Review
Linking RDoC and HiTOP: A new interface for advancing psychiatric nosology and neuroscience

https://doi.org/10.1016/j.cpr.2021.102025Get rights and content

Highlights

  • This article provides a narrative review outlining an interface connecting RDoC and HiTOP dimensions.

  • RDoC provides a solid transdiagnostic framework for elucidating the underpinnings of HiTOP dimensions.

  • HiTOP may aid RDoC-informed research by providing psychometrically robust clinical targets.

  • Leveraging the complementary strengths of RDoC and HiTOP may advance clinical neuroscience and psychopathology research.

  • This interface may facilitate the development of future biobehaviorally-grounded classifications of psychopathology.

Abstract

The Research Domain Criteria (RDoC) and the Hierarchical Taxonomy of Psychopathology (HiTOP) represent major dimensional frameworks proposing two alternative approaches to accelerate progress in the way psychopathology is studied, classified, and treated. RDoC is a research framework rooted in neuroscience aiming to further the understanding of transdiagnostic biobehavioral systems underlying psychopathology and ultimately inform future classifications. HiTOP is a dimensional classification system, derived from the observed covariation among symptoms of psychopathology and maladaptive traits, which seeks to provide more informative research and treatment targets (i.e., dimensional constructs and clinical assessments) than traditional diagnostic categories. This article argues that the complementary strengths of RDoC and HiTOP can be leveraged in order to achieve their respective goals. RDoC's biobehavioral framework may help elucidate the underpinnings of the clinical dimensions included in HiTOP, whereas HiTOP may provide psychometrically robust clinical targets for RDoC-informed research. We present a comprehensive mapping between dimensions included in RDoC (constructs and subconstructs) and HiTOP (spectra and subfactors) based on narrative review of the empirical literature. The resulting RDoC-HiTOP interface sheds light on the biobehavioral correlates of clinical dimensions and provides a broad set of dimensional clinical targets for etiological and neuroscientific research. We conclude with future directions and practical recommendations for using this interface to advance clinical neuroscience and psychiatric nosology. Ultimately, we envision that this RDoC-HiTOP interface has the potential to inform the development of a unified, dimensional, and biobehaviorally-grounded psychiatric nosology.

Introduction

Accurately classifying mental disorders and elucidating their etiologies remain among the greatest challenges of modern clinical psychology and psychiatry. Ongoing efforts seek to refine psychiatric nosology, but rates of misdiagnosis remain high (Regier et al., 2013) and available categorical classification systems, including the Diagnostic and Statistical Manual of Mental Disorders (DSM; APA, 2013) and the International Classification of Diseases (ICD; WHO, 1992), carry limited clinical utility for prognosis and treatment (Conway et al., 2019). With regard to etiology, we lack a complete understanding of the causes of any mental disorder, despite considerable efforts in elucidating their genetic (Waszczuk et al., 2020) and neural (Thompson et al., 2020) bases.

These two issues (i.e., diagnostic classification and etiology) are strongly interdependent. On the one hand, developing a refined taxonomy of clinical problems requires a better understanding of the antecedents and processes that lead to different forms psychopathology in order to develop better treatments. On the other hand, progress in understanding the etiology of mental illnesses is hindered by common misdiagnosis and limited validity of diagnoses based on traditional nosologies. Integrating advances in empirical research on diagnostic classification and etiology has the potential to accelerate progress in these fields (Latzman et al., 2020; Waszczuk et al., 2020).

This article proposes an interface to advance these two fronts by leveraging two major initiatives that are using dimensional approaches to promote a radical change in the way mental illness is studied and classified: the Research Domain Criteria (RDoC) framework by the National Institute of Mental Health (NIMH; Cuthbert and Insel, 2013; Kozak and Cuthbert, 2016) and the Hierarchical Taxonomy of Psychopathology (HiTOP; Kotov et al., 2017; Kotov et al., 2021; Krueger et al., 2018). We start with an overview of the challenges of psychiatric nosologies and the solutions offered by RDoC and HiTOP, highlighting the complementary nature of these frameworks and providing rationale for an interface that bridges between them. We then present a comprehensive map of the interface linking between RDoC constructs and HiTOP spectra based on narrative review of the empirical literature. We conclude with examples of integrative research linking biobehavioral systems with dimensions of psychopathology, and with recommendations for implementing this approach in future studies with the goal to promote progress in elucidating the causes of psychopathology and improving future classifications.

