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The aim of the study to examine the level of psychological distress among nursing students volunteering in Covid-19 frontline prevention in Vietnam and related factors. Nursing students volunteering in frontline prevention presented emotional effects, including positive and negative effects on their psychological well-being. A cross-sectional study design was used and four hundred seventy-one students who volunteered for frontline prevention were randomly selected in the study using inclusion criteria. Data were collected from October to December 2021. A demographic questionnaire, the General Self-Efficacy Scale, the 6-item Kessler Psychological Distress Scale, the Brief Coping Orientation to Problems Experienced Inventory Questionnaire, and the Quality of life EQ-5D-5L were used to measure the variables. The data analysis was conducted by using descriptive statistics and linear regression. The research found that students presented a high risk of psychological distress. There was a significant correlation between problem-and emotional-coping strategies, quality of life, and psychological distress. Moreover, family support and psychological distress among nursing students had a strong relationship. Lecturers and high education institutions responsible for nursing students should pay more attention to developing psychological interventions in enhancing coping strategies and quality of life and various supports to reduce distress among nursing students fighting the epidemic.
ABSTRACT
The aim of the study to examine the level of psychological distress among nursing students volunteering in Covid-19 frontline prevention in Vietnam and related factors. Nursing students volunteering in frontline prevention presented emotional effects, including positive and negative effects on their psychological well-being. A cross-sectional study design was used and four hundred seventy-one students who volunteered for frontline prevention were randomly selected in the study using inclusion criteria. Data were collected from October to December 2021. A demographic questionnaire, the General Self-Efficacy Scale, the 6-item Kessler Psychological Distress Scale, the Brief Coping Orientation to Problems Experienced Inventory Questionnaire, and the Quality of life EQ-5D-5L were used to measure the variables. The data analysis was conducted by using descriptive statistics and linear regression. The research found that students presented a high risk of psychological distress. There was a significant correlation between problem-and emotional-coping strategies, quality of life, and psychological distress. Moreover, family support and psychological distress among nursing students had a strong relationship. Lecturers and high education institutions responsible for nursing students should pay more attention to developing psychological interventions in enhancing coping strategies and quality of life and various supports to reduce distress among nursing students fighting the epidemic.Copyright © 2022 Mohan R, et al.
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Four waves of the Covid-19 epidemic have drastically affected consumer behaviors in Vietnam, particularly during the period of social distancing in the second half of 2021. This study was done to investigate changes in household food acquisition and consumption patterns in Ho Chi Minh City. During the most severe wave of Covid-19 in Vietnam, an online poll was used to collect data from 130 customers in Ho Chi Minh City. Before Covid-19 (before January 2021), food was primarily purchased from traditional markets and other direct methods. After Covid-19 occurred (since January 2021), changes in food acquisition methods were found as 52% of respondents went to the grocery stores, traditional markets, and supermarkets less often. Moreover, consumers have changed their online shopping behaviors as 48% bought more food online compared to pre-Covid-19 periods. Since Covid-19, surveyed households consumed less food, specifically fresh produce (44.6%), fast food (60.8%), canned food (37.7%), prepped meals (60.8%), grains (43.1%), and snacks (43.8%). In opposition, more frozen foods (46%) and more meat (47%) were consumed since the pandemic. From the estimated ordinal probit regression, the study found that the determinants that most explain changes in food consumption are age, household size, education, income, affected income, workplace status, and the afraid of food shortage.
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Tiktok rose in the COVID-19 pandemic as a platform for video-sharing that ensures community connection and prevention of pessimism during social distancing. It is of special importance to thoroughly understand its potential in providing information and lockdown optimism, and its potential to cause harm on impressionable young users who occupy a great part of the Tiktok community. This research is implemented in order to learn more about young users' behaviours and their reaction towards common Tiktok contents which depict Tiktok impacts. We developed a survey using both quantitative and qualitative questions, concentrating on user habits, well-known content categories on Vietnamese Tiktok and how they may affect users' perception. 253 participants aged 16-22 in Mekong Delta, Vietnam were involved. Data revealed that young users had higher awareness of toxic contents than was assumed by previous academic works, and eager to diminish these harms. Qualitative answers provided notions about several toxic and inappropriate contents that were not previously addressed. The research also noticed a slight hint of "Tiktok prejudice"which was the fixed concept that Tiktok was negative, inspiring future extensive research. © 2022 ACM.
