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. 2022 Aug 8;11(3):796-819.
doi: 10.1556/2006.2022.00048. Print 2022 Sep 26.

A comprehensive model to understand and assess the motivational background of video game use: The Gaming Motivation Inventory (GMI)

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A comprehensive model to understand and assess the motivational background of video game use: The Gaming Motivation Inventory (GMI)

Orsolya Király et al. J Behav Addict. .

Abstract

Background and aims: The popularity of video gaming has generated significant interest in research methods to examine motivations for gaming. Current measures of gaming motives are limited by lack of scope and/or their applicability to specific game genres only. We aimed to create a comprehensive motivation inventory applicable to any gaming genre and to evaluate its psychometric properties in a large sample of highly engaged video gamers.

Methods: Stage 1 of this project involved a systematic review that generated the items for the Gaming Motivation Inventory (GMI). Stages 2-4 involved an evaluation of the psychometric properties of the GMI. A sample of 14,740 video gamers (89.3% male; mean age 24.1 years) were recruited via an online survey promoted by a popular gaming magazine.

Results: In Stage 2, twenty-six gaming motives were identified, which clustered into six higher-order dimensions (Mastery, Immersion/Escapism, Competition, Stimulation, Social, Habit/Boredom). In Stage 3, construct validity of the six higher-order motives was assessed by associations with gaming-related, personality, and psychological variables. In Stage 4, the relationships between motives and depression symptoms and gaming disorder symptoms were explored. Although gaming motives had weak associations with gaming genres, they were moderately related to variables such as competitiveness, sociability, and positive and negative affect. Gaming disorder symptoms were directly predicted by depression symptoms and indirectly via Immersion/Escapism, Habit/Boredom, and Competition motives.

Discussion and conclusions: These findings support the notion that motives are one of the primary causes of gaming behavior and play an important role in predicting its problematic nature. The GMI is a psychometrically valid tool that will be useful for gaining insights into factors underlying gaming behaviors.

Keywords: addictive; behavior; gaming disorder; motivation; psychometrics; surveys and questionnaires; video games.

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Figures

Fig. 1.
Fig. 1.
Gaming motivation scores compared across the seven most popular gaming genres in the study sample Note. 95% confidence intervals are presented on the bar charts. FPS = first-person shooter; MOBA = multiplayer online battle arena; RPG = role-playing game; MMORPG = massively multiplayer online role-playing game. FPS group (n = 5,307); Battle Royale group (n = 1,835); MOBA group (n = 1,434); Action-adventure group (n = 3,463); RPG group (n = 2,456); MMORPG group (n = 978); Sport group (n = 1,739). The summarized sample size of the seven groups exceeds the total sample size because groups partially overlap
Fig. 2.
Fig. 2.
Mediation model between depression symptoms and gaming disorder symptom severity and gaming time (N = 14,740) Note. Values on single-headed arrows are standardized regression coefficients (β). The value on the double-headed arrow represents a correlation coefficient. Due to the large sample size, only *P < 0.001 was considered as a significant effect. Solid lines represent significant standardized regression coefficients. Dashed lines represent non-significant standardized regression coefficients. Bold letters represent considerable standardized regression coefficients (β > 0.1). Gaming disorder symptoms were calculated by summarizing the dichotomized Ten-Item Internet Gaming Disorder Test items, except for Item 8 (i.e., escaping or relieving a negative mood). We removed Item 8 because its content conceptually overlapped with the higher-order motive Immersion/Escapism, which could have biased the results. The model was controlled for age and gender. However, to ease the interpretation of the figure, correlation coefficients between the latent variables and the covariate effects of gender and age are not shown (see Supplemental Table S10 in the online supplemental materials)

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