The effects of boredom on short video addiction: mediating roles of procrastination and physical activity

Abstract

Boredom is a prevalent emotional experience that shapes individuals’ cognitive and behavioral patterns across various dimensions. Short video addiction has become an increasingly prevalent issue among college students; however, few empirical studies have explored the potential impact of boredom on short video addictive behaviors. Previous studies have shown that, among college students, procrastination and physical activity are both associated with boredom and short-video addiction. In this context, the present study primarily examines the association between boredom and short video addiction among college students, as well as the mediating roles of procrastination and physical activity in this relationship. We constructed a parallel mediation model to test the proposed hypothetical relationships.

Methods

A random sample of 287 college students from a normal university completed questionnaires including the Boredom Proneness Scale, Short Video Addiction Scale, Physical Activity Rating Scale, and Short General Procrastination Scale. Conduct correlation analysis and mediation analysis using SPSS.

Results

(1) Among the 287 college students, 129 scored at the addiction level on the short video addiction scale, representing a rate of 44.9%. (2) Boredom is positively associated with short video addiction. (3) Procrastination independently mediated the relationship between boredom and short video addiction. (4) Physical activity independently mediated the connection between boredom and short video addiction.

Conclusion

This study investigates the relationship between boredom and short video addiction among college students, as well as the roles of procrastination and physical activity in this phenomenon. Our findings provide a theoretical basis for future research on the association between boredom and short video addiction.

Introduction

Currently, with the burgeoning popularity of short video applications, such platforms have become an integral part of individuals’ daily lives. As of June 2025, the number of short video app users in China had reached 1.068 billion, accounting for 95.1% of the country’s total internet user base [1]. Although short video platforms have a large user base and satisfy people’s daily entertainment needs, excessive use may contribute to problematic short video use and addictive tendencies among certain groups. Typical behaviors associated with short video addiction include aimless scrolling and loss of control over usage. This phenomenon has become increasingly prevalent among college students. A 2024 survey of 160 college students, for instance, found that 51.9% reported engaging in excessive short video use [2]. Short video addiction is characterized by the excessive use of these applications, despite the negative consequences [3]. Short video addiction exerts a detrimental impact on college students’ physical and psychological well-being, with empirical research documenting its adverse effects on students’ sleep quality, attention spans and learning burnout [4–6]. Currently, there is debate regarding the definition of short-video addiction, and there are no universally accepted clinical diagnostic criteria. The academic community generally uses standardized scales to assess problematic short-video use and addictive tendencies; however, the results of such screenings do not equate to a clinical diagnosis of addiction. Boredom is a pervasive and influential human emotion. To alleviate boredom, individuals engage in a range of coping activities, such as reading, watching television, and participating in physical exercise. With the continual advancement of the internet and communication technology, short video platforms have gradually emerged as primary tools for alleviating boredom. Boredom is a subjective state perceived as unpleasant and undesirable, characterized by difficulty sustaining attention, a tendency toward cognitive disengagement, and a perception of time passing slowly. It often prompts individuals to seek actions to escape the present moment [7]. Research indicates that boredom is a significant factor influencing smartphone addiction and internet addiction [8, 9]. Research has established a correlation between smartphone use and boredom, with tendencies toward boredom positively influencing smartphone addiction [10]. Similarly, studies have revealed significant positive correlations among boredom tendencies and smartphone addiction [11]. Short video addiction is regarded as a distinct subtype of internet addiction [12]. Short video addiction is more akin to a manifestation of internet addiction within mobile applications; it shares the characteristics of internet addiction while also exhibiting features specific to short video apps, such as “short viewing sessions” and “endless scrolling,” making it a specific form of internet addiction. Considering the correlation between boredom and internet addiction, a potential link may exist between boredom and short video addiction. Research has found that boredom is linked to both procrastination and physical activity [13, 14]. Procrastination and physical activity are also linked to short-video addiction [15, 16]. Procrastination and physical activity may play a role in the link between boredom and short-video addiction. Research has found a link between boredom and a failure to self-regulate [17]. The compensatory internet use theory provides a useful framework for studying short video addiction. For college students, understanding the underlying mechanisms linking short video addiction and boredom is crucial for preventing and reducing the occurrence of short video addiction when they are bored. Based on Internet compensation theory and self-regulation theory, this study investigates the direct impact of boredom on short video addiction, as well as its indirect effects on short video addiction through procrastination and physical activity.

