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Bedtime procrastination related to loneliness among Chinese university students during post-pandemic period: a moderated chain mediation model

BMC Public Health volume 24, Article number: 491 (2024) Cite this article

Abstract

Background

This study examined the relationship between loneliness and bedtime procrastination among Chinese university students, the mediating effects of COVID-19 risk perception and self-regulatory fatigue, and connectedness to nature’s protective role, post pandemic.

Methods

We recruited 855 students to complete the Loneliness, Perceived Risk of COVID-19 Pandemic, Self-Regulatory Fatigue, Bedtime Procrastination, and Connectedness to Nature Scales. Data for descriptive statistics, correlation analysis, and moderated chain mediation effects were analyzed using SPSS 24.0 and process 3.5 macros.

Results

Loneliness positively correlated with bedtime procrastination, COVID-19 risk perception mediated the impact of loneliness on bedtime procrastination, self-regulatory fatigue mediated the effect of loneliness on bedtime procrastination, and COVID-19 risk perception and self-regulatory fatigue mediated the effect between loneliness and bedtime procrastination. Furthermore, connectedness to nature mediated the impact of COVID-19 risk perception on self-regulatory fatigue.

Conclusions

The results indicate the effects and potential mechanisms of loneliness on bedtime procrastination after the relaxation of the pandemic prevention and control policy in China from the perspective of self-regulatory resources and provide insights into improving university students’ sleep routine and mental health post pandemic.

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Introduction

The outbreak of COVID-19 not only causes tremendous public property damage and public safety hazards but also threatens the public's physical and mental health. Several studies have suggested that the combination of physical and psychological effects may lead to the emergence and exacerbation of sleep problems [1, 2], affecting the regularity of people's routines and disrupting sleep rhythms [3]. University students, as representatives of the young population, appear to be more vulnerable to psychological and post-traumatic stress during the outbreak of COVID-19, which in turn leads to sleep problems [4,5,6]. A recent survey conducted in North America showed that university students’ sleep–wake patterns changed during the pandemic [7]. Many have experienced multiple sleep problems [8], and bedtime procrastination has become more common. Similarly, the Chinese Sleep Research Society [9] published a white paper on sleep among Chinese residents during the 2020 pandemic lockdown, which found a significantly late bedtime, with more than 50% going to bed after midnight.

Recently, China entered a post-pandemic period. On December 7, 2022, based on the current pandemic situation and virus variations, China issued "10 new measures " [10] to optimize the COVID-19 response. The number of positive nucleic acid tests in the reported population increased continuously in all provinces, reaching a peak of 6.94 million on December 22 [11]. The risk of a pandemic remains high, and its negative consequences remain critical factors in individuals’ physical and mental health.

A review of previous studies revealed that most research on bedtime procrastination related to mental health focused on the COVID-19 pandemic [12, 13]. However, few studies have yet to be conducted during the post-pandemic period. Although the lockdown was over, the pandemic is ongoing and the negative effect of pandemic is also ongoing. A prediction published by Nature News on June 9, 2023 shows that China will usher in a peak of infections every 6 months [14]. The virus that causes COVID-19 is constantly changing over time. On Dec. 8, 2023, JN.1 is being shown separately for the first time on Centers for Disease Control and Prevention(CDC)’s SARS-CoV-2 Nowcast, and CDC predicts that COVID-19 activity is likely to increase [15]. At the same time, many research found that some individuals infected with COVID-19 had persistent or new symptoms that lasted several months beyond their initial infection, which influenced their life mentally and physically [16, 17]. Moreover, insomnia triggered by stressful life events continues for a long period [18]. After university students returned to campus, their wake-up time advanced and sleep debt increased [19], and they are the group that is most likely to have mental health problems during any public health emergency [20]. Focusing on loneliness and bedtime procrastination among university students during this period has practical implications for improving mental health and gains experience for similar public health issues in the future.

From a theoretical perspective, most scholars have examined the mechanisms of loneliness and bedtime procrastination from the perspective of coping with stress and physiological responses [21, 22]. However, in response to COVID-19, high levels of uncertainty and risk perception can lead to negative emotions and maladaptive behaviors [23,24,25,26], causing individuals to consume psychological resources to control their state [23, 27]. Thus, it may be possible to further explain the impact and underlying mechanisms of negative experiences (loneliness) on bedtime procrastination from a self-regulatory perspective. Ego depletion theory points out that psychological resources are indispensable to the executive function of the self, and psychological resources are limited, and psychological resources will be reduced after self-control [28]. The impact of emotions on psychological resources has always been one of the hot spots of research. When psychological resources are consumed, individual behavior and cognition will also change accordingly [29]. In the post-epidemic period, university students still have the same negative emotions and psychological problems as during the epidemic, which will consume individuals' psychological resources for adjustment and affect participants' perception of external risks and bedtime behavior in the process. This study will provide a theoretical basis for reducing emotional and behavioral problems in the post-pandemic period.

In addition, previous studies exploring the adverse effects of chronic stressors, such as COVID-19, on individuals have often considered the role of individual traits, such as personality traits, cognitive-emotional regulation, and coping styles [30,31,32], or the role of social environment variables, such as social support and parent–child relationships [33, 34], but often overlook the role of the natural environment. The consequences of psychological resource depletion are often negative, and it is necessary to explore ways to mitigate or even eliminate such negative consequences [29]. Some studies have suggested that natural exposure facilitates the replenishment of self-control resources [35], which is likely to have significant positive implications for an individual's psychological well-being [36]. Therefore, it is also important for this study to further explore whether connectedness to nature is a protective factor for the psychological condition of university students in the post-pandemic period and whether it can provide long-term positive suggestions for improving the emotional experience and sleep quality.

Loneliness

Loneliness is a negative emotional experience that arises when individuals do not fulfill their interpersonal relationships [37]. Most people sometimes experience loneliness [38]. However, the beneficial aspects of loneliness, which is a universal but avoidable subjective experience, diminish when the emotions are intense and persistent, especially when individuals are trapped in long-term and chronic feelings of loneliness, which can negatively affect both physical and mental health [39, 40]. In addition, some individuals experience poor sleep quality throughout their lifespans [41, 42]. Today, an increasing number of people are beginning to report frequent, severe, and persistent feelings of loneliness [43, 44], and the situation has been worsened by COVID-19 [45]. People experience an overall increase in loneliness during the pandemic, such as older adults asked to self-isolate [46], parents who are unable to see their children [47], and adolescents whose social activities are reduced and academic lives are affected [48]. The restriction of social distancing and the anxiety of being infected under the lockdown brought a great deal of stress and loneliness among university students [49, 50]. It has also been suggested that the loneliness associated with COVID-19 leads to more intense negative emotions [51] and a range of sleep problems [52], which severely disrupt students' transitions to university and later school plans, causing numerous mental health problems [53]. With the relaxation of prevention and control policies in China, individuals are at an extremely high risk of infection or reinfection and are asked to be responsible for their health [54], so self-prevention remains necessary. Interpersonal interaction and campus life still influence university students [55]. Thus, the frequency of social activities is still low [56], and the impact of loneliness on individuals’ lives cannot be ignored.

Bedtime procrastination

Procrastination refers to the voluntary delay of a desired course of action despite knowing that it would be worse to put it off [57]. Kroese et al. [58] introduced procrastination to the sleep domain for the first time, introducing the concept of "bedtime procrastination" to describe the phenomenon of people's inability to go to bed at their scheduled time without external environmental disturbances. The short-term mood repair of procrastination suggests that it can be viewed as a phenomenon in which short-term emotional processing takes precedence over long-term goal attainment [59]. Dealing with negative emotional states, such as loneliness, is often central to understanding the emergence of procrastination behaviors [60]. A similar perspective holds in the sleep domain. In addition to influencing bedtime state, negative emotions also cause procrastinators to exhibit negative expectations about the future and trigger bedtime procrastination [61, 62]. Therefore, this study hypothesized that loneliness in the post-pandemic university population positively correlates with bedtime procrastination.

