Characteristics of Adaptation in Undergraduate University Students Suddenly Exposed to Fully Online Education During the COVID-19 Pandemic

Daiki Ishimaru; Hiroyoshi Adachi; Hajime Nagahara; Shizuka Shirai; Haruo Takemura; Noriko Takemura; Alizadeh Mehrasa; Teruo Higashino; Yasushi Yagi; Manabu Ikeda

doi:10.3389/fpsyt.2021.731137

Characteristics of Adaptation in Undergraduate University Students Suddenly Exposed to Fully Online Education During the COVID-19 Pandemic

Front Psychiatry. 2021 Sep 13:12:731137. doi: 10.3389/fpsyt.2021.731137. eCollection 2021.

Authors

Affiliations

¹ Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.
² Health and Counseling Center, Osaka University, Toyonaka, Japan.
³ Department of Artificial Intelligence and Mathematics, Institute for Datability Science, Osaka University, Suita, Japan.
⁴ Infomedia Education Research Division, Cybermedia Center, Osaka University, Toyonaka, Japan.
⁵ Language Education Support Research Division, Cybermedia Center, Osaka University, Toyonaka, Japan.
⁶ Department of Information Networking, Osaka University Graduate School of Information Science and Technology, Suita, Japan.
⁷ Department of Intelligent Media, The Institute of Scientific and Industrial Research, Osaka University, Ibaraki, Japan.

Abstract

This study aimed to clarify the adaptation features of University students exposed to fully online education during the novel coronavirus disease 2019 (COVID-19) pandemic and to identify accompanying mental health problems and predictors of school adaptation. The pandemic has forced many universities to transition rapidly to delivering online education. However, little is known about the impact of this drastic change on students' school adaptation. This cross-sectional study used an online questionnaire, including assessments of impressions of online education, study engagement, mental health, and lifestyle habits. In total, 1,259 students were assessed. The characteristics of school adaptation were analyzed by a two-step cluster analysis. The proportion of mental health problems was compared among different groups based on a cluster analysis. A logistic regression analysis was used to identify predictors of cluster membership. P-values < 0.05 were considered statistically significant. The two-step cluster analysis determined three clusters: school adaptation group, school maladaptation group, and school over-adaptation group. The last group significantly exhibited the most mental health problems. Membership of this group was significantly associated with being female (OR = 1.42; 95% CI 1.06-1.91), being older (OR = 1.21; 95% CI 1.01-1.44), those who considered online education to be less beneficial (OR = 2.17; 95% CI 1.64-2.88), shorter sleep time on weekdays (OR = 0.826; 95% CI 0.683-.998), longer sleep time on holidays (OR = 1.21; 95% CI 1.03-1.43), and worse restorative sleep (OR = 2.27; 95% CI 1.81-2.86). The results suggest that academic staff should understand distinctive features of school adaptation owing to the rapid transition of the educational system and should develop support systems to improve students' mental health. They should consider ways to incorporate online classes with their lectures to improve students' perceived benefits of online education. Additionally, educational guidance on lifestyle, such as sleep hygiene, may be necessary.

Keywords: COVID-19; University students; mental health; online learning; school adaptation.