Longitudinal change in sleep and daytime sleepiness in postpartum women

Sleep disruption strongly influences daytime functioning; resultant sleepiness is recognised as a contributing risk-factor for individuals performing critical and dangerous tasks. While the relationship between sleep and sleepiness has been heavily investigated in the vulnerable sub-populations of shift workers and patients with sleep disorders, postpartum women have been comparatively overlooked. Thirty-three healthy, postpartum women recorded every episode of sleep and wake each day during postpartum weeks 6, 12 and 18. Although repeated measures analysis revealed there was no significant difference in the amount of nocturnal sleep and frequency of night-time wakings, there was a significant reduction in sleep disruption, due to fewer minutes of wake after sleep onset. Subjective sleepiness was measured each day using the Karolinska Sleepiness Scale; at the two earlier time points this was significantly correlated with sleep quality but not to sleep quantity. Epworth Sleepiness Scores significantly reduced over time; however, during week 18 over 50% of participants were still experiencing excessive daytime sleepiness (Epworth Sleepiness Score ≥12). Results have implications for health care providers and policy makers. Health care providers designing interventions to address sleepiness in new mothers should take into account the dynamic changes to sleep and sleepiness during this initial postpartum period. Policy makers developing regulations for parental leave entitlements should take into consideration the high prevalence of excessive daytime sleepiness experienced by new mothers, ensuring enough opportunity for daytime sleepiness to diminish to a manageable level prior to reengagement in the workforce.

Cancer-related symptom clusters for symptom management in outpatients after commencing adjuvant chemotherapy, at 6 months, and 12 months

Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.

Can a community pharmacy sleep assessment tool aid the identification of patients at risk of sleep disorders in the community : a pilot study

Background: When experiencing sleep problems for the first time, consumers may often approach community pharmacists for advice as they are easily accessible health care professionals in the community. In Australian community pharmacies there are no specific tools available for use by pharmacists to assist with the assessment and handling of consumers with sleep enquiries. Objective: To assess the feasibility of improving the detection of sleep disorders within the community through the pilot of a newly developed Community Pharmacy Sleep Assessment Tool (COP-SAT). Method: The COP-SAT was designed to incorporate elements from a number of existing, standardized, and validated clinical screening measures. The COP-SAT was trialed in four Australian community pharmacies over a 4-week period. Key findings: A total of 241 community pharmacy consumers were assessed using the COP-SAT. A total of 74 (30.7%) were assessed as being at risk of insomnia, 26 (10.7%) were at risk of daytime sleepiness, 19 (7.9%) were at risk of obstructive sleep apnea, and 121 (50.2%) were regular snorers. A total of 116 (48.1%) participants indicated that they consume caffeine before bedtime, of which 55 (47%) had associated symptoms of sleep onset insomnia. Moreover, 85 (35%) consumed alcohol before bedtime, of which 50 (58%) experienced fragmented sleep, 50 (58%) were regular snorers, and nine (10.6%) had apnea symptoms. The COP-SAT was feasible in the community pharmacy setting. The prevalence of sleep disorders in the sampled population was high, but generally consistent with previous studies on the general population. Conclusion: A large proportion of participants reported sleep disorder symptoms, and a link was found between the consumption of alcohol and caffeine substances at bedtime and associated symptoms. While larger studies are needed to assess the clinical properties of the tool, the results of this feasibility study have demonstrated that the COP-SAT may be a practical tool for the identification of patients at risk of developing sleep disorders in the community.

Hush-a-by mummy : interactions between co-sleeping and maternal sleep disturbance

Childbirth is an extraordinary, everyday experience; in 2011, 301 617 infants were born in Australia [1], resulting in countless potential occurrences of sleep disturbance and subsequent daytime sleepiness. While the relationship between sleep and sleepiness has been heavily investigated in the vulnerable sub-populations of shift workers and patients with sleep disorders, comparatively postpartum women have been overlooked. Previous research has reported slower reaction times to the Psychomotor Vigilance Task [2] and shorter sleep onset in the multiple sleep latency test [3] in new mothers compared with control women. However little is known about change in sleep and sleepiness over time or potential interactions with infant care behaviour choices, such as co-sleeping (mother and infant sharing a bed). This study aims to investigate change in new mothers sleep quantity, sleep quality and resulting daytime sleepiness over postpartum weeks 6, 12 and 18, while evaluating the impact of co-sleeping.

