Distinguishing Between Gaming and Gambling Activities in Addiction Research (King et al., 2015)

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Full citation

King, D. L., Gainsbury, S. M., Delfabbro, P. H., Hing, N., & Abarbanel, B. (2015). Distinguishing between gaming and gambling activities in addiction research. Journal of Behavioral Addictions, 4(4), 215–220. https://doi.org/10.1556/2006.4.2015.045

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Region & Target Population

• ‍Region: Conceptual and international (not country-specific)‍
• Target population:‍
  
  • Players of digital gaming, gambling, and hybrid gambling-like activities
  • Strong relevance to adolescents and emerging adults (18–25), who are disproportionately exposed to:
    
    • Social casino games
    • Simulated gambling
    • Loot boxes, virtual currencies, and gambling-like monetization systems

Study Design

• Narrative conceptual review synthesis of:
  
  • Psychological research
  • Regulatory definitions
  • Industry practices
• Develops a structural-feature typology to distinguish gaming from gambling
• Introduces a practical checklist tool for classifying digital activities

Sample Characteristics (with data-collection years)

• ‍No empirical participant samples‍
• Evidence base drawn from:
  
  • Prior gambling and gaming studies (2004–2014)
  • Industry reports (e.g., Morgan Stanley, 2012)
  • Regulatory documents and classification frameworks
• Examples used to illustrate typology:‍
  
  • Zynga Poker (social casino game)‍
  • Red Dead Redemption (console game with simulated gambling)‍
  • myVegas Slots (social casino game with loyalty rewards)

Conceptual Comparison Framework & Logic

The authors distinguish gaming and gambling using nine structural dimensions, rather than labels

or surface appearance:‍

1. ‍Interactivity
2. Monetization level (free, purchasable, financially redeemable)‍
3. Betting / wagering mechanics
4. Role of skill vs chance
5. Nature of outcomes (non-financial vs financial)‍
6. Structural fidelity to real gambling
7. ‍Context (stand-alone vs embedded in gambling ecosystems)
8. ‍Centrality of gambling within the activitY
9. ‍Advertising and cross-promotion

This framework explicitly addresses hybrid products that distort gaming–gambling boundaries.

Measures Used

• ‍Not a measurement study, but introduces a classification checklist‍
• Checklist evaluates whether an activity contains:
  
  • Betting mechanics
  • Financial risk
  • Redeemable value
  • Gambling-like structural fidelity
• Designed for use by:
  
  • Researchers (classification and prevalence estimation)
  • Clinicians (screening and diagnosis)
  • Policymakers (regulation and consumer protection)

Research Questions

1. What core structural features meaningfully distinguish gambling from gaming?
2. How do hybrid digital products challenge existing diagnostic and regulatory categories?
3. How can addiction research avoid misclassifying gambling-like gaming activities?

Key Findings

• ‍Structural features matter more than labels:‍
  
  • Many activities marketed as “games” contain core gambling mechanics (betting, chance, monetization).‍
• Financial payout is central but insufficient alone:‍
  
  • Even without direct cash-out, activities with wagering mechanics and purchasable currency may function psychologically like gambling.‍
• Hybrid products create classification failures:‍
  
  • Social casino games and simulated gambling can evade gambling regulation while producing gambling-like harms.‍
• Emerging adults are uniquely exposed:‍
  
  • Young adults frequently engage with:
  • Social casino games
  • Simulated gambling
  • Virtual currencies and loot-box-like systems‍
• Diagnostic ambiguity:‍
  
  • Problematic engagement with simulated gambling may not meet formal “gambling disorder” criteria, despite clear harm.‍
• Regulatory blind spots:‍
  
  • Advertising, loyalty systems, and cross-promotion link “games” directly to real money gambling ecosystems.

Study Conclusion

The authors conclude that gambling harm in the digital era cannot be understood through binary categories of “gaming” versus “gambling.” Instead, harm emerges from specific structural features such as betting mechanics, monetization systems, chance-based outcomes, and advertising integration—that increasingly co-exist within hybrid products. For emerging adults (18–25), this convergence is particularly consequential. Young people are routinely exposed to gambling-like mechanics long before entering regulated gambling spaces, normalizing risk-taking, wagering, and monetized chance within entertainment contexts. The authors argue that continuing to classify such activities simply as “games” risks systematically underestimating gambling-related harm in younger populations. They recommend that future research, prevention, and regulation focus on design features rather than product labels, using structural checklists to identify risk. This approach is especially critical for understanding modern gambling trajectories, where emerging adults transition seamlessly between gaming, simulated gambling, and real-money gambling within a single digital ecosystem.