Introduction

Because of its high infectiousness, the COVID-19 epidemic at the end of 2019 quickly swept through countries and became a pandemic. Facing such an outbreak, numerous governments and regions adopted a lockdown control strategy [1]. Lockdown strategies implemented effectively halted the spread of the virus and saved the lives and health of millions of people on time. Lockdown following the outbreak was demonstrated to have a positive effect on epidemic. However, there are two sides of each coin. Lockdown has gradually been discovered to have a significant detrimental impact not only on social level activities such as daily work, schooling, economic activities, and social connection but also on people’s physical and mental health at the individual level [2,3]. It has even been viewed as another public health phenomenon, which has sparked some debate [2,4].

For competitive athletes, the issues of lockdown are considerable. Lockdown does not mean resting at home or working from home with a decreased commute for athletes in competitive sports, but rather creating the conditions to continue training at a certain level and without the opportunity to compete [5,6]. In such circumstances, they must remain physically and mentally prepared for future competitions. Sleep and emotional state are relatively major aspects influencing performance for athletes in lockdown [7,8]. However, research on the influence of lockdown on sleep and mood has repeatedly shown that it induces significant negative changes in sleep and mood [9–15]. This is especially true for athletes. Athletes, like the general public, exhibit comparable patterns of sleep and psychological changes during a lockdown, according to researchers. For example, one study of 399 Australian professional athletes discovered that under the influence of lockdown, athletes experienced an increase in sleep duration, delayed sleep time, and sleep latency [16]; Spanish handball players experienced reduced sleep quality and became emotionally negative during isolation [17]; a survey in 3911 athletes from 49 countries revealed an increase in sleep duration, delayed sleep time [8]; and it is especially noteworthy that a study conducted on 1454 elite athletes found worse sleep quality in lockdown and it also found that those with reduced training intensity had poorer sleep quality, which adds insult to injury [7]. Furthermore, some researchers tracked the mental states of 45 adolescent athletes at different stages of a 10-week lockdown and discovered that negative mental states were stronger in the later stages of the lockdown than in the earlier stages and that players in group sports were more severely affected [18].

It is essential to notice that, governments are actively adapting in attempts to reestablish a relatively normal order of life and work. This is also true in competitive sports. During the widespread lockdown at the beginning of the outbreak, the majority of athletes maintained a strong desire and needed to train, but only a small number of athletes were able to sustain adequate training [6]. Athletes were denied access to sufficient training environments and protections due to factors such as a lack of specialized facilities or venues, distant coaching, and a lack of medical and rehabilitation conditions [19]. Following the initial experience with lockdown, the game’s needs spurred the development of other coping strategies. With significant events like the Tokyo Olympics and the Beijing Winter Olympics on the horizon, more and more sports administrators are focusing on how to balance epidemic prevention with competition and training goals. For example, in the crisis of the Omicron epidemic in early 2022, the organizing committee used closed-loop management to assure the safety of athletes participating in the Beijing Winter Olympics [20].

Aside from sports events, some people have applied closed-loop management to training. For example, researchers have reported a well-tested approach known as “quarantine” training camps (or “bubble” camps) that aims to provide a safe and professional training environment for athletes competing in the Tokyo Olympics [6,21]. A “bubble” camp can be defined as a quarantine-style camp whereby a group of people (e.g., athletes, support staff) is strategically isolated from wider society to resume regular activities for a specified period of time [22]. It is important to note that although researchers use different terms such as “quarantine camp”, “bubble approach”, and “closed-loop management”, the concepts are essentially the same.

The closed-loop management training meets the requirement of epidemic prevention, protects athletes’ health, and produces an appropriate environment for specific training; hence it is recommended as an effective training approach in epidemic prevention [6]. However, it needs to be realized that it is still a type of lockdown, and athletes’ sleep and emotions may be affected as well. However, most existing research on the sleep and mood states of athletes under lockdown has concentrated on isolation at home rather than in a training environment, and research on the sleep and mood changes of athletes under closed-loop management arrangements is extremely limited. Only one practice, which was the first one to employ “quarantine” camps, has conducted a comparison. This study revealed that athletes’ emotional well-being improved over a one-month training camp period, with no difference from the state before the home isolated period; sleep duration was reduced relative to the home isolated period, as were sleep problem behaviors, but this difference did not differ [21].