The mediating role of risk perception of COVID-19

Risk perception refers to an individual's reliance on intuition to estimate and judge risky events [63]. Previous studies have found that loneliness significantly influences risk perception. Loneliness affects the way a person views and thinks about the world and others [64] and is a risk factor for increased negative and depressive perceptions and increased sensitivity to threats [65], which may lead to changes in an individual's perception of risk. Cacioppo et al. [66] outlined the characteristics of lonely individuals from an evolutionary perspective, noting that loneliness leads to self-protective bias and invisible vigilance to threats. Thus, loneliness leads to higher threat perceptions [67], which can cause lonely individuals to make more negative assessments when faced with unexpected situations such as COVID-19 [68], interpret the current environment as threatening, and be in a state of chronic vigilance [21]. Loneliness has the potential to reinforce individuals' risk perceptions of COVID-19. Studies have shown a strong link between risk perception and stress [69, 70]. Implicit theories about willpower state that stress may lead to procrastination, applying to learning procrastination [71, 72] and bedtime procrastination [73]. Furthermore, bedtime procrastination is a short-term, active emotion regulation strategy used by individuals to adjust their emotions to a state suitable for sleep [74]; therefore, when individuals are in a stressful situation due to a high level of risk perception, they are likely to delay going to bed to help them cope with their negative emotions. Accordingly, the present study hypothesized that the risk perception of COVID-19 is an important mediating variable between loneliness and bedtime procrastination among university students during the post-pandemic period.

The mediating role of self-regulatory fatigue

Self-regulatory fatigue is persistent fatigue arising from an individual's chronic depletion of self-control resources [75] must constantly regulate their cognition, emotions, and behavior daily by their social goals [76]. According to ego depletion theory, individuals have limited resources for self-control to cope with adverse situations and emotions [77, 78]. Each time a person transcends, suppresses, or changes negative emotions such as loneliness, it increases the depletion of self-regulatory resources, and the interpersonal interactions faced by lonely individuals tend to be more demanding, which can result in a more significant cognitive burden [78, 79]. Higher levels of loneliness are likely to lead to a more significant depletion of self-regulatory resources [79, 80]. Meanwhile, many researchers have identified self-regulation’s crucial role in bedtime procrastination [81, 82]. In the formal model of procrastination, similar to general procrastination, an individual’s self-control affects bedtime procrastination [83]. When excessive self-regulatory resources are consumed during the day, they are temporarily depleted, which leaves the organism in a state of self-exhaustion, leading to insufficient resources to perform regulation at night, failure of self-regulation, and bedtime procrastination at last [78, 84]. Therefore, we hypothesized that self-regulatory fatigue would mediate the relationship between loneliness and bedtime procrastination.

The chain mediating role of risk perception of covid-19 and self-regulatory fatigue

Cameron et al. [85] integrated the common sense model [86, 87] and temporal self-regulation theory [88] to construct a framework for the self-regulation of disease risk, suggesting that risk representations trigger emotional responses such as fear and worry and that both risk itself and emotional arousal contribute to cognitive regulation efforts The risk perception of COVID-19 and self-regulatory fatigue might play a chain mediating role in the effect of loneliness on bedtime procrastination. During the post-pandemic period, individuals continue to perceive the risk of COVID-19, and the resulting negative emotions are likely to exacerbate the burden of self-regulation. Furthermore, the cognitive maps of risk attitudes and perceptions proposed by Slovic [63] argue that uncertainty is closely linked to individual risk perception [89], and extreme uncertainty resulting from COVID-19 is often accompanied by an individual overestimation of risk [90, 91]. In an environment of uncertainty, individuals tend to increase their sense of control to reduce uncertainty [91, 92], all of which challenges their ability to self-regulate [93].

The moderating role of connectedness to nature

Connectedness to nature occurs when individuals experience a sense of connection with nature [94]. Hypervigilance to external risks requires limited self-control resources and may lead to increased cognitive load, leaving the individual in a state of self-depletion [65, 79]. In contrast, the restorative function of connectedness to nature can effectively replenish depleted resources [95] and improve self-control [96]. The theory of stress recovery during exposure to natural and urban environments suggests [97] that humans living in a natural environment for long periods can relieve their physical and mental stress through the natural environment, where the stress-reducing effect of connectedness to nature is mainly because of the restoration of self-control resources. This suggests that connectedness to nature facilitates the filling of resource gaps, thus relieving fatigue and producing positive effects in areas such as cognition [98]. Higher perceptions of pandemic risk can put individuals in a state of stress [99], bring about negative emotions [100], and trigger more significant uncertainty [101], all of which can lead to limited cognitive resources [65]. In contrast, connectedness to nature can alleviate the state of alertness and restore resources. Therefore, it is likely to compensate for the adverse effects caused by the risk perception of COVID-19 and mitigate the adverse effects. Based on this, the present study verified whether connectedness to nature could act as a protective factor to mitigate the effects of the risk perception of COVID-19 on self-regulatory fatigue.

In summary, this study constructs a moderated chain mediation model using the following hypotheses (Fig. 1):

Fig. 1
figure 1

Proposed model

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  • H1: Loneliness positively correlates with bedtime procrastination.

  • H2: Risk perception of COVID-19 mediates the effect of loneliness on bedtime procrastination.

  • H3: Self-regulatory fatigue mediates the effect of loneliness on bedtime procrastination.

  • H4: Risk perception of COVID-19 and self-regulatory fatigue play a chain mediating role in the effect of loneliness on bedtime procrastination.

  • H5: Connectedness to nature moderates the effect of the risk perception of COVID-19 on self-regulatory fatigue.

Methods

Participants

This study used convenience sampling to select university students from January to February 2023, following the change in China's epidemic policy. We distributed 993 questionnaires. One hundred and thirty-eight invalid (inattentive, missing, regular responses) questionnaires were excluded; finally, 855 valid questionnaires were obtained, with an effective rate of 86.10%. Among them, 460 were male (53.80%), and 395 were female (46.20%). Participants were between 18 and 32 years old (M = 21.16; SD = 1.83). In this study, 508 (59.40%) university students came from cities in China, 247 (28.90%) came from rural areas in China, and 100 (11.70%) came from towns. Among the participants, 133(15.60%) were junior college students, 667 (78.00%) were undergraduate students, and the other 55 (6.50%) were graduate and doctoral students. In this study, 703 (82.22%) reported being infected with COVID-19 in the last three months and 759 (88.77%) participants reported that their loved ones and friends had been infected with COVID-19 in the last three months. This study was conducted with the approval of the Ethics Committee of East China Normal University (No: HR1-0130–2022).

Instruments

Loneliness scale

The Loneliness Scale [102, 103], revised by Wang, was used. There are 18 items on the scale, such as "I feel I lack the friendships of others", and "I do not feel lonely ". The scale is rated on a 4-point Likert scale ranging from 1 (never) to 4 (always). The higher the total score, the greater the sense of loneliness. Questions 1, 4, 5, 6, 8, 9, 14, 15, 16, and 18 are reverse scored. This scale applies to Chinese university students and is reliable [103]. A confirmatory factor analysis showed that construct validity of the scale was acceptable (CMIN/DF = 6.19, RMSEA = 0.08, CFI = 0.91, TLI = 0.87). The standardized factor loadings for all items were between 0.30–0.82. In this study, the Cronbach’s alpha for the questionnaire was 0.90.

Perceived Risk of COVID-19 Pandemic Scale (PRCPS)

The Perceived Risk of the COVID-19 Pandemic Scale (PRCPS) developed by Xi et al. was used [104]. There are nine items in the scale, such as "How likely do I think I am to get COVID-19", and "I am likely to get COVID-19 no matter how small the chance is". A Liker scale of 4–6 was used. The higher the total score, the higher the risk perception of COVID-19, with one question "I am sure I will not get COVID-19" being reverse scored. This scale is applicable to all age groups in China and has good reliability [104]. A confirmatory factor analysis showed that the scale had good construct validity (CMIN/DF = 2.47, RMSEA = 0.04, CFI = 0.99, TLI = 0.98). The standardized factor loadings for all items were between 0.33–0.82. In this study, Cronbach’s alpha for the questionnaire was 0.80.

