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

Smartphone use and well-being of adolescent girls: a population-based study

BACKGROUND AND OBJECTIVES

Recent studies have reported an increasing incidence of anxiety among adolescent girls, and associated this with self-reported social media use. This study aimed to measure smartphone and social media use objectively and to evaluate its associations with measures of mental health and well-being.

METHODS

In autumn 2022, we recruited a cohort of 1164 first-year female students from 21 socioeconomically diverse high schools. Students responded to an online survey comprising validated questionnaires (Bergen Social Media Addiction Scale (BSMAS), Generalised Anxiety Disorder-7, and Body Appreciation Scale 2) and visual analogue scales of current health, mood, tiredness, and loneliness. We also requested that they attach screenshots depicting their smartphone use.

RESULTS

Among participants (mean age 16.3 years), 16% (n=183) had possible social media addiction and 37% (n=371) exceeded the cut-off for possible anxiety disorders. The BSMAS scores were associated with higher anxiety (r=0.380) and poorer body image (r=-0.268), poorer health (r=-0.252), lower mood (r=-0.261), greater tiredness (r=0.347), and greater loneliness (r=0.226) (p<0.001 for all). Among the 564 adolescents (48%) who sent screenshots of their smartphone use, average daily use was 5.8 hours (SD 2.2), including 3.9 hours (SD 2.0) of social media. Participants who sent screenshots had a higher grade point average than participants without screenshot data, but similar BSMAS and well-being measures.

CONCLUSIONS

Consistent with other studies, we found social media addiction was common among adolescent girls and was associated with poorer mental health and well-being. Measures should be taken to protect adolescents from the potential harmful effects of social media use.

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.

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.

Screen use and sleep duration and quality at 15 years old: Cohort study

Objective/background

The evidence on the association between screen use and sleep of adolescents is mainly based on studies about time watching television, with a few examining time using computers, videogames, and mobile devices. Our aim was to investigate the association between screen time for entertainment (watching TV, using computer, or playing games on tablets, smartphones, or videogame consoles) and sleep duration and self-reported sleep quality, among adolescents aged 15 years.

Methods

With data from the 2004 Pelotas Birth Cohort, sleep duration was assessed with questions extracted from the Munich Chronotype Questionnaire and quality was self-reported. Adjusted β coefficients and prevalence ratios (PR) with (95% confidence intervals) were obtained, respectively, by linear and Poisson regressions.

Results

1,949 adolescents had information about screen time and sleep quality, and 1,851 about screen time and sleep duration. The median screen time was 4.5hs/24hs. The mean sleep duration was 7.6hs/24hs and the prevalence of bad sleep was 17.3% (15.7-19.0%). There was an inverse relationship between screen time and sleep duration. When compared with those with less than 2hs/24hs of screen time, adolescents with 6-8.8hs/24hs and ≥9hs experienced, respectively, 23.4 and 32.4 min reduction in sleep duration (β = -0.39; -0.62;-0.16 and β = -0.54; -0.77;-0.30). Adolescents with ≥9hs of screen time were 60% more likely to report bad sleep than those with less than 2hs/24hs (PR: 1.60; 1.10-2.32).

Conclusions

The median time spent using screens was longer than recommended. Screen use for ≥6hs/24hs was associated with a shorter sleep duration, and ≥9hs/24hs with poor sleep quality.

Bidirectional relations between problematic smartphone use and bedtime procrastination among Chinese university students: Self-control as a mediator

OBJECTIVE

Based on theoretical and empirical evidence, this study examined the longitudinal relationship between problematic smartphone use and bedtime procrastination and the potential mediating role of self-control.

METHODS

Between November 2021 and November 2022, a three waves longitudinal design was employed. Wave 1 included 622 Chinese college students (46.95% male, Mage = 18.16, SD = 0.73), with 6-month intervals between waves. The data was collected using self-report assessments.

RESULTS

The results of the cross-lagged panel models show that problematic smartphone use positively predicted later bedtime procrastination, and the bedtime procrastination also positively predicted later problematic smartphone use among college students. More importantly, self-control played a mediating role in their bidirectional predictive relationship.

CONCLUSIONS

These findings add to the understanding of the causal relationship between problematic smartphone use and bedtime procrastination and reveal the core psychological mechanisms underlying their vicious cycle, with important practical implications for the prevention and intervention of problematic smartphone use and sleep problems.

Links Between Objectively-Measured Hourly Smartphone Use and Adolescent Wake Events Across Two Weeks

PURPOSE

Psychosocial and bioregulatory pressures threaten sleep during adolescence. Although recent work suggests that the ubiquity of smartphone use throughout adolescence may also relate to poorer sleep outcomes, most existing research relies upon self-report and retrospective measures. This study drew upon objective measures of smartphone use and sleep at the hourly level to understand how smartphone use was associated with the duration of wake events during sleeping hours.

