Social, lifestyle, and health status characteristics as a proxy for occupational burnout identification: A network approach analysis.

Background: Occupational burnout is a type of psychological syndrome. It can lead to serious mental and physical disorders if not treated in time. However, individuals tend to conceal their genuine feelings of occupational burnout because such disclosures may elicit bias from superiors. This study aims to explore a novel method for estimating occupational burnout by elucidating its links with social, lifestyle, and health status factors. Methods: In this study 5,794 participants were included. Associations between occupational burnout and a set of features from a survey was analyzed using Chi-squared test and Wilcoxon rank sum test. Variables that are significantly related to occupational burnout were grouped into four categories: demographic, work-related, health status, and lifestyle. Then, from a network science perspective, we inferred the colleague's social network of all participants based on these variables. In this inferred social network, an exponential random graph model (ERGM) was used to analyze how occupational burnout may affect the edge in the network. Results: For demographic variables, age (p < 0.01) and educational background (p < 0.01) were significantly associated with occupational burnout. For work-related variables, type of position (p < 0.01) was a significant factor as well. For health and chronic diseases variables, self-rated health status, hospitalization history in the last 3 years, arthritis, cardiovascular diseases, high blood lipid, breast diseases, and other chronic diseases were all associated with occupational burnout significantly (p < 0.01). Breakfast frequency, dairy consumption, salt-limiting tool usage, oil-limiting tool usage, vegetable consumption, pedometer (step counter) usage, consuming various types of food (in the previous year), fresh fruit and vegetable consumption (in the previous year), physical exercise participation (in the previous year), limit salt consumption, limit oil consumption, and maintain weight were also significant factors (p < 0.01). Based on the inferred social network among all airport workers, ERGM showed that if two employees were both in the same occupational burnout status, they were more likely to share an edge (p < 0.0001). Limitation: The major limitation of this work is that the social network for occupational burnout ERGM analysis was inferred based on associated factors, such as demographics, work-related conditions, health and chronic diseases, and behaviors. Though these factors have been proven to be associated with occupational burnout, the results inferred by this social network cannot be warranted for accuracy. Conclusion: This work demonstrated the feasibility of identifying people at risk of occupational burnout through an inferred colleague's social network. Encouraging staff with lower occupational burnout status to communicate with others may reduce the risk of burnout for other staff in the network.

Age-related changes in the risk of high blood pressure.

Background and aims: Understanding the age-related trend of risk in high blood pressure (BP) is important for preventing heart failure and cardiovascular diseases. But such a trend is still underexplored. This study aims to (a) depict the relationship of BP patterns with age, and (b) understand the trend of high BP prevalence over time in different age groups. Materials and methods: Health check-up data with an observational period of 8 years (January 1, 2011, to December 31, 2018) was used as the data source. A total of 71,468 participants aged over 18 years old with complete information on weight, height, age, gender, glucose, triglyceride, total cholesterol, systolic (SBP), and diastolic blood pressure (DBP) were included for analysis. Generalized additive models were adopted to explore the relationship between the risk of high BP and age. Variance analysis was conducted by testing the trend of high BP prevalence in age groups over time. Results: Risk of high SBP showed a continuous rise from age 35 to 79 years and a concurrent early increase in the risk of high DBP; after age 50-65 years, high DBP risk declined. The risk of SBP rises linearly with age for men, whereas increases non-linearly for women. In addition, a significant increasing trend of high SBP risk among middle-aged people was found during the past decade, men experienced a later but longer period of increase in high SBP than women. Conclusion: The high SBP risk progresses more rapidly in the early lifetime in women, compared to the lifetime thereafter. Thresholds of increasing trend of SBP suggest a possible need for hypertension screening in China after the age of 40.

The effect of information literacy heterogeneity on epidemic spreading in information and epidemic coupled multiplex networks.

