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Purpose: Short sleep duration and poor sleep quality are common in swimmers. Sleep-hygiene strategies demonstrated beneficial effects on several sleep parameters. The present study assessed the impact of a multisession sleep-hygiene training course on sleep in elite swimmers. Methods: Twenty-eight elite swimmers (17 [2] y) participated. The sleep-hygiene strategy consisted of 3 interventions. Sleep was measured by actigraphy for 7 days before the beginning of the intervention (baseline), after the first collective intervention (postintervention), after the second collective intervention (postintervention 2), and, finally, after the individual intervention (postintervention 3). The Epworth Sleepiness Scale (ESS) was completed concurrently. Swimmers were classified into 2 groups: nonsomnolent (baseline ESS score ≤ 10, n = 13) and somnolent (baseline ESS score ≥ 11, n = 15). Results: All swimmers had a total sleep time of <8 hours per night. Sixty percent of swimmers were moderately morning type. Later bedtime, less time in bed, and total sleep time were observed in the somnolent group compared with the nonsomnolent group at baseline. An interaction between training course and group factors was observed for bedtime, with a significant advance in bedtime between baseline, postintervention 2, and postintervention 3 for the somnolent group. Conclusions: The present study confirms the importance of implementing sleep-hygiene strategies, particularly in athletes with an ESS score ≥11. A conjunction of individual and collective measures (eg, earlier bedtime, napping, and delaying morning training session) could favor the total sleep time achieved. [ABSTRACT FROM AUTHOR]

Study Objective: The present study is aimed at providing an assessment of the changes in burnout, job strain, isostrain, sleepiness, and fatigue levels over time and identifying factors associated with these symptoms among healthcare workers in French emergency departments (EDs). Method: We conducted a prospective, multicenter study in four EDs and an emergency medical service. Participants completed questionnaires at inclusion and at 90 days to assess burnout, job strain, isostrain, sleepiness, and fatigue. Results: A total of 211 respondents (43.5%) completed the questionnaires at inclusion. At the beginning of the study, 84 (40.8%) participants presented symptoms of burnout, 86 (43.2%) had symptoms of job strain, and 58 (29.4%) of isostrain. Forty‐two (20.1%) healthcare workers presented symptoms of sleepiness, and 8 (3.8%) had symptoms of fatigue. We found that symptoms of burnout were more frequent for healthcare workers with a previous psychiatric history (55.3% vs. 39.1%, p = 0.02) and were lower among participants who had at least one dependent child (33.1% vs. 48.3%, p = 0.013). Symptoms of job strain were higher among administrative staff compared to physicians (55.6% vs. 28.7%, p = 0.01) and among healthcare workers with managerial responsibilities compared to those without (45.6% vs. 28.8%, p = 0.015). Symptoms of isostrain were higher among administrative staff (42.3%) compared to paramedics (34.1%) and physicians (19.8%, p = 0.026). Conclusion: We identified that potential factors associated with the emergence of symptoms of burnout and job strain are suggested, underlining several areas of improvement for the prevention against mental health disorders in the specific population of ED healthcare workers. Trial Registration: ClinicalTrials.gov identifier: NCT04383886. [ABSTRACT FROM AUTHOR]

As sleep problems can impair quality of work, an online questionnaire was used to examine relationships between sleepiness and decision making while obtaining unobtrusive indices of performance. Participants (N = 344) completed the Insomnia Severity Index, Epworth Sleepiness Scale, and the Melbourne Decision Making Questionnaire in a Qualtrics survey while reporting mobile phone use. Qualtrics recorded the time and the number of clicks required to complete each page of the survey. Multiple regression indicated that insomnia was associated with daytime sleepiness and Hypervigilance, and mobile phone use before bed. Participants with moderate sleepiness required a greater number of clicks to complete the questionnaire. Greater sleepiness was associated with longer times to complete these self-assessment tasks. Clinically significant sleepiness produces changes in performance that can be detected from online responsivity. As sleepy individuals can be appreciably and quantitatively slower in performing subjective self-assessment tasks, this argues for objective measures of sleepiness and automated interventions and the design of systems that allow better quality sleep. Practitioner summary: Work can require processing of electronic messages, but 24/7 accessibility increases workload, causes fatigue and potentially creates security risks. Although most studies use people's self-reports, this study monitors time and clicks required to complete self-assessment rating scales. Sleepiness affected online responsivity, decreasing online accuracy and increasing response times and hypervigilance. [ABSTRACT FROM AUTHOR]

