Effects of Perceived Stress and Mood States on Sleep Quality in University Students during a Pandemic Context

Cristina López de Subijana¹, Elena Conde², Sara Pina¹, José L. Chamorro³

¹ Social Sciences Applied to Sport, Physical Activity and Leisure Department, Universidad Politécnica de Madrid, Madrid, Spain
² Sports Faculty, Universidad Católica de San Antonio de Murcia, Murcia, Spain
³ Hum-878 Research Team, Health Research Centre, Department of Psychology, University of Almería, Almería, Spain.

Resumen

El objetivo de este estudio es explorar cómo el estrés predice la calidad del sueño utilizando los estados de ánimo y las características de los estudiantes (edad, género, y actividad física realizada) como moderadores. 178 estudiantes universitarios (Edad media = 21,8 años; DE = 3,8 años; 40,4% mujeres y 59,6% hombres) respondieron a cuestionarios sobre el estrés percibido, los estados de ánimo, y la calidad el sueño en el mes de marzo del 2021. Los estados de ánimo (positive y negative), la edad, y la actividad física realizada, moderaron significativamente la relación entre el estrés percibido y la calidad del sueño. El ser mayor (21-34 años) y el percibir estados de ánimo negativos influencian negativamente en la relación, haciendo que el estrés afecte más a la calidad del sueño. Por el contrario, estados de ánimo positivos y el realizar más de 10 h de actividad física a la semana paliaban esos efectos negativos del estrés en la calidad del sueño. Teniendo en cuenta la importancia del sueño en el bienestar de los estudiantes universitarios, este estudio aporta perspectiva sobre cómo los estudiantes universitarios puedes mejorar su calidad del sueño a través de la regulación de sus estados de ánimo y adaptando su estilo de vida. Así mismo los orientadores universitarios deben de tener en cuenta que los estudiantes mayores y mujeres son más propensos a tener problemas de sueño debido al estrés.

Palabras Clave: estados de ánimo, estrés, hábitos saludables, estudiantes universitarios.

Abstract

This study aimed to explore how perceived stress predicted sleep quality using mood states and student characteristics (age, gender, and physical activity performed) as moderators. One-hundred seventy-eight university students (Mage = 21.8 years; SD = 3.8; 40.4% women and 59.6% men) responded to questionnaires about their perceived stress, mood states, and sleep quality in March 2021. Negative and positive mood states, age, and physical activity significantly moderated the relationship between perceived stress and sleep quality. Being older (21-24 years) and perceiving negative mood states affected negatively as the perceived stress influenced leading to poor sleep quality. In contrast, positive mood states and performing more than 10 hours of physical activity weekly improve the relationship, in the way that stress affected lees to sleep quality. Considering the importance of sleep for university students’ well-being, this study brings insights into how university students could improve their sleep quality by regulating their mood states and adapting their lifestyles. Also, consultants and university counsellors should be aware that older students and women may be more sensitive to suffering sleep problems due to stress.

Keywords: mood, stress, healthy habits, university students.

INTRODUCTION

Sleep is a basic need (Ruiz et al., 2017). It is an active, repetitive, and reversible state necessary for maintaining brain functions (e.g., divergent thinking, language speech, memory, decision-making, attention, mood, learning processes, critical thinking, creativity) in good conditions. University students may sacrifice some sleep hours for other activities such as studying, exercising, or working (Yeung et al., 2008). However, the deprivation of sleep or poor sleeping habits can compromise students’ academic performance (Yeung et al., 2008; Wagner & Rhee, 2013). Also, sleep quality could be affected by the high-pressure level of anxiety during exams, consistent deadlines for tasks, and busy schedules. Poor sleep quality may lead to a chronic sleep pattern which could hurt cognition, learning, and mood (Wagner & Rhee, 2013). The purpose of this study is to explore how university students’ sleep quality was related to perceived stress during the 2020-2021 aca-demic term, a term that was further affected by interruptions and exceptional circumstances due to COVID-19.

