Assessment and management of sleep disorders in shift workers: Challenges and considerations for general practice.

BACKGROUND: Shift work is characterised by displaced sleep opportunities and associated sleep disturbance. Shift workers often report sleepiness and other wake time symptoms associated with poor sleep. However, clinical sleep disorders are also prevalent in shift workers. Although prevalence rates are similar or higher in shift workers compared with the general population, help seeking in shift workers with sleep disorders is low. OBJECTIVE: This article aims to provide general practitioners with a contemporary overview of the prevalence rates for sleep disorders in shift workers, to clarify the existing evidence relating to mental and physical health consequences of sleep disorders in shift workers and to highlight the need to consider undiagnosed sleep disorders before attributing sleep-related symptoms solely to work schedules. DISCUSSION: Symptoms of sleep loss associated with shift work overlap with symptoms experienced by individuals living with sleep disorders. Although >40% of middle-aged Australians live with a sleep disorder that requires investigation and management, symptoms in shift workers are often attributed to the work schedule and, as a result, might not be investigated for appropriate diagnosis and treatment. We argue that screening for sleep disorders in shift workers with sleep complaints should be a priority.

SleepSync: Early Testing of a Personalised Sleep-Wake Management Smartphone Application for Improving Sleep and Cognitive Fitness in Defence Shift Workers.

Shift work, long work hours, and operational tasks contribute to sleep and circadian disruption in defence personnel, with profound impacts on cognition. To address this, a digital technology, the SleepSync app, was designed for use in defence. A pre-post design study was undertaken to examine whether four weeks app use improved sleep and cognitive fitness (high performance neurocognition) in a cohort of shift workers from the Royal Australian Air Force. In total, 13 of approximately 20 shift-working personnel from one base volunteered for the study. Sleep outcomes were assessed using the Insomnia Severity Index (ISI), the Patient-Reported Outcomes Measurement Information System (PROMIS), Sleep Disturbance and Sleep-Related Impairment Scales, the Glasgow Sleep Effort Scale, the Sleep Hygiene Index, and mental health was assessed using the Depression, Anxiety, and Stress Scale-21. Sustained attention was measured using the 3-min Psychomotor Vigilance Task (PVT) and controlled response using the NBack. Results showed significant improvements in insomnia (ISI scores 10.31 at baseline and 7.50 after app use), sleep-related impairments (SRI T-scores 53.03 at baseline to 46.75 post-app use), and healthy sleep practices (SHI scores 21.61 at baseline to 18.83 post-app use; all p < 0.001). Trends for improvement were recorded for depression. NBack incorrect responses reduced significantly (9.36 at baseline; reduced by -3.87 at last week of app use, p < 0.001), but no other objective measures improved. These findings suggest that SleepSync may improve sleep and positively enhance cognitive fitness but warrants further investigation in large samples. Randomised control trials with other cohorts of defence personnel are needed to confirm the utility of this intervention in defence settings.

Circadian adaptation to night shift work is associated with higher REM sleep duration.

OBJECTIVE: To investigate the influence of the degree of circadian adaptation to night work on sleep architecture following night shift. METHODS: Thirty four night workers (11 females; 33.8 ± 10.1years) completed a simulated night shift following 2-7 typical night shifts. Participants completed a laboratory-based simulated night shift (21:00-07:00 hours), followed by a recovery sleep opportunity (∼09:00-17:00 hours), recorded using polysomnography. Urinary 6-sulphatoxymelatonin (aMT6s) rhythm acrophase was used as a marker of circadian phase. Sleep duration and architecture were compared between individuals with aMT6s acrophase before (unadapted group, n = 22) or after (partially adapted group, n = 12) bedtime. RESULTS: Bedtime occurred on average 2.16 hours before aMT6s acrophase in the partially adapted group and 3.91 hours after acrophase in the unadapted group. The partially adapted group had more sleep during the week before the simulated night than the unadapted group (6.47 ± 1.02 vs. 5.26 ± 1.48 hours, p = .02). After the simulated night shift, both groups had similar total sleep time (partially adapted: 6.68 ± 0.80 hours, unadapted: 6.63 ± 0.88 hours, p > .05). The partially adapted group had longer total rapid eye movement sleep duration than the unadapted group (106.79 ± 32.05 minutes vs. 77.90 ± 28.86 minutes, p = .01). After 5-hours, rapid eye movement sleep accumulation was higher in the partially adapted compared to the unadapted group (p = .02). Sleep latency and other stages were not affected by circadian adaptation. DISCUSSION: Partial circadian adaptation to night shift was associated with longer rapid eye movement sleep duration during daytime sleep, highlighting the influence of entrainment between the sleep-wake cycle and the circadian pacemaker in night workers. The findings have important implications for sleep and subsequent alertness associated with shift work.

