Social Media Use Before Bed and Sleep Disturbance Among Young Adults in the United States: A Nationally Representative Study

Associations between bedtime media use and sleep outcomes in an adult population-based cohort

OBJECTIVE

To further examine the relationship between bedtime media use and sleep in adults by taking relevant covariates into account and testing hypothesised mediating and moderating pathways.

METHODS

Bedtime media use and sleep outcomes were examined by questionnaire in 4188 adults (59 % women, aged 19-94 years) from the Specchio cohort based in Geneva, Switzerland. We tested associations between bedtime media use and sleep (bedtimes, rise times, sleep latency, sleep duration, sleep quality, insomnia, and daytime sleepiness), adjusting for prior sleep, mental health, and health behaviours; whether bedtime media use mediates associations between individual susceptibility factors (age, chronotype, and mental health) and sleep; and whether individual susceptibility factors moderate associations between bedtime media use and sleep.

RESULTS

Often using a screen in the 30 minutes before going to sleep at night was associated with a late bedtime (≥midnight; OR [95 % CI] = 1.90 [1.44,2.51], p < 0.001), a short sleep duration (<7 h; 1.21 [1.01,1.46], p < 0.05), and excessive daytime sleepiness (Epworth score >9; 1.47 [1.25,1.74], p < 0.001), adjusting for all covariates. Bedtime media use partly mediated the association between younger age and an evening chronotype and these sleep outcomes. Mental health moderated the association between bedtime media use and sleep quality/insomnia, such that the former was only associated with poorer sleep quality/insomnia among individuals with better mental health.

CONCLUSIONS

Frequent bedtime media use was associated with various sleep outcomes, independently of relevant covariates. Limiting the use of screens at bedtime is important to promote sleep among adults. Individuals with poorer mental health likely require additional support to improve their sleep quality.

Social Media Use, Emotional Investment, Self-Control Failure, and Addiction in Relation to Mental and Sleep Health in Hispanic University Emerging Adults

The number of social media users has increased dramatically in recent years. Common correlates of social media use may be poor mental and sleep health which are pressing issues among emerging adults and Hispanic groups. This study investigated the relationships between five different forms of social media use and mental and sleep health in Hispanic university emerging adults. Hispanic university emerging adults (n = 358) completed a survey assessing sociodemographics, overall social media use frequency, nighttime in-bed social media use, social media addiction, social media self-control failure, emotional investment in social media, depression, anxiety, stress, and sleep quality. Findings demonstrated that social media addiction and social media self-control failure were positively associated with stress and poor sleep quality. Emotional investment in social media was positively associated with depression. Findings may suggest that Hispanic university emerging adults may use social media emotionally and problematically to cope with negative affect and poor sleep quality, or that negative affect and poor sleep quality stem from using social media emotionally and problematically. The clinical implications of these results are discussed. Prospective studies are warranted to assess temporality.

Cross-lagged panel analysis of the relationship between social networking sites use (SNSU) and sleep problems among university students

BACKGROUND

Sleep remains a cornerstone for sociopsychological well-being, but it is in decline, especially among today's youth. Simultaneously, engagement with social media is escalating. Research has identified a link between social networking sites use and sleep problems; however, the nature and direction of the relations remain obscure. Therefore, it is imperative to pursue longitudinal research to elucidate this correlation and guide suitable intervention practices. The present study aimed to examine the reciprocal relationship between social networking sites use and sleep problems.

METHODS

By adopting a three-stage cross-lagged design across four time points, assessment results from 194 university students were gathered at four-week intervals.

RESULTS

The findings indicate that (1) Social networking sites use was significantly greater in females than in males at all four time points, while sleep problems were significantly greater in females than in males at Time 3 and Time 4. (2) Sleep problems at the second time point serve as a positive predictor of subsequent social networking sites use at the third time point. (3) Social networking sites use at the initial time point could marginally significantly predict sleep problems at the fourth time point.

CONCLUSIONS

This study elucidates the dynamic relationship between social networking sites use and sleep problems across an academic term, suggesting the need for temporally tailored interventions.

Nighttime Texting on Social Media, Sleep Parameters, and Adolescent Sadness: A Mediation Analysis

OBJECTIVES

The use of social media during bedtime has increased in the past years among adolescents, contributing to disturbed sleep quality, which could potentially be related to emotional problems. This study aimed to analyze the mediation effects of sleep parameters on the relationship between NightTime Texting (NTT) on social media and adolescent sadness.

METHODS

We used a cross-sectional study and evaluated a total of 1464 Swedish students aged 15-17 (55.7% girls) to examine their frequency of NTT on social media, sleep parameters, and adolescent sadness. Bivariate and mediation analyses were performed.

RESULTS

Approximately 60% (n = 882) of adolescents engaged in nighttime instant messaging, with 37% (n = 330) reporting texting every night. Higher frequency of NTT was significantly associated with later bedtimes (η2 > 0.12), extended weekend wake-up times (η2 = 0.07), increased social jetlag (η2 = 0.07), and reduced sleep duration on schooldays (η2 = 0.10). Multicategorical parallel mediation analyses revealed that sleep duration on schooldays had an indirect effect on the relationship between both Occasional NTT (a11b1 = 0.05, p < .05) and Daily NTT (a21b1 = 0.12, p < .05) with sadness. Mediation effects were not moderated by gender (p > .05), however, the association between Occasional NTT and higher sadness was significantly linked to boys (t = 2.72; p = .007).

CONCLUSIONS

Findings showed a large percentage of adolescents engaging in nighttime social media use with worse quality of sleep, and underlined sleep duration on schooldays as a mediator associated with emotional problems in adolescents. These insights can aid in developing strategies for healthier habits to address the misuse of social media and prevent related health problems.

Self-Selected Versus Assigned Target to Reduce Smartphone Use and Improve Mental Health: Protocol for a Randomized Controlled Trial

BACKGROUND

Smartphones have become integral to people's lives, with a noticeable increase in the average screen time, both on a global scale and, notably, in India. Existing research links mobile consumption to sleep problems, poor physical and mental health, and lower subjective well-being. The comparative effectiveness of monetary incentives given for self-selected versus assigned targets on reducing screen time and thereby improving mental health remains unanswered.

OBJECTIVE

This study aims to assess the impact of monetary incentives and target selection on mobile screen time reduction and mental health.

METHODS

We designed a 3-armed randomized controlled trial conducted with employees and students at an educational institution in India. The study is conducted digitally over 12 weeks, including baseline (2 weeks), randomization (1 week), intervention (5 weeks), and postintervention (4 week) periods. We emailed the employees and students to inquire about their interest in participation. Those who expressed interest received detailed study information and consent forms. After securing consent, participants were asked to complete the initial survey and provide their mobile screen time during the baseline period. At the beginning of the intervention period, the participants were randomly allocated into 1 of 3 study groups in a 2:2:1 ratio (self-selected vs assigned vs control). Participants in the self-selected group were presented with 3 target options: 10%, 20%, and 30%, and they were asked to self-select a target to reduce their mobile screen time from their baseline average mobile screen time. Participants in the assigned group were given a target to reduce their mobile screen time from their baseline average mobile screen time. The assigned target was set as the average of the targets selected by participants in the self-selected group. During the intervention period, participants in the self-selected and assigned group were eligible to receive a monetary incentive of INR (Indian Rupee) 50 (US $0.61) per day for successfully attaining their target. Participants in the control group neither received nor selected a target for reducing their mobile screen time and did not receive any monetary incentives during the intervention period. All participants received information regarding the advantages of reducing mobile screen time. As an incentive, all participants would receive INR 500 (US $6.06) upon completion of the study and a chance to win 1 of 2 lotteries valued at INR 5000 (US $60.55) for consistently sharing their mobile screen time data.

RESULTS

Currently, the study intervention is being rolled out. Enrollment occurred between August 21, 2023, and September 2, 2023; data collection concluded in November 2023. We expect that results will be available by early 2024.