Background: Resilience can mitigate the negative impact produced by the COVID-19 pandemic. Medical students endure significant academic stress, so adjusting to sudden changes can present greater mental health challenges. The aim is to identify the level and prevalence of resilience and to know what are the educational variables and is sleep quality associated with resilience. Methods: A cross-sectional study was conducted using an online questionnaire. The survey was elaborated in Google Forms and shared through social networks. The outcome was resilience, measured with the Connor Davidson Resilience Scale. Its association was assessed with sleep quality (measured with the Pittsburgh Sleep Quality Index), daytime sleepiness (measured with the Epworth Sleepiness Scale), and selected academic/sociodemographic variables. Generalized linear models were used to identify the association between the variables. Results: Of 1277 participants, 35.7% experienced high resilience. Poor sleep quality and sleepiness were present in 88.4% and 36.0% of students, respectively. High resilience was associated with good sleep quality (PR:1.56; 95%CI: 1.34 - 1.83; p-value<0.001), absent sleepiness (PR:1.59; 95%CI: 1.32--1.91; p-value<0.001), male sex (PR: 1.21; 95%CI: 1.05--1.39; p-value 0.006), working (PR:1.14), having family responsibilities (PR: 1.36; 95%CI: 1.09--1.70; p-value 0.005) and spending more than 6 hours studying (PR: 1.35; 95%CI: 1.17--1.54; p-value<0.001). Conclusion: 4 out of 10 students presented high levels of resilience. The development of resil ience depended on multiple individual and sociodemographic factors. These findings are important to support universities in developing resilience-building measures and strategies that can be implemented to mitigate the adverse pandemic event. [ABSTRACT FROM AUTHOR]

Summary: Diagnostic manuals describe insomnia disorder (ID) characterised by fatigue and sleepiness as diurnal consequences of nocturnal symptoms. However, patients with ID do not frequently report sleepiness in the clinical setting. The present study aimed to investigate subjective sleepiness in ID measured through the Epworth Sleepiness Scale (ESS) and its independence towards daytime functioning and fatigue, and to evaluate cognitive behavioural therapy for insomnia (CBT‐I) improvement in daytime consequences and their relationship to sleepiness and fatigue. We retrospectively collected the ESS evaluation in a large sample of 105 healthy controls (HCs), 671 patients with ID, and 602 patients with sleep disorders characterised by excessive daytime sleepiness (EDS). Moreover, we conducted a pre–post evaluation of the ESS in a sub‐sample of patients with ID who underwent CBT‐I. Component 2 of the Insomnia Severity Index and Profile of Mood States–Fatigue Inertia Scale was used to evaluate daytime functioning and fatigue. Patients with ID reported ESS levels comparable to that observed in HCs and significantly lower than the EDS group. No significant correlation arose between ESS and the diurnal impact of the disorder, suggesting the independence between daytime functioning and sleepiness in ID. Contrarily, insomnia severity and diurnal impact significantly correlated with fatigue. Data showed a statistically significant increase in sleepiness after CBT‐I, despite significantly improving daytime consequences and fatigue. Although diagnostic manuals report sleepiness and fatigue as daytime consequences of sleep symptoms in patients with ID, these retrospective data indicate a dissociation between these entities. This evidence aligns with the core feature of ID: the hyperarousal status that pervades patients also during wakefulness. [ABSTRACT FROM AUTHOR]

Summary: People with heart failure (HF) experience a high symptom burden and prevalent insomnia. However, little is known about daytime symptom trajectories after cognitive behavioural therapy for insomnia (CBT‐I). In this study we describe: (1) daytime symptom trajectories among adults with insomnia and stable HF over 1 year, (2) how symptom trajectories differ between CBT‐I versus HF self‐management interventions, and (3) associations between demographic, clinical, and sleep characteristics, perceived stress, health‐related quality of life (HRQoL), functional performance and daytime symptoms trajectories. We retrospectively analysed data from a randomised controlled trial of CBT‐I versus HF self‐management (NCT0266038). We measured sleep, perceived stress, HRQoL, and functional performance at baseline and symptoms at baseline, 3, 6, and 12 months. We conducted group‐based trajectory modelling, analysis of variance, chi‐square, and proportional odds models. Among 175 participants (mean [standard deviation] age 63.0 [12.9] years, 57.1% male, 76% White), we found four daytime symptom trajectories: (A) low improving symptoms (38.3%); (B) low psychological symptoms and high improving physical symptoms (22.8%); (C) high improving symptoms (24.0%); and (D) high not improving symptoms (14.9%). The CBT‐I versus the HF self‐management group had higher odds of belonging to Group A compared to other trajectories after controlling for baseline fatigue (odds ratio = 3.27, 95% confidence interval 1.39–7.68). The difference between the CBT‐I and the HF self‐management group was not statistically significant after controlling for baseline characteristics. Group D had the highest body mass index, perceived stress, and insomnia severity and the lowest cognitive ability, HRQoL, and functional performance. Research is needed to further evaluate factors contributing to symptom trajectories. [ABSTRACT FROM AUTHOR]

