Youngstrom Eric A
PhD, Department of Psychology, University of North Carolina at Chapel Hill, Davie Hall CB 3270, Chapel Hill, NC 27599-3270, USA.
J Pediatr Psychol. 2014 Mar;39(2):204-21. doi: 10.1093/jpepsy/jst062. Epub 2013 Aug 21.
To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder.
Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews.
Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4.
This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.
通过使用一份广为人知的家长清单来评估潜在的情绪障碍，对接受者操作特征（ROC）分析、诊断效率统计及其在临床决策中的应用进行实际演示。
对589个寻求门诊心理健康服务、完成儿童行为清单和半结构化诊断访谈的家庭的数据进行二次分析。
内化问题原始分数对情绪障碍的区分能力明显优于年龄和性别标准化T分数或情感问题分数。内化分数<8时诊断似然比<0.3，分数>30时诊断似然比为7.4。
本研究阐述了定义临床问题、将其操作化、选择有效研究设计以及使用ROC分析生成支持临床决策的统计数据的一系列步骤。ROC框架为临床解释提供了重要优势。附录包括使用SPSS和R检查假设并进行ROC分析的示例脚本。
