Social Ecological Model of Problem Gambling: A Cross-National Survey Study of Young People (Oksanen et al., 2021)

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Full citation

Oksanen, A., Sirola, A., Savolainen, I., Koivula, A., Kaakinen, M., Vuorinen, I., Zych, I., & Paek, H.-J. (2021). Social ecological model of problem gambling: A cross-national survey study of young people in the United States, South Korea, Spain, and Finland. International Journal of Environmental Research and Public Health, 18, 3220. https://doi.org/10.3390/ijerph18063220

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Region & Target Population

• ‍Regions: United States, South Korea, Spain, Finland‍
• Population: Young people aged 15–25

Study Design

• ‍Cross-sectional, cross-national survey study‍
• Explicitly structured around a social ecological model, testing four nested spheres:

1. Intrapersonal
2. Interpersonal
3. Organizational
4. Societal

Sample Characteristics (with data-collection years)

• ‍Total sample: N = 4,816 young people aged 15–25
• Finland: n = 1,200 (data collected 2017)
  
  • United States: n = 1,212 (2018)
  • South Korea: n = 1,192 (2018)
  • Spain: n = 1,212 (2019)‍
• Gender: Approximately 50% male in each country‍
• Mean age:‍
  
  • Finland: 21.29
    
  • United States: 20.05
  • South Korea: 20.61
  • Spain: 20.07

Measures Used

• ‍Problem gambling: South Oaks Gambling Screen (SOGS), continuous score (0–20) and ≥8 cutoff for disordered gambling‍
• Intrapersonal sphere:‍
  
  • Gender, age
  • Impulsivity (Eysenck Impulsivity Scale)
  • Self-esteem (single item)
  • Risk-taking (single item)
• Interpersonal sphere:‍
  
  • Perceived social support
  • Offline and online belonging
  • Social media identity bubble involvement
  • Conformity to group norms (experimental social-media task)‍
• Organizational sphere:‍
  
  • Consumer debt (including payday loans)
  • Online casino participation
  • Online gambling community participation
  • Exposure to online pop-up gambling advertisements
• ‍Societal sphere: Country-level differences (macro context only)

Research Questions

1. How well do intrapersonal, interpersonal, organizational, and societal spheres explain problem gambling among young people aged 15–25?
2. Which social ecological spheres account for the greatest variance in problem gambling?
3. Are these associations consistent across different national and regulatory contexts?

Key Findings

• ‍Prevalence:‍
  
  • Using SOGS ≥8, 3.84% of the full sample met criteria for disordered gambling.
  • Prevalence was highest in Spain (6.27%) and lowest in South Korea (1.76%) ijerph-18-03220-v2
• ‍Explained variance by sphere:‍
• ‍Organizational sphere: 26–27% of variance (strongest)‍
• Intrapersonal sphere: 11%‍
• Interpersonal sphere: 5%‍
• Societal sphere: 3%‍
• Strongest predictors across all countries:‍
  
  • Online gambling community participation
  • Male gender
  • Impulsivity‍
• Other consistent organizational risks:‍
  
  • Online casino participation
  • Consumer debt
  • Weekly exposure to pop-up gambling advertisements
• ‍Cross-national consistency:‍
• Direction and strength of key predictors were highly similar across all four countries, despite large regulatory differences.

Study Conclusion

The authors conclude that the social ecological model is a useful and effective framework for understanding problem gambling among young people across different cultural and regulatory contexts. Their findings show that organizational-level factors related to the online gambling environment explain substantially more variance in problem gambling than individual or interpersonal factors.

In particular, online gambling communities emerged as the single strongest correlate of problem gambling in all four countries, surpassing traditional individual-level risk factors. These communities were primarily oriented toward gambling tips and shared gambling experiences rather than harm reduction or recovery, which the authors argue may reinforce pro-gambling norms and behaviors. The authors further conclude that problem gambling among young people shows more similarities than differences across countries, suggesting that the online gambling environment produces convergent risk pathways despite national differences in legislation and culture. While intrapersonal factors such as male gender and impulsivity remain important, the study emphasizes that digital infrastructure, online gambling platforms, advertising exposure, and access to consumer credit are central drivers of gambling harm in adolescents and emerging adults.

The authors argue that prevention and policy responses should move beyond individual-level interventions and explicitly address online gambling communities, advertising practices, online casinos, and easy access to consumer debt, and they recommend continued use of the social ecological model in future gambling research and regulation.