In early 2020, a viral outbreak called SARS-CoV-2 coronavirus (COVID-19) began to spread internationally. On January 30, 2020, the World Health Organization (WHO) declared the outbreak a «public health emergency of international concern”. Countries implemented control measures to minimize the virus’s transmission and spread, such as closing schools, cancelling large gatherings, suspending social, and sporting events, and confining citizens to their homes. In Spain, on March 13, 2020, the Council of Ministers decreed a «state of alarm» for the entire national territory. In this process, people were isolated in their homes, away from the social environment for 99 days to limit infection, as a crucial public health measure.

During this period of isolation, university students in Spain were confined to attending lectures remotely and completing their courses without in-person contact with their instructors. During this pandemic stage, studies conducted with university students highlighted that mental health problems arose from the sudden adaptation to remote learning and living conditions (Cao, 2020). The prevalence of stress, anxiety, depression, and sleep disturbance was nearly 30% among the university student population (Deng et al., 2021).

Several studies on the general population have shown the effects of COVID-19 confinement on mental health risks due to situations of uncertainty associated with increased negative feelings, high emotional impact, post-traumatic stress disorder (PTSD), depression and higher levels of psychological stress (Conde et al., 2021; González-Sanguino et al., 2020; Lima et al., 2020). Numerous studies pointed out that severe anxiety, depression, and stress were related to poor sleep quality (Cellini et al., 2021). Even though the hours of sleep increased during confinement and stress was perceived as low, the sleep quality was compromised (Cellini et al., 2021).

As this study was framed within the 20-21-year course, it is necessary to explain the teaching situation of that year’s course at the universities of Spain. As of June 21, 2020, Spain abandoned the state of alarm, and each region led the health measures to be applied in their territory (Royal Decree-Law 21/2020, of June 9). The universities maintained some in-person courses with a low number of students (less than 30) under COVID-19 strict protocols (f.e.: wearing a face mask, ventilating the class, hand sanitiser, and a minimum distance of 2 m among students). Still, most of the lessons were given online. Students and instructors had to deal with this “new normality” as most students attended their classes from home. On the part of the instructors, the content had to be adapted to remote teaching trying to involve students in new activities and create new ways to interact with them (Cassachia et al., 2021). From the part of the students, they had to pay attention to the screen for many hours while the uncertainty of how their learning would be affected increased significantly (Balta et al., 2021). As a result, instructors and students suffered from sleeping problems (Cassachia et al., 2021).

In this line, perceived stress has been identified as an antecedent of sleep quality (Cohen et al., 1983; Du et al., 2020). For example, studies such as Eliasson et al. (2010) or Kim and Dimsdale (2007) showed that increasing participants’ stress decreased sleep quality while reducing participants’ stress enhanced sleep quality. The literature has shown the Transactional Model of Stress (Folkman & Lazarus, 1988) as a useful model to explore the stress process and its consequences because it provides a dynamic and multifaceted way of appraising stress, especially in a context of profound change as the COVID-19 pandemic (Brooks et al., 2020). This model suggests that an individual’s perceived stress depends on the process of cognitive appraisal and emotional regulations, rather than the event itself. The Transactional Model of Stress conceptualizes the way people respond to, evaluate, and manage stressors that influence the impact of stressful conditions on their well-being. Thus, emotional and mood states could have a moderator role be-tween perceived stress and consequences like sleep quality. There are studies contextualised in the COVID-19 Pandemic that have shown stressful processes as an antecedent of negative mood states like anxiety or depression (Çıkrıkçı et al., 2022). In this sense, mood states could be classified into positive (i.e., vigour and friendliness) and negative (i.e., anger, fatigue, tension, and depression) depending on the consequences (i.e., pleasant or unpleasant) for individuals to feel one way or another. For example, in an educative context, positive mood states such as vigour moderated the relationship between adaptive coping strategies and better academic performance in university students (Vizoso et al., 2018). However, a negative mood state such as anxiety was related to problematic eating behaviour during the COVID-19 pandemic in a sample of Italian college students (De Pasquale et al., 2021). Furthermore, it could be interesting to test if positive and negative moderate the relationship between perceived stress and sleep quality in university students.

