To our knowledge, no current study has focused explicitly on pandemic fatigue, AS, and PTSS related to COVID-19 among university students. The purpose of this study was to describe the status of COVID-19 related pandemic fatigue and PTSS among university students in South Korea. We also examined the associations of pandemic fatigue and AS, along with COVID-19 related factors with PTSS in this population. A descriptive-correlational research design was used. Participants in this study were adults 18 years of age or older who lived in South Korea during the COVID-19 pandemic, were currently attending three or 4-year colleges and were native speakers of the Korean language. The number of study subjects was calculated using the G-Power program, with an effect size of 0.1, a significance level of 0.05, a power of 0.95, and 26 predictors required for multiple regression analysis. As a result, at least 358 subjects were required. Considering the dropout rate of 10%, 406 questionnaires were collected. After excluding 6 insincere questionnaires, 400 were included in the analysis. Participant students were from universities located in a diverse area in South Korea, including Seoul (the capital) and 9 provinces, with most of the participants (95.5%) from the large metropolitan areas of Seoul and K province.

We distributed the online survey using Google^® Forms between June 2021 and July 2021 to assess pandemic fatigue, AS, and PTSS during the COVID-19 pandemic. The survey link was published on university websites and online community dashboards. The Everytime (https://everytime.kr) is an online anonymous community dashboard for college students belonging to 400 universities in South Korea. It provides general information about college life, such as school life and academic management. Advertised universities include Ajou University, Gachon University, Yonsei University, Seoul National University, Suwon Science College, Dongguk University, Sungkyunkwan University, Hongik University, Korea National University of Arts, Soongsil University, Dongnam Health University, The University of Suwon, Duksung Women’s University, Dankook University, Seoul National University of Science and Technology, and Kookmin University. Information about the study was also posted on institutional homepages or on-campus bulletin boards (e.g., student halls, cafeterias, cafes, libraries, or on the student union hall) for recruitment. The study announcement described the purpose, method, and selection criteria of the study. A detailed explanation of the research was provided in a separate explanatory note, including a clause that there would be no disadvantages due to participation or non-participation in the research. We provided a QR code to access detailed information regarding the study and survey, and potential participants accessed the survey link through the QR code once they agreed to participate. Because of the nature of the online survey, voluntary participation was considered as consent to enroll in the study. Approximately 20–25 min were required to compete the survey; the survey was designed to proceed to the next item when all the previous items were completed to enhance the quality of the responses. Study participants were provided with mobile gift cards ($5) after the completion. The questionnaire consisted of two sections which investigated 1) demographics and COVID-19 related characteristics, 2) pandemic fatigue, AS, and PTSS.

Participant demographics and COVID-19-related characteristics, pandemic fatigue, AS, and PTSS levels were analyzed as descriptive statistics (n, %, mean, SD, range). Normality of the data was checked using histograms and normal probability plots, skewness, or kurtosis measures. An independent t-test or a one-way ANOVA was performed for differences in PTSS according to the participants’ demographics and COVID-19-related stressors. Pearson’s correlation coefficients were used to analyze the correlation among study variables, including pandemic fatigue, AS, and PTSS. The Benjamini-Hochberg procedure was used to control the false discovery rate for multiple comparisons in the bivariate analysis.

Linear mixed models nested by location of university were used to examine factors associated with PTSS. All variables designated as associated with PTSS in bivariate analysis were entered into the models along with several demographic characteristics (gender, major, education, and perceived economic status). Given the strong evidence of gender differences in the mental health characteristics during the COVID-19 pandemic [45, 46], we conducted a subgroup analysis by gender. Six out of 406 participants were excluded due to incomplete responses, and there were no missing data in the dataset. Multicollinearity was evaluated using VIF, residuals, and outliers to determine whether the independent variables were suitable for regression analysis. Data were analyzed using the STATA 15.1 (StataCorp, Texas, United States).

The average participant age was 21.7 years (SD = 2.6, range: 18–39 years). A majority were female (71.8%, n = 287) and attending a 4-year college (82.8%, n = 331). Fifty-two percent of the participants were attending a university located in Seoul, and 42.5% in K province the location of two metropolitan areas in South Korea. Academic fields of study of participating students were diverse, including basic science and engineering (39.5%), social science, humanities, and education (42.3%), and medical (11.5%). Almost half of the participants reported they were “satisfied” with their economic status (46.5%, n = 186). More than 70% of participants did not take any prescribed (86.0%, n = 344) or OTC medications (74.3%, n = 297), while 12.5% were currently smoking. The percent of participants reporting not consuming alcohol or caffeine was 23.8% and 13.8%, respectively (Table 1).

