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Background and Hypothesis: The Cognitive Model of Negative Symptoms is a prominent model that posits that defeatist performance beliefs (DPB) are a key psychological mechanism underlying negative symptoms in those with schizophrenia (SZ). However, the ecological validity of the model has not been established, and temporally specific evaluations of the model's hypotheses have not been conducted. This study tested the model's key hypotheses in real-world environments using ecological momentary assessment (EMA)., Study Design: Fifty-two outpatients with SZ and 55 healthy controls (CN) completed 6 days of EMA. Multilevel models examined concurrent and time-lagged associations between DPB and negative symptoms in daily life., Study Results: SZ displayed greater DPB in daily life than CN. Furthermore, greater DPB were associated with greater concurrently assessed negative symptoms (anhedonia, avolition, and asociality) in daily life. Time-lagged analyses indicated that in both groups, greater DPB at time t led to elevations in negative symptoms (anhedonia, avolition, or asociality) at t + 1 above and beyond the effects of negative symptoms at time t., Conclusions: Results support the ecological validity of the Cognitive Model of Negative Symptoms and identify a temporally specific association between DPB and subsequent negative symptoms that is consistent with the model's hypotheses and a putative mechanistic pathway in Cognitive Behavioral Therapy for negative symptoms. Findings suggest that DPB are a psychological factor contributing to negative symptoms in real-world environments. Implications for measuring DPB in daily life and providing just-in-time mobile health-based interventions to target this mechanism are discussed., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Background and Hypotheses: Poor social functioning is common among individuals at clinical high-risk (CHR) for psychosis and is associated with greater likelihood of conversion. Unfortunately, processes contributing to social impairment are unclear, making social functioning difficult to improve via treatment. The current study examined whether abnormalities in social functioning result from aberrant temporal interactions between social motivation and behavior., Study Design: Participants included 105 individuals at CHR and 62 healthy controls (CN) who completed 6 days of ecological momentary assessment. Multilevel models examined time-lagged interactions between social behavior and motivation., Study Results: CHR and CN did not differ in social motivation; however, CHR were less likely to interact with family and coworkers and more likely to engage in interactions via phone and text/social media. Autocorrelations indicated that social behavior and motivation were generally consistent across time in CHR and CN groups. Time-lagged analyses indicated that both groups had an increase in social motivation across time when they were alone and a decrease in social motivation across time when they were with others. However, the relative decrease when with others and increase when alone were less robust in CHR than CN, particularly for in-person interactions. Social motivation at time t did not differentially impact social partner or modality at time t+1 in the groups., Conclusions: Findings suggest that social behavior and motivation have different temporal interactions in CHR and CN. Psychosocial interventions may benefit from targeting the frequency of social behavior with specific partners and modalities to change social motivation., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background and Hypotheses: Early identification and prevention of psychosis is limited by the availability of tools designed to assess negative symptoms in those at clinical high-risk for psychosis (CHR). To address this critical need, a multi-site study was established to develop and validate a clinical rating scale designed specifically for individuals at CHR: The Negative Symptom Inventory-Psychosis Risk (NSI-PR)., Study Design: The measure was developed according to guidelines recommended by the NIMH Consensus Conference on Negative Symptoms using a transparent, iterative, and data-driven process. A 16-item version of the NSI-PR was designed to have an overly inclusive set of items and lengthier interview to support the ultimate intention of creating a new briefer measure. Psychometric properties of the 16-item NSI-PR were evaluated in a sample of 218 CHR participants., Study Results: Item-level analyses indicated that men had higher scores than women. Reliability analyses supported internal consistency, inter-rater agreement, and temporal stability. Associations with measures of negative symptoms and functioning supported convergent validity. Small correlations with positive, disorganized, and general symptoms supported discriminant validity. Structural analyses indicated a 5-factor structure (anhedonia, avolition, asociality, alogia, and blunted affect). Item response theory identified items for removal and indicated that the anchor range could be reduced. Factor loadings, item-level correlations, item-total correlations, and skew further supported removal of certain items., Conclusions: These findings support the psychometric properties of the NSI-PR and guided the creation of a new 11-item NSI-PR that will be validated in the next phase of this multi-site scale development project., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background and Hypothesis: Deficits in performing and