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1.
Drug Safety ; 45(10):1156-1157, 2022.
Article in English | ProQuest Central | ID: covidwho-2044974

ABSTRACT

Introduction: Chronic rhinosinusitis with nasal polyposis (CRSwNP) is characterized by a type 2 pattern of inflammation resulting in the production of some cytokines such as interleukin (IL)-4, IL5, and IL13. Options for treatment-resistant CRSwNP include aspirin desensitization, recurrent topic and systemic corticosteroid use, and functional endoscopic sinus surgery (FESS). However, frequent relapses after medical and surgical treatment have been observed. Thus, dupilumab, a human recombinant monoclonal IgG4 antibody, changes radically the treatment of CRSwNP because of its binding effects on major drivers of human type 2 inflammatory processes [1-3]. Considering its recent approval, it may be useful to evaluate its safety profile. Objective: The aim of this study was to describe better adverse drug reactions (ADRs) related to dupilumab in the treatment of CRSwNP analyzing all individual case safety reports (ICSRs) collected into the European Spontaneous Reporting System (SRS) database. Methods: All ICSRs recorded starting from the drug approval up to 31 December 2021 with dupilumab reported as suspected and having the specific indication of CRSwNP were considered. A descriptive analysis was conducted to assess demographic characteristics and dupilumab-related variables. Results: Out of 10,400 ICSRs related to dupilumab, only 481 (4.6%) had CRSwNP indication, of which 68.2% were related to adults and 54.3% to females. The 68.4% were serious;however, ICSRs mainly led to a completely or partial recovering (25.4%) and 8 cases were fatal (1.7%). The time to onset (TTO) of ADRs was 25 (1-84.75) days while the time to resolution (TTR) was 5 (1.75-15.75) days. Analyzing ADRs by System Organ Classes (SOCs), the most reported were general and administration site conditions (36.4%) followed by injuries (21.6%), infections (21.2%), respiratory (19.1%), skin (16.6%), and nervous system disorders (16.4%). Looking at Preferred Terms (PTs), arthralgia (7.3%), eosinophilia (6.9%), COVID-19 (6.0%), pyrexia (5.8%), asthenia (5.6%), rash (5.4%), and dyspnoea (5.2%) were the most reported. The 7.5% of ICSRs described an aggravated condition with persistent nasal polyps: in 4 cases (0.8%) a nasal polypectomy was required. Considering fatal ICSRs, two cases were related to progression of COVID-19, one to road traffic accident, one to accidental death and the others were not fully specified. Conclusion: These results showed that dupilumab-related ICSRs are not commonly reported in CRSwNP. However, given the good treatment response and the minimal adverse effects observed, clinicians should consider treating CRSwNP with dupilumab. Moreover, additional analyses are necessary to better outline the safety profile of dupilumab in this particular setting.

2.
IOP Conference Series. Earth and Environmental Science ; 1039(1):012028, 2022.
Article in English | ProQuest Central | ID: covidwho-2037323

ABSTRACT

The COVID-19 pandemic has affected household food security, especially those with low incomes. This study aims to: (1) analyze the influence of socio-demographic factors (gender, age, mother’s education, marital status, occupation, dependents, income, and social assistance) on food security. (2) Measuring the level of food security of low-income families in the Special Region of Yogyakarta seen from the share of food expenditure, using a cross-sectional design and a quantitative approach and involved a sample of 250 low-income households, determined randomly by purposive sampling technique. We collected data through questionnaires, and the data were analyzed using descriptive statistical methods and multiple linear regression models using SPSS software. Three socio-demographic variables affect food security: employment, income, and the number of dependents. Simultaneously, these factors significantly affect the respondents’ food consumption expenditure. This study found that only 42.4% of respondents had food security. It shows that the current COVID-19 pandemic has exacerbated the poverty experienced by respondents. As for recommendations: (1) The government needs to provide social protection to help low-income households through food assistance programs. (2) Social protection programs need to be combined with household-based socio-economic empowerment programs to improve the food security of low-income households sustainably.

