The ALSPAC Gambling Study

Gambling is the act of placing a value on an event that has a random chance of success or failure. There are several ways to gamble, including playing a game of chance, betting on horse races or other sports, or using virtual casino games like online slots. Regardless of the type of gambling, it can be addictive and have negative psychological, personal, social, and professional consequences.

People may gamble as a way to self-soothe unpleasant feelings, such as depression or anxiety, or to relieve boredom. They may also gamble to make money or to socialize with others. They can also become superstitious about their gambling, believing that they have a higher chance of winning if they play a certain game or make a certain move.

Problem gambling is an impulse control disorder that can have serious psychological, personal, financial, and social consequences. It is classified as such in the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM).

Although there are many different causes of gambling problems, researchers have identified some risk factors. These include the presence of a family history of gambling, depression and other mood disorders, alcohol use disorder, a family environment that encourages gambling, low levels of education, and a low socioeconomic status. People who are addicted to gambling often feel compelled to continue their behavior despite losses, and they may even lie about their gambling activity or steal money in an attempt to fund their addiction.

The ALSPAC gambling study is unique in that it provides longitudinal data on the prevalence of gambling at various ages. It also includes information on parental gambling activity. Compared with participants who did not participate in the gambling surveys at age 17, 20 and 24 years, non-responders were more likely to be male, have hyperactivity and conduct disorders, higher sensation seeking scores, be unemployed or not in education, and have mothers with lower educational qualifications. Multiple imputation techniques were used to address the issue of missing data on antecedents, and only those variables associated at each time point with gambling were included in multivariable models. The results are shown in Table 1.