The importance of sleep regularity: a consensus statement of the National Sleep Foundation sleep timing and variability panel.

OBJECTIVE: To develop and present consensus findings of the National Sleep Foundation sleep timing and variability panel regarding the impact of sleep timing variability on health and performance. METHODS: The National Sleep Foundation assembled a panel of sleep and circadian experts to evaluate the scientific evidence and conduct a formal consensus and voting procedure. A systematic literature review was conducted using the NIH National Library of Medicine PubMed database, and panelists voted on the appropriateness of 3 questions using a modified Delphi RAND/UCLA Appropriateness Method with 2 rounds of voting. RESULTS: The literature search and panel review identified 63 full text publications to inform consensus voting. Panelists achieved consensus on each question: (1) is daily regularity in sleep timing important for (a) health or (b) performance? and (2) when sleep is of insufficient duration during the week (or work days), is catch-up sleep on weekends (or non-work days) important for health? Based on the evidence currently available, panelists agreed to an affirmative response to all 3 questions. CONCLUSIONS: Consistency of sleep onset and offset timing is important for health, safety, and performance. Nonetheless, when insufficient sleep is obtained during the week/work days, weekend/non-work day catch-up sleep may be beneficial.

Pilot feasibility testing of biomathematical model recommendations for personalising sleep timing in shift workers.

Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation is undertested. This study tested the feasibility of implementing two biomathematical models-the Phillips-Robinson Model and the Model for Arousal Dynamics-in 28 shift-working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips-Robinson Model. For the Phillips-Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre-study, significant improvements were observed post-study for sleep disturbance (Phillips-Robinson Model), and insomnia severity and sleep-related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof-of-concept for using biomathematical models to recommend sleep in operational contexts.

Tailoring cognitive behavioural therapy for insomnia across contexts, conditions, and individuals: What do we know, where do we go?

Cognitive behavioural therapy for insomnia (CBT-I) is considered the front-line treatment for insomnia. Despite the demonstrated effectiveness of CBT-I, it is necessary to consider how CBT-I may be tailored to different individuals. The purpose of the present review is to provide a summary of literature on tailoring CBT-I to different individuals and provide directions for future research. This review focused on the following domains of adaptation: (i) tailoring CBT-I components to individuals with comorbid mental or physical health conditions such as comorbid depression and pain; (ii) adapting CBT-I delivery for different contexts in which individuals exist, such as inpatient, educational, and different social/cultural settings, (iii) adapting CBT-I to specific individuals via case-formulation in clinical settings. We highlight current gaps in the exploration of tailored CBT-I, including a lack of research methodology to evaluate tailored interventions, a need for the integration of ongoing individualised assessment to inform treatment, and the necessary involvement of consumers and stakeholders throughout the research and treatment development process. Together, this review showed abundant adaptations in CBT-I already exist in the literature. Future research is needed in understanding when and how to apply adaptations in CBT-I and evaluate the benefits of these adaptations.

European NCAP Driver State Monitoring Protocols: Prevalence of Distraction in Naturalistic Driving.

