Interactive vs passive screen time and nighttime sleep duration among school-aged children

Sleep and Technology in Early Childhood

Research suggests that technology use is associated with poorer sleep outcomes among children less than 6 years of age. These associations are evident regardless of the type of technology studied, although evening exposure may have the greatest impact compared with technology use during other parts of the day. More work is needed, particularly given that technology use is relatively high among young children. Clinicians should assess patients' technology exposure, including before bedtime, to assess whether sleep issues stem from children's technology use. Moreover, clinicians should educate caregivers about the association between technology use and sleep problems among young children.

The Impact of Screen Time on Sleep Patterns in School-Aged Children: A Cross-Sectional Analysis

BACKGROUND

In a world filled with technology, there's concern about the impact of screen time on children and teenagers. A recent study of 11,875 children aged nine to 10 in the US explored how screen time affects mental health, behaviour, school performance, sleep, and friendships. The results indicate that more screen time is mildly linked to worse mental health, more behaviour problems, lower academic performance, and poorer sleep, but slightly better peer relationships. However, these connections were weak, with socioeconomic status (SES) having a stronger influence on these outcomes. The study doesn't prove that screen time causes these issues, suggesting that increased screen time might not be directly harmful to children in this age group. The research adds to the understanding of how screen time impacts children's well-being and highlights the importance of promoting healthy habits. Our study aims to add to this literature by examining how screen time impacts sleep quality, dream recall, and academic performance in school-aged children. Understanding the potential consequences of screen time is crucial for promoting healthy habits and ensuring the overall well-being of children. Our research seeks to provide further insights into the relationship between screen time and key aspects of children's lives as its prevalence continues to rise.

METHODS

The research incorporates a cohort of 1000 school-aged children, bifurcated evenly into two categories based on their daily screen exposure: a low screen time group (less than one hour daily, n = 500) and a high screen time group (over three hours daily, n = 500). The study probes into the correlation between screen time and various health parameters, such as sleep patterns, dream recall, and academic prowess.

RESULTS

The analysis showed that children with low screen time had better sleep efficiency (90% vs. 75%), more frequent dream recall (70% vs. 30%), fewer nocturnal awakenings (0.5 vs. 1.5 times weekly), less daytime sleepiness (20% vs. 60%), and higher physical activity levels (60 vs. 30 minutes per day) compared to those with high screen time. They also had less weekend sleep variability (1.2 hours) and a lower risk of circadian rhythm disturbances (20% increased risk in the high screen time group). Additionally, a screen-free bedroom was more common in the low screen time group (85% vs. 30%), and parental involvement in sleep routines was higher (90% vs. 40%). Academically, the low screen time group achieved higher grades ('A' to 'A+' vs. 'B'), and they had more face-to-face social interactions (two vs. one hour per day).

CONCLUSION

Escalating screen time is correlated with detrimental impacts on sleep efficiency, dream recall, physical activity, circadian rhythms, and academic performance in school-aged children. Fostering a screen-free bedroom environment and augmenting parental involvement in sleep routines may alleviate these adverse effects.

Correlations between sleep architecture and sleep-related masseter muscle activity in children with sleep bruxism

BACKGROUND

Sleep bruxism (SB) occurring during No-REM (nREM) sleep and increase in microarousals per hour have been described in adults, but not in children.

OBJECTIVE

To assess the correlation between sleep architecture and masseter muscle activity related to sleep bruxism (SB/MMA) in children.

MATERIALS AND METHODS

Forty-three children aged 7-12 years (mean age: 9.4 ± 1.3) with confirmed SB underwent a two-night polysomnographic (PSG) study in a sleep laboratory, for accommodation (first night) and data collection (second night). Data on sleep architecture (total sleep duration (TSD), sleep efficiency (SE), sleep onset latency (SOL), REM and nREM sleep duration and proportion and microarousals/hour during REM and nREM sleep) and episodes/hour of SB/MMA were recorded. Single and multiple-variable linear regression analyses were performed to assess the correlation between data on sleep architecture (predictors) and SB/MMA (dependent variable).

