Influencing Factors In China Research Articles

Analysis of Industrial Water Use Efficiency Based on SFA–Tobit Panel Model in China

Over the past two decades, the industrial sector of China has experienced rapid development, which has correspondingly led to a significant increase in water resource consumption. To better understand the dynamics of industrial water use, and formulate appropriate water resource conservation and management policies, it is necessary to evaluate the evolution of industrial water use efficiency and its influencing factors in China. Given the high sensitivity and accuracy of the stochastic frontier analysis (SFA) model for efficiency assessment, the Tobit model is more suitable for regression analyses of truncated data. This study employed the SFA–Tobit panel model to evaluate the industrial water use efficiency of provinces in China from 2003 to 2021. The results indicate that national industrial water use efficiency improved from 0.41 to 0.65 during the study period. All provinces showed significant improvements, with developed provinces exhibiting higher industrial water use efficiency than undeveloped provinces. Regionally, the eastern areas demonstrated superior industrial water use efficiency compared to the western regions, with the central regions having the lowest overall water use efficiency. Moreover, the efficiency gap between regions has been narrowing. The national industrial water-saving potential is estimated at 31.306 billion cubic meters, with Jiangsu province having the highest saving potential at 3.709 billion cubic meters. In comparison, Beijing has the lowest at just 32,000 cubic meters. The Tobit regression results reveal that economic development and technological progress positively contribute to increased industrial water use efficiency. In contrast, water use intensity, openness, and urbanization levels negatively impacted the improvement of industrial water use efficiency. Therefore, it is necessary to increase investment in technological innovation, strictly control industrial water intensity, appropriately balance import and export trade with urbanization levels, and promote sustainable economic development. This study can provide effective support for the subsequent green transformation of China’s industry.

Incorporating embodied carbon transfer and sequestration service flows into regional carbon neutrality assessment in China

Reliable and effective carbon neutrality assessments are crucial prerequisites for implementing various low-carbon policies and achieving carbon neutrality goals. Although the impact of embodied carbon transfer and carbon sequestration service flows on regional carbon neutrality is becoming increasingly significant, these factors are not effectively incorporated into current carbon neutrality assessments. Based on a thorough review of the literature and theoretical analysis, this study attempts to construct a regional carbon neutrality assessment framework that incorporates embodied carbon transfer and carbon sequestration service flows. This framework is then applied to assess carbon neutrality and its influencing factors in China's provinces. Our findings reveal that carbon emissions and sequestration capacities have increased across Chinese provinces, with the highest emissions in North and East China, and the highest sequestration in Southwest China. Economically developed provinces like Beijing, Zhejiang, and Jiangsu transfer substantial embodied carbon to provinces such as Inner Mongolia, Shanxi, and Hebei, while Guangxi, Sichuan, Yunnan, and Qinghai are major providers of carbon sequestration services. Carbon neutrality levels in Chinese provinces show a ring-shaped distribution, increasing from the inner to outer rings. Higher levels are found in Southwest and Northwest provinces (e.g., Yunnan, Qinghai, Guangxi), and lower levels in North and East provinces (e.g., Shanxi, Beijing, Zhejiang). Factors like urbanization rate, population density, per capita GDP, and energy consumption structure negatively impact carbon neutrality levels, whereas ecological land area and annual precipitation have positive impacts. In summary, incorporating embodied carbon transfer and carbon sequestration service flows into the regional carbon neutrality assessment framework facilitates a more comprehensive analysis of regional carbon neutrality levels and their influencing factors. This approach broadens the theoretical and methodological scope of regional carbon neutrality assessments and provides scientific references for the implementation of low-carbon policies and the advancement of carbon neutrality goals.

Prevalence of and factors associated with cognitive frailty in elderly patients with chronic obstructive pulmonary disease: A cross-sectional study.

