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. (PsycINFO Database Record

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

Definition and description of schizophrenia in the DSM-5

This article reviews and synthesizes research on reward processing in schizophrenia, which has begun to provide important insights into the cognitive and neural mechanisms associated with motivational impairments. Aberrant cortical-striatal interactions may be involved with multiple reward processing abnormalities, including: (1) dopamine-mediated basal ganglia systems that support reinforcement learning and the ability to predict cues that lead to rewarding outcomes; (2) orbitofrontal cortex-driven deficits in generating, updating, and maintaining value representations; (3) aberrant effort-value computations, which may be mediated by disrupted anterior cingulate cortex and midbrain dopamine functioning; and (4) altered activation of the prefrontal cortex, which is important for generating exploratory behaviors in environments where reward outcomes are uncertain. It will be important for psychosocial interventions targeting negative symptoms to account for abnormalities in each of these reward processes, which may also have important interactions; suggestions for novel behavioral intervention strategies that make use of external cues, reinforcers, and mobile technology are discussed.

/pdf/a-review-of-reward-processing-and-motivational-impairment-in-50dzvu8u57.pdf

A Review of Reward Processing and Motivational Impairment in Schizophrenia

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wps.20167

The influence of illness-related variables, personal resources and context-related factors on real-life functioning of people with schizophrenia

Deconstructing negative symptoms of schizophrenia: avolition-apathy and diminished expression clusters predict clinical presentation and functional outcome.

Pinar Miski

Papers

Deconstructing negative symptoms of schizophrenia: avolition-apathy and diminished expression clusters predict clinical presentation and functional outcome.

Differential patterns of premorbid social and academic deterioration in deficit and nondeficit schizophrenia