Also, living with the pandemic situation may be seen with a different lens depending on the student’s characteristics. First, gender should be considered. Studies show that as in the general population, women university students suffer from depression, stress, and sleep problems more than their men counterparts (Deng et al., 2021; Habe et al., 2021; Gestsdottir et al., 2021). Secondly, age may also influence perceived stress and sleep quality (Odriozola-González et al., 2020; Marelli et al., 2021; Tang et al., 2020). However, the results lack consistency as some studies pose that older university students suffer less stress and better sleep quality than their younger counterparts (Odriozola-González et al., 2020; Marelli et al., 2021) while some other studies report a higher degree of stress or poor sleep quality among older students (Tang et al., 2020). In addition, healthy habits such as good nutrition, no alcohol abuse, staying connected with family and friends, and exercise have been proven to counteract the negative effect of isolation during COVID on perceived stress (Sañudo et al., 2020; Wang & Li, 2022). Therefore, it seems that gender, age, and physical activity may explain better the relationship between perceived stress and sleep quality.

Based on these previous studies, we aimed to explore how the sleep quality of university students could be predicted by perceived stress. We hypothesize that perceived stress will strongly predict sleep quality. Also, this study wants to broaden the explanation of this relationship including positive and negative mood states and other variables related to the student characteristics (e.g., gender, age, physical activity). On one hand, based on the trans-actional model of stress, we hypothesized that positive mood states and physical activity will buffer the relationship between perceived stress and sleep quality. On the other hand, being female will worsen this relationship. With age, as previous studies were not consistent, we did not pose any hypothesis.

METHODOLOGY

Participants

The participants were 178 students enrolled at the Sport Sciences Bachelor of the Universidad Politécnica de Madrid. Students were 21.8 years of age (SD = 3.8) with 59.6% self-identifying as men and 40.4% as women. Students were in the 1st (25.8%), 2nd (20.2%), 3rd (37.1%), and 4th (16.9%) year of their studies.

Instruments

Demographics.

Participants answered the following demographic information: year of sport sciences bachellor studies, age, gender, working status with the number of working hours per week, and the number of hours of physical activity per week.

Perceived Stress.

The Spanish version of the Perceived Stress Scale was administered (PSS; Remor, 2006). This version has 14 items for assessing the level of perceived stress level during the last month. Each item was responded on a 5-point Likert-type scale (0 = never, 1 = hardly ever, 2 = occasionally, 3 = often, 4 = very often). The total PSS score was calculated by first inverting items number 4, 5, 6, 7, 9, 10, and 13 and then adding all the items. The direct score obtained indicates that a higher score corresponds to a higher level of perceived stress. The overall scale had an acceptable Cronbach’s α (.88) for reliability.

Mood states.

The Spanish version of the short questionnaire of Profile of Mood States (POMS; Andrade et al., 2013) was completed. This questionnaire has 30 items across six subscales that assess negative mood states (Anger, fatigue, tension, and depression), and positive mood states (Vigour and Friendliness). Each item was completed on a 5-point Likert-type scale ranging from 0 (Not at all) to 4 (Very Much). Each factor was calculated with the sum of items. All factors had acceptable Cronbach’s α (.88 for NEG, .96 for POS, and .87 for the overall scale).

Sleep Quality.

The Spanish version of the Pittsburgh Sleep Quality Index (PSQI; Macías & Royuela, 1996) assessed the quality of sleep over the last month. This questionnaire has 19 items and provides seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. Each of the components was valued on a scale from 0 to 3. The maximum value of PSQI is 21. Higher scores indicate poorer sleeping quality. This tool showed acceptable reliability properties (Cronbach’s α = .75).

