might be reciprocal. Second, the sample is a homogeneous group of students from a middle school in China. Whether the results can be generalized to all adolescents is a question for future research.

Despite the limitations, our study has examined the association between mobile game addiction and depression, social anxiety, and loneliness, based on an adolescent sample. The results indicated that mobile game addiction was positively related to these mental health problems, and this is especially true for male adolescents as they are more likely to experience a higher level of social anxiety, depression, and loneliness after excessive use of mobile gaming. Therefore, mental health educators and practicers should be aware of the negative effects caused by addictive mobile gaming, as this is such a common phenomenon today. Specifically, attention should be given to male adolescents who are addicted to mobile gaming, as they may suffer more social anxiety.

Data Availability

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

The studies involving human participants were reviewed and approved by Southwest University's Human Research Ethics Committee. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.

Author Contributions

J-LW drafted the initial version of the manuscript and responded to the reviewers' comments. J-RS analyzed the data. H-ZW collected the data and provided the comments.

This study has been supported by the Major Cultivating Project in Southwest University (No. SWU1809006).

Conflict of Interest Statement

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.

1. Su YS, Chiang WL, Lee CTJ, Chang HC. The effect of flow experience on player loyalty in mobile game application. Comput Hum Behav. (2016) 63:240–8. doi: 10.1016/j.chb.2016.05.049

CrossRef Full Text | Google Scholar

2. China Internet Network Information Center. The 41th Statistical Report on the Development of Internet in China. (2018). Available online at: http://www.cnnic.net.cn/ (accessed October 30, 2018).

3. Kandell JJ. Internet addiction on campus: the vulnerability of college student. Cyber Psychol Behav. (1998) 1:11–8. doi: 10.1089/cpb.1998.1.11

4. Stockdale L, Coyne SM. Video game addiction in emerging adulthood :cross-sectional evidence of pathology in video game addicts as compared to matched healthy controls. J Affect Disord. (2018) 225:265–72. doi: 10.1016/j.jad.2017.08.045

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Sun Y, Zhao Y, Jia SQ, Zheng DY. Understanding the antecedents of mobile game addiction: the roles of perceived visibility, perceived enjoyment and flow. In: Proceedings of the 19th Pacific-Asia Conference on Information Systems. Singapore: Marian Bay Sands (2015). p. 1–12. Available online at: http://aisel.aisnet.org/pacis2015/141

Google Scholar

6. Sha P, Sariyska R, Riedl R, Lachmann B, Montag C. Linking Internet communication and smartphone use disorder by taking a closer look at the Facebook and WhatsApp applications. Addict Behav Rep. (2018) 9:100148. doi: 10.1016/j.abrep.2018.100148

7. Lee C, Kim O. Predictors of online game addiction among Korean adolescents. Addict Res Theory. (2017) 25:58–66. doi: 10.1080/16066359.2016.1198474

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

9. Ko C, Yen J, Chen C, Yeh Y, Yen C. Predictive values of psychiatric symptoms for Internet addiction in adolescents. JAMA Pediatrics. (2011) 163:937–43. doi: 10.1001/archpediatrics.2009.159

10. Taylor S. (2017). The theoretical underpinnings of Internet addiction and its association with psychopathology in adolescence. Int J Adolesc Med Health . 2017:46. doi: 10.1515/ijamh-2017-0046

11. Lawrence TL, Peng Z-W. Effect of pathological use of the Internet on adolescent mental health. JAMA Pediatrics . (2010) 164:901–6. doi: 10.1001/archpediatrics.2010.159

12. Mccauley C. Video game play and anxiety during late adolescence: the moderating effects of gender and social context. J Affect Disord. (2018) 226:216–9. doi: 10.1016/j.jad.2017.10.009

13. Liu L, Yao YW, Li CR, Zhang JT, Xia CC, Lan JT. The comorbidity between internet gaming disorder and depression: interrelationship and neural mechanisms. Front Psychiatry. (2018) 9:154. doi: 10.3389/fpsyt.2018.00154

14. Wu AM, Chen JH, Tong KK, Yu S, Lau JT. Prevalence and associated factors of Internet gaming disorder among community dwelling adults in Macao, China. J Behav Addict. (2018) 7:62–9. doi: 10.1556/2006.7.2018.12

