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Unfruitful approaches: Why are slot machine players so hard to study?

Anyone that researches in the area of slot machine gambling will know how difficult to can be to collect data from this group of gamblers. Over a decade ago, Dr. Jonathan Parke and I published a paper in the Journal of Gambling Issues on why slot machine players are so hard to study. Almost all of the things we wrote in that paper are still highly relevant today, so this blog briefly examines some of the issues we raised. The following explanations represented our experiences of several research efforts in attempting to examine the psychology of slot machine gamblers in the UK, Canada and the United States. Our explanations are roughly divided into three categories. More specifically, these relate to what we called (i) player-specific factors, (ii) researcher-specific factors, and (iii) miscellaneous external factors.

Player-specific factors: There are a number of player-specific factors that can impede the collection of reliable and valid data. These include factors such as activity engrossment, dishonesty/social desirability, motivational distortion, fear of ignorance, guilt/embarrassment, infringement of player anonymity, unconscious motivation/lack of self-understanding, chasing, and lack of incentive. These are explained in more detail below:

  • Activity engrossment – Slot machine gamblers can become fixated on their playing almost to the point where they ‘tune out’ to everything else around them. We have observed that many gamblers will often miss meals and/or utilise devices (such as catheters) so that they do not have to take toilet breaks. Given these observations, there is sometimes little chance that we as researchers can persuade them to participate in research studies – especially when they are gambling on the machine when approached.
  • Dishonesty/Social desirability – It is well known that some gamblers will lie and be dishonest about their gambling behaviour. Social and problem gamblers alike are subject to social desirability factors and will be dishonest about the extent of their gambling activities to researchers (in addition to those close to them). This obviously has implications for the reliability and validity of any data collected.
  • Motivational distortion – Many slot machine gamblers experience low self-esteem and when participating in research may provide ego-boosting responses that lead to motivational distortion. For this reason, many report that they win more (or lose less) than they actually do. Again, this self-report data has implications for reliability and validity of the data.
  • Fear of ignorance – We have observed that many slot machine gamblers report to understand how the slot machine works when in fact they know very little. This appears to be a ‘face-saving’ mechanism so that they do not appear to be stupid and/or ignorant to the researchers.
  • Guilt/embarrassment – Slot machine gamblers can often be guilty and/or embarrassed to be in the gambling environment in the first place. They like to convince themselves that they are not ‘gamblers’ but simply ‘social players’ who visit gambling environments infrequently. We have found that gamblers will often cite their infrequency of gambling as a reason or excuse not participate in an interview or fill out a questionnaire. Connected with this, some gamblers just simply do not want to face up to the fact that they gamble.
  • Infringement of player anonymity – Some slot machine gamblers clearly play on machines as a means of escape. Many gamblers will perceive the gaming establishment in which they are gambling as a ‘private’ (rather than public) arena. As such, researchers who approach them may be viewed as people who are infringing on their anonymity.
  • Unconscious motivation and lack of self-understanding – Unfortunately, many slot machine gamblers do not understand why they gamble themselves. Therefore, articulating this accurately to researchers can be very difficult. Furthermore, many gamblers experience the ‘pull’ of the slot machine where they feel compelled to play despite their better judgment but cannot articulate why.
  • Chasing – When trying to carry out research in the playing environments (e.g., arcades, casinos, bingo halls, etc.), many regular gamblers do not want to leave ‘their’ slot machine in case someone “snipes” their machine while they are elsewhere. Understandably, gamblers are more concerned with chasing losses than participating in an interview or filling out a questionnaire for a researcher.
  • Lack of incentive – Some slot machine gamblers simply refuse to take part in research because they feel that there is “nothing in it for them” (i.e., a lack of incentive). Furthermore, very few gamblers take the view that their gambling habits and experiences can be helpful to others.

Researcher-specific factors: In addition to player-specific factors, there are also some researcher-specific factors that can impede the collection of data from slot machine gamblers. Most of these factors concern research issues relating to participant and non-participant observational techniques (i.e., blending in, subjective sampling and interpretation, and lack of gambling knowledge). These are expanded on further below:

