Versatility and Addiction in Gaming: The Number of Video-Game Genres Played Is Associated with Pathological Gaming in Male Adolescents

Abstract

This study tested the predictive power of gaming versatility (i.e., the number of video game genres engaged in) on game addiction in male adolescents, controlling for time spent on gaming. Participants were 701 male adolescents attending high school (M_age=15.6 years). Analyses showed that pathological gaming was predicted not only by higher time spent on gaming, but also by participation in a greater number of video game genres. Specifically, the wider the array of video game genres played, the higher were the negative consequences caused by gaming. Findings show that versatility can be considered as one of the behavioral risk factors related to gaming addiction, which may be characterized by a composite and diversified experience with video games. This study suggests that educational efforts designed to prevent gaming addiction among youth may also be focused on adolescents' engagement in different video games.

Introduction

At the beginning of the 21st century, video game playing has become a very popular pastime for adolescents, who appear to be more likely to show signs of pathological gaming than any other age group.^1,2 Pathological gaming has been defined by scholars as an excessive involvement with video games characterized by symptoms such as withdrawal, loss of control, and conflicts.^3,4 Specifically, while excessive involvement is not necessarily pathological, excessive gaming is accompanied by social and emotional problems and by the inability to control excessive gaming in pathological gaming.⁵

Among the behavioral risk factors associated with pathological gaming in adolescents, a number of studies have shown that time spent playing video games is positively and strongly correlated with pathological gaming. Specifically, the higher the frequency and the duration of play, the higher is the level of pathological gaming.^5–11 However, to the best of the authors' knowledge, no study has until now analyzed if the number of different video game genres¹² that are practiced could be related to pathological gaming. Indeed, although frequency and time spent by adolescents in a wide diversity and array of video game genres—including sports (e.g., FIFA Soccer), racing (e.g., NASCAR), puzzles (e.g., Tetris), art (e.g., Printshop), building model worlds (e.g., Sims), quiz (e.g., Outburst), action (e.g., Call of Duty), and fighting (e.g., Mortal Kombat)—have been analyzed,^13,14 the relationship between personal involvement in various video game genres and pathological gaming has not yet been investigated.

From the gambling literature, it is known that the “composite measure attesting the number of different activities that were practiced,” defined as versatility,¹⁵ is positively associated with the degree of problem gambling.^16–19 Considering adolescents in particular, it has been suggested that gambling activity count was positively correlated with problem gambling severity in gamblers.¹⁹ Consistent with this result, Welte et al.¹⁸ found that both high gambling frequency and high gambling versatility were associated with elevated problem gambling in youth who gamble. Given the existing similarities between gaming and gambling found in various psychological and behavioral risk factors,²⁰ it could be interesting to explore if versatility in gaming—that is, the number of video game genres played—is related to pathological gaming.

Following the above-cited premises about the relationship between the number of different activities engaged in and pathological behavior in gambling among adolescents,^18,19 the aim of this study was to examine whether gaming versatility had a predictive power on pathological gaming, controlling for time spent on gaming. Specifically, it was hypothesized that a greater level of pathological gaming would be predicted not only by increased time spent on gaming, but also by the participation in a greater number of video game genres.

Method

Participants

Participants included 701 male adolescents (M_age=15.6 years, SD=0.96 years, range 13–18 years) who attended high school in Tuscany, Italy. In line with past works,^7,21 only boys were recruited, since research has shown that male adolescents are more likely to play video games excessively and are more prone to experience negative consequences because of their gaming behavior.^6,22

Written informed assent was provided by students, or by the parents if the student was a minor.

Measures and procedure

To measure time spent on gaming, in line with previous studies,^5,7,8,23 participants were asked to indicate the number of days per week and the number of hours per day they spent on playing video games in the last 6 months. Following Lemmens et al.,⁵ overall time spent on gaming was calculated by multiplying the days per week by the number of hours per day spent on gaming.