Insomnia, the most prevalent sleep disorder, is commonly associated with other mental and somatic disorders, making it a significant health concern. It is characterized by nighttime symptoms and daytime dysfunction, with sleepiness being a potential criterion for the latter. Sleepiness is a normal physiological state that is typically experienced near usual bedtime, in normal circumstances. In insomnia, it seems somewhat logical the idea that there is significant daytime sleepiness. However, the topic has been the subject of various discussions in sleep medicine, with studies yielding contradictory and inconsistent results. In this article, we aim to critically examine daytime sleepiness in individuals with insomnia disorder and propose an alternative approach to addressing it, both in clinical practice and research settings. It is crucial to further investigate the role of daytime sleepiness in insomnia, particularly by focusing on sleepiness perception as a more relevant dimension to explore in majority of patients. It is plausible that certain insomnia phenotypes are objectively sleepy during the day, but more studies are necessary, particularly with well-defined clinical samples. The implications of assessing sleepiness perception in insomnia for clinical practice are discussed, and new avenues for research are suggested. [ABSTRACT FROM AUTHOR]

BACKGROUND: Situational awareness is the acquisition of information from elements present in the work environment, the perception of the meaning of this information, and the prediction of future working conditions. Sleepiness and fatigue can influence an individual's ability to reach situation awareness, decision-making, and performance on a task. OBJECTIVE: This scoping review examines methods used to assess situational awareness, fatigue, sleepiness, and their interrelationships. METHODS: A systematic search of online databases was conducted to identify experimental, peer-reviewed articles published in English between 2017 and 2022. A total of 29 publications were selected for analysis. RESULTS: The selected studies originated from various countries, primarily in the northern hemisphere. Health and automotive engineering were the academic categories with the highest publications. The studies employed objective and subjective methods to assess situational awareness, fatigue, and sleepiness. CONCLUSIONS: Most studies reported a decline in situational awareness during fatigue and sleepiness conditions, although one study did not find this association. Future research should focus on employing objective methods to analyze cognitive factors, increasing sample sizes, and conducting testing in real-world situations. [ABSTRACT FROM AUTHOR]

BACKGROUND: The transition from alertness to drowsiness can cause considerable changes in the respiratory system, providing an opportunity to detect driver drowsiness. OBJECTIVE: The aim of this study was to determine which respiratory features indicate driver drowsiness and then use these features to classify the level of drowsiness and alertness. METHODS: Twenty male students (mean age 25.6±2.41 years) participated in the study using a driving simulator, and eight features, including expiration duration (ED), inspiration duration (ID), peak-to-peak amplitude (PA), inspiration-to-expiration time ratio (I/E ratio), driving, timing, respiration rate (RR), and yawning, were extracted from the respiratory signal generated by abdominal motions using a belt equipped with a force sensor. RESULTS: All eight features were statistically significant at the significance level of 0.05. Drowsiness can be detected using respiratory features with 88% accuracy, 82% precision, 86% recall, and an 90% F1 score. CONCLUSION: The findings of this study may be useful in the development of driver drowsiness monitoring systems based on less intrusive respiratory signal analysis, particularly for specific process automation applications when vehicle control is not in the hands of the driver. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Quick returns (

BackgroundEvaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).MethodsUsing previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.ResultsThe ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.ConclusionThis review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Abstract Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be ‘objective’ measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Background and Objective: Lack of sleep and insomnia are associated with an increase in the risk of diabetes. Sleep disorders in diabetic people are significantly higher than in healthy people. Moreover, sleep duration is related to blood sugar control in diabetes. This study was conducted with the purpose of investigating the level of sleepiness and obstructive sleep apnea in type 2 diabetic patients and its relationship with glycemic levels. Materials and Methods: This cross-sectional study was conducted on 200 patients with type 2 diabetes referred to Shahid Beheshti Hospital in Hamadan in­ 2023­. Diabetes control status was evaluated by hemoglobin A1c, and the frequency of sleepiness and obstructive sleep apnea was assessed by the Epworth Sleepiness Scale and STOP-BANG questionnaires. Data analysis was done using SPSS 26 statistical software. Results: The mean age of the participants was 56.16 ± 9.77 years. A significant difference was observed between the frequency of daily sleepiness score with gender (P

