Effects of mindfulness decompression therapy on mental health and job burnout among nurses working in the frontline of the novel coronavirus pandemic: A retrospective study.

OBJECTIVES: As the coronavirus disease 2019 (COVID-19) pandemic continues to spread worldwide, nucleic acid detection is a key step in controlling it. Psychological issues and job burnout of nurses working in nucleic acid sampling roles for long periods have become apparent. This study aimed to explore the effects of mindfulness decompression therapy on mental health and job burnout in front-line nurses working in nucleic acid sampling during the pandemic. METHODS: Nucleic acid sampling frontline nurses who were positive for burnout on both the Symptom Checklist-90 (SCL-90) and the Maslach Burnout Inventory-General Scale (MBI-GS) were selected as the participants. Frontline nurses in the nucleic acid testing area who received routine psychological nursing intervention from June 2020 to April 2021 were used as the control group. Nurses who received both routine psychological nursing and mindfulness decompression therapy from May 2021 to December 2021 formed the "mindfulness" subject group. We compared the two groups' primary outcome measures of SCL-90 and MBI-GS scores. RESULTS: Before the intervention, there were no significant differences between the two groups in general data, SCL-90 scores, and MBI-GS scores. After the mindfulness decompression therapy, according to SCL-90 and MBI-GS scales, psychological distress and job burnout of nurses in the mindfulness group were significantly better than those in the control group. CONCLUSION: Mindfulness decompression therapy can effectively improve mental health and relieve job burnout in frontline nurses in nucleic acid sampling areas, which is worthy of clinical application. Randomized controlled trials are still needed, however, to fully confirm the effects of mindfulness decompression therapy.

Portable nanopore-sequencing technology: Trends in development and applications.

Sequencing technology is the most commonly used technology in molecular biology research and an essential pillar for the development and applications of molecular biology. Since 1977, when the first generation of sequencing technology opened the door to interpreting the genetic code, sequencing technology has been developing for three generations. It has applications in all aspects of life and scientific research, such as disease diagnosis, drug target discovery, pathological research, species protection, and SARS-CoV-2 detection. However, the first- and second-generation sequencing technology relied on fluorescence detection systems and DNA polymerization enzyme systems, which increased the cost of sequencing technology and limited its scope of applications. The third-generation sequencing technology performs PCR-free and single-molecule sequencing, but it still depends on the fluorescence detection device. To break through these limitations, researchers have made arduous efforts to develop a new advanced portable sequencing technology represented by nanopore sequencing. Nanopore technology has the advantages of small size and convenient portability, independent of biochemical reagents, and direct reading using physical methods. This paper reviews the research and development process of nanopore sequencing technology (NST) from the laboratory to commercially viable tools; discusses the main types of nanopore sequencing technologies and their various applications in solving a wide range of real-world problems. In addition, the paper collates the analysis tools necessary for performing different processing tasks in nanopore sequencing. Finally, we highlight the challenges of NST and its future research and application directions.

Impact of a pandemic on attitudes towards immigrants

Immigration control is an issue that figures prominently in public policy discussions and election campaigns throughout the world. Immigrants can be perceived as posing both realistic and symbolic threats to the host society. During the current global pandemic, these threats are amplified. This research investigated how attitudes towards immigrants were likely to be more negative when the impact of the pandemic was made salient. Based on intergroup threat theory (Rios et al., 2018) and uncertainty identity theory (Hogg, 2021a), two empirical studies investigated the effect of realistic and symbolic threats from the COVID-19 pandemic on people's attitudes towards immigrants. Study 1 (N =303) tested if priming pandemic induced symbolic threats increased social identity uncertainty and found that pandemic-related symbolic but not realistic threats increased social identity uncertainty. Study 2 (N =363) again primed the two types of threat induced by the pandemic, measured their effects on attitudes towards immigrants, and examined if the effects could be explained by social identity uncertainty and collective angst. Results showed that people who perceived more COVID-19 related symbolic threat than COVID-19 related realistic threat experienced more COVID-19 related national identity uncertainty and collective angst, which predicted less positive attitudes towards immigrants. People who perceived more COVID-19 related realistic threat than COVID-19 related symbolic threat experienced less COVID-19 specific national identity uncertainty and collective angst, which predicted their more positive attitudes towards immigrants. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Psychological Status and Job Burnout of Nurses Working in the Frontline of the Novel Coronavirus in China During the Delta Variant Outbreak: A Cross-Sectional Survey

