Sleep Variables Research Articles

Effects in Sleep and Recovery Processes of NESA Neuromodulation Technique Application in Young Professional Basketball Players: A Preliminary Study

The competitive calendars in sports often lead to fluctuations in the effort-recovery cycle and sleep quality. NESA noninvasive neuromodulation, achieved through microcurrent modulation of the autonomic nervous system, holds promise for enhancing sleep quality and autonomic activation during stressful situations. The objective of this study was to analyze the sleep and recovery responses of basketball players over six weeks of training and competition, with the integration of NESA noninvasive neuromodulation. A preliminary experimental study involving 12 participants was conducted, with a placebo group (n = 6) and an intervention group (n = 6) treated with NESA noninvasive neuromodulation. Sleep variables and biomarkers such as testosterone, cortisol, and the cortisol:testosterone ratio were analyzed to assess player recovery and adaptations. Significant differences were observed in total, duration, and REM sleep variables (p-value= < 0.001; 0.007; <0.001, respectively) between the intervention and placebo groups. The intervention group demonstrated increased duration of sleep variables. Cortisol levels showed normalization in the experimental group, particularly in the last two weeks coinciding with the start of playoffs. This study highlights the potential of NESA noninvasive neuromodulation to enhance sleep quality despite challenging circumstances, providing valuable insights into the management of athlete recovery in competitive sports settings.

Analysis of Sleep, Nocturnal Physiology, and Physical Demands of NCAA Women's Ice Hockey Across a Championship Season.

Merrigan, JJ, Stone, JD, Kraemer, WJ, Friend, C, Lennon, K, Vatne, EA, and Hagen, JA. Analysis of sleep, nocturnal physiology, and physical demands of NCAA women's ice hockey across a championship season. J Strength Cond Res 38(4): 694-703, 2024-The aims of this study were to evaluate the (a) relationships between daily physical demands and nighttime sleep, heart rate (HR), and heart rate variability (HRV); (b) weekly changes in physical demands and sleep; and (c) differences among positions and between training and competition during a competitive season in National Collegiate Athletic Association (NCAA) women's ice hockey. Twenty-five NCAA Division I women's ice hockey athletes wore a sensor at night to monitor sleep quantity or quality (e.g., time asleep and sleep efficiency) and physiology (e.g., HR and HRV). During training and competitions (31 regular season and 7 postseason), athletes wore performance monitoring systems to assess workload demands (e.g., training impulse and TRIMP). As internal workload (TRIMP, Time >80% of HRmax, Average HR) during training or competition increased, nocturnal HRV decreased, HR increased, and Sleep Duration, Sleep Score, and Readiness Score decreased that night. Across the season, athletes experienced lower HRV, but exhibited longer sleep durations. Training Distance, Duration, Time >80% HRmax, Average HR, and TRIMP decreased, whereas competition Total Distance, Duration, and TRIMP increased across weeks throughout the season. There were differences across positions and season blocks when evaluating these data at the mesocycle level. Athletes slept longer before competition compared with training, but physiological data did not differ. Competitions had greater physiological demands than training. We speculate that the increased focus on sleep hygiene, as evidenced by the increase in sleep over the season, may have served as a recovery aid to combat physiological stress of accumulated demands of competitions that increased over time into postseason tournaments.

Associations between sleep health, negative reinforcement learning, and alcohol use among South Florida college students with elevated internalizing symptoms

Negative reinforcement is proposed to mediate associations between sleep and alcohol use, especially among people with depression and/or anxiety symptoms. Worse sleep (e.g., shorter duration, less efficiency, more irregular timing) exacerbates negative emotions, which alcohol may temporarily relieve. Not yet examined, we propose sleep indirectly impacts early stages of alcohol use via differences in negative reinforcement learning (NRL), since sleep impacts emotion, reward response, and learning. The current study aimed to replicate associations between sleep and alcohol use, test associations with NRL, and examine indirect associations between sleep health and alcohol use via NRL among 60 underage college students (ages 18-20 years, 77% female) varying in depression and anxiety symptoms. Participants wore Fitbit smartwatches and completed daily diaries measuring sleep and substance use for ∼14 days before completing two computer tasks assessing social (SNRL) and monetary (MNRL) negative reinforcement learning. Robust generalized linear models tested direct associations within the proposed model. SNRL performance was positively associated with alcohol use, but no other associations were observed. Statistical mediation models failed to indicate indirect effects of sleep on alcohol use via SNRL or MNRL performance. Post-hoc exploratory models examining depression and anxiety symptoms as moderators of direct associations indicated several interactions. Positive associations between sleep timing variability and alcohol use were weakened at higher anxiety symptom severity and stronger at higher depression symptom severity. The positive association between SNRL performance and alcohol use was also stronger at higher depression symptom severity. Among students with elevated depression symptoms, variable sleep timing and stronger SNRL performance were independently associated with more alcohol use, but indirect effects were not supported. Future research should replicate findings, confirm causality of interactions, and examine sleep timing and behavioral responses to negative social stimuli as targets for improving alcohol-related outcomes among underage college students with elevated depressive symptoms.

