The impact of prolonged violent video-gaming on adolescent sleep: an experimental study

The relationship between chronotype video game addiction and sleep quality in school-age children: A structural equation modeling approach

This study aimed to investigate the relationship between chronotype, video game addiction, and sleep quality in school-age children using structural equation modeling. It was performed using structural equation modeling, with 545 secondary school students in northern Turkey meeting the inclusion criteria. Data were collected through face-to-face interviews utilizing the Personal Information Form, the Morningness Eveningness Scale for Children (MESC), the Video Game Addiction Scale for Children (VASC), and the Sleep Quality Scale. The findings revealed that the average video game addiction score of children was 55.22, which was associated with poor sleep quality and efficiency. Additionally, chronotype was found to mediate the relationship between video game addiction and both sleep quality (β = 0.024; p < 0.001) and sleep efficiency (β = -0.068; p < 0.001). The model was found to be close to acceptable levels for the variables according to the fit indices.

Videoconferencing During the COVID-19 Pandemic is Associated with Sleep Disruption in Young Adults

Purpose

The COVID-19 pandemic resulted in a shift to working and learning from home and a concomitant rise in the use of virtual communication technology, such as videoconferencing. The current study prospectively examined the association between videoconferencing and sleep in a sample of young adults attending a university during the pandemic. The effects of videoconferencing on health and wellness outcomes and academic performance were also evaluated.

Patients and Methods

Participants completed the core Consensus Sleep Diary and reported engagement in videoconferencing, the use of electronic devices, and physical activity daily for 8 consecutive days. They also completed baseline measures of sleep, communication technology use, physical activity, and mental distress, as well as released their end-of-term GPA. Results were evaluated via multilevel modeling and path analysis.

Results

Participants with a heavier videocall volume lost 17 m of sleep and suffered nearly a 1% reduction in sleep efficiency for each additional hour of videoconferencing compared to those with a lower call volume. They also tended to spend more time awake during the night, have earlier sleep midpoints, and report worse sleep, although those trends did not reach statistical significance. For everyone, including individuals with lower videocall volume, earlier sleep midpoints, lower sleep quality, somewhat shorter sleep, and higher fatigue were reported on days with a relatively high videocall load compared to days with a low videocall load. Increased academic engagement with videoconferencing predicted lower academic performance and higher psychological distress: Both relationships were mediated by sleep. Use of videoconferencing for personal reasons, however, was directly associated with a reduction in distress.

Conclusion

Videoconferencing is an important determinant of sleep and may impact health and wellness as well as academic outcomes in young adults. The effects of virtual communication on sleep and human behavior warrant further study in this and other populations.

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.

A bidirectional model of sleep and technology use: A theoretical review of How much, for whom, and which mechanisms

The link between technology and sleep is more complex than originally thought. In this updated theoretical review, we propose a new model informed by the growing body of evidence in the area over the past 10 years. The main theoretical change is the addition of bi-directional links between the use of technology and sleep problems. We begin by reviewing the evidence to date for the originally proposed mechanisms of bright light, arousal, nighttime sleep disruptions, and sleep displacement. Then, in support of the new direction of effect (sleep problems preceding technology use), we propose two new mechanisms: technology before sleep might be used as a time filler and/or as an emotional regulation strategy to facilitate the sleep-onset process. Finally, we present potential moderators of the association between technology and sleep, in recognition of protective and vulnerability factors that may mitigate or exacerbate the effects of technology on sleep and vice versa. The goal of this theoretical review is to update the field, guide future public health messages, and to prompt new research into how much technology and sleep affect each other, for whom it may be problematic, and which mechanisms may explain their association.

Sleep Characteristics of an International Sample of Adult Gamers

Introduction  About 65% of adult Americans report playing video games. Despite potential impacts to functioning, there is limited research on the relationship between video game use and sleep, specifically among adults. The present study expands upon the literature by describing demographic, video game, and sleep characteristics of an international adult sample of gamers. Methods  The participants were 3,481 adults aged 18 to 74 who responded to an online questionnaire about video game use (i.e., quantity of play, most common game type), general sleep characteristics (i.e., sleep onset latency [SOL]; duration, sleep timing, and sleep quality), and gaming-specific sleep disruptors (i.e., game-related night awakenings and sleep delays). Most identified as cisgender male (79.8%) and white (77%). Results  Participants reported an average SOL of 24.63 minutes, and most (64.5%) had a sleep duration from 7 to 9 hours with an overall average of 8.42 hours. Most (58.7%) reported that their sleep quality was fair to very poor . Bed and wake times were generally delayed, with 51% reporting a late evening or early morning bedtime and an average wake time of 8:28 am. A majority (81.2%) indicated that their bedtime was delayed due to game-related activities, but game-related night awakenings were less common. Conclusion  Although many report a sufficient amount of sleep, adult gamers tend to report sleep disruptions in other domains, particularly regarding a delayed sleep schedule and poor sleep quality. This may be attributable to game-related bedtime delays or other game-specific factors (e.g., game type) that should be evaluated in the future.

Increased Sleep Latency and Decreased Sleep Duration are Associated With Elevated Risk of Bed Sharing Among Mother-Infant Dyads

Bed sharing increases risk of sleep-related infant deaths. We hypothesized that infant sleep difficulties increase bed sharing, independent of social determinants of health (SDOH). In total, 191 mother-infant dyads in a prospective, longitudinal cohort study completed the Brief Infant Sleep Questionnaire at 1, 4, 6, and 12 months. Sleep characteristics at 1 month (latency, duration, night awakenings) were compared between dyads with/without bed sharing in the first 12 months. Infants who participated in bed sharing slept fewer hours at night (7.1 ± 1.7 hours vs 8.3 ± 1.5 hours, P = .001, d = -0.79), and took longer to fall asleep (0.7 ± 0.6 hours vs 0.5 ± 0.5 hours, P = .021, d = 0.43), even when controlling for SDOH variables that influence bed sharing. Maternal perception of sleep problems did not differ between groups (P = .12). Our findings suggest that infants with quantifiable sleep difficulties at 1 month are more likely to bed share.

The Relationship between Digital Game Addiction Tendency and Depressive Symptoms in Children (36-72 Months)

Aim: We aimed to evaluate the relationship between digital game addiction tendency and depressive symptoms in children (36-72 months). Method: We conducted this research in a virtual environment with the mothers of 747 children (36-72 months). A predictive evaluation was performed using a simple regression analysis between the mean scores of the Digital Game Addiction Tendency Scale (DGATS) and the Child Depressive Symptoms Assessment Scale (CDSAS). Results: A total of 53.9% of children reported that they play games for 3-24 h a day. The average duration of children playing digital games was 2.86 ± 1.86 h per day. The total mean score of the CDSAS was 142.48 ± 27.36. The total mean score the children received from DGATS was 46.34 ± 17.28. In the regression analysis, it was determined that there was a strong positive correlation between the (DGATS) total score average and the (CDSAS) total score average (R = 0.52, R2 = 0.27, p < 0.05). Accordingly, digital game addiction tendency explains 27% of children's depressive symptoms. Conclusions: When the standardized beta coefficient and t values are examined, it can be said that digital game addiction tendency is a significant predictor of children's depressive symptoms.

