Who Is the Most Vulnerable to Anxiety at the Beginning of the COVID-19 Outbreak in China? A Cross-Sectional Nationwide Survey

Adverse Mental Health Sequelae of COVID-19 Pandemic in the Pregnant Population and Useful Implications for Clinical Practice

The COVID-19 pandemic has increased risk of disturbances in the functioning of everyday life, directly or indirectly has influenced the risk of mental disorders in the most vulnerable populations, including pregnant women. The aim of this study was to analyze adverse mental health effects in the pregnant population during the COVID-19 pandemic, investigate risk factors for adverse mental health outcomes, identify protective factors, and create practical implications for clinical practice, bearing in mind the need to improve perinatal mental healthcare during such pandemics. Qualitative research was conducted in the electronic databases PubMed and Web of Sciences for the keywords COVID-19, pregnancy, depression, anxiety, and telemedicine for relevant critical articles (n = 3280) published from 2020 until October 2021, outlining the outcomes of control studies, meta-analysis, cross-sectional studies, face-to-face evaluation survey studies, remotely administered survey studies, and observational studies regarding the main topic; all were evaluated. Mental health problems among pregnant women linked to the COVID-19 pandemic, in most cases, show symptoms of depression, anxiety, insomnia, and PTSD and may cause adverse outcomes in pregnancy and fetus and newborn development, even at later stages of life. Therefore, useful implications for clinical practice for improving the adverse mental health outcomes of pregnant women associated with the COVID-19 pandemic are highly desirable. Our research findings support and advocate the need to modify the scope of healthcare provider practice in the event of a disaster, including the COVID-19 pandemic, and may be implemented and adopted by healthcare providers as useful implications for clinical practice.

Privacy-Preserving Authentication Protocol for Wireless Body Area Networks in Healthcare Applications

Mobile healthcare service has become increasingly popular thanks to the significant advances in the wireless body area networks (WBANs). It helps medical professionals to collect patient’s healthcare data remotely and provides remote medical diagnosis. Since the health data are privacy-related, they should provide services with privacy-preserving, which should consider security and privacy at the same time. Recently, some lightweight patient healthcare authentication protocols were proposed for WBANs. However, we observed that they are vulnerable to tracing attacks because the patient uses the same identifier in each session, which could leak privacy-related information on the patient. To defeat the weakness, this paper proposes a privacy-preserving authentication protocol for WBANs in healthcare service. The proposed protocol is only based on one-way hash function and with exclusive-or operation, which are lightweight operations than asymmetric cryptosystem operations. We performed two rigorous formal security proofs based on BAN logic and ProVerif tool. Furthermore, comparison results with the relevant protocols show that the proposed protocol achieves more privacy and security features than the other protocols and has suitable efficiency in computational and communicational concerns.