Hong, SaahoonWalton, Betty A.Kim, Hea-Won2022-01-242022-01-24202-01-15Hong, S., Walton, B., & Kim, H. (2022, January). The Intersectionality of Gambling Addiction Recovery and Mental Illness: A Machine Learning Approach. Poster presented at the Society for Social Work and Research (SSWR) 2022 Conference, Washington, DC.https://hdl.handle.net/1805/27547A 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. en-USProblem gamblingGambling addiction recoveryMachine learningPoster