How emotions impact sleep: A quantitative review of experiments

Although sleep and emotional processes are recognized as mutually dependent, the causal impact of emotions on sleep has been comparatively neglected. To appraise evidence for the causal influence of emotions on sleep, a meta-analysis of the existing experimental literature evaluated the strength, form, and context of experimental effects of emotion inductions on sleep parameters (k = 31). Quality of experiments was evaluated, and theoretically-relevant features were extracted and examined as moderating factors of observed effects (i.e., sleep parameter, design, sleep context, types of emotion inductions and emotions). Random-effect models were used to aggregate effects for each sleep parameter, while-mixed effect models examined moderators. There was a significant impact of emotion inductions on delayed sleep onset latency (D = 3.36 min, 95%CI [1.78, 4.94], g = 0.53), but not other parameters. There was little evidence of publication bias regarding sleep-onset latency effect, the studies overall were heterogeneous, sometimes of limited methodological quality, and could only detect moderate-to-large impacts. The findings supported the hypothesis that negative emotions delayed sleep onset, but evidence regarding other sleep parameters was inconclusive. The results call for more targeted investigation to disambiguate distinct features of emotions and their import for sleep.

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.

Using a frequentist and Bayesian approach to examine video game usage, substance use, and sleep among college students

Video games are a popular form of entertainment. However, there is mixed evidence for the association between video game usage and poor sleep quality, short sleep duration, or delayed sleep timing. The current study examined associations between daily sleep behaviours and video game usage via a Bayesian and frequentist statistical approach. Caffeine and alcohol consumption were also assessed as moderators, as these behaviours may co-occur with video game usage and poor sleep. 1032 (72% female) undergraduate students were recruited between 2006-2007. Participants completed questionnaires examining video game and substance use, as well as sleep diaries for 1 week. Frequentist analyses revealed that video game usage was related to increased variability in the total sleep time, and a later average sleep midpoint, but not sleep efficiency. Alcohol use moderated the relationships between video game usage and both average and variability in total sleep time. Caffeine use was related to shorter average total sleep time and more variability in sleep efficiency. Alcohol consumption was related to more variability in the total sleep time and sleep midpoint, and a later average sleep midpoint. Bayesian models suggested strong evidence that video game playing was associated with later average sleep midpoint. Like the frequentist approach, alcohol consumption moderated the relationship between video game usage and both average and variability in total sleep time, but the evidence was weak. The effect sizes for both approaches tended to be small. Using a rigorous statistical approach and a large sample, this study provides robust evidence that video game usage may not be strongly associated with poor sleep among undergraduate students.

Time Use and Cognitive Achievement among Adolescents in China: Depression Symptoms as Mediators

Everyone's time is limited, and there is competition between different aspects of time use; this requires comprehensive consideration of the effects of different aspects of time use on cognitive achievement in adolescents. This study uses a dataset of 11,717 students from a nationally representative large-scale survey project conducted in 2013 to 2014 to clarify the relationship between time use (including working on homework, playing sports, surfing the Internet, watching TV, and sleeping) and cognitive achievement among Chinese adolescents, and explores the mediating role of depression symptoms in the relationship between time use and cognitive achievement. The results of the correlation analysis show that the average daily time spent on homework, playing sports, and sleeping is significantly positively correlated with cognitive achievement (p < 0.01), while time spent surfing the Internet and watching TV are significantly negatively correlated with cognitive achievement (p < 0.01). The results of the mediating effect model show that depression symptoms play a mediating role in the relationship between time use and cognitive achievement among Chinese adolescents. Specifically, time spent playing sports (indirect effect = 0.008, p < 0.001) and sleeping (indirect effect = 0.015, p < 0.001) have a positive effect on cognitive achievement when using depression symptoms as mediators; time spent on homework (indirect effect = -0.004, p < 0.001), surfing the Internet (indirect effect = -0.002, p = 0.046), and watching TV (indirect effect = -0.005, p < 0.001) have a negative effect on cognitive achievement when using depression symptoms as mediators. This study contributes to the understanding of the relationship between time use and cognitive achievement among Chinese adolescents.

Habitual Videogame Playing Does Not Compromise Subjective Sleep Quality and Is Associated with Improved Daytime Functioning

Research on the effects of videogames (VGs) on health has produced mixed results. Here, we assess the relationships of VG playing with sleep; chronotype; sleepiness; and levels of depression, anxiety, and stress; and how they are modulated by the level of exposure to VGs. Four hundred-and two adult participants (age = 26.2 ± 7.84; 227 F) completed an online survey including questions on VG use and a set of standardized questionnaires. The sample was divided into three groups: habitual gamers (HGs, 42.2%), nonhabitual gamers (NHGs, 36.5%), and non-gamers (NGs, 21.3%). No between-group differences emerged in sleepiness (Epworth Sleepiness Scale) or Pittsburgh Sleep Quality Index measures except the sleep disturbances subscore, which was higher in NHGs. HGs showed delayed bed- and risetimes and higher eveningness (reduced Morningness-Eveningness Questionnaire). HGs and NHGs showed higher depression subscores (Depression Anxiety Stress Scale) but remained in the subclinical range. Moreover, hours/week of VG playing predicted delayed sleep timing, lower daytime dysfunction, and lower sleepiness. Our data suggest that VG playing does not necessarily compromise sleep quality and may even benefit daytime functioning, underlining the need to reconsider the relationships between VG use and health by taking into account possible modulating factors such as habitual VG exposure.

The Health Effects of Video Games in Children and Adolescents

Play has always been an essential part of childhood, but it looks different for modern children, who increasingly engage in virtual play. More than 90% of children older than 2 years play video games, and three-quarters of American households own a video game console. Children 8 to 17 years of age spend an average of 1.5 to 2 hours daily playing video games. Recent developments framed by decades of research have provided insight into how games influence children's physical health, mental health, social behaviors, and cognitive development. Anticipatory guidance surrounding media use is often centered on screen time, but pediatricians should have some knowledge of the unique benefits and risks associated with this nearly ubiquitous activity. In light of the recent addition of gaming disorder to the International Classification of Diseases, 11th Revision, this review includes a discussion of the epidemiology, clinical features, and diagnosis of gaming disorder, including the use of existing screening tools. As games become more popular while ever-increasing in scope and complexity, this review aims to educate the modern pediatric provider about what is known, what is uncertain, and how to use this knowledge in the management of both healthy and unhealthy video gaming in children.

