Literature Review
The influence of technology in the field of both gaming and gambling continues to grow at a rapid pace. The studies conducted on gaming have tended to concentrate on the negative aspects of videogames and their effects on peoples’ behaviour and lives (Griffiths, 2002). While there have been a number of studies conducted on online gaming and online gaming, none so far have looked into online gaming for monetary gain. Therefore the demographics of those who compete in online gaming for money, its effects on their behaviour and lifestyle and the addictive potential of this activity are not known.
Studies that have examined gaming online have tended to look at the demographics and playing variables associated with particular games, such as Everquest (Griffiths, Davies & Chappell, 2003). These studies have used quantitative methodologies, such as online questionnaires in order to gain their data. Research has also examined the structural characteristics of certain websites, for example, gambling websites to determine the aspects that encourage participants to play and return to these websites and the practices that are put in place to protect the vulnerable from possible problems (Smeaton & Griffiths, 2004).
The proposed study therefore intends to investigate if there is any connection between online gaming for money and online gambling (in reference to the effects these two activities have and their structural characteristics), what the demographics are of those who participate in online gaming for monetary gain and if online gaming and online gambling have the same addictive potential. This will be achieved by administering an online questionnaire, alongside a few select interviews with online gamers. The structural characteristics of a number of gaming (for money) websites will also be examined by the researcher using a set of pre-structured questions.
Do online gaming sites have the same addictive potential as online gambling sites and how do the gamers view the sites they use?
The Internet has pervaded our society rapidly and on a broad scale. It is a major means of communication, used for the exchange of information, for news and for shopping, and now ‘one of the most popular online contents is the game’ (Choi & Kim, 2004, p.11). Computer (or video) games can be defined as ‘any forms of computer-based entertainment software, either textual or image based, using any electronic platform such as personal computers or consoles and involving one or multiple players in a physical or networked environment’ (Frasca, 2001, 27).
Online gaming in this review is concentrating mainly on gaming over the Internet, where an amount of money is bet on the prospect of a player or group of players winning, i.e. ‘online gaming for money’. These types of games are usually referred to by the websites as ‘games of skill’, and include chess, backgammon and solitaires. In this sense online gaming is different to online gambling (and therefore doesn’t have to comply to the same laws) since games of skill are games where the skill of the player predominates over chance in determining the outcome of the game. Online gambling refers to activities; where a prize is awarded, it is determined on the basis of chance and where consideration is paid (Moneygaming.com, 2006).
It is only recently that research has begun to be conducted into online gaming, partly due to it being such a new enterprise. Previous research has concentrated mainly on the demographics of online gamers (people who play computer games online) (Griffiths, Davies & Chappell, 2003; Griffiths, Davies & Chappell, 2004) and the economic perspective of online gaming (Castranova, 2001).
To access scientific literature various computerised databases were searched including: EBSCOhost, Business Source Premier, Academic Search Elite, PsycINFO, PsycARTICLES, Science Direct and GoogleScholar. The key terms used to search these databases were; Online gaming, online gambling, gaming and gambling, addiction, money/monetary gain, demographics.
Online gaming has been separated by some researchers into three main types: stand alone games, local and wide network (LAWN) games and Massively multiplayer online role-playing (MMORP) games (Griffiths, et al, 2003). Stand alone games are defined as ‘single player orientated games for the PC with the option to go online to seek a human opponent’ (Griffiths, et al, 2003. p, 82). LAWN games occurred as an attempt to link players together to compete in tournaments, for example, Counterstrike. This form of gaming is now very popular and ‘LAWN parties’ are now held where thousands of individuals meet and compete (Griffiths, et al, 2003).
MMORPG games such as Everquest and Ultimate Online are large, sophisticated and evolving worlds where users are able to see and interact with each other (Brian & Wiemer-Hastings, 2005; Griffiths, et al, 2003). These games allow for a range of identities to be adopted by the player, so the character can be friendly, evil, a team player or a loner (Brian & Wiemer-Hastings, 2005). Online gaming has become progressively more prevalent over the past few years and MMORPG games, such as, Everquest are yet another type of computer game that has been shown to be addictive (Hall, 2005).
Another type of online gaming that is becoming increasing popular is the area of games of skill online, such as, chess and backgammon (Tedeschi, 2004). A relatively new business, Moneygaming.com now offers high stakes, betting and jackpots to players participating in these online ‘games of skill’. This website has a similar look to that of online casinos and is hoping to capitalise on the popularity of online poker (Carter, 2005). Many of the websites that offer gaming for money seem to concentrate mainly on ‘board games’ online. Wolf (2005) states that in relation to videogames, ‘board-games’ are games that are either similar to board games or that are an adaptation of existing board games, for example, checkers, chess or scrabble.
Online gaming has begun to provide the opportunity to gamers to compete without limitations of geographic location (Bryce & Rutter, 2005). This can allow the formation of online communities around competencies and game skills, for example, the incredible size of community that has built up around Everquest (Hall, 2005). This may be significant for female gamers, as it gives them the opportunity to compete against male opponents without the issue of gender (Bryce & Rutter, 2005). In games, such as skilled online gaming for money, studies may find an increase in female participation, due to the increase in confidence in gaming skills and abilities that can grow with anonymity (Bryce & Rutter, 2005).
