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This study established a newly integrative model to explain the determinants of Universiti Teknologi MARA (UiTM) students' Behavior Intention BIs toward using online distance learning (ODL) at an IPTA level. A conceptual model was built based on the UTAUT model in to extend this adequately validated framework by incorporating two additional predictor variables (technology readiness and perceived credibility) both were supportive in the result. Data were collected from 181 participants with experience in using online distance learning (ODL). The results shown a high consistency and reliability, thereby demonstrating that the proposed model holds substantial a new explanatory. This study revealed that technology readiness is a key factor that significantly influences Universiti Teknologi MARA (UiTM) student's BIs toward using online distance learning (ODL). © 2023 Author(s).
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Past research revealed concerns over the depressive symptoms and psychological well-being of university students. The present study utilizes a stratified random sampling to examine the role of perceived social support on psychological well-being between depressed and non-depressed university students during the COVID-19 pandemic in Malaysia. This study recruited a total of 244 university students from different universities across Malaysia from November 2021 to July 2022 through social media such as Facebook, Instagram, and WhatsApp.A prevalence rate of 50.4% of university students was found to present significant depressive symptoms. There is a significant correlation between perceived social support and psychological wellbeing (r = 0.769, p < 0.05). Non-depressed university students reported significantly higher on their perceived social support and psychological well-being than university students with significant depressive symptoms with values of p<0.001 and p<0.043. Among depressed university students, perceived social support from friends and significant others was reported to be significantly lower than non-depressed university students with a value of p<0.001 and p<0.023.Overall, the present study discovered that a higher level of perceived social support could predict greater psychological well-being and reduced depressive symptoms among university students. Hence, perceived social support should be promoted as an effective intervention for university students due to its accessibility and cost. Future research should look into the effectiveness of perceived social support and other psychological resources for university students with di fferent mental health concerns.
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Past research revealed concerns over the depressive symptoms and psychological well -being of university students. The present study utilizes a stratified random sampling to examine the role of perceived social support on psychological wellbeing between depressed and non-depressed university students during the COVID-19 pandemic in Malaysia. This study recruited a total of 244 university students from different universities across Malaysia from November 2021 to July 2022 through social media such as Facebook, Instagram, and WhatsApp. A prevalence rate of 50.4% of university students was found to present significant depressive symptoms. There is a significant correlation between perceived social support and psychological wellbeing (r = 0.769, p < 0.05). Non-depressed university students reported significantly higher on their perceived social support and psychological well -being than university students with significant depressive symptoms with values of p<0.001 and p<0.043. Among depressed university students, perceived social support from friends and significant others was reported to be significantly lower than non-depressed university students with a value of p<0.001 and p<0.023. Overall, the present study discovered that a higher level of perceived social support could predict greater psychological well-being and reduced depressive symptoms among university students. Hence, perceived social support should be promoted as an effective intervention for university students due to its accessibility and cost. Future research should look into the effectiveness of perceived social support and other psychological resources for university students with di fferent mental health concerns. © 2023 Australasian College of Health Service Management. All Rights Reserved.
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Introduction: Coronavirus Disease 2019, or better known as the COVID-19, has caused a global pandemic and high death rate worldwide. Following the rapid increase of COVID-19 cases in Malaysia, the government had enforced Movement Control Order (MCO) started from 18 March 2020 and the restrictions were conducted and reviewed in several phases. The MCO also involved schools closure and commencement of online learning. This study aimed to identify the level of knowledge, attitudes and practices regarding COVID-19 among students in selected boarding schools in Malaysia. Methodology: This cross-sectional study was done in July to September 2020 using a set of questionnaire that was distributed via Google form. The questionnaire consisted of demographic data, knowledge, attitude and practice regarding COVID-19. The data was analysed using the Statistical Package for the Social Science 22. Result(s): A total of 365 students participated in this study. The respondents comprised of 54.2% female and 45.8% male stu-dents. The study found that they have moderate knowledge on COVID-19 while their attitude and practice were high. The study found a significant association between the knowledge and practice scores and between the attitude and practice scores of the respondents. [r = 0.389, p < 0.05] regarding COVID-19 However, there was no significant association between the knowledge and attitude scores. Conclusion(s): This study concluded that students' practice regarding COVID-19 was influenced by their attitude on health care to prevent COVID-19 infection. Therefore, changing their attitude and increasing the students knowledge are necessary to improve their practices regarding COVID-19 preventive measures.Copyright © 2023 Japan University of Health Sciences.
