Reducing the use of screen electronic devices in the evening is associated with improved sleep and daytime vigilance in adolescents

Bedtime Regularity and Sleep Sufficiency in Children With Tourette Syndrome

BACKGROUND

Despite research demonstrating sleep disturbance in children with Tourette syndrome (TS), few studies have examined bedtime regularity and sleep sufficiency, two important sleep health dimensions. Therefore, this study examined bedtime regularity and sleep sufficiency in children with TS relative to matched healthy control subjects, and its associated demographic, clinical, and behavioral factors.

METHODS

Participants were 384 parents or caregivers of children aged three to 17 years, including 192 with current TS and 192 matched healthy control subjects drawn from the 2020-2021 cycle of the National Survey of Children's Health. Parents completed questions assessing demographic (i.e., age, race, sex), clinical (i.e., attention-deficit/hyperactivity disorder [ADHD], autism spectrum disorder, anxiety, depression, tic severity, behavioral or conduct problems, ADHD medication, health condition-related impairment), and behavioral (i.e., screen time) characteristics. Mann-Whitney U test and chi-square test of independence were performed to compare groups on bedtime regularity and sleep sufficiency, respectively. Ordinal regression and binary logistic regression without and with backward elimination were performed to evaluate indicators of bedtime regularity and sleep sufficiency, respectively, in children with TS.

RESULTS

Children with current TS had significantly poorer bedtime regularity, but not sleep sufficiency, relative to matched healthy control subjects. In children with TS, anxiety and two or more hours of daily screen time were associated with higher likelihood of poor bedtime regularity. Autism was associated with lower likelihood of insufficient sleep, and depression was associated with increased likelihood of insufficient sleep.

CONCLUSIONS

Findings put forth screen time, anxiety, and depression as intervention targets to optimize sleep health in children with TS.

The Effect of Prebedtime Behaviors on Sleep Duration and Quality in Children: Protocol for a Randomized Crossover Trial

BACKGROUND

It is recommended that children should avoid eating dinner, being physically active, or using screens in the hour before bed to ensure good sleep health. However, the evidence base behind these guidelines is weak and limited to cross-sectional studies using questionnaires.

OBJECTIVE

The aim of this randomized crossover trial was to use objective measures to experimentally determine whether recommendations to improve sleep by banning electronic media, physical activity, or food intake in the hour before bed, impact sleep quantity and quality in the youth.

METHODS

After a baseline week to assess usual behavior, 72 children (10-14.9 years old) will be randomized to four conditions, which are (1) avoid all 3 behaviors, (2) use screens for at least 30 minutes, (3) be physically active for at least 30 minutes, and (4) eat a large meal, during the hour before bed on days 5 to 7 of weeks 2 to 5. Families can choose which days of the week they undertake the intervention, but they must be the same days for each intervention week. Guidance on how to undertake each intervention will be provided. Interventions will only be undertaken during the school term to avoid known changes in sleep during school holidays. Intervention adherence and shuteye latency (time from getting into bed until attempting sleep) will be measured by wearable and stationary PatrolEyes video cameras (StuntCams). Sleep (total sleep time, sleep onset, and wake after sleep onset) will be measured using actigraphy (baseline, days 5 to 7 of each intervention week). Mixed effects regression models with a random effect for participants will be used to estimate mean differences (95% CI) for conditions 2 to 4 compared with condition 1.

RESULTS

Recruitment started in March 2024, and is anticipated to finish in April 2025. Following data analysis, we expect that results will be available later in 2026.

CONCLUSIONS

Using objective measures, we will be able to establish if causal relationships exist between prebedtime behaviors and sleep in children. Such information is critical to ensure appropriate and achievable sleep guidelines.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12624000206527; https://tinyurl.com/3kcjmfnj.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/63692.

Disrupted Circadian Rhythms and Substance Use Disorders: A Narrative Review

Substance use disorder is a major global health concern, with a high prevalence among adolescents and young adults. The most common substances of abuse include alcohol, marijuana, cocaine, nicotine, and opiates. Evidence suggests that a mismatch between contemporary lifestyle and environmental demands leads to disrupted circadian rhythms that impair optimal physiological and behavioral function, which can increase the vulnerability to develop substance use disorder and related problems. The circadian system plays an important role in regulating the sleep-wake cycle and reward processing, both of which directly affect substance abuse. Distorted substance use can have a reciprocal effect on the circadian system by influencing circadian clock gene expression. Considering the detrimental health consequences and profound societal impact of substance use disorder, it is crucial to comprehend its complex association with circadian rhythms, which can pave the way for the generation of novel chronotherapeutic treatment approaches. In this narrative review, we have explored the potential contributions of disrupted circadian rhythms and sleep on use and relapse of different substances of abuse. The involvement of circadian clock genes with drug reward pathways is discussed, along with the potential research areas that can be explored to minimize disordered substance use by improving circadian hygiene.

The impact of screen use on sleep health across the lifespan: A National Sleep Foundation consensus statement

OBJECTIVE

To achieve consensus on whether screen-based digital media (1) in general, (2) via prebedtime content, and (3) via prebedtime light impairs sleep health in (a) childhood, (b) adolescence, and (c) adulthood. Furthermore, to address whether employing behavioral strategies and interventions may reduce the potential negative effects of screens on sleep health.

METHODS

The National Sleep Foundation convened a 16-person multidisciplinary expert panel ("Panel"). Panelists met virtually 5 times throughout 2023, during which they followed a modified Delphi RAND/UCLA Appropriateness Method to reach consensus.

RESULTS

The Panel conducted a literature review starting with 2209 articles, narrowed down to 522 relevant empirical articles and 52 relevant review articles. The search was refined to include 35 experimental/intervention studies that examined whether there was a causal link between screen-based digital media and sleep. In addition, panelists reviewed 5 recent relevant systematic review articles. After reviewing the summarized current literature, panelists voted on 10 candidate statements about whether screen use impairs sleep health. The Panel met virtually to discuss the results of the first round of votes, which was then followed by a second round of voting, ultimately achieving consensus on 5 out of the 10 statements.

CONCLUSIONS

The Panel achieved consensus that (1) in general, screen use impairs sleep health among children and adolescents, (2) the content of screen use before sleep impairs sleep health of children and adolescents, and (3) behavioral strategies and interventions may attenuate the negative effects of screen use on sleep health.

Turn off that night light! Light-at-night as a stressor for adolescents

Light-at-night is known to produce a wide variety of behavioral outcomes including promoting anxiety, depression, hyperactivity, abnormal sociability, and learning and memory deficits. Unfortunately, we all live in a 24-h society where people are exposed to light-at-night or light pollution through night-shift work - the need for all-hours emergency services - as well as building and street-lights, making light-at-night exposure practically unavoidable. Additionally, the increase in screentime (tvs and smart devices) during the night also contributes to poorer sleep and behavioral impairments. Compounding these factors is the fact that adolescents tend to be "night owls" and prefer an evening chronotype compared to younger children and adults, so these teenagers will have a higher likelihood of being exposed to light-at-night. Making matters worse is the prevalence of high-school start times of 8 am or earlier - a combination of too early school start times, light exposure during the night, and preference for evening chronotypes is a recipe for reduced and poorer sleep, which can contribute to increased susceptibility for behavioral issues for this population. As such, this mini-review will show, using both human and rodent model studies, how light-at-night affects behavioral outcomes and stress responses, connecting photic signaling and the circadian timing system to the hypothalamic-pituitary adrenal axis. Additionally, this review will also demonstrate that adolescents are more likely to exhibit abnormal behavior in response to light-at-night due to changes in development and hormone regulation during this time period, as well as discuss potential interventions that can help mitigate these negative effects.

