The longitudinal impact of life events on short-video addiction: The roles of maladaptive cognitive-emotional regulation strategies and social support

Introduction

Negative life events, such as interpersonal problems and academic setbacks, predict internet addiction among college students (Xue et al., 2025). For student groups, academic pressure and interpersonal conflicts further strengthen this relationship, making individuals more likely to rely on online activities to escape stress (Huang et al., 2025). Common stressful life events among college students include homesickness, interpersonal friction, and underachievement in academics. The mediating and moderating factors linking negative life events to short-video addiction remain underexplored. It is assumed that individuals with higher cognitive self-regulation and social support are less susceptible to such addiction. These hypotheses require empirical testing among students with frequent digital tool use. This study was conducted in the Chinese cultural context, where young students exhibit high levels of digital engagement.

Life events and short-video usage addiction risk

Stressful life events are significantly and positively correlated with internet addiction among college students, and can serve as a positive predictor of such addictive behaviors (Zhang et al., 2019). Specifically, frustrations arising from adverse life events tend to heighten individuals’ internet use tendency, which in turn elevates the risk of developing internet addiction (Aldbyani et al., 2025; Duradoni et al., 2025; Lima-Costa et al., 2024; Malas et al., 2025).

As a major type of digital platform, short video applications feature user-friendly interfaces, innovative gameplay, personalized content recommendations, and immersive sensory experiences. Such platforms can rapidly capture users’ attention and help them alleviate daily stress (Wang et al., 2021). Accordingly, college students often rely on short video applications for stress relief, a coping strategy that ultimately contributes to excessive short video use (Li et al., 2025).

Maladaptive cognitive-emotional regulation mediation

Cognitive-emotional regulation strategies are defined as cognitive and behavioral approaches. When confronted with negative life events, individuals adopt specific psychological mechanisms to adjust their cognitive patterns and thinking contents, so as to regulate emotions, and further enhance mental health and social adaptation (Garnefski et al., 2003). This regulatory strategy system is divided into adaptive and maladaptive subtypes. The current study centers on the latter, which encompasses core dimensions including self-blame, rumination, catastrophizing, and other-blame (Somayeh et al., 2014).

Maladaptive cognitive-emotional regulation strategies represent a negative response style that prevents individuals from adopting constructive coping and problem-solving methods. Research indicates that people exposed to chronic negative life events are prone to intense negative emotions and tend to rely heavily on maladaptive cognitive-emotional regulation. Furthermore, frequent use of such dysfunctional regulatory strategies is positively linked to excessive internet engagement (Gioia et al., 2021; Luo et al., 2022).

According to the cognitive-behavioral theory of internet addiction, maladaptive cognition serves as a proximal and sufficient factor in the development of internet addiction (Davis, 2001). When individuals rely on maladaptive cognition to regulate emotions, the resulting dysfunctional cognitive-emotional regulation strategies can further influence addictive internet use (Guo et al., 2023). Existing research demonstrates that maladaptive cognitive-emotional regulation strategies, such as rumination and catastrophizing, amplify negative emotions elicited by adverse life events, including depression, anxiety, and anger (Moyal et al., 2014). Such distressing emotions are key risk factors for mobile phone dependence. For example, empirical evidence suggests that individuals with elevated anxiety and depressive traits are more vulnerable to addictive behavioral patterns (Cheetham et al., 2010), which in turn increase the likelihood of short-video addiction.

Social support modulation

From the perspective of environmental factors, life events act as external stressful stimuli and have been validated as critical risk factors for addictive behaviors, including short-video addiction (Veytia-López et al., 2019). Perceived social support refers to individuals’ subjective perceptions and evaluations of available support from family, intimate partners, and significant others. Adequate social support obtained from multiple sources can effectively enhance individuals’ problem-solving capacity. An existing study has demonstrated that social support facilitates adaptive coping with stressful events and, as a protective positive resource, buffers the adverse outcomes induced by negative life experiences (Baqutayan, 2011). Featuring convenient social interaction and effective emotional catharsis, short-video platforms offer a direct outlet to satisfy unmet psychological needs. Accordingly, individuals with insufficient social support are more susceptible to excessive short-video use and subsequent addiction.

