The effect of basic public health service equalization on settlement intention of migrant workers in China: the mediating effect model based on subjective feelings.

BACKGROUND: During the 14th Five-Year Plan, China aims to transform rural migrants into urban citizens and ensure equal access to public services to enhance new urbanization. Understanding migrant workers' settlement intentions is crucial for their citizenship development. Based on the fundamental role of the right to life and health, equalization of basic public health services is essential. Therefore, understanding the potential impact of public health services equalization on the settlement intention of migrant workers is crucial in China's new urbanization. METHOD: In this study, we utilized data from the 2017 wave of China Migrants Dynamic Survey (CMDS) and employed the Propensity Score Matching method to investigate the impact of basic public health service equalization policy on the settlement intention of migrant workers. Additionally, we utilized the Mediation Effect Model to uncover the impact mechanism. RESULTS: Our findings indicate that basic public health service equalization policy has a significant positive effect on increasing the settlement intention of migrant workers, with an even greater effect observed among the low-income group, the cross-provincial subsample, and the new generation subsample. The results of the Mediation Effect Model suggest that Basic public health service equalization policy can bolster the subjective integration willingness and subjective identity of migrant workers, thereby enhancing their settlement intention. CONCLUSION: Based on the results, we propose to strengthen the promotion of the basic public health service equalization policy and expand the coverage of health records to further increase the settlement intention of migrant workers.

Does the digital economy improve comprehensive total factor productivity in China?

Total factor productivity is an important symbol of high-quality economic development. At present, the question of whether the digital economy can infuse fresh impetus into enhancing total factor productivity has emerged as a prominent concern in China. This paper constructs a new undesirable output to measure comprehensive total factor productivity (CTFP) with the slack-based measure (SBM) undesirable Malmquist-Luenberger index by using 2011-2020 Chinese provincial panel data. Then, this paper explores the impact of the digital economy (DIG) on CTFP with a fixed effects (FE) panel model and a mediating effect model. The results show that CTFP increases by an average of 3.9%, technical efficiency contributes -1.1%, and the contribution rate of technological progress is 5.0%. Technological progress is the main source of CTFP growth. The empirical findings show that the DIG has a positive and significant impact on CTFP. This paper conducts various robustness tests, and the results remain consistent with the previous conclusion. Moreover, mechanism tests suggest that the promoting effect of the DIG on CTFP can be attributed to three main effects: technological innovation, the factor endowment structure and the educational level. Furthermore, the results of heterogeneity analysis demonstrate that the promoting effect of the DIG on CTFP exists in China's eastern, central and western regions. The findings of this research can serve as a valuable reference for informing decision-making processes related to environmental governance and high-quality economic development in China.

The impact of hydrogen fuel cell heavy-duty trucks purchase subsidies on air quality.

The pollutant emissions of diesel-powered heavy-duty trucks (HDTs) seriously damage the air quality. The promotion of hydrogen fuel cell HDTs through purchase subsidy policy to reduce emissions has become an important approach to control air pollution. This study focuses on the impact of hydrogen fuel cell HDT purchase subsidies on air quality in the context of China, covering the panel data of 31 Chinese cities from 2014 to 2021 and applying a two-way fixed effects model to analyze the contribution of purchase subsidies and hydrogen refueling station construction subsidies to air quality. Results show that (1) the increase in purchase subsidies could improve the air quality by around 6.1% and there is a lag effect. (2) Purchase subsidies make a larger contribution to air quality compared with construction subsidies. (3) Purchase subsidies can improve air quality by reducing carbon emissions in transport industry. In sight of these results, policy makers should emphasize the implementation of purchase subsidies and hydrogen refueling station construction subsidies and stimulate manufacturers to improve the performance of hydrogen fuel cell so as to contribute more to the environment.

Can green finance reduce carbon emission? A theoretical analysis and empirical evidence from China.

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction.

Digital product import and domestic value-added ratio of export: Theory and demonstration.