interpreting communicative nonverbal behaviors, such as gesture, have been linked to varied psychopathology and dysfunction. Some evidence suggests that individuals at risk for psychosis have deficits in gesture interpretation and performance; however, individuals with internalizing disorders (eg, depression) may have similar deficits. No previous studies have examined whether gesture deficits in performance and interpretation are specific to those at risk for psychosis. Additionally, the underlying mechanisms (eg, cognition) and consequences (eg, functioning) of these deficits are poorly understood., Study Design: This study examined self-reported gesture interpretation (SRGI) and performance (SRGP) in those at clinical high risk for psychosis (CHR; N = 88), those with internalizing disorders (INT; N = 51), and healthy controls (HC; N = 53). Participants completed questionnaires, clinical interviews, and neurocognitive tasks., Study Results: Results indicated that the CHR group was characterized by significantly lower SRGI scores than the HC or INT groups (d = 0.41); there were no differences among groups in SRGP. Within CHR participants, greater deficits in SRGP were associated with lower verbal learning and memory (r = -.33), but not general intelligence or processing speed. Furthermore, gesture deficits were associated with higher cross-sectional risk for conversion to a full psychotic disorder in the CHR group., Conclusions: Overall, these findings suggest that specific subdomains of gesture may reflect unique vulnerability for psychosis, self-report may be a viable assessment tool in understanding these phenomena, and gesture dysfunction may signal risk for transition to psychosis., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background and Hypothesis: Despite decades of "proof of concept" findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometric evaluation of these measures. There is overwhelming evidence that criterion and content validity can be achieved for many purposes, particularly using machine learning procedures. However, there has been very little evaluation of test-retest reliability, divergent validity (sufficient to address concerns of a "generalized deficit"), and potential biases from demographics and other individual differences., Study Design: This article highlights these concerns in development of an NLP measure for tracking clinically rated paranoia from video "selfies" recorded from smartphone devices. Patients with schizophrenia or bipolar disorder were recruited and tracked over a week-long epoch. A small NLP-based feature set from 499 language samples were modeled on clinically rated paranoia using regularized regression., Study Results: While test-retest reliability was high, criterion, and convergent/divergent validity were only achieved when considering moderating variables, notably whether a patient was away from home, around strangers, or alone at the time of the recording. Moreover, there were systematic racial and sex biases in the model, in part, reflecting whether patients submitted videos when they were away from home, around strangers, or alone., Conclusions: Advancing NLP measures for psychosis will require deliberate consideration of test-retest reliability, divergent validity, systematic biases and the potential role of moderators. In our example, a comprehensive psychometric evaluation revealed clear strengths and weaknesses that can be systematically addressed in future research., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: This is a placebo-controlled multi-national trial of roluperidone, a compound with antagonist properties for 5-HT2A, sigma2, and α1A-adrenergic receptors, targeting negative symptoms in patients with schizophrenia. This trial follows a previous trial that demonstrated roluperidone superiority over placebo in a similar patient population., Methods: Roluperidone 32 mg/day, roluperidone 64 mg/day, or placebo was administered for 12 weeks to 513 patients with schizophrenia with moderate to severe negative symptoms. The primary endpoint was the PANSS-derived Negative Symptom Factor Score (NSFS) and the key secondary endpoint was Personal and Social Performance scale (PSP) total score., Results: NSFS scores were lower (improved) for roluperidone 64 mg compared to placebo and marginally missing statistical significance for the intent-to-treat (ITT) analysis data set (P ≤ .064), but reached nominal significance (P ≤ .044) for the modified-ITT (m-ITT) data set. Changes in PSP total score were statistically significantly better on roluperidone 64 mg compared to placebo for both ITT and m-ITT (P ≤ .021 and P ≤ .017, respectively)., Conclusions: Results of this trial confirm the potential of roluperidone as a treatment of negative symptoms and improving everyday functioning in patients with schizophrenia. Study registration: Eudra-CT: 2017-003333-29; NCT03397134., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Objectives: Negative symptom studies frequently use single composite scores as indicators of symptom severity and as primary endpoints in clinical trials. Factor analytic and external validation studies do not support this practice but rather suggest a multidimensional construct. The current study used structural equation modeling (SEM) to compare competing dimensional models of negative symptoms to determine the number of latent dimensions that best capture variance in biological, psychological, and clinical variables known to have associations with negative symptoms., Methods: Three independent studies (total n = 632) compared unidimensional, two-factor, five-factor, and hierarchical conceptualizations of negative symptoms in relation to cognition, psychopathology, and community functioning (Study 1); trait emotional experience and defeatist performance beliefs (Study 2); and glutamate and gamma-aminobutyric acid levels in the anterior cingulate cortex quantified using proton magnetic resonance spectroscopy (Study 3)., Results: SEM favored the five-factor and hierarchical models over the unidimensional and two-factor models regardless of the negative symptom measure or external validator. The five dimensions-anhedonia, asociality, avolition, blunted affect, and alogia-proved vital either as stand-alone domains or as first-order domains influenced by second-order dimensions-motivation and pleasure and emotional expression. The two broader dimensions sometimes masked important associations unique to the five narrower domains. Avolition, anhedonia, and blunted affect showed the most domain-specific associations with external variables across study samples., Conclusions: Five domains and a hierarchical model reflect the optimal conceptualization of negative symptoms in relation to external variables. Clinical trials should consider using the two dimensions as primary endpoints and the five domains as secondary endpoints., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Digital phenotyping has been proposed as a novel assessment tool for clinical trials targeting negative symptoms in psychotic disorders (PDs). However, it is unclear which digital phenotyping measurements are most appropriate for this purpose., Aims: Machine learning was used to address this gap in the literature and determine whether: (1) diagnostic status could be classified from digital phenotyping measures relevant to negative symptoms and (2) the 5 negative symptom domains (anhedonia, avolition, asociality, alogia, and blunted affect) were differentially classified by active and passive digital phenotyping variables., Methods: Participants included 52 outpatients with a PD and 55 healthy controls (CN) who completed 6 days of active (ecological momentary assessment surveys) and passive (geolocation, accelerometry) digital phenotyping data along with clinical ratings of negative symptoms., Results: Machine learning algorithms classifying the presence of a PD diagnosis yielded 80% accuracy for cross-validation in H2O AutoML and 79% test accuracy in the Recursive Feature Elimination with Cross Validation feature selection model. Models classifying the presence vs absence of clinically significant elevations on each of the 5 negative symptom domains ranged in test accuracy from 73% to 91%. A few active and passive features were highly predictive of all 5 negative symptom domains; however, there were also unique predictors for each domain., Conclusions: These findings suggest that negative symptoms can be modeled from digital phenotyping data recorded in situ. Implications for selecting the most appropriate digital phenotyping variables for use as outcome measures in clinical trials targeting negative symptoms are discussed., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

COVID-19 has led to a great deal of general suffering and an increased prevalence of psychiatric illness worldwide. Within the area of psychosis-risk syndromes, a highly heterogeneous clinical population, the picture is quite nuanced as the social restrictions resulting from the pandemic have reduced stress for some and increased it for others. Further, a number of pandemic-related societal and cultural changes have obfuscated the diagnostic and treatment landscape in this area as well. In this opinion article, we describe several prototypical cases, representative of presentations seen in our clinical high-risk (CHR) research programs. The cases highlight considerable clinical variability and, in addition, speak to the current complexities faced by diagnosticians and treatment providers. In addition to discussing these issues, this piece introduces potential solutions highlighting the promise of incorporating data-driven strategies to identify more homogenous CHR subtypes and employ precision medicine., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Negative symptoms are prevalent in the prodromal and first-episode phases of psychosis and highly predictive of poor clinical outcomes (eg, liability for conversion and functioning). However, the latent structure of negative symptoms is unclear in the early phases of illness. Determining the latent structure of negative symptoms in early psychosis (EP) is of critical importance for early identification, prevention, and treatment efforts. In the current study, confirmatory factor analysis was used to evaluate latent structure in relation to 4 theoretically derived models: 1. a 1-factor model, 2. a 2-factor model with expression (EXP) and motivation and pleasure (MAP) factors, 3. a 5-factor model with separate factors for the 5 National Institute of Mental Health (NIMH) consensus development conference domains (blunted affect, alogia, anhedonia, avolition, and asociality), and 4. a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 consensus domains. Participants included 164 individuals at clinical high risk (CHR) who met the criteria for a prodromal syndrome and 377 EP patients who were rated on the Brief Negative Symptom Scale. Results indicated that the 1- and 2-factor models provided poor fit for the data. The 5-factor and hierarchical models provided excellent fit, with the 5-factor model outperforming the