Social media addiction as the central mediating variable to explore the mechanism between physical exercise and sleep quality

Abstract

In recent years, the sleep quality of college students has garnered increasing attention from scholars. Physical activity, as a healthy lifestyle, has been extensively investigated in relation to the sleep quality of college students. However, the psychological mechanisms underlying this relationship warrant further exploration. This study aimed to examine the internal relationship between physical activity and sleep quality among college students, with anxiety, depression and social media addiction serving as mediating variables. A total of 4101 college students (1,509 males, 2,592 females; mean age 19.05 ± 1.16 years) were included in this study. Data on physical activity, anxiety, depression, social media addiction, and sleep quality were collected through a cross-sectional subjective survey. The basic characteristics of the variables were described using SPSS, and correlation analyses were conducted. Finally, a chain mediation model was constructed using the PROCESS plugin. The study found a significant positive correlation between physical exercise and the sleep quality of college students, and significant negative correlations with anxiety, depression and social media addiction. Anxiety and depression were also significantly negatively correlated with sleep quality and significantly positively correlated with social media addiction. Ultimately, anxiety, depression and social media addiction were found to play a chain mediating role between physical exercise and the sleep quality of college students. This study further elucidates the mechanisms underlying the relationship between physical exercise and sleep quality among college students by incorporating psychological (anxiety and depression) and behavioral (social media addiction) variables. It is recommended that college students actively engage in physical exercise, which can help alleviate anxiety and depression, reduce social media addiction, and thereby improve sleep quality.

Introduction

Sleep quality is defined by four key elements: Sleep Latency (the time it takes to fall asleep), Awakenings (the number of times one wakes up during the night), Wake After Sleep Onset (the amount of time spent awake after first falling asleep), and Sleep Efficiency (the ratio of time asleep to time lying in bed). This definition was established by an expert panel led by the National Sleep Foundation (NSF) after an extensive review of 277 studies¹. Chinese college students, having experienced the high-pressure environment of high school, enter the relatively more flexible and free university campus life, where they have greater control over their time and schedules². This transition may lead them to indulge more freely, potentially neglecting healthy sleep habits. A recent cross-sectional survey involving 6284 college students revealed that over 30% had poor sleep quality³. Sleep quality is associated with individual depression^4,5, academic performance^6,7, and cardiovascular diseases^8,9. Therefore, promoting good sleep quality among college students is an important research topic.

A recent review study on the determinants of sleep quality among college students identified physical activity as a significant factor¹⁰. Physical activity is typically defined as any bodily movement produced by skeletal muscles that requires energy expenditure¹¹. During physical exercise, body temperature increases, and after the exercise ceases, the body cools down. This temperature regulation promotes better sleep quality¹². A meta-analysis conducted in 2021 found a correlation between moderate-to-vigorous physical activity and higher sleep quality (N = 141,035; r = 0.18)¹³. Additionally, the meta-analysis found that physical activity increased total sleep time, delayed the onset of REM sleep (by 10 min), increased slow-wave sleep (SWS), and reduced REM sleep (by 2–5 min)¹⁴. The results of the cross-sectional study show that mindfulness and rumination have a chain mediating effect between physical activity and the sleep quality of college students¹⁵. In contrast, longitudinal studies found no causal relationship between physical exercise and sleep quality among college students, but suggested that emotional regulation mediates this relationship¹⁶.

Physical activity may enhance sleep quality among college students by alleviating negative emotions such as anxiety and depression, which are common during the transitional phase of life¹⁷. A recent meta-analysis that synthesized 64 primary studies found the prevalence of anxiety and depression among global college students to be 33.6% (95% CI: 29.3–37.8%) and 39% (95% CI: 34.6–43.4%), respectively¹⁸. Another meta-analysis conducted during the COVID-19 pandemic in China revealed the prevalence rates of anxiety and depression among college students to be 19% (95% CI: 15–24%) and 22% (95% CI: 19–25%), respectively¹⁹. An earlier review study found that depression appears to have a bidirectional predictive relationship with sleep quality among college students²⁰. Strong evidence indicates that poor sleep quality, including sleep disorders and insomnia, is often correlated with depression and anxiety^20–23. Numerous studies have also shown that physical exercise can alleviate negative emotions. A meta-analysis that included 14,170 participants found that physical exercise had a significant effect on depression²⁴. Additionally, a randomized controlled meta-analysis involving 24 original studies demonstrated that physical exercise could significantly alleviate anxiety and depression in college students²⁵. Moreover, a substantial body of research has identified a significant negative correlation between physical activity and both anxiety and depression in college students^26–28.