Based on the matching of the database of China Industry Business Performance and China Customs Trade from 2000 to 2013, this paper constructs the digital product import index, and adopts the method of panel data modeling to systematically investigate the impact and mechanism of digital product import on the domestic value-added rate of Chinese enterprises' export from the theoretical and empirical aspects. The research finds that the import of digital products significantly promotes the improvement of the domestic value-added rate of enterprises' export, and the core conclusion is still valid after considering the endogeneity of variables, changing the measurement index and estimation method. The mechanism test finds that the import of digital products improves the domestic value-added rate of enterprises' export through two channels: cost markup and relative price. In addition, the heterogeneity test finds that the import of digital products has a stronger effect on the improvement of the domestic value-added rate of enterprises' export in non-export enterprises, pure general trading enterprises, foreign-funded enterprises, labor-intensive enterprises and enterprises in the eastern region.

Carbon neutrality endeavors: the impact of carbon emission trading policies on total factor carbon emission efficiency.

Deepening the carbon market allocation reform is a strong support for carbon peaking and carbon neutrality. China has been piloting carbon trading in batches since 2013. However, there is little literature on whether and how carbon emission trading (CET) improves total factor carbon emission efficiency (TFCEE). To fill this gap, this study first calculates urban TFCEE using an extended Epsilon-based model and then designs a quasi-natural experiment based on causal inference. The staggered DID model is adopted to investigate the impact of CET pilot policies on urban TFCEE and its impact mechanism. Our results show that (1) the CET policy has a significant promoting effect on TFCEE in pilot cities, and this conclusion is reconfirmed by adopting robustness tests. (2) The mediating effect models are employed to confirm the mediating role of green technology innovation, industrial structure upgrading, and resource allocation efficiency in CET policy promoting regional TFCEE. (3) The heterogeneity test of CET policy depicts a considerable positive impact on TFCEE in cities with abundant resources. Eastern and developed cities are more likely to experience better carbon efficiency promotion through this policy than other cities. This study provides evidence for the important role of CET in promoting the development of a low-carbon economy and carbon neutrality.

Economic freedom and carbon emissions across the globe: the mediating effect of renewable energy consumption.

A growing number of studies have examined the extent to which economic liberalization policies would influence carbon emissions. These studies have examined this relationship while neglecting the key role that renewable energy could play in this complex relationship. The study fills that gap. It aims to examine the mediated effect of renewable energy consumption in the relationship between economic freedom and carbon emissions in 138 countries worldwide over the period 1995-2018. In this perspective, the study followed a second-generation panel econometric tests. We used Driscoll and Kraay standard errors (DKSE) and common correlated effect mean group (CCEMG) estimators for baseline results. The robustness of the results was checked using fully modified ordinary least squares (FMOLS), system generalized method of moments (System-GMM), and quantile regression (QREG). Furthermore, the study mobilized Dumitrescu and Hurlin's panel causality test to examine the causal relationship between the variables under study. The results suggest that economic freedom has a direct and indirect negative effect on carbon emissions and that renewable energy consumption mediates the effect of economic freedom on carbon emissions. These results remained unchanged at the battery of robustness checks. Moreover, Dumitrescu and Hurlin's panel causality test results indicated a bidirectional causal relationship between economic freedom, renewable energy consumption, economic growth, economic globalization, and population size with carbon emissions. The various empirical findings have helped to formulate useful policy implications for policy-makers to ensure environmental sustainability.

Variation of digital economy's effect on carbon emissions: improving energy efficiency and structure for energy conservation and emission reduction.

The significance of accurately assessing the influence of digital economy growth upon reducing emission of carbon in the context of worldwide climate governance cannot be overstated. This is crucial in encouraging low-carbon economic advancement at national level, achieving carbon peak and neutrality as soon as possible, and creating a shared future for humanity. A mediating effect model is established using cross-country panel data from 100 countries, ranging from 1990 to 2019, to assess the influence of digital economy development upon emission of carbon and to explore its underlying mechanism. The study found that: the growth of national emission of carbon can be considerably suppressed by digital economy development, and the reduction of emissions is positively associated to each country's level of economic advancement. Digital economy growth influences regional emission of carbon via intermediary channels like energy structure and efficiency, with energy intensity having a particularly noticeable intermediary impact. The inhibitory influence of digital economy development upon emission of carbon differs among countries with different levels of income, and improvements in energy structure and efficiency can precede to energy savings and emission reduction in both middle- and high-income countries. The above findings offer policy guidance for harmoniously advancing the growth of digital economy and climate management, hastening the low-carbon transformation of national economies, and implementing China's carbon peaking initiative.