CONCLUSIONS

The monetary incentives and self-selected versus assigned targets might be effective interventions in reducing mobile screen time among working professionals and students.

TRIAL REGISTRATION

AsPredicted 142497; https://aspredicted.org/hr3nn.pdf.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53756.

Disruptions in self-regulatory processes predict depression and sleep disturbance in bereaved young adults

Losing a loved one is both common and profoundly stressful for young adults. Little research has examined the longitudinal course of post-loss cognitive processing, depression, and sleep difficulties. Further, little is known about the context of other stressors or the role of individual regulatory resources, such as attentional regulation, that might determine whether loss-related cognitive processing reduces distress. This prospective study examined changes in depression and sleep disturbance over 9 weeks as a function of within- and between-person variation in stress exposure, loss-related cognitive processing, and attention regulation. Participants were 108 recently bereaved college students completing a lab-based assessment of attention regulation and four self-report surveys, spaced three weeks apart. Results revealed that most participants gradually reduced loss-related processing over the study period, with corresponding improvements in depression and sleep. Stress exposure was associated with increased processing, depression, and sleep disturbance. In exploratory analyses, high attentional alertness and slow re-orienting strengthened the association of within-person loss processing with sleep disturbance. Both within- and between-person variation in stress appear to engender risk for a prolonged course of bereavement. Future research should integrate objective attention measures with self-reported adjustment to stress to illuminate reciprocal links between depression, sleep, and loss-related cognitive processing.

The Impact of Social Media Use on Sleep and Mental Health in Youth: a Scoping Review

PURPOSE OF REVIEW

Social media use (SMU) and other internet-based technologies are ubiquitous in today's interconnected society, with young people being among the commonest users. Previous literature tends to support that SMU is associated with poor sleep and mental health issues in youth, despite some conflicting findings. In this scoping review, we summarized relevant studies published within the past 3 years, highlighted the impacts of SMU on sleep and mental health in youth, while also examined the possible underlying mechanisms involved. Future direction and intervention on rational use of SMU was discussed.

RECENT FINDINGS

Both cross-sectional and longitudinal cohort studies demonstrated the negative impacts of SMU on sleep and mental health, with preliminary evidence indicating potential benefits especially during the COVID period at which social restriction was common. However, the limited longitudinal research has hindered the establishment of directionality and causality in the association among SMU, sleep, and mental health. Recent studies have made advances with a more comprehensive understanding of the impact of SMU on sleep and mental health in youth, which is of public health importance and will contribute to improving sleep and mental health outcomes while promoting rational and beneficial SMU. Future research should include the implementation of cohort studies with representative samples to investigate the directionality and causality of the complex relationships among SMU, sleep, and mental health; the use of validated questionnaires and objective measurements; and the design of randomized controlled interventional trials to reduce overall and problematic SMU that will ultimately enhance sleep and mental health outcomes in youth.

What's your religious coping profile? Differences in religious orientation and subjective sleep among religious coping groups in the United States

OBJECTIVES

To determine various profiles/subgroups of religious copers based on indices of positive and negative religious coping; and to determine whether religious copers differ in their religious orientations, subjective sleep characteristics, and strategies used to cope with sleep problems.

METHOD

Six hundred and ninety-five adults (77.3% female, 70.4% White) in the United States completed a 20-minute online questionnaire in January 2020.

RESULTS

Results of a latent profile analysis, based on 8 indicators of positive and negative religious coping, indicated a 5-class solution: (i) "Absent" (n = 101, 14.5%); (ii) "Anxious" (n = 122, 17.6%); (iii) "Ambivalent" (n = 101, 14.5%); (iv) "Secure" (n = 200, 28.8%); and (v) "Conflicted" copers (n = 171, 24.6%). Results of MANOVA tests indicated that Secure copers reported the least religious doubt and highest religious-based social support. Conflicted and Anxious copers had the worst sleep quality, while Secure, Ambivalent, and Absent copers had healthier sleep profiles. In terms of strategies used to cope with sleep problems, Secure and Conflicted copers reported the greatest use of prayer and meditation, while the use of technology was most prevalent among Conflicted and Anxious copers.

CONCLUSIONS

Individuals differ in their combined use of positive and negative religious coping, which is related to differences in their religious orientation, sleep characteristics, and strategies used to cope with sleep problems. Religious leaders should be mindful of the diverse ways in which religious coping strategies are harnessed to effectively cater to the unique religious and sleep needs of their members.

The role of sleep in prospective associations between parent reported youth screen media activity and behavioral health

BACKGROUND

Screen media activity (SMA) can negatively affect youth behavioral health. Sleep may mediate this association but has not been previously explored. We examined whether sleep mediated the association between SMA and youth behavioral health among a community sample.

METHOD

Parents completed questions about their child (N = 564) ages 3-17 at Wave 1, Wave 2 (4-8 months later), and Wave 3 (12 months later). Path analyses were conducted to examine links between Wave 1 SMA and Wave 3 behavioral health problems (i.e., internalizing, externalizing, attention, peer problems) through Wave 2 sleep disturbance and duration.

RESULTS

SMA was significantly associated with greater sleep disturbance, β = .11, 95% CI [.01, .21] and shorter sleep duration, β = -.16 [-.25, -.06], and greater sleep disturbance was associated with worse youth behavioral health across internalizing, β = .14 [.04, .24], externalizing, B = .23 [.12, .33], attention, β = .24 [.15, .34], and peer problems, β = .25 [.15, .35]. Longer sleep duration was associated with more externalizing, β = .13 [.04, .21], and attention problems, β = .12 [.02, .22], and fewer peer problems, β = -.09 [-.17, -.01], but not with internalizing problems. Lastly, there was a direct effect of SMA on peer problems, β = -.15 [-.23, -.06] such that higher SMA that does not impact sleep may have a positive impact on reducing peer problems.

CONCLUSIONS

Sleep (i.e., disturbances and shorter duration) may partially account for the small associations observed between SMA and worse behavioral health in youth. To continue expanding our understanding, future research should utilize more diverse representative samples, use objective measures of SMA and sleep, and examine other relevant aspects of SMA, including content, device type, and timing of use.

Latent profile analysis for health-related quality of life, sleep quality, morning and evening type, and internet addiction among medical students

Health-related quality of life, sleep quality, morning and evening types, and internet addiction are of significant importance to the development of medical students, yet they have rarely been studied. Taking this into consideration, the study aimed to confirm latent profiles in health-related quality of life, sleep quality, morning and evening types, and internet addiction in medical students and investigate the characteristics of participants in each profile to provide suggestions for students' health. This was an observational cross-sectional study including 1221 medical student subjects at China Medical University in 2019. Multiple correspondence analysis was the initial step to verify the correspondence, dispersion, and approximation of variable categories. Latent profile analysis was used to identify the multiple correspondences between the levels of variables. Three profiles were found, including: (1) The Low sleep quality profile was characterized by the lowest sleep quality among the three existing profiles. (2) The High health-related quality of life and Low internet addiction profile was characterized by the highest level of health-related quality of life but the lowest level of internet addiction. (3) The Low health-related quality of life and High internet addiction profile was characterized by the highest standardized values of internet addiction but the lowest standardized values of health-related quality of life. This study had important implications for improving student health and supported the medical universities and hospitals in implementing targeted policies based on distinctive student characteristics.

To Binge Watch TV Series: How a Leisure Activity May Affect Sleep, Mood and Quality of Life

Objective

New TV-watching patterns increased the practice of binge-watching (BW). Considering the adaptive-maladaptive continuum of BW, the relationship between BW and health outcomes is still unclear. This study aimed to analyze some features of BW related to quality of life, focusing on sleep quality.

Methods

Four-hundred eighty-two young adults were classified into four groups according to their BW approach. Then, sleep quality, mood, and quality of life were assessed.

