Social media reveals population dynamics of dysphoric dreaming

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Authors: Remington Mallett, Laura Sowin, Michelle Carr
Cited by: 2
References: 31

Abstract

Nightmares disrupt sleep health and predict future psychiatric diagnoses, yet reliable population estimates and their fluctuations over time are difficult to obtain. Here, we set out to test if a digital surveillance approach could be used to observe reliable estimates of nightmare frequency and dysphoric dreaming in the general population from social media posts. English-language posts from r/Dreaming, a subreddit where users share their dreams, were analyzed using Linguistic Inquiry and Word Count to quantify nightmare frequency and anxious dreaming from text. An interrupted time series analysis was used to show that both nightmare frequency and dysphoric dreaming increased immediately following the World Health Organization's declaration of COVID-19 as a global pandemic. This observation mirrors a large body of existing work that used more traditional methods. This "digital dream surveillance" approach might offer the field of sleep medicine a low-cost and real-time system for monitoring population sleep health.

Fields of Study & Subjects

Sleep and Wakefulness Research Human Mobility and Location-Based Analysis Sleep and related disorders

Publication details

Journal / source
Sleep Epidemiology
Publisher
Elsevier BV
Volume
6
Pages
100156–100156
Publication date
4 August 2026
Language
EN