Mandatory naptimes in child care and children's nighttime sleep

Objectives To examine the relationship between mandatory naptimes in child care and children's nighttime sleep duration, both concurrently and 12 months later once in school. Methods A sample of 168 children (50-72 months; 55% males) attending licensed child care centers were observed across their morning and throughout their scheduled naptime. Mandatory naptime was determined as the period in which children were not permitted any alternative activity except lying on their bed. Teachers reported each child's napping in child care. Nighttime and total sleep duration was reported by parents at 2 time points, in child care and in the second semester of their first school year. General linear models were used to examine group differences in sleep duration between children experiencing 0 to 60 minutes and >60 minutes of mandatory naptime, adjusting for key confounders. Path analysis was conducted to test a mediation model in which mandatory naptime is associated with nighttime sleep duration through increased napping in child care. Results Children who experienced >60 minutes of mandatory naptime in child care had significantly less nighttime sleep than those with 0 to 60 minutes of mandatory naptime. This difference persisted at 12-month follow-up, once children were in school. Napping in child care mediated the relationship between mandatory naptime and duration of nighttime sleep. Conclusions Exposure to mandatory naptimes of >60 minutes in child care is associated with decreased duration of nighttime sleep that endures beyond child care attendance. Given the large number of children who attend child care, sleep practices within these settings present an important focus for child health.

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.

What parents want: Parent preference regarding sleep for their preschool child when attending Early Care and Education

Background While most children cease napping between the ages of 2 and 5 years, across a range of international settings the allocation of a mandatory naptime is a common feature of the daily routine in Early Care and Education (ECE) programs for children of this age. Evidence regarding the developmental effects of napping is limited but, beyond age 2, is consistently associated with delayed night sleep onset and increased number of awakenings. Objectives The present study examined parent preferences towards napping in ECE. Methods Participants were 750 parents of preschool-aged children attending a representative sample of Australian ECE programs across metropolitan, regional and rural sites in 2011. We analysed quantitative and open-ended questionnaire data from a large, longitudinal study of the effectiveness of Australian early education programs (E4Kids). Statistical analyses examined prevalence of parent preference for sleep and demographic correlates. Thematic analyses were employed to identify parents' rationale for this preference. Results The majority of parents (78.7%) preferred that their children did not regularly sleep while attending ECE. The dominant explanation provided by parents was that regular naps were no longer appropriate and adversely impacted their children's health and development. Parents of younger children were more likely to support regular naps. Conclusions The results highlight a disjuncture between parent preferences and current sleep policy and practices in ECE. Further research is needed to establish evidence-based guidelines to support healthy sleep-rest practices in ECE. Such evidence will guide appropriate practice and support parent-educator communication regarding sleep and rest.

Sleep-related crash characteristics: Implications for applying a fatigue definition to crash reports

Sleep-related (SR) crashes are an endemic problem the world over. However, police officers report difficulties in identifying sleepiness as a crash contributing factor. One approach to improving the sensitivity of SR crash identification is by applying a proxy definition post hoc to crash reports. To identify the prominent characteristics of SR crashes and highlight the influence of proxy definitions, ten years of Queensland (Australia) police reports of crashes occurring in ≥100 km/h speed zones were analysed. In Queensland, two approaches are routinely taken to identifying SR crashes. First, attending police officers identify crash causal factors; one possible option is ‘fatigue/fell asleep’. Second, a proxy definition is applied to all crash reports. Those meeting the definition are considered SR and added to the police-reported SR crashes. Of the 65,204 vehicle operators involved in crashes 3449 were police-reported as SR. Analyses of these data found that male drivers aged 16–24 years within the first two years of unsupervised driving were most likely to have a SR crash. Collision with a stationary object was more likely in SR than in not-SR crashes. Using the proxy definition 9739 (14.9%) crashes were classified as SR. Using the proxy definition removes the findings that SR crashes are more likely to involve males and be of high severity. Additionally, proxy defined SR crashes are no less likely at intersections than not-SR crashes. When interpreting crash data it is important to understand the implications of SR identification because strategies aimed at reducing the road toll are informed by such data. Without the correct interpretation, funding could be misdirected. Improving sleepiness identification should be a priority in terms of both improvement to police and proxy reporting.

