Can social connections become stressful? Exploring the link between social media use and perceived stress in cross-sectional and longitudinal analyses of 25,053 adults.

BACKGROUND: Social media has become a dominant part of daily lives for many, but excessive use may lead to an experience of stress. Only relatively few studies have investigated social media's influence on mental health. AIMS: We aimed to investigate whether social media use is associated with perceived stress and changes in perceived stress over 18 months. METHODS: The study population consisted of 25,053 adults (mean age 42.8; 62% women) from the SmartSleep Study. Self-reported frequency of social media use, of 10 specific social media platforms, and of perceived stress (the Perceived Stress Scale 4 item) was obtained at baseline and 18-months follow-up (N = 1745). The associations were evaluated at baseline and follow-up using multiple linear regression models adjusted for potential confounders. RESULTS: Compared to non-use, high social media use (at least every second hour) was associated with a slightly higher perceived stress level at baseline. No association was found between the frequency of social media use and changes in perceived stress during follow-up. Only small differences in these associations were noted across social media platforms. CONCLUSIONS: Further studies are needed to comprehensively explore the relationship between excessive social media use and mental health, recognizing different characteristics across social media platforms.

Tracked and self-reported nighttime smartphone use, general health, and healthcare utilization: results from the SmartSleep Study.

STUDY OBJECTIVES: Nighttime smartphone use is an increasing public health concern. We investigated whether nighttime smartphone use is associated with general health and primary healthcare utilization. METHODS: 4,520 individuals (age 35.6 ± 9.7 years, 35% male) provided self-reported information on smartphone use frequency, symptoms of depression, and general health (one-item perceived health and cross-symptom composite score). A subset of the study sample (n=3,221) tracked their nighttime smartphone use. Primary healthcare utilization, i.e., the number of weeks in which at least one service from the patient's general practitioner was billed in 2020, was extracted from Danish population registries. Statistical analysis comprised logistic and multiple linear regression, controlling for sociodemographics. RESULTS: 319 individuals (7%) reported using their smartphone almost every night or more. More frequent self-reported nighttime smartphone use was associated with poor general health across all measures. Using the smartphone almost every night or more was associated with 2.8 [95CI: 1.9,4.1] fold higher odds of reporting poor health and with an average of 1.4 [95CI: 0.7,2.1] additional GP utilizations per year compared to no use. Associations were also found for the cross-symptom composite score across all symptoms. Further adjustment for symptoms of depression attenuated some associations. Smartphone use towards the end of the sleep period (sleep-offset use) was associated with poorer self-reported general health, but not with healthcare utilization. CONCLUSION: Nighttime smartphone use frequency is associated with poor general health and healthcare utilization. Further studies should investigate the underlying causal structure and nighttime smartphone use as a transdiagnostic intervention target.

Self-reported and tracked nighttime smartphone use and their association with overweight and cardiometabolic risk markers.

Nighttime smartphone use is associated with sleep problems, which in turn have a bidirectional association with overweight. We aim to investigate whether nighttime smartphone use and sleep are related to overweight and metabolic dysfunction in adult populations. We used data from three population samples (aged 16-89) from the SmartSleep Study, which included survey data (N = 29,838), high-resolution tracking data (N = 3446), follow-up data (N = 1768), and cardiometabolic risk markers (N = 242). Frequent self-reported nighttime smartphone use was associated with 51% higher odds (95% CI: 1.32; 1.70) of overweight compared with no use. Tracked nighttime smartphone use was also associated with overweight. Similar results were found for obesity as an outcome. No consistent associations were found between nighttime smartphone use and cardiometabolic risk markers in a small subsample of healthy young women. Poor sleep quality (vs. good sleep quality) was associated with overweight (OR = 1.19, 85% CI: 1.10; 1.28). Overall, frequent nighttime smartphone use was consistently associated with overweight and a higher BMI across diverse population samples. The bidirectional interplay between nighttime smartphone use, sleep, and overweight may create a vicious circle of metabolic dysfunction over time. Therefore, nighttime smartphone use may be a potential target point for public health interventions to reduce overweight at the population level.

Cohort profile: The SmartSleep Study, Denmark, combining evidence from survey, clinical and tracking data.