With the COVID-19 pandemic, better understanding of the co-evolution of information and epidemic diffusion networks is important for pandemic-related policies. Using the microscopic Markov chain method, this study proposed an aware-susceptible-infected model (ASI) to explore the effect of information literacy on the spreading process in such multiplex networks. We first introduced a parameter that adjusts the self-protection related execution ability of aware individuals in order to emphasis the importance of protective behaviors compared to awareness in decreasing the infection probability. The model also captures individuals' heterogeneity in their information literacy. Simulation experiments found that the high information-literate individuals are more sensitive to information adoption. In addition, epidemic information can help to suppress the epidemic diffusion only when individuals' abilities of transforming awareness into actual protective behaviors attain a threshold. In communities dominated by highly literate individuals, a larger information literacy gap can improve awareness acquisition and thus help to suppress the epidemic among the whole group. By contrast, in communities dominated by low information-literate individuals, a smaller information literacy gap can better prevent the epidemic diffusion. This study contributes to the literature by revealing the importance of individuals' heterogeneity of information literacy on epidemic spreading in different communities and has implications for how to inform people when a new epidemic disease emerges.

Characterizing research leadership on geographically weighted collaboration network.

Research collaborations, especially long-distance and international collaborations, have become increasingly prevalent worldwide. Recent studies highlighted the significant role of research leadership in collaborations. However, existing measures of the research leadership do not take into account the intensity of leadership in the co-authorship network. More importantly, the spatial features, which influence the collaboration patterns and research outcomes, have not been incorporated in measuring the research leadership. To fill the gap, we construct an institution-level weighted co-authorship network that integrates two types of weight on the edges: the intensity of collaborations and the spatial score (the geographical distance adjusted by the cross-linguistic-border nature). Based on this network, we propose a novel metric, namely the spatial research leadership rank, to identify the leading institutions while considering both the collaboration intensity and the spatial features. The leadership of an institution is measured by the following three criteria: (a) the institution frequently plays the corresponding rule in papers with other institutions; (b) the institution frequently plays the corresponding rule in longer distance and even cross-linguistic-border collaborations; (c) the participating institutions led by the institution have high leadership status themselves. Harnessing a dataset of 323,146 journal publications in pharmaceutical sciences during 2010-2018, we perform a comprehensive analysis of the geographical distribution and dynamic patterns of research leadership flows at the institution level. The results demonstrate that the SpatialLeaderRank outperforms baseline metrics in predicting the scholarly impact of institutions. And the result remains robust in the field of Information Science and Library Science. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11192-021-03943-w.

Characterizing the patterns of China's policies against COVID-19: A bibliometric study.

Since the beginning of 2020, the Chinese government has implemented substantial policies to prevent and control the COVID-19 epidemic. This research attempts to reveal and characterize the patterns of China's policy against COVID-19. Bibliometric methods are applied for studying policy evolution, with the aim of discovering the transitions of the policies over time, the collaborations among policy makers, and the effects of the policies. A total of 366 policies of epidemic prevention are collected. Policy topic shifting, the cooperation of policy-issuing agencies, and the policy content of agencies are analyzed. According to the results, China's policies are implemented in four stages. Moreover, the policy's foci against COVID-19 shifted from medical support in the early stage to economic development in the late stage. Agencies involved in the policymaking can be categorized into three types: leading agencies, key agencies, and auxiliary agencies, with their corresponding administrative influence ranked in this order. Especially, the Chinese government adopted a multi-agency, joint epidemic prevention and control mechanism to ensure the efficiency of the policymaking cooperation. Furthermore, aside from ensuring cooperation among the policy-issuing agencies, they each had their own primary focus of policies in the early stage, but their foci were gradually shared as the epidemic situation changed. This research reveals how China responded to the public health emergency of COVID-19 from the perspective of policy making.

Proximity-Induced Superconductivity with Subgap Anomaly in Type II Weyl Semi-Metal WTe2.

Due to the nontrivial topological band structure in type II Weyl semi-metal tungsten ditelluride (WTe2), unconventional properties may emerge in its superconducting phase. While realizing intrinsic superconductivity has been challenging in the type II Weyl semi-metal WTe2, the proximity effect may open an avenue for the realization of superconductivity. Here, we report the observation of proximity-induced superconductivity with a long coherence length along the c axis in WTe2 thin flakes based on a WTe2/NbSe2 van der Waals heterostructure. Interestingly, we also observe anomalous oscillations of the differential resistance during the transition from the superconducting to the normal state. Theoretical calculations show excellent agreement with experimental results, revealing that such a subgap anomaly is the intrinsic property of WTe2 in superconducting state induced by the proximity effect. Our findings enrich the understanding of the superconducting phase of type II Weyl semi-metals and pave the way for their future applications in topological quantum computing.