Fatigue risk management for cabin crew: the importance of company support and sufficient rest for work-life balance-a qualitative study.

Knowledge about cabin crew fatigue associated with ultra-long range (ULR) flights is still limited. Current ULR scheduling for cabin crew is therefore predominantly based on flight crew data. Cabin crews' views on fatigue, and their strategies for mitigating it, have seldom been sought. To better understand the causes and consequences of cabin crew fatigue, semi-structured focus group discussions were held. Thematic analysis was undertaken with data from 25 cabin crew. Participants indicated that the consequences of fatigue are twofold, affecting 1) cabin crew health and wellbeing and 2) safety (cabin, passenger and personal) and cabin service. While the primary causes of fatigue were sleep loss and circadian disruption, participants also identified other key factors including: insufficient rest, high workload, the work environment, a lack of company support, and insufficient fatigue management training. They highlighted the importance of sufficient rest, not only for obtaining adequate recovery sleep but also for achieving a work-life balance. They also highlighted the need for company support, effective communication, and management's engagement with cabin crew in general. We recommend that priority is given to fatigue management training for cabin crew, which may also enhance perceived company support and assist with achieving a better work-life balance.

Shared responsibility for managing fatigue: Hearing the pilots.

In commercial aviation, fatigue is defined as a physiological state of reduced mental or physical performance capability resulting from sleep loss, extended wakefulness, circadian phase, and/or workload. The International Civil Aviation Organisation mandates that responsibility for fatigue risk management is shared between airline management, pilots, and support staff. However, to date, the majority of research relating to fatigue mitigations in long range operations has focused on the mitigations required or recommended by regulators and operators. Little research attention has been paid to the views or operational experience of the pilots who use these (or other) mitigations. This study focused on pilots' views and experiences of in-flight sleep as the primary fatigue mitigation on long range flights. It also sought information about other fatigue mitigation strategies they use. Thematic analysis was used to explore written comments from diary and survey data collected during long range and ultra-long range trips (N = 291 pilots on three different aircraft types, 17 different out-and-back trips, and four airlines based on three continents). The findings indicate that the recommended fatigue mitigation strategies on long-haul flights (particularly in-flight sleep) are effective and well-utilised, consistent with quantitative findings from the same trips. Importantly however, the analyses also highlight areas that require further investigation, including flight preparation strategies in relation to the uncertainty of in-flight break allocation. There were two strategies for sleep prior to a flight: maximising sleep if pilots were expecting later breaks in the flight; or minimising sleep if they were expecting breaks earlier or at unfavourable times in the circadian cycle. They also provide a broader view of the factors that affect the amount and quality of pilots' in-flight sleep, about which evidence has previously been largely anecdotal. The study underscores the value of including the views and experience of pilots in fatigue risk management.

Equivalence Testing as a Tool for Fatigue Risk Management in Aviation.

BACKGROUND: Many civilian aviation regulators favor evidence-based strategies that go beyond hours-of-service approaches for managing fatigue risk. Several countries now allow operations to be flown outside of flight and duty hour limitations, provided airlines demonstrate an alternative method of compliance that yields safety levels "at least equivalent to" the prescriptive regulations. Here we discuss equivalence testing in occupational fatigue risk management. We present suggested ratios/margins of practical equivalence when comparing operations inside and outside of prescriptive regulations for two common aviation safety performance indicators: total in-flight sleep duration and psychomotor vigilance task reaction speed. Suggested levels of practical equivalence, based on expertise coupled with evidence from field and laboratory studies, are ≤ 30 min in-flight sleep and ± 15% of reference response speed. METHODS: Equivalence testing is illustrated in analyses of a within-subjects field study during an out-and-back long-range trip. During both sectors of their trip, 41 pilots were monitored via actigraphy, sleep diary, and top of descent psychomotor vigilance task. Pilots were assigned to take rest breaks in a standard lie-flat bunk on one sector and in a bunk tapered 9 from hip to foot on the other sector. RESULTS: Total in-flight sleep duration (134 ± 53 vs. 135 ± 55 min) and mean reaction speed at top of descent (3.94 ± 0.58 vs. 3.77 ± 0.58) were equivalent after rest in the full vs. tapered bunk. DISCUSSION: Equivalence testing is a complimentary statistical approach to difference testing when comparing levels of fatigue and performance in occupational settings and can be applied in transportation policy decision making.Wu LJ, Gander PH, van den Berg M, Signal TL. Equivalence testing as a tool for fatigue risk management in aviation. Aerosp Med Hum Perform. 2018; 89(4):383-388.