Results

All the investigated variables were associated with problematic and moderate BW. No differences emerged between BW as a leisure activity and not watching TV series. Moreover, quality of life is directly affected by BW.

Conclusion

Accordingly, BW should be considered a continuum of behavioral patterns from a leisure activity characterized by positive outcomes to a maladaptive behavior characterized by negative outcomes for sleep, mood, and quality of life.

A preliminary study on the association between social media at night and sleep quality: The relevance of FOMO, cognitive pre-sleep arousal, and maladaptive cognitive emotion regulation

Research shows that nighttime social media is negatively associated with sleep quality and that it might be utilized to cope with aversive psychological states related to cognitive pre-sleep arousal (i.e., transdiagnostic psychopathology variables, referring to maladaptive repetitive thought), namely Fear of Missing Out (FoMO). The use of nighttime social media to cope with other aversive cognitive states (i.e., worry/rumination), their relationship with FoMO, and these variables' association with sleep are not fully understood. This study explored the relationships between nighttime social media, sleep quality, FoMO, cognitive pre-sleep arousal, and maladaptive cognitive emotion regulation (i.e., worry/rumination). The present correlational study followed a cross-sectional design. Participants were 525 university students, ranging in age from 18 to 64 (M = 22.39, SD = 5.62). Measures of sleep quality, morningness/eveningness, cognitive pre-sleep arousal, worry, rumination, FoMO, nighttime screen, and social media use were collected online or in pencil-paper format. Multiple linear regression analyses were performed. Nighttime social media and FoMO were associated with rumination, worry (H1) and cognitive pre-sleep arousal. Both FoMO and worry predicted higher levels of cognitive pre-sleep arousal (H2) and nighttime social media use (H3). Nighttime social media use independently predicted poor sleep quality (H4). These results suggest that worry and FoMO may potentially affect sleep quality by increasing cognitive pre-sleep arousal and nighttime social media. A possible explanation for these findings is that nighttime social media might be used as a strategy to cope with aversive cognitive states. These conclusions may contribute to improving sleep intervention in this population.

Social media use is linked to poor sleep quality: The opportunities and challenges to support evidence-informed policymaking in the UAE

BACKGROUND

This study was conducted among a convenience sample of Ajman University students in UAE between February 2018 and May 2019.

METHODS

All undergraduate and master's degree students from the 1st to 5th year of medical and non-medical colleges. The survey was carried out by distributing a pre-designed, pre-structured questionnaire to the students during lectures. The questionnaires were primarily composed of three sections: demographic characteristics, educational characteristics and sleep quality characteristics. The data were analyzed using STATA version 14.2. Logistic regression analysis was used to investigate the association between sleep characteristics, social media use and other significant risk factors. The P-values < 0.05 were considered to be statistically significant.

RESULTS

The vast majority of the study participants were social media users, and a considerable proportion suffered from poor sleep quality. A significantly increased risk of bad sleep quality and intermittent/anxious sleep patterns were observed among social media users.

CONCLUSION

Health policymakers should fully consider these factors in improving the sleep quality of university students.

Estimation of Bedtimes of Reddit Users: Integrated Analysis of Time Stamps and Surveys

BACKGROUND

Individuals with later bedtimes have an increased risk of difficulties with mood and substances. To investigate the causes and consequences of late bedtimes and other sleep patterns, researchers are exploring social media as a data source. Pioneering studies inferred sleep patterns directly from social media data. While innovative, these efforts are variously unscalable, context dependent, confined to specific sleep parameters, or rest on untested assumptions, and none of the reviewed studies apply to the popular Reddit platform or release software to the research community.

OBJECTIVE

This study builds on this prior work. We estimate the bedtimes of Reddit users from the times tamps of their posts, test inference validity against survey data, and release our model as an R package (The R Foundation).

METHODS

We included 159 sufficiently active Reddit users with known time zones and known, nonanomalous bedtimes, together with the time stamps of their 2.1 million posts. The model's form was chosen by visualizing the aggregate distribution of the timing of users' posts relative to their reported bedtimes. The chosen model represents a user's frequency of Reddit posting by time of day, with a flat portion before bedtime and a quadratic depletion that begins near the user's bedtime, with parameters fitted to the data. This model estimates the bedtimes of individual Reddit users from the time stamps of their posts. Model performance is assessed through k-fold cross-validation. We then apply the model to estimate the bedtimes of 51,372 sufficiently active, nonbot Reddit users with known time zones from the time stamps of their 140 million posts.

RESULTS

The Pearson correlation between expected and observed Reddit posting frequencies in our model was 0.997 on aggregate data. On average, posting starts declining 45 minutes before bedtime, reaches a nadir 4.75 hours after bedtime that is 87% lower than the daytime rate, and returns to baseline 10.25 hours after bedtime. The Pearson correlation between inferred and reported bedtimes for individual users was 0.61 (P<.001). In 90 of 159 cases (56.6%), our estimate was within 1 hour of the reported bedtime; 128 cases (80.5%) were within 2 hours. There was equivalent accuracy in hold-out sets versus training sets of k-fold cross-validation, arguing against overfitting. The model was more accurate than a random forest approach.

CONCLUSIONS

We uncovered a simple, reproducible relationship between Reddit users' reported bedtimes and the time of day when high daytime posting rates transition to low nighttime posting rates. We captured this relationship in a model that estimates users' bedtimes from the time stamps of their posts. Limitations include applicability only to users who post frequently, the requirement for time zone data, and limits on generalizability. Nonetheless, it is a step forward for inferring the sleep parameters of social media users passively at scale. Our model and precomputed estimated bedtimes of 50,000 Reddit users are freely available.

Digital media use and sleep in late adolescence and young adulthood: A systematic review

Despite much attention on digital media use and young peoples' sleep, the literature on digital media and its impact on sleep in older adolescents and young adults remains to be synthesized. We conducted a systematic review of studies including young people aged 16-25 years. We searched Medline, Web of Science, and CINAHL for observational studies, identifying 60 studies. These studies were assessed for methodological quality. Only studies rated as moderate or high-quality studies were included (n = 42). A narrative synthesis summarized the impact of digital media use on eight sleep outcomes: Bedtime; Sleep onset latency or problems falling asleep; Sleep duration; Early awakening; Sleep disturbance; Daytime tiredness and function; Sleep deficits; Sleep quality. In summary, digital media use was associated to shorter sleep duration and poorer sleep quality. These associations were found for general screen use and use of mobile phone, computer, internet, and social media, but not for television, game console, and tablet use. Most studies investigating bedtime or nighttime use found associations to poor sleep outcomes. Later bedtime and daytime tiredness were associated with mobile phone use at night. Additional research is warranted to draw solid conclusions about the causal direction and to understand the underlying mechanisms.

"Leave your smartphone out of bed": quantitative analysis of smartphone use effect on sleep quality

Smartphones have become an integral part of people's everyday lives. Smartphones are used across all household locations, including in the bed at night. Smartphone screens and other displays emit blue light, and exposure to blue light can affect one's sleep quality. Thus, smartphone use prior to bedtime could disrupt the quality of one's sleep, but research lacks quantitative studies on how smartphone use can influence sleep. This study combines smartphone application use data from 75 participants with sleep data collected by a wearable ring. On average, the participants used their smartphones in bed for 322.8 s (5 min and 22.8 s), with an IQR of 43.7-456. Participants spent an average of 42% of their time in bed using their smartphones (IQR of 5.87-55.5%). Our findings indicate that smartphone use in bed has significant adverse effects on sleep latency, awake time, average heart rate, and HR variability. We also find that smartphone use does not decrease sleep quality when used outside of bed. Our results indicate that intense smartphone use alone does not negatively affect well-being. Since all smartphone users do not use their phones in the same way, extending the investigation to different smartphone use types might yield more information than general smartphone use. In conclusion, this paper presents the first investigation of the association between smartphone application use logs and detailed sleep metrics. Our work also validates previous research results and highlights emerging future work.

