Dataset Information

Modeling Incoherent Discourse in Non-Affective Psychosis.

ABSTRACT:

Background

Computational linguistic methodology allows quantification of speech abnormalities in non-affective psychosis. For this patient group, incoherent speech has long been described as a symptom of formal thought disorder. Our study is an interdisciplinary attempt at developing a model of incoherence in non-affective psychosis, informed by computational linguistic methodology as well as psychiatric research, which both conceptualize incoherence as associative loosening. The primary aim of this pilot study was methodological: to validate the model against clinical data and reduce bias in automated coherence analysis.

Methods

Speech samples were obtained from patients with a diagnosis of schizophrenia or schizoaffective disorder, who were divided into two groups of n = 20 subjects each, based on different clinical ratings of positive formal thought disorder, and n = 20 healthy control subjects.

Results

Coherence metrics that were automatically derived from interview transcripts significantly predicted clinical ratings of thought disorder. Significant results from multinomial regression analysis revealed that group membership (controls vs. patients with vs. without formal thought disorder) could be predicted based on automated coherence analysis when bias was considered. Further improvement of the regression model was reached by including variables that psychiatric research has shown to inform clinical diagnostics of positive formal thought disorder.

Conclusions

Automated coherence analysis may capture different features of incoherent speech than clinical ratings of formal thought disorder. Models of incoherence in non-affective psychosis should include automatically derived coherence metrics as well as lexical and syntactic features that influence the comprehensibility of speech.

SUBMITTER: Just SA

PROVIDER: S-EPMC7466436 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modeling Incoherent Discourse in Non-Affective Psychosis.

Just Sandra A SA Haegert Erik E Kořánová Nora N Bröcker Anna-Lena AL Nenchev Ivan I Funcke Jakob J Heinz Andreas A Bermpohl Felix F Stede Manfred M Montag Christiane C

Frontiers in psychiatry 20200819

<h4>Background</h4>Computational linguistic methodology allows quantification of speech abnormalities in non-affective psychosis. For this patient group, incoherent speech has long been described as a symptom of formal thought disorder. Our study is an interdisciplinary attempt at developing a model of incoherence in non-affective psychosis, informed by computational linguistic methodology as well as psychiatric research, which both conceptualize incoherence as associative loosening. The primary ...[more]

PMID: 32973586

Similar Datasets

Project description:Psychosis disorders share overlapping symptoms and are characterized by a wide-spread breakdown in functional brain integration. Although neuroimaging studies have identified numerous connectivity abnormalities in affective and non-affective psychoses, whether they have specific or unique connectivity abnormalities, especially within the early stage is still poorly understood. The early phase of psychosis is a critical period with fewer chronic confounds and when treatment intervention may be most effective. In this work, we examined whole-brain functional network connectivity (FNC) from both static and dynamic perspectives in patients with affective psychosis (PAP) or with non-affective psychosis (PnAP) and healthy controls (HCs). A fully automated independent component analysis (ICA) pipeline called "Neuromark" was applied to high-quality functional magnetic resonance imaging (fMRI) data with 113 early-phase psychosis patients (32 PAP and 81 PnAP) and 52 HCs. Relative to the HCs, both psychosis groups showed common abnormalities in static FNC (sFNC) between the thalamus and sensorimotor domain, and between subcortical regions and the cerebellum. PAP had specifically decreased sFNC between the superior temporal gyrus and the paracentral lobule, and between the cerebellum and the middle temporal gyrus/inferior parietal lobule. On the other hand, PnAP showed increased sFNC between the fusiform gyrus and the superior medial frontal gyrus. Dynamic FNC (dFNC) was investigated using a combination of a sliding window approach, clustering analysis, and graph analysis. Three reoccurring brain states were identified, among which both psychosis groups had fewer occurrences in one antagonism state (state 2) and showed decreased network efficiency within an intermediate state (state 1). Compared with HCs and PnAP, PAP also showed a significantly increased number of state transitions, indicating more unstable brain connections in affective psychosis. We further found that the identified connectivity features were associated with the overall positive and negative syndrome scale, an assessment instrument for general psychopathology and positive symptoms. Our findings support the view that subcortical-cortical information processing is disrupted within five years of the initial onset of psychosis and provide new evidence that abnormalities in both static and dynamic connectivity consist of shared and unique features for the early affective and non-affective psychoses.

Project description:AimAlthough mindfulness-based interventions (MBIs) are routinely used in clinical practice, a comprehensive synthesis of the effectiveness of MBIs for non-affective psychosis has yet to be conducted. The aim of the present review and meta-analysis was to investigate the effectiveness of MBIs including those with mindfulness as an active treatment component for alleviating symptoms of psychosis to inform future clinical practice.MethodsA systematic review of studies published in journals or in dissertations in CINAHL, PubMed, EMBASE, PsycINFO, CENTRAL, ISRCTN, or CNKI from January 1990 until December 2020. A total of 31 eligible studies (n = 2146) were included.ResultsEffect-size estimates suggested that 22 independent samples (n = 1632) produced a statistically significant small effect for psychotic symptoms (g = -0.48), and with a clinically significant reduction of 50% from baseline (pooled OR: 1.84). Separate meta-analyses demonstrated small effects for affective symptoms (g = -0.44) and small-to-large positive effects for quality of life (g = 0.38), mindfulness skills (g = 0.45), and insight into illness/treatment (g = 1.35). The heterogeneity was high across the studies.ConclusionResults suggest that short-term MBIs can be beneficial for non-affective psychosis. Future research is needed to test the efficacy and safety of dedicated MBIs for this population group over a longer term. KEY MESSAGESSchizophrenia spectrum and other psychotic disorders, also known as non-affective psychosis, is the most chronic and debilitating type of psychosis, seriously affecting every aspect of a person's life, including social, occupational, or general functioning.The aim of the current systematic review and meta-analysis was to investigate formerly unexamined questions regarding the clinical significance of MBIs including yoga as an increasingly utilized, conceptualized psychological intervention on overall psychotic symptoms for people with non-affective psychosis.No serious adverse events were reported in the studies, suggesting that MBIs may be safe interventions, while there is robust evidence to support the view that MBIs are beneficial to young people in particular.

Dataset Information

Modeling Incoherent Discourse in Non-Affective Psychosis.

Background

Methods

Results

Conclusions

Publications

Modeling Incoherent Discourse in Non-Affective Psychosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets