scholarly journals Trait emotional experience in individuals with schizophrenia and youth at clinical high risk for psychosis

BJPsych Open ◽  
2019 ◽  
Vol 5 (5) ◽  
Author(s):  
Claire I. Yee ◽  
Gregory P. Strauss ◽  
Daniel N. Allen ◽  
Claudia M. Haase ◽  
David Kimhy ◽  
...  
Keyword(s):  
High Risk ◽  
Negative Affect ◽  
Positive Affect ◽  
Negative Symptoms ◽  
Clinical Symptoms ◽  
Emotional Experience ◽  
Self Report ◽  
Clinical High Risk ◽  
Clinical Correlates ◽  
Trait Emotions

Background Disturbances in trait emotions are a predominant feature in schizophrenia. However, less is known about (a) differences in trait emotion across phases of the illness such as the clinical high-risk (CHR) phase and (b) whether abnormalities in trait emotion that are associated with negative symptoms are driven by primary (i.e. idiopathic) or secondary (e.g. depression, anxiety) factors. Aims To examine profiles of trait affective disturbance and their clinical correlates in individuals with schizophrenia and individuals at CHR for psychosis. Method In two studies (sample 1: 56 out-patients diagnosed with schizophrenia and 34 demographically matched individuals without schizophrenia (controls); sample 2: 50 individuals at CHR and 56 individuals not at CHR (controls)), participants completed self-report trait positive affect and negative affect questionnaires, clinical symptom interviews (positive, negative, disorganised, depression, anxiety) and community-based functional outcome measures. Results Both clinical groups reported lower levels of positive affect (specific to joy among individuals with schizophrenia) and higher levels of negative affect compared with controls. For individuals with schizophrenia, links were found between positive affect and negative symptoms (which remained after controlling for secondary factors) and between negative affect and positive symptoms. For individuals at CHR, links were found between both affect dimensions and both types of symptom (which were largely accounted for by secondary factors). Conclusions Both clinical groups showed some evidence of reduced trait positive affect and elevated trait negative affect, suggesting that increasing trait positive affect and reducing trait negative affect is an important treatment goal across both populations. Clinical correlates of these emotional abnormalities were more integrally linked to clinical symptoms in individuals with schizophrenia and more closely linked to secondary influences such as depression and anxiety in individuals at CHR. Declaration of interest None.

scholarly journals O3.1. CLUSTER ANALYSIS FINDS THREE CLINICALLY-RELEVANT SUBGROUPS OF TRAIT EMOTIONAL EXPERIENCE IN SCHIZOPHRENIA OUTPATIENTS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S5-S6
Author(s):  
Henry Cowan ◽  
Vijay Mittal ◽  
Daniel Allen ◽  
James Gold ◽  
Gregory Strauss
Keyword(s):  
Negative Affect ◽  
Functional Outcome ◽  
Schizoaffective Disorder ◽  
Negative Symptoms ◽  
Clinical Symptoms ◽  
Emotional Experience ◽  
Symptom Presentation ◽  
Cross Sectional ◽  
Affective Traits ◽  
Trait Affect

Abstract Background Previous research shows that trait emotion is more affected than state emotion in schizophrenia. This literature is also somewhat inconsistent, particularly in terms of specific links between affective traits and clinical symptoms. The current study examined whether subgroups of trait emotional experience predict symptom presentation and functional outcome in schizophrenia. Methods In this cross-sectional observational study, 192 outpatients diagnosed with schizophrenia or schizoaffective disorder (SZ) and 149 matched healthy controls completed the trait version of the Positive and Negative Affect Scale and symptom and functional outcome assessments. Cluster and discriminant function analyses identified distinct profiles of trait affect, which were then compared on clinical and functional variables. Results Three SZ clusters reflected normative affect (n = 80, 42%), low trait positive affect (PA; n = 54, 28%), and high trait negative affect (NA; n = 58, 30%), compared to controls. Symptom profiles differentiated the three subgroups. Compared to the Normative Affect cluster, the Low PA cluster had more severe negative symptoms; the High NA cluster had more severe positive symptoms, disorganization, anxiety, and depression; and both the Low PA and High NA cluster had poorer overall functioning. Diagnostic and medication status also differentiated the three subgroups. The Low PA subgroup was most likely to be prescribed 1st-generation antipsychotics, while the High NA subgroup was most likely to be diagnosed with schizoaffective disorder. Discussion Distinct subgroups with unique trait affect profiles can be identified within the broader diagnosis of schizophrenia. These subgroups show meaningful clinical differences in presentation, with theoretical and clinical implications.