Furthermore, physical activity may improve sleep quality among college students by reducing social media addiction. Social media addiction refers to a psychological and behavioral pattern where individuals become overly dependent on social media platforms, struggle to control their usage, and exhibit withdrawal reactions²⁹. Although the DSM-5³⁰ and ICD-11³¹ do not include it as a diagnosable disease, it shares similar behavioral and psychological manifestations with substance addiction and is widely recognized. Additionally, Terms such as problematic social media use and social media dependence are often used interchangeably with social media addiction. Notably, social media addiction, along with problematic internet use and smartphone dependence, is collectively referred to as technological addiction due to their significant similarities^32–35. A recent meta-analysis found that the detection rate of social media addiction among global college students was 18.4%, with the highest rate in Asia at 22.8%³⁶. With the widespread popularity of smart electronic devices and wireless networks, college students often use their phones before sleep, affecting their sleep schedule management³⁷. An early study found that poor sleep quality and daytime sleepiness among college students were largely due to their frequent use of electronic devices before sleep³⁸. Moreover, the blue light emitted from social media use may suppress the secretion of melatonin^39,40, thereby affecting sleep quality. Studies have also found a significant positive correlation between smartphone addiction and insomnia among medical students⁴¹. Additionally, an observational study of 2,661 college students found that social media addiction significantly predicted sleep quality⁴². According to the social bond theory⁴³, physical activity can enhance social connections and support, alleviate negative emotions, and thereby reduce the degree of social media addiction among college students. Recent studies have found a significant negative correlation between physical activity and social media addiction⁴⁴, and physical activity can negatively predict social media addiction among college students⁴⁵. Considering the evidence, social media addiction may serve as a mediator between physical activity and sleep quality among college students for two reasons. First, it can displace time that could otherwise be spent on physical activity, which is a protective factor for sleep quality. This displacement can lead to poorer sleep quality. Conversely, when college students actively engage in physical activity instead of using social media, they may experience better sleep quality. Both scenarios align with the “Isotemporal Substitution Paradigm”⁴⁶, which suggests that reallocating time from one activity to another can have significant health implications.

There is also a significant relationship between negative emotion and social media addiction. According to the compensatory internet use theory⁴⁷, when individuals experience negative emotions, they tend to use virtual social networks to escape these feelings. In the university campus, students from all over the country gather together, with diverse cultural, economic backgrounds, and lifestyles. Therefore, they face many sources of anxiety and depression, including psychological, academic, economic factors, or romantic relationships⁴⁸. As a result, social media plays an increasingly important role in their studies and lives. Studies have found a significant positive correlation between anxiety and social media addiction among college students^49,50. Moreover, anxiety significantly predicts social media addiction among college students^49,50. Additionally, studies have revealed a significant positive correlation between depression and social media addiction in college students⁵¹. A network analysis study involving 432 college students found that “depression” consistently serves as the most central node, playing a critical role in the network linking social media addiction with other variables⁵².

To sum up, despite the well-documented associations between sleep quality, negative emotions, social media addiction, and physical activity among college students, the complex interplay among these factors remains underexplored. While existing studies have identified the prevalence of sleep disorders, anxiety, depression, and social media addiction in college populations, few have examined the mediating roles of these factors in the relationship between physical activity and sleep quality. The unique transitional phase of college life, characterized by increased autonomy and potential neglect of healthy habits, further complicates this relationship. Moreover, the rapid evolution of digital technology and its pervasive use among young adults underscores the need to understand how social media addiction impacts sleep and mental health. This study aims to fill these critical gaps by providing a comprehensive analysis of the mediating pathways between physical activity, negative emotions, social media addiction, and sleep quality. By doing so, it will offer valuable insights for developing targeted interventions to improve sleep quality and mental health among college students, ultimately contributing to their overall well-being and academic success. Therefore the current study explores the chain-mediated model between physical exercise and sleep quality of college students with social media addiction as the center role, further enriching the relationship between physical activity and sleep quality among college students through psychological and behavioral variables, and providing a theoretical basis for improving sleep quality among college students. The hypothesized model is shown in Fig. 1.

Fig. 1.

Hypothetical model diagram.