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We offered blended learning models for high schools in Nam Dinh province to satisfy Vietnam's new criteria. These models were based on general approaches to issues, theoretical research, and field research based on surveys and anket questionnaires conducted throughout the area. The results of a survey demonstrate that high school teachers in Nam Dinh have gained a fundamental grasp of blended learning and have, in practice, embraced both online and face-to-face instruction, particularly during the height of the Covid-19 outbreak. However, there was not a standard model for blended learning, therefore it was only used by a few persons. In other contexts, the concept of "blended learning" referred to what was effectively a face-to-face session that was broadcast over the Internet without the necessary adjustments being made to the content, methodology, or evaluation. As a result, we offer a number of different ways to blended learning for high schools in Nam Dinh in order to improve the quality of education provided throughout the province.
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Plastic pollution is a global issue, seriously affecting soil by preventing oxygen intake and causing soil erosion and degradation. The outbreak of COVID-19 has worsened the plastic pollution from traditional plastic face masks. This phenomenon demands that the community and stakeholders should take action to reduce “white pollution”. At the same time, million of tons of agricultural garbage, mainly rice straw and sugarcane garbage, were produced in the Asian region causing difficulties in treatment. Most of them were burned in the field, releasing tiny particles of PM 2.5 and air pollutants. This paper aims to transform cellulose material wastes, particularly rice straws and sugarcane bagasse, into bio-plastic products that can replace traditional degradable plastics. Several steps were conducted to extract the maximum mass of cellulose from agricultural residue. To minimize the chemical use, a new approach in the repreparation steps was achieved by integrating cellulose extracted from Bacillus subtilis. Different ratios of adding chemicals and processes were applied to form and mold plastic film. The new bioplastic materials generated from rice straw and sugarcane garbage exhibit excellent mechanical properties with tensile strength from 10 to 42 MPa. The elongation was from 25 % to 100 % in different ratios of plasticizers and types of cellulose material. The morphology of bio-plastic was investigated by scanning electron microscopy (SEM) and showed a uniform and compact structure. The changing functional groups were analyzed by infrared spectrum IR. The results showed that different methods of extraction and molding would produce bio-plastic with other properties. Bioplastic from agricultural waste is a high-potential plastic for various applications. This result will help reduce traditional plastic pollution and CO2 emissions to the atmosphere by burning agriculture residue, thereby contributing to the Sustainable Development Goals of The United Nations. © 2022, Publishing House of Natural Science and Technology, VAST. All rights reserved.
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Resit exams permit students who have failed a subject to sit a supplementary exam to demonstrate achievement of the academic standards required for program progression. This study analyses student perceptions of the strengths and limitations of resit exams during a pandemic and discusses their potential role in Australian Higher Education. The data were obtained from student performance metrics, questionnaires, and focus groups. Students acknowledged the pedagogical and psychological benefits of resit exams within the context of the challenges posed by exam thresholds, high-stakes summative exams, and the COVID-19 pandemic. Students questioned whether the imposition of exam thresholds and high-stakes summative exams adequately supported their learning and accurately measured their performance. © 2022 Elsevier Ltd. All rights reserved.
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Corona Virus and Conspiracies Multimedia Analysis Task is the task in MediaEval 2021 Challenge that concentrates on conspiracy theories that assume some kind of nefarious actions related to COVID-19. Our HCMUS team performs different approaches based on multiple pretrained models and many techniques to deal with 2 subtasks. Based on our experiments, we submit 5 runs for subtask 1 and 1 run for subtask 2. Run 1 and 2 both introduces BERT[5] pretrained model but the difference between them is that we add a sentimental analysis to extract semantic feature before training in the first run. In run 3 and 4, we propose a naive bayes classifier[4] and a LSTM[8] model to diversify our methods. Run 5 ultilize an ensemble of machine learning and deep learning models - multimodal approach for text-based analysis[3]. Finally, in the only run in subtask 2, we conduct a simple naive bayes algorithm to classify those theories. In the final result, our method achieves 0.5987 in task 1, 0.3136 in task 2. Copyright 2021 for this paper by its authors.