PURPOSE: The SmartSleep Study is established to comprehensively assess the impact of night-time smartphone use on sleep patterns and health. An innovative combination of large-scale repeated survey information, high-resolution sensor-driven smartphone data, in-depth clinical examination and registry linkage allows for detailed investigations into multisystem physiological dysregulation and long-term health consequences associated with night-time smartphone use and sleep impairment. PARTICIPANTS: The SmartSleep Study consists of three interconnected data samples, which combined include 30 673 individuals with information on smartphone use, sleep and health. Subsamples of the study population also include high-resolution tracking data (n=5927) collected via a customised app and deep clinical phenotypical data (n=245). A total of 7208 participants are followed in nationwide health registries with full data coverage and long-term follow-up. FINDINGS TO DATE: We highlight previous findings on the relation between smartphone use and sleep in the SmartSleep Study, and we evaluate the interventional potential of the citizen science approach used in one of the data samples. We also present new results from an analysis in which we use 803 000 data points from the high-resolution tracking data to identify clusters of temporal trajectories of night-time smartphone use that characterise distinct use patterns. Based on these objective tracking data, we characterise four clusters of night-time smartphone use. FUTURE PLANS: The unprecedented size and coverage of the SmartSleep Study allow for a comprehensive documentation of smartphone activity during the entire sleep span. The study has been expanded by linkage to nationwide registers, which allow for further investigations into the long-term health and social consequences of night-time smartphone use. We also plan new rounds of data collection in the coming years.

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.

Night-time smartphone use, sleep duration, sleep quality, and menstrual disturbances in young adult women: A population-based study with high-resolution tracking data.

Study Objectives: To explore the relationship among night-time smartphone use, sleep duration, sleep quality, and menstrual disturbances in young adult women. Methods: Women aged 18-40 years were included in the SmartSleep Study in which they objectively tracked their smartphone use via the SmartSleep app between self-reported sleep onset and offset times (n = 764) and responded to a survey (n = 1068), which included background characteristics, sleep duration, sleep quality (Karolinska Sleep Questionnaire), and menstrual characteristics (International Federation of Gynecology and Obstetrics' definitions). Results: The median tracking time was four nights (interquartile range: 2-8). Higher frequency (p = .05) and longer duration (p = .02) of night-time smartphone use were associated with long sleep duration (≥9 h), but not with poor sleep quality or short sleep duration (<7 h). Short sleep duration was associated with menstrual disturbances (OR = 1.84, 95% confidence interval [CI] = 1.09 to 3.04) and irregular menstruation (OR = 2.17, 95% CI = 1.08 to 4.10), and poor sleep quality was associated with menstrual disturbances (OR = 1.43, 95% CI = 1.19 to 1.71), irregular menstruation (OR = 1.34, 95% CI = 1.04 to 1.72), prolonged bleedings (OR = 2.50, 95% CI = 1.44 to 4.43) and short-cycle duration (OR = 1.40, 95% CI = 1.06 to 1.84). Neither duration nor frequency of night-time smartphone use was associated with menstrual disturbances. Conclusions: Night-time smartphone use was associated with longer sleep duration, but not with menstrual disturbances in adult women. Short sleep duration and sleep quality were associated with menstrual disturbances. Further investigation of the effects of night-time smartphone use on sleep and female reproductive function in large prospective studies is needed.

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

Frequent nighttime smartphone use can disturb healthy sleep patterns and may adversely affect mental health and wellbeing. This study aims at investigating whether nighttime smartphone use increases the risk of poor mental health, i.e. loneliness, depressive symptoms, perceived stress, and low life satisfaction among young adults. High-dimensional tracking data from the Copenhagen Network Study was used to objectively measure nighttime smartphone activity. We recorded more than 250,000 smartphone activities during self-reported sleep periods among 815 young adults (university students, mean age: 21.6 years, males: 77%) over 16 weekdays period. Mental health was measured at baseline using validated measures, and again at follow-up four months later. Associations between nighttime smartphone use and mental health were evaluated at baseline and at follow-up using multiple linear regression adjusting for potential confounding. Nighttime smartphone use was associated with a slightly higher level of perceived stress and depressive symptoms at baseline. For example, participants having 1-3 nights with smartphone use (out of 16 observed nights) had on average a 0.25 higher score (95%CI:0.08;0.41) on the Perceived stress scale ranging from 0 to 10. These differences were small and could not be replicated at follow-up. Contrary to the prevailing hypothesis, nighttime smartphone use is not strongly related to poor mental health, potentially because smartphone use is also a social phenomenon with associated benefits for mental health.

