Primary students' online homework completion and learning achievement

Online homework has become an important teaching and learning activity due to the impact of COVID-19 pandemic-related restrictions. This study explored the relationship between primary students' online homework completion and learning achievement. It also investigated the moderating effects of key factors including the role of the students and the involvement of their parents on this relationship. Based on a total of 3,210 Chinese online homework assigned in the Spring of 2020 to fourth grade primary school students in Wuhan, China, hierarchical linear modeling was employed to examine the relationship between primary students' online homework completion and their learning achievement. Simultaneously, the effects of potential moderators including students' information literacy, students' prior academic achievement, parental digital self-efficacy, and parent - teacher partnership were investigated. The results showed a significant positive effect of students' online homework completion on learning achievement. Moreover, students' information literacy, students' prior achievement, and parent - teacher partnership positively moderated this relationship. Based on the findings, practical implications for school administrators, teachers, and parents are discussed herein to promote online homework completion and enhance students' learning achievement. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Impact of information literacy, self-directed learning skills, and academic emotions on high school students' online learning engagement: A structural equation modeling analysis.

The adoption of online learning for adolescent students accelerated with the outbreak of the COVID-19 pandemic. However, few studies have investigated the mechanisms influencing adolescent students' online learning engagement systematically and comprehensively. This study applied the Presage-Process-Product (3P) model of learning to investigate the direct effects of presage factors (i.e., information literacy and self-directed learning skills) and process factors (i.e., academic emotions) on high school students' online learning engagement; and the mediating role of process factors. Data from 1993 high school students in China (49.3% males and 50.7% females) were analyzed using structural equation modeling. The result showed that students' information literacy, self-directed learning skills, and positive academic emotions positively predicted their online learning engagement. Moreover, the positive impact of self-directed learning skills on students' online learning engagement was significantly and largely enhanced through the mediation effects of positive academic emotions (ß = 0.606, 95% CI = [0.544, 0.674]). Based on these results, to enhance adolescent students' online learning engagement, it is important for school administrators, teachers, and parents to improve students' information literacy, self-directed learning skills, and positive academic emotions.

Impact of information literacy, self-directed learning skills, and academic emotions on high school students' online learning engagement: A structural equation modeling analysis

The adoption of online learning for adolescent students accelerated with the outbreak of the COVID-19 pandemic. However, few studies have investigated the mechanisms influencing adolescent students' online learning engagement systematically and comprehensively. This study applied the Presage-Process-Product (3P) model of learning to investigate the direct effects of presage factors (i.e., information literacy and self-directed learning skills) and process factors (i.e., academic emotions) on high school students' online learning engagement;and the mediating role of process factors. Data from 1993 high school students in China (49.3% males and 50.7% females) were analyzed using structural equation modeling. The result showed that students' information literacy, self-directed learning skills, and positive academic emotions positively predicted their online learning engagement. Moreover, the positive impact of self-directed learning skills on students' online learning engagement was significantly and largely enhanced through the mediation effects of positive academic emotions (AN - PMC10061396

Patients' satisfaction on primary healthcare services in China and its associated factors during COVID-19 pandemic: A cross-sectional study.

Introduction: The provision of a satisfactory service by community healthcare centres in China plays an important role in the prevention and control of communicable diseases, especially during the COVID-19 pandemic. However, there is a lack of study in this field. This study aimed to determine the level of patient satisfaction with primary healthcare services in China and its associated factors during the COVID-19 pandemic. Method: This cross-sectional study was conducted at 10 primary healthcare clinics in Xi'an, China. The 18-Item Patient Satisfaction Questionnaire was used for data evaluation and SPSS version 23.0 for data analysis. Results: A total of 315 patients were recruited. The overall patient satisfaction score was 26.1±3.1. In the multiple linear regression analysis, the highly educated patients had a higher patient satisfaction score than the low-educated patients (ß=1.138, 95% confidence interval=0.135-2.141, P=0.026). Conclusion: The overall patient satisfaction level of the patients who attended community healthcare centres in Xi'an was high. The patients with a higher educational level showed a higher patient satisfaction level than did those with a lower educational level.