Digital addiction, academic performance, and sleep disturbance among nursing students

PURPOSE

This study aimed to examine the relationship between digital addiction, academic performance, and sleep disturbance among nursing students.

DESIGN AND METHODS

The study was a correlational and cross-sectional design. Four hundred twenty-nine nursing students were enrolled in this study.

FINDINGS

There was a positive significant relationship between the mean Sleep Disturbance (SD) T-scores and Digital Addiction Scale (DAS) scores (r = 0.203, p < 0.01). Furthermore, a positive correlation was found between the mean SD T-scores and DAS subscale scores (p < 0.01) PRACTICE IMPLICATIONS: This study demonstrated that digital addiction had an influence on sleep disturbance. It is recommended that nursing students be provided with training to inform them about negative effects of digital addiction.

Development of An Ecological Momentary Assessment of the Impact of Social Media Use Among Suicidal Adolescents

OBJECTIVE

We aimed to develop an ecological momentary assessment (EMA) measure and sampling protocol to assess the near-term impact of experiences with social media use (SMU) that are associated with risk and protective factors for adolescent suicide.

METHODS

To develop the EMA measure, we consulted literature reviews and conducted focus groups with the target population, adolescents at risk for suicide. Subsequently, we refined the measure through interviews with experts and cognitive interviews with adolescents, through which we explored adolescents' thought processes as they considered questions and response options. Data were recorded, transcribed, and analyzed using thematic analysis.

RESULTS

The initial measure had 37 items assessing a range of harmful and beneficial aspects of SMU. Through expert and cognitive interviews, we refined the measure to 4 pathways assessing positive and negative experiences with SMU as well as positive and negative in-person interactions. Each pathway included a maximum of 11 items, as well as 2 items pertaining to SMU at nighttime to be assessed once daily. Acceptable targets the EMA measure's sampling protocol included a 10-day data collection window with text message-based prompts to complete the measure triggered 2-4 times daily.

CONCLUSIONS

By assessing a range of risk and protective factors for youth suicide, while using methods to reduce participant burden, we established content validity for the EMA measure and acceptability for the sampling protocol among youth at high risk of suicide.HIGHLIGHTSDevelopment of an ecological momentary assessment measure and sampling protocolExploring brief momentary assessment of social media's impact on adolescent suicidal riskMulti-phase approach to establishing content validity and an acceptable sampling protocol.

Establishing Healthy Lifestyle Choices Early: How to Counsel Children and Their Parents

Promoting childhood and adolescent health and long-term well-being requires an emphasis on preventative care and anticipatory guidance. In this review, the authors will focus on pertinent ear, nose, and throat preventative health in children, providing clinicians with relevant and succinct information to counsel children and their parents on the following essential subjects: foreign body aspiration and ingestion, upper respiratory infection prevention, noise exposure risks, aural hygiene, risks of primary and secondhand smoke exposure, and sleep hygiene.

Association of Social Media Use on Sleep Quality and Performance Among Collegiate Athletes

OBJECTIVE

(1) To examine the effect of social media (SM) use on sleep quality and (2) to determine the effect of SM on competition performance among college athletes.

DESIGN

Cross-sectional study.

SETTING

Two local Division III colleges, MA, USA.

PARTICIPANTS

National Collegiate Athletic Association Division III swim and track and field athletes.

INTERVENTION

Data were collected onsite through an SM use form, the lifestyle survey, and the Patient-Reported Outcomes Measurement Information System Sleep Disturbance Questionnaire. Participants were divided into 3 groups based on their SM volume: (1) less active SM users (≤2 h/d), (2) moderately active SM users (>2-≤5 h/d), and (3) active SM users (>5 h/d) for analysis.

MAIN OUTCOME MEASURES

Sleep quality and sport performance data collected through publicly available competition results. The independent variable, SM volume (hours of SM use per day over 7 days), was collected using the iPhone screen time function.

RESULTS

The cohort consisted of 40 male track and field athletes and 47 female track and field (37, 79%) and swimming (10, 21%) athletes. Mean SM use was 4.6 ± 3.4 h/d. The sleep quality of active SM users was worse than less active SM users ( P = 0.033). There was an independent association between increased Facebook time and poor performance after adjusting confounders (adjusted odds ratio: 0.990, 95% confidence interval: 0.981-0.999, P = 0.049).

CONCLUSIONS

High SM use has a negative impact on sleep quality and may hinder competition performance among college athletes. These findings may have implications for developing SM use guidelines for college athletes to improve their sleep quality and performance.

Bedtime procrastination predicts the prevalence and severity of poor sleep quality of Chinese undergraduate students

ObjectiveBedtime procrastination is a type of unhealthy sleep behavior, but whether it affects sleep quality remains unknown. The current study aimed to examine the relationship between bedtime procrastination and poor sleep quality among Chinese college students. Participants: A total of 1550 Chinese undergraduates participated and effectively completed the study. Methods: This cross-sectional study collected information on bedtime procrastination and self-reported sleep quality via the Bedtime Procrastination Scale and the Pittsburgh Sleep Quality Index. Results: The prevalence of poor sleep quality was 39.42% among Chinese undergraduates. Age, education, and bedtime procrastination independently predicted the prevalence of poor sleep quality. Bedtime procrastination was a unique contributor to the severity of poor sleep quality. Conclusions: This study highlighted the independent associations between bedtime procrastination and the prevalence and severity of self-reported poor sleep quality. These findings may be helpful in designing effective measures to improve the sleep quality of college students.

Using Structural Equation Modeling to Examine Pathways between Physical Activity and Sleep Quality among Chinese TikTok Users

TikTok, the most popular social media, brings various benefits to nowadays living. However, the problematic use of TikTok has also elicited a range of health problems, such as sleep problems. Physical activity (PA) appears to play a protective role in the problematic use of TikTok and its health consequences, but the pathways between PA and sleep health are understudied. Therefore, we aimed to propose a framework to check whether PA can benefit the sleep health of TikTok users by reducing bedtime delays for TikTok. Stress and mental health issues were also considered as they are potential mediators between PA and sleep health and may also influence the problematic use of smartphones. A cross-sectional investigation that involved 660 Chinese TikTok users was conducted in April 2021. The volume of PA, perceived stress (PSS-10), depression (PHQ-9), anxiety (GAD-7), bedtime delay for TikTok use, and sleep quality (PSQI) were investigated through an online questionnaire survey. Structural equation modeling was employed to examine pathways from PA to sleep quality through stress, mental health issues (depression and anxiety), and bedtime delay for TikTok. We found that PA exerted a significant effect on sleep quality through indirect pathways (β = −0.056, p = 0.001). Stress was a critical mediator of all indirect pathways, and the pathway mediated by stress and mental health issues made a major contribution to the total effect (β = −0.048, p = 0.002). The identified pathways mediated by bedtime delay for TikTok were relatively weak but significant. PA showed a distinct effect on bedtime delay for TikTok through stress and mental health issues (β = −0.043, p = 0.001). In conclusion, our framework highlights some pathways to understanding the benefits of PA on TikTok users’ sleep quality. Future research is warranted to explore extra indirect pathways and re-examine the causal relationships between variables.

Smartphone keyboard interaction monitoring as an unobtrusive method to approximate rest-activity patterns: Inter-individual and metric-specific variations (Preprint)

BACKGROUND

Sleep is an important determinant of individuals' health and behavior during the wake phase. Novel research methods for field assessments are required to enable the monitoring of sleep over a prolonged period and across a large number of people. The ubiquity of smartphones offers new avenues for detecting rest-activity patterns in everyday life in a noninvasive an inexpensive manner and on a large scale. Recent studies provided evidence for the potential of smartphone interaction monitoring as a novel tracking method to approximate rest-activity patterns based on the timing of smartphone activity and inactivity throughout the 24-hour day. These findings require further replication and more detailed insights into interindividual variations in the associations and deviations with commonly used metrics for monitoring rest-activity patterns in everyday life.