Procedure

Following ethical approval from the lead author’s institution which was conducted in accordance with the Declaration of Helsinki, the students’ representatives were contacted. They distributed the online questionnaire among the Sport Sciences Bachelor students from the last week of March until the second week of April 2021. Each student took on average 10 min to answer the questionnaires.

Data Analysis

For the main analysis, we first examined bivariate correlations of all the variables, then, conducted regression analyses considering moderations using SPSS macro termed PROCESS (Hayes, 2018). The dependent variable (DV) was the Sleep Quality (SQ) score, and the independent variable (IV) was the Perceived Stress (PS) score. We were interested in the extent to which the relationships between DV and IV were moderated by gender, athlete age, negative mood states, positive mood states, and the number of hours of physical activity per week. The continuous moderators were divided into three levels (0 = Mean -1SD; 1 = Mean; 2 = Mean + 1SD). Gender as moderator was coded, too (0=Male; 1= Female). Each moderator was tested in a separate model. The continuous DV and IV were centred before performing analyses. To interpret the meaning of these results, the significant interaction was decomposed by contrasting simple slopes for the relationship between the DV and IV at the levels of each moderator (Hayes, 2018). Mann-Whitney U tests were applied for group comparisons (gender). Cohen’s F2 and r indexes were the effect size indicators (Cohen, 1988). The α-level was set at .05.

RESULTS

Preliminary Analysis

Means, standard deviations, and correlations, for all variables, are reported in Table 1. No missing data was found. Three cases were identified as multivariate outliers through Malahanobis distance and were deleted. So, the final sample was 175 participants. The post hoc power was .98 for medium effect size at α = .05. The correlations showed direct relationships between perceived stress, sleep quality, and negative mood state (p<.001). While positive mood states were negatively related to perceived stress, sleep quality and negative mood states (p<.001).

Table 1. Descriptive Statistics and Correlations of Study Variables

Main Analysis

Table 2 presents the results of the regression models. The overall models were significant for gender F(3,171) = 30.1; p < .001; R² = .35; C’s F² = .53), age (F(3,171) = 35.8; p < .001; R² = .39; C’s F² = .63), negative mood state (F(3,171) = 41.5; p < .001; R² = .42; C’s F² = .73), positive mood state (F(3,171) = 38.0; p < .001; R² =40; C’s F² = .67), and physical activity (F(3,171) = 33.5; p < .001; R² =.37; C’s F² = .59). No significant interaction effects were detected for gender or physical activity. An additional analysis was completed where the physical activity variable was reanalysed considering two groups divided by the median. Group 0 was involved in less than 9.5 hours per week of physical activity, while group 1 was involved in more than 10 hours per week of physical activity. The World Health Organization (WHO, 2020) recommends 5 hours of physical activity per week. The regression model for physical activity divided into two groups was significant (F(3,171) = 32.5; p < .001; R² =.36; C’s F² = .57). There were significant interaction effects in these regressions between age, negative mood state, positive mood state, and physical activity divided into two group moderators.

Table 2. Moderation Regression Results for Primary Analyses for Perceived Stress as independent variable and Sleep Quality as the dependent variable

Age significantly moderated the relationship between Perceived Stress and Sleep Quality with a significant interaction (b =.02; t(171) = 3.3, p = .007). Perceived stress more strongly predicted Sleep Quality among older students (24 years; b = .19, t(171) = 9.2, p < .001) and among those at the mean (21 years; b = .14; t(171) = 9.8; p < .001) than within younger students (19 years; b = .09, t(171) = 4.6, p < .001; Figure 1.1). Thus, when Stress was perceived to be high, older athletes showed poorer Sleep Quality compared to younger students.