According to the findings of this study, closed-loop management has a positive effect on athletes’ moods but a smaller effect on sleep issues. However, by the time the study was started, the athletes had already been exposed to a nationwide lockdown outside of the camp, which may have interfered with the impact of the camp itself. And, because of training camp in this study was used as part of a program in which everyone participated for no more than 30 days, the results have little or no way to reveal the characteristics of the effects of this method on mood and sleep over a longer period of time. However, longer closed-loop management is probable, particularly if more infectious variants emerge or before significant events. Finally, in terms of methodology, while the study asked athletes to describe their sleep and mood status before lockdown, during a lockdown, and during camp, these responses were collected simultaneously at the end of training camp. This strategy may have resulted in bias in the reporting.

Closed-loop management has emerged as a promising approach to strike a balance between epidemic prevention/control and training effectiveness. This study seeks to expand on previous research regarding the effects of one month of closed-loop management on sleep and mood among athletes. Specifically, the study aims to compare the impact of closed-loop management over a longer duration (approximately 2 months) both longitudinally (in comparison to the effects observed after approximately 1 month) and horizontally (in comparison to management in the community / home isolation) to comprehensively evaluate the efficacy of this management style. To achieve these objectives, the study undertook an analysis of the sleep and mood of professional athletes under closed-loop management at different time points (after approximately 1 month and after 2 months) during the Omicron Wave in Shanghai, China, 2022. Additionally, the study conducted a cross-sectional comparison between high school-aged athletes under closed-loop management and high school students of the same age who were in home isolation for approximately 2 months. High school students were chosen due to their requirement to follow a daily schedule of online classes, including physical education, while in isolation, thereby offering a comparable routine to that of the athletes. The study’s findings have practical implications for promoting targeted sleep and mood precautions during future outbreaks or other public health emergencies.

Materials and methods

Results

1-month vs. 2-month closed-loop management

Results of sleep showed no difference in PSQI score, t(109) = -0.16, p = 0.873. Subjectively rated sleep quality did not differ, t(109) = -1.16, p = .250. Sleep time did not differ, t(109) = -1.11, p = 0.269. The result of wake time revealed a difference, t(109) = 3.19, p = 0.002, Cohen’s d = 0.205. wake-up time was earlier at 2-month than at 1-month (see Table 1). There was no difference in sleep latency, t(109) = -0.92, p = 0.357. There was a significant difference in sleep hours, t(109) = 2.29, p = 0.024, Cohen’s d = 0.217. Hours of sleep was shorter at 2-month than at 1-month. Sleep efficiency was not different, t(109) = -0.76, p = 0.452. Sleep disorder did not show a difference, t(109) = -1.36, p = 0.178. There was a difference in daytime dysfunction, t(109) = 2.32, p = 0.022, Cohen’s d = 0.212. Daytime dysfunction at 2-month was less severe than at 1-month.

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Table 1. Descriptive results of sleep quality of athletes in closed-loop management (M ± SD).

https://doi.org/10.1371/journal.pone.0284858.t001

Results of mood revealed no difference in tension, t(109) = -0.94, p = 0.348. There was a difference in anger, t(109) = -2.49, p = 0.014, and Cohen’s d = -0.231. Anger was more sever at 2-month than at 1-month (see Table 2). There was no difference in fatigue, t(109) = 0.55, p = 0.583. Depression was similarly unaffected, t(109) = -1.77, p = 0.080. In terms of vigor, there was no change, t(109) = 0.52, p = 0.601. The difference in confusion was not significant, t(109) = -1.08, p = 0.282. The difference in esteem was similarly not significant, t(109) < 0.001, p > 0.999.

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Table 2. Descriptive results of mood of athletes in closed-loop management (M ± SD).

https://doi.org/10.1371/journal.pone.0284858.t002

Closed-loop management vs. management in the community

Results of sleep revealed a difference in PSQI scores, t(227) = 4.35, p < 0.001, Cohen’s d = 0.626. Athletes had worse sleep quality problems than students (see Table 3). Subjectively rated sleep quality differed, t(227) = 4.41, p < 0.001, Cohen’s d = 0.634. Athletes rated their sleep quality problems worse than students. Differences was also found in sleep time, t(227) = -6.16, p < 0.001, Cohen’s d = -0.887. Athletes slept earlier than students. Wake time was not different, t(227) = -1.85, p = 0.065. Differences existed in sleep latency, t(227) = 3.52, p < 0.001, Cohen’s d = 0.507. Athletes had a longer latency than students. There was no difference in hours of sleep, t(227) = 1.59, p = 0.114. A difference existed in sleep efficiency, t(227) = -2.79, p = 0.006, Cohen’s d = -0.402. Athletes slept less efficiently than students. Differences existed in sleep disturbance, t(227) = 7.24, p < 0.001, Cohen’s d = 1.043. Athletes had more serious sleep disorder than students. Daytime dysfunction was not different, t(227) = 1.23, p = 0.220.

