Nurses' experience of work stress related to COVID-19 regular prevention and control in China: A qualitative study.

AIM: To explore the experiences of nurses' work stress related to COVID-19 regular epidemic prevention and control in China. BACKGROUND: The global COVID-19 epidemic is still severe, and China's ongoing regular epidemic prevention and control still cannot be relaxed, which places demands on nurses. METHODS: Thirty nurses and eight nurse managers were interviewed using semistructured in-depth interviews, and the data were analysed by the Colaizzi seven-step analysis method. RESULTS: Four themes were extracted as follows: environmental factors, organizational factors, personal factors and positive factors in coping with stress. CONCLUSIONS: Nursing managers should pay attention to construction of the first-line departments of regular epidemic prevention and control. The shortage of nurses' human resources and the increase of nurse-patient conflicts are problems that need to be solved urgently. In addition, this research also emphasizes the importance of promoting nurses' stress-related growth and thinking about the possibility of reform. IMPLICATIONS FOR NURSING MANAGEMENT: The construction of the hospital environment and increasing the resilience of nursing teams require attention. We should attach importance to the training of nurses' communication skills and provide sufficient organizational support and economic guarantees for nurses. Finally, perhaps we should also consider whether it is necessary to reform the relevant hospital systems and how to reform them.

The collaboration between infectious disease modeling and public health decision-making based on the COVID-19

Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future.

Factors Influencing Public Panic During the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has been regarded as a public health emergency that caused a considerable degree of public panic (such as anxiety and insomnia) during its early stage. Some irrational behaviors (such as excessive search for information related to the pandemic and excessive hoarding of supplies) were also triggered as a result of such panic. Although there has been plenty of news coverage on public panic due to the outbreak, research on this phenomenon has been limited. Since panic is the main psychological reaction in the early stage of the pandemic, which largely determines the level of psychological adaptation, time of psychological recovery, and the incidence of PTSD, there exists a demand to conduct investigation on it. From a public governance perspective, the government's assessment of public panic may affect the efficiency and effectiveness of pandemic prevention and control. Therefore, it is of obvious practical significance to investigate public panic during the COVID-19 pandemic and analyze its influential factors. The self-compiled COVID-19 Social Mentality Questionnaire was used to collect data from a total of 16,616 participants online, and 13,511 valid responses were received. The results from the chi-square test showed that there were differences in gender, educational level, age, pandemic-related knowledge, self-efficacy, risk level, and objective social support. Furthermore, multiple linear regression analysis results showed that self-efficacy, gender, educational level, age, risk level, pandemic-related knowledge, and objective social support were significant predictors of public panic. Among the research variables, self-efficacy, gender, educational level, and age were negative predictors of panic while risk level, pandemic-related knowledge, and objective social support were positive predictors of panic.

Antecedents of Public Mental Health During the COVID-19 Pandemic: Mediation of Pandemic-Related Knowledge and Self-Efficacy and Moderation of Risk Level.

Background: COVID-19 affects not only patients' physical health but also their mental health. For the general public, although their physical health may not be directly affected, their mental health may be affected by stress, anxiety, and social panic caused by COVID-19. Controlling the pandemic should focus on not only physical health but also mental health. For the general public, mental health is even more important, as good mental health at the individual level can form a positive social mentality conducive to pandemic prevention and control. Therefore, it is important to assess mental health during the pandemic, and analyze risk and protective factors. Methods: A self-compiled COVID-19 Social Mentality Questionnaire was used to conduct an online survey. A total of 16,616 participants responded, with 13,511 valid questionnaires. Results: Results showed that 10.7% of participants rated their mental health as "worse than usual" during the pandemic, and there were gender, age, and educational differences. Social support was positively correlated with pandemic-related knowledge and self-efficacy, and could indirectly predict mental health. Pandemic-related knowledge was positively correlated with self-efficacy and mental health, and risk level was negatively correlated with mental health. Hierarchical regression analysis showed that pandemic-related knowledge played a partial mediating role in the relationship between social support and self-efficacy, while self-efficacy played a complete mediating role in the relationship between social support and mental health. Logistic regression analysis showed that risk level moderated the relationship between self-efficacy and mental health. Conclusions: Social support can increase pandemic-related knowledge, thus improving self-efficacy and maintaining/promoting mental health. High risk levels can undermine the role of self-efficacy in promoting mental health. Therefore, in the fight against the COVID-19, people need to support and cooperate with each other, to improve self-efficacy and reduce risk, thus maintaining and promoting mental health.