What is the relationship between accessibility and problem gambling?

Environmental factors additional to gambling exposure are known to have an impact on problem gambling. Some are part of, or closely associated with, the physical and social contexts in which gambling occurs and play a role in increasing or decreasing exposure. Others, while more peripheral, include a number of major risk factors for problem gambling. A number of researchers in the gambling studies field have noted that empirical investigation of relationships between proposed risk factors and outcomes requires accurate and reliable measurement coupled with methodologically robust studies in which exposure levels are varied while other factors that may affect outcomes are held constant or controlled for statistically. If this is not achieved, the findings and conclusions may be invalid and/or misleading.

With most drug-based addictions, different parameters of exposure are typically examined including dose, potency and duration. In the gambling situation, it is much more difficult to quantify social and behavioural exposures. Furthermore, practical and ethical considerations place constraints on experimental investigation. Gambling research is at a relatively early stage of development and it is only recently that public health approaches have been incorporated. In the future, it is likely that more complex measures of gambling exposure will be used. This could include the availability of, and expenditure on, different forms of gambling, the dispersal of and degree of accessibility to these forms, the time they have been available and extent to which harm minimisation strategies have been prescribed and implemented.

Back in 1999, the Australian Productivity Commission (APC) developed a multidimensional framework to assess exposure. It highlighted nine specific dimensions comprising: (i) number of opportunities to gamble, (ii) number of venues, (iii) location of venues, (iv) opportunities to gamble per venue, (v) opening hours, (vi) conditions of entry, (vii) ease of use of gambling form, (viii) initial outlay required, and (ix) social accessibility. Using these criteria the APC conducted several analyses to examine the relationships between accessibility and gambling using state-level electronic gaming machine (EGM) density and expenditure data as well as data drawn from a national Australian gambling survey of gambling prevalence. The results suggested that high levels of problem gambling with gambling machines was correlated to their density relative to the population. In one analysis, the pathological gambling prevalence rate for different Australian States was plotted against the number of gaming machines per 1000 adults in each State. In another analysis, the number of gaming machines per 1000 adults was plotted against the estimated amount spent per capita on gaming machines. Both analyses showed positive relationships suggesting that (at a State level) a greater density of gaming machines per capita was associated with both higher per capita expenditure and higher problem gambling prevalence rates.

However, it should be noted that although several other studies have shown that a higher density of gaming machines in the population correlated to higher rates of problem gambling, this does not, in itself, show that the number of machines in a specific venue has any impact on levels of problem gambling. The number of machines in these studies was related to a large number of venues, and consequently the number of gaming machines in this context does not tell us much about the impact of the number of gambling opportunities in one or a few centralized venues. Furthermore, it could perhaps be speculated that far fewer games in a venue could conceivably encourage a problem gambler to stay on one particular machine for fear of having to wait for another machine to become vacant.

A more complex quantitative procedure was proposed by a group of researchers affiliated to Harvard University led by Professor Howard Shaffer in the US. They generated a ‘standardised exposure gradient’ that assessed gambling exposures within a particular region. This index includes the: (i) dose (i.e., number of gaming venues and people working in the gambling industry), (ii) potency (i.e., the number of different major gambling modalities), and (iii) duration (i.e., the time casinos have been legalized). Although limited, the accuracy could be enhanced by the integration of further information, (e.g., the extent of illegal gambling, access to gambling in adjoining jurisdictions, gaming venue attendance, and advertising). Whether or not exposure indexed by these types of measure has an impact is strongly influenced by the form of gambling involved.

In a review of situational factors that affect gambling behaviour, Professor Max Abbott of Auckland University in New Zealand, concluded that although increased availability of and exposure to gambling activities have contributed to increases in problem gambling, it was highly probable that other situational factors including venue characteristics, social context, access to cash or credit, availability of alcohol, and industry marketing and advertising also have an influence.

Dr Rachel Volberg, Director of Gemini Research in the US, also reached a similar conclusion suggesting there is a correlation between increased availability of gambling opportunities and problem gambling. However, she then reported that in a number of replication studies that problem gambling rates had stabilized or decreased. Looking at these jurisdictions in more detail, she reported that all of them had introduced comprehensive services for problem gamblers including public awareness campaigns, helplines, and professional counselling programmes. She concluded that the relationship between increased opportunities to gamble and problem gambling may be moderated by the availability of helping agencies/services for problem gamblers. In areas of the US (like Montana and North Dakota) that saw an increase in problem gambling following the introduction of casinos, no public awareness campaigns or services for problem gamblers were introduced. Consequently, it appears that the increased availability of gambling opportunities do not necessarily equate to increased levels of problem gambling.

Professor Peter Collins of Salford University (UK) also reviewed this evidence and concluded that if a jurisdiction introduces new forms of gambling and does nothing else, it will most likely see an increase in problem gambling. However, if the jurisdiction combines the introduction of new forms of gambling with appropriate prevention and treatment services, it is likely to decrease numbers of problem gamblers. Collins noted that in the national South African gambling prevalence study that the country witnessed a decline in problem gambling over a two-year period following the introduction of the National Responsible Gambling Program.

Overall, evidence suggests that gambling availability has a positive, but complex, relationship to the prevalence of problem gambling. The relationship is not linear and there are many other factors that determine problem gambling.

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

Further reading

Abbott, M.W.  (2007). Situational factors that affect gambling behavior. In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies. pp.251-278. New York: Elsevier.

Collins, P.  (2007). Gambling and governance. In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies. pp.617-639. New York: Elsevier.

Delfabbro, P.H. (2002). The Distribution of Electronic Gaming Machines (EGMs) and Gambling-related Harm in Metropolitan Adelaide. Report Commissioned by the Independent Gambling Authority of South Australia.

Griffiths, M.D. & Parke, J. (2003). The environmental psychology of gambling. In G. Reith (Ed.), Gambling: Who wins? Who Loses? pp. 277-292. New York: Prometheus Books.

Shaffer, HJ., LaPlante, DA., LaBrie, RA., Kidman, RC., Donato, AN., Stanton, MV. (2004). Toward a syndrome model of addiction: Multiple expressions, common etiology. Harvard Review of Psychiatry, 12, 367-374.

Productivity Commission. (1999). Australia’s gambling industries, Report No. 10. Canberra:  AusInfo.  Available at  http://www.pc.gov.au/.

Volberg, R.A. (2004). Fifteen years of problem gambling prevalence research. What do we know? Journal of Gambling Issues, 10.