Forms of Gambling, Gambling Involvement and Problem Gambling: Evidence from a Swedish Population Survey (Binde, Romild, & Volberg, 2017)

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Full citation

Binde, P., Romild, U., & Volberg, R. A. (2017). Forms of gambling, gambling involvement and problem gambling: Evidence from a Swedish population survey. International Gambling Studies, 17(3), 490–507. https://doi.org/10.1080/14459795.2017.1360928

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Region & Target Population

• ‍Region: Sweden‍
• Target population: General population aged 16–84 years
• Relevance to emerging adults: Includes 16–25-year-olds, with young adults forming a meaningful subgroup within the nationally representative sample‍
• Context: Legal, regulated gambling market with wide availability of lotteries, sports betting, EGMs, poker, casino games, and bingo

Study Design‍

• ‍Cross-sectional population survey, secondary analysis
• Based on Wave 1 of the Swedish Longitudinal Gambling Study (Swelogs)‍
• Designed explicitly to test competing explanations of gambling harm:
  
  • Product-specific risk
  • Gambling involvement (number of forms)
  • Gambling intensity (time and money)

Sample Characteristics (with data-collection years)

• ‍Total Swelogs Wave 1 sample: 8,165 respondents‍
• Analytic sample: n = 4,991 individuals who had gambled at least once in the past year‍
• Age range: 16–84 years‍
• Problem gambling prevalence: 1.5% classified as problem gamblers (PGSI ≥ 5)‍
• Data collection period: 2008–2009

Cross-Form Structure & Analytical Logic

• The study explicitly separates three related but distinct concepts:‍
  
  • Forms of gambling (e.g., EGMs, sports betting, lotteries)‍
  • Gambling involvement (number of forms played)‍
  • Gambling intensity (time and money spent)
• Tests four hypotheses:
  
  • Some forms are more strongly associated with problem gambling than others
  • Higher involvement predicts problem gambling
  • Involvement is linked to higher intensity
  • The involvement–harm relationship depends on which forms are played
  • Uses non-parametric statistics due to skewed distributions

Measures Used‍

• ‍Problem gambling:‍
  
  • Problem Gambling Severity Index (PGSI), 9-item scale
  • Cut-off: PGSI ≥ 5 for problem gambling‍
• Gambling forms:‍
  
  • Lotteries / number games
  • Sports betting
  • Horse betting
  • Poker
  • Electronic Gaming Machines (EGMs)
  • Casino table games
  • Bingo‍
• Gambling involvement: Number of different forms played (past year and monthly+)‍
• Gambling intensity:‍
  
  • Money spent (past 30 days)
  • Time spent gambling (past 30 days)

Research Questions

1. Are some forms of gambling more closely associated with problem gambling than others?
2. Is gambling involvement (number of forms) positively associated with problem gambling?
3. Is gambling involvement associated with greater gambling intensity?
4. Does the relationship between involvement and problem gambling depend on the specific gambling forms involved?

Key Findings‍

‍Form-specific risk‍

• The proportion of problem gamblers differed markedly by gambling form.‍
• Highest problem-gambling prevalence among:
  
  • Electronic Gaming Machines (EGMs)
  • Casino games
  • Bingo
  • Poker
• Among regular players, PG prevalence reached:
  • 13–19% for EGMs, casino games, and bingo
• Lotteries, number games, and horse betting showed substantially lower PG prevalence.‍

Gambling involvement:

• Gambling involvement was strongly associated with problem gambling
• Risk increased sharply with the number of forms played:
  
  • 3× higher PG prevalence at 5 forms64
  • Approzx.14× higher at 7–8 forms‍

Intensity‍

• Gambling involvement correlated strongly with Money and Time spent gambling
• Intensity acts as a key mechanism linking involvement and harm.‍

Interaction between form and involvement

• ‍EGMs showed consistently high PG prevalence at all levels of involvement.
• For other forms, PG prevalence increased mainly as involvement increased.
• At very high involvement (5+ forms), PG prevalence converged across forms

9. Study Conclusion

The authors conclude that problem gambling cannot be explained by involvement alone, nor by product choice alone. Instead, gambling harm emerges through a structured interaction between product characteristics, involvement, and intensity. Crucially, the study demonstrates that:

• Some gambling forms, especially EGMs and casino-style games are intrinsically more harmful, showing elevated risk even at low involvement.
• High involvement increases risk largely because it drives greater intensity, but many problem gamblers concentrate their play on one or two high-risk products.
• Regulatory and harm-reduction strategies should therefore prioritize high-risk gambling forms, rather than focusing exclusively on reducing overall participation.

The authors explicitly argue against treating all gambling products as equivalent and emphasize that effective policy must be product-sensitive, not just behaviorally generic.