Based on the aforementioned literature, the following hypotheses were formulated for this study:

1. There is a significant positive correlation between physical activity and sleep quality among college students.

2. Anxiety and depression significantly mediate the relationship between physical activity and sleep quality among college students.

3. Social media addiction significantly mediates the relationship between physical activity and sleep quality among college students.

4. Anxiety and depression, as well as social media addiction, significantly mediate the relationship between physical activity and sleep quality among college students in a chain-like manner.

Methods

Participants

This study employed a convenience sampling method to recruit university students from 6 provinces in China in October 2024. Prior to the commencement of the study, ethical approval was obtained from the ethics committee of the author’s institution. Online electronic questionnaires were distributed via class group chats, with an informed consent form placed on the first page of the questionnaire. Participants were required to read and click “agree” before proceeding with the survey. Data was collected only from participants who completed all items in the questionnaire. Thus, individuals who declined to participate or chose to exit during the survey were fully respected for their right to participate freely, and no adverse effects were incurred. The first page of the questionnaire outlined the purpose of the study, data anonymity, confidentiality, and usage. Participants typically completed the electronic questionnaire within 15 min. A total of 4,506 complete data samples were initially collected. Data was screened to exclude samples with extreme response times and those showing obvious patterned responses. The final analytical sample comprised 4,101 participants (effective response rate: 91.01%). The sample included 1,509 males, 2,592 females, with a mean age of 19.05 years (SD = 1.16). Additional demographic information is detailed in Table 1.

Table 1.

Basic information.

Variables			N	Percent (%)
Grade	Freshman		1851	45.1%
	Sophomore		1951	47.6%
	Junior		279	6.8%
	Senior		20	0.5%
Only-child status	Only		1026	25%
	Not only		3075	75%
Parental education	Father	Unclear	231	5.6%
		Primary and below	851	20.8%
		Middle school	2573	62.7%
		Collegiate	415	10.1%
		Graduate student	31	0.8%
	Mother	Unclear	245	6.0%
		Primary and below	1121	27.3%
		Middle school	2326	56.7%
		Collegiate	383	9.3%
		Graduate student	26	0.6%

Measurement tools

Considering the daily academic stress of participants and the instability of online questionnaires, as well as the desire to minimize disruption to the daily teaching schedules of participants and teachers, measurement tools with fewer items were selected. Simple measurement tools offer numerous advantages^53,54, such as reduced cognitive and time costs for participants, decreased response bias, increased satisfaction, and lower subsequent data processing costs.

Physical activity

Physical activity was assessed using a single item: “In the past 7 days, how many days did you engage in at least 20 minutes of physical exercise or activity that made you sweat or breathe hard?” Response options ranged from 0 to 7 days⁵⁵. This measurement question has been widely used in previous studies^56–58.

Anxiety and depression

In this study, the Generalized Anxiety Disorder scale (GAD-2)⁵⁹ and the Patient Health Questionnaire (PHQ-2)⁶⁰ will be employed to assess the levels of anxiety and depression. Both scales consist of two items each and utilize a Likert-4 point scoring system, ranging from 1 (not at all) to 4 (nearly every day), with a total score ranging from 2 to 8. Higher total scores indicate more severe levels of anxiety and depression. The Cronbach’s α coefficients for anxiety and depression in the sample of this study are 0.861 and 0.789.

Social media addiction

Social media addiction was evaluated using the Bergen Social Media Addiction Scale (BSMAS)⁶¹. A 5-point Likert scale was adopted for scoring, with the range from 1 (rarely) to 5 (often). This scale contains 6 items, and the score range is from 6 to 30 points. A higher BSMAS score indicates a higher degree of addiction to social media. In the current study, the Cronbach’s α coefficient is 0.867.

Sleep quality

A single-item measure was used to assess the sleep quality of the sample in this study⁶². Participants were asked: “Kindly reflect upon your comprehensive sleep quality over the past seven-day period. This includes aspects such as the number of hours you slept, the ease with which you were able to fall asleep, the frequency of nocturnal awakenings (excluding those for bathroom visits), the incidence of waking up earlier than necessary in the morning, and the overall sense of refreshment upon waking. How would you evaluate your sleep quality during the past seven days?” This question was scored on a 10-point scale, where a higher score indicated better sleep quality. Notably, this measurement approach has been extensively utilized in prior research studies, attesting to its reliability and applicability in the assessment of sleep quality within the studied population^63–66.