Sleep on Long Haul Layovers and Pilot Fatigue at the Start of the Next Duty Period.

INTRODUCTION: Layovers are critical for pilot recovery between flights and minimum layover durations are required by regulation. However, research on the factors affecting layover sleep and safety performance indicators (SPIs) before subsequent flights is relatively sparse. The present project combined data from 6 studies, including 8 long-range and 5 ultra-long range out-and-back trips across a range of different layover destinations (299 pilots in 4-person crews, 410 layovers, 1-3 d layover duration). METHODS: Sleep was monitored via actigraphy from 3 d pre-trip to at least 3 d post-trip. Pilots rated their sleepiness (Karolinska Sleepiness Scale, KSS) and fatigue (Samn-Perelli scale, SP) at duty start for the inbound flight. Mixed model ANOVAs identified independent associations between fatigue and sleepiness SPIs and operational factors (domicile time of duty start for the inbound flight in six 4-h bins, layover duration, and total sleep time (TST) in the 24 h prior to inbound duty start). RESULTS: TST was greatest on layovers ending between 1200-1559 domicile time (time in the city from which the outbound flight departed) and TST was a significant predictor of both KSS and SP ratings at duty start for the inbound flight. DISCUSSION: TST in the 24 h prior to the inbound flight was greatest when duty start time allowed for the inclusion of a full domicile night time period. In this dataset, circadian end-time of layovers is a key determinant of pilot fatigue status at the beginning of the inbound duty period.Cosgrove J, Wu LJ, van den Berg M, Signal TL, Gander PH. Sleep on long haul layovers and pilot fatigue at the start of the next duty period. Aerosp Med Hum Perform. 2018; 89(1):19-25.

New Zealanders working non-standard hours also have greater exposure to other workplace hazards.

Exposure to workplace hazards, such as dust, solvents, and fumes, has the potential to adversely affect the health of people. However, the effects of workplace hazards on health may differ when exposure occurs at different times in the circadian cycle, and among people who work longer hours or who do not obtain adequate sleep. The aim of the present study was to document exposures to workplace hazards across a national sample of New Zealanders, comparing people who work a standard 08:00 -17:00 h Monday-to-Friday working week (Std hours) and those who do not (N-Std hours). New Zealanders (n = 10 000) aged 20-64 yrs were randomly selected from the Electoral Roll to take part in a nationwide survey of workplace exposures. Telephone interviews were conducted between 2004 and 2006, using a six-part questionnaire addressing demographics, detailed information on the current or most recent job (including exposures to a range of workplace hazards), sleep, sleepiness, and health status. N-Std hours were categorised on the basis of: being required to start work prior to 07:00 h or finish work after 21:00 h and/or; having a regular on-call commitment (at least once per week) and/or; working rotating shifts and/or; working night shift(s) in the last month. The response rate was 37% (n = 3003), with 22.2% of participants (n = 656) categorised as working N-Std hours. Industry sectors with the highest numbers of participants working N-Std hours were manufacturing, health and community services, and agriculture, fishing, and forestry. Response rate was 37% (n = 3003) with 22.2% (n = 656) categorised as working N-Std hours. Participants working N-Std hours were more likely to be exposed to all identified hazards, including multiple hazards (OR = 2.45, 95% CI = 2.01-3.0) compared to those working Std hours. Participants working N-Std hours were also more likely to report 'never/rarely' getting enough sleep (OR = 1.38, 95% CI = 1.15-1.65), 'never/rarely' waking refreshed (OR = 1.23, 95% CI = 1.04-1.47), and excessive sleepiness (OR = 1.77, 95% CI = 1.29-2.42). New Zealanders working N-Std hours are more likely to be exposed to hazards in the workplace, to be exposed to multiple hazards, and to report inadequate sleep and excessive sleepiness than their colleagues working a standard 08:00-17:00 h Monday-to-Friday working week. More research is needed on the effects of exposure to hazardous substances outside the usual waking day, on the effects of exposure to multiple hazards, and on the combination of hazard exposure and sleep restriction as a result of shift work.

