Every year the ICRG offers webinars on the latest research on gambling disorder and responsible gambling. Treatment providers can earn continuing education hours approved by various agencies. Best of all, the webinars are free—thanks to the generosity of the American Gaming Association and Global Gaming Expo! Next Webinar: June 27, 2023 2-3:30 p.m. Eastern […]
In video games, a loot box is a consumable virtual item which can be redeemed. Studies have shown a link between loot box engagement and gambling problems. However, the causal connections are unknown. Dr. Clark will report on his longitudinal research that traced the migration from video games to gambling.
Early detection and intervention could make a big difference in helping people with gambling disorder, which often goes undiagnosed and untreated. However, there is low awareness about how or why to expand screening for Gambling Disorder. One U.S. national study from Harvard Medical School reported that although none of those who were identified as meeting lifetime diagnostic criteria for Gambling Disorder reported seeking treatment for those problems, about half were involved in behavioral treatment for other psychiatric problems. This tells us that expanding screening for Gambling Disorder could improve identification of gambling problems and increase the rate of treatment-seeking among people with this disorder.
Dr. Whelshula has worked extensively with Native American communities nationwide on local and national policy development, education and behavioral health. Her most recent work is the development of an integrative cultural healing model to address trauma, mental health, and substance use disorders for tribes. She is a citizen of the Arrow Lakes Nation of the Colville Indian Reservation in Washington state.
Responsible gambling (RG) algorithms appear to have become more complex and nuanced over time, with “AI” and “machine learning” serving as buzz words to signal their legitimacy. However, no matter how complex our models, they are only as valid as the data and outcomes upon which they are built and validated. This talk entreats the audience to return to basics and consider both the building blocks and pitfalls of RG algorithms. The talk will touch on the outcomes used to validate and evaluate these algorithms, how we distinguish involvement from risk for problems, potential algorithmic biases, and the proper use of algorithms within a larger RG system.