Sleep Disturbance in Bipolar Disorder. Treatment Implications

IntroductionRelationship between sleep and bipolar disorder involves the following aspects: decreased need for sleep is a fundamental marker of the manic state, sleep deprivation is one cause of mania and may in fact be a fundamental etiological agent in mania, total sleep time is a predictor of future manic episodes, and total sleep time may be a marker of response as well as a target of treatment in mania.ObjectivesThis e-poster aimed to summarize evidence regarding the sleep disturbance in Bipolar Disorder.MethodsBibliopgraphical review was performed using PubMed platform. All relevant articles were found using the keywords: sleep disturbance, bipolar disorder, mania.ResultsSleep disturbances are frequent in BD patients in different phases of illness, including the euthymic state and remission. These sleep aberrations are represented not only by insomnia but also by sleep–wake rhythm disorders, especially delayed sleep–wake phase disorders. During the manic state, most patients experience a reduced need for sleep and longer sleep onset latency. Likewise, in the depressive state, insomnia and hypersomnia are commonly observed. Meta-analyses of trials conducted on remitted BD patients demonstrated prolonged total sleep time, increased awakenings after sleep onset, greater variability of sleep–wake variables, and reduced sleep efficiency.ConclusionsOverall, all kinds of sleep disorders and parasomnias are very common especially in youth patients with BD. Thus, compared to the general population, youth with BD exhibit lower sleep efficiency, longer slow wave sleep, and reduced REM sleep, features that could affect the genesis and prognosis of the disorder. Sleep disturbances may also be used as predictors of the onset of BD in a subset of high-risk young subjects.Disclosure of InterestNone Declared

Objective and subjective sleep patterns and biomarkers of stress among women with a history of sexual abuse in childhood.

Childhood sexual abuse (CSA) is associated with posttraumatic stress symptoms (PTSSs) and sleep disturbance into adulthood. The latter is thought to emerge from dysregulation in biobehavioral systems, including nighttime hyperarousal; however, studies investigating specific mechanisms to explain these long-term sleep problems are limited. The present study examined presleep arousal, fear of sleep, and the cortisol awakening response (CAR) as putative mediators between PTSS and sleep disturbance in women with a history of CSA. N = 64 cis-gendered women with a self-reported history of CSA completed a baseline diagnostic interview, self-reported mental health and sleep measures, 7 days of actigraphy monitoring with concurrent sleep diary, and 2 days of saliva sampling. PTSSs were not significantly associated with actigraphy-estimated sleep variables but were positively associated with self-reported sleep onset latency (SOL) and negatively associated with self-reported sleep quality. Similarly, PTSSs were not significantly associated with CAR but were associated with higher presleep arousal and fear of sleep ratings. Mediational models identified greater presleep cognitive arousal to partially explain the PTSS-SOL relationship. Specific features of CSA (i.e., age at time of abuse, location of abuse, relationship to the perpetrator) did not moderate this association. Findings suggest that targeting maladaptive cognitions (e.g., worries, rumination) that occur during the presleep period may be a potential intervention target in mitigating sleep disturbance and PTSSs in this population. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A cross-sectional analysis of the association between sleep disorders and cancer using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2014.

