Prevalence and correlates of sleep disorder symptoms in psychiatric disorders

Predicting long-term sleep deprivation using wearable sensors and health surveys

Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have significant negative impacts on our attention, cognition, and mood. The measurement of sleep from in-bed physiological signals has progressed to where commercial devices already incorporate this functionality. However, the prediction of sleep duration from previous awake activity is less studied. Previous studies have used daily exercise summaries, actigraph data, and pedometer data to predict sleep during individual nights. Building upon these, this article demonstrates how to predict a person's long-term average sleep length over the course of 30 days from Fitbit-recorded physical activity data alongside self-report surveys. Recursive Feature Elimination with Random Forest (RFE-RF) is used to extract the feature sets used by the machine learning models, and sex differences in the feature sets and performances of different machine learning models are then examined. The feature selection process demonstrates that previous sleep patterns and physical exercise are the most relevant kind of features for predicting sleep. Personality and depression metrics were also found to be relevant. When attempting to classify individuals as being long-term sleep-deprived, good performance was achieved across both the male, female, and combined data sets, with the highest-performing model achieving an AUC of 0.9762. The best-performing regression model for predicting the average nightly sleep time achieved an R-squared of 0.6861, with other models achieving similar results. When attempting to predict if a person who previously was obtaining sufficient sleep would become sleep-deprived, the best-performing model obtained an AUC of 0.9448.

Neocortical long-range inhibition promotes cortical synchrony and sleep

Behavioral states such as sleep and wake are highly correlated with specific patterns of rhythmic activity in the cortex. During low arousal states such as slow wave sleep, the cortex is synchronized and dominated by low frequency rhythms coordinated across multiple regions. Although recent evidence suggests that GABAergic inhibitory neurons are key players in cortical state modulation, the in vivo circuit mechanisms coordinating synchronized activity among local and distant neocortical networks are not well understood. Here, we show that somatostatin and chondrolectin co-expressing cells (Sst-Chodl cells), a sparse and unique class of neocortical inhibitory neurons, are selectively active during low arousal states and are largely silent during periods of high arousal. In contrast to other neocortical inhibitory neurons, we show these neurons have long-range axons that project across neocortical areas. Activation of Sst-Chodl cells is sufficient to promote synchronized cortical states characteristic of low arousal, with increased spike co-firing and low frequency brain rhythms, and to alter behavioral states by promoting sleep. Contrary to the prevailing belief that sleep is exclusively driven by subcortical mechanisms, our findings reveal that these long-range inhibitory neurons not only track changes in behavioral state but are sufficient to induce both sleep-like cortical states and sleep behavior, establishing a crucial circuit component in regulating behavioral states.

Sleep disruptions and the pathway to psychosis: An in-depth case and literature review

Key Clinical Message

The case highlights an unusual presentation where sleep issues preceded psychotic symptoms, implying link between disrupted sleep and psychosis onset. Earlier symptoms were viewed as depression but may have signaled psychosis exacerbated by insomnia.

Abstract

Sleep disorders, prevalent yet frequently overlooked in individuals with psychotic disorders, have significant associations with the onset and severity of psychosis. Here we describe the case of a patient who first presented with insomnia, but whose condition improved with the use of risperidone and was diagnosed with first-episode psychosis. Multiple studies emphasize the critical relationship between sleep disturbances and psychosis, particularly in the lead-up to first-episode psychosis. Structural abnormalities in the brain, notably the thalamus, combined with neurotransmitter imbalances involving dopamine and acetylcholine, seem pivotal in this interrelation. The connection between dopamine, sleep disturbances, and psychosis, specifically the role of D2 dopamine receptors, highlights a potential pathway bridging sleep irregularities with psychosis. The study underscores the need for further research to delineate the relationship between sleep disturbances and psychosis and to assess the efficacy of various therapeutic interventions targeting both conditions.

Brief Psychoeducational and Cognitive Therapy for Nightmare Disorder (BPCT-ND)

In adults, nightmare disorder is related to sleep deprivation, drug consumption or abuse, or other comorbid sleep disorders such as insomnia or insufficient sleep syndrome. Behavioral treatment has solid scientific evidence in disorders such as insomnia and, more recently, parasomnias. The aim of the present study was to investigate the clinical effectiveness of a Brief Behavioral Telemedicine Therapy in Nightmare Disorder in a 23-year-old female patient. The procedure consisted of the case study, with pre and posttreatment measures as well as follow-up after 1 month; and the Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Paris Arousal Disorders Severity Scale, and a sleep diary were applied. In parallel with changes recorded in the sleep diary, a decrease in nightmares, sleepiness, and insomnia symptoms was observed when the intervention was finished. The behavioral intervention was clinically effective; therefore, the present case report provides information on behavioral treatments for nightmare disorder.

Device-assessed physical activity and sleep quality of post-COVID patients undergoing a rehabilitation program

BACKGROUND

An infection with SARS-CoV-2 can lead to persistent symptoms more than three months after the acute infection and has also an impact on patients' physical activity behaviour and sleep quality. There is evidence, that inpatient post-COVID rehabilitation can improve physical capacity and mental health impairments, but less is known about the change in physical behaviour and sleep quality.

METHODS

This longitudinal observational study used accelerometery to assess the level of physical activity and sleep quality before and after an inpatient rehabilitation program. The study sample consists of 100 post-COVID patients who acquired COVID-19 in the workplace. Group differences related to sex, age, COVID-19 severity, and pre-existing diseases were also analysed.

RESULTS

Level of physical activity and sleep quality didn't increase after rehabilitation. Overall, there is a high extent of inactivity time and poor sleep quality at both measurement points. Regarding group differences, male patients showed a significantly higher inactivity time before rehabilitation, and younger patients (< 55 years) spend significant more time in vigorous physical activity than older patients. Post-COVID patients with pre-existing cardiovascular, respiratory, and metabolic disease show slightly less physical activity than post-COVID patients without these comorbidities. Female patients and younger patients showed better sleep quality in some sleep parameters at both measurement points. However, no differences could be detected related to COVID-19 severity.

CONCLUSIONS

Ongoing strategies should be implemented to address the high amount of inactivity time and the poor sleep quality in post-COVID patients.

Sleep disorders in a naturalistic cohort of Dutch psychiatric outpatients: prevalence rates and associations with psychopathology symptom severity and well-being

Sleep problems are very common in individuals with a mental disorder. Given the abundant evidence indicating the negative impact of disturbed sleep on mental health outcome, insight into the prevalence of all types of sleep disorders in specific mental disorders and neurodevelopmental conditions is of practical importance. Therefore, we estimated the prevalence of six types of sleep disorders with the Holland Sleep Disorders Questionnaire in an overall mental health sample (n = 1082) and separately for different mental and neurodevelopmental conditions. Furthermore, associations between specific sleep disorders, psychopathology and well-being were studied. The impact of the total number of sleep disorders on these associations was examined. Overall, 46.2% of all participants scored above the cut-off for having a sleep disorder. Specifically, 26.8% scored on insomnia, 12.1% on sleep breathing disorders, 9.7% on hypersomnia, 13.7% on circadian rhythm sleep-wake disorders, 11.2% on parasomnia, and 17.9% on sleep-related movement disorders. Most sleep disorders were associated with greater severity of psychopathology and lower well-being. These associations got stronger with an increasing number of sleep disorders. Our study revealed higher suspected prevalence of most sleep disorders in a mental disorder sample compared to the general population. Moreover, the presence of sleep disorder(s) was strongly associated with symptom severity and reduced well-being. These findings extend the notion that early detection and treatment of sleep disorders in mental health populations is essential for psychiatric outcome.

UNC5C: Novel Gene Associated with Psychiatric Disorders Impacts Dysregulation of Axon Guidance Pathways

The UNC-5 family of netrin receptor genes, predominantly expressed in brain tissues, plays a pivotal role in various neuronal processes. Mutations in genes involved in axon development contribute to a wide spectrum of human diseases, including developmental, neuropsychiatric, and neurodegenerative disorders. The NTN1/DCC signaling pathway, interacting with UNC5C, plays a crucial role in central nervous system axon guidance and has been associated with psychiatric disorders during adolescence in humans. Whole-exome sequencing analysis unveiled two compound heterozygous causative mutations within the UNC5C gene in a patient diagnosed with psychiatric disorders. In silico analysis demonstrated that neither of the observed variants affected the allosteric linkage between UNC5C and NTN1. In fact, these mutations are located within crucial cytoplasmic domains, specifically ZU5 and the region required for the netrin-mediated axon repulsion of neuronal growth cones. These domains play a critical role in forming the supramodular protein structure and directly interact with microtubules, thereby ensuring the functionality of the axon repulsion process. We emphasize that these mutations disrupt the aforementioned processes, thereby associating the UNC5C gene with psychiatric disorders for the first time and expanding the number of genes related to psychiatric disorders. Further research is required to validate the correlation of the UNC5C gene with psychiatric disorders, but we suggest including it in the genetic analysis of patients with psychiatric disorders.

