Lower Sleepiness Research Articles

Associations of mood, stress, and social support with sleep duration and daytime sleepiness among adolescents in semi-rural Georgia

ObjectiveAdolescents are at greater risk for poor sleep compared to childhood; however, there is limited data regarding psychosocial determinants of adverse sleep health among semi-rural adolescents. We investigated associations of mood, stress, and social support with self-reported sleep duration and daytime sleepiness among adolescents. MethodsAdolescents (n = 254) in semi-rural Georgia self-reported depressive and anxiety symptoms, stress, social support, sleep duration and daytime sleepiness in November 2020. Multinomial linear and logistic models were fit to examine associations of psychosocial factors with sleep duration and sleepiness; and effect modification by social support was tested after adjustment for covariates. ResultsMost participants were non-Hispanic White (55 %), female (53 %), and approximately 35 % were eligible for free-reduced lunch. Mean sleep duration (± SD) and daytime sleepiness was 8.04 ± 1.36 and 5.17 ± 2.37, respectively; and 42 % of participants reported insufficient sleep (<8 h). Depressive (β = 0.13, 95 % CI: 0.08, 0.18) and anxiety (β = 1.20, 95 % CI 0.51, 1.88) symptoms, and stress (β = 1.97, 95 % CI 1.21, 2.74) were associated with higher sleepiness scores. The psychosocial factors were associated with higher odds of insufficient sleep duration, but not continuous sleep duration. Higher social support was associated with lower sleepiness, but not sleep duration. There was no observed effect modification by social support. ConclusionsExperiences of psychosocial factors were associated with more sleepiness and insufficient sleep, while social support was associated with less sleepiness. Future studies should explore intervention strategies to enhance mood and social support and reduce stress to improve sleep among semi-rural adolescents.

Assessing ‘readiness’ by tracking fluctuations in daily sleep duration and their effects on daily mood, motivation, and sleepiness

Study objectivesConsumer sleep trackers issue daily guidance on ‘readiness’ without clear empirical basis. We investigated how self-rated mood, motivation, and sleepiness (MMS) levels are affected by daily fluctuations in sleep duration, timing, and efficiency and overall sleep regularity. We also determined how temporally specific these associations are. Methods119 healthy university students (64 female, mean age = 22.54 ± 1.74 years) wore a wearable sleep tracker and undertook twice-daily smartphone-delivered ecological momentary assessment of mood, motivation, and sleepiness at post-wake and pre-bedtime timings for 2–6 weeks. Naps and their duration were reported daily. Nocturnal sleep on 2471 nights were examined using multilevel models to uncover within-subject and between-subject associations between sleep duration, timing, efficiency, and nap duration on following day MMS ratings. Time-lagged analyses examined the temporal specificity of these associations. Linear regression models investigated associations between MMS ratings and sleep variability, controlling for sleep duration. ResultsNocturnal sleep durations were short (6.03 ± 0.71 h), and bedtimes were late (1:42AM ± 1:05). Within-subjects, nocturnal sleep longer than a person's average was associated with better mood, higher motivation, and lower sleepiness after waking. Effects of such longer sleep duration lingered for mood and sleepiness till the pre-bedtime window (all Ps < .005) but did not extend to the next day. Between-subjects, higher intraindividual sleep variability, but not sleep duration, was associated with poorer mood and lower motivation after waking. Longer average sleep duration was associated with less sleepiness after waking and lower motivation pre-bedtime (all Ps < .05). Longer naps reduced post-nap sleepiness and improved mood. Controlling for nocturnal sleep duration, longer naps also associated with lower post-waking sleepiness on the following day. ConclusionsPositive connections between nocturnal sleep and nap duration with MMS are temporally circumscribed, lending credence to the construction of sleep-based, daily ‘readiness’ scores. Higher sleep duration variability lowers an individual's post waking mood and motivation. Clinical trial idClinicalTrials.gov NCT04880629.

Habitual Videogame Playing Does Not Compromise Subjective Sleep Quality and Is Associated with Improved Daytime Functioning.