METHODS

Across a 14-day daily study, 59 racially and ethnically diverse adolescents ages 15 to 18 had their sleep assessed via Fitbit Inspire 2 devices and uploaded screenshots of their screen time, pickups, and notifications as logged by their iPhone's iOS. Multi-level modeling was performed to assess hourly level associations between adolescent smartphone use and wake-events during their sleep sessions (N = 4,287 hourly cases).

RESULTS

In hours during adolescents' sleep session with more screen time or pickups, adolescents had longer wake event duration. More notifications in a given hour were not associated with wake event duration in the same hour.

CONCLUSIONS

Using objectively measured smartphone and sleep data collected at the hourly level, we found that during sleeping hours, when adolescents are actively engaging with their smartphones, their sleep is disrupted, such that their wake events are longer in that hour.

Associations between combinations of 24-h movement behaviors and physical fitness among Chinese adolescents: Sex and age disparities

OBJECTIVE

To analyze the relationship between 24-h movement behaviors and adolescents' physical fitness, with sex difference and age disparity explored specifically.

METHODS

A total of 135 852 Chinese adolescents aged 13-22 years were included in this cross-sectional study. Self-reported 24-h movement behavioral times, including moderate to vigorous physical activity (MVPA), recreational screen, and sleep, were identified as meeting guidelines based on Canadian recommendations. Physical fitness indicator (PFI) was calculated through sex- and age-specific z scores of body mass index, forced vital capacity, 50 m dash, sit-and-reach, standing long jump, body muscle strength, and endurance running, and then classified as: low level (<20th), middle level (20th-80th), and high level (>80th). Mixed effect logistic regression was applied to analyze the association, and interaction terms were constructed to prove the sex and age disparities.

RESULTS

Only 12.4% of adolescents aged 13-22 years met all three recommendations. The number of meeting guidelines exhibited a typical dose-response relationship with high level PFI (OR = 1.22 [95% CI: 1.19-1.25]), and in detail, meeting MVPA + recreational screen (OR = 2.29 [95% CI: 2.09-2.51]) or MVPA-only (OR = 2.16 [95% CI: 1.93-2.41]) guidelines were better associated with high-level PFI. Besides, meeting MVPA-only guideline was proved with stronger association with high-level PFI for boys (p-interaction = 0.005). The dose-response relationship in boys of the number of guidelines met with PFI was stronger in 19- to 22-year-olds (p-interaction <0.001) and 16- to 18-year-olds (p-interaction = 0.001) than that in 13- to 15-year-olds.

CONCLUSION

The prevalence of meeting 24-h movement behaviors guidelines among Chinese adolescents aged 13-22 years was relatively low. It was associated with adolescents' physical fitness, with meeting MVPA + recreational screen or MVPA-only guidelines bringing greater benefits, and sex difference and age disparity existing.

The role of objectively recorded smartphone usage and personality traits in sleep quality

Purpose

The proliferation of smartphones, accompanied by internet facilities, has contributed to a decrease in sleep quality over the last decades. It has been revealed that excessive internet usage impacts the physical and mental health of smartphone users, while personality traits (PT) could play a role in developing internet addictions and preventing their negative effects. The objective of the present study is to assess the role of PT and smartphone usage in sleep quality.

Method

The sample comprised 269 participants, 55% females, within the age range of 15-64 years. We objectively collected one-week smartphone apps usage data from the participants. They also responded to demographics and the PT (BFI-10) questionnaires. The usage data of smartphone apps were processed to calculate smartphone usage amounts and sleep variables, including sleep duration, sleep distraction, sleeping time, and wake-up time. The data were analyzed using the correlation coefficient and regression analyses.

Results

The results indicated that more smartphone usage was associated with reduced sleep duration, increased sleep distraction, and later bedtime. Furthermore, smartphone users with the conscientiousness trait had a longer sleep duration, earlier sleeping time, less sleep distraction, and earlier wakeablity. Sleep distraction was positively associated with openness. Extraversion and neuroticism were found to be positive predictors of early wakeablity. Neuroticism had a negative association with early wakeablity. Finally, the implications of the study have been discussed.

Conclusion

Our study's usage of data that was acquired objectively has strong methodological qualities. The present study is the first to contribute to the literature on the role of PT and objectively measured smartphone usage in the prediction of sleep quality. We found that smartphone use and sleep variables are associated with PT. Other scholars can use our dataset for benchmarking and future comparisons.

