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Background/Objectives: This study was conducted to investigate the class satisfaction of dental hygiene students according to the class type due to COVID-19 and to reflux it to future education. Methods/Statistical analysis: The data collected in this study were analyzed using SPSS Window Ver 25.0, and the statistical significance determination was used at a significance level of less than 0.05. For analysis related to theory and practice class type by grade, descriptive statistics and Pearson's correlation coefficient were conducted, and an independent sample t-test was conducted for class satisfaction by class type. Logistic regression analysis was conducted on the effect of class form on class satisfaction. Findings: As a result of the study, 21 students (70.0%) in 2nd grade and 30 (38.5%) in 3rd grade were conducted in face-to-face practice (p<0.05), In the actual theoretical lecture format, 8 face-to-face lectures (26.7%) were conducted in the second grade, and 23 (29.5%) were mixed with real-time online lectures and online recorded lectures in the third grade (p<0.05). As a result of logistic regression analysis as dependent variable, the combination of face-to-face and real-time online lectures increased 43.392 times compared to real-time online lectures, and the combination of face-to-face and online recorded lectures decreased 0.030 times in theoretical lectures (p<0.05) compared to online recorded lecture. Improvements/Applications: In conclusion, in order to improve students' class satisfaction and academic achievement according to the change in class form due to Covid 19, it is necessary to develop various lecture types according to the delivery of theoretical lectures and practical lectures. For this, active development efforts of instructors and financial and administrative support of university resources will be required © 2023, Journal for ReAttach Therapy and Developmental Diversities.All Rights Reserved.
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Purpose: This integrative review aims to identify changes in people with schizophrenia during the COVID-19 pandemic. Methods: An integrative literature review method of Whittemore and Knafl was applied to integrate the studies. The literature search was conducted in six electronic databases using English and Korean search terms. Three researchers independently reviewed the extracted papers and rated their quality based on predetermined inclusion and exclusion criteria. A total of fifteen relevant studies were included. Results: The selected articles were all international papers, and most of them were quantitative studies. The changes observed in people with schizophrenia were summarized as follows: (1) changes in health outcomes: psychosocial (increased levels of depression, stress, anxiety, sleep disturbance, and psychotic-like experience) and physical (reduction in food intake, weight loss, changes in immune-related clinical values, etc.);(2) changes in treatment and health management: increased hospitalization, decreased ICU hospitalization, and a decrease in outpatient visits and prescription rate. Conclusion: This study confirmed the impacts of the COVID-19 pandemic on people with schizophrenia. It is necessary to develop mental health policies and appropriate nursing interventions to help people in preparing for possible future crises. ⓒ 2022.
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BACKGROUND: Children living with chronic comorbid conditions are at increased risk for severe COVID-19 disease, though there is limited evidence regarding the risks associated with specific conditions and which children may benefit from targeted COVID-19 therapies. Age-specific baseline indicators of COVID-19 severity are also needed to evaluate the effectiveness of SARS-CoV-2 vaccination strategies in the paediatric population. OBJECTIVE(S): In this study, we aimed to 1) identify factors associated with severe COVID-19 in children, and 2) describe rates of hospitalization, intensive care unit (ICU) admission, and severe COVID-19 within specific pediatric age groups. DESIGN/METHODS: We conducted a national prospective study on hospitalized children with microbiologically confirmed SARS-CoV-2 infection via the Canadian Paediatric Surveillance Program from March 2020-May 2021. Cases were reported voluntarily by a network of >2800 paediatricians and paediatric subspecialists. SARS-CoV-2 hospitalizations were classified as COVID-19-related, incidental infection, or infection control/social admissions. Severe disease was defined as intensive care, ventilatory or hemodynamic requirements, select organ system complications, or death. Outcomes were described among children aged <6 months, 6-23 months, 2-4 years, 5-11 years, and 12-17 years. Risk factors for severe disease were identified using multivariable Poisson regression, adjusting for child age and sex, coinfections, and timing of hospitalization. RESULT(S): We identified 541 children