Summary Patients with idiopathic hypersomnia frequently report having unrefreshing naps. However, whether they have abnormal sleep architecture during naps that may explain their unrefreshing aspect is unknown. We compared sleep architecture during short daytime naps in patients with idiopathic hypersomnia reporting unrefreshing and refreshing naps. One‐hundred and thirty‐four patients tested with one‐night polysomnography, followed by an adapted version of the Multiple Sleep Latency Test with four naps, were included. They were asked about the refreshing aspect of their habitual naps during a clinical interview. They were classified as having objective (Multiple Sleep Latency Test ≤ 8 min) or subjective idiopathic hypersomnia (Multiple Sleep Latency Test > 8 min), and as presenting refreshing or unrefreshing naps. We tested Group differences (refreshing versus unrefreshing naps) on nap sleep architecture in the whole sample and for subjective and objective idiopathic hypersomnia subgroups separately using ANCOVAs. No Group effects were observed in the Multiple Sleep Latency Test architecture in the whole sample and in objective and subjective idiopathic hypersomnia subgroups. This study provides preliminary evidence that reporting unrefreshing naps is not associated with clinically significant findings in Multiple Sleep Latency Test sleep architecture in patients with idiopathic hypersomnia. Given that naps taken by patients with idiopathic hypersomnia are typically long, future studies should investigate longer daytime sleep episodes. [ABSTRACT FROM AUTHOR]

The bimodal preference is a fourth diurnal preference proposed by re-scoring the Morningness-Eveningness Questionnaire. The present work aimed to describe the prevalence of the bimodal preference in a sample of undergraduate students and to characterize the bimodal type in terms of their health and sleep-related outcomes. A web-based cross-sectional study conducted between September 2018 and March 2021 (convenience sampling method). The sample was composed of undergraduate students who completed an electronic form that included the Morningness and Eveningness Questionnaire, the Pittsburgh Sleep Quality Index, the Self-Compassion Scale, the Epworth Sleepiness Scale, the Hospital Anxiety and Depression Scale, and the World Health Organization Subjective Well-Being Index. The final sample consisted of 615 students (82% female, mean age: 23.4 ± 6.5 years), of whom 108 (18%) had positive bimodality indexes. Bimodal subjects comprised 48 students, 8% of the total sample. Bimodal subjects had poorer subjective sleep quality, more daytime sleepiness, lower subjective well-being, greater anxiety and depression symptoms, and lower self-compassion than morning and/or intermediate types; they did not differ from evening types. The description of bimodal diurnal preference in this population may be of interest for the design of academic policies more in line with the circadian reality of students. [ABSTRACT FROM AUTHOR]

Purpose: To clarify the relationship between quality of sleep and pregnancy outcomes and to explore how sleep quality affects mood state in the first trimester of pregnancy. Methods: This prospective cohort study enrolled pregnant women from June 2020 to June 2021. Maternal sleep conditions, daytime sleepiness, and mood state in the first trimester were assessed using four Chinese self-rating scales, namely, the Pittsburgh Sleep Quality Index (PSQI), the Sleep Hygiene Practice Scale (SHPS), Epworth Sleepiness Scale (ESS), and the abbreviated version of the Profile of Mood States (a-POMS). Participants were divided into an exposed group (PSQI score > 5, poor sleep quality group) and a non-exposed group (PSQI score ≤ 5, good sleep quality group). Maternal characteristics, pregnancy outcomes, and the relationship among sleep quality, sleepiness, and mood state were analyzed. Comparisons of sleep hygiene behavior variables between the two subgroups were also analyzed. Results: A total of 2703 pregnant women were enrolled in the study. Poor sleep quality increased the probability of gestational diabetes mellitus (GDM) (1.573, 1.315–1.863), liver function damage (1.467, 1.021–2.107), preterm delivery (1.468, 1.077–2.002), mild sleepiness (1.612, 1.357–1.915), and excessive sleepiness (2.134, 1.686–2.701). Poor maternal sleep quality was significantly associated with the occurrence of preterm premature rupture of membranes (1.947, 1.168–3.243) and perinatal death (1.003, 1.000–1.006). Additionally, a significant positive correlation between the PSQI score and the total mood disturbance (TMD) score was revealed by Spearman's correlation analysis (r = 0.378, P < 0.01). Enter Regression analysis demonstrated that sleep quality (R2 = 0.390, P < 0.01) and sleepiness (R2 = 0.234, P < 0.01) exerted significant direct effects on mood state during pregnancy. Furthermore, Spearman's correlation analysis indicated a positive association between the PSQI score and the SHPS total score (r = 0.227, P < 0.01). Conclusions: Poor sleep quality is significantly associated with elevated rates of maternal mood disturbances, obstetric complications, and adverse outcomes in infants. The findings suggest that it may be useful to provide comprehensive sleep assessment and education on sleep hygiene during the early stages of pregnancy. [ABSTRACT FROM AUTHOR]