The SmartSleep Experiment: Evaluation of changes in night-time smartphone behavior following a mass media citizen science campaign.

The increasing 24-hour smartphone use is of public health concern. This study aims to evaluate whether a massive public focus on sleep and smartphone use generated through a large-scale citizen science project, the SmartSleep Experiment, influence participants' night-time smartphone behavior. A total of 8,894 Danish adults aged 16 and above participated in the SmartSleep Experiment, a web-based survey on smartphones and sleep behavior. The survey was carried out for one week in 2018, combined with an extensive national mass media campaign focusing on smartphone behaviors and sleep. A follow-up survey aimed at evaluating whether survey-participants had changed their night-time smartphone behavior was carried out two weeks after the campaign. A total of 15% of the participants who used their smartphone during sleep hours at baseline had changed their night-time smartphone behavior, and 83% of those indicated that they used their smartphone less at follow-up. The participants who had changed their smartphone behavior had primarily taken active precautions to avoid night-time smartphone use, e.g., activating silent mode (36%) or reduced their smartphone use before (50%) and during sleep hours (52%). The reduction in sleep problems (54%), recognition of poor smartphone behavior (48%), and the increased focus on night-time smartphone use (42%) were motivational factors for these behavior changes. Using citizen science and mass media appeared to be associated with changes in night-time smartphone behavior. Public health projects may benefit from combining citizen science with other interventional approaches.

Daytime and nighttime smartphone use: A study of associations between multidimensional smartphone behaviours and sleep among 24,856 Danish adults.

The around-the-clock smartphone use and its relation to disturbed sleep is a public health concern. The present study aimed to quantify the effects of different dimensions of smartphone behaviours (frequency of daytime use, problematic use, use before sleep and use during the sleep period) on disturbed sleep (sleep quality and sleep quantity) and to disentangle their inter-relationship in a large population-based sample of 24,856 Danish adults aged ≥16 years. Data come from the SmartSleep Experiment, which is a web-based survey carried out using a citizen science approach. Tested items were used to evaluate smartphone use and disturbed sleep was evaluated with the Karolinska Sleep Questionnaire (KSQ). Linear and multinomial logistic regression was employed to evaluate the relationship between smartphone use and disturbed sleep. While several of the smartphone measures were associated with disturbed sleep when assessed individually, smartphone use during the sleep period was the only dimension consistently associated with disturbed sleep when assessed independently of other smartphone behaviours. Weekly smartphone use during the sleep period versus no use was associated on average with a 0.96 point higher score (95% confidence interval [CI] 0.90-1.02) on the 5-point KSQ scale, and a higher risk of both short (odds ratio [OR] 1.32, 95% CI 1.08-1.62) and long (OR 1.94, 95% CI 1.63-2.32) sleep duration. Smartphone use during the sleep period is the factor strongest associated to disturbed sleep relative to other dimensions of smartphone use. Recommendations around smartphone use during the sleep period are warranted in order to protect the fundamentally important biological and mental processes of sleep.

'Standing together - at a distance': Documenting changes in mental-health indicators in Denmark during the COVID-19 pandemic.

Aims: There is a need to document the mental-health effects of the COVID-19 pandemic and its associated societal lockdowns. We initiated a large mixed-methods data collection, focusing on crisis-specific worries and mental-health indicators during the lockdown in Denmark. Methods: The study incorporated five data sources, including quantitative surveys and qualitative interviews. The surveys included a time series of cross-sectional online questionnaires starting on 20 March 2020, in which 300 (3×100) Danish residents were drawn every three days from three population groups: the general population (N=1046), families with children (N=1032) and older people (N=1059). These data were analysed by trend analysis. Semi-structured interviews were conducted with 32 people aged 24-83 throughout Denmark to provide context to the survey results and to gain insight into people's experiences of the lockdown. Results: Absolute level of worries, quality of life and social isolation were relatively stable across all population groups during the lockdown, although there was a slight deterioration in older people's overall mental health. Many respondents were worried about their loved ones' health (74-76%) and the potential long-term economic consequences of the pandemic (61-66%). The qualitative interviews documented significant variation in people's experiences, suggesting that the lockdown's effect on everyday life had not been altogether negative. Conclusions: People in Denmark seem to have managed the lockdown without alarming changes in their mental health. However, it is important to continue investigating the effects of the pandemic and various public-health measures on mental health over time and across national contexts.