SALBIS Research Group, Department of Electric, Systems and Automatics Engineering, Universidad de León, Campus of Vegazana s/n, 24071, León, Spain.
The Research Group in Gen-Environment and Health Interactions (GIIGAS), Institute of Biomedicine (IBIOMED), Universidad de León, 24071, León, Spain.
Sci Rep. 2021 Jul 21;11(1):14877. doi: 10.1038/s41598-021-94383-2.
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.
新冠疫情意味着大学生不得不调整学习方式，社交环境也受到限制。逆境环境会根据人际关系来塑造人类行为模式。但是，目前缺乏分析大学生在大流行背景下基于其社会结构的行为的研究。这些信息对于制定如何规划集体应对逆境的决策可能很有用。我们选择社会网络分析（SNA）方法来解决这个结构问题。我们的研究目的是描述新冠疫情期间大学生在大学宿舍中的结构行为，并更深入地分析学生领袖。这是一项在西班牙莱昂的一所公立大学进行的描述性横断面研究，时间为 2020 年 10 月 23 日至 11 月 20 日。共有 93 名学生参加了来自四个宿舍的研究。数据是从大学专门为“追踪”新冠疫情中的接触情况而创建的数据库 SiVeUle 中收集的。我们应用 SNA 分析数据。使用中心度测量法来衡量大学宿舍的领导力。通过 Egonetwork 分析和关键人物评估来分析顶级领袖。社会声誉较高的学生在新冠感染方面的疫情传播率更高。网络中心度与新冠感染结果之间的关系具有统计学意义。网络中的最主要学生表现出较高的桥接程度，并且有三名学生在网络中具有关键人物结构。宿舍中大学生的社交行为可能与新冠疫情的传播有关。这可以根据学生之间的相似性方面来描述，甚至可以描述领导者连接同居子网的情况。在这种情况下，社会网络分析可以被视为健康紧急情况网络研究的一种方法。