Covariates

In testing the mediation model, gender, age, and the demographic variables mentioned in Table 1 were controlled for.

Data analysis

Before analyzing the data, a common method bias (CMB) test was conducted. Following the recommendations of Podsakoff et al.⁶⁷, a threshold of 40% was set to determine whether significant bias existed in the data. Secondly, the four main variables in this study were presented in terms of means and standard deviations (SD) and were subjected to descriptive and correlational analysis using SPSS 26.0. Additionally, the mediation model was tested using the PROCESS 4.0 macro in SPSS. Additionally, the mediation model was tested using the PROCESS 4.0 macro in SPSS. To assess potential multicollinearity among the variables, the variance inflation factor (VIF) was calculated. A VIF value less than 5 indicated that multicollinearity was not a concern in this study⁶⁸. Prior to conducting the mediation analysis, the variables were standardized. Physical activity was set as the independent variable, sleep quality as the dependent variable, and anxiety, depression and social media addiction as the mediators, with demographic variables included as covariates in the chain mediation model (Model 80)⁶⁹. To assess model fit and estimate 95% confidence intervals (95% CI), 5,000 bootstrap resampling iterations were performed, ensuring the robustness of the analysis⁷⁰. The significance level was set at 0.05.

Results

Common method bias test

The results of the common method bias test in this study revealed the presence of 4 factors with eigenvalues greater than 1. The first factor accounted for 21.25% of the total variance, which is below the threshold of 40%. This indicates that there is no significant risk of common method bias in the current study.

Correlation analysis

The results presented in Table 2 show that physical activity was significantly negatively correlated with college student anxiety (r = -0.077, p < 0.001), depression (r = -0.087, p < 0.001) and social media addiction (r = -0.116, p < 0.001), and significantly positively correlated with sleep quality (r = 0.106, p < 0.001). Anxiety and depression was significantly positively correlated with social media addiction among college students (r = 0.371, p < 0.001; r = 0.366, p < 0.001) and significantly negatively correlated with sleep quality (r = -0.370, p < 0.001; r = -0.374, p < 0.001). Social media addiction was significantly negatively correlated with sleep quality among college students (r = -0.220, p < 0.001). The correlation between anxiety and depression was 0.782. Therefore, we examined the VIF levels. The results showed that the VIF values for all variables were less than 3, indicating that multicollinearity was not a concern.

Table 2.

Correlation analysis.

Variables	Mean	Sd	VIF	1	2	3	4
1 Physical activity	3.09	2.16	1.08	–
2 Anxiety	3.34	1.26	2.68	−0.077***	–
3 Depression	3.49	1.21	2.67	−0.087***	0.782***	–
4 Social media addiction	15.35	4.59	1.20	−0.116***	0.371***	0.366***	–
5 Sleep quality	7.08	1.96	1.20	0.106***	−0.370***	−0.374***	−0.220***

VIF variance inflation factor.

***p < 0.001.

Mediation model test

After controlling for demographic variables, the results shown in Table 3; Fig. 2 demonstrate a significant positive correlation between physical exercise and sleep quality among college students (β = 0.108, SE = 0.016, p < 0.001). When the mediating variables were incorporated into the analysis, this positive correlation remained significant (β = 0.068, SE = 0.015, p < 0.001). In addition, physical activity was found to be significantly negatively correlated with anxiety (β= -0.078, SE = 0.016, p < 0.001), depression (β= -0.089, SE = 0.016, p < 0.001) and social media addiction (β= -0.069, SE = 0.015, p < 0.001) in college students. Anxiety (β= -0.182, SE = 0.023, p < 0.001), depression (β= -0.200, SE = 0.023, p < 0.001) and social media addiction (β= -0.070, SE = 0.016, p < 0.001) were all significantly negatively correlated with sleep quality in college students. Finally, anxiety (β = 0.217, SE = 0.023, p < 0.001) and depression (β = 0.190, SE = 0.023, p < 0.001) were significantly positively correlated with social media addiction in college students. The proportion of the predictive path is detailed in Table 4.

Table 3.

Mediation model testing.