The relationship between boredom and short video addiction

Boredom is highly prevalent in daily life. It refers to a state of relatively low arousal and dissatisfaction, denoting an existential or conscious condition characterized by specific combinations of perceptions, emotions, and other factors [18]. Boredom is a negative emotional experience arising from a mismatch between current activities or environments and an individual’s internal standards [19]. Boredom is on the rise among college students, with Chinese university students exhibiting significantly increased levels of boredom tendencies over the past 12 years (2009–2020) [20]. With the rise of short video platforms, short video apps have gradually become a new way for college students to kill time when they are bored. However, the phenomenon of short video addiction among college students is becoming increasingly evident. With the rise of short video apps, these platforms have become a new way for people to pass the time during moments of boredom. Increasing research is now examining the causes of short video addiction. From a neuroimaging perspective, studies have revealed that, similar to other behavioral addictions, short video addiction correlates with heightened reward responses [21]. A further study indicates that the qualities of short videos affect addiction by stimulating users’ perceptual satisfaction and withdrawal symptoms [22]. A review of 54 studies encompassing 36,245 people demonstrated a substantial positive link between boredom and smartphone addiction [23]. Some scholars have examined boredom as a mediating factor in the association between other variables and short video addiction, including social exclusion and loneliness [24, 25]. A survey of 662 college students found that when bored, students tend to use short videos to escape negative emotions [26]. In summary, we propose Hypothesis 1: Boredom is positively associated with short video addiction.

The mediating role of procrastination

Procrastination is the voluntary delay of planned, essential, or personally significant actions despite the expectation of negative repercussions, even when they outweigh the benefits [27]. Research on procrastination suggests that negative emotions can influence people’s procrastination behavior [28]. Boredom is viewed as a negative emotion. A connection exists between boredom and procrastination. A study involving 668 university students found a positive correlation between sleep procrastination and boredom proneness [11]. With the advancement of new media technologies, research has begun investigating how these technologies serve as substitutes for task engagement. Studies involving German and Turkish samples revealed that persistence in boredom tendencies is a particularly prominent predictor of online procrastination [29]. Findings from a sample of 490 students demonstrated a significant, positive, direct effect of boredom on procrastination [30]. Procrastination has been shown to be influenced by boredom in previous research. The correlation between procrastination and short-video addiction is being increasingly investigated as short-video applications become more prevalent. A substantial positive connection is seen between TikTok scrolling addiction and academic procrastination [31]. The addiction of college students to short videos is strongly correlated with academic procrastination [32]. A study of college students found that a tendency to procrastinate directly predicts problematic short-video viewing [33]. Previous research suggests that boredom is associated with procrastination, which in turn is associated with short video addiction. Therefore, this study proposes Research Hypothesis 2: Procrastination mediates the relationship between boredom and short video addiction.

The mediating role of physical activity

Physical activity positively impacts both mental and physical health [34]. The lifestyles of contemporary college students are often characterized by insufficient physical activity [35]. Boredom is a significant factor affecting exercise engagement and performance [36]. Research investigating students’ perceptions of boredom in physical education classes found that experiencing boredom serves as a form of resistance, arising when students feel little power or control over their learning process [37]. Boredom partially led to lower participation in physical activity by reducing the perceived value of physical labor [38]. Thus, a link exists between feelings of boredom and physical activity. Similar to other screen devices, such as televisions, smartphone use appears to be a sedentary leisure activity [39]. Several studies have found that physical exercise has a significant negative impact on adolescents’ addiction to short videos [40, 41]. Furthermore, research indicates that physical activity levels are directly associated with reduced nighttime short video use [16]. These studies collectively demonstrate a connection between physical activity and short video addiction. Therefore, based on the above, we propose Research Hypothesis 3: Physical activity mediates the relationship between boredom and short video addiction.

