The structure of psychopathology: Toward an expanded quantitative empirical model.

Wright, Aidan G.C.; Krueger, Robert F.; Hobbs, Megan J.; Markon, Kristian E.; Eaton, Nicholas R.; Slade, Tim

doi:10.1037/a0030133

“…Recent studies that used class-based methods (e.g., latent class analysis) found classes that represent extreme levels of dimensions identified in factor analytic research (Olino et al, 2012;Vaidyanathan, Patrick, & Iacono, 2011), but older studies produced different sets of clusters (Kessler et al, 2005). Dimensional models have shown better fit to the data than latent classes or hybrid models (Eaton et al, 2013;Carragher et al, 2014;Haslam et al, 2012;Vrieze, Perlman, Krueger, & Iacono, 2012;Walton et al, 2011;Wright et al, 2013). Individual symptoms also have been found to be dimensions rather than binary absent/present states (Flett, Vredenburg, & Krames, 1997;Strauss, 1969;Van Os et al, 2009).…”

Section: Addressing Limitations Of Traditional Taxonomiesmentioning

confidence: 99%

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Dimensional Alternative to Traditional Nosologies

Kotov¹,

Krueger²,

Watson³

et al. 2017

Preprint

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The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures.

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“…There is no conclusive evidence of categorical entities in mental health to challenge this assumption (Haslam et al, 2012;Walton et al, 2011;Widiger & Samuel, 2005;Wright et al, 2013), but if such entities were to emerge, they could be incorporated easily into a quantitative nosology. Modern statistical tools, such as factor mixture models (Hallquist & Wright, 2014;Y.…”

Section: Addressing Limitations Of Traditional Taxonomiesmentioning

confidence: 99%

“…The internalizing, externalizing, and thought disorder dimensions have emerged in both community and patient samples (Kotov, Chang, et al, 2011;Kotov, Ruggero et al, 2011;Miller, Fogler, Wolf, Kaloupek, & Keane, 2008). Extensive data are now available on these spectra with studies including as many as 25 disorders (Røysamb et al, 2011) and 43,093 participants (Eaton et al, 2013). Finally, initial evidence suggests existence of an additional somatoform spectrum (Kotov, Ruggero et al, 2011).…”

Section: Spectramentioning

confidence: 99%

“…One caveat to this organization is that panic disorder appears to have features of both fear and distress, and has been found to load on both subfactors (Greene & Eaton, 2016;H. Kim & Eaton, 2015;Nelson et al, 2015;Watson et al, 2012;Wright et al, 2013). Also, OCD is a relatively weak member of the fear cluster and shows some overlap with the thought disorder dimension (Caspi et al, 2014;Chmielewski & Watson, 2008;Watson, Wu, & Cutshall, 2004).…”

Section: Subfactorsmentioning

confidence: 99%

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The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies.

Kotov¹,

Krueger²,

Watson³

et al. 2017

Journal of Abnormal Psychology

Self Cite

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The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures.

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“…[1][2][3][4] These efforts have been directed at addressing inherent limitations associated with pervasive clinical heterogeneity and diagnostic comorbidity, [5][6][7][8] along with the fact that covariance patterns among differing psychopathologies and temperament/personality traits are not addressed by dominant classification systems of mental disorders. 9,10 In response to these limitations, different researchers have modeled the underlying structure of common psychiatric conditions to characterize diagnostic overlap using structural equation modeling techniques.…”

Section: Introductionmentioning

confidence: 99%

The joint structure of major depression, anxiety disorders, and trait negative affect

Carvalho

¹

,

Andreoli

²

,

Lara

³

et al. 2014

Rev. Bras. Psiquiatr.

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Objective: Dimensional models of psychopathology demonstrate that two correlated factors of fear and distress account for the covariation among depressive and anxiety disorders. Nevertheless, these models tend to exclude variables relevant to psychopathology, such as temperament traits. This study examined the joint structure of DSM-IV-based major depression and anxiety disorders along with trait negative affect in a representative sample of adult individuals residing in the cities of Sã o Paulo and Rio de Janeiro, Brazil. Methods: The sample consisted of 3,728 individuals who were administered sections D (phobic, anxiety and panic disorders) and E (depressive disorders) of the Composite International Diagnostic Interview (CIDI) 2.1 and a validated version of the Positive and Negative Affect Schedule. Data were analyzed using correlational and structural equation modeling. Results: Lifetime prevalence ranged from 2.4% for panic disorder to 23.2% for major depression. Most target variables were moderately correlated. A two-factor model specifying correlated fear and distress factors was retained and confirmed for models including only diagnostic variables and diagnostic variables along with trait negative affect. Conclusions: This study provides support for characterization of internalizing psychopathology and trait negative affect in terms of correlated dimensions of distress and fear. These results have potential implications for psychiatric taxonomy and for understanding the relationship between temperament and psychopathology.

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The structure of psychopathology: Toward an expanded quantitative empirical model.

Cited by 314 publications

References 87 publications

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Dimensional Alternative to Traditional Nosologies

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Dimensional Alternative to Traditional Nosologies

The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies.

The joint structure of major depression, anxiety disorders, and trait negative affect

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