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  • This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix. (xsd:string)
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  • 2022 (xsd:gyear)
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  • 2022 (xsd:gyear)
?:doi
  • 10.1007/s00406-022-01440-6 ()
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  • en (xsd:string)
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  • 1433-8491 ()
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  • 3 (xsd:string)
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  • Mapping Research Domain Criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis (xsd:string)
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  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
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  • GESIS-SSOAR (xsd:string)
  • In: European Archives of Psychiatry and Clinical Neuroscience, 273, 2022, 3, 527-539 (xsd:string)
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?:urn
  • urn:nbn:de:0168-ssoar-98345-6 ()
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  • 273 (xsd:string)