Epidemiology of disturbing dreams in a diverse US sample

Factor Analysis and Validation of the Disturbing Dream and Nightmare Severity Index in an Inpatient Sample

STUDY OBJECTIVES

The Disturbing Dream and Nightmare Severity Index (DDNSI) has been used widely in research and clinical practice without psychometric evidence supporting its use in clinical samples. The present study aimed to explore and confirm the factor structure of the DDNSI in an inpatient sample. We also sought to test the measure's construct validity.

METHODS

Two samples of U.S. inpatients including adult (N = 937) and adolescent (N = 274) participants provided data on nightmares (i.e. DDNSI), sleep quality (i.e. the Pittsburgh Sleep Quality Index) and related psychopathology symptoms (e.g. depression, posttraumatic stress disorder, anxiety).

RESULTS

Exploratory and confirmatory factor analyses found the six original items of the DDNSI to load onto a single latent factor.

CONCLUSIONS

The DDNSI was found to be a valid measure of nightmare frequency and distress, as it was significantly correlated with the items related to disturbing dreams, and the DDNSI was able to differentiate between nightmares and psychopathology symptoms. Though this research comes nearly two decades after the initial creation and use of the DDNSI, it provides a foundation for the scientific rigor of previous and future studies on nightmares using the DDNSI.

Nightmare Disorder

This article presents a comprehensive review of nightmare disorder, covering diagnosis, treatment approaches, guidelines, and considerations. It begins with an introduction, defining the disorder and addressing its prevalence and psychosocial implications. The article explores assessment tools for diagnosis and then delves into psychological and pharmacologic treatment modalities, examining their efficacy and side effects. Considerations for optimizing therapeutic outcomes are highlighted, including medication versus psychotherapy, co-morbidities, cultural implications, and the use of technology and service animals. The review concludes by offering key recommendations for effective treatment and clinical care for individuals with nightmare disorder.

Neurobiology of dream activity and effects of stimulants on dreams

The sleep-wake cycle is the result of the activity of a multiple neurobiological network interaction. Dreaming feature is one interesting sleep phenomena that represents sensorial components, mostly visual perceptions, accompanied with intense emotions. Further complexity has been added to the topic of the neurobiological mechanism of dreams generation by the current data that suggests the influence of drugs on dream generation. Here, we discuss the review on some of the neurobiological mechanism of the regulation of dream activity, with special emphasis on the effects of stimulants on dreaming.

Adverse Childhood Experiences Are Associated With Adult Dream Content: A Cross-Sectional Survey

Background

Dreams can be affected by recent life events and long-term life experiences. Previous evidence has shown that childhood adverse experiences are associated with sleep quality and dream experiences.

Objective

The aim of this study was to explore the relationship between childhood adverse experiences and dream content in adults.

Participants and Setting

A total of 163 participants without current or past physical or mental disorders aged between 18 and 35 were screened in the hospital. Among them, 120 subjects who completed a dream content record at home and whose anxiety and depression levels and sleep quality were within the normal range were included in the data analysis.

Methods

A cross-sectional survey was conducted from June 2017 to December 2019. Dream content for 10 consecutive days was recorded by the participants and coded by the Hall and Van de Castle coding system. Childhood adversity was assessed by the Childhood Trauma Questionnaire (CTQ). In the end, 719 dreams out of 626 nights for 120 participants (44 female) were included in the data analysis, gender differences between groups were analyzed using t-tests or U tests, and Spearman’s partial correlation and multiple linear regression were used to investigate the relationship between childhood trauma and dream content.

Results

Childhood adversity was associated with characters, friendly interactions, and objects in dream content. Regression models of childhood adversity predicting characters and objects in dream content were constructed. There were no gender differences in general demographic data, sleep quality, emotional state, childhood adversity, dream recall frequency, or dream content.

Conclusion

Childhood adversity is associated with adult dream content.