Sleep, insomnia, and depression

The interplay between sleep and cancer-related fatigue in breast cancer: A casual and computer-simulated network analysis

Objective

Sleep problems and cancer-related fatigue are common symptoms in women for breast cancer, during and after treatment. Identifying key intervention targets for this symptom cluster may improve patient reported outcomes. This study aimed to explore the relationship between sleep and cancer-related fatigue to identify optimal intervention targets.

Methods

In the "Be Resilient to Breast Cancer" program, self report data were collected on sleep and cancer-related fatigue the Multidimensional Fatigue Symptom Inventory-Short Form and the Pittsburgh Sleep Quality Index. Gaussian network analysis was employed to identify central symptoms and nodes, while a Bayesian network explored their causal relationships. Computer-simulated interventions were used to identify core symptoms as targets for intervention.

Results

General fatigue (Str ​= ​0.95, Bet ​= ​7, Clo ​= ​0.007) was considered the node with the strongest centrality. The daytime dysfunction item on the Pittsburgh sleep quality index had the strongest bridge strength. Core symptoms were identified as targets for intervention by the computer-simulated analysis.

Conclusions

Sleep quality is the strongest predictor of cancer-related fatigue from a casual networking perspective. Sleep latency and daytime dysfunction should be targeted to break the chained symptom interaction between sleep and cancer-related fatigue.

Impact of cardiovascular risk factors on associations between state and trait indices of major depression disorder and objectively assessed physical activity, sleep and circadian rhythmicity within a population based cohort

BACKGROUND

Few studies of the association between accelerometry-assessed physical activity with major depressive disorder (MDD) have considered the influence of both the averages and variability of all three domains of the 24 hour activity cycle including sleep, physical activity, and circadian rhythmicity, the physical health correlates of depression, and the extent to which changes in sleep and physical activity reflect current state versus enduring patterns of MDD in people with depression.

METHODS

The sample includes 2307 participants from a population cohort from Lausanne, Switzerland. Average and variability of daily sleep (SL), physical activity (PA), and circadian rhythmicity (CR) were derived from accelerometry.

RESULTS

Cardiovascular risk factors, particularly cigarette smoking and body mass index (BMI), were significantly associated with both the average and variability of sleep, phyiscal activity and circadian rhythmicity, and with MDD. Lower average and less variable physical activity, as well as more variable circadian rhythmicity were associated with remitted MDD, whereas later sleep midpoint and greater variation of sleep duration variability were associated with depressive states.

LIMITATION

The single geographic setting, cross-sectional nature and two-week assessment period may limit the generalizability of these findings.

CONCLUSION

These results demonstrate the importance of considering both the average and variability of accelerometry-derived phenotypes that may distinguish state from trait manifestations of MDD. Further, the confounding influence of smoking, particularly on state manifestations of MDD, should be considered in studies of accelerometer derived phenotypes, particularly sleep characteristics. Interventions for depression should therefore consider modification of health behaviors such as smoking and overweight, as well as stabilizing the 24-hour rest-activity cycle, rather than treatments that focus solely on the average levels of mood, sleep or physical activity alone.

Brain activity differences between difficulty in falling asleep and early awakening symptoms in major depressive disorder: A resting-state fMRI study

Numerous studies have revealed that patients with major depressive disorder (MDD) suffer from insomnia symptoms. However, the dysfunction pattern in specific insomnia symptoms in patients with MDD remains unclear. The present study aimed to examine the regional brain neuroimaging activity features of difficulty falling asleep (DFA) and early awakening (EA) in patients with MDD. The resting-fMRI by applying the amplitude of low-frequency fluctuation (ALFF) method was estimated in 50 MDD patients with DFA, 36 patients with EA, 46 patients without insomnia symptoms, and 60 matched healthy controls. The Pearson correlation analysis was used among the ALFF with significant difference brain regions, the 17-item Hamilton Depression Rating Scale factor scores, and the Pittsburgh Sleep Quality Index scores. Patients with DFA showed lower ALFF values in the left precentral gyrus than those with EA and higher ALFF values in the left insula than those without insomnia symptoms. Patients with EA showed higher ALFF values in the left precentral gyrus than those without insomnia symptoms. This study revealed distinct neural mechanisms underlying specific insomnia symptoms, identifying the left insula as a potential pathological region in DFA patients and the left precentral gyrus as a characteristic neuropathological region in EA patients.

Study on the correlation between insomnia degree and quality of life in psychiatric outpatients in Chifeng city

BACKGROUND

Insomnia is a common sleep disorder that negatively impacts quality of life and is frequently comorbid with depression and anxiety. Chronic insomnia affects approximately 15% of the global population, with higher prevalence among females and the elderly. While existing research suggests a bidirectional relationship between insomnia and emotional disorders, the specific impact of insomnia severity on depression, anxiety, and quality of life remains unclear. This study investigates the correlation between insomnia severity and these factors in psychiatric outpatients, hypothesizing that greater insomnia severity is associated with higher levels of depression and anxiety, as well as poorer quality of life.

AIM

To explore the correlation between insomnia severity and depression, anxiety, and quality of life in primary chronic insomnia patients.

METHODS

From June to December 2023, 345 patients with primary insomnia in Chifeng city were recruited and divided into three groups based on Pittsburgh sleep quality index (PSQI) scores: Mild (n = 137), moderate (n = 162), and severe (n = 46). Demographic data were collected via questionnaires. Self-rating depression scale (SDS), self-rating anxiety scale (SAS), PSQI, and short form 36 (SF-36) scores were compared, and Pearson and partial correlation analyses were performed.

RESULTS

The greater the degree of insomnia, the greater the symptoms of depression and anxiety (P < 0.001). The more severe the insomnia, the lower the SF-36 score (excluding body pain), and the difference between the three groups was statistically significant (P < 0.001). Pearson correlation analysis and partial correlation analysis depicted the SDS score and SAS score were apparently positively correlated with the severity of insomnia (P < 0.001). Pearson correlation analysis and partial correlation analysis depicted the SF-36 scores were apparently positively correlated with the severity of insomnia (P < 0.05).

CONCLUSION

Depression and anxiety are independent factors influencing insomnia severity in primary chronic insomnia patients. Higher depression/anxiety levels correlate with worse insomnia, impacting quality of life.

HPA axis in psychotic and non-psychotic major depression: Cortisol plasma levels and hippocampal volume

BACKGROUND

Psychotic major depression (PMD) differs from non-psychotic MD (NPMD) in psychopathology and is linked to changes in brain volumetry and hypothalamic-pituitary-adrenal (HPA) axis function that can be reflected by its principal output - the glucocorticoid cortisol. NPMD patients exhibit smaller hippocampi than healthy controls (HC), purportedly representing exposure to chronic stress. However, the relationship between the individual clinical phenotype, hippocampal volume and diurnal cortisol signaling remains unclear.

METHODS

Since understanding the interplay among symptoms, neuroimaging and HPA function is crucial for discerning biological differences between PMD and NPMD, this study explored the link between clinical phenotype, hippocampal structural MRI and circadian plasma cortisol levels in 32 HC, 27 NPMD and 26 PMD patients.

RESULTS

PMD patients showed significantly elevated evening (6 p.m. - 1 a.m.) cortisol levels compared to NPMD and HC, while NPMD and HC did not differ. No group differences in hippocampal volume were observed, but a significant interaction effect emerged between overnight (1 a.m. - 9 a.m.) cortisol levels, hippocampal volume, and clinical phenotype. NPMD patients displayed a negative correlation between overnight cortisol levels and hippocampal volume, which was specific to the ascending cortisol curve (2 a.m. - 5 a.m.) and absent in PMD and HC. The hippocampus-cortisol interaction was associated with depressive symptom severity in NPMD but not PMD, where cortisol alone predicted greater severity.

CONCLUSIONS

These findings imply a time-dependent relationship between hippocampal volume and overnight cortisol in NPMD, which is absent in PMD and HC. In contrast, PMD patients exhibited increased evening cortisol levels. In an exploratory analysis, these effects were also related to symptom severity at similar timepoints. While correlational, these results point to distinct neurobiological mechanisms underlying NPMD and PMD, which are potentially related to the heterogeneous clinical manifestations.

Melanin-concentrating hormone: A promising target for antidepressant treatment

Depression represents a complex neuropsychiatric disorder with an escalating global health burden, characterized by heterogeneous pathophysiology and profound impairments in cognitive-emotional functioning. Current treatment methods have limited efficacy in some individuals and may induce undesirable side effects, necessitating the exploration of novel therapeutic targets and techniques. Emerging research has identified neuropeptide systems as pivotal regulators of mood-related circuits, with melanin-concentrating hormone (MCH) signaling emerging as a particularly promising candidate for antidepressant development. The potential involvement of MCH in the pathophysiology of depression was first proposed over two decades ago. Since then, accumulating evidence from recent studies has progressively illuminated its multifaceted roles in modulating depressive behaviors and underlying neurobiological mechanisms. This review systematically analyzes the mechanistic interplay between MCH signaling and depression pathophenotypes, including its relationship with the hypothalamic-pituitary-adrenal (HPA) axis, neurotransmitter systems, synaptic plasticity, and the regulation of sleep-wakefulness. Particular emphasis is placed on advancing the therapeutic rationale for MCH receptor 1 (MCHR1) antagonists, which demonstrate rapid-onset antidepressant efficacy in preclinical studies compared to traditional agents. Nonetheless, the antidepressant mechanism of the MCH system still requires further elucidation to confirm its therapeutic potential.