Cancer is one of the main causes of death in the world, and sleep disorders are a serious public health problem, especially in large cities; of these, insomnia and obstructive sleep apnea (OSA) are the most common. In the last decade, studies have pointed to a possible association between sleep disorders and cancer. The aim of this study is to evaluate whether there is any association between sleep disorders and cancer. Five National Health and Nutrition Examination Surveys (NHANES) (2005-2014) from the United States were combined in order to obtain the sample. Two main sleep variables were assessed: having trouble sleeping and/or ever telling a doctor one had a sleep problem. The odds ratio of ever having a cancer diagnosis was the main outcome. Data were analyzed by binary logistic regression models in Jamovi. The final sample comprised 26,821 participants. Individuals who reported having trouble sleeping had an odds ratio of 1.48 (95% confidence interval = [1.336-1.646]; P < .001) of having been diagnosed with cancer, and those who had already been diagnosed with a sleep disorder had an odds ratio of 1.21 (95% confidence interval = [1.046-1.415]; P = .011), showing an increased chance of having been diagnosed with cancer. In men, these values were even greater, with an odds ratio of 1.56 (95% confidence interval = [1.321-1.843]; P < .001) and an odds ratio of 1.26 (95% confidence interval = [1.013-1.582]; P = .037), respectively, for having trouble sleeping and for having been diagnosed with a sleep disorder, in relation to having been diagnosed with cancer. Individuals who had trouble sleeping or who had been diagnosed with a sleep disorder at any time in their life were more likely to have been diagnosed with cancer. Porcacchia AS, Pires GN, Andersen ML, Tufik S. A cross-sectional analysis of the association between sleep disorders and cancer using data from the National Health and Nutrition Examination Survey (NHANES) 2005-2014. J Clin Sleep Med. 2024;20(4):515-520.

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model

BackgroundPrior research has associated spoken language use with depression, yet studies often involve small or non-clinical samples and face challenges in the manual transcription of speech. This paper aimed to automatically identify depression-related topics in speech recordings collected from clinical samples. MethodsThe data included 3919 English free-response speech recordings collected via smartphones from 265 participants with a depression history. We transcribed speech recordings via automatic speech recognition (Whisper tool, OpenAI) and identified principal topics from transcriptions using a deep learning topic model (BERTopic). To identify depression risk topics and understand the context, we compared participants' depression severity and behavioral (extracted from wearable devices) and linguistic (extracted from transcribed texts) characteristics across identified topics. ResultsFrom the 29 topics identified, we identified 6 risk topics for depression: ‘No Expectations’, ‘Sleep’, ‘Mental Therapy’, ‘Haircut’, ‘Studying’, and ‘Coursework’. Participants mentioning depression risk topics exhibited higher sleep variability, later sleep onset, and fewer daily steps and used fewer words, more negative language, and fewer leisure-related words in their speech recordings. LimitationsOur findings were derived from a depressed cohort with a specific speech task, potentially limiting the generalizability to non-clinical populations or other speech tasks. Additionally, some topics had small sample sizes, necessitating further validation in larger datasets. ConclusionThis study demonstrates that specific speech topics can indicate depression severity. The employed data-driven workflow provides a practical approach for analyzing large-scale speech data collected from real-world settings.

Longer sleep duration and neuroinflammation in at-risk elderly with a parental history of Alzheimer's disease.

Although short sleep could promote neurodegeneration, long sleep may be a marker of ongoing neurodegeneration, potentially as a result of neuroinflammation. The objective was to evaluate sleep patterns with age of expected Alzheimer's disease (AD) onset and neuroinflammation. We tested 203 dementia-free participants (68.5 ± 5.4 years old, 78M). The PREVENT-AD cohort includes older persons with a parental history of AD whose age was nearing their expected AD onset. We estimated expected years to AD onset by subtracting the participants' age from their parent's at AD dementia onset. We extracted actigraphy sleep variables of interest (times of sleep onset and morning awakening, time in bed, sleep efficiency, and sleep duration) and general profiles (sleep fragmentation, phase delay, and hypersomnia). Cerebrospinal fluid (CSF) inflammatory biomarkers were assessed with OLINK multiplex technology. Proximity to, or exceeding, expected age of onset was associated with a sleep profile suggestive of hypersomnia (longer sleep and later morning awakening time). This hypersomnia sleep profile was associated with higher CSF neuroinflammatory biomarkers (IL-6, MCP-1, and global score). Interaction analyses revealed that some of these sleep-neuroinflammation associations were present mostly in those closer/exceeding the age of expected AD onset, APOE4 carriers, and those with better memory performance. Proximity to, or exceeding, parental AD dementia onset was associated with a longer sleep pattern, which was related to elevated proinflammatory CSF biomarkers. We speculate that longer sleep may serve a compensatory purpose potentially triggered by neuroinflammation as individuals are approaching AD onset. Further studies should investigate whether neuroinflammatory-triggered long sleep duration could mitigate cognitive deficits.

Characteristics of sleep in children with heavy prenatal alcohol exposure.