To assess gaming versatility, a list of the most widespread genres of video games at that time, including 14 gaming genres, was created. The categorization of the genres was derived from examples cited in the literature^13,14,24,25 and by examining the online Web sites Steam and Wikipedia.^26,27 The genres included the following: management games, browser games, first-person shooters, real time strategy games, role playing games, action games, simulation games, massively multiplayer online (MMO) games, fighting games, arcade/platform games, retro games, Indie games, sport games, and casual games. To avoid double dipping, examples of video games were provided for each genre (see Table 1). Referring to the last 6 months, participants were asked to indicate if they had played each of the listed genres using a dichotomous format (yes or no). A gaming versatility score was calculated by summing the number of video game genres played.

Table 1.

Participants Engaging in Each Video Game Genre

Video game genres	%
Management (e.g., The Sims, Sim City)	51
Browser (e.g., Farmville, Marvel's Avengers)	42
First person shooters (e.g., Call of Duty, Far Cry, Crysis)	83
Real time strategy (e.g., Starcraft, Total War)	32
Role playing (e.g., Mass Effect, Dragon Age, The Elder Scrolls)	44
Action (e.g., Assassin's Creed, Diablo, Borderlands, GTA)	88
Simulation (e.g., Colin McRae, Euro Truck Simulator, F1)	46
Massively multiplayer online (e.g., World of Warcraft, Guild Wars, Planetside)	27
Fighting (e.g., Street Fighter, Tekken)	57
Arcade/platform (e.g., NFS, Super Mario, Mario Kart, Cat Mario)	82
Retro (e.g., Legend of Grimrock, Final Fantasy, MAME)	30
Indie (e.g., Minecraft, Chivalry: Medieval Warfare)	46
Sports (e.g., FIFA, PES)	84
Casual (e.g., Ruzzle, Angry Birds, Candy Crush)	86

Pathological gaming was measured through the 7-item Game Addiction Scale for adolescents.⁵ An example item was “Have you neglected other important activities (e.g., school or work) to play games?” Items were preceded by the statement: “During the last 6 months, how often…,” and they were rated on a 5-point scale where 1=“never,” 2=“rarely,” 3=“sometimes,” 4=“often,” and 5=“very often.” For this study, the Italian version of the scale was used. In a previous unpublished study conducted with a large sample of Italian adolescents,²⁸ evidence was provided that it was psychometrically equivalent to the original scale. Specifically, the scale was found to be unidimensional and characterized by adequate reliability. A total score was calculated by summing responses to each item, so that higher scores represented high levels of pathological gaming.

The scales were administered in the classroom in a paper and pencil format following the order of description. Students were required to work individually.

Results

The results indicated that 99% of participants have played at least one video game genre in the last 6 months. As shown in Table 1, the most common activities were action (88%), casual (86%), and sports (84%) games, while MMO (27%), retro games (30%), and real time strategy (32%) games were the less practiced.

As shown in Table 2, time spent on gaming and gaming versatility were both significantly and positively correlated with pathological gaming. The results also found that time spent on gaming was significantly and positively correlated with gaming versatility. Age did not show any significant correlation with the other variables.

Table 2.

Intercorrelations Among Independent Variables (TSG and GV), Outcome (PG), and Age

	1	2	3	4
1. PG	—
2. TSG	0.35^**	—
3. GV	0.21^**	0.25^**	—
4. Age	−0.06	0.03	−0.07	—
M	10.25	7.97	12.79	15.60
SD	10.56	2.96	4.67	0.96

p<0.001.

PG, pathological gaming; TSG, time spent on gaming; GV, gaming versatility.

To test the effect of gaming versatility on pathological gaming, controlling for time spent on video games, a stepwise multivariate regression was conducted. Given nonsignificant correlations with the other variables, age was not taken into account. As shown in Table 3, time spent on gaming was entered into the regression in step 1, and it accounted for 12% of variance (R²_Adj=0.12, p<0.001) of pathological gaming. In the next step, gaming versatility was added to the model, and the introduction of this variable explained an additional 2% (ΔR²=0.02) of the variance. This increase in the amount of variance explained was statistically significant (p<0.001). In model 2, both time spent on gaming (β=0.32) and gaming versatility (β=0.13) had a significant predictive power on pathological gaming (p<0.001).

