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An exploratory study of the association between online gaming addiction and enjoyment motivations for playing massively multiplayer online role-playing games

Authors :
Hussain, Z
Williams, GA
Griffiths, MD
Source :
Computers in Human Behavior. 50:221-230
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

Latent Class Analysis revealed seven classes of motivations for playing MMORPGs.Five classes of gaming addiction-related experiences were extracted.Three classes of motivations for playing were linked to higher risk of addiction. Massively multiplayer online role-playing games (MMORPGs) are a popular form of entertainment used by millions of gamers worldwide. Potential problems relating to MMORPG play have emerged, particularly in relation to being addicted to playing in such virtual environments. In the present study, factors relating to online gaming addiction and motivations for playing in MMORPGs were examined to establish whether they were associated with addiction. A sample comprised 1167 gamers who were surveyed about their gaming motivations. Latent Class Analysis revealed seven classes of motivations for playing MMORPGs, which comprised: (1) novelty; (2) highly social and discovery-orientated; (3) aggressive, anti-social and non-curious; (4) highly social, competitive; (5) low intensity enjoyment; (6) discovery-orientated; and (7) social classes. Five classes of gaming addiction-related experiences were extracted including: (1) high risk of addiction, (2) time-affected, (3) intermediate risk of addiction, (4) emotional control, and (5) low risk of addiction classes. Gender was a significant predictor of intermediate risk of addiction and emotional control class membership. Membership of the high risk of addiction class was significantly predicted by belonging to a highly social and competitive class, a novelty class, or an aggressive, anti-social, and non-curious class. Implications of these findings for assessment and treatment of MMORPG addiction are discussed.

Details

ISSN :
07475632
Volume :
50
Database :
OpenAIRE
Journal :
Computers in Human Behavior
Accession number :
edsair.doi.dedup.....03ebc95186fe0f90a4b52e4733a23b22
Full Text :
https://doi.org/10.1016/j.chb.2015.03.075