Sleep, mood disorders, and the ketogenic diet: potential therapeutic targets for bipolar disorder and schizophrenia

Bipolar disorder and schizophrenia are serious psychiatric conditions that cause a significant reduction in quality of life and shortened life expectancy. Treatments including medications and psychosocial support exist, but many people with these disorders still struggle to participate in society and some are resistant to current therapies. Although the exact pathophysiology of bipolar disorder and schizophrenia remains unclear, increasing evidence supports the role of oxidative stress and redox dysregulation as underlying mechanisms. Oxidative stress is an imbalance between the production of reactive oxygen species generated by metabolic processes and antioxidant systems that can cause damage to lipids, proteins, and DNA. Sleep is a critical regulator of metabolic homeostasis and oxidative stress. Disruption of sleep and circadian rhythms contribute to the onset and progression of bipolar disorder and schizophrenia and these disorders often coexist with sleep disorders. Furthermore, sleep deprivation has been associated with increased oxidative stress and worsening mood symptoms. Dysfunctional brain metabolism can be improved by fatty acid derived ketones as the brain readily uses both ketones and glucose as fuel. Ketones have been helpful in many neurological disorders including epilepsy and Alzheimer's disease. Recent clinical trials using the ketogenic diet suggest positive improvement in symptoms for bipolar disorder and schizophrenia as well. The improvement in psychiatric symptoms from the ketogenic diet is thought to be linked, in part, to restoration of mitochondrial function. These findings encourage further randomized controlled clinical trials, as well as biochemical and mechanistic investigation into the role of metabolism and sleep in psychiatric disorders. This narrative review seeks to clarify the intricate relationship between brain metabolism, sleep, and psychiatric disorders. The review will delve into the initial promising effects of the ketogenic diet on mood stability, examining evidence from both human and animal models of bipolar disorder and schizophrenia. The article concludes with a summary of the current state of affairs and encouragement for future research focused on the role of metabolism and sleep in mood disorders.

Exercising healthy behaviors: A latent class analysis of positive coping during the COVID-19 pandemic and associations with alcohol-related and mental health outcomes

OBJECTIVE

To identify latent classes of positive coping behaviors during the COVID-19 pandemic and examine associations with alcohol-related and mental health outcomes across participants with and without a history of alcohol use disorder (AUD).

METHODS

Baseline data from 463 participants who were enrolled in the NIAAA COVID-19 Pandemic Impact on Alcohol (C19-PIA) Study were analyzed. Latent class analysis (LCA) was applied to five positive coping behaviors during COVID-19: taking media breaks, taking care of their body, engaging in healthy behaviors, making time to relax, and connecting with others. Latent class differences and the moderating role of history of AUD on six alcohol-related and mental health outcomes were examined using multiple regression models.

RESULTS

LCA revealed two latent classes: 83.4% High Positive Coping and 16.6% Low Positive Coping. Low Positive Coping was associated with higher levels of perceived stress, anxiety symptoms, and loneliness. A history of AUD was consistently associated with higher levels of alcohol-related and mental health outcomes. Significant interactions between Coping Latent Classes and history of AUD indicated that the associations of Low Positive Coping with problematic alcohol use, depressive symptoms, and drinking to cope motives were either stronger or only significant among individuals with a history of AUD.

CONCLUSIONS

Individuals with a history of AUD may be particularly vulnerable to depressive symptoms and alcohol-related outcomes, especially when they do not utilize positive coping strategies. The promotion of positive coping strategies is a promising avenue to address alcohol-related and mental health problems during a public health crisis and warrants future research.

Sleep and mental health among youth experiencing homelessness: A retrospective pilot diary study

OBJECTIVES

The goal of this study was to describe the nightly sleep conditions of youth experiencing homelessness, and examine the association between sleep and mental health, both cross-sectionally and using diary data.

METHODS

n = 147 youth (ages 16-24) experiencing homelessness completed a baseline survey assessing self-reported sleep and depressive and anxious symptoms. A subsample of n = 49 completed a follow-up 7-day diary study measuring nightly sleep conditions and daily depressive and somatic symptoms.

RESULTS

According to baseline data, the majority of the sample (71%) reported sleeping less than 7 hours per night on average, and feeling like they did not get adequate sleep, especially among youth identifying as LGBTQ. In a qualitative follow-up question, the plurality attributed poor sleep to mental health woes. Cross-sectionally, youth with lower levels of self-reported sleep quality (more daytime fatigue and insomnia) reported higher levels of depressive and anxious symptoms. The diary data indicated that the most common nightly complaints among shelter utilizers are lack of privacy, noise, and uncomfortable temperatures. Multilevel models suggest that poor sleep conditions predicted higher levels of somatic symptoms the following day, after controlling for baseline levels of depressive and anxious symptoms.

CONCLUSIONS

This study highlights the role environmental context plays in sleep health and its subsequent impacts. Individuals experiencing homelessness lack autonomy over their sleeping environments, and thus cannot make adjustments such as reducing disruptions such as noise, temperature, and light. Importantly, these less-than-ideal sleeping conditions contribute to pre-existing health disparities and may have long-term implications.

Correlation analysis and gender differences of cognitive function based on mini-mental state examination (MMSE) and suicidal tendency in patients with schizophrenia

BACKGROUND

The aim of this study was to investigate the correlation and gender differences between cognition and suicidal tendency in patients with schizophrenia.

METHODS

A total of 554 patients with schizophrenia were recruited. The Mini-Mental State Examination (MMSE), Positive and Negative Syndrome Scale (PANSS), Interpersonal Reactivity Index (IRI), Toronto Alexithymia Scale (TAS), and Insomnia Severity Index (ISI) were used to assess clinical symptoms.

RESULTS

In male patients, MMSE score and the incidence of suicidal tendency were correlated (P = 0.04, OR = 1.06, 95%CI: 1.00-1.12). Among patients with cognitive dysfunction, IRI score (P = 0.01, OR = 1.04, 95%CI: 1.01-1.06), and types of antipsychotic drugs (P < 0.01, OR = 3.97, 95%CI: 1.76-8.97) in male patients were associated risk factors for suicidal ideation. Among patients without cognitive dysfunction, PANSS positive subscale score (P = 0.03, OR = 1.06, 95%CI: 1.01-1.11), and PANSS general psychopathology score (P = 0.02, OR = 1.05, 95%CI: 1.01-1.08) were associated risk factors for suicidal ideation in male patients and PANSS positive subscale score (P < 0.01, OR = 1.15, 95%CI: 1.05-1.26) were associated risk factors for suicidal ideation in female patients.

CONCLUSIONS

There were significant gender differences in the correlation between cognitive functioning and suicidal ideation in patients with schizophrenia. Cognitive function may play an important mediating role in other factors on suicide.

Prevalence and clinical correlates of restless legs syndrome in psychiatric patients: A cross-sectional study from North India

Background

Restless legs syndrome (RLS) is a neuro-sensorimotor disorder which is scarcely researched and is commonly missed in routine psychiatry practice.

Aim

To evaluate the prevalence of RLS and its correlates in patients with anxiety, depression, and somatoform disorders.

Methods

A cross-sectional single-center study was undertaken in patients aged 18-65 years suffering from ICD-10 (International Statistical Classification of Diseases-10th edition) diagnosis of anxiety, depressive, and somatoform disorders. RLS was evaluated by using diagnostic criteria of International Restless Legs Syndrome Study Group (IRLSSG) and severity measured on IRLSSG scale. Depression and anxiety were rated on Hamilton Depression and Anxiety Rating Scales respectively, insomnia severity measured by Insomnia Severity Index (ISI), and quality of life measured by WHO Quality of Life-Brief version (WHO-QOL BREF) scale. Serum ferritin levels were measured for evaluating iron deficiency.

Results

The rate of RLS was 66.7%, 50%, and 48% in patients with depressive, anxiety, and somatoform disorders, respectively, with no significant inter-group difference. Nearly one-third of patients suffered from severe to very severe symptoms of RLS, and quality of life was poorest in those with depressive disorders. RLS was significantly higher in females (P = 0.019), who were married (P = 0.040), diagnosed with severe depression (P = 0.029), and abused benzodiazepines (P = 0.045). On binary logistic regression, female gender and presence of clinical insomnia predicted occurrence of RLS.

Conclusion

The prevalence of RLS is very high in patients with common psychiatric disorders which is often missed. Clinical enquiry and examination for reversible causes such as iron deficiency may assist in its diagnosis and improve clinical outcome.