The status of cognitive frailty in elderly patients with chronic obstructive pulmonary disease (COPD) and its influencing factors in China remains unclear. This study aimed to investigate the prevalence of and factors associated with cognitive frailty in elderly patients with COPD. This cross-sectional study enrolled elderly patients with stable COPD between May and November 2022 from the Respiratory Department of the First Affiliated Hospital of Zhengzhou University and the Fifth Affiliated Hospital of Zhengzhou University. Convenience sampling method was adopted. Frailty Phenotype scale, Montreal Cognitive Assessment scale, Geriatric Depression Scale, and Clinical Dementia Rating scale were used to assess the prevalence of cognitive frailty in elderly patients with COPD. Multivariable logistic regression analysis was used to explore the associated factors. A total of 406 valid questionnaires were collected, and 173 patients (35.6%) had cognitive frailty. Binary logistic regression analysis showed that sex (odds ratio [OR] = 0.009; 95%CI: 0.001-0.770; P = .038), depression (OR = 17.780; 95%CI: 1.092-289.478; P = .043), modified Medical Research Council grade 1-3 (OR = 28.394-4095.683; 95%CI: 1.086-4,592,652.211; P < .05), global initiative for chronic obstructive lung disease grade 2 and 3 (OR = 32.508-282.072; 95%CI: 1.101-12,516.874; P < .05), and frequencies of acute exacerbations of COPD and hospitalizations within 1 year of 2 times (OR = 21.907; 95%CI: 4.587-104.622; P < .001) were independently associated with cognitive frailty. The prevalence of cognitive frailty in elderly patients with stable COPD was high. Female, depression, modified Medical Research Council grade, global initiative for chronic obstructive lung disease grade, and frequencies of acute exacerbations of COPD and hospitalizations within 1 year might be the factors independently associated with cognitive frailty, educational level might be a protective associated factor for cognitive frailty.

Resilient city construction efficiency and its influencing factors in China's Chengdu-Chongqing Economic Circle: Considering both construction input and resilience level of the city

The growing expansion of urban centers combined with a deteriorating climatic environment raises the likelihood and severity of urban disasters. Thus, there is an urgent need to accelerate the resilient city construction. Here, we use efficiency theory to structure an assessment indicator system of the resilient city construction efficiency to examine the actual correlation of urban resilience enhancement and urban resource consumption. Specifically, 16 key cities in the Chengdu-Chongqing Economic Circle (CCEC) are investigated using the super-efficient SBM and GTWR models. The findings reveal that the resilient city construction efficiency varies greatly among cities in the region, but most cities have relatively low resilient city construction efficiency, showing high resource consumption and low resilience levels. Also, the lower efficiency of regional resilient city construction is mainly due to the serious ineffectiveness of technical and resource inputs, insufficient outputs of ecological resilience and engineering resilience, and is also greatly influenced by factors such as the economic level and the technological innovation level. Upon this basis, we suggest the development strategies for resilient city construction in CCEC. This study broadens the perspective and scope of urban resilience research, and also provides a realistic reference for accelerating the construction of resilient cities.

Applying the LightGBM model and SHAP interpretation to understand the urban land price index and its influencing factors in China

ABSTRACT Investigating the key factors affecting land prices is conducive to establishing targeted market-oriented reforms of the land market and promoting its healthy development. Traditional linear analysis cannot comprehensively compare the importance of feature variables and is unable to analyse the nonlinear influence process of feature variables. Therefore, based on the land transaction dataset from 2011 to 2020 in China, we used machine learning and the Shapley Additive exPlanations method to analyse the importance ranking of factors affecting land prices and analyse the nonlinear influence processes. The government fiscal, industrial development, and financial system indices are determined as the most important factors affecting residential, commercial, and industrial land price indices, respectively, and each exhibits different characteristics. The financial system index exerts the strongest impact on land price indices in large cities, whereas transportation and communication indices are the most dominant in small cities. Moreover, industrial development index is the most important influencing factor in industrial cities, whereas regional economic index exerts the greatest impact in small cities. By employing machine learning methods, we determined nonlinear effects that traditional linear models fail to obtain. Based on the results, we propose policy recommendations for market-oriented reforms on the land market, real-estate policies, and a stable monetary system.