  • Blending in – The most important aspect of non-participant observation work while monitoring fruit machine players is the art of being inconspicuous. If the researcher fails to ‘blend in’, slot machine gamblers soon realise they are being watched. As a result, they are increasingly likely to change their behaviour in some way. For instance, some players will get nervous and/or agitated and stop playing immediately whereas others will do the exact opposite and try to show off by exaggerating their playing ritual. Furthermore, these gamblers will discourage spectators as they are often considered to be “skimmers” (individuals trying to make profits by playing “other peoples machines”). Blending into the setting depends upon a number of factors. If the gambling establishment is crowded, it is very easy to just wander around without looking too suspicious. The researcher’s experience, age and sex can also affect the situation. In the UK, amusement arcades are generally frequented by young men and elderly women. The general rule is that the older the researcher gets, the harder it will be for them to mingle in successfully. If the arcade is not too crowded then there is little choice but to be one of the ‘punters’. The researcher will probably need to stay in the arcade for lengthy periods of time, therefore spending money is unavoidable unless the researcher has a job there – an approach that Dr. Parke took to collect data.
  • Subjective sampling and interpretation – When the researcher is in the gambling environment, they cannot possibly study everyone at all times, in all places. Therefore it is a matter of personal choice as to what data are recorded, collected and observed. This obviously impacts on the reliability and validity of the findings. Furthermore, many of the data collected during observation will be qualitative in nature and therefore will not lend themselves to quantitative data analysis.
  • Lack of gambling knowledge – Lack of ‘street knowledge’ about slot machine gamblers and the environments they frequent (e.g., terminology that players use, knowledge of the machine features, gambling etiquette, etc.) can lead to misguided assumptions. For instance, non-participant observation may lead to the recording of irrelevant data and/or an idiosyncratic interpretation of something that is widely known amongst gamblers. As above, this can lead to subjective interpretation issues.

External factors: In addition to player-specific and researcher-specific factors, there are also some external factors that can impede the collection of data from slot machine gamblers. Most of these factors concern the gaming industry’s reactions to researchers being in their establishments although there are other factors too. These are briefly outlined below:

  • Gaming establishment design It is clear from many of the arcades and casinos that we have done research in over the years that many are not ideally designed for doing covert research in. Non-participant observation is often very difficult in small establishments or in places where the clientele numbers are low.
  • “Gatekeeper” issues and beaurocratic obstacles – The questions of ‘how?’ and ‘where?’ to access to the research situation can be gained raise ethical questions. Access is often determined by “informants” (quite often an acquaintance of the researcher) or “gatekeepers” (usually the manager of the organisation etc.). Getting permission to carry out research in a gambling establishment can be very difficult and is often the hardest obstacle that a researcher has to overcome to collect the data required. Many establishments do not have the power to make devolved decisions and have to seek the permission of their head office. The prevention of access by the industry can be for many reasons but the main ones are highlighted next.
  • Management concerns – From the perspective of arcade or casino managers, the last thing they want are researchers that disturb their clientele (i.e., their players), by taking them away from their gambling and/or out of the establishment. Furthermore, they do not want us to give their customers any chance to make gamblers feel guilty about their gambling. In our experience, this is something that researchers are perceived by management to do. This obviously impacts on whether permission to carry out research is given in the first place.
  • Industry perceptions – From the many years we have spent researching (and gambling on) slot machines, it has become evident that there are some people in the gaming industry that view researchers such as ourselves as ‘anti-gambling’ and/or that any research will report negatively about their clientele or establishment/organization. As with management concerns, this again impacts on whether permission to carry out research is given in the first place.

Dr. Parke and I envisaged that our explanations might enhance future research in this area by providing researchers with an understanding of some of the difficulties with data collection. Unfortunately, identification of slot machine gamblers is often limited to a “search and seek” method of trawling local gambling establishments (e.g., amusement arcades, casinos etc.). Therefore, researchers are often limited to collecting data during play rather than outside of it. Obviously data facilitation would be better if gamblers were not occupied by their machine gambling.

Dr. Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (1991). The observational study of adolescent gambling in UK amusement arcades. Journal of Community and Applied Social Psychology, 1, 309-320.

Griffiths, M.D. (1994). The observational analysis of marketing methods in UK amusement arcades. Society for the Study of Gambling Newsletter, 24, 17-24.

Griffiths, M.D. (1995). Adolescent Gambling. London: Routledge.

Griffiths, M.D. (1996). Observing the social world of fruit-machine playing. Sociology Review, 6(1), 17-18.

Parke, A., & Griffiths, M.D. (2004). Aggressive behavior in slot machine gamblers: A preliminary observational study. Psychological Reports, 95, 109-114.

Parke, A. & Griffiths, M.D. (2005). Aggressive behaviour in adult slot machine gamblers: A qualitative observational study. International Journal of Mental Health and Addiction, 2, 50-58.

Parke, J. & Griffiths, M.D. (2002). Slot machine gamblers – Why are they so hard to study? Journal of Gambling Issues, 6. Located at:

Parke, J. & Griffiths. M.D. (2008). Participant and non-participant observation in gambling environments. ENQUIRE, 1, 1-18.