Theoretical basis

Reaction style theory posits that individual emotional responses to life events are largely shaped by coping strategies. As a detrimental response pattern, maladaptive cognitive-emotional regulation hinders people from adopting constructive problem-solving methods. Empirical evidence suggests that individuals facing chronic negative life events are more susceptible to negative affect and tend to employ maladaptive cognitive-emotional regulation strategies more frequently. In turn, habitual reliance on these dysfunctional regulatory patterns is strongly associated with excessive internet engagement (Gioia et al., 2021; Luo et al., 2022).

The Chinese context

According to the 55th Statistical Report on Internet Development in China, the number of short video users in China had reached 1.04 billion by December 2024, accounting for 93.8% of the country’s total internet users. College students represent the core user group of mobile short video platforms (Ye et al., 2024). Relevant empirical research further indicates that this group serves as a key driving force for the development of the short-video industry (Mou et al., 2021).

Goals of the Study

With the rapid iteration of information technology and the continuous expansion of the internet ecosystem, adolescents nowadays have access to increasingly diverse digital lifestyles. They utilize online resources to meet their needs in entertainment, social interaction, and learning. Among various online activities, browsing and creating short videos has become a dominant form of daily leisure entertainment. Figure 1 presents the hypothetical model underlying the following hypotheses:

Figure 1. Hypothetical model diagram. Note. CERS = Cognitive-Emotional Regulation Strategies.

Hypothesis 1: Life events can positively predict short-video addiction.

Hypothesis 2: Maladaptive cognitive-emotional regulation strategies mediate the relationship between life events and short-video addiction for higher levels of short-video addiction.

Hypothesis 3: Social support plays a moderating role in the relationship between life events and short-video addiction. As social support increases, the predictive effect of life events on short-video addiction weakens.

This study aims to explore the predictive effect of life events on college students’ short-video addiction. Its findings offer practical implications for guiding college students to reduce maladaptive cognitive-emotional regulation and mitigate problematic short-video overuse.

Methods

Research design

This study employed a two-wave longitudinal design to examine the mediating effect of maladaptive cognitive-emotional regulation strategies on the association between negative life events and short-video addiction, as well as the moderating role of perceived social support. Data were collected at two time points (T1 and T2) across a six-month interval, enabling an investigation of the dynamic associations and underlying mechanisms between the core study variables.

Participants and setting

Participants were 501 students from a university in Anhui Province, China. The age range was 17 to 23 years (M = 18.89; SD = 0.98), with 60.28% male participants. The attrition rate was 4.93%. No statistically significant differences were found between the attrited participants and valid follow-up participants in total scores of life events (t = −1.26, p > 0.05), short-video addiction (t = 1.64, p > 0.05), maladaptive cognitive-emotional regulation strategies (t = 0.12, p > 0.05), or social support (t = −0.36, p > 0.05) at the T1 stage.

Measures

Participants completed survey measures on two occasions (TI, T2) in September 2024 (T1) and March 2025 (T2), as follows: life events, short-video addiction, maladaptive cognitive-emotional regulation strategies, and social support. We briefly describe these next.

Life events scale

The Self-Rating Life Events Scale (Liu et al., 1997) consists of 27 items organized into six factors: interpersonal relationships (5 items, e.g., “Be misunderstood or wrongly blamed”), academic stress (5 items, e.g., “Heavy academic burden”), punishment (7 items, e.g., “Be criticized or punished”), loss (3 items, e.g., “A relative or friend is seriously ill”), health adaptation (4 items, e.g., “Being away from family for a long time and unable to reunite”), and others. Items are on a 5-point Likert scale (1 = no impact, 5 = extremely severe impact). Higher scores on each dimension indicate greater psychological negative reactions. The scale has demonstrated good reliability and validity in previous studies (Liu et al., 1997). In the present study, the Cronbach’s α coefficients of the scale at T1 and T2 were 0.93 and 0.96, respectively, and the ω coefficients were 0.93 and 0.96, respectively.

Short-video addiction scale

The Short-Video Scale (Zhang et al., 2019) comprises 6 items rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Sample items are “Spending too much time on short videos has led to insomnia” and “Short videos have disrupted my normal social interactions”. Higher scores indicate a higher level of short-video addiction. The scale has shown good reliability and validity in previous university student research (Zhang et al., 2019). In the present study, the Cronbach’s α coefficients of the scale at T1 and T2 were 0.83 and 0.90, respectively, and the ω coefficients were 0.83 and 0.90, respectively.

