Advancing the Measurement of Social Functioning in Schizophrenia: Applications of Egocentric Social Network Analysis.

People with schizophrenia face challenges with forming and maintaining social relationships, often resulting in poor social functioning. Commonly used measures of social functioning provide broad information relating to social relationships, but they do not adequately capture information regarding network structure and characteristics of network members. One method that can assess these more detailed aspects of social networks and provide a more comprehensive understanding of social functioning deficits is egocentric social network analysis (SNA). SNA is a scientific discipline that uses principles of network science and graph theory to analyze social relations quantitatively. Even though some types of SNA have been applied in prior schizophrenia studies, its application as a framework to measure social functioning has been extremely limited. Therefore, this article aims to formally introduce SNA and select quantitative SNA metrics, including measures of network composition, structure, homophily, and centrality, to schizophrenia researchers as novel ways of measuring components of social functioning. To demonstrate the application of SNA, we provide illustrative examples of the SNA metrics and graphical diagrams of social networks for two individuals with schizophrenia.

Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks.

BACKGROUND: Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables. METHODS: Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants. RESULTS: Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls. CONCLUSIONS: Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.

Linking social motivation, general motivation, and social cognition to interpersonal functioning in schizophrenia: insights from exploratory graph analysis.

Motivation in general, and social motivation in particular are important for interpersonal functioning in individuals with schizophrenia. Still, their roles after accounting for social cognition, are not well understood. The sample consisted of 147 patients with schizophrenia. General motivation was measured using the Behavioral inhibition/activation scale (BIS/BAS). Social motivation was measured by Passive social withdrawal and Active social avoidance items from PANSS. Interpersonal functioning was evaluated with Birchwood's Social Functioning Scale (SFS). We used Exploratory Graph Analysis for network estimation and community detection. Active social avoidance, passive social withdrawal, and social withdrawal/engagement (from SFS) were the most important nodes. In addition, three distinct communities were identified: Social cognition, Social motivation, and Interpersonal functioning. Notably, the BIS and BAS measures of general motivation were not part of any community. BAS showed stronger links to functioning than BIS. Passive social withdrawal was more strongly linked to interpersonal functioning than social cognitive abilities. Results suggest that social motivation, especially social approach, is more closely related to interpersonal functioning in schizophrenia than general motivation. In contrast, we found that general motivation was largely unrelated to social motivation. This pattern highlights the importance of type of motivation for understanding variability in interpersonal difficulties in schizophrenia.

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

OBJECTIVES: 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. STUDY DESIGN: 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. STUDY RESULTS: 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. CONCLUSIONS: 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.

Connections between and within extended psychosis and autistic phenotypes and social relationships in the general population.

OBJECTIVES: Non - clinical individuals with higher levels of autistic traits and psychotic experiences also have problems in social relationships. Therefore, this study aimed to model complex associations between autistic and psychotic phenotypes and indicators of social relationships in the general population using a network approach. METHODS: The sample consisted of 649 participants with a mean age of M = 40.23 and SD = 13.09 sampled from the general population. The sample was representative for the 18-65 years old general population in the Slovak Republic. The following scales were administered: Community Assessment of Psychic Experiences, The Comprehensive Autistic Trait Inventory, and NIH Toolbox Adult Social Relationship Scales. Associations between variables and the presence of communities were identified using Exploratory Graph Analysis. RESULTS: Results revealed four highly stable and densely connected communities within the network: social relationships, autistic traits, positive symptoms, and the last one consisting of all negative symptoms, problems in social interactions, and depression. The most important variables in the network were difficulties in social interaction, perceived rejection, bizarre ideas, depression, and social withdrawal. CONCLUSIONS: The psychotic and autistic phenotypes in the general population showed a network of connections with characteristics of social relationships. Community detection revealed that autistic traits and psychotic-like experiences formed relatively independent communities. Further, there was substantial overlap between negative symptoms (e.g., social withdrawal), and core features of the autistic phenotype, especially social interaction difficulties.

