Unraveling the Pathway: How Physical Activity Enhances Sleep Quality Through Reduced Mobile Addiction and Maladaptive Thought Patterns in University Students

Unraveling the Pathway: How Physical Activity Enhances Sleep Quality Through Reduced Mobile Addiction and Maladaptive Thought Patterns in University Students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Unraveling the Pathway: How Physical Activity Enhances Sleep Quality Through Reduced Mobile Addiction and Maladaptive Thought Patterns in University Students Junjie Wang, Yuan-guo Liu, Guang-bo Dou, Qi-fei Xia, Yaocheng Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6824913/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim Physical exercise improves sleep quality, whereas its underlying mechanisms remain underexplored. This study examines how mobile phone addiction and rumination mediate the relationship between physical exercise and college students' sleep quality, offering a theoretical basis for preventing and addressing sleep problems. Methods A cross-sectional survey was conducted among 1,300 college students from seven universities using the Physical Activity Rating Scale, the Pittsburgh Sleep Quality Index, the Mobile Phone Addiction Tendency Scale, and the Rumination Scale. Results (1) Physical exercise significantly negatively predicted college students' mobile phone addiction, rumination, and sleep quality (β = -0.039, P < 0.01; β = -0.011, P < 0.01; β = -0.022, P < 0.01). (2) Mobile phone addiction significantly positively predicted college students' rumination and sleep quality (β = 0.388, P < 0.01; β = 0.244, P < 0.01). (3) Rumination significantly positively predicted college students' sleep quality (β = 0.272, P < 0.01). (4)The mediating pathway whereby physical exercise influences sleep quality through mobile phone addiction and rumination was statistically significant. Conclusion (1) Actively participating in physical exercise can effectively improve college students' mobile phone addiction, rumination, and sleep quality (2) Reducing mobile phone addiction and rumination among college students can significantly enhance their sleep quality (3)The effect of college students' participation in physical exercise on sleep quality is mediated in a chain by mobile phone addiction and rumination. Biological sciences/Psychology Health sciences/Health care College Students Physical Exercise Sleep Quality Mobile Phone Addiction Rumina-tion Figures Figure 1 Figure 2 Figure 3 Figure 4 0. Introduction College students, regarded as the backbone of national development, have long been a focus for society concerning their physical and mental well-being. The decline in their overall health is an undeniable reality (Lv et al., 2023 ). Given their crucial role, the state of college students' physical and mental health continues to attract widespread attention across various sectors (Ghrouz et al., 2019a ). Social progress and rising academic pressure have contributed to declining sleep quality among college students (Zhu et al., 2023 ). According to the "2024 China Resident Sleep Health White Paper" by the Chinese Sleep Association, the average sleep duration among Chinese residents is 6.75 hours, with 28% sleeping less than 6 hours. For individuals born after 2000, the average bedtime is around 12:30 AM; among college students, 51% go to sleep after midnight and 19% after 2:00 AM, with a sleep disorder detection rate of 23.8% (Liu et al., 2025 ). Good sleep is essential for academic performance, daily functioning, and overall well-being, whereas poor sleep can trigger anxiety, depression, cognitive dysfunction, and an increased risk of illness (Yu et al., 2013 ). Therefore, identifying the factors that influence sleep quality, especially those that can enhance it, is of significant theoretical and practical importance. Among the various factors that contribute to improving individual sleep quality, the positive role of physical exercise has been widely recognized. Numerous studies have shown that moderate, scientifically planned physical activity can regulate the biological clock, alleviate life stress, and adjust emotional states, thereby enhancing sleep quality (Kline, 2014 ). However, the internal mechanisms by which physical exercise affects sleep quality have not been thoroughly explained. Research indicates that negative psychological factors, such as mobile phone addiction and rumination, may also influence the sleep quality of college students (Thomée et al., 2011 ). Additionally, studies have found that mobile phone addiction can lead individuals to overuse their phones before bedtime, resulting in dependence that interferes with sleep (Kim et al., 2015 ; Q.-Q. Liu et al., 2017 ). As a negative psychological state, rumination occurs when individuals face setbacks and stress, leading the brain to continuously process negative events and emotions, which in turn affects sleep quality (Clark & Rhyno, 2005 ; Espie, 2007 ). Nonetheless, systematic research on the relationships among these factors and their mechanisms of impact on sleep quality remains lacking in the academic community. The factors influencing college students’ sleep quality encompass both protective and risk factors. However, examining these factors from a single dimension reveals many unexplained phenomena in real-world situations, suggesting that previous research may require revision and reflection. Based on this, the present study aims to explore the impact of physical exercise on college students’ sleep quality and to examine the chain mediating role of mobile phone addiction and ruminative thinking. By gaining an in-depth understanding of the relationships among these factors, the study seeks to provide a deeper theoretical understanding and practical guidance for the prevention and intervention of sleep problems among college students. 1. Literature Review and Hypotheses 1.1 The Relationship Between Physical Exercise and Sleep Quality Physical exercise refers to a type of physical activity that individuals engage in regularly, in a scientific and reasonable manner, based on their physical, mental, and psychological needs, with a certain frequency, duration, and intensity. Over the years, scholars have widely recognized physical exercise as one of the effective interventions for developing positive psychological traits and promoting harmonious physical and mental development among college students (Zhang & Min, 2022 ). Participation in physical exercise enhances college students' physical fitness by reducing obesity and disease incidence and boosting overall health (Penedo & Dahn, 2005 ). Regular exercise also improves resilience to setbacks and sleep quality, reduces aggressive behaviors and mobile phone addiction, and fosters greater awareness of exercise and mental well-being (Herbert et al., 2020 ). Sleep is crucial for recovery and regulating physical and mental functions, forming a foundation for effective performance. However, rapid socioeconomic development and widespread internet use have led to increased incidences of insomnia, social anxiety, delayed bedtimes, and heightened stress, all of which detrimentally affect sleep quality. A 2020 report found that nearly half of the population engages in mobile phone, television, or internet use before bed—with 52.5% of those born in the '90s and '00s—and that overall sleep quality is declining (Cahuas et al., 2020 ). Additionally, research by Chen Jiangyuan and Wu Ran (2021) revealed that college students sleep less than 7 hours per day on average, with a sleep deprivation rate of 34.7% and a growing prevalence of severe sleep deprivation and poor sleep habits (Chen & Wu, 2021 ). Therefore, researching the sleep quality of college students is of great significance. This paper draws on empirical research on physical exercise primarily focusing on college student populations, both domestically and internationally, to examine the relationship between physical exercise and college students' sleep quality. According to the neurotransmitter regulation theory, physical exercise can stimulate the brain to secrete various neurotransmitters such as serotonin and dopamine. These neurotransmitters, including serotonin, are closely related to mood and sleep regulation. They help individuals reduce stress, alleviate anxiety, enhance feelings of pleasure and satisfaction, regulate the sleep cycle, and increase deep sleep duration (Weicker & Strüder, 2001 ). Scientific and reasonable physical exercise is one of the effective methods to alleviate sleep disorders and improve sleep quality, even mitigating related symptoms (Wang & Boros, 2021 ). Ye J and Jia X (2022), using a stratified cluster sampling method on 1,006 college students, found that participating in physical exercise can mitigate persistent negative emotions, reduce the level of ruminative thinking, and, to some extent, enhance college students’ high-level ruminative thinking, thereby improving sleep problems (Ye et al., 2022 ). Santos M and Sirtoli R (2023) found that practicing FTPA 1–3 times per week significantly improves subjective sleep quality, sleep duration, and daytime dysfunction, while practicing FTPA 4–7 days per week is beneficial for the sleep disorder and daytime dysfunction dimensions of sleep quality (Santos et al., 2023 ). However, a study tracking over 300 college students found that engaging in physical exercise during spare time could lead to a reduction in sleep quality (Ghrouz et al., 2019b ). Dance-based, group, and racket sports have been shown to effectively improve college students' sleep quality by reducing the impacts of environmental and academic or employment pressures, helping them form a positive outlook on life, enhancing their psychological resilience, and reducing potential risks to sleep quality. Based on this, this study puts forward Hypothesis 1: Physical exercise can positively predict college students’ sleep quality. 1.2 The Mediating Role of Mobile Phone Addiction Mobile phone addiction refers to the phenomenon where smartphone users continuously engage with their devices, leading to a specific psychological state that gradually affects their cognition, emotions, sleep, and behavior. In severe cases, it may even impact their normal social interactions and adaptability (Saju, 2019 ). Self-determination theory posits that humans have three basic psychological needs: autonomy, relatedness, and competence (Ryan & Deci, 2000 ). In recent years, with the development of smartphone technology, various mobile apps have increasingly played a significant role in fulfilling these basic psychological needs. All three needs can be met to varying degrees through smartphone use. When college students are unable to satisfy their basic psychological needs in the real world, they may turn to smartphones for compensation, potentially leading to smartphone addiction. The theory of psychological need satisfaction holds that individuals generally have the basic needs for autonomy, competence, and belonging. When individuals achieve better performance in a given task and receive corresponding psychological satisfaction, they exhibit stronger intrinsic motivation. Moderate physical exercise enables individuals to experience a sense of bodily control during activities, attain a sense of achievement through completing various exercise tasks, and even feel a sense of belonging in team sports. When physical activities fulfill an individual’s psychological needs, reliance on smartphones for psychological satisfaction is reduced, thereby decreasing smartphone usage time (Gunnell et al., 2013 ). Yang G and Li Y, using a cross-sectional survey design and randomly selecting 650 undergraduates from 10 universities in the Guangzhou Higher Education Center in China, found that physical exercise might be an important intervention method for addressing college students’ smartphone addiction, with longer intervention durations potentially yielding better outcomes (Yang et al., 2021 ). Similarly, Guo K and Ma Q, employing a stratified cluster sampling method with 1,550 student questionnaires, discovered that physical exercise can negatively affect college students’ smartphone addiction. Moreover, physical exercise serves as a significant external environmental stimulus—it not only improves physical health but also has a notable impact on mental health and smartphone addiction (Guo et al., 2022 ). Research by Gong Yanbin and Yang Haibo indicated that physical exercise can reduce college students' smartphone addiction, improve their innovative behavior and mental health, and that both innovative behavior and mental health play positive roles in mitigating smartphone addiction (Gong & Yang, 2023 ). According to immersion theory (Nilsson et al., 2016 ), many mobile apps and games are designed based on the concept of immersion. Numerous mobile games offer clear levels, objectives, and reward feedback, with increasing difficulty as the player's skills improve. This continuous challenge can lead players to become immersed, eventually fostering mobile phone addiction. Individuals with mobile phone addiction become deeply absorbed in the pleasurable experiences provided by their phones, which suppresses self-control and distorts their perception of time, thereby encroaching on their rest and sleep. Research shows that mobile phone addiction adversely affects sleep quality—those with more severe addiction tend to experience poorer sleep. For example, Jiang Wenyuan and Chen Lilan surveyed 851 middle school students and found that increased phone usage not only elevates risks such as impaired social skills and depression but also contributes to declining sleep quality due to academic pressures (Jiang & Chen, 2023 ). Similarly, Li Xiaojing and Liu Chang studied over 2,000 primary and secondary school students and observed that while overall dependency on phones was relatively low, girls scored higher than boys, and higher-grade students scored higher than lower-grade ones. Their findings suggest that prolonged exposure to fragmented online information can impair memory and sleep quality, and in severe cases, negatively affect both physical and mental health (Li & Liu, 2023 ). Furthermore, research by Gou Shuangyu, Du Meijie, and colleagues found a positive correlation between mobile phone addiction and deteriorating sleep quality. They noted that mobile phone dependency is a form of technological addiction where individuals willingly sacrifice sleep for entertainment, despite the high costs in terms of fatigue (Xun et al., 2021 ). Fang Leqin, Xu Xiaoheng, and others also discovered that individuals with mobile phone addiction are at high risk for declining sleep quality because extended use before bedtime suppresses melatonin production and delays the onset of deep sleep, ultimately reducing daytime efficiency (Fang et al., 2019 ). Based on this, this study puts forward Hypothesis H2: Mobile phone addiction plays a mediating role in the effect of physical exercise on college students’ sleep quality. 