Internet and Video Games: Causes of Behavioral Disorders in Children and Teenagers

Even though video games have been present among children for many years, children are using them more continuously and in an abusive and indiscriminate way nowadays because of the "technological boom". It is affecting the behavior of children and adolescents. This is the reason why we are carrying out this systematic review. The main objective of this article is to investigate literature that directly connects the continuous and undifferentiated use of video games with the emergence of behavioral disorders in children and young people. The PRISMA statement was followed in the process of this article. We used SCOPUS, Web of Science and PubMed as databases, moreover, we searched studies with a scoping review. The results indisputably supported six out of seven of our hypotheses. We find that the excessive use of video games causes addiction to technology, aggressive behaviors, sleep disorders, and poor school performance. In addition, it hinders social relationships and the development of emotional intelligence. To conclude, it is necessary to correctly use video games in particular, and technologies in general, adapting their content to children's age, as well as the amount of time that they dedicate to use them.

Digital media use and sleep in late adolescence and young adulthood: A systematic review

Despite much attention on digital media use and young peoples' sleep, the literature on digital media and its impact on sleep in older adolescents and young adults remains to be synthesized. We conducted a systematic review of studies including young people aged 16-25 years. We searched Medline, Web of Science, and CINAHL for observational studies, identifying 60 studies. These studies were assessed for methodological quality. Only studies rated as moderate or high-quality studies were included (n = 42). A narrative synthesis summarized the impact of digital media use on eight sleep outcomes: Bedtime; Sleep onset latency or problems falling asleep; Sleep duration; Early awakening; Sleep disturbance; Daytime tiredness and function; Sleep deficits; Sleep quality. In summary, digital media use was associated to shorter sleep duration and poorer sleep quality. These associations were found for general screen use and use of mobile phone, computer, internet, and social media, but not for television, game console, and tablet use. Most studies investigating bedtime or nighttime use found associations to poor sleep outcomes. Later bedtime and daytime tiredness were associated with mobile phone use at night. Additional research is warranted to draw solid conclusions about the causal direction and to understand the underlying mechanisms.

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.

Sleep troubles in adolescence relate to future initiation of ENDS USE: A longitudinal cohort design using the PATH study waves 4.5–5 (2017–2019)

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First longitudinal study on the association between sleep trouble and ENDS use.

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Past year sleep trouble increased risk of initiating ENDS use in following year.

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Healthy sleep serves as a protective factor against ENDS uptake for youth.

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Nearly half of youths aged 12–17, experienced sleep troubles during wave 4.5.

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Sleep classes for youth/delayed school start times may help deter future ENDS use.

In a recent study, we demonstrated a relationship between self-reported sleep deprivation and youth susceptibility to initiate electronic nicotine delivery systems (ENDS) use; however, we were hampered by cross-sectional data. This study builds on our previous work by performing secondary analysis using the nationally representative Population Assessment of Tobacco and Health study datasets from wave 4.5 (2017–2018) and wave 5 (2018–2019) among respondents aged 12–17. Using a longitudinal cohort design, we assessed the extent self-reported sleep troubles at wave 4.5 related to transition from never-to-ever ENDS use by wave 5. We assessed youth who reported never having used any type of tobacco previously and who reported not using alcohol or other illicit substances the previous year. We ran four Poisson regression models on the dependent variable never-to-ever ENDS users at wave 5 and self-reported sleep troubles in the past year at wave 4.5. We controlled for demographic and sociographic factors and, in our final model, tobacco availability in home, exposure to ENDS advertising on social media, past year anxiety, depression, body mass index, physical activity, close friends that use ENDS, perceived harm of ENDS, school performance, sensation seeking, and the susceptibility of youth to initiate ENDS. Even when controlling for these factors, sleep troubles at wave 4.5 significantly and positively related to ENDS initiation by wave 5 (Past year sleep trouble: RR = 1.48 95 % CI = [1.14–1.93]). This key and novel finding has important implications for preventing youth ENDS use via protective self-care and social-environmental approaches.

Videospiele und Schlaf – negativer Zusammenhang oder unbedenkliches Zocken?

Hintergrund

Das Spielen von Videospielen vor dem Schlafengehen kann einen Einfluss auf die Qualität und Quantität des Schlafs haben.

Fragestellung

Es gilt herauszufinden, welche Faktoren dabei beeinflusst werden und wie diese messbar gemacht werden können.

Material und Methode

Um eine Übersicht zu geben und Handlungsempfehlungen auszusprechen, wurden aktuelle Studien analysiert und gegenübergestellt.

Ergebnisse

Das Spielen von Videospielen vor dem Schlafengehen kann speziell bei Kindern und Jugendlichen zu einer erhöhten Einschlafdauer und insgesamt einer erhöhten Müdigkeit führen. Die Bildschirmhelligkeit (Exposition von blauem Licht) und die Aktivierung des Sympathikus durch das Spielen sind dabei relevante Faktoren. Vor allem actionreiche Videospiele führen zu einer größeren Aktivierung als vergleichbare ruhigere Aktivitäten.

Schlussfolgerung

Zusammenfassend kann gesagt werden, dass der Schlaf grundsätzlich durch das Videospielen negativ beeinflusst werden kann. Eine verlängerte Einschlafdauer und verringerte Tiefschlafphasen können als Folge vom abendlichen Videospielkonsum auftreten. Hierbei scheint die Sympathikotonie eine dominantere Rolle als die Exposition von blauem Licht zu spielen. Kinder, Jugendliche und professionelle Videospielende sind potenzielle Risikogruppen und müssen demnach über ein verantwortungsvolles Videospielverhalten aufgeklärt werden. Zur Quantifizierung der Aktivierung können verschiedene Messparameter dienen. Insbesondere die Herzratenvariabilität stellt einen praktikablen Parameter dar.

Sleep's role in the development and resolution of adolescent depression

Two adolescent mental health fields - sleep and depression - have advanced largely in parallel until about four years ago. Although sleep problems have been thought to be a symptom of adolescent depression, emerging evidence suggests that sleep difficulties arise before depression does. In this Review, we describe how the combination of adolescent sleep biology and psychology uniquely predispose adolescents to develop depression. We describe multiple pathways and contributors, including a delayed circadian rhythm, restricted sleep duration and greater opportunity for repetitive negative thinking while waiting for sleep. We match each contributor with evidence-based sleep interventions, including bright light therapy, exogenous melatonin and cognitive-behaviour therapy techniques. Such treatments improve sleep and alleviate depression symptoms, highlighting the utility of sleep treatment for comorbid disorders experienced by adolescents.

