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Who suffered most?
(2022)
Objective:
This study examines gender and socioeconomic inequalities in parental psychological wellbeing (parenting stress and psychological distress) during the COVID-19 pandemic in Germany.
Background:
The dramatic shift of childcare and schooling responsibility from formal institutions to private households during the pandemic has put families under enormous stress and raised concerns about caregivers' health and wellbeing. Despite the overwhelming media attention to families’ wellbeing, to date limited research has examined parenting stress and parental psychological distress during the COVID-19 pandemic, particularly in Germany.
Method:
We analyzed four waves of panel data (N= 1,771) from an opt-in online survey, which was conducted between March 2020 and April 2021. Multivariable OLS regressions were used to estimate variations in the pandemic's effects on parenting stress and psychological distress by various demographic and socioeconomic characteristics.
Results:
Overall, levels of parenting stress and psychological distress increased during the pandemic. During the first and third wave of the COVID-19 pandemic, mothers, parents with children younger than 11 years, parents with two or more children, parents working from home as well as parents with financial insecurity experienced higher parenting stress than other sociodemographic groups. Moreover, women, respondents with lower incomes, single parents, and parents with younger children experienced higher levels of psychological distress than other groups.
Conclusion:
Gender and socioeconomic inequalities in parents' psychological wellbeing increased among the study participants during the pandemic.
Since COVID-19 became a pandemic, many studies are being conducted to get a better understanding of the disease itself and its spread. One crucial indicator is the prevalence of SARS-CoV-2 infections. Since this measure is an important foundation for political decisions, its estimate must be reliable and unbiased. This paper presents reasons for biases in prevalence estimates due to unit nonresponse in typical studies. Since it is difficult to avoid bias in situations with mostly unknown nonresponse mechanisms, we propose the maximum amount of bias as one measure to assess the uncertainty due to nonresponse. An interactive web application is presented that calculates the limits of such a conservative unit nonresponse confidence interval (CUNCI).
Time for change?
(2022)
Purpose:
This study aims to provide probable future developments in the form of holistic scenarios for business negotiations. In recent years, negotiation research did not put a lot of emphasis on external changes. Consequently, current challenges and trends are scarcely integrated, making it difficult to support negotiation practice perspectively.
Design/methodology/approach:
This paper applies the structured, multi-method approach of scenario analysis. To examine the future space of negotiations, this combines qualitative and quantitative measures to base our analysis on negotiation experts’ assessments, estimations and visions of the negotiation future.
Findings:
The results comprise an overview of five negotiation scenarios in the year 2030 and of their individual drivers. The five revealed scenarios are: digital intelligence, business as usual, powerful network – the route to collaboration, powerful network – the route to predominance and system crash.
Originality/value:
The scenario analysis is a suitable approach that enables to relate various factors of the negotiation environment to negotiations themselves and allows an examination of future changes in buyer–seller negotiations and the creation of possible future scenarios. The identified scenarios provide an orientation for business decisions in the field of negotiation.
The hospitality industry worldwide is among the hardest-hit industries from the COVID-19 lockdowns. Initial theoretical and practical observations in the hospitality industry indicate that business model innovation (BMI) might be a solution to recover from and successfully cope with the COVID-19 crisis. Interestingly, some firms in the hospitality industry already started to successfully adapt their business models. This study explores the why and how of these successful recovery attempts through BMI by conducting a multiple case study of six hospitality firms in Austria. We rely on interview data from managers together with one of their main stammgasts for each case, which we triangulate with secondary data for the analysis. Findings show that BMI is applied during and after the crisis to create new revenue streams and secure a higher level of liquidity, with an important role of stammgasts.
Despite new challenges like climate change and digitalization, global and regional organizations recently went through turbulent times due to a lack of support from several of their member states. Next to this crisis of multilateralism, the COVID-19 pandemic now seems to question the added value of international organizations for addressing global governance issues more specifically. This article analyses this double challenge that several organizations are facing and compares their ways of managing the crisis by looking at their institutional and political context, their governance structure, and their behaviour during the pandemic until June 2020. More specifically, it will explain the different and fragmented responses of the World Health Organization, the European Union and the International Monetary Fund/World Bank. With the aim of understanding the old and new problems that these international organizations are trying to solve, this article argues that the level of autonomy vis-a-vis the member states is crucial for understanding the politics of crisis management. <br /> Points for practitioners <br /> As intergovernmental bodies, international organizations require authorization by their member states. Since they also need funding for their operations, different degrees of autonomy also matter for reacting to emerging challenges, such as the COVID-19 pandemic. The potential for international organizations is limited, though through proactive and bold initiatives, they can seize the opportunity of the crisis and partly overcome institutional and political constraints.