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Background: Concerns about safety and treatment interference are known barriers to COVID-19 vaccination in cancer patients. Data on safety and tolerability in this population remain scarce. One of the objectives of this study is to describe COVID-19 vaccination safety in cancer patients. Methods: Patients diagnosed with a malignancy requiring systemic treatment in the last 12 months and undergoing COVID-19 vaccination were prospectively enrolled in this single-center study. Validated questionnaires to assess vaccine-related adverse events (VRAEs) were collected;chart review identified baseline characteristics and treatments received. Descriptive statistics and logistic regressions were performed. Results: 253 questionnaires were collected from 171 patients, enrolled between May and September 2021. 130 patients were survey-eligible after the 1st dose (D1) and 185 after 2nd dose (D2). 91 questionnaires were collected after D1 (Questionnaire 1: Q1) and 162 after D2 (Questionnaire 2: Q2). Surveys couldn't be collected due to interval > 1 month between D1 / enrollment, patients' unavailability, withdrawal of study or death. Median age was 55 (24-87) and 62.8% were female. 58.5% had solid tumors, treated with chemotherapy (49%) or checkpoint inhibitors only (9.5%);19.4% malignancies were treated with targeted therapies and 22.1% had hematological malignancies. Most frequent solid tumors were breast (31.3%), lung (15.9%) and gastro-intestinal (GI) (14.3%). Patients received 45.6% Pfizer/BioNTech, 52.8% Moderna and 1.6% Oxford/AstraZeneca. A combination of 2 different vaccines was administered to 11.9%. Interval between D1 and D2 was ≤30 days in 53.1%, 31-90 days in 42.6%, and 91-180 days in 4.3%. Among all patients, 84.1% developed VRAEs after a median of 2 days post-vaccine for a median of 4 days. 74.5% had local symptoms (Sx) (pain, sensitivity and/or redness at injection site and/or arm) and 65.8% had systemic Sx. Most frequent systemic Sx were fatigue, chills or myalgia (39.4%), GI (6.3%) and fever (2.9%). Most patients (90.7%) described their Sx as having no / minimal impact (Gr 1), 7.8% reported seeking medical consultation (Gr 2), and 1.5% lead to hospitalization (Gr 3) (1 cardiovascular event, 1 infection;causality with concurrent systemic treatment not excluded and 1 due to malignancy). Gr 2, but not Gr 3, VRAEs were more common after D2 (11.4% vs 2.5%, p = 0.03). 41.7% considered their Sx as a new health problem. On multivariate analysis, younger age and female sex were significantly associated with the development of any Sx (OR 1.08, p = 0.01;OR 2.92, p = 0.02, respectively) and local Sx (OR 1.04, p = 0.04;OR 2.19, p = 0.04), but not systemic Sx or new health problem. Conclusions: Patients experienced mostly minor and transient symptoms post-vaccination;few perceived these as a new health problem. COVID-19 vaccination is overall safe and well-tolerated among cancer patients.
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Introduction: During the COVID-19 pandemic, college students experienced occupational disruptions to their daily routines and alarming mental health outcomes. This paper seeks to examine associations between college students' occupational engagement and psychological well-being;identify potential protective and risk factors for gender, race, and ethnic identities;and explore the impacts of occupational disruptions during COVID-19. Method: Undergraduate students (n = 152) were recruited through social media and ResearchMatch and completed an online survey. Associations and differential impacts on identity were analyzed for occupational balance, satisfaction with participation in discretionary activities, depression, fatigue, general anxiety, stress, loneliness, and COVID-19 behaviors, beliefs, and experiences (CBBE). Results: Occupational engagement had significant negative correlations with the five mental health measures. Females reported more fatigue, anxiety, and stress than males. Hispanic/Latinx participants reported greater occupational engagement. Black/African American participants reported greater occupational balance than their multiracial peers. Occupational Impairment subscale was positively associated with depression, anxiety, and stress. Participants who lost their job were more depressed. Males reported a greater increase in alcohol, cigarette, and recreational drug consumption than females. The COVID-19 Preventative Action subscale was positively correlated with COVID-19 Worry. Females both engaged in more preventive actions and worried more than males. Conclusion: Overall, this study reveals that increasing occupational engagement during the COVID-19 pandemic could be beneficial for mental health and well-being, that COVID-19 had differential impacts on occupational engagement and mental health outcomes based on identity, and that behaviors, beliefs, and experiences shifted with the global occupational disruption.
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Purpose: This paper presents the impact of the COVID-19 pandemic on Vietnam's tourism industry to propose appropriate recovery strategies in the future. Design/methodology/approach: This study uses a combination of research methods. Data were collected from the Ministry of Culture, Sports and Tourism, General Statistics Office, Vietnam National Administration of Tourism and Ministry of Health. Non-parametric statistical methods were applied to analyze the differences between epidemic and non-epidemic periods and find correlations between the number of infections and data related to the performance of the tourism industry. In-depth interviews with 20 people linked to tourism activities were conducted to analyze the impacts and propose strategies for future recovery. Findings: The results demonstrate the severe impact of the pandemic on Vietnam's tourism industry based on a decrease in the number of visitors, business activities, revenue and employment rate. Therefore, to recover tourism – Vietnam's key economic sector in the future – developing reasonable strategies to build a safe tourism environment, building a sustainable tourist market, diversifying and improving tourism high-quality tourism products, marketing, human resources, digital transformation and sustainable tourism are necessary, along with the development trend of the industry after COVID-19. Originality/value: This paper synchronously and systematically presents the effects of COVID-19 on Vietnam's tourism industry based on official data. Strategies are proposed to handle these effects on a reliable scientific basis. This study can be considered a valuable reference for researchers and managers of tourism in developing countries, such as Vietnam. © 2022, Hoa Dinh Vu, Anh Thi Ngoc Nguyen, Nga Thi Phuong Nguyen and Duy Ba Tran.
