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

Development of a Protocol for Objectively Measuring Digital Device Use in Youth

INTRODUCTION

Screen time is predominantly measured using questionnaires assessing a limited range of activities. This project aimed to develop a coding protocol that reliably identified screen time, including device type and specific screen behaviors, from video-camera footage.

METHODS

Screen use was captured from wearable and stationary PatrolEyes video cameras in 43 participants (aged 10-14 years) within the home environment (May-December 2021, coding in 2022, statistical analysis in 2023). After extensive piloting, the inter-rater reliability of the final protocol was determined in 4 coders using 600 minutes of footage from 18 participants who spent unstructured time on digital devices. Coders independently annotated all footage to determine 8 device types (e.g., phone, TV) and 9 screen activities (e.g., social media, video gaming) using Observer XT (behavioral coding software). Reliability was calculated using weighted Cohen's κ for duration per sequence (meets criteria for total time in each category) and frequency per sequence (meets criteria for total time in each category and order of use) for every coder pair on a per-participant and footage type basis.

RESULTS

Overall reliability of the full protocol was excellent (≥0.8) for both duration per sequence (κ=0.89-0.93) and the more conservative frequency per sequence (κ=0.83-0.86) analyses. This protocol reliably differentiates between different device types (κ=0.92-0.94) and screen behaviors (κ=0.81-0.87). Coder agreement ranged from 91.7% to 98.8% across 28.6-107.3 different instances of screen use.

CONCLUSIONS

This protocol reliably codes screen activities in adolescents, offering promise for improving the understanding of the impact of different screen activities on health.

Longitudinal reallocations of time between 24-h movement behaviours and their associations with inflammation in children and adolescents: the UP&DOWN study

BACKGROUND

While there is evidence that physical activity, sedentary behaviour (SB) and sleep may all be associated with modified levels of inflammatory markers in adolescents and children, associations with one movement behaviour have not always been adjusted for other movement behaviours, and few studies have considered all movement behaviours in the 24-hour day as an exposure.

PURPOSE

The aim of the study was to explore how longitudinal reallocations of time between moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), SB and sleep are associated with changes in inflammatory markers in children and adolescents.

METHODS

A total of 296 children/adolescents participated in a prospective cohort study with a 3-year follow-up. MVPA, LPA and SB were assessed by accelerometers. Sleep duration was assessed using the Health Behavior in School-aged Children questionnaire. Longitudinal compositional regression models were used to explore how reallocations of time between movement behaviours are associated with changes in inflammatory markers.

RESULTS

Reallocations of time from SB to sleep were associated with increases in C3 levels (difference for 60 min/d reallocation [d₆₀] = 5.29 mg/dl; 95% confidence interval [CI] = 0.28, 10.29) and TNF-α (d₆₀ = 1.81 mg/dl; 95% CI = 0.79, 15.41) levels. Reallocations from LPA to sleep were also associated with increases in C3 levels (d₆₀ = 8.10 mg/dl; 95% CI = 0.79, 15.41). Reallocations from LPA to any of the remaining time-use components were associated with increases in C4 levels (d₆₀ ranging from 2.54 to 3.63 mg/dl; p < 0.05), while any reallocation of time away from MVPA was associated with unfavourable changes in leptin (d₆₀ ranging from 3088.44 to 3448.07 pg/ml; p < 0.05).

CONCLUSIONS

Reallocations of time between 24-h movement behaviours are prospectively associated with some inflammatory markers. Reallocating time away from LPA appears to be most consistently unfavourably associated with inflammatory markers. Given that higher levels of inflammation during childhood and adolescence are associated with an increased risk of chronic diseases in adulthood, children and adolescents should be encouraged to maintain or increase the level of LPA to preserve a healthy immune system.

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.

