Toward the future of psychiatric diagnosis: the seven pillars of RDoC
TLDR
The rationale, status and long-term goals of RDoC are summarized, challenges in developing a research classification system are outlined, and seven distinct differences in conception and emphasis from current psychiatric nosologies are discussed.Abstract:
Current diagnostic systems for mental disorders rely upon presenting signs and symptoms, with the result that current definitions do not adequately reflect relevant neurobiological and behavioral systems - impeding not only research on etiology and pathophysiology but also the development of new treatments. The National Institute of Mental Health began the Research Domain Criteria (RDoC) project in 2009 to develop a research classification system for mental disorders based upon dimensions of neurobiology and observable behavior. RDoC supports research to explicate fundamental biobehavioral dimensions that cut across current heterogeneous disorder categories. We summarize the rationale, status and long-term goals of RDoC, outline challenges in developing a research classification system (such as construct validity and a suitable process for updating the framework) and discuss seven distinct differences in conception and emphasis from current psychiatric nosologies. Future diagnostic systems cannot reflect ongoing advances in genetics, neuroscience and cognitive science until a literature organized around these disciplines is available to inform the revision efforts. The goal of the RDoC project is to provide a framework for research to transform the approach to the nosology of mental disorders.read more
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Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity
Emily S. Finn,Xilin Shen,Dustin Scheinost,Monica D. Rosenberg,Jessica S. Huang,Marvin M. Chun,Xenophon Papademetris,R. Todd Constable +7 more
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The Hierarchical Taxonomy of Psychopathology (HiTOP): A Dimensional Alternative to Traditional Nosologies
Roman Kotov,Robert F. Krueger,David Watson,Thomas M. Achenbach,Robert R. Althoff,R. Michael Bagby,Timothy A. Brown,William T. Carpenter,Avshalom Caspi,Lee Anna Clark,Nicholas R. Eaton,Miriam K. Forbes,Kelsie T. Forbush,David Goldberg,Deborah S. Hasin,Steven E. Hyman,Masha Y. Ivanova,Donald R. Lynam,Kristian E. Markon,Joshua D. Miller,Terrie E. Moffitt,Leslie C. Morey,Stephanie N. Mullins-Sweatt,Johan Ormel,Christopher J. Patrick,Darrel A. Regier,Leslie Rescorla,Camilo J. Ruggero,Douglas B. Samuel,Martin Sellbom,Leonard J. Simms,Andrew E. Skodol,Tim Slade,Susan C. South,Jennifer L. Tackett,Irwin D. Waldman,Monika A. Waszczuk,Thomas A. Widiger,Aidan G. C. Wright,Mark Zimmerman +39 more
TL;DR: The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies and provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response.
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Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms.
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TL;DR: This work reviews recent advances in data driven and theory driven Computational psychiatry, with an emphasis on clinical applications, and highlights the utility of combining them.
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