hospitalized with SARS-CoV-2 infection, including 329 (60.8%) with COVID-19-related disease. Median age at admission was 2.8 years (IQR 0.3-13.5) and 42.9% (n=232) had at least one comorbidity. Among COVID-19-related hospitalizations, severe disease occurred in 29.5% of children (n=97/329), including a higher proportion of children aged 2-4 years (48.7%) and 12-17 years (41.3%) (Table 1). Comorbidities associated with severe disease are described in Figure 1, and included technology dependence (adjusted risk ratio [aRR] 1.96, 95% confidence interval [CI] 1.31-2.95), neurologic conditions (e.g. epilepsy and chromosomal/genetic conditions) (aRR 1.87, 95% CI 1.34-2.61), and pulmonary conditions (e.g. bronchopulmonary dysplasia and uncontrolled asthma) (aRR 1.66, 95% CI 1.13-2.42). CONCLUSION(S): While severe outcomes were detected at all ages and among patients with and without comorbidities, neurologic and pulmonary conditions as well as technology dependence were associated with increased risk of severe COVID-19. Children aged 2-4 years more commonly experienced severe COVID-19 in this study, which was conducted at a time when no children were eligible for SARS-CoV-2 vaccines. Notably, this high-risk group remains without access to approved vaccines. These findings may help guide vaccination programs and prioritize targeted COVID-19 therapies for children.
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BACKGROUND: Throughout the COVID-19 pandemic, concerns have emerged regarding missed cases of child maltreatment. Evidence suggests an increased incidence of child maltreatment despite a documented decline in reports to child protective services. In Ottawa, reports dropped by 30-40% at the start of the pandemic in 2020. Pediatricians play an important role in the detection of child maltreatment and many have shifted from in person to virtual care. However, there is a paucity of published literature on this topic. We hypothesize that the shift to virtual visits is a barrier to identifying cases of child maltreatment and may contribute to missed cases. OBJECTIVE(S): Our survey assesses if and how Canadian pediatricians are identifying child maltreatment over virtual medical appointments, as well as the barriers and enabling factors to doing so. DESIGN/METHODS: The Canadian Paediatric Surveillance Program (CPSP) is a joint effort with the Canadian Paediatric Society and Public Health Agency of Canada towards national pediatric surveillance through monthly surveys to 95% of Canadian pediatricians. Using their infrastructure, a one-time survey was sent to 2770 pediatricians between November 2021 and January 2022 with data analyzed for qualitative themes and descriptive statistics. RESULT(S): There was a 34% response rate (n= 928) and 704 valid responses. Exclusions were for no provision of virtual care, incomplete surveys or no reported cases of child maltreatment in their career (n=93, 10%). The average number of years in independent practice was 17.5 years, and 69% had not provided virtual care prior to the pandemic. Based on a virtual visit, at least one case of child maltreatment was reported by 16% of physicians prior to the pandemic, and by 11% following March 2020. Nearly one-third (30%) of these cases required a subsequent in-person visit prior to making the report. Social stressors and clear disclosures from patients and caregivers were the main factors leading to reports. The virtual physical exam was not a factor that triggered concerns of maltreatment in any case. Respondents reported at a rate of 68% that it was slightly or much more difficult to detect child maltreatment over virtual visits. Concerns that a case had been missed or identified late in association with virtual care were reported by 29% of physicians (n=206) with some commenting that clear harm resulted. CONCLUSION(S): This survey shows that virtual medical care presents barriers to identifying child maltreatment and may be an important factor in missed cases of child maltreatment.
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A correlation between COVID-19 and Alzheimer's disease (AD) has been proposed recently. Although the number of case reports on neuroinflammation in COVID-19 patients has increased, studies of SARSCoV- 2 neurotrophic pathology using brain organoids have restricted recapitulation of those phenotypes due to insufficiency of immune cells and absence of vasculature. To overcome these limitations, we developed fused cortical-blood vessel organoids to provide blood vessels to brain organoids and obtained the characteristics of increased expression of glial cells and blood-brain barrier-like structures in brain organoids. Furthermore, we observed AD pathologies, including Abeta plaques, which were affected by the inflammatory response from SARS-CoV-2 infection. These findings provide an advanced platform to investigate human neurotrophic diseases, including COVID-19, and suggest that neuroinflammation caused by viral infection facilitates AD pathology.