In real life, individuals experiencing boredom often first exhibit procrastination and low levels of physical activity before subsequently choosing activities to alleviate boredom. The compensatory internet use theory asserts that individuals pursue compensation and relief from discomfort by using the internet and related applications to cope with negative real-life situations, unmet needs, or negative emotions. This may lead to excessive use and even trigger negative behavioral patterns [42]. Based on self-regulation theory, failure in self-regulation may be an important factor associated with addiction-related behaviors. Individuals with reduced self-regulatory capacity may have greater difficulty sustaining goal-directed behavior and may be more vulnerable to impulsive or uncontrolled responses [43]. Compensatory Internet Use Theory and Self-Regulation Theory can explain the relationship between boredom and short video addiction, as well as the roles of procrastination and physical activity in this relationship. Based on the above theory, we constructed a structural equation model of boredom and short video addiction (Fig. 1).

Fig. 1.

Research Model

Methods

Participants and procedure

This research was performed at a university in a central province of China. Participants were full-time undergraduate students in their freshman to junior years. This study collected data via convenience sampling through teacher-facilitated recruitment on WeChat and sought to include students of different genders and grade levels. During the study, three instructors used the WeChat messaging app to distribute survey announcements and QR codes for the electronic surveys to college students in different grade levels. Participants completed the questionnaire via the Wenjuanxing website, and the survey took approximately 10–15 min to complete. The research has been approved by the Ethics Committee of Shangqiu Normal University (No: SQNU-2025-012). At the start of the test, respondents were provided with the questionnaire and instructions for completing the scales. The test emphasized anonymity, voluntary participation, and data confidentiality. Informed consent was confirmed by all participants, who were free to withdraw at any time. Invalid questionnaires were excluded to ensure data validity (Incomplete answers, identical answers, etc.). Of 304 questionnaires distributed, 287 were valid, resulting in a valid response rate of 94.4%. The mean age of respondents was 19.96 years (SD = 1.57), with 161 females (56.1%) and 126 males (43.9%). First-year students comprised 129 (44.9%), second-year students 74 (25.8%), and third-year students 84 (29.3%).

Measures

Boredom Proneness Scale (BPS)

The Chinese short form of the BPS was developed by Li et al. [44]. It comprises 12 items measuring internal and external stimuli characteristics of boredom proneness. Each item uses a 7-point rating scale, with items 1, 12, 4, 7, 8, and 2 reverse-scored. Higher total scores indicate greater boredom proneness. The results of the confirmatory factor analysis for the scale are as follows: χ²/df = 1.83, RMR = 0.07, RMSEA = 0.05, TLI = 0.97, GFI = 0.96. In this study, Cronbach’s α was 0.86.

Short video addiction scale

The Short Video Addiction Scale is stable and reliable, capable of independently measuring short video addiction among college students [45]. The scale measures retreat, avoidance, loss of control, and ineffectiveness. The 14 items are evaluated on a scale of 1–5. The four factors demonstrate excellent structural fit and an internal consistency reliability coefficient of 0.91 for the total scale. Positive answers (≥ 4 points) to any four of the seven diagnostic feature items (Items 2, 3, 4, 5, 7, 12, 13) suggest short-video addiction. The results of the confirmatory factor analysis for the scale are as follows: χ²/df = 1.88, RMR = 0.07, RMSEA = 0.05, GFI = 0.94, TLI = 0.97. Cronbach’s α in this study was 0.92.

Short General Procrastination Scale (SGPS)

The Chinese version of the SGPS was developed by Zhang et al. [46]. The SGPS consists of 9 items. Items are scored on a 5-point Likert scale. Higher total scores indicate a stronger tendency toward procrastination. The results of the confirmatory factor analysis for the scale are as follows: χ²/df = 2.65, RMR = 0.05, RMSEA = 0.07, GFI = 0.95, TLI = 0.92. In this study, Cronbach’s α was 0.78.