Association of Night-Time Screen-Viewing with Adolescents' Diet, Sleep, Weight Status, and Adiposity

Night-time screen-viewing (SV) contributes to inadequate sleep and poor diet, and subsequently excess weight. Adolescents may use many devices at night, which can provide additional night-time SV. Purpose: To identify night-time SV patterns, and describe differences in diet, sleep, weight status, and adiposity between patterns in a cross-sectional and longitudinal manner. Methods: Adolescents (10–16 y) reported devices they viewed at night and completed food recalls. Accelerometry, anthropometrics, and imaging were conducted to measure sleep, weight status, and adiposity, respectively. Latent class analysis was performed to identify night-time SV clusters. Linear regression analysis was used to examine associations between clusters with diet, sleep, weight status, and adiposity. Results: Amongst 273 adolescents (12.5 ± 1.9 y, 54% female, 59% White), four clusters were identified: no SV (36%), primarily cellphone (32%), TV and portable devices (TV+PDs, 17%), and multiple PDs (17%). Most differences in sleep and adiposity were attenuated after adjustment for covariates. The TV+PDs cluster had a higher waist circumference than the no SV cluster in cross-sectional analysis. In longitudinal analysis, the primarily cellphone cluster had less change in waist circumference compared to the no SV cluster. Conclusions: Directing efforts towards reducing night-time SV, especially TV and PDs, may promote healthy development.

Use of digital screens by adolescents and association on sleep quality: a systematic review

This study aimed to analyze the influence of digital screen use on adolescents’ quality of sleep. This systematic review was recorded on PROSPERO (CRD42020203403) and conducted according to PRISMA guidelines. Studies covering adolescents from 10 to 19 years were included without language or publication restrictions which answered the following guiding question: “Does the use of digital screen influence adolescents’ quality sleep?”. Article search included the following databases: (MEDLINE/PubMed), LILACS, SciELO, Scopus, EMBASE, Web of Science, IBECS, Cochrane Library, ClinicalTrials.gov, and Open Gray. The following descriptors were used: “Sleep Quality”, “Screen Time”, and “Adolescent”. The Newcastle-Ottawa Scale (NOS) assessed the methodological quality of the cohort studies, and a modified NOS was used to assess the cross-sectional ones. In total, 2,268 articles were retrieved, of which 2,059 were selected for title and abstract reading, after duplicates were deleted. After this stage, 47 articles were selected for full reading, resulting in the 23 articles which compose this review. Excessive use of digital screens was associated with worse and shorter sleep, showing, as its main consequences, night awakenings, long sleep latency, and daytime sleepiness. The use of mobile phones before bedtime was associated with poor quality of sleep among adolescents. Our evaluation of the methodological quality of the chosen studies found seven to be poor and 16, moderate.

Quantity, Content, and Context Matter: Associations Among Social Technology Use and Sleep Habits in Early Adolescents

PURPOSE

This study aimed to investigate the associations of social technology access and content, bedtime behaviors, parental phone restrictions, and timing and duration of sleep on school nights in early adolescents.

METHODS

Adolescents (aged 11-15 years, n = 772) in the Northeast U.S. completed an online survey during or after school in spring 2019.

RESULTS

Quantity of social technology use (e.g., checking social media, problematic internet behaviors, mobile use), content viewed (e.g., emotional or violent videos, risky behaviors), and social context (e.g., bedtime behaviors, starting social media at an early age) were significantly related to later bedtimes and fewer hours of sleep on school nights. Parental rules restricting mobile phone and online use before bed and obtaining a smartphone at a later age were associated with increased sleep time and earlier bedtime.

CONCLUSIONS

Quantity, content, and context of social technology use may affect sleep timing and duration in early adolescents.

Youths' Habitual Use of Smartphones Alters Sleep Quality and Memory: Insights from a National Sample of Chinese Students

A growing body of work has been devoted to studying the smartphone addiction in youths and its impact on their lives, but less is known about the predictors and effects of youth habitual use of smartphones. Guided by social cognitive theory, this study investigates how habitual smartphone use affects sleep quality and everyday memory based on a nationally representative sample of Chinese students (N = 2298). It uses a cluster-randomized sampling with stratification of different areas, consisting of both urban and rural students aged 6–18 years from elementary, middle, and high schools across China. It found that Chinese students exhibited a habitual smartphone use, who were generally confident in using mobile devices, but few had smartphone addiction. Significant gender and age differences were identified concerning the habitual use of smartphone. Specifically, boys demonstrated higher levels of habitual use and smartphone self-efficacy than the girls. High school students showed the highest level of habitual smartphone use compared to those in elementary and middle schools. Smartphone use duration, frequency, and self-efficacy predicted the habitual use, which also led to poorer sleep quality and worse memory outcomes. Prebedtime exposure moderated the relationship between habitual smartphone uses and sleep quality. The results show that students’ habitual smartphone use had a significant impact on their health, cognition and more, even when they exhibited little smartphone addiction. The findings contribute to a better understanding of smartphone impact on school-age youths.