15. King DL, Delfabbro PH, King DL. The cognitive psychopathology of Internet gaming disorder in adolescence. J Abnormal Child Psychol. (2016) 44:1635–45. doi: 10.1007/s10802-016-0135-y

16. Blazer D. Loneliness: a source book of current theory, research and therapy. J Behav Ther Exp Psychiatry. (1983) 14:281. doi: 10.1016/0005-7916(83)90066-6

CrossRef Full Text

17. Spilkova J, Chomynova P, Csemy L. Predictors of excessive use of social media and excessive online gaming in Czech teenagers. J Behav Addict. (2017) 6:611–9. doi: 10.1556/2006.6.2017.064

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

19. Lemmens JS, Valkenburg PM, Peter J. Development and validation of a game addiction scale for adolescents. Media Psychol. (2012) 12:77–95. doi: 10.1080/15213260802669458

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

21. Maldonado L, Huang Y, Chen R, Kasen S, Cohen P, Chen H. Impact of early adolescent anxiety disorders on self-esteem development from adolescence to young adulthood. J Adolesc Health. (2013) 53:287–92. doi: 10.1016/j.jadohealth.2013.02.025

22. Merikangas KR, He J, Burstein M, Swanson SA, Avenevoli S, Cui L, et al. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry . 49:980–9. doi: 10.1016/j.jaac.2010.05.017

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

24. Lo S, Wang C, Fang W. Physical interpersonal relationship and social anxiety among online game players. Cyber Psychol Behav. (2005) 8:15–20. doi: 10.1089/cpb.2005.8.15

25. Duven E, Beutel ME, Wolfling KJ. (2013). The neuroscience of internet and computer game addiction—what do we know about what is going on inside our patients brains? Eur Psychiatry. 28:818. doi: 10.1016/S0924-9338(13)75997-2

26. Yen C, Chou W, Liu T. The association of Internet addiction symptoms with anxiety, depression and self-esteem among adolescents with attention-deficit/hyperactivity disorder. Compr Psychiatry. (2014) 55:1601–8. doi: 10.1016/j.comppsych.2014.05.025

27. Shi X, Wang J, Zou H. Family functioning and Internet addiction among Chinese adolescents: the mediating roles of self-esteem and loneliness. Computers Human Behav. (2017) 76:201–10. doi: 10.1016/j.chb.2017.07.028

28. Beranuy M, Oberst U, Carbonell X, Chamarro A. Problematic Internet and mobile phone use and clinical symptoms in college students: the role of emotional intelligence. Computers Human Behav. (2009) 25:1182–7. doi: 10.1016/j.chb.2009.03.001

29. Sheng J-R, Wang J-L. Development and psychometric properties of the problematic mobile video gaming scale. Curr Psyol. (2019) 20191–11. doi: 10.1007/s12144-019-00415-6

30. Derogatis LR, Melisaratos N. The brief symptom inventory: an introductory report. Psychol Med. (1983) 13:595–605. doi: 10.1017/S0033291700048017

31. Li X, Zou H, Liu Y. Psychometric evaluation of loneliness scale in Chinese middle school students. Chin J Clin Psychol. (2014) 22:731–60. doi: 10.16128/j.cnki.1005-3611.2014.04.037

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

33. Snedecor GW, Cochran WG. Statistical Methods, 8th ed. Ames, IA: Iowa State University Press (1989).

34. Lim TS, Loh WY. A comparison of tests of equality of variances. Comput Stat Data Anal. (1996) 22:287–301. doi: 10.1016/0167-9473(95)00054-2

35. George D, Mallery P. SPSS for Windows Step by Step: A Simple Guide and Reference, 11.0 Update, 4th ed. Boston: Allyn & Bacon (2003).

36. Johnson RA, Wichern DW. Applied Multivariate Statistical Analysis, 5th ed. Englewood Cliffs, NJ: Prentice Hall (2006).

37. Harris J, Hagger MS. Do basic psychological needs moderate relationships within the theory of planned behavior? J Appl Biobehav Res. (2007) 12:43–64. doi: 10.1111/j.1751-9861.2007.00013.x

38. Saxton T, Dollinger M. Target reputation and appropriability: picking and deploying resources in acquisitions. J Manag. (2004) 30:123–47. doi: 10.1016/j.jm.2003.01.006

39. Wu ML. Structural Equation Modeling: The Operation and Application of AMOS. Chongqing: Chongqing University Press (2009).