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INTRODUCTION: Prolonged COVID-19 symptoms is one of the major challenges in the management of the disease. As the number of COVID-19 cases increased drastically, the number of those with prolonged symptoms are also accumulating, either diagnosed or undiagnosed. This study aimed to identify the long-term clinical symptoms of COVID- 19 and the associated risk factors among Malaysian populations. MATERIALS AND METHODS: A cross-sectional survey using Google Form link for distribution of a selfadministered questionnaire was shared and disseminated via online platforms such as Facebook, WhatsApp, and Telegram. The inclusion criteria included those with a history of positive COVID-19 from 1st March 2020 until one month prior to the survey, and age above 18 years old. RESULTS: A total of 215 Malaysians participated, with 74% female respondents and a mean age of 36.4 years. Twenty-seven (12.6%) were asymptomatic when diagnosed with COVID-19. More than half (56%) still had symptoms at one-month of diagnosis, while 39% and 18% still had symptoms at the second and third months respectively. The most reported symptoms were lethargy (45.1%), difficult concentrating (22.3%) and cough (21.9%). Female, chronic lung disease and hypertension were significantly associated with prolonged symptoms at one month of COVID-19 infection. CONCLUSIONS: Lethargy, difficulty to concentrate and cough were the most common symptoms reported months after COVID-19 diagnosis. Apart from treating acute conditions, physicians should also be able to recognize and manage those symptoms. The findings of this study will help policymakers better grasp the social and economic consequences of long-term post-COVID-19 symptoms.
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Introduction: The world has been badly affected by the spread of a novel virus known as Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first reported in Wuhan, China back in December 2019. As the virus is transmitted through aerosol, respiratory droplets and close contact, hand hygiene and wearing mask are the most important preventive measures for COVID-19. Studies showed hand hygiene intervention improved compliances. This paper discussed the development of a hand hygiene intervention module, validation, usability and effectiveness reports. Methods: This study involved 5 stages;need analysis, module development, validation, usability and effectiveness studies. Need analysis and module development were carried out through brainstorming and literature search. The content was evaluated by three experts, whereas the usability was screened by four preschool teachers. The effectiveness of knowledge transfer was evaluated via pre and post intervention surveys. Results: The hand hygiene educational module received valuable comments from the content expert and the end-users (teachers). Knowledge score related to COVID-19 transmission, prevention and hand hygiene moments among pre-school children were significantly increased after the intervention. Conclusion: This module can be used to improve teaching method related to COVID-19 and hand hygiene. The ‘learn and play' approach may increase excitement, thus make learning process enjoyable and memorable. © 2023 Authors. All rights reserved.
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The COVID-19 pandemic has been an extraordinary event, the type of event that rarely occurs but that has major impacts on the stock market. The pandemic has created high volatility and caused extreme fluctuations in the stock market. The stock market can be characterized as either linear or nonlinear. One method that can detect extreme fluctuations is extreme value theory (EVT). This study employed a semisystematic literature review on the use of the EVT method to estimate investment risk in the stock market. The literature used was selected by applying the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines, sourced from the ScienceDirect.com, ProQuest, and Scopus databases. A bibliometric analysis was conducted to determine the study characteristics and identify any research gaps. The results of the analysis show that studies on this topic are rarely carried out. Research in this field is generally performed only in univariate cases and is very complicated in multivariate cases. Given these limitations, further research could focus on developing a conceptual model that is dynamic and sensitive to extreme fluctuations, with multivariable inputs, in order to predict investment risk. The model developed here considered the variables that affect stock price fluctuations as the input data. The combination of VaR–EVT and machine-learning methods is effective in increasing model accuracy because it combines linear and nonlinear models. © 2023 by the authors.