Background:
There is evidence that fully recovered COVID-19 patients usually resume physical exercise, but do not perform at the same intensity level performed prior to infection. The aim of this study was to evaluate the impact of COVID-19 infection and recovery as well as muscle fatigue on cardiorespiratory fitness and running biomechanics in female recreational runners.
Methods:
Twenty-eight females were divided into a group of hospitalized and recovered COVID-19 patients (COV, n = 14, at least 14 days following recovery) and a group of healthy age-matched controls (CTR, n = 14). Ground reaction forces from stepping on a force plate while barefoot overground running at 3.3 m/s was measured before and after a fatiguing protocol. The fatigue protocol consisted of incrementally increasing running speed until reaching a score of 13 on the 6-20 Borg scale, followed by steady-state running until exhaustion. The effects of group and fatigue were assessed for steady-state running duration, steady-state running speed, ground contact time, vertical instantaneous loading rate and peak propulsion force.
Results:
COV runners completed only 56% of the running time achieved by the CTR (p < 0.0001), and at a 26% slower steady-state running speed (p < 0.0001). There were fatigue-related reductions in loading rate (p = 0.004) without group differences. Increased ground contact time (p = 0.002) and reduced peak propulsion force (p = 0.005) were found for COV when compared to CTR.
Conclusion:
Our results suggest that female runners who recovered from COVID-19 showed compromised running endurance and altered running kinetics in the form of longer stance periods and weaker propulsion forces. More research is needed in this area using larger sample sizes to confirm our study findings.
Background: There is evidence that fully recovered COVID-19 patients usually resume physical exercise, but do not perform at the same intensity level performed prior to infection. The aim of this study was to evaluate the impact of COVID-19 infection and recovery as well as muscle fatigue on cardiorespiratory fitness and running biomechanics in female recreational runners.
Methods: Twenty-eight females were divided into a group of hospitalized and recovered COVID-19 patients (COV, n = 14, at least 14 days following recovery) and a group of healthy age-matched controls (CTR, n = 14). Ground reaction forces from stepping on a force plate while barefoot overground running at 3.3 m/s was measured before and after a fatiguing protocol. The fatigue protocol consisted of incrementally increasing running speed until reaching a score of 13 on the 6–20 Borg scale, followed by steady-state running until exhaustion. The effects of group and fatigue were assessed for steady-state running duration, steady-state running speed, ground contact time, vertical instantaneous loading rate and peak propulsion force.
Results: COV runners completed only 56% of the running time achieved by the CTR (p < 0.0001), and at a 26% slower steady-state running speed (p < 0.0001). There were fatigue-related reductions in loading rate (p = 0.004) without group differences. Increased ground contact time (p = 0.002) and reduced peak propulsion force (p = 0.005) were found for COV when compared to CTR.
Conclusion: Our results suggest that female runners who recovered from COVID-19 showed compromised running endurance and altered running kinetics in the form of longer stance periods and weaker propulsion forces. More research is needed in this area using larger sample sizes to confirm our study findings.
The COVID-19 pandemic and related closures of day care centres and schools significantly increased the amount of care work done by parents. There has been much speculation over whether the pandemic increased or decreased gender equality in parental care work. Based on representative data for Germany from spring 2020 and winter 2021 we present an empirical analysis that shows that although gender inequality in the division of care work increased to some extent in the beginning of the pandemic, it returned to the pre-pandemic level in the second lockdown almost nine months later. These results suggest that the COVID-19 pandemic neither aggravated nor lessened inequality in the division of unpaid care work among mothers and fathers in any persistent way in Germany.
The economics of COVID-19
(2020)
Purpose
Within a very short period of time, the worldwide pandemic triggered by the novel coronavirus has not only claimed numerous lives but also caused severe limitations to daily private as well as business life. Just about every company has been affected in one way or another. This first empirical study on the effects of the COVID-19 crisis on family firms allows initial conclusions to be drawn about family firm crisis management.
Design/methodology/approach
Exploratory qualitative research design based on 27 semi-structured interviews with key informants of family firms of all sizes in five Western European countries that are in different stages of the crisis.