Sleep and Postpartum Psychosis: A Narrative Review of the Existing Literature

Sleep problems are extremely common during the postpartum period. The role of sleep in the development of postpartum psychosis (PP) is, however, still under-researched. This narrative review aims to (1) provide a summary of the existing evidence for the associations between sleep problems and PP, (2) discuss the relevant risk factors associated with sleep problems and PP, and (3) suggest future lines of research in this area. Some of the existing literature suggests an association between sleep problems, specifically insomnia, sleep loss and sleep disruption during pregnancy and postpartum, and PP, with the most relevant risk factors including history of bipolar disorder and time of delivery. However, it is still unclear whether the previously mentioned sleep problems are a symptom of, or a trigger for PP. Thus, further research is needed to identify the specific role of sleep problems in PP, using longitudinal designs and more objective measures of sleep. This will allow appropriate detection, intervention and support for women experiencing and/or at risk for PP.

Light-Dark and Activity Rhythm Therapy (L-DART) to Improve Sleep in People with Schizophrenia Spectrum Disorders: A Single-Group Mixed Methods Study of Feasibility, Acceptability and Adherence

People with a diagnosis of schizophrenia often have poor sleep, even when their psychotic symptoms are relatively well managed. This includes insomnia, sleep apnoea, hypersomnia, and irregular or non-24 h sleep-wake timing. Improving sleep would better support recovery, yet few evidence-based sleep treatments are offered to this group. This paper presents a mixed methods feasibility and acceptability study of Light-Dark and Activity Rhythm Therapy (L-DART). L-DART is delivered by an occupational therapist over 12 weeks. It is highly personalisable to sleep phenotypes and circumstances. Ten participants with schizophrenia spectrum diagnoses and sleep problems received L-DART; their sleep problems and therapy goals were diverse. We measured recruitment, attrition, session attendance, and adverse effects, and qualitatively explored acceptability, engagement, component delivery, adherence, activity patterns, dynamic light exposure, self-reported sleep, wellbeing, and functioning. Recruitment was ahead of target, there was no attrition, and all participants received the minimum 'dose' of sessions. Acceptability assessed via qualitative reports and satisfaction ratings was good. Adherence to individual intervention components varied, despite high participant motivation. All made some potentially helpful behaviour changes. Positive sleep and functioning outcomes were reported qualitatively as well as in outcome measures. The findings above support testing the intervention in a larger randomised trial ISRCTN11998005.

The Roles of Stress, Sleep, and Fatigue on Depression in People with Visual Impairments

The study aimed to investigate the mediating effect of fatigue and the moderating effect of sleep quality on stress and depressive symptoms among people with visual impairments. A total of 155 participants completed the online survey. The Perceived Stress Scale, the Fatigue Symptom Inventory, the Centre for Epidemiological Studies-Depression Inventory (CES-D), and the Pittsburgh Sleep Quality Index (PSQI) were used. Descriptive analysis, correlations, and moderated mediation modelling were conducted using R software. From the mediator variable (FSI) model (F = 22.427, R2 = 56.5, p < .001) and the dependent variable (CES-D) model (F = 35.912, R2 = 70.5, p < .001), after controlling for age, sex, employment, and education, sleep quality positively predicted fatigue levels (β = 2.422, p = .009), and fatigue positively predicted depressive symptoms (β = .152, p < .001). Sleep quality is an essential component of psychological well-being in people with visual impairments.

Nighttime sleep quality & daytime sleepiness across inpatient psychiatric treatment is associated with clinical outcomes

Prior research has demonstrated the strong link between sleep disturbance and mental health outcomes, including the importance of examining nighttime sleep quality and daytime sleepiness as separate constructs in relation to mental health outcomes. As such, the current study examined patients' self-reported nighttime sleep quality and daytime sleepiness trajectories over the course of inpatient treatment and how these trajectories related to treatment outcomes. Participants were 1,500 adults who voluntarily admitted to an inpatient psychiatric hospital. Mental health outcomes measured were emotion regulation problems, anxiety severity, depression severity, nightmare severity, and suicide risk. Group-based trajectory modeling was used to determine nighttime sleep quality and daytime sleepiness trajectory groups. Multivariate analyses of covariance (MANCOVA) were used to determine between group differences on mental health outcomes. Patients fit into distinct groups based on their trajectories of nighttime sleep quality and daytime sleepiness across inpatient psychiatric treatment: Low, Moderate, and High. Individuals with greater nighttime sleep disturbance and greater daytime sleepiness throughout treatment (High group) demonstrated significantly increased suicide risk, higher nightmare severity, more anxiety, more depression, and more emotion regulation difficulties at discharge. Results suggest an important connection exists between nighttime sleep quality and excessive daytime sleepiness and mental health outcomes for inpatient psychiatry.

Sleep problems and referral intentions in mental health services: service user self-report and staff proxy report surveys

BACKGROUND

Sleep problems are common in mental health service users, but few non-pharmacological therapies are offered. Therapies are being developed and tested, but there may be barriers to these therapies reaching those who need them.

METHODS

Light-Dark and Activity Rhythm Therapy (L-DART), is a new sleep therapy delivered by an occupational therapist, which has been feasibility tested in people with schizophrenia spectrum diagnoses. This paper presents two surveys, conducted with mental health staff and service users, on sleep problems, treatment wishes; and barriers and facilitators to uptake of L-DART or similar therapies. Descriptive statistics, single-level and multi-level ordinal logistic regression were used to examine factors associated with sleep problems and referral intentions.

FINDINGS

Sleep problems were commonly identified by staff and service users, there was demand for non-pharmacological intervention across diagnostic and demographic categories, but staff readiness to refer differed according to NHS Trust and service user diagnosis. Staff and service user reports differed in awareness of sleep disordered breathing and parasomnias, and wish for referral. Staff were more confident identifying sleep problems than addressing them, but more training was associated with greater confidence concerning both assessment and treatment.

CONCLUSIONS

A range of sleep problems are prevalent and recognised in mental health service users, and there is an unmet need for non-pharmacological sleep interventions. Improving suitable resources to support self-management in this group may help; Staff and service users also reported a high readiness to refer or be referred for sleep interventions. Staff training to improve identification of sleep problems, and differentiation between types of sleep problems, would support access to the most appropriate treatments.

Sleep quality is a predictor of muscle mass, strength, quality of life, anxiety and depression in older adults with obesity

We aimed to investigate associations between sleep quality with selected quantitative and qualitative parameters of health in older individuals with obesity. Cross-sectional assessment (n = 95 men/women; ≥ 65 years; BMI ≥ 30 kg/m²) of sleep quality, body composition, handgrip strength, quality-of-life, anxiety/depression. Mean PSQI score was 6.3. Poor sleepers (n = 49) presented lower appendicular lean mass (ALM) (16.2 vs 17.8 kg; p = 0.0273), ALM/BMI (0.47 vs 0.53 kg/BMI; p = 0.0085), fat mass (48.6 vs 46.6%; p = 0.0464), handgrip strength (19.7 vs 22.0 kgf; p = 0.0542) and handgrip/BMI (0.57 vs 0.66 kgf/BMI; p = 0.0242) than good sleepers. They also had higher anxiety (8.6 vs 5.6; p = 0.0100) and depression (4.8 vs 3.2; p = 0.0197) scores, worse health-related quality-of-life and lower scores in mental (62.8 vs 73.0; p = 0.0223) and physical (52.9 vs 67.3; p = 0.0015) domains. Adjusted models showed that PSQI was negatively associated with ALM (β = - 0.13, 95% CI - 0.25; - 0.01) and health-related quality of life on physical (β = - 2.76, 95% CI - 3.82; - 1.70) and mental (β = - 2.25, 95% CI - 3.38; - 1.12) domains, and positively associated with anxiety (β = 0.57; 95% CI 0.26; 0.87) and depression (β = 0.31; 95% CI 0.13; 0.49). Poor sleep quality associates with impaired selected quantitative and qualitative parameters of health. Additionally, sleep quality was shown as an independent predictor of ALM, health-related quality-of-life, anxiety and depression in older individuals with obesity.

Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient's inability to obtain the necessary information to understand their conditions and detect illness, such as depression, objectively, methods for evaluating various mental disorders, such as the Montgomery-Asberg depression rating scale (MADRS) and observations, currently require a significant amount of effort on the part of specialists. In this study, a novel dataset was provided, comprising sensor data gathered from depressed patients. The dataset included 32 healthy controls and 23 unipolar and bipolar depressive patients with motor activity recordings. Along with the sensor data collected over several days of continuous measurement for each patient, some demographic information was also offered. The result of the experiment showed that less than 70 of the 100 epochs of the model's training were completed. The Cohen Kappa score did not even pass 0.1 in the validation set, due to an imbalance in the class distribution, whereas in the second experiment, the majority of scores peaked in about 20 epochs, but because training continued during each epoch, it took much longer for the loss to decline before it fell below 0.1. In the second experiment, the model soon reached an accuracy of 0.991, which is as expected given the outcome of the UMAP dimensionality reduction. In the last experiment, UMAP and neural networks worked together to produce the best outcomes. They used a variety of machine learning classification algorithms, including the nearest neighbors, linear kernel SVM, Gaussian process, and random forest. This paper used the UMAP unsupervised machine learning dimensionality reduction without the neural network and showed a slightly lower score (QDA). By considering the ratings of the patient's depressive symptoms that were completed by medical specialists, it is possible to better understand the relationship between depression and motor activity.