Actigraphy assessment of mother's sleep at 6, 12 & 18 weeks postpartum

Introduction: Mothers’ sleep during the postpartum period is commonly characterised by bouts of sleep across the night, resulting in low sleep efficiency and daytime sleepiness. Understanding of the nature of mothers’ sleep disruption needs to incorporate indices of both sleep quantity and sleep quality, but objective assessment of sleep disturbance experienced during the first postpartum months has not been investigated in great detail. This longitudinal study aimed to objectively measure mothers’ sleep during the first 18 weeks postpartum, to ascertain the level of sleep disturbance experienced. Method: Eleven mothers (Mean age = 29.82, SD = 4.45) from Australia wore Actiwatch-2 devices for up to 7 days and nights at 6, 12 and 18 weeks postpartum. For each night of recording, a number of sleep bouts were identified. Total sleep time (TST) was calculated as the total number of minutes across the night within these bouts. Sleep efficiency was calculated as the percentage of minutes across the night classified as being part of a sleep bout, with higher scores indicating higher efficiency. Sleep quality captured the efficiency of sleep within sleep bouts, and was calculated as the percentage of epochs classified as sleep within sleep bouts, with higher scores indicating higher sleep quality. Results: At 6 weeks postpartum, mean total sleep time was 420.22 minutes (SD = 50.61). Total sleep time did not significantly differ across the assessment; however there was a trend towards an increase over time. Sleep efficiency increased across the time periods (F(2,10) = 10.30, p = .001), with a significant increase between week 12 and week 18. At 6 weeks postpartum, mean sleep quality was 93.15% (SD = 2.68) and scores did not significantly change across the assessment periods. While there was no relationship between sleep efficiency and sleep quality during weeks 6 and 12, a significant positive relationship was observed at week 18, r2 = .52, p = .013. Conclusions: Within this sample, a low level of disruption was consistently shown within the mothers’ night time sleep bouts. However, overall sleep efficiency suggested a significant proportion of time spent awake between sleep bouts. While TST remained stable over time, overall sleep efficiency improved, suggesting the mothers’ sleep was becoming more consolidated. A single sleep bout a night was not often experienced.

Continuous positive air pressure treatment for obstructive sleep apnoea patients : effects on sleep quality and quantity as measured by actigraphy

Objectives Actigraphy can reliably assess sleep in healthy adults and be used to estimate total sleep time in suspected obstructive sleep apnoea (OSA) patients. We compared sleep quality for Continuous Positive Air Pressure (CPAP) treated OSA patients and controls, evaluating the impact of stopping CPAP for one night. Methods 11 men, aged 51–75 years (m = 65.6 years), compliant CPAP users, treated for 1–19 years (m = 7.8 years) wore Cambridge Neurotechnology Ltd actiwatches for one night while using CPAP and for one night sleeping without CPAP. A control group of 11 healthy men, aged 63–74 years (m = 64.1 years) slept normally whilst wearing an actiwatch. Subsequent daytime sleepiness was recorded using Karolinska sleepiness scores (KSS). Results Actimetry showed no significant differences between actual sleep time, sleep efficiency, sleep disturbance index or number of wake bouts when comparing OSA participants using CPAP, with controls; there was no difference in subsequent daytime sleepiness, control KSS = 4.21, OSA KSS = 4.17. Without CPAP there was no significant difference in sleep length or sleep onset latency compared with using CPAP, but there was a significant impact on sleep quality as shown by: increased sleep disturbance index from 7.9 to 13.8 [t(10) = 3.510, P < 0.05], decreased percent of actual sleep from 92.05% to 86.15% [t(10) = 3.51, P < 0.05], decreased sleep efficiency from 86.6% to 81% [t(10) = 2.204, P < 0.05] and increased number of wake bouts from 29 to 42.5 [t(10) = 3.877, P < 0.05]. Daytime sleepiness became significantly worse increasing from KSS 4.17 to 6.27 [t(10) = )4.96, P < 0.05]. Conclusion There was no disparity in sleep quality or KSS scores between CPAP treated OSA patients and healthy controls of a similar age. Treated OSA patients obtained quality sleep with no elevated day time sleepiness. However, cessation of treatment for one night caused sleep quality to deteriorate despite a comparable sleep time; the deterioration in sleep quality could explain the increase in daytime sleepiness. OSA patients need to know that even short-term noncompliance with CPAP treatment significantly impairs sleep quality, leading to excessive sleepiness during monotonous tasks such as driving. Actigraphy successfully identified nights of non-compliance in treated OSA patients; but did not differentiate between the sleep of CPAP treated OSA patients and healthy controls.

