Nepal Subigya, Wang Weichen, Vojdanovski Vlado, Huckins Jeremy F, daSilva Alex, Meyer Meghan, Campbell Andrew
Dartmouth College, Hanover, NH, USA.
Biocogniv Inc., Burlington, VT, USA.
Proc SIGCHI Conf Hum Factor Comput Syst. 2022 Apr;2022. doi: 10.1145/3491102.3502043. Epub 2022 Apr 28.
The COVID-19 pandemic continues to affect the daily life of college students, impacting their social life, education, stress levels and overall mental well-being. We study and assess behavioral changes of N=180 undergraduate college students one year prior to the pandemic as a baseline and then during the first year of the pandemic using mobile phone sensing and behavioral inference. We observe that certain groups of students experience the pandemic very differently. Furthermore, we explore the association of self-reported COVID-19 concern with students' behavior and mental health. We find that heightened COVID-19 concern is correlated with increased depression, anxiety and stress. We evaluate the performance of different deep learning models to classify student COVID-19 concerns with an AUROC and F1 score of 0.70 and 0.71, respectively. Our study spans a two-year period and provides a number of important insights into the life of college students during this period.
新冠疫情持续影响着大学生的日常生活，冲击着他们的社交生活、教育、压力水平以及整体心理健康。我们以疫情爆发前一年N = 180名本科大学生的行为变化作为基线进行研究和评估，然后在疫情第一年使用手机传感和行为推断进行研究。我们观察到，某些学生群体对疫情的体验截然不同。此外，我们探讨了自我报告的对新冠疫情的担忧与学生行为和心理健康之间的关联。我们发现，对新冠疫情的高度担忧与抑郁、焦虑和压力的增加相关。我们评估了不同深度学习模型对学生新冠疫情担忧程度进行分类的性能，其受试者工作特征曲线下面积（AUROC）和F1分数分别为0.70和0.71。我们的研究跨越两年时间，为这一时期大学生的生活提供了许多重要见解。
