Socio-ecological model of problem gambling: a cross-national comparison on young people in the United States, South Korea, Spain and Finland
Objectives: Problem gambling among young people is an emerging trend across different countries. The online environment particularly offers various possibilities for gambling engagement. Online environment is also potential area for social learning from peers that may also impact gambling behaviors. Yet, there is a lack of studies aiming to understand behavioral and situational factors impacting gambling behavior and development of gambling problems. The aim of this presentation is to build a socio-ecological model of gambling problems among young people.
Method: Empirical evidence is based on cross-national data collected from young people aged 15 to 25 in the United States (N=1212, 50.17% female), South Korea (N=1192, 50.42% female), Spain (N=1212, 48,76 % female) and Finland (N=1200, 50,0% female). Study 1 analyzes risk factors for problem gambling using a cross-sectional design. South Oaks Gambling Screen (SOGS) was used as measure for problem gambling. Covariates include situational measures such as involvement in social media identity bubbles (Identity Bubble Reinforcement Scale, IBRS-6) and exposure to gambling communities, casino sites and pop-up gambling advertisements. Controls included age, gender and personality measures for impulsivity (Eysenck Impulsiveness Scale, EIS) and self-esteem (Single-Item Self-Esteem Scale, SISE). Study 2 examines the relationship between self-reported problem gambling and behavioral measures derived from the experimental design simulating user reactions to gambling messages online. Behavioral measures are conformity to online group norms and user preferences for pro-gambling content and experience-driven content. Controls include age, gender and personality measures.
Results: Study 1 showed that situational factors are strongly tied to problem gambling in all of the countries. These include being exposed to gambling content online (gambling communities, casino sites, pop-up-advertisements) and factors connected to social media usage, especially involvement in a social media bubble. Study 2 showed that problem gambling was more prevalent among young people following online group norms and prioritizing pro-gambling content.
Discussion: The results indicate that there are both situational and social psychological factors that are associated with problem gambling. First of all, being exposed to online gambling content and advertisement could be considered as a major risk factor for problem gambling. Second, online social learning may induce problem gambling as conformity to both online group norms and online bubbles was associated with higher problem gambling. Third, problem gambling was associated with an interest in online gambling promotion. Our models controlled for personality factors (impulsivity and self-esteem) that are also important when considering risk factors for problem gambling. Overall, the findings underline that situational and social-psychological factors are significant in understanding youth problem gambling behavior. It is important to understand the existence of these factors besides the macro-level factors such as gambling legislation.