Sleep latency and sleep disturbances mediates the association between nighttime cell phone use and psychological well-being in college students

To examine sleep latency and sleep disturbance as mediators between nighttime cell phone use variables (cell phone use for unstructured leisure activities and for accessing emotionally charged media content before sleep: CPU_BeforeBed and CPU_Arousal) and psychological well-being (PWB) of college students. 521 (74% female) undergraduate students from a large public university were surveyed using a validated self-report quantitative questionnaire assessing CPU variables, sleep quality, and PWB. Pearson correlation analyses were used to compute the correlation between CPU_BeforeBed, CPU_Arousal, sleep latency, and sleep disturbance. Ordinary least-squares regressions were conducted to assess the estimates of the relationships within the models. One-way ANOVA was used to see the difference between the groups. The partial eta squared was used to determine the effect size between the groups. The PROCESS method was used to perform mediation analyses. The sample consisted of undergraduate students between 18 and 29 years old, with an average age of 20 years (SD = 3.18). The sample was diverse in terms of ethnicity (49% Caucasian, 24% Latinx, 19% Asian, 3% African American, 1% Native American, 3% identified as "other") and the number of years the participants had been attending a 2 year or 4 year higher institution (38% incoming freshman, 19% sophomore, 17% junior, 14% senior, and 13% returning senior). The correlation between CPU_BeforeBed and PWB (α = - 0.044, p = 0.615), and the correlation between CPU_Arousal and PWB (α = - 0.061, p = 0.228) were not statistically significant. However, the correlation between sleep latency and PWB (α = - 0.140, p = 0.001), and the correlation between sleep disturbance and PWB (α = - 0.121, p = 0.005) were statistically significant. The mediation effect of sleep latency on the association between CPU_BeforeBed and PWB (Effect = - 0.0325, SE = 0.0145, p < 0.05), and the mediation effect of sleep disturbance on the association between CPU_Arousal and PWB (Effect = - 0.0214, SE = 0.0086, p < 0.05) were statistically significant. Sleep latency and sleep disturbance act as a mediator on the association between CPU_BeforeBed and PWB, and the association between CPU_Arousal and PWB. However, CPU_BeforeBed and CPU_Arousal did not have a direct impact on their PWB. These findings may help college students in regulating CPU habits before going to bed. These findings may also help medical practitioners make informed decisions about the use of cell phones for patients with sleep-related disorders.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00388-3.

Problem mobile gaming: The role of mobile gaming habits, context, and platform

Aims: Mobile gaming is a dominant form of gaming, known for its portability and for game characteristics that motivate continuous play and spending. Such involvement may also turn problematic, but research on problem gaming (PG) has tended to focus on non-mobile forms of gaming. The study was based on a cross-sectional observational design where students in upper secondary schools were recruited to a survey about mobile gaming. The age of the respondents ranged from 16 to 23 years (n = 519; 52.4% men; mean age = 17.2 years, SD = 1.1). Methods: We examined (1) gaming frequency, gaming contexts, and in-game spending in relation to PG; (2) gaming context in relation to academic achievement and sleep quality; and (3) PG according to gaming platform (i.e., playing on mobile, console/computer, or mixed platforms) with Kruskal−Wallis tests, chi-square tests and Spearman rank-order correlations. Results: PG was positively associated with mobile gaming hours per week (η² = .02, p < .01), minutes per session (η² = .03, p < .001), making in-app purchases (Cramer's V = .15, p < .05), and gaming during homework (Cramer's V = .14, p < .05). Statistically significant associations were found between mobile gaming in bed and later sleep midpoint for weekdays (r_s = .18, p < .001) and weekends (r_s = .11, p < .05). Mixed platform gamers had increased likelihood of PG, console/computer gamers had increased likelihood of being at risk for PG, and mobile gamers had lower risk for PG (Cramer's V = .18, p < .001). Conclusion: Future studies should include specific measures of mobile gaming as it appears implicated in problem gaming, albeit to a lesser degree than console and computer gaming.

Sleep deprivation and adolescent susceptibility to vaping in the United States

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Adolescent sleep deprivation is associated with susceptibility to ENDS use.

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Less than 6 h sleep relates to higher perceived likelihoods of trying ENDS.

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ENDS prevention efforts may benefit by incorporating sleep hygiene measures.

Sleep deprivation may be a contributing factor to adolescents’ willingness to experiment with substance use, including electronic nicotine devices (ENDS). While it is generally accepted that nicotine has a negative overall effect on sleep, no studies have yet explored whether sleep deprivation may contribute to adolescents’ initiation of ENDS use. The purpose of this study is to explore whether sleep deprivation is associated with adolescents’ self-reported susceptibility to initiating ENDS use in the next month. Respondents were 1,100 adolescents aged 13–17 across the United States who participated in the Vaping Attitudes Youth Perspectives Survey (VAYPS). We used logistic regression to examine cross-sectional associations between self-reported average sleep duration and self-reported likelihood of trying ENDS in the future. Results of the three logistic regression models show that adolescents who reported getting less than six hours of sleep per night were associated with greater odds of reporting any likelihood to try a vape in the next 30 days even when controlling for demographics and potential confounders (<6hrs sleep: OR = 2.63, 95% CI 1.30–5.31). Future research on the association between sleep deprivation and ENDS use among adolescents will benefit from using longitudinal approaches to better understand causality.

Gaming Behaviors and the Association with Sleep Duration, Social Jetlag, and Difficulties Falling Asleep among Norwegian Adolescents

The relationship between gaming and sleep is mostly informed by studies of addictive gaming behavior, thus limiting our understanding of sleep in the context of nonproblematic engaged gaming. The present study investigated whether addicted, problem, and engaged gaming behavior was associated with sleep duration, social jetlag, and difficulties falling asleep. The sample consisted of 13- and 16-year-old Norwegian adolescents (n = 3228) participating in the Health Behavior in School-Aged Children (HBSC) survey in 2018. Participants were categorized into addicted, problem, engaged, and normal/non-gaming behavior groups according to which GAS-7 criteria they fulfilled. Robust generalized linear mixed models with a random intercept for class ID were used to examine the association between the sleep variables and gaming behavior. Addicted gaming behavior was unfavorably associated with all sleep parameters. The findings for engaged gaming and problem gaming behavior were somewhat mixed. Engaged gamers slept less on weekends, less on weekdays for those aged 16, and experienced greater social jetlag compared to the normal/non-gaming group. Problem gamers experienced greater social jetlag and had higher odds of experiencing difficulties falling asleep. Overall, the results suggest that all types of gaming behaviors might harm sleep health, but to a greater extent for the addicted gamers.

Nighttime cell phone use and sleep quality in young adults

Young adults are particularly vulnerable to sleep disturbances related to their cell phone use (CPU). The purpose of this study was to test Sleep Displacement and Psychological Arousal theories of CPU-led sleep disruption in relation in a sample of university students. CPU for unstructured leisure activities before sleep (CPU_BeforeBed), as well as CPU for accessing explicit or emotionally charged media content before sleep (CPU_Arousal), were both measured. 525 (75% female) undergraduate students from a large public institution participated in this study during fall 2019. The data were collected using a battery of validated self-report questionnaires. Questionnaires included the Pittsburgh Sleep Quality Index scale, which was used to measure sleep latency and sleep difficulty, and a contemporary questionnaire developed to measure CPU_BeforeBed and CPU_Arousal. A crude odds ratio analysis was implemented to analyze findings. Sleep Displacement data showed higher odds of sleep latency occurring with CPU_BeforeBed [Exp (B) = 1.091, p < 0.001]. Psychological Arousal data showed higher odds of sleep difficulty occurring with CPU_Arousal [Exp (B) = 1.065, p < 0.001]. CPU_BeforeBed significantly predicted sleep latency [Exp (B) = 1.062, p < 0.01], and CPU_Arousal significantly predicted the sleep difficulty [Exp (B) = 1.069, p < 0.001] of undergraduate students. Young adults who used cell phones before sleep and access emotionally charged content before going to bed were more likely to report trouble sleeping. They took more time to fall asleep at night as their sleep hours were compressed due to CPU. These findings support the Sleep Displacement and Arousal theories of sleep disruption and provide further insight into possible mechanisms for sleep disturbance in young adults.