OBJECTIVE: examine the prevalence of driver distraction in naturalistic driving when implementing European New Car Assessment Program (Euro NCAP)-defined distraction behaviours. BACKGROUND: The 2023 introduction of Occupant Status monitoring (OSM) into Euro NCAP will accelerate uptake of Driver State Monitoring (DSM). Euro NCAP outlines distraction behaviours that DSM must detect to earn maximum safety points. Distraction behaviour prevalence and driver alerting and intervention frequency have yet to be examined in naturalistic driving. METHOD: Twenty healthcare workers were provided with an instrumented vehicle for approximately two weeks. Data were continuously monitored with automotive grade DSM during daily work commutes, resulting in 168.8 hours of driver head, eye and gaze tracking. RESULTS: Single long distraction events were the most prevalent, with .89 events/hour. Implementing different thresholds for driving-related and driving-unrelated glance regions impacts alerting rates. Lizard glances (primarily gaze movement) occurred more frequently than owl glances (primarily head movement). Visual time-sharing events occurred at a rate of .21 events/hour. CONCLUSION: Euro NCAP-described driver distraction occurs naturalistically. Lizard glances, requiring gaze tracking, occurred in high frequency relative to owl glances, which only require head tracking, indicating that less sophisticated DSM will miss a substantial amount of distraction events. APPLICATION: This work informs OEMs, DSM manufacturers and regulators of the expected alerting rate of Euro NCAP defined distraction behaviours. Alerting rates will vary with protocol implementation, technology capability, and HMI strategies adopted by the OEMs, in turn impacting safety outcomes, user experience and acceptance of DSM technology.

Mobile app for personalized sleep-wake management for shift workers: A user testing trial.

Objective: Development of personalized sleep-wake management tools is critical to improving sleep and functional outcomes for shift workers. The objective of the current study was to test the performance, engagement and usability of a mobile app (SleepSync) for personalized sleep-wake management in shift workers that aid behavioural change and provide practical advice by providing personalized sleep scheduling recommendations and education. Methods: Shift workers (n = 27; 20 healthcare and 7 from other industries) trialled the mobile app for two weeks to determine performance, engagement and usability. Primary outcomes were self-reported total sleep time, ability to fall asleep, sleep quality and perception of overall recovery on days off. Secondary performance outcomes included sleep disturbances (insomnia and sleep hygiene symptoms, and sleep-related impairments) and mood (anxiety, stress and depression) pre- and post-app use. Satisfaction with schedule management, integration into daily routine and influence on behaviour were used to determine engagement, while the usability was assessed for functionality and ease of use of features. Results: Total sleep time (P = .04), ability to fall asleep (P < .001), quality of sleep (P = .001), insomnia (P = .02), sleep hygiene (P = .01), sleep-related impairments (P = .001), anxiety (P = .001), and stress (P = .006) were all improved, with non-significant improvements in recovery on days off (P = .19) and depression (P = .07). All measures of engagement and usability were scored positively by the majority of users. Conclusions: This pilot trial provides preliminary evidence of the positive impact of the SleepSync app in improving sleep and mood outcomes in shift workers, and warrants confirmation in a larger controlled trial.

The impact of break duration, time of break onset, and prior shift duration on the amount of sleep between shifts in heavy vehicle drivers.

This study aimed to examine the impact of break duration between consecutive shifts, time of break onset, and prior shift duration on total sleep time (TST) between shifts in heavy vehicle drivers (HVDs), and to assess the interaction between break duration and time of break onset. The sleep (actigraphy and sleep diaries) and work shifts (work diaries) of 27 HVDs were monitored during their usual work schedule for up to 9 weeks. Differences in TST between consecutive shifts and days off were assessed. Linear mixed models (followed by pairwise comparisons) assessed whether break duration, prior shift duration, time of break onset, and the interaction between break duration and break onset were related to TST between shifts. Investigators found TST between consecutive shifts (mean [SD] 6.38 [1.38] h) was significantly less than on days off (mean [SD] 7.63 [1.93] h; p < 0.001). Breaks starting between 12:01 and 8:00 a.m. led to shorter sleep (p < 0.05) compared to breaks starting between 4:01 and 8:00 p.m. Break durations up to 7, 9, and 11 h (Australian and European minimum break durations) resulted in a mean (SD) of 4.76 (1.06), 5.66 (0.77), and 6.41 (1.06) h of sleep, respectively. The impact of shift duration prior to the break and the interaction between break duration and time of break were not significant. HVDs' sleep between workdays is influenced independently by break duration and time of break onset. This naturalistic study provides evidence that current break regulations prevent sufficient sleep duration in this industry. Work regulations should evaluate appropriate break durations and break onset times to allow longer sleep opportunities for HVDs.