Gut Microbiome Composition and Its Association with Sleep in Major Psychiatric Disorders

INTRODUCTION

Sleep disturbances are highly prevalent across most major psychiatric disorders. Alterations in the hypothalamic-pituitary-adrenal axis, neuroimmune mechanisms, and circadian rhythm disturbances partially explain this connection. The gut microbiome is also suspected to play a role in sleep regulation, and recent studies suggest that certain probiotics, prebiotics, synbiotics, and fecal microbiome transplantation can improve sleep quality.

METHODS

We aimed to assess the relationship between gut-microbiota composition, psychiatric disorders, and sleep quality in this cross-sectional, cross-disorder study. We recruited 103 participants, 63 patients with psychiatric disorders (major depressive disorder [n = 31], bipolar disorder [n = 13], psychotic disorder [n = 19]) along with 40 healthy controls. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). The fecal microbiome was analyzed using 16S rRNA sequencing, and groups were compared based on alpha and beta diversity metrics, as well as differentially abundant species and genera.

RESULTS

A transdiagnostic decrease in alpha diversity and differences in beta diversity indices were observed in psychiatric patients, compared to controls. Correlation analysis of diversity metrics and PSQI score showed no significance in the patient and control groups. However, three species, Ellagibacter isourolithinifaciens, Senegalimassilia faecalis, and uncultured Blautia sp., and two genera, Senegalimassilia and uncultured Muribaculaceae genus, were differentially abundant in psychiatric patients with good sleep quality (PSQI >8), compared to poor-sleep quality patients (PSQI ≤8).

CONCLUSION

In conclusion, this study raises important questions about the interconnection of the gut microbiome and sleep disturbances.

Mapping associations between anxiety and sleep problems among outpatients in high-altitude areas: a network analysis

BACKGROUND

Anxiety and sleep problems are common comorbidities among outpatients living in high-altitude areas. Network analysis is a novel method to investigate the interaction and the association between symptoms across diverse disorders. This study used network analysis to investigate the network structure symptoms of anxiety and sleep problems among outpatients in high-altitude areas, and to explore the differences in symptom associations in various sex, age, educational levels and employment groups.

METHODS

The data was collected from the Sleep Medicine Center of The First People's Hospital of Yunnan Province from November 2017 to January 2021 with consecutive recruitment (N = 11,194). Anxiety and sleep problems were measured by the Chinese version of the seven-item Generalized Anxiety Disorder Scale (GAD-7) and the Pittsburgh Sleep Quality Index (PSQI) respectively. Central symptoms were identified based on centrality indices and bridge symptoms were identified with bridge indices. The difference of network structures in various sex, age, educational levels and employment groups were also explored.

RESULTS

Among all the cases, 6,534 (58.37%; 95% CI: 57.45-59.29%) reported experiencing anxiety (GAD-7 total scores ≥ 5), and 7,718 (68.94%; 95% CI: 68.08-69.80%) reported experiencing sleep problems (PSQI total scores ≥ 10). Based on the results of network analysis, among participants, "Nervousness", "Trouble relaxing", "Uncontrollable worry" were the most critical central symptoms and bridge symptoms within the anxiety and sleep problems network structure. The adjusted network model after controlling for covariates was significantly correlated with the original (r = 0.75, P = 0.46). Additionally, there were significant differences in edge weights in the comparisons between sex, age and educational levels groups (P < 0.001), while the employed and unemployed groups did not show significant differences in edge weights (P > 0.05).

CONCLUSIONS

In the anxiety and sleep problems network model, among outpatients living in high-altitude areas, nervousness, uncontrollable worry, and trouble relaxing were the most central symptoms and bridge symptoms. Moreover, there were significant differences between various sex, age and educational levels. These findings can be used to provide clinical suggestions for psychological interventions and measures targeting to reduce symptoms that exacerbate mental health.

Provider Perspectives on Sleep as a Determinant of Health and Housing Outcomes among Veterans Experiencing Homelessness: An Exploratory, Social-Ecological Study

Sleep problems are common among United States (U.S.) veterans and are associated with poor health, mental health, and functioning. Yet, little is known about insufficient sleep and factors contributing to sleep disparities among veterans experiencing homelessness. We conducted semi-structured interviews to better understand the clinical, environmental, and structural factors contributing to insufficient sleep among veterans and to improve care for this population. Interviews were conducted with 13 providers caring for veterans experiencing homelessness, including physicians, psychologists, nurses, social workers, and peer support specialists. Providers worked at a West Coast VA institution serving a large population of veterans experiencing homelessness. Interviews were analyzed for themes pertaining to sleep using the social-ecological model as a framework. On an individual level, factors influencing sleep included psychiatric disorders and use of substances. On an interpersonal level, factors included safety concerns while sleeping. On an environmental level, factors included noise and proximity to others as barriers to sleep. On the organizational level, logistical issues scheduling sleep clinic appointments and lack of transportation to attend sleep clinic appointments were identified as treatment barriers. These findings can inform future research studying the impact of sleep on health and housing outcomes and interventions addressing sleep among veterans experiencing homelessness.

Sleep changes during a spontaneous manic episode: PSG assessment in a clinical context

Sleep plays a key role in the pathogenesis and clinical presentation of mood disorders. However, only a few studies have investigated sleep architecture during the manic episodes of Bipolar Disorder (BD) and changes in sleep parameters that follow clinical variations. Twenty-one patients (8 males, 13 females) affected by BD, manic phase, underwent polysomnographic recordings (PSG) at the beginning of the admission in our ward (T₀) and after three weeks of hospital treatment (T₁). All participants were clinically evaluated using Young Mania Rating Scale (YMRS), Pittsburgh Sleep Quality Index (PSQI) and Morningness-Eveningness Questionnaire (MEQ). During the admission, we observed an increase in both quantity (Total Sleep Time - TST) and quality (Sleep Efficiency - SE) of sleep. In addition, clinical improvement, evaluated with YMRS and PSQI scales, was accompanied by a significant increase in the percentage of REM sleep. According to our findings, the improvement of manic symptoms is accompanied by an increase in "REM pressure" (increase in REM% and REM density, reduction of REM latency). Overall, changes in sleep architecture appear to be markers sensitive to clinical variations during manic phases of Bipolar Disorder.

Do better nights lead to better days? Guided internet-based cognitive behavioral therapy for insomnia in people suffering from a range of mental health problems: Protocol of a pragmatic randomized clinical trial

BACKGROUND

Insomnia is the transdiagnostically shared most common complaint in disorders of anxiety, stress and emotion regulation. Current cognitive behavioral therapies (CBT) for these disorders do not address sleep, while good sleep is essential for regulating emotions and learning new cognitions and behaviours: the core fundaments of CBT. This transdiagnostic randomized control trial (RCT) evaluates whether guided internet-delivered cognitive behavioral therapy for insomnia (iCBT-I) (1) improves sleep, (2) affects the progression of emotional distress and (3) enhances the effectiveness of regular treatment of people with clinically relevant symptoms of emotional disorders across all mental health care (MHC) echelons.

METHODS

We aim for 576 completers with clinically relevant symptoms of insomnia as well as at least one of the dimensions of generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), posttraumatic stress disorder (PTSD) or borderline personality disorder (BPD). Participants are either pre-clinical, unattended, or referred to general- or specialized MHC. Using covariate-adaptive randomization, participants will be assigned to a 5 to 8-week iCBT-I (i-Sleep) or a control condition (sleep diary only) and assessed at baseline, and after two and eight months. The primary outcome is insomnia severity. Secondary outcomes address sleep, severity of mental health symptoms, daytime functioning, mental health protective lifestyles, well-being, and process evaluation measures. Analyses use linear mixed-effect regression models.

DISCUSSION

This study can reveal for whom, and at which stage of disease progression, better nights could mean substantially better days.

TRIAL REGISTRATION

International Clinical Trial Registry Platform (NL9776). Registered on 2021-10-07.