RESULTS

Shorter TSD, REM and nREM stage 1 sleep duration, longer SOL and more microarousals/hour during REM and nREM sleep were found to be positive predictors of SB/MMA in children in the multiple-variable regression analysis (R2  = 0.511).

CONCLUSION

Within the limitations of this study, it can be concluded that SB/MMA is correlated with altered sleep architecture in children (shorter total sleep duration (TSD), shorter nREM and REM sleep and higher microarousals during REM and nREM sleep). Nevertheless, the clinical significance of these findings need to be demonstrated in future studies.

The effect of solution-focussed education and counselling on problematic internet usage, sleep quality and school achievement: A randomized controlled trial

AIM

The aim of this study was to determine the effects of solution-focussed education and counselling on problematic internet usage, sleep quality and school achievement.

METHODS

This randomized controlled trial was conducted between January - December 2016 with 44 adolescents who participated in a solution-focussed intervention to address their problematic internet usage and poor sleep quality. After the intervention, the teens were followed up for 6 months to measure problematic Internet usage, sleep quality and school achievement using the Internet Addiction Test, Pittsburg Sleep Quality Index, Parent-Child Internet Addiction Scale and the students' end-of-term school grades. Data were analysed in Statistical Package for the Social Sciences programme using Chi-square test, Independent t test, Man-Whitney U test, Friedman test and Spearman correlation analysis.

RESULTS

The median Internet Addiction Test and Pittsburg Sleep Quality Index scores of the adolescents in the intervention group were significantly lower than those of the controls (P < 0.05), and there was a positive and moderate association between problematic Internet usage and sleep quality in both groups after the follow-up (r = 0.537, P = 0.010; r = 0.576 P = 0.005).

CONCLUSION

The education and counselling intervention decreased problematic Internet usage and increased sleep quality. There was also an improvement in school achievement, but the difference was not significant.

Relationships between screen viewing and sleep quality for infants and toddlers in China: A cross-sectional study

AIM

Currently young children have more opportunity to access all kinds of media, while their sleep duration has been steadily decreasing. However, little is known about the relationships between screen viewing and sleep quality, and the reasons of screen viewing for children under three years old in China. This study aimed to describe the relationships between screen viewing and sleep quality of infants and toddlers in mainland China.

METHODS

A cross-sectional study was conducted. Eight hundred twenty-seven children were recruited at a health care unit from a university affiliated hospital in China, and the questionnaires were completed by their parents. An extended Brief Infant Sleep Questionnaire and a Screen Viewing Questionnaire were used to collect information on children's sleep quality and screen viewing. Multivariate linear regression models were used to assess the relationships between screen viewing and sleep quality among infants and toddlers, adjusted for sociodemographic variables.

RESULTS

Of the 827 children, 26.9% of the infants and 61.4% of the toddlers did not comply with the World Health Organization (WHO) guideline on screen time. Even after adjusting for the sociodemographic covariates for both infants and toddlers, negative relationships between screen time and total sleep time (P < 0.001), and screen time and nighttime sleep (P < 0.001) existed. TV viewing time was negatively related to infants' total sleep time (β = -0.15, P < 0.001) and toddlers' nighttime sleep (β = -0.1, P < 0.05). Smartphone viewing time was negatively related to toddlers' total sleep time (β = -0.12, P < 0.05) and daytime sleep (β = -0.22, P < 0.05). Parents who offered screen media for children when they needed to do house chores were more likely to report that their children had less total sleep time (β = -0.1, P < 0.05) and shorter longest sleep episode (β = -0.1, P < 0.05).