Self-Regulatory Fatigue Scale (SRF-S)

The Self-Regulatory Fatigue Scale (SRF-S) developed by Nes et al. and modified by Wang et al. [105, 106] was used to assess the level of self-regulatory fatigue. The scale has 18 items, such as "I feel energetic", and "I have difficulty executing my exercise program". A 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) was used. The higher the total score, the greater the degree of self-regulatory fatigue. Questions 1, 2, 5, 9, 11 and 14 were reverse-scored. This scale is reliable and applicable to the Chinese youth population and has good reliability [106]. Considering that the factor loading of question 14 is less than 0.3, in addition, the residual correlation between question 5 and question 13, question 1 and question 3, question 4 and question 9 is high, so the questions with low factor loading among questions with high residual correlation are deleted. Questions 14, 13, 3 and 9 was deleted [107]. After deletion, the number of questions in each dimension is still greater than 3. We conducted confirmatory factor analysis on the remaining questions, and the results showed that construct validity of the scale was good (CMIN/DF = 5.8, RMSEA = 0.08, CFI = 0.95, TLI = 0.93). The standardized factor loadings for all items were between 0.60–0.80. In this study, Cronbach’s alpha was 0.88.

Bedtime Procrastination Scale (BPS)

The Bedtime Procrastination Scale (BPS) developed by Kroese et al. and modified by Ma et al. [58, 108] was used. There are nine items on the scale, such as "I go to bed later than expected", and "I easily stop the activity I am doing if it is time to go to bed". A 5-point Likert scale ranging from 1 (rarely) to 5 (almost always) was used. The higher the total score, the more severe the bedtime procrastination. Questions 2, 3, 7, and 9 were reverse-scored. This scale is reliable for Chinese university students [108]. A confirmatory factor analysis showed that the scale had good construct validity (CMIN/DF = 3.31, RMSEA = 0.05, CFI = 0.99, TLI = 0.98). The standardized factor loadings for all items were between 0.38–0.85. In this study, Cronbach’s alpha was 0.89.

Connectedness to Nature Scale (CNS)

The Connectedness to Nature Scale (CNS) developed by Mayer et al. and revised by Na et al. [94, 109] was used. The scale has 14 items, such as "I often feel at one with nature," and "My well-being is not related to the good or bad aspects of nature". A 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) was used. The higher the total score, the stronger the individual's connectedness to nature. Questions 4, 12, and 14 were reverse-scored. This scale is reliable and applicable to Chinese university students and has good reliability [109]. A confirmatory factor analysis showed the standardized factor loadings of question 4, 12, 13 and 14 were lower than 0.3. Therefore we delete these questions. For the remaining 10 items we conducted confirmatory factor analysis and results showed that the scale had good construct validity (CMIN/DF = 3.66, RMSEA = 0.06, CFI = 0.96, TLI = 0.94). In this study, Cronbach’s alpha for the questionnaire was 0.83.

Statistical analysis

SPSS 24. 0 and process 3.5 macro programs were used to perform descriptive statistical analysis, correlation analysis, and moderated chain-mediated effect tests on the data. Confirmatory factor analysis was performed using Mplus 8.0.

Results

Common method deviation test

As the results may be affected by common method bias owing to the use of self-reported methods for data collection, the Harman one-way test was used to test for common method bias [110]. Fifteen common factors with eigenvalues greater than one were obtained without rotation, with the first common factor having an explanatory rate of 21.16%, well below 40%. No serious common method bias was observed.

Descriptive statistics and correlation analysis among variables

Table 1 presents the results of the descriptive statistics and correlation analyses for each study variable. Significant positive correlations were found between loneliness, risk perception of COVID-19, self-regulatory, and bedtime procrastination.

Table 1 Descriptive statistics and correlations among main variables
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In this study, 703 (82.22%) reported being infected with COVID-19 in the last three months. Independent sample t-tests found that this group of participants had higher levels of loneliness (t = 2.27, p < 0.05), risk perception of COVID-19 (t = 10.11, p < 0.001), self-regulatory fatigue (t = 2.85, p < 0.01), and bedtime procrastination (t = 3.38, p < 0.001). In this study, 759 (88.77%) participants reported that their loved ones and friends had been infected with COVID-19 in the last three months. Independent sample t-tests revealed higher levels of risk perception of COVID-19 (t = 5.00, p < 0.001) and bedtime procrastination (t = 3.11, p < 0.01) in this group of participants.

Model 6 in the macro process program developed by Hayes was used to test the mediating role of risk perception of COVID-19 and self-regulatory fatigue between loneliness and bedtime procrastination [111]. Gender and age were included as control variables. In addition, the effect of infection with COVID-19 on oneself, loved ones, and friends in the last three months on the study variables was considered. Therefore, the presence or absence of COVID-19 infection in oneself, loved ones, and friends over the last three months was also included as a control variable in the model.

The results (Table 2) showed that loneliness significantly and positively predicted bedtime procrastination (β = 0.50, p < 0.001). After including risk perception of COVID-19 and self-regulatory fatigue in the model, loneliness significantly and positively predicted risk perception of COVID-19 (β = 0.11, p < 0.001) and self-regulatory fatigue (β = 0.74, p < 0.001); risk perception of COVID-19 significantly and positively predicted self-regulatory fatigue (β = 0.10, p < 0.001) and bedtime procrastination (β = 0.09, p < 0.05); self-regulatory fatigue significantly and positively predicted bedtime procrastination (β = 0.43, p < 0.001); at this point, loneliness remained a significant predictor of bedtime procrastination (β = 0.16, p < 0.001).

Table 2 Test for the chain mediation model
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The results of the mediation effect analysis (see Table 3) showed that the mediated effect value of risk perception of COVID-19 was 0.009, that the mediated effect value of self-regulatory fatigue was 0.318, and that the effective value of the chain mediated effect of risk perception of COVID-19 and self-regulatory fatigue was 0.005. The bootstrap 95% confidence intervals for all three mediated paths did not contain zero, and all three mediated effects reached significant levels, accounting for total effects of 1.82%, 64.24%, and 1.01%. Hypotheses 2, 3, and 4 are supported.

Table 3 Mediating effect analysis of the chain mediating model
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To explore the moderating role of connectedness to nature, Model 91 of the process macro program developed by Hayes was used [111]. The results (see Table 4) showed that after controlling for the variables such as age and gender, and whether getting infection of COVID-19 for oneself and loved ones and friends in the last 3 months, the coefficients of each path of the model reached significant levels, and the interaction of risk perception of COVID-19 and connectedness to nature had a significant predictive effect on self-regulatory fatigue (β = -0.06, p = 0.0094). This suggests that connectedness to nature moderates the effect of risk perception of COVID-19 on self-regulatory fatigue, and therefore, hypothesis 5 is supported.

Table 4 Test for the moderated chain mediation model
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We performed a simple slope analysis better to illustrate the moderating role of connectedness to nature. Figure 2 shows that for participants with low connectedness to nature (M-SD), the risk perception of COVID-19 significantly and positively predicted self-regulatory fatigue (simple slope = 0.17, p < 0.001), whereas, for participants with high connectedness to nature (M + SD), the risk perception of COVID-19 was not a significant predictor of self-regulatory fatigue (simple slope = 0.05, p = 0.111). This suggests that the effect of the risk perception of COVID-19 on self-regulatory fatigue decreases significantly as connectedness to nature increases.