Background: Boxing exposes fighters to head impacts and potential traumatic brain injury (TBI). Though research has explored the neuropsychiatric consequences of contact sports, there is limited research into Excessive Daytime Sleepiness (EDS) and its relationship to other outcomes, such as impulsiveness and depression. Therefore, this study aimed to describe EDS in retired boxers using the Epworth Sleepiness Scale (ESS) and to examine how boxing and sleepiness relate to impulsiveness and depression symptomatology. Methods: 86 male retired professional boxers from the Professional Fighters Brain Health Study (PFBHS) met the inclusion criteria. Adjusted multivariable models analyzed relationships between professional boxing bouts, EDS (ESS), impulsiveness (Barratt Impulsiveness Scale Version 11 (BIS-11)), and/or depression (Patient Health Questionnaire-9 (PHQ-9)). A causal mediation analysis was performed to assess whether boxing bouts and ESS scores predicted BIS-11 and PHQ-9 scores. Results: Mean age was ∼51 years, fighters averaged ∼36 professional bouts, and ESS mean(SD) was 7.5(5.3). ESS scores were significantly associated with raw BIS-11 (Beta = 1.26, 95%CI = 0.77–1.75, p < 0.001) and ordinal PHQ-9 (OR = 1.20, 95%CI = 1.11–1.31, p < 0.001) scores in adjusted models, and the significant relationship between boxing bouts and BIS-11/PHQ-9 was mediated by ESS. Conclusions: EDS in retired male professional boxers may be strongly associated with other neuropsychiatric sequelae of TBI (impulsiveness and depression). Sleepiness; sleep; boxing; contact sports; impulsiveness; impulsivity; depression; Epworth sleepiness scale box [ABSTRACT FROM AUTHOR]

Summary: Sleep symptoms, including excessive sleepiness, are frequently reported by patients with functional motor disorders (FMD). We aimed to classify the comorbid sleep disorders in FMD, and to investigate the relationship between subjective sleepiness and objective measures of hypersomnia, comparing them with data from people with central hypersomnia. A total of 37 patients (mean [SD] age 46.4 [11.2] years) with clinically definite FMD, and 17 patients (mean [SD] age 41.1 [11.6] years) with central hypersomnia underwent structured medical and sleep history, neurological examination, polysomnography, multiple sleep latency test (MSLT), and questionnaires assessing sleepiness, fatigue, and depression. In all, 23 patients with FMD (62%) reported excessive daytime sleepiness. Evidence of specific sleep disorders was identified in our cohort, with 35% having restless legs syndrome; 49% obstructive sleep apnea; and 8% periodic limb movements in sleep; however, the presence of these disorders was not correlated with subjective sleepiness. Patients with FMD with self‐reported sleepiness reported higher fatigue (p = 0.002), depression (p = 0.002), and had longer sleep latencies in the MSLT (p < 0.001) compared to the patients with central hypersomnia. No correlation was found between subjective and objective sleepiness in either group. Fatigue positively correlated with self‐reported sleepiness in patients with FMD (p < 0.001). This study did not find objective correlates of increased sleepiness in patients with FMD. While sleep abnormalities were found to be common in FMD, they were not correlated with self‐reports of excessive sleepiness. Positive correlations between self‐reported sleepiness and fatigue support the current unified model of non‐motor symptoms in FMD. [ABSTRACT FROM AUTHOR]

