Sleep Quality In College Students Research Articles

The relationship between sleep quality and daytime dysfunction among college students in China during COVID-19: a cross-sectional study.

College Students' sleep quality and daytime dysfunction have become worse since the COVID-19 outbreak, the purpose of this study was to explore the relationship between sleep quality and daytime dysfunction among college students during the COVID-19 (Corona Virus Disease 2019) period. This research adopts the form of cluster random sampling of online questionnaires. From April 5 to 16 in 2022, questionnaires are distributed to college students in various universities in Fujian Province, China and the general information questionnaire and PSQI scale are used for investigation. SPSS26.0 was used to conduct an independent sample t-test and variance analysis on the data, multi-factorial analysis was performed using logistic regression analysis. The main outcome variables are the score of subjective sleep quality and daytime dysfunction. During the COVID-19 period, the average PSQI score of the tested college students was 6.17 ± 3.263, and the sleep disorder rate was 29.6%, the daytime dysfunction rate was 85%. Being female, study liberal art/science/ engineering, irritable (due to limited outdoor), prolong electronic entertainment time were associated with low sleep quality (p < 0.001), and the occurrence of daytime dysfunction was higher than other groups (p < 0.001). Logistics regression analysis showed that sleep quality and daytime dysfunction were associated with gender, profession, irritable (due to limited outdoor), and prolonged electronic entertainment time (p < 0.001). During the COVID-19 epidemic, the sleep quality of college students was affected, and different degrees of daytime dysfunction have appeared, both are in worse condition than before the COVID-19 outbreak. Sleep quality may was inversely associated with daytime dysfunction.

Effect of physical exercise on sleep quality in college students: Mediating role of smartphone use.

To investigate the effect of physical exercise on sleep quality and the mediating effect of smartphone use behavior in college students. A cross-sectional study design was adopted. An online survey of 5,075 college students was conducted using the Physical Activity Rating Scale-3, the Pittsburgh Sleep Quality Index, and the Mobile Phone Addiction Tendency Scale. The sleep quality of college students was poor, and the proportion of college students with good sleep quality was 23.567%. A significant correlation existed between sleep quality and physical exercise (r = -0.159, P < 0.001) and mobile phone addiction (r = 0.355, P < 0.001). Physical exercise can predict sleep quality in college students (β = -0.011, P < 0.001). Smartphone use plays a part in mediating the process by which physical exercise affects sleep quality. Chinese college students have poor sleep quality. Physical exercise and smartphone use behavior are important factors affecting the sleep quality of college students. Physical exercise can directly predict the sleep quality of college students and can predict the sleep quality of college students through the mediating effect of smartphone use behavior.

12주 필라테스 교양체육수업이 대학생의 신체구성, 신체활동 수준, 수면의 질에 미치는 영향

12주 필라테스 교양체육수업이 대학생의 신체구성, 신체활동 수준, 수면의 질에 미치는 영향

Increased Salivary IL-1 Beta Level Is Associated with Poor Sleep Quality in University Students.

Poor sleep quality is a major public health concern for all ages. In particular, university students often face stress levels and changes in social life habits that negatively influence their quality of sleep. This could be associated with psychological well-being in terms of anxiety and depressive symptoms, stress levels, and a poor self-perceived health status. The increases in the pro-inflammatory cytokine interleukin 6 (IL-6), IL-1 beta (IL-1β), and tumor necrosis factor alpha (TNFα), in blood have been linked to poor sleep quality in many diseases, but data on salivary cytokine levels in students are missing or are seldom analyzed. In this study we determined the quality of sleep in a sample of university students and the role of psychological assessment and factors affecting sleep (alcohol intake, tobacco, consumption of stimulant drinks, exercise, and body mass index). We also aimed to shed new light on the associations between sleep quality and salivary inflammatory cytokines (IL-1β, IL-6, and TNFα). Sleep quality was measured with the Athens Insomnia Scale (AIS) and Pittsburgh Sleep Quality Index (PSQI). Perceived stress was assessed using Cohen's Perceived Stress Scale (PSS), and the Goldberg Anxiety and Depression Scale (GADS) was used to assess the level of anxiety or depression. Perceived health status was measured with a visual analogue. Saliva samples was taken in the morning and the inflammatory cytokines was measured via enzyme-linked immunoassay. There was a direct and significant association between the salivary IL-1β concentration and AIS score (r = 0.248; p = 0.038, Pearson correlation) and Pittsburgh scale score (r = 0.274; p = 0.022, Pearson correlation). The relationship between IL-1β and AIS controlling for sex, age, and chronic disease, is still significant (r = 0.260; p = 0.033). The relationship between IL-1β and PSQI controlling for the influence of these variables is also significant (r = 0.279; p = 0.022). Salivary IL-1β concentrations were not significantly associated with any of the scores of the other psychological assessments (PSS, anxiety, depression symptoms, or self-perceived health). Salivary TNFα was significantly and inversely associated with self-perceived health (r = -0.259; p = 0.033, Pearson correlation), but the salivary IL-6 concentration was not associated with any of the sleep quality scale or psychological assessment scores. Our results provide a novel relationship between pro-inflammatory cytokine IL-1β in saliva and poor sleep quality. However, the role of inflammation in poor sleep quality requires further study to identify strategies that could lower inflammation and thus, likely improve sleep quality.