Table 3.

Stepwise Regression Analysis with Pathological Gaming as Outcome and Predictors: Time Spent on Gaming (Model 1), Time Spent on Gaming and Gaming Versatility (Model 2)

Model	Predictors	B	β	t	p
Model 1^*	Time spent on gaming	0.16	0.35	9.69	<0.001
Model 2^**	Time spent on gaming	0.14	0.32	8.59	<0.001
	Gaming versatility	0.21	0.13	3.57	<0.001

F(1, 663)=93.83, p<0.001.

F(2, 662)=54.11, p<0.001.

Discussion

Although previous research has considered the link between time spent on playing video games and pathological gaming in adolescents,^5–11 to date, no study had examined whether the number of video game genres played had an independent predictive power on pathological gaming. Investigating gaming versatility among adolescents—that is, the sum of video game genres that adolescents had played—for the first time, this paper expands current knowledge about the behavioral risk factors for gaming addiction.

First, a small correlation was found between time spent on playing video games and gaming versatility, suggesting that they are related aspects, but at the same time they are not largely coincident. This result provided evidence that it makes sense to investigate their independent influence of on gaming addiction. After that, the regression analysis attested that time spent on gaming was linked to pathological gaming, but there was also an effect on pathological gaming uniquely attributable to the amount of video game genres practiced.

Findings essentially imply that adolescents are at risk of developing gaming-related addiction symptoms not only if they spend many hours on videogames, but also if they are involved in a wide series of video game genres. Showing the predictive role of versatility, versatility in playing video games could have a role in leading to negative consequences associated with gaming habits. Indeed, this study evidences that gaming addiction may also be characterized by a composite and diversified experience with games and not only by a continued and uncontrolled use of a specific game. Thus, versatility can be considered as one of the behavioral risk factors related to gaming experience.

From an educational perspective, these results indicate that interventions designed to prevent pathological gaming among youth should focus not only on educating adolescents about the risks associated with great amounts of time spent on gaming, but also about the importance of paying attention to engagement in different video games. In fact, this is an important aspect of gaming habits, which may play a role in leading adolescents to develop addictive behaviors related to gaming. Both time and versatility may also be addressed in interventions aimed at favoring effective educational practices for parents in order to monitor adolescents' participation in video games.

Other implications of this study involve the relationship between adolescent gaming habits and the gaming market, in which new forms of games generally proliferate very quickly. From the results of this study, it could be hypothesized that the quick and continual development of new video game genres could be related to the development of versatility in gaming in younger players.

Some limitations of this study should be noted. First, as with all self-report questionnaire-based studies, these findings may have been affected by response bias (such as acquiescence or social desirability), and by how confident participants were that their answers would be kept confidential. Also, the findings are limited to male adolescents. Future studies should explore the role of gaming versatility on pathological gaming in females and with both younger and older youths. Future research is also needed to address some issues related to gaming versatility. Specifically, it could be interesting to take into account the concept of versatility, that is, the different platforms used to play games (computer, consoles, mobile phone, tablet, etc.). In fact, different platforms allow for different video game genres. Thus, it could be analyzed if playing on different platforms contributes to increase time spent on gaming and gaming versatility and, consequently, pathological gaming.

In spite of these limitations, the current study contributes to the literature by exploring the concept of versatility in gaming, and it provides evidence of its relationship to pathological gaming in adolescence.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

References

Griffiths

, Davies

, Chappell

. Demographic factors and playing variables in online computer gaming. Cyberpsychology & Behavior, 2004; 7:479–487.

, Kim

, Bae

, et al. Depression and Internet addiction in adolescents. Psychopathology, 2007; 40:424–430.

Gentile

. Pathological video game use among youth 8 to 18: a national study. Psychological Science, 2009; 20:594–602.

Grüsser

, Thalemann

, Griffiths

. Excessive computer game playing: evidence for addiction and aggression?. Cyberpsychology & Behavior, 2007; 10:290–292.

Lemmens

, Valkenburg

, Peter

. Development and validation of a game addiction scale for adolescents. Media Psychology, 2009; 12:77–95.