Twitter Discussions on #digitaldementia: Content and Sentiment Analysis

BACKGROUND

Digital dementia is a term that describes a possible decline in cognitive abilities, especially memory, attributed to the excessive use of digital technology such as smartphones, computers, and tablets. This concept has gained popularity in public discourse and media lately. With the increasing use of social media platforms such as Twitter (subsequently rebranded as X), discussions about digital dementia have become more widespread, which offer a rich source of information to understand public perceptions, concerns, and sentiments regarding this phenomenon.

OBJECTIVE

The aim of this research was to delve into a comprehensive content and sentiment analysis of Twitter discussions regarding digital dementia using the hashtag #digitaldementia.

METHODS

Retrospectively, publicly available English-language tweets with hashtag combinations related to the topic of digital dementia were extracted from Twitter. The tweets were collected over a period of 15 years, from January 1, 2008, to December 31, 2022. Content analysis was used to identify major themes within the tweets, and sentiment analysis was conducted to understand the positive and negative emotions associated with these themes in order to gain a better understanding of the issues surrounding digital dementia. A one-way ANOVA was performed to gather detailed statistical insights regarding the selected tweets from influencers within each theme.

RESULTS

This study was conducted on 26,290 tweets over 15 years by 5123 Twitter users, mostly female users in the United States. The influencers had followers ranging from 20,000 to 1,195,000 and an average of 214,878 subscribers. The study identified four themes regarding digital dementia after analyzing tweet content: (1) cognitive decline, (2) digital dependency, (3) technology overload, and (4) coping strategies. Categorized according to Glaser and Strauss's classifications, most tweets (14,492/26,290, 55.12%) fell under the categories of wretched (purely negative) or bad (mostly negative). However, only a small proportion of tweets (3122/26,290, 11.86%) were classified as great (purely positive) or swell sentiment (mostly positive). The ANOVA results showed significant differences in mean sentiment scores among the themes (F3,3581=29.03; P<.001). The mean sentiment score was -0.1072 (SD 0.4276).

CONCLUSIONS

Various negative tweets have raised concerns about the link between excessive use of digital devices and cognitive decline, often known as digital dementia. Of particular concern is the rapid increase in digital device use. However, some positive tweets have suggested coping strategies. Engaging in digital detox activities, such as increasing physical exercise and participating in yoga and meditation, could potentially help prevent cognitive decline.

Sleep Patterns in Patients After Solid Organ Transplantation Including Gender and Age Differences. Survey Results From One Transplantation Centre in Poland

INTRODUCTION

Sleep plays a crucial role in maintaining health. Transplant patients are exposed to numerous stressors and are at risk of sleep disturbances. The aim of this study was to assess the sleep patterns of transplant patients.

METHODS

An anonymous paper survey was carried out among patients from one transplant center in Poland. Respondents were asked about the quality and quantity of sleep and the overall impact of the transplantation on their night rest. Data were collected from June to November 2023.

RESULTS

Data were obtained from 212 respondents (122 males and 90 females), aged 48.38 ± 13.68. The positive impact of transplantation on sleep hygiene was indicated by 57.4% of respondents, 28.9% observed no impact, and 13.6% rated the impact as negative. Our study showed that sleep is more satisfying in males than in females (62.8% of males and 46.7% of females). The analysis revealed that 38.9% of females need 30 minutes more than men to fall asleep. Additionally, females tend to get up half an hour later compared to men. About 71.9% of males declared good well-being the next day compared to 62.2% of females. Furthermore females declared more sleepiness the next day. The study also showed that older transplant recipients (over 50 years-of-age) report more frequent awakenings at night.

CONCLUSIONS

The data collected showed differences in sleep patterns according to gender and age. Females and older patients should be screened for sleep disturbances during post-transplantation care.

Solar clock and school start time effects on adolescents' chronotype and sleep: A review of a gap in the literature

Circadian rhythms are entrained by external factors such as sunlight and social cues, but also depend on internal factors such as age. Adolescents exhibit late chronotypes, but worldwide school starts early in the morning leading to unhealthy sleep habits. Several studies reported that adolescents benefit from later school start times. However, the effect of later school start time on different outcomes varies between studies, and most previous literature only takes into consideration the social clock (i.e. local time of school starting time) but not the solar clock (e.g. the distance between school start time and sunrise). Thus, there is an important gap in the literature: when assessing the effect of a school start time on chronotype and sleep of adolescents at different locations and/or seasons, the solar clock might differ and, consistently, the obtained results. For example, the earliest school start time for adolescents has been suggested to be 08:30 hours, but this school start time might correspond to different solar times at different times of the year, longitudes and latitudes. Here, we describe the available literature comparing different school start times, considering important factors such as geographic position, nationality, and the local school start time and its distance to sunrise. Then, we described and contrasted the relative role of both social and solar clocks on the chronotype and sleep of adolescents. As a whole, we point and discuss a gap in literature, suggesting that both clocks are relevant when addressing the effect of school start time on adolescents' chronotype and sleep.

Interactive Screen-Based Activities Predict Worse Actigraphic Sleep Health That Night Among Adolescents

PURPOSE

To determine the micro-longitudinal effects of duration and timing of screen-based activities on sleep within and between adolescents.

METHODS

Daily survey and actigraphy data from the age 15 wave of the Future of Families and Child Wellbeing Study were analyzed using multilevel modeling. Four hundred seventy five adolescents provided three or more days of valid daily survey and nighttime sleep data.

RESULTS

Within-person results showed that on days when adolescents played video games more than their daytime average ± SE (1.3 ± 1.2 hours), sleep onset (6 ± 2 minutes, p < .01) and midpoint (4 ± 2 minutes, p < .02) were delayed for each additional hour of gaming. Between-person results showed that for each hour adolescents used screens to communicate with friends across the day, sleep onset was later (11 ± 3 minutes, p < .01), sleep midpoint was later (8 ± 3 minutes, p < .01), and sleep duration was shorter (-5 ± 2 minutes, p < .03). Adolescents who used screens to communicate with friends or play video games in the hour before bed had later sleep onset (30 ± 14 minutes, p < .03) and midpoint (25 ± 13 minutes, p < .05).

DISCUSSION

Among adolescents, passive screen usage such as browsing the Internet or watching videos may not affect sleep timing or duration, but limiting interactive screen-based activities could protect adolescent sleep health and well-being.

Nocturnal Smartphone Use Affects Sleep Quality and Cognitive and Physical Performance in Tunisian School-Age Children

Nocturnal smartphone use emits blue light, which can adversely affect sleep, leading to a variety of negative effects, particularly in children. Therefore, the present study aimed to determine the effect of acute (AC) (one night) and repeated (RC) (five nights) nocturnal smartphone exposure on sleep, cortisol, and next-day performance in Tunisian children. Thirteen participants (seven girls and six boys, age 9 ± 0.6, height 1.32 ± 0.06, weight 34.47 ± 4.41) attended six experimental nights. The experiment started with a baseline night (BL) with no smartphone exposure, followed by repeated sessions of nocturnal smartphone exposure lasting 90 minutes (08:00 pm-09:30 pm). Actigraphy; salivary cortisol; the Stroop test (selective attention); choice reaction time (CRT); N-back (working memory); counter-movement jump (CMJ), composed of flight time (time spent in the CMJ flight phase) and jump height; and a 30 m sprint were assessed the morning after each condition. Both AC and RC shortened total sleep time (TST) (p < 0.01), with a greater decrease with RC (-46.7 min, ∆% = -9.46) than AC (-28.8 min, ∆% = -5.8) compared to BL. AC and RC significantly increased waking after sleep onset (3.5 min, ∆% = 15.05, to 9.9 min, ∆% = 43.11%) and number of errors made on the Stroop test (1.8 error, ∆% = 74.23, to 3.07 error, ∆% = 97.56%). Children made 0.15 and 0.8 more errors (∆% = 6.2 to 57.61%) and spent 46.9 s and 71.6 s more time on CRT tasks (∆% = 7.22 to 11.11%) with AC and RC, respectively, compared to BL. The high-interference index of the Stroop task, CMJ performance, and 30 m sprint speed were only altered (p < 0.01) following RC (0.36, Δ% = 41.52%; -34 s, Δ% = -9.29%, for flight time and -1.23 m, -8.72%, for jump height; 0.49 s, Δ% = 6.48, respectively) when compared to BL. In conclusion, one- or five-night exposure to smartphones disturbed the children's sleep quality and their performance, with more pronounced effects following RC.