Slumber under pressure: REM sleep and stress response

Sleep, a state of reduced responsiveness and distinct brain activity, is crucial across the animal kingdom. This review explores the potential adaptive functions of REM sleep in adapting to stress, emphasizing its role in memory consolidation, emotional regulation, and threat processing. We further explore the underlying neural mechanisms linking stress responses to REM sleep. By synthesizing current findings, we propose that REM sleep allows animals to "rehearse" or simulate responses to danger in a secure, offline state, while also maintaining emotional balance. Environmental factors, such as predation risk and social dynamics, further influence REM sleep. This modulation may enhance survival by optimizing stress responses while fulfilling physiological needs in animals. Insights into REM sleep's role in animals may shed light on human sleep in the context of modern stressors and sleep disruptions. This review also explores the complex interplay between stress, immunity, sleep disruptions-particularly involving REM sleep-and their evolutionary underpinnings.

Association between occupational stress and depression among construction workers: The chain mediating of sleep disorders and anxiety

BackgroundDue to the unique nature of their work, construction workers are prone to mental health problems. However, few studies in China have explored the relationship between psychological variables about them.ObjectiveThe purpose of this study was to explore the relationship between occupational stress and depression and to analyze the mediating role of sleep disorders and anxiety.MethodsA stratified cluster sampling method randomly selected 1871 construction workers in Chongqing, China. The survey was conducted as a questionnaire. SPSS 25.0 software was used for data analysis and statistical description. SPSS PROCESS macro version 4.0 was used for the chained mediation effect test.ResultsThe detection rates of occupational stress, sleep disorders, anxiety, and depression among construction workers were 26.4%, 89.8%, 30.2%, and 18.7%, respectively. Analysis showed that these factors were positively correlated with each other. Mediation effect analysis showed that occupational stress directly influenced depression (β = 0.156, p < 0.001) and also had an indirect effect through sleep disorders and anxiety, with respective mediation effects of 4.48% and 47.93%. Sleep disorders and anxiety played a chain-mediating role between occupational stress and depression, with a mediating effect of 3.69%.ConclusionsOccupational stress affects depression directly and also indirectly through sleep disorders and anxiety. These results indicate that reducing occupational stress, sleep disorders, and anxiety may be effective in preventing depression.

Beneficial Effects of Dendrobium officinale Extract on Insomnia Rats Induced by Strong Light and Noise via Regulating GABA and GABAA Receptors

OBJECTIVE

To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia.

METHODS

Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry.

RESULTS

DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABAA receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01).

CONCLUSION

DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABAA receptors expressions and GA/GABA ratio.

Effect of insomnia on anxiety about COVID- 19 patients: the mediating role of psychological capital

INTRODUCTION

The outbreak of Corona Virus Disease (COVID- 19) in 2019 has continued until now, posing a huge threat to the public's physical and mental health, resulting in different degrees of mental health problems. Previous studies have shown that insomnia is one of the main influences on anxiety. However, due to the specificity of the disease and the situation of centralized treatment of COVID- 19 patients in mobile cabin hospitals, insomnia interventions are limited. Therefore, it is necessary to find the complex mediating variables between insomnia and anxiety to provide new ideas for the prevention and intervention of anxiety caused by insomnia in COVID- 19 patients.

METHODS

The measurement tools were the Athens Insomnia Scale, Psychological Capital Questionna-ire, and Self-Rating Anxiety Scale. Statistical analysis was performed using SPSS 25.0 software, and a mediator model was established and corrected using Amos software.

RESULTS

More than one in five patients in this study had anxiety, and the total score was significantly higher than the Chinese standard total score. Insomnia was positively correlated with anxiety, but negatively correlated with psychological capital; and psychological capital was negatively correlated with anxiety. Psychological capital can act as a mediating factor in the relationship between insomnia and anxiety. Psychological capital played a mediating role in the relationship between insomnia and anxiety among COVID- 19 patients, that is, insomnia not only directly affected anxiety, but also indirectly affected anxiety through the mediating role of psychological capital.

CONCLUSION

It is recommended that patients and health care professionals increase the psychological capital of COVID- 19 patients through various methods to counter the effects of insomnia on anxiety.

Clinical predictors of insomnia in borderline personality disorder: a polysomnographic and subjective examination

BACKGROUND

Sleep disturbances are common in patients with borderline personality disorder (BPD) and are associated with a poor prognosis and symptom severity. Research findings on sleep abnormalities in individuals with BPD have been inconsistent, with limited evidence linking subjective and objective measures.

METHODS

We compared 44 women with BPD with 41 healthy controls. We examined differences (using ANCOVAs and ordinal logistic regression) and associations (using correlations) between objective sleep assessment (polysomnography) and subjective measures (Consensus Sleep Diary, Insomnia Severity Index, Pittsburgh Sleep Quality Index). We explored predictors of insomnia in BPD patients, including BPD severity, symptomatology, comorbid conditions, and medication use, via standard least squares regressions and ANOVAs.

RESULTS

A total of 22% of patients with BPD had clinically significant insomnia (cut-off ≥ 15), 85% reported mild (subthreshold) insomnia (cut-off > 10) (Insomnia Severity Index; ISI), and 94% reported sleep quality disturbances (PSQI > 5). Compared with those in HC, PSG results in individuals with BPD revealed a longer duration in bed, longer sleep period, REM latency, wake after sleep onset latency, Stage N1 sleep duration, shorter N2 sleep duration, and, with age, more arousals and awakenings. The correlations between objective and subjective sleep measures were weak in both groups. In patients with BPD, a greater degree of insomnia predicted a reduction in total sleep time and increased awakenings and arousals on PSG. Clinical BPD severity, emotional reactivity and dysregulation, depression symptoms, posttraumatic stress symptoms, alexithymia, and presleep arousal were associated with greater insomnia in BPD patients.

CONCLUSIONS

Our study confirmed high rates of insomnia and sleep disturbances in individuals with BPD, which contrasted with relatively minor PSG alterations. Clinical BPD severity and symptomatology are associated with sleep abnormalities in individuals with BPD. Insomnia is a neglected yet important characteristic of the BPD phenotype, warranting more attention in future research and clinical guidelines.

Antepartum insomnia symptoms and its association with postpartum depression symptoms in women with and without psychiatric vulnerability: A prospective cohort study

BACKGROUND

Postpartum depression is common and may be linked to antepartum insomnia, a potentially modifiable risk factor. We examine the association between insomnia- and postpartum depression symptoms, considering whether psychiatric vulnerability moderates this link.

METHOD

Participants completed the Insomnia Severity Index during trimester two and three and the Hospital Anxiety and Depression questionnaire postpartum. Linear regression analyses were used to investigate the associations between antepartum insomnia- and postpartum depression symptoms. We used stratified regression models and a test for multiplicative interaction to understand if psychiatric vulnerability moderates this association.

RESULTS

A total of 217 women participated (median age 37, IQR 5). Women with clinically significant insomnia symptoms in trimester two and three reported higher postpartum depression symptoms (p = .008 and p = .002 respectively). Linear regression analyses showed effect sizes that were almost equal for both trimesters (two: β = 0.19, 95 % CI -0.20., 0.40, p = .069 and three: β = 0.23, 95 % CI 0.09., 0.36, p ≤ .001), but only statistically significant for trimester three. When antepartum depression was taken into account, neither the second nor third trimester was significantly associated with postpartum depressive symptoms. Psychiatric vulnerability did not moderate the relationship (p = .163).

CONCLUSION

Insomnia symptoms in the second and third trimesters are not associated with postpartum depression when antepartum depression is taken into account in both women with and without psychiatric vulnerability. Hence it is important to screen for both insomnia and depression during pregnancy to prevent postpartum depression in all pregnant women.

Analysis of the prevalence and influencing factors of depression in middle-aged women: A nationwide study from CHARLS

Depression accounts for a large portion of the global burden of disease, and few large-sample studies have investigated the prevalence of depression in middle-aged women. This study examined the prevalence and factors influencing depression in middle-aged women. Cross-sectional data from the China Health and Retirement Longitudinal Study (CHARLS) were used, selecting middle-aged women aged 45-59 years. Binary logistic regression was used to analyze the influencing factors. 3723 middle-aged women were included in the study, 1537 (41.28 %) had depressive symptoms, 2186 (58.72 %) had no depressive symptoms. The results of binary logistic regression analysis showed that sleep duration, old-age insurance, body pain, drinking, fall, self-related health, life satisfaction, residence, education and marital status were the influencing factors for middle-aged women (P<0.05). Depression in middle-aged Chinese women is influenced by a variety of factors. This study suggests that this population can be targeted for prevention in terms of demographic characteristics, behavioral habits, and healthcare configuration for middle-aged women who are in poor health, and with low life satisfaction.

