Social media reveals population dynamics of dysphoric dreaming
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study using interrupted time series analysis |
|---|---|
| Population | English-language posts from the subreddit r/Dreaming |
| Measures | Linguistic Inquiry and Word Count |
| Topics | Dreaming |
| Key findings | Nightmare frequency and dysphoric dreaming increased immediately following the WHO's pandemic declaration, as measured in social media posts, suggesting that digital dream surveillance can provide reliable population estimates. |
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.