Findings
The COVID-19 crisis represents a new type and quality of challenge for companies. These companies are applying measures that can be assigned to three different strategies to adapt to the crisis in the short term and emerge from it stronger in the long run. Our findings show how companies in all industries and of all sizes adapt their business models to changing environmental conditions within a short period of time. Finally, the findings also show that the crisis is bringing about a significant yet unintended cultural change. On the one hand, a stronger solidarity and cohesion within the company was observed, while on the other hand, the crisis has led to a tentative digitalization.
Originality/value
To the knowledge of the authors, this is the first empirical study in the management realm on the impacts of COVID-19 on (family) firms. It provides cross-national evidence of family firms' current reactions to the crisis.
Due to the COVID-19 pandemic, all schools in Germany were locked down for several months in 2020. How schools realized teaching during the school lockdown greatly varied from school to school. N = 2,647 parents participated in an online survey and rated the following activities of teachers in mathematics, language arts (German), English, and science / biology during the school lockdown: frequency of sending task assignments, task solutions and requesting for solutions, giving task-related feedback, grading tasks, providing lessons per videoconference, and communicating via telecommunication tools with students and / or parents. Parents also reported student academic outcomes during the school lockdown (child's learning motivation, competent and independent learning, learning progress). Parents further reported student characteristics and social background variables: child's negative emotionality, school engagement, mathematical and language competencies, and child's social and cultural capital. Data were separately analyzed for elementary and secondary schools. In both samples, frequency of student-teacher communication was associated with all academic outcomes, except for learning progress in elementary school. Frequency of parent-teacher communication was associated with motivation and learning progress, but not with competent and independent learning, in both samples. Other distant teaching activities were differentially related to students' academic outcomes in elementary vs. secondary school. School engagement explained most additional variance in all students' outcomes during the school lockdown. Parent's highest school leaving certificate incrementally predicted students' motivation, and competent and independent learning in secondary school, as well as learning progress in elementary school. The variable "child has own bedroom" additionally explained variance in students' competent and independent learning during the school lockdown in both samples. Thus, both teaching activities during the school lockdown as well as children's characteristics and social background were independently important for students' motivation, competent and independent learning, and learning progress. Results are discussed with regard to their practical implications for realizing distant teaching.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics
(2021)
Newly emerging pandemics like COVID-19 call for predictive models to implement precisely tuned responses to limit their deep impact on society. Standard epidemic models provide a theoretically well-founded dynamical description of disease incidence. For COVID-19 with infectiousness peaking before and at symptom onset, the SEIR model explains the hidden build-up of exposed individuals which creates challenges for containment strategies. However, spatial heterogeneity raises questions about the adequacy of modeling epidemic outbreaks on the level of a whole country. Here, we show that by applying sequential data assimilation to the stochastic SEIR epidemic model, we can capture the dynamic behavior of outbreaks on a regional level. Regional modeling, with relatively low numbers of infected and demographic noise, accounts for both spatial heterogeneity and stochasticity. Based on adapted models, short-term predictions can be achieved. Thus, with the help of these sequential data assimilation methods, more realistic epidemic models are within reach.
Background:
Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial.
Objective:
This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others.
Methods:
A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables.
Results:
Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one's own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that "too much" concern leads to defensive reactions and reduces app uptake.
Conclusions:
As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.
Reacting, fast and slow
(2021)
The COVID-19 pandemic created extraordinary challenges for governments to safeguard the well-being of their people. To what extent has leaders' reliance on scientific advice shaped government responses to the COVID-19 outbreak? We argue that leaders who tend to orient themselves on expert advice realized the extent of the crisis earlier. Consequently, these governments would adopt containment measures relatively quickly, despite the high uncertainty they faced. Over time, differences in government responses based on the use of science would dissipate due to herding effects. We test our argument on data combining 163 government responses to the pandemic with national- and individual-level characteristics. Consistent with our argument, we find that countries governed by politicians with a stronger technocratic mentality, approximated by holding a PhD, adopted restrictive containment measures faster in the early, but not in the later, stages of the crisis. This importance of expert-based leadership plausibly extends to other large-scale societal crises.