Outbreak of acute respiratory disease caused by human adenovirus type 7 and human coronavirus-229E in Zhejiang Province, China.

In 2019, an outbreak of pharyngoconjunctival fever (PCF) occurred at a swimming center in Zhejiang Province, China. A total of 97 (13.55%) of the 716 amateur swimmers had illnesses, with 24 patients (24.74%) hospitalized in the pediatric ward. Human adenovirus serotype 7 (HAdV-7) was isolated from one concentrated water from the swimming pool, and 20 of 97 positive cases without liver damage. This outbreak led to a nosocomial outbreak in the pediatric ward, in which 1 nurse had a fever and was confirmed to be adenovirus positive. The hexon, fiber, and penton genes from 20 outbreak cases, 1 water sample, and 1 nurse had 100% homology. Furthermore, 2 cases admitted to the pediatric ward, 2 parents, and 1 doctor were confirmed to be human coronaviruses (HCoV-229E) positive. Finally, all outbreak cases had fully recovered, regardless of a single infection (adenovirus or HCoV-229E) or coinfection of these two viruses simultaneously. Thus, PCF and acute respiratory disease outbreaks in Zhejiang were caused by the completely homologous type 7 adenovirus and HCoV-229E, respectively. The swimming pool water contaminated with HAdV-7 was most likely the source of the PCF outbreak, whereas nosocomial transmission might be the source of HCoV-229E outbreak.

Epidemiology and pathogen profile of Kawasaki disease from a single center in China, 2018-2020

Background: It has been reported that the infections have played an important role in the pathogenesis for pediatric rheumatic diseases. The COVID-19 had the impact on the frequency of these diseases and led to a remarkable decrease of them, which confirmed the role of infections in these diseases. Objectives: To investigate the epidemiologic characteristics and pathogen profile of Kawasaki disease(KD) from a single center in China from 2018 to 2020 during the Coronavirus Disease 2019 (COVID-19) pandemic period.

Multisystem inflammatory syndrome (MIS-C) with SARS-CoV-2 omicron variant BA.2.38 in a four-year-old Chinese girl: A case report.

We report a severe COVID-19 complicated with MIS-C in a girl treated by the author in China, and discuss the current research status and progress in the diagnosis and therapy of MIS-C in children. The patient was a 4-year-old child previously healthy who was referred to the hospital with a complaint of fever, finally, Multisystem inflammatory syndrome was diagnosed with COVID-19.

A Rebuilding-Free Nucleic Acid Detection Strategy Enables Ultrasensitive Genotyping, N-in-1 Logic Screening and Accurate Multiplex Assay of Dangerous Pathogens.

Sensitive, rapid and low-cost nucleic acid detection is critical for controlling infectious pathogens. Here, we develop a ready-to-use and multimodal detection based on a rebuilding-free, ultrasensitive and selective strategy named dual hairpin ligation-induced isothermal amplification pro (DHLApro). Taking influenza A, influenza B, MERS-CoV, SARS-CoV-2 as model targets, we demonstrate DHLApro provides ≈zM level ultra-sensitivity, being equaling to 0.45 copy/µL in original sample. By simply changing the recognition module, a set of DHLApro components can be applied to a new target without performance loss. Moreover, DHLApro innovatively allows flexible logic/multiplex assay using one set of primer, for example, the "N pathogens-in-1" OR gate screening and accurate multi-channel multiplex assay. Compared with traditional methods, the cost of this logic/multiplex assay has been largely reduced and the cross-interference between the multiple primer sets is also avoided.

Prediction of potential severe coronavirus disease 2019 patients based on CT radiomics: A retrospective study.