Prospective associations between sedentary behavior and physical activity in adolescence and sleep duration in adulthood

The purpose of this prospective study was to investigate whether sedentary screen time (SST) and physical activity in adolescence were related to sleep duration in adulthood and whether these associations varied by sex. We analyzed data from 9279 adolescents who participated in Waves I and V of the National Longitudinal Study of Adolescent Health (Add Health) in the United States. SST was measured by reported hours spent watching television/videos or playing video/computer games per week. Physical activity was measured with participation in school team club sports and frequency (times/week) of moderate to vigorous physical activity (MVPA). Results from multinomial regression models indicated that adolescents with more SST, particularly 15-21 h (Relative Risk Ratio [RRR] = 1.18, 95% CI: 1.02-1.36) or 22 or more hours (RRR = 1.19, 95% CI: 1.06-1.35) compared to 0-7 h per week SST, had significantly higher relative risk of short sleep (six or fewer hours) in adulthood, after controlling for demographic characteristics, socioeconomic status and health behaviors at Waves I and V, sleep duration at Wave I, and SST and MVPA at Wave V. The association between 22 or more hours per week SST in adolescence and later short sleep varied by sex (RRR = 0.75, 95% CI: 0.58-0.95) and was significantly stronger among males. Measures of physical activity in adolescence did not predict sleep duration. Decreasing adolescents' SST to prevent suboptimal sleep later in development may be a target for further investigation, particularly for males.

Sleep and screen exposure across the beginning of life: deciphering the links using big-data analytics

STUDY OBJECTIVES

Evidence for the association between screen time and insufficient sleep is bourgeoning, and recent findings suggest that these associations may be more pronounced in younger compared to older children, and for portable compared to non-portable devices. However, these effects have yet to be investigated within the beginning of life. Importantly, there are no data for the relationship between screen exposure and objectively measured infant sleep. This study examined the moderating role of age for both touchscreens' and television's relationship with sleep, using auto-videosomnography within a big-data sample of infants.

METHODS

The sleep of 1074 infants (46% girls) aged 0-18 months was objectively assessed using computer-vision technology in this cross-sectional study. Sleep was additionally reported by parents in an online survey, as was infant exposure to screens.

RESULTS

Age significantly moderated the relationship between daytime touchscreen exposure and sleep with a distinct pattern for younger infants, in which screen exposure was associated with decreased daytime sleep, but with a proposed compensatory increase in nighttime sleep consolidation. Compared to touchscreens, television exposure was less likely to be associated with sleep metrics, and age moderated this relationship only for daytime and 24-hour sleep duration.

CONCLUSIONS

In young infants, a daytime-nighttime sleep "trade-off" emerged, suggesting that the displacement of daytime sleep by screens may lead to greater accumulation of sleep homeostatic pressure, which in turn facilitates more consolidated nighttime sleep.

Social Media Use and Sleep Disturbance among Adolescents: A Cross-Sectional Study

Objective: Recently, social media use has become prevalent in the daily lives of many adolescents. This study was performed to address adolescents' sleep quality and depression in relation to social media use. Method : This cross-sectional cluster-sampling study was directed on 576 high school students in 2019 in Hamadan, Iran. Three standard self-reported questionnaires were used for recording sleep patterns (Pittsburgh Sleep Questionnaire Index (PSQI)), depression (Beck), and Electronic Media Use. Data was analyzed using SPSS. P-values less than 0.05 were considered as being significant. Results: Among the adolescents 290 (50.3%) were female and the age median was 17. The average time of all Smart devices used was 7.5±4.4 hours per day. Among all students 62.3 % (359) said that they had their cell phone on in their bedroom when they sleep. In boys, the amount of social media use was significantly more than girls and poor sleep quality had a statically significant relationship with social media use (P-Value = 0.02). Additionally, there was a reverse correlation between the average use of electronic devices and sleep duration (Spearman's rho = 0.17; P-Value = 0.03), and a direct correlation between the average use in social media and depression (Spearman's rho = 0.171; P-Value < 0.001). Conclusion: In this important age group a high level of electronic devices use and its relationship with sleep quality, daily dysfunction, sleep duration and depression is worthy of issue awareness among health managers, parents and teachers for providing interventional programs, based on standard updated guidelines, in order to reduce the problem and familiarize adolescents and their parents, at home or school, with restrictions on using devices to view and participate in social media.

Impact of pre-sleep habits on adolescent sleep: an Italian population-based study

OBJECTIVE

Several evidences demonstrate that pre-sleep habits may negatively impact adolescent sleep, yet few data exist on Italian population. This study aimed to investigate the relationship between pre-sleep habits, use of technology/activity and sleep in Italian adolescents.

METHODS

Self-report questionnaires including Italian version of School Sleep Habits Survey and use of technology/activity (eg smartphone, PC) at bedtime were administered to 972 adolescents (13-19 years) from Lombardia. We stratified the sample in five groups according to the age: Group I (13-14 years), Group II (15 years), Group III (16 years), Group IV (17 years), Group V (18-19 years).

RESULTS

Our descriptive analysis reveals a different sleep profile across age-groups: Group III showed highest percentage of bad sleep (26.7%) and frequent nocturnal awakenings (24.1%), Group V had the highest percentage of insufficient sleep (40,4%) and difficulty falling asleep (42.7%) and Group IV presented an elevated difficulty in waking up in the morning (70.1%). A significant negative correlation was found in total group between use of smartphone, internet and studying/doing homework and total sleep time. The use of smartphone, internet videogames, listening to music and studying/doing homework was positively associated with delayed bedtime.

CONCLUSIONS

This study confirms the great impact of pre-sleep habits, and in particular the use of technology on adolescent sleep. Our results demonstrate that sleep is strongly altered among Italian adolescents using electronic devices in evening. The type of technology may be related to specific sleep profile, emphasizing the importance of stratification analyses to identify associated factors to sleep problems.