Gaming in Pandemic Times: An International Survey Assessing the Effects of COVID-19 Lockdowns on Young Video Gamers' Health

The onset of COVID-19 coincided with the peak growth of video game usage, with 2.7 billion gamers in 2020. During the pandemic, gaming and streaming platforms offered an entertaining, social, and safe alternative to recreation during severe lockdowns and social isolations. This study aimed to examine the impact of the COVID-19 pandemic on health-related outcomes in self-proclaimed video gamers based on the type of lockdown experienced and to discuss the potential role of video games during times of preventive lockdown measures. This was a cross-sectional international survey constructed by two academic institutions, NYIT (NY, USA) and McGill University (Montreal, Canada), and Adamas Esports (BC, Canada). The survey consisted of questions including demographics, multiple choice, ratings, and Likert scales relating to the periods prior to and during the COVID-19 lockdowns. There were 897 respondents from North America (72.7%), Europe (10.9%), Asia (4.9%), and other countries (11.5%), with a mean age of 22 years. Significant increases in game time were reported in casual and competitive gamers during the first months of the pandemic. The level of gaming, type of lockdown, and physical activity level prior to the pandemic were examined as potential moderating factors. Significant increases in sedentary behaviors (video game time and sitting time) were observed, while physical activity levels remained unchanged in most participants, regardless of the type of lockdown. Sleep time, but not sleep quality, increased, while mental health exhibited opposing effects, influenced by the type of lockdown and gaming competition levels. Video games, when played moderately, could offer a cost-effective, safe strategy to promote socialization and mental health and improve the overall well-being of the non-gaming and gaming population during pandemic times when strict lockdowns are in place.

Depression and lifestyle: Focusing on nutrition, exercise, and their possible relevance to molecular mechanisms

Accumulating evidence has suggested the important role of lifestyle factors in depressive disorder. This paper aimed to introduce and outline recent research on epidemiological and intervention studies on lifestyle-related factors in depressive disorder with a special focus on diet. Evidence on exercise, sleep. and related behaviors is also described. Here, findings from meta-analytic studies are emphasized and related studies by the author's research group are introduced. Dietary factors that increase the risk of the illness include energy overload, skipping breakfast, unhealthy diet styles such as Western diet, inflammation-prone diet, and high consumption of ultraprocessed food (UPF). Nutritional imbalances such as inadequate intake of protein, fish (Ω3 polyunsaturated fatty acids), vitamins (folate and vitamin D), and minerals (iron and zinc) increases the risk of depression. Poor oral hygiene, food allergy, addiction to alcohol, and smoking constitute risk factors. Sedentary lifestyle and increased screen time (e.g. video games and the internet) confer the risk of depression. Insomnia and disturbed sleep-wake rhythm are also involved in the pathogenesis of depression. There is accumulating evidence at the meta-analysis level for interventions to modify these lifestyle habits in the protection and treatment of depressive disorder. Main biological mechanisms of the link between lifestyle factors and depression include monoamine imbalance, inflammation, altered stress response, oxidative stress, and dysfunction of brain-derived neurotrophic factor, although other players such as insulin, leptin, and orexin also play a role. To increase resilience to modern stress and ameliorate depression through modification of lifestyle habits, a list of 30 recommendable interventions is presented.

Factors associated with melatonin use in child sleep disturbance: A survey of Australian parents

OBJECTIVE

Sleep disturbances are prevalent in Australian children and cause a significant amount of stress to both children and their parents. If sleep disturbances are left untreated, they can result in detrimental consequences to both child and parental wellbeing. While behavioural interventions are recognised as the gold standard treatment for paediatric insomnia, there is a growing use of melatonin from both prescription and non-prescription sources in paediatrics. However, empirical research on the efficacy and safety of melatonin for children is sparse, conflicting, and inconsistent. This first Australian study aimed to investigate correlates of melatonin use in a sample of children with sleep disturbance in Australia and assess whether melatonin is being administered to children contrary to Therapeutic Goods Administration Guidelines.

METHODS

An exploratory online study was undertaken with 318 parents of Australian children with sleep disturbance (95.30% females). Logistic regression, mediation and descriptive analysis were conducted.

RESULTS

As hypothesised, higher parental stress, older child age, and a diagnosis of ADHD were significantly associated with melatonin use in this sleep disturbed sample. Other potential correlates such as financial stress, number of household dependents, child sleep disturbance, and autism were not significantly associated with melatonin use in adjusted analyses.

CONCLUSION

Findings show off-label melatonin use in children with sleep disturbance is prevalent. For the first time, this study showed an indirect path linking child sleep disturbances with melatonin use via parental stress. Overall, while the safety of melatonin use remains unknown, there is a clear need to mitigate parental stress to minimise potentially unmonitored and improper use of melatonin in children.

Light as a Modulator of Non-Image-Forming Brain Functions—Positive and Negative Impacts of Increasing Light Availability

Light use is rising steeply, mainly because of the advent of light-emitting diode (LED) devices. LEDs are frequently blue-enriched light sources and may have different impacts on the non-image forming (NIF) system, which is maximally sensitive to blue-wavelength light. Most importantly, the timing of LED device use is widespread, leading to novel light exposure patterns on the NIF system. The goal of this narrative review is to discuss the multiple aspects that we think should be accounted for when attempting to predict how this situation will affect the NIF impact of light on brain functions. We first cover both the image-forming and NIF pathways of the brain. We then detail our current understanding of the impact of light on human cognition, sleep, alertness, and mood. Finally, we discuss questions concerning the adoption of LED lighting and screens, which offer new opportunities to improve well-being, but also raise concerns about increasing light exposure, which may be detrimental to health, particularly in the evening.

Associations Between Multidimensional Sleep Health Parameters and Adolescents' Self-reported Light Exposure in the Free-living Environment

The objective of this study was to characterize the associations between light exposure in the free-living environment and multiple dimensions of sleep health of typically developing adolescents. Fifty-six (29 girls, 27 boys) typically developing adolescents (mean age = 13.59, SD = 0.89, range = 12-17 years) participated. For six consecutive nights, sleep was assessed in the home environment using actigraphy. During the same period, participants were asked to fill out a daily sleep log and a daily light exposure log, and to complete questionnaires regarding their alertness and subjective sleep satisfaction. Longer self-reported exposure to daylight in the morning was associated with longer objectively measured sleep duration. Longer self-reported exposures to electronic devices in the evening were associated with later objectively measured sleep onset and offset times, shorter sleep duration, and greater day-to-day sleep variability. Longer morning exposure to outdoor light was associated with a longer sleep duration. Self-reported light exposure was not associated with sleep satisfaction, alertness/sleepiness, or sleep efficiency. Among the covariates, circadian preference accounted for the highest percentage of variance. Adolescents' sleep health is associated with the self-reported duration of exposure to daylight in the morning and to electronic devices in the evening.

