Neurocognitive deficits in a transdiagnostic clinical staging model

Research in developmental psychopathology and clinical staging models has increasingly sought to identify trans-diagnostic biomarkers or neurocognitive deficits that may play a role in the onset and trajectory of mental disorders and could represent modifiable treatment targets. Less attention has been directed at the potential role of cognitive-emotional regulation processes such as ruminative response style. Maladaptive rumination (toxic brooding) is a known mediator of the association between gender and internalizing disorders in adolescents and is increased in individuals with a history of early adversity. Furthermore, rumination shows moderate levels of genetic heritability and is linked to abnormalities in neural networks associated with emotional regulation and executive functioning. This review explores the potential role of rumination in exacerbating the symptoms of alcohol and substance misuse, and bipolar and psychotic disorders during the peak age range for illness onset. Evidence shows that rumination not only amplifies levels of distress and suicidal ideation, but also extends physiological responses to stress, which may partly explain the high prevalence of physical and mental co-morbidity in youth presenting to mental health services. In summary, the normative developmental trajectory of rumination and its role in the evolution of mental disorders and physical illness demonstrates that rumination presents a detectable, modifiable trans-diagnostic risk factor in youth.

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Right Care, First Time: Developing a Theory-Based Automated Protocol to Help Clinically Stage Young People Based on Severity and Persistence of Mental Illness

Frontiers in Public Health ◽

10.3389/fpubh.2021.621862 ◽

2021 ◽

Vol 9 ◽

Author(s):

Frank Iorfino ◽

Vanessa Wan Sze Cheng ◽

Shane P. Cross ◽

Hannah F. Yee ◽

Tracey A. Davenport ◽

...

Keyword(s):

Mental Disorders ◽

Information Technologies ◽

Clinical Decision Making ◽

Clinical Decision ◽

Evidence Base ◽

Clinical Staging ◽

Health Information Technologies ◽

Staging Model ◽

Automated Protocol ◽

First Time

Most mental disorders emerge before the age of 25 years and, if left untreated, have the potential to lead to considerable lifetime burden of disease. Many services struggle to manage high demand and have difficulty matching individuals to timely interventions due to the heterogeneity of disorders. The technological implementation of clinical staging for youth mental health may assist the early detection and treatment of mental disorders. We describe the development of a theory-based automated protocol to facilitate the initial clinical staging process, its intended use, and strategies for protocol validation and refinement. The automated clinical staging protocol leverages the clinical validation and evidence base of the staging model to improve its standardization, scalability, and utility by deploying it using Health Information Technologies (HIT). Its use has the potential to enhance clinical decision-making and transform existing care pathways, but further validation and evaluation of the tool in real-world settings is needed.

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Clinical staging model in bipolar disorder: A few considerations

Bipolar Disorders ◽

10.1111/bdi.12750 ◽

2019 ◽

Vol 21 (3) ◽

pp. 278-279

Author(s):

Siddharth Sarkar ◽

Nishtha Chawla

Keyword(s):

Bipolar Disorder ◽

Clinical Staging ◽

Staging Model

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Staging of Schizophrenia With the Use of PANSS: An International Multi-Center Study

The International Journal of Neuropsychopharmacology ◽

10.1093/ijnp/pyz053 ◽

2019 ◽

Vol 22 (11) ◽

pp. 681-697 ◽

Cited By ~ 3

Author(s):

Konstantinos N Fountoulakis ◽

Elena Dragioti ◽

Antonis T Theofilidis ◽

Tobias Wikilund ◽

Xenofon Atmatzidis ◽

...