Preliminary Results: The Impact of Smartphone Use and Short-Wavelength Light during the Evening on Circadian Rhythm, Sleep and Alertness

Smartphone usage strongly increased in the last decade, especially before bedtime. There is growing evidence that short-wavelength light affects hormonal secretion, thermoregulation, sleep and alertness. Whether blue light filters can attenuate these negative effects is still not clear. Therefore, here, we present preliminary data of 14 male participants (21.93 ± 2.17 years), who spent three nights in the sleep laboratory, reading 90 min either on a smartphone (1) with or (2) without a blue light filter, or (3) on printed material before bedtime. Subjective sleepiness was decreased during reading on a smartphone, but no effects were present on evening objective alertness in a GO/NOGO task. Cortisol was elevated in the morning after reading on the smartphone without a filter, which resulted in a reduced cortisol awakening response. Evening melatonin and nightly vasodilation (i.e., distal-proximal skin temperature gradient) were increased after reading on printed material. Early slow wave sleep/activity and objective alertness in the morning were only reduced after reading without a filter. These results indicate that short-wavelength light affects not only circadian rhythm and evening sleepiness but causes further effects on sleep physiology and alertness in the morning. Using a blue light filter in the evening partially reduces these negative effects.

Insomnia Status of Middle School Students in Indonesia and Its Association with Playing Games before Sleep: Gender Difference

The excessive use of online gaming before sleep in adolescents could be a risk factor of sleep disorders such as insomnia. This study aimed to assess the association between playing online games before sleep and insomnia based on gender perspective among middle school students in Indonesia. This was a retrospective study and the data came from a cross-sectional survey that included 315 of Grade 8 and 9 students from four middle schools in Jakarta, Indonesia. Self-reported data were collected via a structured questionnaire, which consisted of demographic variables, sleep duration per day, frequency of playing online games before sleep and the Insomnia Severity Index (ISI). Insomnia status was classified into "none or mild" and "moderate to severe" according to ISI score. The proportions of male and female students who often or always played online games before sleep were 50.3% and 21.7%, respectively. Grade 9 students were more likely to have moderate to severe insomnia than Grade 8 students for males (odds ratio-OR = 4.34, p = 0.005) but not for females (OR = 0.69, p = 0.363). However, female students who often or always played online games before sleep were more likely to have moderate to severe insomnia (OR = 4.60, p = 0.001); such an association was relatively smaller for male students (OR = 3.09, p = 0.061). Gender differences should be taken into account when developing health education or interventions.

Effect of internet use and electronic game-play on academic performance of Australian children

This study examined the association of internet use, and electronic game-play with academic performance respectively on weekdays and weekends in Australian children. It also assessed whether addiction tendency to internet and game-play is associated with academic performance. Overall, 1704 children of 11–17-year-olds from young minds matter (YMM), a cross-sectional nationwide survey, were analysed. The generalized linear regression models adjusted for survey weights were applied to investigate the association between internet use, and electronic-gaming with academic performance (measured by NAPLAN–National standard score). About 70% of the sample spent > 2 h/day using the internet and nearly 30% played electronic-games for > 2 h/day. Internet users during weekdays (> 4 h/day) were less likely to get higher scores in reading and numeracy, and internet use on weekends (> 2–4 h/day) was positively associated with academic performance. In contrast, 16% of electronic gamers were more likely to get better reading scores on weekdays compared to those who did not. Addiction tendency to internet and electronic-gaming is found to be adversely associated with academic achievement. Further, results indicated the need for parental monitoring and/or self-regulation to limit the timing and duration of internet use/electronic-gaming to overcome the detrimental effects of internet use and electronic game-play on academic achievement.

The effect of computer game playing habits of university students on their sleep states

OBJECTIVE

The aim of this study is to evaluate the effect of computer game playing habits of university students on their sleep states.

DESIGN AND METHODS

The study was conducted cross-sectionally with the online survey method.

FINDING

In this study, it was determined that the students who played games for an average of ≥2 hours per day had later bedtime and later wake-up time, poorer sleep quality, and higher daytime sleepiness. It was found that as the level of game addiction increased, sleep quality decreased, the severity of daytime sleepiness increased, and the wake-up time shifted to a later time.

PRACTICE IMPLICATIONS

Nurses should develop effective intervention strategies involving technology management and sleep hygiene studies to reduce game-playing time of students.

Examining the day-to-day bidirectional associations between physical activity, sedentary behavior, screen time, and sleep health during school days in adolescents

BACKGROUND

Adolescence is a vulnerable period for experiencing poor sleep health. Growing studies have demonstrated lifestyle behaviors including physical activity (PA), screen time (SCT), and sedentary behaviors (SED) as the potential factors associated with sleep health in adolescents; yet, the evidence is inconclusive and the directionality of temporal associations across school days are not well understood. This study examined the day-to-day bidirectional associations of lifestyle behaviors with sleep health parameters in adolescents.

METHODS

A total of 263 adolescents (58% boys) in 6th - 8th grades wore an accelerometer for 24-hour across the three consecutive school days and completed recording SCT in time-diary and answering sleep quality (SQ) questions for each day. Sleep-wake patterns as well as time spent in moderate- and vigorous-intensity PA (MVPA) and SED were objectively quantified from the wrist-worn accelerometry data across the two segments of the day (during and after school hours). Mixed model analyses were conducted to test bidirectional associations between lifestyle factors and sleep health parameters in each temporal direction across the days. Additionally, indirect associations across the days were tested using an autoregressive cross-lagged model analysis in the framework of path analysis.

RESULTS

MVPA minutes in a day did not predict sleep health parameters that night. The bidirectional associations were partially observed between SED and sleep health, but the significance and direction of the associations largely varied by the time segment of a day as well as types of sleep health parameters. Additionally, greater SCT during the day was associated with lower SQ that night (b = -0.010; P = .018), and greater SQ was associated with greater MVPA during school hours (b = 6.45; P = .028) and lower SED after school hours (b = -39.85; P = .029) the next day. Lastly, there were significant indirect associations of SCT with sleep health parameters across the days indicating multi-day lagged effects of SCT on sleep health the later nights.

CONCLUSION

This study highlights the importance of lowering SCT for better sleep health in adolescents during school days. Additionally, perceived SQ is shown to be a potential significant predictor promoting healthy behaviors the next day independent of sleep-wake patterns. Further studies are warranted to confirm the observed temporal associations between SCT, SQ, and behavioral outcomes in this vulnerable population.

Social and Behavioral Health Factors Associated with Violent and Mature Gaming in Early Adolescence

We examined how risk level of video games, measured by maturity and violence level, was associated with behavioral health, social impacts, and online social interactions. School-based surveys in two different cohorts assessed self-reported gaming behaviors, health, and social media use. For Study 1, our 700 participants were 52% female and 48% White (mean age 12.7). Middle school students who played the high-risk games reported higher depressive symptoms and problematic internet behaviors, less sleep, more time spent playing games, and higher frequency of checking social media than non-gaming students. Those who played high-risk games were less likely to play alone and to play with strangers than those who played minimal-risk games. For Study 2, our 772 participants were 50% female and 57% White (mean age 12.6). Similar to Study 1, we found that those who played the high-risk games spent significantly more time playing games, were more interactive with other players, and had poorer sleep outcomes than non-high-risk gamers. Additionally, playing high-risk games had significantly different social impacts of gaming compared to less-risky gaming, including spending more money on games, spending less time on homework and with family or skipping meals due to gaming. Mature and violent content of video games and amount of online social interaction associated with gaming play a strong role in behavioral health and social impacts within families. These results can inform guidelines to intervene when problematic behaviors emerge.