Characterizing self-reported sleep disturbance after mild traumatic brain injury

Sleep disturbance after mild traumatic brain injury (mTBI) is commonly reported as debilitating and persistent. However, the nature of this disturbance is poorly understood. This study sought to characterize sleep after mTBI compared with a control group. A cross-sectional matched case control design was used. Thirty-three persons with recent mTBI (1–6 months ago) and 33 age, sex, and ethnicity matched controls completed established questionnaires of sleep quality, quantity, timing, and sleep-related daytime impairment. The mTBI participants were compared with an independent sample of close-matched controls (CMCs; n=33) to allow partial internal replication. Compared with controls, persons with mTBI reported significantly greater sleep disturbance, more severe insomnia symptoms, a longer duration of wake after sleep onset, and greater sleep-related impairment (all medium to large effects, Cohen's d>0.5). No differences were found in sleep quantity, timing, sleep onset latency, sleep efficiency, or daytime sleepiness. All findings except a measure of sleep timing (i.e., sleep midpoint) were replicated for CMCs. These results indicate a difference in the magnitude and nature of perceived sleep disturbance after mTBI compared with controls, where persons with mTBI report poorer sleep quality and greater sleep-related impairment. Sleep quantity and timing did not differ between the groups. These preliminary findings should guide the provision of clearer advice to patients about the aspects of their sleep that may change after mTBI and could inform treatment selection.

Driver sleepiness self-regulation : physiological and subjective evidence

Introduction: Sleepiness contributes to a substantial proportion of fatal and severe road crashes. Efforts to reduce the incidence of sleep-related crashes have largely focussed on driver education to promote self-regulation of driving behaviour. However, effective self-regulation requires accurate self-perception of sleepiness. The aim of this study was to assess capacity to accurately identify sleepiness, and self-regulate driving cessation, during a validated driving simulator task. Methods: Participants comprised 26 young adult drivers (20-28 years) who had open licenses. No other exclusion criteria where used. Participants were partially sleep deprived (05:00 wake up) and completed a laboratory-based hazard perception driving simulation, counterbalanced to either at mid-morning or mid-afternoon. Established physiological measures (i.e., EEG, EOG) and subjective measures (Karolinska Sleepiness Scale), previously found sensitive to changes in sleepiness levels, were utilised. Participants were instructed to ‘drive’ on the simulator until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 36.1 minutes (±17.7 minutes). Subjective sleepiness increased significantly from the beginning (KSS=6.6±0.7) to the end (KSS=8.2±0.5) of the driving period. No significant differences were found for EEG spectral power measures of sleepiness (i.e., theta or alpha spectral power) from the start of the driving task to the point of cessation of driving. During the nap opportunity, 88% of the participants (23/26) were able to reach sleep onset with an average latency of 9.9 minutes (±7.5 minutes). The average nap duration was 15.1 minutes (±8.1 minutes). Sleep architecture during the nap was predominately comprised of Stages I and II (combined 92%). Discussion: Participants reported high levels of sleepiness during daytime driving after very moderate sleep restriction. They were able to report increasing sleepiness during the test period despite no observed change in standard physiological indices of sleepiness. This increased subjective sleepiness had behavioural validity as the participants had high ‘napability’ at the point of driving cessation, with most achieving some degree of subsequent sleep. This study suggests that the nature of a safety instruction (i.e. how to view sleepiness) can be a determinant of driver behaviour.

Sleep-related eye symptoms and their potential for identifying driver sleepiness

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep-related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night-time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. ‘Eye strain’, ‘difficulty focusing’, ‘heavy eyelids’ and ‘difficulty keeping the eyes open’ were identified as the four key sleep-related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have ‘heavy eyelids’ and ‘difficulty keeping the eyes open’. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice ‘stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open’.

New parameters for daytime wandering

This study aimed to describe wandering using new parameters and to evaluate parameters as a function of cognitive impairment and mobility. Forty-four wanderers in long-term care settings were videotaped 12 times. Rate and duration of wandering episodes were plotted and used to derive parameters from values above and below case medians, proportion of hours wandering, and time of day. Participants wandered during 47% of observations; on average, the hourly rate was 4.3 episodes, the peak hourly rate was 18 episodes, and the peak hourly duration was 19.9 minutes. Mini-Mental State Examination (MMSE) scores was negatively correlated with overall duration and number of observations during which duration exceeded 15 minutes per hour, was positively correlated with number of observations without wandering, and was not significantly correlated with rate-related parameters. Mobility correlated positively with rate and duration parameters. Interaction of MMSE score and mobility was the strongest predictor of wandering duration. Parameters derived from repeated measures provide a new view of daytime wandering and insight into relationships between MMSE score and mobility status with specific parameters of wandering.