1.3 The Mediating Role of Ruminative Thinking Ruminative thinking refers to a response pattern in which, after an individual experiences the impact of a negative event on their physical or mental state, they continuously and repeatedly process the causes and consequences of the event at a psychological level, resulting in a decline in physical and mental functioning (Nolen-Hoeksema et al., 2008 ). According to the neuroplasticity theory (Dawson, 2008 ), long-term, scientific physical exercise can improve the brain’s neural plasticity, thereby enhancing its structure and function. Research indicates that physical exercise promotes the connections between neurons, improving the brain’s information processing and regulatory abilities. For example, when facing negative events, the brain can regulate emotions and engage in cognitive restructuring more effectively, thus increasing its flexibility and adaptability and reducing susceptibility to ruminative thinking. Yu et al. found through a survey of college students that they are more prone to ruminative thinking, which negatively affects their development. Physical exercise has a positive effect on reducing ruminative thinking (Yu et al., 2020 ). Participants who engaged in ruminative thinking after exposure to stressors exhibited stronger and more persistent negative emotions than those who ruminated less. However, when participants completed aerobic exercise before exposure to stressors, these lingering negative emotions were alleviated, suggesting that exercise can mitigate the impact of subsequent stressors on subjective emotions. Puterman et al. demonstrated that a tendency toward ruminative thinking can increase and prolong physiological stress responses, including HPA axis activation, whereas individuals who consistently engage in physical exercise are less affected by the influence of ruminative thinking on HPA axis reactivity and acute stress recovery; in short, exercise can improve ruminative thinking (Puterman et al., 2011 ). Slavish and Graham-Engeland found that sedentary participants reported a higher degree of reflection on stressors, and a lack of physical exercise tends to lead to excessive ruminative thinking, which in turn affects sleep quality (Slavish & Graham-Engeland, 2015 ). Schmitter M’s research revealed that, under conditions of high rumination, exercise was associated with a greater negative memory bias (Schmitter et al., 2023 ). Individual differences in trait rumination moderated the relationship between exercise and memory bias; for instance, exercise increased negative memory bias in those with higher levels of rumination. Long-term exercise programs might be necessary to alter cognitive processes associated with depression. Liu Y’s study found that physical activity negatively predicted rumination (β = -0.322, t = -10.440, p < 0.01) (Liu et al., 2023 ). Overall, physical exercise negatively predicts ruminative thinking, anxiety, and depression among college students, indicating that physical exercise can alleviate ruminative thinking, anxiety, and depression. According to response style theory (Nolen-Hoeksema, 1991 ), ruminative thinking drives individuals to focus their attention on their own negative emotions and adverse behaviors, thereby reinforcing the negative impact of these factors. The sleep cognitive model posits that intrusive thoughts (such as ruminative thinking) can make it more difficult for individuals to fall asleep or maintain sleep (Espie, 2007 ). Liu Qingqi, Zhou Zongkui, and colleagues, in a survey of 1,258 high school students, found that ruminative thinking continuously triggers negative emotions, thereby affecting sleep quality, while mindfulness serves as a buffer against these negative emotions (Q. Q. Liu et al., 2017 ). Li Jiahui, Wang Juan, Chen Qingyi, and others conducted a cross-sectional survey of over 700 nurses in Jinan and found that nurses’ sleep quality was affected by work stress; high levels of work stress exacerbated nurses’ ruminative thinking, interfered with their internal awareness and behavioral responses, disrupted emotional regulation, and led to sleep delay, triggering various sleep problems (Li et al., 2020 ). Fu Litong, Men Ruixue, and colleagues, in a survey of over 1,900 elderly individuals above 60, discovered that those with high levels of ruminative thinking paid greater attention to negative events in life—whether in personal or social contexts—thereby intensifying negative emotions such as pessimism and anxiety. Their inability to change adverse circumstances resulted in an amplification of negative emotions, which troubled their sleep quality (Fu et al., 2022 ). Yan Xiaofan, Wang Xiaojie, and colleagues investigated insomnia among new soldiers and found that the severity of insomnia in new recruits was influenced by ruminative thinking; when faced with new stressors, individuals tended to repeatedly ruminate over negative events, reactivating prior negative emotional memories and resulting in poorer sleep quality (Yan et al., 2022 ). Gong Jinchao, Guo Siwen, and others, in a study involving over 5,000 students, found that individuals with higher levels of procrastination experienced ruminative thinking more frequently, continuously focusing on negative emotions and the impact of related events. This heightened cognitive arousal before bedtime created significant psychological and physiological stress, leading to a decline in sleep quality (Gong et al., 2024 ). Li Qiong, Liu Meng, and colleagues, in a study of sleep quality among 1,147 college students in Sichuan Province, found that negative ruminative thinking affected sleep quality by elevating individuals’ negative emotions. When individuals are influenced by negative emotions, their procrastination behaviors serve as a defense mechanism to maintain emotional balance; however, if negative emotions remain high, engaging in relaxing or entertaining activities may lower these emotions, resulting in delayed sleep onset and a decline in sleep quality (Li et al., 2024 ). Based on this, this study puts forward Hypothesis 3: Ruminative thinking plays a mediating role in the relationship between physical exercise and college students’ sleep quality. 1.4 The Chain Mediating Role of Mobile Phone Addiction and Ruminative Thinking Emotional self-regulation theory posits that individuals have the ability to regulate their own emotions (Koole et al., 2011 ). Mobile phone addiction may interfere with this emotional regulation ability (Lepp et al., 2015 ). When individuals encounter negative events in real life that trigger negative emotions such as anxiety and depression, they should ideally regulate these emotions through mindfulness, communication, or physical exercise. However, once individuals develop mobile phone addiction, they tend to immerse themselves in the virtual world of their phones to distract their attention, which does not effectively resolve the negative emotional issues. Upon returning from the virtual world to reality, the negative emotions persist, and due to the lack of proper relief, individuals are more likely to fall into ruminative thinking. In addition, mobile phones can amplify negative emotions (Q. Q. Liu et al., 2017 ). For instance, short videos, games that showcase idealized lifestyles, or instances of online violence may exacerbate the negative emotions of those with mobile phone addiction, thereby reducing their ability to regulate emotions and leading to further amplification of negative feelings. Intense negative emotions are a key factor that triggers ruminative thinking. Therefore, mobile phone addiction, by impairing emotional regulation, increases the likelihood of developing ruminative thinking. Cao Guanghai, Liu Juan, and colleagues, in their study involving 1,099 college students from Shandong Province, found that reliance on online social networking can positively influence ruminative thinking. Prolonged mobile phone use may intensify individuals’ negative beliefs, with the brain continuously processing past real-life social interactions, which reinforces negative evaluations of one’s behavior and attitudes, ultimately leading to cognitive distortions and increased social anxiety (Cao et al., 2023 ). Lin Wenyi, He Hao, and Guan Qing studied the brain functional network mechanisms of ruminative thinking and found, firstly, that ruminative thinking is closely linked to neural activity within the brain’s networks, although the causal relationship between them remains unclear (Lin et al., 2022 ). Secondly, ruminative thinking can significantly alter an individual’s brain functional network, but the specific internal connection mechanisms have yet to be thoroughly explored. Finally, the impact of ruminative thinking tends to decrease with age, primarily because individuals employ distraction strategies; however, this requires further investigation. Based on this, this study puts forward Hypothesis 4: Mobile phone addiction and ruminative thinking play a chain mediating role in the relationship between physical exercise and college students’ sleep quality. From the literature review, previous research on the pairwise relationships among physical exercise, sleep quality, mobile phone addiction, and ruminative thinking has yielded certain findings, yet several gaps remain: Research Outcomes: There is a substantial body of empirical literature on the relationship between physical exercise and sleep quality across different populations, but the results are inconsistent. Variations in measurement instruments, sample sizes, study populations, and statistical methods—as well as differing effect sizes of various exercise interventions—necessitate a comprehensive integration and analysis of these findings to clarify the strength of the relationship. Research Content: Prior studies have primarily focused on the relationships between two variables at a time. There is a paucity of research that simultaneously examines physical exercise, mobile phone addiction, ruminative thinking, and sleep quality, and little exploration into the specific mechanisms connecting these four variables—such as whether mediating effects exist and what their nature might be. Addressing these questions could provide new insights for diagnosing and intervening in sleep quality issues. Research Subjects: Most previous studies on the relationships among mobile phone addiction, ruminative thinking, and sleep quality have focused on adults and adolescents, with relatively few investigations involving college students. Given that ruminative thinking and mobile phone addiction are critical factors affecting the psychological health of college students, examining whether these factors mediate the relationship between physical exercise and sleep quality can offer new practical strategies for enhancing sleep quality among this group. Based on mobile phone addiction theory, ruminative thinking theory, and the analysis of related literature and variable relationships, this study proposes a hypothetical model (see Fig. 1 ). 2. Research Methods 2.2. Measurement Tools (1) Physical Activity Rating Scale (PASR-3) The Physical Activity Rating Scale (PASR-3) developed by Liang Deqing (Liang, 1994 ) was used to assess college students’ participation in physical exercise. This scale has an internal consistency coefficient of 0.82. It evaluates exercise volume based on three aspects: intensity, frequency, and duration of exercise. Each aspect is divided into 5 levels, scored from 1 to 5. In this study, the scale’s internal consistency (Cronbach’s alpha) was 0.72. The total exercise score ranges from 0 to 100 points, where scores of ≤ 19 indicate low exercise participation, scores between 20 and 42 indicate moderate participation, and scores of ≥ 43 indicate high participation. (2) Mobile Phone Addiction Scale (MPATS) The Mobile Phone Addiction Scale (MPATS) was developed by Xiong Jie, Zhou Zongkui, and others (Xiong et al., 2012 ). It consists of 16 items rated on a 5-point Likert scale from “strongly disagree” to “strongly agree.” The scale includes four dimensions: withdrawal symptoms, salience, social comfort, and mood change. Items are scored from 1 to 5, yielding a total score range from 16 to 80. Higher scores indicate a greater tendency toward mobile phone addiction, while lower scores indicate a lesser tendency. Typically, a score below 47 reflects normal mobile phone use, whereas a score of 48 or above suggests mobile phone addiction, with higher scores signifying more severe addiction. Exploratory and confirmatory factor analyses have demonstrated good reliability and validity, with an internal consistency coefficient of 0.83 and test-retest reliability of 0.91. In this study, the internal consistency coefficient was 0.93, indicating excellent reliability. (3) Ruminative Thinking Scale (GSES) The Ruminative Thinking Scale, translated and revised by Han Xiuhua and Yang Hongfei (2009) from the original scale developed by Nolen-Hoeksema, is tailored to the Chinese college student population. It consists of 22 items covering 3 dimensions: symptom rumination, compulsive thinking, and reflective pondering. The scale employs a 4-point Likert format (ranging from “never” to “always”), with higher scores indicating more severe ruminative thinking. The overall internal consistency coefficient of the scale is 0.90, with subscale coefficients ranging from 0.68 to 0.85. In this study, the overall internal consistency coefficient was 0.945, with reliability coefficients for the dimensions ranging from 0.797 to 0.889. (4) Pittsburgh Sleep Quality Index (PSQI) The Chinese version of the Pittsburgh Sleep Quality Index (PSQI) was compiled by Liu Xiancai and colleagues (Liu et al., 1996 ). The original version was developed by Dr. Buysse and his team at the University of Pittsburgh to assess sleep quality over the past month. This version has an internal consistency reliability ranging from 0.80 to 0.84, split-half reliability between 0.78 and 0.87, and test-retest reliability from 0.72 to 0.81. The PSQI consists of 24 items (19 self-rated and 5 rated by others). Eighteen self-rated items contribute to seven dimensions: subjective sleep quality (1 item), sleep latency (2 items), sleep duration (1 item), sleep efficiency (3 items), sleep disturbances (9 items), use of sleeping medication (1 item), and daytime dysfunction (2 items). Each item is rated on a 0–3 scale, so the total score ranges from 0 to 21. Higher scores indicate poorer sleep quality, with a PSQI score > 7 used to indicate “sleep quality problems.” In this study, the internal consistency coefficient was 0.822, demonstrating good reliability. 2.3. Statistical Methods This study utilized computer software including SPSS 23.0, AMOS 24.0, and Excel to input the demographic and scale data collected from college students. The questionnaires were screened, invalid responses removed, and the data organized while further testing the reliability and validity of the scales. Descriptive statistics, correlation and regression analyses, as well as structural equation modeling were employed to process the organized data and to test the proposed hypotheses. Finally, a structural equation model was established to examine the relationship between physical exercise and college students’ sleep quality. 3. Results 3.1. Common Method Bias This study employed a cross-sectional design to explore college students’ physical exercise and the related variables. Therefore, a common method bias test was conducted prior to analysis. An exploratory factor analysis was performed on all items from the Mobile Phone Addiction Scale, Ruminative Thinking Scale, Physical Activity Rating Scale, and Pittsburgh Sleep Quality Index. The analysis revealed that seven factors had eigenvalues greater than 1, and the first factor explained 20.713% of the variance, which is below the critical threshold of 40%. This indicates that common method bias is not a concern. 