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Title: Analyzing Social Factors to Enhance Suicide Prevention Across Population Groups
Social factors like family background, education level, financial status, and stress can impact public health outcomes, such as suicidal ideation. However, the analysis of social factors for suicide prevention has been limited by the lack of up-to-date suicide reporting data, variations in reporting practices, and small sample sizes. In this study, we analyzed 172,629 suicide incidents from 2014 to 2020 utilizing the National Violent Death Reporting System Restricted Access Database (NVDRS-RAD). Logistic regression models were developed to examine the relationships between demographics and suicide-related circumstances. Trends over time were assessed, and Latent Dirichlet Allocation (LDA) was used to identify common suiciderelated social factors. Mental health, interpersonal relationships, mental health treatment and disclosure, and school/work-related stressors were identified as the main themes of suicide-related social factors. This study also identified systemic disparities across various population groups, particularly concerning Black individuals, young people aged under 24, healthcare practitioners, and those with limited education backgrounds, which shed light on potential directions for demographic-specific suicidal interventions.  more » « less
Award ID(s):
2505865
PAR ID:
10631172
Author(s) / Creator(s):
; ; ; ; ; ; ; ; ; ;
Publisher / Repository:
IEEE
Date Published:
ISBN:
979-8-3503-8373-7
Page Range / eLocation ID:
189 to 199
Format(s):
Medium: X
Location:
Orlando, FL, USA
Sponsoring Org:
National Science Foundation
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