Fig. 2
figure 2

The moderating role of connectedness to nature between risk perception of COVID-19 and self-regulatory fatigue

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Discussion

From the perspective of self-regulatory resources, this study is based on the pandemic situation in the new era, the "limited" nature of individual psychological resources, and the characteristics of university students' high psychological stress and emotional problems. By constructing a moderated chain mediation model, we investigated the effects of loneliness on university students' bedtime procrastination and the underlying psychological mechanisms. The results showed that, in the post-pandemic period, university students' loneliness correlated with bedtime procrastination through both direct and indirect pathways. In addition, connectedness to nature moderated the effect of risk perception of COVID-19 on self-regulatory fatigue.

The relationship between loneliness and bedtime procrastination

This study found that loneliness significantly and positively correlated with bedtime procrastination, consistent with previous findings [52, 112]. University students, as a target group among young people, have been shown to experience widespread loneliness in several studies [113, 114]. A short-term focus on adjusting to negative experiences and feelings associated with negative emotions, such as loneliness, can lead to a failure of control in other areas of life [115], such as an increase in bedtime procrastination. This negative expectations to the future causes individuals to delay bedtime to slow the arrival of the next day [62].

The mediating role of risk perception of covid-19

In a post-pandemic environment, loneliness caused by a lack of social bonds triggers more negative perceptions, making individuals tend to interpret environments as having high risk [21, 65], and suffer higher levels of distress. Risk perception positively predicts individual stress levels [116], which can further exacerbate a range of negative emotions[117]. Based on emotional responses to the risk perception of COVID-19, uncertainty arises and leads to multiple types of maladaptive problems [118], ultimately affecting bedtime procrastination [119].

The mediating role of self-regulatory fatigue

The present study also confirmed that loneliness could correlated with bedtime procrastination in university students through the mediating role of self-regulatory fatigue, which further supports ego depletion theory [77, 78]. When an individual's limited resources are greatly depleted, the individual enters a state of ego depletion, leading to bedtime procrastination. Additionally, loneliness motivates individuals to regulate their emotions and seek closer social connections [65, 120]. However, during the adjustment process, both the negative emotions themselves and the demanding interpersonal interactions in the pandemic environment increase the burden of cognitive processing [78, 79], thus consuming more psychological resources and making individuals more likely to fall into a state of self-regulatory fatigue and delay bedtime [84].

The chain mediating role of risk perception of COVID-19 and self-regulatory fatigue

In addition, the findings showed significant chain mediating effects of risk perception of COVID-19 and self-regulatory fatigue. Loneliness can make individuals more susceptible to perceptions of insecurity in the social environment and heightened sensitivity to external risks [69, 112], while elevated perceptions of pandemic-related threats can generate stress and negative emotions, which in turn deplete intrinsic attention and cognitive resources, lead to de-inhibition and self-regulatory fatigue, and trigger bedtime procrastination [93, 121].

Moreover, elevated risk perceptions due to loneliness can lead to higher uncertainty. The information-seeking and processing model of risk suggests that individuals at higher risk tend to actively gather risk-related information to construct defensive attitudes, beliefs, and behaviors to maintain their health due to uncertainty about risky events [122]. Therefore, to cope with the high-risk perception of COVID-19 and uncertainty in the current post-pandemic period, university students, who are the main users of the Internet medium [123], are more inclined to seek more knowledge and information through the Internet to reduce the sense of threat and negative emotions caused by uncertainty [118, 124, 125]. However, various online platforms and related reports are filled with a large amount of information that is difficult to distinguish between true and false and often overwhelms individuals, causing information overload, taking up more limited cognitive resources [126], and leading to self-depletion.

The moderating role of connectedness to nature

Our results also revealed that connectedness to nature mitigated the adverse effects of risk perception COVID-19 on self-regulatory fatigue. This result further supports the stress recovery theory during exposure to natural and urban environments [97]. Exposure to nature helps reduce fatigue, replenish self-control resources, and increase the availability of psychological resources in the face of the pandemic risk, allowing people to better cope with stressful situations [96, 127] and avoid ego-depletion states [95]. By contrast, individuals with low connectedness to nature have fewer psychological resources. Their over-perception of pandemic risk results in a cognitive load that is difficult to regulate [65, 79], leading them to become more susceptible to a state of self-regulatory fatigue and ultimately increase bedtime procrastination [128, 129].

Implications and future directions

In contrast to previous perspectives on coping with stress and physiological responses, this study explains the relationship between loneliness and bedtime procrastination in the post-pandemic period from the perspective of regulatory resources, emphasizing the importance of psychological resources in regulating emotional experiences and daily routines. Considering the negative effect of COVID-19 pandemic is ongoing and it has brought with significant health, economic and social uncertainties, people will still face the challenge of self-control. Plus, From a future perspective, people are still facing the continued mutation of coronaviruses and may encounter similar public health crises in the future. COVID-19 has made considerable physical and psychological impacts on governments and individuals [130, 131]. Such impacts have been shown to continually affect individuals' daily lives and even influence their responses to future public health crises [131]. Therefore, this study provides us with a new perspective, that is, from the perspective of regulatory resources, we should understand the internal mechanism of how loneliness affects the sleep behavior of college students in the context of the current social environment which is full of uncertainty, which also provides more insights for evidence-based interventions.

Moreover, for university students, contact with nature is closely linked to daily travel and campus life and is an easy, convenient, and feasible measure to regulate mood. With the complete relaxation of pandemic prevention and control measures, university students' opportunities and frequency of going outside will gradually rebound, and their exposure to the natural environment will increase. The results of this study also call for university students to be more exposed to the natural environment, which may bring many physical and mental benefits.

However, the present study has some limitations. First, the data in this study were obtained from participants’ self-reports, and a possible subjective reporting bias may have affected the reliability of the results. Second, a cross-sectional study design was used in the study design, which made it difficult to reveal the causal relationships between the variables. Moreover, since the pandemic outbreak, China has taken strict preventive and control measures and insisted on "dynamic zero,” In contrast, the post-pandemic period, all the strict preventive and control measures for the pandemic were phased out in the short term. As people cope with high infection rates and risks, there is a greater need to adapt to sudden changes in policy and lifestyle, all of which can impact the individuals’ psychological state. Therefore, the post-pandemic period in China was unique. There may be differences in emotions and psychological adjustment resources between Chinese individuals and individuals in other countries post-pandemic, and future research could further examine research models in a cross-cultural scenario.

Conclusions

This study explored the effects and potential mechanisms of loneliness on bedtime procrastination after the relaxation of the pandemic prevention and control policy in China from a new perspective. Results showed that loneliness significantly correlated with bedtime procrastination. Risk perception of COVID-19 mediated the effect between loneliness and bedtime procrastination. Self-regulatory fatigue also mediated the effect of loneliness on bedtime procrastination. Risk perception of COVID-19 and self-regulatory fatigue mediated the chain between loneliness and bedtime procrastination. Connectedness to nature mediates the effect of risk perception of COVID-19 on self-regulatory fatigue.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Marelli S, et al. Impact of COVID-19 lockdown on sleep quality in university students and administration staff. J Neurol. 2021;268:8–15. https://doi.org/10.1007/s00415-020-10056-6.

    Article  CAS  PubMed  Google Scholar 

  2. Becker SP, Gregory AM. Editorial Perspective: Perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic. J Child Psychol Psychiatry. 2020;61:757–9. https://doi.org/10.1111/jcpp.13278.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Gulia KK, Kumar VM. Importance of sleep for health and wellbeing amidst COVID-19 pandemic. Sleep and vigilance. 2020;4(1):49–50. https://doi.org/10.1007/s41782-020-00087-4.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Wathelet, M., et al., Factors Associated With Mental Health Disorders Among University Students in France Confined During the COVID-19 Pandemic. Jama Network Open, 2020. 3(10). https://doi.org/10.1001/jamanetworkopen.2020.25591

  5. Baloran ET. Knowledge, Attitudes, Anxiety, and Coping Strategies of Students during COVID-19 Pandemic. J Loss Trauma. 2020;25(8):635–42. https://doi.org/10.1080/15325024.2020.1769300.