Sleep plays an important role in neurodevelopment. However, the effects of prenatal alcohol exposure on sleep quality have been understudied, despite reports of sleep disturbance in infants prenatally exposed to alcohol and elevated levels of sleep problems reported by caregivers of children with fetal alcohol spectrum disorders. The current study characterizes sleep in children with prenatal alcohol exposure using both objective (actigraphy) and subjective (questionnaires, sleep diaries) methods. Participants aged 6-10 years, with and without prenatal alcohol exposure, were included in the study (alcohol-exposed [AE]: n = 35; control [CON]: n = 39). Objective sleep was measured via 24-h actigraphy for 2 weeks. Parents completed sleep diaries and sleep questionnaires (Children's Sleep Habits Questionnaire, Pediatric Sleep Questionnaire). Multivariate analysis of variance was used to characterize the sleep profile (objective, subjective) and examine group differences. There were no group differences on actigraphy metrics averaged across 2 weeks. However, the AE group showed significantly greater intraindividual variability on most actigraphy measures, particularly total sleep time, percent sleep, wake after sleep onset, and number of wake bouts. Parents reported significantly more sleep problems in the AE group than in the CON group, primarily driven by night wakings, parasomnias (e.g., sleepwalking), snoring, and daytime sleepiness. These effects were more severe in children >8.5 years of age. Despite similar 2-week average sleep outcomes, children with prenatal alcohol exposure showed greater intraindividual sleep variability and parents reported more sleep problems related to sleep behavior and snoring. These difficulties with sleep may be related to other cognitive and behavioral outcomes. Importantly, sleep is a modifiable behavior, and interventions that focus on variability in sleep, particularly in sleep duration, can impact the quality of life in children with prenatal alcohol exposure and their families.

Objectively assessed sleep quality parameters in Multiple Sclerosis at home: Association to disease, disease severity and physical activity

BackgroundMultiple Sclerosis (MS) is a chronic inflammatory autoimmune, neurodegenerative disease that affects regular mobility and leads predominantly to physical disability. Poor sleep quality, commonly reported in MS patients, impacts their physical activity (PA). Accelerometers monitor 24-h activity patterns, offering insights into disease progression in daily life. ObjectiveTo test if the sleep quality variables of MS patients, as assessed with wrist-worn accelerometers, differ from those of controls and are associated with PA and disease severity variables. MethodsSeven-day raw accelerometer data collected from 40 MS patients and 24 controls was processed using an open-source GGIR package, from which variables of sleep quality (sleep efficiency, wake after sleep onset (WASO), sleep regularity index (SRI), intradaily variability (IV)) and PA (of different intensities: inactivity, light (LPA), moderate (MPA), vigorous (VPA)) were analyzed. The variables were compared between the two study groups and in MS patients, correlation tested associations among the variables of sleep quality, PA, and disease severity (assessed with the Expanded Disability Status Scale, EDSS). ResultsSleep efficiency was the only variable that differed significantly between MS patients and controls (lower in MS, p = 0.01). Both SRI (positively) and IV (negatively) correlated with the time spent in LPA and MPA. WASO correlated negatively with inactivity. ConclusionThis is one of the few studies with a wrist-worn accelerometer that shows a difference in sleep efficiency between MS patients and controls and, in MS, an association of sleep quality variables with PA variables.

Abstract P521: Sleep Timing and Duration in Relation to DNA Methylation in Adolescents: An Epigenome-Wide Analysis

Background: Accumulating evidence suggests that both sleep duration and sleep timing can impact metabolic health of adolescents, potentially through epigenetic modification. The objective of this study was to investigate the relationship between sleep duration and timing and DNA methylation, one type of epigenetic modification that may be responsive to changes in sleep. Methods: Cross-sectional epigenome-wide analysis of DNA methylation was conducted to identify sleep-related CpG sites in 269 females and 233 males (14.4±2.1 years on average) participating in the Early Life Exposure in Mexico to ENvironmental Toxicants (ELEMENT) cohort study. Sleep duration and midpoint on weekdays and weekends were assessed using7-day wrist actigraphy (Actigraph GTX-BT), and DNA methylation in blood leukocytes was measured using the Illumina Infinium Methylation EPIC BeadChip. Linear regression was conducted to assess the relationship between sleep variables and DNA methylation at each locus on the array (using beta values), adjusting for sex, age, maternal education, batch effects, monocytes, natural killer cells, B lymphocyte, granulocyte, and naïve CD8 T cells. A false discovery rate (FDR) using the Benjamini-Hochberg method was applied to correct for multiple testing. Sex-stratified associations were also examined. Results: The average sleep duration was 8.5±1.3 hours on weekdays and 9.1±1.3 hours on weekends, and the average sleep midpoint was 3:48AM±1.4 hours on weekdays and 4.48AM±1.3 hours on weekends. At false discovery rate &lt;0.05, there were no significant associations at any of the 762,657 CpG sites. However, at a false discovery rate of &lt;0.2, there were positive associations between weekday sleep duration and 4 CpG sites (i.e., longer sleep duration associated with higher % DNA methylation), including a site in or near CpG islands annotated to the gene DENND2C. Sex-stratified analyses revealed associations were more evident in males. Conclusion: Epigenome-wide analysis identified possible associations between sleep duration and multiple CpG sites, and in a sex-specific manner. Findings suggest that sleep duration may impact the epigenome in a distinct manner from sleep timing.