Non-pharmacological interventions for managing dementia-related sleep problems within community dwelling pairs: A mixed-method approach.

Dementia-related sleep problems can be complex and challenging. Environmental interventions which resynchronise the sleep/wake cycle have been trialled with promising results for people with dementia in institutionalised settings. However, there is less research concerning community-dwelling people with dementia and their family carers. This study involved a five-week feasibility study including timed light therapy, exercise and sleep education. Sleep and physical and mental functioning were measured at the beginning and end of the trial using objective measures, standardised questionnaires and structured participant feedback. Of 15 community-dwelling pairs who participated, nine completed the trial. The case studies presented here reveal that it is feasible for this population to use non-pharmacological interventions, with positive outcomes. However, there are also issues that can mask benefits or prevent compliance. The options for treating dementia are limited. Environmental interventions may help manage dementia-related sleep problems and further trials would be worthwhile to improve compliance and evaluate effectiveness.

Subjective Measurements of In-Flight Sleep, Circadian Variation, and Their Relationship with Fatigue.

BACKGROUND: This study examined whether subjective measurements of in-flight sleep could be a reliable alternative to actigraphic measurements for monitoring pilot fatigue in a large-scale survey. METHODS: Pilots (3-pilot crews) completed a 1-page survey on outbound and inbound long-haul flights crossing 1-7 time zones (N = 586 surveys) between 53 city pairs with 1-d layovers. Across each flight, pilots documented flight start and end times, break times, and in-flight sleep duration and quality if they attempted sleep. They also rated their fatigue (Samn-Perelli Crew Status Check) and sleepiness (Karolinska Sleepiness Scale) at top of descent (TOD). Mixed model ANCOVA was used to identify independent factors associated with sleep duration, quality, and TOD measures. Domicile time was used as a surrogate measure of circadian phase. RESULTS: Sleep duration increased by 10.2 min for every 1-h increase in flight duration. Sleep duration and quality varied by break start time, with significantly more sleep obtained during breaks starting between (domicile) 22:00-01:59 and 02:00-05:59 compared to earlier breaks. Pilots were more fatigued and sleepy at TOD on flights arriving between 02:00-05:59 and 06:00-09:59 domicile time compared to other flights. With every 1-h increase in sleep duration, sleepiness ratings at TOD decreased by 0.6 points and fatigue ratings decreased by 0.4 points. DISCUSSION: The present findings are consistent with previous actigraphic studies, suggesting that self-reported sleep duration is a reliable alternative to actigraphic sleep in this type of study, with use of validated measures, sufficiently large sample sizes, and where fatigue risk is expected to be low. van den Berg MJ, Wu LJ, Gander PH. Subjective measurements of in-flight sleep, circadian variation, and their relationship with fatigue. Aerosp Med Hum Perform. 2016; 87(10):869-875.

Differences in circadian phase and weekday/weekend sleep patterns in a sample of middle-aged morning types and evening types.