3.
Land ; 11(8):1237, 2022.
Article in English | ProQuest Central | ID: covidwho-2023855

ABSTRACT

Cemeteries are globally culturally protected greenspaces in cities that meet different societal needs and often harbor high biodiversity. To harness the potential of cemeteries as urban green infrastructure, stakeholders need to understand why people visit cemeteries and their preferences. We conducted an online survey in Berlin, Germany (n = 627) to understand (i) the reasons for cemetery visits;(ii) preferences for cemetery features;(iii) the effect of a dead tree as a wilderness component on preferences for differently managed green areas (wild, meadows, lawns);(iv) preferences of nature elements as comforting experiences;and (v) how reasons for the visit and sociodemographic variables relate to respondents’ preferences. The major reasons to visit cemeteries were ‘enjoying nature’, ‘mourning’, and ‘historical interest’ and most preferred cemetery features were ‘wildlife‘, ‘solitude’, and ‘vegetation‘. Presenting a dead tree did not modulate preference ratings for green areas that were depicted on photographs. Comforting experiences with nature elements were high overall. The reasons to visit had besides socio-demographic variables predictive potential on pronounced preferences. The results underscore the importance of cemeteries as multidimensional places and indicate tolerance for the inclusion of dead trees as important wildlife habitat. Strategies to develop cemeteries as shared habitats for people and nature should also consider, besides socio-demographic background, the reasons for cemetery visits.

4.
The International Journal of Cardiovascular Imaging ; 38(8):1733-1739, 2022.
Article in English | ProQuest Central | ID: covidwho-1990682

ABSTRACT

BackgroundCOVID-19 has caused a global pandemic unprecedented in a century. Though primarily a respiratory illness, cardiovascular risk factors predict adverse outcomes. We aimed to investigate the role of baseline echocardiographic abnormalities in further refining risk in addition to clinical risk factors.MethodsAdults with COVID-19 positive RT-PCR test across St Luke’s University Health Network between March 1st 2020-October 31st 2020 were identified. Those with trans-thoracic echocardiography (TTE) within 15–180 days preceding COVID-19 positivity were selected, excluding severe valvular disease, acute cardiac event between TTE and COVID-19, or asymptomatic patients positive on screening. Demographic, clinical, and echocardiographic variables were manually extracted from patients’ EHR and compared between groups stratified by disease severity. Logistic regression was used to identify independent predictors of hospitalization.Results192 patients met inclusion criteria. 87 (45.3%) required hospitalization, 34 (17.7%) suffered severe disease (need for ICU care/mechanical ventilation/in-hospital death). Age, co-morbidities, and several echocardiographic abnormalities were more prevalent in those with moderate-severe disease than in mild disease, with notable exceptions of systolic/diastolic dysfunction. On multivariate analysis, age (OR 1.039, 95% CI 1.011–1.067), coronary artery disease (OR 4.184, 95% CI 1.451–12.063), COPD (OR 6.886, 95% CI 1.396–33.959) and left atrial diameter ≥ 4.0 cm (OR 2.379, 95% CI 1.031–5.493) predicted need for hospitalization. Model showed excellent discrimination (ROC AUC 0.809, 95% CI 0.746–0.873).ConclusionsBaseline left atrial enlargement is an independent risk factor for risk of hospitalization among patients with COVID-19. When available, baseline LA enlargement may identify patients for (1) closer outpatient follow up, and (2) counseling vaccine-hesitancy.