40. Bruchas MR, Schindler AG, Shankar H, Messinger DI, Miyatake M, Land BB, et al. Selective p38 a MAPK deletion in serotonergic neurons produces stress resilience in models of depression and addiction. Neuron. (2011) 71:498–511. doi: 10.1016/j.neuron.2011.06.011

41. Whang LS, Ph D, Lee S, Ph D, Chang G. Internet over-users' psychological profiles: a behavior sampling analysis on internet addiction. Cyber Psychol Behav. (2003) 6:143–51. doi: 10.1089/109493103321640338

42. Yen J, Ko C, Yen C, Chen S. Psychiatric symptoms in adolescents with Internet addiction : comparison with substance use. Psychiatry Clin Neurosci. (2008) 62:9–16. doi: 10.1111/j.1440-1819.2007.01770.x

43. Kraut R, Patterson M, Lundmark V. Internet paradox: a social technology that reduces social involvement and psychological well-being? Am Psychol. (1998) 53:1017–31. doi: 10.1037//0003-066X.53.9.1017

44. Wang J-L, Jackson LA, Zhang D-J. The mediator role of self-disclosure and moderator roles of gender and social anxiety in the relationship between Chinese adolescents' online communication and their real-world social relationships. Computers Human Behav. (2011) 27:2161–8. doi: 10.1016/j.chb.2011.06.010

45. Schouten AP, Valkenburg PM, Peter J. Precursors and underlying processes of adolescents' online self-disclosure: developing and testing an “internet-attribute-perception” model. Media Psychol. (2007) 10:292–315. doi: 10.1080/15213260701375686

46. Caplan SE. Relations Among Loneliness, Social Anxiety, and Problematic Internet Use. Cyber Psychol Behav. (2007) 10:234–42. doi: 10.1089/cpb.2006.9963

Keywords: mobile game addiction, social anxiety, depression, loneliness, adolescents

Citation: Wang J-L, Sheng J-R and Wang H-Z (2019) The Association Between Mobile Game Addiction and Depression, Social Anxiety, and Loneliness. Front. Public Health 7:247. doi: 10.3389/fpubh.2019.00247

Received: 04 June 2019; Accepted: 16 August 2019; Published: 06 September 2019.

Reviewed by:

Copyright © 2019 Wang, Sheng and Wang. 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: Jin-Liang Wang, wjl200789@163.com

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.

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Effects Of Online Games in Academic Performance Among Senior High School

RODICA, PAULINE DENISE V. AND TALANIA, HANES ANDREW Department of Science, Technology, Engineering and Mathematics, Mount Carmel School of Maria Aurora (MCSMA), Silvestre Street Brgy. 2, Maria Aurora, Aurora, zip code 3202, in the school year 2019-2020. “EFFECTS OF ONLINE GAMES IN ACADEMIC PERFORMANCE AMONG SENIOR HIGH SCHOOL (SHS) STUDENTSOF MOUNT CARMEL SCHOOL OF MARIA AURORA.” The study dealt with the Effects of Online Games in Academic Performance among Senior High School (SHS) Students of Mount Carmel School of Maria Aurora. This aimed to determine the effects of online games among SHS in MCSMA. There were one hundred fifty + one (151) respondents which are composed of males and females from Academic Tracks which are Accountancy, Business and Management strand (ABM), General Academic strand (GAS), Humanities and Social Sciences strand (HUMSS). The study was laid out in descriptive design where researcher formulated questionnaire through Likert Scale. By collecting answers received from the surveys given out to the respondents, each criteria was tallied and was divided to the total number of tallies of all criteria; then, the quotient was converted to a percentage by multiplying it to 100. The parameters used to evaluate the result were the effects of online games among SHS in MCSMA. The result of the study showed that online game have negative effect to academic performance of Senior High School students of MCSMA. Study revealed that online gaming has a huge impact among them regarding on their academic performance which lead them to poor or low grade and physical distress as well. Majority of the respondents are replied and favored that online games gave negative outcome to their study and health. They found out that the students cannot focus on their studies, they cannot do their home works as well as their projects and that they have low grades. Based on the general result, the researchers conclude that a number of students playing online games could have a negative effect in their academic performance. Furthermore, students, teachers, and parents must be aware of the effects of playing online games and should regulate the time playing such game because it could ruin every students focus on their study. Students should be disciplined when it comes to playing online games which they could still perform satisfactorily in their studies and it should not be given much priority over higher and more realistic priorities.

