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Background: Depression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models. Methods: We used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later. Results: The network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave. Conclusions: The somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles. [ABSTRACT FROM AUTHOR]

Background: Access to evidence-based psychological treatment is a challenge worldwide. We assessed the effectiveness of a fully automated aviophobia smartphone app treatment delivered in combination with a $5 virtual reality (VR) viewer. Methods: In total, 153 participants from the Dutch general population with aviophobia symptoms and smartphone access were randomized in a single-blind randomized controlled trial to either an automated VR cognitive behavior therapy (VR-CBT) app treatment condition (n = 77) or a wait-list control condition (n = 76). The VR-CBT app was delivered over a 6-week period in the participants' natural environment. Online self-report assessments were completed at baseline, post-treatment, at 3-month and at 12-month follow-up. The primary outcome measure was the Flight Anxiety Situations Questionnaire (FAS). Analyses were based on intent-to-treat. Results: A significant reduction of aviophobia symptoms at post-test for the VR-CBT app compared with the control condition [ p < 0.001; d = 0. 98 (95% CI 0.65–1.32)] was demonstrated. The dropout rate was 21%. Results were maintained at 3-month follow-up [within-group d = 1.14 (95% CI 0.46–1.81)] and at 12-month follow-up [within-group d = 1.12 (95% CI 0.46–1.79)]. Six participants reported adverse effects of cyber sickness symptoms. Conclusions: This study is the first to show that fully automated mobile VR-CBT therapy delivered in a natural setting can maintain long-term effectiveness in reducing aviophobia symptoms. In doing so, it offers an accessible and scalable evidence-based treatment solution that can be applied globally at a fraction of the cost of current treatment alternatives. [ABSTRACT FROM AUTHOR]

Background: Psychotic experiences (PEs) frequently occur and are associated with a range of negative health outcomes. Prospective studies on PEs are scarce, and to date no study investigated PE prevalence, incidence, persistence, their risk indicators, and psychiatric comorbidity, in one dataset. Furthermore, most studies are based on self-report, and it is unclear how this compares to clinical interviews. Methods: Data are used from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), a psychiatric cohort study among a representative sample of adults (baseline characteristics: N = 6646; 49.6% female; 18–64 years). Results are presented for self-reported and clinically validated PEs. Associations are assessed for mental disorders, socio-demographic, vulnerability, physical health, and substance use factors. Results: Based on self-report, at baseline 16.5% of respondents had at least one PE in their lifetime, of those, 30.1% also reported a PE at 3-year follow-up. 4.8% had a first PE at 3-year follow up. The 3-year prevalence of PE was associated with almost all studied risk indicators. Generally, the strongest associations were found for mental health disorders. Prevalence and incidence rates were two to three times higher in self-report than in clinical interview but results on associated factors were similar. Conclusions: Validated prevalence and incidence estimates of PE are substantially lower than self-reported figures but results on associated factors were similar. Therefore, future studies on associations of PEs can rely on relatively inexpensive self-reports of PEs. The associations between PE and mental disorders underline the importance of assessment of PE in general practice. [ABSTRACT FROM AUTHOR]

Background: Military personnel deployed to combat and peacekeeping missions are exposed to high rates of traumatic events. Accumulating evidence suggests an important association between deployment and the development of other mental health symptoms beyond post-traumatic stress disorder. Methods: This study examined the prevalence of agoraphobia, anxiety, depression, and hostility symptoms in a cohort of Dutch ISAF veterans (N = 978) from pre-deployment up to 10 years after homecoming. The interaction of potential moderating factors with the change in mental health symptoms relative to pre-deployment was investigated at each time point. Results: The probable prevalence of agoraphobia, anxiety, depression, and hostility symptoms significantly increased over time to respectively 6.5, 2.7, 3.5, and 6.2% at 10 years after deployment. Except for hostility symptoms, the probable prevalence at 10 years after deployment was the highest compared to all previous follow-up assessments. Importantly, less perceived social support after returning from deployment was found as a risk factor for all different mental health symptoms. Unit support was not associated with the development of mental health problems. Conclusions: This study suggests a probable broad and long-term impact of deployment on the mental health of military service members. Due to the lack of a non-deployed control group, causal effects of deployment could not be demonstrated. Continued effort should nevertheless be made in the diagnosis and treatment of a wide range of mental health symptoms, even a decade after deployment. The findings also underscore the importance of social support after homecoming and its potential for the prevention of long-term mental health problems. [ABSTRACT FROM AUTHOR]