Section snippets

Dimensional classifications of psychopathology

Extensive evidence points to major limitation of categorical classifications that make them a poor guide for research and clinical practice, as explained in detail elsewhere (Cuthbert and Insel, 2013; Kotov et al., 2017). First, categorical diagnoses do not adequately reflect the extensive evidence that forms of psychopathology and their underlying processes are continuous in nature (Cuthbert and Insel, 2013; Markon and Krueger, 2005). The imposition of artificial categories can lead to low

A new interface linking RDoC and HiTOP

The complementary nature and strengths of RDoC and HiTOP can be leveraged to advance understanding of psychopathology and inform clinical practice (Latzman et al., 2020). Since RDoC currently lacks direct clinical applicability, HiTOP may aid RDoC-informed research by providing psychometrically robust clinical targets. Additionally, since HiTOP does not consider the etiology of psychopathology, RDoC provides a solid transdiagnostic framework for elucidating the underpinnings of the clinical

Literature review

Our review identified numerous HiTOP correlates of each RDoC construct/subconstruct.

RDoC-HiTOP interface summary and general discussion

In the previous section, we have delineated an interface between RDoC and HiTOP frameworks by identifying connections between their dimensions based on available literature. Our review indicates a large number of associations of between RDoC constructs/subconstructs and HiTOP spectra/subfactors, which are of varying strength and documented by a varying number of studies. More associations are expected to emerge in future research informed by this interface. Fig. 2 illustrates the most robust

Practical recommendations and future directions

In this article we have provided a detailed map (section 4, Supplementary Figs. 1–5) as well as an overarching summary (section 5, Fig. 2) of an interface between RDoC and HiTOP. We have delineated associations between transdiagnostic biobehavioral systems included in RDoC and various clinical phenomena organized in the HiTOP model, but also highlighted more tentative associations where additional research is needed. The identified connections between RDoC and HiTOP dimensions can guide design

Conclusions

The dimensional approach to clinical research endorsed by both RDoC and HiTOP is the most promising way forward. It requires larger samples and different sampling designs than those with which many clinical researchers are familiar, but the payoff will be more effective scientific research, illuminating the etiology and clinical manifestations of psychopathology. The RDoC-HiTOP interface delineated in this article provides a synergistic approach that brings these dimensional frameworks

Role of funding sources

Dr. Michelini was funded by a NARSAD Young Investigator Award from the Brain & Behavior Research Foundation (grant number 28566). Dr. Kotov was funded by the National Institute of Mental Health (grant number R01MH122537).

Contributors

Michelini, Kotov, Latzman and DeYoung conceived this work. Michelini, Palumbo, Latzman and Kotov reviewed the literature. Michelini wrote a first draft of most sections and prepared the figures. All authors contributed to the manuscript and approved the final version.

Declaration of Competing Interest

All authors report no conflict of interest.

References (354)

  • K.A. Bonfils et al.

    Affective empathy in schizophrenia: A meta-analysis

    Schizophrenia Research

    (2016)
  • K.A. Bonfils et al.

    Empathy in schizophrenia: A meta-analysis of the Interpersonal Reactivity Index

    Psychiatry Research

    (2017)
  • E. Bora et al.

    Theory of mind impairment in schizophrenia: meta-analysis

    Schizophrenia Research

    (2009)
  • D. Bzdok et al.

    Machine learning for precision psychiatry: Opportunities and challenges

    Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

    (2018)
  • R.N. Carleton et al.

    Addressing revisions to the Brief Fear of Negative Evaluation scale: Measuring fear of negative evaluation across anxiety and mood disorders

    Journal of Anxiety Disorders

    (2011)
  • R.N. Carleton et al.

    Increasingly certain about uncertainty: Intolerance of uncertainty across anxiety and depression

    Journal of Anxiety Disorders

    (2012)
  • S.R. Carlson et al.

    Externalizing behavior, the UPPS-P impulsive behavior scale and reward and punishment sensitivity

    Personality and Individual Differences

    (2013)
  • R.C. Chan et al.

    Impaired facial emotion perception in schizophrenia: A meta-analysis

    Psychiatry Research

    (2010)
  • H.W. Chase et al.

    The neural basis of drug stimulus processing and craving: An activation likelihood estimation meta-analysis

    Biological Psychiatry

    (2011)
  • L. Collin et al.

    Facial emotion recognition in child psychiatry: A systematic review

    Research in Developmental Disabilities

    (2013)
  • P.R. Corlett et al.

    The neurobiology of schizotypy: Fronto-striatal prediction error signal correlates with delusion-like beliefs in healthy people

    Neuropsychologia

    (2012)
  • K.A. Correa et al.

    The role of intolerance of uncertainty in current and remitted internalizing and externalizing psychopathology

    Journal of Anxiety Disorders

    (2019)
  • H.P. da Costa et al.

    DSM-5 pathological personality traits are associated with the ability to understand the emotional states of others

    Journal of Research in Personality

    (2018)
  • S. Dawe et al.

