DARC-NESS: a mastery-based cognitive-behavioral model for treating chronic nightmares in youth
Lisa DeMarni Cromer, Emily Kaier Cromwell, Lauren Prince, Tara R. Buck
Frontiers in Sleep February 27, 2026 DOI: 10.3389/frsle.2026.1772987 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Topics | Dreaming |
| Keywords | Psychological intervention Dysfunctional family Distress Intervention counseling Mnemonic Dream Sleep system call Sleep deprivation Cognitive behavioral therapy Psychotherapist Cognition Clinical psychology Sleep disorder Sleep hygiene Cognitive therapy Cognitive model |
| Key points | Proposes that nightmare self-efficacy is a central mechanism in the maintenance of chronic nightmares, integrated into the DARC-NESS model. |
Abstract
Theories of chronic nightmare maintenance highlight dysfunctional beliefs about sleep and nightmares, distress and arousal, anticipatory anxiety, maladaptive sleep habits, and sleep deprivation as perpetuating factors that maintain nightmare disorder over time. Theories of nightmare treatment suggest that self-efficacy is a common factor in nightmare mitigation. The current article introduces DARC-NESS, a multi-component theory of nightmare maintenance that emphasizes nightmare self-efficacy as a central mechanism influencing the maintenance cycle at multiple points. DARC-NESS is a mnemonic for the model's components: Dream (nightmare) content, Appraisals, Resources for regulation, Conditioned arousal, Nightmare Efficacy, Sleep hygiene and patterns, and Sleep quality and quantity, that interact to perpetuate nightmares. This model provides the theoretical basis for cognitive behavioral therapy (CBT) for child nightmares. The manuscript proposes treatment counterparts to each model component and presents a case illustration demonstrating how these interventions can disrupt the vicious cycle of chronic nightmares. Finally, flexible clinical applications are offered to guide clinicians in selecting and sequencing modular intervention elements to match individual case presentations.