Dataset Information

Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses.

ABSTRACT: Objective:Common genetic variation spans schizophrenia, schizoaffective and bipolar disorders, but historically, these syndromes have been distinguished categorically. A symptom dimension shared across these syndromes, if such a general factor exists, might provide a clearer target for understanding and treating mental illnesses that share core biological bases. Method:We tested the hypothesis that a bifactor model of the Positive and Negative Syndrome Scale (PANSS), containing 1 general factor and 5 specific factors (positive, negative, disorganized, excited, anxiety), explains the cross-diagnostic structure of symptoms better than the traditional 5-factor model, and examined the extent to which a general factor reflects the overall severity of symptoms spanning diagnoses in 5094 total patients with a diagnosis of schizophrenia, schizoaffective, and bipolar disorder. Results:The bifactor model provided superior fit across diagnoses, and was closer to the "true" model, compared to the traditional 5-factor model (Vuong test; P < .001). The general factor included high loadings on 28 of the 30 PANSS items, omitting symptoms associated with the excitement and anxiety/depression domains. The general factor had highest total loadings on symptoms that are often associated with the positive and disorganization syndromes, but there were also substantial loadings on the negative syndrome thus leading to the interpretation of this factor as reflecting generalized psychosis. Conclusions:A bifactor model derived from the PANSS can provide a stronger framework for measuring cross-diagnostic psychopathology than a 5-factor model, and includes a generalized psychosis dimension shared at least across schizophrenia, schizoaffective, and bipolar disorder.

SUBMITTER: Anderson AE

PROVIDER: S-EPMC6192503 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses.

Anderson Ariana E AE Marder Stephen S Reise Steven P SP Savitz Adam A Salvadore Giacomo G Fu Dong Jing DJ Li Qingqin Q Turkoz Ibrahim I Han Carol C Bilder Robert M RM

Schizophrenia bulletin 20181001 6

<h4>Objective</h4>Common genetic variation spans schizophrenia, schizoaffective and bipolar disorders, but historically, these syndromes have been distinguished categorically. A symptom dimension shared across these syndromes, if such a general factor exists, might provide a clearer target for understanding and treating mental illnesses that share core biological bases.<h4>Method</h4>We tested the hypothesis that a bifactor model of the Positive and Negative Syndrome Scale (PANSS), containing 1 ...[more]

PMID: 29420822

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Project description:The corpus callosum has been implicated in the pathogenesis of schizophrenia and bipolar disorder. However, it is unclear whether corpus callosum alterations are related to the underlying familial diathesis for psychotic disorders. We examined the corpus callosum and its subregion volumes and their relationship to cognition, psychotic symptoms, and age in probands with schizophrenia (SZ), psychotic bipolar disorder (PBD), and schizoaffective disorder; their first-degree relatives; and healthy control subjects.We present findings from morphometric and neurocognitive analyses of 1381 subjects (SZ probands, n = 224; PBD probands, n = 190; schizoaffective disorder probands, n = 142; unaffected relatives, n = 483 [SZ relatives, n = 195; PBD relatives, n = 175; schizoaffective disorder relatives, n = 113]; control subjects, n = 342). Magnetization prepared rapid acquisition gradient-echo T1 scans across five sites were obtained using 3-tesla magnets. Image processing was done using FreeSurfer Version 5.1. Neurocognitive function was measured using the Brief Assessment of Cognition in Schizophrenia scale.Anterior and posterior splenial volumes were significantly reduced across the groups. The SZ and PBD probands showed robust and significant reductions, whereas relatives showed significant reductions of intermediate severity. The splenial volumes were positively but differentially correlated with aspects of cognition in the probands and their relatives. Proband groups showed a significant age-related decrease in the volume of the anterior splenium compared with control subjects. Among the psychosis groups, the anterior splenium in probands with PBD showed a stronger correlation with psychotic symptoms, as shown by the Positive and Negative Syndrome Scale. All five subregions showed significantly high familiality.The splenial volumes were significantly reduced across the psychosis dimension. However, this volume reduction impacts cognition and clinical manifestation of the illnesses differentially.

Project description:BackgroundThe network approach to psychopathology has become increasingly popular. Little research has examined the dynamic network structure of mental disorders, and, to date, no study has investigated the network dynamics of positive affect, negative affect, and physical activity in bipolar disorder. This represents the first study to estimate the dynamic network structure of affect and physical activity in individuals with and without bipolar I disorder.MethodsAn intensive longitudinal design was used to assess positive affect, negative affect, and actigraphy-based estimates of physical activity. The overall sample consisted of 32 adults with bipolar I disorder and 36 healthy control participants. Eligible participants underwent an 8-week assessment period, in which once-per-day ratings of affect and actigraphy estimates were obtained. Participants were re-assessed on baseline measures afterwards. Dynamic network analysis was used to examine the network structure of affect and physical activity over time. Multilevel models were used to examine the relationship between autocorrelation and changes in depression symptoms among participants with bipolar disorder.LimitationsThe network analyses assume stationarity. Future research should consider time-varying multilevel network models to better account for time trends.ResultsThe results of the temporal networks indicated that the directed edges between positive and negative affect were mostly positive among individuals with bipolar I disorder. Among healthy control participants, the directed edges between positive and negative affect were mostly negative in direction. Physical activity, as assessed by daily actigraphy indices, was more densely connected in the healthy control network than the bipolar disorder network. Furthermore, the results indicated that critical slowing down predicted worsening of mood symptoms in the bipolar I disorder group.ConclusionsThis study suggests that certain dynamic patterns of affect may be an underlying process that contributes to the maintenance of bipolar disorder. These results have both theoretical and practical implications.

Dataset Information

Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses.

Publications

Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses.

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