The Power of Theory, Research Design, and Transdisciplinary Integration in Moving Psychopathology Forward

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20 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)209-230
Number of pages22
JournalPsychological Inquiry
Issue number3
StatePublished - Jul 3 2015

Bibliographical note

Funding Information:
Preparation of this article was supported by the NARSAD Young Investigator Award, National Institute of Drug Abuse grants DA 024417, DA 05147, DA 13240, DA 034606, DA 036216, and DA 037904, National Institute of Alcohol Abuse and Alcoholism grants AA 023974 and AA 09367, and the National Institute of Mental Health grant MH 66140.

Publisher Copyright:
© 2015, Copyright © Taylor & Francis Group, LLC.


  • etiology of mental disorders
  • neurobiology
  • pitfalls and advantages of technology and statistical modeling
  • quasi-experimental designs
  • theory versus data-driven approaches


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