3.2 Correlation Analysis of Physical Exercise and Other Variables Table 1. Descriptive Statistics and Correlations Among Physical Exercise and Other Variables M SD Physical Exercise Mobile Phone Addiction Ruminative Thinking Sleep Quality Physical Exercise 21.839 21.063 1 Mobile Phone Addiction 9.640 3.48 -0.234** 1 Ruminative Thinking 6.691 2.401 -0.230** 0.586** 1 Sleep Quality 5.00 3.902 -0.209** 0.344** 0.322** 1 *Note: *p < 0.05, *p < 0.01 In this study, college students scored an average of 21.839±21.063 on physical exercise, 5.007±3.902 on sleep quality, 9.640±3.489 on mobile phone addiction, and 6.691±2.401 on ruminative thinking. To explore the relationships among these variables, Pearson correlation analysis was conducted on physical exercise, sleep quality, ruminative thinking, and mobile phone addiction. The analysis revealed that physical exercise was significantly negatively correlated with mobile phone addiction (r = -0.234, p < 0.01), ruminative thinking (r = -0.230, p < 0.01), and sleep quality (r = -0.209, p < 0.01). In contrast, mobile phone addiction showed significant positive correlations with both ruminative thinking (r = 0.586, p < 0.01) and sleep quality (r = 0.344, p < 0.01). Moreover, ruminative thinking was also significantly positively associated with sleep quality (r = 0.322, p < 0.01). （ See Tab 1 ） 3.3 Regression Analysis of Physical Exercise and Other Variables Table 2. Regression Analysis Results for Physical Exercise and Other Variables Regression Equation Overall Fit Index Significance of Regression Coefficients Dependent Variable Predictor(s) R R2 F β T Mobile Phone Addiction Physical Exercise 0.234 0.055 75.353** -0.039 -8.681** Ruminative Thinking Physical Exercise 0.594 0.353 353.580*** -0.011 -4.284** Mobile Phone Addiction 0.388 24.512** Sleep Quality Physical Exercise 0.392 0.154 78.474*** -0.022 -4.498** Mobile Phone Addiction 0.244 6.860** Ruminative Thinking 0.272 5.260*** Note: * p < 0.05, ** p < 0.01, *** p < 0.001 Based on the hierarchical regression results in Table 2, physical exercise significantly influences mobile phone addiction (β = -0.039, t = -8.681, p < 0.01). In addition, both physical exercise (β = -0.011, t = -4.284, p < 0.01) and mobile phone addiction (β = 0.388, t = 24.512, p < 0.01) have significant effects on ruminative thinking. Furthermore, physical exercise, mobile phone addiction, and ruminative thinking all significantly predict sleep quality (β = -0.022, t = -4.498, p < 0.01; β = 0.244, t = 6.860, p < 0.01; β = 0.272, t = 5.260, p < 0.01). （ See Tab 2 ） 3.4 The Chain Mediating Effect between Physical Exercise and Sleep Quality 3.4.1 The Mediating Effect of Mobile Phone Addiction between Physical Exercise and Sleep Quality To further verify the effect of physical exercise on college students' sleep quality and to test the mediating role of mobile phone addiction, this study employed Bootstrap analysis with a sample size of 5000 and Model 6, setting a 95% confidence interval. The model examining the influence of physical exercise on sleep quality through mobile phone addiction was tested, and the mediating effect size of mobile phone addiction is presented in Table 3. （ See Tab 3 ） Table 3. Bootstrap Analysis for Testing the Significance of the Mediation Effect Path Relationship Standardized Path Coefficient Standard Error C.R. Significance (P) Mobile Phone Addiction <--- Physical Exercise -0.237 0.001 -8.346 *** Sleep Quality <--- Physical Exercise -0.157 0.001 -5.474 *** Sleep Quality <--- Mobile Phone Addiction 0.385 0.022 11.72 *** Note: * p < 0.05, ** p < 0.01, *** p < 0.001 Table 4: Analysis of the Total Effect of Mobile Phone Addiction Mediating Path Effect Size SE BootstrapCI(95%) P Lower Limit Upper Limit Physical Exercise-Mobile Phone Addiction-Sleep Quality -0.091 0.014 -0.12 -0.063 0.001 According to Table 4, when mobile phone addiction is used as the mediating variable between physical exercise and sleep quality, the Bootstrap 95% confidence interval has an upper limit of -0.063 and a lower limit of -0.12. Since this interval does not include 0, it indicates that the mediating effect of mobile phone addiction on the influence of physical exercise on college students' sleep quality is significant, following the pathway "physical exercise → mobile phone addiction → sleep quality." （ See Tab 4 ） Table 5: Fitting Indices for the Mediation Effect of Mobile Phone Addiction on Physical Exercise and Sleep Quality Fit Test Index Ideal Standard General Standard Model results Conclusion X 2 /df（Chi-Square/Degrees of Freedom Ratio) ） 1-3 ＜5 2.81 Ideal RMSEA（Root Mean Square Error of Approximation） ＜0.06 ＜0.08 0.054 Ideal NFI（Normed Fit Index） ＞0.90 ＞0.80 0.988 Ideal RFI（Relative Fit Index） ＞0.90 ＞0.80 0.97 Ideal IFI（Incremental Fit Index） ＞0.90 ＞0.80 0.981 Ideal TLI（Tucker-Lewis Index） ＞0.90 ＞0.80 0.95 Ideal CFI（Comparative Fit Index） ＞0.90 ＞0.80 0.981 Ideal According to Table 5, the fit indices for the mediating effect of mobile phone addiction indicate that X²/df = 2.81 (< 3), NFI = 0.988, RFI = 0.97, IFI = 0.981, TLI = 0.95, and CFI = 0.981; all these indices exceed 0.90. Additionally, RMSEA = 0.054 (< 0.08), which shows that there is no serious common method bias in the study of the mediating effect of mobile phone addiction on the relationship between physical exercise and sleep quality. The mediating model for mobile phone addiction fits well and is acceptable. （See Tab 5） Using a structural equation model, the model linking physical exercise, mobile phone addiction, and sleep quality is shown in Figure 2. In this model, physical exercise directly affects sleep quality, mobile phone addiction directly affects sleep quality, and physical exercise indirectly influences college students’ sleep quality through the mediating effect of mobile phone addiction. 3.4.2 The Mediating Effect of Ruminative Thinking between Physical Exercise and Sleep Quality To further validate the impact of physical exercise on college students' sleep quality and to examine the mediating role of ruminative thinking, this study employed Bootstrap analysis with a sample size of 5000, using Model 6 and a 95% confidence interval. The model testing the effect of physical exercise on sleep quality through ruminative thinking was evaluated, and the mediating effect size of ruminative thinking is shown in Table 6. Table 6: Bootstrap Analysis for Testing the Significance of the Mediation Effect Path Relationship Standardized Path Coefficient Standard Error C.R. Significance (P) Ruminative Thinking <--- Physical Exercise -0.215 0.001 -7.453 *** Sleep Quality <--- Physical Exercise -0.17 0.001 -5.903 *** Sleep Quality <--- Ruminative Thinking 0.362 0.027 10.996 *** Note: * p < 0.05, ** p < 0.01, *** p < 0.001 Table 7: Analysis of the Total Effect of Ruminative Thinking Mediating Path Effect Size SE Bootstrap CI(95%) P Lower Limit Upper Limit Physical Exercise-Ruminative Thinking-Sleep Quality -0.078 0.012 -0.103 -0.055 0.001 According to Table 7, when ruminative thinking is used as the mediating variable between physical exercise and sleep quality, the Bootstrap 95% confidence interval has an upper limit of -0.055 and a lower limit of -0.103. Since the interval does not include 0, the mediating effect of ruminative thinking is significant. The influence pathway is "physical exercise → ruminative thinking → sleep quality." Table 8: Fitting Indices for the Mediation Effect of Ruminative Thinking on Physical Exercise and Sleep Quality Fit Test Index Ideal Standard General Standard Model results Conclusion X 2 /df（Chi-Square/Degrees of Freedom Ratio) ） 1-3 ＜5 2.951 Ideal RMSEA（Root Mean Square Error of Approximation） ＜0.06 ＜0.08 0.055 Ideal NFI（Normed Fit Index） ＞0.90 ＞0.80 0.974 Ideal RFI（Relative Fit Index） ＞0.90 ＞0.80 0.975 Ideal IFI（Incremental Fit Index） ＞0.90 ＞0.80 0.982 Ideal TLI（Tucker-Lewis Index） ＞0.90 ＞0.80 0.926 Ideal CFI（Comparative Fit Index） ＞0.90 ＞0.80 0.982 Ideal According to Table 8, the fit indices for the mediating effect of ruminative thinking indicate that X²/df = 2.951 (< 3), NFI = 0.974, RFI = 0.975, IFI = 0.982, TLI = 0.926, and CFI = 0.982; all of these indices exceed 0.90. Additionally, RMSEA = 0.055 (< 0.08) shows that there is no serious common method bias in the study of the mediating effect of ruminative thinking on the relationship between physical exercise and sleep quality. The mediating model for ruminative thinking fits well and is acceptable. Using a structural equation model, the relationship among physical exercise, ruminative thinking, and sleep quality is depicted in Figure 3. In this model, physical exercise has a direct effect on sleep quality, ruminative thinking directly influences sleep quality, and physical exercise indirectly affects college students' sleep quality through the mediating effect of ruminative thinking. 3.4.3 Chain Mediation Model Test of Mobile Phone Addiction and Ruminative Thinking To further investigate the impact of physical exercise on sleep quality and test the chain mediating effects of mobile phone addiction and ruminative thinking, this study employed Bootstrap analysis with a sample size of 5000, using Model 6 and a 95% confidence interval. The model examining the influence of physical exercise on sleep quality through mobile phone addiction and ruminative thinking was tested. The indirect effect sizes for each path are presented in Table 9. Table 9: Standardized Path Coefficient Table Path Relationship Standardized Path Coefficient Standard Error C.R. Significance (P) Mobile Phone Addiction <--- Physical Exercise -0.237 0.001 -8.358 *** Ruminative Thinking <--- Physical Exercise -0.122 0.001 -4.383 *** Ruminative Thinking <--- Mobile Phone Addiction 0.394 0.025 13.112 *** Sleep quality <--- Physical Exercise -0.126 0.001 -4.502 *** Sleep quality <--- Mobile Phone Addiction 0.287 0.023 8.594 *** Sleep quality <--- Ruminative Thinking 0.252 0.028 7.591 *** Table 10: Analysis of the Total Effect of Mobile Phone Addiction on Ruminative Thinking Mediating Path Effect Size SE Bootstrap CI(95%) P Lower Limit Upper Limit Physical Exercise-Mobile Phone Addiction-Ruminative Thinking-Sleep quality -0.024 0.005 -0.034 -0.015 0.001 According to Table 10, the 95% Bootstrap confidence interval has an upper bound of -0.015 and a lower bound of -0.034. Since this interval does not include 0, it indicates that the chain mediating effect of mobile phone addiction and ruminative thinking in the relationship between physical exercise and sleep quality is significant. The pathway is "physical exercise → mobile phone addiction → ruminative thinking → sleep quality." Table 11: Fitting Indices for the Mediation Effect of Ruminative Thinking on Physical Exercise and Sleep Quality Fit Test Index Ideal Standard General Standard Model results Conclusion X 2 /df（Chi-Square/Degrees of Freedom Ratio) ） 1-3 ＜5 4.741 良好 RMSEA（Root Mean Square Error of Approximation） ＜0.06 ＜0.08 0.054 理想 NFI（Normed Fit Index） ＞0.90 ＞0.80 0.959 理想 RFI（Relative Fit Index） ＞0.90 ＞0.80 0.982 理想 IFI（Incremental Fit Index） ＞0.90 ＞0.80 0.975 理想 TLI（Tucker-Lewis Index） ＞0.90 ＞0.80 0.938 理想 CFI（Comparative Fit Index） ＞0.90 ＞0.80 0.989 理想 According to Table 11, the fit indices for the mediating effect model of ruminative thinking indicate that X²/df = 4.741 (< 5), NFI = 0.959, RFI = 0.982, IFI = 0.975, TLI = 0.938, and CFI = 0.989; all these indices exceed 0.90, and RMSEA = 0.054 (< 0.08). This demonstrates that the study of the mediating effects of ruminative thinking and mobile phone addiction on the influence of physical exercise on college students' sleep quality does not suffer from serious common method bias, and the mediating model fits well and is acceptable. Using a structural equation model, the model linking physical exercise, college students’ mobile phone addiction, ruminative thinking, and sleep quality is presented in Figure 4. In this model, physical exercise directly affects sleep quality, mobile phone addiction directly affects sleep quality, and self-efficacy directly affects sleep quality. Mobile phone addiction can indirectly influence sleep quality through the mediating effect of self-efficacy, and physical exercise can indirectly influence sleep quality through the chain mediating effect of mobile phone addiction and self-efficacy. 4. Discussion 4.1 Analysis of the Mediating Effect of Mobile Phone Addiction This study confirmed that physical exercise can predict college students' sleep quality through the mediating effect of mobile phone addiction, indicating that participation in physical exercise effectively improves both mobile phone addiction and sleep quality among college students. This finding not only broadens the understanding of the pathways through which physical activity influences sleep quality, but also highlights the emerging significance of mobile phone addiction as a critical mediating variable. Existing research on the mechanisms underlying sleep quality has predominantly focused on traditional psychological factors such as anxiety, depression, cognitive function, and stress, as well as intervention strategies like mindfulness training and social support. However, little attention has been paid to the increasingly prominent issue of mobile phone addiction among university students. Recent statistics reveal that as many as 52.5% of students born in the 1990s and 2000s use their phones before bedtime, indicating that mobile devices have become deeply embedded in their daily routines and may pose a potential risk to sleep quality. Grounded in this social reality, the present study is the first to incorporate mobile phone addiction into the pathway linking physical activity and sleep quality, thereby filling a significant gap in the current body of research. On one hand, physical exercise directly affects sleep quality; college students can alleviate anxiety, shift their attention, and expand their social networks through exercise, thereby enhancing their sleep quality. On the other hand, physical exercise also indirectly influences sleep quality via mobile phone addiction, which acts as a mediator in the relationship between physical exercise and sleep quality. Specifically, physical exercise is a negative predictor of sleep quality, whereas mobile phone addiction is a positive predictor of sleep quality. Furthermore, the findings of this study align with previous research by confirming the link between physical exercise and mobile phone addiction, as well as the close relationship between mobile phone addiction and sleep quality. Building on earlier conclusions, this study further demonstrates that mobile phone addiction mediates the relationship between physical exercise and sleep quality, thus enriching the existing literature. Bandura's reciprocal determinism theory posits that behavior is influenced by both personal and environmental factors (Bandura, 1978 ). From an environmental perspective, mobile short videos permeate every aspect of smartphone use. In addition to mainstream short video platforms, various social media channels such as Weibo and WeChat also push a range of short videos. Moreover, college students are highly dependent on mobile games, which can diminish their self-regulation abilities. Addictive behavior can impair brain regions responsible for self-regulation, reducing inhibitory control, while the uneven allocation of attention toward online games further hampers individuals' ability to regulate their behavior. Sharma M. P.'s insomnia model identifies poor behavioral habits as another key factor (Sharma & Andrade, 2012 ). Mobile phone dependency, as a maladaptive behavioral habit, is significantly and positively correlated with overall sleep quality scores; specifically, the more severe the mobile phone dependency, the poorer the sleep quality. From a physiological standpoint, engaging in moderate-intensity physical exercise can stimulate the brain to secrete endorphins, enhancing feelings of well-being and reducing the discomfort associated with being away from one's phone. This study reveals the positive impact of physical exercise on college students' sleep quality and emphasizes the partial mediating role of mobile phone addiction in this process. The findings offer valuable insights for developing interventions to address sleep issues among college students. They underscore the need for enhanced regulation and guidance of mobile phone usage while encouraging an increase in physical exercise frequency to improve sleep quality and overall health. 