Although the past few decades have seen much work in psychopathology research that has yielded provocative insights, relatively little progress has been made in understanding the etiology of mental disorders. We contend that this is due to an overreliance on statistics and technology with insufficient attention to adequacy of experimental design, a lack of integration of data across various domains of research, and testing of theoretical models using relatively weak study designs. We provide a conceptual discussion of these issues and follow with a concrete demonstration of our proposed solution. Using two different disorders—depression and substance use—as examples, we illustrate how we can evaluate competing theories regarding their etiology by integrating information from various domains including latent variable models, neurobiology, and quasi-experimental data such as twin and adoption studies, rather than relying on any single methodology alone. More broadly, we discuss the extent to which such integrative thinking allows for inferences about the etiology of mental disorders, rather than focusing on descriptive correlates alone. Greater scientific insight will require stringent tests of competing theories and a deeper conceptual understanding of the advantages and pitfalls of methodologies and criteria we use in our studies.

中文翻译：

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理论、研究设计和跨学科整合在推动精神病理学向前发展方面的力量

尽管在过去的几十年里，在精神病理学研究中已经看到了很多工作，这些工作已经产生了具有启发性的见解，但在理解精神障碍的病因学方面取得的进展相对较少。我们认为这是由于过度依赖统计和技术而没有充分关注实验设计的充分性，缺乏跨研究领域的数据整合，以及使用相对较弱的研究设计来测试理论模型。我们对这些问题进行了概念性讨论，然后具体演示了我们提出的解决方案。使用两种不同的疾病——抑郁症和物质使用——作为例子，我们说明了我们如何通过整合来自不同领域的信息来评估关于其病因的竞争理论，包括潜在变量模型、神经生物学、和准实验数据，例如双胞胎和收养研究，而不是单独依赖任何单一方法。更广泛地说，我们讨论了这种综合思维在多大程度上允许推断精神障碍的病因，而不是仅关注描述性相关性。更深入的科学洞察力需要对相互竞争的理论进行严格的测试，并对我们在研究中使用的方法和标准的优势和缺陷有更深入的概念理解。