Non-social Cognition Research Articles

The spectrum effect: Convergence of clinical and neuropsychological characteristics in adults referred for autism assessment

Clinical and neuropsychological profiles of adults referred for autism assessment are not thoroughly understood, and information derived from studies comparing autistic adults to neurotypical controls might not be accurate to infer on individuals in a real-world, clinical setting. 263 adults (aged 18–65 years, 70 % males) referred to our clinic with a suspected diagnosis of autism were clinically explored and administered neuropsychological investigations. The suspected diagnosis was either confirmed or rejected. We conducted multivariate and post-hoc univariate analyses of covariance (MANCOVA; ANCOVA), controlling for possible confounders, to evaluate differences between autistic and non-autistic participants and further associations. Effect sizes (partial η²) were calculated for significant results. There were no significant differences in age means and sex ratios. Both groups showed high Autism Questionnaire (AQ) scores, high schizoid, avoidant, and obsessive-compulsive scores, and mild depressive symptoms, without significant difference between groups. The effect sizes of differences ranged from negligible to small for measures of nonsocial cognition, but were large for a measure of social cognition, the emotion recognition 40 (ER40). Autistic and non-autistic participants present converging features across multiple measures. In this diagnostic setting, psychiatric and neuropsychological measures are helpful in identifying individual difficulties and strengths. However, most of them, including the AQ, are poor indicators of autism. Our results mostly aligned with previous research and showed that information derived from comparisons to neurotypical controls cannot be directly transferred to a real-world setting. Detected impairments in emotion recognition were fairly specific to autism, expanding on previous findings.

Using machine learning to understand social isolation and loneliness in schizophrenia, bipolar disorder, and the community

Social disconnection, including objective social isolation and subjective loneliness, is linked to substantial health risks. Yet, little is known about the predictors of social disconnection in individuals with mental illness. Here, we used machine learning to identify predictors of social isolation and loneliness in schizophrenia (N = 72), a psychiatric condition associated with social disconnection. For comparison, we also included two other groups: a psychiatric comparison sample of bipolar disorder (N = 48) and a community sample enriched for social isolation (N = 151). We fitted statistical models of social isolation and loneliness within and across groups. Each model included five candidate predictors: social avoidance motivation, depression, nonsocial cognition, social anhedonia, and social cognition. The results showed that social anhedonia explained unique variance in social isolation and loneliness in all samples, suggesting that it contributes to social isolation and loneliness broadly. However, nonsocial cognition explained unique variance in social isolation only within schizophrenia. Thus, social anhedonia could be a potential intervention target across populations, whereas nonsocial cognition may play a unique role in determining social disconnection in schizophrenia.

Multivariate Association Between Functional Connectivity Gradients and Cognition in Schizophrenia Spectrum Disorders

BackgroundSchizophrenia spectrum disorders (SSDs), which are characterized by social cognitive deficits, have been associated with dysconnectivity in unimodal (e.g., visual, auditory) and multimodal (e.g., default mode and frontoparietal) cortical networks. However, little is known about how such dysconnectivity is related to social and nonsocial cognition and how such brain-behavior relationships associate with clinical outcomes of SSDs. MethodsWe analyzed cognitive (nonsocial and social) measures and resting-state functional magnetic resonance imaging data from the SPINS [Social Processes Initiative in Neurobiology of the Schizophrenia(s)] study (247 stable participants with SSDs and 172 healthy control participants, ages 18–55 years). We extracted gradients from parcellated connectomes and examined the association between the first 3 gradients and the cognitive measures using partial least squares correlation (PLSC). We then correlated the PLSC dimensions with functioning and symptoms in the SSD group. ResultsThe SSD group showed significantly lower differentiation on all 3 gradients. The first PLSC dimension explained 68.53% (p < .001) of the covariance and showed a significant difference between the SSD and the control group (bootstrap p < .05). PLSC showed that all cognitive measures were associated with gradient scores of unimodal and multimodal networks (gradient 1); auditory, sensorimotor, and visual networks (gradient 2); and perceptual networks and the striatum (gradient 3), which were less differentiated in SSDs. Furthermore, the first dimension was positively correlated with negative symptoms and functioning in the SSD group. ConclusionsThese results suggest a potential role of lower differentiation of brain networks in cognitive and functional impairments in SSDs.