Moderate-Vigorous Physical Activity, Screen Time and Sleep Time Profiles: A Cluster Analysis in Spanish Adolescents

The study had two aims: (1) To classify the adolescents according to their levels of moderate-vigorous physical activity, screen time and sleep time, and (2) to analyze, in a descriptive and correlational manner, the profiles of moderate-vigorous physical activity, screen time and sleep time of each cluster according to the sex and grade of the adolescents. The study design was cross-sectional, with descriptive and correlational analysis. The sample consisted of 663 adolescents in Compulsory Secondary Education from Soria (Spain). The Four by One-Day Physical Activity Questionnaire was used to measure levels of physical activity, screen time and sleep time. The results showed that the young people had an average of 67.99 ± min/day of moderate-vigorous physical activity, 112.56 min/day of screen time and 548.63 min/day of sleep time. Adolescents were classified into three clusters according to their levels of physical activity, screen time and sleep time (F_MANOVA (6,1318) = 314.439; p ≤ 0.001; β = 1; f = 1.177). In conclusion, only 28.21% of the young people accomplished the recommendations for physical activity practice, screen time and sleep time. Moreover, these results vary according to the sex and grade of the adolescents.

Associations between digital media use and lack of physical exercise among middle-school adolescents in Korea

OBJECTIVES

The reported effects of digital media overuse on physical activity among adolescents are inconsistent. This study examined the association between hours of digital media use and lack of moderate-intensity physical exercise (mPE) according to the type of digital media.

METHODS

This study included 1,837 middle school students from the iCURE (Internet user Cohort for Unbiased Recognition of gaming disorder in Early Adolescence) study conducted in Korea. Hours spent using digital media were measured by self-reported daily usage time for Internet games, messengers, social media, and watching game streaming on weekdays. Lack of mPE was defined as performing a minimum of 30 minutes at a time less than twice weekly. Multivariable logistic regression analysis stratified by sex was performed.

RESULTS

Among male students, the group with the highest hours of using either Internet games or watching game streaming was more likely to lack mPE than each non-user group. In contrast, among male students, the group using either messengers or social media had a higher rate of mPE compared to each non-user group. Female students showed no association between hours spent using Internet games, messengers, social media, or watching game streaming and a lack of mPE.

CONCLUSIONS

Among male middle school students in Korea, the excessive use of Internet games or watching game streaming was associated with a lack of mPE. Thus, guidelines should be established regarding adolescent use of internet games and watching game streaming.

Differential Associations Between Meeting 24-Hour Movement Guidelines With Mental Wellbeing and Mental Illness Among Chinese Adolescents

PURPOSE

Contemporary mental health models simultaneously consider psychological distress and wellness. Researchers have proposed that adhering to the 24-hour movement guidelines (24-HMG) contributes to mental health. 24-HMG integrates recommendations of time distribution among sleep, screen use, and moderate to vigorous physical activity (MVPA). Yet, there are few studies on the relationship between meeting 24-HMG and mental health, especially mental wellbeing. This study aimed to examine the associations between adherence to 24-HMG with mental wellbeing and mental illness among Chinese adolescents.

METHODS

Cross-sectional data of 67,281 Chinese adolescents aged 10-17 years (mean age = 13.0 years, 51.9% males) were collected by sending online questionnaires to local primary and middle schools in Shenzhen in 2021. We used multilevel generalized linear models to analyze associations between meeting 24-HMG with mental wellbeing (subjective wellbeing, resilience, and positive youth development) and mental illness (depression and anxiety).

RESULTS

Only 1.7% of participants met recommendations for all three behaviors (sleep, screen use, and MVPA). Compared with meeting none of the recommendations, participants who met one or more recommendations reported significantly better performance in mental wellbeing (all p < .001); on the contrary, meeting one or more recommendations (except for only meeting the MVPA recommendation) were significantly related to lower severity of mental illness (all p < .001). The relationship between the number of recommendations met with mental well-being and mental illness indicators presented a dose-response pattern (all p < .001).

DISCUSSION

Meeting 24-HMG was associated with superior mental health, including a higher propensity for mental wellbeing and a lower risk of mental illness. The importance of limiting screen time and getting enough sleep should be highlighted in promoting mental health in adolescents.

Psychological resilience buffers the association between cell phone addiction and sleep quality among college students in Jiangsu Province, China

BACKGROUND AND AIMS

Excessive use of cell phones can take up college students' time and energy, and the sleep quality will inevitably be affected. A high level of psychological resilience can help them to maintain a positive attitude and cope with stressful events. However, few studies were conducted to investigate the effects of psychological resilience buffering cell phone addiction on sleep quality. In our hypothesis, psychological toughness would mitigate the worsening impact of cell phone addiction on sleep quality.

