Suchergebnisse

Although there is a large body of theoretical and empirical research supporting a relationship between Zhongyong thinking and creativity, some studies have found that the association is positive, while others have reported that it is negative. Therefore, we performed a meta-analysis
of 18 relevant studies to further clarify this relationship. On the basis of 19 independent effect sizes, the results indicated there was a medium-strength, positive, and significant relationship between Zhongyong thinking and creativity. Moderator analyses suggested that this relationship
was stronger in studies in which creativity was self-evaluated than in the studies in which others evaluated the individual's creativity. The moderating effect of the tools used to measure Zhongyong thinking and publication status were not significant.

Investigating the spatial distribution patterns of disease and suspected determinants could help one to understand health risks. This study investigated the potential risk factors associated with COVID-19 mortality in the continental United States. We collected death cases of COVID-19 from 3108 counties from 23 January 2020 to 31 May 2020. Twelve variables, including demographic (the population density, percentage of 65 years and over, percentage of non-Hispanic White, percentage of Hispanic, percentage of non-Hispanic Black, and percentage of Asian individuals), air toxins (PM2.5), climate (precipitation, humidity, temperature), behavior and comorbidity (smoking rate, cardiovascular death rate) were gathered and considered as potential risk factors. Based on four geographical detectors (risk detector, factor detector, ecological detector, and interaction detector) provided by the novel Geographical Detector technique, we assessed the spatial risk patterns of COVID-19 mortality and identified the effects of these factors. This study found that population density and percentage of non-Hispanic Black individuals were the two most important factors responsible for the COVID-19 mortality rate. Additionally, the interactive effects between any pairs of factors were even more significant than their individual effects. Most existing research examined the roles of risk factors independently, as traditional models are usually unable to account for the interaction effects between different factors. Based on the Geographical Detector technique, this study's findings showed that causes of COVID-19 mortality were complex. The joint influence of two factors was more substantial than the effects of two separate factors. As the COVID-19 epidemic status is still severe, the results of this study are supposed to be beneficial for providing instructions and recommendations for the government on epidemic risk responses to COVID-19.