Factors contributing to sleep timing and sleep restriction in daily life include chronotype and less flexibility in times available for sleep on scheduled days versus free days. There is some evidence that these two factors interact, with morning types and evening types reporting similar sleep need, but evening types being more likely to accumulate a sleep debt during the week and to have greater sleep extension on weekend nights. The aim of the present study was to evaluate the independent contributions of circadian phase and weekend-to-weekday variability to sleep timing in daily life. The study included 14 morning types and 14 evening types recruited from a community-based sample of New Zealand adults (mean age 41.1 ± 4.7 years). On days 1-15, the participants followed their usual routines in their own homes and daily sleep start, midpoint and end times were determined by actigraphy and sleep diaries. Days 16-17 involved a 17 h modified constant routine protocol in the laboratory (17:00 to 10:00, <20 lux) with half-hourly saliva samples assayed for melatonin. Mixed model ANCOVAs for repeated measures were used to investigate the independent relationships between sleep start and end times (separate models) and age (30-39 years versus 40-49 years), circadian phase [time of the dim light melatonin onset (DLMO)] and weekday/weekend schedules (Sunday-Thursday nights versus Friday-Saturday nights). As expected on weekdays, evening types had later sleep start times (mean = 23:47 versus 22:37, p < .0001) and end times (mean = 07:14 versus 05:56, p < .0001) than morning types. Similarly on weekend days, evening types had later sleep start times (mean = 00:14 versus 23:07, p = .0032) and end times (mean = 08:56 versus 07:04, p < .0001) than morning types. Evening types also had later DLMO (22:06 versus 20:46, p = .0002) than morning types (mean difference = 80.4 min, SE = 18.6 min). The ANCOVA models found that later sleep start times were associated with later DLMO (p = .0172) and weekend-to-weekday sleep timing variability (p < .0001), after controlling for age, while later sleep end times were associated with later DLMO (p = .0038), younger age (p = .0190) and weekend days (p < .0001). Sleep end times showed stronger association with DLMO (for every 30 min delay in DLMO, estimated mean sleep end time occurred 14.0 min later versus 10.19 min later for sleep start times). Sleep end times also showed greater delays on weekends versus weekdays (estimated mean delay for sleep end time = 84 min, for sleep start time = 28 min). Comparing morning types and evening types, the estimated contributions of the DLMO to the mean observed differences in sleep timing were on weekdays, 39% for sleep start times and 49% for sleep end times; and on weekends, 41% for sleep start times and 34% of sleep end times. We conclude that differences in sleep timing between morning types and evening types were much greater than would be predicted on the basis of the independent contribution of the difference in DLMO on both weekdays and weekend days. The timing of sleep in daily life involves complex interactions between physiological and psychosocial factors, which may be moderated by age in adults aged 30-49 years.

Explaining ethnic inequities in sleep duration: a cross-sectional survey of Maori and non-Maori adults in New Zealand.

OBJECTIVES: The aims were: (1) to investigate the independent associations between suboptimal sleep duration and neighborhood deprivation, employment status, self-rated general health, overweight/obesity, and preferred sleep timing (chronotype); and (2) to determine the statistical contribution of socioeconomic, health, and chronotype factors to ethnic inequities in suboptimal sleep duration. PARTICIPANTS: Mail-out survey to a stratified national sample of 5100 Maori (indigenous New Zealanders) and 4000 non-Maori adults (20-59 years) randomly selected from the electoral rolls (54% response rate). MEASUREMENTS: Data on usual sleep duration were obtained using a NZ version of the Munich Chronotype Questionnaire. A range of sociodemographic and health-related variables were also available. RESULTS: The prevalence of insufficient (≥2 hours difference in average sleep duration on free days versus scheduled days), short (<7 hours) and long sleep durations (≥9 hours) were consistently higher for Maori than non-Maori. For insufficient sleep, the inequity was partly explained by greater socioeconomic deprivation and more night work among Maori, and further attenuated after adjustment for health-related factors and chronotype. In contrast, ethnic inequities in short and long sleep durations remained, even in the fully adjusted models. CONCLUSIONS: Ethnic inequities in insufficient and suboptimal sleep duration narrowed but were not fully explained by differences in socioeconomic position and health status between Maori and non-Maori. Growing evidence suggests that poor sleep may mediate ethnic inequities in other areas of health, therefore, actions that target the basic causes of sleep health inequities should be considered as part of broader population health policies and interventions.

Estimating long-haul airline pilots' at-home baseline sleep duration.

OBJECTIVE: Characterize the baseline sleep of long-haul airline pilots. METHODS: Sleep of 332 pilots (median age = 51 years, range = 23-64 years) from 4 airlines was measured by actigraphy while at home and off-duty and by retrospective estimate of the total amount of nighttime sleep usually obtained at home. RESULTS: Mean actigraphic sleep per 24 hours during baseline periods was 6.8 hours (SD = 1.0 hour), 52 minutes shorter than mean self-reported usual nighttime sleep (7.6 hours, SD = 1.1 hours). CONCLUSIONS: Pilots' self-reported sleep duration was comparable to weekend sleep of men in general population samples, but their actigraphic baseline sleep was longer than objectively monitored sleep of other samples. Long-haul pilots routinely experience sleep restriction and circadian disruption across trips, both of which are implicated in increased health risks. We recommend that they be educated about the long-term importance for health of obtaining adequate sleep on off-duty days.