Screen use, sleep duration, daytime somnolence, and academic failure in school-aged adolescents

In this study, we examined the relationship between screen time use, sleep characteristics, daytime somnolence, and academic performance in school-aged adolescents. We surveyed 1,257 12- to 18-year-old adolescents attending 52 schools in urban or suburban areas of Argentina. We recorded the daily exposure to various screen-based activities, including video- and online-gaming, social media, TV or streaming. Screen time and device type in the hour before bedtime, sleep patterns during weekdays and weekends, somnolence (Pediatric Daytime Sleepiness Scale score), and grades in language and mathematics were also assessed. Structural Equation Modelling was used to identify a path connecting the latent variables. Results are expressed as standardized regression weights (srw). Missing data were present in 393 subjects, and thus the final sample consisted of 864 complete responses. Daytime somnolence (i.e., PDSS score ≥ 15) was observed in 614 participants (71%), and academic failure (i.e., grades < 7/10) in 352 of them (41%). Time spent using video gaming consoles was negatively associated with sleep duration (srw = -0.22, p<0.01) and positively connected with daytime somnolence (srw = 0.11, p<0.01). Use of mobile devices was associated with lower academic performance (srw = -0.11, p<0.01). Sleep duration was inversely related to daytime somnolence (srw = -0.27, p<0.01), which was in turn negatively associated with academic performance (srw = -0.18, p<0.05). Bedtime computer use did not influence any outcome. In summary, among adolescents, screen use adversely affected nighttime sleep, daytime somnolence, and academic performance. These findings call for the implementation of educational public campaigns aimed at promoting healthy sleep and reducing screen exposure among adolescents.

[Sleepiness among adolescents: etiology and multiple consequences]

Over the past century a dramatic decline in sleep duration among adolescents, such as more than one hour of sleep loss per night, has been reported. A debt in sleep duration could lead to sleep deprivation, a major risk factor associated with daytime sleepiness. Sleepiness refers to the inability to maintain an adequate level of alertness during the day which may result in more or less being able to control falling asleep at inappropriate times. This literature review updates on sleepiness regarding its characteristics, etiology and consequences on adolescents. Studies revealed that from 25 % to 78 % of adolescents had reported sleepiness. Its manifestations may include heavy lids, yawns, difficulties to concentrate and emotional irritability. In addition, while it is recommended that adolescents under 18 years-old should sleep from eight to ten hours a night, only 63 % of them actually do so. The etiology of sleep deprivation and sleepiness in this population can be explained by various biological and societal factors. First, the sleep-wake cycle of adolescents shows a biological shift from the beginning of pubertal maturation, described as a perfect storm. It refers to a social jetlag by going to sleep and waking up later and accumulating a sleep debt during weekdays which they try to reimburse during weekends. This phenomenon can be explained by physiological changes such as a slower accumulation of sleep pressure. In addition to this perfect storm, environmental and societal factors contribute to the social jetlag and reduce sleep duration in adolescents. Screen exposure before bedtime can delay sleep and wake onset, which is a risk factor for sleeping debt. Substance use such as caffeine, cigarettes or electronic vaporizer, ADHD or freely available medication, alcohol, cannabis use or drug consumption could further disrupt sleep-wake cycle by stimulating, depressing or otherwise disrupting the central nervous system. Early, before 8:30 am, class start times have been associated with chronic sleep deprivation, higher level of sleepiness and delayed melatonin peak secretion. Adolescents working or doing extracurricular occupations for more than 20hours a week are more at risk for reduced sleep duration and sleepiness. Parental supervision about sleep during the weekdays were associated with more appropriate bedtime. Adolescents from low socio-demographic characteristics and from minority ethnic groups have reported displaying a shorter sleep duration. Finally, sleep disorders of a physiological origin such as narcolepsy, sleep apnea or restless legs syndrome, may explain the sleep deprivation and sleepiness. Sleep deprivation and sleepiness in adolescents have consequences on their health. Cognitive functioning, such as problem solving, attention or memory, as well as school performance, can be compromised by sleep deprivation and sleepiness. At the psychological level, adolescents reporting sleepiness are more prone to display mental health problems: associations were found between sleepiness and subjective perception of depression, anxiety, somatic complaints as well as with antisocial behaviors. Finally, 68 % of 16 year-old adolescents reported they drove a car, and the reported sleepiness could lead to road accidents due to reduced attentional functioning, reaction time and decision-making abilities. In the United-States, from 7 % to 16.5 % of deadly accidents were related to driving while drowsy. Highlighting etiology and problems associated with sleep deprivation and sleepiness in adolescents could guide researchers and clinicians towards the development of possible interventions. Public health measures and knowledge transfer programs regarding modifiable psychosocial and societal factors associated with sleep-wake bioregulation could increase awareness in parents as well as in political and societal decision makers.

Moderate-Vigorous Physical Activity, Screen Time and Sleep Time Profiles: A Cluster Analysis in Spanish Adolescents

The study had two aims: (1) To classify the adolescents according to their levels of moderate-vigorous physical activity, screen time and sleep time, and (2) to analyze, in a descriptive and correlational manner, the profiles of moderate-vigorous physical activity, screen time and sleep time of each cluster according to the sex and grade of the adolescents. The study design was cross-sectional, with descriptive and correlational analysis. The sample consisted of 663 adolescents in Compulsory Secondary Education from Soria (Spain). The Four by One-Day Physical Activity Questionnaire was used to measure levels of physical activity, screen time and sleep time. The results showed that the young people had an average of 67.99 ± min/day of moderate-vigorous physical activity, 112.56 min/day of screen time and 548.63 min/day of sleep time. Adolescents were classified into three clusters according to their levels of physical activity, screen time and sleep time (F_MANOVA (6,1318) = 314.439; p ≤ 0.001; β = 1; f = 1.177). In conclusion, only 28.21% of the young people accomplished the recommendations for physical activity practice, screen time and sleep time. Moreover, these results vary according to the sex and grade of the adolescents.

Changes in Sleep Satisfaction of Korean Adolescents in the Pre- and Post-COVID-19 Eras and Its Effects on Health Behaviors

Adolescence is a crucial period for cognitive and psychological development and physical maturation. During this period, hormonally influenced circadian rhythms lead to reduced hours of sleep, and it is important to determine whether sleep quality is sufficient for fatigue relief. Non-face-to-face classes during coronavirus disease-2019 (COVID-19) potentially affected adolescents' sleep quality, psychological state, amount of physical activity, smoking, alcohol consumption, and internet (smartphone) use. We investigated the effects of the COVID-19 situation on adolescents' sleep satisfaction and its relation to the aforementioned factors. Data of 109,281 adolescents collected via an online survey, conducted from 3 June 2019 to 12 July 2019 and from 3 August 2020 to 13 November 2020, were analyzed. Health status comparison between the satisfactory and unsatisfactory sleep groups yielded significant results (odds ratio [OR] = 1.10, confidence interval [CI] = 1.04-1.17) for 2020. In both groups, perceived health was worse in 2019 than in 2020 (OR = 2.72, CI = 2.53-2.92). During COVID-19, non-face-to-face classes increased adolescents' sleep satisfaction. Their psychological state improved, while amount of physical activity (muscle-strengthening exercises), average weight, and internet (smartphone) use increased. Smoking and alcohol consumption decreased.

Promoting Sleep Duration in the Pediatric Setting Using a Mobile Health Platform: A Randomized Optimization Trial

Objective

Determine the optimal combination of digital health intervention component settings that increase average sleep duration by ≥30 minutes per weeknight.