Sleep alterations in major depressive disorder and insomnia disorder: A network meta-analysis of polysomnographic studies

Major depressive disorder (MDD) and Insomnia disorder (ID) are characterized by sleep alterations. To define their polysomnographic profiles, we conducted a Network Meta-Analysis comparing MDD and ID patients versus healthy controls (HCs). The literature search, conducted from 2008 up to January 2023 and following PRISMA guidelines, covered PubMed, Web of Science, Scopus, and Embase databases. We addressed publication bias using funnel plot asymmetry inspection and Egger's test, evaluated statistical heterogeneity with I2, and local and global inconsistencies with the separate indirect from direct evidence method and Q between designs, respectively. Pairwise meta-analyses employed a fixed-effects model, while network analysis utilized a random-effect approach. We evaluated 86 ID and 17 MDD studies, comparing sleep parameters for 636 MDDs versus 491 HCs, and 3661 IDs versus 2792 HCs. The network meta-analysis reported that patients with MDD have greater rapid eye movement (REM) sleep duration and REMs density, and lower REM sleep latency compared to IDs. ID patients instead exhibited lower total sleep time and time in bed, and greater wake after sleep onset and non-REM sleep stage 3 than MDD patients. This work emphasized sleep depth and continuity alterations in both MDD and ID, with major involvement of REM sleep in MDD.

Impact of living environment on sleep quality in older adults and the mediating role of depression: a cross-sectional study

Sleep quality significantly affects the well-being of older adults. This study aimed to analyse the current state of sleep quality among older adults in China and to examine the effects of living environment and depression on sleep quality, as well as their interrelationship(s). A survey was conducted using a self-designed questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire Depression Scale (PHQ-9), targeting a sample of adults ≥ 60 years of age in the central province of China, yielding 6211 valid responses. Correlation analysis indicated that the living environment was negatively correlated with both depression and PSQI score (r = - 0.140, p < 0.01; r = - 0.174, p < 0.01). The living environment (β = - 0.049, p < 0.001) was a negative predictor of PSQI, while depression (β = 0.477, p < 0.001) was a positive predictor. Mediation analysis revealed that depression acted as a mediator between the living environment and sleep quality, contributing 61.7% of the overall effect. Further analysis through hierarchical regression and simple slope plotting indicated that in a favourable living environment, the impact of depression on sleep quality was more pronounced. These findings suggest that a supportive living environment has a protective effect against poor sleep hygiene among older adults and that depression plays a significant mediating role. Intervention strategies should focus on improving living environments and implementing mental health measures to enhance sleep quality among older adults.

Chronic insomnia, REM sleep instability and emotional dysregulation: A pathway to anxiety and depression?

The world-wide prevalence of insomnia disorder reaches up to 10% of the adult population. Women are more often afflicted than men, and insomnia disorder is a risk factor for somatic and mental illness, especially depression and anxiety disorders. Persistent hyperarousals at the cognitive, emotional, cortical and/or physiological levels are central to most theories regarding the pathophysiology of insomnia. Of the defining features of insomnia disorder, the discrepancy between minor objective polysomnographic alterations of sleep continuity and substantive subjective impairment in insomnia disorder remains enigmatic. Microstructural alterations, especially in rapid eye movement sleep ("rapid eye movement sleep instability"), might explain this mismatch between subjective and objective findings. As rapid eye movement sleep represents the most highly aroused brain state during sleep, it might be particularly prone to fragmentation in individuals with persistent hyperarousal. In consequence, mentation during rapid eye movement sleep may be toned more as conscious-like wake experience, reflecting pre-sleep concerns. It is suggested that this instability of rapid eye movement sleep is involved in the mismatch between subjective and objective measures of sleep in insomnia disorder. Furthermore, as rapid eye movement sleep has been linked in previous works to emotional processing, rapid eye movement sleep instability could play a central role in the close association between insomnia and depressive and anxiety disorders.

Methods and exploratory findings of the first Swiss agricultural health cohort FarmCoSwiss

FarmCoSwiss is Switzerland's first agricultural cohort study on farmers' health and wellbeing. It aims to longitudinally describe farmers' mental and physical health and identify risk and protective factors. Between November 2022 and August 2023, 872 participants (65.9% men) were enrolled in the baseline survey assessing farm characteristics, occupational hazards, lifestyle and wellbeing, and physical and mental health. Selected variables were descriptively compared to the general population using Swiss Health Survey (SHS) data (2022) and the Swiss-wide SAPALDIA cohort (2020-2023). Findings suggest better physical health-related quality of life (HRQoL) in younger participants, and better mental HRQoL in older farmers. Furthermore, descriptive comparisons indicate that female farmers may have higher physical, but lower mental HRQoL than men. Most participants (60.5%) were classified as overweight or obese based on self-reported height and weight. Descriptive comparisons between the SHS and FarmCoSwiss suggest that farmers might spend less hours sitting, consume less alcohol and tobacco, but eat more red and processed meat. FarmCoSwiss participants further reported lower prevalences of most diseases compared to SAPALDIA participants. Occupational accidents were common in the farmers' cohort. These high accident rates as well as high BMI values and indications for sex-based differences in physical and mental health highlight the need for further research and in-depth studies. Given increasing political, societal, and environmental pressures on agriculture, epidemiological evidence on farmers' health and wellbeing is crucial to maintain a thriving agricultural workforce.

Advances in the research of comorbid insomnia and depression: mechanisms, impacts, and interventions

Insomnia and depression, both significantly impacting public health, are common psychosomatic illnesses that frequently co-occur in the same individual. Not only do these two conditions commonly co-occur, but they also exhibit a bidirectional link, where the existence of one may heighten the risk for the other. Latest research offers compelling evidence of significant overlap in biological, psychological, and sociological aspects in the comorbidity of insomnia and depression. Building on this, we aim to examine the pathophysiology of insomnia and depression, along with their comorbid mechanisms, encompassing biological routes (like genetics, HPA axis, immune-inflammatory activation, neuroendocrine regulation, microbiome alterations, and neural circuits integrating sleep and emotion regulation), as well as psychosocial routes. Consequently, proposing a self-perpetuating and mutually reinforcing "snowball effect" model of comorbid insomnia and depression, and examining corresponding preventative intervention strategies to rectify associated imbalances. Finally, this article encapsulates the challenges in this field of study and the directions for future research. Finally, the paper points out the limitations of current research (cross-sectional data being dominant, and the mechanism of multi-omics dynamics being unknown) and the future direction (longitudinal cohort combined with computational modeling to resolve temporal interactions), which will provide a theoretical basis for precision interventions.

The role and therapeutic potential of mitophagy in major depressive disorder

Major depressive disorder, also known as MDD, affects more than 264 million people globally, making it a prevalent and critical health challenge. Traditional treatments show limited efficacy in many patients. Therefore, exploring new treatment methods is particularly crucial. Mitophagy, as a regulatory process, can help understand and treat MDD. This paper focuses on the molecular mechanisms of mitophagy, starting from proteins and related pathways, and its role in MDD. The study also explores the associations between mitophagy and neuroinflammation, oxidative stress, neurotransmitter synthesis, and neuroplasticity in MDD and discusses the progress of clinical research on the role of mitophagy in MDD. In addition, the article describes the current pharmaceutical and non-pharmaceutical interventions that can regulate mitophagy in MDD and unravels the potential and challenges of these therapeutic strategies in clinical settings. This article offers a deeper insight into the pathogenesis of MDD and offers a scientific basis for the development of new treatment strategies.

Exploring predictors of insomnia severity in shift workers using machine learning model

Introduction

Insomnia in shift workers has distinctive features due to circadian rhythm disruption caused by reversed or unstable sleep-wake cycle work schedules. While previous studies have primarily focused on a limited number of predictors for insomnia severity in shift workers, there is a need to further explore key predictors, and develop a data-driven prediction model for insomnia in shift workers. This study aims to identify potential predictors of insomnia severity in shift workers using a machine learning (ML) approach and evaluate the accuracy of the resulting prediction model.

Methods

We assessed the predictors of insomnia severity in large samples of individuals (4,572 shift workers and 2,093 non-shift workers). The general linear model with the least absolute shrinkage and selection operator (LASSO) was used to determine an ML-based prediction model. Additional analyses were conducted to assess the interaction effects depending on the shift work schedule.

Results

The ML algorithms identified 41 key predictors from 281 variables: 1 demographic, 7 physical health, 13 job characteristics, and 20 mental health factors. Compared to the non-shift workers, the shift workers showed a stronger association between insomnia severity and five predicting variables: passiveness at work, authoritarian work atmosphere, easiness to wake up, family and interpersonal stress, and medication. The prediction model demonstrated good performance with high accuracy and specificity overall despite a limited F1 score (classification effectiveness) and recall (sensitivity). Specifically, a prediction model for shift workers showed better balance in F1 scores and recall compared to that for non-shift workers.

