A Fully Remote Randomized Trial of Transcranial Alternating Current Stimulation for the Acute Treatment of Major Depressive Disorder.

Objective: Major depressive disorder (MDD) is common, but current treatment options have significant limitations in terms of access and efficacy. This study examined the effectiveness of transcranial alternating current stimulation (tACS) for the acute treatment of MDD.Methods: We performed a triple-blind, fully remote, randomized controlled trial comparing tACS with sham treatment. Adults aged 21-65 years meeting DSM 5 criteria for MDD and having a score on the Beck Depression Inventory, Second Edition (BDI-II), between 20 and 63 were eligible to participate. Participants utilized tACS or sham treatment for two 20-minute treatment sessions daily for 4 weeks. The primary outcome was change in BDI-II score from baseline to the week 2 time point in an intent-to treat analysis, followed by analyses of treatment-adherent participants. Secondary analyses examined change at the week 1 and 4 time points, responder rates, subgroup analyses, other self-report mood measures, and safety. The study was conducted from April to October 2022.Results: A total of 255 participants were randomized to active or sham treatment. Improvement in intent-to-treat analysis was not statistically significant at week 2 (P= .056), but there were significant effects in participants with high adherence (P= .005). Significantly greater improvement at week 1 (P= .020) and greater response at week 4 (P= .028) occurred following tACS. Improvements were significantly larger for female participants. There were no significant effects on secondary mood measures. Side effects were minimal and mild.Conclusions: Rapid, clinically significant improvement in depression in adults with MDD was associated with tACS, particularly for women. Compared to other depression therapies, tACS has 3 key advantages: rapid, clinically significant treatment effect, the ability of patients to use the treatment on their own at home, and the rarity and low impact of adverse events.Trial Registration: ClinicalTrials.gov identifier: NCT05384041.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. We developed a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry. After exclusion, 1448 participant nights of data were used for training. The difference between polysomnography and the model classifications on the external validation was 34.7 min (95% limits of agreement (LoA): -37.8-107.2 min) for total sleep duration, 2.6 min for REM duration (95% LoA: -68.4-73.4 min) and 32.1 min (95% LoA: -54.4-118.5 min) for NREM duration. The sleep classifier was deployed in the UK Biobank with 100,000 participants to study the association of sleep duration and sleep efficiency with all-cause mortality. Among 66,214 UK Biobank participants, 1642 mortality events were observed. Short sleepers (<6 h) had a higher risk of mortality compared to participants with normal sleep duration of 6-7.9 h, regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.58; 95% confidence intervals (CIs): 1.19-2.11) or high sleep efficiency (HRs: 1.45; 95% CIs: 1.16-1.81). Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Nurse practitioner-led, virtually delivered, motivational enhancement and device support intervention to improve CPAP adherence: A feasibility randomized control trial.

BACKGROUND: Evidence indicates continuous positive airway pressure (CPAP) therapy improves several important patient-centered outcomes. However, adherence to this safe and effective intervention remains poor. OBJECTIVES: Assess nine feasibility outcomes of a nurse practitioner-led, virtually delivered motivational enhancement and device support (MENDS) intervention to improve CPAP adherence in adults with Obstructive Sleep Apnea (OSA). Secondary aims compared the changes in CPAP adherence to patient-reported outcomes, patient activation, and perceived self-efficacy. METHODS: This two-group feasibility randomized controlled trial included 29 patients newly diagnosed with OSA and prescribed CPAP therapy. The study was conducted from July 2020 through December 2021 at a midwestern sleep/pulmonary clinic. Participants were randomized to the MENDS intervention group (n=14) (30-45 minute interactive tele-discussions on weeks 2, 4, 6, and 8) or to the usual care (n=15) group. Feasibility, patient-reported outcomes, and behavioral constructs were measured at baseline and 12 weeks. CPAP adherence was measured weekly. RESULTS: Feasibility of the MENDS sessions was demonstrated (56 sessions offered, 52 completed remotely without technical difficulties) with minimal participant attrition and no missing CPAP data. Generalized linear mixed models showed no statistically significant time-by-group interactions on adherence or patient-reported outcomes. Higher adherence and lower CPAP apnea-hypopnea index (AHI) scores were associated with declines in pre- to post-changes in fatigue and sleep disturbance. Lower CPAP AHI scores were associated with pre- to post-decreases in PROMIS Anxiety scores (r=.532, p=.005). CONCLUSION: The virtual MENDS intervention was feasible. Higher CPAP adherence and lower AHI levels led to positive improvements in fatigue, sleep disturbance, and anxiety.