Monitoring and Managing Cabin Crew Sleep and Fatigue During an Ultra-Long Range Trip.

BACKGROUND: The aims of this study were to monitor cabin crew fatigue, sleep, and performance on an ultra-long range (ULR) trip and to evaluate the appropriateness of applying data collection methods developed for flight crew to cabin crew operations under a fatigue risk management system (FRMS). METHODS: Prior to, throughout, and following the ULR trip (outbound flight ULR; mean layover duration=52.6 h; inbound flight long range), 55 cabin crew (29 women; mean age 36.5 yr; 25 men; mean age 36.6 yr; one missing data) completed a sleep/duty diary and wore an actigraph. Across each flight, crewmembers rated their fatigue (Samn-Perelli Crew Status Check) and sleepiness (Karolinska Sleepiness Scale) and completed a 5-min Psychomotor Vigilance Task (PVT) at key times. RESULTS: Of crewmembers approached, 73% (N=134) agreed to participate and 41% (N=55) provided data of suitable quality for analysis. In the 24 h before departure, sleep averaged 7.0 h and 40% took a preflight nap. All crewmembers slept in flight (mean total sleep time=3.6 h outbound, 2.9 h inbound). Sleepiness and fatigue were lower, and performance better, on the longer outbound flight than on the inbound flight. Post-trip, crewmembers slept more on day 1 (mean=7.9 h) compared to baseline days, but there was no difference from day 2 onwards. DISCUSSION: The present study demonstrates that cabin crew fatigue can be managed effectively on a ULR flight and that FRMS data collection is feasible for cabin crew, but operational differences between cabin crew and flight crew need to be considered.

Effects of sleep/wake history and circadian phase on proposed pilot fatigue safety performance indicators.

The Karolinska Sleepiness Scale and Samn-Perelli fatigue ratings, and psychomotor vigilance task performance are proposed as measures for monitoring commercial pilot fatigue. In laboratory studies, they are sensitive to sleep/wake history and circadian phase. The present analyses examined whether they reliably reflect sleep/wake history and circadian phase during transmeridian flight operations. Data were combined from four studies (237 pilots, 730 out-and-back flights between 13 city pairs, 1-3-day layovers). Sleep was monitored (wrist actigraphy, logbooks) before, during and after trips. On duty days, sleepiness, fatigue and mean response speed were measured pre-flight and at the top of the descent. Mixed-model analysis of variance examined associations between these measures and sleep/wake history, after controlling for operational factors. Circadian phase was approximated by local (domicile) time in the city where each trip began and ended. More sleep in the 24 h prior to duty was associated with lower pre-flight sleepiness and fatigue and faster response speed. Sleepiness and fatigue were greater before flights departing during the domicile night and early morning. At the top of the descent, pilots felt less sleepy and fatigued after more in-flight sleep and less time awake. Flights arriving in the early-mid-morning (domicile time) had greater sleepiness and fatigue and slower response speeds than flights arriving later. Subjective ratings showed expected associations with sleep/wake history and circadian phase. The response speed showed expected circadian variation but was not associated with sleep/wake history at the top of the descent. This may reflect moderate levels of fatigue at this time and/or atypically fast responses among pilots.

Mitigating and monitoring flight crew fatigue on a westward ultra-long-range flight.

