Does insomnia treatment prevent depression?

When they just don't sleep: differential impacts of reduced child sleep on depression, anxiety, and stress among caregivers of children with and without neurogenetic syndromes

Introduction

Children with neurogenetic syndromes commonly experience significant and pervasive sleep disturbances, however, associations with caregiver mental health remains unclear. Previous studies have linked sleep disturbances with increased caregiver depression in typically developing populations, and heightened caregiver stress among neurogenetic populations. The present study expands on findings by exploring the longitudinal association between child sleep duration and caregiver mental health (depression, anxiety, stress) throughout development (infancy to school-aged children) in dyads with and without a child affected by a neurogenetic syndrome.

Methods

Participants were drawn from the Purdue Early Phenotype Study, including 193 caregivers (Age: M = 34.40 years, SD = 4.53) of children with neurogenetic syndromes (Age: M = 40.91 months, SD =20.72) and typically developing children (n = 55; Age: M = 36.71 months, SD = 20.68). Children in the neurogenetic group were diagnosed with Angelman (n = 49), Prader Willi (n = 30), Williams (n = 51), and Fragile X (n = 8) syndromes. Caregivers completed assessments every six months up to child age three, and annual assessments thereafter. Child sleep duration was measured using the Brief Infant Sleep Questionnaire, and caregiver internalizing symptoms were assessed using the Depression, Anxiety, Stress Scale. Multilevel models were conducted to examine caregiver depression, anxiety, and stress in relation to child sleep duration at both between- and within-person levels, with child age as a moderator.

Results

Results indicated a between-person effect of child sleep duration on caregiver depression (i.e., differences between families) and a within-person effect on caregiver stress (i.e., change over time) in the full, combined sample. These effects were not maintained when examined separately in neurogenetic and typically developing groups, except for a between-person effect on caregiver stress in the typically developing cohort. Moderating effects of child age were significant for depression and stress only in the typically developing cohort.

Discussion

In summary, persistent child sleep disruptions were linked to exacerbated caregiver depression across the sample, while acute child sleep disruptions exacerbate caregiver stress within dyads over time. These findings emphasize the importance of addressing child sleep to enhance caregiver wellbeing and has potential relevance for a wide range of neurogenetic syndromes.

Associations between Sleep Disturbances, Personality Traits and Self-Regulation in a Sample of Healthy Adults

Background: Scientific evidence and everyday experience show that sleep disturbances and self-regulation as a proxy of stress reactivity are linked. Particular personality traits such as neuroticism, internalizing and externalizing problems are also associated with sleep disturbances. Here, we combined self-regulation and personality traits and associated these variables with subjective sleep disturbances. Methods: A total of 846 adults (mean age: 33.7 years; 78.7% females) completed questionnaires covering sleep disturbances, self-regulation and personality traits. Results: Higher scores for sleep disturbances were associated with higher scores for externalization, internalization, and instability and with lower scores for stability (all trait variables) and with poorer self-regulation (state variable). The regression model showed that higher scores for externalization and internalization (traits), and lower scores for self-regulation (state) predicted higher scores for sleep disturbance. Next, self-regulation had both a direct effect on sleep disturbance, and an indirect effect via personality traits. Conclusions: Sleep disturbances were related to both state (i.e., self-regulation) and trait (e.g., internalization and instability) dimensions. The current data analysis leapfrogs the state-trait dichotomy discussion and reconciles the state-and-trait approach in the prediction of poor sleep, though self-regulation appeared to have both direct and indirect effects on sleep disturbances.

Sleep regulation and host genetics

Due to the multifactorial and complex nature of rest, we focus on phenotypes related to sleep. Sleep regulation is a multifactorial process. In this chapter, we focus on those phenotypes inherent to sleep that are highly prevalent in the population, and that can be modulated by lifestyle, such as sleep quality and duration, insomnia, restless leg syndrome and daytime sleepiness. We, therefore, leave in the background those phenotypes that constitute infrequent pathologies or for which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Similarly, the regulation of sleep quality is intimately linked to the regulation of the circadian rhythm. Although this relationship is discussed in the sections that require it, the in-depth study of circadian rhythm regulation at the molecular level deserves a separate chapter, and this is how it is dealt with in this volume.