4.2 Analysis of the Mediating Effect of Ruminative Thinking This study confirmed that physical exercise can predict college students’ sleep quality through the mediating effect of ruminative thinking, demonstrating that engaging in physical exercise effectively improves both ruminative thinking and sleep quality. Physical exercise directly enhances sleep quality by enabling college students to shift their focus and build psychological resilience, thereby promoting better sleep. In addition, exercise indirectly influences sleep outcomes through its effect on ruminative thinking. Specifically, higher levels of physical exercise predict improved sleep quality, whereas increased ruminative thinking is associated with poorer sleep outcomes. Furthermore, our findings are consistent with some previous studies; they confirm the relationship between physical exercise and ruminative thinking and underscore the close connection between ruminative thinking and sleep quality. Building on earlier conclusions, this study further demonstrates that ruminative thinking mediates the relationship between physical exercise and sleep quality, thereby enriching the existing literature. Excessive ruminative thinking can diminish the beneficial impact of positive emotions on sleep quality. Although moderate positive emotions can enhance sleep, over-processed or exaggerated positive emotions may lead to heightened emotional arousal, ultimately impairing sleep quality (Butz & Stahlberg, 2018 ). Similarly, insomnia models indicate that both cognitive and emotional arousal can disturb the neurophysiological system and contribute to sleep problems. Physical exercise, however, can consciously boost individuals’ ability to regulate both cognition and emotions, thus improving the physiological conditions related to sleep and, in turn, enhancing sleep quality (Guastella & Moulds, 2007 ). Moreover, physical exercise acts as an effective means of emotion regulation, helping college students relieve accumulated stress, balance their emotions, and maintain a calm mindset. A relaxed and balanced mental state not only fosters better cognitive functioning but also reduces the risk of falling into ruminative thinking. In summary, this study highlights the positive impact of physical exercise on sleep quality among college students and emphasizes the partial mediating role of ruminative thinking. These findings provide valuable insights into the mechanisms by which physical exercise influences mental health, paving the way for more targeted interventions to improve sleep quality. 4.3 Chain Mediation Effect Analysis The results of the chain mediation analysis indicate that the impact of physical exercise on college students’ sleep quality is jointly achieved through mobile phone addiction and ruminative thinking. Physical exercise improves sleep quality by helping college students alleviate anxiety, shift their focus, and expand their social networks. It also boosts physical fitness and social skills, which reduces mobile phone addiction and buffers ruminative thinking. This chain mediating effect is significant: higher mobile phone addiction increases ruminative thinking, leading to continuous processing of negative events and emotions, ultimately resulting in poorer sleep quality—a finding consistent with previous research (Wang et al., 2021 ). By constructing a chain mediation model, this study explains how physical exercise affects college students’ sleep quality: not only does exercise have a direct impact on sleep quality, but it also exerts a positive influence via the chain mediation of mobile phone addiction and ruminative thinking. Therefore, Hypothesis H3 is supported. The research confirms that active participation in physical exercise is beneficial for enhancing sleep quality and establishes the relationships among physical exercise, mobile phone addiction, ruminative thinking, and sleep quality. Furthermore, it lays a theoretical foundation for further studies aimed at improving college students’ physical health and sleep quality. In summary, physical exercise has a significant negative effect on poor sleep quality, and improving sleep quality among college students can be achieved by reducing both mobile phone addiction and ruminative thinking. Although these findings are consistent with current theoretical models, further empirical research is needed to verify and expand on these results. 5. Recommendations 5.1 Enhance Physical Exercise Interventions to Mitigate Mobile Phone Addiction Universities should fully recognize the positive role of physical exercise in reducing mobile phone addiction and strengthen related intervention efforts. Schools need to offer well-designed physical education courses and organize a variety of sports activities and competitions. Developing personalized exercise plans tailored to the diverse lifestyles and academic schedules of college students is recommended. By specifying appropriate exercise times, frequencies, and intensities, regular physical activity can help relieve stress, regulate emotions, and ultimately enhance sleep quality. 5.2 Promote Engaging and Trendy Extracurricular Sports Activities Colleges should organize more interesting and innovative extracurricular sports events to encourage students to leave their dorms and enrich their leisure time. Participating in group activities not only reduces feelings of loneliness and improves social interactions but also helps control the occurrence of ruminative thinking. By verbalizing internal thoughts during discussions or confiding in peers, students might find the answers they seek. Additionally, listeners can share their concerns and suggest reasonable solutions based on real-life situations, which can prevent unnecessary ruminative thinking and help resolve issues in a positive manner. 5.3 Implement Effective Interventions to Improve Sleep Habits Improving sleep quality among college students requires addressing not only poor personal sleep habits but also external environmental factors, with the dormitory atmosphere being particularly important. To tackle issues like mobile phone addiction and ruminative thinking, students are encouraged to develop positive psychological adjustment strategies. These may include finding practical solutions to problems, engaging in open communication, and learning relaxation techniques. By reducing negative thoughts and emotions, the psychological stress experienced before sleep can be alleviated, ultimately enhancing sleep quality. Declarations Ethics approval and consent to participate The study followed strict procedures to ensure confidentiality, and approval was obtained from the Ankang University Review Committee. All participants signed informed consent forms before taking part in the study. Our research adheres to the Declaration of Helsinki. Consent for publication All authors agreed to submit the manuscript after reviewing it. Availability of data and material All data material can be further obtained from the corresponding author upon request. Competing interests The authors declare that the research was conducted without any commercial or financial relationships that could be perceived as a potential conflict of interest. Funding The work was funded by the Shaanxi Provincial Education Department Project for 2024 (Project Number 24JK0004), the Shaanxi Province "14th Five-Year Plan" Education Science Planning Project for 2024 (Project Number SGH24Q301), and the 2024 Shaanxi Provincial Sports Bureau Regular Project Initiation Project (Project Number 20240001). Author Contributions Author Contributions: Conceptualization, J.W. and Q.X.; methodology, J.W. and Y.L.; data curation, J.W.; formal analysis, G.D. and Y.L.; writing—original draft preparation, J.W. and G.D.; writing—review and editing, J.W.; supervision, J.W. All authors have read and agreed to the published version of the manuscript. Acknowledgements We thank all the participants in this research. Clinical trial number: not applicable Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). 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(2023). Depression and Anxiety Mediate the Association between Sleep Quality and Self-Rated Health in Healthcare Students. Behavioral sciences , 13 (2). [CrossRef] Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6824913","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":486690436,"identity":"cd3691e6-b831-4fcc-91cd-f1ef0b44bdc6","order_by":0,"name":"Junjie Wang","email":"","orcid":"","institution":"Ankang College","correspondingAuthor":false,"prefix":"","firstName":"Junjie","middleName":"","lastName":"Wang","suffix":""},{"id":486690437,"identity":"636a0c7d-5452-427f-a672-d17e305b7a99","order_by":1,"name":"Yuan-guo Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIie3PsQrCMBCA4QuBuBy4XqnSV4gInSp9FhHiIqiL4CYIWV0FfQjfIVgX0VXQQRf3DkoGB6tOLq1ugvmXLPdxOQCX6xej14OxKadHkF+QCqygLr8iEWwhpI/+FczGyemiI2RjUEPbOwRQMstFHmHzpF2vaoWcQ7JHea6NUKldHuHUCX1PGxSc6T1Iw0aEYS4R1L0+SbZG9K00cSFB6ggvzQhxIQClaRYSIhX6sFEoOXI/Iy1ddEswbZ09O4hiWV6z1N5MY1IySS55xPHtuqLxR8x+MuVyuVz/2x2FhUAorLWlFgAAAABJRU5ErkJggg==","orcid":"","institution":"Shenyang Sports University","correspondingAuthor":true,"prefix":"","firstName":"Yuan-guo","middleName":"","lastName":"Liu","suffix":""},{"id":486690439,"identity":"f853c5c0-5cf2-4f53-b665-d1093173c7b7","order_by":2,"name":"Guang-bo Dou","email":"","orcid":"","institution":"Shenyang Sports University","correspondingAuthor":false,"prefix":"","firstName":"Guang-bo","middleName":"","lastName":"Dou","suffix":""},{"id":486690440,"identity":"795018a5-8ade-4d1f-880e-fd9fafa18154","order_by":3,"name":"Qi-fei Xia","email":"","orcid":"","institution":"Shenyang Sports University","correspondingAuthor":false,"prefix":"","firstName":"Qi-fei","middleName":"","lastName":"Xia","suffix":""},{"id":486690441,"identity":"17562386-3249-45e6-8598-d578aeb90e21","order_by":4,"name":"Yaocheng Liu","email":"","orcid":"","institution":"Ankang College","correspondingAuthor":false,"prefix":"","firstName":"Yaocheng","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-06-05 03:53:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6824913/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6824913/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87045471,"identity":"d925c0f9-c74b-4d0a-bafa-d21ba262823f","added_by":"auto","created_at":"2025-07-18 14:31:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55036,"visible":true,"origin":"","legend":"\u003cp\u003eHypothetical Mediation Model\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6824913/v1/486e4d12626b751b8d211b8d.png"},{"id":87045470,"identity":"97cb3a07-717c-4a95-afc0-bae577a0f2d9","added_by":"auto","created_at":"2025-07-18 14:31:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179318,"visible":true,"origin":"","legend":"\u003cp\u003eMobile Phone Addiction Mediating Model\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6824913/v1/ca7352472901a7a1caf632a0.png"},{"id":87047111,"identity":"daa8ec3d-5982-4320-8095-61d9e26d1763","added_by":"auto","created_at":"2025-07-18 14:39:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":193106,"visible":true,"origin":"","legend":"\u003cp\u003eRuminative Thinking Mediating Model\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6824913/v1/1b71f6bf75757a032d3e4b4d.png"},{"id":87045476,"identity":"cb7da05d-8837-4467-bfac-7db5ed411ff1","added_by":"auto","created_at":"2025-07-18 14:31:01","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":207389,"visible":true,"origin":"","legend":"\u003cp\u003eChain Mediation Model\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6824913/v1/2240a01f132250b42cf9e001.png"},{"id":91900173,"identity":"611b87ea-3387-4faa-a558-45a52f3b815b","added_by":"auto","created_at":"2025-09-22 20:31:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1370747,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6824913/v1/9a8f7f58-310c-4161-8383-b0d973ead8d1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unraveling the Pathway: How Physical Activity Enhances Sleep Quality Through Reduced Mobile Addiction and Maladaptive Thought Patterns in University Students","fulltext":[{"header":"0. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eCollege students, regarded as the backbone of national development, have long been a focus for society concerning their physical and mental well-being. The decline in their overall health is an undeniable reality (Lv et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Given their crucial role, the state of college students' physical and mental health continues to attract widespread attention across various sectors (Ghrouz et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e). Social progress and rising academic pressure have contributed to declining sleep quality among college students (Zhu et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to the \"2024 China Resident Sleep Health White Paper\" by the Chinese Sleep Association, the average sleep duration among Chinese residents is 6.75 hours, with 28% sleeping less than 6 hours. For individuals born after 2000, the average bedtime is around 12:30 AM; among college students, 51% go to sleep after midnight and 19% after 2:00 AM, with a sleep disorder detection rate of 23.8% (Liu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Good sleep is essential for academic performance, daily functioning, and overall well-being, whereas poor sleep can trigger anxiety, depression, cognitive dysfunction, and an increased risk of illness (Yu et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Therefore, identifying the factors that influence sleep quality, especially those that can enhance it, is of significant theoretical and practical importance.\u003c/p\u003e\u003cp\u003eAmong the various factors that contribute to improving individual sleep quality, the positive role of physical exercise has been widely recognized. Numerous studies have shown that moderate, scientifically planned physical activity can regulate the biological clock, alleviate life stress, and adjust emotional states, thereby enhancing sleep quality (Kline, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, the internal mechanisms by which physical exercise affects sleep quality have not been thoroughly explained. Research indicates that negative psychological factors, such as mobile phone addiction and rumination, may also influence the sleep quality of college students (Thom\u0026eacute;e et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Additionally, studies have found that mobile phone addiction can lead individuals to overuse their phones before bedtime, resulting in dependence that interferes with sleep (Kim et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Q.-Q. Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As a negative psychological state, rumination occurs when individuals face setbacks and stress, leading the brain to continuously process negative events and emotions, which in turn affects sleep quality (Clark \u0026amp; Rhyno, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Espie, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Nonetheless, systematic research on the relationships among these factors and their mechanisms of impact on sleep quality remains lacking in the academic community.\u003c/p\u003e\u003cp\u003eThe factors influencing college students\u0026rsquo; sleep quality encompass both protective and risk factors. However, examining these factors from a single dimension reveals many unexplained phenomena in real-world situations, suggesting that previous research may require revision and reflection. Based on this, the present study aims to explore the impact of physical exercise on college students\u0026rsquo; sleep quality and to examine the chain mediating role of mobile phone addiction and ruminative thinking. By gaining an in-depth understanding of the relationships among these factors, the study seeks to provide a deeper theoretical understanding and practical guidance for the prevention and intervention of sleep problems among college students.