hierarchical model. These findings suggest that similar to the chronic phase of schizophrenia, the latent structure of negative symptom is best conceptualized in relation to the 5 consensus domains in the CHR and EP populations. Implications for early identification, prevention, and treatment are discussed., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Negative symptoms are a critical, but poorly understood, aspect of schizophrenia. Measurement of negative symptoms primarily relies on clinician ratings, an endeavor with established reliability and validity. There have been increasing attempts to digitally phenotype negative symptoms using objective biobehavioral technologies, eg, using computerized analysis of vocal, speech, facial, hand and other behaviors. Surprisingly, biobehavioral technologies and clinician ratings are only modestly inter-related, and findings from individual studies often do not replicate or are counterintuitive. In this article, we document and evaluate this lack of convergence in 4 case studies, in an archival dataset of 877 audio/video samples, and in the extant literature. We then explain this divergence in terms of "resolution"-a critical psychometric property in biomedical, engineering, and computational sciences defined as precision in distinguishing various aspects of a signal. We demonstrate how convergence between clinical ratings and biobehavioral data can be achieved by scaling data across various resolutions. Clinical ratings reflect an indispensable tool that integrates considerable information into actionable, yet "low resolution" ordinal ratings. This allows viewing of the "forest" of negative symptoms. Unfortunately, their resolution cannot be scaled or decomposed with sufficient precision to isolate the time, setting, and nature of negative symptoms for many purposes (ie, to see the "trees"). Biobehavioral measures afford precision for understanding when, where, and why negative symptoms emerge, though much work is needed to validate them. Digital phenotyping of negative symptoms can provide unprecedented opportunities for tracking, understanding, and treating them, but requires consideration of resolution., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Negative symptoms are characteristic of schizophrenia and closely linked to numerous outcomes. A body of work has sought to identify homogenous negative symptom subgroups-a strategy that can promote mechanistic understanding and precision medicine. However, our knowledge of negative symptom subgroups among individuals at clinical high-risk (CHR) for psychosis is limited. Here, we investigated distinct negative symptom profiles in a large CHR sample (N = 244) using a cluster analysis approach. Subgroups were compared on external validators that are (1) commonly observed in the schizophrenia literature and/or (2) may be particularly relevant for CHR individuals, informing early prevention and prediction. We observed 4 distinct negative symptom subgroups, including individuals with (1) lower symptom severity, (2) deficits in emotion, (3) impairments in volition, and (4) global elevations. Analyses of external validators suggested a pattern in which individuals with global impairments and volitional deficits exhibited more clinical pathology. Furthermore, the Volition group endorsed more disorganized, anxious, and depressive symptoms and impairments in functioning compared to the Emotion group. These data suggest there are unique negative symptom profiles in CHR individuals, converging with studies in schizophrenia indicating motivational deficits may be central to this symptom dimension. Furthermore, observed differences in CHR relevant external validators may help to inform early identification and treatment efforts., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Research suggests that early identification and intervention with individuals at clinical high risk (CHR) for psychosis may be able to improve the course of illness. The first generation of studies suggested that the identification of CHR through the use of specialized interviews evaluating attenuated psychosis symptoms is a promising strategy for exploring mechanisms associated with illness progression, etiology, and identifying new treatment targets. The next generation of research on psychosis risk must address two major limitations: (1) interview methods have limited specificity, as recent estimates indicate that only 15%-30% of individuals identified as CHR convert to psychosis and (2) the expertise needed to make CHR diagnosis is only accessible in a handful of academic centers. Here, we introduce a new approach to CHR assessment that has the potential to increase accessibility and positive predictive value. Recent advances in clinical and computational cognitive neuroscience have generated new behavioral measures that assay the cognitive mechanisms and neural systems that underlie the positive, negative, and disorganization symptoms that are characteristic of psychotic disorders. We hypothesize that measures tied to symptom generation will lead to enhanced sensitivity and specificity relative to interview methods and the cognitive intermediate phenotype measures that have been studied to date that are typically indicators of trait vulnerability and, therefore, have a high false positive rate for conversion to psychosis. These new behavioral measures have the potential to be implemented on the internet and at minimal expense, thereby increasing accessibility of assessments., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.)