Discussion

This ML algorithm provides an effective method for identifying key factors that predict insomnia severity in shift workers. Our findings align with the traditional insomnia model while also reflecting the distinctive features of shift work such as workplace conditions. Although the potential for immediate clinical application is limited, this study can serve as guidance for future research in improving a prediction model for shift workers. Constructing comprehensive ML-based prediction models that include our key predictors could be a crucial approach for clinical purposes.

Hyperbaric oxygen treatment for chronic insomnia at high altitude: A prospective, randomized, open-label, parallel-group trial

BACKGROUND

Hyperbaric oxygen (HBO) has been proposed to be effective for treating chronic insomnia at high altitudes.

METHODS

Patients suffering from chronic insomnia at high altitude were randomly assigned at a 1:1 ratio to either the hyperbaric oxygen (HBO) treatment group or the control group for a 10-day procedure. The primary outcome was insomnia status, which was assessed via the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI). The secondary outcomes included stratified comparisons of changes in the PSQI score and ISI score, Fatigue Severity Scale (FSS) score and Hospital Anxiety and Depression Scale (HADS) score. Analyses were performed for multiple comparisons for the primary outcomes at 2-sided 0.05 significance levels with Bonferroni corrections.

RESULTS

A total of 80 patients were randomized in this study, and the median age was 25.0 years (IQR, 21.25-29.75). For the primary outcome of sleep quality, the PSQI score after treatment was significantly lower in the HBO group than in the control group (4.6 ± 3.15 vs. 9.1 ± 4.02; adjusted mean difference [aMD] -3.96 [-5.26 to -2.66], p < 0.0001). The ISI was also significantly lower in the HBO group than in the control group (5.0 ± 4.09 vs. 9.8 ± 6.47; aMD -4.10 [95 % CI, -5.68 to -2.51], p < 0.0001). For the secondary outcomes, the HBO group showed improvements in terms of fatigue, anxiety, and depression. No serious adverse events were reported in either group.

CONCLUSION

HBO is an efficacious and safe treatment for chronic insomnia at high altitude.

TRIAL REGISTRATION

ChiCTR2100046917.

Insomnia Comorbid With Depression: A Bibliometric and Visualized Analysis of Research Trends and Hotspots From 2000 to 2024

Background: Sleep disorders, such as insomnia, are pervasive and frequently comorbid with depression, significantly affecting the quality of life of patients. Insomnia is characterized by difficulty initiating or maintaining sleep, which leads to impairment. Depression is characterized by persistent sadness and loss of interest, and it often features symptoms of insomnia. Understanding their interaction will be done for treatment strategies concerning both disorders. Despite the existence of extensive studies on insomnia and depression, there is a significant gap in bibliometric analysis specifically addressing the comorbidity of these two conditions. Objectives: This study is aimed at conducting a bibliometric analysis of research in insomnia comorbid with depression (ICD) to identify research trends, collaboration patterns, influential works, and hotspots. Methods: The study involved performance analysis to evaluate research productivity and trends, science mapping to visualize the intellectual structure and thematic evolution of the field, and network analysis to examine research collaboration and knowledge structure. Tools such as VOSviewer, CiteSpace, and GraphPad Prism were utilized for data analysis. Results: A total of 1624 publications on the comorbidity of insomnia and depression from 2000 to 2024 were included, encompassing both articles and reviews. Publication volume showed a steady growth from 2000 to 2008, followed by a significant increase from 2019 onward. The United States was the most productive country, followed by China. Key authors such as Allison G. Harvey, Charles M. Morin, and Daniel J. Buysse have made substantial contributions to the field. Major influential journals included Sleep Medicine, Journal of Affective Disorders, and Frontiers in Psychiatry. Research trends identified included the exploration of neurobiological mechanisms, cognitive behavioral therapy for insomnia (CBT-i), and personalized treatment approaches. Conclusion: This bibliometric analysis provides valuable insights into the evolving landscape of research on ICD. Future research should focus on personalized, multimodal interventions, expanding the application of CBT-i, exploring neurobiological mechanisms, and improving patients' quality of life through integrated treatment strategies.

The Guardian of Dreams: The Neglected Relationship Between Sleep and Psychoanalysis

Knowledge about sleep was very limited at the time when Freud published his seminal work on the interpretation of dreams. He was also not interested in sleep, which was considered a problem of physiology; however, sleep appears to have a central role in his model, since dreaming is considered the guardian of sleep. The function of dreaming, according to Freud, is to protect sleep from disruption, with the dream working to avoid repressed stimuli interrupting the "biological" function of sleep. Before neurophysiological studies provided evidence that sleep is not a passive state, Freud also recognized sleep as an active process, as human beings voluntarily withdraw their attention from the external world to actively move to sleep. The discovery of REM sleep in the 1950s led psychoanalysts to see sleep as the necessary background to the occurrence of dreaming. Although Freud dismissed the clinical importance of sleep disturbances, viewing them as the somatic expression of an instinctual disturbance which would disappear during psychoanalytic treatment, successive authors highlighted the fact that sleep disturbances might have a more specific psychological significance. The similarities between the loss of self that occurs during sleep and the fragmentation of the identity experienced during schizophrenia represent an interesting and yet not fully explored area of research. Thanks to Freud's work, the desire to sleep assumes the important role of a psychological, active factor that contributes to the occurrence and function of sleep.

Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study

OBJECTIVE

Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.

METHODS

Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).

RESULTS

LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.

CONCLUSION

Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

"Sleep Quality and Depression Level in Nurses in COVID-19 Pandemic"

The COVID-19 spread rapidly all over the world and pandemic process has negatively affected nurses. Sleep disorders and depression are among these negative effects. Managers' awareness of problems experienced by nurses and taking precautions will increase employee and patient satisfaction and provide quality patient care. The study was conducted in descriptive, cross-sectional and correlational design to explain nurses' sleep quality and depression levels and relationship between them during the COVID-19 pandemic with 142 nurses who completed Personel Information Form, Pittsburgh Sleep Quality Index (PSQI) and Beck Depression Index (BDI). Sleep quality of nurses (64.8%) was poor, 33.1% had depression, and high school education, having a chronic illness and PSQI score increased the risk of depression level of nurses. Results highlight COVID-19 pandemic affected nurses' sleep quality and depression levels. All managers should be pioneers in providing psychological support to nurses and preparing and implementing a program for prevention of insomnia and depression.

Systematic review: REM sleep, dysphoric dreams and nightmares as transdiagnostic features of psychiatric disorders with emotion dysregulation - Clinical implications

BACKGROUND

Fragmented rapid eye movement (REM) sleep disrupts the overnight resolution of emotional distress, a process crucial for emotion regulation. Emotion dysregulation, which is common across psychiatric disorders, is often associated with sleep disturbances. This systematic review explores how REM sleep and nightmares affect emotion processing and regulation in individuals with psychiatric disorders where emotion dysregulation is a key concern, suggesting novel sleep-related treatment pathways.

METHODS

We performed a PRISMA-compliant systematic search of the PUBMED, Web of Science, and EBSCO databases from January 1994-February 2023. This systematic review targeted studies on REM sleep, nightmares, and emotion regulation in a postpubescent clinical population with affective dysregulation. The quality of the studies was assessed via the Newcastle‒Ottawa Scale (NOS), adapted for cross-sectional studies.

RESULTS

From the 714 screened records, 28 articles met the inclusion criteria and focused on REM sleep, dreams, or nightmares in individuals with mood disorders (k = 8), anxiety disorders (k = 1), posttraumatic stress disorder (PTSD) (k = 16), non-suicidal self-injury (NSSI), personality disorders (k = 2), and autism (k = 1). Fifteen studies used objective sleep measures, seventeen used self-reported assessments, six included treatment components, eight investigated nightmares, and three examined dreams. NOS scores ranged from moderate to high.

CONCLUSIONS

REM sleep disturbances represent a transdiagnostic feature across psychiatric disorders and are crucial for emotion regulation. Nightmares are associated with suicidal behaviour and emotion dysregulation. Targeted sleep interventions may improve emotion regulation and mental health outcomes. Future research should explore the role of REM sleep in disorder prognosis to develop tailored interventions.

Wearable, self-administered transcranial photobiomodulation for major depressive disorder and sleep: A randomized, double blind, sham-controlled trial

BACKGROUND

Device-based treatments exist in psychiatry for decades, but are usually operated by clinicians and require multiple office visits. Near-infrared transcranial photobiomodulation (tPBM) is a safe neurostimulation modality with potential antidepressant and hypnotic effects. We investigated the feasibility and efficacy of adjunctive tPBM treatment, self-administered by a wearable headband.

METHODS

We randomized 48 outpatients with major depressive disorder (MDD) into tPBM or sham with 1:1 ratio. All participants were advised to receive the device-based intervention for at least 20 min daily at their preferred time and place for 8 weeks. The compliance and adverse events were monitored throughout the trial. The Hamilton Depression Rating Scale (HAMD), Beck's Depression Inventory (BDI) and Pittsburgh Sleep Quality Index (PSQI) were used to evaluate the symptoms from baseline until week-12.