OBJECTIVE

This study aimed to replicate and expand on earlier findings regarding the associations and deviations between smartphone keyboard-derived and self-reported estimates of the timing of the onset of the rest and active periods and the duration of the rest period. Moreover, we aimed to quantify interindividual variations in the associations and time differences between the 2 assessment modalities and to investigate to what extent general sleep quality, chronotype, and trait self-control moderate these associations and deviations.

METHODS

Students were recruited to participate in a 7-day experience sampling study with parallel smartphone keyboard interaction monitoring. Multilevel modeling was used to analyze the data.

RESULTS

In total, 157 students participated in the study, with an overall response rate of 88.9% for the diaries. The results revealed moderate to strong relationships between the keyboard-derived and self-reported estimates, with stronger associations for the timing-related estimates (β ranging from .61 to .78) than for the duration-related estimates (β=.51 and β=.52). The relational strength between the time-related estimates was lower, but did not substantially differ for the duration-related estimates, among students experiencing more disturbances in their general sleep quality. Time differences between the keyboard-derived and self-reported estimates were, on average, small (<0.5 hours); however, large discrepancies were also registered for quite some nights. The time differences between the 2 assessment modalities were larger for both timing-related and rest duration-related estimates among students who reported more disturbances in their general sleep quality. Chronotype and trait self-control did not significantly moderate the associations and deviations between the 2 assessment modalities.

CONCLUSIONS

We replicated the positive potential of smartphone keyboard interaction monitoring for estimating rest-activity patterns among populations of regular smartphone users. Chronotype and trait self-control did not significantly influence the metrics' accuracy, whereas general sleep quality did: the behavioral proxies obtained from smartphone interactions appeared to be less powerful among students who experienced lower general sleep quality. The generalization and underlying process of these findings require further investigation.

The complicated impact of media use before bed on sleep: Results from a combination of objective EEG sleep measurement and media diaries

Media use has been linked to sleep disturbance, but the results are inconsistent. This study explores moderating conditions. A media diary study with 58 free-living adults measured the time spent with media before bed, the location of use, and multitasking. Electroencephalography (EEG) captured bedtime, total sleep time, and the percent of time spent in deep (Stage N3), and rapid eye movement (REM) sleep. Media use in the hour before sleep onset was associated with an earlier bedtime. If the before bed use did not involve multitasking and was conducted in bed, that use was also associated with more total sleep time. Media use duration was positively associated with (later) bedtime and negatively associated with total sleep time. Sleep quality, operationalised as the percent of total sleep time spent in N3 and REM sleep, was unaffected by media use before bed. Bedtime media use might not be as detrimental for sleep as some previous research has shown. Important contextual variables moderate the relationship, such as location, multitasking, and session length.

Spectrophotometric properties of commercially available blue blockers across multiple lighting conditions

Lenses that filter short-wavelength ("blue") light are commercially marketed to improve sleep and circadian health. Despite their widespread use, minimal data are available regarding their comparative efficacy in curtailing blue light exposure while maintaining visibility. Fifty commercial lenses were evaluated using five light sources: a blue LED array, a computer tablet display, an incandescent lamp, a fluorescent overhead luminaire, and sunlight. Absolute irradiance was measured at baseline and for each lens across the visual spectrum (380-780 nm), which allowed calculation of percent transmission. Transmission specificity was also calculated to determine whether light transmission was predominantly circadian-proficient (455-560 nm) or non-proficient (380-454 nm and 561-780 nm). Lenses were grouped by tint and metrics were compared between groups. Red-tinted lenses exhibited the lowest transmission of circadian-proficient light, while reflective blue lenses had the highest transmission. Orange-tinted lenses transmitted similar circadian-proficient light as red-tinted lenses but transmitted more non-circadian-proficient light, resulting in higher transmission specificity. Orange-tinted lenses had the highest transmission specificity while limiting biologically active light exposure in ordinary lighting conditions. Glasses incorporating these lenses currently have the greatest potential to support circadian sleep-wake rhythms.

The Relationship Between Digital Activity and Bedtime, Sleep Duration, and Sleep Quality in Chinese Working Youth

PURPOSE

The study aims to examine whether and how digital activities influence sleep issues among working Chinese youth.

METHODS

This study used data from the China Family Panel Studies (CFPS) a Chinese population-based survey, and employed the multilevel ordinal logistic regression model (MOLRM) to test the associations between digital engagement (whether to engage in digital activity, frequency, and duration) and sleep issues (bedtime, sleep duration, and quality) among Chinese working youth. Additionally, the restricted cubic spline model (RCSM) was adopted to fit the MOLRM to evaluate the nonlinear relationship between digital activity duration and sleep quality, and thus determine the optimal range of digital activity duration.

RESULTS

The analysis included 7849 working young adults. The digital usage rate was 84.11%. Digital use was not significantly associated with average, workday, or free-day sleep duration, after controlling for all potential confounders. However, most digital activity indicators could significantly predict bedtime and sleep quality. Furthermore, the RCSM indicated a non-linear relationship pattern between digital activity duration and sleep quality, with a weekly peak point of 25 h. Age significantly moderated the relationship between digital activity, sleep duration and bedtime. Younger youth who used digital media more frequently and for a longer time tended to sleep later and had shorter sleep duration than older youth.

CONCLUSION

Digital usage significantly predicted later bedtime among Chinese working youth; however, it was not linked with sleep duration on workdays or free days. In parallel, a nonlinear correlation between digital activity duration and sleep quality indicated that appropriate digital activity duration (less than 25 h weekly) may contribute to good sleep quality.

Pre-sleep social media use does not strongly disturb sleep: a sleep laboratory study in healthy young participants

OBJECTIVE

Sleep is critical for our mental health and optimal cognitive functioning. Social media use is increasingly common and suspected to disturb sleep due to increasing bedtime arousal. However, most studies rely on self-reported sleep.

METHODS

We tested the effects of 30 min social media use on arousal and subsequent sleep in the sleep laboratory in 32 healthy young volunteers. Effects of blue-light were excluded in this study. We compared it to 30 min progressive muscle relaxation (PMR) and neutral sleep in a within-subject design.

RESULTS

Thirty minutes of social media use immediately before sleep did not significantly increase arousal and did neither disturb objective nor subjective sleep. After social media use, participants only spent less time in sleep stage N2. In contrast, PMR had the expected positive effects on pre-sleep arousal level indicated by reduced heart rate. In addition, PMR improved sleep efficiency, reduced sleep onset latency, and shortened the time to reach slow-wave sleep compared to a neutral night. Oscillatory power in the slow-wave activity and spindle bands remained unaffected.

CONCLUSION

Social media use before sleep (controlling for effects of blue-light) had little effect on bedtime arousal and sleep quality than what was previously expected. The most notable effect appears to be the additional time spent engaging in social media use at bedtime, potentially keeping people from going to sleep. As wake up-time is mostly determined externally, due to school or working hours, limiting personal media use at bedtime-and especially in bed-is recommended to get sufficient hours of sleep.

Electronic Device Use before Bedtime and Sleep Quality among University Students

Using electronic devices before bedtime impacts sleep quality and has become a major public health issue. This study aims to investigate the associations between electronic devices (EDs) use before bedtime and sleep quality in Vietnamese university students. A total of 369 university students from three departments were recruited. Participants completed self-report surveys, including demographic characteristics, lifestyle, ED-use behaviors, the Pittsburgh Sleep Quality Index, and the Center for Epidemiologic Studies Depression Scale. A total of 48.8% of the students experienced poor sleep quality, and 98.1% reported using at least one type of ED every day within two hours before bedtime. Smartphones are the most used devices (92.3%). ED usage within two hours before bedtime (p = 0.031), lack of exercise (p = 0.006), alcohol consumption (p = 0.025), and coffee intake after 4 pm (p = 0.018) were associated with poor sleep quality. ED use near bedtime for a duration longer than 30 min (p = 0.001) and depression (p < 0.001) were associated with poorer sleep quality among university students. ED use near bedtime more than 30 min was significantly associated with poorer sleep quality after adjusting depression status, exercise, and caffeine/alcohol intake in the latter part of the day. This study emphasizes the importance of adequate sleep and restriction of ED use near bedtime, which are necessary for better sleep in university students.