BACKGROUND: This study examined the uptake and effectiveness of fatigue mitigation guidance material including sleep recommendations for a trip with a westward ultra-long-range flight and return long-range flight. METHODS: There were 52 flight crew (4-pilot crews, mean age 55 yr) who completed a sleep/duty diary and wore an actigraph prior to, during, and after the trip. Primary crew flew the takeoff and landing, while relief crew flew the aircraft during the Primary crew's breaks. At key times in flight, crewmembers rated their fatigue (Samn-Perelli fatigue scale) and sleepiness (Karolinska Sleepiness Scale) and completed a 5-min Psychomotor Vigilance Task. RESULTS: Napping was common prior to the outbound flight (54%) and did not affect the quantity or quality of in-flight sleep (mean 4.3 h). Primary crew obtained a similar amount on the inbound flight (mean 4.0 h), but Secondary crew had less sleep (mean 2.9 h). Subjective fatigue and sleepiness increased and performance slowed across flights. Performance was faster on the outbound than inbound flight. On both flights, Primary crew were less fatigued and sleepy than Secondary crew, particularly at top of descent and after landing. Crewmembers slept more frequently and had more sleep in the first 24 h of the layover than the last, and had shifted their main sleep to the local night by the second night. DISCUSSION: The suggested sleep mitigations were employed by the majority of crewmembers. Fatigue levels were no worse on the outbound ultra-long-range flight than on the return long-range flight.

Pilot fatigue: relationships with departure and arrival times, flight duration, and direction.

INTRODUCTION: Flight timing is expected to influence pilot fatigue because it determines the part of the circadian body clock cycle that is traversed during a flight. However the effects of flight timing are not well-characterized because field studies typically focus on specific flights with a limited range of departure times and have small sample sizes. The present project combined data from four studies, including 13 long-range and ultra-long range out-and-back trips across a range of departure and arrival times (237 pilots in 4-person crews, 730 flight segments, 1-3 d layovers). METHODS: All studies had tripartite support and underwent independent ethical review. Sleep was monitored (actigraphy) from 3 d prior to ≥ 3 d post-trip. Preflight and at top of descent (TOD), pilots rated their sleepiness (Karolinska Sleepiness Scale) and fatigue (Samn-Perelli scale), and completed a psychomotor vigilance task (PVT) test. Mixed model ANOVA identified independent associations between fatigue measures and operational factors (domicile times of departure and arrival, flight duration and direction, landing versus relief crew). RESULTS: Preflight subjective fatigue and sleepiness were lowest for flights departing 14:00-17:59. Total in-flight sleep was longest on flights departing 18:00-01:59. At TOD, fatigue and sleepiness were higher and PVT response speeds were slower on flights arriving 06:00-09:59 than on flights arriving later. PVT response speed at TOD was also faster on longer flights. DISCUSSION: The findings indicate the influence of flight timing (interacting with the circadian body clock cycle), as well as flight duration, on in-flight sleep and fatigue measures at TOD.

Crew fatigue safety performance indicators for fatigue risk management systems.

INTRODUCTION: Implementation of Fatigue Risk Management Systems (FRMS) is gaining momentum; however, agreed safety performance indicators (SPIs) are lacking. This paper proposes an initial set of SPIs based on measures of crewmember sleep, performance, and subjective fatigue and sleepiness, together with methods for interpreting them. METHODS: Data were included from 133 landing crewmembers on 2 long-range and 3 ultra-long-range trips (4-person crews, 3 airlines, 220 flights). Studies had airline, labor, and regulatory support, and underwent independent ethical review. SPIs evaluated preflight and at top of descent (TOD) were: total sleep in the prior 24 h and time awake at duty start and at TOD (actigraphy); subjective sleepiness (Karolinska Sleepiness Scale) and fatigue (Samn-Perelli scale); and psychomotor vigilance task (PVT) performance. Kruskal-Wallis nonparametric ANOVA with post hoc tests was used to identify significant differences between flights for each SPI. RESULTS: Visual and preliminary quantitative comparisons of SPIs between flights were made using box plots and bar graphs. Statistical analyses identified significant differences between flights across a range of SPls. DISCUSSION: In an FRMS, crew fatigue SPIs are envisaged as a decision aid alongside operational SPIs, which need to reflect the relevant causes of fatigue in different operations. We advocate comparing multiple SPIs between flights rather than defining safe/unsafe thresholds on individual SPIs. More comprehensive data sets are needed to identify the operational and biological factors contributing to the differences between flights reported here. Global sharing of an agreed core set of SPIs would greatly facilitate implementation and improvement of FRMS.

Identifying advanced and delayed sleep phase disorders in the general population: a national survey of New Zealand adults.

