Internet Gaming Disorder: the interplay between physical activity and user–avatar relationship

ABSTRACT

Understanding both the risk and protective factors associated with Internet Gaming Disorder (IGD) has been viewed by many in the gaming studies field as an area of research priority. The present study focused on the potential risk and protective effects of user–avatar (game figure) relationship and physical activity (PA), respectively. To address these aims, a cross-sectional and a longitudinal mixed-methods design were combined (comprising both psychological and physiological assessments). A sample of 121 emerging adult gamers (18–29 years) residing in Australia, who played massively multiplayer online games, were assessed in relation to their IGD behaviours using the nine-item Internet Gaming Disorder Scale – Short Form. Additionally, the Proto-Self-Presence (PSP) scale was used to evaluate the extent to which gamers identified with the body of their avatar. Finally, a PA monitor (Fitbit Flex) measured levels of energy consumed during real-world daily activities (active minutes). A number of linear regressions and moderation analyses were conducted. Findings confirmed that PSP functioned as an IGD risk factor and that PA acted protectively, weakening the association between PSP and IGD behaviours. Implications of these findings are discussed in relation to IGD treatment and gaming development aspects.

KEYWORDS:

• Internet Gaming Disorder
• Proto-Self-Presence
• physical activity
• emerging adulthood
• massively multiplayer online games

Summary points

• Gamers, who experience higher levels of identification with the body of their avatars, tend to present with higher levels of Internet Gaming Disorder behaviors

• Internet Gaming Disorder behaviors exhibited by gamers with higher levels of identification with their avatars tends to be lower the more physiologically active they are in real life.

• Future research should investigate the longitudinal interplay between individual and gaming related factors considering the development of Internet Gaming Disorder behaviors.

• Future research would need to increase the length of longitudinal observations considering Internet Gaming Disorder risk factor related effects.

Acknowledgements

LL and VS contributed to the data collection and analyses. MG contributed to the literature review and hypotheses formulation. BA and TT contributed to the structure and sequence of theoretical arguments and hypothesis formulation. All authors contributed to the writing of the paper.

Informed consent: Informed consent was obtained from all the parents and the guardians of the adolescents participating in the study, as well as the individual participants themselves.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Vasilis Stavropoulos http://orcid.org/0000-0003-3851-4624

Notes

1. The present study is part of a wider project of Federation University Australia that addresses the interplay between individual, Internet, and proximal context factors in the development of Internet Gaming Disorder symptoms among emerging adults. Instruments used in the data include the: (1) Internet Gaming Disorder – Short Form 9 (Pontes and Griffiths 2015); (2) Beck Depression Inventory – 2nd edition (21 items) (Beck, Steer, and Brown 1996); (3) Beck Anxiety Inventory (21 items) (Beck and Steer 1990); (4) Hikikomori-Social Withdrawal Scale (5 items) (Teo et al. 2015); (5) Attention Deficit Hyperactivity Self-Report Scale (18 items) (Kessler et al. 2005); (6); Ten Item Personality Inventory (Gosling, Rentfrow, and Swann 2003); (7) The Balanced Family Cohesion Scale (7 items) (Olson 2000); (8) Presence Questionnaire (10 items) (Faiola et al. 2013); (9) Online Flow Questionnaire (5 items) (Chen, Wigand, and Nilan 2000); (10) Self-Presence Questionnaire (Ratan and Hasler 2010); (11) The Gaming-Contingent Self-Worth Scale (12 items) (Beard, and Wickham 2016) and; (12) Demographic and Internet Use Questions. The battery of questionnaires was utilized for both online and face-to-face data collection. The use of the fitness tracker (FBF) was used only for face-to-face data collection. It is noted that different parts of the present data have been used in two more published studies to address different research questions/hypotheses (Adams et al. 2018; Burleigh et al. 2017).

2. Statistical power was computed separately for the cross-sectional and the longitudinal sample. A probability error of 0.05, power (1 − β error probability) of 0.95 and effect size of 0.15 was used for the cross-sectional sample (N = 125) resulting to an observed statistical power of Powerα − β = 0.99 (F₍₁₂₂₎ = 3.92, λ = 18.75). A probability error of 0.05, power (1 − β error probability) of 0.95 and effect size of 0.25 was used for the longitudinal sample (N = 61) resulting to an observed statistical power of Powerα − β = 0.73 (α_{error probability} = 0.27, β_{error probability} = 0.27, F_(2,61) = 1.34, Pilai V = 0.06, λ = 3.81).

3. In line with the approval received by the ethics committee of Federation University, the flyers: (a) indicated that participants were required to participate on three separate measurement occasions approximately one month apart; (b) included an email address to contact the investigators; and (c) clearly described the process and stages of the data collection (face-to-face and online). MMO players, aged between 18 and 29 years old, interested in the study received the Plain Language Information Statement (PLIS). The PLIS clearly indicated that participation was voluntary and that participants could independently decide to withdraw from the study at any point. Individuals who choose to participate were required to provide informed consent.