Neighborhood disadvantage is associated with sleep disturbance in a sample of trauma-exposed Veterans.

OBJECTIVES: This study examined associations among neighborhood disadvantage, all-night respiratory sinus arrhythmia, fear of sleep, nightmare frequency, and sleep duration in a sample of trauma-exposed Veterans. METHODS: Participants completed baseline assessments and slept on a mattress actigraphy system for seven nights. Neighborhood disadvantage was assessed with the Area Deprivation Index, a census-based socioeconomic index. Differences between the least and most disadvantaged groups on the sleep variables were analyzed. RESULTS: Data were available from 37 Veterans. Residing in neighborhoods with greater disadvantage was associated with elevated fear of sleep and reduced sleep-period respiratory sinus arrhythmia. No significant differences were observed for nightmare frequency or sleep duration. A regression confirmed that neighborhood context had a significant effect on respiratory sinus arrhythmia, after controlling for other baseline sleep variables. CONCLUSIONS: In this sample of Veterans, sleep context may increase hypervigilance in turn serving as a mechanism by which trauma-induced sleep disruptions are maintained.

The relationship between alcohol- and sleep-related traits: Results from polygenic risk score and Mendelian randomization analyses.

STUDY OBJECTIVES: We investigated whether genetic risk for insomnia and sleep duration abnormalities are associated with AUD and alcohol consumption. We also evaluated the causal relationships between sleep- and alcohol-related traits. METHODS: Individual-level phenotype and genotype data from the Million Veteran Program were used. Polygenic risk scores (PRS) were computed using summary statistics from two recent discovery GWAS of insomnia (N= 453,379 European-ancestry (EA) individuals) and sleep duration (N= 446,118 EAs) and tested for association with lifetime AUD diagnosis (N= 34,658 EA cases) and past-year Alcohol Use Disorders Identification Test-Consumption scale scores (AUDIT-C, N= 200,680 EAs). Bi-directional two-sample Mendelian Randomization (MR) analyses assessed causal associations between the two sleep traits and the two alcohol-related traits. RESULTS: The insomnia PRS was positively associated with AUD at 2/9 PRS thresholds, with p<0.01 being the most significant (OR = 1.02, p = 3.48 × 10-5). Conversely, insomnia PRS was negatively associated with AUDIT-C at 6/9 PRS thresholds (most significant threshold being p = 0.001 (ß = -0.02, p = 5.6 × 10-8). Sleep duration PRS was positively associated with AUDIT-C at 2/9 PRS thresholds, with the most significant threshold being p = 1 × 10-6 (ß = 0.01, p = 0.0009). MR analyses supported a significant positive causal effect of insomnia on AUD (14 SNPs; ß = 104.14; SE = 16.19; p = 2.22 × 10-5), although with significant heterogeneity. MR analyses also showed that shorter sleep duration had a causal effect on the risk of AUD (27 SNPs; ß = -63.05; SE = 3.54; p = 4.55 × 10-16), which was robust to sensitivity analyses. CONCLUSION: The genetic risk for insomnia shows pleiotropy with AUD, and sleep continuity abnormalities have a causal influence on the development of AUD.

Resting-state functional connectivity changes in older adults with sleep disturbance and the role of amyloid burden.

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid ß (Aß) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aß burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aß data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aß positivity and sleep disturbance was evaluated using the linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aß burden on rsFC of SN (ß = 0.11, P = 0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aß burden. Sleep disturbance may lead to altered connectivity in the SN when Aß is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

Antidepressant effects of acute sleep deprivation are reduced in highly controlled environments.

BACKGROUND: Numerous studies summarized in a recent meta-analysis have shown sleep deprivation rapidly improves depressive symptoms in approximately 50 % of individuals with major depressive disorder (MDD), however those studies were typically conducted in clinical settings. Here we investigated the effects of sleep deprivation utilizing a highly controlled experimental approach. METHODS: 36 antidepressant-free individuals with MDD and 10 healthy controls (HC) completed a 5 day/4-night protocol consisting of adaptation, baseline, total sleep deprivation (TSD), and recovery phases. Light was kept consistently dim (≤50 lx), meals were regulated, and activity was restricted. In-the-moment mood was assessed using a modified Hamilton Rating Scale for Depression (HRSD) at screening and each morning following the experimental nights. RESULTS: Day of study had a significant effect on mood in both groups. Post-hoc analyses revealed that significant effects were attributed to mood improvement in the MDD group following study initiation prior to beginning TSD, and in the HC group following recovery sleep, but were not due to mood improvement in the MDD group during TSD. No further improvement in mood occurred during 36 h of TSD. LIMITATIONS: Strict eligibility requirements may limit generalizability. The requirement to be medication free may have biased toward a less severely depressed sample. CONCLUSIONS: Results revealed that individuals with moderate MDD can experience a significant reduction in depressive symptoms upon entering a highly controlled laboratory environment. Environmental effects on mood can be substantial and need to be considered.