The role of circadian phase in sleep and performance during Antarctic winter expeditions.

The Antarctic environment presents an extreme variation in the natural light-dark cycle which can cause variability in the alignment of the circadian pacemaker with the timing of sleep, causing sleep disruption, and impaired mood and performance. This study assessed the incidence of circadian misalignment and the consequences for sleep, cognition, and psychological health in 51 over-wintering Antarctic expeditioners (45.6 ± 11.9 years) who completed daily sleep diaries, and monthly performance tests and psychological health questionnaires for 6 months. Circadian phase was assessed via monthly 48-h urine collections to assess the 6-sulphatoxymelatonin (aMT6s) rhythm. Although the average individual sleep duration was 7.2 ± 0.8 h, there was substantial sleep deficiency with 41.4% of sleep episodes <7 h and 19.1% <6 h. Circadian phase was highly variable and 34/50 expeditioners had sleep episodes that occurred at an abnormal circadian phase (acrophase outside of the sleep episode), accounting for 18.8% (295/1565) of sleep episodes. Expeditioners slept significantly less when misaligned (6.1 ± 1.3 h), compared with when aligned (7.3 ± 1.0 h; p < .0001). Performance and mood were worse when awake closer to the aMT6s peak and with increased time awake (all p < .0005). This research highlights the high incidence of circadian misalignment in Antarctic over-wintering expeditioners. Similar incidence has been observed in long-duration space flight, reinforcing the fidelity of Antarctica as a space analog. Circadian misalignment has considerable safety implications, and potentially longer term health risks for other circadian-controlled physiological systems. This increased risk highlights the need for preventative interventions, such as proactively planned lighting solutions, to ensure circadian alignment during long-duration Antarctic and space missions.

Study protocol for the Shifting Weight using Intermittent Fasting in night shift workers (SWIFt) study: a three-arm randomised controlled trial comparing three weight loss strategies in night shift workers with obesity.

INTRODUCTION: Shift workers are at an increased risk of developing obesity and type 2 diabetes. Eating and sleeping out of synchronisation with endogenous circadian rhythms causes weight gain, hyperglycaemia and insulin resistance. Interventions that promote weight loss and reduce the metabolic consequences of eating at night are needed for night shift workers. The aim of this study is to examine the effects of three weight loss strategies on weight loss and insulin resistance (HOMA-IR) in night shift workers. METHODS AND ANALYSIS: A multisite 18-month, three-arm randomised controlled trial comparing three weight loss strategies; continuous energy restriction; and two intermittent fasting strategies whereby participants will fast for 2 days per week (5:2); either during the day (5:2D) or during the night shift (5:2N). Participants will be randomised to a weight loss strategy for 24 weeks (weight loss phase) and followed up 12 months later (maintenance phase). The primary outcomes are weight loss and a change in HOMA-IR. Secondary outcomes include changes in glucose, insulin, blood lipids, body composition, waist circumference, physical activity and quality of life. Assessments will be conducted at baseline, 24 weeks (primary endpoint) and 18 months (12-month follow-up). The intervention will be delivered by research dietitians via a combination of face-to-face and telehealth consultations. Mixed-effect models will be used to identify changes in dependent outcomes (weight and HOMA-IR) with predictor variables of outcomes of group, time and group-time interaction, following an intention-to-treat approach. ETHICS AND DISSEMINATION: The study protocol was approved by Monash Health Human Research Ethics Committee (RES 19-0000-462A) and registered with Monash University Human Research Ethics Committee. Ethical approval has also been obtained from the University of South Australia (HREC ID: 202379) and Ambulance Victoria Research Committee (R19-037). Results from this trial will be disseminated via conference presentations, peer-reviewed journals and student theses. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry (ACTRN-12619001035112).

Sleep, alertness and performance across a first and a second night shift in mining haul truck drivers.

