COLLABORATIVE LONGITUDINAL STUDY OF PERSONALITY DISORDER

本研究的总体目标是提供一个全面的图片， 四种特定人格障碍（PD）的过程和结果： 典型型（STPD）、边缘型（BPD）、回避型（AVPD）和强迫型- 强迫症（OCPD）。 采用前瞻性纵向重复测量 设计我们将开发关于过程和结果的相同的基本知识 对于以前因类似调查而导致的PD， 情感和焦虑障碍。 缺乏可比数据， 被诊断患有PD的个体代表了知识上的重要差距。 为了实现我们的总体目标，我们提出了三种方法：I。描述性的， 二.预测，和III。验证 描述性方法将 提供有关精神病理学和社会稳定性的基本数据 允许PD之间进行比较的损伤， I轴紊乱。 预测方法将产生基本的临床 深入了解PD内和PD间预后的决定因素。 的 验证方法将检查描述性和 DSM系统定义的PD的纵向特征，以及 这与其他方案相比。 为实现这些目标，本提案要求提供资金， 严格评估，并跟踪750名受试者的样本，年龄在18岁至 45，即，四种PD各150例，对照组150例， 抑郁症（NDD）。 样本将足够大， 在种族上足够多样化，以取得对大多数人普遍适用的结果 临床设置和检查应用的几个维度 接近。

The overall aim of this study is to provide a comprehensive picture of the course and outcome of four specific personality disorders (PDs): schizotypal (STPD), borderline (BPD), avoidant (AVPD), and obsessive- compulsive (OCPD). Using a prospective longitudinal, repeated measures design we will develop the same basic knowledge about course and outcome for the PDs that has previously resulted from similar investigations of affective and anxiety disorders. The absence of comparable data for individuals diagnosed with PDs represents an important gap in knowledge. To accomplish our overall aim we propose three approaches: I. descriptive, II. predictive, and III. validating. The descriptive approach will provide the basic data on stability of psychopathology and social impairment that allows comparison between the PDs and to similar data from Axis I disorders. The predictive approach will yield basic clinical insights into the determinants of prognosis within and across PDs. The validating approach will examine the homogeneity of descriptive and longitudinal features for the PDs as defined by the DSM system and how this compares with alternative schemes. To accomplish these aims, this proposal requests funds to recruit, rigorously assess, and follow a total sample of 750 subjects, aged 18 to 45, i.e., 150 of each of the four PDs and 150 controls with major depressive disorder (NDD). The sample will be large enough and sufficiently diverse ethnically to attain results generalizable to most clinical settings and to examine the application of several dimensional approaches.