Occupational Exposure to Pesticides as a Risk Factor for Sleep Disorders

Inadequate sleep has been linked to a variety of impairments in bodily functions, including endocrine, metabolic, higher cortical function, and neurological disorders. For this reason, the aim of this study was to analyze the link between occupational pesticide exposure and sleep health among farmers in Almeria. A cross-sectional study was conducted among a population living on the coast of Almeria (southeastern Spain), where about 33,321 hectares of land are used for intensive agriculture in plastic greenhouses. A total of 380 individuals participated in the study: 189 greenhouse workers and 191 control subjects. The participants were contacted during their annual scheduled occupational health survey. Data on sleep disturbances were collected using the Spanish version of the Oviedo Sleep Questionnaire. Agricultural workers were found to be at a significantly higher risk of insomnia, especially among those who did not wear protective gloves (OR = 3.12; 95% C.I. = 1.93-3.85; p = 0.04) or masks (OR = 2.43; 95% C.I. = 1.19-4.96; p = 0.01). The highest risk of insomnia related to pesticide applicators was observed in those who did not wear a mask (OR = 4.19; 95% C.I. = 1.30-13.50; p = 0.01) or goggles (OR = 4.61; 95% C.I. = 1.38-10.40; p = 0.01). This study supports previous findings indicating an increased risk of sleep disorder in agricultural workers exposed to pesticides at work.

Impact of ground-level ozone exposure on sleep quality and electroencephalogram patterns at different time scales

Ozone exposure is associated with various adverse health outcomes, but its impact on sleep quality is uncertain. Here we assessed the causal effect of long-term (yearly and monthly) exposure to ozone on nocturnal workday sleep time in a national representative sample from the China Family Panel Study, using a difference-in-differences approach. We further followed ninety healthy Chinese young adults four times in four seasons from September 2020 to June 2021, measured their daily sleep architecture using accelerometers, ascertained daily ozone exposure, recorded 5-min eye-closed resting-state electroencephalogram (EEG) signals at the last day of each one-week-long measurement session, and explored the effect of ozone exposure on objectively-measured sleep architecture. In the national sample, we found that every 1 interquartile range (IQR) μg/m³ increase in yearly and monthly ozone exposure was causally associated with 7.31 (p = 0.0039) and 4.19 (p = 0.040) minutes decline in nocturnal workday sleep time; the dose-response curve represented a quasi-linear pattern with no safety threshold, and plateaued at higher concentrations. In the small-scale study with objectively-measured sleep architecture, we found that every 1 IQR μg/m³ increase in the weekly ozone exposure was associated with 5.33 min decrease in night-time total sleep time (p = 0.031), 1.63 percentage points decrease in sleep efficiency (p < 0.001), 1.99 min increase in sleep latency (p = 0.0070), and 5.34 min increase in wake after sleep onset time (p = 0.0016) in a quasi-linear pattern. Notably, we found the accumulating trend of ozone exposure on sleep quality during both the short-term and long-term periods. We also found that short-term ozone exposure was associated with altered EEG patterns, mediated by sleep quality. This study indicates that long-term and short-term ozone exposures have negative and accumulating impacts on sleep quality and might impair brain functioning. More hidden health burdens of ozone are worth exploring.

Global prevalence and associated factors of sleep disorders and poor sleep quality among firefighters: A systematic review and meta-analysis

Lack of sleep can affect the health and performance of firefighters. This systematic review and meta-analysis estimated the global prevalence of sleep disorders and poor sleep quality among firefighters and reported associated factors. Four academic databases (Scopus, PubMed, Web of Science, and Embase) were systematically searched from January 1, 2000 to January 24, 2022. These databases were selected as they are known to index studies in this field. The search algorithm included two groups of keywords and all possible combinations of these words. The first group included keywords related to sleep and the second group keywords related to the firefighting profession. The relevant Joanna Briggs Institute checklist was used to evaluate study quality. Data from eligible studies were included in a meta-analysis. In total, 47 articles informed this review. The pooled prevalence of sleep disorders and poor sleep quality in firefighters were determined as 30.49% (95% CI [25.90, 35.06]) and 51.43% (95% CI [42.76, 60.10]), respectively. The results of a subgroup analysis showed that individuals in low- and middle-income countries (LMICs) had a higher prevalence of sleep disorders than those in high-income countries (HICs) but HICs had a higher prevalence of poor sleep quality than LMICs. Various factors, including shift work, mental health, injuries and pain, and body mass index were associated with sleep health. The findings of this review highlight the need for sleep health promotion programs in firefighters.

Understanding the research on tracking, diagnosing, and intervening in sleep disorders using mHealth apps: Bibliometric analysis and systematic reviews

Objectives

In solving the global challenge of sleep disorders, Mobile Health app is one of the important means to monitor, diagnose, and intervene in sleep disorders. This study aims to (1) summarize the status and trends of research in this field; (2) assess the production and usage of sleep mHealth apps; (3) calculate the conversion rate of grants that the proportion of newly developed apps from being funded and developed to published on application stores.

Methods

Using bibliometric and content analysis methods, based on "Research Paper-Product Output-Product Application" chain and considering the "Research Grants" of articles, we conducted a systematic review of eight databases, to identify relevant studies over the last decade.

Results

Over the past decade, 1399 authors published 313 papers in 182 journals and conferences. The number of publications increased with an average annual growth of 41.6%. The current focus area is research using cognitive behavioral therapy to intervene in sleep. Sleep-staging tracking is a shortcoming of this field. A total 368 sleep mHealth apps (233 newly developed and 135 existing) were examined in 313 papers; 323 grants supported 178 articles (56.9%). Only 12 of the newly developed apps are used in the real world, resulting in a 9% grant conversion rate.

Conclusions

In the last decade, the field of tracking, diagnosing, and intervening in sleep disorders using mHealth apps has shown a trend of rapid development. However, the conversion rate of products from being funded and developed for use by end-users is low.

Sleep and Rest-Activity Rhythms in Recovering Patients with Severe Concurrent Mental and Substance Use Disorder: A Pilot Study

Objective: Mental health and substance use disorders are commonly associated with disrupted sleep and circadian rest-activity rhythms. How these disorders in combination relate to sleep and circadian organization is not well studied. We provide here the first quantitative assessment of sleep and rest-activity rhythms in inpatients with complex concurrent disorders, taking into account categories of substance use (stimulant vs. stimulant and opioid use) and psychiatric diagnosis (psychotic disorder and mood disorder). We also explore how sleep and rest-activity rhythms relate to psychiatric functioning. Methods: A total of 44 participants (10 female) between the age of 20-60 years (median = 29 years) wore wrist accelerometers over 5-70 days and completed standardized questionnaires assessing chronotype and psychiatric functioning (fatigue, psychiatric symptom severity, and impulsiveness). To examine potential influences from treatment, we computed (1) length of stay; (2) days of abstinence from stimulants and opioids as a measure of withdrawal; and (3) a sedative load based on prescribed medications. Results: Participants exhibited a sustained excessive sleep duration, frequent nighttime awakenings, and advanced rest-activity phase related to sedative load. Sleep disruptions were elevated in participants with a history of opioid use. Patients with a psychotic disorder showed the longest sleep and most fragmented and irregular rest-activity patterns. Non-parametric circadian rhythm analysis revealed a high rhythm amplitude by comparison with population norms, and this was associated with greater psychiatric symptom severity. Psychiatric symptom severity was also associated with greater fatigue and later MCTQ chronotype. Conclusions: This pilot study provides initial information on the prevalence and severity of sleep and circadian rhythm disturbances in individuals with severe concurrent disorders. The results underline the need for further studies to start to understand the role of sleep in the disease and recovery process in this understudied population.

Calling on All Child and Family Practitioners to Help Mitigate the Impacts of the Poor Behavioural Health of Children with Psychiatric Illness

Adolescents and children (aged 6 to 17+ years) admitted to inpatient psychiatry or intensive out-of-home mental health programs (formerly called residential mental health treatment centres) are among those with the most severe psychiatric illnesses. Moreover, these children also have very poor behavioural and biopsychosocial health including sleep deprivation, difficult relationships, problematic use of electronic devices, academic difficulty, poor school engagement, insufficient exercise and poor diets; all of these were noted before the pandemic. The pandemic has only increased the social isolation, poor health behaviours and mental health challenges for many children and adolescents. The poor behavioural and psychosocial health of those in their youth with psychiatric illnesses can exacerbate symptoms and can interfere with academic performance, development and good decision making; these biopsychosocial health behaviours are modifiable. All child and family practitioners including pediatricians, family physicians, nurses, social workers, psychologists and psychotherapists have an important role in fostering the behavioural and biopsychosocial health (i.e., sleep, positive relationships, electronic device use, exercise and diet) of all family members and especially children with psychiatric illness. Enacting biopsychosocial lifestyle interventions before or during childhood and adolescence may reduce the burden of mental illness.

