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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.
Traditionally, mental disorders have been identified based on specific symptoms and standardized diagnostic systems such as the DSM-5 and ICD-10. However, these symptom-based definitions may only partially represent neurobiological and behavioral research findings, which could impede the development of targeted treatments. A transdiagnostic approach to mental health research, such as the Research Domain Criteria (RDoC) approach, maps resilience and broader aspects of mental health to associated components. By investigating mental disorders in a transnosological way, we can better understand disease patterns and their distinguishing and common factors, leading to more precise prevention and treatment options.
Therefore, this dissertation focuses on (1) the latent domain structure of the RDoC approach in a transnosological sample including healthy controls, (2) its domain associations to disease severity in patients with anxiety and depressive disorders, and (3) an overview of the scientific results found regarding Positive (PVS) and Negative Valence Systems (NVS) associated with mood and anxiety disorders.
The following main results were found: First, the latent RDoC domain structure for PVS and NVS, Cognitive Systems (CS), and Social Processes (SP) could be validated using self-report and behavioral measures in a transnosological sample. Second, we found transdiagnostic and disease-specific associations between those four domains and disease severity in patients with depressive and anxiety disorders. Third, the scoping review showed a sizable amount of RDoC research conducted on PVS and NVS in mood and anxiety disorders, with research gaps for both domains and specific conditions.
In conclusion, the research presented in this dissertation highlights the potential of the transnosological RDoC framework approach in improving our understanding of mental disorders. By exploring the latent RDoC structure and associations with disease severity and disease-specific and transnosological associations for anxiety and depressive disorders, this research provides valuable insights into the full spectrum of psychological functioning. Additionally, this dissertation highlights the need for further research in this area, identifying both RDoC indicators and research gaps. Overall, this dissertation represents an important contribution to the ongoing efforts to improve our understanding and the treatment of mental disorders, particularly within the commonly comorbid disease spectrum of mood and anxiety disorders.
Predictors and prevalence of hazardous alcohol use in middle-late to late adulthood in Europe
(2022)
Objectives:
Even low to moderate levels of alcohol consumption can have detrimental health consequences, especially in older adults (OA). Although many studies report an increase in the proportion of drinkers among OA, there are regional variations. Therefore, we examined alcohol consumption and the prevalence of hazardous alcohol use (HAU) among men and women aged 50+ years in four European regions and investigated predictors of HAU.
Methods:
We analyzed data of N = 35,042 participants of the European SHARE study. We investigated differences in alcohol consumption (units last week) according to gender, age and EU-region using ANOVAs. Furthermore, logistic regression models were used to examine the effect of income, education, marital status, history of a low-quality parent-child relationship and smoking on HAU, also stratified for gender and EU-region. HAU was operationalized as binge drinking or risky drinking (<12.5 units of 10 ml alcohol/week).
Results:
Overall, past week alcohol consumption was 5.0 units (+/- 7.8), prevalence of HAU was 25.4% within our sample of European adults aged 50+ years. Male gender, younger age and living in Western Europe were linked to both higher alcohol consumption and higher risks of HAU. Income, education, smoking, a low-quality parent-child relationship, living in Northern and especially Eastern Europe were positively associated with HAU. Stratified analyses revealed differences by region and gender.
Conclusions:
HAU was highly prevalent within this European sample of OA. Alcohol consumption and determinants of HAU differed between EU-regions, hinting to a necessity of risk-stratified population-level strategies to prevent HAU and subsequent alcohol use disorders.
Background:
From birth to young adulthood, health and development of young people are strongly linked to their living situation, including their family's socioeconomic position (SEP) and living environment. The impact of regional characteristics on development in early childhood beyond family SEP has been rarely investigated. This study aimed to identify regional predictors of global developmental delay at school entry taking family SEP into consideration.
Method:
We used representative, population-based data from mandatory school entry examinations of the German federal state of Brandenburg in 2018/2019 with n=22,801 preschool children. By applying binary multilevel models, we hierarchically analyzed the effect of regional deprivation defined by the German Index of Socioeconomic Deprivation (GISD) and rurality operationalized as inverted population density of the children's school district on global developmental delay (GDD) while adjusting for family SEP (low, medium and high)
Results:
Family SEP was significantly and strongly linked to GDD. Children with the highest family SEP showed a lower odds for GDD compared to a medium SEP (female: OR=4.26, male: OR=3.46) and low SEP (female: OR=16.58, male: OR=12.79). Furthermore, we discovered a smaller, but additional and independent effect of regional socioeconomic deprivation on GDD, with a higher odds for children from a more deprived school district (female: OR=1.35, male: OR=1.20). However, rurality did not show a significant link to GDD in preschool children beyond family SEP and regional deprivation.
Conclusion:
Family SEP and regional deprivation are risk factors for child development and of particular interest to promote health of children in early childhood and over the life course.