Fifty-six percent of participating university students reported staying at home most of the time or always to avoid infection. Most participants (95.9%) always wore a mask when going outside, and KF-94 masks specifically produced to avoid droplet infection were the most commonly used mask (58.2%). Fifty-six percent of participants watched news about COVID-19 for 1, 2 h per week. More than half (55.0%) of the participants had COVID-19-like symptoms in the past week, including coughing, chills, or runny nose. Approximately twenty-five percent of the participants had COVID-19 test, and all were negative. Most participants worried about COVID-19 exposure (75.3%) and going outside (68.8%) at moderate or higher levels. At the time of the survey, only 13% of the participants were vaccinated, but 85.3% of non-vaccinated participants answered they are likely or definitely getting vaccinated when it’s available. About fifty percent of participants were at least moderately worried about side effects of COVID-19 vaccines (Table 2).

The average of PTSS of the participants was 14.06 (SD = 5.04) and ranged from 6 to 29. Using the cutoff score of 10 previously validated for the IES-6 scale [39, 40], 32.3% of the participants self-reported levels of PTSS indicative of PTSD. The average total pandemic fatigue score was 22.27 (SD = 7.41), ranging from 6 to 40. The anxiety sensitivity level of the participants averaged 11.27 (SD = 8.75), ranging from 0 to 52 (Table 3).

Demographic and COVID-19 related factors associated with PTSS in the bivariate analysis included education, having been taking OTC/prescribed medication, staying home to avoid infection, mask type, having had COVID-19 like symptoms, worry about COVID-19 exposure, worry about going outside, and worry about side effects of COVID-19 vaccines (Supplementary S1–S3). Among these variables, mask type was excluded in the final model due to its low level of variance.

The linear mixed model (Table 4), nested by location of university, revealed that staying at home to avoid infection (β = 2.345, p < 0.001, 95% CI = [1.034, 3.656]), being worried about COVID-19 exposure (β = 1.404, p = 0.050, 95% CI = [0.003, 2.805]), COVID-19 fatigue (β = 0.124, p < 0.001, 95% CI = [0.062, 0.186]), and AS (β = 0.212, p < 0.001, 95% CI = [0.158, 0.265]) were significantly associated with PTSS after controlling for other demographic and COVID-19 related factors. Those who stayed at home about half of the time to avoid infection were estimated to be 2.3 units higher in PTSS compared to those who never or sometimes stayed home. Those who worried quite a bit or extremely about COVID-19 exposure were estimated to be 1.4 units higher in PTSS compared to those who worried not at all or a little bit. Higher COVID-19 fatigue and AS was associated with higher PTSS. Subgroup analysis by gender indicated that COVID-19 fatigue (β = 0.237, p < 0.001, 95% CI = [0.113, 0.360]) and AS (β = 0.262, p < 0.001, 95% CI = [0.139, 0.375]) were significantly associated with PTSS in males, while staying at home to avoid infection (β = 2.874, p = 0.001, 95% CI = [1.208, 4.540]), being worried about going outside due to COVID-19 (staying at home to avoid infection (β = 1.988, p = 0.029, 95% CI = [0.207, 3.768]), COVID-19 fatigue (β = 0.086, p = 0.017, 95% CI = [0.015, 0.157]), and AS (β = 0.208, p < 0.001, 95% CI = [0.148, 0.267]) were significantly associated with PTSS in females (Table 4).

One limitation of this study is that we collected data only from South Korean university students in urban areas where relatively high COVID-19 transmission exists. Also, risk of selection bias and response-set bias may have occurred due to the convenience sampling method and data collection using an online/self-reported format. Therefore, generalizability of our results is limited. The scales used to measure AS and pandemic fatigue have not previously been used or validated among South Koreans. However, the undertook a thorough translation process and the internal consistency of the scales from the current sample was adequate. Future studies validating these measures among South Korean population are needed. Other important factors affecting mental health among university students, including self-rated health status, and life-style such as spending times outside or on electronic screens [15] were not captured in this study. Lastly, the incidence, pattern, and mutation of SARS-CoV-2 is dynamic; therefore, it is necessary to longitudinally examine changes in PTSD-like symptomatology related to the COVID-19 pandemic among university students.

Covid-19 pandemic has been prolonged with new variants (e.g., Delta, Omicron), and their impact on mental health should be recognized. Approximately one-third of the university students reported having experienced PTSS related to COVID-19 indicative of clinical PTSD. Pandemic fatigue and AS was significantly associated with PTSS in this population. Based on the results of the current study, we suggest university-wide programs to enhance mental health status among students, including providing platforms of social networking and interactions with peers to share their thoughts and emotions. Using various forms of digital and other interactions, including messaging or calls using social media has been reported to be associated with better mental health among university students [60]. Easily accessible online counseling for students who need the service should be provided, especially during the pandemic. AS was previously reported associated with suicidal ideation and past suicide attempts [24], and more attention should be given regarding this issue among Korean university students during the COVID-19 pandemic. Based on the previous evidence on efficacy of brief cognitive interventions on AS reduction [61], we also suggest providing interventions through convenient therapy platforms, such as video-based intervention [62], online interactions using social media and email/phone calls to foster bonding and social connection [15] to reduce AS among vulnerable university students.