A Systematic Review and Meta-Analysis of Social Cognition Among People Living with HIV: Implications for Non-Social Cognition and Social Everyday Functioning.

Social cognition-the complex mental ability to perceive social stimuli and negotiate the social environment-has emerged as an important cognitive ability needed for social functioning, everyday functioning, and quality of life. Deficits in social cognition have been well documented in those with severe mental illness including schizophrenia and depression, those along the autism spectrum, and those with other brain disorders where such deficits profoundly impact everyday life. Moreover, subtle deficits in social cognition have been observed in other clinical populations, especially those that may have compromised non-social cognition (i.e., fluid intelligence such as memory). Among people living with HIV (PLHIV), 44% experience cognitive impairment; likewise, social cognitive deficits in theory of mind, prosody, empathy, and emotional face recognition/perception are gradually being recognized. This systematic review and meta-analysis aim to summarize the current knowledge of social cognitive ability among PLHIV, identified by 14 studies focused on social cognition among PLHIV, and provides an objective consensus of the findings. In general, the literature suggests that PLHIV may be at-risk of developing subtle social cognitive deficits that may impact their everyday social functioning and quality of life. The causes of such social cognitive deficits remain unclear, but perhaps develop due to (1) HIV-related sequelae that are damaging the same neurological systems in which social cognition and non-social cognition are processed; (2) stress related to coping with HIV disease itself that overwhelms one's social cognitive resources; or (3) may have been present pre-morbidly, possibly contributing to an HIV infection. From this, a theoretical framework is proposed highlighting the relationships between social cognition, non-social cognition, and social everyday functioning.

Early identification of autism spectrum disorder based on machine learning with eye-tracking data

BackgroundEarly identification of autism spectrum disorder (ASD) improves long-term outcomes, yet significant diagnostic delays persist. MethodsA retrospective cohort of 449 children (ASD: 246, typically developing [TD]: 203) was used for model development. Eye-movement data were collected from the participants watching videos that featured eye-tracking paradigms for assessing social and non-social cognition. Five machine learning algorithms, namely random forest, support vector machine, logistic regression, artificial neural network, and extreme gradient boosting, were trained to classify children with ASD and TD. The best-performing algorithm was selected to build the final model which was further evaluated in a prospective cohort of 80 children. The Shapley values interpreted important eye-tracking features. ResultsRandom forest outperformed other algorithms during model development and achieved an area under the curve of 0.849 (< 3 years: 0.832, ≥ 3 years: 0.868) on the external validation set. Of the ten most important eye-tracking features, three measured social cognition, and the rest were related to non-social cognition. A deterioration in model performance was observed using only the social or non-social cognition-related eye-tracking features. LimitationsThe sample size of this study, although larger than that of existing studies of ASD based on eye-tracking data, was still relatively small compared to the number of features. ConclusionsMachine learning models based on eye-tracking data have the potential to be cost- and time-efficient digital tools for the early identification of ASD. Eye-tracking phenotypes related to social and non-social cognition play an important role in distinguishing children with ASD from TD children.

Heterogeneity in functional connectivity: Dimensional predictors of individual variability during rest and task fMRI in psychosis