Towards sustainability: the impact of industrial synergistic agglomeration on the efficiency of regional green development.

Guided by the concept related to sustainable development, we investigate the effects related to the synergistic agglomeration development of productive service and manufacturing industries on regional green development, which is also an important path for promoting the global sustainable development process and achieving carbon neutrality goals. Using the panel data of 285 prefecture-level cities in China from 2011 to 2020 as the basis of our study, we focus on the impact of industrial synergistic agglomeration on the efficiency of regional green development and the mediating influence of technological innovation. Results show that (1) industrial synergistic agglomeration positively contributes to the improvement of regional green development efficiency level and is significantly positive at the 5% level, (2) technological innovation plays a mediating role in the process of promoting regional green development efficiency through industrial synergistic agglomeration and can better realise the green development effect of industrial synergistic agglomeration, (3) results of the threshold effect test show the nonlinear effect of industrial synergistic agglomeration on regional green development efficiency with a single threshold value of 3.2397, and (4) the effect of industrial synergistic agglomeration on regional green development efficiency shows significant variability under different geographical locations, city scales, and resource endowment conditions. On the basis of these findings, we propose corresponding policy recommendations for improving the quality of inter-regional industrial synergistic agglomeration and formulating differentiated policy guidelines to help regions achieve long-term sustainable development.

The role of renewable energy investment and energy resource endowment in the evolution of carbon emission efficiency: spatial effect and the mediating effect.

With climate change caused by massive greenhouse gas emissions emerging as an issue of global concern, it is urgent to improve carbon emission efficiency (CEE) for countries along the Belt and Road (BRI). Considering the resource endowment characteristics of green development in BRI countries, the super-efficiency slacks-based measure (SBM) model is adopted to evaluate the current status and tendency of CEE in 60 BRI countries, while the Global Malmquist-Luenberger (GML) index to quantify the spatial and temporal variation and dynamic evolution of CEE. Subsequently, from the perspective of energy development and utilization, the spatial Durbin model (SDM) and the mediating effect model are employed to empirically examine the spillover effects and driving mechanisms of renewable energy investment and energy resource endowment on CEE. Empirical results reveal that (1) from a static perspective, the CEE of BRI countries is generally poor and unevenly distributed in terms of temporal and spatial dimensions, with significant room for enhancement. (2) Referring to the dynamic level, the GML index featured a U-shaped fluctuation, with technological progress contributing to the improvement of CEE. (3) There is a significant positive effect of renewable energy investment on CEE in the home country and neighboring countries, while energy resource endowment presents a remarkable adverse correlation. Consequently, it is suggested that inter-regional cooperation among BRI countries should be strengthened to reinforce renewable energy investment, exert the technology and knowledge spillover effect sufficiently, and break the resource curse in the environmental field. (4) The mediating effect model confirms the significant mediating mechanism of technological innovation. Renewable energy investment can enhance the CEE of BRI members by promoting the positive mediating effect of technological innovation, while energy resource endowment can inhibit the local level of technological innovation and indirectly inhibit the CEE of BRI members. The findings provide new ideas on the green development and ecological sustainability of the energy industry in BRI members and other economies.

Examination of the transmission mechanism of energy prices influencing carbon prices: an analysis of mediating effects based on demand heterogeneity.

Carbon prices are important for promoting a low-carbon transformation of the economy. The fluctuation of energy prices affects carbon prices through supply and demand chains, thus affecting the achievement of emission reduction targets through carbon pricing tools. Based on daily time series data, a mediating effect model is constructed to study the impact of energy prices on carbon prices. We analyze how energy prices impact carbon prices using four different transmission paths and then test the resulting differences. The main findings are as follows. First, an increase in energy prices significantly negatively affects carbon prices through economic fluctuation, investment demand, speculative demand, and transaction demand. Second, energy price fluctuations mainly affect carbon emission prices through economic fluctuations. The impacts of the remaining transmission paths are in the order of speculative demand, investment demand, and transaction demand. This paper provides theoretical and practical support for reasonably responding to energy price fluctuations and forming effective carbon prices to address climate change.