The aim was to estimate the prevalence of, and identify independent risk factors for, Advanced (ASPD) and Delayed Sleep Phase Disorder (DSPD) among Maori (indigenous New Zealanders) and non-Maori adults using a self-report questionnaire. The Munich Chronotype Questionnaire was mailed to a stratified sample of 9100 adults (5100 Maori and 4000 non-Maori) aged 20-59 years randomly selected from the electoral rolls (54% response rate). Different definitions for ASPD and DSPD were developed using combinations of symptoms including self-reported bed and rising times, current chronotype, and a desire to change sleep schedule. Logistic regression models were used to model the likelihood of reporting ASPD or DSPD separately after adjusting for ethnicity (Maori versus non-Maori), sex (males versus females), age (in decades), socio-economic deprivation (NZDep2006 deciles) and employment status (unemployed, night work versus employed with no night work). The prevalence of ASPD ranged from 0.25% to 7.13% whereas the prevalence of DSPD was 1.51 to 8.90% depending on the definition used. The prevalence of ASPD was higher among men and increased with age. The prevalence of DSPD was higher among those living in more deprived areas and decreased with age. After controlling for ethnicity, gender, age, socio-economic deprivation and employment status, people with ASPD were more likely to report excessive daytime sleepiness, whereas those with DSPD were more likely to report poor or fair self-rated health. Reporting ASPD and DSPD were associated with self-reported night work. In this large sleep timing survey, we found no differences in the prevalence of self-identified ASPD and DSPD between Maori and non-Maori. This has implications for the development and provision of sleep health services and strategies for managing the significant impact of work patterns on sleep.

Understanding the sleep problems of people with dementia and their family caregivers.

Sleep disturbances are common with dementia and can adversely affect waking function. However, the perspectives of people with dementia and their family caregivers concerning their sleep are under-researched. We conducted three focus groups with 12 community-dwelling pairs (a person with dementia and their family caregiver). Discussions addressed sleep disturbances, coping strategies, and beliefs and attitudes surrounding sleep. Thematic analysis indicated that dementia-related sleep disturbances were common, including confused awakenings and dementia-related behaviors at night, changes to sleep timing, and nightmares. Common issues for caregivers included being woken at night, having problems getting back to sleep, trips to the bathroom, and daytime sleepiness. Participants often normalized their sleeping problems and had developed a number of coping strategies. These findings highlight the impact that sleep disturbances can have on people living with dementia. Their experiences and beliefs need to be considered for developing effective interventions to improve sleep, waking function, and wellbeing.

In-flight sleep, pilot fatigue and Psychomotor Vigilance Task performance on ultra-long range versus long range flights.

This study evaluated whether pilot fatigue was greater on ultra-long range (ULR) trips (flights >16 h on 10% of trips in a 90-day period) than on long range (LR) trips. The within-subjects design controlled for crew complement, pattern of in-flight breaks, flight direction and departure time. Thirty male Captains (mean age = 54.5 years) and 40 male First officers (mean age = 48.0 years) were monitored on commercial passenger flights (Boeing 777 aircraft). Sleep was monitored (actigraphy, duty/sleep diaries) from 3 days before the first study trip to 3 days after the second study trip. Karolinska Sleepiness Scale, Samn-Perelli fatigue ratings and a 5-min Psychomotor Vigilance Task were completed before, during and after every flight. Total sleep in the 24 h before outbound flights and before inbound flights after 2-day layovers was comparable for ULR and LR flights. All pilots slept on all flights. For each additional hour of flight time, they obtained an estimated additional 12.3 min of sleep. Estimated mean total sleep was longer on ULR flights (3 h 53 min) than LR flights (3 h 15 min; P(F) = 0.0004). Sleepiness ratings were lower and mean reaction speed was faster at the end of ULR flights. Findings suggest that additional in-flight sleep mitigated fatigue effectively on longer flights. Further research is needed to clarify the contributions to fatigue of in-flight sleep versus time awake at top of descent. The study design was limited to eastward outbound flights with two Captains and two First Officers. Caution must be exercised when extrapolating to different operations.

In-flight sleep of flight crew during a 7-hour rest break: implications for research and flight safety.