BackgroundIndividuals with schizophrenia spectrum disorders (SSD) often demonstrate cognitive impairments, associated with poor functional outcomes. While neurobiological heterogeneity has posed challenges when examining social cognition in SSD, it provides a unique opportunity to explore brain-behavior relationships. The aim of this study was to investigate the relationship between individual variability in functional connectivity during resting state and the performance of a social task and social and non-social cognition in a large sample of controls and individuals diagnosed with SSD. MethodsNeuroimaging and behavioral data were analyzed for 193 individuals with SSD and 155 controls (total n = 348). Individual variability was quantified through mean correlational distance (MCD) of functional connectivity between participants; MCD was defined as a global ‘variability score’. Pairwise correlational distance was calculated as 1 – the correlation coefficient between a given pair of participants, and averaging distance from one participant to all other participants provided the mean correlational distance metric. Hierarchical regressions were performed on variability scores derived from resting state and Empathic Accuracy (EA) task functional connectivity data to determine potential predictors (e.g., age, sex, neurocognitive and social cognitive scores) of individual variability. ResultsGroup comparison between SSD and controls showed greater SSD MCD during rest (p = 0.00038), while no diagnostic differences were observed during task (p = 0.063). Hierarchical regression analyses demonstrated the persistence of a significant diagnostic effect during rest (p = 0.008), contrasting with its non-significance during the task (p = 0.50), after social cognition was added to the model. Notably, social cognition exhibited significance in both resting state and task conditions (both p = 0.01). ConclusionsDiagnostic differences were more prevalent during unconstrained resting scans, whereas the task pushed participants into a more common pattern which better emphasized transdiagnostic differences in cognitive abilities. Focusing on variability may provide new opportunities for interventions targeting specific cognitive impairments to improve functional outcomes.

Familial Risk for Schizophrenia vs Bipolar Disorder and Task-Based Neural Activation: A functional Magnetic Resonance Imaging Meta-Analysis.

Individuals at familial risk for developing schizophrenia (FRSZ) or bipolar disorder (FRBD) have shared and unique genetic risks. Few studies have compared neural activation between these two groups. Therefore, the present meta-analysis investigated functional brain similarities and differences between FRSZ and FRBD individuals. A systematic literature review was conducted of articles that compared FRSZ or FRBD individuals to healthy controls (31 FRSZ and 22 FRBD). Seed-based d mapping was used to conduct the meta-analysis. Analyses included comparisons of FRSZ to controls, FRBD to controls, and both relative groups to each other. Using a highly conservative family-wise error rate correction, there were no significant findings. Using a less conservative threshold, FRSZ compared to controls had lower activation in the left precuneus (Puncorrected = .02) across all studies and in the left middle frontal gyrus (Puncorrected = .03) in nonsocial cognition studies. FRBD compared to controls had lower activation in the left superior parietal gyrus (Puncorrected = .03) and right angular gyrus (Puncorrected = .03) in nonsocial cognition studies, and higher activation in the left superior frontal gyrus (Puncorrected = .01) in social tasks. Differences between FRSZ and FRBD were not significant. There were few robust differences between FRSZ or FRBD compared to controls. This suggests only weak support for neural activation differences between individuals at genetic risk for schizophrenia or bipolar disorder and controls. The tentative findings observed were in different brain regions for FRSZ and FRBD, with no strong evidence for shared effects between schizophrenia and bipolar genetic risk on neural activation.

Beyond cognitive deficits: how social class shapes social cognition.

Lower social class is thought to contribute to poorer executive functioning and working memory. Nevertheless, lower social class individuals consistently outperform their higher-class counterparts on social cognitive tasks that rely on similar underlying cognitive processes (e.g., working memory and executive functioning). Why would lower social class inhibit such processes in one domain, but promote them in another? We argue that features of lower-class communities (e.g., resource scarcity) promote social cognition via cultural processes. We then argue that social cognition involves partially unique task and neural demands that are separate from nonsocial cognition. We conclude that unique task and neural demands, together with the distinctive cognitive proclivities of lower- and higher-class cultures, can explain variable associations between social class and cognitive functioning.

Multivariate associations between cognition and neighborhood geospatial characteristics in schizophrenia.