5.
Journal of Advanced Medical and Dental Sciences Research ; 10(7):72-76, 2022.
Article in English | ProQuest Central | ID: covidwho-1964916

ABSTRACT

Background: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered SARS-COV2. Most people infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. Older people and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illnesses. Objectives: To assess the level of knowledge regarding covid-19 among nursing students studying in Dasmesh college of nursing, Faridkot. To find out association between knowledge regarding COVID-19 among nursing students with their demographical variables. Methods: A descriptive study was conducted on 41 nursing students of Dasmesh College of nursing Faridkot Punjab. Non-probability convenient sampling technique was used to collect data with the help of a self-administered structured knowledge questionnaire. Data wereanalyzedbased onthe objectives of the study byusing descriptive and inferential statistics such as frequency, percentage, mean, and chi-square. Results: The major findings of the study depictthat 18 (43.9%) students had good knowledge, 20 (48.7%) students had average knowledge, and 3 (7.3%) students had poor knowledge. Conclusion: It was concluded that the majority of the students had an average level of knowledge regarding COVID-19.

6.
American Journal of Public Health ; 112(8):1089-1091, 2022.
Article in English | ProQuest Central | ID: covidwho-1958134

ABSTRACT

t is well established that socioeconomic and demographic factors, such as race and ethnicity, income, and education, are independently linked to health disparities.1 Tools that combine multiple socioeconomic and demographic variables into an overall rank, such as the Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI), provide a quantitative framework that can be used by policymakers to identify communities that have higher overall social vulnerability with regard to disparate health outcomes and living conditions across multiple factors, and to develop targeted interventions.2 Historically, the SVI and similar frameworks have been crafted for emergency preparedness and response and used for study and practice in more extreme natural and human-caused disaster scenarios. Over the years, the SVI has been used for public health research and practice, communications, and accessibility planning, and to target geographically specific interventions related to natural disasters such as flooding and hurricanes,3, human-caused events such as chemical spills,2 and disease outbreaks like the recent COVID-19 pandemic.4 However, addressing issues of health inequity attributable to environmental injustice is imperative, and should not be restricted to alleviating the impact of event-specific hazards. Environmental injustice in the built environment is often associated with the disproportionate placement of hazardous and industrial sites and polluting transportation infrastructure in socially vulnerable neighborhoods,5 where residents often lack the social or economic capital to influence policy decisions.6 Although existing research links housing and health equity,7 the impact of poor housing conditions and household exposures to lead, pests, and indoor air pollutants on the health and well-being of socially vulnerable populations is an important and often overlooked aspect of environmental injustice.7,8 The Environmental Protection Agency's definition of environmental justice is all-encompassing and espouses the idea that environmental justice is only achieved when "everyone enjoys: The SVI has already been used outside the realm of disaster management to better characterize obesity10 and physical fitness.11 Hollar et al. set a new precedent for the value it may bring to the environmental justice sector, and additional research should be done to understand its utility in identifying communities that may be more likely to experience other socially linked conditions associated with environmental injustice, such as routine exposure to indoor and outdoor environmental pollutants, chronic disease burden, poor working conditions, lack of greenspace, and other issues with the built environment, in addition to housing conditions.

7.
Dirasat: Human and Social Sciences ; 49(3):586-597, 2022.
Article in English | Scopus | ID: covidwho-1935007

ABSTRACT

Background: This study aimed to investigate the impact of the Coronavirus pandemic on the level of life satisfaction among Al Ain University students and its relationship with some demographic variables (gender, academic level). Subjects and method: The study sample consisted of (405) male and female students from Al Ain University from the humanities and scientific colleges in the headquarters of the university in Al Ain and Abu Dhabi, the Life Satisfaction Scale prepared by El-Desouki (1999) was distributed electronically. Results: The study results showed that the level of life satisfaction was high, and there were no differences between males and females. As for the marital status, there were no differences in socialization and social appreciation dimensions, while a difference appeared in favor of married students in the dimensions of happiness, tranquility, psychological stability, and contentment. There were no differences in the level of satisfaction with life among students of scientific and humanitarian colleges. As for the academic level, there were no differences in the dimensions of happiness and socialization, psychological stability, and social appreciation, while differences appeared in the tranquility dimension in favor of the fourth-year level. As for the age variable, there were no differences between all age groups in the socialization and stability dimensions, but there were differences in the dimension of happiness, tranquility, social estimation, and contentment in favor of the age group 18-22. © 2022 DSR Publishers/ The University of Jordan.