    Article  Google Scholar 

  6. Cerqueira TRDC, et al. Impact of the COVID-19 pandemic on stress, sleep, and oral health in university students. Front Pain Res. 2021;2:744264. https://doi.org/10.3389/fpain.2021.744264.

    Article  Google Scholar 

  7. Wright KP, et al. Sleep in university students prior to and during COVID-19 Stay-at-Home orders. Curr Biol. 2020;30(14):R797–8. https://doi.org/10.1016/j.cub.2020.06.022.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Dongol E, et al. Sleep quality, stress level and COVID-19 in university students; the forgotten dimension. Sleep Sci. 2022;15:347–54. https://doi.org/10.5935/1984-0063.20210011.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Society, C.S.R. White Paper on Sleep in China during the 2020 Pandemic Lockdown. 2020; Available from: https://www.derucci.com/article-202003-1116-1.html.

  10. Council, T.J.P.a.C.M.o.t.S. Notice on further optimization of the implementation of measures for the prevention and control of the COVID-19. 2022; Available from: http://www.gov.cn/xinwen/2022-12/07/content_5730443.htm.

  11. Prevention, C.C.f.D.C.a. National outbreak of the COVID-19. 2023; Available from: https://www.chinacdc.cn/jkzt/crb/zl/szkb_11803/jszl_13141/202302/t20230201_263576.html

  12. Pilcher JJ, et al. Social isolation and sleep: manifestation during COVID-19 quarantines. Front Psychol. 2022;12:6476. https://doi.org/10.3389/fpsyg.2021.810763.

    Article  Google Scholar 

  13. Ali A, et al. Effects of COVID-19 pandemic and lockdown on lifestyle and mental health of students: A retrospective study from Karachi, Pakistan. Ann Méd Psychol. 2022;180(6):S29–37. https://doi.org/10.1016/j.amp.2021.02.004.

    Article  Google Scholar 

  14. Ye, Y., China’s rolling COVID waves could hit every six months — infecting millions, in Nature News. 2023.

  15. Prevention, C.f.D.C.a. Update on SARS-CoV-2 Variant JN.1 Being Tracked by CDC. 2023.

  16. Mueller, M.R., et al. Post-COVID conditions. in Mayo Clinic Proceedings. 2023. Elsevier.

  17. Abul Y, Leeder C, Gravenstein S. Epidemiology and clinical presentation of COVID-19 in older adults. Infect Dis Clin. 2023;37(1):1–26. https://doi.org/10.1016/j.idc.2022.11.001.

    Article  Google Scholar 

  18. Lavie P. Sleep disturbances in the wake of traumatic events. N Engl J Med. 2001;345(25):1825–32. https://doi.org/10.1056/nejmra012893.

    Article  CAS  PubMed  Google Scholar 

  19. Kayaba, M., et al., Delayed sleep-wake rhythm due to staying at home during the COVID-19 pandemic and sleep debt after returning to campus among Japanese nursing university students: A longitudinal study. Heliyon, 2023. 9(4). https://doi.org/10.1016/j.heliyon.2023.e14994

  20. Gu Y, Tao L, Zheng W. Relationship between COVID-19-related stress and social inhibition among university students in China: The mediating role of psychological richness. Soc Pers Psychol Compass. 2023;17(11):e12872. https://doi.org/10.1111/spc3.12872.

    Article  Google Scholar 

  21. Eccles AM, et al. Trajectories of early adolescent loneliness: implications for physical health and sleep. J Child Fam Stud. 2020;29:3398–407. https://doi.org/10.1007/s10826-020-01804-3.

    Article  Google Scholar 

  22. Perez LG, et al. Loneliness and multiple health domains: Associations among emerging adults. J Behav Med. 2022;45(2):260–71. https://doi.org/10.1007/s10865-021-00267-1.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Li J-B, et al. Self-control moderates the association between perceived severity of coronavirus disease 2019 (COVID-19) and mental health problems among the Chinese public. Int J Environ Res Public Health. 2020;17(13):4820. https://doi.org/10.3390/ijerph17134820.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Scharmer C, et al. Eating disorder pathology and compulsive exercise during the COVID-19 public health emergency: Examining risk associated with COVID-19 anxiety and intolerance of uncertainty. Int J Eat Disord. 2020;53(12):2049–54. https://doi.org/10.1002/eat.23395.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Satici B, et al. Intolerance of uncertainty and mental wellbeing: Serial mediation by rumination and fear of COVID-19. Int J Ment Heal Addict. 2022;20(5):2731–42. https://doi.org/10.1007/s11469-020-00305-0.

    Article  Google Scholar 

  26. Bulut, M.B., Relationship between COVID-19 anxiety and fear of death: the mediating role of intolerance of uncertainty among a Turkish sample. Current Psychology, 2022: p. 1–10. https://doi.org/10.1007/s12144-022-03281-x

  27. Yang Q, Van den Bos K, Li Y. Intolerance of uncertainty, future time perspective, and self-control. Personality Individ Differ. 2021;177:110810. https://doi.org/10.1016/j.paid.2021.110810.

    Article  Google Scholar 

  28. Baumeister, R.F., Ego depletion and the self's executive function. 2000. https://doi.org/10.1037/10357-001

  29. Tan S, et al. Ego Depletion: Theory, Influencing Factors and Research Trend. Adv Psychol Sci. 2012;20(5):715–25. https://doi.org/10.3724/SP.J.1042.2012.00715.

    Article  Google Scholar 

  30. Peterson C, Seligman ME, Vaillant GE. Pessimistic explanatory style is a risk factor for physical illness: a thirty-five-year longitudinal study. J Pers Soc Psychol. 1988;55(1):23. https://doi.org/10.1037/0022-3514.55.1.23.

    Article  CAS  PubMed  Google Scholar 

  31. Flouri E, Mavroveli S. Adverse life events and emotional and behavioural problems in adolescence: The role of coping and emotion regulation. Stress Health. 2013;29(5):360–8. https://doi.org/10.1002/smi.2478.

    Article  PubMed  Google Scholar 

  32. Folkman S, et al. Appraisal, coping, health status, and psychological symptoms. J Pers Soc Psychol. 1986;50(3):571. https://doi.org/10.1037/0022-3514.50.3.571.

    Article  CAS  PubMed  Google Scholar 

  33. Hazel NA, et al. Parent relationship quality buffers against the effect of peer stressors on depressive symptoms from middle childhood to adolescence. Dev Psychol. 2014;50(8):2115. https://doi.org/10.1037/a0037192.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Fan F, et al. Mental Health Problems and Correlates among Adolescents 6 Months after Exposed to the Wenchuan Earthquake. Chin J Clin Psychol. 2010;18(01):56–9. https://doi.org/10.16128/j.cnki.1005-3611.2010.01.040.

    Article  Google Scholar 

  35. Tang I-C, Sullivan WC, Chang C-Y. Perceptual evaluation of natural landscapes: The role of the individual connection to nature. Environ Behav. 2015;47(6):595–617. https://doi.org/10.1177/0013916513520604.

    Article  Google Scholar 

  36. Izenstark, D.M., The effects of the natural environment on attention and family functioning: An experimental study. 2017.

  37. Russell DW. UCLA Loneliness Scale (Version 3): Reliability, validity, and factor structure. J Pers Assess. 1996;66(1):20–40. https://doi.org/10.1207/s15327752jpa6601_2.

    Article  CAS  PubMed  Google Scholar 

  38. Mansfield L, et al. A conceptual review of loneliness in adults: Qualitative evidence synthesis. Int J Environ Res Public Health. 2021;18(21):11522. https://doi.org/10.3390/ijerph182111522.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Marangoni C, Ickes W. Loneliness: A theoretical review with implications for measurement. J Soc Pers Relat. 1989;6(1):93–128. https://doi.org/10.1177/026540758900600107.