CONCLUSION

The majority of toddlers did not meet the WHO guidelines on screen time in China. Screen time was negatively related to total sleep time and nighttime sleep among infants and toddlers. Practical strategies, such as education programs on children's screen viewing, more outdoor exercises and indoor parent-child activities, providing other educational materials instead of screening, early sleep, restricted use of TVs and smartphones, and screen co-viewing, are needed to improve young children's sleep quality and promote their development.

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

Background

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

Prevalence of Sleep Disorders in Adolescents and its Relation with Screen Time during the COVID-19 Pandemic Era

BACKGROUND: Sleep disorders encompass disturbances in the amount, quality, or timing of sleep. Several factors have contributed to sleep disorders in adolescents, including the use of electronic devices. In the COVID-19 pandemic era, there is a rising trend of screen time. AIM: The objective of the study was to identify the prevalence of sleep disorders in adolescents and its relation with screen time during the COVID-19 pandemic era. METHODS: This is a cross-sectional study involving students aged 15–18 years at three State High School, Denpasar, and Santo Yoseph Senior High School, Denpasar, in August 2020, using purposive sampling method. Data collections on characteristics of the subjects and Pittsburgh Sleep Quality Index (PSQI) were performed using Google Forms. Statistical analysis was performed using Chi-square test. RESULTS: A total of 243 students participated in this study, of which 39 students were excluded due to chronic diseases and consumption of caffeine within 6 h before bedtime. Sleep disorder was found in 30.4% of subjects and mostly characterized by sleep duration of <8 h (62.9%). Analysis of the association between screen time and sleep disorders showed a significant result (PR = 3.8, 95%CI = 1.09–13.1, p = 0.02). CONCLUSION: The prevalence of sleep disorders in adolescents is considerably high. There is an association between screen time and sleep disorders that occur in adolescents during the COVID-19 pandemic era.

Contemporary screen time modalities among children 9-10 years old and binge-eating disorder at one-year follow-up: A prospective cohort study

OBJECTIVE

To determine the prospective associations between contemporary screen time modalities in a nationally representative cohort of 9-10-year-old children and binge-eating disorder at one-year follow-up.

METHOD

We analyzed prospective cohort data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,025). Logistic regression analyses were conducted to estimate associations between baseline child-reported screen time (exposure) and parent-reported binge-eating disorder based on the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-5, outcome) at one-year follow-up, adjusting for race/ethnicity, sex, household income, parent education, BMI percentile, site, and baseline binge-eating disorder.

RESULTS

Each additional hour of total screen time per day was prospectively associated with 1.11 higher odds of binge-eating disorder at 1-year follow-up (95% CI 1.05-1.18) after adjusting for covariates. In particular, each additional hour of social networking (aOR 1.62, 95% CI 1.18-2.22), texting (aOR 1.40, 95% CI 1.08-1.82), and watching/streaming television shows/movies (aOR 1.39, 95% CI 1.14-1.69) was significantly associated with binge-eating disorder.

DISCUSSION

Clinicians should assess screen time usage and binge eating in children and adolescents and advise parents about the potential risks associated with excessive screen time.

Sleep and Technology in Early Childhood

Research suggests that technology use is associated with poorer sleep outcomes among children less than 6 years of age. These associations are evident regardless of the type of technology studied, although evening exposure may have the greatest impact compared with technology use during other parts of the day. More work is needed, particularly given that technology use is relatively high among young children. Clinicians should assess patients' technology exposure, including before bedtime, to assess whether sleep issues stem from children's technology use. Moreover, clinicians should educate caregivers about the association between technology use and sleep problems among young children.