This study examined the impact of first and second night shift work on sleep and performance in mining haul truck drivers. Sleep-wake patterns were monitored using wrist actigraphy. The Karolinska Sleepiness Scale (KSS), Psychomotor Vigilance Test (PVT) and a truck simulator were administered at the start and end of the first (N1) or second (N2) night shift (19:00-07:00 h). Participants were categorised into those who demonstrated a decline in performance (increase of one or more PVT lapses [reaction time >500 msec] from the start to the end of shift) or those who did not demonstrate a decline in performance (no increase in lapses) from the start to the end of shift. Total sleep time (TST) was longer in the 24 h prior to N1 (9.05 ± 1.49 h) compared to N2 (5.38 ± 1.32 h). PVT lapses and the slowest 10% of reaction times were similar at the start and end of N1, while greater impairments on these outcomes were observed at the end of N2 compared to the end of N1 (p < .05). In contrast, subjective sleepiness was equally impaired at the end of both night shifts. PVT performance (lapses and slowest 10% of reaction times) and drive violations demonstrated a similar direction of change on N1 and N2. Participants who demonstrated a decline in performance showed reduced TST in the 48 h prior to shifts compared to those who demonstrated no decline in performance across the shift. Likely due to short sleep prior, the end of N2 was associated with pronounced performance impairments on the PVT and drive violations compared to the start of the shift. The findings suggest that drive violations may be more sensitive to sleep loss compared to the other driving measures examined in this study. This study also emphasizes the need for adequate recovery sleep between night shifts.

The effectiveness of an individualized sleep and shift work education and coaching program to manage shift work disorder in nurses: a randomized controlled trial.

STUDY OBJECTIVES: While insomnia and sleepiness symptoms are common in shift workers, 20%-30% experience more severe symptoms and meet the criteria for shift work disorder (SWD). SWD can lead to impairments in cognitive function, physical and mental health, and reduced productivity and increased risk of workplace injury. The aim of this study was to deliver and evaluate a shift work individual management coaching program, focusing on sleep education, promoting good sleep hygiene, and providing individualized behavioral strategies to cope with shift schedules. METHODS: A clustered randomized controlled trial of sleep education and sleep disorders screening was undertaken, based on hospital wards at a tertiary hospital in Melbourne, Australia. Participants identified as high risk for SWD underwent one of two 8-week programs, a shift work individualized management program, or an active control. The primary outcome was ward-based sick leave. Secondary outcomes were SWD risk, sleep hygiene, insomnia, depression, and anxiety. A total of 149 nurses, across 16 wards (96% female, 34.66 ± 11.99 years) completed both baseline and follow-up questionnaires (23.9% were high risk SWD). RESULTS: There was no significant reduction in sick leave between intervention and control wards (mean difference = 1.2 days, P = .063). Improvements were seen in insomnia (P < .0001) and depression (intervention, P ≤ .0001, control, P = .023) in both groups, but were not significantly different between programs. Anxiety (P = .001. control P = .079) and Functional Outcomes of Sleep Questionnaire 10 (P = .001 control P = .056) improved only for the intervention. CONCLUSIONS: This SWD intervention trial did not reduce sick leave compared to the active control but there was an improvement. Improvements in sleep hygiene, insomnia, depression, and anxiety severity were seen for both groups. Future intervention trials should consider including both sleep and mental health interventions, strategies to avoid between group contamination and the duration of programs for optimal behavioral modification. CLINICAL TRIAL REGISTRATION: Registry: Australian New Zealand Clinical Trials Registry; Name: Sleep Health Management for Healthcare Workers; URL: https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12616000369426; Identifier: ACTRN12616000369426. CITATION: Booker LA, Sletten TL, Barnes M, et al. The effectiveness of an individualized sleep and shift work education and coaching program to manage shift work disorder in nurses: a randomized controlled trial. J Clin Sleep Med. 2022;18(4):1035-1045.

Prevalence of sleep disturbance and the association between poor disease control in people with ankylosing spondylitis within the Australian clinical setting (ASLEEP study): a real-world observational study using the OPAL dataset.