Abstract P205: Poor Sleep Quality and Daytime Sleepiness Associated With Lower Quality Diet in an Israeli Cohort

Introduction: Sleep health and diet quality are bidirectionally linked. Poor sleep can impair metabolic function and alter eating behavior, while a poor quality diet may negatively impact sleep and daytime function through multiple pathways (i.e. inflammation, obesity, daytime fatigue). Methods: In a 2017 Israeli Bureau of Statistics population-based survey of households, 7,230 Israeli individuals reported habitual sleep and diet quality. Sleep variables included sleep duration (≤5, 6, 7, 8, or ≥9 hours per night), sleep disturbances (0, ≤1, 2-3, or 4+ nights per week), and daytime sleepiness (categorized as either “None”, “Not Much”, “Somewhat”, or “Greatly”). Diet variables were categorized as 0, 1, 2, 3, or 4+ daily servings of vegetables, fruits, and whole grains, and 0, 1, 2, 3, or 4+ weekly servings of legumes, red meat, and fish. Covariates included age, sex, BMI, financial status, and ethnicity. Results: Individuals who slept ≤5 hours were less likely to eat daily vegetables (oOR=0.863, p&lt;0.05). Individuals who slept ≤7 hours were less likely to eat daily fruits (oOR=0.858, p&lt;0.02), and whole grains (oOR=0.0.772, p&lt;0.0005). Individuals who slept ≥9 hours were less likely to eat daily vegetables (oOR=0.803, p=0.038), fruits (oOR=0.783, p=0.025), or wholegrains (oOR=0.783, p=0.027), as well as weekly legumes (oOR=0.788, p=0.025), and fish (oOR=0.779, p=0.028). Those with severe sleep disturbances (4+ per week) were less likely to eat daily vegetables (oOR=0.675, p&lt;0.0005), fruits (oOR=0.765, p&lt;0.0005), and whole grains (oOR=0.840, p=0.011), or weekly legumes (oOR=0.806), p=0.001). Mild daytime sleepiness was associated with fewer daily vegetables (oOR=0.834, p=0.007), while “great” daytime sleepiness was associated with fewer vegetables (oOR=0.558, p&lt;0.0005), fruits (oOR=0.689, p&lt;&gt;0.0005), wholegrains (oOR=0.751, p&lt;0.0005), and legumes (oOR=0.734, p&lt;0.0005). In a stepwise model adjusting for all sleep variables, many measures of poor sleep were independently associated with fewer daily vegetables, fruits, and wholegrains, fewer weekly legumes, and more weekly red meat. Conclusions: While the relationship between sleep and diet is complex, these data suggest that multiple independent pathways link poor sleep with an objectively unhealthier diet. The interaction between diet and daytime function, in particular, warrants further attention. Interventions targeting healthier sleep and diet must consider all aspects of sleep quality, including nocturnal sleep itself and daytime sleepiness.