Maladaptive cognitive-emotional regulation strategies scale

The Chinese version of the Cognitive Emotion Regulation Questionnaire (Zhu et al., 2007) comprises 16 items across four dimensions: self-blame (4 items, e.g., “I feel that I should be blamed”), rumination (4 items, e.g., “I am immersed in the feelings and thoughts about the things I have already experienced”), catastrophizing (4 items, e.g., “I keep thinking about how terrifying this matter is”), and other-blame. Responses are scores on a 5-point Likert scale (1 = never, 5 = always). The scale has exhibited good psychometric properties in prior university student research (Zhu et al., 2007). In the present study, the Cronbach’s α coefficients of the scale at T1 and T2 were 0.86 and 0.92, respectively, and the ω coefficients were 0.86 and 0.92, respectively.

Perceived social support scale

The Chinese version of the Perceived Social Support Scale (PSSS Dahlem et al., 1991 and revised by Jiang (1999)), comprizes 12 items across three dimensions: family support (4 items, e.g., “My family can indeed offer me specific assistance”), friend support (4 items, e.g., “My friends can truly help me”), and other support (4 items, e.g., “I can share happiness and sadness with some people (teachers, classmates, relatives)”). Considering the social context of university students and referring to the research of Yan and Zheng (2006), the “other support” dimension was modified by replacing “leaders, relatives, colleagues” with “teachers, classmates, relatives.” Responses are scored on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree), with higher scores indicating higher perceived social support. The scale has demonstrated good reliability and validity in previous studies on university students (Yan & Zheng, 2006). The construct validity of the Perceived Social Support Scale was analyzed, and the fitting index was acceptable: χ2/df = 3.06, CFI = 0.97, TLI = 0.96, IFI = 0.97, RMSEA = 0.06. In the present study, the Cronbach’s α coefficients of the scale at T1 and T2 were 0.93 and 0.96, respectively, and the ω coefficients were 0.93 and 0.96, respectively.

Procedure

All procedures involving human participants in this study were conducted in accordance with the ethical standards of institutional research committees, the 1964 Helsinki Declaration and its subsequent revisions, as well as other relevant ethical guidelines. This research was formally approved by the Academic Committee of the School of Teacher Education of Chaohu University (No.: 0600001). Prior to participation, all participants provided informed consent and received a small souvenir as compensation for their time. Participation was entirely voluntary. Participants were fully informed of data confidentiality protections and their right to withdraw from the survey at any time without penalty. In addition, participants were permitted to access the overall research findings upon completion of the study.

Data analysis

This study conducted data analysis using SPSS 26.0 and Mplus 8.3. First, descriptive statistics were calculated to describe the distribution of all study variables, and Pearson correlation analysis was adopted to examine the bivariate associations among core variables. Second, longitudinal mediation analysis was performed to verify the mediating effect of friendship quality on the association between family function and problematic smartphone use. Third, structural equation modeling (SEM) was established via Mplus 8.3 to test the moderating effect of gender on the hypothesized pathways.

Common method bias

To mitigate potential common method bias in this study, several procedural and statistical controls were adopted. First, participants were recruited across different grades, majors, and genders. Reverse-scored items were incorporated into the questionnaire, and all surveys were completed anonymously in paper-and-pencil format. Second, data collection was conducted at separate time points to reduce response consistency bias. Third, confirmatory factor analysis was performed to examine common method bias across all self-reported scales. The results showed that the model fit was poor: χ2/df = 4.50, CFI = 0.30, TLI = 0.29, RMSEA = 0.08, SRMR = 0.11. Collectively, these findings indicated that severe common method bias was not present in the current dataset.

Results

Descriptive statistics and correlation analysis

Pearson correlation analyses were conducted to examine the relationships among the key variables, with the means, standard deviations, and correlation matrix of all main variables presented in Table 1. The correlation results indicated the following: (1) Life events at Time 1 (T1) were significantly and positively correlated with maladaptive cognitive-emotional regulation strategies at both Time 1 (T1) and Time 2 (T2); (2) Life events at T1 also showed a significant positive correlation with short-video addiction at T1 and T2; (3) Maladaptive cognitive-emotional regulation strategies at T1 were significantly positively correlated with short-video addiction at both T1 and T2; (4) Social support at T1 exhibited a significant negative correlation with short-video addiction at T1 and T2.

