Supporting sleep in early care and education: An assessment of observed sleep-times using a sleep practices optimality index

Aim: The aim was to investigate whether the sleep practices in early childhood education (ECE) settings align with current evidence on optimal practice to support sleep. Background: Internationally, scheduled sleep times are a common feature of daily schedules in ECE settings, yet little is known about the degree to which care practices in these settings align with the evidence regarding appropriate support of sleep. Methods: Observations were conducted in 130 Australian ECE rooms attended by preschool children (Mean = 4.9 years). Of these rooms, 118 had daily scheduled sleep times. Observed practices were scored against an optimality index, the Sleep Environment and Practices Optimality Score, developed with reference to current evidence regarding sleep scheduling, routines, environmental stimuli, and emotional climate. Cluster analysis was applied to identify patterns and prevalence of care practices in the sleep time. Results: Three sleep practices types were identified. Supportive rooms (36%) engaged in practices that maintained regular schedules, promoted routine, reduced environmental stimulation, and maintained positive emotional climate. The majority of ECE rooms (64%), although offering opportunity for sleep, did not engage in supportive practices: Ambivalent rooms (45%) were emotionally positive but did not support sleep; Unsupportive rooms (19%) were both emotionally negative and unsupportive in their practices. Conclusions: Although ECE rooms schedule sleep time, many do not adopt practices that are supportive of sleep. Our results underscore the need for education about sleep supporting practice and research to ascertain the impact of sleep practices in ECE settings on children’s sleep health and broader well-being.

Sleep and self-regulation from birth to 7 years: A retrospective study of children with and without ADHD at 8-9 years

Objective To examine mean level differences, and longitudinal and reciprocal relations among behavioral sleep problems, emotional dysregulation, and attentional regulation across early childhood for children with and without ADHD at 8-9 years. Method This study used data from Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort (n = 4109 analyzed). Children with and without ADHD were identified at age 8-9 years via parent-report of ADHD diagnosis and the 5-item Inattention-Hyperactivity subscale from the Strengths and Difficulties Questionnaire. Maternal report of child sleep problems and self-regulation was collected at 0-1, 2-3, 4-5 and 6-7 years of age. ANOVA was used to compare mean level differences in sleep problems, emotional and attentional regulation by ADHD group. Longitudinal structural equation modeling examined the relations among sleep and self-regulation across time in children with and without ADHD. Results Children with ADHD had persistently elevated levels of sleep problems (from infancy) and emotional and attentional dysregulation compared to controls (from 2-3 years of age). Sleep problems, emotional dysregulation, and attentional regulation were stable over time for both groups. Sleep problems were associated with greater emotional dysregulation two years later from 2-3 years of age for both groups, which in turn was associated with poorer attentional regulation. There was no direct relationship between sleep problems and later attentional regulation. Conclusion Sleep problems in children with and without ADHD are associated with emotional dysregulation, which in turn contributes to poorer attentional functioning. This study highlights the importance of assessing and managing sleep problems in young children.

Early childhood profiles of sleep problems and self-regulation predict later school adjustment

Background Children’s sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims This study explores the normative developmental pathway for sleep problems and self-regulation across early childhood, and investigates whether departure from the normative pathway is associated with later social-emotional adjustment to school. Sample This study involved 2880 children participating in the Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC) – Infant Cohort from Wave 1 (0-1 years) to Wave 4 (6-7 years). Method Mothers reported on children’s sleep problems, emotional, and attentional self-regulation at three time points from birth to 5 years. Teachers reported on children’s social-emotional adjustment to school at 6-7 years. Latent profile analysis was used to establish person-centred longitudinal profiles. Results Three profiles were found. The normative profile (69%) had consistently average or higher emotional and attentional regulation scores and sleep problems that steadily reduced from birth to 5. The remaining 31% of children were members of two non-normative self-regulation profiles, both characterised by escalating sleep problems across early childhood and below mean self-regulation. Non-normative group membership was associated with higher teacher-reported hyperactivity and emotional problems, and poorer classroom self-regulation and prosocial skills. Conclusion Early childhood profiles of self-regulation that include sleep problems offer a way to identify children at risk of poor school adjustment. Children with escalating early childhood sleep problems should be considered an important target group for school transition interventions.