Sleep deprivation and brain energy metabolism : in vivo studies in rats and humans

Sleep deprivation leads to increased subsequent sleep length and depth and to deficits in cognitive performance in humans. In animals extreme sleep deprivation is eventually fatal. The cellular and molecular mechanisms causing the symptoms of sleep deprivation are unclear. This thesis was inspired by the hypothesis that during wakefulness brain energy stores would be depleted, and they would be replenished during sleep. The aim of this thesis was to elucidate the energy metabolic processes taking place in the brain during sleep deprivation. Endogenous brain energy metabolite levels were assessed in vivo in rats and in humans in four separate studies (Studies I-IV). In the first part (Study I) the effects of local energy depletion on brain energy metabolism and sleep were studied in rats with the use of in vivo microdialysis combined with high performance liquid chromatography. Energy depletion induced by 2,4-dinitrophenol infusion into the basal forebrain was comparable to the effects of sleep deprivation: both increased extracellular concentrations of adenosine, lactate, and pyruvate, and elevated subsequent sleep. This result supports the hypothesis of a connection between brain energy metabolism and sleep. The second part involved healthy human subjects (Studies II-IV). Study II aimed to assess the feasibility of applying proton magnetic resonance spectroscopy (1H MRS) to study brain lactate levels during cognitive stimulation. Cognitive stimulation induced an increase in lactate levels in the left inferior frontal gyrus, showing that metabolic imaging of neuronal activity related to cognition is possible with 1H MRS. Study III examined the effects of sleep deprivation and aging on the brain lactate response to cognitive stimulation. No physiologic, cognitive stimulation-induced lactate response appeared in the sleep-deprived and in the aging subjects, which can be interpreted as a sign of malfunctioning of brain energy metabolism. This malfunctioning may contribute to the functional impairment of the frontal cortex both during aging and sleep deprivation. Finally (Study IV), 1H MRS major metabolite levels in the occipital cortex were assessed during sleep deprivation and during photic stimulation. N-acetyl-aspartate (NAA/H2O) decreased during sleep deprivation, supporting the hypothesis of sleep deprivation-induced disturbance in brain energy metabolism. Choline containing compounds (Cho/H2O) decreased during sleep deprivation and recovered to alert levels during photic stimulation, pointing towards changes in membrane metabolism, and giving support to earlier observations of altered brain response to stimulation during sleep deprivation. Based on these findings, it can be concluded that sleep deprivation alters brain energy metabolism. However, the effects of sleep deprivation on brain energy metabolism may vary from one brain area to another. Although an effect of sleep deprivation might not in all cases be detectable in the non-stimulated baseline state, a challenge imposed by cognitive or photic stimulation can reveal significant changes. It can be hypothesized that brain energy metabolism during sleep deprivation is more vulnerable than in the alert state. Changes in brain energy metabolism may participate in the homeostatic regulation of sleep and contribute to the deficits in cognitive performance during sleep deprivation.

In bed with technology: Challenges and opportunities for sleep tracking

In recent years a variety of mobile apps, wearable technologies and embedded systems have emerged that allow individuals to track the amount and the quality of their sleep in their own beds. Despite the widespread adoption of these technologies, little is known about the challenges that current users face in tracking and analysing their sleep. Hence we conducted a qualitative study to examine the practices of current users of sleep tracking technologies and to identify challenges in current practice. Based on data collected from 5 online forums for users of sleep-tracking technologies, we identified 22 different challenges under the following 4 themes: tracking continuity, trust, data manipulation, and data interpretation. Based on these results, we propose 6 design opportunities to assist researchers and practitioners in designing sleep-tracking technologies.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

Influences on sleep-wake behaviour in older adults and community dementia care: Light exposure and partner impact

This project described sleep-wake behaviour in community-dwelling older adults and in community dementia care. It examined the applicability of a newly presented conceptual model (the Multifactorial Influences on Sleep Health model) to evaluate factors influencing sleep in ageing, with a particular focus on the importance of daytime light exposure and the impact of partners.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Associations between personality traits and sleep quality and quantity in young adults

This thesis examines the associations between personality traits and sleep quantity and quality in young adults. Additionally the possible effects of birth status on these associations are examined. The data used in this thesis is part of a birth cohort study (Helsinki Study of Very Low Birth Weight Adults). The personality traits are based on the five-factor model of personality. The sleep quantity and quality are based on actigraphy assessments. Four hypothesis were made about the personality and sleep associations: (1) neuroticism is related to a lesser quality of sleep, (2) there will be more significant associations between personality traits and sleep quality than between personality traits and sleep quantity, (3) the Very Low Birth Weight (VLBW) as well as, (4) the Small for Gestational Age (SGA) status will affect the associations. Linear regressions were used to study the associations between personality traits and sleep quality and quantity. Whenever an association was significant, it was tested whether this association was moderated first, by the VLBW and second, by the SGA status of the participant. The results were mostly in line with previous research especially demonstrating the negative association between neuroticism and the quality of sleep and suggesting that vulnerability to stress decreases sleep quality. Also it was found that agreeableness and conscientiousness were associated with better sleep quality and extraversion was associated with lower sleep quantity. In addition SGA status moderated the personality and sleep associations. It is proposed that there are two factors behind the interaction. First, prenatally developing mechanisms have an effect on the development of sleep as well as personality. Second, differences in the postnatal environment, for instance the parenting practices, can account for this finding. Future research could focus especially on what kind of prenatal disturbances SGA infants have in the development of mechanisms related to sleep and personality. Also focusing on the differences in parental interaction might shed more light on the results.

Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.