Methods

Optimization trial using a 25 factorial design. The trial included 2 week run-in, 7 week intervention, and 2 week follow-up periods. Typically developing children aged 9-12y, with weeknight sleep duration <8.5 hours were enrolled (N=97). All received sleep monitoring and performance feedback. The five candidate intervention components (with their settings to which participants were randomized) were: 1) sleep goal (guideline-based or personalized); 2) screen time reduction messaging (inactive or active); 3) daily routine establishing messaging (inactive or active); 4) child-directed loss-framed financial incentive (inactive or active); and 5) caregiver-directed loss-framed financial incentive (inactive or active). The primary outcome was weeknight sleep duration (hours per night). The optimization criterion was: ≥30 minutes average increase in sleep duration on weeknights.

Results

Average baseline sleep duration was 7.7 hours per night. The highest ranked combination included the core intervention plus the following intervention components: sleep goal (either setting was effective), caregiver-directed loss-framed incentive, messaging to reduce screen time, and messaging to establish daily routines. This combination increased weeknight sleep duration by an average of 39.6 (95% CI: 36.0, 43.1) minutes during the intervention period and by 33.2 (95% CI: 28.9, 37.4) minutes during the follow-up period.

Conclusions

Optimal combinations of digital health intervention component settings were identified that effectively increased weeknight sleep duration. This could be a valuable remote patient monitoring approach to treat insufficient sleep in the pediatric setting.

Association between visual impairment and sleep duration in college students: A study conducted in UAE and Lebanon

Objective: To examine whether self-reported sleep duration and visual impairment were associated among College students. Participants: Students (n = 1002, age 17-35 years) from Lebanon and the United Arab Emirates. Methods: Students were asked to complete a validated questionnaire between October 2018 and May 2019. The questions were related to sociodemographics, lifestyle characteristics, visual impairment status, sleeping pattern, mobile-phone use and chronic conditions. Results: 18.3% of the respondents reported to suffer from visual impairment. Among them, 72.7% were females (p < .001), 65% admitted to frequently use mobile phones before sleeping (p < .001), 54.6% reported to sleep less than 7 h (p = .008) and 71.6% reported to suffer from sleep disturbances (p = .05). Visual impairment was associated with poor sleep quality (p < .001), mobile phone use before sleeping (p < .01) and daily stress (p < .05). Conclusion: Visual impairment in college students is associated with short sleep duration, mobile phone use before sleeping and stress level.

What's "app"-ning to adolescent sleep? Links between device, app use, and sleep outcomes

This study investigated the associations between adolescent evening use of technology devices and apps, night time sleep, and daytime sleepiness. Participants were 711 adolescents aged 12-18 years old (46% Female, M_age = 15.1, SD = 1.2). Time spent using technology devices and apps in the hour before bed, and in bed before sleep onset, was self-reported. Participants additionally completed a questionnaire about their sleep on school nights and next day sleepiness. In the hour before bed, 30 min of phone use was associated with a 9-min delay in bedtimes. Thirty minutes spent using laptops, gaming consoles, and watching YouTube was associated with later lights out times of 9 min, ∼16 min and ∼11 min respectively, while watching TV was associated with a 9 min earlier lights out times. Using gaming consoles and watching YouTube were associated with greater odds of receiving insufficient sleep (≤7 h TST). In bed before sleep onset, 30 min spent using laptops, phones, iPad/tablets, and watching YouTube were linked with later lights out times of ∼7 min for phones and laptops, 9 min for iPad/tablets, and ∼13 min for YouTube. Watching Netflix was associated with greater daytime sleepiness. YouTube at this time point was associated with increased odds of sleeping ≤7 h on school nights. Adolescents are engaging with a wide range of technology devices and apps in the evenings. However, certain devices and apps (e.g., phones, laptops, gaming and YouTube) might lead to more negative sleep outcomes for adolescents on school nights compared to others.

Cascading bidirectional influences of digital media use and mental health in adolescence

A substantial portion of critical adolescent development is occurring within digital environments. However, certain individual differences may lead adolescents to use digital media in diverse ways. In this chapter we suggest that the way teens use digital media influences how digital media affects their mental health. Further, we propose a model in which these influences, in the context of ongoing development, may have feedback effects on how digital media is subsequently used, thus resulting in a self-perpetuating cycle. Our model suggests that certain developmental risk/protective factors and maladaptive/adaptive digital media behaviors likely perpetuate each other in a cyclical manner each serving to maintain and/or escalate the other. We discuss existing evidence of these processes in psychosocial, identity, incentive processing, and physical health development. Future research focusing on individual differences and self-reinforcing digital media behaviors that manifest these feedback loops may portray a more complete picture of cascading digital media influences across adolescent development.

What time do you plan to sleep tonight? An intense longitudinal study of adolescent daily sleep self-regulation via planning and its associations with sleep opportunity

BACKGROUND

Most adolescents are sleep deprived on school days, yet how they self-regulate their sleep-wake behaviours is poorly understood. Using ecological momentary assessment, this intense longitudinal study explored patterns of adolescents' daily bedtime and risetime planning and execution, and whether these behaviours predicted sleep opportunity.

METHODS

Every afternoon, for 2 school weeks and the subsequent 2 vacation weeks, 205 (54.1% female, 64.4% non-White) adolescents from year 10 to 12 (M ± SD_age  = 16.9 ± 0.9) reported their plans for bedtime (BT) that evening, and for risetimes (RT) the following day. Actual daily sleep was measured via actigraphy and sleep diary.

RESULTS

Some adolescents never planned bedtime (school 19.5%, non-school 53.2%) or risetime (school 1.5%, non-school 24.4%). More adolescents planned consistently (≥75% of days) on school (BT = 29.9%, RT = 61.3%) compared to non-school nights (BT = 3.5%, RT = 2.5%). On average, adolescents went to bed later than planned, with longer delays on non-school (71 min) compared to school nights (46 min). Of those who executed their plans within ≤15 min, more did it consistently (≥75% of days) on school (BT = 40.9%, RT = 67.7%) than on non-school nights/days (BT = 29.7%, RT = 58.6%). Mixed effects models utilizing daily data, controlling for sex, race, and study day, showed that bedtime planning predicted longer time in bed (TIB; p < .01) on school and shorter TIB on non-school nights (p < .01); and greater delay in actual (compared to planned) BT predicted shorter TIB (p < .001).

CONCLUSIONS

Adolescents may require support during the transition from parent-controlled to autonomous sleep self-regulation. Bedtime planning on school nights and going to bed as planned are two modifiable sleep regulatory behaviours that are protective and potential therapeutic targets for increasing sleep opportunity in adolescents.

Prevalence and trends in Australian adolescents' adherence to 24-hour movement guidelines: findings from a repeated national cross-sectional survey

BACKGROUND

24-hour movement guidelines recommend a healthy balance of high levels of physical activity, low levels of sedentary behaviour and appropriate sleep duration each day. At present, surveillance data on how Australian adolescents are performing against these guidelines are lacking. This study aims to describe the extent to which Australian secondary school students are adhering to the physical activity, sedentary recreational screen time and sleep duration recommendations outlined in the national 24-hour movement guidelines for children and young people. It also examines whether there are socio-demographic differences in levels of compliance and if there have been significant changes in these behaviours over time.

METHODS

A repeated national cross-sectional survey of students in grades 8 to 11 (ages 12-17 years) was conducted in 2009-2010 (n=13,790), 2012-2013 (n=10,309) and 2018 (n=9,102). Students' self-reported physical activity, screen time and sleep behaviours were assessed using validated instruments administered in schools via a web-based questionnaire.