Objective: Negative symptoms and functional outcome have traditionally been assessed using clinical rating scales, which rely on retrospective self-reports and have several inherent limitations that impact validity. These issues may be addressed with more objective digital phenotyping measures. In the current study, we evaluated the psychometric properties of a novel "passive" digital phenotyping method: geolocation., Method: Participants included outpatients with schizophrenia or schizoaffective disorder (SZ: n = 44), outpatients with bipolar disorder (BD: n =19), and demographically matched healthy controls (CN: n = 42) who completed 6 days of "active" digital phenotyping assessments (eg, surveys) while geolocation was recorded., Results: Results indicated that SZ patients show less activity than CN and BD, particularly, in their travel from home. Geolocation variables demonstrated convergent validity by small to medium correlations with negative symptoms and functional outcome measured via clinical rating scales, as well as active digital phenotyping behavioral indices of avolition, asociality, and anhedonia. Discriminant validity was supported by low correlations with positive symptoms, depression, and anxiety. Reliability was supported by good internal consistency and moderate stability across days., Conclusions: These findings provide preliminary support for the reliability and validity of geolocation as an objective measure of negative symptoms and functional outcome. Geolocation offers enhanced precision and the ability to take a "big data" approach that facilitates sophisticated computational models. Near-continuous recordings and large numbers of samples may make geolocation a novel outcome measure for clinical trials due to enhanced power to detect treatment effects., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: Anhedonia, traditionally defined as a diminished capacity for pleasure, is a core symptom of schizophrenia (SZ). However, modern empirical evidence indicates that hedonic capacity may be intact in SZ and anhedonia may be better conceptualized as an abnormality in the temporal dynamics of emotion., Method: To test this theory, the current study used ecological momentary assessment (EMA) to examine whether abnormalities in one aspect of the temporal dynamics of emotion, sustained reward responsiveness, were associated with anhedonia. Two experiments were conducted in outpatients diagnosed with SZ (n = 28; n = 102) and healthy controls (n = 28; n = 71) who completed EMA reports of emotional experience at multiple time points in the day over the course of several days. Markov chain analyses were applied to the EMA data to evaluate stochastic dynamic changes in emotional states to determine processes underlying failures in sustained reward responsiveness., Results: In both studies, Markov models indicated that SZ had deficits in the ability to sustain positive emotion over time, which resulted from failures in augmentation (ie, the ability to maintain or increase the intensity of positive emotion from time t to t+1) and diminution (ie, when emotions at time t+1 are opposite in valence from emotions at time t, resulting in a decrease in the intensity of positive emotion over time). Furthermore, in both studies, augmentation deficits were associated with anhedonia., Conclusions: These computational findings clarify how abnormalities in the temporal dynamics of emotion contribute to anhedonia., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

A recent conceptual development in schizophrenia is to view its manifestations as interactive networks rather than individual symptoms. Negative symptoms, which are associated with poor functional outcome and reduced rates of recovery, represent a critical need in schizophrenia therapeutics. MIN101 (roluperidone), a compound in development, demonstrated efficacy in the treatment of negative symptoms in schizophrenia. However, it is unclear how the drug achieved its effect from a network perspective. The current study evaluated the efficacy of roluperidone from a network perspective. In this randomized clinical trial, participants with schizophrenia and moderate to severe negative symptoms were randomly assigned to roluperidone 32 mg (n = 78), 64 mg (n = 83), or placebo (N = 83). Macroscopic network properties were evaluated to determine whether roluperidone altered the overall density of the interconnections among symptoms. Microscopic properties were evaluated to examine which individual symptoms were most influential (ie, interconnected) on other symptoms in the network and are responsible for successful treatment effects. Participants receiving roluperidone did not differ from those randomized to placebo on macroscopic properties. However, microscopic properties (degree and closeness centrality) indicated that avolition was highly central in patients receiving placebo and that roluperidone reduced this level of centrality. These findings suggest that decoupling the influence of motivational processes from other negative symptom domains is essential for producing global improvements. The search for pathophysiological mechanisms and targeted treatment development should be focused on avolition, with the expectation of improvement in the entire constellation of negative symptoms if avolition is effectively treated., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Network analysis was used to examine how densely interconnected individual negative symptom domains are, whether some domains are more central than others, and whether sex influenced network structure. Participants included outpatients with schizophrenia (SZ; n = 201), a bipolar disorder (BD; n = 46) clinical comparison group, and healthy controls (CN; n = 27) who were rated on the Brief Negative Symptom Scale. The mutual information measure was used to construct negative symptom networks. Groups were compared on macroscopic network properties to evaluate overall network connectedness, and microscopic properties to determine which domains were most central. Macroscopic analyses indicated that patients with SZ had a less densely connected negative symptom network than BD or CN groups, and that males with SZ had less densely connected networks than females. Microscopic