Since birth, human beings are immersed in a multifaceted sensory world that requires the need to extrapolate multiple levels of sensory regularities and to apply this knowledge to an internal representational model of their external environment (Aslin, 2017; Saffran & Kirkham, 2018). The human ability to use statistical learning to extract patterns of regularities in language is a classical example of this (Benitez & Saffran, 2018; Saffran, Aslin, & Newport, 1996). One of the most important sources of predictability human beings exploit from very early on is the ability to implicitly build up a subjective statistical report of the temporal structure of an event's sequence and, consequently, use this knowledge to instantiate temporal expectancy toward future events, either when anticipation actually implies action prepara

SummarySystematic reviews and meta‐analyses pool data from individual studies to generate a higher level of evidence to be evaluated by guidelines. These reviews ultimately guide clinicians and stakeholders in health‐related decisions. However, the informativeness and quality of evidence synthesis inherently depend on the quality of what has been pooled into meta‐research projects. Moreover, beyond the quality of included individual studies, only a methodologically correct process, in relation to systematic reviews and meta‐analyses themselves, can produce a reliable and valid evidence synthesis. Hence, quality of meta‐research projects also affects evidence synthesis reliability. In this overview, the authors provide a synthesis of advantages and disadvantages and main characteristics of some of the most frequently used tools to assess quality of individual studies, systematic reviews, and meta‐analyses. Specifically, the tools considered in this work are the Newcastle‐Ottawa scale (NOS) and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for observational studies, the Consolidated Standards of Reporting Trials (CONSORT), the Jadad scale, the Cochrane risk of bias tool 2 (RoB2) for randomized controlled trials, the Preferred Reporting Items for Systematic Reviews and Meta‐analysis (PRISMA) and the Assessment of Multiple Systematic Reviews 2 (AMSTAR2), and AMSTAR‐PLUS for meta‐analyses.What is already known?The informativeness and quality of evidence synthesis inherently depend on the quality of what has been pooled into meta‐research projects. Beyond the quality of included individual studies, only a methodologically correct process, in relation to systematic reviews and meta‐analyses themselves, can produce a reliable and valid evidence synthesis.What is new?In this overview, the authors provide a synthesis of advantages and disadvantages and main characteristics of some of the most frequently used tools to assess quality of individual studies, systematic reviews, and meta‐analyses.Potential impactThis overview serves as a starting point and a brief guide to identify and understand the main and most frequently used tools for assessing the quality of studies included in meta‐research. The authors here share their experience in publishing several meta‐research‐related articles covering different areas of medical sciences.

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.

The COVID-19 pandemic represents a major stressor for the psychological health of people worldwide. In the UK, the COVID19-Psychological Research Consortium Study (C19PRC) launched to evaluate the psychological impact of COVID-19 in the general population and its implications. The project was then extended to Italy and several other countries. This article provides an overview of the Italian C19PRC study and its replication of two specific findings from the UK C19PRC. In the first part, the relationship between anxiety and somatic symptomatology is examined. In the second part, we analyze the association between several factors and psychological health outcomes: depression/anxiety, traumatic stress, COVID-19 anxiety. In line with the study conducted in the UK, an online survey was administered to the adult Italian general population. The sample included 1038 respondents (age, mean = 49.94, SD = 16.14, 51.15% females) taken from four regions: Lombardia, Veneto, Lazio, and Campania. The relationship between predictors and outcomes was evaluated by means of logistic regression models. Somatic indices showed a positive association with anxiety, worse somatic symptoms were associated with mourning a loss of a beloved one due to COVID-19 and with precarious health conditions. Females showed a higher incidence of psychological issues. No differences in anxiety, depression, and traumatic stress were found across regions but the Campania region showed the most severe somatic symptomatology. In the second analysis, the factors associated with more severe psychological outcomes (i.e., anxiety and/or depression, traumatic stress, and COVID-19 related anxiety) were younger age, the presence of minors in the household, traumatic stressors, and precarious health conditions. No differences across regions emerged. The Italian results correspond to the UK findings for anxiety, depression, and traumatic stress. Both in the UK and Italy, the factors associated with worse psychological health were gender (female), younger age, having children, pre-existing health issues (both for oneself or someone close), and the moderate/high perceived risk of contracting COVID-19 within one month. In Italy, unlike the UK, lower household income and having (had) COVID-19 were not associated with poorer mental health. The psychological impact of COVID-19 can last for months; future research should explore all aspects of the psychological burden of COVID-19 in order to implement psychological interventions and promote psychological health.

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Background. Stigma is one of the most important barriers to help-seeking and to personal recovery for people suffering from mental disorders. Stigmatizing attitudes are present among mental health professionals with negative effects on the quality of health care. Methods. Network and moderator analysis were used to identify what path determines stigma, considering demographic and professional variables, personality traits, and burnout dimensions in a sample of mental health professionals (n = 318) from six Community Mental Health Services. The survey included the Attribution Questionnaire-9, the Maslach Burnout Inventory, and the Ten-Item Personality Inventory. Results. The personality trait of openness to new experiences resulted to determine lower levels of stigma. Burnout (personal accomplishment) interacted with emotional stability in predicting stigma, and specifically, for subjects with lower emotional stability lower levels of personal accomplishment were associated with higher levels of stigma. Conclusions. Some personality traits may be accompanied by better empathic and communication skills, and may have a protective role against stigma. Moreover, burnout can increase stigma, in particular in subjects with specific personality traits. Assessing personality and burnout levels could help in identifying mental health professionals at higher risk of developing stigma. Future studies should determine whether targeted interventions in mental health professionals at risk of developing stigma may be effective in stigma prevention.

The clinical assessment of mental disorders can be a time-consuming and error-prone procedure, consisting of a sequence of diagnostic hypothesis formulation and testing aimed at restricting the set of plausible diagnoses for the patient. In this article, we propose a novel computerized system for the adaptive testing of psychological disorders. The proposed system combines a mathematical representation of psychological disorders, known as the "formal psychological assessment," with an algorithm designed for the adaptive assessment of an individual's knowledge. The assessment algorithm is extended and adapted to the new application domain. Testing the system on a real sample of 4,324 healthy individuals, screened for obsessive-compulsive disorder, we demonstrate the system's ability to support clinical testing, both by identifying the correct critical areas for each individual and by reducing the number of posed questions with respect to a standard written questionnaire.