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Table 3. Descriptive results of sleep quality of athletes and students (M ± SD).

https://doi.org/10.1371/journal.pone.0284858.t003

The results for mood showed differences in perceived distress, t(227) = -2.91, p = 0.004, Cohen’s d = -0.419. Athletes perceived lower distress than students (see Table 4). There was a difference in belief about coping capacity, t(227) = -2.24, p = 0.026, Cohen’s d = -0.322. Coping capacity were lower in athletes than in students. There was no difference in positive mood experience, t(227) = -1.62, p = 0.107.

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Table 4. Descriptive results of mood of athletes and students (M ± SD).

https://doi.org/10.1371/journal.pone.0284858.t004

Discussion

The results revealed no significant change in sleep quality as the length of closed-loop management increased, but a significant reduction in sleep duration and a reduction in daytime dysfunction. In terms of mood, only anger occurred significantly elevated. When compared to the students studying at home, the athletes’ sleep quality appeared significantly worse. Athletes, in particular, experienced significant deficiencies in subjective sleep quality, sleep latency, sleep efficiency, and sleep disorder. These features, however, did not change across closed-loop management, suggesting that they are stable negative characteristics of athletes. In terms of mood, athletes reported lower stress levels but also lower confidence in dealing with stress.

Several large-sample surveys of athletes have revealed that lockdown has negative effects such as decreased sleep efficiency, increased sleep duration, delayed sleep, and difficulty falling asleep [7,8,32]. In contrast to these findings, athletes reported shorter sleep duration but lower sleep problem behaviors in an attempt to "quarantine" camp training [21]. The current study found that, similar to the changes observed in this practice, sleep duration decreased significantly as time passed under closed-loop management. In addition, contrary to previous research that found lockdown to cause athletes to sleep late and wake up late [32], we discovered that this trend may be associated with an earlier waking time rather than a later falling asleep time. This finding adds to previous research by examining changes in longer duration and more detailed sleep indicators [21]. Furthermore, while athletes’ sleep duration was reduced and the mean values obtained are close to the suggested lower bound of sleep duration for athletes [33], daytime dysfunction decreased with prolonged closed-loop management. This finding could imply that athletes recovered more quickly from fatigue by sleeping for shorter periods of time. Overall, sleep quality has remained stable, but some positive changes may have occurred.

The logistical support and regulations of closed-loop management may be the primary contributors to the phenomenon observed in this study. Previous research has shown that in a closed-loop management setting, sleep behavior problems can be reduced [21]. Athletes in closed-loop management have almost no opportunity to go out (for vacation or competition) and thus can receive scientifically proven training, dietary, and rehabilitation programs more systematically, and the effects of these scientific training tools may gradually manifest themselves over time, even in their sleep, with closed-loop management. More importantly, closed-loop management could have aided in the improvement of sleep hygiene. This is especially important for non-clinical sleep problems [34]. This closed-loop management eliminated some sleep-harming habits, such as nighttime entertainment and dining out, as well as nighttime dorm parties. Furthermore, sports team administrators were present throughout the closed-loop management period, allowing for effective practice and flexible adjustment of sleep hygiene regulations.

Although studies on "quarantine" training revealed that athletes had better sleep quality when compared to the home isolation phase [21,22], no studies have compared the differences between closed-loop management in athletes and lockdown management in the general population in the same period. For the first time, this was investigated using athletes and high school students of the same age group. The comparison results revealed that, while athletes’ sleep quality did not change significantly during closed-loop management, they had more significant sleep quality issues throughout the procedure than students. It is important to note that sleep quality problems were relatively common among athletes even before the epidemic [35–37]. Given that the primary purpose of closed-loop management is to allow athletes to return to regular training [21], these problems with sleep quality may show exactly the characteristics of the athlete’s sleep in general.

The results of the current study were different from those of previous research in terms of mood. A study that tracked adolescent athletes for 10 weeks during a lockdown observed a decrease in depression and confusion [18]. The current study, however, discovered that only anger seems to have significantly increased during closed-loop management. During the first lockdown following the pandemic outbreak, one study found that Polish athletes had higher levels of anger than Spanish athletes, raising the possibility that cultural differences and the degree of agreement with the management approach may be the cause of this discrepancy [38]. Another study has also found that negative emotions, such as anger, were reduced after the lockdown was lifted and enhanced after re-entry into semi-closure from the perspective of a prolonged lockdown [39]. More referentially, Shenzhen, China, experienced a week-long lockdown at the end of March. A study on this lockdown found a negative correlation between residents’ anger and confidence in anti-epidemic efforts [40]. The closed-loop management in the current study was extended over time, and no one knew how long it would last. Such uncertainty may exacerbate anger by influencing psychosocial factors such as confidence and trust [40].