Longitudinal mediating effect of maladaptive cognitive-emotional regulation strategies

To explore the relationship among life events, maladaptive cognitive-emotional regulation strategies, and short-video addiction, a first-order lag model was constructed using Mplus 8.3 to test the longitudinal mediation model. The model fit was approximately acceptable: χ²/df = 5.71, CFI = 0.99, TLI = 0.91, SRMR = 0.02, RMSEA = 0.09. As shown in Figure 2, after controlling for maladaptive cognitive-emotional regulation strategies at T1, life events at T1 significantly predicted maladaptive cognitive-emotional regulation strategies at T2 positively (β = 0.21, p < 0.001, 95%CI [0.12, 0.29]). After controlling for short-video addiction at T1, maladaptive cognitive-emotional regulation strategies at T1 significantly predicted short-video addiction at T2 positively (β = 0.21, p < 0.001, 95%CI [0.12, 0.29]), indicating that both the first-half and second-half paths of the longitudinal mediation were significant. Thus, maladaptive cognitive-emotional regulation strategies mediated the relationship between life events and short-video addiction, with a longitudinal mediating effect of 0.04 (95%CI [0.01, 0.02]). Life events at T1 significantly predicted short-video addiction at T2 positively (β = 0.20, p < 0.001, 95%CI [0.11, 0.28]), indicating a significant direct effect of life events on short-video addiction. Furthermore, when the maladaptive cognitive-emotional regulation strategy T1 was not involved as a mediator, life events T1 significantly positively predicted short-video addiction T2. The total effect size β = 0.40 (p < 0.001, 95%CI [0.32, 0.47]). Hypothesis 1 was supported.

Figure 2. The longitudinal mediating role of maladaptive cognitive emotion regulation strategies. Note. CERS = Cognitive-Emotional Regulation Strategies. ***p < 0.001.

Social support: Moderating effect

To further explore whether the mediating process through which life events influence short-video addiction after 6 months is moderated by social support, a moderated mediation model was constructed by incorporating life events at T1, social support at T1, maladaptive cognitive-emotional regulation strategies at T1, and short-video addiction at T2, considering the longitudinal causal logic where antecedent and outcome variables have a temporal sequence. The model fit was approximately acceptable: χ²/df = 5.24, CFI = 0.94, TLI = 0.90, SRMR = 0.04, RMSEA = 0.09. As shown in Figure 3, the interaction term of life events at T1 and social support at T1 significantly predicted short-video addiction at T2 negatively (β = −0.09, p < 0.05, 95%CI [−0.16, −0.02]). The results indicated that social support significantly moderated the relationship between life events and short-video addiction, i.e., the direct path of the mediation. Hypothesis 2 was supported.

Figure 3. The longitudinal mediating role of maladaptive cognitive emotion regulation strategies. Note. CERS = Cognitive-Emotional Regulation Strategies. *p < 0.05, ***p < 0.001.

To visualize the moderating effect, social support was categorized into high and low groups following the criterion of one standard deviation above and below the mean, respectively (see Figure 4). A simple slope analysis was further conducted to examine the conditional effects of life events on short-video addiction across the two groups. Results indicated that: (1) In the low social support group, life events exerted a significant positive predictive effect on short-video addiction (βsimple = 0.40, t = 7.73, p < 0.001); (2) In the high social support group, the predictive effect of life events on short-video addiction weakened (βsimple = 0.27, t = 5.04, p < 0.001).

Figure 4. The longitudinal mediating role of maladaptive cognitive emotion regulation strategies

Discussion

The results of this study revealed that stressful life events are positively associated with increased short-video addiction among college students. This result aligns with a previous longitudinal study, which demonstrated that life events positively predict problematic internet use in adolescents (Zhang & Li, 2022). Nevertheless, the prior research failed to control for baseline problematic internet use at Time 1, thereby limiting its empirical credibility. By contrast, the current study adopted a first-order cross-lagged panel model and adjusted for short-video addiction levels at Time 1, effectively enhancing the reliability and validity of our findings. Furthermore, another recent study also confirmed the predictive effect of life stressors on adolescent internet addiction (Lv et al., 2025). On the basis of existing literature, the present study further narrowed down the scope of addictive internet behaviors and focused specifically on short-video addiction, a prevalent and time-sensitive behavioral issue in the digital era.