The effect of single-component sleep restriction therapy on depressive symptoms: A systematic review and meta-analysis

Sleep restriction therapy is a behavioural component within cognitive behavioural therapy for insomnia and is an effective standalone treatment for insomnia, but its effect on depressive symptoms remains unclear. This review aimed to synthesise and evaluate the impact of single-component sleep restriction therapy on depressive symptoms relative to a control intervention. We searched electronic databases and sleep-related journals for randomised controlled trials and uncontrolled clinical trials, published from 1 January 1986 until 19 August 2023, that delivered sleep restriction therapy to adults with insomnia. Random-effects meta-analysis of standardised mean differences and Cochrane risk of bias assessment were performed on randomised controlled trials, while uncontrolled clinical trials were discussed narratively. The meta-analysis was pre-registered on PROSPERO (ID: CRD42020191803). We identified seven randomised controlled trials (N = 1102) and two uncontrolled clinical trials (N = 22). Findings suggest that sleep restriction therapy is associated with a medium effect for improvement in depressive symptoms at post-treatment (Nc  = 6, g = -0.45 [95% confidence interval = -0.70 to -0.21], p < 0.001) and a small effect at follow-up (Nc  = 4, g = -0.31 [95% confidence interval = -0.45 to -0.16], p < 0.001). Five of the seven included randomised controlled trials were judged to have a high risk of bias. Standalone sleep restriction therapy appears to be efficacious for improving depressive symptoms at post-treatment and follow-up. However, conclusions are tentative due to the small number of trials and because none of the trials was performed in a population with clinically defined depression. Large-scale trials are needed to test the effect of sleep restriction therapy in patients experiencing depression and insomnia. Findings also highlight the need to improve the standardisation and reporting of sleep restriction therapy procedures, and to design studies with more rigorous control arms to reduce potential bias.

Automatic Sleep Staging Based on Contextual Scalograms and Attention Convolution Neural Network Using Single-Channel EEG

Single-channel EEG based sleep staging is of interest to researchers due to its broad application prospect in daily sleep monitoring recently. We proposed using contextual scalograms as input and developed a convolutional neural network with attention modules named Co-ScaleNet for sleep staging. The contextual scalograms were obtained by combining the same color channels of three original RGB scalograms from consecutive epochs, and a simple and efficient data augmentation was designed according to their various forms. The Co-ScaleNet consists of two main parts. Firstly, three parallel convolutional branches with attention modules correspondingly extract and fuse features from contextual scalograms at the top layers. The remaining part is a stack of lightweight blocks. We achieved an overall accuracy of 87.0% for healthy individuals, 84.7% for depressed patients. And we obtained comparable performance on the public Sleep-EDFx (82.8%), ISRUC (84.6%) and SHHS datasets (87.7%), including a high recall of N1. The contextual scalograms of R channel as input achieved the best performance, which conform to the features of interest in visual scoring. The attention modules improved the recall of N1 and N3. Overall, the contextual scalograms provided a novel scheme for both contextual information extraction and data augmentation. Our study successfully expanded its application to depression datasets, as well as patients with sleep apnea, demonstrating its wide applicability.

Circadian rhythms and mood disorders: Time to see the light

The importance of time is ever prevalent in our world, and disruptions to the normal light/dark and sleep/wake cycle have now become the norm rather than the exception for a large part of it. All mood disorders, including seasonal affective disorder (SAD), major depressive disorder (MDD), and bipolar disorder (BD), are strongly associated with abnormal sleep and circadian rhythms in a variety of physiological processes. Environmental disruptions to normal sleep/wake patterns, light/dark changes, and seasonal changes can precipitate episodes. Moreover, treatments that target the circadian system have proven to be therapeutic in certain cases. This review will summarize much of our current knowledge of how these disorders associate with specific circadian phenotypes, as well as the neuronal mechanisms that link the circadian clock with mood regulation. We also discuss what has been learned from therapies that target circadian rhythms and how we may use current knowledge to develop more individually designed treatments.