Keyword(s):

Factor Analysis ◽

Exploratory Factor Analysis ◽

Discriminant Function ◽

Discriminant Function Analysis ◽

Function Analysis ◽

Analysis Of Covariance ◽

Clinical Staging ◽

Staging Model ◽

Multi Center Study ◽

Stage 1

Abstract Introduction A specific clinically relevant staging model for schizophrenia has not yet been developed. The aim of the current study was to evaluate the factor structure of the PANSS and develop such a staging method. Methods Twenty-nine centers from 25 countries contributed 2358 patients aged 37.21 ± 11.87 years with schizophrenia. Analysis of covariance, Exploratory Factor Analysis, Discriminant Function Analysis, and inspection of resultant plots were performed. Results Exploratory Factor Analysis returned 5 factors explaining 59% of the variance (positive, negative, excitement/hostility, depression/anxiety, and neurocognition). The staging model included 4 main stages with substages that were predominantly characterized by a single domain of symptoms (stage 1: positive; stages 2a and 2b: excitement/hostility; stage 3a and 3b: depression/anxiety; stage 4a and 4b: neurocognition). There were no differences between sexes. The Discriminant Function Analysis developed an algorithm that correctly classified >85% of patients. Discussion This study elaborates a 5-factor solution and a clinical staging method for patients with schizophrenia. It is the largest study to address these issues among patients who are more likely to remain affiliated with mental health services for prolonged periods of time.

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Clinical Staging of Psychotic Disorders: From Dimensions to Neurobiology

European Psychiatry ◽

10.1016/j.eurpsy.2017.01.164 ◽

2017 ◽

Vol 41 (S1) ◽

pp. S35-S35

Author(s):

A. Batalla

Keyword(s):

Psychotic Disorders ◽

Clinical Staging ◽

Treatment And Prevention ◽

Ultra High Risk ◽

Specific Subgroup ◽

Competing Interest ◽

Staging Model ◽

New Biomarkers ◽

Extent Of Disease ◽

At Risk Mental State

The clinical staging model is an approach used in medicine to define the extent of disease. In psychiatry, this model has recently been applied to psychotic disorders to distinguish the earlier, non-specific features of illness (e.g. ultra-high risk [UHR]; at-risk mental state [ARMS]), from later, more severe features associated with chronic illness. A key element of the staging model is to identify and classify the neurobiological processes underlying the disorder and to define potential interventions in the different stages. With the premise that dysfunctional neural mechanisms underlie symptomatology, the integration of categorical phenotypic classifications (class of disorder) with dimensional criteria (domains of dysfunction) becomes crucial. This approach aims to better classify trans-diagnostic dimensions of disease and discrete symptom-specific subgroup populations within biological frameworks, which may lead to the detection of new biomarkers and the development of more effective treatment and prevention strategies.Disclosure of interestThe author has not supplied his declaration of competing interest.

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Clinical staging in severe mental disorder: evidence from neurocognition and neuroimaging

The British Journal of Psychiatry ◽

10.1192/bjp.bp.112.119156 ◽

2013 ◽

Vol 202 (s54) ◽

pp. s11-s17 ◽

Cited By ~ 42

Author(s):

Ashleigh Lin ◽

Renate L. E. P. Reniers ◽

Stephen J. Wood

Keyword(s):

Affective Disorders ◽

Bipolar Affective Disorder ◽

Mental Illnesses ◽

Clinical Staging ◽

Psychotic Symptoms ◽

Clinical Samples ◽

Future Research ◽

Large Variability ◽

Diagnostic Applications ◽

Staging Model

SummaryA new approach to understanding severe mental illnesses such as schizophrenia and affective disorders is to adopt a clinical staging model. Such a model defines the extent of the illness such that earlier and milder phenomena are distinguished from later, more impairing features. Part of the appeal of such a model is that it should have cross-diagnostic applications, but to date there has been no attempt to examine imaging or neurocognrtive evidence for staging in this way. We review these two domains of study with particular focus on major depression and bipolar affective disorder. Although there is some support for the staging model in affective disorders, conclusions are limited by the large variability in the clinical samples studied, especially with regard to the presence of psychotic symptoms. We suggest that future research needs to take a transdiagnostic and longitudinal approach.

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