Physical Activity Rating Scale (PARS-3)

The PARS-3, revised by Liang [47], has been widely used as a measure of physical activity in previous studies [48, 49]. This Scale considers three factors: duration, intensity, and frequency. Physical activity level = intensity × (duration − 1) × frequency. The intensity, frequency, and duration are evaluated on a scale of 1 to 5. The test-retest reliability of the Scale is 0.82.

Statistical analysis

Statistical analysis was conducted using SPSS 26.0. First, data were collected via questionnaires. To examine common-method bias, we employed Harman’s one-factor test. The first factor accounted for 26.53% of the variance, and eight factors produced eigenvalues greater than 1, indicating that there was no significant standard method bias. Descriptive analysis of participants’ personal characteristics followed. Spearman’s correlation analysis was implemented to determine correlations. Ultimately, the Hayes PROCESS macro (Model 4) in SPSS was used to conduct a mediation analysis. The study used the Bootstrap method to test for mediating effects. Data were simulated 5000 times to obtain 95% confidence intervals [50]. A mediation effect was considered significant if the 95% confidence interval excluded 0.

Results

Description and correlations

Table 1 presents the correlations among the primary study variables. The boredom was positively correlated with short video addiction and procrastination (r = 0.315, p < 0.01; r = 0.448, p < 0.01) and negatively correlated with physical activity (r = − 0.306, p < 0.01); Short video addiction was positively correlated with procrastination (r = 0.391, p < 0.01) and negatively correlated with physical activity (r = − 0.296, p < 0.01); Procrastination was negatively correlated with physical activity (r = -0.213, p < 0.01). Furthermore, based on the criteria for assessing short video addiction levels outlined in the Short Video Addiction Scale, the findings revealed that 129 university students reached the level of short video addiction, meaning 44.9% of students exhibited short video addiction.

Table 1.

Correlation analysis between the variables

	M	SD	Boredom	Short video addiction	Procrastination	Physical activity
Boredom	44.68	8.01	1	-	-	-
Short video addiction	42.91	11.98	0.315**	1	-	-
Procrastination	25.16	5.81	0.448**	0.391**	1	-
Physical activity	22.98	24.05	-0.306**	-0.296**	-0.213**	1

** p < 0.01

Mediating effect analysis

The mediating effect was tested using the bootstrap method and Hayes’ SPSS macro tool, Model 4 [51]. Regression analysis results (Table 2), controlling for gender and grade level, are as follows. Boredom positively predicted short video addiction (β = 0.296, p < 0.01), procrastination (β = 0.426, p < 0.001), and inversely predicted physical activity (β = −0.256, p < 0.001). Upon integrating procrastination and physical activity into the regression model, short video addiction was positively predicted by boredom (β = 0.137, p < 0.05) and procrastination (β = 0.286, p < 0.001), while negatively predicted by physical activity (β = −0.142, p < 0.05). These results provide preliminary support for the proposed parallel mediation model.

Table 2.

Regression analysis between the variables

Regression Equation		Overall Fit Index			Significance of Regression Coefficient
Result Variable	Predictive Variable	R	R2	F	β	t
Short video addiction		0.385	0.148	12.289
	Gender				0.088	1.553
	Grade				-0.183	-3.204**
	Boredom				0.296	5.326**
Procrastination		0.471	0.222	20.149
	Gender				-0.051	-0.936
	Grade				-0.150	-2.753**
	Boredom				0.426	8.020***
Physical activity		0.546	0.298	30.03
	Gender				-0.144	-2.787**
	Grade				0.386	7.454***
	Boredom				-0.256	-5.071***
Short video addiction		0.478	0.228	13.826
	Gender				0.082	1.494
	Grade				-0.084	-1.408
	Boredom				0.137	2.263*
	Procrastination				0.286	4.810***
	Physical activity				-0.142	-2.273*

*p < 0.05, **p < 0.01, ***p < 0.001

We further tested the mediating effects (Table 3; Fig. 2). Neither the direct effect of boredom proneness on short video addiction nor the mediating effects of procrastination and physical activity included zero in the upper and lower bounds of the Bootstrap 95% confidence intervals. Table 3 reports unstandardized effects. The total mediation effect was 0.237, with procrastination and physical activity mediating 53.50% of boredom’s total effect (0.443) on short video addiction. This mediation effect comprised two pathways: First, boredom → procrastination → short video addiction (Indirect effect 1), with a mediation effect value of 0.182 (41.08%); Second, boredom → physical activity → short video addiction (Indirect effect 2), with a mediation effect value of 0.055 (12.42%).