Research on the effects of videogames (VGs) on health has produced mixed results. Here, we assess the relationships of VG playing with sleep; chronotype; sleepiness; and levels of depression, anxiety, and stress; and how they are modulated by the level of exposure to VGs. Four hundred-and two adult participants (age = 26.2 ± 7.84; 227 F) completed an online survey including questions on VG use and a set of standardized questionnaires. The sample was divided into three groups: habitual gamers (HGs, 42.2%), nonhabitual gamers (NHGs, 36.5%), and non-gamers (NGs, 21.3%). No between-group differences emerged in sleepiness (Epworth Sleepiness Scale) or Pittsburgh Sleep Quality Index measures except the sleep disturbances subscore, which was higher in NHGs. HGs showed delayed bed- and risetimes and higher eveningness (reduced Morningness-Eveningness Questionnaire). HGs and NHGs showed higher depression subscores (Depression Anxiety Stress Scale) but remained in the subclinical range. Moreover, hours/week of VG playing predicted delayed sleep timing, lower daytime dysfunction, and lower sleepiness. Our data suggest that VG playing does not necessarily compromise sleep quality and may even benefit daytime functioning, underlining the need to reconsider the relationships between VG use and health by taking into account possible modulating factors such as habitual VG exposure.

THE MEDIATING ROLE OF FATIGUE/SLEEPINESS BETWEEN STATE MINDFULNESS AND SUBJECTIVE COGNITION

Abstract Previous studies have established a connection between higher mindfulness and cognitive abilities; however, few studies have considered the mechanism underlying this relationship. The cognitive benefit of mindfulness may be through reduced fatigue and daytime sleepiness. This study examined if higher, naturally occurring mindfulness is associated with higher subjective cognition and whether lower fatigue or sleepiness mediate this relationship. Two independent samples of nurses (N1=60 inpatient (IP); N2=84 outpatient (OP)) completed 14 days of ecological momentary assessment (EMA). Fatigue/sleepiness, mindfulness, and subjective cognition (mental speed, processing sharpness, memory) were assessed using EMA. The 5-item Mindful Attention Awareness Scale assessed state mindfulness. Multilevel mediations were conducted in Mplus to account for the nested data. At the within-person level, daily subjective cognition was higher than average on days when mindfulness was higher in both OP and IP samples. This association was mediated by lower levels of fatigue (IP indirect effect: B=2.08, p&amp;lt;.001; OP indirect effect: B=2.57, p&amp;lt;.001) and lower sleepiness (IP indirect effect: B=1.72, p=.001; OP indirect effect: B=0.92, p=.027). The daily indirect pathways were found after controlling for between-person differences; those with higher mindfulness reported higher subjective cognition through lower fatigue, and this effect was only significant in OP nurses (indirect effect: B=11.61, p=.001). Results highlight the importance of monitoring momentary mindfulness and intervening on daily fatigue and sleepiness as these may influence one’s subjective cognition and ultimately their objective performance. These findings may help identify modifiable factors to promote quality of care in nurses and their own well-being.

Sleepiness Moderates the Associations between Personality and Financial Risk Tolerance and Spending Habits among College Students

ABSTRACT Objectives Personality and sleep characteristics are related to financial attitudes and behaviors. However, to our knowledge no study has examined how personality and sleep may be conjointly associated with these financial outcomes. The present study examined sleepiness as a moderator of the associations between college students’ personality traits and financial risk tolerance and spending habits. Methods Undergraduates (N = 177, 77% women, 78% White) self-reported their personality traits and sleepiness using well-established questionnaires. Financial attitudes and behaviors were assessed via students’ self-reported responses to a set of scenarios assessing risk tolerance as well as their spending habits over the prior two weeks. Results Multiple regression analyses were run. Across five significant two-way interactions, high levels of sleepiness exacerbated risk for greater financial risk tolerance and higher spending among those characterized by high open-mindedness and low neuroticism, whereas low sleepiness increased protection for lower risk tolerance and less spending among those high in agreeableness and conscientiousness. Conclusions Sleepiness may act as both a vulnerability and protective factor in relations between personality and financial attitudes and behaviors. Improvements in sleepiness, which is modifiable via intervention, may have significant implications for individuals’ financial well-being.