It has long been suggested that gaming is a predominately male dominated activity (Provenzo, 1991) (see also studies, Griffiths et al, 2004; Gentile, Lynch, Linder & Walsh, 2004). However there is increasing literature that proposes that female players make up a significantly larger proportion of gamers than previously thought. Colwell and Payne (2000) showed that 88% of twelve to fourteen year old females questioned in their study played computer games on a regular basis and research by IDSA (2000) has suggested that female gamers actually make up the majority of online players (53%).
There appears to be slightly conflicting views and data as to the proportion of players that are male and female in gaming. Some advocate that females find videogames unappealing due to the apparent endorsement of gender stereotypes and the promotion of antisocial behaviour (Newman, 2004). However it has also been argued that female gamers have similar interests, aptitudes and preferences in regard to ‘masculine’ game themes as male gamers (Cassell & Jenkins, 1998). Due to the emerging research that suggests a significant number of females do play video games, it could be deemed reasonable to hypothesise that the apparent lack of female gamers may be due to the general gender dynamics of gaming in public rather than an actual lack of interest in gaming by females. There is also evidence that for females the computer game may form part of a joint leisure activity within existing networks (Bryce & Rutter, 2005). All of these factors could suggest that skilled online gaming would be an appealing activity for females. This could indicate that research into the demographics of such a study would expect to find a reasonable number of female participants.
Demographics usually assessed in online videogame research are age, nationality, education level and financial income (Griffiths et al, 2003; Brian & Wiemer-Hastings, 2005). These factors have been assessed to build up a picture of video game players. This information is vital as a ‘benchmark’ in order for future research to be built on.
Studies that have examined online videogames have looked at a variety of variables. These have included, on a basic level, variables such as game play frequency, duration of play, favourite activities, least favourite activities, playing history, role playing and gender swapping (Griffiths et al, 2003; Brian & Wiemer-Hastings, 2005). These have been used to build a picture of playing behaviour but only give a very limited view of what it actually means to be a gamer and how exactly it effects or impacts on people’s lives.
Some studies have examined the addictive qualities or level of addiction that videogame players exhibit (Wood, Gupta, Devevensky & Griffiths, 2004) and the effects on certain behaviours, such as aggression (Gentile, et al, 2004). The majority of these studies have shown that videogames can be addictive (Griffiths, 1995) and that some video games have been associated with aggressive behaviour (Anderson and Bushman, 2001). However these studies have been relatively controversial as they examine these factors using self-report methods and artificial scenarios. This type of research is fraught with problems and criticism.
There appears to be little research on the subject of people who play online games for money, especially when examining games of skill, such as chess. Therefore the general demographics of people who participate in games for money, if they are similar to those who play for pure entertainment or whether there is a livelihood behind it, are unknown.
Online gaming for monetary gain is an important area to examine not only because it is an under researched field but also due to its association with online gambling (see section on ‘Connections between gaming and gambling’). Online gambling has continued to grow at a rapid pace since its inception (Griffiths, 2003). The technological advances within this industry have made gambling accessible and constantly available to a much wider population of people. Whilst this does have a number of benefits for the gambling industry and its customers, it has raised serious concerns about the effect it could have on some people who may not be able to control their gambling behaviour (Smeaton & Griffiths, 2004).
It has already been established that gambling can become very addictive. However online gambling is particularly problematic due to a number of factors, such as anonymity, convenience, escapism, accessibility, event frequency, interactivity, and disinhibition (Griffiths, 2003). It is also more difficult to protect the vulnerable over the Internet; as it is virtually impossible to tell if a person is in a fit state to compete i.e. intoxicated, various problems with mental health, etc when accessing sites over the Internet or to assist in stopping them if needed (Griffiths & Parke, 2002).
Video games and games of chance, such as gambling often share very similar features; both contain elements of randomness and provide rewards sporadically (Gupta & Derevensky, 1996). As a results it has been suggested by some researchers that one of these activities may precede from the other, for example, video game playing in adolescents may lead to some to pursue gambling (Griffiths, 1991). Griffiths (1991) has also proposed that video games could be considered a non financial form of gambling, where instead of money, points are collected.
Video game playing and gambling can also be seen to be similar on a psychological and behavioural level. Both make use of light, colour and sound effects to keep players, interested and engaged in the activities; both offer ‘near miss’ opportunities and both provide similar intermittent reinforcements (Griffiths & Wood, 2000). The structural characteristics of gaming and gambling also share a number of similarities, such as the requirement of total concentration and hand-eye coordination, auditory and visual rewards for winning, electronic display of points gained or money won and the opportunity for approval and attention through competition (Fisher & Griffiths, 1995). These similarities suggest that online gaming is an even more important area to study.
The Internet is a part of many people’s everyday life and there is now a significant amount of research that has suggested that users can become addicted to the Internet (Brian & Wiemer- Hastings, 2005; Young, 1996a). More recent research has indicated that Internet addicts are not male introverts as previously thought but are primarily middle-aged females on home computers (Griffiths, 1997; Young, 1996a). The most addictive aspects of the Internet seem to be ‘real time’ services such as live chats. It has been observed that escaping into these types of activity can result in the loss of control of time spent on the Internet, thus indicating that users can become addicted and that there is a potential for more addictive applications in the future (Young, 1996b; Young, 1996c).