Elder people can be more susceptible to the association between short-term ambient air pollution and sleep disorder outpatient visits: a time-series study

Sleep disorders attract increasing concerns. However, the evidence of the association between ambient air pollution and sleep disorders is limited. Therefore, our aim was to determine the association between short-term air pollution exposure and outpatient visits for sleep disorders in Xi'an, the largest city in Northwest China. Baseline outpatient data of daily sleep disorders between 2011 and 2013 were collected. Quasi-Poisson distribution was applied by adjusting the day of the week and weather conditions. A total of 49,282 sleep disorder outpatient visits were recorded. The most significant association between air pollutants and outpatient visits was observed on concurrent day: per 10 μg/m3 increase of NO2, SO2, and PM10 at lag 0 corresponded to increased outpatient sleep disorder visits at 0.22% (95% CI: 0.03%, 0.42%), 1.53% (95% CI: 0.53, 2.53%), and 2.57% (95% CI: 1.33%, 3.82%), respectively. As for gender-specific analysis, there was no statistically significant difference between males and females. The result of season-specific analysis showed no statistically significant difference between warm seasons and cool seasons, either. As for age-specific analysis, obvious associations were observed in 20-40 age group (NO2) and > 40 age group (PM10 and SO2), while no evident association was found for the young age group (< 20 years old). Conclusively, short-term exposure to air pollutants, especially gaseous air pollutants, might increase the risk of sleep disorders, and such association appears to be more obvious in elder people. We provide novel data that there may be age differences in the relationship between short-term air pollution exposure and sleep disorders.

Effect of anxiolytic drug silexan on sleep - a narrative review

OBJECTIVES

Silexan is an orally administered, proprietary essential oil from Lavandula angustifolia with significant anxiolytic and sleep improving properties. Here we present a narrative review that provides an overview of the available evidence of the effects of silexan on sleep.

METHODS

We start with a summary of the pharmacological background and continue with presenting sleep-related results from controlled clinical trials with silexan. Then we report on a meta-analysis of item 'insomnia' from the Hamilton Anxiety Scale, which includes data from all randomised, placebo-controlled clinical trials with silexan in which the scale was administered. Finally, we summarise the results of a mediation analysis that was performed to elucidate the pathway of the effect of silexan on sleep.

RESULTS

In randomised, placebo-controlled trials in patients suffering from anxiety disorders silexan had a significant anxiolytic effect and improved sleep along with recovery from anxiety. Mediation analysis demonstrates that more than 98% of the effect of silexan on sleep was mediated by its anxiolytic effect while the direct effect on sleep was marginal.

CONCLUSIONS

Silexan improves sleep as a result of its anxiolytic effect.

Changes in quality of sleep, mood and other neuropsychiatric symptoms after switching dolutegravir/lamivudine/abacavir to darunavir/cobicistat/emtricitabine/tenofovir alafenamide in a randomized study of people living with HIV with poor sleep quality. GESIDA 10418

Background

While switching ART in people with HIV experiencing insomnia due to dolutegravir-related neurotoxicity is well-founded upon evidence, there is a lack of proof in regards to the outcome of stopping dolutegravir-based ART in people without insomnia but reporting poor sleep quality.

Methods

Randomized, multicentre, open-label study to evaluate reversibility of patient-reported sleep disturbances in patients on dolutegravir/lamivudine/abacavir without insomnia after switching to darunavir/cobicistat/emtricitabine/tenofovir-alafenamide. The participants were randomized to switch ART at baseline or a week 4 and then completed 8 weeks of darunavir/cobicistat/emtricitabine/tenofovir-alafenamide. Our primary objective was to compare changes in sleep quality between arms at week 4. Secondary objectives were to compare changes in mood and neuropsychiatric symptoms (NS) at week 4 and 4 and 8 weeks after switching to darunavir/cobicistat/emtricitabine/tenofovir-alafenamide. The participants completed a survey, including the Pittsburgh Sleep Quality Index (PSQI), the Hospital Anxiety and Depression scale (HAD) and specific questions to explore NS, at each visit to assess those objectives.

Results

We included seventy-two participants. The results show that study arms were similar at baseline, though at week 4, PSQI scores remained unchanged with dolutegravir/lamivudine/abacavir while patients improved significantly after switching to darunavir/cobicistat/emtricitabine/tenofovir-alafenamide. Similar differences between arms were also observed in HAD and NS changes. At weeks 4 and 8 after all participants switched to darunavir/cobicistat/emtricitabine/tenofovir-alafenamide, we have observed significant improvements in PSQI and HAD scores and in NS.

Conclusion

In patients reporting subclinical sleep disturbances without insomnia, switching from dolutegravir/lamivudine/abacavir to darunavir/cobicistat/emtricitabine/tenofovir-alafenamide was associated with better sleep quality and improvements in mood and NS.

Classification of Depressive and Schizophrenic Episodes Using Night-Time Motor Activity Signal

Major depressive disorder (MDD) is the most recurrent mental illness globally, affecting approximately 5% of adults. Furthermore, according to the National Institute of Mental Health (NIMH) of the U.S., calculating an actual schizophrenia prevalence rate is challenging because of this illness’s underdiagnosis. Still, most current global metrics hover between 0.33% and 0.75%. Machine-learning scientists use data from diverse sources to analyze, classify, or predict to improve the psychiatric attention, diagnosis, and treatment of MDD, schizophrenia, and other psychiatric conditions. Motor activity data are gaining popularity in mental illness diagnosis assistance because they are a cost-effective and noninvasive method. In the knowledge discovery in databases (KDD) framework, a model to classify depressive and schizophrenic patients from healthy controls is constructed using accelerometer data. Taking advantage of the multiple sleep disorders caused by mental disorders, the main objective is to increase the model’s accuracy by employing only data from night-time activity. To compare the classification between the stages of the day and improve the accuracy of the classification, the total activity signal was cut into hourly time lapses and then grouped into subdatasets depending on the phases of the day: morning (06:00–11:59), afternoon (12:00–17:59), evening (18:00–23:59), and night (00:00–05:59). Random forest classifier (RFC) is the algorithm proposed for multiclass classification, and it uses accuracy, recall, precision, the Matthews correlation coefficient, and F1 score to measure its efficiency. The best model was night-featured data and RFC, with 98% accuracy for the classification of three classes. The effectiveness of this experiment leads to less monitoring time for patients, reducing stress and anxiety, producing more efficient models, using wearables, and increasing the amount of data.

Outcomes From the Transdiagnostic Sleep and Circadian Intervention (TranS-C) for Midlife and Older Adults With Serious Mental Illness and Sleep and Circadian Dysfunction

The present study tested outcomes of the Transdiagnostic Sleep and Circadian Intervention (TranS-C) among midlife and older adults with serious mental illness (SMI). Further, we tested predictors-credibility, expectancy, usefulness, and utilization-that may affect TranS-C outcomes. Midlife and older participants from a community setting (>49 years, 62.3% female, 37.7% African American or Black) with sleep and circadian problems and SMI were randomized to receive TranS-C plus usual care (TranS-C+UC, n = 27) or usual care followed by delayed treatment with TranS-C (UC-DT, n = 26). Immediate and delayed TranS-C data were combined to increase power (combined n = 52). Outcomes were assessed at pretreatment, posttreatment, and 6-month follow-up. Credibility and expectancy were assessed during the second session. Usefulness and utilization of TranS-C skills were assessed at posttreatment and 6-month follow-up. TranS-C+UC, relative to UC-DT, was associated with improvements in depression symptoms, sleep disturbance, overall sleep health, and select sleep/wake outcomes, though not all improvements were sustained at 6-month follow-up. Lower usefulness of TranS-C skills predicted more severe sleep disturbance at posttreatment and daytime sleep-related impairment at posttreatment and 6-month follow-up. Lower utilization predicted more severe psychiatric symptoms at posttreatment, sleep disturbance at posttreatment and 6-month follow-up, and overall impairment and daytime sleep-related impairment at 6-month follow-up. Higher credibility and expectancy predicted greater usefulness of TranS-C skills at posttreatment and 6-month follow-up and greater utilization at 6-month follow-up. Together, findings highlight benefits of TranS-C for midlife and older adults with SMI. However, boosting credibility, expectancy, utilization, and usefulness may meaningfully improve TranS-C outcomes.

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.

Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

Sleep Deficiency: Epidemiology and Effects

Adequate sleep is an important pillar of physical and mental health. Sleep deficiency, resulting from short sleep or suboptimal sleep quality, is highly prevalent in modern society. Occupation, social demands, psychiatric disorders, physical disorders, and sleep disorders are some of the contributing factors to sleep deficiency. Some populations are at increased risk of sleep deficiency based on ethnicity, age, marital status, sex, and hospitalization. Sleep deficiency influences cognition, alertness, mood, behavior, diabetes, cardiovascular health, renal function, immune system, and respiratory physiology. This review summarizes the epidemiology and effects of sleep deficiency.

