Doomscrolling and Mental Fatigue: Cognitive Overload in the Era of Crisis Media

The phenomenon of doomscrolling—the compulsive consumption of negative news content through digital media—has emerged as a significant public health concern in the digital age. This paper examines the psychological and cognitive mechanisms underlying doomscrolling behavior and its relationship to mental fatigue and cognitive overload. Through analysis of recent neuropsychological research, social media usage patterns, and crisis media consumption data, this study reveals three primary pathways through which doomscrolling contributes to mental exhaustion: (1) cognitive resource depletion through continuous information processing of threatening stimuli, (2) emotional regulation breakdown resulting from sustained exposure to distressing content, and (3) attention fragmentation caused by the addictive design features of digital media platforms. The research demonstrates that doomscrolling creates a paradoxical cycle where individuals seek information to reduce uncertainty but instead experience heightened anxiety and cognitive fatigue. Drawing on cognitive load theory and dual-process models of information processing, this analysis reveals how the human brain's evolutionary threat-detection mechanisms become maladaptive in the context of infinite digital news feeds. The findings indicate that prolonged doomscrolling can lead to measurable decrements in cognitive performance, increased susceptibility to misinformation, and significant deterioration in mental health outcomes. This paper concludes with evidence-based interventions for breaking doomscrolling patterns and protecting cognitive resources in an era of unprecedented information abundance.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-10
DOI
https://doi.org/10.5281/zenodo.15627962
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Doomscrolling and Mental Fatigue: Cognitive Overload in the Era of Crisis Media

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

Doomscrolling and Mental Fatigue: Cognitive Overload in the Era of Crisis Media

article en

Abstract

The phenomenon of doomscrolling—the compulsive consumption of negative news content through digital media—has emerged as a significant public health concern in the digital age. This paper examines the psychological and cognitive mechanisms underlying doomscrolling behavior and its relationship to mental fatigue and cognitive overload. Through analysis of recent neuropsychological research, social media usage patterns, and crisis media consumption data, this study reveals three primary pathways through which doomscrolling contributes to mental exhaustion: (1) cognitive resource depletion through continuous information processing of threatening stimuli, (2) emotional regulation breakdown resulting from sustained exposure to distressing content, and (3) attention fragmentation caused by the addictive design features of digital media platforms. The research demonstrates that doomscrolling creates a paradoxical cycle where individuals seek information to reduce uncertainty but instead experience heightened anxiety and cognitive fatigue. Drawing on cognitive load theory and dual-process models of information processing, this analysis reveals how the human brain's evolutionary threat-detection mechanisms become maladaptive in the context of infinite digital news feeds. The findings indicate that prolonged doomscrolling can lead to measurable decrements in cognitive performance, increased susceptibility to misinformation, and significant deterioration in mental health outcomes. This paper concludes with evidence-based interventions for breaking doomscrolling patterns and protecting cognitive resources in an era of unprecedented information abundance.

Zenodo (CERN European Organization for Nuclear Research)
Chaudhary Charan Singh Haryana Agricultural University (IN)
Openalex Percentile: Top 53%
Computational Drug Discovery Methods
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