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Gambling and the trait of addiction in a sample of New Zealand university students

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Addictions & Substance Use

New Zealand Journal of Psychology,  Jun 2003  by Clarke, Dave

Continued from page 3.

Much of their lifetime gambling preferences was similar to those of 1017 young people in Melbourne, Australia (Moore & Ohtsuka, 1997). However, more of them purchased lottery tickets than the Australians (74% versus 48%), played gaming machines (82% versus 43%), and gambled in casinos (47% versus 32%). Compared with university students in North America, the lifetime prevalence of lottery gambling (74%) was higher than that for Oregon students (31%; Browne & Brown, 1994), and the prevalence averaged across five American States (46%; Lesieur et al., 1991) including New York (69%) and New Jersey (66%). On any activity, 97% of the present sample, 87% of the national participants, 85% of the five United States' groups, and 90% of the students in a Canadian survey (Ladouceur et al., 1994) had gambled at least once. It would thus seem that the prevalence of gambling among the students in the present sample was greater than that among overseas students. However, because the prevalence of gambling is on the increase in general populations with the increasing availability of gambling activities (Abbott, 2001; Sullivan, 1994a), it would be expected that North American students' current involvement in gambling would be comparable to that of university students in the present sample.

Problem Gamblers versus Non-problem Gamblers

Compared with six-month problem gambling rates among general populations in New Zealand (1.3%), and in Australia, the United States of America, Canada and Sweden, ranging from 1.2 to 6.6 percent of the populations (Abbott & Volberg, 1999), the rate of 16% in the university sample was extremely high, even when taking into consideration that the SOGS-R measured problems over a twelve-month period. Higher levels of education are usually associated with lower rates of problem gambling (Abbott & Volberg, 1991; Browne & Brown, 1994; Reid & Searle, 1996). Yet more than four times as many gamblers in the present study were classified as problem gamblers, as compared to representative general population samples in New Zealand and in some other countries, rates comparable to representative samples overseas which included lower educated, troubled and disadvantaged youth (Fisher, 1993; Winters et al., 1995). Like substance abuse, however, over time gambling problems usually decrease (Abbott & Volberg, 2000; Buchta, 1995; Ladouceur et al., 1994; Winters et al., 1993).

All of the hypotheses were supported. As expected, there were significant differences between the problem and non-problem gamblers. The findings were very similar to findings with university students in other countries, indicating that similar variables are operating among New Zealand university students. Converging with previous research in the United States (Browne & Brown, 1994), Canada (Ladouceur et al., 1997), Australia (Steel & Blaszczynski, 1996) and Europe (Hendriks et al, 1997), compared to non-problem gamblers, the problem student gamblers in the present New Zealand sample spent more money on gambling, gambled more frequently and on more activities, were more involved in continuous gambling activities, were more likely to consider that their parents gambled excessively, were more depressed and were stronger on the addictive personality trait.

Problem Gambling and the Addictive Personality

The present study provided some limited support for the possibility of an addictive personality trait in problem gambling. However, it would be only one part of a complex, integrated conceptualisation of problem gambling involving biological, psychological and ecological factors (Blaszczynski & Nower, 2002; Slutske et al., 2001). Blaszczynski and Nower (2002) have proposed an integrated pathways model of problem gambling, based on an extensive review of the literature and empirical research. The pathway to problem gambling begins with ecological factors such as availability and accessibility of gambling activities which are socially accepted, encouraged and promoted. It then continues via classical and operant conditioning with concomitant cognitive schemas of irrational beliefs and illusion of control, resulting in habituation, chasing and unexpected losses, to problem gambling symptoms. While drug addicts are consistently reinforced for their drug-taking behavior, gamblers' steps to addiction are reinforced intermittently and randomly. The gamblers in this group may initially gamble for entertainment or socialization and have the least symptoms.

Another group follows the same path, except that before getting involved in gambling and associated conditioning, they are biologically and emotionally at risk for problem behaviors. Biologically, receptor genes and neurotransmitters are linked to reward deficiency, arousal levels, impulsivity and pathological gambling (Blum et al., 1996; cited in Blaszczynski & Nower, 2002). Eysenck (1997) suggested that addiction may have a biological or genetic basis. Others (Blanco et al., 1996; Shaffer, 1996) also indicated that changes in neurochemistry are involved in addictive gambling. Emotional vulnerability arises from childhood disturbances, boredom proneness, depression and/ or anxiety due to biological and psychosocial deficiencies, and poor coping and problem-solving skills. This group escapes unpleasant physiological states by choosing monotonous gambling activities such as gaming machines to dissociate from their feelings, or by seeking stimulating activities such as increasing bets on horse racing and sports events. They are less likely to change than the first group because of their underlying biological and psychological predispositions toward emotional disturbances. It is this group that may be high on the addiction trait, due to predisposing biological and psychosocial conditions which could lead to various addictive behaviors.

Although the Eysencks' Addiction scale consists of items which do not refer to addiction at all, it seems to be useful for measuring a trait that is present in addiction to drugs and gambling. With further research, it might be applied to other addictions such as shopping, food or sex.


Because the sample consisted of psychology undergraduates, it was not representative of the university students in New Zealand. The findings have been based on data collected from a non-representative sample of well-educated and predominantly female, European New Zealanders living in a large city. Most came from families with average or above average socio-economic status. There were disproportionately fewer Maori (8%) in the sample than in the New Zealand population. Some students may have selected psychology to understand personal problems, including those associated with problem gambling.

Although Addiction contributed significantly to the classification of problem gamblers, the results need to be treated with caution. First, the internal consistency of the Addiction scale was satisfactory, but marginal (.69). Secondly, the size of the problem group was small, resulting in very large confidence intervals. With 95% confidence, the 17% increase in odds of being a problem gambler with each of 32 Addiction points falls between 1% and 36%. Thirdly, the logistic regression did not include interaction effects or demographic variables due to the small number of problem gamblers in the sample. Abbott and Volberg (2000) reported that logistic regression analysis of demographic data from a large, representative Australian national survey revealed that only age, marital status and city living were predictors of problem gambling. Gender, income and education were not significant predictors. The predictors may also be different for different gambling activities (Dickerson, 1993).

The present survey did not examine the prevalence of Internet gambling in the sample. Some authors (e.g., Griffiths & Parke, 2002) have expressed concern that Internet gambling may be conducive to problem gambling, especially for people prone to gambling addiction (Shaffer, 1996). Ladd and Retry (2002) found that among American 389 medical and dental patients treated at university clinics, the 32 Internet gamblers were more likely to be younger, non-Caucasian and have higher SOGS scores than the 367 non-Internet gamblers.

Compulsive gambling > 1 > 2 > 3 > 4 > 5 > 6

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