Abstract P520: Sleep Duration and Quality Associated With Behavioral Cardiometabolic Health in Israel: Jewish / Arab Ethnic Differences

Introduction: The role of sleep health in global cardiometabolic disparities has not been sufficiently explored as a modifiable factor. Israeli Jews and Arabs share national and cultural experiences, but differ with respect to important historical, socio-economic, and cultural aspects. Hypothesis: Jewish/Arab Israeli disparities in cardiometabolic health may be partially explained by differences in sleep. Methods: 7,230 Israeli individuals (N=5880 Jews and N=1350 Arabs) responded to the 2017 Israeli Bureau of Statistics population-based survey of households. Behavioral risk factors included poor diet (&lt;4 servings/day of vegetables), sedentary lifestyle (no exercise within the past 3 months), smoking, and obesity (based on self-reported height and weight). Sleep variables included sleep duration (&lt;=5, 6, 7, 8 [reference], or &gt;=9 hours) and sleep difficulty in the past month (none [reference], mild, moderate, or severe). Covariates included age and sex. Results: Israeli Arabs were more likely to be smokers (OR=1.41), sedentary (OR=1.44), obese (OR=1.73), and consume &lt;4 vegetable servings (OR=3.23). In adjusted analyses of sleep duration, smoking was associated with &lt;=5h (OR=1.49, 95%CI [1.23,1.80], p&lt;0.0005) and &gt;=9h (OR=1.33, 95% CI [1.02,1.72], p=0.035), and it was associated with moderate (OR=1.45, 95%CI [1.21,1.75], p&lt;0.0005) and severe (OR=1.57, 95%CI [1.33,1.86], p&lt;0.0005) sleep difficulties. A significant duration-by-ethnicity interaction was observed (p=0.003). Stratified analyses showed that smoking was associated with &lt;=5h and 6h and relationships were stronger in Israeli Arabs. Insufficient vegetable consumption was associated with moderate (OR=1.25, 95%CI [1.04,1.52], p=0.02) and severe (OR=1.32, 95%CI [1.12,1.57], p=0.001) sleep difficulties. A significant duration-by-ethnicity interaction was observed (p=0.02). In stratified analyses, no relationships were seen among Israeli Jews, but among Israeli Arabs, insufficient vegetable consumption was negatively associated with shorter sleep. Sedentary lifestyle was associated with severe sleep difficulties (OR=1.31, 95%CI [1.04,1.65], p=0.02). No interactions were found. Obesity was associated with &lt;=5h (OR=1.36, 95%CI [1.10,1.68], p=0.004) and severe sleep difficulties (OR=1.40, 95%CI [1.17,1.67], p&lt;0.0005). A significant duration-by-ethnicity interaction was found. In stratified analyses, among Israeli Jews, obesity was associated with 7h sleep duration, but among Israeli Arabs, obesity was associated with &lt;=5h, 6h, and &gt;=9h. Conclusions: Behavioral cardiometabolic health factors were associated with poor sleep health, but these relationships were generally stronger among Israeli Arabs. Sleep health may be a fruitful intervention target to reduce disparities.

Temporal patterns of sleep latency in central hypersomnia and attention deficit hyperactivity disorder: a cluster analysis exploration using Multiple Sleep Latency Test.

Excessive daytime sleepiness (EDS) is a crucial symptom that diminishes the quality of life. The primary causes of EDS are central hypersomnia, including narcolepsy type 1 (NT1), type 2 (NT2), and idiopathic hypersomnia (IH). EDS is often associated with other psychiatric disorders, particularly attention deficit hyperactivity disorder (ADHD). The Multiple Sleep Latency Test (MSLT) is the standard assessment tool for EDS. Although the MSLT yields numerous parameters, most are not employed in clinical practice. In this study, we leveraged novel MSLT parameters to discern central hypersomnia and ADHD presence. Our analysis focused on sleep latency variability and employed cluster analysis to identify unique temporal patterns. We examined the MSLT data from 333 patients; of these, 200 (aged 14-54, mean: 24.9 ± 8.1, years; 114 females) met the inclusion criteria comprising comprehensive data an Apnea-Hypopnea Index (AHI) below 5, and no prior diagnosis of sleep apnea syndrome. We employed a time-course cluster approach that specifically targeted sleep latency variability during the MSLT. Considering both multiple clustering quality evaluations and the study's objectives, we identified 9 distinct clusters. Clusters 1 and 3 predominantly had MSLT-positive results; Cluster 2 was entirely MSLT-positive; Clusters 4, 5, 6, 8, and 9 were mainly MSLT-negative; and Cluster 7 had mixed results. The diagnosis of hypersomnia varied notably among Clusters 1, 2, 3, and 7, with Cluster 2 demonstrating a pronounced tendency towards NT1 and NT2 diagnoses (p < 0.005). However, no significant correlation was observed between ADHD diagnoses and specific sleep latency patterns in any cluster. Our study highlights the value of time-course clustering in understanding sleep latency patterns of patients with central hypersomnia.