    Reward drive and rash impulsiveness as dimensions of impulsivity: implications for substance misuse

    Addictive Behaviors

    (2004)
  • E.K. Diekhof et al.

    Functional neuroimaging of reward processing and decision-making: a review of aberrant motivational and affective processing in addiction and mood disorders

    Brain Research Reviews

    (2008)
  • G.C. Dieleman et al.

    Alterations in HPA-axis and autonomic nervous system functioning in childhood anxiety disorders point to a chronic stress hypothesis

    Psychoneuroendocrinology

    (2015)
  • A.R. Docherty et al.

    Alogia and formal thought disorder: Differential patterns of verbal fluency task performance

    Journal of Psychiatric Research

    (2011)
  • E. Du Rietz et al.

    Autonomic arousal profiles in adolescents and young adults with ADHD as a function of recording context

    Psychiatry Research

    (2019)
  • J. Edwards et al.

    Emotion recognition via facial expression and affective prosody in schizophrenia: a methodological review

    Clinical Psychology Review

    (2002)
  • L.E. Ethridge et al.

    Behavioral response inhibition in psychotic disorders: Diagnostic specificity, familiality and relation to generalized cognitive deficit

    Schizophrenia Research

    (2014)
  • G. Fervaha et al.

    Neural substrates underlying effort computation in schizophrenia

    Neuroscience and Biobehavioral Reviews

    (2013)
  • D. Foti et al.

    Depression and reduced sensitivity to non-rewards versus rewards: Evidence from event-related potentials

    Biological Psychology

    (2009)
  • D. Foti et al.

    Beyond the broken error-related negativity: Functional and diagnostic correlates of error processing in psychosis

    Biological Psychiatry

    (2012)
  • D. Foti et al.

    Impaired error processing in late-phase psychosis: Four-year stability and relationships with negative symptoms

    Schizophrenia Research

    (2016)
  • I.H.A. Franken

    Behavioral approach system (BAS) sensitivity predicts alcohol craving

    Personality and Individual Differences

    (2002)
  • S.N. Geniole et al.

    The Point Subtraction Aggression Paradigm as a laboratory tool for investigating the neuroendocrinology of aggression and competition

    Hormones and Behavior

    (2017)
  • G.R. Abbott et al.

    Facial affect recognition and schizotypal personality characteristics

    Early Intervention in Psychiatry

    (2013)
  • T.M. Achenbach

    The classification of children’s psychiatric symptoms: A factor-analytic study

    Psychological Monographs

    (1966)
  • J. Agnes Brunnekreef et al.

    Information processing profiles of internalizing and externalizing behavior problems: Evidence from a population-based sample of preadolescents

    Journal of Child Psychology and Psychiatry

    (2007)
  • APA

    Diagnostic and statistical manual of mental disorders

    (2013)
  • P. Asherson et al.

    Efficacy of atomoxetine in adults with attention deficit hyperactivity disorder: an integrated analysis of the complete database of multicenter placebo-controlled trials

    Journal of Psychopharmacology

    (2014)
  • M.Y. Baars et al.

    Depressive and aggressive responses to frustration: development of a questionnaire and its validation in a sample of male alcoholics

    Depression Research and Treatment

    (2011)
  • D.E. Babinski et al.

    Sensitivity to peer feedback in young adolescents with symptoms of ADHD: Examination of neurophysiological and self-report measures

    Journal of Abnormal Child Psychology

    (2019)
  • D.M. Barch et al.

    Cognitive impairments in psychotic disorders: Common mechanisms and measurement

    World Psychiatry

    (2014)
  • D.H. Barlow et al.

    The unified protocol for transdiagnostic treatment of emotional disorders compared with diagnosis-specific protocols for anxiety disorders: A randomized clinical trial

    JAMA Psychiatry

    (2017)
  • A.R. Baskin-Sommers et al.

    Differentiating the cognition-emotion interactions that characterize psychopathy versus externalizing

    Handbook of Cognition and Emotion

    (2013)
  • R. Bedford et al.

    The role of infants’ mother-directed gaze, maternal sensitivity, and emotion recognition in childhood callous unemotional behaviours

    European Child & Adolescent Psychiatry

    (2017)
  • R.A. Bevins et al.

    Internal stimuli generated by abused substances: Role of Pavlovian conditioning and its implications for drug addiction

  • W.K. Bickel et al.

    Toward a behavioral economic understanding of drug dependence: Delay discounting processes

    Addiction

    (2001)
  • S.L. Bistricky et al.

    Facial affect processing and depression susceptibility: Cognitive biases and cognitive neuroscience

    Psychological Bulletin

    (2011)
  • Cited by (104)

    View all citing articles on Scopus
    1

    These two authors contributed equally.

    View full text