Air quality and health benefits of increasing carbon mitigation tech-innovation in China.

Most studies on the short-term local benefits of carbon mitigation technologies on air quality improvement and health focus on specific technologies such as biofuels or carbon sequestration technologies, while ignoring the overall role of the growing scale of low-carbon technologies. Based on STIRPAT model and EKC hypothesis, this paper takes 30 provinces in China from 2004 to 2016 as research samples. We builded the panel double fixed effect model to empirical analysis of climate change on carbon mitigation tech-innovation suppressing the influence of haze pollution, on this basis, the mediating effect model was used to explore the mediation function of industrial structure and energy structure. Meanwhile, we drawed on the existing studies on air quality and health benefits, and quantify the co-benefits of carbon mitigation tech-innovation on health through the equivalent substitution formula. It shows that a 1% increase in the number of low-carbon patent applications can reduce haze pollution by 0.066%. According to this estimate, to 2029, China's carbon mitigation tech-innovation could reduce PM2.5 concentration to 15 µg/m3 preventing 5.597 million premature deaths. Moreover, carbon mitigation tech-innovation can also indirectly inhibit haze pollution by triggering more systematic economic structure changes such as energy and industrial structure. Additionally, we found that the role of gray tech-innovation (GT) related to improving the efficiency of fossil energy is stronger than that of clean technology (CT) related to the use of renewable energy. This suggests that for a large economy such as China, where coal is still the dominant source of energy consumption, the short-term local benefits of improving air quality and health through the use of gray tech-innovation to improve energy and industrial structure are still important to balance the cost of carbon mitigation.

Impact of the Digital Economy on PM2.5: Experience from the Middle and Lower Reaches of the Yellow River Basin.

The development of the digital economy holds great significance for alleviating haze pollution. To estimate the impact of the digital economy on haze pollution, this paper explores the spatiotemporal evolutionary characteristics of the digital economy and PM2.5 concentration in the middle and lower reaches of the Yellow River Basin from 2011 to 2019 and conducts regression analysis by combining a fixed effect (FE) model and the spatial Durbin model (SDM). Moreover, this study divides the mitigation effect of haze pollution into a direct effect and a spatial spillover effect, and it further analyzes the mechanism from the perspectives of technological innovation and the industrial structure. The empirical results show that the development level of the digital economy increases year by year and that the concentration of PM2.5 decreases year by year. The digital economy level and PM2.5 concentration in the downstream region are higher than those in the middle region, and the digital economy is negatively correlated with haze pollution. Similarly, the spatial spillover effect of the digital economy is conducive to curbing haze pollution. The robustness test also supports this conclusion. In addition, there is regional heterogeneity in the impact of the digital economy on haze pollution. The direct effect and spatial spillover effect of the digital economy on haze pollution in the downstream region are greater than those in the middle region. This study suggests that to realize air pollution prevention and control, it is necessary to strengthen the construction of digital infrastructure and create a good digital economy development environment based on local conditions. Encouraging the development of digital technological innovation and promoting industrial digital transformation hold great significance for alleviating haze pollution.

Sports Participation and Anti-Epidemic: Empirical Evidence on the Influence of Regular Physical Activity on the COVID-19 Pandemic in Mainland China.