Cognitive impairment contributes to functional impairment in schizophrenia. Yet, little is known about how environmental characteristics are related to cognition in schizophrenia. By examining how cognition and the environment are intertwined, it may be possible to identify modifiable risk and protective factors that can improve cognitive outcomes in schizophrenia. We aimed to identify multivariate associations between cognition and three geospatial characteristics (built-space density, habitable green spaces, and public spaces for social interaction) within one's immediate neighborhood among individuals with schizophrenia. We recruited participants with schizophrenia from three sites - an urban metropolitan and two towns in southern India. We administered standard cognitive assessments and performed a principal axis factoring to identify episodic memory, cognitive control, and social inference-making factors for use in further analyses. We estimated geospatial characteristics of an individual's neighborhood, i.e., up to 1km2 around the residence, by sourcing data from Google Earth. We performed unconditional and conditional (to examine the effect of clinical covariates) canonical correlation analyses to understand the multivariate relationship between cognition and geospatial characteristics. We analyzed data from 208 participants; the first canonical cognitive variate (higher social inference-making and poorer cognitive control) shared 24% of the variance (r=0.49; P<0.001) with the first geospatial variate (lower built density and poorer access to public spaces). Years of education, age at onset, and place of residence significantly modulated this relationship. We observe differential associations of the built environment with social and non-social cognition in schizophrenia, and highlight the clinical and demographic characteristics that shape these associations.

A Bayesian Network Approach to Social and Nonsocial Cognition in Schizophrenia: Are Some Domains More Fundamental than Others?

Social and nonsocial cognition are defined as distinct yet related constructs. However, the relative independence of individual variables-and whether specific tasks directly depend on performance in other tasks-is still unclear. The current study aimed to answer this question by using a Bayesian network approach to explore directional dependencies among social and nonsocial cognitive domains. The study sample comprised 173 participants with schizophrenia (71.7% male; 28.3% female). Participants completed 5 social cognitive tasks and the MATRICS Consensus Cognitive Battery. We estimated Bayesian networks using directed acyclic graph structures to examine directional dependencies among the variables. After accounting for negative symptoms and demographic variables, including age and sex, all nonsocial cognitive variables depended on processing speed. More specifically, attention, verbal memory, and reasoning and problem solving solely depended on processing speed, while a causal chain emerged between processing speed and visual memory (processing speed → attention → working memory → visual memory). Social processing variables within social cognition, including emotion in biological motion and empathic accuracy, depended on facial affect identification. These results suggest that processing speed and facial affect identification are fundamental domains of nonsocial and social cognition, respectively. We outline how these findings could potentially help guide specific interventions that aim to improve social and nonsocial cognition in people with schizophrenia.

Cognitive functions and their correlates in people with psychosis: are there gender differences?

AbstractImpairments in social and non-social cognition are common in psychosis and may be sparsely present even before the onset of the disorder. Genetic and environmental influences have been linked to cognitive dysfunctions, which, in turn, may significantly impact the real-world functioning of people with psychosis. The role of gender in determining the interplay between cognitive skills, risk factors, and outcomes has been relatively unexplored. Nevertheless, identifying putative gender differences in cognitive functions and their correlates may favor the identification of individualized prevention and treatment strategies.Disclosure of InterestNone Declared

Intranasal Oxytocin Modulates Decision-Making Depending on Outcome Predictability-A Randomized Within-Subject Controlled Trial in Healthy Males.

Oxytocin (OT) has been extensively studied with regard to its socio-cognitive and -behavioral effects. Its potential as a therapeutic agent is being discussed for a range of neuropsychiatric conditions. However, there is limited evidence of its effects on non-social cognition in general and decision-making in particular, despite the importance of these functions in neuropsychiatry. Using a crossover/within-subject, blinded, randomized design, we investigated for the first time if intranasal OT (24 IU) affects decision-making differently depending on outcome predictability/ambiguity in healthy males. The Iowa Gambling Task (IGT) and the Cambridge Risk Task (CRT) were used to assess decision-making under low outcome predictability/high ambiguity and under high outcome probability/low ambiguity, respectively. After administration of OT, subjects performed worse and exhibited riskier performance in the IGT (low outcome predictability/high ambiguity), whereas they made borderline-significant less risky decisions in the CRT (high outcome probability/low ambiguity) as compared to the control condition. Decision-making in healthy males may therefore be influenced by OT and adjusted as a function of contextual information, with implications for clinical trials investigating OT in neuropsychiatric conditions.