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The objective of this research was to findout the effect of online gaming habits on student,s learning outcomes in class X of social sciences in economics subject at SMA Negeri 1 Tapa, Bone Bolango Regency, It employed a quantitative method with a sample of 66 students. At the sama time, the data analysis used in this research was a simple linear regression analysis assisted by IBM Statistics SPSS 26.0 program. The research findings signified that the variable of online gaming habits partially had a negatif and significant effect on students’ learning outcomes in class X of social Sciences at SMA Negeri 1 Tapa, the results of this research obtainet a coefficient of determination (R2) of 0.169, meaning that the effect of online gaming habbits variabel on students’ learning outcomes at SMA Negeri 1 Tapa was 16.9%. in contrast, the remaining 83.1% was affected by other variables that contribute to students’ learning outcomes at SMA Negeri 1 Tapa, which were not examinet in this research.

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Dr. Rose Wyatt

This study determined the effect of computer games on the academic performance of grade six pupils in selected catholic schools in Davao City during the school year 2012-2013. This research was initiated to identify the game type most suitable to our teaching environment and to identify game elements that students found interesting or useful within the different game types. This study looked into the following: (1) the profile of the pupil-respondents in terms of (1) Pupils’ Profile: (1.1) gender; (1.2) parental monitoring; (1.3) type of computer games; (1.4) number of hours spent in playing on the computer; (1.5) game systems used. (2) Behavioral Factors: (2.1) pupils’ attitudes towards computer games; (2.2) study habits; (2.3) teachers’ perceptions about the pupils’ behaviour. (2) the academic performance of the pupils in terms of the following subjects: (2.1) English, Science and Mathematics. (3) the significant relationship between the academic performance of the pupil-respondents and the hours spent in playing computer games? The descriptive research design was employed in the study with the questionnaire as the instrument. The study made use of purposive sampling on the pupil-respondents and parent-respondents and random sampling in the selection of the teacher- respondents. The respondents were selected from three catholic schools namely: Ateneo de Davao University presently located in Matina, Davao City, Our Lady of Fatima Academy situated at Fatima St., Davao City and Assumption College of Davao in Cabagiuo St.,Davao City. The respondents were twenty-seven (27) teachers, and 218 pupils along with their parents. The analytical design was used in this study including the testing of the null hypothesis were the central tendency to utilize in the descriptive part of the analysis of data. Pearson-Product Moment of Correlation was used to test the reliability of the research instrument. Analysis of Variance was used to measure the significant difference between the academic performance of the pupils and the hours spent in playing computer games. On Respondents’ Profile, out of 218 pupil-respondents, there were 112 boys or (51.4 percent) and 106 girls or (48.6 percent). There were more boys than girls-respondents. On the other hand, on parental monitoring, out of ten indicators, five were rated agree. The parents want to monitor and guide their children because they know the positive and negative effects of playing computer games. This further revealed that pupils who are supported very well by their parents perform well in their studies. However, four of the indicators were rated disagree by the parents. The pupils strongly agree that playing computer games is for fun because they enjoy them. Whereas at school they are required to study many subjects that are boring to them. Playing computer games is actually an escape from the rigid rules and regulations they must follow at school. On the types of computer games played by the pupil-respondents, children answered with a multiple response. The majority of the respondents played action/fighting games. Second, are the online gaming sites followed by adventure & RPG Games, puzzle games, simulation, social networking sites and the last is the card games. The average of hours that the pupil-respondents played is three to four (3-4) hours in a day. Pupils have multiple responses about the game systems they used in playing computer games. Most of the respondents used the PC game system which was followed in use by the portable , table/phone and console game system. Pupils rated agree on the indicators that interactive games improve their logical thinking and reasoning; help them to become more computer literate; and creative; keep from getting bored until their friends are available to play and make new friends as well as strengthening their relationships with old friends. The pupils think that playing computer games is a positive experience to them and not a negative experience like their teachers, parents and other role models seem to believe. On study habits, the majority of the pupils studied their lessons on an average of 0-1 hour a day. On teachers’ perception on pupils’ behavior, the teacher-respondents agreed that playing computer manifests better computer skills and knowledge of facts, exhibits motor skills and hand-eye coordination and gain other skills, enhances creativity and inculcates a taste for graphics, and design and technology. However, it also manifests aggressive behaviors such as gets in many fights, cruelty, bullying, or meanness to others, doesn’t seem to feel guilty after misbehaving; develops attention problems like daydreaming (getting lost in thought and staring blankly); exhibits a decline in school achievements(repeated low grade, poor school work). On academic performance by subject, the pupil-respondents generally received a fair (80-84) to good (85-89) rating. Thus, their rating means that playing computer games do not have significant effect on their academic performance. However, there is an impact on their behaviour based on various researches. It was noted that English and Mathematics have no significant difference in the academic performance of the pupil-respondents in relation to hours spent in playing computer games. The result showed that thirty-seven percent explains the variation of the pupils’ academic performance which is due to playing computer games while sixty-three percent went to other factors that affect their performance in school. However, Science subjects showed significance on their academic performance. Perhaps, this subject requires a higher level of thinking skills. Some factors can be considered why these pupils did not perform in the said subject due to pupils’ study habits, attitudes towards the subject, thinking skills, peer and media influences. From the results and conclusions, it is recommended that the policy maker and school administrators will intensify the integration of Information Technology in the existing curriculum, improve lesson plan making using the computer –aided instructions (CAI) and provide more trainings/ seminars/ workshops/ to teachers that will equip them with IT skills. Lastly, design a Homeroom Guidance (HG) Activity on the effect of playing of computer games in their life.