Exploring associations between social media addiction, social media fatigue, fear of missing out and sleep quality among university students: A cross-section study.

Social media use has been linked to poor sleep outcomes among university students in the cyber age, but the association between the negative consequences of social media use and sleep problems is not yet well understood. The present study investigated the relationships among social media usage, social media fatigue (SMF), fear of missing out (FoMO), social media addiction (SMA) and sleep quality in university students. An online survey was administered to 2744 respondents that included the Pittsburgh Sleep Quality Index (PSQI); questionnaires evaluating FoMO, SMF, and SMA; and questions regarding sleep duration, social media use, health status, and demographic information. A total of 19.9% of respondents suffered from sleep disturbance. A total of 15.6% of participants had sleep durations less than 5 h, and 21.6% of subjects had sleep durations longer than 9 h. Sleep quality was positively associated with SMF (OR = 1.387, 95% CI: 1.103~1.743), and SMA (OR = 1.415, 95% CI: 1.118~1.791). The relationship between FoMO and sleep disturbance was not significant. Compared to a sleep duration > 9 h, SMF increased the risk of shorter sleep durations [5-6 h sleep (OR = 2.226, 95% CI: 1.132~4.375), 6-7 h sleep (OR = 1.458, 95% CI: 1.061~2.002), and 7-8 h sleep (OR = 1.296, 95% CI: 1.007~1.670)]. FoMO and SMA did not significantly affect sleep duration. In addition, SMA (OR = 3.775, 95% CI: 3.141~4.537), FoMO (OR = 3.301, 95% CI: 2.753~3.958), and sleep disorders (OR = 1.284, 95% CI: 1.006~1.638) increased SMF. Upon experiencing negative consequences of social media use, such as SMF and SMA, university students were likely to experience sleep problems. Further research exploring the interventions that improve sleep and alleviate negative consequences of social media use should be conducted.

Poor sleep quality and stress differentially predict delay discounting for food, but not money, in college students

AbstractEarly college is a time when eating habits change and subsequent weight gain may occur. Moreover, college students report higher stress levels and poorer sleep quality while enrolled in courses. This study investigated the extent to which stress and sleep quality in college students may be related to delay discounting (DD) for food—a psychological process in which immediate outcomes are preferred over larger, more delayed outcomes. College students (N = 297) completed the Food Choice Questionnaire (FCQ) and the Monetary Choice Questionnaire (MCQ)—measures of food and monetary DD, respectively. The Perceived Stress Scale (PSS), the Pittsburg Sleep Quality Index (PSQI), and measures of subjective hunger, substance use, and demographic variables were also administered. Perceived stress was related to poor sleep quality, alcohol use, substance use, and vaping. Analyses revealed that, when controlling for subjective hunger, perceived stress and poor sleep quality contributed unique variance to food DD, though in opposing directions. Perceived stress uniquely predicted preferences for immediate food, a phenomenon consistent with stress‐induced urgent eating. Poor sleep quality uniquely predicted preferences for larger amounts of delayed food, a pattern consistent with eating later in the day. Stress and sleep quality, when controlling for substance use variables, were unrelated to monetary discounting. Stress and poor sleep quality, then, predict independent and opposing discounting processes in college students that are food‐specific, as opposed to more general cross‐commodity processes.