Summary: The aim of this study was to assess work productivity and activity impairments and to explore their association with excessive daytime sleepiness, body mass index (BMI), depression, and anxiety in patients with narcolepsy type 1. We carried out a cross‐sectional study in which patients with narcolepsy type 1 and matched controls for sex, age, and education were assessed for occupational features, EDS (Epworth Sleepiness Scale), BMI, depression (Beck Depression Inventory), anxiety (State–Trait Anxiety Inventory), and Work Productivity and Activity Impairment (WPAI). Different statistical approaches were used to investigate differences between groups and correlations between WPAI scores and clinical features. The 127 patients with narcolepsy type 1 (mean age 38.2 ± 15.5, 91.3% taking drugs for narcolepsy) and 131 controls (mean age of 37.4 ± 14.3) included did not differ in terms of occupational features, except for hours worked/week (29.9 in patients vs. 34.9 in controls) and officially recognised disability (30.7% vs. 5.3%). Impairment in all WPAI scores was approximately three times greater in patients. Narcolepsy was associated with work time missed in 27.4% of patients, while 93.2% to 95.5% of them had some impairment while working or during daily activities (vs. 37.5–46.8% of controls). Correlations with WPAI scores were found for excessive daytime sleepiness only in patients, and for both depression and anxiety in patients and controls, with a stronger correlation for activity impairment in patients. These results suggest that, despite treatment, narcolepsy type 1 was associated with extensive impairment especially regarding job effectiveness and daily activities. Future studies should investigate risk factors and effects of interventions on these outcomes. [ABSTRACT FROM AUTHOR]

Summary: Sleep variability is commonly seen in the young populations. This study aimed to examine the impacts of experimentally induced sleep variability on sleepiness, mood, cognitive performance and sleep architectures among young adults. Thirty‐six healthy individuals (aged 18–22 years) were randomly assigned to either variable sleep schedule (n = 20) or control (n = 16) groups. The protocol involved 1 week of regular sleep (time in bed = 7.5 hr) in the home setting, followed by one adaptation night (time in bed = 7.5 hr), one baseline night (time in bed = 7.5 hr), and 6 nights of sleep manipulation in the laboratory monitored by polysomnography (three cycles of variable sleep schedule by changing daily time in bed alternating between 6 hr and 9 hr for variable sleep schedule group versus fixed sleep schedule with daily time in bed for 7.5 hr for control group). Sleepiness, mood, sustained attention, processing speed, response inhibition and working memory were measured every morning and evening. The variable sleep schedule group reported a higher level of sleepiness, especially in the mornings, and increased negative mood in the evenings. There were no significant differences in positive mood, cognitive performance and sleep macro‐ and micro‐structures. Our results showed the negative effects of sleep variability on daytime functioning especially sleepiness and negative mood, suggesting the need to address variable sleep schedules through sleep intervention. [ABSTRACT FROM AUTHOR]

Summary: The Maintenance of Wakefulness Test is widely used to objectively assess sleepiness and make safety‐related decisions, but its interpretation is subjective and normative values remain debated. Our work aimed to determine normative thresholds in non‐subjectively sleepy patients with well‐treated obstructive sleep apnea, and to assess intra‐ and inter‐scorer variability. We included maintenance of wakefulness tests of 141 consecutive patients with treated obstructive sleep apnea (90% men, mean (SD) age 47.5 (9.2) years, mean (SD) pre‐treatment apnea–hypopnea index of 43.8 (20.3) events/h). Sleep onset latencies were independently scored by two experts. Discordant scorings were reviewed to reach a consensus and half of the cohort was double‐scored by each scorer. Intra‐ and inter‐scorer variability was assessed using Cohen's kappa for 40, 33, and 19 min mean sleep latency thresholds. Consensual mean sleep latencies were compared between four groups according to subjective sleepiness (Epworth Sleepiness Scale score < versus ≥11) and residual apnea–hypopnea index (< versus ≥15 events/h). In well‐treated non‐sleepy patients (n = 76), the consensual mean (SD) sleep latency was 38.4 (4.2) min (lower normal limit [mean – 2SD] = 30 min), and 80% of them did not fall asleep. Intra‐scorer agreement on mean sleep latency was high but inter‐scorer was only fair (Cohen's kappa 0.54 for 33‐min threshold, 0.27 for 19‐min threshold), resulting in changes in latency category in 4%–12% of patients. A higher sleepiness score but not the residual apnea–hypopnea index was significantly associated with a lower mean sleep latency. Our findings suggest a higher than usually accepted normative threshold (30 min) in this context and emphasise the need for more reproducible scoring approaches. [ABSTRACT FROM AUTHOR]