    Article  Google Scholar 

  40. Peng A, et al. Association between loneliness, sleep behavior and quality: a propensity-score-matched case–control study. Sleep Med. 2021;86:19–24. https://doi.org/10.1016/j.sleep.2021.08.008.

    Article  PubMed  Google Scholar 

  41. Harris RA, Qualter P, Robinson SJ. Loneliness trajectories from middle childhood to pre-adolescence: Impact on perceived health and sleep disturbance. J Adolesc. 2013;36(6):1295–304. https://doi.org/10.1016/j.adolescence.2012.12.009.

    Article  PubMed  Google Scholar 

  42. Matthews T, et al. Sleeping with one eye open: loneliness and sleep quality in young adults. Psychol Med. 2017;47(12):2177–86. https://doi.org/10.1017/S0033291717000629.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ipsos. Global perceptions of the impact of COVID-19. 2021; Available from: https://www.ipsos.com/en-cn/loneliness-increase-worldwide-increase-local-community-support.

  44. Index, C.U.S.L. Survey of 20,000 Americans examining behaviors driving loneliness in the United States. 2018; Available from: https://www.multivu.com/players/English/8294451-cigna-us-loneliness-survey/docs/IndexReport_1524069371598-173525450.pdf.

  45. O’sullivan R, et al. Impact of the COVID-19 pandemic on loneliness and social isolation: A multi-country study. Int J Environ Res Public Health. 2021;18(19):9982. https://doi.org/10.3390/ijerph18199982.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Armitage R, Nellums LB. COVID-19 and the consequences of isolating the elderly. Lancet Public Health. 2020;5(5):e256. https://doi.org/10.1016/S2468-2667(20)30061-X.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Coughlan, S. Kate warns of lockdown loneliness for parents. BBC News 2020; Available from: https://www.bbc.com/news/education-55078644.

  48. Fumagalli E, Dolmatzian MB, Shrum L. Centennials, FOMO, and loneliness: An investigation of the impact of social networking and messaging/VoIP apps usage during the initial stage of the coronavirus pandemic. Front Psychol. 2021;12:620739. https://doi.org/10.3389/fpsyg.2021.620739.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Yeung, Y.Y. and C.P. Yu, Motivating young adults to connect with nature for stress relief: A study in Taiwan during the COVID-19 pandemic. Front Psychiatry, 2022. 13. https://doi.org/10.3389/fpsyt.2022.922107

  50. Padmanabhanunni, A. and T.B. Pretorius, The unbearable loneliness of COVID-19: COVID-19-related correlates of loneliness in South Africa in young adults. Psychiatry Res, 2021. 296. https://doi.org/10.1016/j.psychres.2020.113658

  51. Killgore WD, et al. Loneliness: A signature mental health concern in the era of COVID-19. Psychiatry Res. 2020;290:113117. https://doi.org/10.1016/j.psychres.2020.113117.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Grey, I., T. Arora, and A. Sanah, Generalized Anxiety Mediates the Relationship Between Loneliness and Sleep Quality Amongst Young Adults During the COVID-19 Pandemic. Psychol Rep, 2022: p. 00332941221079723. https://doi.org/10.1177/00332941221079723

  53. Dingle GA, Han R, Carlyle M. Loneliness, Belonging, and Mental Health in Australian University Students Pre- and Post-COVID-19. Behav Chang. 2022;39(3):146–56. https://doi.org/10.1017/bec.2022.6.

    Article  Google Scholar 

  54. Daily, D. Everyone is the first person responsible for his or her own health. 2022; Available from: http://www.qchdj.gov.cn/staticPage/dtsy/redianguanzhu/20221217/12392345.html

  55. Ge, D., Challenges and Countermeasures for the Development of Higher Education in the Post-Pandemic Era. China Assoc High Educ, 2023(02): p. 31–39. https://doi.org/10.16298/j.cnki.1004-3667.2023.02.05

  56. Liu, B. 2023, the first year of the post-epidemic era. 2023; Available from: https://www.cankaoxiaoxi.com/culture/20230109/2501223.shtml.

  57. Steel P. The nature of procrastination: a meta-analytic and theoretical review of quintessential self-regulatory failure. Psychol Bull. 2007;133(1):65. https://doi.org/10.1037/0033-2909.133.1.65.

    Article  MathSciNet  PubMed  Google Scholar 

  58. Kroese FM, et al. Bedtime procrastination: introducing a new area of procrastination. Front Psychol. 2014;5:611. https://doi.org/10.3389/fpsyg.2014.00611.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Sirois F, Pychyl T. Procrastination and the priority of short-term mood regulation: Consequences for future self. Soc Pers Psychol Compass. 2013;7(2):115–27. https://doi.org/10.1111/spc3.12011.

    Article  Google Scholar 

  60. Baumeister RF, Zell AL, Tice DM. How emotions facilitate and impair self-regulation. Handbook Emotion Regul. 2007;1:408–26.

    Google Scholar 

  61. Teneva N, Lemay EP Jr. Projecting loneliness into the past and future: Implications for self-esteem and affect. Motiv Emot. 2020;44(5):772–84. https://doi.org/10.1007/s11031-020-09842-6.

    Article  Google Scholar 

  62. Nauts S, et al. Aversive bedtime routines as a precursor to bedtime procrastination. Eur Health Psychol. 2016;18(2):80–5.

    Google Scholar 

  63. Slovic P. Perception of risk. Science. 1987;236(4799):280–5. https://doi.org/10.1126/science.3563507.

    Article  CAS  PubMed  ADS  Google Scholar 

  64. Śmieja M, et al. Not moved, still lonely: the negative relation between loneliness and being moved. Motiv Emot. 2022;46(4):557–71. https://doi.org/10.1007/s11031-022-09955-0.

    Article  Google Scholar 

  65. Cacioppo JT, Hawkley LC. Perceived social isolation and cognition. Trends Cogn Sci. 2009;13(10):447–54. https://doi.org/10.1016/j.tics.2009.06.005.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Cacioppo JT, et al. Loneliness within a nomological net: An evolutionary perspective. J Res Pers. 2006;40(6):1054–85. https://doi.org/10.1016/j.jrp.2005.11.007.

    Article  Google Scholar 

  67. Qualter P, et al. Investigating hypervigilance for social threat of lonely children. J Abnorm Child Psychol. 2013;41:325–38. https://doi.org/10.1007/s10802-012-9676-x.

    Article  PubMed  Google Scholar 

  68. Okruszek Ł, et al. Safe but lonely? Loneliness, anxiety, and depression symptoms and COVID-19. Front Psychol. 2020;11:579181. https://doi.org/10.3389/fpsyg.2020.579181.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Komasi S, et al. Subjective correlates of stress management in outpatient cardiac rehabilitation: the predictive role of perceived heart risk factors. J Cardiovasc Thor Res. 2018;10(2):104. https://doi.org/10.15171/jcvtr.2018.16.

    Article  Google Scholar 

  70. Lange LJ, Fleming R, Toussaint LL. Risk perceptions and stress during the threat of explosion from a railroad accident. Soc Behav Personal Int J. 2004;32(2):117–27. https://doi.org/10.2224/sbp.2004.32.2.117.

    Article  Google Scholar 

  71. Job V, et al. Implicit Theories About Willpower Predict Self-Regulation and Grades in Everyday Life. J Pers Soc Psychol. 2015;108(4):637–47. https://doi.org/10.1037/pspp0000014.

    Article  PubMed  Google Scholar 

  72. Job V, Dweck CS, Walton GM. Ego Depletion-Is It All in Your Head? Implicit Theories About Willpower Affect Self-Regulation. Psychol Sci. 2010;21(11):1686–93. https://doi.org/10.1177/0956797610384745.