Table 3.

Mediation Effects in Parallel Mediator Models

Effect Type	Effect Value	Bootstrap SE	Bootstrap 95% CI		Proportion of Relative Effect
			LLCI	ULCI
Direct effect	0.206	0.091	0.026	0.385	46.50%
Indirect effect1	0.182	0.048	0.093	0.283	41.08%
Indirect effect2	0.055	0.029	0.002	0.119	12.42%
Total indirect effect	0.237	0.051	0.141	0.343	53.50%
Total effect	0.443	0.083	0.279	0.607

Fig. 2.

Pathway map of Boredom affecting Short video addiction. Note: *p < 0.05，** p<0.01, ***p < 0.001

Discussion

This study seeks to investigate the psychological mechanisms that connect boredom and short video addiction, focusing on the concurrent mediating effects of procrastination and physical activity. Results indicate that 129 out of 287 college students met the criteria for short video addiction, representing a rate of 44.9%. According to several cross-sectional studies of college students conducted in recent years, the prevalence of short-video addiction among college students was 21.6%, 30.2%, and 31.3%, respectively [52–54]. These studies used the same short-video addiction scale as the present study. This indicates that short-video addiction among college students is at a relatively high level, highlighting the urgent need for intervention strategies. Although the same scale was used, the higher prevalence observed in this study should still be interpreted cautiously, given differences in sample characteristics and study context. The findings suggest that boredom is significantly associated with short video addiction, both directly and indirectly through two relatively independent pathways: procrastination and physical activity. The significant grade effect suggests that academic-year-related factors may partly shape physical activity and short video addiction beyond boredom alone. These results collectively support the core hypothesis of this study, demonstrating that boredom among college students can directly predict short video addiction and indirectly influence its occurrence and development through the parallel mediating effects of procrastination and physical activity.

In this investigation, we examined the correlation between short video addiction and boredom. Following the widespread adoption of the internet and smartphones, boredom levels among college students have increased rather than decreased. A meta-analysis examining boredom levels among college students from 2009 to 2020 found that their propensity for boredom increased over time, with internet accessibility emerging as a significant predictor of this increase [20]. With the rapid growth of short-video platforms, college students have become the primary users. This study found that short video addiction is significantly positively associated with boredom, consistent with previous research [55]. Hypothesis 1 was supported, indicating that boredom positively influences short video addiction. When individuals seek to alleviate boredom and satisfy psychological needs, short video apps are among their primary methods. Thus, for college students, consuming digital media—such as watching short TikTok videos—emerges as the optimal way to escape boredom and seek stimulation [56]. Based on the compensatory internet use theory, when confronted with the unpleasant state of boredom, short video consumption rewards college students and provides satisfaction. This alignment between an individual’s need for arousal and readily available environmental stimuli contributes to their short video addiction. Boredom is a positive factor influencing college students’ short-video addiction.

The findings suggest that boredom is indirectly associated with short video addiction through procrastination. Hypothesis 2 is confirmed. College students experiencing high levels of boredom exhibit increased procrastination, which in turn affects their short video addiction. Procrastination—the voluntary and unreasonable postponement of anticipated actions—has become a widespread concern affecting both individuals and society. Procrastination is frequently studied as an intermediary variable affecting college students’ lives and studies, such as influencing their academic performance and psychological well-being [57, 58]. A tendency toward boredom correlates with more pronounced procrastination behaviors [59]. Previous study has established a relationship between procrastination and short video addiction [60]. The fundamental usage logic of short video applications is based on a user reward model. Through positive and negative reinforcement mechanisms grounded in operant conditioning, users must consistently interact with short videos to maintain positive feelings or mitigate negative ones [22]. Task aversion, future incentives, and the temporal delay of these incentives have been identified as three primary task characteristics influencing procrastination [61]. Consequently, college students experiencing procrastination are more likely to seek rewards through short video app usage to compensate for the negative emotions stemming from delay. According to self-regulation theory, an individual’s self-regulation relies on limited resources. When boredom depletes these resources and leads to self-exhaustion, self-control diminishes, making the individual more prone to impulsive behaviors such as procrastination, which further exacerbates the tendency toward short-video addiction. Bored college students find task goals unmotivating, lose drive to act, and thus procrastinate. The incentive mechanisms of short video apps provide sufficient stimulation for college students who procrastinate, satisfying their needs and ultimately influencing the level of short video addiction among this demographic.