PURPOSE: Coronavirus disease 2019 (COVID-19) is a recently declared worldwide pandemic. Triaging of patients into severe and non-severe could further help in targeted management. "Potential severe patients" is a category of patients who did not have severe symptoms at their initial diagnosis, but eventually progressed to be severe patients and are easily overlooked in the early stage. This work aimed to develop and evaluate a CT-based radiomics signature for the prediction of these potential severe COVID-19 patients. METHODS: One hundred fifty COVID-19 patients were enrolled and randomly divided into cross-validation and independent test sets. First, their clinical characteristics were screened using the univariate and multivariate logistic regression step by step. Then, radiomics features were extracted from the lesions on their chest CT images. Subsequently, the inter- and intra-class correlation coefficients (ICC) analysis, minimum-redundancy maximum-relevance (mRMR) selection, and the least absolute shrinkage and selection operator (LASSO) algorithm were used step by step for feature selection and construction of a radiomics signature. Finally, the screened clinical risk factors and constructed radiomics signature were combined for the combined model and Radiomics+Clinics nomogram construction. The predictive performance of the Radiomics and Combined models were evaluated and compared using receiver operating characteristic curve (ROC) analysis, Hosmer-Lemeshow test and Delong test. RESULTS: Clinical characteristics analysis resulted in the screening of five clinical risk factors. The combination of ICC, mRMR, and LASSO methods resulted in the selection of ten radiomics features, which made up of the radiomics signature. The differences in the radiomics signature between the potential severe and non-severe groups in cross-validation set and test sets were both p < 0.001. All Radiomics and Combined models showed a very good predictive performance with the accuracy and AUC of nearly or above 0.9. Additionally, we found no significant difference in the predictive performance between these two models. CONCLUSIONS: A CT-based radiomics signature for the prediction of potential severe COVID-19 patients was constructed and evaluated. Constructed Radiomics and Combined model showed good feasibility and accuracy. The Radiomics+Clinical nomogram, acted as a useful tool, may assist clinicians to better identify potential severe cases to target their management in the COVID-19 pandemic prevention and control.

Risk factors of severe and critical patients with COVID-19 in Hubei, China. (Special Issue: Spatio-temporal dynamics analysis, risk assessment and emergency management for COVID-19 epidemic.) [Chinese]

Objective: To investigate the risk factors of severe and critical patients with coronavirus disease 2019(COVID-19)in Hubei, China. Methods All patients with COVID-19 registered in the National Legal Infectious Disease Reporting System of Hubei Provincial Center for Disease Control and Prevention, as of March 18, 2020, were recruited. According to the symptoms, the patients were divided into two groups: mild/moderate patients and severe/critical patients. Their general characteristics were described, and the risk factors of severe and critical patients with COVID-19 were explored by using a Logistic regression model. Results A total of 48 814 cases were included, of which 38 730 were mild/moderate patients and 10 084 were severe/critical patients. The median age was 54(41, 65)years. Multivariate analysis showed that the elderly, male, home workers, people in Wuhan City, migrants, longer interval between onset and diagnosis, low temperature, higher concentrations of PM2.5/PM10/SO2/O3 increased the risk of severe/critical diagnosis in patients with COVID-19. Conclusion The elderly, male, home workers, people in Wuhan City, migrants, longer interval between onset and diagnosis, low temperature, and air pollution exposure are risk factors for severe/critical COVID-19 patients. More attention should be paid to people with these characteristics.

How Policy Mix Choices Affect the COVID-19 Pandemic Response Outcomes in Chinese Cities: An Empirical Analysis.