Outcome variables	Predictor variables	β	SE	t	R²	F
Sleep quality	Physical activity	0.108	0.016	6.738***	0.015	8.884***
	Gender	0.021	0.016	1.307
	Age	0.008	0.020	0.420
	Grade	−0.036	0.019	−1.816
	Only-child status	−0.014	0.016	−0.913
	Father’s educational background	0.014	0.021	−0.675
	Mother’s educational background	0.029	0.021	1.359
Anxiety	Physical activity	−0.078	0.016	−4.886***	0.008	4.457***
	Gender	−0.004	0.016	−0.236
	Age	0.017	0.020	0.841
	Grade	−0.013	0.020	−0.665
	Only-child status	−0.002	0.016	−0.154
	Father’s educational background	0.021	0.021	0.980
	Mother’s educational background	−0.049	0.021	−2.307*
Depression	Physical activity	−0.090	0.016	−5.583***	0.009	4.998***
	Gender	−0.008	0.016	−0.513
	Age	0.004	0.020	0.180
	Grade	−0.007	0.020	−0.362
	Only-child status	0.010	0.016	0.635
	Father’s educational background	0.016	0.021	0.758
	Mother’s educational background	−0.034	0.021	−0.592
Social media addiction	Physical activity	−0.069	0.015	−4.681***	0.163	88.713***
	Anxiety	0.217	0.023	9.429***
	Depression	0.190	0.023	8.250***
	Gender	0.049	0.015	3.278**
	Age	0.011	0.018	0.610
	Grade	0.039	0.018	2.152*
	Only-child status	0.001	0.015	0.074
	Father’s educational background	−0.007	0.019	−0.340
	Mother’s educational background	−0.005	0.019	−0.242
Sleep quality	Physical activity	0.068	0.015	4.619***	0.168	82.387***
	Anxiety	−0.182	0.023	−7.836***
	Depression	−0.200	0.023	−8.650***
	Social media addiction	−0.070	0.016	−4.517***
	Gender	0.022	0.015	1.480
	Age	0.013	0.018	0.722
	Grade	−0.037	0.018	−2.048*
	Only-child status	−0.013	0.015	−0.873
	Father’s educational background	0.021	0.019	1.097
	Mother’s educational background	0.012	0.019	0.594

***p < 0.001.

Fig. 2.

The chain mediation model (***: p<0.001).

Table 4.

Path analysis of mediation model.

Paths	Effect size	SE	Bootstrap 95% CI	Proportion of mediating effect
Total effect	0.1077	0.0160	0.0763, 0.1390
Direct effect	0.0683	0.0148	0.0393, 0.0973
Total indirect effect	0.0394	0.0067	0.0268, 0.0527	36.11%
Physical activity→Depression→Sleep quality	0.0179	0.0039	0.0108, 0.0261	16.67%
Physical activity→Anxiety→Sleep quality	0.0142	0.0035	0.0079, 0.0215	12.96%
Physical activity→Social media addiction→Sleep quality	0.0048	0.0017	0.0020, 0.0086	4.63%
Physical activity→Depression→Social media addiction→Sleep quality	0.0012	0.0004	0.0054, 0.0021	0.93%
Physical activity→Anxiety→Social media addiction→Sleep quality	0.0012	0.0004	0.0005, 0.0021	0.93%

Discussion

This study further explored the psychological and behavioral mechanisms between physical activity and sleep quality among college students, revealing potential mediating variables. The findings indicate a significant positive correlation between physical activity and sleep quality among college students, which remained significant even after the introduction of mediating variables, albeit at a reduced level. Additionally, physical activity was found to be significantly negatively correlated with anxiety, depression and social media addiction. Anxiety, depression and social media addiction were also significantly negatively correlated with sleep quality among college students, acting as mediators in the relationship between physical activity and sleep quality.

Physical activity and sleep quality

The positive correlation between physical activity and sleep quality among college students aligns with our initial hypothesis (H1). Prior research suggests that physical activity can enhance interpersonal relationships⁷¹, alleviate negative emotions⁷², and increase subjective well-being⁷³, thereby promoting better sleep quality. Moreover, physical activity can boost metabolism, leading to a stronger sense of fatigue before sleep⁷⁴, facilitating easier onset of sleep, such as reducing sleep latency and extending deep sleep duration^75,76. Furthermore, physical activity can lower cortisol levels⁷⁷, promote the secretion of melatonin⁷⁸, and increase the release of dopamine and serotonin^79,80, all of which contribute to improved sleep quality. Numerous observational studies have also reported a negative correlation between physical activity and sleep quality among college students^15,81,82, suggesting that further investigation into the factors influencing this relationship is warranted. A recent meta-analysis found that both acute and regular physical activity have small to medium effects on sleep efficiency, total sleep time, and sleep latency (Cohen’s d effect sizes = 0.18–0.35), while regular physical activity has a large effect on overall sleep quality (Cohen’s d = 0.73). These effects are relatively stable across different age groups of adults⁸³. This stability may be related to the way exercise improves slow-wave sleep quality by increasing slow-wave stability⁸⁴. Therefore, the relationship between physical activity and sleep quality among college students involves complex physiological and psychological mechanisms. The current study primarily explores this relationship through psychological mechanisms.