Food Related Behaviors and Sleep Quality in University Students: A Descriptive Study

Purpose: The purpose of this study was to evaluate the relationship between food addiction, night eating status and sleep quality in students studying at different faculties or departments of various universities in Turkey. &#x0D; Methods: A total of 1044 students from 11 different departments/faculties were included. Night Eating Questionnaire, Yale Food Addiction Scale and Pittsburgh Sleep Quality Scale were applied to the students. Also, the dietary habits (main meal and snack consumptions, the meal they skipped and the reasons, duration of meals, consumption of tea and coffee etc.) of the students were questioned.&#x0D; Results: Significant relationships were found between BMIs, faculties/departments, use of antidepressants, skipping breakfast status and tea/coffee consumption of students. Moreover, there were significant differences between both food addiction status (p

The Relationship Between Academic Performance and Physical Activity, Smart Phone Use and Sleep Quality in University Students

Objective: Our study was planned to examine the academic achievement, physical activity, smart phone use and sleep quality of university students. &#x0D; Methods: Young individuals between the ages of 18-25 studying at a vocational school were included in the study. While recording the demographic information of the participants, individuals were classified as "heavy users" and "light users", taking into account the duration of smartphone use during the day. In addition, the physical activity levels of the individuals were evaluated with the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the smartphone usage level with the Smartphone Addiction Scale-Short Form (SAS-SF), and the sleep quality with the Pittsburg Sleep Quality Index (PSQI). &#x0D; Results: A total of 424 people, 326 of whom were women, with a mean age of 20.30±1.34 years, participated in the study. It was determined that 70.3% of the participants used smartphones for more than 4 hours a day. It was determined that there was a weak negative correlation between the academic success of the students and their physical activity levels, and that their academic success was not affected by smart phone use and sleep quality. However, it was determined that there was a weak positive correlation between the sleep quality of the students and their smartphone use. It was observed that the physical activity levels of male students were higher, while the academic success and sleep quality of normal education students were better. &#x0D; Conclusion: We think that active life, adequate and conscious smartphone use and quality sleep habits can affect academic success in university students.

What complex factors influence sleep quality in college students? PLS-SEM vs. fsQCA.

Sleep quality has a significant impact on the health-related quality of life, particularly among college students. This study proposes a framework for identifying factors that influence college students' sleep quality, including stress, self-control, bedtime habits, and neighborhood environment. The study employed a cross-sectional analytical approach on a convenience sample of 255 medical students from a private university in China during the 2021/2022 academic year, of which 80.39% (205) were women. Two complementary methodologies, partial least squares-structural equation modeling (PLS-SEM), and fuzzy sets qualitative comparative analysis (fsQCA), were utilized in the study. The results of the PLS-SEM analysis suggest that Stress and Self-control act as mediating variables in the model, with Bedtime habits and Neighborhood environment influencing sleep quality through these variables. Additionally, the fsQCA analysis reveals that Bedtime habits and Neighborhood environment can combine with Stress and Self-control, respectively, to influence sleep quality. These findings provide insight into how multiple factors, such as Stress, Self-control, Bedtime habits, and Neighborhood environment, can impact college students' sleep quality, and can be used to develop intervention programs aimed at improving it. Moreover, the use of both methodologies enables the expansion of new methodological approaches that can be applied to different contexts.

Investigation of the Effects of Physical Activity Level on Posture, Depression and Sleep Quality in University Students

University years are a critical period for physical activity, which has physical, mental, and social benefits throughout life. This study aimed to understand how the posture, depression, and sleep quality levels of university students with different physical activity levels are affected and to emphasize the importance of interventions that increase physical activity levels. Our study included 366 students from Ankara Medipol University who were studying in 2022-2023 and agreed to participate in our study. Postures of students; with Posture Screen Mobile, physical activity levels; with the International Physical Activity Questionnaire (IPAQ), depression levels; with the Beck Depression Inventory (BDI), and Sleep quality; with the Sleep Quality Scale and Sleep Variables Questionnaire (SQS-SVS) were evaluated. According to the results obtained from the study, when the beck depression inventory scores of the students were compared according to their physical activity levels, there was a difference in favor of the physically active group (p&amp;lt;0.05), while no difference was found in the sleep quality scale scores (p&amp;gt;0.05). No difference was observed between the groups when the posture disorders were compared according to the student's physical activity levels (p&amp;gt;0.05). When university students were classified according to different physical activity levels, it was determined that sleep quality and posture disorders did not change, while depression levels were positively affected as activity levels increased. Directing students to physical activities and evaluating their posture and directing them to necessary activities is essential.