Active interventions of dynamic lighting on human circadian rhythm and sleep quality in confined spaces

People in closed spaces without daylight for a long time are prone to circadian rhythm desynchrony and sleep disorders. To explore the effects of different lighting patterns on circadian rhythm and sleep, 20 adults were confined in an underground lab by within-subject design for four consecutive weeks with one lighting pattern per week. The static lighting pattern (SLP) was used in the 1st week, then the circadian forward lighting pattern (FLP) in the 2nd and 4th weeks, and the backward lighting pattern (BLP) in the 3rd week. Their salivary melatonin, Karolinska Sleepiness Scale(KSS),core body temperature (CBT), Pittsburgh Sleep Quality Index (PSQI), sleep latency and the number of awakenings were measured. The results showed dim light melatonin onset (DLMO) was delayed by 0.62 h during the 1st week, indicating the backward tendency of circadian rhythm but without significance (p = 0.295). In the 2 nd week, the schedule was forced to bring forward by 2 h, assisted with FLP. The BLP in the 3rd week resulted in a significant delay of 1.87 h in DLMO(p = 0.002) and lower melatonin at bedtime (p = 0.001), with progressively longer sleep latency, lower sleepiness at night and CBT when waking up, and PSQI increased day by day, meaning the gradually deteriorated sleep. In the 4th week, DLMO was significantly shifted forward by 2.13 h (p = 0.003), melatonin at bedtime was higher (p = 0.000), and sleep quality gradually improved. Lighting interventions on KSS, CBT, PSQI and sleep latency showed day-by-day cumulative effects, and the dynamic lighting interventions can help maintain circadian rhythm stability in closed spaces and adapt to shift hours.

A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions

Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1–9 or a binary decision as alert (defined as KSS 1–6) or sleepy (defined as KSS 7–9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.

Effect of an Acute Insect Preload vs. an Almond Preload on Energy Intake, Subjective Food Consumption and Intestinal Health in Healthy Young Adults.

Protein is considered the most satiating macronutrient, and its effect on satiety and food intake is source-dependent. For the first time, we compared the effect of the administration of an insect or almond preload, both containing 20 g of protein, on appetite and food intake in human subjects. Participants consumed both foods and a vehicle as a liquid preload on three separate days. They were then offered a breakfast and lunch buffet meal at which food intake was measured. Visual analogue scale (VAS) questionnaires were completed following the three preloads to assess appetite and other sensations. At breakfast, reduced energy intake was observed for both preloads compared with vehicle. At lunch, food intake only differed in the insect group, which consumed more than the vehicle. Insect preload increased the total amount of protein ingested with a slight increase in total energy consumed, differently than almond, which significantly increased total protein and energy consumed. There was no correlation between indigestion-sensation ratings and food intake. Moreover, the insect preload resulted in lower sleepiness and tiredness ratings compared with the almond preload. Thus, insect-derived protein may be suitable as a safe ingredient for snacks intended for elderly or infirm patients who require increased protein intake.

Sleepiness is a signal to go to bed: data and model simulations.

Study ObjectivesAssess the validity of a subjective measure of sleepiness as an indicator of sleep drive by quantifying associations between intraindividual variation in evening sleepiness and bedtime, sleep duration, and next morning and subsequent evening sleepiness, in young adults.MethodsSleep timing and sleepiness were assessed in 19 students in late autumn and late spring on a total of 771 days. Karolinska Sleepiness Scales (KSS) were completed at half-hourly intervals at fixed clock times starting 4 h prior to participants’ habitual bedtime, and in the morning. Associations between sleepiness and sleep timing were evaluated by mixed model and nonparametric approaches and simulated with a mathematical model for the homeostatic and circadian regulation of sleepiness.ResultsIntraindividual variation in evening sleepiness was very large, covering four or five points on the 9-point KSS scale, and was significantly associated with subsequent sleep timing. On average, a one point higher KSS value was followed by 20 min earlier bedtime, which led to 11 min longer sleep, which correlated with lower sleepiness next morning and the following evening. Associations between sleepiness and sleep timing were stronger in early compared to late sleepers. Model simulations indicated that the directions of associations between sleepiness and sleep timing are in accordance with their homeostatic and circadian regulation, even though much of the variance in evening sleepiness and details of its time course remain unexplained by the model.ConclusionSubjective sleepiness is a valid indicator of the drive for sleep which, if acted upon, can reduce insufficient sleep.