STUDY OBJECTIVES: To assess the amount and quality of sleep that flight crew are able to obtain during flight, and identify factors that influence the sleep obtained. DESIGN: Flight crew operating flights between Everett, WA, USA and Asia had their sleep recorded polysomnographically for 1 night in a layover hotel and during a 7-h in-flight rest opportunity on flights averaging 15.7 h. SETTING: Layover hotel and in-flight crew rest facilities onboard the Boeing 777-200ER aircraft. PARTICIPANTS: Twenty-one male flight crew (11 Captains, mean age 48 yr and 10 First Officers, mean age 35 yr). INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Sleep was recorded using actigraphy during the entire tour of duty, and polysomnographically in a layover hotel and during the flight. Mixed model analysis of covariance was used to determine the factors affecting in-flight sleep. In-flight sleep was less efficient (70% vs. 88%), with more nonrapid eye movement Stage 1/Stage 2 and more frequent awakenings per h (7.7/h vs. 4.6/h) than sleep in the layover hotel. In-flight sleep included very little slow wave sleep (median 0.5%). Less time was spent trying to sleep and less sleep was obtained when sleep opportunities occurred during the first half of the flight. Multivariate analyses suggest age is the most consistent factor affecting in-flight sleep duration and quality. CONCLUSIONS: This study confirms that even during long sleep opportunities, in-flight sleep is of poorer quality than sleep on the ground. With longer flight times, the quality and recuperative value of in-flight sleep is increasingly important for flight safety. Because the age limit for flight crew is being challenged, the consequences of age adversely affecting sleep quantity and quality need to be evaluated.

Post-sleep inertia performance benefits of longer naps in simulated nightwork and extended operations.

Operational settings involving shiftwork or extended operations require periods of prolonged wakefulness, which in conjunction with sleep loss and circadian factors, can have a negative impact on performance, alertness, and workplace safety. Napping has been shown to improve performance and alertness after periods of prolonged wakefulness and sleep loss. Longer naps may not only result in longer-lasting benefits but also increase the risk of sleep inertia immediately upon waking. The time course of performance after naps of differing durations is thus an important consideration in weighing the benefits and risks of napping in workplace settings. The objective of this study was to evaluate the effectiveness of nap opportunities of 20, 40, or 60 min for maintaining alertness and performance 1.5-6 h post-nap in simulated nightwork (P1) or extended operations (P2). Each protocol included 12 participants in a within-subjects design in a controlled laboratory environment. After a baseline 8 h time-in-bed, healthy young males (P1 mean age 25.1 yr; P2 mean age 23.2 yr) underwent either ≈ 20 h (P1) or ≈ 30 h (P2) of sleep deprivation on four separate occasions, followed by nap opportunities of 0, 20, 40, and 60 min. Sleep on the baseline night and during the naps was recorded polysomnographically. During the nap opportunities, sleep onset latency was short and sleep efficiency was high. A greater proportion of slow-wave sleep (SWS) was obtained in nap opportunities of 40 and 60 min compared with 20 min. Rapid eye movement (REM) sleep occurred infrequently. A subjective sleepiness rating (Karolinska Sleepiness Scale, KSS), 2-Back Working Memory Task (WMT), and Psychomotor Vigilance Task (PVT) were completed 1.5, 2, 2.5, 3, 4, 5, and 6 h post-nap. The slowest 10% of PVT responses were significantly faster after 40 and 60 min naps compared with a 20 min (P1) or no (P2) nap. There were significantly fewer PVT lapses after 40 and 60 min naps compared with no nap (P2), and after 60 min naps compared with 20 min naps (P1). Participants felt significantly less sleepy and made more correct responses and fewer omissions on the WMT after 60 min naps compared with no nap (P2). Subjective sleepiness and WMT performance were not related to the amount of nap-time spent in SWS. However, PVT response speed was significantly slower when time in SWS was <10 min compared with 20-29.9 min. In conclusion, in operationally relevant scenarios, nap opportunities of 40 and 60 min show more prolonged benefits 1.5-6 h post-nap, than a 20 min or no nap opportunity. Benefits were more apparent when the homeostatic pressure for sleep was high and post-nap performance testing occurred across the afternoon (P2). For sustained improvement in cognitive performance, naps of 40-60 min are recommended.