Scientists Map Risk Factors in Online Gambling as Digital Operators Expand

08 October 2026

As online gambling continues to expand, researchers are identifying more specific risk factors and behavioral patterns that may signal harm.

The most consistent population-level risk factors across studies include young age, male gender, marital status, education level, income source, and experiencing social stressors such as divorce, retirement, or a loved one's death. According to a 2024 meta-analysis in *Addiction*, young age and male gender are the top demographic risk factors for problem gambling worldwide.

But it's not just about who gambles online, but how they do it. Frequent gambling, especially with high intensity and variability, is a key behavioral risk factor. Using gambling to cope with psychological distress, and having an impulsive or emotionally dysregulated gambling style, may also signal escalating risk.

A 2024 longitudinal study of online sports bettors, published in *Frontiers in Psychiatry*, identified substance use, stress, and mental health comorbidity as risk factors for escalating gambling behavior over time. Younger men, in particular, were more likely to demonstrate risky gambling patterns, matching previous research.

The practical implications are clear: demographic risk markers can help target education and prevention efforts, while identifying behavioral risk signals may provide more immediate indications of harm. Operators increasingly have access to player data that can detect these patterns and lead to intervention.

Common behavioral markers associated with higher risk in online gambling include:

* no deposits or declined transactions * removing or easing responsible gambling settings * repeated deposits within single sessions * chasing bonus offers * depleting accounts during play * gambling alone or during unusual hours

A 2025 Springer study of 1,743 online casino gamblers in multiple countries found that self-exclusions, frequent in-session deposits, and account depletion were especially strong predictors of self-reported problem gambling. Machine learning improved the accuracy of these predictive markers.

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The same study showed that some product types have higher risk, such as slots, in-play betting, and certain combination bets. Slot machines are fast-paced, high-intensity games that may encourage escalating risk. In-play sports betting aligns with emotional stress. And high-stakes games can prompt players to chase losses quickly.

Expanding gambling access also seems to come with increasing risk.

The convenience and immersion of mobile gambling, and the constant availability of 24/7 online gambling, may in and of themselves be significant risk drivers. Further, people experiencing socioeconomic disadvantage or discrimination could also face higher gambling risk and more severe harms.

The joint Council of Europe/UN World Tourism Organization expert report on responsible gambling emphasizes the need to integrate protective mechanisms and interventions into the broader regulatory framework for digital gambling. Recommendations include improving access to evidence-based tools, mandating harmonized responsible gambling measures, and addressing gambling harms in public health policy.

Online gambling operators should focus on newer methods for predicting and mitigating gambling-related harm, beyond standard responsible gambling tools. These companies should work more closely with researchers to share and analyze gambling data in ways that produce valid, generalizable evidence, rather than proprietary findings.

When done with public health in mind, this research can directly lead to real-world impact and improvement, supporting the field's ultimate mission.

The full impact of the rapidly evolving digital gaming and gambling landscape is still unknown, but current evidence suggests a need for continued rigorous research and robust public health coordination to protect vulnerable populations.