PubMed COVID-19 Clinical Care

No abstract

CONCLUSIONS: During the COVID-19 pandemic, a significant proportion (>50%) of patients self-cancelled their appointments and nearly a quarter of patients discontinued their medications. Providing a documentation of the problems experienced by

CONCLUSIONS: Preventive measures and early detection of nosocomial outbreaks of COVID-19 should be prioritized to minimize the negative impact of this infection.

CONCLUSION: In our cohort, patients with lower health literacy scores, older and male patients, or who have poor internet access showed a lower level of technological comfort. At risk patients can be identified and provided additional support in

Internet gaming disorder (IGD) and problematic internet use (PIU) are becoming increasingly detrimental to modern society, with serious consequences for daily functioning. IGD and PIU may be exacerbated by lifestyle changes imposed by the coronavirus

CONCLUSION: La pandémie de la COVID-19 amplifie les iniquités structurelles. Les réfugiés et les nouveaux arrivants nécessitent et méritent des soins de santé et du soutien efficaces durant ces moments éprouvants. Cet article présente des approches

The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology

CONCLUSIONS: These data indicate that once patients were hospitalized, the risk of dying was similar between females and males. Therefore, future studies should aim at understanding the reasons why, for a given number of SARS-CoV-2 infections, fewer

CONCLUSION: The findings suggested that the spatial dynamics have an important role in the COVID-19 epidemic process since the results provided evidence that spatiotemporal models are more accurate to estimate the general patterns of the occurrence

This study tested the utility of the Risk Information Seeking and Processing (RISP) model in understanding why people seek or avoid online information about COVID-19. Data collected at three different time points (i.e., February, April, and May 2020)