Driver sleepiness detection with deep neural networks using electrophysiological data

Objective. The objective of this paper is to present a driver sleepiness detection model based on electrophysiological data and a neural network consisting of convolutional neural networks and a long short-term memory architecture. Approach. The model was developed and evaluated on data from 12 different experiments with 269 drivers and 1187 driving sessions during daytime (low sleepiness condition) and night-time (high sleepiness condition), collected during naturalistic driving conditions on real roads in Sweden or in an advanced moving-base driving simulator. Electrooculographic and electroencephalographic time series data, split up in 16 634 2.5 min data segments was used as input to the deep neural network. This probably constitutes the largest labeled driver sleepiness dataset in the world. The model outputs a binary decision as alert (defined as ≤6 on the Karolinska Sleepiness Scale, KSS) or sleepy (KSS ≥ 8) or a regression output corresponding to KSS ϵ [1–5, 6, 7, 8, 9]. Main results. The subject-independent mean absolute error (MAE) was 0.78. Binary classification accuracy for the regression model was 82.6% as compared to 82.0% for a model that was trained specifically for the binary classification task. Data from the eyes were more informative than data from the brain. A combined input improved performance for some models, but the gain was very limited. Significance. Improved classification results were achieved with the regression model compared to the classification model. This suggests that the implicit order of the KSS ratings, i.e. the progression from alert to sleepy, provides important information for robust modelling of driver sleepiness, and that class labels should not simply be aggregated into an alert and a sleepy class. Furthermore, the model consistently showed better results than a model trained on manually extracted features based on expert knowledge, indicating that the model can detect sleepiness that is not covered by traditional algorithms.

Seeking confirmation? Biased information search and deliberation in the food domain

Individuals are often confronted with choosing between competing food attributes (e.g., healthiness vs. tastiness). To promote healthier food choices, is it important to understand what drives these choices. One potential driver of food choices is a confirmation bias, namely, a systematic bias in our approach to seeking information related to food attributes. This bias may generate avoidance of belief-disconfirming information and/or discounting of the value of belief-disconfirming arguments, both of which are documented in other domains (e.g., politics, religion). This study aimed to examine the confirmation bias in the food domain. We conducted an online study with a large sample (N = 427) stratified by sex and body mass index. Our sample, hypotheses, and analysis plan were pre-registered on the Open Science Framework. We measured pro-health and pro-taste food-related information aimed at directly testing the presence of the confirmation bias in the food domain. We also examined whether higher deliberation (indexed by higher amount of thought, lower sleepiness, and higher cognitive reflection) modulated this bias. Results showed that individuals avoided exposure to information that promoted the food attribute that they utilized less (i.e., healthiness or tastiness). Furthermore, arguments promoting less used food attributes were perceived as weaker, and this effect was enhanced for more alert individuals (i.e., less sleepy). To our knowledge, these findings provide the first evidence for a confirmation bias in the food domain and suggest that unlike other cognitive biases, higher deliberation may enhance this bias. Marketing could focus efforts on convincing consumers that healthy food is tasty, rather than convincing them to care more about health.

Sleepiness, sleep duration, and human social activity: An investigation into bidirectionality using longitudinal time-use data