RESULTS

Participants reported this self-administered intervention well-tolerated. Treatment compliance was equally good between various group-comparisons, and the adverse effects were minimal and transient. Post-treatment, the HAMD and BDI scores of patients in both tPBM group and sham group significantly decreased compared to baseline, with no between-group difference. However, a significant PSQI score reduction was only found in tPBM group from week-2 onward compared with baseline, with significant between-group difference lasting until week-12 (F1,46 = 6.16, p = 0.017).

LIMITATIONS

This smaller sample size and short treatment and follow-up durations.

CONCLUSIONS

Self-administered wearable tPBM appears to be a feasible and well-tolerated in MDD patients. The low-level dosimetry appeared insufficient to produce an antidepressant effect but effective in improving sleep quality. Further studies should investigate different dosimetry and intervention time. CLINICAL TRIALS REGISTRATION NUMBER IN CLINICALTRIAL.GOV: NCT04619121.

Trends in anti-insomnia medication utilization among pediatric patients in nine cities in China: A real-world study (2016-2023)

OBJECTIVE

To investigate prescription patterns of insomnia medications among Chinese children, assess the current status of drug treatment, and offer data to support the guidance of clinical prescribing practices.

METHODS

This study analyzed pediatric prescriptions for insomnia medications from the China Hospital Prescription Analysis Cooperation Project database across nine cities between 2016 and 2023. The analysis focused on demographic characteristics, prescription trends, and frequency of medication use among pediatric insomnia patients. Patterns of combination therapy were also examined.

RESULTS

The number of children receiving insomnia medications increased substantially from 228 in 2016 to 1166 in 2023, representing an approximate 409 % increase. A growing proportion of patients were aged 12-14 years, with female patients outnumbering males by a ratio of 1.50: 1. There was an increased representation of patients from psychiatry and neurology departments. Regarding medication choices, benzodiazepines (BZDs) remained the most commonly prescribed class, though their use showed a declining trend. Similarly, non-benzodiazepine receptor agonists (nBZRAs) demonstrated a downward trend (P > 0.05), while antidepressant prescriptions significantly increased (P < 0.05). The most commonly prescribed medications within each class were alprazolam, zolpidem, trazodone, sertraline, and quetiapine. A significant proportion of patients (37.25 %) received combination therapy, with benzodiazepine receptor agonists (BZRAs) plus antidepressants being the most common combination.

CONCLUSIONS

The utilization of pharmacological interventions for pediatric insomnia in China has risen markedly in recent years. Despite growing concerns about adverse effects, BZDs continue to be the primary therapeutic choice. The increasing prevalence of combination therapy suggests a trend toward more individualized treatment approaches. These findings underscore the importance of careful monitoring and rational prescribing practices in pediatric insomnia management.

Associations between multiple sleep dimensions and suicide and non-suicidal self-injury: a cross-sectional study of 3828 Chinese young people

PURPOSE

Suicide and non-suicidal self-injury (NSSI) are preventable concerns in young people. Suicidal ideation (SI), suicidal plans (SP) and suicidal attempt (SA) are closely related to death. Sleep problems are known risk factors for suicide and NSSI. This study aimed to explore the relationship between sleep, suicidality and NSSI.

METHODS

Participants were 3,828 middle school and college students aged 11-23 years from urban and rural areas of Henan Province. Sleep, suicidal phenomena and NSSI were assessed by applying self-reported questionnaires. Chi-squared tests were utilized to demonstrate the demographic data and sleep variables. The correlation between sleep, suicidality and NSSI were explored by using binary logistic regression, while adjusting socio-demographic characteristics with multivariate models.

RESULTS

Sleep variables except mid-sleep time were related to suicidal phenomena (P < 0.05). Greater social jet lag (SJL) [≥ 2 h (h)] was associated with increased risk of SI [Odds ratios (OR) = 1.72, 95% confidence intervals (CI):1.40-2.11], SP (OR = 2.10, 95%CI:1.59-2.79) and SA (OR = 1.50, 95%CI:1.00-2.26). Non-only child participants with SJL (≥ 2 h) had significantly increased odds of SI (OR = 1.75, 95%CI: 1.41-2.18) and SP (OR = 2.25, 95%CI: 1.66-3.05). Eveningness chronotype had the strongest correlation with SI (OR = 3.87, 95%CI:2.78-5.38), SP (OR = 4.72, 95%CI:2.97-7.50), SA (OR = 6.69, 95%CI:3.08-14.52) and NSSI (OR = 1.39, 95%CI:1.02-1.90).

CONCLUSION

Overlong or short sleep duration, SJL, eveningness chronotype and other sleep abnormalities (e.g., daytime dysfunction, low sleep efficiency) were associated with a higher prevalence of SI, SP and SA. Additionally, eveningness was significantly correlated with NSSI among young people. These findings suggested the importance of assessing and intervening in sleep habits to prevent suicide and NSSI in young people.

Isolated Rem Sleep Behavior Disorder: A Model to Assess the Overnight Habituation of Emotional Reactivity

(1) Background: Phasic events in rapid eye movement (REM) sleep are a core feature of isolated REM behavior disorder (iRBD), which is often associated with emotion dysregulation. This study explores the relationship between sleep and the overnight habituation of emotional reactivity in healthy controls (HCs) and iRBD patients, focusing on the role of REM phasic events and a specific non-REM waveform, namely sleep spindles. (2) Methods: Participants underwent polysomnography and completed arousal rating tasks and mood scales before and after sleep. In total, eight HCs (4 M, mean age 60.62 ± 6.8) and eight iRBD patients (7 M, mean age 68.25 ± 5.12) were included in the analyses. (3) Results: In HCs, longer REM sleep duration correlated positively with overnight habituation. In the whole sample, overnight habituation negatively correlated with REM sleep latency and wake-after-sleep onset, and positively with N2 sleep. Higher overnight habituation was associated with fewer REM arousals and awakenings in the whole sample, and with greater N2 sleep spindle density in HCs. (4) Conclusions: Our preliminary results suggest that REM sleep and spindles in N2 play critical roles in emotional processing. The study confirms the relationship between emotion dysregulation and REM phasic events, enhancing our understanding of how sleep impacts emotional reactivity and also in the prodromal phase of neurodegenerative disease.

Genetic Correlates of Treatment-Resistant Depression

Importance

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits and explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us (AoU) Research Program.

Design, Setting, and Participants

This study was a cohort design with observational data from participants in the AoU Research Program who have both electronic health records and genomic data. Data analysis was performed from March 27 to October 24, 2024.

Exposures

PGS for 61 unique traits from 7 domains.

Main Outcomes and Measures

Logistic regressions to test if PGS was associated with treatment-resistant depression (TRD) compared with treatment-responsive major depressive disorder (trMDD). Cox proportional hazard model was used to determine if the progressions from MDD to TRD were associated with PGS.

Results

A total of 292 663 participants (median [IQR] age, 57 (41-69) years; 175 981 female [60.1%]) from the AoU Research Program were included in this analysis. In the discovery set (124 945 participants), 11 of the selected PGS were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia (odds ratio [OR], 1.11; 95% CI, 1.07-1.15) and specific neuroticism (OR, 1.11; 95% CI, 1.07-1.16) traits were associated with increased TRD risk, whereas higher education (OR, 0.88; 95% CI, 0.85-0.91) and intelligence (OR, 0.91; 95% CI, 0.88-0.94) scores were protective. The associations held across different TRD definitions (meta-analytic R2 >83%) and were consistent across 2 other independent sets within AoU (the whole-genome sequencing Diversity dataset, 104 388, and Microarray dataset, 63 330). Among 28 964 individuals followed up over time, 3854 developed TRD within a mean of 944 days (95% CI, 883-992 days). All 11 previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD.

Conclusions and Relevance

Results of this cohort study suggest that genetic predisposition related to neuroticism, cognitive function, and sleep patterns had a significant association with the development of TRD. These findings underscore the importance of considering psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance understanding of pathways leading to treatment resistance.

Effect of insomnia on anxiety and depression: Mediation of cognitive failures and moderated mediation of neuroticism

BACKGROUND

The coronavirus disease 2019 pandemic has had an ongoing impact on the public's mental health that requires long-term attention. Exploring the relationship between mental health indicators would aid in identifying solutions to improve public mental health.

AIM

To investigate the prevalence of anxiety, depression, and insomnia and explore the relationship among neuroticism, cognitive failures, and mental health.

METHODS

A cross-sectional survey was conducted in December 2023 using an online platform to recruit adult participants. The neuroticism, subjective cognitive function, and mental health of the participants were assessed using the neuroticism subscale of the Chinese Big Five Personality Inventory Brief Version, cognitive failures questionnaire, generalized anxiety disorder-7, patient health questionnaire-9, and insomnia severity index. Pearson's correlation analysis, independent samples t-tests, one-way analysis of variance, and structural equation model were used to examine the relationship between mental health indicators.

