Browsing by Subject "Problem gambling"

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    The intersectionality of gambling addiction recovery and mental illness: A machine learning approach 
    (Society for Social Work and Research 26th Annual Conference, 202-01-15) Hong, Saahoon; Walton, Betty A.; Kim, Hea-Won
    A machine learning algorithm identified that struggling with substance use, impulse control, education, and resourcefulness was the significant barriers to improvement from problem gambling in state-funded behavioral health services.  Interestingly, White adults were more likely to be improved from problem gambling than their peers of color. The machine learning-based gambling addiction recovery model could be a promising approach to detect the intersection of race/ethnicity, behavioral health challenges, and their improvement from problem gambling. It could eventually be a basis for developing a gambling addiction recovery model for adults with needs for gambling addiction treatment at the initial assessment. Such a relationship study will support the development of an efficient mental health and gambling recovery model. 
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    Recovery from Problem Gambling: A Machine Learning Approach
    (2022-07-29) Hong, Saahoon; Walton, Betty; Kim, Hea-Won
    The primary purpose of this study was to examine and identify intersections of the first wave of the COViD-19 pandemic, behavioral health needs/strengths, demographic characteristics, and recovery from problem gambling. By analyzing Adult Needs and Strengths Assessment (ANSA) datasets, we identified critical factors associated with improvement from problem gambling. In addition, we discussed risk factors that led to the continued struggling with problem gambling.