Background: The search for relevant biomarkers of major depressive disorder (MDD) is challenged by heterogeneity; biological alterations may vary in patients expressing different symptom profiles. Moreover, most research considers a limited number of biomarkers, which may not be adequate for tagging complex network-level mechanisms. Here we studied clusters of proteins and examined their relation with MDD and individual depressive symptoms. Methods: The sample consisted of 1621 subjects from the Netherlands Study of Depression and Anxiety (NESDA). MDD diagnoses were based on DSM-IV criteria and the Inventory of Depressive Symptomatology questionnaire measured endorsement of 30 symptoms. Serum protein levels were detected using a multi-analyte platform (171 analytes, immunoassay, Myriad RBM DiscoveryMAP 250+). Proteomic clusters were computed using weighted correlation network analysis (WGCNA). Results: Six proteomic clusters were identified, of which one was nominally significantly associated with current MDD (p = 9.62E-03, Bonferroni adj. p = 0.057). This cluster contained 21 analytes and was enriched with pathways involved in inflammation and metabolism [including C-reactive protein (CRP), leptin and insulin]. At the individual symptom level, this proteomic cluster was associated with ten symptoms, among which were five atypical, energy-related symptoms. After correcting for several health and lifestyle covariates, hypersomnia, increased appetite, panic and weight gain remained significantly associated with the cluster. Conclusions: Our findings support the idea that alterations in a network of proteins involved in inflammatory and metabolic processes are present in MDD, but these alterations map predominantly to clinical symptoms reflecting an imbalance between energy intake and expenditure. [ABSTRACT FROM AUTHOR]

Background: Perceived discrimination is associated with worse mental health. Few studies have assessed whether perceived discrimination (i) is associated with the risk of psychotic disorders and (ii) contributes to an increased risk among minority ethnic groups relative to the ethnic majority. Methods: We used data from the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions Work Package 2, a population-based case−control study of incident psychotic disorders in 17 catchment sites across six countries. We calculated odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between perceived discrimination and psychosis using mixed-effects logistic regression models. We used stratified and mediation analyses to explore differences for minority ethnic groups. Results: Reporting any perceived experience of major discrimination (e.g. unfair treatment by police, not getting hired) was higher in cases than controls (41.8% v. 34.2%). Pervasive experiences of discrimination (≥3 types) were also higher in cases than controls (11.3% v. 5.5%). In fully adjusted models, the odds of psychosis were 1.20 (95% CI 0.91–1.59) for any discrimination and 1.79 (95% CI 1.19–1.59) for pervasive discrimination compared with no discrimination. In stratified analyses, the magnitude of association for pervasive experiences of discrimination appeared stronger for minority ethnic groups (OR = 1.73, 95% CI 1.12–2.68) than the ethnic majority (OR = 1.42, 95% CI 0.65–3.10). In exploratory mediation analysis, pervasive discrimination minimally explained excess risk among minority ethnic groups (5.1%). Conclusions: Pervasive experiences of discrimination are associated with slightly increased odds of psychotic disorders and may minimally help explain excess risk for minority ethnic groups. [ABSTRACT FROM AUTHOR]

Background: The coronavirus disease 2019 (COVID-19) pandemic had brought negative consequences and new stressors to mothers. The current study aims to compare factors predicting maternal mental health during the COVID-19 lockdown in China, Italy, and the Netherlands. Methods: The sample consisted of 900 Dutch, 641 Italian, and 922 Chinese mothers (age M = 36.74, s.d. = 5.58) who completed an online questionnaire during the lockdown. Ten-fold cross-validation models were applied to explore the predictive performance of related factors for maternal mental health, and also to test similarities and differences between the countries. Results: COVID-19-related stress and family conflict are risk factors and resilience is a protective factor in association with maternal mental health in each country. Despite these shared factors, unique best models were identified for each of the three countries. In Italy, maternal age and poor physical health were related to more mental health symptoms, while in the Netherlands maternal high education and unemployment were associated with mental health symptoms. In China, having more than one child, being married, and grandparental support for mothers were important protective factors lowering the risk for mental health symptoms. Moreover, high SES (mother's high education, high family income) and poor physical health were found to relate to high levels of mental health symptoms among Chinese mothers. Conclusions: These findings are important for the identification of at-risk mothers and the development of mental health promotion programs during COVID-19 and future pandemics. [ABSTRACT FROM AUTHOR]