RESULTS

A total of 1011 valid questionnaires were collected, of which 343 were completed by male (33.93%) respondents and 668 were completed by female (66.07%) respondents. The rates of anxiety, depression, and insomnia were 41.3%, 44.6%, and 36.3%, respectively, most cases of which were mild. Among the mental health indicators, there were significant differences by age and between those with siblings and those who were only children. Neuroticism and cognitive failures were significantly positively correlated with mental health indicators. Further moderated mediation analysis showed that cognitive failures mediated the relationship between insomnia and anxiety and between insomnia and depression, with neuroticism moderating the first half of this pathway and the effect being greater in the low-neuroticism group.

CONCLUSION

Cognitive failures and neuroticism play important roles in mental health. Therefore, enhancing subjective cognitive function and regulating emotional stability may contribute to the improvement of mental health.

Explainable Artificial Intelligence Models for Predicting Depression Based on Polysomnographic Phenotypes

Depression is a common mental health disorder and a leading contributor to mortality and morbidity. Despite several advancements, the current screening methods have limitations in enabling the robust and automated detection of depression, thereby hindering early diagnosis and timely intervention. This study aimed to develop explainable artificial intelligence (AI) models to predict depression using polysomnographic phenotype data, ensuring high predictive performance while providing clear insights into the importance of features influencing the risk of depression. Advanced machine learning algorithms such as random forest, extreme gradient boosting, categorical boosting, and light gradient boosting machines were employed to train and validate the predictive AI models. Phenotype data from subjective health questionnaires, clinical assessments, and demographic factors were analyzed. The explainable AI models identified the important features, and their performance was evaluated using cross-validation. The study population, comprising 114 control participants and 39 individuals with depression, was stratified based on validated depression-scoring methods. The proposed explainable AI models achieved an F1-score of 85%, verifying their high reliability in predicting depression. Key features influencing the risk of depression, such as anxiety disorders, sleep efficiency, and demographic factors, offer actionable insights for clinical practice, highlighting the transparency of these models. This study proposed and developed explainable AI models based on polysomnographic phenotype data for the automated detection of depression and verified that these models help improve mental health diagnostics, enabling timely interventions.

Association between sleep duration and depression in adolescents and young adults: a system review of observational studies and a genetic research of Mendelian randomization analysis

OBJECTIVES

This study aimed to explore the causal association between sleep duration and depression in adolescents and young adults.

METHODS

We conducted a systematic review and Mendelian randomization (MR) to research the causal relationship between short sleep duration and adolescent depression risk from an observational and genetic perspective. In the systematic review, we searched observational studies from the PubMed, Embase, and Cochrane Library databases. In the MR analysis part, we screened Single Nucleotide Polymorphism (SNP) significantly relative to short sleep and conforming MR concept to investigate the genetic causality.

RESULTS

All research evidence shows that adolescents who sleep <6 h have the highest rates of depression. According to the MR result, short sleep duration significantly affected the depression risk (odds ratio, 1.034; 95% confidence interval, 1.012-1.058, P = .003). Sleep duration of 7-8 h has the lowest depression incidence. Insufficient sleep (≤6 h) and excessive sleep (≥8 h) also elevates adolescent depression risk. Genetic evidence shows that short sleep duration (<6 h) has significant causal effects on depression risk.

CONCLUSIONS

Sleep duration was causally associated with depression in adolescents and young adults. Sleep duration of <6 h or >8 h daily increases the depression risk in adolescents and young adults.

Dynamic functional connectivity patterns predict early antidepressant treatment response in drug-naïve, first-episode adolescent MDD

Objective

Adolescents with major depressive disorder (MDD) exhibit abnormal dynamic functional connectivity (dFC) patterns, but it remains unclear whether these aberrant dFC patterns are linked to antidepressant treatment. The aim of this study is to investigate whether dFC patterns will be changed by antidepressant treatment, as well as whether baseline dFC pattern could predict treatment response in adolescent MDD patients.

Method

We included 35 drug-naïve, first-episode MDD adolescents (age 14.40 ± 1.24; 8 males and 27 females) and 24 healthy controls (HCs, age 14.21 ± 1.41; 11 males and 13 females). All MDD adolescents received 6 weeks of antidepressant treatment. Resting state and T1 MRI data were collected in MDD adolescents before and after treatment and in HCs. Independent component analysis (ICA) was used to compare the different dFC pattern between MDD adolescents and HCs at baseline, as well as which between before and after treatment in MDD adolescents. Finally, Pearson correlation and multivariate linear regression analyses were used to explore the associations between dFC pattern and changed score of BDI in MDD adolescents.

Results

The mean dFC value between right inferior frontal gyrus (IFG) and bilateral insular cortex (IC; right, r = -0.461, p-FDR = 0.012; left, r = -0.518, p-FDR = 0.007) at baseline were negatively correlated with BDI score reduction. The mean dFC value between left frontal pole (FP) and right superior parietal lobule (SPL) after treatment was positively correlated with BDI score reduction (r = 0.442, p-FDR = 0.014). And the mean dFC values between right IFG and bilateral IC (right, β = -1.563, p-FDR = 0.021; left, β = -1.868, p-FDR = 0.012) at baseline could predict antidepressant treatment response.

Conclusion

These findings demonstrate that dFC patterns between some brain areas could be a prospective factor for predicting antidepressant treatment response.

Trends in hypnotic drug use in depression 2007-2017: A Swedish population-based study

Insomnia is a common feature of depression; however, depression treatment guidelines provide limited recommendations regarding hypnotic drugs. Few studies have thoroughly investigated the use of hypnotic drugs in depression. In this cohort study using national Swedish registers, we included all patients ≥18 years with incident unipolar depression during 2007-2017. Patients were followed for 3 years, noting the annual and quarterly prevalence of hypnotic drug use from prescription fills. Prevalence ratios (PR) comparing 2017 to 2007 were calculated with 95% confidence intervals (CI). A total of 222,077 patients with depression were included (mean age 41 years, 59% women). In the year following diagnosis, 44.1% used any hypnotic drug in 2017, compared with 46.7% in 2007 (PR 0.94, 95% CI 0.92-0.97). The most commonly used drugs were Z-drugs (zopiclone, zolpidem, and zaleplon) with a prevalence of 27.6% in 2017 and 35.6% in 2007 (PR 0.78, 95% CI 0.75-0.80). Melatonin use increased sharply to 12.0% in 2017 from 0.4% in 2007 (PR 28.9, 95% CI 23.5-35.7). Hypnotic drug use was most prevalent in the first two quarters after diagnosis; however, after 3 years, the quarterly prevalence was still 19.2%. Hypnotics were more common among women, older patients, those with somatic comorbidities, more severe depression, or a history of suicide attempt. Evidence from this large register-based study demonstrates that hypnotics were used to a large extent in depression in Sweden 2007-2017. Z-drugs use declined and melatonin use increased dramatically. Hypnotic drug use remained high even 3 years after diagnosis.

States of consciousness and interoceptive hypersensibility: A study in patients with insomnia disorder

This exploratory study aimed to investigate the relationship between interoceptive sensibility and quality of consciousness in individuals with insomnia disorder, in order to understand how the modulation of internal states may contribute to modifying the experience of consciousness during sleep difficulties. A total of 37 patients with insomnia disorder (mean age = 46.05 ± 18.16) and 41 healthy good sleepers (mean age = 50.2 ± 12.99) underwent a psychometric sleep and interoceptive sensibility assessment, using Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and Multidimensional Assessment of Interoceptive Awareness (MAIA). Moreover, patients with insomnia disorder also completed a quality of consciousness evaluation, using the Phenomenology of Consciousness Inventory (PCI). Patients with insomnia disorder exhibited heightened interoceptive sensibility, particularly in noticing body sensations (p < 0.0001) and emotional awareness (p = 0.032), along with diminished abilities in attention regulation (p = 0.040), not-worrying (p = 0.001), and trusting (p = 0.002). Furthermore, correlations between interoceptive sensibility and multiple aspects of the consciousness state during the insomnia night were identified. Specifically, higher emotional awareness was linked to a 2.49-fold increase in the likelihood of subjectively experiencing altered consciousness states during insomnia. The study sheds light on the relationship between interoceptive sensibility and the subjective state of consciousness during insomnia, emphasising the importance of exploring and considering interoception as part of the therapeutic process for insomnia disorder. Given the exploratory nature of the study and the increased risk of type-I error from numerous correlations, the results should be interpreted with caution. Further research is needed to validate and confirm their robustness.

Bidirectional relationship between sleep and depression

Patients with depression almost inevitably exhibit abnormalities in sleep, such as shortened latency to enter rapid eye movement (REM) sleep and decrease in electroencephalogram delta power during non-REM sleep. Insufficient sleep can be stressful, and the accumulation of stress leads to the deterioration of mental health and contributes to the development of psychiatric disorders. Thus, it is likely that depression and sleep are bidirectionally related, i.e. development of depression contributes to sleep disturbances and vice versa. However, the relation between depression and sleep seems complicated. For example, acute sleep deprivation can paradoxically improve depressive symptoms. Thus, it is difficult to conclude whether sleep has beneficial or harmful effects in patients with depression. How antidepressants affect sleep in patients with depression might provide clues to understanding the effects of sleep, but caution is required considering that antidepressants have diverse effects other than sleep. Recent animal studies support the bidirectional relation between depression and sleep, and animal models of depression are expected to be beneficial for the identification of neuronal circuits that connect stress, sleep, and depression. This review provides a comprehensive overview regarding the current knowledge of the relationship between depression and sleep.

