Background: Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. Methods: Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of “network analysis” with the terms “anxiety,” “affective disorders,” “depression,” “schizophrenia,” “psychosis,” “personality disorders,” “substance abuse” and “psychopathology.” Results: The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. Conclusions: A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

Given the need to understand both the negative and positive psychological consequences of the current global COVID-19 pandemic (Brewin et al.

In the midst of the COVID–19 epidemic, Spain was one of the countries with the highest number of infections and a high mortality rate. The threat of the virus and consequences of the pandemic have a discernible impact on the mental health of citizens. This study aims to (a) evaluate the levels of anxiety, depression and well-being in a large Spanish sample during the confinement, (b) identify potential predictor variables associated to experiencing both clinical levels of distress and well-being in a sample of 2,122 Spanish people. By using descriptive analyses and logistic regression results revealed high rates of depression, anxiety and well-being. Specifically, our findings revealed that high levels of anxiety about COVID–19, increased substance use and loneliness as the strongest predictors of distress, while gross annual incomes and loneliness were strongest predictors of well-being. Finding of the present study provide a better insight about psychological adjustment to a pandemic and allows us to identify which population groups are at risk of experiencing higher levels of distress and which factors contribute to greater well-being, which could help in the treatments and prevention in similar stressful and traumatic situations.

Background The Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder scale (GAD-7) are self-report measures of major depressive disorder and generalised anxiety disorder. The primary aim of this study was to test for differential item functioning (DIF) on the PHQ-9 and GAD-7 items based on age, sex (males and females), and country. Method Data from nationally representative surveys in UK, Ireland, Spain, and Italy (combined N = 6,054) were used to fit confirmatory factor analytic and multiple-indictor multiple-causes models. Results Spain and Italy had higher latent variable means than the UK and Ireland for both anxiety and depression, but there was no evidence for differential items functioning. Conclusions The PHQ-9 and GAD-7 scores were found to be unidimensional, reliable, and largely free of DIF in data from four large nationally representative samples of the general population in the UK, Ireland, Italy and Spain.

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