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The emergence of new variants of SARS-CoV-2 associated with varying infectivity, pathogenicity, diagnosis, and effectiveness against treatments challenged the overall management of the COVID-19 pandemic. Wastewater surveillance (WWS), i.e., monitoring COVID-19 infections in communities through detecting viruses in wastewater, was applied to track the emergence and spread of SARS-CoV-2 variants globally. However, there is a lack of comprehensive understanding of the use and effectiveness of WWS for new SARS-CoV-2 variants. Here we systematically reviewed published articles reporting monitoring of different SARS-CoV-2 variants in wastewater by following the PRISMA guidelines and provided the current state of the art of this study area. A total of 80 WWS studies were found that reported different monitoring variants of SARS-CoV-2 until November 2022. Most of these studies (66 out of the total 80, 82.5%) were conducted in Europe and North America, i.e., resource-rich countries. There was a high variation in WWS sampling strategy around the world, with composite sampling (50/66 total studies, 76%) as the primary method in resource-rich countries. In contrast, grab sampling was more common (8/14 total studies, 57%) in resource-limited countries. Among detection methods, the reverse transcriptase polymerase chain reaction (RT-PCR)-based sequencing method and quantitative RT-PCR method were commonly used for monitoring SARS-CoV-2 variants in wastewater. Among different variants, the B1.1.7 (Alpha) variant that appeared earlier in the pandemic was the most reported (48/80 total studies), followed by B.1.617.2 (Delta), B.1.351 (Beta), P.1 (Gamma), and others in wastewater. All variants reported in WWS studies followed the same pattern as the clinical reporting within the same timeline, demonstrating that WWS tracked all variants in a timely way when the variants emerged. Thus, wastewater monitoring may be utilized to identify the presence or absence of SARS-CoV-2 and follow the development and transmission of existing and emerging variants. Routine wastewater monitoring is a powerful infectious disease surveillance tool when implemented globally.
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As a result of the COVID-19 outbreak in Malaysia, educational institutions, including universities, were forced to conduct all academic activities online. If online learning continues in subsequent academic sessions, it may have a big impact on the academic performance of the student. Thus, the purpose of this study is to classify student's academic performance by using principal component analysis (PCA) before and during pandemic COVID-19. The sample consisted of 234 undergraduates from the Department of Mathematics at the Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris (UPSI). Data collection is conducted using a questionnaire. Data were gathered from students' grades for each subject in the first semester of the session 2019/2020, which is during face-to-face learning, and each subject's grade in the second semester of the session 2019/2020, which is during online learning. The finding of the study was divided into two parts which are preliminary analysis and further analysis. According to the eigenvalues greater than one criteria (Kaisar, 1960), when using the correlation matrix in eigen analysis, only, values greater than one should be included in the analysis. As a result, the researcher decided to cut-off the dimension at the second dimension from the eigenvalues obtained by the R software because the eigenvalues for the second dimension were greater than one which is 1.111. For further analysis, the researcher will be using the principal component one in classifying students based on their overall academic achievement, and principal component two will be used in classifying in which semester they did best in. With regard to overall academic performance, the majority of students' 51.4% were in the classification of good performance, while just 24.3% were considered excellent performance. Further, 15.7% of students are categorized as performing averagely in their academic performance, whereas 8.6% are categorized as performing below average. The results indicate that 65.7% of students performed similarly in both semesters, indicating that most students are performing in their academic performance either before or during the pandemic COVID-19, while only 14.3% of students performed in semester 1 session 2019/2020, which is during face-to-face learning, and only, 20% of students performed in semester 2 session 2019/2020, which is during online learning. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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We conducted this systematic review and meta-analysis to evaluate the existing evidence and to quantitatively synthesise evidence on the impact of therapeutic plasma exchange (TPE) on severe COVID-19 patients. This systematic review and meta-analysis protocol was prospectively registered on PROSPERO (CRD42022316331). We systemically searched six electronic databases (PubMed, Scopus, Web of Science, ScienceDirect, clinicaltrial.gov, and Cochrane Central Register of Controlled Trials) from inception until 1 June 2022. We included studies comparing patients who received TPE versus those who received the standard treatment. For risk of bias assessment, we used the Cochrane risk of bias assessment tool, the ROBINS1 tool, and the Newcastle Ottawa scale for RCTs, non-RCTs, and observational studies, respectively. Continuous data were pooled as standardized mean difference (SMD), and dichotomous data were pooled as risk ratio in the random effect model with the corresponding 95% confidence intervals (CI). Thirteen studies (one randomized controlled trials (RCT) and 12 non-RCTs) were included in the meta-analysis, with a total of 829 patients. There is a moderate-quality evidence from one RCT that TPE reduces the lactic dehydrogenase (LDH) levels (SMD -1.09, 95% CI [-1.59 to -0.60]), D-dimer (SMD -0.86, 95% CI [-1.34 to -0.37]), and ferritin (SMD -0.70, 95% CI [-1.18 to -0.23]), and increases the absolute lymphocyte count (SMD 0.54, 95% CI [0.07-1.01]), There is low-quality evidence from mixed-design studies that TPE was associated with lower mortality (relative risk 0.51, 95% CI [0.35-0.74]), lower IL-6 (SMD -0.91, 95% CI [-1.19 to -0.63]), and lower ferritin (SMD -0.51, 95% CI [-0.80 to -0.22]) compared to the standard control. Among severely affected COVID-19 patients, TPE might provide benefits such as decreasing the mortality rate, LDH, D-dimer, IL-6, and ferritin, in addition to increasing the higher absolute lymphocyte count. Further well-designed RCTs are needed.
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COVID-19 , Humans , COVID-19/therapy , Plasma Exchange , Interleukin-6ABSTRACT
Background: Rheumatoid Arthritis (RA) flare post-COVID- 19 vaccination has been reported and poses a great concern among patients. This study aims to evaluate the prevalence of RA flare post COVID-19 vaccination and its associated risk factors. Method(s): This was a cross-sectional questionnaire-based study assessing RA flare based on patient self-report disease flare or documented physician assessment (physician-reported flare). The study was conducted from May to July 2022 in Hospital Putrajaya and recruited RA patients who received at least one dose of COVID-19 vaccine under the Malaysian National Vaccination Programme. Patient self-reported disease flare was defined as 'a sudden worsening of rheumatology condition or arthritis within 1 month post-vaccination' while physician-reported flare was defined as 'an increment of disease activity score 28-joint (DAS28 CRP/ESR) documented within 3 months post-vaccination' from either a scheduled or unscheduled clinic visit. Demographic data, vaccination history and disease parameters were retrieved from electronic medical records. Statistical analysis included descriptive and univariate analyses were performed using SPSS. Result(s): A total of 186 patients were enrolled. Majority (93%) were female with the mean age of 58 years old (standard deviation, SD 12.2). Most patients were seropositive (66% Rheumatoid factor, 63% anti-citrullinated peptide antibodies) with mean disease duration of 12 years (SD 7.7). Majority were on methotrexate (MTX) (71%), 21.5% were on leflunomide and only 4.8% were on biologics or targeted synthetic disease modifying anti-rheumatic drugs. A small proportion of patients were on steroids (14%). Half of the patients were in remission prior to vaccination. All patients completed 2 doses of vaccination in which 62% received Pfizer-BioNTech vaccine followed by Sinovac (coronaVac) vaccine (24.6%) and Oxford-AstraZaneca vaccine (13.4%). Only 80% received booster dose, of which 88.7% was Pfizer-BioNTech vaccine. A total of 52 patients who were on MTX therapy discontinued the drug post-vaccination for a week duration. The prevalence of flare was only 12.9% (n: 24) in which 14 were self-reported and 10 were physician-reported flares (4 severe flare, 6 mild-moderate flare). Majority of flares occurred during the first and second dose of vaccination with 29.2% respectively, and only 12.5% were reported after booster vaccination. There were no significant differences in the occurrence of flare post-vaccination between age, gender, disease activity prior to vaccination, types of vaccine, usage of MTX and steroids, and discontinuation of MTX post-vaccination. Conclusion(s): Prevelance of RA flare post-COVID- 19 vaccination is low and there were no significant associated risk factors identified in this study.