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The emergence of variants of Covid-19, the persistence of lockdowns in many countries, and the necessity to maintain sustainable education have resulted in a shift from the traditional classroom to virtual space. As such, there is a strong need to leverage technological advances while mitigating the challenges faced by primary teachers. Through the incorporation of eight elements, the authors sought to better understand factors that influence teacher readiness to deliver sex education in primary schools. Structural Equation Modeling was employed to assess the proposed conceptual model. The online survey was designed and distributed by Google Forms. Based on the results from 383 individuals, the findings revealed that facilitating conditions, educational policy, and parental involvement all had a relationship with teacher readiness. Digital content positively influenced performance expectancy and effort expectancy. Sexual knowledge had a statistically significant and positive influence on effort expectancy. Finally, openness had a statistically significant and positive influence on performance expectancy. The significant exceptions were that effort expectancy was not found to predict teacher readiness, and performance expectancy was not found to influence teacher readiness. The reasons for these non-significant correlations were briefly discussed and more studies on this topic are called to investigate these unexpected outcomes in more detail. The level of readiness, as well as theoretical and practical implications for scholars and practitioners, were discussed. ©Authors
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Since 2020, COVID-19 has completely changed the daily activities of almost all nations, and education has been heavily affected. Becauseof school closures, face-to-face classrooms were halted or replaced with onlineclasses in which both lecturers and learners had to adjust their teaching andlearning styles to cope with unexpected situations. The ‘new normal’ of learningfrom homes, spending hours staring at screens, and struggling with piles ofonline tasks has somehow demotivated students to continue learning. This studyexplores factors affecting students’ desire to take online courses after experiencinge-learning during COVID-19. Nine hundred fifty-five students of VietnamNational University took part in the survey via an online questionnaire. Datawere analyzed using SPSS 20;correlation, hierarchical regression was employedto examine how online factors influence students’ decision. The research resultsshowed that skill enhancement, self-regulated learning, lecturer interactionduring the course were among the most important predictors of students’ desire totake more online courses. In contrast, student interaction imposed no significantinfluence. This study gives the theoretical background for other studies in thesame field and suggests practical implications for governments and universitiesto implement online training better to cope with the pandemic © 2022, International Journal of Interactive Mobile Technologies. All Rights Reserved.
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From the end of 2019, numerous comments and opinions relating to the COVID-19 pandemic have been posted on Twitter. The number of opinions rapidly increased since the countries began implementing social isolation and reduction. In these comments, users often express different emotions regarding COVID-19 signs and symptoms, the majority of which are sadness and fear sentiments. It is important to determine the symptom effect level for the emotions of symptomatic persons based on their opinions. However, no study analyzes the tweets' sentiment related to the COVID-19 topic to predict the symptoms effect level. Therefore, in this study, we present a method to predict the symptoms effect level based on the sentiment analysis of symptomatic persons according to the following steps. First, the sentiments in tweets are analyzed by using a combination of the text representation model and convolutional neural network. Second, a topic modeling model is built based on the latent Dirichlet allocation algorithm to group symptoms into small clusters that conform to sadness and fear sentiments. Finally, the symptom effect level is predicted based on the probability distribution of the symptoms in each sentiment cluster. Experiments using tweets promise that the proposed method achieves significant results toward the accuracy and obtained information.