scholarly journals Lab-Based and Self-Reported Indices of Fitness Show Lowered Fitness and Insight into Fitness in Individuals at Clinical High Risk for Psychosis

2020 ◽  
Author(s):  
Katherine S. F. Damme ◽  
Richard P. Sloan ◽  
Matthew N. Bartels ◽  
Alara Ozsan ◽  
Luz H. Ospina ◽  
...  
Keyword(s):  
High Risk ◽  
Healthy Volunteers ◽  
Negative Symptoms ◽  
Population Characteristics ◽  
Self Report ◽  
Positive Symptoms ◽  
Clinical High Risk ◽  
Laboratory Findings ◽  
Exercise Interventions ◽  
Intensity Of Exercise

AbstractIntroductionExercise is a promising intervention for clinical high-risk for psychosis (CHR) populations, who have attenuated positive symptoms, but evidence suggests that these youth may require tailored exercise interventions. Presently, the scope of the problem is unknown, as these youth may not be reliable reporters on fitness. This issue is compounded by the fact that there have been no investigations that utilized a formal fitness assessment in this critical population. The present study aims to determine the level of fitness in CHR youth with lab-based measures, test how effectively self-report measures characterize objective fitness indices, and explore clinical factors that may be interrupting reliable self-report-an important tool if these interventions are to be taken to scale.MethodsForty CHR individuals completed an exercise survey and lab-based indices of fitness (i.e., VO2max and BMI). Forty healthy volunteers completed lab indices of fitness and a structured clinical interview ruling out the presence of psychiatric illness.ResultsCHR youth showed greater BMI and lower VO2max compared to healthy volunteers. In the CHR group, abstract self-report items (perceived fitness) did not reflect lab indices of fitness, whereas specific exercise behaviors (intensity of exercise) showed stronger correlations with laboratory-based fitness measurements. Exploratory analyses suggested that positive symptoms involving grandiosity, and negative symptoms such as avolition, correlated with discrepancy between self-perception and laboratory findings of fitness.DiscussionResults suggest that CHR individuals are less objectively fit than matched controls, and that it will be important to consider unique population characteristics when weighing self-report data.

scholarly journals Alterations in Emotional Diversity Correspond With Increased Severity of Attenuated Positive and Negative Symptoms in the Clinical High-Risk Syndrome

2021 ◽  
Vol 12 ◽  
Author(s):  
Zachary Anderson ◽  
Tina Gupta ◽  
William Revelle ◽  
Claudia M. Haase ◽  
Vijay A. Mittal
Keyword(s):  
High Risk ◽  
Negative Symptoms ◽  
Medication Use ◽  
Structured Interview ◽  
Clinical High Risk ◽  
Future Studies ◽  
Clinical Interviews ◽  
Clinical Correlates ◽  
Psychosis Risk ◽  
Positive And Negative Symptoms

Background: Alterations in emotional functioning are a key feature of psychosis and are present in individuals with a clinical high-risk (CHR) syndrome. However, little is known about alterations in emotional diversity (i.e., the variety and relative abundance of emotions that humans experience) and clinical correlates in this population.Methods: Individuals meeting criteria for a CHR syndrome (N = 47) and matched healthy controls (HC) (N = 58) completed the modified Differential Emotions Scale (used to derive scores of total, positive, and negative emotional diversity) and clinical interviews (i.e., Structured Interview for Psychosis-Risk Syndromes).Results: Findings showed that the CHR group experienced lower levels of positive emotional diversity compared to HCs. Among the CHR individuals, lower levels of positive and higher levels of negative emotional diversity were associated with more severe attenuated positive and negative symptoms. Analyses controlled for mean levels of emotion and current antipsychotic medication use.Discussion: Results demonstrate that altered emotional diversity (in particular lower levels of positive and higher levels of negative emotional diversity) is a clinically relevant marker in CHR individuals, above and beyond alterations in mean levels of emotional experiences. Future studies may probe sources, downstream consequences, and potential modifiability of decreased emotional diversity in individuals at CHR.

scholarly journals The relationship of social function to depressive and negative symptoms in individuals at clinical high risk for psychosis

2010 ◽  
Vol 41 (2) ◽  
pp. 251-261 ◽  
Author(s):  
C. M. Corcoran ◽  
D. Kimhy ◽  
M. A. Parrilla-Escobar ◽  
V. L. Cressman ◽  
A. D. Stanford ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
High Risk ◽  
Negative Symptoms ◽  
Skills Training ◽  
Social Function ◽  
Self Report ◽  
Clinical High Risk ◽  
Social Dysfunction ◽  
Relationship Of ◽  
The Relationship