Prediction of Carbon Emissions Level in China’s Logistics Industry Based on the PSO-SVR Model

Adjusting the energy structure of various industries is crucial for achieving China’s carbon peak and carbon neutrality goals. Given the significant proportion of carbon emissions from the logistics industry in the tertiary sector, the research on predicting the carbon emissions of the logistics industry is of great significance for China to achieve its “Dual carbon” target. In this paper, the gray relational analysis (GRA) methodology is adopted to screen the influencing factors of carbon emissions in the logistics industry firstly. Then, the particle swarm optimization (PSO) algorithm was used to optimize the penalty coefficientand kernel function range parameter of the support vector regression (SVR) model (i.e. PSO- SVR model). The data from 2000 to 2021 regarding carbon emissions and related influencing factors in China’s logistics industry are analyzed, and the mean absolute percentage error (MAPE) of the PSO-SVR model is 0.82%, which shows that the proposed PSO-SVR model in this paper is effective. Finally, instructive suggestions are provided for China to achieve the “Dual Carbon” goal and upgrading of the logistics industry.

Health utility of patients with established rheumatoid arthritis and its influencing factors: a multi-center study in China

To assess the health utility value (HUV) of Rheumatoid Arthritis (RA) patients and its influencing factors in China. A cross-sectional survey was conducted in 8 tertiary hospitals across four capital-cities. The demographic characteristics, patient-reported outcomes including the HUV got by EQ-5D-5L, clinical characteristics, and clinician-reported outcomes of 171 RA patients were collected both from themselves and their physicians. Both the univariate and multivariate analyses were used to assess the potential factors of EQ-5D-5L HUV of the patients. The mean age of the patients was 50.7 years, with female being 64.9% (n = 111). The mean HUV and EQ visual analogue scale score of all patients were 0.586 and 47.3, respectively. The univariate analysis showed that the patients who were female, older, living in rural areas, with lower education level, advanced disease stage, higher the patient's assessment of arthritis pain visual analogue scale (PtAAP-VAS), the patient's global assessment of disease activity visual analogue scale (PtGADA-VAS), and the Physician’s global assessment of disease activity visual analogue scale (PhGADA-VAS) scores had significantly lower EQ-5D-5L HUVs. The multivariate analysis further suggested that older age, female, higher body mass index and higher PtGADA-VAS score were statistically significantly related to lower HUVs. The study provided the HUVs for RA patients with different characteristics and outcomes, which could be used in the economic evaluation of interventions for the RA patients. The identified factors could also assist the health care managing and improving the health-related quality of life on RA patients.

Study on healthcare level and its relationship with medical radiation in China

ObjectiveTo evaluate the health-care level (HCL), one of the most extensively used indicators to assess the level of medical exposure, and its influencing factors in China. MethodsBased on the data from the China Statistical Yearbook of the National Bureau of Statistics and other public documents, HCL was calculated in terms of the number of physicians per head of population throughout the country. Multiple linear regression was used to analyze the association of HCL with main socioeconomic factors, including population size, area, number of administrative divisions and gross domestic product (GDP). ResultsSince 2015, there has been at least one physician for every 1,000 people in China on average. However, by 2019, there has yet been one physician for more than 1,000 people in each of two provinces. By 2020, there was at least one physician for every 1,000 people across all 31 provincial-level administrative districts (provinces). The population size and GDP were the influencing factors on HCL, with correlation coefficients of 0.416 and −0.583, respectively. Furthermore, a moderate correlation was found between HCL and the frequency of medical exposure (FME) to ionizing radiation (r ​= ​−0.620, P ​= ​0.028). ConclusionThere has been at least one physician for every 1,000 people since 2015, but there are great differences between various provinces. HCL as an indicator to evaluate level of medical exposure is warranted further research in China.

