RESUMEN
BACKGROUND: Decision fatigue is a new concept in the field of psychology and refers to a state of fatigue alongside impaired cognitive processing and emotional regulation ability. Previous studies have confirmed that nurses are prone to decision fatigue, and nurses who experience decision fatigue may implement nursing measures that are inconsistent with clinical evidence, thus affecting patients' benefits. COVID-19, as a large-scale global public health emergency, increased the workload and burden of nurses and aggravated decision fatigue. However, the factors leading to decision fatigue among nurses have not yet been identified. METHODS: This study is guided by interpretative phenomenology. During the epidemic period of COVID-19: From November 2022 to February 2023, a one-to-one, semi-structured in-depth interview was conducted among nurses with decision fatigue experience who were participating in front-line work in Jilin Province using homogenous sampling. The interview recordings and related data were transcribed into text within 24 h, and data analysis was assisted by NVivo 12.0 software. RESULTS: After a total of 14 front-line nurses were analyzed in this study, The thematic level reaches saturation, the findings present a persuasive and coherent narrative, and the study is terminated, and finally extracted and formed three core themes: "Cognition, influence and attitude of decision fatigue", "Approaching factors of decision fatigue" and "Avoidant factors of decision fatigue". CONCLUSION: This study confirmed that decision fatigue was widespread in the work of front-line nurses, affecting the physical and psychological health of nurses, the quality of nursing work, the degree of benefit of patients and the clinical outcome. However, nursing staff do not know enough about decision fatigue, so the popularization and research of decision fatigue should be strengthened. Improve the attention of medical institutions, nursing managers and nursing staff.Some suggestions are put forward for the intervention of decision fatigue through personnel, task, tool and technology, organization and environment.
RESUMEN
Clarifying the mechanism of influence of urban form on carbon emissions is an important prerequisite for achieving urban carbon emission reduction. Taking the Yangtze River Economic Belt as an example, this study elaborated on the general mechanism of urban form on carbon emissions, used multi-source data to quantitatively evaluate the urban form, and explored the impacts of urban form indicators on carbon emissions from 2005 to 2020 at global and sub-regional scales with the help of spatial econometric models and geodetector, respectively. The results showed that:â The carbon emissions of the Yangtze River Economic Belt increased from 2 365.31 Mt to 4 230.67 Mt, but the growth rate gradually decreased. Its spatial distribution pattern was bipolar, with high-value areas mainly distributed in core cities such as Shanghai and Chongqing and low-value areas concentrated in the western regions of Sichuan and Yunnan. â¡ The area of construction land in the study area expanded over the past 15 years, but the population density of construction land had been decreasing. The degree of urban fragmentation was decreasing, and the difference between cities was also progressively narrowing. The average regularity of urban shape improved, and the compactness increased significantly. ⢠All indicators of urban scale had significant positive effects on carbon emissions at the global scale, urban fragmentation had a significant negative effect in 2005, and the effective mesh size (MESH) indicator of urban compactness showed a significant negative correlation with carbon emissions in the study period. ⣠Total class area, patch density, and effective mesh size had the most significant impacts on carbon emissions in upstream cities. Effective mesh size, mean perimeter-area ratio, and total class area had higher influences in midstream cities. Effective mesh size, percentage of like adjacencies, and largest patch index were the key factors to promote carbon reduction in downstream cities. Cities in different regions should comprehensively consider the impacts of various urban form indicators on carbon emissions and then optimize their urban form to promote sustainable development.