analyses indicated that alogia and avolition were most central in the SZ group, whereas anhedonia was most central in BD and CN groups. In addition, blunted affect, alogia, and asociality were most central in females with SZ, and alogia and avolition were most central in males with SZ. These findings suggest that negative symptoms may be highly treatment resistant in SZ because they are not very densely connected. Less densely connected networks may make treatments less likely to achieve global reductions in negative symptoms because individual domains function in isolation with little interaction. Sex differences in centralities suggest that the search for pathophysiological mechanisms and targeted treatment development should be focused on different sets of symptoms in males and females., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Prior studies using exploratory factor analysis provide evidence that negative symptoms are best conceptualized as 2 dimensions reflecting diminished motivation and expression. However, the 2-dimensional model has yet to be evaluated using more complex mathematical techniques capable of testing structure. In the current study, network analysis was applied to evaluate the latent structure of negative symptoms using a community-detection algorithm. Two studies were conducted that included outpatients with schizophrenia (SZ; Study 1: n = 201; Study 2: n = 912) who were rated on the Brief Negative Symptom Scale (BNSS). In both studies, network analysis indicated that the 13 BNSS items divided into 6 negative symptom domains consisting of anhedonia, avolition, asociality, blunted affect, alogia, and lack of normal distress. Separation of these domains was statistically significant with reference to a null model of randomized networks. There has been a recent trend toward conceptualizing the latent structure of negative symptoms in relation to 2 distinct dimensions reflecting diminished expression and motivation. However, the current results obtained using network analysis suggest that the 2-dimensional conceptualization is not complex enough to capture the nature of the negative symptom construct. Similar to recent confirmatory factor analysis studies, network analysis revealed that the latent structure of negative symptom is best conceptualized in relation to the 5 domains identified in the 2005 National Institute of Mental Health consensus development conference (anhedonia, avolition, asociality, blunted affect, and alogia) and potentially a sixth domain consisting of lack of normal distress. Findings have implications for identifying pathophysiological mechanisms and targeted treatments., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Negative symptoms occur early in the clinical high risk (CHR) state and indicate increased risk of conversion to psychotic disorder and poor functional outcome. However, while the negative symptom domain has shown to be parsimoniously explained by a 2-factor construct in schizophrenia, there has yet to be an established factor structure of negative symptoms in CHR., Methods: 214 individuals meeting the Structured Interview for Psychosis-Risk Syndromes (SIPS) criteria for CHR were recruited through 3 active research programs in the United States. Exploratory Factor Analysis was conducted on the 6 negative symptom items of the SIPS, and factors were evaluated with respect to functional outcome and depression., Results: Factor analysis indicated a 2-factor hierarchical model with 2 negative symptom dimensions reflecting volition (Occupational Functioning and Avolition) and emotion (Expression of Emotion, Experience of Emotion and Social Anhedonia). Linear Regression showed that the emotion factor was associated with poor social function, and the volition factor was associated with poor role function and depression., Conclusions: Similar to factor solutions identified in adults diagnosed with psychotic disorders, results indicated that the SIPS negative symptom subscale is not a unidimensional construct. Rather, the SIPS negative subscale has 2 distinct factors that have different associations with clinical outcome and should be interpreted independently. Results have significant relevance for informing the valid assessment and conceptual interpretation of early clinical phenomenology in the psychosis prodrome., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: Negative symptoms are currently viewed as having a 2-dimensional structure, with factors reflecting diminished expression (EXP) and motivation and pleasure (MAP). However, several factor-analytic studies suggest that the consensus around a 2-dimensional model is premature. The current study investigated and cross-culturally validated the factorial structure of BNSS-rated negative symptoms across a range of cultures and languages., Method: Participants included individuals diagnosed with a psychotic disorder who had been rated on the Brief Negative Symptom Scale (BNSS) from 5 cross-cultural samples, with a total N = 1691. First, exploratory factor analysis was used to extract up to 6 factors from the data. Next, confirmatory factor analysis evaluated the fit of 5 models: (1) a 1-factor model, 2) a 2-factor model with factors of MAP and EXP, 3) a 3-factor model with inner world, external, and alogia factors; 4) a 5-factor model with separate factors for blunted affect, alogia, anhedonia, avolition, and asociality, and 5) a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 aforementioned domains., Results: Models with 4 factors or less were mediocre fits to the data. The 5-factor, 6-factor, and the hierarchical second-order 5-factor models provided excellent fit with an edge to the 5-factor model. The 5-factor structure demonstrated invariance across study samples., Conclusions: Findings support the validity of the 5-factor structure of BNSS-rated negative symptoms across diverse cultures and languages. These findings have important implications for the diagnosis, assessment, and treatment of negative symptoms., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In the DSM5, negative symptoms are 1 of the 5 core dimensions of psychopathology evaluated for schizophrenia. However, negative symptoms are not pathognomonic-they are also part of the diagnostic