预测南非大学生的自杀风险:流行病学研究中心抑郁量表的最佳分值

T. Pretorius, A. Padmanabhanunni
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引用次数: 0

摘要

由于COVID-19预防措施对教育部门的独特影响,大学生被确定为心理健康不良后果的特别脆弱群体。甚至在大流行之前,就已确定大学生面临不良心理健康结果和自杀的风险增加。虽然各种因素都能增加自杀的风险,但其中一个最有力的自杀预测因素是抑郁症状的出现。目前的研究使用受试者工作特征(ROC)分析来确定在南非COVID-19期间筛查大学生自杀风险时CES-D的最佳截止分数。参与者(n = 337)是南非一所历史上处境不利的大学的学生。ROC分析显示,男性和女性的曲线下面积(AUC)无统计学差异;因此,单个AUC可用于整个样品。研究发现,截断值为30,灵敏度为89.30,特异性为62.60,即为可接受的截断点。建议在学生群体中使用该工具时,那些得分在30分及以上的学生需要通过临床医生管理的访谈进行随访,以确认自杀风险并促进及时干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Suicide Risk among South African University Students: Optimal Cutoff Score for the Center for Epidemiological Studies Depression Scale
University students have been identified as a particularly vulnerable group for adverse mental health outcomes owing to the distinctive implications of the COVID-19 prevention measures on the educational sector. Even prior to the pandemic, university students were identified as being at increased risk for adverse mental health outcomes and suicidality. Although various factors can enhance the risk of suicide, one of the strongest predictors of suicidality is the presence of depressive symptomology. The current study used receiver operating characteristic (ROC) analysis to determine the optimal cutoff score on the CES-D when screening for suicide risk in university students during COVID-19 in South Africa. Participants (n = 337) were students at a historically disadvantaged university in South Africa. The ROC analysis showed no statistically significant difference between men’s and women's area under the curve (AUC); thus, a single AUC can be used for the whole sample. The study found that a cutoff score of 30 with a sensitivity of 89.30 and a specificity of 62.60 represented an acceptable cutoff point. It is recommended that when the instrument is used among student populations, those with scores of 30 and above need to be followed up with a clinician-administered interview to confirm suicide risk and facilitate timely intervention.
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