Serrano-Macias Maribel, Alvarez-Galvez Javier
Department of General Economy (Sociology), Faculty of Nursing and Physiotherapy, University of Cádiz, 11009 Cádiz, Spain.
Computational Social Science DataLab (CS2 DataLab), University Institute for Social Sustainable Development, University of Cádiz, 11405 Jerez de la Frontera, Spain.
Behav Sci (Basel). 2024 Aug 23;14(9):735. doi: 10.3390/bs14090735.
The COVID-19 pandemic has contributed to the increase in mortality and morbidity rates globally, but it has also led to a generalized worsening of mental health and risk behaviors in different population groups regardless of the measures adopted by different governments. In this paper, using data from a Spanish survey of emotional well-being, we aim to explore through mixed graphical models the complex structure of relationships between the mental health of populations, their lifestyles, and forms of cultural and leisure consumption during the pandemic. The results bring to light some interesting findings, such as the association between teleworking and greater rest or greater stress with the use of social media, a variable that enables the connection with other mental health problems of greater severity. Increased physical activity and the consumption of streaming content at home, as well as increased care for family, friends, and neighbors, are some of the variables that show relevant associations. These findings highlight the usefulness and versatility of this network approach for the study of health behaviors and health outcomes, which offer the researcher a holistic and organic view of the relational structure of complex data characterized by high dimensionality and variables with different levels of measurement.
新冠疫情导致全球死亡率和发病率上升，但也导致不同人群的心理健康和风险行为普遍恶化，无论各国政府采取何种措施。在本文中，我们利用西班牙一项关于情绪健康的调查数据，旨在通过混合图形模型探讨疫情期间人群心理健康、生活方式以及文化和休闲消费形式之间复杂的关系结构。研究结果揭示了一些有趣的发现，比如远程工作与更多休息或使用社交媒体带来的更大压力之间的关联，社交媒体这一变量还与更严重的其他心理健康问题相关。增加体育活动、在家消费流媒体内容，以及增加对家人、朋友和邻居的关心，都是显示出相关关联的一些变量。这些发现凸显了这种网络方法在研究健康行为和健康结果方面的实用性和通用性，它为研究人员提供了一个整体且有机的视角，以审视具有高维度和不同测量水平变量的复杂数据的关系结构。