RESULTS

In 2018, around one in four students (26%) did not meet any of the 24-hour movement guidelines, while only 2% of students met all three. Adherence to the sleep duration recommendation was highest (67%), with substantially smaller proportions of students meeting the physical activity (16%) and screen time (10%) recommendations. Differences in adherence by sex, grade level and socio-economic area were apparent. Students' compliance with the screen time recommendation has declined over time, from 19% in 2009-2010 to 10% in 2018. However, there has been no significant change in the proportion meeting the physical activity (15% in 2009-2010 cf. 16% in 2018) and sleep duration (69% in 2009-2010 cf. 67% in 2018) recommendations. Compliance with all three guidelines has remained very low (<3%) across each survey round.

CONCLUSIONS

There is considerable scope to improve Australian adolescents' physical activity and sedentary behaviours in line with the national 24-hour movement guidelines. Policy proposals and environmental interventions, particularly those focused on replacing sedentary screen time with physical activity (e.g. promotion of active commuting to/from school), are needed to better support Australian adolescents in meeting the 24-hour movement guidelines.

Electronic media use and sleep in children and adolescents in western countries: a systematic review

Background

Sleep is essential for child and adolescent health and well-being. There is an increasing interest in whether electronic media use affects children and young adolescents’ sleep. Prior reviews have focused on a school-aged population. Moreover, it is crucial that research continuously addresses the processes of technology and media use and the implication on sleep. This systematic review examines the evidence of electronic media use related to sleep among 0–15-year-olds.

Methods

Searches were carried out in four databases (CINAHL, Web of Science, EMBASE, and Medline). Inclusion criteria included age ≤ 15 years, and intervention, cohort, or cross-sectional studies from western countries. Methodological quality was rated using the Quality Assessment Tool for Quantitative Studies by two independent reviewers. Data was extracted using a standardized data extraction form. Synthesis was done by summarizing results across studies by age groups of 0–5, 6–12, and 13–15 years within four sleep domains: Bedtime and sleep onset; Sleep quality; Sleep duration; Daytime tiredness.

Results

The search identified 10,719 unique studies, of which 109 fulfilled inclusion and exclusion criteria and were assessed for methodological quality. In total, 49 studies were included in the review. The study designs were randomized controlled trials (n = 3), quasi-experimental studies (n = 2), prospective cohort studies (n = 15), and cross-sectional studies (n = 29). Evidence for an association between electronic media use and sleep duration was identified, with stronger evidence for 6–15-years-olds than 0–5-year-olds. The evidence for a relationship between electronic media use and other sleep outcomes was more inconclusive. However, for 6–12-year-old children, there was evidence for associations of electronic media use with delayed bedtime and poor sleep quality. For 13–15-year-olds, there was evidence for associations between screen time and problems falling asleep, and between social media use and poor sleep quality.

Conclusions

Overall, electronic media use was generally associated with shorter sleep duration in children and adolescents. Studies with stronger research design and of higher quality are needed to draw solid conclusions about electronic media’s impact on other sleep outcomes. Public awareness and interventions could be promoted about the potential negative impact on children’s sleep of electronic media devices that are used excessively and close to bedtime.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11640-9.

Contemporary Variables that Impact Sleep and Development in Female Adolescent Swimmers and Gymnasts

The effects of sleep on elite athletes in late adolescence and early adulthood have been well documented in a myriad of sports. However, there is underrepresentation of pre-pubertal and young female adolescent athlete research between the ages of 11-17, and specifically female gymnast and swimmers. Neglecting to understand how high energy demand at a young age relates to sleep and restoration may lead to developmental ramifications for this group, as they display physiological dysfunctions like delayed puberty, amenorrhea and are at risk for the female athlete triad or components of the triad. This review aims to summarize the contemporary variables of blue light emitting screens, social media, and caffeine on quality and quantity of sleep in young athletes while identifying gaps in the literature on how these factors impact the target group of young female swimmers and gymnasts.  The implications of this work include sleep hygiene recommendations for increasing duration and quality of sleep, as well as future research with respect to electronic device usage, social media participation, caffeine consumption, and sport engagement in female early adolescent athletes.

Gender moderates the relationship between media use and sleep quality

With high screen time and poor sleep commonly reported in adolescents, it is important to more fully understand how screen time impacts sleep. Despite similar overall screen times, male and female media preferences and usages differ, making it critical to determine if different domains of screen time differentially affect sleep quality. The present study examined whether differing amounts and domains of screen-based media vary in impact on sleep quality of 16-year-old male and female adolescents over a 3-month period. A total of 98 adolescents (mean [SD] age 16.27 [0.29] years; 51% female) completed two online surveys spaced 3 months apart and comprised of well-validated self-reported measures of sleep quality, media usage, and depressive symptoms. The various domains of media were categorised into screen-based media with little-to-no peer-to-peer interaction involved (video-only) and screen-based media with interaction a predominant component to the usage (peer-to-peer interaction-involved). Self-reported sleep quality decreased across the 3-month study period. Gender moderated the effect of interactive screen time on sleep quality 3 months later, with interactive screen time associated with better sleep quality in males, but remaining poorer in females. Screen time competes with sleep time and may do so differentially depending on the media domain. Compared to females, interactive components of screen time may lessen worsening sleep quality over time in males. Understanding the relationships among screen time, its content, age, and gender may inform guidelines for educators, parents, and adolescents to help improve sleep quality of adolescents.

Trait-like nocturnal sleep behavior identified by combining wearable, phone-use, and self-report data

Using polysomnography over multiple weeks to characterize an individual’s habitual sleep behavior while accurate, is difficult to upscale. As an alternative, we integrated sleep measurements from a consumer sleep-tracker, smartphone-based ecological momentary assessment, and user-phone interactions in 198 participants for 2 months. User retention averaged >80% for all three modalities. Agreement in bed and wake time estimates across modalities was high (rho = 0.81–0.92) and were adrift of one another for an average of 4 min, providing redundant sleep measurement. On the ~23% of nights where discrepancies between modalities exceeded 1 h, k-means clustering revealed three patterns, each consistently expressed within a given individual. The three corresponding groups that emerged differed systematically in age, sleep timing, time in bed, and peri-sleep phone usage. Hence, contrary to being problematic, discrepant data across measurement modalities facilitated the identification of stable interindividual differences in sleep behavior, underscoring its utility to characterizing population sleep and peri-sleep behavior.

Headache in Children and Adolescents

PURPOSE OF REVIEW

This article reviews the approach to a child or adolescent with headache, the criteria for common diagnoses, and the evidence base for treatments.

RECENT FINDINGS

The guidelines for acute and preventive treatment of migraine were updated in 2019. These guidelines summarize the available evidence and outline the questions that should be addressed in future research. The US Food and Drug Administration (FDA) approval of several new classes of drugs and devices to treat adult migraine in the past few years has resulted in ongoing or planned pediatric trials.

SUMMARY

Headache is a common symptom in children, and it is important to take a detailed history and perform a thorough physical examination to make the diagnosis. Nearly 1 in 10 children experience recurrent headaches due to migraine, which cause significant impairment in school performance and quality of life. The acute and preventive treatments that are currently available will help at least two-thirds of children with migraine, and several trials of new therapies offer hope for the future.

Social Media and Mental Health Among Early Adolescents in Sweden: A Longitudinal Study With 2-Year Follow-Up (KUPOL Study)

PURPOSE

The aim of this study is to assess the longitudinal associations between the frequency of social media use and symptoms of mental ill-health among Swedish adolescents.