This study demonstrates that maladaptive cognitive-emotional regulation strategies exert a partial mediating effect between college students’ stressful life events and short-video addiction. From the perspective of emotional regulation decompensation, individuals exposed to intense life events tend to engage in maladaptive cognitive processing if they have not developed adequate adaptive emotion regulation skills in early socialization (Guo et al., 2023). Furthermore, the use of maladaptive cognitive-emotional regulation strategies, such as other-blame, strengthens hostile perceptions of the external world and intensifies social avoidance tendencies (Read et al., 2018). Short-video platforms, driven by algorithmic recommendation mechanisms, establish a selective information filtering system that offers low-risk alternative social options for vulnerable individuals. Excessive engagement in such virtual interactions gradually impairs real-life social competence, which in turn fosters a vicious behavioral cycle and ultimately exacerbates short-video addiction (Liu et al., 2025).

This study reveals that social support serves as a significant moderator in the association between life events and short-video addiction. Social support is crucial for individuals’ healthy development and buffers the adverse outcomes induced by stressful life events. Consistent with prior evidence, perceived social support effectively moderates the link between negative life events and adolescent depression (Miloseva et al., 2017). Furthermore, individuals with higher levels of perceived social support tend to employ positive coping strategies when facing stress (Alenezi et al., 2026). In contrast, those who lack adequate social support and interpersonal understanding are more inclined to engage in maladaptive coping behaviors, including excessive short-video addiction (Zhao & Kou, 2024).

Implications for Theory, Research, and Practice

The findings of this study provide empirical evidence for the cognitive-behavioral model of addiction. This theoretical framework highlights that chronic environmental stress functions as a core trigger of addictive behaviors. To cope with real-life frustrations, individuals tend to engage in addictive behaviors as a maladaptive coping strategy (Davis, 2001). Negative life experiences, including academic pressure and interpersonal conflicts, can induce intense negative emotions among college students. The cumulative psychological burden thereby constitutes a prominent stressor for this population (Chiu, 2014).

This study also carries important practical implications. First, greater attention should be paid to college students’ stressful life events, which profoundly affect their academic performance and daily functioning. Families and educational institutions ought to offer timely care and guidance, helping students cope with adversities and adjust to difficulties in a positive manner. Second, university administrators and mental health service centers should deliver targeted emotional counseling for students exposed to negative life events. Combined with cognitive-behavioral intervention, professional guidance can assist students in reducing maladaptive cognitive-emotional regulation and adopting more adaptive regulatory strategies. Third, college counselors are advised to organize diverse group activities to strengthen students’ social support resources. Adequate social support can further alleviate the risk of short-video addiction among college students.

Limitations and Future Directions

This study also has some limitations. First, concerning the mediating mechanism, maladaptive cognitive-emotional regulation exerted only a partial mediating effect with a small effect size, implying that additional mediating variables may be involved in this relational pathway. Future research could further explore other potential mediators. Second, the research sample was geographically confined, restricting population representativeness. Subsequent studies may adopt nationwide sampling to improve the generalizability of the results. Third, short-video addiction was measured solely through self-report questionnaires, which are susceptible to subjective response bias. Future research should incorporate objective assessment tools to achieve a more accurate evaluation of short-video addiction severity.

Conclusions

Adopting a longitudinal design, this study yielded two key findings. First, stressful life events significantly predict college students’ short-video addiction, and this predictive association is mediated by maladaptive cognitive-emotional regulation strategies. Second, social support acts as a critical moderator in the link between life events and short-video addiction. Overall, these findings enrich the existing literature by offering new evidence regarding the internal mechanisms and boundary conditions of college students’ short-video addiction, thereby presenting important theoretical contributions and empirical value.

Acknowledgement: Thanks to all students and researchers who were involved in the study for their inputs.

Funding Statement: This research was funded by 2024 University-Level Teaching Reform and Research Project of Chaohu University (x24jyxm15), 2024 Annual Provincial Quality Engineering Project of Anhui Higher Education Institutions (2024dzxkc115).

Author Contributions: The authors confirm contribution to the paper as follows: study conception and design: Wangyan Ma; data collection: Yuanyuan Xie, Mengran Gao; analysis and interpretation of results: Mengying Huang, Liyang Sixu; draft manuscript preparation: Jinliang Guan. All authors reviewed and approved the final version of the manuscript.

Availability of Data and Materials: The data that support the findings of this study are available from the Corresponding Author, [Wangyan Ma], upon reasonable request.

Ethics Approval: This study was conducted in accordance with the Declaration of Helsinki, and approved by the Academic Committee of School of Teacher Education of Chaohu University (No.: 0600001). Informed consent was obtained from all individual participants included in the study.

Conflicts of Interest: The authors declare no conflicts of interest.

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