Objectively-Measured Smartphone Usage, Sleep Quality, and Physical Activity Among Chinese Adolescents and Young Adults

Abstract

Objectives: 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 (n = 357, 67% female).Methods: 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%).Results: The participants on average spent 2 hours 46 minutes per day on their smartphone. Multilevel regression showed that, among secondary school students, one minute of daytime smartphone usage was associated with 0.12 minute decrease in total sleeping time that night (p = 0.042, 95% CI: -0.23, -0.007). One minute of bedtime smartphone usage was associated with 0.32 minute increase in wake after sleep onset that night (p = 0.04, 95% CI: 0.02, 0.62). One minute of smartphone usage during sleep was associated with sleep efficiency (β = 0.013%, p = 0.01, 95% CI: 0.003%, 0.023%) and WASO (β=-0.05, p = 0.04, 95% CI: -0.10, -0.005). One minute of daytime smartphone usage was associated with 7.15 steps increase in the number of steps (p = 0.02, 95% CI: 1.02, 13.28) among secondary school students and 3.52 steps increase in the number of steps (p = 0.03, 95% CI: 0.37, 6.66) among university students on the next day.Conclusion: Time spent on smartphone was associated with total sleeping time, the number of steps, and MVPA among Hong Kong adolescents and young adults.

Smartphone use and daily cognitive failures: A critical examination using a daily diary approach with objective smartphone measures

“…The adjusted model controlled for participant‐level demographic factors (age, sex, monthly household income, and subjective socioeconomic status) as well as day‐level variables. In order to account for within‐person fluctuations in daily stress and affective states as potential confounds, we controlled for stressor exposure, positive affect, and negative affect (Lee et al, 2020; Majeed et al, 2021) in our adjusted model at Level 1 (i.e., daily) and Level 2 (i.e., person‐level averages). All non‐binary variables measured at Level 2—age, monthly household income, subjective socioeconomic status—were grand‐mean centered while daily positive affect and negative affect were person‐mean centered with their person means reintroduced at Level 2.…”