Temporal association between objectively measured smartphone usage, sleep quality and physical activity among Chinese adolescents and young adults

We studied the association between objectively measured smartphone usage and objectively measured sleep quality and physical activity for seven consecutive days among Hong Kong adolescents and young adults aged 11-25 years (n = 357, 67% female). We installed an app that tracked the subjects' smartphone usage and had them wear an ActiGraph GT3X accelerometer on their wrist to measure their sleep quality and physical activity level. Smartphone usage data were successfully obtained from 187 participants (52.4%). The participants on average spent 2 h 46 min per day on their smartphone. Multilevel regression showed that 1 min of daytime smartphone usage was associated with 0.07 min decrease in total sleeping time that night (p = .043, 95% confidence interval [CI]: -0.14, -0.003). Broken down for different usage purposes, 1 min of daytime social network usage and games and comics was associated with a 0.28 (p = .02, 95% CI: -0.52, -0.04) min and 0.18 min (p = .01, 95% CI: -0.32, -0.04) decrease in total sleeping time that night, respectively. One minute of daytime smartphone usage was associated with an increase of 4.55 steps in the number of steps (p = .001, 95% CI: 1.77, 7.34) on the next day. To conclude, time spent on a smartphone in the daytime was associated with total sleeping time that night and number of steps the next day, but was not associated with sleep efficiency, wake after sleep onset and moderate-to-vigorous-intensity activity (MVPA) among Hong Kong adolescents and young adults.

The Effect of Timing and Type of Exercise on the Quality of Sleep in Trained Individuals

Sleep is an extremely important component for overall health and for a well-balanced training program. Recent studies have highlighted the interaction between sleep, recovery, and performance in elite and recreational athletes alike. Exercise has been known to affect the quality of sleep, nevertheless the impact is not well understood in the current research, particularly the effects of exercise timing and intensity on sleep quality. The purpose of this study was to understand if exercise timing and intensity significantly impact sleep quality among recreational exercisers. The participants involved were recreational exercisers who were self-grouped into an AM or PM exercise group. They participated in a seven-day quantitative, quasi-experimental, exploratory study wearing an Actigraph watch. The participant's intensity was also self-grouped into moderate intensity or high intensity based on criteria cut points. Data was analyzed using a factorial ANOVA to examine if there was a significant difference between exercise timing and intensity on sleep quality of the participants. There were no significant differences in sleep quality in either the time group (AM vs PM) or the intensity group (MOD vs VIG) within the four measures of sleep that were looked at throughout this study; total sleep time, sleep onset latency, sleep efficiency % and wake after sleep onset (TST, SOL, SE, and WASO). Results within both, the AM and PM group and the MOD and VIG group, results showed no significant differences. These results conclude that neither exercise intensity or timing had an effect on sleep quality.

Interventions to control children's screen use and their effect on sleep: A systematic review and meta-analysis

Prolonged viewing of screen-based media is associated with poor sleep in children. Previous systematic reviews have analysed the effectiveness of interventions that aim to limit children's screen use; however, none have evaluated its effect on sleep. The aim of this systematic review was to evaluate the effect of interventions that incorporate strategies to control children's screen use on screen use and sleep. The databases Pubmed, Embase, Eric, Scopus and PsycInfo were searched during October 2017 and updated in February 2019 for experimental studies with a control that assessed interventions to control screen use in children aged 2-14 years and reported both screen use and sleep outcomes. From 3,872 initial records, 11 studies (six randomized control [RCT], four cluster RCT and one cluster, quasi-experimental) were eligible for inclusion. A total of 4,656 children aged 2-13 years were included in the studies. The mean reduction in screen time was 0.56 hr (33 min)/day (95% confidence interval [CI], 0.92, 0.20) and the mean sleep duration increased by 0.19 hr (11 min)/day (95% CI, 0.05, 0.33). Bedtime was advanced by 0.16 hr (10 min) on weekdays and by 1.0 hr at the weekend. Subgroup analyses indicated stronger intervention effects for interventions of shorter duration (<3 months), which specifically targeted screen use or sleep, and those with direct participant contact. In conclusion, small improvements in screen time and sleep duration can be achieved in children. It is not possible to determine if a reduction in screen time directly improves sleep, due to the limited number of studies, the presence of co-interventions, issues with studies' methodological quality and heterogeneity.