criteria for other schizophrenia-spectrum disorders, disorders that sometimes have comorbid psychosis, diagnoses not in the schizophrenia-spectrum, and the general "nonclinical" population. Although etiological models of negative symptoms have been developed for chronic schizophrenia, there has been little attention given to whether these models have transdiagnostic applicability. In the current review, we examine areas of commonality and divergence in the clinical presentation and etiology of negative symptoms across diagnostic categories. It was concluded that negative symptoms are relatively frequent across diagnostic categories, but individual disorders may differ in whether their negative symptoms are persistent/transient or primary/secondary. Evidence for separate dimensions of volitional and expressive symptoms exists, and there may be multiple mechanistic pathways to the same symptom phenomenon among DSM-5 disorders within and outside the schizophrenia-spectrum (ie, equifinality). Evidence for a novel transdiagnostic etiological model is presented based on the Research Domain Criteria (RDoC) constructs, which proposes the existence of 2 such pathways-a hedonic pathway and a cognitive pathway-that can both lead to expressive or volitional symptoms. To facilitate treatment breakthroughs, future transdiagnostic studies on negative symptoms are warranted that explore mechanisms underlying volitional and expressive pathology., (© The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In 2005, the National Institute of Mental Health held a consensus development conference on negative symptoms of schizophrenia. Among the important conclusions of this meeting were that there are at least 5 commonly accepted domains of negative symptoms (blunted affect, alogia, avolition, anhedonia, asociality) and that new rating scales were needed to adequately assess these constructs. Two next-generation negative symptom scales resulted from this meeting: the Brief Negative Symptom Scale (BNSS) and Clinical Assessment Interview for Negative Symptoms (CAINS). Both measures are becoming widely used and studies have demonstrated good psychometric properties for each scale. The current study provides the first direct psychometric comparison of these scales. Participants included 65 outpatients diagnosed with schizophrenia or schizoaffective disorder who completed clinical interviews, questionnaires, and neuropsychological testing. Separate raters completed the BNSS and CAINS within the same week. Results indicated that both measures had good internal consistency, convergent validity, and discriminant validity. High correspondence was observed between CAINS and BNSS blunted affect and alogia items. Moderate convergence occurred for avolition and asociality items, and low convergence was seen among anhedonia items. Findings suggest that both scales have good psychometric properties, but that there are important distinctions among the items related to motivation and pleasure., (© The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Studies have supported the validity of the deficit form of schizophrenia (ie, people with primary and enduring negative symptoms). A test of whether that group is a true taxon-that is, a distinct, discontinuous group-has yet to be conducted and the underlying structure of negative symptoms as categorical or dimensional remains undetermined. The present study examined the latent structure of negative and deficit symptoms to determine if a nonarbitrary boundary distinguishes deficit from nondeficit forms of schizophrenia (ie, whether these symptoms reflect a continuous or categorical variable). Schedule for the Deficit Syndrome ratings of 789 individuals with a psychotic disorder were submitted to taxometric and latent variable mixture analyses to test categorical vs dimensional hypotheses of negative symptoms and deficit schizophrenia. Analytic models favored a taxonic structure of negative symptoms and the validity of the deficit/nondeficit classification scheme. Taxometric classification outperformed clinician-based deficit/nondeficit classification in its association with summer birth, male sex, premorbid adjustment, neurocognition, and psychosocial functioning. Within taxon and complement classes, severity scores remained significant predictors of premorbid adjustment, neurocognition, and psychosocial functioning. Thus, although a categorical approach is validated, a hybrid categorical-dimensional conceptualization of negative symptoms also has validity for the prediction of external variables., (© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Contrary to early conceptualizations of emotional experience in schizophrenia (SZ), recent research indicates that patients do not self-report less in-the-moment pleasure than controls (CN). Rather, patients report experiencing elevated levels of negative emotionality in response to a range of evocative stimuli. In this study, we examined the possibility that elevations in negative emotionality in SZ may reflect an underlying emotion regulation abnormality. Event-related potentials (ERPs) were recorded from outpatients with SZ (n = 25) and demographically matched healthy controls (n = 21) during passive viewing of unpleasant and neutral photographs. Unpleasant images were preceded by an audio description that described the image as being either negative or neutral. Neutral images were preceded by neutral audio descriptions. The late positive potential (LPP), an ERP component sensitive to cognitive change strategies, was examined as an index of emotion regulation. Both CN and SZ showed an increased LPP to negatively described unpleasant images compared with neutral images. In addition, CN showed evidence of emotion regulation, as reflected by a smaller LPP for unpleasant images preceded by a neutral descriptor, relative to a negative descriptor. In contrast, SZ patients showed an inability to downregulate emotional response, as evidenced by no difference in the amplitude of the LPP for unpleasant images preceded by negative or neutral descriptors. Findings provide neurophysiological evidence for an emotion regulation abnormality in SZ and suggest that failures in cognitive change may underlie increased negative emotionality in SZ.

