Xiangdan Piao

Objectives: The World Health Organization states that mental illness will become the leading burden of disease globally, by 2030. Thus, examinations of job-stress might require more heterogeneous and innovative solutions. This study aims to confirm causality of the effect of the work environment and employees’ responses on improving their psychological well-being, in Japan. Methods: We used data from over 1 million questionnaires collected from 390 companies for a large scale 3-year longitudinal study (N = 1,021,178), from 2017 to 2019. The lagged variable method was used to investigate the casual effect. Results: We found that psychological stress-related health conditions have been continuously worsening among employees’ of Japanese companies. Considering both the work environment and employees’ responses, is crucial for improving the psychological health of employees. Positive thinking had the most positive impact on employees’ job stress status among the determinant factors. Work environment stressors that negatively impacted job stress included high job demand, low decision latitude, low social support, high psychological demand, effort–reward imbalance, high work load, job insecurity, work-life imbalance, and harassment. Conclusions: Employees’ responses associated change in mood, positive thinking, and talking to people they trust, with a positive influence on reducing stress. Further, thinking positively, not taking the problem too seriously, and avoiding directing feelings of anger and frustration toward others, reduced high-stress in 49% of respondent employees. Among these characteristics, we found that positive thinking has the greatest impact on employees’ psychological well-being.

Under the dual-carbon goals and the new quality productivity development strategy, how artificial intelligence (AI) systematically reshapes the energy efficiency (EE) landscape has become a critical issue. Although prior studies have widely examined the effects of AI on energy efficiency (EE), a comprehensive understanding of the role of AI remains limited. To address this gap, this study constructs a three-level nested CES production function incorporating AI capital, green technology, and human capital, and identifies three mechanisms through which AI influences energy efficiency from a structural perspective: factor substitution, technology induction, and human capital augmentation. Empirical analysis based on panel data from Chinese prefecture-level cities (2000-2024) and 30 provinces (2003-2024) indicates a significant promoting effect of AI on energy efficiency, a conclusion that remains robust after a series of robustness and endogeneity tests. Furthermore, structural estimation reveals key parameters: an AI-energy substitution elasticity of 0.35, a human capital augmentation coefficient of 0.6, and a green technology efficiency parameter of 0.25. Finally, counterfactual simulations demonstrate that human capital augmentation is the most prominent channel, and coordinated policies promoting AI, green technology, and human capital development can achieve greater energy efficiency improvements compared to single-policy approaches, with this effect being particularly pronounced in central and western regions. The combination of AI and human capital policies is the most effective, increasing energy efficiency by 11.76% and significantly outperforming other policy combinations.

The use of full-battery electric vehicles is an essential strategy for reducing greenhouse gas emissions and mitigating climate change. This study examined the transition to full-battery electric vehicles by conducting a cross-sectional household survey in 2023 that collected information on vehicle preferences, evaluations, purchase intentions, environmental attitudes, and socioeconomic and demographic characteristics. The results show that among households using a vehicle as their primary mode of transportation, approximately 89% relied on fossil fuel vehicles, whereas only 6% used electric vehicles. The study further finds that acceptance of vehicles during inter-vehicle transitions is closely linked to energy type: households currently owning fossil fuel vehicles exhibited a high likelihood of repurchasing a fossil fuel vehicle, while electric vehicle owners were more inclined to choose another electric vehicle across cities and areas of different sizes. Households that own electric vehicles tend to report higher levels of well-being compared with those that own fossil fuel vehicles. In addition, sufficient charging infrastructure, stronger knowledge of environmental issues, participation in altruistic donation activities, and cooperative behavior positively influenced electric vehicle adoption. These findings suggest several policy implications, including the expansion of charging stations for business and public use, setting reasonable vehicle prices, improving charging speed, developing electric vehicles suitable for large families, and encouraging individuals to gain initial driving experience with electric vehicles to promote adoption.

The well-organized medical security system plays an important role in improving public health. This study investigates the effect of the diagnosis-related groups (DRG) policy, which is a way to control cost, on medical care services, including hospital revenue status. Based on the panel data on derived from public medical institutions in Sanming City from 2014 to 2022, the average length of stay for discharged patients, number of admissions per 100 visits, and bed utilization rate were used to measure medical services status. The difference-in-difference method was used to explore the impact of the DRG policy implementation on the overall hospital operation in medical care services in Sanming City, China. We found the DRG policy introduction has a negative effect on the average length of stay for discharged patients, emergency admissions per 100 visits, and the hospital bed occupancy rate. On the contrary, the DRG policy reduces the total medical revenue in terms of the reduced drug revenue. However, the DRG policy increases the examination and the test income, average charge per emergency visit, and drug cost per discharged patient. In sum, the introduction of the DRG policy reduces the medical care system operating cost by reducing drug revenue and bed occupancy, reducing the length of hospitalization, worsening hospital revenue, and increasing the charge for examination and test, emergency visits, and drug cost per discharge. The C-DRG policy implementation in Sanming city effected improvements in public health and overall medical care system services.

Understanding emotional stress stability in populations is crucial because stress is a key factor in causing depression, and it worsens well-being. In this study, using repeated cross-sectional data from 149 countries from 2007 to 2021 (N = 2,450,043), we examined time trends of psychological stress in populations worldwide. Over half of the population experienced emotional stress in 20 countries, and 85% of the countries reported worse psychological stress in 2020 compared with 2008. We found that psychological well-being declined most rapidly among young people compared with other age groups. Individuals living and working in all types of locations (rural/farm, town/village, large city, and suburban areas) and employment (full-time, self-employed, part-time, and unemployed), respectively, experienced continuously worsening emotional stress when comparing three time periods (2008–2011, 2012–2019, and 2020–2021). Furthermore, reducing physical pain and increasing income were noted to be more important than solving health problems for the purpose of decreasing stress. Emotional stress continuously worsened worldwide over the past few decades, but the trend varied among countries. Our findings highlight the significance of improving people’s living environments to reduce their likelihood of experiencing emotional stress.

When studies investigate the impact of average schooling or learning scores on economic development, they rarely focus on the effect of inequality in learning quality on economic development. Human capital is defined as inclusive sources combining citizens’ knowledge and treatment skills. This study uses global learning data to investigate a novel effect of the inequality of reading, math, and science learning scores on economic development and energy selection based on links between and within countries. We found that reducing learning outcome inequality among secondary students is crucial for improving economic development from both short-term and long-term perspectives. Moreover, the positive association between students' learning quality and economic development is confirmed. Compared to the within-country effect, the greater between-country effect of the relationship between learning quality and economic development is confirmed, showing that expectations of the between-country effect might overestimate the favorable effect of education on economic development. On the contrary, the findings show that population learning inequality is less likely to affect national attitudes toward nuclear electricity generation or renewable energy adoption. The insightful policy implications suggest that policy makers should consider reducing learning outcome inequality among students and improving the within-country relationship between education and economic development.