Department
School of Data Science and Analytics
Document Type
Article
Publication Date
7-4-2022
Abstract
Rising rates of suicide over the past two decades have increased the need for wide-ranging suicide prevention efforts. One approach is to target high-risk groups, which requires the identification of the characteristics of these population sub-groups. This suicidology study was conducted using large-scale, secondary data to answer the question: using the research on suicide, are there variables studied at the community level that are linked to suicide and are measurable using quantitative, demographic data that are already collected and updated? Data on deaths from suicide in U.S. counties for the years 2000, 2005, 2010 and 2015 were analyzed using multiple regression, longitudinal regression, and cluster analysis. Results indicated that the suicide rate in a county can be predicted by measuring the financial stability of the residents, the quality of mental health in the county, and the economic opportunity in the county. The results are further analyzed using two sociological theories, Social Strain Theory and the Theory of Anomie, and two psychological theories, the Shame Model and the Interpersonal Theory of Suicide.
Journal Title
International Journal of Environmental Research and Public Health
Journal ISSN
1660-4601
Volume
19
Issue
13
Digital Object Identifier (DOI)
10.3390/ijerph19138173
Comments
This article received funding through Kennesaw State University's Faculty Open Access Publishing Fund, supported by the KSU Library System and KSU Office of Research.