Contemporary Variables that Impact Sleep and Development in Female Adolescent Swimmers and Gymnasts

The effects of sleep on elite athletes in late adolescence and early adulthood have been well documented in a myriad of sports. However, there is underrepresentation of pre-pubertal and young female adolescent athlete research between the ages of 11-17, and specifically female gymnast and swimmers. Neglecting to understand how high energy demand at a young age relates to sleep and restoration may lead to developmental ramifications for this group, as they display physiological dysfunctions like delayed puberty, amenorrhea and are at risk for the female athlete triad or components of the triad. This review aims to summarize the contemporary variables of blue light emitting screens, social media, and caffeine on quality and quantity of sleep in young athletes while identifying gaps in the literature on how these factors impact the target group of young female swimmers and gymnasts.  The implications of this work include sleep hygiene recommendations for increasing duration and quality of sleep, as well as future research with respect to electronic device usage, social media participation, caffeine consumption, and sport engagement in female early adolescent athletes.

It's not all about the likes: Social media affordances with nighttime, problematic, and adverse use as predictors of adolescent sleep indicators

OBJECTIVES

Adolescents are the most prominent users of social media, and their exposure to different contents, platforms, and types of use continues to develop. At the same time, sleep deprivation is on the rise, which may contribute to worsened health. Therefore, this cross-sectional study set out to examine the relationships among several social media affordances, habits of use, and sleep indicators in adolescents.

METHODS

Students ages 12-18 from a high school on Long Island, New York (N = 410) participated in an anonymous online survey focusing on various aspects of social media use as well as major sleep indicators (sleep displacement, presleep arousal, sleep quality, fatigue).

RESULTS

Snapchat was the only platform to predict a worsened sleep indicator (later bedtime) and it correlated with problematic, adverse, and nighttime use, possibly due to closer relationships among users. More viewing of posts of sports, friends, and family predicted better sleep. Additionally, nighttime social media use, problematic social media use, and adverse social media use each predicted at least one worsened sleep indicator in a hierarchical regression model.

CONCLUSIONS

Although some implications were positive, results provided insight into the cons of social media use. This study provides evidence that in order to understand the role of social media in the sleep-wake process, one must look at the specific affordances each platform provides and the different nighttime, problematic, and adverse habits of use that can arise. Documenting the variety of media use behaviors, however, introduces a considerable multiple testing threat to this research area.

Practice change: Social Media Screening Questionnaire to identify high-risk adult psychiatric patients

PURPOSE

Include social media screening during initial psychiatric examination with new adult patients to increase psychiatric providers' awareness of the rate and impact of social media use in their patients.

DESIGN AND METHODS

Plan-Do-Study-Act cycles were implemented to evaluate the effectiveness of psychiatric provider 5-question social media screening during the initial evaluation.

FINDINGS

Screening for social medial usage (N = 136) improved providers' a wareness of the rate and impact of social media use on patients' distress levels. The process of screening influenced a conversation between provider and patient about healthy social media use.

PRACTICE IMPLICATIONS

The inclusion of social media screening during initial psychiatric evaluation may aid in the assessment of risk factors for psychological distress.

"It's Been Negative for Us Just All the Way Across the Board": Focus Group Study Exploring Parent Perceptions of Child Screen Time During the COVID-19 Pandemic

BACKGROUND

Child screen time (ST) has soared during the COVID-19 pandemic as lockdowns and restrictions have forced changes to regular family routines. It is important to investigate how families are navigating ST.

OBJECTIVE

This study aimed to explore families' experiences of ST during the COVID-19 pandemic.

METHODS

Virtual focus group sessions were conducted between December 2020 and February 2021 in English and Spanish. Transcripts were analyzed using reflexive thematic analysis.

RESULTS

In total, 48 parents (predominantly Hispanic) residing in California participated in 1 of 14 focus group sessions. Children were attending school remotely at the time of the study. A total of 6 themes and 1 subtheme were identified: (1) total ST has increased; (2) children are too attached to screens; (3) ST has advantages and disadvantages but parents perceive ST as mostly negative; (4) parents and children have limited options; (5) ST restrictions (subtheme: children react negatively when ST is restricted); and (6) parents are concerned that children are not getting enough exercise.

CONCLUSIONS

This study provides a cross-sectional insight into how family life has changed with regard to ST during the COVID-19 pandemic. Parents expressed concerns about total ST, the addictive nature of it, and lack of physical activity. It is important that future studies examine the long-term effects of heavy ST and preemptively introduce ways to redirect children's ST habits as the country attempts to establish a new normal.

Relation among Perceived Weight Change, Sedentary Activities and Sleep Quality during COVID-19 Lockdown: A Study in an Academic Community in Northern Italy

In Italy, COVID-19 lockdown was imposed from 8 March until 3 May 2020 with negative consequences on the lifestyles and health of people. Within this context, the paper aims: (i) to analyse the impact of COVID-19 lockdown on perceived weight changes; (ii) to evaluate factors associated with the perception of weight changes (Body Mass Index (BMI), sleep quality, time spent in sedentary activities), in an Italian academic community of students and workers. A total of 3666 participants took part in this cross-sectional study (2838 students and 828 workers, of whom 73.0% were female). T-test, Chi-square test and the two-way ANOVA were used. Results showed that 43.3% of participants perceived a weight gain. Workers experienced a more substantial increase in body weight (0.7 kg) compared to students (0.3 kg; p = 0.013). A significant difference between preobese/obese workers (0.9 kg) and students (-0.3 kg; p < 0.001) was found. Overall, 57.0% of the sample was characterized by high levels of sedentary activities. Sedentary people noticed a higher weight gain (0.4 kg) compared to less sedentary people (0.3 kg; p = 0.048). More than 45% of participants reported a worsening of sleep quality and showed a perceived increase in body weight (0.5 kg) in comparison to those who improved their sleep quality (no weight change; p = 0.001). Designing tailored interventions to promote health-related behaviours during lockdown periods is essential.

Effect of evening blue light blocking glasses on subjective and objective sleep in healthy adults: A randomized control trial

OBJECTIVES

Evening blue light has been shown to suppress melatonin, which can negatively impact sleep quality. The impact of evening blue light blocking (BLB) interventions on sleep remains ambiguous due to lack of randomized control trials. The present study tests the hypothesis that BLB glasses improve subjective and objective sleep in a population of healthy adults.

DESIGN

Two-week, randomized, controlled, crossover design.

SETTING

At-home testing of individuals in Michigan and Montana.

PARTICIPANTS

Twenty healthy adults (11 men, 9 women, age: 32 ± 12, body mass index: 28 ± 4 kg/m²).

INTERVENTION

Following a 1-week run-in baseline (ie, no glasses), participants were randomized to 1-week of BLB or control (ie, clear lens) glasses. Upon finishing the 1-week intervention, participants crossed over to the opposite condition. In both conditions, glasses were worn for 7 consecutive days from 6 PM until bedtime.

MEASUREMENTS

Objective sleep parameters were obtained using wrist actigraphy. Subjective sleep measures were assessed using sleep diaries. Karolinska Sleep Diaries were used to assess perceived sleep quality.

RESULTS

BLB reduced subjective sleep onset (21 ± 28 vs 24 ± 21 minute, P = .033) and awakenings (1.6 ± 1.0 vs 2.2 ± 1.0 awakenings, P = .019) compared to the control condition. In contrast, objective measures of sleep were not significantly impacted. In fact, our primary outcome variable of total sleep time (TST) tended to be paradoxically shorter in the BLB condition for both subjective (468 ± 45 vs 480 ± 48 minute, P = .066) and objective (433 ± 40 vs 449 ± 39 minute, P = .075) TST.