METHODS

Data came from KUPOL, a Swedish school-based longitudinal cohort accrued in 101 participating schools in 8 regions of Sweden. The study sample consisted of 3,501 adolescents in grade 8 (14-15 years, 51.5%, n = 1,765 girls) followed for 2 consecutive years. Daily social media use was measured as weighted average of self-reported use in weekdays and weekend days. Mental health was measured with the Strength and Difficulties Questionnaire (SDQ). A Random-Intercept Cross-Lagged Panel Model was applied to distinguish between-person from within-person associations between social media use and symptoms of mental ill-health.

RESULTS

Median SDQ score at baseline was 9 (interquartile range [IQR] 6-14). Median social media use was 1.7 hours at baseline (interquartile range .6-3.0) and increased over the 3-year period. Adolescents with more social media use also reported higher SDQ scores, B (95% confidence interval [CI]) = 2.40 (2.03-2.77). On a within-person level, no cross-lagged associations were found between changes in social media use and subsequent changes in symptoms of mental ill-health after 1 year, B (95% CI) = .02 (-.12 to .16) or vice versa B (95% CI) = .00 (-.02 to .02). Weak cross-sectional associations were found between changes in social media use and concurrent changes in symptoms of mental ill-health, B (95% CI) = .24 (.00-.48).

CONCLUSIONS

Adolescents with higher use of social media report more symptoms of mental health problems, but there is no evidence for a longitudinal association between increased use and mental health problems. This suggests that social media may be rather an indicator than a risk factor for symptoms of mental ill-health.

Sleep Assessment for Sleep Problems in Children

The breadth of childhood sleep problems is broad and can be associated with biologic, psychiatric, behavioral, social, and environmental processes. Unrecognized childhood sleep problems may threaten daytime behaviors and negatively impact school and psychosocial functioning. Left unattended, overall child biopsychosocial development may be impaired. Thus, identifying and addressing sleep problems has potential to optimize childhood health, development, and overall well-being. Nurses need to be cognizant of detrimental impacts of child sleep deprivation and advocate for appropriate sleep assessments while offering sleep education to parents and children.

Identifying electronic-sport athletes' sleep-wake cycle characteristics

Organized electronic-sport competitions (e-Sport) is related to several health problems, including sleep disorders. The objective of this study was to evaluate the characteristics of the sleep-wake cycle of League of Legends (LoL) athletes during their pre-training, training, pre-competition, and competition routines. Twenty male elite LoL players completed the questionnaires related to sleep pattern (Pittsburgh Sleep Quality Index), sleepiness (Epworth Sleepiness Scale), and chronotype (Morningness-Eveningness Questionnaire), and they wore an actigraph for 7 days. Pre-training and pre-competition assessments were carried out by questionnaires (n = 20) and training and competition assessments by actigraph (n = 16). The chronotype that most Eathletes presented was a moderately evening type. They presented a poor sleep quality and were borderline for excessive daytime sleepiness. Sleep onset and offset times were significantly prolonged during the competition condition (t = 2.11, p < .05; t = 2.51, p < .05). Correlations showed a relationship between PSQI and Sleepiness in the pre-training and pre-competition conditions (r = 0.50, p = .02) and chronotype with sleep onset (r = 0.61, p = .01), total sleep time (r = 0.55, p = .02), and time awake (r = 0.49, p = .04) in the competition condition. Linear regression analysis indicated associations between the PSQI and sleepiness (25%; p = .02) during pre-training and pre-competition. During the competition there were associations between chronotype and sleep onset (37%; p = .01), chronotype and time awake (24%; p = .04), and chronotype and TST (30%; p = .02). In general, the findings support the conclusion that LoL athletes presented an altered sleep pattern during their training routines.

Sleep and Mental Health Disturbances Due to Social Isolation during the COVID-19 Pandemic in Mexico

The coronavirus disease (COVID-19) that broke out in China in December 2019 rapidly became a worldwide pandemic. In Mexico, the conditions requiring the declaration of a sanitary emergency were reached by the last week of March 2020, and health authorities' limited mobility and imposed social isolation were the main strategies to keep the virus from spreading. Thus, daily living conditions changed drastically in a few days, generating a stressful situation characterized by an almost complete lack of mobility, social isolation, and forced full-time interactions with family members. Soon, complaints of sleep disturbances, anxiety, and symptoms of depression were reported. The present study reports the results of an online survey performed during the first two months of isolation. Questionnaires exploring sleep disturbances, anxiety, and depression were sent to people who responded to an open invitation. A total of 1230 participants filled out the sleep questionnaire, 812 responded to the anxiety questionnaire, and 814 responded to the depression questionnaire. Both men and women reported poor sleep quality, but women showed a higher proportion (79%) than men (60%); young women were more likely to be affected by social isolation. Concerning anxiety and depression, both sexes reported high similar symptoms. These data suggest that stressful conditions related to social isolation and the economic uncertainty caused by the pandemic may induce mental health disturbances, which may become worse with sleep restriction.

Prospective associations between pre-sleep electronics use and same-night sleep in healthy school-aged children

Electronic devices are routinely associated with adverse effects on sleep; however, prospective studies among healthy children are unavailable. This study examined relationships among specific and total electronic device use within the hour before bed and same-night sleep patterns among 55 pre-pubertal children (7-11 years) without medical, psychiatric or sleep disorders. Sleep was assessed via subjective reports and actigraphy for 5 weeknights and pre-bed device use was assessed via daily diary. Neither total devices use nor any single type predicted sleep parameters the same night. The extent to which pre-bed electronics use impacts sleep in healthy children requires further investigation.

Update on school-based sleep education programs: how far have we come and what has Australia contributed to the field?

OBJECTIVE

School-based sleep education programs help to promote sleep health information to many children and adolescents. The aim of this systematic review was to identify and describe school-based sleep education programs, to update previous reviews and identify recent advances and improvements in this field worldwide.

METHODS

Four electronic databases were searched. Eligibility criteria included children aged 5-18 years, sleep education intervention conducted in a school setting, and at least one pre-post-measure of a sleep variable.

RESULTS

A total of 32 articles met eligibility criteria with Australian sleep researchers constituting ∼ one quarter of these studies. Studies dated from 2007 to 2020 with sample sizes ranging from 9 to 3713 students. The majority of participants were high school students and predominantly female. Education programs generally took 4-6 weeks and content was consistent across studies. Overall, exposure to sleep education increased sleep knowledge, however changes in sleep behaviour variables and secondary outcome variables (eg, mental health; cognitive function; sleep hygiene practices) presented varied results. Studies conducted since 2015 were more likely to be randomised controlled trials and to include more interactive, online designs utilising innovative content such as mindfulness.

CONCLUSIONS

An exponential growth in school sleep education programs was identified since 2016. Future studies should consider utilising objective sleep measures, longer-term follow-ups, innovative delivery methods, and stronger attempts at implementing a knowledge-to-action approach for more sustainable programs.

The intersection of COVID-19, school, and headaches: Problems and solutions

OBJECTIVE

To equip clinicians with recommendations specific to concerns related to the novel coronavirus disease 2019 (COVID-19), which impact the physical, emotional, and social health of youth with headache disorders.

BACKGROUND

COVID-19 has affected societies on a global scale including children and youth with chronic headache disorders. Many concerns are predicted to arise in the 2020-2021 school year, whether classes are conducted in-person or virtually.

METHODS

Clinical impressions were combined with a review of the literature, although limited due to the recent nature of this issue.

RESULTS

We describe recommendations to support caregivers and youth as they face changes expected with the return to school in the fall of 2020.

CONCLUSION

Although there are significant concerns for caregivers and youth with migraine given the context of changes related to the pandemic, there are many recommendations that can help minimize exacerbations of the physical, emotional, and social health of youth with chronic migraine.

