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About RDoC

What is RDoC?

RDoC is a research framework for investigating mental disorders. It integrates many levels of information (from genomics and circuits to behavior and self-report) to explore basic dimensions of functioning that span the full range of human behavior from normal to abnormal.

RDoC is not meant to serve as a diagnostic guide, nor is it intended to replace current diagnostic systems. The goal is to understand the nature of mental health and illness in terms of varying degrees of dysfunction in general psychological/biological systems.

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(framework graphic description)

The RDoC framework is a research strategy that is implemented as a matrix of elements. The matrix is a dynamic structure that currently focuses on six major domains of human functioning (e.g., Negative Valence Systems, Cognitive Systems). Contained within each domain are several behavioral elements, or constructs, that comprise different aspects of its overall range of functions. Constructs are studied along a span of functioning from normal to abnormal with the understanding that each is situated in, and affected by, environmental and neurodevelopmental contexts. Measurements of constructs can be made using several different classes of variables, or units of analysis, which include genetic, physiological, behavioral, and self-report assessments. The RDoC matrix is designed to evolve based on new findings from the research community and thus will be modified to include new and/or revised constructs and domains.   

The goal of RDoC is to provide information about the basic biological and cognitive processes that lead to mental health and illness, broadly conceived. The information gained using RDoC may help inform the creation of mental health screening tools, diagnostic systems, and treatments.

Why RDoC?

Traditionally, mental illnesses have been conceptualized as disorders that are diagnosed on the basis of the number and type of symptoms, and the presence of distress or impairment. This view of mental disorders – and the resulting diagnostic systems – provides benefits such as reliability and ease of diagnosis across a variety of contexts; however, this approach has come at the cost of numerous tradeoffs including the following:

  • Research based on diagnostic categories can suffer from problems with heterogeneity because of the varied ways people can qualify for a symptom-based disorder diagnosis. Two people, in some cases, can be diagnosed with the same disorder despite having few symptoms in common. This makes it difficult for researchers to pinpoint specific aspects of disorders because the neurobiological mechanisms may differ greatly among patients who share little to no symptomatology.
  • Also, patients who meet criteria for one mental disorder often tend to meet criteria for other mental disorders – a phenomenon known as comorbidity. This has led researchers to question whether too much emphasis has been placed on studying specific disorders in isolation from other disorders. It has also led to concerns that common dimensions underlying mental disorders are not being properly reflected in mental health research.
  • Researchers seeking to reduce heterogeneity in their samples often limit participants to those with “pure” diagnoses. In order to do this, they do not enroll individuals representing the larger spectrum of functioning or those with related disorders; however, this type of variation can be important for understanding the underlying contributors to mental health and illness.
  • Clinical criteria for defining a disorder, while created through expert practitioner consensus, are somewhat arbitrary. Research indicates that there are important similarities between those whose symptoms meet the criteria for a disorder versus those who just miss the cutoff for diagnosis due to fewer and/or less severe symptoms. To understand the full spectrum of mental health and illness, it is important to adopt dimensional conceptualizations. Therefore, dividing research subjects into two groups based on symptom counts may obscure important information about the ways in which psychopathology gradually emerges across development, how risk factors operate, and how quantitative outcomes of prevention and treatment trials can be implemented.

These problems, and others, suggest that in order to understand both the development and treatment of mental disorders, the field needs a comprehensive picture of typical and atypical brain and behavioral development across the lifespan. It is essential to find a way to increase knowledge concerning the biological, physiological, and behavioral components and mechanisms through which multiple and interacting mental-health risk and protective factors operate – a research framework that does not rely on disorder-based categories.

The RDoC project, launched in 2009, was the response to the growing awareness of these issues. The development of the RDoC matrix was the collaborative effort of over 200 leading scientists who worked together to articulate and define the knowledge for each of the domains and constructs in the matrix. Since its inception, RDoC has grown into a significant initiative for NIMH.