This study aims to investigate the effects and influencing mechanisms of regular physical activity (RPA) on the COVID-19 pandemic. Daily data from 279 prefecture-level cities in mainland China were collected from 1 January to 17 March 2020. A two-way fixed-effects model was used to identify the causal relationship between physical activity and COVID-19, while also considering factors such as patterns of human behavior and socioeconomic conditions. The instrumental variable (IV) approach was applied to address potential endogeneity issues for a more accurate causal identification, and the mediating effect model was applied to examine the mechanisms of the influence of physical activity on the epidemic. We found that regular physical activity significantly improves individual immunity, which, in turn, leads to a reduction in the probability of being infected with COVID-19. Furthermore, we investigated the heterogeneity of the influence, finding that the negative impact of physical activity on the pandemic is more pronounced in the absence of adequate medical resources, strong awareness of prevention among residents, and fully implemented public health measures. Our results provide empirical evidence for the mechanisms of influence of physical activity on the pandemic. We would suggest that not only should physical activity be actively practiced during the pandemic, but also long-term regular exercise habits should be consciously cultivated to improve the ability of the individual immune system to better cope with sudden outbreaks of emerging infectious diseases.

Does China's Eco-Province Policy Effectively Reduce the Pollutant Emission Intensities?

Economic development and environmental conservation are two important challenges for China. A series of initiatives including Eco-province (EP) policies have been taken to achieve sustainable development by the Chinese government. Increasing concerns regarding policy implications on sustainable development have increased attention to the topic. However, the research on the relationship between economic development and pollutant (COD, SO2) emission intensities after the implementation of EP policy remains inadequate. We applied a Time-Varying Difference-in-Differences Model by employing Chinese provincial panel data to quantitatively study the policy effect, and further utilized the Mediating Effect Model to analyze the mechanism. The article generates several findings: (1) The EP policy had overall inhibitory effects on both COD and SO2 emission intensities, and it would reduce the emission intensity by 4.99% and 6.77% on average, respectively. However, there was a five year lag in the policy effect. (2) The policy effect was significant in the western and central provinces with high pollutant emission intensities, but not in the eastern provinces. (3) The primary inhibiting mediating effects of Eco-province policy to lower pollutant emission intensity were increased GDP per capita and inventions.

The effect of China's carbon emission trading on eco-efficiency: an empirical study at the city level.

Carbon emission trading has been actively applied in many countries, and its operational effect has received widespread attention. However, previous studies mostly focused on single environmental effect, and the investigation of the comprehensive environmental effect needs to be further supplemented. Based on this, this paper explores the comprehensive environmental effect of carbon emission trading with eco-efficiency as the starting point. First, this paper measures eco-efficiency using the super-efficient minimum distance to strong efficient frontier (MinDS) model with undesirable outputs. Second, this paper uses the propensity score matching difference in difference (PSM-DID) model to quantify the effect of carbon emission trading on eco-efficiency. Finally, this paper examines the mediating mechanism of the effect of carbon emission trading on eco-efficiency based on the mediating effect model. The results show that carbon emission trading can improve the level of urban eco-efficiency. Energy savings and increased efficiency effectively mediate the promoting effect of carbon emission trading on eco-efficiency. The mediating push effect of R&D innovation and industrial structure restructuring has not yet appeared. This paper can not only provide policy basis for the improvement of carbon emission trading market but also provide reference for the construction of carbon emission trading market in developing countries.

Does industrial intelligence improve resource misallocation? An empirical test based on China.

Resource misallocation has become a new threat to China's high-quality economic development, and industrial intelligence may play an important role in optimizing resource allocation. Using panel data of 30 Chinese provinces from 2010 to 2020, the relationship between industrial intelligence and resource misallocation is studied using the spatial Durbin (SDM) model. To further explore the indirect effect of environmental pollution on resource misallocation, the interaction term between industrial intelligence and environmental pollution is added to test how environmental pollution affects the relationship between industrial intelligence and resource. The research results show that industrial intelligence in China has significant spatial correlation. Local industrial intelligence can improve the local resource allocation, but the intelligence of neighboring industries will intensify the resource misallocation in the region. The interaction between environmental pollution and industrial intelligence also further affects resource allocation, and the interaction term can intensify local capital allocation to improve local labor allocation, and the interaction term in the surrounding area will also improve capital and labor misallocation in the region. Heterogeneous results find that industrial intelligence exacerbates resource misallocation in regions with insufficient capital allocation, and the mediating effect of environmental pollution is not significant. However, in places with excess capital allocation, the development of industrial intelligence helps improve resource misallocation, while the mediating effect of environmental pollution is also present, and industrial intelligence can improve resource misallocation through the indirect effect of improving environmental pollution. Therefore, the policies of local industrial development policies need to fully consider the resource allocation situation in the region. At the same time, it needs to smooth the capital circulation mechanism, reduce the cost of capital allocation, establish a sound employment mechanism, and improve labor misallocation.