The physiological and biochemical effects of gaming: A review

BACKGROUND

Recreational, seated video gaming (gaming) has become a favorite pastime of children, adolescents, and adults (gamers) in developed countries. Some engage in gaming behavior for more than 6 h daily, which can subsequently lead to less time spent being physically active. Gaming can potentially have a serious impact on the physiology and biochemistry of gamers and can influence both short-term and long-term health. The aim of this review was to provide an overview of what is known about how gaming affects physiological and biochemical parameters in the human body and how studies have previously been designed and to discuss how studies can be designed moving forward.

METHODS

The literature search included material from three scientific databases (PubMed, EMBASE, and Web of Science) using a two-block search strategy. To be included in this review, studies had to investigate a biochemical or physiological aspect of sedentary, video game-related activities. Studies that investigated neurological, psychologic or musculoskeletal outcomes along with physiological or biochemical outcomes in gaming were eligible for inclusion. Studies regarding psychiatric conditions were excluded as this subject was outside the scope of this review. Additionally, non-English language articles were excluded.

RESULTS

A total of 5417 articles were screened, 138 studies from the literature search and 4 studies from reference lists were selected for further evaluation. The studies were evaluated based on their abstracts or full texts, and 51 studies were eventually included in the review. Thirty-seven studies included physiological results, seven studies included biochemical results, and seven studies included both. Several outcomes such as heart rate, blood pressure, blood glucose levels, and cortisol levels, were the subjects of a large number of investigations.

CONCLUSION

This field is heterogenic and does not lend itself to firm conclusions. Tentatively, it seems reasonable to conclude that heart rate variability studies show that gaming increases activity in the sympathetic nervous system. More high-quality studies are required, and the lack of studies using uniform, standardized designs and realistic gaming sessions (i.e., longer than 30 min) limits our current knowledge.

Insomnia, sleepiness, anxiety and depression among different types of gamers in African countries

Gaming has increasingly become a part of life in Africa. Currently, no data on gaming disorders or their association with mental disorders exist for African countries. This study for the first time investigated (1) the prevalence of insomnia, excessive daytime sleepiness, anxiety and depression among African gamers, (2) the association between these conditions and gamer types (i.e., non-problematic, engaged, problematic and addicted) and (3) the predictive power of socioeconomic markers (education, age, income, marital status, employment status) on these conditions. 10,566 people from 2 low- (Rwanda, Gabon), 6 lower-middle (Cameroon, Nigeria, Morocco, Tunisia, Senegal, Ivory Coast) and 1 upper-middle income countries (South Africa) completed online questionnaires containing validated measures on insomnia, sleepiness, anxiety, depression and gaming addiction. Results showed our sample of gamers (24 ± 2.8 yrs; 88.64% Male), 30% were addicted, 30% were problematic, 8% were engaged and 32% were non-problematic. Gaming significantly contributed to 86.9% of the variance in insomnia, 82.7% of the variance in daytime sleepiness and 82.3% of the variance in anxiety [p < 0.001]. This study establishes the prevalence of gaming, mood and sleep disorders, in a large African sample. Our results corroborate previous studies, reporting problematic and addicted gamers show poorer health outcomes compared with non-problematic gamers.

The effects of prolonged single night session of videogaming on sleep and declarative memory

Use of electronic media is widespread among adolescents. Many male adolescents spend a major part of their evenings playing video games. The increased exposure to artificial light as well as the exciting nature of this pastime is under suspicion to impair sleep. Sleep is considered to be important for memory consolidation, so there is also a potential risk for memory impairment due to video gaming. As learning and gaining knowledge is a very important part of adolescence, we decided to study the effects of prolonged video gaming on sleep and memory. The study was structured in a repeated measures design. Eighteen male participants played either the violent video game "Counter Strike: Global Offensive" or the board game "Monopoly" for five hours each on two Saturday nights. The game evenings were followed by sleep studies. Memory testing and vigilance evaluation was performed the next morning. During the course of the study, saliva samples were taken to determine melatonin and cortisol levels. The results of this crossover study showed slightly reduced sleep efficiency after "Counter Strike: Global Offensive" (-3.5%, p = .017) and impaired declarative memory recall (p = .005) compared to "Monopoly". Melatonin levels at bedtime were lower after "Counter Strike: Global Offensive" (p = .005), cortisol levels were elevated while playing the video game (p = .031). Negative effects on sleep were not strong but consistent with more wake after sleep onset (+12 min) and a higher arousal index after "Counter Strike: Global Offensive". We conclude that excessive video gaming in the evening can contribute to worsened sleep and impaired memory in male adolescents.

Sleep and stress in adolescents: the roles of pre-sleep arousal and coping during school and vacation

STUDY OBJECTIVES

This study explored the relationship between stress and actigraphy-measured and self-reported sleep in adolescents during periods of restricted (school) and unrestricted (vacation) sleep opportunities. We further examined whether (1) cognitive pre-sleep arousal (PSA) mediated the relationship between stress and sleep onset latency (SOL), and (2) coping moderated the effect of stress on PSA.

METHODS

Participants were 146 (77 females) adolescents (M = 16.2, SD = 1.0) recruited from the community. Actigraphy assessed daily sleep over the last week of a school-term and the following two-week vacation. The following self-report measures were administered during both school and vacation: the Pittsburgh Sleep Quality Index, Inventory of High-School Students Recent Life Experiences (stress), Pre-Sleep Arousal Scale, and the Brief COPE (coping).

RESULTS

Path analyses showed that during both school and vacation, higher cognitive PSA mediated the relationship between higher stress and longer self-report SOL (p < 0.01). During vacation, higher PSA also mediated the relationship between higher stress and longer actigraphy SOL (p < 0.05). During vacation (but not school), problem-focused coping moderated the mediating effects of PSA (p < 0.05), such that more frequent use of coping was associated with weaker association between stress and cognitive PSA, and shorter actigraphy and self-report SOL.

CONCLUSIONS

Cognitive PSA and coping may be two modifiable factors influencing how stress affects adolescents' sleep onset. Interventions that reduce cognitive arousal at bedtime may therefore shorten adolescents' sleep onset during both school and vacation. Further, the use of problem-focused coping strategies might be protective against the effects of stress on sleep onset, especially during vacation periods.

STATEMENT OF SIGNIFICANCE

This paper expands the understanding of the stress-sleep association in adolescents by examining the mediating role of cognitive pre-sleep arousal and the moderating effects of coping. By examining these associations during both school and vacation periods, findings are likely to be applicable to both restricted and relatively unconstrained sleep conditions. Practically, our findings suggest that interventions directed towards the reduction of cognitive pre-sleep arousal may improve adolescents' sleep onset latency. Additionally, fostering healthy coping, especially problem-focused coping strategies such as problem solving, may mitigate the effects of stress on adolescents' sleep.