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Purpose: This study aims to investigate customer experience (CE) and its relationship with intermediate variables to analyze the impact of digital banking (DB) on banks’ financial performance (FP) before Covid-19 and during the lockdown in Vietnam. Design/methodology/approach: These research data are from a survey of Vietnamese customers. The survey was deployed to a sample of 238 and 218 customers of 20 Vietnamese commercial banks via email in 2018Q4 and 2020Q2, respectively. FP is measured using banks’ quarterly financial statements before Covid-19 and during the lockdown. Findings: CE with DB had a significant and positive impact on FP via customer satisfaction before Covid-19, while the other two intermediate variables (word-of-mouth [WoM] and trust) had no considerable impact. During the lockdown, only WoM had a positive impact on FP. These findings indicate that before Covid-19, when customers could easily interact with their bank through many touchpoints, customer satisfaction with DB services created higher FP for the bank. However, during the lockdown, DB became the customer’s main touchpoint and WoM mediated the CE–FP relationship. Originality/value: During the national lockdown from the beginning of the Covid-19 pandemic in January 2020, customers in Vietnam may have had different experiences with DB when no alternate modes of payment were available. The study uses Covid-19 as a moderator variable to offer different viewpoints and findings related to CE with DB and its impact on FP. © 2021, Emerald Publishing Limited.
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Purpose: To deal with the present situation and recover after the COVID-19 pandemic, construction firms are required to recognise the trends in construction supply chain management (CSCM) for the upcoming years and determine the appropriate practices towards the trends for the improvement of construction activities in terms of strategy, tactic and operations. This paper aims to recognise key trends in CSCM and uses these trends as strategic criteria for the evaluation and prioritisation of lean construction (LC) tools at different project phases including design and architectural engineering, planning and control, on-site construction and safety management. Design/methodology/approach: The integrated analytic hierarchy process–Delphi method is used to collect and analyse the data from construction experts to evaluate the importance levels of the CSCM trends and recommend the appropriate tools for LC practices to improve project performances. Findings: Seven key CSCM trends are identified: lean supply chain management (SCM), supply chain (SC) integration, SC standardisation, SC problem-solving, SC information-sharing, SC flexibility and SC sustainability. Based on these trends, a set of prioritised lean tools are suggested for LC practices, in which “virtual design construction” (VDC) and “last planner system” are considered as the central tools. These two LC practices can be integrated with other effective tools to support the strategic, tactical and operational targets in construction supply chain (CSC) projects. Research limitations/implications: This study gives the managerial implications by developing an application framework of LC practices for CSC projects. The framework promotes “VDC” as a strategic tool for the phase of design and architectural engineering and considers “last planner system” as the central LC practice for the phase of project planning and control. The framework also focuses on the improvement of efficiency in construction operations by taking into account the aspects of on-site collaboration, problem-solving, improvement and safety. Originality/value: Up to date, there is still a lack of researches in classifying and prioritising the significant LC tools for each project phase to deal with CSC issues in both breadth and depth. Thus, this study is performed to provide construction managers with the awareness of CSCM trends on which they can focus to have strategic criteria for selecting LC practices to improve CSC performances. © 2021, Emerald Publishing Limited.
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Anti-vaccination attitudes have been an issue since the development of the first vaccines. The increasing use of social media as a source of health information may contribute to vaccine hesitancy due to anti-vaccination content widely available on social media, including Twitter. Being able to identify anti-vaccination tweets could provide useful information for formulating strategies to reduce anti-vaccination sentiments among different groups. This study aims to evaluate the performance of different natural language processing models to identify anti-vaccination tweets that were published during the COVID-19 pandemic. We compared the performance of the bidirectional encoder representations from transformers (BERT) and the bidirectional long short-term memory networks with pre-trained GLoVe embeddings (Bi-LSTM) with classic machine learning methods including support vector machine (SVM) and naive Bayes (NB). The results show that performance on the test set of the BERT model was: accuracy = 91.6%, precision = 93.4%, recall = 97.6%, F1 score = 95.5%, and AUC = 84.7%. Bi-LSTM model performance showed: accuracy = 89.8%, precision = 44.0%, recall = 47.2%, F1 score = 45.5%, and AUC = 85.8%. SVM with linear kernel performed at: accuracy = 92.3%, Precision = 19.5%, Recall = 78.6%, F1 score = 31.2%, and AUC = 85.6%. Complement NB demonstrated: accuracy = 88.8%, precision = 23.0%, recall = 32.8%, F1 score = 27.1%, and AUC = 62.7%. In conclusion, the BERT models outperformed the Bi-LSTM, SVM, and NB models in this task. Moreover, the BERT model achieved excellent performance and can be used to identify anti-vaccination tweets in future studies.
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This paper reports the design, development, and testing of a novel, yet simple and low-cost portable device for rapid SARS-CoV-2 detection. The device performs loop mediated isothermal amplification (LAMP) and provides visually distinguishable images of the fluorescence emitted from the samples. The device utilises an aluminium block embedded with a cartridge heater for isothermal heating of the sample and a single-board computer and camera for fluorescence detection. The device demonstrates promising results within 20 minutes using clinically relevant starting concentrations of the synthetic template. © 2020 CBMS-0001