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Abstract Background Social health inequalities are still of great public health importance in modern societies. The COVID-19 pandemic may have affected social inequalities in people's health due to containment measures. As these measures particularly affected children, they might have been particularly vulnerable to increased social inequalities. The aim of the study was to describe health inequalities during the pandemic based on language delay (LD) in children in order to inform public health interventions for a population at risk of long-term health and education inequalities. Methods Data of 5–7 year old children from three consecutive school entry surveys in the German federal state of Brandenburg were used, including data compulsorily collected before the pandemic (2018/2019: n = 19,299), at the beginning of the pandemic (2019/2020: n = 19,916) and during the pandemic (2020/2021: n = 19,698). Bivariate and multivariate binary regression analyses [OR, 95% CI] cross-sectionally examined the relationship between the prevalence of LD [yes/no] and social inequalities, operationalized by family socioeconomic position [SEP low/middle/high], migration background [native-German language/non-native German language] and length of kindergarten attendance [

Background: It is well known that there are gender differences in the health behaviour and physical and mental health of children. The COVID-19 pandemic influenced the health and lifestyles of children and adolescents by changing their living conditions. The present work investigates whether gender differences in selected health indicators are evident more than two years after the onset of the pandemic. Methods: In the study Kindergesundheit in Deutschland aktuell (KIDA) (German Children’s Health Update), cross-sectional telephone surveys were conducted with parents of 3- to 15-year-olds (n=3,478). Parental information on the general and mental health of the child, on increased need for health care and mental health services, as well as on physical activity and utilisation of sports activities were queried in standardised manner. Gender differences were assessed using Chi2 tests. Results: A total of 91% of the girls and 92% of the boys had their general health assessed as being (very) good by their parents (difference not significant, n.s.). An increased need for care and support was indicated for 10.6% of the 3- to 15-year-olds (girls: 9%, boys: 12%, n.s.). Boys met the physical activity recommendations of the WHO significantly more often (60%) than girls (54%). Good to excellent mental health was reported for 93% of both boys and girls. When changes during the pandemic were reported, no differences were found in the responses for girls compared to boys. Conclusions: Gender differences were found for individual parameters and age groups. These differences must be assessed in the context of other social determinants of health, and need to be considered when planning preventive measures.

BackgroundAs the climate and environmental crises unfold, eco-anxiety, defined as anxiety about the crises’ devastating consequences for life on earth, affects mental health worldwide. Despite its importance, research on eco-anxiety is currently limited by a lack of validated assessment instruments available in different languages. Recently, Hogg and colleagues proposed a multidimensional approach to assess eco-anxiety. Here, we aim to translate the original English Hogg Eco-Anxiety Scale (HEAS) into German and to assess its reliability and validity in a German sample.MethodsFollowing the TRAPD (translation, review, adjudication, pre-test, documentation) approach, we translated the original English scale into German. In total, 486 participants completed the German HEAS. We used Bayesian confirmatory factor analysis (CFA) to assess whether the four-factorial model of the original English version could be replicated in the German sample. Furthermore, associations with a variety of emotional reactions towards the climate crisis, general depression, anxiety, and stress were investigated.ResultsThe German HEAS was internally consistent (Cronbach’s alphas 0.71–0.86) and the Bayesian CFA showed that model fit was best for the four-factorial model, comparable to the factorial structure of the original English scale (affective symptoms, rumination, behavioral symptoms, anxiety about personal impact). Weak to moderate associations were found with negative emotional reactions towards the climate crisis and with general depression, anxiety, and stress.DiscussionOur results support the original four-factorial model of the scale and indicate that the German HEAS is a reliable and valid scale to assess eco-anxiety in German speaking populations.

BackgroundAnxiety 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.MethodsWithin 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).ResultsThe results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: β = −0.35; NVS: β = 0.39; CS: β = −0.12; SP: β = −0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.LimitationsThe cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.ConclusionOur key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.

IntroductionWhile a growing body of research is adopting Research Domain Criteria (RDoC)-related methods and constructs, there is still a lack of comprehensive reviews on the state of published research on Positive Valence Systems (PVS) and Negative Valence Systems (NVS) in mood and anxiety disorders consistent with the RDoC framework.MethodsFive electronic databases were searched to identify peer-reviewed publications covering research on “positive valence” and “negative valence” as well as “valence,” “affect,” and “emotion” for individuals with symptoms of mood and anxiety disorders. Data was extracted with a focus on disorder, domain, (sub-) constructs, units of analysis, key results, and study design. Findings are presented along four sections, distinguishing between primary articles and reviews each for PVS, NVS, and cross-domain PVS and NVS.ResultsA total of 231 abstracts were identified, and 43 met the inclusion criteria for this scoping review. Seventeen publications addressed research on PVS, seventeen on NVS, and nine covered cross-domain research on PVS and NVS. Psychological constructs were typically examined across different units of analysis, with the majority of publications incorporating two or more measures. Molecular, genetic, and physiological aspects were mainly investigated via review articles, primary articles focused on self-report, behavioral, and, to a lesser extent, physiological measures.ConclusionsThis present scoping review shows that mood and anxiety disorders were actively studied using a range of genetic, molecular, neuronal, physiological, behavioral, and self-report measures within the RDoC PVS and NVS. Results highlight the essential role of specific cortical frontal brain structures and of subcortical limbic structures in impaired emotional processing in mood and anxiety disorders. Findings also indicate overall limited research on NVS in bipolar disorders and PVS in anxiety disorders, a majority of self-report studies, and predominantly observational studies. Future research is needed to develop more RDoC-consistent advancements and intervention studies targeting neuroscience-driven PVS and NVS constructs.