Since January 2020, the COVID-19 pandemic has caused millions of deaths and has posed a major public health threat worldwide. Such a massive and complex crisis requires quick and comprehensive policy responses. We developed an empirical dataset of policy mixes that included 4915 policies across 36 Chinese cities and investigated the relationships between the policy design choices and the COVID-19 pandemic response outcomes of a city. Using topic modeling and ordinary least squares regression analysis, we found considerable variation among cities in the compositions and design features of their policy mixes. Our analysis revealed that restriction measures did not significantly influence limiting the spread of the pandemic, but they were negatively correlated with the economic growth rate. By contrast, health protection measures greatly contributed to controlling viral spread. Intensive socioeconomic support reduced the occurrence of secondary disasters. The most effective policy strategy to deal with the COVID-19 pandemic appears to be a comprehensive policy design with a mix of restrictions, health protection measures, and socioeconomic support policies accompanied by a timely lockdown. Our empirical findings can help to improve pandemic policy design and contribute to generating broader lessons for how local governments should deal with similar crises in the future.

A genetic variant in IL-6 lowering its expression is protective for critical patients with COVID-19.

Critical coronavirus disease 2019 (COVID-19) is associated with high mortality and potential genetic factors have been reported to be involved in the development of critical COVID-19. We performed a genome-wide association study to identify the genetic factors responsible for developing critical COVID-19. 632 critical patients with COVID-19 and 3021 healthy controls from the Chinese population were recruited. First, we identified a genome-wide significant difference of IL-6 rs2069837 (p = 9.73 × 10-15, OR = 0.41) between 437 critical patients with COVID-19 and 2551 normal controls in the discovery cohort. When replicated these findings in a set of 195 patients with critical COVID-19 and 470 healthy controls, we detected significant association of rs2069837 with COVID-19 (p = 8.89 × 10-3, OR = 0.67). This variant surpassed the formal threshold for genome-wide significance (combined p = 4.64 × 10-16, OR = 0.49). Further analysis revealed that there was a significantly stronger expression of IL-6 in the serum from patients with critical COVID-19 than in that from patients with asymptomatic COVID-19. An in vitro assay showed that the A to G allele changes in rs2069837 within IL-6 obviously decreased the luciferase expression activity. When analyzing the effect of this variant on the IL-6 in the serum based on the rs2069837 genotype, we found that the A to G variation in rs2069837 decreased the expression of IL-6, especially in the male. Overall, we identified a genetic variant in IL-6 that protects against critical conditions with COVID-19 though decreasing IL-6 expression in the serum.

Mendelian randomization study on the causal effects of COVID-19 on childhood intelligence.

Although individuals with coronavirus disease 2019 (COVID-19) are known to be at increased risk for other conditions resulting from pathogenic changes (including metaplastic or anaplastic) in the lungs and other organs and organ systems, it is still unknown whether COVID-19 affects childhood intelligence. The present two-sample Mendelian randomization study aims to identify the genetic causal link between COVID-19 and childhood intelligence. Four COVID-19 genetic instrumental variants (IVs) were chosen from the largest genome-wide association studies (GWAS) for COVID-19 (hospitalized vs. population) (6406 cases and 902 088 controls of European ancestry). The largest childhood intelligence GWAS (n = 12 441 individuals of European ancestry) was used to evaluate the effect of the identified COVID-19-associated genetic IVs on childhood intelligence. We found that as the genetic susceptibility to COVID-19 increased, childhood intelligence followed a decreasing trend, according to mr_egger (ß = -0.156; p = 0.601; odds ratio [OR] = 0.856; 95% confidence interval [CI]: 0.522-1.405), simple mode (ß = -0.126; p = 0.240; OR = 0.882; 95% CI: 0.745-1.044), and weighted mode (ß = -0.121; p = 0.226; OR = 0.886; 95% CI: 0.758-1.036) analyses. This trend was further demonstrated by the weighted median (ß = -0.134; p = 0.031; OR = 0.875; 95% CI: 0.774-0.988) and the inverse variance weighted (ß = -0.152; p = 0.004; OR = 0.859; 95% CI: 0.776-0.952). Our analysis suggests a causal link between genetically increased COVID-19 and decreased childhood intelligence. Thus, COVID-19 may be a risk factor for declines in childhood intelligence.

Which urban communities are susceptible to COVID-19? An empirical study through the lens of community resilience.

