Abstract

Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting latent class model on a sample of graduate students. Data were collected through the Interactive Screening Program deployed by the American Foundation for Suicide Prevention. LCA identified 6 subgroups from the undergraduate sample (N = 5654). In the group with the most students reporting current suicidal thoughts (N = 623, 66% suicidal), 22.5% reported a prior suicide attempt, and 97.6% endorsed moderately severe or worse depressive symptoms. Notably, LCA identified a second at-risk group (N = 662, 27% suicidal), in which only 1.5% of respondents noted moderately severe or worse depressive symptoms. When graduate students (N = 1138) were classified using the model, a similar frequency distribution of groups was found. Finding multiple replicable groups at-risk for suicidal behavior, each with a distinct prevalence of risk factors, including a group of students who would not be classified as high risk with depression-based screening, is consistent with previous studies that identified multiple potential etiologies of SB.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.