BackgroundSocial dysfunction is a hallmark symptom of schizophrenia which commonly precedes the onset of psychosis. It is unclear if social symptoms in clinical high-risk patients reflect depressive symptoms or are a manifestation of negative symptoms.MethodWe compared social function scores on the Social Adjustment Scale-Self Report between 56 young people (aged 13–27 years) at clinical high risk for psychosis and 22 healthy controls. The cases were also assessed for depressive and ‘prodromal’ symptoms (subthreshold positive, negative, disorganized and general symptoms).ResultsPoor social function was related to both depressive and negative symptoms, as well as to disorganized and general symptoms. The symptoms were highly intercorrelated but linear regression analysis demonstrated that poor social function was primarily explained by negative symptoms within this cohort, particularly in ethnic minority patients.ConclusionsAlthough this study demonstrated a relationship between social dysfunction and depressive symptoms in clinical high-risk cases, this association was primarily explained by the relationship of each of these to negative symptoms. In individuals at heightened risk for psychosis, affective changes may be related to a progressive decrease in social interaction and loss of reinforcement of social behaviors. These findings have relevance for potential treatment strategies for social dysfunction in schizophrenia and its risk states and predict that antidepressant drugs, cognitive behavioral therapy and/or social skills training may be effective.

scholarly journals Dysregulation of complement and coagulation pathways: emerging mechanisms in the development of psychosis

2021 ◽  
Author(s):  
Meike Heurich ◽  
Melanie Föcking ◽  
David Mongan ◽  
Gerard Cagney ◽  
David R. Cotter
Keyword(s):  
High Risk ◽  
Psychotic Disorder ◽  
Psychotic Disorders ◽  
Clinical Symptoms ◽  
First Episode Psychosis ◽  
Specific Protein ◽  
First Episode ◽  
Clinical High Risk ◽  
Blood Proteins ◽  
Episode Psychosis

AbstractEarly identification and treatment significantly improve clinical outcomes of psychotic disorders. Recent studies identified protein components of the complement and coagulation systems as key pathways implicated in psychosis. These specific protein alterations are integral to the inflammatory response and can begin years before the onset of clinical symptoms of psychotic disorder. Critically, they have recently been shown to predict the transition from clinical high risk to first-episode psychosis, enabling stratification of individuals who are most likely to transition to psychotic disorder from those who are not. This reinforces the concept that the psychosis spectrum is likely a central nervous system manifestation of systemic changes and highlights the need to investigate plasma proteins as diagnostic or prognostic biomarkers and pathophysiological mediators. In this review, we integrate evidence of alterations in proteins belonging to the complement and coagulation protein systems, including the coagulation, anticoagulation, and fibrinolytic pathways and their dysregulation in psychosis, into a consolidated mechanism that could be integral to the progression and manifestation of psychosis. We consolidate the findings of altered blood proteins relevant for progression to psychotic disorders, using data from longitudinal studies of the general population in addition to clinical high-risk (CHR) individuals transitioning to psychotic disorder. These are compared to markers identified from first-episode psychosis and schizophrenia as well as other psychosis spectrum disorders. We propose the novel hypothesis that altered complement and coagulation plasma levels enhance their pathways’ activating capacities, while low levels observed in key regulatory components contribute to excessive activation observed in patients. This hypothesis will require future testing through a range of experimental paradigms, and if upheld, complement and coagulation pathways or specific proteins could be useful diagnostic or prognostic tools and targets for early intervention and preventive strategies.

scholarly journals Longitudinal outcome of attenuated positive symptoms, negative symptoms, functioning and remission in people at clinical high risk for psychosis: a meta-analysis

2021 ◽  
Vol 36 ◽  
pp. 100909
Author(s):  
Gonzalo Salazar de Pablo ◽  
Filippo Besana ◽  
Vincenzo Arienti ◽  
Ana Catalan ◽  
Julio Vaquerizo-Serrano ◽  
...  
Keyword(s):  
High Risk ◽  
Negative Symptoms ◽  
Meta Analysis ◽  
Positive Symptoms ◽  
Clinical High Risk ◽  
Longitudinal Outcome

scholarly journals Secondary sources of negative symptoms in those meeting criteria for a clinical high-risk syndrome

