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高校学生自杀意念和行为:潜在类别分析。

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

机构信息

Department of Psychiatry, Columbia University, NY, USA; New York State Psychiatric Institute, NY, USA.

Department of Psychiatry, Columbia University, NY, USA; Department of Biostatistics, Columbia University, NY, USA.

出版信息

J Psychiatr Res. 2017 Dec;95:253-259. doi: 10.1016/j.jpsychires.2017.09.003. Epub 2017 Sep 9.

DOI:10.1016/j.jpsychires.2017.09.003
PMID:28923719
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5826724/
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.

摘要

自杀是大学生的第二大死因,年发生率为每 10 万人中有 7.5 人。自杀行为(SB)是复杂和异质的,这可以用 SB 的多种病因来解释。通过数据驱动的方法在大学生中识别出不同的高危亚组,可以支持这一观点。我们对来自一个大型便利样本的大学生调查数据进行了潜在类别分析(LCA),以确定亚组,并在研究生样本上验证了由此产生的潜在类别模型。数据是通过美国自杀预防基金会部署的互动筛查计划收集的。LCA 从本科生样本中识别出 6 个亚组(N=5654)。在报告当前自杀想法的学生比例最高的组(N=623,66%有自杀想法)中,22.5%的人报告曾有过自杀企图,97.6%的人有中度或更严重的抑郁症状。值得注意的是,LCA 还识别出第二个高危亚组(N=662,27%有自杀想法),其中只有 1.5%的受访者有中度或更严重的抑郁症状。当使用该模型对研究生(N=1138)进行分类时,发现了具有相似组频率分布的组。发现多个可复制的有自杀行为风险的群体,每个群体都有不同的风险因素发生率,包括一个不会被基于抑郁的筛查分类为高风险的学生群体,这与之前确定 SB 多种潜在病因的研究一致。

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