Understanding Connections and Boundaries Between Positive Symptoms, Negative Symptoms, and Role Functioning Among Individuals With Schizophrenia: A Network Psychometric Approach.

Importance: Improved understanding of the boundaries and connections between positive symptoms, negative symptoms, and role functioning in schizophrenia is critical, given limited empirical support for clear distinctions among these clinical areas. This study's use of network psychometrics to investigate differential associations and structural overlap between positive symptoms, negative symptoms, and functional domains in schizophrenia may contribute to such understanding. Objective: To apply network analysis and community detection methods to examine the interplay and structure of positive symptoms, negative symptoms, and functional domains in individuals with schizophrenia. Design, Setting, and Participants: Cross-sectional study in 5 geographically distributed research centers in the US as part of the Consortium on the Genetics of Schizophrenia-2 from July 1, 2010, through January 31, 2014. Data were analyzed from November 2021 to June 2022. Clinically stable outpatients with schizophrenia or schizoaffective disorder were included. Participants were excluded if they had evidence of neurologic or additional Axis I psychiatric disorders. Other exclusion criteria included head injury, stroke, and substance abuse. Of 1415 patients approached, 979 were included in the final analysis. Main Outcomes and Measures: Measures included the Scale for the Assessment of Positive Symptoms, the Scale for the Assessment of Negative Symptoms, and the Role Functioning Scale. Main outcomes were expected influence, which assesses the relative importance of items to the network and is defined as the association of an item with all others, and community detection and stability, defined as the presence of statistical clusters and their replicability. Results: Participants with complete data included 979 outpatients (mean [SD] age, 46 [11] years; 663 male [67.7%]; 390 participants [40%] self-identified as African American, 30 [3%] as Asian, 7 [0.7%] as Native American, 8 [0.8%] as Pacific Islander, 412 [42.1%] as White, 125 [12.8%] as more than 1 race, and 5 [0.5%] did not identify). Anhedonia had the highest expected influence in the most comprehensive network analysis, showing connections with negative and positive symptoms and functional domains. Positive symptoms had the lowest expected influence. Community detection analyses indicated the presence of 3 clusters corresponding to positive symptoms; negative symptoms and work functioning; functional domains, including independent living, family relationships, and social network; and avolition, anhedonia, and work functioning. Hallucinations and delusions replicated in 1000 bootstrapped samples (100%), while bizarre behavior and thought disorder replicated in 390 (39%) and 570 (57%), respectively. In contrast, negative symptoms and work functioning replicated between 730 (73%) and 770 (77%) samples, respectively, and the remaining functional domains in 940 samples (94%). Conclusions and Relevance: The high centrality of anhedonia and its connections with multiple functional domains suggest that it could be a treatment target for global functioning. Interventions for work functioning may benefit from a specialized approach that focuses primarily on avolition.

Symptom Structure in Schizophrenia: Implications of Latent Variable Modeling vs Network Analysis.

The structure of schizophrenia symptoms has a substantial impact on the development of pharmacological and psychosocial interventions. Typically, reflective latent variable models (eg, confirmatory factor analysis) or formative latent variable models (eg, principal component analysis) have been used to examine the structure of schizophrenia symptoms. More recently, network analysis is appearing as a method to examine symptom structure. However, latent variable modeling and network analysis results can lead to different inferences about the nature of symptoms. Given the critical role of correctly identifying symptom structure in schizophrenia treatment and research, we present an introduction to latent variable modeling and network analysis, along with their distinctions and implications for examining the structure of schizophrenia symptoms. We also provide a simulation demonstration highlighting the statistical equivalence between these models and the subsequent importance of an a priori rationale that should help guide model selection.

The centrality of motivation in psychosocial functioning: Network and bifactor analysis of the Quality of Life Scale in first-episode psychosis.

