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Objectives: The Mental Health Inventory (MHI‐5) is frequently used as a screener for mood and anxiety disorders. However, few population‐based studies have validated it against a diagnostic instrument assessing disorders following current diagnostic criteria. Methods: Within the third Netherlands Mental Health Survey and Incidence Study (NEMESIS‐3), a representative population‐based study of adults (N = 6194; age: 18–75 years), the MHI‐5 was used to measure general mental ill‐health in the past month. Presence of mood (major depressive disorder, persistent depressive disorder, or bipolar disorder) and anxiety disorders (panic disorder, agoraphobia, social phobia, or generalized anxiety disorder) in the past month was assessed with a slightly modified version of the Composite International Diagnostic Interview 3.0 per the Diagnostic and Statistical Manual of Mental disorders‐5. Results: The MHI‐5 was good to excellent at distinguishing people with and without a mood disorder, an anxiety disorder, and any mood or anxiety disorder. The cut‐off value associated with the highest sensitivity and highest specificity for mood disorder was ≤68, and ≤76 for an anxiety disorder or any mood or anxiety disorder. Conclusions: The MHI‐5 can identify individuals at high risk of a current mood or anxiety disorder in the general population when diagnostic interviews are too time consuming. [ABSTRACT FROM AUTHOR]

Background: Empirical evidence suggests that people use cannabis to ameliorate anxiety and depressive symptoms, yet cannabis also acutely worsens psychosis and affective symptoms. However, the temporal relationship between cannabis use, anxiety and depressive symptoms and psychotic experiences (PE) in longitudinal studies is unclear. This may be informed by examination of mutually mediating roles of cannabis, anxiety and depressive symptoms in the emergence of PE. Methods: Data were derived from the second longitudinal Netherlands Mental Health Survey and Incidence Study. Mediation analysis was performed to examine the relationship between cannabis use, anxiety/depressive symptoms and PE, using KHB logit in STATA while adjusting for age, sex and education status. Results: Cannabis use was found to mediate the relationship between preceding anxiety, depressive symptoms and later PE incidence, but the indirect contribution of cannabis use was small (for anxiety: % of total effect attributable to cannabis use = 1.00%; for depression: % of total effect attributable to cannabis use = 1.4%). Interestingly, anxiety and depressive symptoms were found to mediate the relationship between preceding cannabis use and later PE incidence to a greater degree (% of total effect attributable to anxiety = 17%; % of total effect attributable to depression = 37%). Conclusion: This first longitudinal cohort study examining the mediational relationship between cannabis use, anxiety/depressive symptoms and PE, shows that there is a bidirectional relationship between cannabis use, anxiety/depressive symptoms and PE. However, the contribution of anxiety/depressive symptoms as a mediator was greater than that of cannabis. [ABSTRACT FROM AUTHOR]

Previous studies from a wide variety of European countries have demonstrated that low educated adolescents engage more frequently in health risk behaviors compared to high educated adolescents. The present study investigates the mediating roles of parental knowledge and time spent with peers in this relationship. Data were retrieved from a nationally representative sample of 12- to 16-year old Dutch adolescents (N = 5422). Risk behaviors were measured by adolescents' report of daily smoking, binge drinking and cannabis use in the previous month, and sexual debut before age 17. Low educated adolescents indicated that their parents had less knowledge on their whereabouts and reported spending more time with peers than high educated adolescents. Both factors mediated the relationship with health risk behaviors. These results hint to parenting practices and adolescent peer relations as points of reference for prevention and intervention work aiming to reduce educational inequalities in adolescent health risk behaviors. (Contains 2 tables and 1 figure.)

Heavy episodic drinking is more common among adolescents with a lower educational level. Aim: This study probed into the mechanism through which a lower educational level is linked to heavier adolescent drinking. Methods: Structural equation modelling was conducted using data from the 2005 Health Behaviour in School-aged Children Survey (n = 5169). Findings: Mediation analyses revealed that higher frequencies of heavy episodic drinking among adolescents with a lower educational level could be partially explained by spending more time with friends, a higher number of drinking peers, less monitoring by parents and less restrictive parental rules. Conclusions: Parenting as well as peer influence could explain part of the educational differences in heavy episodic drinking. More research is required to reveal additional factors that might explain heavier drinking patterns among adolescents with lower educational levels. (Contains 1 table and 1 figure.)

Background: A transdiagnostic and contextual framework of 'clinical characterization', combining clinical, psychopathological, sociodemographic, etiological, and other personal contextual data, may add clinical value over and above categorical algorithm-based diagnosis. Methods: Prediction of need for care and health care outcomes was examined prospectively as a function of the contextual clinical characterization diagnostic framework in a prospective general population cohort (n = 6646 at baseline), interviewed four times between 2007 and 2018 (NEMESIS-2). Measures of need, service use, and use of medication were predicted as a function of any of 13 DSM-IV diagnoses, both separately and in combination with clinical characterization across multiple domains: social circumstances/demographics, symptom dimensions, physical health, clinical/etiological factors, staging, and polygenic risk scores (PRS). Effect sizes were expressed as population attributable fractions. Results: Any prediction of DSM-diagnosis in relation to need and outcome in separate models was entirely reducible to components of contextual clinical characterization in joint models, particularly the component of transdiagnostic symptom dimensions (a simple score of the number of anxiety, depression, mania, and psychosis symptoms) and staging (subthreshold, incidence, persistence), and to a lesser degree clinical factors (early adversity, family history, suicidality, slowness at interview, neuroticism, and extraversion), and sociodemographic factors. Clinical characterization components in combination predicted more than any component in isolation. PRS did not meaningfully contribute to any clinical characterization model. Conclusion: A transdiagnostic framework of contextual clinical characterization is of more value to patients than a categorical system of algorithmic ordering of psychopathology. [ABSTRACT FROM AUTHOR]

Objectives: NEMESIS‐3 (Netherlands Mental Health Survey and Incidence Study‐3) is a psychiatric epidemiological cohort study of the Dutch general population that replicates and expands on two previous NEMESIS‐studies conducted in 1996–1999 and 2007–2018 respectively. The main aims of NEMESIS‐3 are to provide up‐to‐date information on the prevalence, incidence, course and consequences of mental disorders, their risk indicators, and to study the relevant time trends. This paper gives an overview of the objectives and methods of NEMESIS‐3, especially of the recently completed first wave, and describes the sample characteristics. Methods: NEMESIS‐3 is based on a multistage, stratified random sampling of individuals aged 18–75 years. Face‐to‐face interviews were laptop computer‐assisted and held at the respondent's home. A slightly modified Composite International Diagnostic Interview (CIDI) version 3.0 was used to assess both Diagnostic and Statistical Manual of Mental Disorders‐IV (DSM‐IV) and DSM‐5 mental disorders. Two follow‐up waves are planned three and six years after baseline. Results: In the first wave, performed from November 2019 to March 2022, 6194 individuals were interviewed: 1576 respondents before and 4618 respondents during the COVID‐19 pandemic. The average interview duration was 91 min and the response rate was 54.6%. The sample consisted of 50.4% women and had a mean age of 47.9 years. The sample was reasonable nationally representative, although some sociodemographic groups were somewhat underrepresented. Conclusions: Despite the COVID‐19 restrictions, we were able to build a large and comprehensive dataset of good quality, permitting us to investigate the latest trends in mental health status, various new topics related to mental health, and the extent to which the pandemic has had an effect on the population's mental health. [ABSTRACT FROM AUTHOR]