2021 ◽  
Author(s):  
Tina Gupta ◽  
Gregory P. Strauss ◽  
Henry R. Cowan ◽  
Andrea Pelletier-Baldelli ◽  
Lauren M. Ellman ◽  
...  
Keyword(s):  
High Risk ◽  
Negative Symptoms ◽  
Clinical High Risk ◽  
Secondary Sources

scholarly journals Association of baseline inflammatory markers and the development of negative symptoms in individuals at clinical high risk for psychosis

2019 ◽  
Vol 76 ◽  
pp. 268-274 ◽  
Author(s):  
David R. Goldsmith ◽  
Ebrahim Haroon ◽  
Andrew H. Miller ◽  
Jean Addington ◽  
Carrie Bearden ◽  
...  
Keyword(s):  
High Risk ◽  
Inflammatory Markers ◽  
Negative Symptoms ◽  
Clinical High Risk

scholarly journals Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors

10.2196/16875 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16875 ◽  
Author(s):  
Nicholas C Jacobson ◽  
Berta Summers ◽  
Sabine Wilhelm
Keyword(s):  
Social Anxiety ◽  
Negative Affect ◽  
Positive Affect ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Self Report ◽  
Sensor Data ◽  
Digital Phenotyping ◽  
Passive Sensor ◽  
Digital Biomarkers

Background Social anxiety disorder is a highly prevalent and burdensome condition. Persons with social anxiety frequently avoid seeking physician support and rarely receive treatment. Social anxiety symptoms are frequently underreported and underrecognized, creating a barrier to the accurate assessment of these symptoms. Consequently, more research is needed to identify passive biomarkers of social anxiety symptom severity. Digital phenotyping, the use of passive sensor data to inform health care decisions, offers a possible method of addressing this assessment barrier. Objective This study aims to determine whether passive sensor data acquired from smartphone data can accurately predict social anxiety symptom severity using a publicly available dataset. Methods In this study, participants (n=59) completed self-report assessments of their social anxiety symptom severity, depressive symptom severity, positive affect, and negative affect. Next, participants installed an app, which passively collected data about their movement (accelerometers) and social contact (incoming and outgoing calls and texts) over 2 weeks. Afterward, these passive sensor data were used to form digital biomarkers, which were paired with machine learning models to predict participants’ social anxiety symptom severity. Results The results suggested that these passive sensor data could be utilized to accurately predict participants’ social anxiety symptom severity (r=0.702 between predicted and observed symptom severity) and demonstrated discriminant validity between depression, negative affect, and positive affect. Conclusions These results suggest that smartphone sensor data may be utilized to accurately detect social anxiety symptom severity and discriminate social anxiety symptom severity from depressive symptoms, negative affect, and positive affect.

scholarly journals Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors (Preprint)

2019 ◽  
Author(s):  
Nicholas C Jacobson ◽  
Berta Summers ◽  
Sabine Wilhelm
Keyword(s):  
Social Anxiety ◽  
Negative Affect ◽  
Positive Affect ◽  
Symptom Severity ◽  
Anxiety Symptom ◽  
Self Report ◽  
Sensor Data ◽  
Digital Phenotyping ◽  
Passive Sensor ◽  
Digital Biomarkers

BACKGROUND Social anxiety disorder is a highly prevalent and burdensome condition. Persons with social anxiety frequently avoid seeking physician support and rarely receive treatment. Social anxiety symptoms are frequently underreported and underrecognized, creating a barrier to the accurate assessment of these symptoms. Consequently, more research is needed to identify passive biomarkers of social anxiety symptom severity. Digital phenotyping, the use of passive sensor data to inform health care decisions, offers a possible method of addressing this assessment barrier. OBJECTIVE This study aims to determine whether passive sensor data acquired from smartphone data can accurately predict social anxiety symptom severity using a publicly available dataset. METHODS In this study, participants (n=59) completed self-report assessments of their social anxiety symptom severity, depressive symptom severity, positive affect, and negative affect. Next, participants installed an app, which passively collected data about their movement (accelerometers) and social contact (incoming and outgoing calls and texts) over 2 weeks. Afterward, these passive sensor data were used to form digital biomarkers, which were paired with machine learning models to predict participants’ social anxiety symptom severity. RESULTS The results suggested that these passive sensor data could be utilized to accurately predict participants’ social anxiety symptom severity (<i>r</i>=0.702 between predicted and observed symptom severity) and demonstrated discriminant validity between depression, negative affect, and positive affect. CONCLUSIONS These results suggest that smartphone sensor data may be utilized to accurately detect social anxiety symptom severity and discriminate social anxiety symptom severity from depressive symptoms, negative affect, and positive affect.

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