Analysis of loss to follow-up status and influencing factors of children born to pregnant women with HIV infection in China in 2019

Objective: To understand the loss to follow-up of children born to pregnant women with HIV infection (HIV-exposed children) and analyze its influencing factors in China in 2019. Methods: The data were collected from the follow-up records of pregnant women with HIV infection and their children reported by the national "Management Information System for the Prevention of HIV, syphilis and Hepatitis B Mother-to-Child Transmission" in 2019. HIV-exposed children were defined as those who were not followed up after birth or who were not followed up at 18 months of age and who were not followed up at 21 months of age. The univariate and multivariate influencing factors of loss to follow-up of children born to HIV-infected pregnant women were analyzed by χ2 test and logistic regression model. SPSS 25.0 software was used for statistical analysis. Results: The number of HIV-infected pregnant women was 5 039, the number of live-born children was 5 035, the number of loss to follow-up children within 18 months of age was 283, and the loss to follow-up rate children was 5.62%(283/5 035). The results of multivariate logistic regression analysis showed that the rate of loss to follow-up of exposed children born to pregnant women who worked as farmers (animal husbandry and fishery) (aOR=0.34, 95%CI: 0.22-0.53), unmarried (aOR=0.47, 95%CI: 0.24-0.93), first marriage (aOR=0.38, 95%CI: 0.22-0.67), remarriage (aOR=0.36, 95%CI: 0.20-0.67) and cohabiting (aOR=0.47, 95%CI: 0.23-0.97), and knew they had HIV infection before this pregnancy (aOR=0.53, 95%CI: 0.40-0.70) was lower. Han nationality (aOR=1.52, 95%CI: 1.09-2.13), primary school (aOR=2.06, 95%CI: 1.10-3.89) and junior middle school (aOR=1.81, 95%CI: 1.03-3.17) educational level, non-use of antiviral drugs (aOR=6.21, 95%CI: 4.32-8.93) and delivery in township (street) level midwifery institutions (aOR=5.72, 95%CI: 1.61-20.27) had higher rates of loss to follow-up among infants born to HIV-infected pregnant women. Conclusions: HIV-exposed children still have a specific rate of loss to follow-up in China in 2019. In order to further reduce the rate of loss to follow-up, it is of great significance to improve the detection rate of HIV before pregnancy and the rate of antiviral drugs used in pregnant women with HIV infection, which is of great significance for the effective implementation of comprehensive intervention measures of prevention of mother-to-child transmission of HIV.

Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions and Influencing Factors in China

Abstract: Industrialization has increased global carbon emissions, necessitating effective climate change mitigation measures. China, the most populous developing nation, faces the challenge of strategizing emissions to meet national carbon neutrality objectives. However, research on specific regions’ carbon emissions drivers and causal factors is limited, particularly across prefectural-level cities. This study estimates the spatial and temporal patterns of carbon emissions across China’s prefectural cities and utilizes both OLS regression and stepwise regression models to analyze the impact of various factors influencing carbon emissions in these cities. Results reveal the following: (1) The country’s overall 20-year carbon emissions continue to grow from 3020.29 Mt in 2001 to 9169.74 Mt in 2020, with an average annual growth rate of 5.71%; the eastern region has seen a gradual deceleration in emissions, whereas the western region continues to experience an increase. Carbon emissions in cities within each subregion consistently rise. (2) Carbon emissions in Chinese prefectural-level cities exhibit strong spatial autocorrelation and clustering (Z &gt; 1.96, p &lt; 0.05), with hot spots primarily in the eastern coastal areas and cold spots in the northwest to southwest regions. (3) Economic and demographic factors significantly increase carbon emissions, while climate and urbanization effects are more complex and variable. Economic growth and population increase are the most significant influencing factors, but regional variances exist in carbon emissions determinants in subregional prefectural cities. These insights provide valuable insights into national emission dynamics at the prefectural level, providing a theoretical basis for enhancing carbon emission strategies across various jurisdictions.