This cross-sectional study investigated the level of daytime sleepiness and sleep-related behaviors in preschool children and compared their self-evaluations with the evaluations of their parents. It was conducted in Split-Dalmatian County, Croatia, among 196 preschool children aged 6–7 years seen at regular medical examinations, accompanied by their parents, using the Epworth sleepiness scale for children and parents/caregivers. Compared to their child's reports, parents tended to underestimate their child's sleepiness while sitting in a classroom at school (p = 0.001) and overestimate their child's sleepiness when lying down to rest or nap in the afternoon (p < 0.001). Boys were sleepier while sitting in a classroom at school during the morning than girls (p = 0.032). As much as 48.2% of preschool children had their own cellphones/tablets. Boys used video games (p < 0.001) and cellphones/tablets more than girls did (p = 0.064). Parental estimation of children playing video games at bedtime was lower than the child's report (p < 0.001). Children who had a TV in their bedroom reported more daytime sleepiness (p = 0.049), and those who played video games at bedtime went to sleep later during the weekend (p = 0.024). Also, children owning cellphone/tablets had longer sleep latency during the weekend compared to children not owning a cellphone (p = 0.015). This study confirmed that parents tend to underestimate children's habits of playing video games at bedtime and children's sleepiness during morning classes. Preschool children who use electronic devices at bedtime more frequently have prolonged sleep latency. These findings provide further evidence of the effects of electronic media devices on preschoolers' sleep patterns and daytime sleepiness. [ABSTRACT FROM AUTHOR]

Aims Background Method EQUATOR checklist Results Conclusion Implications for nursing and nursing policy This study aimed to determine the peak hours of sleepiness and the factors affecting the sleepiness levels of nurses.Sleepiness is commonly seen in individuals working night shifts. However, in case of nurses, this sleepiness can be a major threat to patient and staff safety.This was a prospective cross‐sectional study. Data were collected between July and September 2023, and a stratified sampling method was used according to the departments in which the nurses worked. Data were collected using the Personal Information Form and Visual Analog Scale. Nurses reported their sleepiness levels at the beginning of each hour between midnight and 8:00 am.The study adhered to the STROBE checklist for reporting.The mean sleepiness levels of emergency department nurses, intensive care nurses, internal or surgical clinic nurses, and all nurses were 59.75 ± 15.50, 43.53 ± 20.49, 44.67 ± 18.88, and 49.15 ± 19.67, respectively. The highest sleepiness level of the nurses was at 05:00 am. A significant correlation was found between the variables of age, gender, marital status, sleep quality, number of patients cared, working style and satisfaction with working in the department, and sleepiness level (P < 0.05).Nurses working night shifts experience sleepiness (highest at 5:00 am). In addition, the sleepiness levels of nurses are affected by some personal and clinical factors.Based on the results, there is a need for necessary policies regarding nurses' working hours and working conditions. To protect patient and employee safety, necessary strategies should be devised regarding the hours when nurses experience the highest sleepiness and the factors affecting sleepiness levels. [ABSTRACT FROM AUTHOR]

• Synchrony between chronotype and time of day is largely associated with subjective mood and driving speed. • Driving behavior and mood constantly impair with time-on-task while driving under sleepiness. • Under sleep inertia, driving behavior and mood stay rather constant on a low level. • Performance and mood are differentially affected by the time of day under sleepiness versus sleep inertia. Sleep is a desired use case in highly automated driving and promises drivers relief from sleepiness. Benefits of sleeping on subjective mood and performance in the driving task may be opposed by sleep inertia, the post-sleep grogginess and performance impairment. The magnitude of both, sleepiness and sleep inertia may depend on sleep-homeostatic and circadian factors. We therefore investigated how the effects of sleep inertia are affected by the time of day a nap is taken during automated driving and the role of individual chronotypes both in comparison to the effects of sleepiness. In the presented driving simulator study, 10 distinct morningness and 10 eveningness chronotypes were invited to two test sessions, one in the early morning (starting at 6 a.m.) and one in the late evening (starting at 9 p.m.). Participants slept during an automated drive and were requested to drive manually before and after an instructed nap. We examined the time course of the subjective state, driving behavior and vigilance in dependence of time of day and individual chronotype under sleepiness and sleep inertia. Effects of both, sleepiness and sleep inertia on subjective arousal, wellbeing, motivation, and driving speed were stronger when the time of day did not fit the individual chronotype. This counts particularly for morningness types. Subjective arousal, wellbeing, and motivation were more impaired after the instructed nap in the evening than in the morning. Analogously, driving speed was slower and take-over times were longer after napping in the evening compared to in the morning. Compared to sleepiness, lane keeping and reaction times were not significantly impaired under sleep inertia, probably because the task induced workload could be compensated by reducing speed and prolonging take-over times. Under sleepiness, driving was characterized by distinct time-on-task effects, which caused mood, lane keeping, and vigilance to deteriorate with driving time. In contrast, the investigated measures were more stable with time on task under sleep inertia, possibly due to a compensation by speed reduction and a balance between beneficial and detrimental effects of the intermediate sleep. [ABSTRACT FROM AUTHOR]