Same sleep disorder but different sleep patterns: individual differences in sleep health and depressive symptomatology in veterans with obstructive sleep apnea.

Poor sleep health, a composite measure of key sleep characteristics, may relate to increased depressive symptoms among individuals treated for obstructive sleep apnea. The current investigation examined the association between sleep health and depressive symptomatology. In a pilot sample of 13 symptomatic OSA military Veterans with adequate CPAP adherence (mean age = 54.8, 76.9% male, 100% White), empirically validated cutoffs were applied to actigraphy-derived sleep variables: duration, efficiency, timing, and regularity. Participants with zero optimal sleep scores had significantly higher depressive scores (M = 19.0, SD = 3.0) than participants with 1 or 2 (M = 9.8. SD = 4.3, p = .016) and 3 or more optimal sleep scores (M = 11.3, SD = 4.9, p = .038). These preliminary findings suggest that better sleep health was associated with lower depressive symptomatology. Future work should replicate these preliminary findings in a larger sample.

Associations between disturbed sleep and attenuated psychotic experiences in people at clinical high risk for psychosis.

Pre-diagnostic stages of psychotic illnesses, including 'clinical high risk' (CHR), are marked by sleep disturbances. These sleep disturbances appear to represent a key aspect in the etiology and maintenance of psychotic disorders. We aimed to examine the relationship between self-reported sleep dysfunction and attenuated psychotic symptoms (APS) on a day-to-day basis. Seventy-six CHR young people completed the Experience Sampling Methodology (ESM) component of the European Union Gene-Environment Interaction Study, collected through PsyMate® devices, prompting sleep and symptom questionnaires 10 times daily for 6 days. Bayesian multilevel mixed linear regression analyses were performed on time-variant ESM data using the brms package in R. We investigated the day-to-day associations between sleep and psychotic experiences bidirectionally on an item level. Sleep items included sleep onset latency, fragmentation, and quality. Psychosis items assessed a range of perceptual, cognitive, and bizarre thought content common in the CHR population. Two of the seven psychosis variables were unidirectionally predicted by previous night's number of awakenings: every unit increase in number of nightly awakenings predicted a 0.27 and 0.28 unit increase in feeling unreal or paranoid the next day, respectively. No other sleep variables credibly predicted next-day psychotic symptoms or vice-versa. In this study, the relationship between sleep disturbance and APS appears specific to the item in question. However, some APS, including perceptual disturbances, had low levels of endorsement amongst this sample. Nonetheless, these results provide evidence for a unidirectional relationship between sleep and some APS in this population.

Behavioural therapy for shift work disorder improves shift workers' sleep, sleepiness and mental health: A pilot randomised control trial.

The present study evaluates the efficacy of behavioural therapy adapted for shift work disorder with a randomised control design in a healthcare population. Forty-three night shift workers (m. age: 34 years; 77% women) experiencing shift work disorder were randomised to either the behavioural therapy for shift work disorder (BT-SWD) or a waiting-list control group offered after the waiting period. Participants completed questionnaires on insomnia, sleepiness and mental health pre- and post-treatment, pre- and post-waiting, and at follow-up, and a sleep diary. As night shift workers alternate between sleeping during the day after their night shifts and transitioning to nighttime sleep on days off, insomnia severity and sleep variables were analysed for daytime and nighttime sleep. The BT-SWD involved sleep restriction therapy, stimulus control and fixed sleep periods in the dark. Statistical analyses were performed under intent-to-treat and per-protocol approaches. Repeated-measures two-way ANCOVA analysis, controlling for age, sex and pre-treatment daytime total sleep time, was performed with Bonferroni corrections, and between-group effect sizes computed. Fourteen participants dropped out after randomisation. Under the intent-to-treat analysis, BT-SWD participants had a significant greater decrease in daytime insomnia severity and an increase in daytime total sleep time at post-treatment than the control group, with large between-group effect sizes (-1.25 and 0.89). These corresponding results were also significant with large effect sizes under the per-protocol analysis. Sleepiness, anxiety and depression levels improved at post-treatment and maintained at follow-up when the BT-SWD treated controls were added to the BT-SWD group. The behavioural therapy for shift work disorder can be used to improve the sleep and mental health of healthcare night workers.

Actigraphic sleep dimensions and associations with academic functioning among adolescents.

