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Burdensomeness, depression, and suicide in a sample of American-Indian college students

Purpose – The interpersonal theory of suicide (ITS; Joiner, 2005) has gained empirical support as a framework for understanding why people die by suicide in the general population, and more recently, among American Indians (AIs). The purpose of this paper is to examine two key constructs of the theo...

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Published in:Ethnicity and inequalities in health and social care 2013-04, Vol.6 (2/3), p.77-86
Main Authors: Cole, Ashley B, Wingate, LaRicka R, Slish, Meredith L, Tucker, Raymond P, Hollingsworth, David W, O'Keefe, Victoria M
Format: Article
Language:English
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Summary:Purpose – The interpersonal theory of suicide (ITS; Joiner, 2005) has gained empirical support as a framework for understanding why people die by suicide in the general population, and more recently, among American Indians (AIs). The purpose of this paper is to examine two key constructs of the theory, perceived burdensomeness and thwarted belongingness as mediators of depression and suicidal ideation within an AI sample. Design/methodology/approach – In all, 156 self-identified AI students completed measures of depression symptoms, thwarted belongingness, perceived burdensomeness, and suicidal ideation online. Non-parametric bootstrapping procedures were conducted. Findings – Results of bootstrapping analyses indicated that perceived burdensomeness had an indirect effect on the relationship between symptoms of depression and suicidal ideation; however, thwarted belongingness did not demonstrate an indirect effect between symptoms of depression and suicidal ideation. Findings suggest that the ITS construct of perceived burdensomeness may be relevant for the study of AI suicide. Implications for targeting perceptions of burdensomeness in preventative efforts against suicide among AIs are discussed. Originality/value – This is the first study to examine perceived burdensomeness and thwarted belongingness as mediators of symptoms of depression and suicidal ideation in a sample of AI participants.
ISSN:1757-0980
2056-4902
2056-4910
DOI:10.1108/EIHSC-10-2013-0026