It is therefore possible that online gaming and online gambling could be doubly addictive as the Internet (Brian & Wiemer- Hastings), and gaming (Klein, 1984) and gambling (Griffiths, 2003) have all been shown to have addictive qualities. However at the moment there is no research to show that this is true.
The methodology used within video game and gambling research can vary significantly. Within research studies the type of data that is required (data-driven research), the problem that needs to be solved (problem driven research) or the development or exploration of an interesting, plausible or useful theory (theory driven research), could all define the methodology used. In gaming research the methodology can also be affected by the type of games that are being investigated, for example, analysing a MMORPG game, such as, Everquest would require an entirely different approach than looking into games such as Tetris. The type of games that are to be included within gaming research is also an issue. Should games that are akin to board games, such as online chess, be looked at alongside fighting games such as Soul Calibur?
Theory and research around video games have undergone a striking increase in recent years. Previous research on areas such as television violence has been adapted to researching these elements within videogames. It has been discussed that qualitative and contextual analysis can aid and inform quantitative measures in this area (Anderson and Bushman, 2001). Therefore a combination of approaches has been applied to understand specific aspects of the effects of video games on different people. However the area regarding online gaming has had a significantly smaller proportion of research dedicated to it than that of offline video gaming. This may be due to the fact that online video gaming is still a relatively new phenomenon (Griffiths, et al, 2004).
Research on the effects of videogames on specific behaviour, such as violence and aggression, has used a variety of methods to gain data. Many studies favour quantitative methodologies in order to attempt to infer causal direction. However many can only suggest a relationship between aggressive behaviour and violent video games, and have not proceeded beyond a simple association (Anderson & Dill, 2000), as the generative mechanisms of the process (observing aggression to behaving aggressively) have not been addressed. It has also been postulated in violent videogame research that this process could be bi-directional. Therefore those who are more aggressive in nature are drawn towards violent video games and then playing these violent games increases aggression. This should always be taken into account when assessing a causal process.
Research on videogame play when assessing its effect on certain behaviours has used a variety of methods ranging from self-report surveys to experimental ‘artificial’ conditions. Fling, Smith, Rodriguez, Thornton, Atkins, and Nixon, (1992) measured the effects of video games on behaviour by using a mixture of self, teacher and peer reports. Although this seemed an appropriate way of examining certain types of behaviour, this type of data collection is associated with a number of problems. These types of measure rely heavily on the participant to both correctly interpret the question being asked and also to provide an answer that is usually relatively restricted, for example, choosing an answer from a likert scale. It is also possible that different people may interpret behaviours in very different ways. If, for example, two teachers are asked on a scale of 1 to 5 to describe the aggressive behaviour of one of their pupils they may give a different score from each other, as it will be based on their perceptions of what aggression is and the boundaries that they define as acceptable behaviour.
Experimental studies have also produced varied results (Graybill, Strawniak, Hunter & O’Leary, 1987; Anderson & Dill, 2000) when examining the behavioural effects of video game playing. These studies have been carried out in artificial conditions, often having participants playing a game for a period of time and measuring certain aspects before and after play. This may be either by asking participants to fill in a questionnaire or by making them perform a task, for example, administering a load blast to a competitor, to judge aggression, excitement, etc (Anderson & Dill, 2000). These types of studies, while addressing the issue directly, are produced in an artificial setting. Therefore participants’ responses may be altered, as they are aware they are being studied. It is therefore difficult to apply the results to the real world.
Research onto actual online gaming has been relatively limited, despite its growing popularity (Griffiths, et al, 2004). The research has tended to concentrate on negative aspects, such as excessive play and addiction (May, 1994; Griffiths & Hunt, 1998). Addiction to online gaming (and gambling) has often been measured using various adaptations of the DSM-III-R or DSM-IV criteria for pathological gambling (Griffiths & Hunt, 1998; Wood, et al, 2004). These measurements ask direct questions about gambling or gaming behaviour, for example, have you made repeated unsuccessful efforts to control, cut back, or stop gambling? These direct questions, while addressing the fundamental basis of addiction are possibly too explicit and obvious as participants may not be aware of, or want to admit to, their level of gambling or gaming problem. Therefore it may be appropriate to also ask specific questions about their behaviour in relation to gaming and about their playing frequency. These questions combined with questions adapted from the DSM criteria for pathological gambling may provide a greater insight and more reliable information on a participant’s relationship with gaming.
One recent study has attempted to investigate addiction in gaming to a greater extent (however it has not yet been published). Charlton & Danforth (article in press) used an Asheron’s Call-specific Addiction Engagement questionnaire (containing 29 items) and IPIP Seven Factor Personality Scale to explore participants’ possible addiction to gaming. This study attempted to identify the differences between addiction to gaming and high engagement of gaming. The researchers were able to separate these two behaviours and stated that it is important not to mistake one for the other as it could lead to an overestimation of the prevalence of pathological computer related behaviours.