Interaction between visual status, driver age and distracters on daytime driving performance

This study investigated the effects of visual status, driver age and the presence of secondary distracter tasks on driving performance. Twenty young (M = 26.8 years) and 19 old (M = 70.2 years) participants drove around a closed-road circuit under three visual (normal, simulated cataracts, blur) and three distracter conditions (none, visual, auditory). Simulated visual impairment, increased driver age and the presence of a distracter task detrimentally affected all measures of driving performance except gap judgments and lane keeping. Significant interaction effects were evident between visual status, age and distracters; simulated cataracts had the most negative impact on performance in the presence of visual distracters and a more negative impact for older drivers. The implications of these findings for driving behaviour and acquisition of driving-related information for people with common visual impairments are discussed

Stop and revive? : the effectiveness of nap and active rest breaks for reducing driver sleepiness

The incidence of sleep-related crashes has been estimated to account for approximately 20% of all fatal and severe crashes. The use of sleepiness countermeasures by drivers is an important component to reduce the incidence rates of sleep-related crashes. Taking a brief nap and stopping for a rest break are two highly publicised countermeasures for driver sleepiness and are also believed by drivers to be the most effective countermeasures. Despite this belief, there is scarce evidence to support the utility of these countermeasures for reducing driver sleepiness levels. Therefore, determining the effectiveness of these countermeasures is an important road safety concern. The current study utilised a young adult sample (N = 20) to investigate the effectiveness of a nap and an active rest break. The countermeasures effects were evaluated by physiological, behavioural (hazard perception skill), and subjective measures previously found sensitive to sleepiness. Participants initially completed two hours of a simulated driving task followed by a 15 minute nap opportunity or a 15 minute active rest break that included 10 minutes of brisk walking. After the break, participants completed one final hour of the simulated driving task. A within-subjects design was used so that each participant completed both the nap and the active rest break conditions on separate occasions. The analyses revealed that only the nap break provided any meaningful reduction in physiological sleepiness, reduced subjective sleepiness levels, and maintained hazard perception performance. In contrast, the active rest break had no effect for reducing physiological sleepiness and resulted in a decrement in hazard perception performance (i.e., an increase of reaction time latencies), with a transient reduction in subjective sleepiness levels. A number of theoretical, empirical and practical issues were identified by the current study.

Too sleepy to drive : self-perception and regulation of driving when sleepy

Background: Sleepiness is a direct contributor to a substantial proportion of fatal and severe road cashes. A number of technological solutions designed to detect sleepiness have been developed, but self-awareness of increasing sleepiness remains a critical component in on-road strategies for mitigating this risk. In order to take appropriate action when sleepy, drivers’ perceptions of their level of sleepiness must be accurate. Aims: This study aimed to assess capacity to accurately identify sleepiness and self-regulate driving cessation during a validated driving simulator task. Participants: Participants comprised 26 young adult drivers (20-28 years). The drivers had open licenses but no other exclusion criteria where used. Methods: Participants woke at 5am, and took part in a laboratory-based hazard perception driving simulation, either at mid-morning or mid-afternoon. Established physiological measures (including EEG) and subjective measures (sleepiness ratings) previously found sensitive to changes in sleepiness levels were utilised. Participants were instructed to ‘drive’ until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 39 minutes (±18 minutes). Almost all (23/26) of the participants then achieved sleep during the nap opportunity. These data suggest that the participants’ perceptions of sleepiness were specific. However, EEG data from a number of participants suggested very high levels of sleepiness prior to driving cessation, suggesting poor sensitivity. Conclusions: Participants reported high levels of sleepiness while driving after very moderate sleep restriction. They were able to identify increasing sleepiness during the test period, could decide to cease driving and in most cases were sufficiently sleepy to achieve sleep during the daytime session. However, the levels of sleepiness achieved prior to driving cessation suggest poor accuracy in self-perception and regulation. This presents practical issues for the implementation of fatigue and sleep-related strategies to improve driver safety.

In the blink of an eye : the circadian effects on ocular and subjective indices of driver sleepiness

Driver sleepiness contributes substantially to fatal and severe crashes and the contribution it makes to less serious crashes is likely to as great or greater. Currently, drivers’ awareness of sleepiness (subjective sleepiness) remains a critical component for the mitigation of sleep-related crashes. Nonetheless, numerous calls have been made for technological monitors of drivers’ physiological sleepiness levels so drivers can be ‘alerted’ when approaching high levels of sleepiness. Several physiological indices of sleepiness show potential as a reliable metric to monitor drivers’ sleepiness levels, with eye blink indices being a promising candidate. However, extensive evaluations of eye blink measures are lacking including the effects that the endogenous circadian rhythm can have on eye blinks. To examine the utility of ocular measures, 26 participants completed a simulated driving task while physiological measures of blink rate and duration were recorded after partial sleep restriction. To examine the circadian effects participants were randomly assigned to complete either a morning or an afternoon session of the driving task. The results show subjective sleepiness levels increased over the duration of the task. The blink duration index was sensitive to increases in sleepiness during morning testing, but was not sensitive during afternoon testing. This finding suggests that the utility of blink indices as a reliable metric for sleepiness are still far from specific. The subjective measures had the largest effect size when compared to the blink measures. Therefore, awareness of sleepiness still remains a critical factor for driver sleepiness and the mitigation of sleep-related crashes.