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Initial Interpretation and Evaluation of a Profile-Based Classification System for the Anxiety and Mood Disorders: Incremental Validity Compared to DSM-IV Categories

机译:基于概要的焦虑和情绪障碍分类系统的初步解释和评估:与DSM-IV类别相比增量有效性

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摘要

Limitations in anxiety and mood disorder diagnostic reliability and validity due to the categorical approach to classification used by the Diagnostic and Statistical Manual of Mental Disorders (DSM) have been long recognized. Although these limitations have led researchers to forward alternative classification schemes, few have been empirically evaluated. In a sample of 1,218 outpatients with anxiety and mood disorders, the present study examined the validity of proposal to classify the anxiety and mood disorders using an integrated dimensional-categorical approach based on transdiagnostic emotional disorder vulnerabilities and phenotypes. Latent class analyses of seven transdiagnostic dimensional indicators suggested that a six-class (i.e., profile) solution provided the best model fit and was the most conceptually interpretable. Interpretation of the classes was further supported when compared with DSM-IV diagnoses (i.e., within-class prevalence of diagnoses, using diagnoses to predict class membership). In addition, hierarchical multiple regression models were used to demonstrate the incremental validity of the profiles; class probabilities consistently accounted for unique variance in anxiety and mood disorder outcomes above and beyond DSM diagnoses. These results provide support for the potential development and utility of a hybrid dimensional-categorical profile approach to anxiety and mood disorder classification. In particular, the availability of dimensional indicators and corresponding profiles may serve as a useful complement to DSM diagnoses for both researchers and clinicians.
机译:人们早已认识到由于精神疾病诊断和统计手册(DSM)所采用的分类方法,焦虑和情绪障碍的诊断可靠性和有效性受到限制。尽管这些局限性导致研究人员提出了替代分类方案,但很少有经验进行评估。在1,218名焦虑和情绪障碍门诊患者的样本中,本研究检查了使用基于经诊断的情绪障碍的脆弱性和表型的综合维度分类方法对焦虑和情绪障碍进行分类的建议的有效性。对七个经诊断的尺寸指标的潜在分类分析表明,六类(即轮廓)解决方案提供了最佳模型拟合,并且在概念上最具解释性。与DSM-IV诊断相比(例如,使用诊断来预测班级成员资格的诊断在班级内的患病率),进一步支持对班级的解释。另外,使用了分层的多元回归模型来证明轮廓的增量有效性。在DSM诊断之上和之外,班级概率始终是造成焦虑和情绪障碍结果独特差异的原因。这些结果为焦虑和情绪障碍分类的混合量纲分类方法的潜在发展和实用性提供了支持。特别是,对于研究人员和临床医生而言,尺寸指示器和相应配置文件的可用性可以作为DSM诊断的有用补充。

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