The Research Domain Criteria
Further complexities are inherent in the application of existing diagnostic classification systems and their use for different purposes (i.e. research-focused versus clinical practice-based). Given such difficulties, the US National Institute of Mental Health (NIMH) initiated the Research Domain Criteria (RDoC) Project in 2009, in an attempt to align more closely ‘the dimensions of observable behaviour with neurobiological measures’, as a new way of classifying mental disorders (NIMH, 2017; Cuthbert, 2015; McKay and Tolin, 2016). The aim was to 'forge new approaches that can translate advances in brain and behavioral science to assessment and treatment' (Cuthbert, 2015). This experimental framework was developed mainly for research purposes, not as a clinical tool, but has gained considerable wider interest for its potential use in future psychiatric nosologies, aspiring to add further ‘precision’ to psychiatric diagnoses, guiding treatment decisions and expected outcomes or course of illness, tailored to an individual.
Rather than starting with clinically-derived definitions of mental disorders based on presenting signs and symptoms and seeking biological or psychological correlates, RDoC adopts the rather radical approach of first creating a compendium of basic behavioural and cognitive functions and related brain circuits, and considering ‘disorders’ in terms of dysregulation or dysfunction in these foundational systems, informed by initiatives such as the Human Connectome Project [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] and the US BRAIN programme (Cuthbert, 2015). You can read the definitions of the six RDoC domains and associated constructs on the NIMH website (the sensorimotor domain was added in 2019).
RDoC attempts to change the way that mental disorders are conceptualised and studied by (i) acknowledging 'that mental illnesses are increasingly understood to be disorders of neurodevelopment’ and that ‘the study of normal development provides a basis for understanding aberrant trajectories at different points along developmental pathways'; (ii) that 'environmental events exert profound influences, not only in neurodevelopment, but throughout the lifecourse'; and (iii) that constructs are 'dimensional and can be defined in terms of the degree of departure from the normal range', providing the capability of 'more readily establishing cut-off points to define (for example) mild, moderate or severe levels of disorder' achieving ‘quantitative’ dimensional measures.
But the broader problems of heterogeneity, individual differences, subtypes, symptom clusters and their overlap remain challenging issues, even with the move away from a categorical to a more dimensional (spectrum-based) understanding supported by the new RDoC approach.
Thomas Insel, the former NIMH Director involved in the launch of RDoC, wrote in 2013:
The strength of each of the editions of DSM has been ‘reliability’ – each edition has ensured that clinicians use the same terms in the same ways. The weakness is its lack of validity. Unlike our definitions of ischemic heart disease, lymphoma, or AIDS, the DSM diagnoses are based on a consensus about clusters of clinical symptoms, not any objective laboratory measure. In the rest of medicine, this would be equivalent to creating diagnostic systems based on the nature of chest pain or the quality of fever. Indeed, symptom-based diagnosis, once common in other areas of medicine, has been largely replaced in the past half century as we have understood that symptoms alone rarely indicate the best choice of treatment… NIMH has launched the Research Domain Criteria (RDoC) project to transform diagnosis by incorporating genetics, imaging, cognitive science, and other levels of information to lay the foundation for a new classification system.
He went on to say:
It became immediately clear that we cannot design a system based on biomarkers or cognitive performance because we lack the data. In this sense, RDoC is a framework for collecting the data needed for a new nosology. But it is critical to realize that we cannot succeed if we use DSM categories as the ‘gold standard’. The diagnostic system has to be based on the emerging research data, not on the current symptom-based categories. Imagine deciding that EKGs were not useful because many patients with chest pain did not have EKG changes. That is what we have been doing for decades when we reject a biomarker because it does not detect a DSM category. We need to begin collecting the genetic, imaging, physiologic, and cognitive data to see how all the data – not just the symptoms – cluster and how these clusters relate to treatment response.