Emotional disturbance, physical activity and sleep quality

This study also found that anxiety and depression mediate the relationship between physical activity and sleep quality among college students, supporting our initial hypothesis (H2). Previous studies have shown that physical activity can foster better peer relationships^85,86, increase social support⁸⁷, and enhance self-efficacy and confidence⁸⁸, significantly reducing anxiety and depression levels among college students. Additionally, physical activity can regulate the homeostasis of the HPA axis⁸⁹, reduce stress^90,91, and thereby alleviate anxiety and depression. As anxiety and depression levels decrease, sleep quality is expected to improve. Research has found that individuals with anxiety and depression are more prone to sleep disorders^92–96. Studies have indicated that individuals with high levels of anxiety often have higher sleep reactivity⁹⁷. Moreover, anxiety, depression, and pre-sleep rumination may affect vivid dreaming during rapid eye movement (REM) sleep⁹⁸. Therefore, when anxiety and depression is mitigated, sleep quality among college students correspondingly improves. Besides improving sleep quality by alleviating negative emotions, physical activity can also enhance sleep quality by reducing social media addiction.

Physical activity, sleep quality and social media addiction

The study found that social media addiction mediates the relationship between physical activity and sleep quality among college students, confirming our hypothesis (H3). When college students actively engage in physical activities, their time spent on social media may be displaced and consequently reduced⁹⁹. Moreover, physical activity can enhance social support among college students¹⁰⁰, further alleviating negative emotions and reducing the tendency to immerse themselves in social media. Studies have found a significant negative correlation between physical activity and media addiction among college students and adolescents^44,101. Furthermore, when social media addiction is reduced, the circadian rhythms of college students become more stable^102,103, leading to further improvements in sleep quality^104,105. Research indicates that higher levels of social media addiction are associated with poorer sleep quality among college students¹⁰⁶, and a cohort study found that poor sleep quality due to social media use among college students may stem from “fear of missing out”¹⁰⁷. Thus, social media addiction plays a mediating role between physical activity and sleep quality among college students.

Emotional disturbance, physical activity, sleep quality and social media addiction

Furthermore, anxiety and depression and social media addiction act as chain mediators between physical activity and sleep quality among college students, validating our final hypothesis (H4). When individuals experience high levels of anxiety and depression, they tend to use social networks as a means of relief^47,108, which can lead to increased dependence on social media over time. Cross-sectional studies involving college student samples have consistently shown significant positive correlations between anxiety (0.47 < r < 0.49), depression (0.36 < r < 0.49), and problematic internet use^27,109–111. Studies have found that social media seems to have a “sedative” effect on individuals with high levels of anxiety¹¹². A previous study found that physical activity can enhance psychological well-being and alleviate negative emotions, thereby reducing smartphone addiction among college students¹¹³. According to the self-medication hypothesis¹¹⁴, individuals tend to use “substance abuse” to relieve or alter a range of painful emotional states, and social media addiction serves as an almost perfect substitute for this behavior. Therefore, college students who engaged in more physical activity tended to report lower levels of anxiety and depression, which were associated with less social media addiction and better sleep quality.

Research advantages, significance and implications

Based on a large cross-sectional survey of over 4,000 college students, this study collected self-reported data on physical activity, anxiety, depression, social media addiction, and sleep quality. It analyzed the interrelationships among these variables and constructed a chain mediation model with physical activity as the independent variable, sleep quality as the dependent variable, and anxiety, depression, and social media addiction as mediating variables. This model elucidates the underlying psychological and behavioral mechanisms between physical activity and sleep quality among college students, further expanding the theoretical foundation of this relationship.