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"1. Literature Review and Hypotheses","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e1.1 The Relationship Between Physical Exercise and Sleep Quality\u003c/p\u003e\u003cp\u003ePhysical exercise refers to a type of physical activity that individuals engage in regularly, in a scientific and reasonable manner, based on their physical, mental, and psychological needs, with a certain frequency, duration, and intensity. Over the years, scholars have widely recognized physical exercise as one of the effective interventions for developing positive psychological traits and promoting harmonious physical and mental development among college students (Zhang \u0026amp; Min, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Participation in physical exercise enhances college students' physical fitness by reducing obesity and disease incidence and boosting overall health (Penedo \u0026amp; Dahn, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Regular exercise also improves resilience to setbacks and sleep quality, reduces aggressive behaviors and mobile phone addiction, and fosters greater awareness of exercise and mental well-being (Herbert et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSleep is crucial for recovery and regulating physical and mental functions, forming a foundation for effective performance. However, rapid socioeconomic development and widespread internet use have led to increased incidences of insomnia, social anxiety, delayed bedtimes, and heightened stress, all of which detrimentally affect sleep quality. A 2020 report found that nearly half of the population engages in mobile phone, television, or internet use before bed\u0026mdash;with 52.5% of those born in the '90s and '00s\u0026mdash;and that overall sleep quality is declining (Cahuas et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Additionally, research by Chen Jiangyuan and Wu Ran (2021) revealed that college students sleep less than 7 hours per day on average, with a sleep deprivation rate of 34.7% and a growing prevalence of severe sleep deprivation and poor sleep habits (Chen \u0026amp; Wu, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, researching the sleep quality of college students is of great significance. This paper draws on empirical research on physical exercise primarily focusing on college student populations, both domestically and internationally, to examine the relationship between physical exercise and college students' sleep quality.\u003c/p\u003e\u003cp\u003eAccording to the neurotransmitter regulation theory, physical exercise can stimulate the brain to secrete various neurotransmitters such as serotonin and dopamine. These neurotransmitters, including serotonin, are closely related to mood and sleep regulation. They help individuals reduce stress, alleviate anxiety, enhance feelings of pleasure and satisfaction, regulate the sleep cycle, and increase deep sleep duration (Weicker \u0026amp; Str\u0026uuml;der, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Scientific and reasonable physical exercise is one of the effective methods to alleviate sleep disorders and improve sleep quality, even mitigating related symptoms (Wang \u0026amp; Boros, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Ye J and Jia X (2022), using a stratified cluster sampling method on 1,006 college students, found that participating in physical exercise can mitigate persistent negative emotions, reduce the level of ruminative thinking, and, to some extent, enhance college students\u0026rsquo; high-level ruminative thinking, thereby improving sleep problems (Ye et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Santos M and Sirtoli R (2023) found that practicing FTPA 1\u0026ndash;3 times per week significantly improves subjective sleep quality, sleep duration, and daytime dysfunction, while practicing FTPA 4\u0026ndash;7 days per week is beneficial for the sleep disorder and daytime dysfunction dimensions of sleep quality (Santos et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, a study tracking over 300 college students found that engaging in physical exercise during spare time could lead to a reduction in sleep quality (Ghrouz et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e). Dance-based, group, and racket sports have been shown to effectively improve college students' sleep quality by reducing the impacts of environmental and academic or employment pressures, helping them form a positive outlook on life, enhancing their psychological resilience, and reducing potential risks to sleep quality.\u003c/p\u003e\u003cp\u003eBased on this, this study puts forward Hypothesis 1: Physical exercise can positively predict college students\u0026rsquo; sleep quality.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e1.2 The Mediating Role of Mobile Phone Addiction\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMobile phone addiction refers to the phenomenon where smartphone users continuously engage with their devices, leading to a specific psychological state that gradually affects their cognition, emotions, sleep, and behavior. In severe cases, it may even impact their normal social interactions and adaptability (Saju, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Self-determination theory posits that humans have three basic psychological needs: autonomy, relatedness, and competence (Ryan \u0026amp; Deci, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In recent years, with the development of smartphone technology, various mobile apps have increasingly played a significant role in fulfilling these basic psychological needs. All three needs can be met to varying degrees through smartphone use. When college students are unable to satisfy their basic psychological needs in the real world, they may turn to smartphones for compensation, potentially leading to smartphone addiction.\u003c/p\u003e\u003cp\u003eThe theory of psychological need satisfaction holds that individuals generally have the basic needs for autonomy, competence, and belonging. When individuals achieve better performance in a given task and receive corresponding psychological satisfaction, they exhibit stronger intrinsic motivation. Moderate physical exercise enables individuals to experience a sense of bodily control during activities, attain a sense of achievement through completing various exercise tasks, and even feel a sense of belonging in team sports. When physical activities fulfill an individual\u0026rsquo;s psychological needs, reliance on smartphones for psychological satisfaction is reduced, thereby decreasing smartphone usage time (Gunnell et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eYang G and Li Y, using a cross-sectional survey design and randomly selecting 650 undergraduates from 10 universities in the Guangzhou Higher Education Center in China, found that physical exercise might be an important intervention method for addressing college students\u0026rsquo; smartphone addiction, with longer intervention durations potentially yielding better outcomes (Yang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Similarly, Guo K and Ma Q, employing a stratified cluster sampling method with 1,550 student questionnaires, discovered that physical exercise can negatively affect college students\u0026rsquo; smartphone addiction. Moreover, physical exercise serves as a significant external environmental stimulus\u0026mdash;it not only improves physical health but also has a notable impact on mental health and smartphone addiction (Guo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Research by Gong Yanbin and Yang Haibo indicated that physical exercise can reduce college students' smartphone addiction, improve their innovative behavior and mental health, and that both innovative behavior and mental health play positive roles in mitigating smartphone addiction (Gong \u0026amp; Yang, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to immersion theory (Nilsson et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), many mobile apps and games are designed based on the concept of immersion. Numerous mobile games offer clear levels, objectives, and reward feedback, with increasing difficulty as the player's skills improve. This continuous challenge can lead players to become immersed, eventually fostering mobile phone addiction. Individuals with mobile phone addiction become deeply absorbed in the pleasurable experiences provided by their phones, which suppresses self-control and distorts their perception of time, thereby encroaching on their rest and sleep.\u003c/p\u003e\u003cp\u003eResearch shows that mobile phone addiction adversely affects sleep quality\u0026mdash;those with more severe addiction tend to experience poorer sleep. For example, Jiang Wenyuan and Chen Lilan surveyed 851 middle school students and found that increased phone usage not only elevates risks such as impaired social skills and depression but also contributes to declining sleep quality due to academic pressures (Jiang \u0026amp; Chen, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, Li Xiaojing and Liu Chang studied over 2,000 primary and secondary school students and observed that while overall dependency on phones was relatively low, girls scored higher than boys, and higher-grade students scored higher than lower-grade ones. Their findings suggest that prolonged exposure to fragmented online information can impair memory and sleep quality, and in severe cases, negatively affect both physical and mental health (Li \u0026amp; Liu, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, research by Gou Shuangyu, Du Meijie, and colleagues found a positive correlation between mobile phone addiction and deteriorating sleep quality. They noted that mobile phone dependency is a form of technological addiction where individuals willingly sacrifice sleep for entertainment, despite the high costs in terms of fatigue (Xun et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Fang Leqin, Xu Xiaoheng, and others also discovered that individuals with mobile phone addiction are at high risk for declining sleep quality because extended use before bedtime suppresses melatonin production and delays the onset of deep sleep, ultimately reducing daytime efficiency (Fang et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBased on this, this study puts forward Hypothesis H2: Mobile phone addiction plays a mediating role in the effect of physical exercise on college students\u0026rsquo; sleep quality.\u003c/p\u003e\u003cp\u003e1.3 The Mediating Role of Ruminative Thinking\u003c/p\u003e\u003cp\u003eRuminative thinking refers to a response pattern in which, after an individual experiences the impact of a negative event on their physical or mental state, they continuously and repeatedly process the causes and consequences of the event at a psychological level, resulting in a decline in physical and mental functioning (Nolen-Hoeksema et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). According to the neuroplasticity theory (Dawson, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), long-term, scientific physical exercise can improve the brain\u0026rsquo;s neural plasticity, thereby enhancing its structure and function. Research indicates that physical exercise promotes the connections between neurons, improving the brain\u0026rsquo;s information processing and regulatory abilities. For example, when facing negative events, the brain can regulate emotions and engage in cognitive restructuring more effectively, thus increasing its flexibility and adaptability and reducing susceptibility to ruminative thinking. Yu et al. found through a survey of college students that they are more prone to ruminative thinking, which negatively affects their development. Physical exercise has a positive effect on reducing ruminative thinking (Yu et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Participants who engaged in ruminative thinking after exposure to stressors exhibited stronger and more persistent negative emotions than those who ruminated less. However, when participants completed aerobic exercise before exposure to stressors, these lingering negative emotions were alleviated, suggesting that exercise can mitigate the impact of subsequent stressors on subjective emotions. Puterman et al. demonstrated that a tendency toward ruminative thinking can increase and prolong physiological stress responses, including HPA axis activation, whereas individuals who consistently engage in physical exercise are less affected by the influence of ruminative thinking on HPA axis reactivity and acute stress recovery; in short, exercise can improve ruminative thinking (Puterman et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Slavish and Graham-Engeland found that sedentary participants reported a higher degree of reflection on stressors, and a lack of physical exercise tends to lead to excessive ruminative thinking, which in turn affects sleep quality (Slavish \u0026amp; Graham-Engeland, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Schmitter M\u0026rsquo;s research revealed that, under conditions of high rumination, exercise was associated with a greater negative memory bias (Schmitter et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Individual differences in trait rumination moderated the relationship between exercise and memory bias; for instance, exercise increased negative memory bias in those with higher levels of rumination. Long-term exercise programs might be necessary to alter cognitive processes associated with depression. Liu Y\u0026rsquo;s study found that physical activity negatively predicted rumination (β = -0.322, t = -10.440, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Liu et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Overall, physical exercise negatively predicts ruminative thinking, anxiety, and depression among college students, indicating that physical exercise can alleviate ruminative thinking, anxiety, and depression.\u003c/p\u003e\u003cp\u003eAccording to response style theory (Nolen-Hoeksema, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), ruminative thinking drives individuals to focus their attention on their own negative emotions and adverse behaviors, thereby reinforcing the negative impact of these factors. The sleep cognitive model posits that intrusive thoughts (such as ruminative thinking) can make it more difficult for individuals to fall asleep or maintain sleep (Espie, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Liu Qingqi, Zhou Zongkui, and colleagues, in a survey of 1,258 high school students, found that ruminative thinking continuously triggers negative emotions, thereby affecting sleep quality, while mindfulness serves as a buffer against these negative emotions (Q. Q. Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Li Jiahui, Wang Juan, Chen Qingyi, and others conducted a cross-sectional survey of over 700 nurses in Jinan and found that nurses\u0026rsquo; sleep quality was affected by work stress; high levels of work stress exacerbated nurses\u0026rsquo; ruminative thinking, interfered with their internal awareness and behavioral responses, disrupted emotional regulation, and led to sleep delay, triggering various sleep problems (Li et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Fu Litong, Men Ruixue, and colleagues, in a survey of over 1,900 elderly individuals above 60, discovered that those with high levels of ruminative thinking paid greater attention to negative events in life\u0026mdash;whether in personal or social contexts\u0026mdash;thereby intensifying negative emotions such as pessimism and anxiety. Their inability to change adverse circumstances resulted in an amplification of negative emotions, which troubled their sleep quality (Fu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Yan Xiaofan, Wang Xiaojie, and colleagues investigated insomnia among new soldiers and found that the severity of insomnia in new recruits was influenced by ruminative thinking; when faced with new stressors, individuals tended to repeatedly ruminate over negative events, reactivating prior negative emotional memories and resulting in poorer sleep quality (Yan et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Gong Jinchao, Guo Siwen, and others, in a study involving over 5,000 students, found that individuals with higher levels of procrastination experienced ruminative thinking more frequently, continuously focusing on negative emotions and the impact of related events. This heightened cognitive arousal before bedtime created significant psychological and physiological stress, leading to a decline in sleep quality (Gong et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Li Qiong, Liu Meng, and colleagues, in a study of sleep quality among 1,147 college students in Sichuan Province, found that negative ruminative thinking affected sleep quality by elevating individuals\u0026rsquo; negative emotions. When individuals are influenced by negative emotions, their procrastination behaviors serve as a defense mechanism to maintain emotional balance; however, if negative emotions remain high, engaging in relaxing or entertaining activities may lower these emotions, resulting in delayed sleep onset and a decline in sleep quality (Li et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBased on this, this study puts forward Hypothesis 3: Ruminative thinking plays a mediating role in the relationship between physical exercise and college students\u0026rsquo; sleep quality.