Daytime sleepiness impairs cognitive ability, but recent evidence suggests it is also an important driver of human motivation and behavior. We aimed to investigate the relationship between sleepiness and a behavior strongly associated with better health: social activity. We additionally aimed to investigate whether a key driver of sleepiness, sleep duration, had a similar relationship with social activity. For these questions, we considered bidirectionality, time of day, and differences between workdays and days off. Over 3 wk, 641 working adults logged their behavior every 30 min, completed a sleepiness scale every 3 h, and filled a sleep diary every morning (rendering >292,000 activity and >70,000 sleepiness datapoints). Using generalized additive mixed-effect models, we analyzed potential nonlinear relationships between sleepiness/sleep duration and social activity. Greater sleepiness predicted a substantial decrease in the probability of social activity (odds ratio 95% CI = 0.34 to 0.35 for days off), as well as a decreased duration of such activity when it did occur. These associations appear especially robust on days off and in the evenings. Social duration moderated the typical time-of-day pattern of sleepiness, with, for example, extended evening socializing associated with lower sleepiness. Sleep duration did not robustly predict next-day social activity. However, extensive social activity (>5 h) predicted up to 30 min shorter subsequent sleep duration. These results indicate that sleepiness is a strong predictor of voluntary decreases in social contact. It is possible that bouts of sleepiness lead to social withdrawal and loneliness, both risk factors for mental and physical ill health.

Cognitive Functions Predict Trajectories of Sleepiness Over 10 Years: A Population-Based Study.

Excessive daytime sleepiness is associated with chronic disorders of aging and mortality. Because longitudinal data are limited on the development of sleep disturbances and cognitive changes in older adults, we investigated the demographic, clinical, and cognitive predictors of self-reported daytime sleepiness over a period of 10 years. We jointly modeled latent trajectories over time of sleepiness, cognitive domains, and informative attrition and then fit models to identify cognitive trajectories and baseline characteristics that predicted the trajectories of sleepiness. Three latent trajectory groups were identified: emerging sleepiness, persistent sleepiness, and consistently low daytime sleepiness accounting for attrition in all groups. Compared with low sleepiness, emerging sleepiness was significantly associated with declining attention and subjective memory complaints; persistent sleepiness was associated with lower baseline scores in all cognitive domains, declining language trajectory, and more subjective memory complaints. These findings suggest that persistent sleepiness and emerging daytime sleepiness are associated with cognitive decline and multiple morbidities, albeit more subtly in emerging daytime sleepiness. Furthermore, these data suggest that change in the cognitive domain of attention and subjective memory complaints may be early indicators of future sleep disturbance.

The Effect of Aromatherapy Application on Cognitive Functions and Daytime Sleepiness in Older Adults Living in a Nursing Home.

Changes in the aging process affect the duration and quality of sleep. Not having a quality night's sleep leads to a reduction in daytime wakefulness in older adults. We examined the effect of aromatherapy on the cognitive functions and daytime sleepiness of older adults living in a nursing home. The research was a pretest and posttest design, which was conducted without a control group. The sample included 39 elders. A rosemary-lemon oil mixture was smelled by elders in the mornings for a week. After a 1-week washout period, lavender oils were smelled in the evenings for a week. After application of the rosemary-lemon oil mixture, the mean score of participants' daytime sleepiness was lower, but that decline was not statistically meaningful (P > .050). After the same application, the mean score of the participants' cognitive functions was significantly lower (P < .001). After application of lavender oil, the scores were significantly lower (P < .001). Lower scores on the scales used indicate lower sleepiness. The results showed that the 2 applications can be used to improve cognitive functions in older adults; in addition, lavender oil has an advantage in reducing daytime sleepiness.

Heightened sleep propensity: a novel and high-risk sleep health phenotype in older adults

ObjectivesTo reveal sleep health phenotypes in older adults and examine their associations with time to 5-year all-cause and cardiovascular mortality. DesignProspective longitudinal cohorts. SettingThe Study of Osteoporotic Fractures and Outcomes of Sleep Disorders in Older Men Study. ParticipantsN = 1722 men and women aged ≥65 years matched 1:1 on sociodemographic and clinical measures. MeasurementsSelf-reported habitual sleep health characteristics (satisfaction, daytime sleepiness, timing, efficiency, and duration) measured at an initial visit and longitudinal follow-up for mortality. ResultsLatent class analysis revealed 3 sleep health phenotypes: (1) heightened sleep propensity (HSP; medium to long duration, high sleepiness, high efficiency/satisfaction; n = 322), (2) average sleep (AS; medium duration, average efficiency, high satisfaction, low sleepiness; n = 1,109), and (3) insomnia with short sleep (ISS; short to medium duration, low efficiency/satisfaction, moderate sleepiness; n = 291). Phenotype predicted time to all-cause mortality (χ2 = 9.4, P = .01), with HSP conferring greater risk than AS (hazard ratio [95% confidence interval] = 1.48 [1.15-1.92]) or ISS (1.52 [1.07-2.17]), despite ISS reporting the poorest mental and physical health. Although sex did not formally moderate the relationship between phenotype and mortality, subgroup analyses indicated that these findings were driven primarily by women. Phenotype did not predict cardiovascular mortality. ConclusionsThese analyses support the utility of examining multidimensional sleep health profiles by suggesting that the combination of long sleep, high efficiency/satisfaction, and daytime sleepiness—previously identified as independent risk factors—may be components of a single high-risk sleep phenotype, HSP. Further investigation of sex differences and the mechanisms underlying mortality risk associated with HSP is warranted.

