Individual traits and experiences predict the content of dreams
Valentina Elce, Giorgia Bontempi, Serena Scarpelli, Bianca Pedreschi, Pietro Pietrini, Luigi De Gennaro, Michele Bellesi, Giulio Bernardi, Giacomo Handjaras
Communications Psychology April 28, 2026 DOI: 10.1038/s44271-026-00447-2 (opens in new tab) via OpenAlex
Summary
AI-generated from the abstractDreams are universal yet highly personal. By analyzing 3,366 reports of dreams and waking experiences from 207 adults collected between 2020 and 2024, along with demographic, cognitive, psychometric, and sleep measures, researchers found that dreams differ from waking thoughts: they are less self-referential and thought-centered, and more perceptual, dominated by visuo-spatial details, multiple characters, and bizarre events. Stable traits like attitude toward dreaming, mind-wandering propensity, and subjective sleep quality selectively influenced dream content. During the first 2020 COVID-19 lockdown, dreams from an independent dataset of 80 participants showed increased references to limitations and heightened emotional intensity, which gradually normalized over subsequent years. Stable individual traits and incidental experiences jointly shape dream semantics.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 207 |
| Population | Adults |
| Duration | 2020 to 2024 |
| Topics | Lucid dreaming |
| Keywords | Content measure theory Narrative Stressor Rumination |
| Key finding | Dreams shift from self-referential, thought-centered narratives to perceptual experiences dominated by visuo-spatial details, multiple characters, and bizarre events, and are shaped by both stable individual traits and incidental experiences. |
Abstract
Dreams are universal yet highly idiosyncratic experiences. While memories and personal concerns are known to influence dream content, how such influences evolve over time and how stable individual traits shape dreaming remain unclear. Here, we systematically quantified the semantic structure of dreams in a large, multimodal dataset comprising 3366 reports of dreams and waking experiences collected from 207 adults between 2020 and 2024, alongside demographic, cognitive, psychometric, and sleep measures. To this end, we combined large language model-assisted evaluation of hypothesis-driven semantic dimensions and a data-driven lexical domain approach. Relative to waking reports, dreams shifted from self-referential, thought-centered narratives to perceptual experiences dominated by visuo-spatial details, multiple characters, and bizarre events. Stable traits, including attitude toward dreaming, mind-wandering propensity, and subjective sleep quality, selectively influenced dream content. A second, independent dataset collected during the first 2020 COVID-19 lockdown (80 participants) allowed us to examine the impact of a major external stressor on dream semantics. During lockdown, dreams showed increased references to limitations and heightened emotional intensity, effects that gradually normalized over the following years. These findings demonstrate that stable individual traits and incidental experiences jointly shape dream semantics.