Insomnia and the incidence, recurrence and persistence of common mental disorders: Sex-differences in the general population

Insomnia is common throughout the population and thought to be a risk factor for mental disorders. We assessed the association of insomnia symptoms with incidence, recurrence and persistence of mood, anxiety and substance use disorders. In 4007 participants (55 % women, mean age 51.0 ± 12.3) of the population-based Netherlands Mental Health Survey and Incidence Study (NEMESIS), having insomnia symptoms increased the odds of developing, recurring and persisting mood disorders, mostly in men. Insomnia only associated with recurring anxiety disorders, particularly in women, and not with substance use disorders. Treating insomnia may aid recovery and prevention of mental disorders, particularly mood disorders.

Relationship between fruit and vegetable consumption and internet addiction with insomnia and depression as multiple mediators during the COVID-19 pandemic: a three-wave longitudinal study in Chinese college students

BACKGROUND

The relationships between fruit and vegetable consumption (FV) and Internet addiction (IA) in college students still remained unknown together with the internal mechanisms. Given the limitations of previous cross-sectional design, longitudinal research was necessary to be conducted to explore more precise correlations. Using the three-wave data in a longitudinal design, this study aimed to explore the association between FV and IA among Chinese college students and potential multiple mediators of insomnia and depression during the COVID-19 pandemic.

METHODS

A total of 579 college students were recruited during three waves (T1: August 2020; T2: November 2020; T3: February 2021). FV (T1), insomnia (T2), depression (T2) and IA (T3) symptoms were reported. The descriptive statistics of the sociodemographic characteristics and correlation analyses of the study variables were calculated. The significance of the mediation effects was measured conducting a bootstrap method with SPSS PROCESS macro.

RESULTS

FV was negatively correlated with IA, and lower FV predicted higher risk of IA. Depression mediated the association between FV and subsequent IA. Insomnia and depression were multiple mediators, which in turn mediated the links between FV and subsequent IA.

CONCLUSIONS

The three-wave longitudinal study has revealed that FV had indirect effects on IA through individual mediating factor of depression and multiple mediating roles of insomnia and depression sequentially. The policy makers, educators and researchers should pay attention to the impact of the interventions from healthy diet, in order to optimize the coping strategies for preventing college students from IA.

Protocol for a randomised controlled trial evaluating the effect of a CBT-I smartphone application (Sleep Ninja®) on insomnia symptoms in children

BACKGROUND

Sleep is necessary for healthy development and mental wellbeing. Despite this, many children do not get the recommended duration of sleep each night, and many experience sleep problems. Although treatable, existing interventions for sleep disturbance are time-consuming, burdensome for families, and focus on providing behavioural strategies to parents rather than upskilling children directly. To address this gap, we modified Sleep Ninja®, an evidence-based cognitive behavioural therapy for insomnia (CBT-I) smartphone app for adolescent sleep disturbance, to be appropriate for 10 to 12 year olds. Here, we describe the protocol for a randomised controlled trial to evaluate the effect of Sleep Ninja on insomnia and other outcomes, including depression, anxiety, sleep quality, and daytime sleepiness, and explore effects on the emergence of Major Depressive Disorder (MDD), compared to an active control group.

METHODS

We aim to recruit 214 children aged 10 to 12 years old experiencing disturbed sleep. Participants will be screened for inclusion, complete the baseline assessment, and then be randomly allocated to receive Sleep Ninja, or digital psychoeducation flyers (active control) for 6-weeks. The primary outcome, insomnia symptoms, along with depression, anxiety, sleep quality, and daytime sleepiness will be assessed at 6-weeks (primary endpoint), 3-months, and 9-months post-baseline (secondary and tertiary endpoints, respectively). A mixed model repeated measures analytic approach will be used to conduct intention-to-treat analyses to determine whether reductions in insomnia and secondary outcomes are greater for those receiving Sleep Ninja relative to the control condition at the primary and secondary endpoints. The difference in relative risk for MDD onset will be explored at 9-months and compared between conditions.

DISCUSSION

This is the first clinical trial examining the effects of a CBT-I smartphone app in children experiencing sleep disturbance. Results will provide empirical evidence about the effects of Sleep Ninja on insomnia and other mental health outcomes.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN12623000587606).

UNIVERSAL TRIAL NUMBER

U1111-1294-4167.