Facebook use and sleep quality: Light interacts with socially induced alertness

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.

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.

Daily links between objective smartphone use and sleep among adolescents

INTRODUCTION

Concerns abound on how digital technology such as smartphone use may impair adolescent sleep. Although these linkages are supported in cross-sectional studies, research involving intensive longitudinal assessments and objective measures has called into question the robustness of associations.

METHODS

In this study, a sample of ethnically diverse U.S. adolescents (N = 71; Mage = 16.49; 56% girls) wore Fitbit devices and submitted screenshots of their smartphone screen time, pickups, and notifications over a 14-day period in 2021. The Fitbits recorded nightly sleep quality and sleep onset. Adolescents also completed daily diaries reporting the previous night's sleep onset time and sleep quality.

RESULTS

On days when adolescents engaged in greater nighttime screen time and, to some extent, pickups relative to their own average, they also had poorer sleep outcomes that night. Greater screen time was associated with later self-reported and Fitbit-recorded sleep onset and poorer self-reported sleep quality. Greater pickups was associated with later self-reported and Fitbit-recorded sleep onset. Smartphone use during the day did not relate to sleep outcomes, indicating the importance of distinguishing nighttime from daytime use.

CONCLUSIONS

Parents and clinicians should help adolescents develop healthy digital skills to avoid exacerbating sleep problems that are known to occur during this developmental period.

When and what: A longitudinal study on the role of screen time and activities in adolescent sleep

OBJECTIVES

Previous research has highlighted a link between electronic media use and sleep outcomes, but the nuanced impacts of screen use at different time of day and activities on adolescent sleep are underexplored.

METHODS

831 participants underwent online assessment three times with interval of three months regarding their screen time and activities at specific times of the day, daytime sleepiness was assessed with the Epworth Sleepiness Scale, and sleep outcomes were assessed with the Pittsburgh Sleep Quality Index and Insomnia Severity Index. The associations between time spent on various screen activities, and sleep outcomes were examined respectively after controlling for inter-individual differences using the Random Intercept Cross-Lagged Panel Model models and LMMs.

RESULTS

The RI_CLPM model revealed that both electronic screen time during daytime and after lights off in the evening in Wave1 negatively predicted the sleep quality in Wave2; the nighttime screen time before lights off in Wave1 significantly negatively predicted the seventy of insomnia in Wave2. Whereas no cross-lag and predictive effects of sleep outcomes on screen time were revealed. Moreover, daytime screen exposure, including T.V. watching and social media use, and nighttime music listening were negatively associated with sleep quality. Conversely, nighttime screen time of shopping and working/studying positively influenced sleep quality. Additionally, daytime screen time of T.V. viewing was positively associated with increased insomnia severity, whereas nighttime work/study-related screen time negatively affected insomnia severity. Nighttime screen time of music listening negatively predicted daytime sleepiness.

CONCLUSIONS

The current findings contributed to the existing literature suggesting that the effects of electronic screen time on sleep depended on both the time of day and type of screen activities.

Evolution of Sleep Duration and Screen Time Between 2018 and 2022 Among Canadian Adolescents: Evidence of Drifts Accompanying the COVID-19 Pandemic

PURPOSE

We quantified the joint evolution of sleep duration and screen time between 2018 and 2022 in a large sample of adolescents from Quebec, Canada, to ascertain changes that occurred during the COVID-19 pandemic.

METHODS

A natural experiment design was used to compare variations from year to year and in association with the pandemic outbreak. Using structural equation modeling on data collected between 2018 and 2022 among adolescents attending 63 high schools, we analyzed the joint evolution of sleep duration and screen time while adjusting for previous year values, concurrent flourishing score, sex, age, and family level of material deprivation.

RESULTS

A total of 28,307 adolescents, aged on average 14.9 years, were included in the analyses. Between 2019 and 2022, sleep duration increased by 9.6 (5.7, 13.5) minutes and screen time by 129.2 (120.5, 138.0) minutes on average. In 2022, the adolescents spent almost equal amounts of time sleeping and using screens. Lower flourishing scores were associated with shorter sleep duration and lengthier screen time. Girls' screen time became similar to boys' over time.