Migraine and Sleep in Children: A Bidirectional Relationship

Migraine and sleep disorders in children exhibit a bidirectional relationship. This relationship is based on shared pathophysiology. Migraine involves activation of the trigeminal vascular system. Nociceptive neurons that innervate the dura release various vasoactive peptides. Calcitonin gene-related peptide is the most active of these peptides. Neural pathways that are involved in sleep generation are divided into those responsible for circadian rhythm, wake promotion, non-rapid eye movement, and rapid eye movement sleep activation. Sleep state switches are a critical component of these systems. The cerebral structures, networks, and neurochemical systems that are involved in migraine align closely with those responsible for the regulation of sleep. Neurochemical systems that are involved with both the pathogenesis of migraine and regulation of sleep include adenosine, melatonin, orexin, and calcitonin gene-related peptide. Sleep disorders represent the most common comorbidity with migraine in childhood. The prevalence of parasomnias, obstructive sleep apnea, and sleep-related movement disorders is significantly greater in children migraineurs. Infantile colic is a precursor of childhood migraine. Treatment of comorbid sleep disorders is important for the appropriate management of children with migraine. Sleep-based behavioral interventions can be of substantial benefit. These interventions are particularly important in children due to limited evidence for effective migraine pharmacotherapy.

Lights Out! The Body Needs Sleep: Electronic Devices and Sleep Deficiency

Sleep hygiene in children and young adults has been a topic of interest in scientific studies geared towards understanding metabolism, mental health, neuroscience, and in reference to the quality of life. There are multiple factors that may contribute to poor sleep hygiene in children, many of these include environmental factors and genetic components. This review article will pay particular focus on environmental factors which as of late, have been increasing contributors to poor sleep hygiene in children. Ultimately, these factors lead to unhealthy habits that transform into unhealthy lifestyles in younger populations worldwide. This article will concentrate on studies conducted in the United States, Canada, Switzerland, Norway, and Belgium. In each of these studies, children who are exposed to increased use of electronic devices such as tablet computers, television, desktop computers, and other mobile devices during the late hours of the night, are evaluated and assessed for changes in their rapid eye movement (REM) sleep cycles, sleep latency, body mass index (BMI) levels, obesity risks, and other neurologic deficits which may be linked to this inappropriate use of technology during peak hours of the night. We will understand the physiology behind how sleep works, the events leading up to sleep, and disruptions that can occur, and their devastating effects.

The challenges of adolescent sleep

Sleep is vital for our physical, emotional and cognitive health. However, adolescents face many challenges where their sleep is concerned. This is reflected in their sleep patterns including the timing of their sleep and how much sleep they achieve on a regular basis: their sleep is characteristically delayed and short. Notably, insufficient sleep is associated with impairments in adolescent functioning. Endogenous and exogenous factors are known to affect sleep at this age. Alterations in the bioregulation of sleep, comprising the circadian timing system and the sleep/wake homeostatic system, represent the intrinsic mechanisms at work. Compounding this, environmental, psychosocial and lifestyle factors may contribute to shortened sleep. This review discusses the amount of sleep gained by adolescents and its implications, the challenges to adolescent sleep and the interventions introduced in an effort to prioritize sleep health in this important developmental period.

Prebedtime Screen Use in Adolescents: A Survey of Habits, Barriers, and Perceived Acceptability of Potential Interventions

PURPOSE

This study aimed to investigate (1) access to screens and screen use in the hour before bedtime and in bed; (2) attitudes and barriers to reducing screen time, and (3) perceptions of potential interventions to reduce screen time to benefit the sleep of New Zealand adolescents.

METHODS

Adolescents (aged 13-17 years, n = 4,811) living in New Zealand were recruited online between November 2015 and March 2016 with a direct link to complete a questionnaire about screen use in the hour before bedtime (including the types of screens used and activities) and screen use when in bed. Sleep patterns and quality were measured, and attitudes to reducing screen time using potential interventions were explored.

RESULTS

The most common prebedtime screen activities reported on most nights were social media (88%) and texting/instant messaging (77%). The majority of participants reported they used phones in bed (86%) and "agreed" they spent too much time on screens (70%), a perception that increased with age (p = .008). Being unable to communicate with friends was the most common barrier to reducing screen time (67% agreed).

CONCLUSIONS

Screen use in adolescents is complex; however, there is scope to improve sleep by reducing the impact of in-bed use of portable devices and addressing barriers to reduce screen time in adolescents.

Associations of Objectively-Assessed Smartphone Use with Physical Activity, Sedentary Behavior, Mood, and Sleep Quality in Young Adults: A Cross-Sectional Study

This study assesses the associations of objectively-measured smartphone time with physical activity, sedentary behavior, mood, and sleep patterns among young adults by collecting real-time data of the smartphone screen-state. The sample consisted of 306 college-aged students (mean age ± SD: 20.7 ± 1.4 years; 60% males). Over seven days of time, the following variables were measured in the participants: objectively-measured smartphone use (Your Hour and Screen Time applications), objective and subjective physical activity (GoogleFit and Apple Health applications, and the International Physical Activity Questionnaire (IPAQ), respectively), the number of hours sitting (IPAQ), mood (The Profile of Mood State (POMS)), and sleep (The Pittsburgh Sleep Quality Index (PSQI)). Multiple regressions analyses showed that the number of hours sitting per day, physical activity, and the POMS Global Score significantly predicted smartphone use (adj.R2 = 0.15). Further, participants with low levels of physical activity were more likely to increase the use of smartphones (OR = 2.981). Moreover, mood state (β = 0.185; 95% CI = 0.05, 0.32) and sleep quality (β = 0.076; 95% CI = -0.06, 0.21) predicted smartphone use, with those reporting poor quality of sleep (PSQI index >5) being more likely to use the smartphone (OR = 2.679). In conclusion, there is an association between objectively-measured smartphone use and physical activity, sedentary behavior, mood, and sleep patterns. Those participants with low levels of physical activity, high levels of sedentary behavior, poor mood state, and poor sleep quality were more likely to spend more time using their smartphones.

Waking to use technology at night, and associations with driving and work outcomes: a screenshot of Australian adults

The use of smartphones/electronic devices and their relationship with outcomes are understudied in adult populations. We determined daytime functional correlates of using technology during the night in a population sample of Australian adults. A cross-sectional, national online survey of sleep health was conducted in 2019 (n = 1984, 18–90 years). Nocturnal technology use was assessed with: “In the past seven days, how often did you wake or were woken to send or receive text messages, emails or other electronic communications?” Waking to use technology during all/most nights was reported by 4.9%, with 13.8% reporting two to three nights per week, and 12.7% reporting just one night per week. Technology users were more likely to be younger, employed, experience financial stress, and speak English as a second language. In adjusted analyses, compared to no use, technology use at least two to three nights per week was significantly associated with daytime problems (sleepiness, fatigue and impaired mood, motivation, and attention) and was more evident in participants not reporting/perceiving a sleep problem. Technology use was independently associated with at least one drowsy driving-related motor vehicle accidents/near miss per month (odds ratio [OR] = 6.4, 95% CI = 3.8 to 10.7) and with missing work (OR = 4.8, 95% CI: 3.2 to 7.2) and making errors at work (OR = 2.2, 95% CI = 1.5 to 3.3) at least 1 day in the past 3 months due to sleepiness/sleep problem. These associations were not significantly modified by age. Public health implications of waking to engage with electronic devices at night may be significant in terms of safety, productivity, and well-being. Limiting sleep-disrupting technology use will require innovative language-diverse strategies targeted broadly across age groups.