Psychosocial functioning impairment is prevalent in first-episode psychosis and chronic schizophrenia. The Quality of Life Scale (QLS) is a widely used tool to measure psychosocial functioning; however, given the overlap between negative symptoms and functioning, along with the QLS being conceptualized initially as a measure of the deficit syndrome, it is unclear whether summing QLS items into a total score is an appropriate measure of overall psychosocial functioning. This study aimed to examine the centrality of QLS items and the appropriateness of using a QLS total score. Participants with first-episode psychosis (n = 404) completed the QLS. Item centrality was assessed using a network analysis approach, while reliability and dimensionality of the QLS total score and subscales were measured using bifactor modeling and related psychometric indices. Network analysis results showed that an item relating to motivation was the most central item within the scale. Moreover, bifactor modeling results found that motivation and other items relating to negative symptoms may reflect the QLS total score more strongly than other functioning (i.e., Interpersonal, Instrumental) domains. Based on these findings, we urge researchers to use caution when using a QLS total score, as it may unequally confound functional domains and motivation. Moreover, our results continue to underscore the importance of negative symptoms, particularly motivational impairment, in psychosocial functioning. Future studies should aim to examine the centrality of other functioning measures in psychosis and schizophrenia, as our results suggest that psychosocial functioning may be greatly influenced by motivation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Parsing social motivation: development and validation of a self-report measure of social effort.

BACKGROUND: Reduced efforts to form and maintain social bonds can exist in the context of a sufficient desire for social connection. Thus, social impairment common across many psychiatric conditions may often reflect failures in social effort exertion, despite normative levels of social liking and wanting. Although there are many questionnaires available that assess sociability, desire, or lack thereof for connection and perceived social support, there is no current self-report assessment of the behavioral outputs of social motivation. AIMS: We aimed to develop and validate a measure of the social effort in college students and the general population. METHODS: College students (n = 981) and a broader sample of adults via Amazon's Mechanical Turk (MTurk; n = 506) participated in the study. RESULTS: We identified two factors that represented content related to general social effort and social effort in adherence with social norms; we named the measure the Social Effort and Conscientiousness Scale (SEACS). Results suggest the SEACS is a reliable and valid measure of social effort. CONCLUSIONS: Lower scores on the SEACS were associated with symptoms of depression and anxiety, highlighting the scale's potential utility in clinical populations. We include a discussion of possible applications of the SEACS, including its further use and application in psychopathology research.

Effort-Based Decision-Making and Gross Motor Performance: Are They Linked?

The purpose of this study was to investigate the relationship between effort-based decision making and gross motor performance. Effort-based decision making was measured using a modified version of the Effort Expenditure for Rewards Task (EEfRT), in which participants pressed a button on a keyboard to fill a bar on a screen for monetary reward. Participants received monetary rewards that were commensurate with the level of effort that they were willing to expend. Gross motor performance was measured with a walking task, in which participants matched their steps to the beat of an audio metronome; they walked to metronome beats that were slower and also faster than their normal walking pace. We hypothesized that increased effort during the effort-based decision making task would be paired with an increase in steps taken per minute during the gross motor task. However, the results of this study indicated a lack of a statistically significant relationship between the effort-based decision making task and the gross motor task. Planning rather than decision-making may have been the cognitive construct that governed our gross motor task. These findings can be beneficial when thinking about potential interventions for populations who experience deficits in motor performance and cognition as well as for understanding the relationship between both cognitive and motor performance in healthy adults.

The role of physical pain in global functioning of people with serious mental illness.

While people with serious mental illness (SMI) endorse clinical pain at rates on par or exceeding those in the general population, the association between pain and functioning remains unclear. In this paper we present data on the cross-sectional association between clinical pain and global functioning in a large, mixed diagnostic sample of people with SMI. Eight-hundred ninety-eight people diagnosed with bipolar disorder, major depressive disorder, or schizophrenia were administered the Global Assessment Scale and the 12-item Short Form Survey, which includes an assessment of the extent to which the experience of pain interfered with daily activities over the past month. People with major depressive disorder reported higher pain interference than those with schizophrenia and bipolar disorder. The presence of physical health conditions and psychiatric symptoms were also assessed. After controlling for age, gender, psychiatric symptoms, education level, and physical health problems, pain interference in the past month was associated with significantly lower global functioning. The findings suggest that the experience of pain is associated with poorer global functioning across major SMI diagnoses. Moreover, the impact of pain in global functioning appears independent of physical health problems, and thus may warrant routine screening from mental health providers.