Self-supervised learning of accelerometer data provides new insights for sleep and its association with mortality.

Background: Sleep is essential to life. Accurate measurement and classification of sleep/wake and sleep stages is important in clinical studies for sleep disorder diagnoses and in the interpretation of data from consumer devices for monitoring physical and mental well-being. Existing non-polysomnography sleep classification techniques mainly rely on heuristic methods developed in relatively small cohorts. Thus, we aimed to establish the accuracy of wrist-worn accelerometers for sleep stage classification and subsequently describe the association between sleep duration and efficiency (proportion of total time asleep when in bed) with mortality outcomes. Methods: We developed and validated a self-supervised deep neural network for sleep stage classification using concurrent laboratory-based polysomnography and accelerometry data from three countries (Australia, the UK, and the USA). The model was validated within-cohort using subject-wise five-fold cross-validation for sleep-wake classification and in a three-class setting for sleep stage classification wake, rapid-eye-movement sleep (REM), non-rapid-eye-movement sleep (NREM) and by external validation. We assessed the face validity of our model for population inference by applying the model to the UK Biobank with 100,000 participants, each of whom wore a wristband for up to seven days. The derived sleep parameters were used in a Cox regression model to study the association of sleep duration and sleep efficiency with all-cause mortality. Findings: After exclusion, 1,448 participant nights of data were used to train the sleep classifier. The difference between polysomnography and the model classifications on the external validation was 34.7 minutes (95% limits of agreement (LoA): -37.8 to 107.2 minutes) for total sleep duration, 2.6 minutes for REM duration (95% LoA: -68.4 to 73.4 minutes) and 32.1 minutes (95% LoA: -54.4 to 118.5 minutes) for NREM duration. The derived sleep architecture estimate in the UK Biobank sample showed good face validity. Among 66,214 UK Biobank participants, 1,642 mortality events were observed. Short sleepers (<6 hours) had a higher risk of mortality compared to participants with normal sleep duration (6 to 7.9 hours), regardless of whether they had low sleep efficiency (Hazard ratios (HRs): 1.69; 95% confidence intervals (CIs): 1.28 to 2.24 ) or high sleep efficiency (HRs: 1.42; 95% CIs: 1.14 to 1.77). Interpretation: Deep-learning-based sleep classification using accelerometers has a fair to moderate agreement with polysomnography. Our findings suggest that having short overnight sleep confers mortality risk irrespective of sleep continuity.

Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation.

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

Does insomnia treatment prevent depression?

Rates of major depressive disorder (MDD) are increasing globally, in part due to the coronavirus disease 2019 pandemic, contributing to disease burden. It has long been known that insomnia is intricately connected with depression as indicated by greater depression severity and lower treatment response. Furthermore, insomnia is a significant risk factor for new-onset depression. Treatment of insomnia is thus a logical target for prevention of incidents and recurrent MDD. This systematic review sought to evaluate the current evidence for the preventive effects of insomnia treatment on depression onset. A database search yielded 186 studies, six of which met criteria for inclusion in this review. All of the studies utilized cognitive behavioral treatment for insomnia (CBT-I) as the target intervention and most delivered treatment via a digital platform. Four of the studies found significantly lower rates of MDD onset in those who received CBT-I compared to a control condition. The two remaining studies failed to confirm these effects in primary analyses but secondary analyses suggested evidence of a preventive effect. There was significant methodologic heterogeneity across studies in terms of sample selection, outcomes, and follow-up periods, limiting the ability to draw firm conclusions. The evidence overall is in the direction of insomnia treatment reducing the risk for onset of MDD, but further research is warranted.

In-person and telehealth treatment of veterans with insomnia disorder using cognitive behavioral therapy for insomnia during the COVID-19 pandemic.