There have been a few recent studies that have begun to examine the demographics of online gamers. However these have tended to concentrate on the online game Everquest (Brian & Wiemer-Hastings, 2005; Griffiths, et al, 2004; Griffiths, et al, 2003). This may be due to its incredible popularity and available access through fan-sites. Researching the demographics of players has been relatively straightforward, by administering a questionnaire with specific questions pertaining to participants; age, gender, education, financial income and nationality.
Many studies have been criticised for the samples they have used within their research. Charlton’s (2002) study on computer addiction and engagement was an interesting and important piece which looked further into behavioural addictions and presented a measurement that examined addiction and engagement in computers. However Charlton’s (2002) study only had participants that were higher education students. Even though it is common practice to include students in studies (due to their availability) it produces a number of problems. One being that when examining something such as addiction it would be expected that, due to the relatively low frequency of computer addicts in the general population, the expected number within such a specific sample would also be expected to be quite low (Charlton & Danforth, in press). It would be much more appropriate to attempt to gain a more representative sample, rather than approaching one specific group.
Due to the nature of studies on areas such as online gaming and online gambling, an almost ideal way of gaining participants is presented. Collecting data online is a good medium to carry out both online gaming and online gambling research. It is accessible to those who the researcher wants to study, it allows studies to be administered to large scale samples quickly and efficiently, it does not require ‘post outs’, pen and paper, etc therefore is significantly less expensive, it is not administered face to face and consequently participants can have a level of anonymity that is usually not possible within studies. This may then lead to increased levels of honesty and therefore more reliable and valid results. Finally, it can also reach a much larger demographic, therefore allowing researchers to examine different cultures at the same time (Wood, Griffiths & Eatough, 2002).
Studies who have gained participants via online participation have benefited from the use of this medium. Brian & Wiemer-Hastings (2005) and Griffiths et al (2004) have all gained participants and data by approaching online websites such as www.everlore.com and www.eqvault.ign.com and posting online surveys. Both of these studies were examining demographics and game usage/ playing variables of participants who played the popular online game Everquest. A large number of participants have been gained from such methods with Griffiths et al, (2004) obtaining 540 participants for their study and Brian & Wiemer-Hastings (2005) having a total of 91 responses after 10 days of the survey being online. Both these studies were able to gain a large demographic and gain understanding of the frequency of game play and the reasons why people participated in these games. The surveys mainly used likert scales to gain information in order to aid analysis and assist participants in their interpretation of the question and possible answers.
There are some issues with this form of data collection. It does not allow the participants to fully express themselves about the game and sometimes gives options that are not entirely suited to the answer a participant wishes to give. This could mean that participants may become frustrated with the questionnaire administered and that the data gathered may not truly represent a participant’s behaviour and opinions.
Some research has relied purely on secondary data. Griffiths, et al, (2003) used secondary analysis at two fan sites for Everquest players to examine socio-demographic variables and data relating to game playing, such as, frequency, duration, etc. Even though the sample size was extremely large, the data gained was very limited. It was restricted to the poll questions previously asked by the websites and was based on a self-selected sample. As the research was also on a specific game it limited the ability to generalize the findings. The researchers were cautious about their interpretation of the findings. Since they were used as a benchmark or starting point for further research to be conducted, it can be seen that this method is satisfactory, although not generally recommended as the only way to gain data.
No research on online gaming seems to have been approached from a qualitative perspective. However, within video gaming research, case studies and interviews have been conducted with some people, especially when exploring excessive gaming or addiction. Griffiths (2000) concentrated on five case studies of excessive computer game use. Of the five case studies within this research it was deemed only two of the participants could be said to be addicted. The research was purely qualitative: participants were either corresponded with by mail, via the Internet or by giving a face-to-face interview. While this research gave rich and in-depth data, the analysis and conclusions reached were purely from the perspective of the researcher. Therefore the research was subjective and possibly prone to bias.
Some studies have started to examine the structural characteristics of online websites in order to determine what the aspects of these sites encourage players to return and to examine the possible addictive qualities they possess. This can be achieved in a number of ways. Smeaton & Griffiths (2004) studied the websites themselves, examining them with the use of a set of pre-structured questions. They then drew up a list of recommendations for gambling sites to adhere to, to improve good practice. Choi & Kim (2004) conducted a large scale survey to evaluate online games. Both of these types of research procedures were able to examine the variables that were the intention of the study. Therefore each methodology was appropriate for the research question in mind.
It is clear that within both qualitative and quantitative methodologies there are various issues and benefits. The combination of a variety of methods, for example, questionnaires, self report surveys, and semi structured interviews, would give a range of data that would add to a valid and varied view of a topic such as online gaming.
It can be seen from this review that while extensive research has been conducted on gambling and gaming. There has been little research on online gaming and no research on online gaming for monetary gain. Therefore the demographics and effects this activity has on its players is unknown. This is especially important to establish as gaming and gambling share so many similarities (Wood, et al, 2004) and that research has already shown gaming to be an addictive activity (Klein, 1984).
The research questions to be addressed are therefore: is there any connection between online gaming for money and online gambling (in reference to the effects these two activities have and their structural characteristics), what are the demographics of those who participate in online gaming for monetary gain and what is the addictive potential of both online gaming and online gambling?
