Nighttime smartphone use and changes in mental health and wellbeing among young adults: a longitudinal study based on high-resolution tracking data

Association Between Electronic Device Use at Bedtime and COVID-19 Vaccine-Related Adverse Events During the COVID-19 Pandemic in Korean Adults: A Nationwide Cross-Sectional Population-Based Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has led to heightened mood disturbances linked to increased electronic device use at bedtime (EUB). General anxiety may contribute to an increased likelihood of experiencing nocebo responses, which have been reported to be associated with COVID-19 vaccine-related adverse events (CAEs). However, no related studies have been conducted to examine this association to date.

METHODS

We executed a nationwide cross-sectional study to explore these correlations during the pandemic. Using data from the 2022 National Sleep Survey of South Korea, we analyzed the sleep health of 4,000 adults aged 20-69 years between January and February 2022. Shift workers and those with severe sleep disorders were excluded. Participants with EUB more than four days a week were labeled as high frequency EUB, and those reporting CAEs after both vaccine doses were marked as having a presence of CAEs. The survey also included details about anthropometric data, socioeconomic status, and sleep status.

RESULTS

Of the 3,702 participants, 92.6% had received two or more vaccine doses, with 41.2% experiencing CAEs. Furthermore, 73.7% had a high EUB frequency. Factors associated with CAE reporting included younger age, female sex, and high EUB frequency, while heavy alcohol use was found to be less likely to be associated with CAE reporting. Notably, a high EUB frequency was significantly associated with reported CAEs (odds ratio, 1.223; 95% confidence interval, 1.028-1.455; P = 0.023).

CONCLUSION

A nationwide online survey conducted in South Korea during the pandemic found that individuals who engaged in the relatively frequent use of electronic devices during bedtime had worse sleep quality and increased COVID-19-related adverse events compared with those using these devices less frequently. These findings have the potential to enhance our understanding of the impact of the use of electronic devices at bedtime on health.

Nighttime smartphone use, sleep quality, and mental health: investigating a complex relationship

STUDY OBJECTIVES

This study investigated the complex relationship between nighttime smartphone use, sleep, and mental health among adult populations in Denmark.

METHODS

Data from three interconnected samples (aged 16-89 years) from the SmartSleep Study included 5798 individuals with survey and register data; 4239 individuals also provided high-resolution smartphone tracking data. Logistic regression models and causal discovery algorithms, which suggest possible causal pathways consistent with the underlying data structure, were used to infer the relationship between self-reported and tracked nighttime smartphone use, self-reported sleep quality, mental health indicators, and register-based psychotropic medication use.

RESULTS

Frequent self-reported nighttime smartphone use was associated with high perceived stress (OR: 2.24, 95% CI = 1.42 to 3.55) and severe depressive symptoms (OR: 2.96, 95% CI = 2.04 to 4.28). We found no clear associations between tracked nighttime smartphone use and mental health outcomes, except for the cluster that used their smartphones repeatedly during the sleep period, which was associated with severe depressive symptoms (OR = 1.69, 95% CI = 1.24 to 2.31). Poor sleep quality (vs. good sleep quality) was associated with high perceived stress (OR = 5.07, 95% CI = 3.72 to 6.90), severe depressive symptoms (OR = 9.67, 95% CI = 7.09 to 13.19), and psychotropic medication use (OR = 2.13, 95% CI = 1.36 to 3.35). The causal discovery models suggest that nighttime smartphone use affects mental health through both problematic smartphone use and poor sleep quality.

CONCLUSION

The complex relationship between nighttime smartphone use, sleep, and poor mental health may create a vicious circle over time, and nighttime smartphone use may constitute a potential leverage point for public health interventions aimed at improving sleep and mental health.

Addressing the Increasing Mental Health Distress and Mental Illness Among Young Adults in the United States

ABSTRACT

Recent surveys show rising numbers of young people who report anxiety and depression. Although much attention has focused on mental health of adolescent youth, less attention has been paid to young people as they transition into adulthood. Multiple factors may have contributed to this steady increase: greater exposure to social media, information, and distressing news via personal electronic devices; increased concerns regarding social determinants of health and climate change; and changing social norms due to increased mental health literacy and reduced stigma. The COVID-19 pandemic may have temporarily exacerbated symptoms and impacted treatment availability. Strategies to mitigate causal factors for depression and anxiety in young adults may include education and skills training for cognitive, behavioral, and social coping strategies, as well as healthier use of technology and social media. Policies must support the availability of health insurance and treatment, and clinicians can adapt interventions to encompass the specific concerns and needs of young adults.

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.

Decisional style, sleepiness, and online responsiveness

As sleep problems can impair quality of work, an online questionnaire was used to examine relationships between sleepiness and decision making while obtaining unobtrusive indices of performance. Participants (N = 344) completed the Insomnia Severity Index, Epworth Sleepiness Scale, and the Melbourne Decision Making Questionnaire in a Qualtrics survey while reporting mobile phone use. Qualtrics recorded the time and the number of clicks required to complete each page of the survey. Multiple regression indicated that insomnia was associated with daytime sleepiness and Hypervigilance, and mobile phone use before bed. Participants with moderate sleepiness required a greater number of clicks to complete the questionnaire. Greater sleepiness was associated with longer times to complete these self-assessment tasks. Clinically significant sleepiness produces changes in performance that can be detected from online responsivity. As sleepy individuals can be appreciably and quantitatively slower in performing subjective self-assessment tasks, this argues for objective measures of sleepiness and automated interventions and the design of systems that allow better quality sleep.Practitioner summary: Work can require processing of electronic messages, but 24/7 accessibility increases workload, causes fatigue and potentially creates security risks. Although most studies use people's self-reports, this study monitors time and clicks required to complete self-assessment rating scales. Sleepiness affected online responsivity, decreasing online accuracy and increasing response times and hypervigilance.

Associations of smartphone usage patterns with sleep and mental health symptoms in a clinical cohort receiving virtual behavioral medicine care: a retrospective study

Study Objectives

We sought to develop behavioral sleep measures from passively sensed human-smartphone interactions and retrospectively evaluate their associations with sleep disturbance, anxiety, and depressive symptoms in a large cohort of real-world patients receiving virtual behavioral medicine care.

Methods

Behavioral sleep measures from smartphone data were developed: daily longest period of smartphone inactivity (inferred sleep period [ISP]); 30-day expected period of inactivity (expected sleep period [ESP]); regularity of the daily ISP compared to the ESP (overlap percentage); and smartphone usage during inferred sleep (disruptions, wakefulness during sleep period). These measures were compared to symptoms of sleep disturbance, anxiety, and depression using linear mixed-effects modeling. More than 2300 patients receiving standard-of-care virtual mental healthcare across more than 111 000 days were retrospectively analyzed.

Results

Mean ESP duration was 8.4 h (SD = 2.3), overlap percentage 75% (SD = 18%) and disrupted time windows 4.85 (SD = 3). There were significant associations between overlap percentage (p < 0.001) and disruptions (p < 0.001) with sleep disturbance symptoms after accounting for demographics. Overlap percentage and disruptions were similarly associated with anxiety and depression symptoms (all p < 0.001).

Conclusions

Smartphone behavioral measures appear useful to longitudinally monitor sleep and benchmark depressive and anxiety symptoms in patients receiving virtual behavioral medicine care. Patterns consistent with better sleep practices (i.e. greater regularity of ISP, fewer disruptions) were associated with lower levels of reported sleep disturbances, anxiety, and depression.