Sleep quantity and quality during heat-based training and the effects of cold-water immersion recovery

- Introduction Heat-based training (HT) is becoming increasingly popular as a means of inducing acclimation before athletic competition in hot conditions and/or to augment the training impulse beyond that achieved in thermo-neutral conditions. Importantly, current understanding of the effects of HT on regenerative processes such as sleep and the interactions with common recovery interventions remain unknown. This study aimed to examine sleep characteristics during five consecutive days of training in the heat with the inclusion of cold-water immersion (CWI) compared to baseline sleep patterns. - Methods Thirty recreationally-trained males completed HT in 32 ± 1 °C and 60% rh for five consecutive days. Conditions included: 1) 90 min cycling at 40 % power at VO2max (Pmax) (90CONT; n = 10); 90 min cycling at 40 % Pmax with a 20 min CWI (14 ± 1 °C; 90CWI; n = 10); and 30 min cycling alternating between 40 and 70 % Pmax every 3 min, with no recovery intervention (30HIT; n = 10). Sleep quality and quantity was assessed during HT and four nights of 'baseline' sleep (BASE). Actigraphy provided measures of time in and out of bed, sleep latency, efficiency, total time in bed and total time asleep, wake after sleep onset, number of awakenings, and wakening duration. Subjective ratings of sleep were also recorded using a 1-5 Likert scale. Repeated measures analysis of variance (ANOVA) was completed to determine effect of time and condition on sleep quality and quantity. Cohen's d effect sizes were also applied to determine magnitude and trends in the data. - Results Sleep latency, efficiency, total time in bed and number of awakenings were not significantly different between BASE and HT (P > 0.05). However, total time asleep was significantly reduced (P = 0.01; d = 1.46) and the duration periods of wakefulness after sleep onset was significantly greater during HT compared with BASE (P = 0.001; d = 1.14). Comparison between training groups showed latency was significantly higher for the 30HIT group compared to 90CONT (P = 0.02; d = 1.33). Nevertheless, there were no differences between training groups for sleep efficiency, total time in bed or asleep, wake after sleep onset, number of awakenings or awake duration (P > 0.05). Further, cold-water immersion recovery had no significant effect on sleep characteristics (P > 0.05). - Discussion Sleep plays an important role in athletic recovery and has previously been demonstrated to be influenced by both exercise training and thermal strain. Present data highlight the effect of HT on reduced sleep quality, specifically reducing total time asleep due to longer duration awake during awakenings after sleep onset. Importantly, although cold water recovery accelerates the removal of thermal load, this intervention did not blunt the negative effects of HT on sleep characteristics. - Conclusion Training in hot conditions may reduce both sleep quantity and quality and should be taken into consideration when administering this training intervention in the field.

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.

Mixed reality stories: How creative writers integrate virtual and physical realities

Mixed reality stories (MRS) unfold simultaneously in the physical and the virtual world. Advancements in digital technologies, which are now able to capture more contextual information about our physical environments, are enabling novel ways of blending the two worlds. To explore the process of creating stories from this perspective, we conducted a study with creative writers, in which we asked them to write a MRS script for outdoor running. While we saw instances of intentional connections between physical and virtual worlds in their work, we also observed the use of ambiguity or even deliberate contradiction with available contextual information. In this paper we discuss how these approaches can be beneficial for MRS and propose directions for future work.

Being chased by zombies!: Understanding the experience of mixed reality quests

Both researchers and practitioners show increasing interest in exploring mixed reality games: games, where physical environments blend together with digital technologies. In this paper we have extended earlier work by bringing attention to the role of narrative in mixed reality games. For our case study we chose a mobile phone application Zombies Run!, which is designed to support actual running. This application contains a fictional story about a zombie apocalypse and provides runners with various quests (in the form of missions) to complete during their run. We investigated different aspects of participants' experience with the application and how it changed their running. Our findings show how the app changed running in three major ways. Firstly, it changed the way runs were organised. Secondly, it shook up established running routines. And lastly, it shaped the meanings associated with running.

