Sleep and cognition in schizophrenia spectrum disorders: A systematic review protocol.

2020 ◽  
Author(s):  
Sean Carruthers ◽  
Gemma Brunetti ◽  
Susan Rossell
Keyword(s):  
Systematic Review ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Systematic Review Protocol ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Review Protocol ◽  
Spectrum Disorders ◽  
Sleep And Cognition ◽  
The Relationship

Schizophrenia spectrum disorders are chronic and debilitating mental illnesses characterised by both cognitive impairments and sleep deficits. In this systematic review protocol, we outline an approach to examine the available literature investigating the relationship between sleep and cognition in individuals with schizophrenia spectrum disorder.

Development of a suspicion index for secondary schizophrenia using the Delphi method

2021 ◽  
pp. 000486742110257
Author(s):  
Olivier Bonnot ◽  
Jose Luis Insua ◽  
Mark Walterfang ◽  
Juan Vincente Torres ◽  
Stefan Armin Kolb
Keyword(s):  
Clinical Practice ◽  
Sensitivity And Specificity ◽  
Delphi Method ◽  
Schizophrenia Spectrum Disorders ◽  
Differential Distribution ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Aids Diagnosis ◽  
Suspicion Index

Aim: The aim of this study was to develop a suspicion index that aids diagnosis of secondary schizophrenia spectrum disorders in regular clinical practice. Method: We used the Delphi method to rate and refine questionnaire items in consecutive rounds. Differences in mean expert responses for schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders populations allowed to define low/middle/high predictive items, which received different weights. Algorithm performance was tested in 198 disease profiles by means of sensitivity and specificity. Results: Twelve experts completed the Delphi process, and consensus was reached in 19/24 (79.2%) items for schizophrenia spectrum disorders and 17/24 (70.8%) for secondary schizophrenia spectrum disorders. We assigned rounded values to each item category according to their predictive potential. A differential distribution of scores was observed between schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders when applying the suspicion index for validation to 198 disease profiles. Sensitivity and specificity analyses allowed to set a >8/10/16 risk prediction score as a threshold to consider medium/high/very high suspicion of secondary schizophrenia spectrum disorders. Conclusion: Our final outcome was the Secondary Schizophrenia Suspicion Index, the first paper-based and reliable algorithm to discriminate secondary schizophrenia spectrum disorders from schizophrenia spectrum disorders with the potential to help improve the detection of secondary schizophrenia spectrum disorder cases in clinical practice.

scholarly journals Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool

2021 ◽  
pp. 1-11
Author(s):  
J. N. de Boer ◽  
A. E. Voppel ◽  
S. G. Brederoo ◽  
H. G. Schnack ◽  
K. P. Truong ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Structured Interview ◽  
Diagnostic Value ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Speech Technology ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Methods Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. Results The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Conclusions Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

Variable Insight in OCD

2017 ◽  
Author(s):  
Rebecca J. Hamblin ◽  
Jennifer Moonjung Park ◽  
Monica S. Wu ◽  
Eric A. Storch
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Assessment Tools ◽  
Schizophrenia Spectrum Disorders ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Definition Of ◽  
The Relationship ◽  
Insight Into

Individuals with obsessive-compulsive disorder (OCD) often have good insight into the irrational nature of their obsessions and the excessive character of their compulsions, but insight exists along a continuum and is markedly poor in some patients. This chapter reviews the assessment and phenomenological correlates of variable insight in OCD in both pediatric and adult populations. It reviews the definition of insight and its relationship to the evolution of diagnostic criteria for obsessive-compulsive disorder, as well as the major assessment tools used to measure and quantify insight for clinical and research purposes. The relationships between insight and clinical characteristics of OCD, including symptom severity, comorbidity, and treatment response are reviewed, followed by a review of neurobiological correlates of insight and the relationship between poor insight and schizophrenia spectrum disorders.

scholarly journals How do ethnicity and deprivation impact on life expectancy at birth in people with serious mental illness? Observational study in the UK

2020 ◽  
pp. 1-9
Author(s):  
Jayati Das-Munshi ◽  
Chin-Kuo Chang ◽  
Alex Dregan ◽  
Stephani L. Hatch ◽  
Craig Morgan ◽  
...  
Keyword(s):  
General Population ◽  
Life Expectancy ◽  
Bipolar Disorders ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Life Expectancy At Birth ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
The Impact ◽  
Deprived Areas

Abstract Background Across international contexts, people with serious mental illnesses (SMI) experience marked reductions in life expectancy at birth. The intersection of ethnicity and social deprivation on life expectancy in SMI is unclear. The aim of this study was to assess the impact of ethnicity and area-level deprivation on life expectancy at birth in SMI, defined as schizophrenia-spectrum disorders, bipolar disorders and depression, using data from London, UK. Methods Abridged life tables to calculate life expectancy at birth, in a cohort with clinician-ascribed ICD-10 schizophrenia-spectrum disorders, bipolar disorders or depression, managed in secondary mental healthcare. Life expectancy in the study population with SMI was compared with life expectancy in the general population and with those residing in the most deprived areas in England. Results Irrespective of ethnicity, people with SMI experienced marked reductions in life expectancy at birth compared with the general population; from 14.5 years loss in men with schizophrenia-spectrum and bipolar disorders, to 13.2 years in women. Similar reductions were noted for people with depression. Across all diagnoses, life expectancy at birth in people with SMI was lower than the general population residing in the most deprived areas in England. Conclusions Irrespective of ethnicity, reductions in life expectancy at birth among people with SMI are worse than the general population residing in the most deprived areas in England. This trend in people with SMI is similar to groups who experience extreme social exclusion and marginalisation. Evidence-based interventions to tackle this mortality gap need to take this into account.

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