STUDY OBJECTIVES: Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line treatment for insomnia disorder. The goal of this study was to evaluate clinical benefits of CBT-I to veterans with insomnia disorder during the early months of the COVID-19 pandemic using an uncontrolled observational design. METHODS: A cohort of 63 Veterans Affairs (VA) mental health providers delivered CBT-I to 180 veterans as part of an evidence-based psychotherapy training program and captured de-identified treatment outcome data through a data portal. The main patient outcomes were change in the Insomnia Severity Index (ISI) total score from the initial clinical assessment session to the last treatment session, response rate (% with ISI change > 7 from assessment to last session), and remission rate (% with ISI < 8 at the last session). We tested the noninferiority of telehealth only compared with at least 1 in-person session. RESULTS: Fifty-six percent of veterans seen for an evaluation completed CBT-I treatment during the structured training program phase and completed an initial and final ISI. Among these veterans, ISI scores decreased by an average of 9.9 points from before to after treatment (P < .001), 66% experienced a clinically meaningful treatment response, and 43% experienced insomnia symptom remission. Benefits were similar whether the veteran received some in-person care or received CBT-I entirely via telehealth. CONCLUSIONS: Findings suggest, regardless of treatment modality, CBT-I remained highly effective during the early months of the pandemic, which was a challenging time for both clinical providers and veterans in need of insomnia treatment. CITATION: Martin JL, DeViva J, McCarthy E, et al. In-person and telehealth treatment of veterans with insomnia disorder using cognitive behavioral therapy for insomnia during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(7):1211-1217.

Potential genetic and epigenetic mechanisms in insomnia: A systematic review.

Insomnia is a stress-related sleep disorder conceptualised within a diathesis-stress framework, which it is thought to result from predisposing factors interacting with precipitating stressful events that trigger the development of insomnia. Among predisposing factors genetics and epigenetics may play a role. A systematic review of the current evidence for the genetic and epigenetic basis of insomnia was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) system. A total of 24 studies were collected for twins and family heritability, 55 for genome-wide association studies, 26 about candidate genes for insomnia, and eight for epigenetics. Data showed that insomnia is a complex polygenic stress-related disorder, and it is likely to be caused by a synergy of genetic and environmental factors, with stress-related sleep reactivity being the important trait. Even if few studies have been conducted to date on insomnia, epigenetics may be the framework to understand long-lasting consequences of the interaction between genetic and environmental factors and effects of stress on the brain in insomnia. Interestingly, polygenic risk for insomnia has been causally linked to different mental and medical disorders. Probably, by treating insomnia it would be possible to intervene on the effect of stress on the brain and prevent some medical and mental conditions.

Effect of sleep manipulations on intrusive memories after exposure to an experimental analogue trauma: A meta-analytic review.

Sleep plays an important role in memory processing and is disrupted in individuals with post-traumatic stress disorder (PTSD). A growing body of research has experimentally investigated how sleep - or lack thereof - in the early aftermath of a traumatic experience contributes to intrusive memory formation. The aim of this meta-analytic review was to examine the effects of various experimental sleep manipulations (e.g., sleep deprivation, daytime naps) on intrusive memories following exposure to an experimentally induced analogue traumatic event. Eight eligible studies were systematically identified through PsycInfo and PubMed and provided sufficient data to contribute to a meta-analysis of the effects of sleep versus wakefulness on intrusive memory frequency. Sleep was found to reduce intrusive memory frequency when compared to wakefulness at a small but significant effect size (Hedge's g = 0.29). There was no evidence of publication bias and heterogeneity of effect sizes across studies was moderate. Results suggest that sleep plays a protective role in the aftermath of exposure to a traumatic event with implications for early post-trauma intervention efforts.

Resting-State Functional Connectivity Changes in Older Adults with Sleep Disturbance and the Role of Amyloid Burden.

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid ß (Aß) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aß burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aß data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aß positivity and sleep disturbance was evaluated using linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aß burden on rsFC of SN (ß=0.11, P=0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aß burden. Sleep disturbance may lead to altered connectivity in the SN when Aß is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

Persistent Ventral Anterior Cingulate Cortex and Resolved Amygdala Hyper-responses to Negative Outcomes After Depression Remission: A Combined Cross-sectional and Longitudinal Study.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent mood disorder affecting more than 300 million people worldwide. Biased processing of negative information and neural hyper-responses to negative events are hallmarks of depression. This study combined cross-sectional and longitudinal experiments to explore both persistent and resolved neural hyper-responses to negative outcomes from risky decision making in patients with current MDD (cMDD) and remitted MDD (rMDD). METHODS: A total of 264 subjects participated in the cross-sectional study, including 117 patients with medication-naïve, first-episode current depression; 45 patients with rMDD with only 1 episode of depression; and 102 healthy control subjects. Participants completed a modified balloon analog risk task during functional magnetic resonance imaging. In the longitudinal arm of the study, 42 patients with cMDD were followed and 26 patients with rMDD were studied again after 8 weeks of antidepressant treatment. RESULTS: Patients with cMDD showed hyper-responses to loss outcomes in multiple limbic regions including the amygdala and ventral anterior cingulate cortex (vACC). Amygdala but not vACC hyperactivity correlated with depression scores in patients with cMDD. Furthermore, amygdala hyperactivity resolved while vACC hyperactivity persisted in patients with rMDD in both cross-sectional and longitudinal studies. CONCLUSIONS: These findings provide consistent evidence supporting differential patterns of amygdala and vACC hyper-responses to negative outcomes during depression remission. Amygdala hyperactivity may be a symptomatic and state-dependent marker of depressive neural responses, while vACC hyperactivity may reflect a persistent and state-independent effect of depression on brain function. These findings offer new insights into the neural underpinnings of depression remission and prevention of depression recurrence.