Sleepiness among personnel in the Norwegian Air Ambulance Service

Purpose To examine the effects of shift work and extended working hours on sleepiness among pilots and Helicopter Emergency Medical Service (HEMS) crew members in the Norwegian Air Ambulance.MethodsThis field study investigated sleepiness during 3 consecutive weeks: the week before work, the work week, and the week after work. The pilots and HEMS crew members (N = 50) kept a wake diary during all 3 weeks and completed reaction time tests during the work week.ResultsThe overall sleepiness scores were low during all 3 weeks. When comparing the 3 weeks, the lowest sleepiness levels were found for the work week. There was a small difference across work days, in which subjective sleepiness scores were highest the first duty day. No change in the reaction time tests was evident during the work week. The crew members reported being most sleepy at midnight, compared to all the other timepoints over the course of a duty day. Regarding workload and total work time, having larger workload was associated with lower sleepiness scores, while having higher total work time was associated with higher sleepiness score, both compared to the medium category.ConclusionsThe findings indicate that the work schedules and setting for this distinct occupational group do not seem to negatively affect the sleepiness levels.

Prudent diet is associated with low sleepiness among short-haul truck drivers.

The lifestyle of postindustrial society has undergone major shifts characterized by changes in demographic and epidemiologic profiles, eating habits, and job structures, with irregular working hours, particularly night shifts. The investigation of dietary patterns is of great importance for the discussion and devising of effective dietary strategies for shift and night workers in general, particularly in view of the increased sleepiness reported during night work. We aimed to determine the association between dietary patterns of Brazilian truck drivers and sleepiness levels, according to work shift. A cross-sectional study of 52 drivers (25 long haul and 27 short haul) at a freight company was carried out. This study entailed application of a structured questionnaire collecting sociodemographic, lifestyle, and nutritional status data. Assessment of dietary intake using a 24-h dietary recall and an evaluation of sleepiness by the Karolinska Sleepiness Scale were performed. The principal components of the diet were analyzed by factor analysis to derive dietary patterns. A linear mixed model was then applied to determine a model for sleepiness levels of the drivers as a function of dietary pattern, time of day, and work shift. Three intake patterns were derived: traditional, prudent, and Western. Associations of time of day (F = 23.629, P < 0.01) and shift type (F = 42.218, P < 0.01) on sleepiness were found. An association between diet and sleepiness was also evident, where the prudent pattern was associated with low sleepiness among short-haul truck drivers (F = 3.865, P = 0.02). The results of the present study revealed an association between dietary patterns and short-haul driving, in which the healthy pattern produced low sleepiness during the day. The sleepiness curve of long-haul drivers appears to have a flattening pattern, probably because of irregular working times.

Daytime sleepiness affects gait auditory synchronization ability.

