Skip to content

1197 Differentiating Typical Dreams, Disruptive Dreams, Perceived Nightmares, and True Nightmares Using Discriminant Function Analysis

Odalis G Garcia, Michael Price, Katherine A. Duggan

Sleep May 1, 2025 DOI: 10.1093/sleep/zsaf090.1197 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Observational study using self-report and dream diaries with discriminant function analysis Preregistered Peer reviewed
Sample size 53
Population Participants who self-reported psychosocial factors, sleep, and their most recent dream
Duration One week of actigraphy, sleep diaries, and dream diaries
Topics Dreaming
Key findings Dream content distinguished dream types better than chance, but not according to current clinical guidelines: true (clinical) nightmares and perceived nightmares were more similar to each other than to other categories, and grouped together were significantly more negative than disruptive and typical dreams. The authors argue the awakening criterion for nightmares is too restrictive and that intense negativity may best distinguish clinically meaningful nightmares.

Abstract

There is currently no consensus on the definition of nightmares. Most participants define nightmares as “bad dreams” with intense, distressing emotions. Per the DSM-5, nightmares are distressing dreams, but to be diagnosed with nightmare disorder, the dreams must awaken the dreamer. Surprisingly, research has not evaluated the characteristics dreamers use to categorize their nightmares. Evaluating the characteristics that distinguish between dream types can reduce ambiguity and potentially improve clinical research. In this ongoing pre-registered study, participants (n=53) self-report their psychosocial factors, sleep, and the most recent dream. Participants are given instructions to maintain actigraphy, sleep diaries, and dream diaries for one week. Thus, participants have up to 2 dream reports across the week of the study. We utilized discriminant function analysis (DFA) to describe the differences in dream content for dreams classified as true nightmares, perceived nightmares, disruptive dreams, and typical dreams. Overall, the DFA could distinguish between dream types using one canonical correlation (p<.0001) which classified dreams much better than chance. However, errors were heterogeneous and were highest for classifying true nightmares, followed by perceived nightmares (33% and 30%, respectively). Adversity, positivity, negativity, and deception were important in distinguishing dream types. Follow-up contrast analyses showed dream characteristics did not significantly differentiate true nightmares from other dream types. However, when true and perceived nightmares were grouped, they were significantly more negative than disruptive and typical dreams (p=.002). Surprisingly, there were no significant differences between dreams that woke participants up and those that did not, as well as no differences between typical dreams and all others (ps≥.08). These results suggest that dream content distinguishes dream types, but not following current clinical guidelines: true (clinical) nightmares and perceived nightmares were more similar to each other than all other categories. This implies the awakening definition of nightmares is too restrictive, and that intense negativity perhaps best distinguishes clinically-meaningful nightmares from all other dream types. The definition of nightmares is important when considering the generalizability of research and screening for nightmares at the population level. This research was supported in part by funding from the NSF GRFP and NIGMS (P30GM114748).