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The objective of this study is to examine the main constraints experienced in the online mode of education during this pandemic at higher education level in Pakistan. The COVID-19 pandemic credibly transformed the method of learning and teaching from face to face to online. In unexpected sudden septicity, universities in Pakistan have started online education without proper instructional provision and relevant experience. For this purpose, the data is collected from 750 students and teachers across all over the regions in Pakistan. The study has used partial least square structural equation modeling (PLS-SEM). The findings show that technological bottlenecks, institutional preparedness, and digital divide are significant challenges. The differences in perceptions of rural and urban areas are also very important referring to several policies implications, implementing information communication technology (ICT), friendly curriculums, enhancing online accessibility and infrastructure development. This study contributes to help universities for developing effective e-learning policies for students in the situation of COVID-19.
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The COVID-19 outbreak is considered as one of the most severe infectious viruses experienced by the world during the 21st century. This pandemic has economic, social, and psychological consequences on all countries, so the main purpose of this paper is to determine the impact of COVID-19 on the Egyptian stock return specifically as Egypt has been one of the countries that were strongly affected. The impact of COVID-19 on the Egyptian Stock Exchange (EGX100) was investigated using a multiple regression model and historical data from 20 listed firms in the EGX100 index between February 2020 and March 2022. Additionally, we included inflation as a control variable in our model. The results indicated that COVID-19 significantly impacted the stock's cumulative returns when used as an independent variable and measured using the cumulative coronavirus cases (CCC) and cumulative coronavirus deaths (CCD) collected for the time period of February 2020 through March 2022 from the World Health Organization (WHO) database. The findings also showed a negative correlation between these elements and the cumulative returns of the stock. Furthermore, The outcome of our model also showed that there was no significant relationship between inflation as measured by headline CPI and the stock's cumulative returns. © 2022 The Authors.
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Background: Pregnant women is one of the most group who are at high risk for COVID-19 infection. To protect them should keep them away from exposure for infection and enhance their knowledge and practice about self-protective measures towards COVID-19 pandemic. Aim(s): The study aimed to assess knowledge and practice of pregnant women regarding prevention of COVID-19. Subjects & Method: A descriptive study design was performed on 195 pregnant women in the antenatal clinic of Zagazig University Hospital using purposive sampling. Data were collected using three tools: an interview questionnaire, the pregnant women's knowledge questionnaire regarding COVID-19 and Pregnant women's practice questionnaire of self-protective measures in relation to prevention COVID-19. Result(s): mean age of pregnant women was 33.74+/-6.51 years old. About 63.7% of the studied pregnant women had adequate level of knowledge about COVID-19. Additionally, 58.6% of the studied pregnant women had satisfactory performed of self-protective measure against COVID-19. Furthermore, there was highly statistically significant difference of studied pregnant women regarding both total mean score of knowledge and practice (P= 0.000**). Conclusion(s): most of the studied pregnant women had adequate level of knowledge about COVID-19 as well as had satisfactory performed of self-protective measure against COVID-19 this supported the study's aims. Furthermore, there was highly statistically significant difference of studied pregnant women regarding both total mean score of knowledge and practice (P= 0.000**). Recommendations: Incorporates the educational program within outpatient clinics, providing a printed copy of the educational brochure in outpatient clinics for other pregnant women and their relatives. Also, antenatal heath care should have a plan to communicate online with pregnant women to manage such these crisis situations. Copyright © 2022, Anka Publishers. All rights reserved.
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To control congestion in the workplace environment especially in crises like the COVID-19 pandemic, this requires careful control of highly crowded workplace locations. Therefore, innovative technologies, such as geofencing and sequential pattern mining can be used to estimate people movement pattern and combat the spread of COVID-19. In this paper, the workplace area is divided into a set of geofences by using geofencing technology. Then, the movement profiles of each user are estimated to control the possible congestion in the workplace's enviroment. To accomplish this, the user's historical geofence transitions are used to anticipate the next time the user will leave the current geofence. The Sequential Pattern Discovery using Equivalence classes (CM-SPADE), Succinct BWT-based Sequence prediction model (SuBSeq) and Compact Prediction Tree + (CPT+) algorithms are adopted to predict the user's next geofence. In the CM-SPADE algorithm, a vertical database is obtained from the available database and the frequent sequence is found based on relative support, confidence, and lift measures. Meanwhile, in the training phase of the SuBSeq algorithm, Ferragina and Manzini (FM)-index and Burrows-Wheeler Transform string are generated. Then, in the ready-to-predict phase, the next geofence is anticipated. The CPT+ algorithm is based on generating Prediction Tree (PT), Lookup Table (LT), and Inverted Index (IIdx) for the training data. Then, Frequent Subsequence Compression (FSC) and Simple Branches Compression (SBC) are used to reduce the size of the PT. In addition, the Prediction with improved Noise Reduction (PNR) method is utilized to reduce the execution time. The results show remarkable superiority for SuBSeq algorithm over CM-SPADE and CPT+ with the accuracy greater than 90% withh an average of 8 input geofences to predict the next geofence. © 2022 IEEE.