Charlton

, Danforth

IDW

. Distinguishing addiction in high engagement in the context of online game playing. Computer in Human Behavior, 2007; 23:1531–1548.

van Holst

, Lemmens

, Valkenburg

, et al. Attentional bias and disinhibition toward gaming cues are related to problem gaming in male adolescents. Journal of Adolescent Health, 2012; 50:541–546.

Lemmens

, Valkenburg

, Peter

. The effects of pathological gaming on aggressive behavior. Journal of Youth & Adolescence, 2011; 40:38–47.

Liu

, Peng

. Cognitive and psychosocial predictors of the negative outcomes associated with plying MMOGs (massively multiplayer online games). Computer in Human Behavior, 2009; 25:1306–1311.

10.

Salguero

RAT

, Moran

RMB

. Measuring problem video game playing in adolescents. Addiction, 2002; 97:1601–1606.

11.

Turner

, Paglia-Boak

, Ballon

. Prevalence of problematic video gaming among Ontario adolescents. International Journal of Mental Health & Addiction, 2012; 10:877–889.

12.

King

, Delfabbro

, Griffiths

. Trajectories of problem video gaming among adult regular gamers: an 18-month longitudinal study. Cyberpsychology, Behavior, & Social Networking, 2013; 16:72–76.

13.

Willoughby

, Adachi

PJC

, Good

. A longitudinal study of the association between violent video game play and aggression among adolescents. Developmental Psychology, 2012; 48:1044–1057.

14.

Adachi

PJC

, Willoughby

. Demolishing the competition: the longitudinal links between competitive video games, competitive gambling, and aggression. Journal of Youth & Adolescence, 2013; 42:1090–1104.

15.

Slutske

, Piasecki

, Blaszczynski

, et al. Pathological gambling recovery in the absence of abstinence. Addiction, 2010; 105:2169–2175.

16.

Clarke

, Clarkson

. A preliminary investigation into motivational factors associated with older adults' problem gambling. International Journal of Mental Health & Addiction, 2009; 7:12–28.

17.

McCready

, Mann

, Zhao

, et al. Correlates of gambling-related problems among older adults in Ontario. Journal of Gambling Issues, 2008; 22:174–194.

18.

Welte

, Barnes

, Tidwell

, et al. The association of form of gambling with problem gambling among American youth. Psychology of Addictive Behaviors, 2009; 23:105–112.

19.

Winters

, Stinchfield

, Fulkerson

. Toward the development of an adolescent gambling problem severity scale. Journal of Gambling Studies, 1993; 9:63–84.

20.

Wood

RTA

, Gupta

, Derevensky

, et al. Video game playing and gambling in adolescents: common risk factors. Journal of Child & Adolescence Substance Abuse, 2004; 14:77–100.

21.

Spekman

MLC

, Konijn

, Roelofsma

PHMP

, et al. Gaming addiction, definition and measurement: a large-scale empirical study. Computers in Human Behavior, 2013; 29: 2150–2155.

22.

Chiu

, Lee

, Huang

. Video game addiction in children and teenagers in Taiwan. CyberPsychology & Behavior, 2004; 7:571–581.

23.

Lemmens

, Valkenburg

, Peter

. Psychosocial causes and consequences of pathological gaming. Computer in Human Behavior, 2011; 2:144–152.

24.

Bonanno

, Kommers

PAM

. Gender differences and styles in the use of digital games. Educational Psychology: An International Journal of Experimental Educational Psychology, 2005; 25:37–41.

25.

Trepte

, Reinecke

, Juechems

. The social side of gaming: how playing online computer games creates online and offline social support. Computers in Human Behavior, 2012; 832–839.

26.

http://store.steampowered.com/ (accessed Feb. 10, 2013).

27.

http://en.wikipedia.org/wiki/Video_game_genres (accessed Feb. 10, 2013).

28.

Ammannato

. Un contributo allo studio delle proprietà psicometriche della Game Addiction Scale for Adolescents [A preliminary study on the psychometric properties of the Game Addiction Scale for Adolescents]. Unpublished thesis, University of Florence, Italy, 2013.