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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Most diagnoses adequately tested had good to very good reliability with these representative clinical populations assessed with usual clinical interview methods. Some diagnoses that were revised to encompass a broader spectrum of symptom expression or had a more dimensional approach tested in the good to very good range.

The associations between the one-month prevalence rates of mental disorders and sociodemographic characteristics were investigated for 18,571 people interviewed in the first-wave community samples of all 5 sites in the US National Institute of Mental Health (NIMH) Epidemiologic Catchment Area program. Men were found to have a significantly higher rate of cognitive impairment than women after controlling for the effects of age, race or ethnicity, marital status and socioeconomic status. Marital status was one of the most powerful correlates of mental disorder risk: the odds of separated or divorced people having any NIMH Diagnostic Interview Schedule disorder were twice that of married people after controlling for age, gender, race or ethnicity and socioeconomic status. The odds of those in the lowest socioeconomic status group having any Diagnostic Interview Schedule disorder was about 2.5 times that of those in the highest socioeconomic status group, controlling for age, gender, race or ethnicity and marital status. For all disorders except cognitive impairment, race or ethnicity did not remain statistically significant after controlling for age, gender, marital status and socioeconomic status.