Analysis of the coupling coordination between traditional Chinese medicine medical services and economy and its influencing factors in China.

The coordinative relationship between medical treatment and the economy is an important part of promoting the sustainable and healthy development of a social economy, and it is conducive to promoting the coordinated development of the two systems. Based on constructing a comprehensive evaluation index system for the relationship between traditional Chinese medicine medical services and economic development, the entropy method, coupling coordination model, and Tobit model are used to calculate the comprehensive development level, coupling coordination degree, and influencing factors of the two systems in 31 provinces of China from 2015 to 2021. Suggestions are proposed for the coordinated development of traditional Chinese medicine medical services, and economy. The results showed that the development level of traditional Chinese medicine was higher than that of social and economic development, the relative development gap between the two systems was gradually narrowed, and the coupling coordination degree increased steadily; however, the regional differences were large. The relative development level and coupling coordination degree of each region show a development pattern of eastern > central > western > northeast; the coupling coordination degree of the two systems in the spatial region was positively correlated and was enhanced year by year. From the perspective of influencing factors, the level of economic development is the decisive factor in the coupling and coordination between traditional Chinese medicine medical treatment and the social economy. Factors such as human capital and health level in traditional Chinese medicine have an inhibitory effect on the coordinated development of the two systems. So, China should focus on optimizing the regional allocation of traditional Chinese medicine medical personnel, improving the quality of medical services, and enhancing the health level of medical personnel.

Spatial Relationship of Inter-City Population Movement and Socio-Economic Determinants: A Case Study in China Using Multiscale Geographically Weighted Regression

In the current field of regional studies, there is a growing focus on regional spatial relationships from the perspective of functional linkages between cities. Inter-city population movement serves as an embodiment of the integrated functionality of cities within a region, and this is closely tied to the socio-economic development of urban areas. This study utilized Location-Based Services (LBSs) to collect the scale of inter-city population movement across 355 cities in China. Additionally, socio-economic data published by local governments were incorporated. By establishing a Multiscale Geographically Weighted Regression (MGWR) model, this research explores the spatial relationships between inter-city population movement and socio-economic influencing factors in China. This study aims to elucidate the spatial scales of the relationships between various variables. Our research findings indicate that the relationship between inter-city population movement and potential socio-economic determinants exhibits spatial non-stationarity. It is better to explore this spatial relationship through the MGWR model as there are different determinants operating on inter-city population movement at different spatial scales. The spatial distribution of the coefficient estimates shows significant regional differences and numerical variations. In China’s economically developed coastal regions, there is relatively balanced development among cities, with advanced manufacturing and producer service industries acting as significant drivers of mobility. In inland regions of China, city size is the most influential variable, directing a substantial flow of human and economic resources towards regional socio-economic hubs such as provincial capitals. The main contribution of this study is the re-examination of the relationship between inter-city population movement and socio-economic factors from the perspective of spatial scales. This approach will help China to consider the heterogeneity of different regions more extensively when formulating regional development policies, thereby facilitating the targeted promotion of regional element flow.

Spatial correlation network of municipal solid waste carbon emissions and its influencing factors in China

Clarifying the provincial spatial correlation network of municipal solid waste (MSW) carbon emissions and its influencing factors is significant for reducing MSW carbon emissions and for ensuring cross-regional coordinated emission reduction. This study used a modified gravity model and social network analysis to explore the structural characteristics of the spatial correlation network of MSW carbon emissions. The quadratic assignment procedure was then used to examine the influencing factors. The results are as follows: (1) From 2005 to 2020, the MSW carbon emissions spatial correlation network showed an intuitive and complex network structure. The tightness of the network increased with fluctuations but still needs improvement, while the network structure exhibited good accessibility and stability. (2) The spatial network exhibited a significant “core-edge” distribution, with Beijing, Tianjin, Shanghai, Jiangsu, Zhejiang, and Fujian being at the center of the spatial correlation network and playing leading roles. (3) The spatial correlation network of MSW carbon emissions was divided into four parts, with the four parts having few internal connections but with the relationships between them being close. (4) Geographical adjacency, economic development level, science and technology level, and MSW treatment structure significantly influenced spatial correlations, while the urbanization level and degree of government intervention had no significant influence on spatial correlations.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Enhancing Agricultural Ecological Efficiency in China: An Evolution and Pathways under the Carbon Neutrality Vision

