Risk Factors for the Transition from Suicide Ideation to Suicide Attempt: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)
Risk Factors for the Transition from Suicide Ideation to Suicide Attempt: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)
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DOI：
10.1037/abn0000317
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发表时间：
2018-02-01
影响因子：
4.6
通讯作者：
Kessler, Ronald C.
中科院分区：
文献类型：
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作者：
Nock, Matthew K.;Millner, Alexander J.;Kessler, Ronald C.
先前的研究表明，一般人群中大多数已知的自杀企图风险因素实际上预测了自杀意念，而不是自杀者的企图。然而，临床上对预测自杀企图的兴趣往往涉及对有意念患者的风险评估。我们在一项回顾性分析中研究了自杀想法的一些特征，这些特征被假设为预测事件企图，这些自杀想法来自一个大型（N = 29,982）的美国陆军士兵代表性样本。在控制先前已知的预测因子（例如，人口统计学、精神障碍）是：最近开始的想法，存在和最近开始的自杀计划，自杀想法的低可控性，极端冒险或“冒险”，以及未能回答有关自杀想法特征的问题。使用这些风险因素的预测模型具有很强的准确性（曲线下面积[AUC] = 0.93），所有事件自杀企图中有66.2%发生在5%具有最高复合预测风险的士兵中。这项回顾性研究中的高风险集中表明，可以从前瞻性数据中构建一个有用的临床决策支持模型，以识别那些随后自杀企图风险最高的患者。
Prior research has shown that most known risk factors for suicide attempts in the general population actually predict suicide ideation rather than attempts among ideators. Yet clinical interest in predicting suicide attempts often involves the evaluation of risk among patients with ideation. We examined a number of characteristics of suicidal thoughts hypothesized to predict incident attempts in a retrospective analysis of lifetime ideators (N = 3,916) drawn from a large (N = 29,982), representative sample of United States Army soldiers. The most powerful predictors of first nonfatal lifetime suicide attempt in a multivariate model controlling for previously known predictors (e.g., demographics, mental disorders) were: recent onset of ideation, presence and recent onset of a suicide plan, low controllability of suicidal thoughts, extreme risk-taking or "tempting fate," and failure to answer questions about the characteristics of one's suicidal thoughts. A predictive model using these risk factors had strong accuracy (area under the curve [AUC] = .93), with 66.2% of all incident suicide attempts occurring among the 5% of soldiers with highest composite predicted risk. This high concentration of risk in this retrospective study suggests that a useful clinical decision support model could be constructed from prospective data to identify those with highest risk of subsequent suicide attempt.