Psychology and Education: A Multidisciplinary Journal

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In modern society, computers have become almost a non-negotiable part of every individual's life. Then this is bound to have both positive and negative consequences on people. Because of this many young children and individuals anywhere can become addicted to playing such games online and offline gaming. It became a huge distraction to the academic performance of the learners by being addicted to computer games. The main goal of this study was to determine the level of understanding on playing in computer games and academic performance of learners in Sultan Palao Ali Memorial Elementary School, SPAMES (127217), Tagoloan District, Division of Lanao del Norte. The study used descriptive-correlational research design. Descriptive research determined the profile of elementary learners of Sultan Palao Ali Elementary School located at Barangay Inagonan, Tagoloan Lanao, Del Norte and the level of understanding on playing in computer games and the academic performance of the respondents. Based on the results of the study, most of the learners at Sultan Palao Ali Elementary School, Tagoloan District, Division of Lanao del Norte, were age ranges from 11-13, females and in satisfactory level as to their academic performance. In the level of understanding of playing computer games of the respondents, among the indicators of the level of understanding, the indicator "Playing computer games can enhance the accuracy/speed of my hands), got the highest mean score which can also be interpreted in the agreed level, while the indicator "Playing computer games can increase my empathy and supports my mental well-being) garnered the lowest mean of 1.80, which can be interpreted in the disagreed level in which the respondents believed that playing computer games negatively impacted their health. Further, in correlation, the null hypothesis, which states that there is no significant relationship between academic performance and profile in terms of age, was not rejected, while sex was rejected. At the same time, the null hypothesis, which states that there is no significant relationship between academic performance and the level of understanding of playing computer games, was also rejected. Furthermore, in the regression analysis, the null hypothesis stating that "there is no variable/s best predict the academic performance" was rejected.

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The Play Store saw many critically acclaimed games arrive on Android devices in May 2024, from retro creations like Sonic Mania Plus to newer hits like Katana Zero. However, we saw a new and exciting puzzle game, Paper Trails, a must-play for anyone with one of the top Android tablets .

Many of the games released this month are Netflix exclusives, so you'll need a Netflix account to play. If you're unsure whether a subscription is worth it, check out our roundup of the best games in the Netflix Games library .

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1 paper trail, tactile and clever puzzle adventure, paper trail.

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