This study investigated the predictive effects of nomophobia, netlessphobia, and sleepiness on fatigue. The sample consisted of 907 students from a public university. Data were collected using Demographical Information Form, the Fırat Netlessphobia Scale, the Fırat Nomophobia Scale, the Epworth Sleepiness Scale, and the Chalder Fatigue Scale. Therefore, structural equation modeling was used to identify factors affecting fatigue. The structural equation modeling was performed using the Analysis of Moment Structures. The results showed that nomophobia, netlessphobia, and sleepiness predicted fatigue, explaining 31% of the total variance. Nomophobia and netlessphobia predicted sleepiness, with nomophobia and netlessphobia explaining 18% and 30% of the total variance, respectively. [ABSTRACT FROM AUTHOR]

Impaired daytime vigilance is an important consequence of OSA, but several studies have reported no association between objective measurements of vigilance and the apnea-hypopnea index (AHI). Notably, the AHI does not quantify the degree of flow limitation, that is, the extent to which ventilation fails to meet intended ventilation (ventilatory drive). Is flow limitation during sleep associated with daytime vigilance in OSA? Nine hundred ninety-eight participants with suspected OSA completed a 10-min psychomotor vigilance task (PVT) before same-night in-laboratory polysomnography. Flow limitation frequency (percent of flow-limited breaths) during sleep was quantified using airflow shapes (eg, fluttering and scooping) from nasal pressure airflow. Multivariable regression assessed the association between flow limitation frequency and the number of lapses (response times > 500 ms, primary outcome), adjusting for age, sex, BMI, total sleep time, depression, and smoking status. Increased flow limitation frequency was associated with decreased vigilance: a 1-SD (35.3%) increase was associated with 2.1 additional PVT lapses (95% CI, 0.7-3.7; P =.003). This magnitude was similar to that for age, where a 1-SD increase (13.5 years) was associated with 1.9 additional lapses. Results were similar after adjusting for AHI, hypoxemia severity, and arousal severity. The AHI was not associated with PVT lapses (P =.20). In secondary exploratory analysis, flow limitation frequency was associated with mean response speed (P =.012), median response time (P =.029), fastest 10% response time (P =.041), slowest 10% response time (P =.018), and slowest 10% response speed (P =.005). Increased flow limitation during sleep was associated with decreased daytime vigilance in individuals with suspected OSA, independent of the AHI. Flow limitation may complement standard clinical metrics in identifying individuals whose vigilance impairment most likely is explained by OSA. [ABSTRACT FROM AUTHOR]

Summary: Sleepiness is a multicausal condition, and previous research has highlighted associations between this symptom and the circadian timing system, specifically concerning social jetlag and sleep variability. Recent inquiries have shown that the effects of social jetlag on sleepiness can be confounded with the consequences of sleep debt. In light of the current evidence, we aimed to assess the effects of social jetlag and sleep variability on sleepiness and the potential mediating role of sleep debt. We used data from the EPISONO study, a cross‐sectional population‐based study with a sample size of 1042 participants, representative of the city of Sao Paulo, Brazil. Participants completed the UNIFESP Sleep Questionnaire (self‐reported bedtime and get‐up time) and the Epworth Sleepiness Scale (subjective daytime sleepiness). Subsequently, sleep‐corrected mid‐sleep time (chronotype), total sleep time, social jetlag (absolute difference between the mid‐sleep time on workdays and mid‐sleep time on free days), sleep variability (standard deviation of mid‐sleep time), and sleep debt (difference between total sleep time on workdays and free days) were calculated. Generalised linear models were used to test whether social jetlag and sleep variability affected sleepiness. Mediation models were used to determine if any observed significant effects were mediated by sleep debt. The prevalence of social jetlag was 23% for >1 h and 12% for >2 h. The mean sleep variability was 41 ± 30 min. Social jetlag had a significant effect on the Epworth Sleepiness Scale scores. This association was no longer statistically significant after controlling for age, sex, body mass index, work schedule, and chronotype. A significant indirect effect of social jetlag on sleep debt and subsequently on the Epworth Sleepiness Scale scores was found. No effect of sleep variability on sleepiness could be identified. In conclusion, the association between social jetlag and sleepiness was mediated by sleep debt but was not independent of demographic, work, and chronotype variables. This study provides new evidence on the importance of circadian misalignment and sleep debt for sleep health on a population level. [ABSTRACT FROM AUTHOR]