\u003c/p\u003e\u003cp\u003e1.4 The Chain Mediating Role of Mobile Phone Addiction and Ruminative Thinking\u003c/p\u003e\u003cp\u003eEmotional self-regulation theory posits that individuals have the ability to regulate their own emotions (Koole et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Mobile phone addiction may interfere with this emotional regulation ability (Lepp et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). When individuals encounter negative events in real life that trigger negative emotions such as anxiety and depression, they should ideally regulate these emotions through mindfulness, communication, or physical exercise. However, once individuals develop mobile phone addiction, they tend to immerse themselves in the virtual world of their phones to distract their attention, which does not effectively resolve the negative emotional issues. Upon returning from the virtual world to reality, the negative emotions persist, and due to the lack of proper relief, individuals are more likely to fall into ruminative thinking. In addition, mobile phones can amplify negative emotions (Q. Q. Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For instance, short videos, games that showcase idealized lifestyles, or instances of online violence may exacerbate the negative emotions of those with mobile phone addiction, thereby reducing their ability to regulate emotions and leading to further amplification of negative feelings. Intense negative emotions are a key factor that triggers ruminative thinking. Therefore, mobile phone addiction, by impairing emotional regulation, increases the likelihood of developing ruminative thinking.\u003c/p\u003e\u003cp\u003eCao Guanghai, Liu Juan, and colleagues, in their study involving 1,099 college students from Shandong Province, found that reliance on online social networking can positively influence ruminative thinking. Prolonged mobile phone use may intensify individuals\u0026rsquo; negative beliefs, with the brain continuously processing past real-life social interactions, which reinforces negative evaluations of one\u0026rsquo;s behavior and attitudes, ultimately leading to cognitive distortions and increased social anxiety (Cao et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Lin Wenyi, He Hao, and Guan Qing studied the brain functional network mechanisms of ruminative thinking and found, firstly, that ruminative thinking is closely linked to neural activity within the brain\u0026rsquo;s networks, although the causal relationship between them remains unclear (Lin et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Secondly, ruminative thinking can significantly alter an individual\u0026rsquo;s brain functional network, but the specific internal connection mechanisms have yet to be thoroughly explored. Finally, the impact of ruminative thinking tends to decrease with age, primarily because individuals employ distraction strategies; however, this requires further investigation.\u003c/p\u003e\u003cp\u003eBased on this, this study puts forward Hypothesis 4: Mobile phone addiction and ruminative thinking play a chain mediating role in the relationship between physical exercise and college students\u0026rsquo; sleep quality.\u003c/p\u003e\u003cp\u003eFrom the literature review, previous research on the pairwise relationships among physical exercise, sleep quality, mobile phone addiction, and ruminative thinking has yielded certain findings, yet several gaps remain:\u003c/p\u003e\u003cp\u003eResearch Outcomes: There is a substantial body of empirical literature on the relationship between physical exercise and sleep quality across different populations, but the results are inconsistent. Variations in measurement instruments, sample sizes, study populations, and statistical methods\u0026mdash;as well as differing effect sizes of various exercise interventions\u0026mdash;necessitate a comprehensive integration and analysis of these findings to clarify the strength of the relationship.\u003c/p\u003e\u003cp\u003eResearch Content: Prior studies have primarily focused on the relationships between two variables at a time. There is a paucity of research that simultaneously examines physical exercise, mobile phone addiction, ruminative thinking, and sleep quality, and little exploration into the specific mechanisms connecting these four variables\u0026mdash;such as whether mediating effects exist and what their nature might be. Addressing these questions could provide new insights for diagnosing and intervening in sleep quality issues.\u003c/p\u003e\u003cp\u003eResearch Subjects: Most previous studies on the relationships among mobile phone addiction, ruminative thinking, and sleep quality have focused on adults and adolescents, with relatively few investigations involving college students. Given that ruminative thinking and mobile phone addiction are critical factors affecting the psychological health of college students, examining whether these factors mediate the relationship between physical exercise and sleep quality can offer new practical strategies for enhancing sleep quality among this group.\u003c/p\u003e\u003cp\u003eBased on mobile phone addiction theory, ruminative thinking theory, and the analysis of related literature and variable relationships, this study proposes a hypothetical model (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Research Methods","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e2.2. Measurement Tools\u003c/p\u003e\u003cp\u003e(1) Physical Activity Rating Scale (PASR-3)\u003c/p\u003e\u003cp\u003eThe Physical Activity Rating Scale (PASR-3) developed by Liang Deqing (Liang, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) was used to assess college students\u0026rsquo; participation in physical exercise. This scale has an internal consistency coefficient of 0.82. It evaluates exercise volume based on three aspects: intensity, frequency, and duration of exercise. Each aspect is divided into 5 levels, scored from 1 to 5. In this study, the scale\u0026rsquo;s internal consistency (Cronbach\u0026rsquo;s alpha) was 0.72. The total exercise score ranges from 0 to 100 points, where scores of \u0026le;\u0026thinsp;19 indicate low exercise participation, scores between 20 and 42 indicate moderate participation, and scores of \u0026ge;\u0026thinsp;43 indicate high participation.\u003c/p\u003e\u003cp\u003e(2) Mobile Phone Addiction Scale (MPATS)\u003c/p\u003e\u003cp\u003eThe Mobile Phone Addiction Scale (MPATS) was developed by Xiong Jie, Zhou Zongkui, and others (Xiong et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). It consists of 16 items rated on a 5-point Likert scale from \u0026ldquo;strongly disagree\u0026rdquo; to \u0026ldquo;strongly agree.\u0026rdquo; The scale includes four dimensions: withdrawal symptoms, salience, social comfort, and mood change. Items are scored from 1 to 5, yielding a total score range from 16 to 80. Higher scores indicate a greater tendency toward mobile phone addiction, while lower scores indicate a lesser tendency. Typically, a score below 47 reflects normal mobile phone use, whereas a score of 48 or above suggests mobile phone addiction, with higher scores signifying more severe addiction. Exploratory and confirmatory factor analyses have demonstrated good reliability and validity, with an internal consistency coefficient of 0.83 and test-retest reliability of 0.91. In this study, the internal consistency coefficient was 0.93, indicating excellent reliability.\u003c/p\u003e\u003cp\u003e(3) Ruminative Thinking Scale (GSES)\u003c/p\u003e\u003cp\u003eThe Ruminative Thinking Scale, translated and revised by Han Xiuhua and Yang Hongfei (2009) from the original scale developed by Nolen-Hoeksema, is tailored to the Chinese college student population. It consists of 22 items covering 3 dimensions: symptom rumination, compulsive thinking, and reflective pondering. The scale employs a 4-point Likert format (ranging from \u0026ldquo;never\u0026rdquo; to \u0026ldquo;always\u0026rdquo;), with higher scores indicating more severe ruminative thinking. The overall internal consistency coefficient of the scale is 0.90, with subscale coefficients ranging from 0.68 to 0.85. In this study, the overall internal consistency coefficient was 0.945, with reliability coefficients for the dimensions ranging from 0.797 to 0.889.\u003c/p\u003e\u003cp\u003e(4) Pittsburgh Sleep Quality Index (PSQI)\u003c/p\u003e\u003cp\u003eThe Chinese version of the Pittsburgh Sleep Quality Index (PSQI) was compiled by Liu Xiancai and colleagues (Liu et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The original version was developed by Dr. Buysse and his team at the University of Pittsburgh to assess sleep quality over the past month. This version has an internal consistency reliability ranging from 0.80 to 0.84, split-half reliability between 0.78 and 0.87, and test-retest reliability from 0.72 to 0.81. The PSQI consists of 24 items (19 self-rated and 5 rated by others). Eighteen self-rated items contribute to seven dimensions: subjective sleep quality (1 item), sleep latency (2 items), sleep duration (1 item), sleep efficiency (3 items), sleep disturbances (9 items), use of sleeping medication (1 item), and daytime dysfunction (2 items). Each item is rated on a 0\u0026ndash;3 scale, so the total score ranges from 0 to 21. Higher scores indicate poorer sleep quality, with a PSQI score\u0026thinsp;\u0026gt;\u0026thinsp;7 used to indicate \u0026ldquo;sleep quality problems.\u0026rdquo; In this study, the internal consistency coefficient was 0.822, demonstrating good reliability.\u003c/p\u003e\u003cp\u003e2.3. Statistical Methods\u003c/p\u003e\u003cp\u003eThis study utilized computer software including SPSS 23.0, AMOS 24.0, and Excel to input the demographic and scale data collected from college students. The questionnaires were screened, invalid responses removed, and the data organized while further testing the reliability and validity of the scales. Descriptive statistics, correlation and regression analyses, as well as structural equation modeling were employed to process the organized data and to test the proposed hypotheses. Finally, a structural equation model was established to examine the relationship between physical exercise and college students\u0026rsquo; sleep quality.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1. Common Method Bias\u003c/p\u003e\n\u003cp\u003eThis study employed a cross-sectional design to explore college students\u0026rsquo; physical exercise and the related variables. Therefore, a common method bias test was conducted prior to analysis. An exploratory factor analysis was performed on all items from the Mobile Phone Addiction Scale, Ruminative Thinking Scale, Physical Activity Rating Scale, and Pittsburgh Sleep Quality Index. The analysis revealed that seven factors had eigenvalues greater than 1, and the first factor explained 20.713% of the variance, which is below the critical threshold of 40%. This indicates that common method bias is not a concern.\u003c/p\u003e\n\u003cp\u003e3.2 Correlation Analysis of Physical Exercise and Other Variables\u003c/p\u003e\n\u003cp\u003eTable 1. Descriptive Statistics and Correlations Among Physical Exercise and Other Variables\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e21.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e21.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e9.640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.234**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e6.691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e2.401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.230**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.586**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e3.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.209**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e0.344**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.322**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Note: *p \u0026lt; 0.05, *p \u0026lt; 0.01\u003c/p\u003e\n\u003cp\u003eIn this study, college students scored an average of 21.839\u0026plusmn;21.063 on physical exercise, 5.007\u0026plusmn;3.902 on sleep quality, 9.640\u0026plusmn;3.489 on mobile phone addiction, and 6.691\u0026plusmn;2.401 on ruminative thinking. To explore the relationships among these variables, Pearson correlation analysis was conducted on physical exercise, sleep quality, ruminative thinking, and mobile phone addiction. The analysis revealed that physical exercise was significantly negatively correlated with mobile phone addiction (r = -0.234, p \u0026lt; 0.01), ruminative thinking (r = -0.230, p \u0026lt; 0.01), and sleep quality (r = -0.209, p \u0026lt; 0.01). In contrast, mobile phone addiction showed significant positive correlations with both ruminative thinking (r = 0.586, p \u0026lt; 0.01) and sleep quality (r = 0.344, p \u0026lt; 0.01). Moreover, ruminative thinking was also significantly positively associated with sleep quality (r = 0.322, p \u0026lt; 0.01).\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eSee Tab 1\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e3.3 Regression Analysis of Physical Exercise and Other Variables\u003c/p\u003e\n\u003cp\u003eTable 2. Regression Analysis Results for Physical Exercise and Other Variables\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 31px;\"\u003e\n \u003cp\u003eRegression Equation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 40px;\"\u003e\n \u003cp\u003eOverall Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 27px;\"\u003e\n \u003cp\u003eSignificance of Regression Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eDependent Variable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003ePredictor(s)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e75.353**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-8.681**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e353.580***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-4.284**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e24.512**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSleep Quality\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e78.474***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e-4.498**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e6.860**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eRuminative Thinking\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e5.260***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003eBased on the hierarchical regression results in Table 2, physical exercise significantly influences mobile phone addiction (\u0026beta; = -0.039, t = -8.681, p \u0026lt; 0.01). In addition, both physical exercise (\u0026beta; = -0.011, t = -4.284, p \u0026lt; 0.01) and mobile phone addiction (\u0026beta; = 0.388, t = 24.512, p \u0026lt; 0.01) have significant effects on ruminative thinking. Furthermore, physical exercise, mobile phone addiction, and ruminative thinking all significantly predict sleep quality (\u0026beta; = -0.022, t = -4.498, p \u0026lt; 0.01; \u0026beta; = 0.244, t = 6.860, p \u0026lt; 0.01; \u0026beta; = 0.272, t = 5.260, p \u0026lt; 0.01).