Recovery from Problem Gambling: A Machine Learning Approach

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dc.contributor.authorHong, Saahoon
dc.contributor.authorWalton, Betty
dc.contributor.authorKim, Hea-Won
dc.date.accessioned2022-08-02T16:38:03Z
dc.date.available2022-08-02T16:38:03Z
dc.date.issued2022-07-29
dc.description.abstractThe 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.en_US
dc.description.sponsorshipThis study was developed through a collaborative effort by the IU School of Social Work , IU Racial Justice Research Fund (RJRF), and FSSA's Division of Mental Health and Addiction (DMHA).en_US
dc.identifier.citationHong, S., Walton, B., & Kim, H. (2022, July 29). Recovery from Problem Gambling: A Machine Learning Approach. Paper presented at the State Epidemiological Outcomes Workgroup (SEOW) 2022 Bimonthly Meeting, Indianapolis, IN.en_US
dc.identifier.urihttps://hdl.handle.net/1805/29704
dc.language.isoenen_US
dc.subjectProblem gamblingen_US
dc.subjectGambling addiction recoveryen_US
dc.subjectMachine learningen_US
dc.titleRecovery from Problem Gambling: A Machine Learning Approachen_US
dc.typePresentationen_US
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