8.
2022 International Conference on Interdisciplinary Research in Technology and Management, IRTM 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1932118

ABSTRACT

The Covid-19 pandemic has caused a lot of stress and anxiety. This study aims to observe the impact of the demographic variables of age, gender, educational level and area of residence on the anxiety and depression levels due to the pandemic. Data was obtained using a questionnaire to record demographic variables such as Age, Gender, educational level and area of residence. Data was also obtained using a questionnaire that measured questions related to depression and anxiety. Results indicated that age recorded a significant impact of chances for depression. This means that individuals between the age group of <30years had a 3 times greater chance of developing depression due to the pandemic compared to the 30-59 years and >60-year-old age groups. On the other hand, males recorded an increased level of anxiety which was 2.5 times higher than females. © 2022 IEEE.

9.
Journal of Urban Planning and Development ; 148(3), 2022.
Article in English | ProQuest Central | ID: covidwho-1921857

ABSTRACT

Since March 2020, the COVID-19 disease has become a global concern, and its concentration has been primarily in urban settings. Previous research suggests that multidimensional factors allow understanding the distribution of the disease but has limitations such as having nonhomogeneous units as the object of study, not incorporating changes in sanitary control measures over time or the absence of mobility variables. To overcome these shortcomings, we investigated the association between socioeconomic, demographic, and built environment factors with infection rates in the Metropolitan Area of Barcelona, one of the most compact and mixed-use environments in Europe. For this purpose, we use spatial regression models at five different stages that capture variations in sanitary control measures. Our results indicate that before the lockdown, infections were concentrated in high-income areas, but once it started the pattern shifted toward areas characterized by overcrowding, with more people who did not have the opportunity to telework, as well as nursing homes. Although commuting time also maintained a positive association with infections, the use of public transportation was not observed to have a direct impact. Contrary to what was speculated at the beginning of the pandemic, density was not shown to be a decisive factor in explaining infection rates;therefore, the results suggest keeping the focus on the quality of housing to avoid intrafamily infections but particularly in those where elderly dependents live. Likewise, public transportation can maintain its benefits for the most vulnerable urban populations as long as minimum safety measures are guaranteed in its interior.

10.
Journal of Enterprise Information Management ; : 24, 2022.
Article in English | Web of Science | ID: covidwho-1915916

ABSTRACT

Purpose This exploratory research aims to (1) investigate the bright and dark sides of social media use during the COVID-19 pandemic;(2) explore the impact of demographic factors on social media usage;and (3) assess the effects of cultural dimensions on social media usage. Design/methodology/approach The data are collected through an online survey. Factors derived from grounded theories and models such as affordance theory and Hofstede's cultural framework were considered. Spearman correlation and nonparametric analysis were used to test the hypotheses. Findings The results revealed that social media usage was positively associated with healing and affiliation, and negatively associated with self-control. There are also positive associations between social media usage and sharing information related to COVID-19 without verification, perceived reliability of COVID-19 information on social media and relapse. The impact of demographic and cultural factors indicated significant effects of gender, age, marital status, educational level, power distance and collectivism on social media usage, sharing information, perceived information reliability, healing and affiliation. Originality/value This study contributes to technology affordances by examining social media's positive and negative affordances in a new context (COVID-19 pandemic). From the positive side, this study explores the use of social media for healing and affiliation. As for the negative impact of social media during the pandemic, this study assesses the user's addiction to social media use (relapse) and perception of the social media information reliability and information sharing without verification. It is among few research endeavors conducted in a non-Western country. This study also examines the influence of demographic and cultural factors on social media users. The results provide insights for both researchers and policymakers regarding social media usage.

