Abstract

BackgroundThroughout the developed world, adolescents are growing up with increased access to and engagement with a range of screen-based technologies, allowing them to encounter ideas and people on a global scale from the intimacy of their bedroom. The concerns about digital technologies negatively influencing sleep are therefore especially noteworthy, as sleep has been proven to greatly affect both cognitive and emotional well-being. The associations between digital engagement and adolescent sleep should therefore be carefully investigated in research adhering to the highest methodological standards. This understood, studies published to date have not often done so and have instead focused mainly on data derived from general retrospective self-report questionnaires. The value of this work has been called into question by recent research showing that retrospective questionnaires might fail to accurately measure these variables of interest. Novel and diverse approaches to measurement are therefore necessary for academic study to progress.MethodsThis study analyses data from 11,884 adolescents included in the UK Millennium Cohort Study to examine the association between digital engagement and adolescent sleep, comparing the relative effects of retrospective self-report vs. time-use diary measures of technology use. By doing so, it provides an empirical lens to understand the effects of digital engagement both throughout the day and before bedtime and adds nuance to a research area primarily relying on retrospective self-report.ResultsThe study finds that there is a small negative association relating digital engagement to adolescent sleep both on weekdays and weekend days (median standardized association βweekday = −0.06 and βweekend = −0.03). There is a more negative association between digital engagement and total sleep time on weekdays compared to weekend days (median standardized βweekday = −0.08, median standardized βweekend = −0.02), while there is no such difference when examining adolescents’ bedtime. Surprisingly, and contrary to our expectations, digital technology use before bedtime is not substantively associated with the amount of sleep and the tardiness of bedtime in adolescents.ConclusionsResults derived from the use of transparent Specification Curve Analysis methods show that the negative associations in evidence are mainly driven by retrospective technology use measures and measures of total time spent on digital devices during the day. The effects are overall very small: for example, an additional hour of digital screen time per day was only related to a 9 min decrease in total time spent sleeping on weekdays and a 3 min decrease on weekends. Using digital screens 30 min before bed led to a 1 min decrease in total time spent sleeping on weekdays and weekends. The study shows that more work should be done examining how to measure digital screen time before interventions are designed.

Highlights

  • British children spend an average of 2 h and 11 min each day online, using a diverse range of smartphone, tablet and computer screens (Ofcom, 2019)

  • In this study we found that digital technology use is negatively correlated with sleep measured on both weekends and weekdays, these correlations were small

  • While there were not many pronounced differences between the relations on a weekday compared to a weekend day, weekdays showed a more negative association between digital technology use and total time spent sleeping, something that could hint at the rigidity of waking times on school days

Read more

Summary

Introduction

British children spend an average of 2 h and 11 min each day online, using a diverse range of smartphone, tablet and computer screens (Ofcom, 2019) This engagement oftentimes continues past bedtime: research shows that nearly two thirds (62%) of children aged 12–15 are granted permission by their caretakers to take their mobile phone to bed (Ofcom, 2019). Given this emerging norm, it is an understandable concern that digital screen engagement might impact both sleep quantity and quality (Owens, 2014).

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.