Sleep Quality Among College Students

Many activities and lecture assignments of student cause students unable to divide their time well. Playing games or social media cause students often sleep late at night, and this has an impact on the disturbance of sleep quality. This study aims to identify the sleep quality of college students at Manokwari West Papua Province. We conducted cross sectional research in male and female students aged of 18-25 years who carry out activities on campus. Sleep quality data was collected through semi-structural interviews using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Our results showed that most Papua University students had poor sleep quality (78%) in the past 1 month. The sleep quality of girls (48%) were poorer than boys (30%).

Mobile phone dependency and sleep quality in college students during COVID-19 outbreak: the mediating role of bedtime procrastination and fear of missing out

ObjectiveThe purpose of this study was to investigate the associations between mobile phone dependency, bedtime procrastination, FoMO, and sleep quality among college students during the COVID-19 outbreak. Specifically, we examined whether bedtime procrastination and FoMO mediate the relationship between mobile phone dependency and sleep quality.MethodsA total of 881 college students completed an online survey in May 2022 in Shanghai, China. Mobile Phone Involvement Questionnaire, Bedtime Procrastination Scale, Fear of Missing Out Scale and Pittsburgh Sleep Quality Index were used to assess mobile phone dependency, bedtime procrastination, fear of missing out, and sleep quality, respectively. Multiple linear regression and mediation analysis were conducted.ResultsThe correlation analyses indicated mobile phone dependency was positively associated with fear of missing out, bedtime procrastination, and poor sleep quality among college students. The structural equation modeling analyses revealed that mobile phone dependency had significant indirect effects on sleep quality through bedtime procrastination (indirect effect: 0.030, 95%CI: 0.022–0.041) and fear of missing out (indirect effect: 0.013, 95%CI: 0.003–0.023).ConclusionThe findings indicated that bedtime procrastination and fear of missing out are mediators mediating the relationship between mobile phone dependency with sleep quality. Bedtime procrastination and fear of missing out should be considered as potential intervention targets for reducing mobile phone dependency and improving sleep quality in college students.

College Students' Social Media Addiction and Sleep Problems: Chain Mediating Effects of Fear of Missing Out and Nocturnal Social Media Use

This study investigated the effect of social media addiction on sleep problems in college students, and the chain mediating effects in this relationship of fear of missing out and nocturnal social media use. We conducted a survey of 907 college students in China using the Social Media Addiction Scale, the Fear of Missing Out Scale, the Nocturnal Social Media Use Scale, and the Pittsburgh Sleep Index Scale. Results showed that social media addiction significantly and positively predicted poor sleep quality, and that fear of missing out and nocturnal social media use had a chain mediating effect in this relationship. Reducing social media addiction and nocturnal social media use, and developing education-guided measures aimed at reducing fear of missing out will be beneficial to improving the sleep quality of college students.

Breakfast Frequency and Sleep Quality in College Students: The Multiple Mediating Effects of Sleep Chronotypes and Depressive Symptoms.

Sleep disorders, which are prominent problems among college students, may be associated with skipping breakfast. Therefore, we aimed to explore the role of sleep chronotypes and depressive symptoms as mediators in the relationship between breakfast frequency and sleep quality. A cross-sectional survey enrolling random samples of 712 college students was conducted by the Questionnaire Star online platform. Statistical description and correlation analysis were performed by SPSS 25.0, and a chain mediation test was performed by model 6 in PROCESS 3.5. The result of the article demonstrated that breakfast frequency can affect sleep quality through two mediating pathways: ① sleep chronotypes, with a mediating effect of 32%; and ② depressive symptoms, with a mediating effect of 52.4%. However, the chain mediating effects of sleep chronotypes and depressive symptoms was not significant, and neither was the direct effect of breakfast frequency on sleep quality. Breakfast frequency can indirectly affect sleep quality by adjusting sleep chronotypes and depressive symptoms. Regular breakfast can increase morning and intermediate sleep chronotypes, reduce depressive symptoms, and thus improve sleep quality.