    Article  PubMed  Google Scholar 

  73. Bernecker K, Job V. Too exhausted to go to bed: Implicit theories about willpower and stress predict bedtime procrastination. Br J Psychol. 2020;111(1):126–47. https://doi.org/10.1111/bjop.12382.

    Article  PubMed  Google Scholar 

  74. Fu Y, Ma X, Mu L. The Physiological and Psychological Mechanisms of Bedtime Procrastination. J Psychol Sci. 2020;43(05):1190–6. https://doi.org/10.16719/j.cnki.1671-6981.20200523.

    Article  Google Scholar 

  75. Wright WF, Bower GH. Mood effects on subjective probability assessment. Organ Behav Hum Decis Process. 1992;52(2):276–91. https://doi.org/10.1016/0749-5978(92)90039-A.

    Article  Google Scholar 

  76. Lopez-Kidwell V, et al. What matters when: a multistage model and empirical examination of job search effort. Acad Manag J. 2013;56(6):1655–78. https://doi.org/10.5465/amj.2011.0546.

    Article  Google Scholar 

  77. Baumeister RF, et al. Ego depletion: Is the active self a limited resource? J Pers Soc Psychol. 1998;74(5):1252–65. https://doi.org/10.1037/0022-3514.74.5.1252.

    Article  CAS  PubMed  Google Scholar 

  78. Muraven M, Baumeister RF. Self-regulation and depletion of limited resources: Does self-control resemble a muscle? Psychol Bull. 2000;126(2):247–59. https://doi.org/10.1037/0033-2909.126.2.247.

    Article  CAS  PubMed  Google Scholar 

  79. Yang, H., et al., Workplace loneliness, ego depletion and cyberloafing: can leader problem-focused interpersonal emotion management help? Int Res, 2022(ahead-of-print). https://doi.org/10.1108/INTR-01-2021-0007

  80. Fan ZP, Chen M, Lin YP. Self-Control and Problematic Internet Use in College Students: The Chain Mediating Effect of Rejection Sensitivity and Loneliness. Psychol Res Behav Manag. 2022;15:459–70. https://doi.org/10.2147/prbm.S352060.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Kamphorst, B.A., et al., Too Depleted to Turn In: The Relevance of End-of-the-Day Resource Depletion for Reducing Bedtime Procrastination. Front Psychol, 2018. 9. https://doi.org/10.3389/fpsyg.2018.00252

  82. Exelmans L, Van den Bulck J. Self-control depletion and sleep duration: the mediating role of television viewing. Psychol Health. 2018;33(10):1251–68. https://doi.org/10.1080/08870446.2018.1489048.

    Article  PubMed  Google Scholar 

  83. Procee, R., et al., A formal model of procrastination. 2013.

  84. Sirois FM, Nauts S, Molnar DS. Self-Compassion and Bedtime Procrastination: an Emotion Regulation Perspective. Mindfulness. 2019;10(3):434–45. https://doi.org/10.1007/s12671-018-0983-3.

    Article  Google Scholar 

  85. Cameron, L.D., et al., Self-Regulation Principles Underlying Risk Perception and Decision Making within the Context of Genomic Testing. Social and personality psychology compass, 2017. 11(5). https://doi.org/10.1111/spc3.12315

  86. Cameron LD. Illness risk representations and motivations to engage in protective behavior: The case of skin cancer risk. Psychol Health. 2008;23(1):91–112. https://doi.org/10.1080/14768320701342383.

    Article  PubMed  Google Scholar 

  87. Cameron LD, Jago L. Emotion regulation interventions: A common-sense model approach. Br J Health Psychol. 2008;13:215–21. https://doi.org/10.1348/135910708x288800.

    Article  PubMed  Google Scholar 

  88. Hall PA, Fong GT. Temporal self-regulation theory: A model for individual health behavior. Health Psychol Rev. 2007;1:52–6. https://doi.org/10.1080/17437190701492437.

    Article  Google Scholar 

  89. Johnson BB, Slovic P. PRESENTING UNCERTAINTY IN HEALTH RISK ASSESSMENT - INITIAL STUDIES OF ITS EFFECTS ON RISK PERCEPTION AND TRUST. Risk Anal. 1995;15(4):485–94. https://doi.org/10.1111/j.1539-6924.1995.tb00341.x.

    Article  CAS  PubMed  Google Scholar 

  90. Ho, H. and T. Watanabe, The Roles of Three Types of Knowledge and Perceived Uncertainty in Explaining Risk Perception, Acceptability, and Self-Protective Response-A Case Study on Endocrine Disrupting Surfactants. Int J Environ Res Public Health, 2018. 15(2). https://doi.org/10.3390/ijerph15020296

  91. Li, Q., et al., Intolerance of COVID-19-Related Uncertainty and Negative Emotions among Chinese Adolescents: A Moderated Mediation Model of Risk Perception, Social Exclusion and Perceived Efficacy. Int J Environ Res Public Health, 2021. 18(6). https://doi.org/10.3390/ijerph18062864

  92. Flores A, et al. Intolerance of uncertainty as a vulnerability factor for excessive and inflexible avoidance behavior. Behav Res Ther. 2018;104:34–43. https://doi.org/10.1016/j.brat.2018.02.008.

    Article  PubMed  Google Scholar 

  93. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. Psychiatry Res. 2020;288:112954–112954. https://doi.org/10.1016/j.psychres.2020.112954.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Mayer FS, Frantz CM. The connectedness to nature scale: A measure of individuals’ feeling in community with nature. J Environ Psychol. 2004;24(4):503–15. https://doi.org/10.1016/j.jenvp.2004.10.001.

    Article  Google Scholar 

  95. Kaplan S. The restorative benefits of nature: Toward an integrative framework. J Environ Psychol. 1995;15(3):169–82. https://doi.org/10.1016/0272-4944(95)90001-2.

    Article  Google Scholar 

  96. Beute F, De Kort Y. Natural resistance: Exposure to nature and self-regulation, mood, and physiology after ego-depletion. J Environ Psychol. 2014;40:167–78. https://doi.org/10.1016/j.jenvp.2014.06.004.

    Article  Google Scholar 

  97. Ulrich RS, et al. Stress recovery during exposure to natural and urban environments. J Environ Psychol. 1991;11(3):201–30. https://doi.org/10.1016/S0272-4944(05)80184-7.

    Article  MathSciNet  Google Scholar 

  98. Yang Y, et al. Nature connectedness: It’s concept, measurement, function and intervention. Adv Psychol Sci. 2017;25(08):1360–74. https://doi.org/10.3724/SP.J.1042.2017.01360.

    Article  Google Scholar 

  99. Ayran, G., H.N. Çevik Özdemir, and E. Yaman, The effect of risk perception, mask use, and social distance behavior on perceived stress in the COVID‐19 process: A sectional study. J Child Adolesc Psychiatr Nurs, 2023. https://doi.org/10.1111/jcap.12409

  100. Griffin RJ, Dunwoody S, Neuwirth K. Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. Environ Res. 1999;80(2):S230–45. https://doi.org/10.1006/enrs.1998.3940.

    Article  CAS  PubMed  ADS  Google Scholar 

  101. Zhao, J., B.J. Ye, and T.T. Ma, Positive Information of COVID-19 and Anxiety: A Moderated Mediation Model of Risk Perception and Intolerance of Uncertainty. Front Psychiatry, 2021. 12. https://doi.org/10.3389/fpsyt.2021.715929

  102. Russell D, Peplau LA, Cutrona CE. The revised UCLA Loneliness Scale: concurrent and discriminant validity evidence. J Pers Soc Psychol. 1980;39(3):472–80. https://doi.org/10.1037/0022-3514.39.3.472.