Sleep disturbances in modern life lead to cognitive and motor performance impairments in everyday tasks such as gait. The most common symptom of these disturbances is daytime sleepiness, which can be assessed by questionnaires such as the Epworth Sleep Scale (ESS). The ESS evaluates sleep health and daytime dysfunction. The goal of this study is to assess the influence of sleepiness on a motorauditory synchrony task, rhythmed gait. High and low sleepiness clusters were formed based on the participants ESS scores. Walking on a treadmill, two different rhythmic auditory stimulus conditions were set with a metronome: isochronous and non-isochronous. Reflective markers on both heels with seven infrared cameras were used to assess the difference between footfall and metronome beep, what is named synchronization error (SE). There was a tendency to anticipate the beep in the HS group when compared to the LS group only in the non-isochronous stimulus condition that was statistically significant. Sleep disturbances that generate daytime sleepiness may bring detrimental effects on brain areas that could be responsible for the real-time adjustment of gait and sustained attention. These impairments may be responsible for the larger synchronization error with larger relative phase of the group with high sleepiness. More studies are necessary involving other parameters of sleep and gait to identify sleep disturbances through gait analysis.

Driven to discussion: engaging drivers in conversation with a digital assistant as a countermeasure to passive task‐related fatigue

Using a Wizard-of-Oz approach, we explored the effectiveness of engaging drivers in conversation with a digital assistant as an operational strategy to combat the symptoms of passive task-related fatigue. Twenty participants undertook two 30-minute drives in a medium-fidelity driving simulator between 13:00 and 16:30, when circadian and homeostatic influences naturally reduce alertness. Participants were asked to follow a lead-car travelling at a constant speed of 68mph, in a sparsely-populated UK motorway scenario. During one of the counterbalanced drives, participants were engaged in conversation by a digital assistant (‘Vid’). Results show that interacting with Vid had a positive effect on driving performance and arousal, evidenced by better lane-keeping, earlier response to a potential hazard situation, larger pupil diameter, and an increased spread of attention to the road-scene (i.e. fewer fixations concentrated on the road-centre indicating a lower incidence of ‘cognitive tunnelling’). Drivers also reported higher levels of alertness and lower sleepiness following the Vid drive. Subjective workload ratings suggest that drivers exerted less effort to ‘stay awake’ when engaged with Vid. The findings support the development and application of in-vehicle natural language interfaces, and can be used to inform the design of novel countermeasures for driver fatigue.

P 133 Differentiating hypo- and hyperaroused fatigue in major depression and in the context of organic diseases

Introduction Fatigue is a core symptom in patients with major depressive disorder (MDD), and a common symptom in organic diseases involving inflammatory and immunological processes. From a clinical perspective, fatigue in depression is a state with high inner tension and prolonged sleep onset latencies, whereas fatigue in the context of organic diseases describes an anergic state with excessive sleepiness and short sleep latencies. Given that these two states are diametrically opposed in the arousal dimension, it has been proposed to differentiate two subtypes of fatigue ( Hegerl et al., 2013 , Hegerl and Ulke, 2016 ): hyperaroused fatigue (typical for depression) and hypoaroused fatigue (typical in the context of organic diseases). Due to the striking heterogeneity of MDD and frequent occurrence of depressive symptoms in organic diseases, we sought to examine whether both fatigue subtypes can be found within a sample of depressed patients (study 1) and within a sample of subjects with inflammatory-immunological diseases and cancer (study 2). In the first study, we hypothesized that in MDD fatigue with unstable arousal regulation is associated with higher sleepiness scores and more atypical symptoms (e.g. short sleep onset latency) than fatigue with stable arousal regulation. In the second study, we hypothesized that in the context of organic diseases fatigue with stable arousal regulation is associated with higher depression and lower sleepiness scores than fatigue with labile arousal regulation. Methods Sample Study 1: MDD-Patients with clinically relevant fatigue (N = 102). Sample Study 2: Subjects with clinically relevant fatigue in the context of inflammatory-immunological diseases and cancer (N = 127). Arousal regulation was assessed based on 20-min resting-EEG using automatic EEG-vigilance stage classification with the Vigilance Algorithm Leipzig (VIGALL 2.1). Subjects were separated into groups according to their arousal regulation. Results Study 1: According to our hypothesis, fatigue subtypes in the context of MDD differ in regard to daytime sleepiness (ESS: p Conclusions An unstable arousal regulation in MDD-Patients with clinically relevant fatigue could influence the treatment strategy. Stable arousal regulation in persons with clinically relevant fatigue in the context of organic diseases can be an indication of a comorbid depression, which has to be treated according to guidelines.