Objective: To conduct a systematic review and meta-analysis of the prevalence and variability in suicidality in the general adult population of Europe between 2008 and 2017. Methods: Studies containing original data on suicidality were identified in five electronic databases. Point, 12-month and lifetime prevalences were calculated for various types of suicidality. Pooled prevalence rates were calculated using a random effects model. Subgroup analysis and multivariate meta-regression were also performed. Results: We identified 24 papers containing original data, which provided 97 prevalence rates for suicidality. The pooled point prevalence rate was 3.96% (2.37–5.56), pooled 12-month prevalence 2.9% (1.49–4.32), and pooled lifetime prevalence 5.55% (4.31–6.79). The subgroup analysis showed that lifetime prevalence figures for wishing to be dead and suicidal ideation were higher in areas with a population of less than 3,849 inhabitants and in Eastern Europe. Finally, the multivariate meta-regression showed differences with respect to the period and type of suicidality, lower and upper age thresholds, population size, and study area. Conclusion: Our data showed that approximately 21% of European individuals have wished to be dead at some point during their lifetime. Studies like this are necessary to highlight the need for efforts to prevent and intervene in suicidality.

Close to one million people commit suicide each year, with suicidal attempts being the main risk factor for suicide. The aim of this systematic review and meta-analysis is to achieve a greater understanding of suicidality in the general population of Europe by studying associated factors and their statistical significance with suicidality, as well as the effect of the temporal moment in which suicidality is observed in a relationship. A search strategy was carried out in electronic databases: Proquest’s Psychology Database, Scopus, PsycINFO, Medline and Embase. Odds ratios (ORs), publication bias, influential studies on heterogeneity and analysis moderators were calculated. Twenty-six studies were included after meeting the inclusion criteria. Factors statistically associated with suicidality are female gender, age over 65 years, unemployment, low social support, adulthood adversity, childhood adversity, family history of mental disorder, any affective disorder, major depression, anxiety/stress/somatoform disorders, tobacco and substance use, any mental disorder and body mass index. As a limitation, a high heterogeneity between studies was found. Factors associated with suicidality in the general population are relevant for understanding the suicidal phenomenon.

Background: Evidence suggests that different variables associated with the COVID-19 pandemic may increase the risk of relapse in people with Severe Mental Disorders (SMDs). However, no studies have yet looked closely at the different risk factors involved to determine their influence on the worsening of these patients’ illnesses. Objective: To analyze which variables related to the COVID-19 pandemic have increased the risk of relapse in patients with SMDs. Method: A multicenter retrospective cohort study in which data were collected from 270 patients with mental disorders who had been under follow-up in day hospitals during the year 2020. Results: The proportion of full mental health inpatient admissions was significantly higher in those who lost their employment (40.7% vs. 18.1%; p = 0.01), in those who were not receiving psychotherapy interventions (33.9% vs. 16.6%; p = 0.006), and in those who were not receiving occupational therapy (25.7% vs. 13.6%: p = 0.013). Significant associations were detected between urgent mental health consultations, the number of COVID-19 symptoms (B = 0.274; p = 0.02), and the low-income group (1.2424 vs. 0.4583; p = 0.018). Conclusions: COVID-19 symptoms and certain consequences of the pandemic, such as loss of employment, economic hardship, and loss of interventions, have brought about clinical worsening in people with SMDs. Knowledge of these factors is important for health-related decision-making in future outbreaks or pandemics.