Cognitive deficits in children with autism spectrum disorders: Toward an integrative approach combining social and non-social cognition

Autism spectrum disorder (ASD) is associated with neurocognitive impairment, including executive dysfunctioning and social cognition (SC) deficits. Cognitive remediation (CR) is a behavioral training-based intervention aiming to improve cognitive processes. Its first use in psychiatry interested patients with schizophrenia, in whom promising results have been shown. Integrated CR programs targeting both social and non-social cognition have demonstrated to be effective in improving both cognitive domains and functional outcomes. CR studies in children and adolescents with ASD are still new, those regarding CR approaches combining social and executive functioning remediation are scares. One study examining the efficacy of cognitive enhancement therapy (CET) for improving cognitive abilities in ADS adults, showed significant differential increases in neurocognitive function and large social-cognitive improvements. Therefore, taking into account the overlap between ASD and schizophrenia, and considering the close link between executive functions (EF) and SC, we suggest that integrative approach in ASD could result in better outcomes. The present perspective aimed to highlight cognitive remediation (CR) programs contributions in ASD (especially in children and adolescents), and to discuss the value of combining social and non-social programs.

Social cognitive heterogeneity in schizophrenia: A cluster analysis

This study examined social cognitive heterogeneity in Norwegian sample of individuals with schizophrenia (n = 82). They were assessed with three social cognitive tests: Emotion in Biological Motion (emotion processing), Relationships Across Domains (social perception), and Movie for the Assessment of Social Cognition (theory of mind). Hierarchical and k-means cluster analyses using standardized scores on these three tests provided two clusters. The first cluster (68 %) had mild social cognitive impairments (<0.5 standard deviations below healthy comparison participants). The second cluster (32 %) had severe social cognitive impairments (>2 standard deviations below healthy comparison participants). Validity of the two social cognitive subgroups was indicated by significant differences in functioning, symptom load and nonsocial cognition. Our study shows that social cognitive tests can be used for clinical and cognitive subtyping. This is of potential relevance for treatment.

Gender Differences in Clinical and Psychosocial Features Among Persons With Schizophrenia: A Mini Review

An extensive literature regarding gender differences relevant to several aspects of schizophrenia is nowadays available. It includes some robust findings as well as some inconsistencies. In the present review, we summarize the literature on gender differences in schizophrenia relevant to clinical and social outcome as well as their determinants, focusing on clinical variables, while gender differences on biological factors which may have an impact on the outcome of the disorder were not included herewith. Consistent findings include, in male with respect to female patients, an earlier age of illness onset limited to early- and middle-onset schizophrenia, a worse premorbid functioning, a greater severity of negative symptoms, a lower severity of affective symptoms and a higher rate of comorbid alcohol/substance abuse. Discrepant findings have been reported on gender differences in positive symptoms and in social and non-social cognition, as well as in functional outcome and rates of recovery. In fact, despite the overall finding of a more severe clinical picture in males, this does not seem to translate into a worse outcome. From the recent literature emerges that, although some findings on gender differences in schizophrenia are consistent, there are still aspects of clinical and functional outcome which need clarification by means of further studies taking into account several methodological issues.

Improving Knowledge on Pathways to Functional Outcome in Schizophrenia: Main Results From the Italian Network for Research on Psychoses.

The identification of factors associated with functional outcome of subjects with schizophrenia is a great challenge in current research oriented to the personalization of care. The Italian Network for Research on Psychoses (NIRP) is a network of 26 university psychiatric clinics and/or mental health departments aimed to carry out multicenter research projects to improve the standards of prevention, diagnosis, and treatments of schizophrenia. The network has promoted 2 main studies, a cross-sectional one and a longitudinal one and seven “add-on” studies. The cross-sectional study of the network included 921 subjects with schizophrenia, 379 unaffected first-degree relatives of these patients, and 780 healthy controls. Results from this study documented that social and non-social cognition, functional capacity, negative symptoms, resilience, and family or social incentives strongly influence a measure of global functioning. The follow-up study included 618 patients from the original sample and has produced evidence of the key role of cognition, functional capacity, the experiential domain of negative symptoms, and everyday life skills in predicting functional outcome. The longitudinal study demonstrated that social cognition and the experiential domain of negative symptoms had an impact on interpersonal functioning, while non-social cognition had an impact on everyday life skills. Both non-social cognition and social cognition predicted work skills. The research question concerning the relationships of cognitive impairment and negative symptoms has been investigated with an innovative approach, using a structural equation model (SEM) and a network analysis. Both analyses demonstrated that only the experiential domain of negative symptoms had a distinct direct effect on functioning. The network analysis showed that expressive deficit was connected to functional capacity, as were social and non-social cognitive variables, and to disorganization. These findings were confirmed by the follow-up study. The add-on studies showed distinct electrophysiological correlates of the two negative symptom domains and the partial overlap between disorganization and neurocognitive impairment. Moreover, they identified and characterized a specific subgroup of patients suffering from schizophrenia with autism spectrum symptoms. The NIRP studies have implications for personalized management of patients with schizophrenia and highlight the need for a careful assessment of several domains rarely evaluated in clinical settings.

