PubMed COVID-19 Clinical Care

CONCLUSION: An integrated intervention combining communication, surveillance and telehealth, with a strong community engagement component, could reduce COVID-19 mortality and increase case detection in a large vulnerable community in Rio de Janeiro

CONCLUSION: This study offers valuable and insightful implications by combining the SSEIT, PCQ-24, and RBPS models to investigate the effect of emotional intelligence on job performance in Malaysia, which is an unusual combination model to analyse

Since the beginning of the COVID-19 pandemic, great efforts have been made by the academic community to better understand SARS-CoV-2 and COVID-19 features. COVID-19 has been demonstrated to affect several systems of the human body, including the

CONCLUSION: Poor practice of posture and computer ergonomics, despite the good knowledge and attitude is possibly due to the suboptimal work environments. Introducing simple practical measures to facilitate ergonomically appropriate work environments

CONCLUSION: Our study results suggest economic conditions and gender were major factors associated with experiencing violence among our sample of PWUD during COVID-19. These findings highlight criminalization of drug use and widespread socioeconomic

CONCLUSION: This study provided further insights into the liminal patient experiences of being isolated in the ICU due to COVID-19. Robust themes of experience were achieved through an in-depth phenomenological approach. Although, similarities in

Gross anatomy education utilizing body donors and human specimens assists the acquisition of non-traditional, discipline-independent skills (NTDIS) such as teamwork, communication, and leadership. Alterations to anatomy curricula, such as those

CONCLUSION: This study demonstrated that neither the chatbot nor the webinar changed VI importantly compared with control. Interactive webinars could be an effective tool to change vaccine confidence. Further study is needed to identify risk factors

CONCLUSION: Parental anxiety and depression caused by the COVID-19 pandemic and lockdown resulted in decreased attention to childcare, leading to increased accidental ingestion of harmful materials among paediatric forensic cases admitted to the

In this work, we aim to accurately predict the number of hospitalizations during the COVID-19 pandemic by developing a spatiotemporal prediction model. We propose HOIST, an Ising dynamics-based deep learning model for spatiotemporal COVID-19