Griffiths, M.D. (2011). A typology of UK slot machine gamblers: A longitudinal observational and interview study. International Journal of Mental Health and Addiction, 9, 606-626.

What do gambling prevalence studies really tell us?

Prevalence studies are frequently used in the field of gambling studies and are often seen as the pinnacle of good practice within the field. There are a number of good reasons why prevalence studies are important. In an article I co-wrote with Dr. Richard Wood (GamRes Ltd, Canada) we said that some of the benefits of prevalence studies are that they:

  • Provide indicative data on the broad extent of clinical need for the overall population and sub-populations, general population risk factors, and some correlates of a particular disorder. This is useful information for many different stakeholders including those who have responsibility for programmes concerning intervention, treatment and social responsibility.
  • Identify groups of people (for example, 18-24 year olds) where apparent needs do not match up with treatment service use. If we just surveyed treatment populations and/or those who attend Gamblers Anonymous, we would almost inevitably conclude that most problem gamblers are primarily white middle-aged men who typically have problems gambling on horse racing and/or casino games because females, various ethnic groups, and youth are disproportionately represented in treatment. It can also provide new research questions such as why such groups are not accessing treatment services.
  • Allow comparison of different regions (within country or across counties) in terms of prevalence and their association with game availability, treatment availability, economic prosperity, crime rates, etc.
  • Provide a snapshot of the life of a ‘normal’ gambler at a time of our choosing, rather than theirs. In contrast, clinical samples are consistent with people in crisis. We cannot always learn about the “normal” state of gambling, and how individuals can stay that way, from clinical samples.
  • Provide attitudes and beliefs and behaviours in the general public (i.e., non-affected people) rather than non- representative groups (like problem gamblers).

However, they have very little explanatory power for understanding the development of problem gambling. This is the case for several reasons. Dr. Wood and I have argued that:

  • Problem gambling is non-normally distributed across populations: Prevalence surveys select a sample that is representative of the entire adult population. However, problem gamblers are not equally distributed amongst that population and are therefore under- represented in general population surveys. For example, problem gambling in the UK is usually more prevalent amongst males, 18-24 age groups, those on lower incomes, for instance. Consequently, the actual prevalence of problem gambling may be higher.
  • Problem gambling is a ‘sensitive’ issue for participants: Given that gambling is a behaviour that most problem gamblers do not want to talk about, they are much more likely than non-problem gamblers to refuse to agree to participate in any survey. (Conversely, those who do not gamble at all may also be under-represented in gambling surveys as they may feel that the issue is no concern of theirs).
  • Non-response from problem gamblers: If problem gamblers happen to be in a household that is surveyed, they are much less likely to return the form than non-problem gamblers. If they happen to be in a household surveyed, they are less likely to return the call or form. Many may make themselves unavailable to answer survey questions if appointments are made to interview them. Furthermore, problem gamblers who agree to be surveyed are more likely to lie about the amount of time and money they spend on gambling, and about the frequency of their gambling – especially if they have not told their family that they have a problem and their family are not aware of the extent of their gambling. They are even more likely to lie during a survey if another family member is at home when they are answering the survey takers questions. No matter what the interview technique, households are not always places that encourage disclosure of information. Furthermore, household telephone interviews may also facilitate non-response as it is harder for problem gamblers to be honest when compared to self-completion methods. PGs are often in denial until they reach a point where they either get discovered or ask for help.
  • Small numbers of problem gamblers: One of the real disadvantages of prevalence surveys is that they do not tell us very much about problem gambling. Although prevalence surveys can highlight slight fluctuations in problem gambling rates in comparison with other prevalence surveys, they do not tell us very much about problem gambling itself. The two recent British Gambling Prevalence Surveys (BGPSs) had approximately 55 to 70 people were identified as problem gamblers. Many qualitative studies (including treatment) studies have bigger samples of problem gamblers than that but are classed as unrepresentative.
  • Gambling data from diverse groups may be unrepresentative: Some have argued that gambling prevalence surveys rarely capture responses from Culturally and Linguistically Diverse (CALD) groups. Some studies have found that gaming environments such as casinos comprise a disproportionate number of individuals from CALD groups.
  • Problem gambling is not uniformly distributed in the population: Given that many prevalence surveys such as the BGPSs are household surveys, it should be noted that problem gamblers are more likely to be homeless and/or to be institutionalized (in prison, in mental hospitals), and therefore not even accessed to survey about their gambling behaviour in the first place.
  • Unknown effect of false positives and false negatives on problem gambling estimates: One of the most highlighted problems is that when it comes to the screening instruments used to identify problem gambling, we do not know what effect false positives and false negatives have on the data. Typical survey samples worldwide are rather small (1,000 to 10,000 depending on population size). Therefore, the actual numbers of problem gamblers on which conclusions (and policy decisions) are made are very small (e.g., just over 50 problem gamblers in the case of the latest BGPS). To overcome the problem of small numbers and their analysis, the researchers often collapse sub-clinical and clinically significant cases of interest together. This analysis usually fails to consider the impact of false positive (in the sub-clinical group) on the validity of the conclusions drawn.
  • Response rates to national surveys are decreasing: The response rates for national gambling surveys have been decreasing internationally. This may decrease the prevalence of problem gambling as problem gamblers are more likely to be in the group of non-responders.
  • Survey response may differ as a function of media exposure to problem gambling: Australian researchers have argued that any given moment in time, the number of people surveyed who will admit to having a gambling problem is dependent on how much media attention has been given to concerns about gambling losses, and the level of problem gambling in the community. Shame and guilt (and therefore lying about gambling involvement) are apt to increase as public concern about gambling and gambling losses increases and as media reports become more prevalent and shocking.
  • Random samples are still self-selecting samples: Even though most national gambling prevalence surveys are random it could still be argued that those who are approached still ultimately decide whether or not to participate and in that sense the sample is still self- selecting.
  • Self-report methods can be problematic: The use of anonymous self-report methods may allow people to be economical with the truth and/or exaggerate and lie about certain issues. This is coupled with the fact that they may be asked things on which they have to rely on long-term memory (which may not be the most reliable). Furthermore, it is easy for a respondent to exaggerate or lie when they know that they are relatively anonymous and that nobody will question the validity of their answers.
  • Actual problematic gambling behaviour is rarely considered in large-scale surveys: In order to overcome question fatigue and to increase participation rates, very few questions in large prevalence surveys actually focus on gambling problems beyond the screen questions used to identify people with problems. This leaves correlational factors only that are often basic demographics (e.g., age, location, etc.) or frequency questions (how often they play, etc.), that by themselves they do not provide much information as to why problems develop.
  • Lack of theory-driven and/or model-driven research: In almost all gambling prevalence surveys there is a great emphasis on closed (forced) question responses rather than allowing respondents to explain what the issues are for their specific gambling behaviour (i.e., the studies are more about ‘data trawling’ rather than ‘theory building’). This also means that we are just measuring fluctuations rather than developing and testing theories that help us understand the fundamental issues.
  • Understanding severity: There appears to be an assumption that endorsing one or two items on a problem gambling screen indicates a problem at a low level when there is little evidence to support this. Whilst endorsing the specified number of criteria on a diagnostic screen may be a good indicator of a gambling problem, the scores for endorsing one or two items may not have been validated as an indicator of a lesser problem. Answering in this way to one or two items may in fact indicate the extent of ‘normal’ risk inherent in gambling activities.