[Prevalence of sleep disturbance in intensive care nurses: a post hoc analysis of a cross-sectional study]

Background

Intensive care nurses have irregular and unusual working hours due to shift work, which can disrupt the natural light-dark rhythm and thus increase the risk for sleep disorders.

Aim of the work

The aim of this post hoc analysis was to investigate the prevalence of self-reported sleep problems and associated factors among intensive care nurses working in Germany.

Methods

This analysis was a post hoc analysis of a cross-sectional study, which was performed as an online survey. Collected data were sociodemographic, work-related and health-related data. These data were used to calculate the prevalence and respective 95% confidence intervals (95% CI) of sleep problems. Factors associated with sleep problems were identified using the χ2-test, Fisher's exact test, and logistic regression analysis.

Results

The link to the online survey was accessed 1163 times and 490 intensive care nurses participated in the survey. A total of 432 intensive care nurses were included in this analysis, of whom 82.87% were women. A total of 57.64% (95% CI: 52.83-62.35%) reported sleep problems. Significantly associated with sleep problems were age (50-59 years odds ratio [OR]: 2.05, 95% CI: 1.00-4.21, p = 0.047 vs. 20-29 years) and living in a family (OR: 0.50, 95% CI: 0.27-0.93, p = 0.029 vs. single/living alone). In addition, depression (OR: 1.09, 95% CI: 1.06-1.12, p ≤ 0.001), anxiety (OR: 1.10, 95% CI: 1.06-1.14, p ≤ 0.001) and stress (OR: 1.09, 95% CI: 1.06-1.12, p ≤ 0.001) levels were significantly associated with sleep problems.

Conclusion

Sleep problems were present in one out of every two participating intensive care nurses and in particular mental health was associated with sleep problems.

Adult ADHD and sleep disorders: Prevalence, severity and predictors of sleep disorders in a sample of Italian psychiatric outpatients

OBJECTIVE

Sleep disorders are frequent in adult subjects diagnosed with ADHD. The aims of the present study were to assess the prevalence and the severity of sleep disorders in a sample of Italian psychiatric outpatients, to compare the prevalence and severity of sleep disorders in patients with and without diagnosis of adult ADHD, and to evaluate the role of ADHD as an individual predictor of sleep disturbances severity.

METHOD

634 outpatients accessing psychiatric services were assessed with the Mini-International Neuropsychiatric Interview (MINI) Plus V. 5.0.0 interview and the Adult ADHD self-report Scale Symptoms Checklist (ASRS)-V 1.1 Short Form. Patients positive to the ASRS-V 1.1 were assessed with the Diagnostic Interview for ADHD in Adults (DIVA) 2.0. Sleep disorders and sleep disturbances' severity were assessed with the PROMIS Adult Sleep Disturbance Scale.

RESULTS

Sleep disorders were more frequent (p < 0.001) and sleep disturbances were more severe (d = 1.26, p < 0.001) in subjects diagnosed with adult ADHD compared to other outpatients. Among the 44 subjects diagnosed with ADHD, 15 (34.1%) reported no or slight sleep disturbances, 9 (20.5%) a mild sleep disorder, 17 (38.6%) a moderate sleep disorder and 3 (6.8%) a severe sleep disorder. ADHD diagnosis, multiple psychiatric comorbidity and history of suicide attempts emerged as individual predictors of worse sleep disturbances.

CONCLUSION

Sleep disorders are more frequent and severe in subjects diagnosed with ADHD compared to other adult outpatients. Sleep disturbances might represent an intrinsic feature in adult ADHD subjects, presenting important clinical repercussions, and should be routinely evaluated and monitored in this population.

Restless Legs Syndrome Prevalence and Clinical Correlates Among Psychiatric Inpatients: A Multicenter Study

Background

There are only limited reports on the prevalence of restless legs syndrome (RLS) in patients with psychiatric disorders. The present study aimed to evaluate the prevalence and clinical correlates in psychiatric inpatients in Germany and Switzerland.

Methods

This is a multicenter cross-sectional study of psychiatric inpatients with an age above 18 years that were diagnosed and evaluated face-to-face using the International RLS Study Group criteria (IRLSSG) and the International RLS severity scale (IRLS). In addition to sociodemographic and biometric data, sleep quality and mood were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI), the Epworth Sleepiness Scale (ESS), and the Patient Health Questionnaire (PHQ-9). In addition to univariate statistics used to describe and statistically analyze differences in variables of interest between patients with and without RLS, a logistic model was employed to identify predictors for the occurrence of RLS.

Results

The prevalence of RLS in a sample of 317 psychiatric inpatients was 16.4%, and 76.9% of these were diagnosed with RLS for the first time. RLS severity was moderate to severe (IRLS ± SD: 20.3 ± 8.4). The prevalences in women (p = 0.0036) and in first-degree relatives with RLS (p = 0.0108) as well as the body mass index (BMI, p = 0.0161) were significantly higher among patients with RLS, while alcohol consumption was significantly lower in the RLS group. With the exception of atypical antipsychotics, treatment with psychotropic drugs was not associated with RLS symptoms. Regarding subjective sleep quality and mood, scores of the PSQI (p = 0.0007), ISI (p = 0.0003), and ESS (p = 0.0005) were higher in patients with RLS, while PHQ-9 scores were not different. A logistic regression analysis identified gender (OR 2.67; 95% CI [1.25; 5.72]), first-degree relatives with RLS (OR 3.29; 95% CI [1.11; 9.73], ESS score (OR 1.09; 95% CI [1.01; 1.17]), and rare alcohol consumption (OR 0.45; 95% CI [0.22; 0.94] as predictors for RLS.

Conclusions

Clinically significant RLS had a high prevalence in psychiatric patients. RLS was associated with higher BMI, impaired sleep quality, and lower alcohol consumption. A systematic assessment of restless legs symptoms might contribute to improve the treatment of psychiatric patients.

Assessment of Sleep and Sleepiness in Patients With Mental Disorders: Applicability of the German Version of the SCOPA-Sleep Questionnaire

Sleep problems affect the majority of patients with mental disorders and are very clinically relevant. However, they are often not assessed and treated appropriately and, to date, there is no established screening routine for sleep disturbances in this specific patient group. For patients with Parkinson disease, the Scales for Outcomes in Parkinson's Disease-Sleep (SCOPA-Sleep) questionnaire is widely used. This questionnaire has excellent psychometric properties. It consists of 2 scales for assessing nighttime sleep problems (NS) and daytime sleepiness (DS). As the items in the scales are not disease-specific, the goal of this study was to validate the SCOPA-Sleep for use in patients with mental disorders. A total of 370 German patients with mental disorders completed the SCOPA-Sleep as well as a multitude of other instruments for assessment of validity [eg, Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS)]. For validity estimation, 627 healthy subjects were also included in this study. Internal consistency was good with coefficients of 0.806 and 0.772 for the SCOPA-NS and the SCOPA-DS. Factor analysis revealed 2 factors which could each be assigned to one of the subscales. Convergent validity was high with correlations of 0.672 between the SCOPA-NS and the PSQI and 0.644 between the SCOPA-DS and the ESS. The German version of the SCOPA-Sleep showed good diagnostic accuracy, resulting in an area under the receiver operating curve of 0.959 for the SCOPA-NS and 0.728 for the SCOPA-DS. For patients with mental disorders, the SCOPA-Sleep proved to be an economical, reliable, and valid instrument for assessing NS and DS which is well accepted by patients. It can be recommended for routine assessment of both NS and DS.

Sex difference in association between insomnia and cognitive impairment in patients with chronic schizophrenia

OBJECTIVE

Sex differences in schizophrenia have been noted across domains such as sleep and cognitive function； however, how they interact remains unclear. This study aimed to explore sex differences in the relationship between insomnia and cognitive function in patients with chronic schizophrenia.

METHODS

718 schizophrenia patients (480 males and 238 females) and 397 healthy controls were recruited. Insomnia was collected by a questionnaire. Insomnia severity index (ISI) was used to evaluate the severity of insomnia. The clinical symptoms and cognition were assessed with the Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), respectively.

RESULTS

Schizophrenia patients showed significantly lower scores compared to healthy controls on the RBANS total score and four indexes (all p < 0.05). Male patients had a lower rate of insomnia, higher scores on the RBANS visuospatial/constructional, language, and total score than female patients (all P < 0.05). Insomnia patients had lower RBANS immediate memory, language, and total scores than non-insomnia patients, and the results only appeared in female patients (all P < 0.05). In addition, there were significant negative correlations between ISI and RBANS language and delayed memory in male patients, while ISI was significantly negatively correlated with RBANS immediate memory in female patients (all P < 0.05).