Summary: Background: Current evidence points towards a high prevalence of psychological distress in refugee populations, contrasting with a scarcity of resources and amplified by linguistic, institutional, financial, and cultural barriers. The objective of the study is to investigate the overall effectiveness and cost-effectiveness of a Stepped Care and Collaborative Model (SCCM) at reducing depressive symptoms in refugees, compared with the overall routine care practices within Germany's mental healthcare system (treatment-as-usual, TAU). Methods: A multicentre, clinician-blinded, randomised, controlled trial was conducted across seven university sites in Germany. Asylum seekers and refugees with relevant depressive symptoms with a Patient Health Questionnaires score of ≥ 5 and a Refugee Health Screener score of ≥ 12. Participants were randomly allocated to one of two treatment arms (SCCM or TAU) for an intervention period of three months between April 2018 and March 2020. In the SCCM, participants were allocated to interventions tailored to their symptom severity, including watchful waiting, peer-to-peer- or smartphone intervention, psychological group therapies or mental health expert treatment. The primary endpoint was defined as the change in depressive symptoms (Patient Health Questionnaire-9, PHQ-9) after 12 weeks. The secondary outcome was the change in Montgomery Åsberg Depression Rating Scale (MADRS) from baseline to post-intervention. Findings: The intention-to-treat sample included 584 participants who were randomized to the SCCM (n= 294) or TAU (n=290). Using a mixed-effects general linear model with time, and the interaction of time by randomisation group as fixed effects and study site as random effect, we found significant effects for time (p < .001) and time by group interaction (p < .05) for intention-to-treat and per-protocol analysis. Estimated marginal means of the PHQ-9 scores after 12 weeks were significantly lower in SCCM than in TAU (for intention-to-treat: PHQ-9 mean difference at T1 1.30, 95% CI 1.12 to 1.48, p < .001; Cohen's d=.23; baseline-adjusted PHQ-9 mean difference at T1 0.57, 95% CI 0.40 to 0.74, p < .001). Cost-effectiveness and net monetary benefit analyses provided evidence of cost-effectiveness for the primary outcome and quality-adjusted life years. Robustness of results were confirmed by sensitivity analyses. Interpretation: The SSCM resulted in a more effective and cost-effective reduction of depressive symptoms compared with TAU. Findings suggest a suitable model to provide mental health services in circumstances where resources are limited, particularly in the context of forced migration and pandemics. Funding: This project is funded by the Innovationsfond and German Ministry of Health [grant number 01VSF16061]. The present trial is registered under Clinical-Trials.gov under the registration number: NCT03109028. https://clinicaltrials.gov/ct2/show/NCT03109028

Abstract Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions.

Alcohol misuse during adolescence (AAM) has been associated with disruptive development of adolescent brains. In this longitudinal machine learning (ML) study, we could predict AAM significantly from brain structure (T1-weighted imaging and DTI) with accuracies of 73 -78% in the IMAGEN dataset (n∼1182). Our results not only show that structural differences in brain can predict AAM, but also suggests that such differences might precede AAM behavior in the data. We predicted 10 phenotypes of AAM at age 22 using brain MRI features at ages 14, 19, and 22. Binge drinking was found to be the most predictable phenotype. The most informative brain features were located in the ventricular CSF, and in white matter tracts of the corpus callosum, internal capsule, and brain stem. In the cortex, they were spread across the occipital, frontal, and temporal lobes and in the cingulate cortex. We also experimented with four different ML models and several confound control techniques. Support Vector Machine (SVM) with rbf kernel and Gradient Boosting consistently performed better than the linear models, linear SVM and Logistic Regression. Our study also demonstrates how the choice of the predicted phenotype, ML model, and confound correction technique are all crucial decisions in an explorative ML study analyzing psychiatric disorders with small effect sizes such as AAM.

Background: Anxiety and post-traumatic stress disorder (PTSD) are known etiologic and prognostic risk factors in patients with coronary heart disease (CHD). However, few studies have assessed the prevalence of a comprehensive set of anxiety and stress related disorders in CHD. Moreover, it is unclear whether these disorders are associated with CHD symptoms, severity and cardiovascular events and procedures. Methods: We determined the 12-month prevalence of anxiety disorders and PTSD in N = 1024 hospitalized patients with CHD and examined associations with cardiac disease characteristics, cardiovascular events and procedures. Anxiety and PTSD diagnoses were determined with the Composite International Diagnostic Interview. Socio-demographic variables were assessed with a questionnaire and cardiovascular variables were extracted from medical charts. Results: 12-month prevalence for any anxiety disorder was 11.2% for men and 24.8% for women; 12-month PTSD prevalence was 1.1% and 5.2%, respectively. The most common anxiety disorders were specific phobia (men: 8.2%, women: 18.8%) and agoraphobia and/or panic disorder (combined prevalence men: 2.9%, women: 9.9%). Anxiety disorders were not associated with any cardiovascular variables. Limitations: Due to lack of follow-up data no conclusions regarding stability of diagnoses are possible. Associations of PTSD and medical variables could not be determined because of low PTSD prevalence. Conclusions: Compared to the general population, anxiety disorders were more frequent in younger (