Suchergebnisse

Risk information avoidance (RIA) has become an increasingly ubiquitous behavior for people to deal with massive volumes of information. Given its detrimental impact, abundant studies were conducted to explore its antecedents. Nevertheless, the results are scattered and, in some cases, inconsistent. We thereby conducted a meta-analysis to present a synthesis of the current findings by identifying the most relevant antecedents and moderators. Guided by the framework of Planned Risk Information Avoidance, we examined 11 antecedents along cognitive, emotional, and sociocultural dimensions. Based on 52 articles across various contexts, the results indicated that information overload ( r = .30), efficacy belief ( r = −.11), fatalism ( r = .18), information insufficiency ( r = −.09), anxiety ( r = .26), worry ( r = −.08) and information avoiding norms ( r = .50) were significant predictors of RIA. Furthermore, uncertainty avoidance and information type were identified as moderators.

This meta-analysis synthesized 43 empirical articles to summarize the impact of communicating three distinct uncertainty types (i.e., epistemic uncertainty, consensus uncertainty, and technical uncertainty) in science communication. The results revealed divergent effects across these three uncertainty types. Specifically, communicating epistemic uncertainty was found to have a small yet positive effect on credibility perception ( d = 0.09), with a nonsignificant impact on attitudes. Conversely, communicating consensus uncertainty ( d = −0.12) and technical uncertainty ( d = −0.15) demonstrated a slight negative effect on attitudes, without impacting credibility perception. In addition, topic domain, cultural uncertainty avoidance, and text length were important moderators.

With increasingly severe constraints on resources and the environment, it is the mainstream trend of economic development to reduce industrial pollution emissions and promote green industrial development. In this paper, a super-efficiency slacks-based measure (SBM) model is adopted to measure the industrial green development efficiency (IGDE) of 289 cities in China from 2008 to 2018. Moreover, we analyze their spatiotemporal differentiation pattern. On this basis, the multiscale geographical weighted regression (MGWR) model is used to analyze the scale differences and spatial differences of the driving factors. The results show that the IGDE is still at a low level in China. From 2008 to 2018, the overall polarization of IGDE was relatively serious. The number of high- and low-efficiency cities increased, while that of medium-efficiency cities greatly decreased. Secondly, the IGDE presented an obvious spatial positive correlation. MGWR regression results show that the technological innovation, government regulation, and consumption level belonged to the global scale, and there was almost no spatial heterogeneity. Other driving factors were urbanization, industrial structure, economic development, and population density according to their spatial scale. Lastly, the influence of economic development and technological innovation had a certain circular structure in space; the influence of population size mainly occurred in the cities of the southeast coast and northeast provinces; the influence of urbanization was more obvious in the most northern provinces of the Yangtze River, while that of industrial structure was mainly concentrated in the most southern cities of the Yangtze River Economic Belt (YREB). Spatially, the influence of consumption was manifested as a distribution trend of decreasing from north to south, and the government regulation was manifested as increasing from west to east and then to northeast.

ObjectivesWe investigate the impact of wildfire disasters on cognitive health (i.e., thinking and language skills) in individuals aged 10 years and older using 2014 and 2018 wildfire and cognitive ability survey data from China.MethodsWe distinguished wildfires in each county at different wind directions each day by exogenous wind direction changes, and analyzed the effects of wildfires on cognitive abilities through upwind and non-upwind wildfires.ResultsOur analysis shows that for every 10-unit increase in upwind wildfires compared to non-upwind wildfires, respondents' scores on word and math tests decrease by 0.235 and 0.236 standard deviations, respectively. Furthermore, we find that the impact of wildfire on cognitive ability is more pronounced in younger individuals, and those with lower defensive expenditures experience more severe impacts. Additionally, wildfires negatively affect individuals' cognitive abilities by generating air pollution.ConclusionWildfires significantly reduce individuals' cognitive abilities. Two recommendations are as follows: 1) governments should follow the principle of green development, introduce relevant regulations, and increase investment in adaptive technologies. 2) Individuals should raise awareness of climate hazards preparedness and strengthen defensive protection.