CONCLUSION

Our findings suggest that there are sex differences in insomnia, cognitive performance, and their association in patients with chronic schizophrenia. These sex differences may have important potential clinical significance for the identification, evaluation, and treatment of insomnia in patients with chronic schizophrenia.

Physical activity levels associated with insomnia and depressive symptoms in middle-aged and elderly patients with chronic schizophrenia

BACKGROUND

Previous evidence suggested that physical activity had beneficial effects on psychopathological symptoms, insomnia, or depressive symptoms in people with schizophrenia. This study investigated the association between physical activity levels and insomnia and depressive symptoms in middle-aged and elderly hospitalized patients with chronic schizophrenia (CS).

METHODS

179 participants were enrolled. We used the 30-item Positive and Negative Syndrome Scale (PANSS_-30) to assess the psychopathological symptoms. We used the Insomnia Severity Index scale (ISI) and 17-item Hamilton Depression Scale (HAMD-17) to evaluate insomnia and depressive symptoms. Daily physical activity time less than 30 min, within 30-60 min, and more than 60 min were defined as physical inactivity, moderate physical activity, and vigorous physical activity, respectively. The Chi-square test, analysis of variance (ANOVA), and Mann-Whitney U-test were applied for categorical, continuous, and non-normal distribution variables, respectively. The Pearson or Spearman's correlation analyses were utilized to examine the association between physical activity levels, ISI total scores, HAMD total scores, and socio-demographic and clinical variables. Finally, socio-demographic variables with a P-value < 0.05 in the comparison between insomnia/depressive group and non-insomnia/depressive group were considered for inclusion in binary logistic regression analysis to determine the relationship between physical activity levels and insomnia or depressive symptoms.

RESULTS

The ISI total scores (r = -0.247, P = 0.001) and HAMD total scores (r = -0.312, P < 0.001) were negatively correlated with physical activity levels. Logistic regression analysis revealed that older age, higher depressive factor scores, and lower physical activity level were influential factors of insomnia symptoms in CS patients (P < 0.05). In addition, vigorous physical activity (compared with physical inactivity) and higher negative and depressive factor scores were independently associated with depressive symptoms in CS patients (P < 0.05).

CONCLUSION

Physical activity levels were influential factors in comorbid insomnia and depressive symptoms in CS patients. Given the benefits of physical activity, it should be strengthened as a routine adjunct to clinical treatment or psychiatric care so as to improve the physical and mental health of patients with psychiatric symptoms.

Insomnia and other sleep disorders in dermatology patients: A questionnaire-based study with 634 patients

Insufficient sleep duration and quality are associated with various adverse health outcomes. Whereas sleep disorders have been studied in a few skin conditions, data in a more comprehensive dermatology population are lacking. We sought to describe the prevalence, causes, and consequences of sleep disorders in dermatology patients. In this cross-sectional, single-center study, dermatology patients completed a questionnaire addressing skin-related and non-skin-related health, sleep behavior, causes, and consequences of sleep disorders. According to the Regensburg Insomnia Scale, 27.92% of the 634 participants had insomnia (177 of 634 patients). Of these 177 patients, 115 (64.97%) were subjectively sleep disturbed, with skin-related causes accounting for 55.65% (64 of 115 patients), non-skin-related accounting for 33.04% (38 of 115 patients), and combined accounting for 11.30% (13 of 115 patients). Itch was the leading cause of skin-related sleep disorders (64.49%, 50 of 77 patients), followed by skin-related pain (55.84%, 43 of 77 patients) and skin-related fearful thoughts (54.55%, 42 of 77 patients). Sleep disorders reduced daytime performance in 68.70% (79 of 115 patients) and sleep quality of relatives in 20.87% (24 of 115 patients). The prevalence of insomnia among different diagnostic categories ranged from 20.31% to 50.00%. The most common strategy to improve sleep was taking sleep medication (57.39%, 66 of 115 patients). We conclude that sleep disorders are highly prevalent in dermatology patients, often leading to reduced daytime performance, impaired sleep among the patients' relatives, and increased use of substances.

Anxiety and Insomnia Among Urban Slum Dwellers in Bangladesh: The Role of COVID-19 and Its Associated Factors

Background: Although mental health is an important part of health and wellbeing, very little is known about the impact of the COVID-19 pandemic on the mental health of marginalized communities like urban slum dwellers. Our study estimated the prevalence of generalized anxiety disorder and insomnia among the residents of the informal settlements of Dhaka, Bangladesh, during the COVID-19 pandemic. Methods: A cross-sectional phone-based survey was conducted from October to November 2020 among adult residents of five informal settlements of Dhaka city randomly chosen from an existing Urban Health and Demographic Surveillance Systems (UHDSS) run by icddr,b. Data on Generalized Anxiety Disorder-7 (GAD-7) and Insomnia Severity Index (ISI) were collected. A multinomial logistic regression was performed to assess the associated factors of anxiety and insomnia. Results: Of the total 586 participants, the prevalence of mild to severe anxiety and insomnia were 53% and 43%, respectively. As per the multinomial regression analysis, participants with mild anxiety were significantly more likely to be older (>50 years) and afraid of COVID-19 infection. Likewise, participants with moderate/severe anxiety were significantly more likely to share less household facilities (e.g., toilet, kitchen, water) (OR: 2.23; 95% CI: 1.31-3.79), to have difficulties in food availability (OR: 2.76; 95% CI: 1.10-6.93), to be afraid of self (OR: 5.27; 95% CI: 2.82-9.88), and to worry about the family members (OR: 2.26; 95% CI: 1.23-4.17) getting infected. Participants with mild insomnia were significantly more likely to share fewer household facilities and be afraid of being infected with COVID-19 infection. Moreover, participants with moderate/severe insomnia were significantly more likely to be female (OR: 1.90; 95% CI: 1.02-3.56), to receive food aid (OR: 0.50; 95% CI: 0.29-0.88), to be afraid of self (OR: 3.85; 95% CI: 1.81-8.19), and to worry about someone like friends or neighbors (OR: 2.45; 95% CI: 1.07-5.58) getting infected with COVID-19. Conclusions: We found elevated prevalence of both anxiety and insomnia among the urban poor of Bangladesh in the context of COVID-19. This indicates the importance of integrating mental health in the mitigation and recovery efforts related to similar crises for the urban poor in the future.

Relevance of Objective Measures in Psychiatric Disorders-Rest-Activity Rhythm and Psychophysiological Measures

PURPOSE OF REVIEW

We present a review of recent methods of objective measurement in psychiatry and psychology with a focus on home monitoring and its utility in guiding treatment.

RECENT FINDINGS

For individualized diagnostics and treatment of insomnia, actigraphy can generate clinically useful graphical presentations of sleep timing and patterns. Psychophysiological measures may complement psychometrics by tracking parallel changes in physiological responses and emotional functioning, especially during therapy for trauma symptoms and emotion regulation. It seems that rather than defining universal cut-offs, an individualised range of variability could characterize treatment response. Wearable actigraphy and psychophysiological sensors are promising devices to provide biofeedback and guide treatment. Use of feasible and reliable technology during experimental and clinical procedures may necessitate defining healthy and abnormal responses in different populations and pathological states. We present a "call for action" towards further collaborative work to enable large scale use of objective measures.

Outcomes of the Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TranS-C) in a community setting: Unpacking comorbidity

OBJECTIVE

Comorbidity and subdiagnostic symptoms are understudied for sleep and circadian problems. We evaluated 1) impairment associated with (a) number of sleep and circadian problems and (b) diagnostic threshold (full diagnosis vs. subdiagnostic symptoms), and 2) Transdiagnostic Sleep and Circadian Intervention (TranS-C) outcomes for participants with specific sleep and circadian problems.

METHOD

Community participants (N = 121) with serious mental illness and sleep and circadian problem(s) were randomized to receive TranS-C plus usual care (TranS-C + UC) or usual care plus delayed TranS-C (UC-DT). Overall impairment, psychiatric symptoms, and sleep and circadian dysfunction were assessed at pre-treatment, post-treatment, and 6-month follow-up.

RESULTS

Higher numbers of sleep and circadian problems, versus one problem, were associated with worse overall impairment, psychiatric symptoms, and sleep and circadian dysfunction (ps < 0.05, ω2 = 0.06-0.15). Diagnostic threshold was not associated with baseline functioning (ps > 0.05). TranS-C + UC versus UC-DT was associated with psychosocial and sleep and circadian improvements for specific sleep and circadian problems (insomnia, hypersomnia, parasomnias, periodic limb movement/restless leg syndrome, circadian rhythm disorders), though improvements varied by problem. TranS-C + UC outcomes were not moderated by number of sleep and circadian problems (ps > 0.05).

CONCLUSION

Higher numbers of sleep and circadian problems, not diagnostic threshold, were associated with greater impairment. Transdiagnostic utility of TranS-C + UC was supported.