DISCUSSION

Adolescents now spend almost equal amounts of time sleeping and using screens, a situation that calls for urgent public health actions. These findings highlight the importance of tracking changes in adolescents' behaviours over time, to design and implement interventions adapted to the changing health needs of different groups.

Promoting adolescent sleep and circadian function: A narrative review on the importance of daylight access in schools

Adolescent sleep disturbances and circadian delays pose significant challenges to mood and daytime functioning. In this narrative review, we explore the impact of light on sleep and highlight the importance of monitoring and managing light exposure in adolescents throughout the day and night. The benefits of daylight exposure in mitigating sleep and circadian disruptions are well-established; however, interventions targeting access to daylight in adolescents remain understudied and underutilized. The primary aim of this narrative review is to bring attention to this gap in the literature and propose the need for institutional-level interventions that promote access to daylight, especially considering adolescents' early school start times and substantial time spent indoors on weekdays. School-led interventions, such as active commuting to school and outdoor curriculums, have promising effects on sleep and circadian rhythms. Additionally, practical measures to optimize natural light in classrooms, including managing blinds and designing conducive environments, should also be considered. While future studies are necessary to facilitate the implementation of interventions, the potential for these school-level interventions to support adolescent sleep health is evident. Aiming for integration of individual-level regulation and institutional-level intervention of light exposure is necessary for optimal outcomes.

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.

Social media use is linked to poor sleep quality: The opportunities and challenges to support evidence-informed policymaking in the UAE

BACKGROUND

This study was conducted among a convenience sample of Ajman University students in UAE between February 2018 and May 2019.

METHODS

All undergraduate and master's degree students from the 1st to 5th year of medical and non-medical colleges. The survey was carried out by distributing a pre-designed, pre-structured questionnaire to the students during lectures. The questionnaires were primarily composed of three sections: demographic characteristics, educational characteristics and sleep quality characteristics. The data were analyzed using STATA version 14.2. Logistic regression analysis was used to investigate the association between sleep characteristics, social media use and other significant risk factors. The P-values < 0.05 were considered to be statistically significant.

RESULTS

The vast majority of the study participants were social media users, and a considerable proportion suffered from poor sleep quality. A significantly increased risk of bad sleep quality and intermittent/anxious sleep patterns were observed among social media users.

CONCLUSION

Health policymakers should fully consider these factors in improving the sleep quality of university students.

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.

The influence of blue light on sleep, performance and wellbeing in young adults: A systematic review

Introduction: Blue light from electronic devices has a bad reputation. It has a wavelength which may influence our circadian rhythm and cause bad sleep. But there are other aspects of blue light exposure which are often overlooked, for example, it may influence performance and wellbeing. However, few resources summarize its effects systematically. Therefore, the goal of this systematic review was to distil the present evidence on blue light exposure and its influence on sleep, performance and wellbeing and discuss its significance for athletes.

Methods: The databases that were searched were Cochrane, Embase, Pubmed, Scopus, and Virtual Health Library. The studies included investigated the influence of blue light exposure on either sleep, performance, wellbeing or a combination of those parameters on healthy humans. Quality assessment was done based on the quantitative assessment tool “QualSyst.”

Results: Summarizing the influence of blue light exposure, the following results were found (expressed as proportion to the number of studies investigating the particular parameter): Fifty percent of studies found tiredness to be decreased. One fifth of studies found sleep quality to be decreased and one third found sleep duration to be decreased. Half of the studies found sleep efficacy to be decreased and slightly less than half found sleep latency to be increased. More than one half of the studies found cognitive performance to be increased. Slightly more than two thirds found alertness to be increased and reaction time to be decreased. Slightly less than half of the studies found wellbeing to be increased.