How does green credit affect carbon emissions in China? A theoretical analysis framework and empirical study.

As an important part of China's green finance, green credit is regarded as an important tool to promote China's transformation to a low-carbon economy. In order to clarify the mechanism of green credit on carbon emissions, this paper puts forward a theoretical analysis framework including "functional attributes - micro subject response - key influencing factors" from the macro and micro perspectives. We select the panel data of 30 provinces in China from 2005 to 2019 for an empirical test and identify the action paths of green credit on carbon emission based on the mediating effect model. Further, we consider the special mechanism of "signal formation" and test it based on the dynamic panel threshold model. The results show that: (1) China's green credit mainly inhibits carbon emissions through three paths: industrial structure, energy structure and energy intensity. (2) There is a signal formation mechanism for the impact of green credit on carbon emissions, which mainly acts on the two action paths of industrial structure and energy intensity. (3) The signal formation mechanism is heterogeneous in each province. According to the empirical results, we divide the provinces into three echelons and propose corresponding suggestions.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China.

Existing studies reported higher altitudes reduce the COVID-19 infection rate in the United States, Colombia, and Peru. However, the underlying reasons for this phenomenon remain unclear. In this study, regression analysis and mediating effect model were used in a combination to explore the altitudes relation with the pattern of transmission under their correlation factors. The preliminary linear regression analysis indicated a negative correlation between altitudes and COVID-19 infection in China. In contrast to environmental factors from low-altitude regions (<1500 m), high-altitude regions (>1500 m) exhibited lower PM2.5, average temperature (AT), and mobility, accompanied by high SO2 and absolute humidity (AH). Non-linear regression analysis further revealed that COVID-19 confirmed cases had a positive correlation with mobility, AH, and AT, whereas negatively correlated with SO2, CO, and DTR. Subsequent mediating effect model with altitude-correlated factors, such as mobility, AT, AH, DTR and SO2, suffice to discriminate the COVID-19 infection rate between low- and high-altitude regions. The mentioned evidence advance our understanding of the altitude-mediated COVID-19 transmission mechanism.

[The effect of occupational stress on anxiety of nursing staff in a third-grade general hospital and mediating effect of job burnout].

Objective: To explore the mediating effect of job burnout of nursing staff in clinical departments on occupational stress and anxiety, and to provide scientific basis for the formulation of intervention measures to relieve anxiety. Methods: From November 2020 to January 2021, a cross-sectional survey was conducted to investigate the basic situation, occupational stress, job burnout and anxiety of 653 nursing staff in a third class A general hospital in Hebei Province. Spearman rank correlation was used to analyze the relationship between occupational stress, job burnout and anxiety, stepwise regression and mediating effect model were used to verify the mediating effect of job burnout on the relationship between occupational stress and anxiety. Results: 551 valid questionnaires were collected with effective recovery of 84.38%. The incidence of high occupational stress was 68.06% (375/551) , the incidence of job burnout was 63.70% (351/551) [high, moderate and moderate were 11.07% (61/551) and 52.63% (290/551) respectively], and the incidence of anxiety was 55.72% (307/551) [mild, moderate and severe were 38.11% (210/551) , 8.53% (47/551) and 9.08% (50/551) respectively]. Occupational stress was positively correlated with job burnout and anxiety (r=0.545, 0.479) , and job burnout was positively correlated with anxiety (r=0.542, P<0.05) . The mediating effect analysis showed that occupational stress had a statistically significant effect on anxiety (c=0.509, P<0.001) , and the mediating effect of job burnout on the relationship between occupational stress and anxiety accounted for 44.99% of the total effect. Conclusion: The anxiety level of the nursing staff in this third-class A general hospital was relatively high. Job burnout has a mediating effect between occupational stress and anxiety, and anxiety of nursing staff can be alleviated by reducing occupational stress or job burnout.