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This study evaluated the characteristics of PM2.5 pollution and long-range atmospheric transport (LRAT) at the Baengnyeong and Jeju Air Quality Research Centers in South Korea during 2018~2020. The mean concentration of PM2.5 was constant in Baengnyeong but decreased in Jeju owing to COVID-19. The significant seasonal variations of OC, EC, and NO3- in Baengnyeong and Jeju with the highest concentrations in winter may be due to the influence of high PM2.5 episodes. Meanwhile, the concentrations of SO42- and NH4+ were constant throughout the year in Baengnyeong, resulting from regional inflow from surrounding areas. The influence of anthropogenic sources and secondary formation of PM2.5 increased in summer and decreased in autumn at both sites, which was also observed at other background sites. The dominance of NO3-, K+, and Cl- in Baengnyeong was due to the influence of combustion sources and LRAT. The source of SO42-, NH4+, V, and Ni in Jeju was identified as industrial activities with the highest contribution in summer. The secondary formation of PM2.5 with external inflow effects was dominant in Baengnyeong and Jeju. The main emission source area of PM2.5 for both Baengnyeong and Jeju was East China (Hebei, Shandong, Jangsu, and Anhui), but the chemical composition and sources of PM2.5 were different between Baengnyeong and Jeju. The result of this study can be a basis for future monitoring and modeling studies on the influence of LRAT in background areas. © 2022, Journal of Korean Society for Atmospheric Environment. All rights reserved.
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Tremendous efforts have been made to improve diagnosis and treatment of COVID-19, but knowledge on long-term complications is limited. In particular, a large portion of survivors has respiratory complications, but currently, experienced radiologists and state-of-the-art artificial intelligence systems are not able to detect many abnormalities from follow-up computerized tomography (CT) scans of COVID-19 survivors. Here we propose Deep-LungParenchyma-Enhancing (DLPE), a computer-aided detection (CAD) method for detecting and quantifying pulmonary parenchyma lesions on chest CT. Through proposing a number of deep-learning-based segmentation models and assembling them in an interpretable manner, DLPE removes irrelevant tissues from the perspective of pulmonary parenchyma, and calculates the scan-level optimal window, which considerably enhances parenchyma lesions relative to the lung window. Aided by DLPE, radiologists discovered novel and interpretable lesions from COVID-19 inpatients and survivors, which were previously invisible under the lung window. Based on DLPE, we removed the scan-level bias of CT scans, and then extracted precise radiomics from such novel lesions. We further demonstrated that these radiomics have strong predictive power for key COVID-19 clinical metrics on an inpatient cohort of 1,193 CT scans and for sequelae on a survivor cohort of 219 CT scans. Our work sheds light on the development of interpretable medical artificial intelligence and showcases how artificial intelligence can discover medical findings that are beyond sight. Respiratory complications after a COVID infection are a growing concern, but follow-up chest CT scans of COVID-19 survivors hardly present any recognizable lesions. A deep learning-based method was developed that calculates a scan-specific optimal window and removes irrelevant tissues such as airways and blood vessels from images with segmentation models, so that subvisual abnormalities in lung scans become visible.