Cardiovascular disease risk factor clustering in children and adolescents: a prospective cohort study

OBJECTIVE

The early identification of predictors related to cardiovascular disease risk factor clustering (CVD-RFC) can help prevent chronic disease. We aimed to identify the risk factors for CVD-RFC in adolescents.

METHODS

A prospective longitudinal cohort study design was used to obtain data included in these analyses from school-aged children who participated in the Korean Child-Adolescent Study 2008-2014. A total of 1309 children aged 6-15 years were enrolled. We compared the participants based on the presence or absence of CVD-RFC and examined the cumulative incidence of CVD-RFC.

RESULTS

Of the total 1309 children, 410 (31.32%) had CVD-RFC in adolescence. A higher average household income ≥3 million Korean Republic won (KRW)/month (3-5 million KRW/month: HR 0.75 (95% CI 0.58 to 0.97); ≥5 million KRW/month: HR 0.58 (95% CI 0.44 to 0.77)) was associated with a lower CVD-RFC incidence, while the presence of parental CVD history (HR 1.28 (95% CI 1.04 to 1.57)), overweight or obesity (HR 3.83 (95% CI 3.05 to 4.80)) and shorter sleep duration of 8-9 hour/day (HR 1.80 (95% CI 1.05 to 3.07)) and <8 hour/day (HR 1.93 (95% CI 1.11 to 3.34)) had higher CVD-RFC incidences.

CONCLUSIONS

Obesity in childhood, short sleep duration and parental factors such as low socioeconomic status and parental history of CVD are significant risk factors for the development of CVD-RFC in adolescents. Efforts to create awareness regarding sufficient sleep duration in children via intervention programmes targeting cardiometabolic health in children and special attention to lifestyle modifications and socioeconomic components of the family should be considered.

Youth Screen Media Habits and Sleep: Sleep-Friendly Screen Behavior Recommendations for Clinicians, Educators, and Parents

With the widespread use of portable electronic devices and the normalization of screen media devices in the bedroom, insufficient sleep has become commonplace. In a recent literature review, 90% of included studies found an association between screen media use and delayed bedtime and/or decreased total sleep time. This pervasive phenomenon of pediatric sleep loss has widespread implications. There is a need for basic, translational, and clinical research examining the effects of screen media on sleep loss and health consequences in children and adolescents to educate and motivate clinicians, teachers, parents and youth themselves to foster healthy sleep habits.

Agreement between jaw-muscle activity measurement with portable single-channel electromyography and polysomnography in children

BACKGROUND

Polysomnography (PSG) is the gold standard for sleep bruxism (SB) assessment. High economical costs, complex technical equipment, and unfamiliar laboratory setting limit its use in children.

AIM

To determine the night-to-night variability of electromyography (EMG) episodes during a five-night recording with the GrindCare Measure (GCM), and the agreement in the assessment of masticatory muscle activity (MMA) between GCM and PSG in children.

DESIGN

Forty-seven children from clinics of Universidad CES participated. Each participant was assessed with GCM for five consecutive nights. The last night, children underwent a single-night PSG study, together with the GCM. Spearman correlation coefficients were used to analyze data.

RESULTS

The frequency of SB occurrence was 'sometimes' in 12 (25.5%) and 'usually' in 19 (40.4%) children. Simultaneous measurements with GCM and PSG obtained during the fifth night of measurement were not significantly correlated. Correlation between GCM total EMG episodes and EMG episodes/h and PSG total SB episodes, SB episodes/h, total bursts and burst/h measured with PSG was also not significant.

CONCLUSION

EMG measurement with GCM was not accurate to detect PSG/SB in children. There was not advantage of multiple assessment for five nights with GCM, reducing the impact of night-to-night EMG episodes' variability on the GCM/PSG correlation.