\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eSee Tab 2\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e3.4 The Chain Mediating Effect between Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003cp\u003e3.4.1 The Mediating Effect of Mobile Phone Addiction between Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003cp\u003eTo further verify the effect of physical exercise on college students\u0026apos; sleep quality and to test the mediating role of mobile phone addiction, this study employed Bootstrap analysis with a sample size of 5000 and Model 6, setting a 95% confidence interval. The model examining the influence of physical exercise on sleep quality through mobile phone addiction was tested, and the mediating effect size of mobile phone addiction is presented in Table 3.\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eSee Tab 3\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3. Bootstrap Analysis for Testing the Significance of the Mediation Effect\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;Path Relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eStandardized Path Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eStandard Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003eC.R.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eSignificance (P)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e-8.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e-0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e-5.474\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e11.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003eTable 4: Analysis of the Total Effect of Mobile Phone Addiction\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 36px;\"\u003e\n \u003cp\u003eMediating Path\u0026emsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 16px;\"\u003e\n \u003cp\u003eEffect Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 23px;\"\u003e\n \u003cp\u003eBootstrapCI(95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eLower Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 36px;\"\u003e\n \u003cp\u003ePhysical Exercise-Mobile Phone Addiction-Sleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e-0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e-0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 4, when mobile phone addiction is used as the mediating variable between physical exercise and sleep quality, the Bootstrap 95% confidence interval has an upper limit of -0.063 and a lower limit of -0.12. Since this interval does not include 0, it indicates that the mediating effect of mobile phone addiction on the influence of physical exercise on college students\u0026apos; sleep quality is significant, following the pathway \u0026quot;physical exercise \u0026rarr; mobile phone addiction \u0026rarr; sleep quality.\u0026quot;\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eSee Tab 4\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5: Fitting Indices for the Mediation Effect of Mobile Phone Addiction on Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"96%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eFit Test Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003eIdeal Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003eGeneral Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eModel results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eConclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/df（Chi-Square/Degrees of Freedom Ratio)\u003c/p\u003e\n \u003cp\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e1-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eRMSEA（Root Mean Square Error of Approximation）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＜0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eNFI（Normed Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eRFI（Relative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eIFI（Incremental Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eTLI（Tucker-Lewis Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003eCFI（Comparative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 5, the fit indices for the mediating effect of mobile phone addiction indicate that X\u0026sup2;/df = 2.81 (\u0026lt; 3), NFI = 0.988, RFI = 0.97, IFI = 0.981, TLI = 0.95, and CFI = 0.981; all these indices exceed 0.90. Additionally, RMSEA = 0.054 (\u0026lt; 0.08), which shows that there is no serious common method bias in the study of the mediating effect of mobile phone addiction on the relationship between physical exercise and sleep quality. The mediating model for mobile phone addiction fits well and is acceptable.\u003cstrong\u003e（See Tab 5）\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing a structural equation model, the model linking physical exercise, mobile phone addiction, and sleep quality is shown in Figure 2. In this model, physical exercise directly affects sleep quality, mobile phone addiction directly affects sleep quality, and physical exercise indirectly influences college students\u0026rsquo; sleep quality through the mediating effect of mobile phone addiction.\u003c/p\u003e\n\u003cp\u003e3.4.2 The Mediating Effect of Ruminative Thinking between Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003cp\u003eTo further validate the impact of physical exercise on college students\u0026apos; sleep quality and to examine the mediating role of ruminative thinking, this study employed Bootstrap analysis with a sample size of 5000, using Model 6 and a 95% confidence interval. The model testing the effect of physical exercise on sleep quality through ruminative thinking was evaluated, and the mediating effect size of ruminative thinking is shown in Table 6.\u003c/p\u003e\n\u003cp\u003eTable 6: Bootstrap Analysis for Testing the Significance of the Mediation Effect\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;Path Relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eStandardized Path Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eStandard Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eC.R.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eSignificance (P)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e-0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-7.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-5.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eSleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e10.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 7: Analysis of the Total Effect of Ruminative Thinking\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;Mediating Path\u0026emsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eEffect Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 23px;\"\u003e\n \u003cp\u003eBootstrap CI(95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eLower Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003ePhysical Exercise-Ruminative Thinking-Sleep Quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 7, when ruminative thinking is used as the mediating variable between physical exercise and sleep quality, the Bootstrap 95% confidence interval has an upper limit of -0.055 and a lower limit of -0.103. Since the interval does not include 0, the mediating effect of ruminative thinking is significant. The influence pathway is \u0026quot;physical exercise \u0026rarr; ruminative thinking \u0026rarr; sleep quality.\u0026quot;\u003c/p\u003e\n\u003cp\u003eTable 8: Fitting Indices for the Mediation Effect of Ruminative Thinking on Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"96%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eFit Test Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eIdeal Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eGeneral Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eModel results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eConclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/df（Chi-Square/Degrees of Freedom Ratio)\u003c/p\u003e\n \u003cp\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e1-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e2.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eRMSEA（Root Mean Square Error of Approximation）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eNFI（Normed Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eRFI（Relative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eIFI（Incremental Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eTLI（Tucker-Lewis Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eCFI（Comparative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eIdeal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 8, the fit indices for the mediating effect of ruminative thinking indicate that X\u0026sup2;/df = 2.951 (\u0026lt; 3), NFI = 0.974, RFI = 0.975, IFI = 0.982, TLI = 0.926, and CFI = 0.982; all of these indices exceed 0.90. Additionally, RMSEA = 0.055 (\u0026lt; 0.08) shows that there is no serious common method bias in the study of the mediating effect of ruminative thinking on the relationship between physical exercise and sleep quality. The mediating model for ruminative thinking fits well and is acceptable.\u003c/p\u003e\n\u003cp\u003eUsing a structural equation model, the relationship among physical exercise, ruminative thinking, and sleep quality is depicted in Figure 3. In this model, physical exercise has a direct effect on sleep quality, ruminative thinking directly influences sleep quality, and physical exercise indirectly affects college students\u0026apos; sleep quality through the mediating effect of ruminative thinking.\u003c/p\u003e\n\u003cp\u003e3.4.3 Chain Mediation Model Test of Mobile Phone Addiction and Ruminative Thinking\u003c/p\u003e\n\u003cp\u003eTo further investigate the impact of physical exercise on sleep quality and test the chain mediating effects of mobile phone addiction and ruminative thinking, this study employed Bootstrap analysis with a sample size of 5000, using Model 6 and a 95% confidence interval. The model examining the influence of physical exercise on sleep quality through mobile phone addiction and ruminative thinking was tested. The indirect effect sizes for each path are presented in Table 9.\u003c/p\u003e\n\u003cp\u003eTable 9: Standardized Path Coefficient Table\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026nbsp;Path Relationship\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eStandardized Path Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003eStandard Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eC.R.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eSignificance (P)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e-0.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-8.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e-0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-4.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e13.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eSleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003ePhysical Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e-0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e-4.502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eSleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eMobile Phone Addiction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e8.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eSleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003eRuminative Thinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e7.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 10: Analysis of the Total Effect of Mobile Phone Addiction on Ruminative Thinking\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003e\u0026nbsp;Mediating Path\u0026emsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003eEffect Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 134px;\"\u003e\n \u003cp\u003eBootstrap CI(95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eLower Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eUpper Limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 209px;\"\u003e\n \u003cp\u003ePhysical Exercise-Mobile Phone Addiction-Ruminative Thinking-Sleep quality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 10, the 95% Bootstrap confidence interval has an upper bound of -0.015 and a lower bound of -0.034. Since this interval does not include 0, it indicates that the chain mediating effect of mobile phone addiction and ruminative thinking in the relationship between physical exercise and sleep quality is significant. The pathway is \u0026quot;physical exercise \u0026rarr; mobile phone addiction \u0026rarr; ruminative thinking \u0026rarr; sleep quality.\u0026quot;\u003c/p\u003e\n\u003cp\u003eTable 11: Fitting Indices for the Mediation Effect of Ruminative Thinking on Physical Exercise and Sleep Quality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"96%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eFit Test Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003eIdeal Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003eGeneral Standard\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eModel results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eConclusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/df（Chi-Square/Degrees of Freedom Ratio)\u003c/p\u003e\n \u003cp\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e1-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e4.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e良好\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eRMSEA（Root Mean Square Error of Approximation）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＜0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eNFI（Normed Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eRFI（Relative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eIFI（Incremental Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eTLI（Tucker-Lewis Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 177px;\"\u003e\n \u003cp\u003eCFI（Comparative Fit Index）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e＞0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e理想\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAccording to Table 11, the fit indices for the mediating effect model of ruminative thinking indicate that X\u0026sup2;/df = 4.741 (\u0026lt; 5), NFI = 0.959, RFI = 0.982, IFI = 0.975, TLI = 0.938, and CFI = 0.989; all these indices exceed 0.90, and RMSEA = 0.054 (\u0026lt; 0.08). This demonstrates that the study of the mediating effects of ruminative thinking and mobile phone addiction on the influence of physical exercise on college students\u0026apos; sleep quality does not suffer from serious common method bias, and the mediating model fits well and is acceptable.\u003c/p\u003e\n\u003cp\u003eUsing a structural equation model, the model linking physical exercise, college students\u0026rsquo; mobile phone addiction, ruminative thinking, and sleep quality is presented in Figure 4. In this model, physical exercise directly affects sleep quality, mobile phone addiction directly affects sleep quality, and self-efficacy directly affects sleep quality. Mobile phone addiction can indirectly influence sleep quality through the mediating effect of self-efficacy, and physical exercise can indirectly influence sleep quality through the chain mediating effect of mobile phone addiction and self-efficacy.