When compared to the lockdown that the general public received, closed-loop management also has unique properties in terms of its impact on mood. Studies have found that closed management will lead to increased negative emotions such as stress [14]. It has also been discovered that athletes are more anxious than non-athletes during lockdown [41]. However, athletes in the current study had lower levels of perceived stress than their peers of the same age. This finding is consistent with previous research comparing the stress levels of athletes participating in "bubble" training camps before lockdown, during the lockdown, and during the camp, which found that the majority of athletes, including Malaysian-Chinese athletes, perceived lower levels of stress during the camp [21,22]. This study once again demonstrated the significance of closed-loop management. The athletes’ ability to maintain relatively normal training and life in closed-loop management may be the primary cause of this effect.

Based on the findings of this study, the following aspects need to be taken into consideration when adopting closed-loop management in the future so that athletes’ sleep and emotional state during closed-loop management can be guaranteed. In terms of sleep, it is first important to note that the sleep quality problems that were already present in the athlete population remain salient in closed-loop management. This asks for the integration of sleep quality monitoring and intervention in the sports team’s support services during closed-loop management. In the process of closed-loop management, athletes may lose sleep due to early wakeups if the period of closure is prolonged. This problem can be addressed by adding naps after the closure to make up for lost sleep time [42], or by delivering sleep hygiene instruction at the start of the lockdown. In terms of mood, it is necessary to pay attention to the timely explanation and persuasion of management rules and policies in the process of closed-loop management as a way to reduce the possibility of athletes developing negative emotions over time. Additional education and training of athletes’ stress coping abilities are also required to improve their self-efficacy in dealing with stress induced by the epidemic [19]. It should not be forgotten, however, that the above recommendations are based on the findings of the study on longer-term closed-loop management. Based on the previous studies’ recommendations, shorter closed-loop management cycles should be considered first, as conditions permitted [22].

This study has several limitations that should be considered. First, the lack of baseline data limits the interpretation of the results. In this study, closed-loop management was extended over time (more than 3 months) to meet the requirement of citywide epidemic prevention, resulting in a late study design and implementation. As a result, the optimal time to test baseline levels was missed. Despite this limitation, the study focused on comparing the effects of the duration of closed-loop management and the differences between closed-loop management and management in the community. While some new findings emerged, the lack of baseline data remains a limitation. Second, the study only analyzed the impact of approximately 2 months of closed-loop management and did not analyze the impact of a longer period of closed-loop management. It is important to acknowledge that this study was conducted in parallel with the whole city epidemic control process and not actively recruited and operated by the researcher, which limited the duration of the study. Nevertheless, the study’s results may to some extent represent the impact of longer closed-loop management and can inform decision-makers for future epidemic control. Third, data from high school students were used to compare the management of closure with closures in the community. Although the students included in the study were similar to athletes in terms of lifestyle, and the school’s physical education include a portion of specialized sports training, their differences in certain physical or psychological aspects of their characteristics from professional athletes might mask some of the differences caused by the management approach. This was a compromise in the management of epidemic control due to the reluctance to obtain a sample under epidemic control, and should be taken into account when interpreting the results. Finally, the content and methods of measurement did not include athletes’ sleep behavior and objective sleep indicators. This was mainly due to the fact that the athlete sleep behavior questionnaire was not revised in Chinese beforehand and could not be applied in the current study. Additionally, the lack of objective measurement equipment available on the training base during closed-loop management, such as actigraphy, and the consideration of hygiene issues in cross-use of the limited number of devices, did not allow for the use of commonly used objective measures. To sum up, the characteristics of sleep and mood states of athletes who received closed-loop management during the Shanghai 2022 Omicron pandemic were examined in this study. In terms of sleep, the prolonged duration of the closure resulted in athletes waking up earlier, resulting in less sleep time. During the same time period, athletes’ sleep quality was worse than that of the general population in the community. In terms of emotions, the prolonged closure time enhanced athletes’ anger, whereas athletes felt less stressed than the general population in the community. Closed-loop management had an impact on athletes’ sleep and mood in both positive and negative ways. The findings of this study hold significant implications for the development of preplanning strategies aimed at implementing closed-loop management for athletes engaged in competitive sports, thereby augmenting the protective effects of such measures on athletes. Beyond its relevance for competitive sports training, this study may also have practical implications for the design of preplanning strategies for other critical industries and municipalities operating under emergency conditions, thereby enhancing its societal impact.

Supporting information