How short-video usage influences college students’ daily lives: empirical evidence from sleep, self-perception, daily life conditions, and emotional state

The rise of algorithm-driven short-video applications like TikTok, Douyin, and Kuaishou has fundamentally reshaped the digital habits of young adults globally. While general media consumption is often viewed as a benign form of entertainment, a growing body of academic research has begun to investigate the psychological and physiological consequences of problematic digital engagement. A recent empirical study conducted among 538 university students in China offers critical insights into how compulsive short-video viewing interacts with bedtime procrastination, self-control deficits, executive dysfunction, and overall emotional distress. The findings suggest that interventions targeting modern digital addiction must move beyond merely restricting screen time and instead focus on strengthening cognitive and self-regulatory capacities.

Background Context and Research Methodology

In recent years, the ubiquity of smartphones has introduced a new paradigm of digital consumption. Unlike traditional social media platforms that rely primarily on user-curated networks, modern short-video platforms utilize high-velocity, low-friction scrolling interfaces paired with persistent recommendation algorithms. These technological features are engineered to maximize user retention, often making it exceptionally difficult for individuals to disengage voluntarily.

To explore the behavioral and cognitive repercussions of this dynamic, researchers led by a team at Wenzhou University undertook a comprehensive cross-sectional study. Utilizing an anonymous online survey distributed via Sojump in late December 2025, the research team gathered data from 538 university students, predominantly situated in Henan Province. The final analytical dataset comprised responses that successfully passed rigorous data quality screens, including attention checks and completion time thresholds. The study evaluated five core psychological constructs using standardized composite scores: short-video addiction (SVA), bedtime procrastination (BP), self-control deficits (SC), executive dysfunction (ED), and emotional distress (Emo).

Key Empirical Findings and Structural Analysis

The empirical analysis revealed robust positive correlations across all major constructs. Bivariate correlation matrices indicated that short-video addiction was significantly associated with bedtime procrastination ($r = 0.696$), self-control deficits ($r = 0.619$), executive dysfunction ($r = 0.616$), and emotional distress ($r = 0.564$, all $p < 0.001$).

To untangle the complex interplay between these variables, the researchers employed a structural equation modeling (SEM) framework and hierarchical regression analysis. When examining the simultaneous predictors of emotional distress, executive dysfunction emerged as the single strongest independent correlate ($beta = 0.679, p < 0.001$). Conversely, while bedtime procrastination showed a strong zero-order correlation with emotional distress, its unique predictive power was rendered statistically insignificant ($beta = 0.018, p > 0.05$) once executive dysfunction was simultaneously accounted for in the structural model.

This statistical shift provides a nuanced perspective on digital fatigue. Although late-night scrolling inevitably disrupts sleep schedules—as reflected by the high mean score for bedtime procrastination ($M = 3.044$)—the data implies that the core psychological burden of problematic usage is more deeply tied to broader executive-regulatory deficits, such as impaired inhibitory control, working memory, and attentional regulation. Furthermore, exploratory moderation analyses suggested that individual traits like thrill-seeking may slightly amplify the vulnerability between short-video addiction and executive impairments ($beta = 0.156, p = 0.0459$), while socioeconomic indicators, such as monthly living expenses, showed no significant moderating effect.

Broader Implications for Public Health and Digital Well-Being

The implications of these findings extend far beyond academic circles, offering critical guidance for university counselors, public health officials, and platform designers. For decades, institutional responses to compulsive screen time have focused heavily on quantitative metrics—urging students to implement strict hourly limits or digital curfews. However, the Wenzhou University study argues that such one-dimensional strategies fail to address the underlying cognitive vulnerabilities that drive compulsive engagement.

Experts note that because short-video platforms continuously bombard the brain with rapid micro-rewards, they effectively train neural pathways to favor immediate gratification over sustained, goal-directed attention. Over time, this chronic exposure can exacerbate pre-existing executive dysfunctions, culminating in heightened anxiety, depressive symptoms, and general emotional distress. Consequently, campus mental health programs are increasingly urged to incorporate cognitive-behavioral training, mindfulness practices, and executive function enhancement modules into their student support frameworks.

Limitations and Future Research Directions

Despite providing valuable quantitative evidence, the study’s authors emphasize several methodological limitations that warrant cautious interpretation. Because the research relied on a cross-sectional design and self-report measures, establishing definitive causal direction or temporal sequencing remains impossible. It cannot be conclusively determined whether executive dysfunction predisposes individuals to short-video addiction, or whether prolonged compulsive viewing actively degrades cognitive control.

Additionally, the sample exhibited demographic skews, with a heavy concentration of first-year female students predominantly located in Henan Province, limiting the generalizability of the descriptive statistics to the broader national population. Future research will need to employ longitudinal tracking, objective digital telemetry (such as actual smartphone usage logs), and more geographically balanced cohorts to validate these exploratory models and better understand the dynamic feedback loops between digital media and human cognition.