@article{FoerstnerBoettgerMoldavskietal.2023,
  author    = {F{\"o}rstner, Bernd Rainer and B{\"o}ttger, Sarah Jane and Moldavski, Alexander and Bajbouj, Malek and Pfennig, Andrea and Manook, Andre and Ising, Marcus and Pittig, Andre and Heinig, Ingmar and Heinz, Andreas and Mathiak, Klaus and Schulze, Thomas G. and Schneider, Frank and Kamp-Becker, Inge and Meyer-Lindenberg, Andreas and Padberg, Frank and Banaschewski, Tobias and Bauer, Michael and Rupprecht, Rainer and Wittchen, Hans-Ulrich and Rapp, Michael A. and Tschorn, Mira},
  title     = {The associations of positive and negative valence systems, cognitive systems and social processes on disease severity in anxiety and depressive disorders},
  series = {Frontiers in psychiatry},
  volume    = {14},
  journal   = {Frontiers in psychiatry},
  publisher = {Frontiers Research Foundation},
  address   = {Lausanne},
  issn      = {1664-0640},
  doi       = {10.3389/fpsyt.2023.1161097},
  pages     = {10},
  year      = {2023},
  abstract  = {Background Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders. Methods Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP). Results The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: \& beta; = -0.35; NVS: \& beta; = 0.39; CS: \& beta; = -0.12; SP: \& beta; = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association. Limitations The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for. Conclusion Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.},
  language  = {en}
}
@article{FoerstnerTschornReinosoSchilleretal.2022,
  author    = {F{\"o}rstner, Bernd R. and Tschorn, Mira and Reinoso-Schiller, Nicolas and Maričić, Lea Mascarell and R{\"o}cher, Erik and Kalman, Janos L. and Stroth, Sanna and Mayer, Annalina V. and Schwarz, Kristina and Kaiser, Anna and Pfennig, Andrea and Manook, Andr{\´e} and Ising, Marcus and Heinig, Ingmar and Pittig, Andre and Heinz, Andreas and Mathiak, Klaus and Schulze, Thomas G. and Schneider, Frank and Kamp-Becker, Inge and Meyer-Lindenberg, Andreas and Padberg, Frank and Banaschewski, Tobias and Bauer, Michael and Rupprecht, Rainer and Wittchen, Hans-Ulrich and Rapp, Michael A.},
  title     = {Mapping research domain criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis},
  series = {European archives of psychiatry and clinical neuroscience},
  volume    = {273},
  journal   = {European archives of psychiatry and clinical neuroscience},
  number    = {3},
  publisher = {Springer Nature},
  address   = {Heidelberg},
  issn      = {0940-1334},
  doi       = {10.1007/s00406-022-01440-6},
  pages     = {527 -- 539},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}