INTRODUCTION: Sleep disturbance and fatigue are commonly reported in ankylosing spondylitis (AS) but specific prevalence and the relationship to disease control are unknown. METHOD: This retrospective non-interventional observational study of data from the OPAL dataset included patients with AS (ICD code M45, M45.0 or M08.1), aged 18 to 95 years and had completed ≥ 1 sleep questionnaire between 1 January 2019 and 30 September 2020. The prevalence of insomnia and obstructive sleep apnoea were assessed using the Insomnia Severity Index (ISI) and Multivariate Apnoea Prediction Index (MAPI), respectively. Propensity score (PS) matching based on sex, age and symptom duration increased comparability between patients administered tumour necrosis factor inhibitors (TNFi) and interleukin 17A inhibitors (IL-17Ai). RESULTS: Four hundred ninety-five patients were included. The mean ISI total score in the overall population was 8.6 ± 6.2. Self-reported moderate or severe clinical insomnia was present in 16% and 3.2% of patients, respectively. The mean MAPI score was 0.4 ± 0.3, self-reported apnoea was identified in 31.5% of patients and the mean FACIT-Fatigue score was 36.1 ± 10.7. In the PS matched population, the only treatment-related difference was the mean MAPI score (IL-17Ai 0.4 ± 0.3 and TNFi 0.3 ± 0.2, p = 0.046). Those with poor disease control (BASDAI ≥ 4) were more likely (odds ratio [OR] 7.29, 95% CI 2.37 to 22.46, p = 0.001) to have a greater severity of insomnia symptoms than those with good disease control. CONCLUSION: In this real-world AS cohort, poor disease control was associated with sleep disturbance. Little difference in sleep disturbance was observed between biologic TNFi and IL-17Ai treatment. Key Points • Sleep disturbance and fatigue are common in patients with ankylosing spondylitis. • In our real-world cohort, self-reported apnoea was reported in one-third of patients; and one in five patients reported moderate to severe insomnia. • Those with poor disease control were more likely to experience greater sleep disturbance than those with good disease control.

Prediction of shiftworker alertness, sleep, and circadian phase using a model of arousal dynamics constrained by shift schedules and light exposure.

STUDY OBJECTIVES: The study aimed to, for the first time, (1) compare sleep, circadian phase, and alertness of intensive care unit (ICU) nurses working rotating shifts with those predicted by a model of arousal dynamics; and (2) investigate how different environmental constraints affect predictions and agreement with data. METHODS: The model was used to simulate individual sleep-wake cycles, urinary 6-sulphatoxymelatonin (aMT6s) profiles, subjective sleepiness on the Karolinska Sleepiness Scale (KSS), and performance on a Psychomotor Vigilance Task (PVT) of 21 ICU nurses working day, evening, and night shifts. Combinations of individual shift schedules, forced wake time before/after work and lighting, were used as inputs to the model. Predictions were compared to empirical data. Simulations with self-reported sleep as an input were performed for comparison. RESULTS: All input constraints produced similar prediction for KSS, with 56%-60% of KSS scores predicted within ±1 on a day and 48%-52% on a night shift. Accurate prediction of an individual's circadian phase required individualized light input. Combinations including light information predicted aMT6s acrophase within ±1 h of the study data for 65% and 35%-47% of nurses on diurnal and nocturnal schedules. Minute-by-minute sleep-wake state overlap between the model and the data was between 81 ± 6% and 87 ± 5% depending on choice of input constraint. CONCLUSIONS: The use of individualized environmental constraints in the model of arousal dynamics allowed for accurate prediction of alertness, circadian phase, and sleep for more than half of the nurses. Individual differences in physiological parameters will need to be accounted for in the future to further improve predictions.

A Blue-Enriched, Increased Intensity Light Intervention to Improve Alertness and Performance in Rotating Night Shift Workers in an Operational Setting.