Conclusion: Blue light exposure can positively affect cognitive performance, alertness, and reaction time. This might benefit sports reliant on team-work and decision-making and may help prevent injury. Blue light might also have negative effects such as the decrease in sleep quality and sleep duration, which might worsen an athlete’s physical and cognitive performance and recovery. Further research should explore if blue light can improve sleep, performance and wellbeing to significantly benefit athletic performance.

Electric lighting, adolescent sleep and circadian outcomes, and recommendations for improving light health

Light is a potent circadian entraining agent. For many people, daily light exposure is fundamentally dysregulated with reduced light during the day and increased light into the late evening. This lighting schedule promotes chronic disruption to circadian physiology resulting in a myriad of impairments. Developmental changes in sleep-wake physiology suggest that such light exposure patterns may be particularly disruptive for adolescents and further compounded by lifestyle factors such as early school start times. This narrative review describes evidence that reduced light exposure during the school day delays the circadian clock, and longer exposure durations to light-emitting electronic devices in the evening suppress melatonin. While home lighting in the evening can suppress melatonin secretion and delay circadian phase, the patterning of light exposure across the day and evening can have moderating effects. Photic countermeasures may be flexibly and scalably implemented to support sleep-wake health; including manipulations of light intensity, spectra, duration and delivery modality across multiple contexts. An integrative approach addressing physiology, attitudes, and behaviors will support optimization of light-driven sleep-wake outcomes in adolescents.

Facebook Addiction Partially Mediated the Association Between Stress Symptoms and Sleep Disturbance Among Facebook Users

Stress symptoms, Facebook addiction, and sleep disturbances have important effects on the health of every individual. However, very few studies have examined the association between stress symptoms, Facebook addiction, and sleep disturbances. This study investigated the mediating effect of Facebook addiction on the association between stress symptoms and sleep disturbances among Facebook users in Vietnam. Three hundred fifty-four Facebook users in Vietnam have completed measures to assess symptoms of stress, levels of Facebook addiction, and sleep disturbances. In the sample, stress was positively associated with sleep disturbances and Facebook addiction partially mediated the association between stress and sleep disturbance (stress was positively associated with Facebook addiction and Facebook addiction was positively associated with sleep disturbances). Thus, our findings demonstrate that stressful individuals tend to be addicted to Facebook, which increase the risk of sleep disturbances. Therefore, interventions aimed at improving sleep quality for Facebook users should focus on reducing stress and reducing dependence on Facebook.

Blue light emission spectra of popular mobile devices: The extent of user protection against melatonin suppression by built-in screen technology and light filtering software systems

Blue light, with wavelengths shorter than 440-450 nm, is the most energetic radiation of the visible spectrum for the human eye, and its possible multiple effects on the human nervous and other systems have become a line of research by many investigators. The use of mobile devices whose screens emit various amounts of blue light is common nowadays. This study evaluated the efficiency of the blue light screen and control software technologies of eight different mobile devices. Emitted screen spectra of the different mobile devices according to different conditions of blue light emission software control were obtained using a spectrograph, and the derived spectra were compared with the melatonin suppression action spectrum. The amount of blue light emission and predicted melatonin suppression varied according to the unique software control and screen technology of each device. AMOLED screen technology, compared with other screen technologies, achieved better control of blue light emission. The effect of blue light filters depends on the screen technology; however, the melatonin suppression index of mobile devices is not reduced sufficiently by the use of blue light-attenuating software.

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.

SleepOMICS: How Big Data Can Revolutionize Sleep Science

Sleep disorders have reached epidemic proportions worldwide, affecting the youth as well as the elderly, crossing the entire lifespan in both developed and developing countries. "Real-life" behavioral (sensor-based), molecular, digital, and epidemiological big data represent a source of an impressive wealth of information that can be exploited in order to advance the field of sleep research. It can be anticipated that big data will have a profound impact, potentially enabling the dissection of differences and oscillations in sleep dynamics and architecture at the individual level ("sleepOMICS"), thus paving the way for a targeted, "one-size-does-not-fit-all" management of sleep disorders ("precision sleep medicine").