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The pandemic of Covid-19 has changed the lifestyle of people nowadays. Students has to adapt to the new norms in which they need to rely on the digital mediums to interact with others. The main purpose of this study is to investigate the relationship between social media use and the connectedness among the university students in Malaysia during this pandemic of Covid-19. It also aims to investigate connection between the purposes of social media use (academic, socialization, entertainment and informativeness) and the level of social connectedness. Thirdly, the genders difference between social media use and social connectedness are investigated. The measurement used include the online social networking usage questionnaire and the social connectedness scale, and were distributed through snowball sampling method via the online platforms. A total of 300 respondents were recruited in this study with the mean age of 22.26. The results indicate that no significant relationship between social media usage and social connectedness. However, there was significant relationship between the purposes of using social media and social connectedness. Thirdly, no difference was found between females and males on the social media usage and social connectedness. Finally, this study highlights that the purpose of using social media could enhance the social relationship. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Since the Movement Control Order (MCO) was adopted, all the universities have implemented and modified the principle of online learning and teaching in consequence of Covid-19. This situation has relatively affected the students’ academic performance. Therefore, this paper employs the regression method in Support Vector Machine (SVM) to investigate the prediction of students’ academic performance in online learning during the Covid-19 pandemic. The data was collected from undergraduate students of the Department of Mathematics, Faculty of Science and Mathematics, Sultan Idris Education University (UPSI). Students’ Cumulative Grade Point Average (CGPA) during online learning indicates their academic performance. The algorithm of Support Vector Machine (SVM) as a machine learning was employed to construct a prediction model of students’ academic performance., Two parameters, namely C (cost) and epsilon of the Support Vector Machine (SVM) algorithm should be identified first prior to further analysis. The best parameter C (cost) and epsilon in SVM regression are 4 and 0.8. The parameters then were used for four kernels, i.e., radial basis function kernel, linear kernel, polynomial kernel, and sigmoid kernel. from the findings, the finest type of kernel is the radial basis function kernel, with the lowest support vector value and the lowest Root Mean Square Error (RMSE) which are 27 and 0.2557. Based on the research, the results show that the pattern of prediction of students’ academic performance is similar to the current CGPA. Therefore, Support Vector Machine regression can predict students’ academic performance. © 2022 by the authors.
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COVID-19 , SARS-CoV-2 , Humans , Spike Glycoprotein, Coronavirus , Protein Binding , MutationABSTRACT
Background: COVID-19 i s an emergi ng i nfecti ous di sease caused by a novel Severe Acute Respi ratory Syndrome Coronavirus 2 (SARS-CoV-2). In Malaysia, first few cases of COVID-19 were detected in January 2020, among Chinese nationals and the cases keep increasing day by day. Method(s): This self-administered web based cross sectional study using Google forms was conducted among 400 Malaysian adults to explore their level of knowledge, attitude and practice towards COVID-19, as well as factors associated with the variables. Descriptive and binary logistic regression were performed using SPSS version 22. Result(s): Knowledge and practice among Malaysian adults towards COVID-19 were low. Gender (p = 0.030, OR:0.616, 95% CI 0.398-0.955) and occupation (p = 0.002, OR:2.489, 95% CI 1.485-4.172) were found as significant predictors of practice towards COVID-19. Conclusion(s): In conclusion, proper mass public health messages should be conducted by the higher authorities to improve knowledge and practice towards COVID-19. Copyright © 2020 Japan Health Sciences University & Japan International Cultural Exchange Foundation.