Recovery from Problem Gambling: A Machine Learning Approach

Files
Problem Gambling Recovery_SEOW 2022_Final.pptx (2.77 MB)
Date
2022-07-29
Authors
Hong, Saahoon
Walton, Betty
Kim, Hea-Won
Language
English
Embargo Lift Date
Department
Committee Members
Degree
Degree Year
Department
Grantor
Journal Title
Journal ISSN
Volume Title
Found At
Abstract

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.

Description
Keywords
Problem gambling, Gambling addiction recovery, Machine learning
item.page.description.tableofcontents
item.page.relation.haspart
Cite As
Hong, 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.
ISSN
Publisher
Series/Report
Sponsorship
This 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).
Major
Extent
Identifier
Relation
Journal
Rights
Source
Alternative Title
Type
Presentation
Number
Volume
Conference Dates
Conference Host
Conference Location
Conference Name
Conference Panel
Conference Secretariat Location
Permanent Link
https://hdl.handle.net/1805/29704
Version
Full Text Available at
This item is under embargo {{howLong}}
Collections
IU School of Social Work Collection