There is mixed evidence regarding associations of sleep duration with academic functioning in adolescents and a lack of research on other sleep dimensions, particularly using objective sleep measures. We examined associations of multiple actigraphic sleep dimensions with academic functioning among adolescents. Data were from the sleep sub-study of the age 15 wave of the Future of Families and Child Wellbeing Study (n = 774-782; 52% female), a national, diverse sample of teens. Adolescents wore wrist-actigraphs for ~1 week and completed a survey reporting academic performance and school-related behavioral problems. Regression models assessed whether average sleep duration, timing, maintenance efficiency, and SD-variability were associated with self-reported academic functioning in cross-sectional analyses adjusted for demographic characteristics, depressive symptoms, and anxious symptoms. Later sleep timing (hours) and greater sleep variability (SD-hours) were associated with poorer academic outcomes, including sleep onset variability with higher odds of receiving a D or lower (OR = 1.29), sleep onset (β = -.07), sleep offset (β = -.08), and sleep duration variability (β = -.08) with fewer A grades, sleep offset with lower GPA (β = -.07), sleep offset (OR = 1.11), sleep duration variability (OR = 1.31), and sleep onset variability (OR = 1.42) with higher odds of being suspended or expelled in the past 2 years, and sleep duration variability with greater trouble at school (β = .13). Sleep duration, sleep maintenance efficiency, and sleep regularity index were not associated with academic functioning. Later sleep timing and greater sleep variability are risk factors for certain academic problems among adolescents. Promoting sufficient, regular sleep timing across the week may improve adolescent academic functioning.

Objective and Subjective Intraindividual Variability in Sleep: Predisposing Factors and Health Consequences.

We investigated the factors that predispose or precipitate greater intraindividual variability (IIV) in sleep. We further examined the potential consequences of IIV on overall sleep quality and health outcomes, including whether these relationships were found in both self-reported and actigraphy-measured sleep IIV. In Study 1, 699 US adults completed a Sleep Intra-Individual Variability Questionnaire and self-reported psychosocial, sleep quality, and health outcomes. In Study 2, 100 university students wore actigraphy and completed psychosocial, sleep, and health surveys at multiple timepoints. In cross-sectional analyses that controlled for mean sleep duration, predisposing/precipitating factors to greater IIV were being an underrepresented racial/ethnic minority (Study 1: F = 13.95, p < .001; Study 2: F = 7.03, p = .009), having greater stress (Study 2: r values ≥ 0.32, p values ≤ .002) or trait vulnerability to stress (Study 1: r values ≥ 0.15, p values < .001), and showing poorer time management (Study 1: r values ≤ -0.12, p values ≤ .004; Study 2: r values ≤ -0.23, p values ≤ .028). In addition, both studies showed that greater sleep IIV was associated with decreased overall sleep quality, independent of mean sleep duration (Study 1: r values ≥ 0.20, p values < .001; Study 2: r values ≥ 0.33, p values ≤ .001). Concordance across subjective and objective IIV measures was modest ( r values = 0.09-0.35) and similar to concordance observed for subjective-objective mean sleep duration measures. Risk for irregular sleep patterns is increased in specific demographic groups and may be precipitated by, or contribute to, higher stress and time management inefficiencies. Irregular sleep may lead to poor sleep quality and adverse health outcomes, independent of mean sleep duration, underscoring the importance of addressing sleep consistency.

Sleep architecture of elite soccer players surrounding match days as measured by WHOOP straps

ABSTRACT This study aimed to quantify and compare sleep architecture before and after home and away matches in elite soccer players from the English Premier League. Across two seasons, 6 male players (age 28 ± 5 y; body mass 85.1 ± 9.5 kg; height 1.86 ± 0.09 m) wore WHOOP straps to monitor sleep across 13 matches that kicked off before 17:00 h. For each, sleep was recorded the night before (MD−1), after (MD) and following the match (MD +1). Across these 3 days total sleep time (TST), sleep efficiency (SE), sleep disturbances, wake time, light sleep, deep sleep, REM sleep, sleep and wake onsets, alongside external load, were compared. TST was reduced after MD versus MD +1 (392.9 ± 76.4 vs 459.1 ± 66.7 min, p = 0.003) but no differences existed in any other sleep variables between days (p > 0.05). TST did not differ after home (386.9 ± 75.7 min) vs. away matches (401.0 ± 78.3 min) (p = 0.475), nor did other sleep variables (p > 0.05). GPS-derived external load peaked on MD (p < 0.05). In conclusion, despite reduced TST on MD, sleep architecture was unaffected after matches played before 17:00 h, suggesting sleep quality was not significantly compromised.