Negative mood state significantly moderated the relationship between Perceived Stress and Sleep Quality with a significant interaction (b =.002; t(171) = 3.2, p = .002). Per-ceived stress more strongly predicted Sleep Quality among those students perceived negative mood state higher than the mean (b = .14, t(171) = 5.1, p < .001) and among those at the mean (b = ..09; t(171) = 4.4; p < .001) than within those students below the mean (b = .05, t(171) = 2.0, p = .046; Figure 1.2). Thus, when Stress was perceived to be high, students with a high negative mood state showed poorer Sleep Quality in comparison to students having a low negative mood state.

Positive mood state significantly moderated the relationship between Perceived Stress and Sleep Quality with a significant interaction (b =.06; t(171) = -2.7, p = .009). Perceived stress more strongly predicted Sleep Quality among students who perceived negative mood state lower than the mean (b = .14, t(171) = 7.0, p < .001) and among students at the mean (b = .11; t(171) = 6.2; p < .001) than within those students above the mean (b = .07, t(171) = 3.1, p = .003; Figure 1.3). Thus, when Stress was perceived to be high, students with low positive mood states showed poorer Sleep Quality in comparison to students having higher negative mood states.

The number of hours of physical activity per week considering both groups significantly moderated the relationship between Perceived Stress and Sleep Quality with a significant interaction (b =-.07; t(171) = -2.3, p = .02). The Perceived stress more strongly predict-ed Sleep Quality among students than performed 9.5 h per week or less of physical activity (b = .14, t(171) = 7.0, p < .001) than students that performed 10 h per week or more of physical activity (b = .07, t(171) = 3.1, p = .003; Figure 1.4). Thus, when Stress was perceived to be high, students who performed 9.5 hours or less per week of physical activity showed poorer Sleep Quality in comparison to those performing more than 10 h per week of physical activity or more.

Figure 1. The Significant Interactions Between Dependent and Independent Variables Regarding Age, Negative Emotions, Positive Emotions, and Physical Activity.

Gender comparisons are reported in Figure 2 and Table 3. Women perceived higher levels of stress (z = 4.9; p<.001; C’s r = .37), negative mood state (z = 3.3; p<.001; C’s r = .25), and poorer sleep quality (z = 3.7; p<.001; C’s r = .30) than men. On the other hand, they perceived lower levels of positive mood state (z = 3.5; p<.001; C’s r = .26).

Figure 2. Data presented as Mean and 95% CI; significant difference between groups at p<.001.

Table 3. Mean and Standard deviation of Study Variables regarding gender

DISCUSSION

This study aimed to explore how perceived stress predicted sleep quality using student characteristics as moderators. The regression models explained 35 to 49% of the sleep quality variance. Negative and positive mood states, age, and physical activity moderated the relationship with a medium to large effect size. Specifically, a negative mood state seemed to fuel the relationship between perceived stress and sleep quality, while a positive mood state buffered it. Further, higher perceived stress predicted poorer sleep quality in older students (21-24 years) than in younger students (19 years). Regarding physical activity, performing a great number of hours per week (more than 10 hours) buffered the direct relationship be-tween perceived stress and sleep quality. About the gender comparison, women perceived higher stress and negative mood states, and poorer sleep quality than men. Now, we will discuss our main findings with the existing literature.

The averages of our results showed how the perceived stress reported was higher than that of United States (US) college students (Benham, 2021) or than medical students from China (Liu, Liu, et al., 2021). Our sample reported poor sleep quality (>5). This result agrees with previous studies with university students from China, Italy, Spain, and the US (Ben-ham, 2021; Dial et al., 2021; Liu, Qiao, et al., 2021; Marelli et al., 2021; Sañudo et al., 2020). The university students participating in this study are having more trouble with stress and sleep quality than in some other regions or countries that reported no changes during different times before, during, and after the confinement (Johansson et al., 2021).