Intuitive interaction in a mixed reality system

Tangible physical systems are more intuitive than Intangible virtual Systems. Mixed reality systems are considered as an alternative to virtual systems, bringing advantages of tangible systems into an interaction. However, past research has mainly focussed on technical aspects of incorporating pervasive-ness and immersive-ness in the virtual systems. This paper reports on an empirical study of intuitive Interaction in a Mixed Reality game system for children and the design aspects that could facilitate intuitive Interaction in such systems. A related samples Friedman’s test showed that the Mixed Reality game system demonstrated more intuitive interactions than non-intuitive Interactions. A linear regression analysis further established that the variation in intuitive Interaction in the Mixed Reality system could be statistically significantly explained primarily by physical affordances offered by the Mixed Reality system and to a lesser extent by the perceived affordances in the system. Design guidelines to develop intuitive Mixed Reality systems are discussed. These guidelines should allow designers to exploit the wonders of advances in technology and at the same time allow users to directly interact with the physical real world. This will allow users to access maximal physical affordances, which are primary contributors to intuitive interaction in Tangible and Mixed Reality systems.

The tired foot. The effects of physical activity, energy expenditure and sleep on the diabetic foot population

Background The most common pathway to development of diabetes foot ulcers is repetitive daily activity stress on the plantar surface of the neuropathic foot. Studies suggest an association between different diabetic foot complications and physical activity. However, to the best of the authors knowledge the steps/day and sleep patterns of people with diabetic foot ulcers has yet to be investigated. This observational study aims to investigate the physical activity and sleep patterns of three groups of adults with type 2 diabetes and different foot complications Methods Participants with type 2 diabetes were recruited into three groups: 1. those with no reported foot complications (DNIL), 2. those with diagnosis of neuropathy (DPN) and 3. those with a neuropathic ulcer (DFU). Exclusion criteria included peripheral arterial disease and mobility aid use. Participants wore a SenseWear Pro 3 Armband continuously for 7 days and completed an Epworth Sleepiness Scale. The Armband is a validated automated measure of activity (walking steps, average Metabolic Equivalent Task (MET), physical activity (>3 METs) duration), energy expenditure(kJ) (total and physical activity (>3 METs)) and sleep (duration). Data on age, sex, BMI, diabetes duration and HbA1c were also collected. Results Sixty-Six (14 DNIL, 22 DPN and 30 DFU's participants were recruited; 71% males, mean age 61(±12) years, diabetes duration 13(±9) years, HbA1c 8.3(±2.8), BMI 32.6(±5.9), average METs 1.2(0.2). Significant differences were reported in mean(SD) steps/day (5,859(±2,381) in DNIL; 5,007(±3,349) in DPN and 3,271(±2,417) in DFU's and daily energy expenditure (10,868(±1,307)kJ in DNIL; 11,060(±1,916)kJ in DPN and 13,006(± 3,559) in DFU's(p <0.05). No significant differences were reported for average METs, physical activity duration or energy expenditure, sleep time or Epworth score (p>0.1). Conclusions Preliminary findings suggest people with diabetes are sedentary. Results indicate that patients with a diabetic foot ulcer work significantly less than those with neuropathy or nil complications and use significantly more energy to do so. Sleep Parameters showed no differences. Recruitment is still on going.

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.

Involvement of Ca2+-dependent hyperpolarization in sleep duration in mammals

The detailed molecular mechanisms underlying the regulation of sleep duration in mammals are still elusive. To address this challenge, we constructed a simple computational model, which recapitulates the electrophysiological characteristics of the slow-wave sleep and awake states. Comprehensive bifurcation analysis predicted that a Ca2+-dependent hyperpolarization pathway may play a role in slow-wave sleep and hence in the regulation of sleep duration. To experimentally validate the prediction, we generate and analyze 21 KO mice. Here we found that impaired Ca2+-dependent K+ channels (Kcnn2 and Kcnn3), voltage-gated Ca2+ channels (Cacna1g and Cacna1h), or Ca2+/calmodulin-dependent kinases (Camk2a and Camk2b) decrease sleep duration, while impaired plasma membrane Ca2+ ATPase (Atp2b3) increases sleep duration. Pharmacological intervention and whole-brain imaging validated that impaired NMDA receptors reduce sleep duration and directly increase the excitability of cells. Based on these results, we propose a hypothesis that a Ca2+-dependent hyperpolarization pathway underlies the regulation of sleep duration in mammals.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.