0174 Patterns of sleep habits and their impact on nighttime sleep quality in college students

Abstract Introduction Poor sleep quality is common in college student. Unhealthy sleep habits (e.g., delayed bedtime, inconsistent sleep routine between schooldays and weekends) could lead to poor sleep quality, which is associated with poor academic performance, mental and physical health. However, little is known about the patterns of sleep habits in terms of timing and consistency and their impact on nighttime sleep quality in college students. Methods This was a cross-sectional anonymous web-based survey to examine sleep in college students. The Classification and Regression Tree (C&amp;RT) was used to identify distinct patterns based on sleep habits including bedtime and wake-up time (usual, schooldays, and weekends), and consistency of bedtime, wake-up time, and duration between schooldays and weekends. The response variable was nighttime sleep quality measured by the Pittsburgh Sleep Quality Index (PSQI) global score. The imputed PSQI global score was used to minimize missing data. Results A total of 439 students participated in this survey, with a response rate at 22%. Four distinct clusters were identified. Both Cluster 1 (37.8%) and Cluster 2 (10.9%) included participants who reported a difference in sleep duration between schooldays and weekends &amp;lt; 1.75 hours, with Cluster 1 reporting a usual bedtime before 1:45AM while Cluster 2 after 1:45AM. Both Cluster 3 (3.4%) and Cluster 4 (47.8%) included participants who reported a difference in sleep duration between schooldays and weekends ≥ 1.75 hours, with Cluster 3 reporting school-day wake-up time before 7AM while Cluster 4 after 7AM. Among the four clusters, participants in Cluster 3 (late riser with inconsistent schooldays-weekends duration) had the worst sleep quality (8.95±3.43), followed by Cluster 2 (late sleeper with consistent schooldays-weekends duration, 6.98±2.79) and Cluster 4 (late riser with inconsistent schooldays-weekends duration, 6.83±2.87). Cluster 1 (“early” sleepers with consistent schooldays-weekends duration) had the best sleep quality among all (5.61±2.54). Conclusion Distinct patterns of sleep timing and consistency can have significant impact on sleep quality, with some habits such as extremely late bedtime and inconsistent sleep duration between schooldays and weekends had the most negative impact. Tailoring interventions targeting these unhealthy sleep habits are needed in promoting sleep in this population. Support (if any) None

Long-term poor sleep quality is associated with adverse donor reactions in college students in Central China: A population-based cross-sectional study.

Adverse donor reaction (ADR) could adversely impact the recruitment and retention of blood donors, but the evidence of effect of sleep quality on ADR is limited and controversial. The goal of this study was to explore the association between the sleep quality and ADR among college students in Wuhan. The college student blood donors in Wuhan from March to May 2022 were recruited. Self-compiled general information questionnaire and Pittsburgh sleep quality index (PSQI) were investigated by convenience sampling. Univariable and multivariable logistic regression analyses were used to estimate the association. Among 1014 participants included in this study, 63 were in the ADR group and 951 were in the non-ADR group. Compared with the non-ADR group, the PSQI scores of ADR group were higher (3.44 ± 1.81 vs. 2.78 ± 1.82, p < 0.01). The results of multivariable logistic regression analysis showed that after adjusting gender, body mass index, blood donation history and other potential confounding factors, higher PSQI scores were related to the occurrence of ADRs (odds ratio = 1.231, 95% confidence interval 1.075-1.405), that is, the worse the sleep quality, the more likely the ADRs will occur. The long-term poor sleep quality of college students is a risk factor for the occurrence of ADRs. It should be identified early before blood donation to reduce the incidence of ADRs and improve the safety and satisfaction of donors.

Factors associated with sleep quality in university students

To investigate factors associated with poor sleep quality. A cross-sectional study was conducted in 2019 with random sampling. Information on sleep was obtained using the Mini Sleep Questionnaire (MSQ). Independent variables included sociodemographic, behavioural, academic and psychological health characteristics. Adjusted analyzes were performed using Poisson regression. A total of 996 undergraduate students participated in the study. The poor sleep quality affected 23.1% of the sample (95%CI 20.5-25.9), ranging from 13.4% for those with little concern about violence in the neighbourhood to 36.5% for those with less social support. In the adjusted analysis, female sex [PR] 1.81; (95%CI 1.33-2.45), concern about violence in the neighbourhood [PR] 2.21; (95%CI 1.48-3.28), discrimination at university [PR] 1.42; (95%CI 1.08-1.86) and food insecurity [PR] 1.45; (95%CI 1.11-1.89) were associated with the presence of poor sleep quality, as well as having less social support and income and suffering psychological distress. The results highlight socioeconomic and mental health factors that affect sleep quality and demonstrate the need for reflection and interventions capable of minimizing this problem.

