BASIC DIMENSIONS OF CHILD AND ADOLESCENT PSYCHOPATHOLOGY

研究人员长期以来一直认为，将儿童和青少年的精神病理学视为多维度而不是单维度更合适。因此，该领域有着悠久的传统，试图使用经验方法来定义精神病理学的多个维度。尽管有这些努力，但是，仍然有显着的分歧的数量和性质方面的精神病理学的青年。这种对基本测量单位的分歧严重限制了病因学研究的科学进展。这项研究将使用心理测量学和行为遗传学的方法相结合，以解决有关儿童和青少年精神病理学基本维度的分歧。使用双胞胎样本的数据，验证性因素分析将被用来测试从以前的研究和理论中得出的儿童和青少年精神病理学的潜在结构的替代方法的适合性。然而，这项研究将远远超出因素分析，通过使用标准效度和行为遗传策略来验证假定的维度。精神病理学的两个假定维度，如果没有显示出与外部标准变量相关的不同模式，则不被认为是有意义的不同维度。同样，两个不表现出遗传和/或环境影响的推定不同维度也不会被视为不同维度。将使用结构方程模型评估精神病理学维度的潜在发展和性别差异。

Researchers have long agreed that it is more appropriate to view child and adolescent psychopathology as multi-dimensional than un-dimensional. Consequently, the field has a long tradition of attempting to use empirical methods to define the multiple dimensions of psychopathology. In spite of these efforts, however, there is still marked disagreement about the number and nature of dimensions of psychopathology in youths. This disagreement on the fundamental units of measurement seriously limits scientific progress in the study of etiology. The proposed study will use a combination of psychometric and behavior genetic methods to resolve disagreements about the basic dimensions of psychopathology in children and adolescents. Using data from a sample of twins, confirmatory factor analysis will be used to test the fit of alternative methods of the underlying structure of child and adolescent psychopathology derived from prior research and theory. The proposed study will go well beyond factor analysis, however, by validating the putative dimensions using both criterion validity and behavior genetic strategies. Two putative dimensions of psychopathology that do not show different patterns of association with external criterion variables would not be considered to be meaningfully distinct dimensions. Similarly, two putatively distinct dimensions that do not exhibit genetic and/or environmental influences would not be considered to be distinct dimensions. Potential development and gender differences in the dimensions of psychopathology will be evaluated using structural equation modeling.