It is apparent that a variety of methods have been used within gaming and gambling research to obtain data, however many studies tend to use a quantitative approach when examining aspects such as demographics and addiction on a wide scale. This allows for a number of participants to be approached and allows the researcher to generalise the findings more appropriately than with a small n, qualitative study. However it has been noted that qualitative studies can provide rich and detailed data that is vital in understanding specific areas in a greater depth. Therefore this study will mainly use quantitative methods in order to address the demographics and playing variables of online gamers, who play for money. This will be achieved through an online survey posted on a variety of forums and chat rooms connected with online gaming. This will therefore reach a greater number of people and will span cultures and a variety of demographics. However semi-structured interviews will also be conducted with a few participants in order to gain a deeper understanding of online gaming and its effects on behaviour and lifestyle. These two approaches will be combined to analysis online gaming as a whole.
The researcher will also examine the structural characteristics of a number of online gaming sites (where participants can win money) using pre set questions based on research previously conducted in this area (Smeaton & Griffiths, 2004).
Anderson, C.A., & Bushman, B.J. (2001). Effects of Violent Video Games on Aggressive Behaviour, Aggressive Cognition, Aggressive Effect, Physiological Arousal, And Prosocial Behaviour: A Meta-Analytic Review of the Scientific Literature. Psychological Science, 12, 353-359.
Anderson, C.A., & Dill, K.E. (20000. Video Games and Aggressive Thoughts, Feelings, and Behaviour in Laboratory and Life. Journal of Personality and Social Psychology, 78, 772-790
Baron, E., & Dickerson, M.G. (1999). Alcohol consumption and self-control of gambling behaviour. Journal of Gambling studies, 15, 3-5
Brian, D.N.G., & Wiemer-Hastings, P. (2005). Addiction to the Internet and Online Gaming. Cyberpsychology & Behaviour, 8,2, 110-113.
Bryce, J., & Rutter, J. (2005). Gendered Gaming in Gendered Space. In: J, Raessens & J, Goldstein, ed., Handbook of computer game studies. Cambridge. MIT Press, 2005, pp 301-310
Carter, B. (2005), MoneyGaming.com aims to lure women with £1m campaign. Digital Bulletin. Available at: http://www.brandrepublic.com/bulletins/digital/article/482289/moneygamingcom-aims-lure-women-1m-campaign [Accessed 20/3/06]
Castranova, (2001). In Griffiths, M.D., Davies, M.N.O., & Chappell, D. (2004). Demographic Factors and Playing Variables in Online Computer Gaming. Cyberpsychology & Behaviour, 7,4, 479-487
Cassell, J., & Jenkins, H. (1998). From Barbie to Mortal Kombat: Gender and computer games. London: MIT Press.
Charlton, J.P., & Danforth, I.D.W. (article in press). Distinguishing addiction and high engagement in the context of online game playing. Computers in Human Behaviour. [online] Available via: ScienceDirect [Accessed 21 May 2006]
Choi, D., & Kim, J. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. Cyberpsychology Behaviour, 7, 11-24
Colwell, J., & Payne, J. (2000) Negative correlations of computer game play in adolescents. British Journal of Psychology, 91, 295-310.
Fisher, S.L., & Griffiths, M.D. (1995). Current trends in slot machine gambling: Research and policy issues. Journal of Gambling Studies, 11, 239-247.
Fling, S., Smith, L., Rodriguez, T., Thornton, D., Atkins, E., & Nixon, K. (1992). Videogames, aggression, and self-esteem: A survey. Social Behaviour and Personality, 20, 39-46.
Frasca, G. (2001). Videogames of the oppressed. In: J. Newman. Videogames. New York: Routledge 2004 pp, 27.
Gentile, D.A., Lynch, P.J., Linder, J.R., & Walsh, D.A. (2004). The effects of violent video game habits on adolescent hostility, aggressive behaviours, and school performance. Journal of Adolescence, 27, 5-22.
Graybill, D., Strawniak, M., Hunter, T., & O'Leary, M. (1987). Effects of playing versus observing violent versus non-violent video games on children's aggression. Psychology: A Quarterly Journal of Human Behaviour, 24, 1-8.
Griffiths, M.D (1991). Amusement machine playing in childhood and adolescence: A comparative analysis of video games and fruit machines. Journal of Adolescence, 14, 53-73
Griffiths, M.D (1997). In Brian, D.N.G., & Wiemer-Hastings, P. 2005. Addiction to the Internet and Online Gaming. Cyberpsychology & Behaviour, 8,2, 110-113.
Griffiths, M.D. (2000). Does Internet and Computer “Addiction” Exist? Some Case Study Evidence. Cyberpsychology & Behaviour, 3, 211-218.
Griffiths, M.D. (2002). Gambling and Gaming Addictions in Adolescence: PACTS2. Oxford: BPS Blackwell.
Griffiths, M.D. (2003). Internet Gambling: Issues, Concerns, and Recommendations. Cyberpsychology & Behaviour, 6,6, 557- 568.
