Hill Ryan M, Oosterhoff Benjamin, Kaplow Julie B
Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston.
J Consult Clin Psychol. 2017 Jul;85(7):702-711. doi: 10.1037/ccp0000218. Epub 2017 Apr 17.
Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation.
Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2.
Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation.
These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record
尽管已经确定了大量自杀意念的风险标志物，但在社区环境中前瞻性地识别有自杀意念风险的青少年方面，几乎没有提供指导。本研究通过利用分类树分析（CTA）来填补文献中的这一空白，以提供一个用于筛查有自杀意念风险青少年的决策模型。
参与者为N = 4799名青少年（年龄中位数 = 16.15岁，标准差 = 1.63），他们完成了青少年到成人健康全国纵向研究的第1波和第2波调查。CTA被用于生成一系列决策规则，以识别在第2波调查中有报告自杀意念风险的青少年。
研究结果揭示了3种不同的解决方案，用于识别报告自杀意念的青少年时具有不同的敏感性和特异性。分类树的敏感性范围为44.6%至77.6%。特异性最高但敏感性最低的树基于自杀意念史。敏感性中等且特异性高的树基于抑郁症状、自杀未遂或家人及朋友中的自杀情况以及社会支持。最敏感但特异性最低的树利用了这些因素以及性别、种族、睡眠时间、学校相关因素和未来取向。
这些分类树为社区组织提供了选择，可根据可用资源和要提供的服务模式对自杀意念风险进行大规模筛查。本研究为前瞻性识别有自杀意念风险的青少年提供了一个理论和实证驱动的模型，并对高危青少年的预防性干预具有启示意义。（PsycINFO数据库记录）