11.
International Journal of Data Mining, Modelling and Management ; 14(2):89-109, 2022.
Article in English | ProQuest Central | ID: covidwho-1892351

ABSTRACT

Coronavirus disease of 2019 (COVID-19) has become a pandemic in the matter of a few months, since the outbreak in December 2019 in Wuhan, China. We study the impact of weather factors including temperature and pollution on the spread of COVID-19. We also include social and demographic variables such as per capita gross domestic product (GDP) and population density. Adapting the theory from the field of epidemiology, we develop a framework to build analytical models to predict the spread of COVID-19. In the proposed framework, we employ machine learning methods including linear regression, linear kernel support vector machine (SVM), radial kernel SVM, polynomial kernel SVM, and decision tree. Given the nonlinear nature of the problem, the radial kernel SVM performs the best and explains 95% more variation than the existing methods. In line with the literature, our study indicates the population density is the critical factor to determine the spread. The univariate analysis shows that a higher temperature, air pollution, and population density can increase the spread. On the other hand, a higher per capita GDP can decrease the spread.

12.
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLIII-B4-2022:111-116, 2022.
Article in English | ProQuest Central | ID: covidwho-1870915

ABSTRACT

The COVID-19 was first declared by World Health Organization (WHO) as global pandemic on March 11th 2020. While most of COVID-related studies have focused on epidemiological perspective, the spatial analysis of disease outbreak is also important to provide perceptions of transmission rates. Therefore, this paper attempts to identify the potential factors contributing to the COVID-19 incidence rate at provincial-level in Canada. Three statistical regression models, ordinary least squares (OLS), spatial error model, and spatial lag model (SLM) were applied to 14 independent variables including socio-demographic, economic, weather, health and facilities related factors. The results indicated that three factors including median income, diabetes and unemployment significantly affected the COVID-19 rates in Canada. Among three global models, the SLM performed the best to explain the key variables and spatial variability of disease incidence with a R2 value of 61%. However, in this study, the application of local regression models such as geographically weighted regression (GWR) and multiscale GWR (MGWR) have not been considered and this could be a scope for the future research.

13.
Trends in Biomaterials and Artificial Organs ; 36(Special Issue 1):90-93, 2022.
Article in English | Scopus | ID: covidwho-1790664

ABSTRACT

Coronavirus disease 2019 is a communicable disease caused by severe acute metabolic process respiratory syndrome coronavirus. Symptoms begin one to 14 days after exposure to the virus (81%) develop mild to moderate symptoms, while 14% develop severely and 5% suffer critical symptoms. The present study aimed to formulate psychological interventions to enhance mental state and psychological resilience throughout the COVID-19 pandemic. To correlate the level of Psychological impact of COVID 19 among antenatal mothers and to find out association between the Psychological impact of COVID 19 among antenatal mothers with their selected demographic variables. This study was conducted with 60 antenatal mothers in a quantitative approach, non-experimental descriptive design by purposive sampling technique. Demographic variables data were collected by using a multiple-choice questionnaire followed by assessing the psychological impact of COVID 19 among antenatal mothers were assessed using completely three different standardized tools. The results showed that 42(70%) had a high level of anxiety of COVID-19 among antenatal mothers, and 18(30%) had no anxiety. 46(76.6%) had had moderate stress, 10(16.7%) had high perceived stress, and 4(6.7%) had low stress. 35(58.3%) had probable depression, 14(23.3%) had a fairly high possibility of depression, 10(16.7%) had depression possible, and only 1(1.7%) had depression not likely among antenatal mothers. Psychological impact of COVID-19 has moderate to severe levels of stress, anxiety, and depression among antenatal mothers in the second and third trimesters. So it is vital to formulate Psychological interventions to enhance mental state, and maternal mental health should be prioritized during the pandemic. © (2022) Society for Biomaterials & Artificial Organs #20059222.