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We propose a new modeling framework for evaluating the risk of disease transmission during a pandemic in small-scale settings driven by stochasticity in the arrival and service processes, that is, congestion-prone confined-space service facilities. We propose a novel metric, system-specific basic reproduction rate, inspired by the “basic reproduction rate” concept from epidemiology, which measures the transmissibility of infectious diseases. We derive our metric for various queueing models of service facilities by leveraging a novel queueing-theoretic notion: sojourn time overlaps. We showcase how our metric can be used to explore the efficacy of a variety of interventions aimed at curbing the spread of disease inside service facilities. Specifically, we focus on some prevalent interventions employed during the COVID-19 pandemic: limiting the occupancy of service facilities, protecting high-risk customers (via prioritization or designated time windows), and increasing the service speed (or limiting patronage duration). We discuss a variety of directions for adapting our transmission model to incorporate some more nuanced features of disease transmission, including heterogeneity in the population immunity level, varying levels of mask usage, and spatial considerations in disease transmission. © 2022 Production and Operations Management Society.
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The outbreak of the novel coronavirus, severe acute respiratory syndrome (SARS)-CoV-2, has gained unprecedented global attention. SARS-CoV-2, which causes the newly described coronavirus disease 2019 (COVID-19), has affected millions of people and led to over 1.9 million deaths worldwide by the beginning of January 2021. Several governments have opted for lockdown as one of the measures to combat the rapidly increasing number of COVID-19 cases. Academic institutions (i.e., universities, colleges, research centers and national laboratories), which are home to thousands of students, researchers, technicians, and administrative staff, have strictly followed government regulations. Due to the lockdown, the majority of academics have been facing various challenges, especially in transitioning from classroom to remote teaching and conducting research activities from a home office. This article from an early-career researchers' perspective addresses the common challenges that academic institutions have encountered and possible strategies they have adopted to mitigate those challenges at the individual organizational level. Furthermore, we propose a framework to facilitate the handling of such crisis in any near future at the organizational level. We hope academics, policymakers and (non) government organizations across the globe will find this perspective a call to better improve the overall infrastructure of academic institutions.
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The covid-19 pandemic has forced us to reevaluate how we deliver care to our patients. How do we balanceShelter in Place orders with the need to provide well child care and vaccines? We work in an FQHC and serve alargely immigrant Hispanic community, many of our patients' parents are migrant and seasonal farmworkers.We made many changes in our clinic to adapt to covid-19: an outdoor respiratory clinic and covid testing,telephone and telehealth visits to keep patients who are sick out of clinic, telephone outreach to addresssocial determinants of health (mainly food insecurity and housing), administering of free medications forthose uninsured patients who could no longer afford their medications. Throughout these changes to addressimmediate needs, we limited our well child visits to 2 years and under to protect our patients, our staff andour limited clinic resources. However, as we settled into this 'new normal', we quickly realized we needed arecovery plan to address the backlog of well child visits for all ages and vaccines that could be nimble enoughto withstand possibly repeated rounds of social distancing over the months to come. That is how the hybrid clinic model came into fruition. Our pediatrics team was committed to keeping our patients immunized and tosupport their growth and development during covid-19. We began reaching out to colleagues across the stateand country to nd out what others were doing, joined one of the AAP Covid-19 ECHO groups and researchingemerging best practices for how to deliver well child care during a pandemic. We brought the model to ourCovid-19 incident command team and to our frontline medical providers for feedback and ideas. Our currentwell child check model is in pilot stage and involves a combination of telephone and in person components.We are learning and innovating how to best serve our patients. As a Level 3 Patient Centered Medical Homeand a Federally Qualied Health Center, we already do quality improvement and quality assurance tracking onmany topics, including vaccines and well child visit adherence. We will continue to use data to monitor oursuccess with this model and make adjustments along the way as needed. The covid-19 pandemic is a globalchallenge affecting us all. Technology, specically telephone and telehealth services have allowed us toinnovate quickly on how to deliver care-both acute and preventive- to vulnerable populations. This time inhistory is highlighting the advances of hospital and ICU medicine to treat people suffering a new disease and,at the same time, it puts primary care into sharp focus as a critical safety net that must remain intact, evenduring a pandemic, to support our children. An initial overview to train medical providers on how we will approach well child visits in clinic during shelter inplace orders related to covid-19. Summary of Well Child Visits Table depicting how telephone technology will be used to limit the amount oftime the patient is physically in clinic while attempting to maximize adherence to Bright Futures.