Griffiths, M.D., & Davies, M.N.O (2005). Does Video Game Addiction exist? In: J, Raessens and J, Goldstein, ed., Handbook of Computer Game Studies. London: MIT Press 2005, pp 359-369
Griffiths, M.D., Davies, M.N.O., & Chappell, D. (2003). Breaking the Stereotype: The case of Online Gaming. Cyberpsychology & Behaviour, 6, 1, 81-91.
Griffiths, M.D., Davies, M.N.O., & Chappell, D. (2004). Demographic Factors and Playing Variables in Online Computer Gaming. Cyberpsychology & Behaviour, 7,4, 479-487.
Griffiths, M D., & Hunt, N (1998). Computer game "addiction" in adolescence?. A brief report. Psychological Reports, 82, 475–480
Griffiths, M.D., & Parke, J. (2002). The social impact of Internet gambling. Social Science Computer Review, 20, 3, 312-320.
Griffiths, M. D., & Wood R. T. A. (2000). Risk factors in adolescence: The case of
gambling, video-game playing, and the internet. Journal of Gambling Studies, 16,
199-227.
Gupta, R.G ., & Derevensky, J.L.G. (1996).The relationship between gambling and video-game playing behaviour in children and adolescents. Journal of Gambling Studies, 12, 375-394.
Hall, J. (2005). Future of games: mobile gaming. In: J, Raessens & J, Goldstein, ed., Handbook of computer game studies. Cambridge. MIT Press, 2005, pp 47-55
IDSA. (2000). State of the industry report 2000-2001. Washington, DC: Interactive Digital Software Association.
Klein, M. H. (1984). The bite of Pac-Man. The Journal of Psychohistory, 11, 395–401.
May, C.A, (1994). Addiction to video and computer games: A case study. Nervenheilkunde 13, 314–317
Newman, J. (2004). Videogames. New York: Routledge.
O’Connor, J., Dickerson, M., & Philps, M. (1995). Chasing and its relationship to impaired control over gambling. High stakes in the nineties, 2nd edn. Curtin University, Sixth National Conference of the Association for Gambling Studies, 169-183.
Provenzo, E.F. (1991). Video Kids: Making Sense of Nintendo. London: Harvard University Press.
Smeaton & Griffiths, (2004). Internet Gambling and Social Responsibility: An Exploratory Study. Cyberpsychology & Behaviour, 7,1, 49-57.
Wolf, M.J.P. (2005) Genre and the video game. In: J, Raessens & J, Goldstein, ed., Handbook of computer game studies. Cambridge. MIT Press, 2005, pp 193-204
Wood, T.A., Griffiths, M.D., & Eatough, V. (2004) Online data collection from video game players. Cyberpsychology and Behaviour, 7,5, 511-518
Wood, R.T.A., Gupta, R., Derevensky, J. L., & Griffiths, M.D. (2004). Video Game Playing and Gambling in Adolescents, Journal of Child & Adolescent Substance Abuse, 14, 77-100
a)Young, K.(1996). What makes the Internet addictive? Potential explanations for pathological Internet use. Presented at the 105th Annual Conference of the American Psychological Association. Chicago. In Brian, D.N.G., & Wiemer-Hastings, P. 2005. Addiction to the Internet and Online Gaming. Cyberpsychology & Behaviour, 8,2, 110-113.
b)Young, K, (1996). Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychological Reports, 79. 899-902.
c)Young, K, (1996). Internet addiction: the emergence of a new clinical disorder. Cyberpsychology & Behaviour, 1 237-244
Pilot Research
Online Gaming for Money –
The demographics of those who play and its addictive potential
The influence of technology in the field of both gaming and gambling continues to grow at a rapid pace, while there have been a number of studies conducted on online gaming and online gaming, none so far have looked into online gaming for monetary gain. This research examines this relatively new activity compared with online gambling. The results indicate that there are a number of similarities and convergences between the two activities and sheds some light on the demographics of those who participate. However due to the sample that was gained for this study it is not possible to comment on too many of the demographic factors as almost all participants were male, students and within the same income bracket
This research is examining the impact of online gaming on people’s lives, its addictive potential and its relationship to online gambling. This research is an important area to consider as online gaming for money has had little, if no research conducted on it (possibly due to it being a new venture) and has strong similarities to online gambling (Wood, Gupta, Devevensky & Griffiths, 2004). It is therefore important to examine what online gaming entails, whether it is addictive, and the types of people who take part in it.
1) To establish whether online gaming sites that offer playing games of skill for money have the same addictive potential as online gambling sites.
2) To determine how online gamers view online gaming and its effect upon them.
Objectives
1) To determine the demographics of people who participate in online gaming and online gambling, for example, what are the ages, socio-demographics, income, etc
2) To examine the extent (if any) that online gaming and online gambling impact on participants lives/ behaviour (examining how much time, money, etc they devote to these pursuits)
3) To examine whether there are any similarities or convergences between online gaming and gambling (again examining aspects, such as, demographics of those who participate)
4) To determine the main factors that influence people to carry on participating in these activities.
5) To determine if any people who participate in these activities could be considered addicted by using the DSM IV Diagnostic criteria (American Psychiatric Association, 1994).