CONCLUSIONS

Blue light blocking glasses did not improve objective measures of sleep time or quality in healthy adults.

Social Media Use and Adolescents' Sleep: A Longitudinal Study on the Protective Role of Parental Rules Regarding Internet Use before Sleep

The popularity of social media use among adolescents has raised concerns about the potentially harmful effects of social media use on adolescents' sleep. Since longitudinal research considering this relationship is scarce, the present two-wave longitudinal study of 2021 secondary school students (Mage = 13.86, SD = 1.25) examined whether frequency of social media use and problematic social media use predicted adolescents' bedtime and quality of sleep. Moreover, the protective role of parental rules regarding Internet and smartphone use one hour before sleep was examined. The findings indicated that strict parental rules about Internet and smartphone use before sleep might prevent negative consequences of social media use on bedtime and sleep quality, but only among less engaged social media users. Once adolescents are highly engaged social media users, strict parental rules do not seem to prevent negative media influences on sleep. This implies that limiting Internet accessibility before bedtime can help prevent adolescents' sleep problems, but that regulation is less effective for adolescents who are already highly involved in social media use.

Viewing Trends and Users’ Perceptions of the Effect of Sleep-Aiding Music on YouTube: Quantification and Thematic Content Analysis

Background

Sleep plays an essential role in the psychological and physiological functioning of humans. A report from the Centers for Disease Control and Prevention (CDC) found that sleep duration was significantly reduced among US adults in 2012 compared to 1985. Studies have described a significant association between listening to soothing music and an improvement in sleep quality and sleep duration. YouTube is a platform where users can access sleep-aiding music videos. No literature exists pertaining to the use of sleep-aiding music on YouTube.

Objective

This study aimed to examine the patterns of viewing sleep-aiding music videos on YouTube. We also performed a content analysis of the comments left on sleep-aiding music video posts, to describe the perception of users regarding the effects of these music videos on their sleep quality.

Methods

We searched for sleep-aiding music videos published on YouTube between January 1, 2012, and December 31, 2017. We sorted videos by view number (highest to lowest) and used a targeted sampling approach to select eligible videos for qualitative content analysis. To perform the content analysis, we imported comments into a mixed-method analytical software. We summarized variables including total views, likes, dislikes, play duration, and age of published music videos. All descriptive statistics were completed with SAS statistical software.

Results

We found a total of 238 sleep-aiding music videos on YouTube that met the inclusion criteria. The total view count was 1,467,747,018 and the total playtime was 84,252 minutes. The median play length was 186 minutes (IQR 122 to 480 minutes) and the like to dislike ratio was approximately 9 to 1. In total, 135 (56.7%) videos had over 1 million views, and 124 (52.1%) of the published sleep-aiding music videos had stayed active for 1 to 2 years. Overall, 4023 comments were extracted from 20 selected sleep-aiding music videos. Five overarching themes emerged in the reviewed comments, including viewers experiencing a sleep problem, perspective on the positive impact of the sleep-aiding music videos, no effect of the sleep-aiding music videos, time to initiation of sleep or sleep duration, and location of viewers. The overall κ statistic for the codes was 0.87 (range 0.85-0.96).

Conclusions

This is the first study to examine the patterns of viewing sleep-aiding music videos on YouTube. We observed a substantial increase in the number of people using sleep-aiding music videos, with a wide variation in viewer location. This study supports the hypothesis that listening to soothing music has a positive impact on sleep habits.

Sleep Disruption Exacerbates and Prolongs the Inflammatory Response to Traumatic Brain Injury

Traumatic brain injury (TBI) alters stress responses, which may influence neuroinflammation and behavioral outcome. Sleep disruption (SD) is an understudied post-injury environmental stressor that directly engages stress-immune pathways. Thus, we predicted that maladaptive changes in the hypothalamic-pituitary-adrenal (HPA) axis after TBI compromise the neuroendocrine response to SD and exacerbate neuroinflammation. To test this, we induced lateral fluid percussion TBI or sham injury in female and male C57BL/6 mice aged 8-10 weeks that were then left undisturbed or exposed to 3 days of transient SD. At 3 days post-injury (DPI) plasma corticosterone (CORT) was reduced in TBI compared with sham mice, indicating altered HPA-mediated stress response to SD. This response was associated with approach-avoid conflict behavior and exaggerated cortical neuroinflammation. Post-injury SD specifically enhanced neutrophil trafficking to the injured brain in conjunction with dysregulated aquaporin-4 (AQP4) polarization. Delayed and persistent effects of post-injury SD were determined 4 days after SD concluded at 7 DPI. SD prolonged anxiety-like behavior regardless of injury and was associated with increased cortical Iba1 labeling in both sham and TBI mice. Strikingly, TBI SD mice displayed an increased number of CD45+ cells near the site of injury, enhanced cortical glial fibrillary acidic protein (GFAP) immunolabeling, and persistent expression of Trem2 and Tlr4 7 DPI compared with TBI mice. These results support the hypothesis that post-injury SD alters stress-immune pathways and inflammatory outcomes after TBI. These data provide new insight to the dynamic interplay between TBI, stress, and inflammation.

Social media use predicts later sleep timing and greater sleep variability: An ecological momentary assessment study of youth at high and low familial risk for depression

INTRODUCTION

Social media (SM) use has been increasingly recognized as a potential contributor to poor sleep. Few studies have examined SM use and sleep using ecological momentary assessment (EMA), compared different types of media use (SM, television, gaming), or examined whether youth at high and low familial risk for depression are differentially affected by SM use.

METHODS

The current study included 76 youth (46% female; Mean age = 11.28 years) who were recruited based on parental history of recurrent depression (N = 35 high risk; N = 41 low risk) in the United States. Youth completed a 9-day EMA protocol, which included current activity at time of prompt and daily sleep onset and offset times. Regression and multilevel models were conducted to examine the effects of media use on sleep.

RESULTS

Results indicated that youth who used more SM (mean and number of days) went to sleep later, but did not have shorter sleep duration. Youth with more SM use also had higher levels of variability of both sleep timing and sleep duration across the 9-day period. There were no effects of gaming or TV on sleep, and youth at high risk for depression did not have differences in SM use or its effects on sleep compared to low-risk youth.

CONCLUSIONS

These findings indicate a unique impact of SM use on sleep timing and variability for youth (regardless of risk status), which may suggest a unique and modifiable pathway through which SM use contributes to poor health.

Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy

Italy is one of the major COVID-19 hotspots. To reduce the spread of the infections and the pressure on Italian healthcare systems, since March 10, 2020, Italy has been under a total lockdown, forcing people into home confinement. Here we present data from 1,310 people living in the Italian territory (M_age  = 23.91 ± 3.60 years, 880 females, 501 workers, 809 university students), who completed an online survey from March 24 to March 28, 2020. In the survey, we asked participants to think about their use of digital media before going to bed, their sleep pattern and their subjective experience of time in the previous week (March 17-23, which was the second week of the lockdown) and up to the first week of February (February 3-10, before any restriction in any Italian area). During the lockdown, people increased the usage of digital media near bedtime, but this change did not affect sleep habits. Nevertheless, during home confinement, sleep timing markedly changed, with people going to bed and waking up later, and spending more time in bed, but, paradoxically, also reporting a lower sleep quality. The increase in sleep difficulties was stronger for people with a higher level of depression, anxiety and stress symptomatology, and associated with the feeling of elongation of time. Considering that the lockdown is likely to continue for weeks, research data are urgently needed to support decision making, to build public awareness and to provide timely and supportive psychosocial interventions.