Sleep behaviors in children with different frequencies of parental-reported sleep bruxism

OBJECTIVE

Knowledge on the relationship between sleep bruxism (SB) and sleep behaviors in children is still fragmental, especially when socioeconomic factors are concerned. To assess sleep behaviors in children with different frequencies of proxy-reported SB.

METHODS

Parents of 1475 Colombian children, aged 9.8±1.6years, belonging to 3 different social layers, filled out a questionnaire on their childreńs sleep (Childreńs Sleep Habits Questionnaire [CSHQ]). Differences in sleep behaviors were assessed for the total sample and the three socioeconomic layers, using one-way ANOVA and Bonferroni post-hoc tests or Kruskal-Wallis and Dunn's post-hoc tests, based on the normality of outcome variables.

RESULTS

Most sleep patterns and daytime sleepiness were similar for children with different frequencies of proxy-reported SB, without differences among socioeconomic layers, whilst sleep disorders and parasomnias increased with the frequency of proxy-reported SB, independently on the socioeconomic layer (Bonferroni post-hoc<0.001). The association between sleep-related habits and the frequency of proxy-reported SB was different for each socioeconomic layer.

CONCLUSION

Among the various sleep behaviors under investigation, some sleep disorders and parasomnias seem to be associated with parental-reported SB in children. The influence of socioeconomic conditions on sleep behaviors seems not relevant. Based on these results, more specific studies on the association between different sleep behaviors are needed.

CLINICAL SIGNIFICANCE

Sleep behaviors, sociodemographic and socioeconomic features are correlated with SB in adults. However, in children, good evidence about this topic is lacking. This article give information to help clinicians evaluating sleep behaviors, sociodemographic and socioeconomic characteristics, when assessing sleep bruxism, based on evidence.

Sleep habits and pattern in 1-14 years old children and relationship with video devices use and evening and night child activities

BACKGROUND

Sleep in childhood and adolescence is crucial for mental and physical health; however several researches reported an increasing trend towards a sleep deprivation in this age. Due to the lack of recent epidemiological studies in Italy, the aim of our study was to depict sleep habits and patterns in Italian children aged 1-14 years and to evaluate their relationships with video devices use (TV, tablet, smartphone, PC) and evening/night child activities.

METHODS

A structured interview was conducted during 2015 by 72 Family Pediatricians in 2030 healthy children aged 1-14 years by a cross-sectional survey named "Ci piace sognare". Total sleep duration was calculated, 2015 National Sleep Foundation Recommendations were used as reference. Optimal sleepers were defined children sleeping in own bed all night without awakenings. Multivariable median regression was performed to identify predictors of sleep duration and multivariable logistic regression for predictors of optimal sleep.

RESULTS

Total sleep duration and numbers of awakenings decreased with age. Only 66.9% of children had sleep duration in agreement with Recommendations (50% in 10-14 years group). Before sleeping 63.5% of children used video devices (39.6% at 1-3 years), 39.1% read, 27.5% drank and 19.5% ate. Bottle users at bedtime were 30.8% at 1-3 years, 16.6% at 3-5 years and 4.9% at 5-7 years. Overall, 23.4% of children changed sleeping place during the night, 22.4% referred sleeping problems in the first year of life. Video devices use was negative predictor of sleep duration (-0.25 h [95%CI:-0.35,-0.14], p < 0.001). Optimal sleep was inversely related with bedroom TV (OR 0.63 [0.50,0.79], p < 0.001), with sleeping disorders in the first year (OR 0.62 [0.48,0.80], p < 0.001)), with bottle use (OR 0.64 [0.44,0.94], p < 0.05) and posivively related with high mother's education level (OR 1.44 [1.11,1.88], p < 0.01).

CONCLUSIONS

About one third of 1 to 14 year Italian children sleep less than recommended, one half in teenage. Modifiable risk factors for sleep abnormalities such as video devices use, bedroom TV and bottle use should be target of preventive strategies for a correct sleep. Pediatricians should give priority to the identification of sleep disorders early in life.