BACKGROUND: After the lockdown of Wuhan on January 23, 2020, the government used community-based pandemic prevention and control as the core strategy to fight the pandemic, and explored a set of standardized community pandemic prevention measures that were uniformly implemented throughout the city. One month later, the city announced its first lists of "high-risk" communities and COVID-19-free communities. Under the standardized measures of pandemic prevention and mitigation, why some communities showed a high degree of resilience and effectively avoided escalation, while the situation spun out of control in other communities? This study investigated: 1) key factors that affect the effective response of urban communities to the pandemic, and 2) types of COVID-19 susceptible communities. METHODS: This study employs the crisp-set qualitative comparative analysis method to explore the influencing variables and possible causal condition combination paths that affect community resilience during the pandemic outbreak. Relying on extreme-case approach, 26 high-risk communities and 14 COVID-19 free communities were selected as empirical research subjects from the lists announced by Wuhan government. The community resilience assessment framework that evaluates the communities' capacity on pandemic prevention and mitigation covers four dimensions, namely spatial resilience, capital resilience, social resilience, and governance resilience, each dimension is measured by one to three variables. RESULTS: The results of measuring the necessity of 7 single-condition variables found that the consistency index of "whether the physical structure of the community is favorable to virus transmission" reached 0.9, which constitutes a necessary condition for COVID-19 susceptible communities. By analyzing the seven condition configurations with high row coverage and unique coverage in the obtained complex solutions and intermediate solutions, we found that outbreaks are most likely to occur in communities populated by disadvantaged populations. However, if lacking spatial-, capital-, and governance resilience, middle-class and even wealthy communities could also become areas where COVID-19 spreads easily. CONCLUSIONS: Three types of communities namely vulnerable communities, alienated communities, and inefficient communities have lower risk resilience. Spatial resilience, rather than social resilience, constitutes the key influencing factor of COVID-19-susceptible communities, and the dual deficiencies of social resilience and governance resilience are the common features of these communities.

New laboratory evidence for the association between endothelial dysfunction and COVID-19 disease progression.

There is growing evidence that angiotensin-converting enzyme 2 is highly expressed on endothelial cells, endothelial dysfunction plays a critical role in coronavirus disease 2019 (COVID-19) progression, but laboratory evidence is still lacking. This study established a multicenter retrospective cohort of 966 COVID-19 patients from three hospitals in Wuhan, China. We found that male (62.8% vs. 46.5%), old age [72 (17) vs. 60.5 (21)], and coexisting chronic diseases (88.5% vs. 60.0%) were associated with poor clinical prognosis in COVID-19. Furthermore, the deteriorated patients exhibited more severe multiorgan damage, coagulation dysfunction, and extensive inflammation. Additionally, a cross-sectional study including 41 non-COVID-19 controls and 39 COVID-19 patients assayed endothelial function parameters in plasma and showed that COVID-19 patients exhibited elevated vascular cell adhesion molecule-1 (VCAM-1) (median [IQR]: 0.32 [0.27] vs. 0.17 [0.11] µg/ml, p < 0.001), E-selectin (21.06 [12.60] vs. 11.01 [4.63] ng/ml, p < 0.001), tissue-type plasminogen activator (tPA) (0.22 [0.12] vs. 0.09 [0.04] ng/ml, p < 0.001), and decreased plasminogen activator inhibitor-1 (0.75 [1.31] vs 6.20 [5.34] ng/ml, p < 0.001), as compared to normal controls. Moreover, VCAM-1 was positively correlated with d-dimer (R = 0.544, p < 0.001); tPA was positively correlated with d-dimer (R = 0.800, p < 0.001) and blood urea nitrogen (R = 0.638, p < 0.001). Our findings further confirm the strong association between endothelial dysfunction and poor prognosis of COVID-19, which offers a rationale for targeting endothelial dysfunction as a therapeutic strategy for COVID-19.