Predictors of real-life functioning in subjects with schizophrenia: A 4-year follow-up study

In a cross-sectional study, the Italian Network for Research on Psychoses (INReP) found that variables relevant to the disease, personal resources and social context explain 53.8% of real-life functioning variance in a large sample of community dwelling people with schizophrenia. In a longitudinal study, the INReP aimed to identify baseline predictors of main domains of real-life functioning, i.e. work skills, interpersonal relationships and everyday life skills, at 4-year follow-up. We assessed psychopathology, social and non-social cognition, functional capacity, personal resources, and context-related factors, as well as real-life functioning as the main outcome. We used structural equation modeling (SEM) and latent change score (LCS) model to identify predictors of real-life functioning domains at follow-up and changes from baseline in the same domains. Six-hundred-eighteen subjects took part in the study. Neurocognition predicted everyday life and work skills; avolition predicted interpersonal relationships; positive symptoms work skills, and social cognition work skills and interpersonal functioning. Higher neurocognitive abilities predicted the improvement of everyday life and work skills, as well as of social cognition and functional capacity; better baseline social cognition predicted the improvement of work skills and interpersonal functioning, and better baseline everyday life skills predicted the improvement of work skills. Several variables which predict important aspects of functional outcome of people with schizophrenia are not routinely assessed and are not systematically targeted by intervention programs in community mental health services. A larger dissemination of practices such as cognitive training and personalized psychosocial interventions should be promoted in mental health care.DisclosureNo significant relationships.

Factors Associated With Real-Life Functioning in Persons With Schizophrenia in a 4-Year Follow-up Study of the Italian Network for Research on Psychoses

The goal of schizophrenia treatment has shifted from symptom reduction and relapse prevention to functional recovery; however, recovery rates remain low. Prospective identification of variables associated with real-life functioning domains is essential for personalized and integrated treatment programs. To assess whether baseline illness-related variables, personal resources, and context-related factors are associated with work skills, interpersonal relationships, and everyday life skills at 4-year follow-up. This multicenter prospective cohort study was conducted across 24 Italian university psychiatric clinics or mental health departments in which 921 patients enrolled in a cross-sectional study were contacted after 4 years for reassessment. Recruitment of community-dwelling, clinically stable persons with schizophrenia was conducted from March 2016 to December 2017, and data were analyzed from January to May 2020. Psychopathology, social and nonsocial cognition, functional capacity, personal resources, and context-related factors were assessed, with real-life functioning as the main outcome. Structural equation modeling, multiple regression analyses, and latent change score modeling were used to identify variables that were associated with real-life functioning domains at follow-up and with changes from baseline in these domains. In total, 618 participants (427 male [69.1%]; mean [SD] age, 45.1 [10.5] years) were included. Five baseline variables were directly associated with real-life functioning at follow-up: neurocognition with everyday life (β, 0.274; 95% CI, 0.207-0.341; P < .001) and work (β, 0.101; 95% CI, 0.005-0.196; P = .04) skills; avolition with interpersonal relationships (β, -0.126; 95% CI, -0.190 to -0.062; P < .001); positive symptoms with work skills (β, -0.059; 95% CI, -0.112 to -0.006; P = .03); and social cognition with work skills (β, 0.185; 95% CI, 0.088-0.283; P < .001) and interpersonal functioning (β, 0.194; 95% CI, 0.121-0.268; P < .001). Multiple regression analyses indicated that these variables accounted for the variability of functioning at follow-up after controlling for baseline functioning. In the latent change score model, higher neurocognitive abilities were associated with improvement of everyday life (β, 0.370; 95% CI, 0.253-0.486; P < .001) and work (β, 0.102; 95% CI, 0.016-0.188; P = .02) skills, social cognition (β, 0.133; 95% CI, 0.015-0.250; P = .03), and functional capacity (β, 1.138; 95% CI, 0.807-1.469; P < .001); better baseline social cognition with improvement of work skills (β, 0.168; 95% CI, 0.075-0.261; P < .001) and interpersonal functioning (β, 0.140; 95% CI, 0.069-0.212; P < .001); and better baseline everyday life skills with improvement of work skills (β, 0.121; 95% CI, 0.077-0.166; P < .001). Findings of this large prospective study suggested that baseline variables associated with functional outcome at follow-up included domains not routinely assessed and targeted by intervention programs in community mental health services. The key roles of social and nonsocial cognition and of baseline everyday life skills support the adoption in routine mental health care of cognitive training programs combined with personalized psychosocial interventions aimed to promote independent living.