Online gaming has become increasingly popular over the past few years and multiplayer online role-playing games such as Everquest are yet another type of computer game that has been shown to be addictive (Hall, 2005). A relatively new type of ‘online gaming’ that is becoming increasing popular are ‘games of skill’ online, such as chess (Tedeschi, 2004). As previous research has indicated that gaming can be addictive (Klien, 1984) and due to the close association between gaming and gambling (Wood, et al, 2004; Gupta & Derevensky, 1996) and the severe problems that gambling has been associated with (Griffiths, 1990; Griffiths, 2003), online gaming for monetary gain can be seen as an important area to research. Research that has concentrated on online gaming has tended to investigate the demographics of players, playing variables, reasons for continuing the activity and the addictive qualities of these games (Griffiths, Davies & Chappell, 2004; Griffiths, Davies & Chappell, 2003; Jos de Mul, 2005). Online data collection has been shown to be a very appropriate method when examining this type of subject matter (Wood, Griffiths & Eatough, 2004).
Sample:
The population being looked at in this study are the people who participate in online gaming and online gambling for money. Participants were gained by approaching students from
Data Collection:
The data collected for this research has been gained through an online questionnaire (designed by the researcher using Autoform). This will be used to examine basic demographic factors (gender, age, occupation, etc), game play frequency (amount of time spent playing a week), how long have they gambled/ played games online, why they play (favourite aspects, least favourite aspects), money spent online gaming or gambling, etc. These questions have been established in order to answer the research question and address the aims proposed. Participants have also been assessed for any indication of addiction either to gaming or gambling using the DSM IV Diagnostic criteria (American Psychiatric Association, 1994). These questions and the factors being examined are based on extensive work already conducted on the areas of gaming and gambling (see literature review).
Data Analysis:
Descriptive analysis will first be used to examine the data from the survey in order to provide a good basis for further analysis. This can also be used to begin to examine some of the objectives such as exploring any similarities or convergences. Frequency distributions, bar charts and the mean are examples of what will be used for descriptive statistics within this research. Relationships between variables can be assessed by using analysis, such as, crosstabulation, chi-square and bivariate analysis (such as Spearman’s rho), for example, do females gamble more money than males, do those who test as more addictive lose more money, etc. Multiple regression will be used in order to see which factors best predict online gambling and online gaming for money (this will only be conducted if there are over 50 participants). Certain aspects can only be examined depending on the richness and variety of data gained from the questionnaires. Therefore descriptive statistics may be the main element of analysis to judge the similarities between gaming and gambling.
In order to protect participants from any problems that could arise all participants are fully informed as to the nature of the questionnaire and it has been made clear that they are under no obligation to complete or finish the questionnaire if they do not wish. Participants have also been informed that their answers will be kept strictly confidential. Participants have been informed that when they select the ‘submit’ button at the end of the survey that they are agreeing to take part in this study and for their answers to be used as part of it. At the end of the survey links to various help sites for gaming and gambling have been provided.
Results and Discussion:
Analysis of the data focused on the following questions; what are the demographics of those who participate in online gaming for money and gambling, to what extent (if any) do these activities impact on participants lives, are there any similarities between the two activities and are they related in any way.
It can be seen that for both gaming online and gambling online, only a small percentage of participants are female, with 15% of participants who gamble and 18% of participants who game online being female (see table 1 in appendix). This is consistent with previous literature in this area. As all but one of the participants were full-time students the income brackets did not exceed £15,000 a year. It can be seen in table 1 below that the main income for people who participate in gaming, gambling and also both of these activities is below £10,000 a year.
Table 1: Crosstabulation of Income and Activity participated in
Count
|
|
Activity |
Total | |||
|
|
Gaming |
Gambling |
Both gaming and gambling |
| |
|
Income |
No answer |
1 |
1 |
0 |
2 |
|
|
Below £10,00o |
6 |
10 |
5 |
21 |
|
|
£10,000-£15,000 |
3 |
1 |
3 |
7 |
|
Total |
10 |
12 |
8 |
30 | |
The mean age of participants was 21.2 years (see table 2). Of the participants who completed the online forms, 9 played online games for money, 13 participated in online gambling, and 8 took part in both online gaming and online gambling. Considering slightly more people take part in online gaming and online gambling individually rather than combined it cannot be suggested at this stage that the two are connected, for example, that participating in one of these activities leads to participation in another.
Table 2: Age of participants
The reasons participants gave for starting these activities were quite similar, these were; they already played online games (37.5%), because of their friends (37.5%) and also initially from competing in online gambling (25%) (see table 3). A similar distribution can be observed in table 4, for gambling.
Table 3: Reasons participants started to game online
Table 4: Reasons participants started to gamble online
In table 5 and 6 in can be seen that the reasons for taking part in online gaming and online gambling are reasonably similar with winning money, enjoyment and excitement being the three most popular reasons for both.
Table 5: What participants like about online gaming
Table 6: What participants like about online gambling
When calculating the financial aspect of online gaming and gambling it is apparent that the amount both bet and won in online gambling is considerably higher than that of online gaming (for gambling the ‘win’ results had to broken into two as some participants gave two figures, gamwin1 represents the lowest won and gamwin2 the highest) (see table 7 and 8). On average the amount participants stated they won on online gambling varied between –£20.95 and £24.42 a week and people who gamed online won on average £6.75 a week.
