Association between long working hours and mental health among nurses in China under COVID-19 pandemic: based on a large cross-sectional study.

OBJECTIVE: Nurses were more likely to experience mental disorders due to long working hours and irregular schedules. However, studies addressing this issue are scarce; therefore, we aimed to investigate the association between long working hours and mental health in Chinese nurses during the coronavirus disease pandemic. METHODS: A cross-sectional study was conducted with 2,811 nurses at a tertiary hospital in China from March to April 2022. We collected data on demographic, psychological characteristics, dietary habits, life, and work-related factors using a self-reported questionnaire and measured mental health using Patient Health Questionnaire-9 and General Anxiety Disorder-7. Binary logistic regression to determine adjusted odds ratios and 95% confidence intervals. RESULTS: The effective response rates were 81.48%, 7.80% (219), and 6.70% (189) of the respondents who reported depression and anxiety, respectively. We categorized the weekly working hours by quartiles. Compared with the lowest quartile, the odds ratios and 95% confidence intervals across the quartiles for depression after adjustment were 0.98 (0.69, 1.40), 10.58 (2.78, 40.32), and 1.79 (0.81, 3.97) respectively, the P for trend was 0.002. The odds ratios across the quartiles for anxiety after adjustment were 0.87 (0.59, 1.30), 8.69 (2.13, 35.46), and 2.67 (1.26, 5.62), respectively, and the P for trend was 0.008. CONCLUSIONS: This study demonstrated that extended working hours increased the risk of mental disorders among nurses during the coronavirus disease pandemic, particularly in those who worked more than 60 h per week. These findings enrich the literature on mental disorders and demonstrate a critical need for additional studies investigating intervention strategies.

Therapeutic Effect of Tocilizumab on Inhibiting Cytokine Release Syndrome in Severe Coronavirus Disease 2019 Patients

Background and Objectives: Older adults are more susceptible to coronavirus disease 2019 (COVID-19). Interleukin-6 (IL-6) is an important cytokine in the cytokine release syndrome (CRS), and tocilizumab blocks the IL-6 receptor. The objective is to analyze the effect of tocilizumab on CRS in older patients with severe COVID-19. Materials and Methods: Between February 10 and March 21, 2020, a total of 19 patients aged ≥60 years with severe or critical COVID-19 met the study inclusion criteria at the Tongji Hospital in Wuhan City, Hubei Province, China. The patients were divided into two groups: the tocilizumab group, with IL-6 levels, which exceeded the upper limit of normal by >10-fold and non-tocilizumab group. Results: Patients in the tocilizumab group were older (73.20 ± 4.44 vs. 66.21 ± 5.06 years, P = 0.014), had lower lymphocyte counts (0.71 ± 0.18 vs. 1.18 ± 0.59 × 109/L, P = 0.016), and higher high-sensitivity C-reactive protein (hsCRP) levels (94.04 ± 57.24 vs. 51.65 ± 45.37 mg/L, P = 0.035). Increases in ferritin (FER) and hsCRP levels in patients in the tocilizumab group were marked. Except for one patient who died, IL-6, FER, hsCRP levels, and the neutrophil/lymphocyte ratio in the remaining four patients decreased following treatment with tocilizumab. Tocilizumab did not cause any serious adverse reactions. There were no differences in mortality, days until lung computerized tomography improvement, or renal function between the two groups. The total mortality rate was 10.53%. Conclusions: Our results support the therapeutic efficacy and safety of tocilizumab in older patients with severe COVID-19.

Digital Students’ Satisfaction With and Intention to Use Online Teaching Modes, Role of Big Five Personality Traits

During the COVID-19 pandemic, online teaching modes were found vital to continue students’ learning process, but sustainable implementation of online teaching models is an area of concern for policymakers. Psychiatrists are also eager to know students’ behavior toward learning and modes of teaching during COVID-19. We have drawn a model based on the big five personality traits to study students’ satisfaction with online teaching modes and their adoption intentions toward online teaching modes. We have collected data from 718 bachelor’s and master’s level students from four different universities. We have applied the SEM-ANN dual-stage approach to test personality traits’ influence and ranked them based on their normalized importance. The results revealed that agreeableness, conscientiousness, neuroticism, and openness positively influence students’ satisfaction with online teaching models, but that extraversion negatively influences their satisfaction. Agreeableness, extraversion, and neuroticism positively impact, but openness negatively influences. Conscientiousness does not affect adoption intention. Furthermore, agreeableness is the most significant, and conscientiousness is the least important factor for students to adopt online teaching modes. The findings of the study have useful perceptiveness for educational policymakers, academics, and psychiatrists.