Prospective associations between heterogeneous sleep profiles and depressive symptoms in adolescents: The mediating role of coping styles

INTRODUCTION

Extant literature has linked sleep disturbance to depressive symptoms. However, the coexistence of naturally occurring sleep profiles among adolescents and the prospective associations between sleep profiles and depressive symptoms remain poorly understood. This study aims to uncover sleep patterns in Chinese adolescents based on a comprehensive set of sleep features (e.g., latency, daytime dysfunction, etc.) derived from the Pittsburg Sleep Quality Index (PSQI) and investigate the relationship between these profiles and subsequent depressive symptoms mediated by positive and negative coping styles.

METHODS

Five thousand five hundred five adolescents from Shandong province, China, enrolled (Mage = 16.83 years; 49.9% girls) in a two-wave longitudinal study (T1 in August 2023; T2 in February 2024). Latent class analysis (LCA) was conducted to identify adolescent sleep patterns. Mediation and sensitivity analyses were used to examine prospective associations between sleep patterns, coping styles, and depressive symptoms.

RESULTS

Four qualitatively distinct sleep profiles emerged: Healthy Sleepers (18.9%), Latency but Functioning Sleepers (13.6%), Efficient but Dysfunctional Sleepers (57.5%), and Medicated Maladaptive Sleepers (10.0%). Using the Healthy Sleepers as a reference group, Latency but Functional Sleepers, Efficient but Dysfunctional Sleepers, and Medicated Maladaptive Sleepers all predicted subsequent depressive symptoms through positive coping styles rather than negative coping styles. The relative indirect effects were 0.19, 0.19, and 0.32, respectively.

CONCLUSIONS

The study underscored that adolescents exhibit distinct sleep patterns, and specific sleep profiles may be prospectively associated with depressive symptoms mediated by positive coping styles.

Research advances in children's sleep and vitamin D levels

In recent years, studies have revealed that vitamin D, a steroid hormone essential for calcium and phosphorus metabolism, also plays a role in sleep. Adequate levels of vitamin D have been linked to improved sleep quality in children and effective prevention of sleep problems. This report is a review and summary of research on the significance of sleep, the stages of children's sleep, and the impact of vitamin D levels on sleep problems. Additionally, this report explores the mechanisms through which vitamin D improves sleep.

Developing an individual depression risk score based on traditional risk factors and routine biochemical markers

BACKGROUND

Early identification of individuals at high risk for depression is essential for effective implementation of interventions. This study utilized the UK Biobank database to construct an individual depression risk score using nomogram and explored the potential of traditional risk factors and routine biochemical markers for the auxiliary diagnosis of individual depression.

METHODS

A total of 369,407 participants were included in the study and divided into training and testing sets. LASSO regression was employed to select predictive variables for depression from 16 traditional risk factors and 28 routine biochemical markers. Following variable selection, two multivariable logistic regression models were constructed. Nomograms were then generated to visualize the relationships between these variables and depression risk, and to facilitate the calculation of individual depression risk scores.

RESULTS

Twelve traditional risk factors and nine biochemical markers were selected for model building. Model 1, using only traditional risk factors, achieved the area under the curve (AUC) of 0.913 (95 % CI: 0.910-0.915), while Model 2, incorporating both traditional and routine biochemical markers, yielded an AUC of 0.914 (95 % CI: 0.912-0.917). Based on optimal cut-off values, Model 1 exhibited a sensitivity of 81.99 % and a specificity of 83.76 %, while Model 2 demonstrated a sensitivity of 81.54 % and a specificity of 84.31 %.

LIMITATIONS

External validation is still needed to confirm the model's generalizability.

CONCLUSIONS

While the depression risk scoring model built using traditional risk factors effectively identifies high-risk individuals for depression and demonstrates good clinical performance, incorporating routine biochemical markers did not significantly improve the model's performance.

Insomnia symptom severity and dynamics of arousal-related symptoms across the day

Arousal is a central component of many emotional symptoms and can contribute to insomnia. Here we assessed how the timing and fluctuating nature of arousal-related symptoms over the course of the day relate to insomnia symptom severity. In this study, 361 participants (M age = 31.9 years, 282 women, 77 men, 2 non-binary individuals) completed the Insomnia Severity Index to assess severity of insomnia symptoms, followed by repeated ratings of anxiety or nervousness, stress, sleepiness, and feeling down via their mobile phone between ~08:00 hours and 00:00 hours across 1 day. Measures of dynamics included: mean levels across the day; variation (standard deviation); instability (mean squared successive differences); and resistance to change/inertia (first-order autocorrelation). Time-of-day patterns were modelled using generalized additive mixed effects models. Insomnia symptom severity (mean Insomnia Severity Index = 9.1, SD = 5.2, range 0-25) was associated with higher mean levels of all arousal-related symptoms, and increased instability and variation throughout the day in anxiety or nervousness, stress, and feeling down. Resistance to change (inertia) was not associated with insomnia symptom severity. Generalized additive mixed effects analyses showed that while individuals with more severe insomnia symptoms had elevated symptoms across the entire day, they were especially more anxious or nervous and sleepy in the early morning (~08:00 hours), anxious or nervous, stressed and sleepy in the late afternoon/early evening (~16:00 hours-21:00 hours), and anxious or nervous and stressed in the late evening (~22:00 hours). Remarkably, higher arousal occurred in the presence of high subjective sleepiness. Together these results indicate that insomnia symptom severity is associated with problems with daytime and evening arousal regulation.

Comparative efficacy and safety of Chinese patent medicines for primary insomnia: A systematic review and network meta-analysis of 109 randomized trials

ETHNOPHARMACOLOGICAL RELEVANCE

Chinese patent medicine (CPM) is formulated using Chinese herbal medicines as raw materials according to prescribed methods and preparation processes. It is one of the most commonly used complementary and alternative therapies for insomnia in China. Dozens of CPMs have been applied in clinical settings to treat primary insomnia, and ample evidence has proven the efficacy and safety of various CPMs.

AIM OF THE STUDY

We aimed to use the network meta-analysis method to simultaneously compare the efficacy and safety of Chinese patent medicines for primary insomnia.

MATERIALS AND METHODS

We systematically searched eight databases from their inception to July 2022. The relevant randomized controlled trials (RCTs) were eligible if they compared one CPM or one CPM plus a Western drug with another CPM or with Western drug/placebo in adults with primary insomnia. Two reviewers independently performed literature screening, data extraction, and risk of bias assessment. We evaluated the certainty of evidence utilizing CINeMA (Confidence in Network Meta-Analysis) framework.

RESULTS

A total of 109 RCTs involved 11,488 patients (54.26% female) with a median age of 47.97 years. Forty-five CPMs were assessed in this study. Compared with placebo and Benzodiazepine drugs, Shugan Jieyu capsules, Shenqi Wuweizi tablets, and Tianmeng oral liquid/capsules combined with Benzodiazepine drugs significantly improved sleep quality. Compared to Benzodiazepine drugs, both Shenqi Wuweizi tablets and Anshen Bunao liquid/granules significantly prolonged subjective total sleep duration and reduced sleep onset latency. Considering safety, all CPMs showed an insignificant difference or lower risk of gastrointestinal and dizziness events compared to Western drugs or placebo. The certainty of evidences was rated as low or very low.

CONCLUSION

This meta-analysis demonstrated the efficacy and safety of CPMs for primary insomnia, especially several CPMs such as Shugan Jieyu capsules, Shenqi Wuweizi tablets and Tianmeng oral liquid, which have shown their potential benefits. However, the present conclusions are based on low quality trials. Well-designed trials, including rigorous methods and patient-important outcomes, are required to verify these results.

Therapeutic potential of Rosa roxburghii folium extract in insomnia treatment: a comprehensive evaluation of behavioral and neurochemical effects in a PCPA-induced mouse model

BACKGROUND

Insomnia, a prevalent sleep disorder, detrimentally affects quality of life and is often challenging to manage with conventional treatments. This study delved into identifying and quantifying the main compounds by employing ultra-performance liquid chromatography-Q-Exactive-Orbitrap mass spectrometry, and further to evaluate the therapeutic potential of Rosa roxburghii folium (RRF) extract, with multiple pharmacological activities. Previous research had hinted at the efficacy of glycosides in influencing the γ-aminobutyric acid (GABAergic) system, which plays a pivotal role in sleep regulation. Utilizing a p-chlorophenylalanine-induced insomnia model in BALB/C mice, this investigation aimed to unravel the effects of various dosages of RRF extract on sleep quality and elucidated its mechanism of action.

RESULTS

A total of 66 compounds in the RRF extract were analyzed. Behavioral assessments demonstrated notable enhancements in sleep duration and latency. Biochemical analyses further corroborated these findings, revealing modulation in neurotransmitter levels indicative of a potential mechanism through the GABAergic and serotoninergic pathways. Additionally, histological evaluations suggested anti-inflammatory and antioxidant effects of the RRF extract.