Table 7: Gambling - money bet and won
Table 8: Gaming - money bet and won
When examining if there were any differences between the sexes in terms of gaming it can be observed that males spent on average more time online gaming than females (see table 9). However only 3 participants were female which is a very low number to judge the average of female gaming.
Table 9: Comparison of means for hour’s online gaming between genders
According to the DSM IV Diagnostic criteria for Pathological Gambling (which has also been adapted for online gaming) a score of over 4 would indicate a persistent and recurrent maladaptive gambling behaviour. Only one participant who gambled online scored over 5 in this section, and two participants scored over 5 in the online gaming section (see raw data table 1 in appendices). Therefore further analysis was not conducted on the area of addiction to these activities.
Further analysis into other aspects of gaming behaviour showed no significant results (see appendices table 2, 3 and 4). Multiple regression was not conducted as the number of appropriate responses totalled 30 and therefore not enough participants were gained to make this analysis valid.
The validity and reliability of the data in this study can be assessed by examining aspects, such as; face validity, convergent validity, stability, etc. The data in this research can be considered valid as it reflects the content of the concept in question. It therefore can be seen to address the fundamental aims behind this research and on a basic level is valid. It also produces similar results to that of previous research in this area. However as this appears to be one of the first pieces to examine online gaming for money, these results cannot be tested against a completely similar study.
The reliability of this study can be assessed by administering the survey to the same people in order to measure stability, a ‘test-retest’ method. It can be observed in the analysis of the data that many of the results from people who participated in the same activity shared similar responses for other variables, for example, the reason they continued with this activity or hours spent gambling and gaming. The data can therefore be considered both valid and reliable for this study. However the sample size was relatively small, therefore caution should be taken when drawing conclusions from the analysis. Also as some analysis was based on a small proportion (for example, only 3 female participants in online gaming for money were female) it is not advisable to draw conclusions or rely on averages from this.
Conclusion:
The main findings from this study indicate that online gaming for money and online gambling share a number of similarities and it is apparent that there is a connection between the two. However due to the sample that was gained for this study it is not possible to comment on too many of the demographic factors as almost all participants were male, students and within the same income bracket.
It may be more appropriate to break this questionnaire into three separate surveys, one concentrating on online gaming for money, one on online gambling and one that assesses the two activities together. As it is apparent the difference between gaming and gambling was not evident to some who submitted the questionnaire. It would be advisable for future research to now concentrate on trying to gain a more representative sample of online gamers and online gamblers, by approaching forums, websites and meeting rooms and to include a more qualitative approach, such as, interviews in order to explore the area in more depth and detail.
References
American Psychiatric Association. (1994). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition.[online] Washington, D.C. Available at: http://www.npgaw.org/2005/pdfs/PDF5.pdf [Accessed 20 April 2006]
Brian, D.N.G., & Wiemer-Hastings, P. (2005). Addiction to the Internet and Online Gaming. Cyberpsychology & Behaviour, 8,2, 110-113.
Griffiths, M.D. (2003). Internet Gambling: Issues, Concerns, and Recommendations. Cyberpsychology & Behaviour, 6,6, 557- 568
Gupta, R., & Derevensky, J. L. (1996). The relationship between gambling and video-game playing behaviour in children and adolescents. Journal of Gambling Studies,
12, 375-395.
Hall, J. (2005) Future of games: mobile gaming. In J, Raessens & J, Goldstein. 2005. Handbook of computer game studies. Cambridge. MIT Press.
Jos de Mul, (2005). The game of life: Narrative and ludic identitiy formation in computer games. In In J, Raessens & J, Goldstein. 2005. Handbook of computer game studies. Cambridge. MIT Press.
Klein, M. H. (1984). The bite of Pac-Man. The Journal of Psychohistory, 11, 395–401.
Odell, P.M., Korgen, K.O., Schumacher, P., Delucchi, M. (2000). Internet Use Among Female and Male College Students. CyberPsychology & Behavior, 3, 5, 855-862.
Tedeschi, B. (2004). Internet Companies Turn to Games of Skill. [online]. The New York times 24th May 2004. Available at:
http://www.nytimes.com/2004/05/24/business/24ecom.html?ei=5007&en=68a2d477d3d14162&ex=1400731200&partner=TECHDIRT&pagewanted=all&position= [Accessed 25 February 2006]
Wood, T.A., Griffiths, M.D., & Eatough, V. (2004) Online data collection from video game players. Cyberpsychology and Behaviour, 7,5, 511-518
Wood, R.T.A., Gupta, R., Derevensky, J. L., & Griffiths, M.D. (2004). Video Game Playing and Gambling in Adolescents, Journal of Child & Adolescent Substance Abuse, 14, 77-100
Table 1: See separate sheet
Table 2: Spearman’s rank analysis of hours spent online gaming and sex of participant
Table 3: Chi Square analysis of income and amount bet on online gaming
Table 4: Spearman’s rank analysis of hours spent on the Internet and sex of participant
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