ABSTRACT
Managing ecosystems is considered a "wicked problem" without clear solutions due to the limited understanding of complex ecosystems and social dynamics. In this study, a method based on the Driving forces–Pressures–State–Impacts–Responses (DPSIR) framework was developed to reveal the Ecological Civilization Construction (ECC) together with structural equation modeling (SEM), panel data model (PDM), coupling and coordination degree (CCD) model, and data envelopment analysis (DEA). The SEM reveals that component Responses as exogenous variables can better explain the DPSIR framework nexuses than Driving forces, indicating that environmental protection measures taken by Chinese government played a dominant role in ECC. ECC indexes (ECCI) of 30 Chinese provinces were 18–87% higher in 2019 than 2012, and the PDM demonstrates that temperature, precipitation, and GDP can explain about 87.2% of ECCI variation among 30 provinces. About 12–40% increase in CCD within the DPSIR framework were detected in 30 Chinese provinces in 2019 compared to 2012. The DEA suggests that China's ECC's average comprehensive and technical efficiencies were only 0.62 and 0.77 in 2019, respectively. Meanwhile, these results show that ECC remains to be strengthened and coordinated. Implications on ECC were proposed for some provinces. Overall, this study proposes a Response-driven pathway named RDPSI can explain the achievements and limitation factors in China's ECC. Also, our results emphasize the importance of integrating science and technology, policy formulation, and precise implementation to achieve sustainable development. • A new method for studying the dynamic relationship of the SES is developed. • A sustainable development pathway named RDPSI is proposed. • China has formed a SES of positive feedback cycle, but the system is unstable. • There are increasingly significant spatial correlation issues in 30 Chinese provinces. [ FROM AUTHOR] Copyright of Journal of Cleaner Production is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Background: Early in the epidemic of corona virus disease 2019 (COVID-19), Chinese government had recruited a portion of military healthcare workers to support the designated hospital (Wuhan Huoshenshan Hospital) to relieve the front-line workload in Wuhan, China. It was reported that the majority of the front-line medical staff (FLMS) suffered from adverse effects, but their physical and psychological health status and its relationship were still unknown. Hence, a structural equation modeling (SEM) was conducted to establish and test the latent relationship among variables.Methods: This is a cross-sectional study. Totally 115 convenience samples of military medical staff from Xinqiao Hospital in Chongqing were enrolled during February 17th to February 29th, 2020. The medical staff assisting in Huoshenshan Hospital were selected as experimental group(n=55), the other medical staff were control group(n=60). Self-reported sleep status, fatigue status, resilience status and anxiety status were examined.Results: During COVID-19, the medical staff underwent some impairments of physical and psychological health. The anxiety score of experimental group was (42.84±9.44), the fatigue score was (52.85±9.33), and the resilience score was (67.58±11.75). And the score of anxiety, fatigue, resilience of control group were (46.27±9.94), (49.33±11.20), (65.42±14.54) respectively. For experimental group, we found the different working duration and different attitude to work in Wuhan both had significant differences in fatigue scores (P<0.05); As for resilience scores and anxiety scores, only different current perceived health status of participants showed a statistically significant difference (P<0.05). The SEM results indicated the direct path from resilience to fatigue (β=-0.129, P=0.032) and anxiety (β=-0.026, P=0.043) were both significant, it revealed that resilience were negatively associated with the level of fatigue and anxiety, and the indirect path showed fatigue had a significant mediating effect between resilience and anxiety (β=-0.146, P=0.039) of the Huoshenshan Hospital medical staff.Conclusion: During an explosive pandemic, motivating the effect of individual’s internal resilience and making use of proper external interventions is a promising way to protect the physical and mental health of the front-line medical staff.