Measuring strengths and weaknesses in dimensional psychiatry
Measuring strengths and weaknesses in dimensional psychiatry
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DOI：
10.1111/jcpp.13104
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发表时间：
2019-08-18
影响因子：
7.6
通讯作者：
Milham, Michael P.
中科院分区：
文献类型：
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作者：
Alexander, Lindsay M.;Salum, Giovanni A.;Milham, Michael P.
正常行为扩展优势和劣势评估（E-SWAN）将DSM-5所选障碍的每一个诊断标准重新定义为一种行为，其范围可以从高（优势）到低（劣势）。最初的发展集中在恐慌症、社交焦虑、重度抑郁症和破坏性情绪失调障碍。方法收集523名6-17岁参与者的资料。家长完成了四个E-SWAN量表和传统的单向量表，以解决相同的障碍。采用分布特性、项目反应理论分析（IRT）和受试者工作特征（ROC）曲线评估和比较E-SWAN量表与传统量表的表现。结果与传统量表呈截形分布不同，E-SWAN量表均呈对称分布。IRT分析表明，E-SWAN子量表提供了整个人口分布中被调查者的可靠信息；传统的量表只提供了分布中高端受访者的可靠信息。DSM-5诊断的预测值与先前的量表相当。结论E-SWAN双向量表能全面反映DSM障碍行为的人群分布。提供的额外信息可以更好地为人群研究中的个体间差异检查提供信息，并有助于确定临床样本中与恢复力相关的因素。
Background The Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN) reconceptualizes each diagnostic criterion for selected DSM-5 disorders as a behavior, which can range from high (strengths) to low (weaknesses). Initial development focused on Panic Disorder, Social Anxiety, Major Depression, and Disruptive Mood Dysregulation Disorder. Methods Data were collected from 523 participants (ages 6-17). Parents completed each of the four E-SWAN scales and traditional unidirectional scales addressing the same disorders. Distributional properties, Item Response Theory Analysis (IRT), and Receiver Operating Characteristic (ROC) curves were used to assess and compare the performance of E-SWAN and traditional scales. Results In contrast to the traditional scales, which exhibited truncated distributions, all four E-SWAN scales had symmetric distributions. IRT analyses indicate the E-SWAN subscales provided reliable information about respondents throughout the population distribution; traditional scales only provided reliable information about respondents at the high end of the distribution. Predictive value for DSM-5 diagnoses was comparable to prior scales. Conclusions E-SWAN bidirectional scales can capture the full spectrum of the population distribution of behavior underlying DSM disorders. The additional information provided can better inform examination of inter-individual variation in population studies, as well as facilitate the identification of factors related to resiliency in clinical samples.