14.
Trends in Biomaterials and Artificial Organs ; 36(Special Issue 1):87-89, 2022.
Article in English | Scopus | ID: covidwho-1790304

ABSTRACT

Starting in December of 2019, COVID-19 spread worldwide. A rapid infection rate and human-To-human transmission characterize COVID-19. Although the pandemic has been under effective control, numbers of confirmed and suspected cases continue to rise. Physicians, nurses, and ambulance workers are more likely to be infected than any other group. To assess the level of health effect among post COVID patients and to find out association between the level of health effect among post COVID patients with their selected demographic variables. This study was conducted with 60 post-COVID patients in a quantitative approach, non-experimental descriptive design by purposive sampling technique. A self-structured questionnaire method was used to collect both the demographic data and the level of physiological and psychological health effects. 26.7% of them were under grade 1 health effects, 38.3% of them were of grade 2 health effects, and 35% of them had grade 3 health effects due to COVID-19. The study concluded that it is vital to formulate appropriate medical interventions to enhance physical and mental state among post-COVID patients. Mental health should be prioritized during the pandemic. Mental support should be made available and created accessible during and after the COVID-19 outbreak to lessen the ill effect on physiological health status. © (2022) Society for Biomaterials & Artificial Organs #20059122.

15.
6th Latin American Conference on Learning Technologies, LACLO 2021 ; : 91-96, 2021.
Article in Spanish | Scopus | ID: covidwho-1784509

ABSTRACT

Teaching-learning has changed drastically since the coronavirus pandemic and motivation in a pandemic context where students have had to radically change their learning system. The main goal of this research is to identify the relationship between the motivation of students in an online course of Computer Programming in Python, in the context of pandemic with sociodemographic variables (Internet connection, number of people living at home, employment status) and school variables (number of parallel subjects, grades and time spent). 75 first year engineering students participated and motivation was measured through the EME scale that provides Internal Motivation, External Motivation and Amotivation. The results indicate that there are no mean differences between motivation and socio-demographic variables, while significant differences are found in the Amotivation factor compared to students' final grades and the total time taken to complete the learning units. The course in question took place in the second semester of 2020, which ended in January 2021, given the irregularity of the semester © 2021 IEEE.

16.
Polish Journal of Medical Physics and Engineering ; 28(1):19-29, 2022.
Article in English | ProQuest Central | ID: covidwho-1770957

ABSTRACT

Introduction: Predicting the mortality risk of COVID-19 patients based on patient’s physiological conditions and demographic characteristics can help optimize resource consumption along with the provision of effective medical services for patients. In the current study, we aimed to develop several machine learning models to forecast the mortality risk in COVID-19 patients, evaluate their performance, and select the model with the highest predictive power.Material and methods: We conducted a retrospective analysis of the records belonging to COVID-19 patients admitted to one of the main hospitals of Qazvin located in the northwest of Iran over 12 months period. We selected 29 variables for developing machine learning models incorporating demographic factors, physical symptoms, comorbidities, and laboratory test results. The outcome variable was mortality as a binary variable. Logistic regression analysis was conducted to identify risk factors of in-hospital death.Results: In prediction of mortality, Ensemble demonstrated the maximum values of accuracy (0.8071, 95%CI: 0.7787, 0.8356), F1-score (0.8121 95%CI: 0.7900, 0.8341), and AUROC (0.8079, 95%CI: 0.7800, 0.8358). Including fourteen top-scored features identified by maximum relevance minimum redundancy algorithm into the subset of predictors of ensemble classifier such as BUN level, shortness of breath, seizure, disease history, fever, gender, body pain, WBC, diarrhea, sore throat, blood oxygen level, muscular pain, lack of taste and history of drug (medication) use are sufficient for this classifier to reach to its best predictive power for prediction of mortality risk of COVID-19 patients.Conclusions: Study findings revealed that old age, lower oxygen saturation level, underlying medical conditions, shortness of breath, seizure, fever, sore throat, and body pain, besides serum BUN, WBC, and CRP levels, were significantly associated with increased mortality risk of COVID-19 patients. Machine learning algorithms can help healthcare systems by predicting and reduction of the mortality risk of COVID-19 patients.