The study’s findings indicate that boredom affects short video addiction through physical activity. Research Hypothesis 3 is confirmed. College students experiencing high levels of boredom exhibit altered physical activity behaviors, which, in turn, affect their short video addiction. Research has shown that boredom reduces participation in exercise, partly by diminishing the perceived value of physical exertion [38]. Boredom diminishes engagement in physical activity. Studies reveal a robust negative correlation between short video addiction and physical activity levels [6]. When college students feel bored, they tend to sit or lie down, leading to reduced physical activity and making them more likely to use short-video apps. Research indicates that prioritizing homework, physical activity, and short videos can alleviate boredom [62]. As it prompts individuals to seek more valuable activities, it challenges goal-directed behavior—a phenomenon also observed in sports participation [63]. A state of boredom indicates that people’s current activities fail to meet their needs and goals in significant ways, prompting them to explore alternative ways to engage. Consequently, for college students experiencing high levels of boredom, the perceived value of physical activity diminishes. This reduction in physical activity levels leads them to choose short video applications for immediate sensory stimulation and intense value experiences, ultimately increasing their addiction to short videos. Although the indirect effect through physical activity was significant, its relatively small magnitude suggests that this pathway may warrant cautious interpretation.

Limitations and future research directions

This research is subject to certain limitations. First, cross-sectional designs only show associations between variables at a given point in time and cannot establish causality. Therefore, future studies should employ a longitudinal experimental design to elucidate the causal relationship further. Second, this study used convenience sampling, and the participants were first- to third-year undergraduate students from a single normal university. Accordingly, the external validity of the findings is limited. Future studies should employ more rigorous sampling strategies and include students from a wider range of institutions to improve the generalizability of the findings. Additionally, the online survey format used in this research may introduce potential biases. The physical activity variable may have been skewed; therefore, findings related to physical activity should be interpreted with caution. Future studies should address this issue using more appropriate measures or analytic methods. In addition, procrastination and physical activity may not be entirely independent pathways. Their significant correlation suggests possible overlap, and thus the parallel mediation model should be interpreted cautiously. The criteria for determining short video addiction among college students in research studies still need to be refined. Objective data-collection approaches can reduce these constraints in future investigations, such as tracking the actual usage time of short-video apps on mobile devices. In addition, this study primarily examines the association between boredom and short video addiction. Whether there is a bidirectional relationship between boredom and short-video addiction is also a topic worthy of future research.

Conclusion

The findings suggest that boredom among college students is associated with short video addiction both directly and indirectly through the parallel mediating roles of procrastination and physical activity. This study provides theoretical support for elucidating the psychological mechanisms linking boredom and short video addiction. Among college students, lower procrastination and higher physical activity during boredom may be associated with lower levels of short video addiction. These findings provide new insights for future prevention and intervention efforts related to short video addiction.

Authors’ contributions

Z.Z. was mainly responsible for the study design, data analysis and Writing—review and editing, Z.C. was mainly responsible for Data curation, and H.S. worked on review and editing.

Funding

This study is funded by the research start-up fund of Shangqiu Normal University.

Data availability

The datasets used during the current study available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki. Ethical approval for the study was obtained from the Research Ethics Committee of the Shangqiu Normal University on May 15, 2025 (SQNU-2025-012). All the participants received informed consent before the execution of the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.