METHODS

The sample consisted of 7,234 Chinese college students who completed an electronic questionnaire that included demographic characteristics, such as the Mobile Phone Addiction Index (MPAI), the Psychological Resilience Index (CD-RISC), and the Pittsburgh Sleep Quality Index (PSQI). SPSS 26.0 was used for data analysis, the measurement data were described by x ¯ ± s for those conforming to normal distribution, and the comparison of means between groups was analyzed by group t-test or one-way ANOVA. Those that was not conforming to normal distribution were described by median M (P ₂₅, P ₇₅), and the comparison of M between groups was analyzed by Mann-Whitney U test and Kruskal-Wallis H test. Using Spearman correlation analysis, the associations between mobile phone addiction, psychological resilience, and sleep quality were evaluated. Using SPSS Process, the mediating role of psychological resilience was examined.

RESULTS

The mean scores of cell phone addiction and psychological resilience were 45.00 (SD = 13.59) and 60.58 (SD = 18.30), respectively; the sleep quality score M (P ₂₅, P ₇₅) was 5.0 (3.0, 7.0). Cell phone addiction among college students had a direct predictive effect on sleep quality (β = 0.260, P < 0.01), and psychological resilience had a negative correlation with both cell phone addiction and sleep quality (β = -0.073, P < 0.01, and β = -0.210, P < 0.01). Psychological resilience was responsible for a mediating effect value of 5.556% between cell phone addiction and sleep quality.

CONCLUSION

Cell phone addiction has an impact on sleep quality both directly and indirectly through the mediating effect of psychological resilience. Increased psychological resilience has the potential effect to buffer the exacerbating of cell phone addiction on sleep quality. These findings provide an evidence for cell phone addiction prevention, psychological management, and sleep improvement in China.

The Relationships between Physical Activity, Screen Time and Sleep Time According to the Adolescents' Sex and the Day of the Week

This study had two aims: (1) to identify the levels of physical activity, screen time and sleep time of adolescents according to the sex of the participant and the day of the week; (2) to find out the relationships between physical activity, screen time and sleep time according to the sex of the participant and the day of the week. The study design was non-experimental, descriptive-correlational and cross-sectional. The sample consisted of 694 adolescents in Compulsory Secondary Education from Soria (Spain). Four by One-Day Physical Activity Questionnaires were used to measure levels of physical activity, screen time and sleep time. Levene’s test and Student’s t-test were used to calculate the difference between the means of the variables. Pearson’s test was used to calculate bivariate correlations between variables. Results showed higher levels of screen time in males (136.93 min/day ± 81.548). Screen time, sleep time and moderate−vigorous physical activity are higher during the weekend. Positive relationships were found between screen time and light physical activity (rmales = 0.274; p ≤ 0.01; rfemales = 0.065; p > 0.05). The correlations between moderate−vigorous physical activity and screen time were negative (rmales = −0.282; p ≤ 0.01; rfemales = −0.187; p ≤ 0.05). The relationship between screen time and sleep time was negative in males (r = −0.135; p ≤ 0.05). In conclusion, the levels of physical activity, screen time and sleep time vary according to the sex of the participants and the day of the week.

Associations Between Adolescents' Daily Digital Technology Use and Sleep

PURPOSE

Although studies have found associations between greater digital technology use and poorer sleep health among adolescents, these studies typically rely on self-reported sleep and cross-sectional designs. This study applied an ecological momentary assessment design to examine how adolescents' daily digital technology use relates to self-reported sleep and wearable-recorded sleep duration.

METHODS

A socioeconomically and ethnically diverse sample of 388 adolescents completed daily surveys of their digital technology use (i.e., messages sent, time for academics, time for leisure) and sleep for 2 weeks. Sleep duration was recorded through wearable devices among a subsample of 254 adolescents for an average of 3.4 days.

RESULTS

Adolescents who reported spending more time using digital technology for nonacademic purposes than their peers reported both shorter self-reported sleep duration and later bedtime (between-person associations). Adolescents who sent more messages than their peers also had shorter sleep duration as recorded by wearable devices. In contrast, few associations were observed when comparisons were made within-individuals with adolescents used as their own controls.

CONCLUSIONS

Consistent with prior research, adolescents who reported greater nonacademic daily digital technology use relative to their peers exhibited worse sleep outcomes as measured via self-reports and wearable devices. However, associations with sleep outcomes were weak and inconsistent when adolescents were used as their own controls. Future research should continue to explore between- and within-person associations between digital technology use and sleep to understand potential key differences.