This study reinforces the transactional model of stress, where the perceived stress depends on cognitive appraisal and emotional regulation rather than the event itself (Folkman & Lazarus, 1988). Mood states moderated the relationship be-tween perceived stress and sleep quality (Troy et al., 2010). According to the results of a study carried out in China with university students during the confinement period (Ye et al., 2021), appropriate emotion regulation strategies could effectively improve university students’ sleep quality. Effective emotional regulation strategies could be proposed as a way to deal with an enhanced period of stress, such as the 2020-2021 academic term. Based on our results, students should try to manage their negative moods or emotions. This could be trained by regulating the work and rest hours, expressing their anger in an appropriate environment, and sharing with their counterparts or relatives their worries about their life issues. On the other side, the student should seek to promote their own positive emotions.

Another finding of this study is that older students (21-24 years) perceived a stronger direct relationship between perceived stress and sleep quality. Even though the previous studies did not show a clear hypothesis to propose (Dial et al., 2021; Gas et al., 2021; Odriozola-González et al., 2020; Tang et al., 2020), this result could be explained as these students are enrolled at the last years of the Bachelor studies. The students enrolled in a bachelor’s degree aim to qualify to reach the expected position within the sports industry. The uncertainty about their low chances of finding a job position within a pandemic environment may help interpret this result.

A novel finding of this study is that a certain amount of physical activity helps control the strong direct relationship between perceived stress and sleep quality. Although the number of hours re-ported in our study for having such a benefit is double the WHO recommendations, this fact should be considered with caution. It seems that those students who exercised for more than 10 hours per week were better predisposed to less perceived stress and better sleep quality. Moreover, this finding gives more control to individuals because they can commit to physical activity to improve the relationship between perceived stress and sleep quality.

Regarding gender comparison, women were more vulnerable than men. They suffer higher stress, more negative mood states, less positive mood states, and poorer sleep quality. Our result agrees with the previous research on university students during the pandemic (Birmingham et al., 2021; Gas et al., 2021; Gestsdottir et al., 2021; Habe et al., 2021; Marelly et al., 2021; Tang et al., 2021). In this sense, the role of women’s socialization in societies could be explored to deepen awareness of this topic.

PRACTICAL IMPLICATIONS

Furthermore, this research increases knowledge of how university students deal with stress and how this stress relates to their sleep quality. It points out the importance of effective regulation of mood states and considering the students’ characteristics when trying to counsel them. Those reaching the end of their degree and women are prone to encounter more problems with stress and sleeping difficulties. Also, performing physical activity appears to help deal with stressful situations, such as de 2020-2021 academic term. However, this result should be considered with caution.

Some limitations need to be mentioned. First, it is a cross-sectional study, therefore no causal relationship could be established. Second, the study only considers sports sciences students and not some other types of students (e.g., Engineering, Health, Humanities, Social Sciences). Our sample may have higher physical activity habits than regular university students (Odriozola-González, et al., 2021). Third, sleep quality was taken as an indirect measure, as students had to report sleep features on a questionnaire. Today there are direct measures such as a wearable band that may have higher reliability with sleep quality (Sañudo et al., 2020). And finally, the hours of physical activity were self-reported and not measured with a standardized tool such as IPAQ, or a direct measure (accelerometer).

In conclusion, this study describes the relationship between perceived stress and sleep quality in university students of Sports Sciences while considering the moderating factors of age, mood states, and physical activity. Consultants and university counsellors should be aware that the regulation of mood states is a key issue in improving perceived stress and sleep quality. This research highlighted how women, older students, and those involved in a smaller number of hours of physical activity weekly are the most sensitive group to poor sleep quality.

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Cita en Kronos

Cristina López de Subijana, Elena Conde, Sara Pina José L. Chamorro (2024). Effects of Perceived Stress and Mood States on Sleep Quality in University Students during a Pandemic Context. . (1).https://g-se.com/effects-of-perceived-stress-and-mood-states-on-sleep-quality-in-university-students-during-a-pandemic-context-3067-sa-c66a3991033d0c