17.
Journal of Global Information Management ; 30(4):1-27, 2022.
Article in English | ProQuest Central | ID: covidwho-1753735

ABSTRACT

The outbreak of COVID-19 has created a major panic among the agricultural sectors as well as the farmers in India owing to its’ transmissions, severity, and a lack of proper treatment methodology. From the cross-sectional study with the help of designed questionnaire relating to the “demographic-information”, ”knowledge, attitudes and practices” of Indian farmers and “DASS-21 variables”, the data from 143 farmers’ were collected and analyzed. Further, by using the "Interpretive Structural Modeling (ISM)" approach, an ISM model was developed followed by MICMAC analysis for possible mitigation measures during this pandemic outbreak. The findings provided the interrelationships among the possible mitigation measures for the farmers as well as for the benefits in Indian agricultures, which can be suitably used in appropriate psychological-interventions preparation for improving the mental-health among the farmers during this pandemic period.

18.
2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 ; : 202-207, 2021.
Article in English | Scopus | ID: covidwho-1708778

ABSTRACT

This study investigates the effectiveness of working from home during COVID-19 pandemic based on seven characteristics from telecommunication sector in Bahrain, namely, social, job, teleworker, management, teleworking, crisis as well as demographic variables. The data are collected through a questionnaire using a sample of 104 employers working from home. A partial least squares regression that protects against multicollinearity and nonnormality has been employed as a unique technique to build two models. The results of these models have suggested that the teleworking effectiveness and the teleworker, teleworking and crisis characteristics are statistically significant while social, job, management characteristics and demographic variable are not statistically significant. Such results support the importance of teleworker skills and professional quality variation such as autonomy, self-disciplined self-motivation, management skills, likely to work during the most prolific period and to facilitate working in case of sickness as well as crisis. Decision-makers and managers will the most beneficiary of the study and the results. © 2021 IEEE.

19.
14th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2021 ; : 517-519, 2021.
Article in English | Scopus | ID: covidwho-1650567

ABSTRACT

Pandemics are not only medical phenomenon, but they also influence people and society in many respects. It has an effect on almost all markets all over the world. COVID-19 pandemic, expressed as change, empowerment, or post-traumatic growth, with several negative consequences as well as positive consequences. It also has the potential for opportunities. Years of change in the way companies do business have resulted from the COVID 19 crisis across all industries and regions. The aim of this research is to examine the relationship between different demographic variables, COVID-19's impact on digital transformation and post-traumatic effects. The article reflects in practical terms on whether and how the COVID-19 emergence in organizations accelerates digital transformation. This study is a descriptive quantitative approach research based on general survey model. © 2021 ACM.

20.
Sustainability ; 14(2):1024, 2022.
Article in English | ProQuest Central | ID: covidwho-1634276

ABSTRACT

The Eurostat projections indicate that, by 2050, most of the European Union member states will see a fall in their population size, a drop in the share of young people, and a simultaneous rise in the share of elderly persons. There exist visible disproportions in the population structures between the EU countries, and the ageing of the population has two dimensions: it is occurring from the top down and from the bottom up. The goal of the study was to assess the stage of advancement and diversity of the ageing of population in the past and in the year 2050. Convergence models were designed for ten variables (indicators for structures by age, demographic dependency, median age) and a synthetic variable characterising the stage of advancement of the ageing of the structures. The occurrence of beta- and sigma-convergence of population structures in EU-27 in the years 2004–2020 and 2020–2050 were verified. The results indicate that absolute beta-convergence of the variables characterising the population structures in the EU countries happened in the past and will happen in around 2050. No unambiguous proof has been found for sigma-convergence, i.e., for any significant decrease over time in the diversity between the countries in terms of the studied variables that characterise the ageing process. In the past, the bottom-up ageing has occurred faster than the top-down ageing, while, in the future, it is expected to be the other way round.

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