Research and development of intelligent question answering robot system: a case study of its application in response to COVID-19 epidemic in Jinan city

During the epidemic of coronavirus disease 2019(COVID-19), the local Centers for Disease Control were bombarded with large amounts of questions from the public and the human hotline system was unable to meet the demands. As a result, Jinan Centers for Disease Coatrd developed an "intelligent question answering robot system" to cope with this situation. This paper introduces the design of the robot system and construction and classification of the knowledge base, and evaluates its application effects. The robot system can greatly reduce pressure on the human hotline, actively record and analyze users' demands, and improve the quality and efficiency of Centers for Disease Coatrd consultation service. It is a valuable and growable operating mode of consultation service, which can provide reference for the information service in future public health events.

Implications on applying the Web 2.0 software to teach a Chinese L2 learner online

The rise of information and communication technologies has increased people's access to educational resources and stormed the process of E-learners in the past decades. Recently, the COVID-19 pandemic forced more people to stay at home to do things via online. Of course, education is no exception. While numerous distance Chinese learning tools or websites are booming, not all these tools or websites are suitable because of E-learners' variations in Chinese language proficiency, computer literacy, or the complexity of the tools. Hence, being able to choose effective Chinese E-learning tools for Chinese learners is crucial for Teachers of Chinese to Speakers for Other Languages (TCSOL) as it affects not only learners' motivation and overall success as well as teachers' teaching pedagogy and performance. The present study analyzed a series of user-friendly, free Web2.0 digital tools for distance Chinese learners to study along with a textbook, Practical Audio-Visual Chinese 2, designed and carried out experimental teaching courses for Japanese participants with elementary Chinese proficiency. Lastly, it concluded with ST2D implications for TCSOL based the feedback from users.

Intrusion detection by machine learning for multimedia platform.

The multimedia service company, Netflix, increased the number of new subscribers during the Coronavirus pandemic age. Intrusion detection systems for multimedia platforms can prevent the platform from network attacks. An intelligent intrusion detection system is proposed for the security IP Multimedia Subsystem (IMS) based on machine learning technology. For increasing the accuracy of the classifiers, it is vital to select the critical features to construct the intrusion detection system. Two-class classifiers, including the Decision Tree, Support Vector Machine, and Naive Bayesian, are selected to evaluate intrusion detection accuracy. According to the three classifiers' accuracy values, the most critical features are selected based on the features' ranking orders. Six critical features are selected:Service, dst_host_same_srv_rate, Flag, Protocol Type, Dst_host_rerror_rate, and Count. Numerical comparison with state_of_the_art shows that critical features improve intrusion detection accuracy, which can be better than the deep learning method.

Tocilizumab May Be a Key in Therapy for Cytokine Release Syndrome in Older Patients With Severe Symptoms of COVID-19 (preprint)

Background Older adults are more susceptible to the novel coronavirus disease 2019 (hereafter, COVID-19) and more likely to develop severe illness. Cytokine release syndrome (CRS) may be an important factor in the development of severe disease in patients with COVID-19. Interleukin-6 (IL-6) is an important cytokine in CRS, and tocilizumab can block the IL-6 receptor. In this study, we analyzed the therapeutic effects and safety of tocilizumab on CRS in older patients with severe COVID-19. Methods Between February 10 and March 21, 2020, a total of 19 patients with severe or critical COVID-19 aged ≥ 60 years met the study inclusion criteria at Tongji hospital in Wuhan city, Hubei Province, China. Patients were divided into two groups: 1. The tocilizumab group, whose IL-6 levels exceeded the upper limit of normal by > 10-fold; and 2. The no tocilizumab group, with 1L-6 levels < 10-fold the upper normal limit. Results Patients in the tocilizumab group were older (73.20 ± 4.44 vs. 66.21 ± 5.06 years, P = 0.014); had lower lymphocyte counts (0.71 ± 0.18 vs. 1.18 ± 0.59 × 109/L, P = 0.016); and higher high-sensitivity C-reactive protein (hsCRP) levels (94.04 ± 57.24 vs. 51.65 ± 45.37 mg/L, P = 0.035). The increases in ferritin (FER) and hsCRP levels in patients in the tocilizumab group were marked. Except in one patient who died, IL-6, FER, and hsCRP levels, and the neutrophil/lymphocyte ratio, in the remaining four patients decreased following treatment with tocilizumab. Further, patient computerized tomography scan results improved after 3–8 days of tocilizumab treatment. Tocilizumab did not cause any serious adverse reactions. There were no differences in mortality or days until lung computerized tomography improvement between the two groups. The total mortality rate was 10.53%. Conclusions Our results support the therapeutic efficacy and safety of tocilizumab on older patients with severe COVID-19.