Will esports result in a higher prevalence of problematic gaming? A review of the global situation

BACKGROUND AND AIMS

Video gaming is highly prevalent in modern culture, particularly among young people, and a healthy hobby for the majority of users. However, in recent years, there has been increasing global recognition that excessive video gaming may lead to marked functional impairment and psychological distress for a significant minority of players. Esports is a variant of video gaming. It is a relatively new phenomenon but has attracted a considerable number of followers across the world and is a multimillion dollar industry. The aim of this briefing paper is to review the global situation on esports and related public health implications.

METHODS

A non-systematic review was conducted. Information obtained from the Internet and PubMed was collated and presented as genres of games, varieties and magnitudes of impacts, popularity, fiscal impact in monetary terms, government involvement, and public health implications.

RESULTS

There are several different kinds of esports but there was no clear categorization on the genre of games. Many tournaments have been organized by gaming companies across the world with huge prize pools, and some of these events have government support. Little information on the health effects associated with esports was identified.

DISCUSSION AND CONCLUSIONS

A majority of the sources of information were from commercial settings, and failed to declare conflicts of interest, which may result in a biased picture of the current situation. When gaming activity is being further promoted under the umbrella of esports, it seems reasonable to expect an increase in problematic gaming and thus increased prevalence of gaming disorder and hazardous gaming. With increasing demand for treatment services for gaming addition/disorder in different countries across the world, it is a significant public health concern. More empirically based research on this topic is needed.

Does Playing Video Games Before Bedtime Affect Sleep?

Sleep serves a vital role in our ability to function on a daily basis and may be affected by various activities such as playing video games. Teenagers are one of the largest consumers of video games and if played before bedtime may lead to the release of certain neurotransmitters which may, in turn, alter sleep architecture and reduce sleep efficiency. The purpose of this study is to measure 1) sleep efficiency 2) sleep latency 3) time spent in rapid eye movement (REM) stage with and without playing video games 30 minutes to 60 minutes before bedtime. For this study, one patient was recruited. The study was completed using a television, video game console, and a video game (Red Dead Redemption 4), Apnea Risk Evaluation System (ARES) nocturnal polysomnogram (NPSG) unit, a bed and a blanket situated in a quiet room, a computer, printer, and a notebook for data recording. REM time and sleep latency were also measured. There were 45.6 minutes of REM with video games and 56.4 minutes of REM without video games. This was equivalent to 13.06% and 15.74% of the total sleep time, respectively. The sleep latency with video games was shorter than without video games (11.4 and 23 minutes, respectively). Result suggests that there is no significant difference in sleep efficiency with and without video games. However, sleep latency decreased, and REM increased with video games.

Sleep Research: A Primer for Media Scholars

The average amount of sleep people of all ages get has declined sharply in the past 50 years. The detrimental health effects of sleep deprivation are well documented and substantial. Even though electronic media use often takes place in the hours before sleep, the extent to which media use may interact with sleep is understudied and not well understood. Communication scholars are well positioned to contribute to this area, as a systematic, theoretical understanding of the relationship between media and sleep is still lacking. This primer charts the state of knowledge on electronic media and sleep and explores possible next steps. First, we introduce the problem of sleep deprivation and describe the basic science of sleep with relevant terminology. Then, we review the research on electronic media and sleep and offer an agenda for research.

Relationship between Physical Activity, Screen Time, and Sleep Quantity and Quality in US Adolescents Aged 16⁻19

Despite the health benefits associated with physical activity (PA), screen time reduction, and sleep quantity and quality, the relationships between PA, screen time, and sleep quantity and quality remain unclear in adolescents. The present study is a cross-sectional analysis of data from adolescents aged 16–19 years who participated in the 2005–2006 National Health and Nutrition Examination Survey (n = 542). Multivariable logistic regression models, adjusted for confounders, examined the relationship between objectively measured PA, self-reported screen time, and sleep quantity and quality. Respondents who met the current PA recommendation had 50% lower odds of having sufficient sleep (≥8 h) than those not meeting the recommendation (OR = 0.50, 95% CI: 0.26, 0.94). Respondents who met the screen time recommendation (≤2 h/day) had 55% lower odds of reporting poor sleep quality than those whose screen time exceeded the recommendation (OR = 0.45, 95% CI: 0.22, 0.91), with similar patterns observed for females and males. However, males who met both PA and screen time recommendations had 73% lower odds of reporting poor sleep quality than males who met neither recommendation (OR = 0.27, 95% CI: 0.07, 0.99). In conclusion, PA and screen time are associated with sleep quantity or sleep quality in adolescents, and there are differences in these associations by sex.

Sleep quality and video game playing: Effect of intensity of video game playing and mental health

The aim of this study was to explore sleep quality in a video game population and to prospect the role of different factors such as sociodemographic data, video game duration, intensity of video game playing, and mental and physical health. Two hundred and seventeen participants (24.40 ± 6.98 years old) completed an online questionnaire composed of sociodemographic informations, the Pittsburg Sleep Quality Index (PSQI), the Medical Outcomes Study (MOS SF-36), video game play time per week, and intensity of video game playing as defined by Décamps (AIE-Q). We carried out hierarchical cluster analysis on the 7 dimensions of PSQI to determine sleep quality profiles. Two profiles were found: (1) « High sleep quality profile » for 132 (60.83%) participants, and (2) « Low sleep quality profile » for 85 (39.17%) participants. These two profiles were differently associated with video game duration per week, intensity of video game playing, and mental health. Sleep quality was positively related to mental health and negatively with intensity of video game playing. Intensity of video game playing was a more salient factor to predict poor sleep quality than video game duration.

Evening electronic device use and sleep patterns in athletes

The present study aimed to investigate pre-sleep behaviours (including evening electronic device use) and sleep quantity in well-trained athletes. Seventy well-trained athletes (44 females, 26 males) aged 21 ± 4 y from a range of team and individual sports were asked to complete an online sleep diary for 7 days. The sleep diary included questions about pre-sleep behaviours (e.g. napping, caffeine intake), electronic device use in the 2 h prior to bedtime (e.g. type of device and duration of use) and sleep (e.g. time in bed, sleep onset latency). On average, athletes spent 8:20 ± 1:21 h in bed each night. Associations between age, time in bed and sleepiness suggested that younger athletes spent more time in bed (B = -0.05, p = 0.001) but felt sleepier (r = -0.32, p < 0.01) than older athletes. On average, athletes mostly used electronic devices for 0-30 min prior to sleep. The use of multiple devices in the evening was associated with more perceived difficulty in falling asleep (B = 0.22, p = 0.03), but no associations existed with other sleep variables. In summary, younger athletes may require later start times or improved sleep quality to resolve excessive sleepiness.