Objectively-Assessed Physical Activity, Sedentary Behavior, Smartphone Use, and Sleep Patterns Pre- and during-COVID-19 Quarantine in Young Adults from Spain

This study assessed the effects of COVID-19 home confinement on physical activity, sedentary behavior, smartphone use, and sleep patterns. Data was collected in a sample of 20 young adults (mean age ± SD: 22.6 ± 3.4 years; 55% males) over seven days pre- and during the COVID-19 lockdown. Objective and subjective physical activity (Accelerometer and the International Physical Activity Questionnaire (IPAQ), respectively), the number of hours sitting (IPAQ), objectively-measured smartphone use (smartphone screen time applications), and objective and subjective sleep (accelerometer and the Pittsburgh Sleep Quality Index, respectively) were assessed. Results revealed significantly greater walking time and mean steps (p < 0.001, d = 1.223 to 1.605), and moderate and vigorous physical activity (p < 0.05, d = 0.568 to 0.616), in the pre- compared with the during-COVID-19 lockdown phase. Additionally, smartphone use (p = 0.009, d = 0.654), sitting time (p = 0.002, d = 1.120), and total sleep (p < 0.004, d = 0.666) were significantly greater in the during- compared with the pre-COVID-19 lockdown phase. Multiple regressions analyses showed associations between physical activity and sedentary behavior and sleep quality. The number of hours sitting per day and moderate-to-vigorous physical activity significantly predicted deep sleep (adj.R2 = 0.46). In conclusion, this study revealed that during the COVID-19 outbreak, behaviors changed, with participants spending less time engaging in physical activity, sitting more, spending more time using the smartphone, and sleeping more hours. These findings may be of importance to make recommendations, including lifestyle modifications during this time.

Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy

Italy is one of the major COVID-19 hotspots. To reduce the spread of the infections and the pressure on Italian healthcare systems, since March 10, 2020, Italy has been under a total lockdown, forcing people into home confinement. Here we present data from 1,310 people living in the Italian territory (M_age  = 23.91 ± 3.60 years, 880 females, 501 workers, 809 university students), who completed an online survey from March 24 to March 28, 2020. In the survey, we asked participants to think about their use of digital media before going to bed, their sleep pattern and their subjective experience of time in the previous week (March 17-23, which was the second week of the lockdown) and up to the first week of February (February 3-10, before any restriction in any Italian area). During the lockdown, people increased the usage of digital media near bedtime, but this change did not affect sleep habits. Nevertheless, during home confinement, sleep timing markedly changed, with people going to bed and waking up later, and spending more time in bed, but, paradoxically, also reporting a lower sleep quality. The increase in sleep difficulties was stronger for people with a higher level of depression, anxiety and stress symptomatology, and associated with the feeling of elongation of time. Considering that the lockdown is likely to continue for weeks, research data are urgently needed to support decision making, to build public awareness and to provide timely and supportive psychosocial interventions.

Sleep Disorders in Adolescents

Chronic sleep deprivation is a common, treatable condition among adolescents. Growing literature supports a myriad consequences that impact overall health, behavior, mood, and academic performance in this vulnerable age group during a time when there are rapid changes in physical development and emotional regulation. This article reviews the epidemiology and health effects of sleep deprivation in adolescents as well as common disorders leading to sleep loss and evidence to support treatment. Although a variety of important sleep disorders may disrupt quality of sleep in adolescents, such as obstructive sleep apnea, restless leg syndrome, and narcolepsy, this article will focus on common disorders that affect the quantity of sleep, such as poor sleep hygiene, circadian rhythm disorders, and insomnia.

Associations between positive and negative social media experiences and sleep disturbance among young adults

OBJECTIVES

We sought to examine the association of positive and negative experiences using social media (SM) and sleep disturbance in a national survey of U.S. young adults.

METHODS

Experiences using SM were assessed with 2 items asking participants about the percentage of time using SM that involved a negative/positive experience that they were personally involved in. Sleep disturbance was assessed using the validated PROMIS 4-item short form. Ordinal logistic regression was used to examine associations between positive and negative SM experiences and high sleep disturbance, while controlling for relevant covariates.

RESULTS

Although reporting high levels of negative experiences was significantly associated with greater odds of high sleep disturbance (AOR = 1.49, 95%CI = 1.18-1.89), reporting high levels of positive experiences was not associated with sleep disturbance.

CONCLUSIONS

These findings suggest that more robust examinations of negative SM experiences-especially as they relate to sleep disturbance-may be warranted.

Psychometric properties of the Patient-Reported Outcomes Measurement Information System (PROMIS) Sleep Disturbance and Sleep-Related Impairment item banks in adolescents

Sleep problems have a high prevalence and negative daytime consequences in adolescents. Current sleep measures for this age group have limitations. The Patient‐Reported Outcomes Measurement Information System (PROMIS^®) developed sleep item banks for adults. In a previous validation study, these item banks were adapted to a shortened version for adolescents. The current study aimed to further explore the psychometric properties of the 11‐item Sleep‐Related Impairment and 23‐item Sleep Disturbance item banks in Dutch adolescents. We investigated structural validity by testing item response theory assumptions and model fit; measurement invariance by performing differential item functioning analyses; performance as a computerized adaptive test; reliability by marginal reliability estimates and test–retest reliability (intraclass correlation coefficients and limits of agreement); and construct validity by hypothesis testing. Additionally, we provide mean values for the item banks. The study sample consisted of 1,046 adolescents (mean age 14.3 ± 1.6), including 1,013 high‐school students and 33 sleep‐clinic patients. The Sleep Disturbance‐23 showed lack of unidimensionality, but had sufficient test–retest reliability, and could distinguish between adolescents with and without sleep or health issues. The Sleep‐Related Impairment‐11 showed sufficient unidimensionality and model fit and was thus tested as a computerized adaptive test, demonstrating an equal amount of reliable measures to the full item bank. Furthermore, the Sleep‐Related Impairment‐11 could distinguish between adolescents with and without sleep or health issues and test–retest reliability was moderate. The use of both item banks in the full form and the use of the Sleep‐related Impairment‐11 as a computer adaptive test is recommended.

Teenage sleep and technology engagement across the week

BACKGROUND

Throughout 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.

METHODS

This 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.

RESULTS

The 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.

CONCLUSIONS

Results 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.

Social media use and adolescent sleep patterns: cross-sectional findings from the UK millennium cohort study

OBJECTIVES

This study examines associations between social media use and multiple sleep parameters in a large representative adolescent sample, controlling for a wide range of covariates.

DESIGN

The authors used cross-sectional data from the Millennium Cohort Study, a large nationally representative UK birth cohort study.

PARTICIPANTS

Data from 11 872 adolescents (aged 13-15 years) were used in analyses.

METHODS

Six self-reported sleep parameters captured sleep timing and quality: sleep onset and wake times (on school days and free days), sleep onset latency (time taken to fall asleep) and trouble falling back asleep after nighttime awakening. Binomial logistic regressions investigated associations between daily social media use and each sleep parameter, controlling for a range of relevant covariates.

RESULTS

Average social media use was 1 to <3 hours per day (31.6%, n=3720). 33.7% were classed as low users (<1 hour; n=3986); 13.9% were high users (3 to <5 hours; n=1602) and 20.8% were very high users (5+ hours; n=2203). Girls reported spending more time on social media than boys. Overall, heavier social media use was associated with poorer sleep patterns, controlling for covariates. For example, very high social media users were more likely than comparable average users to report late sleep onset (OR 2.14, 95% CI 1.83 to 2.50) and wake times (OR 1.97, 95% CI 1.32 to 2.93) on school days and trouble falling back asleep after nighttime awakening (OR 1.36, 95% CI 1.10 to 1.66).

CONCLUSIONS

This study provides a normative profile of UK adolescent social media use and sleep. Results indicate statistically and practically significant associations between social media use and sleep patterns, particularly late sleep onset. Sleep education and interventions can focus on supporting young people to balance online interactions with an appropriate sleep schedule that allows sufficient sleep on school nights.