Speech production and disorganization in schizotypy: Investigating the role of cognitive and affective systems.

Diminished productivity and elevated disorganization have been detected in the speech of individuals with schizotypy. However, the underlying mechanisms for these disruptions are not well understood. Separate lines of research suggest potential contributions from cognitive and affective systems. In this study, disorganized speech and speech production were examined in speech samples generated by schizotypy (n = 47) and non-schizotypy (n = 51) groups by assessing "reactivity" (i.e., a change in experimental compared with baseline conditions) across baseline, affective, and dual-task (i.e., cognitive) conditions. Relationships with social functioning were also examined within each group. Three key findings emerged: 1) compared to the non-schizotypy group, those with schizotypy exhibited diminished speech production in the affective condition and affective reactivity was observed; 2) the schizotypy group displayed greater levels of disorganized speech in dual-task conditions and cognitive reactivity was observed; and 3) affective reactivity for disorganized speech was linked to worse social functioning within the schizotypy group. This study provides evidence that cognitive and affective systems are uniquely involved in separate characteristics of speech in schizotypy. At this stage, cognitive systems appear to have a specific role in the organization of speech, whereas affective systems are more heavily involved in speech production. Regarding the association between affective reactivity and social functioning, previous research has demonstrated individuals highly reactive to emotional stimuli carry additional risk for conversion to psychosis. Future research identifying a subset with schizotypy who demonstrate affective reactivity could lead to a better understanding of links between schizotypy and future psychosis symptoms.

Physical effort exertion and pain: Links with trait-based risk for psychopathology.

People with serious mental illness (SMI) are at an increased risk for physical health complications, such as cardiovascular disease and obesity. Low levels of physical activity is a major contributor to these health complications. One factor associated with limited physical activity in the broader sedentary population is pain. While preliminary findings suggest an association between lack of physical activity and pain in SMI, conclusions are still unclear. Thus, the goal of this correlational study was to examine associations between trait-based risk for psychopathology (hypomanic personality, schizotypy, and anhedonic depression) and the experience of pain following a physical endurance/effort task. Healthy participants (N = 43; 18 females) completed self-report measures of trait-based risk for psychopathology. They also reported on the experience of pain before and after the Time To Exhaustion (TTE) test. Findings revealed that risk for psychosis and anhedonic depression were associated with increases in pain following the TTE test, accounting for other key variables, such as age and self-reported physical exercise. Risk for mania was unrelated to changes in pain. These results suggest that the experience of pain in relation to physical endurance/effort may contribute to diminished physical activity among people at risk for SMI.

Using lexical analysis to identify emotional distress in psychometric schizotypy.

Through the use of lexical analysis software, researchers have demonstrated a greater frequency of negative affect word use in those with schizophrenia and schizotypy compared to the general population. In addition, those with schizotypy endorse greater emotional distress than healthy controls. In this study, our aim was to expand on previous findings in schizotypy to determine whether negative affect word use could be linked to emotional distress. Schizotypy (n=33) and non-schizotypy groups (n=33) completed an open-ended, semi-structured interview and negative affect word use was analyzed using a validated lexical analysis instrument. Emotional distress was assessed using subjective questionnaires of depression and psychological quality of life (QOL). When groups were compared, those with schizotypy used significantly more negative affect words; endorsed greater depression; and reported lower QOL. Within schizotypy, a trend level association between depression and negative affect word use was observed; QOL and negative affect word use showed a significant inverse association. Our findings offer preliminary evidence of the potential effectiveness of lexical analysis as an objective, behavior-based method for identifying emotional distress throughout the schizophrenia-spectrum. Utilizing lexical analysis in schizotypy offers promise for providing researchers with an assessment capable of objectively detecting emotional distress.