Emergent Virus Reactivation in SARS-CoV-2-Negative Community Acquired Pneumonia Patients During the COVID-19 Pandemic

Emergent viruses (namely, HSV-1, CMV, and EBV) reactivation were common in critically ill patients and/or immunosuppressed patients. This study aimed to understand the clinical manifestations and reactivation of the emergent viruses in SARS-CoV-2-Negative community acquired pneumonia (CAP) patients during the COVID-19 pandemic. We retrospectively reviewed the medical records of CAP patients from January to March 2020, in our university hospital in China. The patients were divided into two groups based on the presence or absence of emergent viruses. In all patients, the positive rates of EBV, HSV, and CMV were 23.43% (15/64), 22.06% (15/68), and 12.50% (8/64), respectively. The most common presenting symptoms were fever (98, 57.99%) and dry cough (55, 32.54%). The levels of albumin, hemoglobin, lymphocyte count, and CD4 + T lymphocyte count in emergent viruses positive group were lower than those of viruses negative group (P < 0.05). The initial chest CT features of these patients were diverse. The most common manifestations were ground-glass opacity (91/169, 53.85%) and pulmonary nodule (88/169, 52.07%). More emergent viruses positive patients have bilateral upper lobes involvement than emergent viruses negative patients (P < 0.05). A total of 80.47% patients (136/169) received empirical antimicrobial treatment. The most commonly used antibiotic regimen was fluoroquinolone monotherapy (80/169, 47.34%). The emergent viruses positive patients have poorer clinical outcome (P < 0.05). In conclusion, emergent viruses reactivation was common in SARS-CoV-2-Negative CAP patients. Emergent viruses positive patients have poorer cellular immune function, more severer conditions and poorer prognosis. Fluoroquinolones may be a therapeutic option for CAP patients.

Emergency care and the patient experience: Using sentiment analysis and topic modeling to understand the impact of the COVID-19 pandemic.

The COVID-19 pandemic has presented many unique challenges to patient care especially in emergency medicine. These challenges result in an altered patient experience. Patient experience refers to the cumulative impression made on patients during their medical visit and is measured by a standardized survey tool. Patient experience is considered a key measure of quality of care. The volume of survey data received makes it difficult to spot trends and concerns in patient comments. Topic modeling and sentiment analysis are well documented analytic techniques that can be used to gain insight into patient experience and make sense of vast quantities of data. This study examined three periods of time, pre, during and post-COVID-19 first wave in order to identify key trends in sentiment and topics related to patient experience. Previously collected, anonymized Press Ganey (PG) survey data was used from three northeastern emergency department that make up an academic emergency department. Data was collected for three contiguous time periods: Pre-COVID-19 (12/10/2019- 3/10/2020), During COVID-19: (3/11/2020-6/10/2020), and Post-first wave COVID-19 (6/11/2020- 9/10/2020). Preprocessing of the data was carried out then a sentiment label (i.e., positive, negative, neutral, mixed) was assigned by the tool. These labels were used to assess the validity of Press Ganey labels. Next, a topic modeling approach from machine learning was used to analyze the contents of the patient comments and uncover concerns and perceptions of patient experiences. Themes that emerged from the analysis of patient comments included concerns over personal safety and exposure to the virus, exclusion of family from decision making and care and high levels of scrutiny over systems issues, care, and treatment protocols. Topic modeling showed shifting priorities and concerns throughout the three periods examined. Prior to the pandemic, patient comments were largely positive and focused on technical expertise and perceptions of competence. New topics and concerns that patients reported relevant to the pandemic were identified during-COVID-19. Comments on systems issues regarding processes to limit viral spread and concerns over family/visitor restrictions were dominant. Although there was evidence of praise and appreciation of the efforts of staff there was also a high level of scrutiny of the processes encountered during the emergency visit. Sentiment analysis and topic modeling offer a unique method for organizing and analyzing the shifting concerns of patients and families. Suggestions of interventions are made to address these evolving concerns. The automation of analysis using artificial intelligence would allow for rapid and accurate analysis of patient feedback.