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e4.1 Analysis of the Mediating Effect of Mobile Phone Addiction\u003c/p\u003e\u003cp\u003eThis study confirmed that physical exercise can predict college students' sleep quality through the mediating effect of mobile phone addiction, indicating that participation in physical exercise effectively improves both mobile phone addiction and sleep quality among college students. This finding not only broadens the understanding of the pathways through which physical activity influences sleep quality, but also highlights the emerging significance of mobile phone addiction as a critical mediating variable. Existing research on the mechanisms underlying sleep quality has predominantly focused on traditional psychological factors such as anxiety, depression, cognitive function, and stress, as well as intervention strategies like mindfulness training and social support. However, little attention has been paid to the increasingly prominent issue of mobile phone addiction among university students. Recent statistics reveal that as many as 52.5% of students born in the 1990s and 2000s use their phones before bedtime, indicating that mobile devices have become deeply embedded in their daily routines and may pose a potential risk to sleep quality. Grounded in this social reality, the present study is the first to incorporate mobile phone addiction into the pathway linking physical activity and sleep quality, thereby filling a significant gap in the current body of research.\u003c/p\u003e\u003cp\u003eOn one hand, physical exercise directly affects sleep quality; college students can alleviate anxiety, shift their attention, and expand their social networks through exercise, thereby enhancing their sleep quality. On the other hand, physical exercise also indirectly influences sleep quality via mobile phone addiction, which acts as a mediator in the relationship between physical exercise and sleep quality. Specifically, physical exercise is a negative predictor of sleep quality, whereas mobile phone addiction is a positive predictor of sleep quality. Furthermore, the findings of this study align with previous research by confirming the link between physical exercise and mobile phone addiction, as well as the close relationship between mobile phone addiction and sleep quality. Building on earlier conclusions, this study further demonstrates that mobile phone addiction mediates the relationship between physical exercise and sleep quality, thus enriching the existing literature.\u003c/p\u003e\u003cp\u003eBandura's reciprocal determinism theory posits that behavior is influenced by both personal and environmental factors (Bandura, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). From an environmental perspective, mobile short videos permeate every aspect of smartphone use. In addition to mainstream short video platforms, various social media channels such as Weibo and WeChat also push a range of short videos. Moreover, college students are highly dependent on mobile games, which can diminish their self-regulation abilities. Addictive behavior can impair brain regions responsible for self-regulation, reducing inhibitory control, while the uneven allocation of attention toward online games further hampers individuals' ability to regulate their behavior. Sharma M. P.'s insomnia model identifies poor behavioral habits as another key factor (Sharma \u0026amp; Andrade, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Mobile phone dependency, as a maladaptive behavioral habit, is significantly and positively correlated with overall sleep quality scores; specifically, the more severe the mobile phone dependency, the poorer the sleep quality. From a physiological standpoint, engaging in moderate-intensity physical exercise can stimulate the brain to secrete endorphins, enhancing feelings of well-being and reducing the discomfort associated with being away from one's phone.\u003c/p\u003e\u003cp\u003eThis study reveals the positive impact of physical exercise on college students' sleep quality and emphasizes the partial mediating role of mobile phone addiction in this process. The findings offer valuable insights for developing interventions to address sleep issues among college students. They underscore the need for enhanced regulation and guidance of mobile phone usage while encouraging an increase in physical exercise frequency to improve sleep quality and overall health.\u003c/p\u003e\u003cp\u003e4.2 Analysis of the Mediating Effect of Ruminative Thinking\u003c/p\u003e\u003cp\u003eThis study confirmed that physical exercise can predict college students\u0026rsquo; sleep quality through the mediating effect of ruminative thinking, demonstrating that engaging in physical exercise effectively improves both ruminative thinking and sleep quality. Physical exercise directly enhances sleep quality by enabling college students to shift their focus and build psychological resilience, thereby promoting better sleep. In addition, exercise indirectly influences sleep outcomes through its effect on ruminative thinking. Specifically, higher levels of physical exercise predict improved sleep quality, whereas increased ruminative thinking is associated with poorer sleep outcomes.\u003c/p\u003e\u003cp\u003eFurthermore, our findings are consistent with some previous studies; they confirm the relationship between physical exercise and ruminative thinking and underscore the close connection between ruminative thinking and sleep quality. Building on earlier conclusions, this study further demonstrates that ruminative thinking mediates the relationship between physical exercise and sleep quality, thereby enriching the existing literature.\u003c/p\u003e\u003cp\u003eExcessive ruminative thinking can diminish the beneficial impact of positive emotions on sleep quality. Although moderate positive emotions can enhance sleep, over-processed or exaggerated positive emotions may lead to heightened emotional arousal, ultimately impairing sleep quality (Butz \u0026amp; Stahlberg, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Similarly, insomnia models indicate that both cognitive and emotional arousal can disturb the neurophysiological system and contribute to sleep problems. Physical exercise, however, can consciously boost individuals\u0026rsquo; ability to regulate both cognition and emotions, thus improving the physiological conditions related to sleep and, in turn, enhancing sleep quality (Guastella \u0026amp; Moulds, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMoreover, physical exercise acts as an effective means of emotion regulation, helping college students relieve accumulated stress, balance their emotions, and maintain a calm mindset. A relaxed and balanced mental state not only fosters better cognitive functioning but also reduces the risk of falling into ruminative thinking. In summary, this study highlights the positive impact of physical exercise on sleep quality among college students and emphasizes the partial mediating role of ruminative thinking. These findings provide valuable insights into the mechanisms by which physical exercise influences mental health, paving the way for more targeted interventions to improve sleep quality.\u003c/p\u003e\u003cp\u003e4.3 Chain Mediation Effect Analysis\u003c/p\u003e\u003cp\u003eThe results of the chain mediation analysis indicate that the impact of physical exercise on college students\u0026rsquo; sleep quality is jointly achieved through mobile phone addiction and ruminative thinking. Physical exercise improves sleep quality by helping college students alleviate anxiety, shift their focus, and expand their social networks. It also boosts physical fitness and social skills, which reduces mobile phone addiction and buffers ruminative thinking. This chain mediating effect is significant: higher mobile phone addiction increases ruminative thinking, leading to continuous processing of negative events and emotions, ultimately resulting in poorer sleep quality\u0026mdash;a finding consistent with previous research (Wang et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBy constructing a chain mediation model, this study explains how physical exercise affects college students\u0026rsquo; sleep quality: not only does exercise have a direct impact on sleep quality, but it also exerts a positive influence via the chain mediation of mobile phone addiction and ruminative thinking. Therefore, Hypothesis H3 is supported. The research confirms that active participation in physical exercise is beneficial for enhancing sleep quality and establishes the relationships among physical exercise, mobile phone addiction, ruminative thinking, and sleep quality. Furthermore, it lays a theoretical foundation for further studies aimed at improving college students\u0026rsquo; physical health and sleep quality. In summary, physical exercise has a significant negative effect on poor sleep quality, and improving sleep quality among college students can be achieved by reducing both mobile phone addiction and ruminative thinking. Although these findings are consistent with current theoretical models, further empirical research is needed to verify and expand on these results.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Recommendations","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e5.1 Enhance Physical Exercise Interventions to Mitigate Mobile Phone Addiction\u003c/p\u003e\u003cp\u003eUniversities should fully recognize the positive role of physical exercise in reducing mobile phone addiction and strengthen related intervention efforts. Schools need to offer well-designed physical education courses and organize a variety of sports activities and competitions. Developing personalized exercise plans tailored to the diverse lifestyles and academic schedules of college students is recommended. By specifying appropriate exercise times, frequencies, and intensities, regular physical activity can help relieve stress, regulate emotions, and ultimately enhance sleep quality.\u003c/p\u003e\u003cp\u003e5.2 Promote Engaging and Trendy Extracurricular Sports Activities\u003c/p\u003e\u003cp\u003eColleges should organize more interesting and innovative extracurricular sports events to encourage students to leave their dorms and enrich their leisure time. Participating in group activities not only reduces feelings of loneliness and improves social interactions but also helps control the occurrence of ruminative thinking. By verbalizing internal thoughts during discussions or confiding in peers, students might find the answers they seek. Additionally, listeners can share their concerns and suggest reasonable solutions based on real-life situations, which can prevent unnecessary ruminative thinking and help resolve issues in a positive manner.\u003c/p\u003e\u003cp\u003e5.3 Implement Effective Interventions to Improve Sleep Habits\u003c/p\u003e\u003cp\u003eImproving sleep quality among college students requires addressing not only poor personal sleep habits but also external environmental factors, with the dormitory atmosphere being particularly important. To tackle issues like mobile phone addiction and ruminative thinking, students are encouraged to develop positive psychological adjustment strategies. These may include finding practical solutions to problems, engaging in open communication, and learning relaxation techniques. By reducing negative thoughts and emotions, the psychological stress experienced before sleep can be alleviated, ultimately enhancing sleep quality.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study followed strict procedures to ensure confidentiality, and approval was obtained from the Ankang University Review Committee. All participants signed informed consent forms before taking part in the study. Our research adheres to the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agreed to submit the manuscript after reviewing it.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data material can be further obtained from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted without any commercial or financial relationships that could be perceived as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe work was funded by the Shaanxi Provincial Education Department Project for 2024 (Project Number 24JK0004), the Shaanxi Province \u0026quot;14th Five-Year Plan\u0026quot; Education Science Planning Project for 2024 (Project Number SGH24Q301), and the 2024 Shaanxi Provincial Sports Bureau Regular Project Initiation Project (Project Number 20240001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor Contributions: Conceptualization, J.W. and Q.X.; methodology, J.W. and Y.L.; data curation, J.W.; formal analysis, G.D. and Y.L.; writing\u0026mdash;original draft preparation, J.W. and G.D.; writing\u0026mdash;review and editing, J.W.; supervision, J.W. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eWe thank all the participants in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u0026nbsp;\u003c/strong\u003enot applicable\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDisclaimer/Publisher\u0026rsquo;s Note:\u003c/strong\u003e The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBandura, A. (1978). 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[CrossRef]\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"College Students, Physical Exercise, Sleep Quality, Mobile Phone Addiction, Rumina-tion","lastPublishedDoi":"10.21203/rs.3.rs-6824913/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6824913/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eAim\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhysical exercise improves sleep quality, whereas its underlying mechanisms remain underexplored. This study examines how mobile phone addiction and rumination mediate the relationship between physical exercise and college students' sleep quality, offering a theoretical basis for preventing and addressing sleep problems.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA cross-sectional survey was conducted among 1,300 college students from seven universities using the Physical Activity Rating Scale, the Pittsburgh Sleep Quality Index, the Mobile Phone Addiction Tendency Scale, and the Rumination Scale.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(1) Physical exercise significantly negatively predicted college students' mobile phone addiction, rumination, and sleep quality (β = -0.039, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; β = -0.011, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; β = -0.022, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (2) Mobile phone addiction significantly positively predicted college students' rumination and sleep quality (β\u0026thinsp;=\u0026thinsp;0.388, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01; β\u0026thinsp;=\u0026thinsp;0.244, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (3) Rumination significantly positively predicted college students' sleep quality (β\u0026thinsp;=\u0026thinsp;0.272, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). (4)The mediating pathway whereby physical exercise influences sleep quality through mobile phone addiction and rumination was statistically significant.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(1) Actively participating in physical exercise can effectively improve college students' mobile phone addiction, rumination, and sleep quality (2) Reducing mobile phone addiction and rumination among college students can significantly enhance their sleep quality (3)The effect of college students' participation in physical exercise on sleep quality is mediated in a chain by mobile phone addiction and rumination.\u003c/p\u003e","manuscriptTitle":"Unraveling the Pathway: How Physical Activity Enhances Sleep Quality Through Reduced Mobile Addiction and Maladaptive Thought Patterns in University Students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 14:30:57","doi":"10.21203/rs.3.rs-6824913/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11e15de8-9a63-4093-aa1c-752fa33f93b6","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51667712,"name":"Biological sciences/Psychology"},{"id":51667713,"name":"Health sciences/Health care"}],"tags":[],"updatedAt":"2025-09-22T20:23:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-18 14:30:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6824913","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6824913","identity":"rs-6824913","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}