The findings hold significant practical implications. By identifying anxiety, depression, and social media addiction as key mediators, this study provides actionable insights for targeted interventions. Promoting regular physical activity in college settings can serve as a powerful tool to mitigate anxiety and depression, thereby enhancing sleep quality. Universities can implement structured exercise programs, sports clubs, or fitness workshops tailored to students’ interests and schedules. These initiatives not only improve mental health but also foster a sense of community and social support, reducing reliance on social media for emotional fulfillment.

Addressing social media addiction is also crucial for improving sleep hygiene. Educating students about the negative impact of excessive social media use on sleep and mental health can encourage healthier digital habits. Implementing digital detox programs or promoting the use of apps that monitor and limit screen time before bedtime can help regulate circadian rhythms and improve sleep quality.

The chain mediating effect of anxiety, depression, and social media addiction underscores the need for a holistic approach. Integrating mental health services, counseling, and mindfulness programs alongside physical activity initiatives can create a supportive environment that addresses both psychological and behavioral factors influencing sleep. By leveraging these findings, universities can develop comprehensive strategies to enhance student well-being, ultimately contributing to better academic performance and overall quality of life.

Based on these findings, this study encourages college students to actively engage in physical activities. These initiatives may not only improve mental health but could also foster a sense of community and social support, contributing to reducing reliance on social media for emotional fulfillment. However, according to previous research, it is recommended that college students pay attention to the timing of their exercise. Engaging in physical activity 4 to 8 h before bedtime is often optimal, while exercising at other times may have the opposite effect¹¹⁵. Future research is recommended to incorporate additional psychological and behavioral variables, such as affective disorders and adverse childhood experiences^116–119, to explore the relationship between physical activity and sleep quality among college students. This is particularly important when these variables have strong direct or indirect relationships with the variables examined in this study¹²⁰. High-quality studies, such as randomized controlled trials or basic experimental research, are also suggested to investigate the underlying mechanisms, providing theoretical references and evidence to promote better sleep quality among college students.

Limitations & recommendations

Despite its strengths, this study has some limitations. First, the study relied on a cross-sectional subjective survey, which is insufficient for explaining the causal order and objective relationships between variables. Future studies should employ longitudinal tracking combined with objective measurements to strengthen the relationships between variables. Second, although the study considered research costs by using single-item measurement tools, this approach is inadequate for explaining the specific effects of internal dimensions of variables, preventing the exploration of deeper-level information. This also led to the situation where, in the context of a large sample (N = 4101), even though the variables were statistically significant (e.g., β = 0.12, p < 0.001 for the direct effect of physical activity on sleep quality), the findings may not be practically significant. This may be related to the low sensitivity of the simple measurement tools. For example, previous studies have found that when exploring the same theme, variables measured using single-item tools had lower correlations with other variables compared to those measured using multi-item tools^58,121–123. Therefore, future studies should use multidimensional tools or objective measurement tools to explain the specific effects of variables. Alternatively, before using simple measurement tools, multi-dimensional tools or objective measurement tools could be used as calibration tools to test the reliability and validity of the simple measurement tools. Lastly, although the study examined a large sample, the convenience sampling method used introduces potential biases, such as selection bias and low external validity, in the sampling process. Future studies should employ stricter sampling methods, such as cluster or stratified sampling based on different cultural, dietary, and economic backgrounds, or a combination of both, and collect samples from more diverse cultural backgrounds to strengthen the relationships between variables.

Conclusion

This study found that physical activity is significantly negatively correlated with anxiety, depression and social media addiction among college students and significantly positively correlated with sleep quality. Anxiety, depression and social media addiction mediate the relationship between physical activity and sleep quality among college students. It is recommended that schools organize more activities conducive to physical activity for college students, improve facilities and policies related to physical exercise, and encourage active participation in physical activities to alleviate anxiety, depression and social media addiction and promote sleep quality.

Author contributions

Xusheng Che 12456, Zhitao Lu 1256, Yu Jin 1256.1 Conceptualization; 2 Methodology; 3 Data curation; 4 Writing - Original Draft; 5 Writing - Review & Editing; 6 Funding acquisition.

Data availability

The datasets generated and/or analysed during the current study are not publicly available due [our experimental team’s policy] but are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

The study was approved by the Nantong University before the initiation of the project (Research number: 2024−07−09). And informed consent was obtained from the participants before starting the program. We confirm that all the experiment is in accordance with the relevant guidelines and regulations such as the declaration of Helsinki.