A model of psychosis and its relationship with impairment

Psychosis superspectrum I: Nosology, etiology, and lifespan development

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

What is a psychopathology dimension?

Coherence in the science and practice of mental health assessment depends upon a tight connection between psychopathology concepts that are used and the way those concepts are operationalized and defined. In contrast, the use of the same word to mean more than one thing contributes to incoherence, inefficiency, and confusion. In this paper, we review three possible meanings of the word "dimension" as it relates to the assessment of psychopathology and describe how the indiscriminate use of this word has caused confusion in the general context of the transition to a more evidence-based approach to mental health diagnosis. We attempt to disambiguate the term "dimension" by demarcating three concepts that can be distinguished based on different empirical standards: continuous variables, unidimensional dimensions, and distinct dimensions.

Les progrès dans la réalisation de la classification quantitative de la psychopathologie☆

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Progress in achieving quantitative classification of psychopathology

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Skew t Mixture Latent State-Trait Analysis: A Monte Carlo Simulation Study on Statistical Performance

This simulation study assessed the statistical performance of a skew t mixture latent state-trait (LST) model for the analysis of longitudinal data. The model aims to identify interpretable latent classes with class-specific LST model parameters. A skew t-distribution within classes is allowed to account for non-normal outcomes. This flexible function covers heavy tails and may reduce the risk of identifying spurious classes, e.g., in case of outliers. Sample size, number of occasions and skewness of the trait variable were varied. Generally, parameter estimation accuracy increases with increasing numbers of observations and occasions. Larger bias compared to other parameters occurs for parameters referring to the skew t-distribution and variances of the latent trait variables. Standard error estimation accuracy shows diffuse patterns across conditions and parameters. Overall model performance is acceptable for large conditions, even though none of the models is free from bias. The application of the skew t mixture model in case of large numbers of occasions and observations may be possible, but results should be treated with caution. Moreover, the skew t approach may be useful for other mixture models.

Dilemmas in the treatment of early-onset first-episode psychosis

Early-onset first-episode psychosis (EOP) is a severe mental disorder that can pose a number of challenges to clinicians, young people and their families. Its assessment and differentiation from other neurodevelopmental and mental health conditions may at times be difficult, its treatment may not always lead to optimal outcomes and can be associated with significant side effects, and its long-term course and prognosis seem to be less favourable compared with the adult-onset disorder. In this paper, we discuss some dilemmas associated with the evaluation and management of EOP and propose approaches that can be used in the clinical decision-making process. A detailed and well-informed assessment of psychotic symptoms and comorbidities, a systematic approach to treatment with minimum possible medication doses and close monitoring of its effectiveness and adverse effects, and multidimensional interventions taking into consideration risks and expectations associated with EOP, are paramount in the achievement of the most favourable outcomes for affected children and young people.

Association between processing speed and subclinical psychotic symptoms in the general population: focusing on sex differences

Evidence is growing that persons along the schizophrenia spectrum, i.e., those who also display subclinical psychotic symptoms, exhibit deficits across a broad range of neuropsychological domains. Because sex differences in the association between cognitive deficits and psychosis have thus far been mostly neglected, we believe that ours is the first study specifically focused upon those differences when examining the relationship between subclinical psychosis and processing speed. Using a sample of 213 persons from the general population from Zurich, Switzerland, psychotic symptoms were assessed with three different questionnaires including the Schizotypal Personality Questionnaire, an adaptation of the Structured Interview for Assessing Perceptual Anomalies, and the Paranoia Checklist. Processing speed was assessed with the WAIS digit-symbol coding test. Two higher-order psychosis domains were factor-analytically derived from the various psychosis subscales and then subjected to a series of linear regression analyses. The results demonstrate that in both men and women associations between subclinical psychosis domains and processing speed were weak to moderate (β ranging from -0.18 to -0.27; all p<0.05). However, we found no sex-differences in the interrelation of subclinical psychosis and processing speed (ΔR(2)<0.005; p>0.30). In conclusion, it appears that sex differences in psychosis manifest themselves only at the high end of the continuum (full-blown schizophrenia) and not across the sub-threshold range. The small magnitude of the effects reported herein conforms to the etiopathology of the disorder. Since schizophrenia and related disorders from the spectrum are assumed to be multifactorial diseases, it follows that many etiological components of small effect are involved.

Internal structure of the Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale: Evidence for a general factor

BACKGROUND

Psychotic-like experiences (PLEs) are prevalent in the general population and are associated with poor mental health and a higher risk of psychiatric disorders. The Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale is a self-screening questionnaire to address subclinical positive psychotic symptoms (PPEs) in community contexts. Although its psychometric properties seem to be adequate to screen PLEs, further research is needed to evaluate certain validity aspects, particularly its internal structure and its functioning in different populations.

AIM

To uncover the optimal factor structure of the CAPE-P15 scale in adolescents aged 13 to 18 years using factorial analysis methods suitable to manage categorical variables.

METHOD

A sample of 727 students from six secondary public schools and 245 university students completed the CAPE-P15. The dimensionality of the CAPE-P15 was tested through exploratory structural equation models (ESEMs). Based on the ESEM results, we conducted a confirmatory factor analysis (CFA) to contrast two factorial structures that potentially underlie the symptoms described by the scale: a) three correlated factors and b) a hierarchical model composed of a general PLE factor plus three specific factors (persecutory ideation, bizarre experiences, and perceptual abnormalities).

RESULTS

The underlying structure of PLEs assessed by the CAPE-P15 is consistent with both multidimensional and hierarchical solutions. However, the latter show the best fit. Our findings reveal the existence of a strong general factor underlying scale scores. Compared with the specific factors, the general factor explains most of the common variance observed in subjects' responses.

CONCLUSIONS

The findings suggest that the factor structure of subthreshold psychotic experiences addressed by the CAPE-P15 can be adequately represented by a general factor and three separable specific traits, supporting the hypothesis according to which there might be a common source underlying PLEs.

Neurodevelopmental Plasticity in Pre- and Postnatal Environmental Interactions: Implications for Psychiatric Disorders from an Evolutionary Perspective

Psychiatric disorders are disadvantageous behavioral phenotypes in humans. Accordingly, a recent epidemiological study has reported decreased fecundity in patients with psychiatric disorders, such as schizophrenia and autism spectrum disorders. Moreover, the fecundity of the relatives of these patients is not exceedingly higher compared to the fecundity of the relatives of normal subjects. Collectively, the prevalence of psychiatric disorders among humans is expected to decrease over generations. Nevertheless, in reality, the prevalence rates of psychiatric disorders in humans either have been constant over a long period of time or have even increased more recently. Several attempts to explain this fact have been made using biological mechanisms, such as de novo gene mutations or variants, although none of these explanations is fully comprehensive. Here, we propose a hypothesis towards understanding the biological mechanisms of psychiatric disorders from evolutionary perspectives. This hypothesis considers that behavioral phenotypes associated with psychiatric disorders might have emerged in the evolution of organisms as a neurodevelopmental adaptation against adverse environmental conditions associated with stress.