Prediction Models for Sleep Quality Among College Students During the COVID-19 Outbreak: Cross-sectional Study Based on the Internet New Media

COVID-19 has been reported to affect the sleep quality of Chinese residents; however, the epidemic's effects on the sleep quality of college students during closed-loop management remain unclear, and a screening tool is lacking. This study aimed to understand the sleep quality of college students in Fujian Province during the epidemic and determine sensitive variables, in order to develop an efficient prediction model for the early screening of sleep problems in college students. From April 5 to 16, 2022, a cross-sectional internet-based survey was conducted. The Pittsburgh Sleep Quality Index (PSQI) scale, a self-designed general data questionnaire, and the sleep quality influencing factor questionnaire were used to understand the sleep quality of respondents in the previous month. A chi-square test and a multivariate unconditioned logistic regression analysis were performed, and influencing factors obtained were applied to develop prediction models. The data were divided into a training-testing set (n=14,451, 70%) and an independent validation set (n=6194, 30%) by stratified sampling. Four models using logistic regression, an artificial neural network, random forest, and naïve Bayes were developed and validated. In total, 20,645 subjects were included in this survey, with a mean global PSQI score of 6.02 (SD 3.112). The sleep disturbance rate was 28.9% (n=5972, defined as a global PSQI score >7 points). A total of 11 variables related to sleep quality were taken as parameters of the prediction models, including age, gender, residence, specialty, respiratory history, coffee consumption, stay up, long hours on the internet, sudden changes, fears of infection, and impatient closed-loop management. Among the generated models, the artificial neural network model proved to be the best, with an area under curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 0.713, 73.52%, 25.51%, 92.58%, 57.71%, and 75.79%, respectively. It is noteworthy that the logistic regression, random forest, and naive Bayes models achieved high specificities of 94.41%, 94.77%, and 86.40%, respectively. The COVID-19 containment measures affected the sleep quality of college students on multiple levels, indicating that it is desiderate to provide targeted university management and social support. The artificial neural network model has presented excellent predictive efficiency and is favorable for implementing measures earlier in order to improve present conditions.

Mobile Phone Addiction and Sleep Quality: The Mediating Role of Anxiety and the Moderating Role of Emotion Regulation.

Smartphones have become a fundamental tool in the daily life of mankind, but its excessive use seriously impairs people's quality of sleep. A specific state of emotion has been shown to play a crucial role in the relationship between mobile phone addiction (MPA) and the sleep quality of college students. However, studies have rarely considered top-down emotion regulation. This study is the first to examine the effects of MPA on the sleep quality of Chinese college students from a top-down emotion regulation perspective. The survey sample comprised 1559 university students (40.73% male; M (SD) age = 19.11 (1.22) years) who completed questionnaires on MPA, sleep quality, anxiety and emotion regulation. The results revealed that (1) Anxiety mediated the relationship between MPA and sleep quality; (2) Cognitive reappraisal (CR) negatively moderated the relationship between MPA and anxiety; and (3) Expressive suppression (ES) positively moderated the relationship between MPA and anxiety. These findings reveal the mechanism of sleep problems in Chinese college students. We provide research ideas and method guidance for the follow-up intervention and treatment of college students' sleep problems.

Factors Affecting Sleep Quality of College Students during the Coronavirus Disease 2019 Pandemic: A Cross-Sectional Study.

Background and Objectives: The purpose of this study was to identify the correlation between college students' fear of coronavirus disease 2019 (COVID-19), intolerance of uncertainty, and sleep quality during the COVID-19 pandemic, and to identify factors affecting sleep quality. Materials and Methods: Data were collected through an online survey of 310 college students from three universities located in three regions in Korea. Results: The average sleep quality score of college students was 4.76 ± 2.86 points, the average fear of COVID-19 was 14.01 ± 5.05 points, and the average intolerance of uncertainty was 31.50 ± 7.92 points. Fear of COVID-19 and intolerance of uncertainty were positively correlated (r = 0.302, p < 0.001). Sleep quality was positively correlated with fear of COVID-19 (r = 0.246, p < 0.001). Sleep quality was positively correlated with intolerance of uncertainty (r = 0.212, p < 0.001). Health status was the most powerful factor that affected sleep quality (β = 0.377, p < 0.001). The next most powerful factors that affected sleep quality were fear of COVID-19 (β = 0.164, p = 0.003) and intolerance of uncertainty (β = 0.122, p = 0.027), respectively. Conclusions: These results are expected to be used as basic data for the development of health intervention programs to protect and improve the psychological well-being of college students by improving their sleep quality.