Leadership and contagion by COVID-19 among residence hall students: A social network analysis approach.

University students have changed their behaviour due to the COVID-19 pandemic. In this paper, we describe the characteristics of PCR+ and PCR- nodes, analyse the structure, and relate the structure of student leaders to pandemic contagion as determined by PCR+ in 93 residential university students. Leadership comes from the male students of social science degrees who have PCR +, with an eigenvector centrality structure, ß-centrality, and who are part of the bow-tie structure. There was a significant difference in ß-centrality between leaders and non-leaders and in ß-centrality between PCR+ and non-leaders. Leading nodes were part of the bow-tie structure. MR-QAP results show how residence and scientific branch were the most important factors in network formation. Therefore, university leaders should consider influential leaders, as they are vectors for disseminating both positive and negative outcomes.

Identification of cohesive subgroups in a university hall of residence during the COVID-19 pandemic using a social network analysis approach.

THE AIMS: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan-Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan-Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.

A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence.

The COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

Musculoskeletal Pain and Teleworking in Times of the COVID-19: Analysis of the Impact on the Workers at Two Spanish Universities.

The special situation brought about by the coronavirus pandemic and the confinement imposed by the Government, has given rise to numerous changes in working habits. The workers at the universities have had to start a period of teleworking that could give rise to consequences for the musculoskeletal system. The objective of this article is to analyze the impact of the confinement on the musculoskeletal health of the staff of two Spanish universities. A cross-sectional, observational study was carried out on the workers. Data was taken in April-May 2020 and included: The Standardized Kuorinka Modified Nordic Questionnaire, the Perceived Stress Scale and another one on sociodemographic data. This study comprised 472 people. The areas of pain noted during the confinement period concluded that it was less in all cases (p < 0.001). The frequency of physical activity carried out increased significantly during the period of confinement (p < 0.04), especially in women. The type of physical activity done was also seen to modify during this period (p < 0.001), with a preference for strength training and stretching exercises. In conclusion, the confinement gave rise to changes in the lifestyle and in the musculoskeletal pain of the workers at the universities. All of this must be taken into account by health institutions and those responsible for the Prevention of Occupational Risks at Spanish universities.

Stress, Emotional Intelligence and the Intention to Use Cannabis in Spanish Adolescents: Influence of COVID-19 Confinement.

The disease brought about by the SARS-CoV-2, COVID-19 coronavirus has had an unprecedented global impact. Confinement to control the outbreak may have mental health consequences for the most vulnerable in the population, including adolescents. This study aims to describe and analyze the relationships between the stress variables, Emotional Intelligence and the intention to use cannabis in healthy adolescents, before and after the end of the COVID-19 pandemic containment stage. A comparative correlational study was carried out with validated self-completed questionnaires through an online platform. The sample is made up of adolescents (n = 300) aged 13-17 from two different schools in Ponferrada (León, Spain). The analysis of correlation and differences between the groups indicate that confinement has had effects on the mental health of the adolescents, specifically on the emotional manifestations of stress. Furthermore, significant gender differences were found for stress values and Emotional Intelligence. However, no differences have been found for cannabis use intention.

Musculoskeletal Pain and Teleworking in Times of the COVID-19: Analysis of the Impact on the Workers at Two Spanish Universities

The special situation brought about by the coronavirus pandemic and the confinement imposed by the Government, has given rise to numerous changes in working habits. The workers at the universities have had to start a period of teleworking that could give rise to consequences for the musculoskeletal system. The objective of this article is to analyze the impact of the confinement on the musculoskeletal health of the staff of two Spanish universities. A cross-sectional, observational study was carried out on the workers. Data was taken in April–May 2020 and included: The Standardized Kuorinka Modified Nordic Questionnaire, the Perceived Stress Scale and another one on sociodemographic data. This study comprised 472 people. The areas of pain noted during the confinement period concluded that it was less in all cases (p <0.001). The frequency of physical activity carried out increased significantly during the period of confinement (p <0.04), especially in women. The type of physical activity done was also seen to modify during this period (p <0.001), with a preference for strength training and stretching exercises. In conclusion, the confinement gave rise to changes in the lifestyle and in the musculoskeletal pain of the workers at the universities. All of this must be taken into account by health institutions and those responsible for the Prevention of Occupational Risks at Spanish universities.

Musculoskeletal Pain and Non-Classroom Teaching in Times of the COVID-19 Pandemic: Analysis of the Impact on Students from Two Spanish Universities.

The lockdown, due to the coronavirus, has led to a change in lifestyle and physical activity in Spanish university students. The objective of this study was to analyze the prevalence of musculoskeletal pain and changes in physical activity and self-perceived stress in the student bodies of two Spanish Universities during the lockdown. A cross-sectional study was carried out in a sample of 1198 students (70.6% women). The main instruments used for measuring were the Standardized Kuorinka Modified Nordic Questionnaire and the Perceived stress scale (the questionnaire regarding the practice of physical activity). A reduction in the prevalence of musculoskeletal pain (p < 0.001) was identified in the sample of men and women, an increase (12.5%) in the frequency of carrying out physical activity from moderate to frequent, and the preference for strength training (15.1%), especially among women, was identified. All of this may be taken into account by health institutions when implementing measures to encourage physical activity in both suitable amounts and types, which improves the quality of life of the students.

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19.

COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated in order to find correlations between these habits and mortality rates caused by COVID-19 using machine learning techniques that group the countries together according to the different distribution of fat, energy, and protein across 23 different types of food, as well as the amount ingested in kilograms. Results shown how obesity and the high consumption of fats appear in countries with the highest death rates, whereas countries with a lower rate have a higher level of cereal consumption accompanied by a lower total average intake of kilocalories.

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated in order to find correlations between these habits and mortality rates caused by COVID-19 using machine learning techniques that group the countries together according to the different distribution of fat, energy, and protein across 23 different types of food, as well as the amount ingested in kilograms. Results shown how obesity and the high consumption of fats appear in countries with the highest death rates, whereas countries with a lower rate have a higher level of cereal consumption accompanied by a lower total average intake of kilocalories.