Background: Psychosis rates are higher among some migrant groups. We hypothesized that psychosis in migrants is associated with cumulative social disadvantage during different phases of migration. Methods: We used data from the EUropean Network of National Schizophrenia Networks studying Gene-Environment Interactions (EU-GEI) case–control study. We defined a set of three indicators of social disadvantage for each phase: pre-migration, migration and post-migration. We examined whether social disadvantage in the pre- and post-migration phases, migration adversities, and mismatch between achievements and expectations differed between first-generation migrants with first-episode psychosis and healthy first-generation migrants, and tested whether this accounted for differences in odds of psychosis in multivariable logistic regression models. Results: In total, 249 cases and 219 controls were assessed. Pre-migration (OR 1.61, 95% CI 1.06–2.44, p = 0.027) and post-migration social disadvantages (OR 1.89, 95% CI 1.02–3.51, p = 0.044), along with expectations/achievements mismatch (OR 1.14, 95% CI 1.03–1.26, p = 0.014) were all significantly associated with psychosis. Migration adversities (OR 1.18, 95% CI 0.672–2.06, p = 0.568) were not significantly related to the outcome. Finally, we found a dose–response effect between the number of adversities across all phases and odds of psychosis (⩾6: OR 14.09, 95% CI 2.06–96.47, p = 0.007). Conclusions: The cumulative effect of social disadvantages before, during and after migration was associated with increased odds of psychosis in migrants, independently of ethnicity or length of stay in the country of arrival. Public health initiatives that address the social disadvantages that many migrants face during the whole migration process and post-migration psychological support may reduce the excess of psychosis in migrants. [ABSTRACT FROM AUTHOR]

Background: Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results. Methods: Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes. Results: The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased. Conclusion: SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients. [ABSTRACT FROM AUTHOR]

Background: It has been claimed that functional somatic syndromes share a common etiology. This prospective population-based study assessed whether the same variables predict new onsets of irritable bowel syndrome (IBS), chronic fatigue syndrome (CFS) and fibromyalgia (FM). Methods: The study included 152 180 adults in the Dutch Lifelines study who reported the presence/absence of relevant syndromes at baseline and follow-up. They were screened at baseline for physical and psychological disorders, socio-demographic, psycho-social and behavioral variables. At follow-up (mean 2.4 years) new onsets of each syndrome were identified by self-report. We performed separate analyses for the three syndromes including participants free of the relevant syndrome or its key symptom at baseline. LASSO logistic regressions were applied to identify which of the 102 baseline variables predicted new onsets of each syndrome. Results: There were 1595 (1.2%), 296 (0.2%) and 692 (0.5%) new onsets of IBS, CFS, and FM, respectively. LASSO logistic regression selected 26, 7 and 19 predictors for IBS, CFS and FM, respectively. Four predictors were shared by all three syndromes, four predicted IBS and FM and two predicted IBS and CFS but 28 predictors were specific to a single syndrome. CFS was more distinct from IBS and FM, which predicted each other. Conclusions: Syndrome-specific predictors were more common than shared ones and these predictors might form a better starting point to unravel the heterogeneous etiologies of these syndromes than the current approach based on symptom patterns. The close relationship between IBS and FM is striking and requires further research. [ABSTRACT FROM AUTHOR]

Background: Both attention-deficit/hyperactivity disorder (ADHD) and insomnia have been independently related to poorer quality of life (QoL), productivity loss, and increased health care use, although most previous studies did not take the many possible comorbidities into account. Moreover, ADHD and insomnia often co-occur. Symptoms of ADHD and insomnia together may have even stronger negative effects than they do separately. We investigated the combined effects of symptoms of ADHD and insomnia, in addition to their independent effects, on QoL, productivity, and health care use, thereby controlling for a wide range of possible comorbidities and confounders. Methods: Data from the third wave of the Netherlands Mental Health Survey and Incidence Study-2 were used, involving N = 4618 from the general population. Both the inattention and the hyperactivity ADHD symptom dimensions were studied, assessed by the ASRS Screener. Results: Mental functioning and productivity were negatively associated with the co-occurrence of ADHD and insomnia symptoms, even after adjusting for comorbidity and confounders. The results show no indication of differences between inattention and hyperactivity. Poorer physical functioning and health care use were not directly influenced by the interaction between ADHD and insomnia. Conclusions: People with both ADHD and sleep problems have increased risk for poorer mental functioning and productivity loss. These results underscore the importance of screening for sleep problems when ADHD symptoms are present, and vice versa, and to target both disorders during treatment. [ABSTRACT FROM AUTHOR]