Sleep Disturbances Associated With Posttraumatic Stress Disorder.

Sleep disturbances, namely insomnia and recurrent nightmares, are ubiquitous following trauma exposure and are considered hallmarks of posttraumatic stress disorder (PTSD). Other sleep disorders frequently co-occur with PTSD. This article describes research examining sleep problems most common in PTSD, including prevalence and clinical characteristics. Sleep disturbances are often robust to trauma-focused treatment; thus, evidence for psychological and pharmacological interventions for insomnia and nightmares in PTSD are discussed. Given the high prevalence of sleep problems in PTSD, more work is needed to empirically study putative mechanisms linking trauma exposure and sleep, as well as how to best target these symptoms in patients with PTSD.

Measuring Daily Activity Rhythms in Young Adults at Risk of Affective Instability Using Passively Collected Smartphone Data: Observational Study.

BACKGROUND: Irregularities in circadian rhythms have been associated with adverse health outcomes. The regularity of rhythms can be quantified using passively collected smartphone data to provide clinically relevant biomarkers of routine. OBJECTIVE: This study aims to develop a metric to quantify the regularity of activity rhythms and explore the relationship between routine and mood, as well as demographic covariates, in an outpatient psychiatric cohort. METHODS: Passively sensed smartphone data from a cohort of 38 young adults from the Penn or Children's Hospital of Philadelphia Lifespan Brain Institute and Outpatient Psychiatry Clinic at the University of Pennsylvania were fitted with 2-state continuous-time hidden Markov models representing active and resting states. The regularity of routine was modeled as the hour-of-the-day random effects on the probability of state transition (ie, the association between the hour-of-the-day and state membership). A regularity score, Activity Rhythm Metric, was calculated from the continuous-time hidden Markov models and regressed on clinical and demographic covariates. RESULTS: Regular activity rhythms were associated with longer sleep durations (P=.009), older age (P=.001), and mood (P=.049). CONCLUSIONS: Passively sensed Activity Rhythm Metrics are an alternative to existing metrics but do not require burdensome survey-based assessments. Low-burden, passively sensed metrics based on smartphone data are promising and scalable alternatives to traditional measurements.

The association of polysomnographic sleep on posttraumatic stress disorder symptom clusters in trauma-exposed civilians and veterans.

Study Objectives: Self-reported sleep disturbance has been established as a risk factor and predictor for posttraumatic stress disorder (PTSD); however, less is known about the relationship between objective sleep and PTSD symptom clusters, and the specific role of hyperarousal. The present study examined the relationships between sleep continuity and architecture on PTSD symptom clusters. Methods: Participants underwent two in-laboratory sleep studies to assess sleep continuity and architecture. They also completed the Clinician-Administered PTSD-IV scale and the Structured Clinical Interview for the DSM-IV to assess for PTSD diagnosis and other psychiatric disorders. Results: Sleep continuity (i.e. total sleep time, sleep efficiency percent, wake after sleep onset, sleep latency) was significantly related to PTSD Cluster B (reexperiencing) symptom severity (R 2 = .27, p < .001). Sleep architecture, specifically Stage N1 sleep, was significantly associated with PTSD Cluster B (t = 2.98, p = .004), C (Avoidance; t = 3.11, p = .003), and D (Hyperarosual; t = 3.79, p < .001) symptom severity independently of Stages N2, N3, and REM sleep. REM sleep variables (i.e. REM latency, number of REM periods) significantly predicted Cluster D symptoms (R 2 = .17, p = .002). Conclusions: These data provide evidence for a relationship between objective sleep and PTSD clusters, showing that processes active during Stage N1 sleep may contribute to PTSD symptomatology in civilians and veterans. Further, these data suggest that arousal mechanisms active during REM sleep may also contribute to PTSD hyperarousal symptoms.This paper is part of the War, Trauma, and Sleep Across the Lifespan Collection. This collection is sponsored by the Sleep Research Society.