Purpose Investigating psychological status and job burnout of nurses working in the frontline of the novel coronavirus in Zhangjiajie city in China during the Delta variant outbreak, comparing differences and analyzing factors of these two variables between the nurses from different nucleic acid testing (NAT) sites. Patients and methods This survey was conducted from August 1 to 31, 2021. The participants were 512 nurses, 198 nurses of whom were from temporary NAT sites in communities/towns in Zhangjiajie city, and the rest were from NAT sites inside hospitals. The psychological status and the job burnout were measured by the Symptom Checklist-90 (SCL-90) and the Maslach Burnout Inventory-General Scale (MBI-GS). Results The prevalence of the SCL-90 positive result and job burnout were 49.4% and 61.1%, respectively. The factors influencing the psychological status of nurses included the contact with COVID-19 patients or their body fluids and specimens, working seniority and the duration of working in the frontline of the novel coronavirus. The independent risk factors of nurses’ job burnout included the following four factors. Firstly, the contact with COVID-19 patients or their body fluids and specimens (OR=150.95, 95% CI=(44.87,507.77), P<0.001). Secondly, five to nine years of working seniority (OR=8.91, 95% CI=(3.59,22.14), P<0.001). Thirdly, 10 to 19 days (OR=2.63, 95% CI=(1.19,5.82), P=0.017), 20 to 29 days (OR=161.31, 95% CI=(49.48,525.9), P<0.001). Lastly, more than 30 days (OR=92.05, 95% CI=(33.88,250.14), P<0.001) of working in the frontline of the novel coronavirus. Conclusion The prevalence of psychological problems and job burnout were at a high level among nurses working in the frontline of the novel coronavirus in different NAT sites. The nurses from NAT sites inside hospitals and temporary NAT sites in communities/towns in Zhangjiajie city had an equal risk of developing psychological problems and job burnout. Interventions need to be immediately implemented to promote psychological well-being and decrease job burnout of nurses.

The burden of being certain: National identity certainty predicts support for COVID-Related restrictive measures and outgroup conspiracy beliefs.

In dealing with the COVID-19 pandemic, government officials often encounter two concurrent concerns: they have to enforce necessary public health and safety measures to manage COVID-19. Meanwhile, they also have to mitigate conspiracy beliefs about COVID-19. To shed light on these issues, we conducted two studies to investigate national identity certainty (i.e., the extent to which people are certain about their national identity) as a predictor of (a) support for restrictive measures to curtail COVID-19 and (b) conspiracy beliefs about an outgroup as the culprit of COVID-19. Study 1 was a three-week longitudinal study (N = 301) where we investigated the relationships both on a between-person level (differences between individuals) and on a within-person level (week-by-week fluctuations of the same individual). We found that individual differences in national identity certainty predicted increased support for restrictive measures and increased outgroup conspiracy beliefs. These relationships emerged, even when we controlled for national identity positivity, that is, the extent to which people see their national identity in positive light. In Study 2 (N = 316), we used a cross-sectional correlational design and replicated the findings of Study 1. Moreover, we found that the relationships were explained by distinct threat perceptions: realistic threat explained the increased support for restrictive measures, whereas symbolic threat explained the increased outgroup conspiracy beliefs. Overall, our findings suggest that support for restrictive measures and outgroup conspiracy beliefs can be seen as attempts of people high in national identity certainty to address the distinct threats of COVID-19.

Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer.

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. This consortium has regularly held topic-focused biannual face-to-face symposiums. These meetings are a place to review cancer informatics and data science priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues that we faced at our respective institutions and cancer centers. Here, we provide meeting highlights from the latest CI4CC Symposium, which was delayed from its original April 2020 schedule because of the COVID-19 pandemic and held virtually over three days (September 24, October 1, and October 8) in the fall of 2020. In addition to the content presented, we found that holding this event virtually once a week for 6 hours was a great way to keep the kind of deep engagement that a face-to-face meeting engenders. This is the second such publication of CI4CC Symposium highlights, the first covering the meeting that took place in Napa, California, from October 14-16, 2019. We conclude with some thoughts about using data science to learn from every child with cancer, focusing on emerging activities of the National Cancer Institute's Childhood Cancer Data Initiative.