Under China’s carbon neutrality vision, the integration of resource consumption and ecological protection in agricultural production requires increased attention to agroecology. This study comprehensively integrates the carbon impact within agricultural ecological efficiency (AEE). Based on the window analysis of super-SBM-undesirable and geographically and temporally weighted regression (GTWR) models, AEE and its influencing factors in China’s 31 provinces from 2000 to 2021 are measured, and then types categorized, mechanisms investigated, and optimization pathways provided. The results revealed that from 2000 to 2021, the AEE showed a growing trend, with the spatial agglomeration degree increased. Its gravity center presented a migration path of “northeast–southwest”. Driven by internal and external mechanisms, both agricultural production conditions and regional socio-economic conditions had a stronger positive effect and wider range of promotion on China’s AEE, and the positive contribution of physical environmental conditions decreased, while the inhibitory effect increased. Furthermore, this study divided three zones and emphasized that the agri-ecological power zone plays a demonstrative role in carbon sequestration and efficiency improvement, the eco-pollution balance zone needs to strike a balance between economic development and agricultural ecological development, and the agri-pollution power zone ought to reduce agricultural carbon emissions and mitigate its environmental impact.

Is NIMBY inevitable? An empirical exploration of determinants of public attitudes towards unwanted facilities using nationally representative data in China

ABSTRACT ‘Not in my Back Yard’ (NIMBY) protests against the construction of unwanted facilities nearby occur when individuals prioritize personal benefits over broader social benefits, which is an interesting phenomenon in China’s government-regulated market economic system. Although this fascinating phenomenon attracts plenty of research attention, it remains unknown regarding the extent of NIMBY intention and its influencing factors in China. This study describes the NIMBY intention of Chinese residents towards a large-scale chemical plant with low pollution and analyzes its determinants utilizing data from a nationally representative survey in 2017. It shows that 85% of the 38,775 respondents have strong NIMBY intentions. Among all factors, education and urbanization are the two most influential ones and are positively related to NIMBY intention. Besides, women, high-income groups, and people living in areas with strong social networks, high GDP per capita, or high pollution, exhibit strong NIMBY intention. Conversely, trust in the government and willingness to participate in public affairs are negatively correlated with NIMBY intention. Our study indicates that NIMBY intention will inevitably rise with educational attainment and urbanization levels, but the NIMBY dilemma can be alleviated by implementing participatory governance and building trust in local government.

The Influencing Factors Analysis of Aquaculture Mechanization Development in Liaoning, China

Promoting the mechanization of aquaculture is one of the most important supporting measures to ensure the high-quality development of the aquaculture industry in China. In order to solve the problems of predominantly manual work and to decrease the costs of aquaculture, the influencing factors of China’s aquaculture mechanization were systematically analyzed. The triple bottom theory was selected, and three aspects were identified, including environmental, economic, and social aspects. Through the literature review, the Delphi method, and the analytic hierarchy process, the comprehensive evaluation indicator system, including 18 influencing factors, was proposed. Moreover, the fuzzy comprehensive evaluation method was combined with the model to solve the evaluation results. A case study in Liaoning Province was offered and, according to the analysis results, the economic aspect at the first level was the most critical factor; the financial subsidy for the purchase of aquaculture machinery, the energy consumption of the machinery and equipment, and the promotion and use of aquaculture technology were the most important factors and had the greatest impact on the development of aquaculture mechanization in China. The effective implementation paths and countermeasures were proposed, such as the promotion of mechanized equipment and the enhancement of the machinery purchase subsidies, in order to provide an important decision-making basis for the improvement of the level of aquaculture mechanization.