By highlighting some of the problems of prevalence surveys, Dr. Wood and I are not saying that these should not be carried out (as they clearly have a use as outlined at the start). However, there are lots of other methodologies for examining and understanding problem gambling. We need to look at the lives of the problem gamblers in far more detail than the data collected from prevalence surveys. Future prevalence surveys should be complemented with other more ‘in-depth’ methodologies including interviews, focus groups, Q-sorts and online discussions

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2010). Gambling, alcohol consumption, cigarette smoking and health: findings from the 2007 British Gambling Prevalence Survey. Addiction Research and Theory, 18, 208-223.

Griffiths, M.D., Wardle, J., Orford, J., Sproston, K. & Erens, B. (2011). Internet gambling, health. Smoking and alcohol use: Findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9, 1-11.

Griffiths, M.D. & Wood, R.T.A. (2009). Prevalence studies: What do they really tell us? Casino and Gaming International, 5(4), 102-104.

Orford, J., Griffiths, M.D., Wardle, J., Sproston, K. & Erens, B. (2009). Negative public attitudes towards gambling: findings from the 2006/07 British Gambling Prevalence Survey using a new attitude scale. International Gambling Studies, 9, 39-54.

Sussman, S., Lisha, N. & Griffiths, M.D. (2011). Prevalence of the addictions: A problem of the majority or the minority? Evaluation and the Health Professions, 34, 3-56.

Wardle, H., Moody. A., Spence, S., Orford, J., Volberg, R., Jotangia, D., Griffiths, M.D., Hussey, D. & Dobbie, F. (2011).  British Gambling Prevalence Survey 2010. London: The Stationery Office.

Wardle, H., Sproston, K., Orford, J., Erens, B., Griffiths, M.D., Constantine, R. & Pigott, S. (2007). The British Gambling Prevalence Survey 2007. London: The Stationery Office