CONCLUSION

The findings from this study underscored the therapeutic efficacy of RRF extract in combating insomnia, particularly highlighting its glycoside components' role. The extract's significant improvement in sleep duration and latency, alongside its modulation of neurotransmitter levels, showcases its potential as a natural remedy for insomnia. Through its action on the GABAergic and serotoninergic pathways, as well as its anti-inflammatory and antioxidant effects, RRF extract emerges as a promising candidate for insomnia treatment, offering a holistic approach to sleep disorder management. © 2024 Society of Chemical Industry.

Systematic Review and Meta-Analysis: The Association Between Newer-Generation Antidepressants and Insomnia in Children and Adolescents With Major Depressive Disorder

OBJECTIVE

To examine the association between newer generation antidepressants and insomnia as an adverse event (AE) in the treatment of children and adolescents with major depressive disorder (MDD).

METHOD

A systematic search was performed in major databases (inception to August 31, 2023) to retrieve double-blind, placebo-controlled, randomized controlled trials (RCTs) evaluating the safety of 19 antidepressants in the acute treatment (initial 6-12 weeks) of children and adolescents ≤18 years of age with MDD (primary analyses). RCTs in anxiety disorders and obsessive-compulsive disorder (OCD) were retrieved from a recent meta-analysis and included in complementary analyses. A mixed-effects logistic regression model was used to compare the frequency of insomnia in the antidepressant relative to the placebo group. Risk of bias was evaluated using the Cochrane Risk of Bias 2 tool.

RESULTS

In total, 20 trials in MDD (N = 5,357) and 8 trials in anxiety disorders and OCD (N = 1,271) evaluating selective serotonin reuptake inhibitors (SSRIs) or serotonin-norepinephrine reuptake inhibitors (SNRIs) were included. In MDD, antidepressant treatment was associated with a modest increase in the odds of insomnia compared with placebo (odds ratio [OR] = 1.65, 95% CI = 1.21-2.27, p = .002), with no significant difference between SSRIs and SNRIs. The RCTs showed low risk of bias or minor concerns for the assessment of insomnia. The odds of treatment-emergent insomnia were significantly lower in MDD (OR = 1.62; 95% CI = 1.21-2.15) compared to anxiety disorders and OCD (OR = 2.89; 95% CI = 1.83-4.57) for treatment with SSRIs (p = .03). Among individual antidepressants with evidence from ≥3 studies, sertraline had the highest OR (3.45; 95% CI = 1.91-6.24), whereas duloxetine had the lowest OR (1.38; 95% CI = 0.79-2.43).

CONCLUSION

Children and adolescents are at a modestly increased risk for experiencing insomnia during the first 6 to 12 weeks of treatment with SSRIs and SNRIs. Antidepressant- and disorder-specific variability in the risk of treatment-emergent insomnia may be relevant to consider in clinical decision making.

STUDY PREREGISTRATION INFORMATION

The association between newer generation antidepressants and insomnia in children and adolescents with major depressive disorder: a meta-analysis of randomized controlled trials; https://www.crd.york.ac.uk; CRD42023330506.

A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly

BACKGROUND

With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China as a sample to predict the risk factors of depression in the elderly population from both holistic and individual level.

METHODS

A total of participants met the inclusion criteria from the fourth waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed with ML algorithms. The level of depression was assessed by the 10-item Center for Epidemiological Studies Depression Scale (CESD-10).

RESULTS

The current study found top 5 factors that were important for predicting depression in the elderly population in China, including average sleep time, gender, age, social activities and nap time during the day. The results also provide reliable diagnostic likelihood at the individual level to support clinicians identify the most impactful factors contributing to patient depression. Our findings also suggested that activities such as interacting with friends and play ma-Jong, chess or join community clubs may have a positive collaborative effect for elderly's mental health.

CONCLUSIONS

Holistic approaches are an effective method of deriving and interpreting sophisticated models of mental health in elderly populations. More detailed information about a patient's demographics, medical history, sleeping patterns and social/leisure activities can help to inform policy and treatment interventions on a population and individual level. Large scale surveys such as CHARLS are effective methods for testing the most accurate models, however, further research using professional clinical input could further advance the field.

Shenling Baizhu San alleviates central fatigue through SIRT1-PGC-1α-Mediated mitochondrial biogenesis

ETHNOPHARMACOLOGICAL RELEVANCE

Shenling Baizhu San (SLBZS) is a Traditional Chinese Medicine (TCM) formula composed of 10 medicinal herbs, historically used to strengthen the spleen, replenish qi, and alleviate fatigue-related symptoms. SLBZS originates from the 'Taiping Huimin Heji Ju Fang' of the Song Dynasty. Central fatigue (CF), a subtype of fatigue, is considered in TCM to be closely associated with spleen deficiency. However, there is currently a lack of research on SLBZS's therapeutic effects on CF and the pharmacological mechanisms underlying its potential benefits.

AIM OF THE STUDY

This study aims to assess the effects of SLBZS on CF in rats induced by the Modified Multiple Platform Method (MMPM) and to elucidate the underlying mechanisms, focusing on mitochondrial biogenesis and SIRT1/PGC-1α pathway regulation.

MATERIALS AND METHODS

CF was induced in male Wistar rats using MMPM, involving intermittent sleep deprivation over 21 days. SLBZS was administered at low(LSLBZS), medium(MSLBZS), and high doses(HSLBZS). Chemical components of SLBZS were identified and quantified using Liquid Chromatography-Tandem Mass Spectrometry(LC-MS/MS). Behavioral tests evaluated physical performance, emotional state, and cognitive function, while serum biochemical markers, mitochondrial morphology, and the protein and gene expression levels of the SIRT1/PGC-1α pathway were analyzed to explore underlying mechanisms.

RESULTS

A total of 141 main compounds in SLBZS were identified, comprising various components such as flavonoids, phenylpropanoids, terpenoids, among others. SLBZS significantly improved physical performance, alleviated negative emotions, and enhanced cognitive function in CF rats. Biochemically, SLBZS increased serum ATP levels and reduced fatigue-related markers. Mitochondrial analysis demonstrated that SLBZS reversed mitochondrial degeneration, increased mitochondrial number, and increased mtDNA copy number in the hippocampus. Furthermore, SLBZS upregulated SIRT1/PGC-1α pathway expression at both the protein and gene levels in the hippocampus. Notably, the HSLBZS group demonstrated particularly pronounced effects.

CONCLUSION

SLBZS significantly alleviates CF symptoms enhances mitochondrial function via upregulating the SIRT1/PGC-1α pathway, positioning it as a promising alternative for CF management by addressing both its physiological and symptomatic aspects.

Aberrant individual large-scale functional network connectivity and topology in chronic insomnia disorder with and without depression

Insomnia is increasingly prevalent with significant associations with depression. Delineating specific neural circuits for chronic insomnia disorder (CID) with and without depressive symptoms is fundamental to develop precision diagnosis and treatment. In this study, we examine static, dynamic and network topology changes of individual large-scale functional network for CID with (CID-D) and without depression to reveal their specific neural underpinnings. Seventeen individual-specific functional brain networks are obtained using a regularized nonnegative matrix factorization technique. Disorders-shared and -specific differences in static and dynamic large-scale functional network connectivities within or between the cognitive control network, dorsal attention network, visual network, limbic network, and default mode network are found for CID and CID-D. Additionally, CID and CID-D groups showed compromised network topological architecture including reduced small-world properties, clustering coefficients and modularity indicating decreased network efficiency and impaired functional segregation. Moreover, the altered neuroimaging indices show significant associations with clinical manifestations and could serve as effective neuromarkers to distinguish among healthy controls, CID and CID-D. Taken together, these findings provide novel insights into the neural basis of CID and CID-D, which may facilitate developing new diagnostic and therapeutic approaches.

Preliminary feasibility and efficacy of a brief behavioural treatment for insomnia after acquired brain injury: A case series

Insomnia after acquired brain injury (ABI) is common and can negatively impact an individual's rehabilitation, recovery, and quality of life. The present study investigated the feasibility and preliminary efficacy of a Brief Behavioural Treatment for Insomnia (BBTI) in a community sample following ABI. Ten participants were recruited. Seven participants attended four weekly sessions of BBTI and kept a daily sleep diary. Participants completed a semi-structured sleep interview at baseline and self-report measures of sleep, anxiety, and depression pre- and post-treatment as well as a treatment acceptability questionnaire post-treatment. Follow-up data were collected at 1-, 2-, and 3-months post-treatment. Visual analyses of the data were performed on a case-by-case basis. Five of the seven participants (71%) no longer met the criteria for insomnia disorder on the Sleep Condition Indicator (SCI) post-treatment. Treatment effects on sleep outcomes were either maintained or augmented at follow-ups. BBTI was found to be well tolerated, as evidenced by the high overall retention rates (70%) and positive feedback on the treatment acceptability questionnaire. These results provide preliminary evidence of BBTI being both feasible to use and potentially efficacious in individuals with post-brain-injury insomnia. Larger-scale randomised controlled trials are needed to establish the effectiveness of BBTI following ABI.