Analyzing the tourism efficiency and its influencing factors of China's coastal provinces.

Tourism efficiency has become an important role in promoting tourism competitiveness and driving sustainable development. It is particularly important to identify and agnalyze the factors and mechanisms that affect efficiency. This paper firstly evaluates the tourism efficiency of 11 coastal provinces regions in China from 2010 to 2020 by using the DEA-BBC model that includes undesirable outputs. After that, it investigates the internal driving mechanism of the efficiency change through the Malmquist index and its decomposition. Finally, it analyzes the external influencing elements of tourist efficiency by the Tobit model. The results show that: (1) Although the average value of the tourism efficiency was changed from 0.727 to 0.707, it does not achieve the target. Its trend shows fluctuating from 2010-2020, which indicates that the tourism efficiency of most provincial regions is not optimal. The main factor that restricts tourism efficiency is scale efficiency. (2) By analyzing the dynamic trend, it is found that the average increase of technical efficiency is 14.0%, the average increase of technical change is 9.5%, and the average increase of MI index is 25.4%. It indicates that the overall tourism efficiency of 11 coastal provinces region in China is on the rise. (3) The spatial difference of tourism efficiency is significant, but there is no obvious spatial correlation. (4) The influencing factors of tourism efficiency are consumer demand, industrial structure, labor force and urbanization.

Nurses’ engagement in antimicrobial stewardship and its influencing factors: A cross-sectional study

ObjectiveThis study aimed to investigate the level and influencing factors of nurses’ antimicrobial stewardship (AMS) engagement in China based on the capability, opportunity, motivation, and behavior (COM-B) theory, providing valuable insights for developing effective strategies to improve nursing quality in AMS. MethodsThis cross-sectional study was conducted in 17 tertiary hospitals in Hunan, China, from November 2021 to January 2022. A total of 4,514 nurses were selected. The Nurse AMS Engagement Questionnaire (NAEQ), developed using the COM-B theory, was used for evaluation. The questionnaire included capability (14 items), opportunity (7 items), motivation (6 items), and behavior (12 items) four dimensions, 39 items. ResultsThe total NAEQ score was 155.08 ± 27.12, indicating a moderate level. The score of the capability, opportunity, motivation, and behavior dimensions were 52.33 ± 13.48, 28.64 ± 5.76, 24.57 ± 4.57 and 49.53 ± 8.83, respectively. Significant differences in nurses’ AMS engagement were based on professional titles, whether working as a part-time infection control nurse, whether knowing the AMS teams and the defined daily doses of antibiotics, department type, the deployment of clinical pharmacists, and frequency of antimicrobial training and physician-nurse joint rounds (P < 0.05). Nurses with junior titles had higher scores on the NAEQ than nurses with intermediate titles (P < 0.05). Nurses who worked as part-time infection control nurses, knew the AMS team, and the defined daily doses of antibiotics had higher NAEQ scores than those who didn’t (P < 0.01). Nurses working in the ICU and infectious disease department had lower NAEQ scores than those in other departments, such as the ear, nose, and throat (ENT) department (P < 0.01). Nurses who had clinical pharmacists deployed in their department had higher NAEQ scores than those without or unclear deployment (P < 0.01). Furthermore, nurses who received more frequent antimicrobial training and participated in physician-nurse joint rounds had higher NAEQ scores (P < 0.01). ConclusionMultiple strategies, including enhanced education and training and improved multidisciplinary communication and collaboration, are expected to improve nurse AMS engagement. It is important to give more attention to nurses with intermediate professional titles, less experience, and those working in specific departments.

The rebound effect of energy consumption and its determinants in China's agricultural production

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies.