We aim to quantitatively synthesise available epidemiological evidence on the prevalence rates of workplace violence (WPV) by patients and visitors against healthcare workers. We systematically searched PubMed, Embase and Web of Science from their inception to October 2018, as well as the reference lists of all included studies. Two authors independently assessed studies for inclusion. Data were double-extracted and discrepancies were resolved by discussion. The overall percentage of healthcare worker encounters resulting in the experience of WPV was estimated using random-effects meta-analysis. The heterogeneity was assessed using the I2 statistic. Differences by study-level characteristics were estimated using subgroup analysis and meta-regression. We included 253 eligible studies (with a total of 331 544 participants). Of these participants, 61.9% (95% CI 56.1% to 67.6%) reported exposure to any form of WPV, 42.5% (95% CI 38.9% to 46.0%) reported exposure to non-physical violence, and 24.4% (95% CI 22.4% to 26.4%) reported experiencing physical violence in the past year. Verbal abuse (57.6%; 95% CI 51.8% to 63.4%) was the most common form of non-physical violence, followed by threats (33.2%; 95% CI 27.5% to 38.9%) and sexual harassment (12.4%; 95% CI 10.6% to 14.2%). The proportion of WPV exposure differed greatly across countries, study location, practice settings, work schedules and occupation. In this systematic review, the prevalence of WPV against healthcare workers is high, especially in Asian and North American countries, psychiatric and emergency department settings, and among nurses and physicians. There is a need for governments, policymakers and health institutions to take actions to address WPV towards healthcare professionals globally.

To understand Wuhan residents’ psychological reactions to the COVID-19 epidemic and offer a reference point for interventions, an online questionnaire survey was conducted. It included the Disorder 7-Item Scale (GAD-7), the Patient Health Questionnaire 9-Item Scale (PHQ-9), Athens Insomnia Scale, and Simplified Coping Style Questionnaire. Categorical data were reported as numbers and percentages. Multivariate logistic regression models were used to evaluate the association between demographic factors and anxiety, depression, sleep disorder, and passive coping style. A total of 1242 Wuhan residents investigated, 27.5% had anxiety, 29.3% had depression, 30.0% had a sleep disorder, and 29.8% had a passive response to COVID-19. Being female was the risk factor for anxiety (OR = 1.62) and sleep disorder (OR = 1.36); being married was associated with anxiety (OR = 1.75); having a monthly income between 1000 and 5000 CNY (OR = 1.44, OR = 1.83, OR = 2.61) or >5000 CNY (OR = 1.47, OR = 1.45, OR = 2.14) was a risk factor for anxiety, depression, and sleep disorder; not exercising (OR = 1.45, OR = 1.71, OR = 1. 85, OR = 1.71) was a common risk factor for anxiety, depression, sleep disorder, and passive coping style; and having a higher education level (bachelor’s degree and above) (OR = 1.40) was associated with having a sleep disorder. Wuhan residents’ psychological status and sleep quality were relatively poorer than they were before the COVID-19 epidemic; however, the rate of passive coping to stress was relatively higher.

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BackgroundSeveral systematic reviews and meta-analyses demonstrated the association between depression and the risk of coronary heart disease (CHD), but the previous reviews had some limitations. Moreover, a number of additional studies have been published since the publication of these reviews. We conducted an updated meta-analysis of prospective studies to assess the association between depression and the risk of CHD.MethodsRelevant prospective studies investigating the association between depression and CHD were retrieved from the PubMed, Embase, Web of Science search (up to April 2014) and from reviewing reference lists of obtained articles. Either a random-effects model or fixed-effects model was used to compute the pooled risk estimates when appropriate.ResultsThirty prospective cohort studies with 40 independent reports met the inclusion criteria. These groups included 893,850 participants (59,062 CHD cases) during a follow-up duration ranging from 2 to 37 years. The pooled relative risks (RRs) were 1.30 (95% CI, 1.22-1.40) for CHD and 1.30 (95% CI, 1.18-1.44) for myocardial infarction (MI). In the subgroup analysis by follow-up duration, the RR of CHD was 1.36 (95% CI, 1.24-1.49) for less than 15 years follow-up, and 1.09 (95% CI, 0.96-1.23) for equal to or more than 15 years follow-up. Potential publication bias may exist, but correction for this bias using trim-and-fill method did not alter the combined risk estimate substantially.ConclusionsThe results of our meta-analysis suggest that depression is independently associated with a significantly increased risk of CHD and MI, which may have implications for CHD etiological research and psychological medicine.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-014-0371-z) contains supplementary material, which is available to authorized users.

BackgroundObservational studies suggest that insomnia might be associated with an increased risk of depression with inconsistent results. This study aimed at conducting a meta-analysis of prospective cohort studies to evaluate the association between insomnia and the risk of depression.MethodsRelevant cohort studies were comprehensively searched from the PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases (up to October 2014) and from the reference lists of retrieved articles. A random-effects model was used to calculate the pooled risk estimates and 95 % confidence intervals (CIs). The I 2 statistic was used to assess the heterogeneity and potential sources of heterogeneity were assessed with meta-regression. The potential publication bias was explored by using funnel plots, Egger’s test, and Duval and Tweedie trim-and-fill methods.ResultsThirty-four cohort studies involving 172,077 participants were included in this meta-analysis with an average follow-up period of 60.4 months (ranging from 3.5 to 408). Statistical analysis suggested a positive relationship between insomnia and depression, the pooled RR was 2.27 (95 % CI: 1.89–2.71), and a high heterogeneity was observed (I 2 = 92.6 %, P < 0.001). Visual inspection of the funnel plot revealed some asymmetry. The Egger’s test identified evidence of substantial publication bias (P <0.05), but correction for this bias using trim-and-fill method did not alter the combined risk estimates.ConclusionsThis meta-analysis indicates that insomnia is significantly associated with an increased risk of depression, which has implications for the prevention of depression in non-depressed individuals with insomnia symptoms.