There is an urgent need for screening of patients with a communicable viral disease to cut infection chains. Recently, we demonstrated that ion mobility spectrometry coupled with a multicapillary column (MCC-IMS) is able to identify influenza-A infections in patients' breath. With a decreasing influenza epidemic and upcoming SARS-CoV-2 infections we proceeded further and analyzed patients with suspected SARS-CoV-2 infections. In this study, the nasal breath of 75 patients (34 male, 41 female, aged 64.4 +/- 15.4 years) was investigated by MCC-IMS for viral infections. Fourteen were positively diagnosed with influenza-A infection and sixteen with SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) of nasopharyngeal swabs. In one patient RT-PCR was highly suspicious of SARS-CoV-2 but initially inconclusive. The remaining 44 patients served as controls. Breath fingerprints for specific infections were assessed by a combination of cluster analysis and multivariate statistics. There were no significant differences in gender or age according to the groups. In the cross validation of the discriminant analysis 72 of the 74 clearly defined patients could be correctly classified to the respective group. Even the inconclusive patient could be mapped to the SARS-CoV-2 group by applying the discrimination functions. Conclusion: SARS-CoV-2 infection and influenza-A infection can be detected with the help of MCC-IMS in breath in this pilot study. As this method provides a fast non-invasive diagnosis it should be further developed in a larger cohort for screening of communicable viral diseases. A validation study is ongoing during the second wave of COVID-19.
Trial registration: ClinicalTrial.gov, NCT04282135 Registered 20 February 2020-Retrospectively registered,
This paper examines and discusses the biases and pitfalls of retrospective survey questions that are currently being used in many medical, epidemiological, and sociological studies on the COVID-19 pandemic. By analyzing the consistency of answers to retrospective questions provided by respondents who participated in the first two waves of a survey on the social consequences of the COVID-19 pandemic, we illustrate the insights generated by a large body of survey research on the use of retrospective questions and recall accuracy.
Background and objectives
AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited.
Design, setting, participants, & measurements
Using data from adult patients hospitalized with COVID-19 from five hospitals from theMount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to theMount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission.
Results
A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93-0.98) and area under the precisionrecall curve (AUPRC; range of 0.78-0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85-0.87, and AUPRC range of 0.27-0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model's prediction.
Conclusions
An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models.
Toll-like receptor (TLR) can trigger an immune response against virus including SARS-CoV-2. TLR expression/distribution is varying in mesenchymal stromal cells (MSCs) depending on their culture environments. Here, to explore the effect of periodic thermomechanical cues on TLRs, thermally controlled shape-memory polymer sheets with programmable actuation capacity were created. The proportion of MSCs expressing SARS-CoV-2-associated TLRs was increased upon stimulation. The TLR4/7 colocalization was promoted and retained in the endoplasmic reticula. The TLR redistribution was driven by myosin-mediated F-actin assembly. These results highlight the potential of boosting the immunity for combating COVID-19 via thermomechanical preconditioning of MSCs.
Background Mass gatherings (MGs) such as music festivals and sports events have been associated with a high risk of SARS-CoV-2 transmission. On-site research can foster knowledge of risk factors for infections and improve risk assessments and precautionary measures at future MGs. We tested a web-based participatory disease surveillance tool to detect COVID-19 infections at and after an outdoor MG by collecting self-reported COVID-19 symptoms and tests. Methods We conducted a digital prospective observational cohort study among fully immunized attendees of a sports festival that took place from September 2 to 5, 2021 in Saxony-Anhalt, Germany. Participants used our study app to report demographic data, COVID-19 tests, symptoms, and their contact behavior. This self-reported data was used to define probable and confirmed COVID-19 cases for the full "study period" (08/12/2021 - 10/31/2021) and within the 14-day "surveillance period" during and after the MG, with the highest likelihood of an MG-related COVID-19 outbreak (09/04/2021 - 09/17/2021). Results A total of 2,808 of 9,242 (30.4%) event attendees participated in the study. Within the study period, 776 individual symptoms and 5,255 COVID-19 tests were reported. During the 14-day surveillance period around and after the MG, seven probable and seven PCR-confirmed COVID-19 cases were detected. The confirmed cases translated to an estimated seven-day incidence of 125 per 100,000 participants (95% CI [67.7/100,000, 223/100,000]), which was comparable to the average age-matched incidence in Germany during this time. Overall, weekly numbers of COVID-19 cases were fluctuating over the study period, with another increase at the end of the study period. Conclusion COVID-19 cases attributable to the mass gathering were comparable to the Germany-wide age-matched incidence, implicating that our active participatory disease surveillance tool was able to detect MG-related infections. Further studies are needed to evaluate and apply our participatory disease surveillance tool in other mass gathering settings.