Self-stigma in psychotic disorders: Clinical, cognitive, and functional correlates in a diverse sample

Self-stigma in mental illness is linked to negative clinical and functional outcomes, but little is known about its correlates specifically in psychotic disorders. Here we investigated the role of clinical symptoms, cognition, and vocational status as correlates of self-stigma in 98 individuals with psychotic disorders (36 Black American, 32 White Hispanic, 11 White Non-Hispanic, 11 Asian American). A principal component analysis of the Internalized Stigma of Mental Illness scale yielded three components: Experiential Stigma, Stereotype Endorsement, and Stigma Resistance. Higher Experiential Stigma was associated with greater severity of affective symptoms and lower vocational status. Higher Stigma Resistance was associated with higher social and non-social cognition, and higher vocational status. Stereotype Endorsement did not significantly correlate with any predictor variable. Linear regression models showed that 13% of the variance in Experiential Stigma was explained by affective symptoms and vocational status, and 20% of the variance in Stigma Resistance was explained by non-social cognition and vocational status. These findings provide new information about the correlates of self-stigma in an ethnically and racially diverse psychotic disorder sample. Such information may lead to a better understanding of self-stigma mechanisms in this population.

The Relationship between Negative Symptoms and Both Emotion Management and Non-social Cognition in Schizophrenia Spectrum Disorders.

There is ongoing debate regarding the relationship between clinical symptoms and cognition in schizophrenia spectrum disorders (SSD). The present study aimed to explore the potential relationships between symptoms, with an emphasis on negative symptoms, and social and non-social cognition. Hierarchical cluster analysis with k-means optimisation was conducted to characterise clinical subgroups using the Scale for the Assessment of Negative Symptoms and Scale for the Assessment of Positive Symptoms in n = 130 SSD participants. Emergent clusters were compared on the MATRICS Consensus Cognitive Battery, which measures non-social cognition and emotion management as well as demographic and clinical variables. Spearman's correlations were then used to investigate potential relationships between specific negative symptoms and emotion management and non-social cognition. Four distinct clinical subgroups were identified: 1. high hallucinations, 2. mixed symptoms, 3. high negative symptoms, and 4. relatively asymptomatic. The high negative symptom subgroup was found to have significantly poorer emotion management than the high hallucination and relatively asymptomatic subgroups. No further differences between subgroups were observed. Correlation analyses revealed avolition-apathy and anhedonia-asociality were negatively correlated with emotion management, but not non-social cognition. Affective flattening and alogia were not associated with either emotion management or non-social cognition. The present study identified associations between negative symptoms and emotion management within social cognition, but no domains of non-social cognition. This relationship may be specific to motivation, anhedonia and apathy, but not expressive deficits. This suggests that targeted interventions for social cognition may also result in parallel improvement in some specific negative symptoms.