Previous studies have typically found that individuals with schizophrenia (SZ) report levels of emotional experience that are similar to controls (CN) when asked to view a single evocative stimulus and make an absolute judgment of stimulus "value." However, value is rarely assigned in absolute terms in real-life situations, where one alternative or experience is often evaluated alongside others, and value judgments are made in relative terms. In the current study, we examined performance on a preference task that requires individuals to differentiate between the relative values of different stimuli. In this task, subjects were presented with many pairs of moderately positive stimuli and asked to indicate which stimulus they preferred in each pair. Resulting data indicated the rank order of preference across stimuli and the consistency of their transitive mapping (ie, if A > B and B > C, then A should be > C). Individuals with SZ (n = 38) were both less consistent in their rankings of stimuli and more likely to have larger magnitudes of discrepant responses than control subjects (n = 27). Furthermore, CN showed clear differentiation between different valence categories of stimuli (ie, highly positive > mildly positive > mildly negative > highly negative); while individuals with SZ showed the same general pattern of results but with less differentiation between the valence levels. These data suggest that individuals with SZ are impaired in developing or maintaining nuanced representations of the different attributes of a stimulus, thus making stimuli of similar general value easily confusable.

Posttraumatic stress disorder (PTSD) is highly comorbid with schizophrenia and may be associated with higher levels or lower levels of negative symptoms. In the current study, we attempted to clarify the relationship between PTSD and negative symptoms by examining the proportion of patients meeting various negative symptom criteria in a sample of patients diagnosed with schizophrenia alone or schizophrenia and comorbid PTSD. Results indicated that the presence of PTSD in schizophrenia was associated with increased secondary negative symptoms, with the deficit syndrome (DS) and primary negative symptoms associated with lower rates of current and lifetime diagnoses of PTSD. Furthermore, the deficit/nondeficit classification provided greater differentiation of PTSD symptoms than did negative symptoms defined more broadly using the Scale for the Assessment of Negative Symptoms or primary vs secondary distinctions. These findings suggest that DS patients are at a uniquely low risk for PTSD., (© The Author 2009. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.)

The participants in the NIMH-MATRICS Consensus Development Conference on Negative Symptoms recommended that an instrument be developed that measured blunted affect, alogia, asociality, anhedonia, and avolition. The Brief Negative Symptom Scale (BNSS) is a 13-item instrument designed for clinical trials and other studies that measures these 5 domains. The interrater, test-retest, and internal consistency of the instrument were strong, with respective intraclass correlation coefficients of 0.93 for the BNSS total score and values of 0.89-0.95 for individual subscales. Comparisons with positive symptoms and other negative symptom instruments supported the discriminant and concurrent validity of the instrument.

Olfactory perception was examined in deficit syndrome (DS) and nondeficit syndrome (ND) schizophrenia patients. Participants included 22 controls (CN) and 41 patients with schizophrenia who were divided into DS (n = 15) and ND (n = 26) subtypes using the Schedule for the Deficit Syndrome (SDS). Olfactory perception for pleasant and unpleasant odors was assessed using the Brief Smell Identification Test. Participants were instructed to identifying each smell as well as provide hedonic judgment ratings of each smell on a 7-point scale (1 = extremely pleasant, 4 = neutral, and 7 = extremely unpleasant). Results indicated that when compared with the ND patients, the DS patients rated pleasant smells as being significantly less pleasant, although no difference between the groups was present for unpleasant smells, and both ND and DS groups significantly differed from CN on rating and identifying pleasant and unpleasant items. Additionally, lower smell identification accuracy was negatively correlated with SDS symptom severity, and valence ratings for pleasant odors were positively correlated with SDS diminished emotional range. Findings suggest that the DS is characterized by a unique pattern of olfactory valence judgment that is characterized by abnormalities in processing positively valenced stimuli.