    Article  CAS  PubMed  Google Scholar 

  103. Wang D. Reliability and Validity of the Russell Loneliness Scale. Chin J Clin Psychol. 1995;01:23–5.

    Google Scholar 

  104. Xi, J., et al., Development and Validity of the Perceived Risk of COVID-19 Pandemic Scale. J Capital Normal University(Social Sciences Edition), 2020(04):131-141 https://doi.org/10.3969/j.issn.1004-9142.2020.04.016

  105. Nes LS, et al. Self-regulatory fatigue in chronic multisymptom illnesses: scale development, fatigue, and self-control. J Pain Res. 2013;6:181–8. https://doi.org/10.2147/jpr.S40014.

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  106. Wang L, et al. Validity and reliability of the Chinese version of the Self-Regulatory Fatigue Scale in young adults. Chin Ment Health J. 2015;29(04):290–4. https://doi.org/10.3969/j.issn.1000-6729.2015.04.010.

    Article  Google Scholar 

  107. Lance, C.E. and R.J. Vandenberg, Statistical and methodological myths and urban legends: Doctrine, verity and fable in the organizational and social sciences. 2009: Taylor & Francis.

  108. Ma X, et al. Reliability and Validity of the Bedtime Procrastination Scale in Chinese College Students Chinese. J Clin Psychology. 2021;29(04):717–20. https://doi.org/10.16128/j.cnki.1005-3611.2021.04.011.

    Article  Google Scholar 

  109. Li N, Wu J. Revise of the Connectedness to Nature Scale and its Reliability and Validity China. J Health Psychology. 2016;24(09):1347–50. https://doi.org/10.13342/j.cnki.cjhp.2016.09.018.

    Article  Google Scholar 

  110. Podsakoff PM, et al. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879. https://doi.org/10.1037/0021-9010.88.5.879.

    Article  PubMed  Google Scholar 

  111. Hayes, A.F., Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. 2017: Guilford publications.

  112. Grossman ES, et al. COVID-19 related loneliness and sleep problems in older adults: Worries and resilience as potential moderators. Personality Individ Differ. 2021;168:110371. https://doi.org/10.1016/j.paid.2020.110371.

    Article  Google Scholar 

  113. Diehl, K., et al., Loneliness at Universities: Determinants of Emotional and Social Loneliness among Students. Int J Environ Res Public Health, 2018. 15(9). https://doi.org/10.3390/ijerph15091865

  114. Bu F, Steptoe A, Fancourt D. Who is lonely in lockdown? Cross-cohort analyses of predictors of loneliness before and during the COVID-19 pandemic. Public Health. 2020;186:31–4. https://doi.org/10.1016/j.puhe.2020.06.036.

    Article  CAS  PubMed  Google Scholar 

  115. Tice DM, Bratslavsky E. Giving in to feel good: the place of emotion regulation in the context of general self-control. Psychol Inq. 2000;11(3):149–59. https://doi.org/10.1207/s15327965pli1103_03.

    Article  Google Scholar 

  116. Vázquez EL. Risk perception interactions in stress and coping facing extreme risks. Environ Manag Health. 2001;12:122–33. https://doi.org/10.1108/09566160110389889.

    Article  Google Scholar 

  117. Leppin A, Aro AR. Risk perceptions related to SARS and Avian Influenza: Theoretical Foundations of Current Empirical Research. Int J Behav Med. 2009;16(1):7–29. https://doi.org/10.1007/s12529-008-9002-8.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Huang Y, Yang C. A metacognitive approach to reconsidering risk perceptions and uncertainty: understand information seeking during COVID-19. Sci Commun. 2020;42(5):616–42. https://doi.org/10.1177/1075547020959818.

    Article  Google Scholar 

  119. Burgard SA, Ailshire JA. Putting work to bed: stressful experiences on the job and sleep quality. J Health Soc Behav. 2009;50(4):476–92. https://doi.org/10.1177/002214650905000407.

    Article  PubMed  PubMed Central  Google Scholar 

  120. Qualter P, et al. Loneliness across the life span. Perspect Psychol Sci. 2015;10(2):250–64. https://doi.org/10.1177/1745691615568999.

    Article  PubMed  Google Scholar 

  121. Hagger MS, et al. Ego Depletion and the Strength Model of Self-Control: A Meta-Analysis. Psychol Bull. 2010;136(4):495–525. https://doi.org/10.1037/a0019486.

    Article  PubMed  Google Scholar 

  122. Griffin RJ, Neuwirth K, Dunwoody S. Using the Theory of Reasoned Action to Examine the Impact of Health Risk Messages. Ann Int Commun Assoc. 1995;18:201–28. https://doi.org/10.1080/23808985.1995.11678913.

    Article  Google Scholar 

  123. Center, C.I.N.I. The 47th China Statistical Report on Internet Development. 2021; Available from: http://www.cac.gov.cn/2021-02/03/c_1613923423079314.htm

  124. Fung TKF, Griffin RJ, Dunwoody S. Testing Links Among Uncertainty, Affect, and Attitude Toward a Health Behavior. Sci Commun. 2018;40(1):33–62. https://doi.org/10.1177/1075547017748947.

    Article  Google Scholar 

  125. Petty RE, et al. The role of metacognition in social judgment. In: Social psychology: Handbook of basic principles. 2nd ed. New York, NY, US: The Guilford Press; 2007. p. 254–84.

    Google Scholar 

  126. Xu C, Yan WH. The relationship between information overload and state of anxiety in the period of regular epidemic prevention and control in China: a moderated multiple mediation model. Curr Psychol. 2022. https://doi.org/10.1007/s12144-022-03289-3.

    Article  PubMed  PubMed Central  Google Scholar 

  127. Chow JT, Lau S. Nature Gives Us Strength: Exposure to Nature Counteracts Ego-Depletion. J Soc Psychol. 2015;155(1):70–85. https://doi.org/10.1080/00224545.2014.972310.

    Article  PubMed  Google Scholar 

  128. Siebenhaar, K.U., A.K. Kother, and G.W. Alpers, Dealing With the COVID-19 Infodemic: Distress by Information, Information Avoidance, and Compliance With Preventive Measures. Front Psychol, 2020. 11. https://doi.org/10.3389/fpsyg.2020.567905

  129. Song, S.J., X.L. Yao, and N.A. Wen, What motivates Chinese consumers to avoid information about the COVID-19 pandemic?: The perspective of the stimulus-organism-response model. Inform Process Manag, 2021. 58(1). https://doi.org/10.1016/j.ipm.2020.102407

  130. Laddu DR, et al. The impact of the COVID-19 pandemic on cardiovascular health behaviors and risk factors: a new troubling normal that may be here to stay. Prog Cardiovasc Dis. 2023;76:38–43. https://doi.org/10.1016/j.pcad.2022.11.017.

    Article  PubMed  Google Scholar 

  131. Sprengholz P, et al. Historical narratives about the COVID-19 pandemic are motivationally biased. Nature. 2023;623(7987):588–93. https://doi.org/10.1038/s41586-023-06674-5.

    Article  CAS  PubMed  ADS  Google Scholar 

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  1. Cheng Xu and Nongying Lin are co-first authors.

Authors and Affiliations

  1. School of Psychology and Cognitive Science, East China Normal University, Shanghai, China

    Cheng Xu, Nongying Lin, Zhiyu Shen, Zhaoyang Xie, Duo Xu & Jingdong Fu

  2. Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China, 200062

    Wenhua Yan

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Cheng Xu, Nongying Lin, Zhiyu Shen and Jingdong Fu. The first draft of the manuscript was written by Cheng Xu, Nongying Lin, Zhaoyang Xie and Duo Xu. Wenhua Yan commented and revised previous versions of the manuscript. All authors read the final manuscript. All authors approved the final manuscript and the submission to this journal.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. This study was conducted with the approval of the Ethics Committee of East China Normal University(No: HR1-0130–2022). Informed consent has been obtained from all the participants.

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Xu, C., Lin, N., Shen, Z. et al. Bedtime procrastination related to loneliness among Chinese university students during post-pandemic period: a moderated chain mediation model. BMC Public Health 24, 491 (2024). https://doi.org/10.1186/s12889-024-18019-6

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ISSN: 1471-2458

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