PURPOSE: This study examined the efficacy of a lighting intervention that increased both light intensity and short-wavelength (blue) light content to improve alertness, performance and mood in night shift workers in a chemical plant. PATIENTS AND METHODS: During rostered night shifts, 28 workers (46.0±10.8 years; 27 male) were exposed to two light conditions each for two consecutive nights (~19:00-07:00 h) in a counterbalanced repeated measures design: traditional-spectrum lighting set at pre-study levels (43 lux, 4000 K) versus higher intensity, blue-enriched lighting (106 lux, 17,000 K), equating to a 4.5-fold increase in melanopic illuminance (24 to 108 melanopic illuminance). Participants completed the Karolinska Sleepiness Scale, subjective mood ratings, and the Psychomotor Vigilance Task (PVT) every 2-4 hours during the night shift. RESULTS: A significant main effect of time indicated KSS, PVT mean reaction time, number of PVT lapses (reaction times > 500 ms) and subjective tension, misery and depression worsened over the course of the night shift (p<0.05). Percentage changes in KSS (p<0.05, partial η2=0.14) and PVT mean reaction time (p<0.05, partial η2=0.19) and lapses (p<0.05, partial η2=0.17) in the middle and end of night shift, expressed relative to start of shift, were significantly improved during the lighting intervention compared to the traditional lighting condition. Self-reported mood did not significantly differ between conditions (p>0.05). CONCLUSION: Our findings, showing improvements in alertness and performance with exposure to blue-enriched, increased intensity light, provide support for light to be used as a countermeasure for impaired alertness in night shift work settings.

The impact of 7-hour and 11-hour rest breaks between shifts on heavy vehicle truck drivers' sleep, alertness and naturalistic driving performance.

BACKGROUND: An inadequate rest break between shifts may contribute to driver sleepiness. This study assessed whether extending the major rest break between shifts from 7-hours (Australian industry standard) to 11-hours, improved drivers' sleep, alertness and naturalistic driving performance. METHODS: 17 heavy vehicle drivers (16 male) were recruited to complete two conditions. Each condition comprised two 13-hour shifts, separated by either a 7- or 11-hour rest break. The initial 13-hour shift was the drivers' regular work. The rest break and following 13-hour shift were simulated. The simulated shift included 5-hours of naturalistic driving with measures of subjective sleepiness, physiological alertness (ocular and electroencephalogram) and performance (steering and lane departures). RESULTS: 13 drivers provided useable data. Total sleep during the rest break was greater in the 11-hour than the 7-hour condition (median hours [25th to 75th percentile] 6.59 [6.23, 7.23] vs. 5.07 [4.46, 5.38], p = 0.008). During the simulated shift subjective sleepiness was marginally better for the 11-hour condition (mean Karolinska Sleepiness Scale [95th CI] = 4.52 [3.98, 5.07] vs. 5.12 [4.56, 5.68], p = 0.009). During the drive, ocular and vehicle metrics were improved for the 11-hour condition (p<0.05). Contrary to expectations, mean lane departures p/hour were increased during the 11-hour condition (1.34 [-0.38,3.07] vs. 0.63 [-0.2,1.47], p = 0.027). CONCLUSIONS: Extending the major rest between shifts substantially increases sleep duration and has a modest positive impact on driver alertness and performance. Future work should replicate the study in a larger sample size to improve generalisability and assess the impact of consecutive 7-hour major rest breaks.

Light-based methods for predicting circadian phase in delayed sleep-wake phase disorder.

Methods for predicting circadian phase have been developed for healthy individuals. It is unknown whether these methods generalize to clinical populations, such as delayed sleep-wake phase disorder (DSWPD), where circadian timing is associated with functional outcomes. This study evaluated two methods for predicting dim light melatonin onset (DLMO) in 154 DSWPD patients using ~ 7 days of sleep-wake and light data: a dynamic model and a statistical model. The dynamic model has been validated in healthy individuals under both laboratory and field conditions. The statistical model was developed for this dataset and used a multiple linear regression of light exposure during phase delay/advance portions of the phase response curve, as well as sleep timing and demographic variables. Both models performed comparably well in predicting DLMO. The dynamic model predicted DLMO with root mean square error of 68 min, with predictions accurate to within ± 1 h in 58% of participants and ± 2 h in 95%. The statistical model predicted DLMO with root mean square error of 57 min, with predictions accurate to within ± 1 h in 75% of participants and ± 2 h in 96%. We conclude that circadian phase prediction from light data is a viable technique for improving screening, diagnosis, and treatment of DSWPD.