Applying the DSM-5 Criteria for Gambling Disorder to Online Gambling Account-Based Tracking Data: An Empirical Study...

Area of Science:

• Behavioral Psychology
• Digital Health
• Addiction Research

Background:

• Online gambling growth necessitates harm reduction strategies.
• Identifying gambling disorder markers is crucial for intervention.
• Existing methods often rely on self-reporting, which can be unreliable.

Purpose of the Study:

• To operationalize the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria for gambling disorder using online gambling transaction data.
• To identify distinct gambler typologies based on behavioral metrics.
• To propose a data-driven approach for online gambling operators to identify individuals at risk of gambling disorder.

Main Methods:

• Analysis of anonymized, three-month gambling activity data from 982 online gamblers.
• Operationalization of DSM-5 criteria using metrics such as customer service contacts, gambling duration, deposit patterns, responsible gambling tool usage, and bonus requests.
• Application of cluster analysis to categorize gamblers into distinct groups.

Main Results:

• Most DSM-5 gambling disorder criteria can be operationalized using transaction data.
• Cluster analysis identified four gambler types: non-problem, at-risk, financially vulnerable, and emotionally vulnerable gamblers.
• This approach offers a method for identifying problem gamblers through their actual behavior.

Conclusions:

• Online gambling transaction data provides a viable method for operationalizing gambling disorder criteria.
• Behavioral typologies can be identified, aiding in targeted harm reduction.
• This data-driven strategy can help operators proactively identify and support at-risk gamblers, reducing reliance on self-report.