Subtypes of work engagement in frontline supporting nurses during COVID-19 pandemic: A latent profile analysis.

AIM: The aim was to examine the subgroups of work engagement in frontline nurses during the COVID-19 pandemic. BACKGROUND: The pandemic may affect the work engagement of nurses who have direct contact with infected patients and lead to a poor quality of care. Identifying classification features of work engagement and tailoring interventions to support frontline nurses is imperative. DESIGN: This study utilized a cross-sectional study design. METHODS: Three hundred fifty-five nurses were enrolled in this cross-sectional study from 14 February to 15 April 2020. A latent profile analysis was performed to identify classification features of work engagement. Multiple logistic regression analyses were used to examine predictors of profile membership. RESULTS: A four-profile model provided the best fit. The four profiles were titled 'low work engagement' (n = 99), 'high vigour-low dedication and absorption' (n = 58), 'moderate work engagement' (n = 63) and 'high work engagement' (n = 135). A regression analysis suggested that young nurses and nurses who were the only children of their family were more likely to be in the 'low work engagement' and 'high vigour-low dedication and absorption' groups. CONCLUSION: This study highlights the importance of tailoring interventions for frontline supporting nurses by considering their distinct work engagement patterns, especially during the COVID-19 pandemic, to improve the promotion of work satisfaction and quality of care. IMPACT: This was the first study to explore the latent profiles of work engagement in frontline nurses during the COVID-19 pandemic. Over 40% of nurses were in the 'low work engagement' and 'high vigour-low dedication and absorption' groups and reported low levels of work engagement. Understanding different patterns of work engagement in frontline nurses can help nursing managers provide emotional, material and organizational support based on the features of each latent profile, which may improve the quality of care and patient safety.

The role of remote sensing during a global disaster: COVID-19 pandemic as case study.

Remotely sensed imagery is used as a tool to aid decision makers and scientists in a variety of fields. A recent world event in which satellite imagery was extensively relied on by a variety of stakeholders was the COVID-19 pandemic. In this article we aim to give an overview of the types of information offered through remote sensing (RS) to help address different issues related to the pandemic. We also discuss about the stakeholders that benefited from the data, and the value added by its availability. The content is presented under four sub-sections; namely (1) the use of RS in real-time decision-making and strategic planning during the pandemic; how RS revealed the (2) environmental changes and (3) social and economic impacts caused by the pandemic. And (4) how RS informed our understanding of the epidemiology of SARS-CoV-2, the pathogen responsible for the pandemic. High resolution optical imagery offered updated on-the-ground data for e.g., humanitarian aid organizations, and informed operational decision making of shipping companies. Change in the intensity of air and water pollution after reduced anthropogenic activities around the world were captured by remote sensing - supplying concrete evidence that can help inform improved environmental policy. Several economic indicators were measured from satellite imagery, showing the spatiotemporal component of economic impacts caused by the global pandemic. Finally, satellite based meteorological data supported epidemiological studies of environmental disease determinants. The varied use of remote sensing during the COVID-19 pandemic affirms the value of this technology to society, especially in times of large-scale disasters.