In an era dominated by digital consumption, the rise of short-form video platforms such as TikTok, Instagram Reels, and YouTube Shorts has revolutionized how content is consumed and produced. Yet, while these platforms offer endless streams of engaging media, emerging research reveals a concerning link between problematic use of short-form video and deficits in cognitive control. A recent study led by Zhu, Fong, and Wu employs sophisticated eye-tracking technology alongside the drift–diffusion model to unravel the cognitive mechanisms impaired in individuals exhibiting problematic engagement with these bite-sized videos.
Cognitive control, the faculty allowing individuals to regulate thoughts, emotions, and actions in accordance with internal goals, is pivotal for adaptive functioning. Heightened exposure to short-form videos, characterized by rapid image transitions and immediate gratification, potentially taxes this control system, leading to attentional lapses and diminished inhibitory control. Zhu and colleagues’ work uses empirical methodologies to clearly demonstrate that individuals who exhibit problematic consumption patterns of short-form video content have measurable dysfunction in these cognitive control processes.
The study’s innovation lies in integrating eye-tracking data with computational modeling provided by the drift–diffusion framework. Eye-tracking provides direct, real-time measurement of visual attention and saccadic movements, which are key proxies for cognitive control and executive function. Meanwhile, the drift–diffusion model mathematically decomposes decision-making processes into parameters that reflect the speed and quality of information accumulation, as well as boundary settings representing decision caution. By combining these techniques, the research elucidates both the overt attentional behavior and the underlying decision-making deficits associated with problematic short-form video use.
Participants recruited for this study were assessed through a battery of neuropsychological and behavioral scales to quantify problematic use alongside detailed eye-tracking sessions. During specific cognitive control paradigms, participants’ gaze trajectories were recorded to monitor fixation duration, gaze shifts, and susceptibility to distraction by emotionally salient stimuli embedded within the stimuli. From these measurements, substantial differences emerged between high-risk individuals and control groups, indicating a reduced ability for sustained attention and inhibitory control during task performance.
Crucially, the drift–diffusion modeling parameter estimates revealed slowed drift rates and lowered decision thresholds among those with problematic short-form video use. The slower drift rate suggests deficits in efficient evidence accumulation when performing cognitive tasks, indicating that information processing is less steady and more error-prone. Reduced decision thresholds further imply an impulsivity bias, manifesting as a readiness to commit to decisions without adequate deliberation. These findings paint a comprehensive picture of impaired cognitive regulation in this cohort aligned with neurocognitive theories of addiction and behavioral dysregulation.
Beyond advancing mechanistic understanding, this research signals potential implications for clinical interventions and digital well-being strategies. Insight into the cognitive control signatures underlying problematic short-form video use can guide the development of tailored cognitive training programs that reinforce executive function. Additionally, platform designers might incorporate features that mitigate compulsive engagement, such as enforced micro-breaks or attentional nudges informed by real-time eye movement data metrics extracted during app usage.
The pervasive appeal of short-form videos is often credited to their dopamine-triggering reward cycles, yet this study highlights a double-edged consequence: the constant barrage of highly stimulating content erodes the very cognitive faculties necessary to regulate consumption. The rapid, fragmented nature of short-form content appears to foster a cycle in which users increasingly lose control over their attentional resources, supporting a neurobehavioral feedback loop akin to substance-related disorders but uniquely situated in digital behavioral addiction.
Zhu, Fong, and Wu’s rigorous experimental design also enables differentiation between attentional deficits stemming from general distraction and those specifically attributable to addictive patterns of use. By controlling for baseline cognitive function and comorbid symptomatology, their findings validate that the observed impairments are not mere correlates of typical video consumption, but specific markers of problematic engagement. This distinction is critical in an era where excessive screen time is commonplace but does not uniformly result in clinical impairment.
Furthermore, the incorporation of eye-tracking technology offers unprecedented granularity in assessing the temporal dynamics of attentional capture and disengagement. The data indicate that problematic users have prolonged fixations on salient cues but struggle to shift attention adaptively, a phenomenon echoing the ‘attentional bias’ observed in substance use disorders. This parallel underscores the neurocognitive similarities between digital addiction and classical addiction frameworks, potentially influencing future diagnostic criteria and treatment modalities.
One of the remarkable facets of this research is the scalability of its methodological approach. Eye-tracking sensors are increasingly embedded in consumer devices, suggesting that future applications could include passive monitoring of cognitive control states in real time. When integrated with predictive models like drift–diffusion, these tools could offer early warning signals for escalating problematic use, enabling timely intervention before more severe consequences manifest.
Critics might argue that the field must carefully balance acknowledging risks while not pathologizing typical media use in a digitally native generation. However, Zhu and colleagues address this tension by emphasizing the spectrum of use—from healthy engagement to disordered patterns—supported by precise neurocognitive profiling. This nuance enriches public discourse by moving beyond binary perspectives on technology usage toward data-driven, individualized assessments.
The implications of these findings extend beyond mental health alone, with potential ripple effects impacting educational outcomes and workplace productivity. Cognitive control deficits linked to compulsive short-form video consumption could impair learning, memory consolidation, and task completion, posing unique challenges in academic and professional environments increasingly reliant on sustained focus amidst digital distractions.
In addition to advancing theoretical knowledge, this study offers concrete pathways for interdisciplinary collaboration. Neuroscientists, clinicians, technologists, and behavioral scientists can converge to develop evidence-based policies and tools that foster healthier digital ecosystems. From algorithmic adjustments reducing addictive content reinforcement to cognitive training apps informed by eye-tracking derived biomarkers, opportunities abound to translate these insights into scalable, impactful interventions.
Ultimately, Zhu, Fong, and Wu’s investigation serves as a clarion call to public health stakeholders on the urgent need to understand and mitigate the cognitive hazards born from short-form video platforms. Their data-driven approach exemplifies the power of combining cutting-edge technology with nuanced modeling to decode the complexities of digital behavioral addiction—illuminating new frontiers in mental health research shaped by the digital age.
As attention allocation becomes an increasingly scarce cognitive resource, the clarity brought forth by this study underscores a pivotal battleground: our ability to master digital temptations through strengthened cognitive control could define not only individual well-being but also collective societal functioning in a hyper-connected world.
In conclusion, the fusion of eye-tracking and drift–diffusion modeling represents a transformative advance in dissecting the nuanced cognitive disturbances induced by problematic short-form video consumption. This research not only expands the scientific understanding of digital behavioral addictions but also charts a course toward innovative clinical and technological solutions to preserve cognitive health in an ever-evolving media landscape.
Subject of Research: Cognitive control deficits associated with problematic use of short-form video content.
Article Title: Cognitive Control Deficits in Individuals with Problematic Use of Short-Form Video: Evidence from an Eye-Tracking Study and the Drift–Diffusion Model.
Article References:
Zhu, J., Fong, L.H.N. & Wu, A.M.S. Cognitive Control Deficits in Individuals with Problematic Use of Short-Form Video: Evidence from an Eye-Tracking Study and the Drift–Diffusion Model. Int J Ment Health Addiction (2025). https://doi.org/10.1007/s11469-025-01585-0
Image Credits: AI Generated
