Adolescents who perceive fewer consequences of risk-taking choose to switch off games later at night

Poor subjective sleep quality and trait impulsivity in patients with bipolar disorder

BACKGROUND

Sleep disturbance and impulsivity are key components of mood vulnerability in bipolar disorder (BD), but few studies have assessed the association between these two symptoms among patients with BD.

METHODS

Forty-seven euthymic patients with bipolar I disorder (BDI) or bipolar II disorder (BDII) and 58 age- and sex-matched healthy controls were enrolled in this cross-sectional study. Trait impulsivity was measured using the Barratt Impulsiveness Scale Version 11 (BIS-11), which yielded 3 second-order factors: attention, motor, and non-planning. Subjective sleep quality was assessed using the self-reported Pittsburgh Sleep Quality Index (PSQI). General linear models (GLMs) were used to assess the associations between subjective poor sleep and trait impulsivity with multiple testing corrections.

RESULTS

Patients with BD scored higher in BIS-11 and PSQI than healthy controls. PSQI total scores positively correlated with BIS-11 total scores, while sleep disturbance and daytime dysfunction were associated with attentional impulsiveness after controlling for covariates. Participants with higher PSQI total scores (>10) had higher scores in BIS-11 total, attention, and non-planning than those with low PSQI scores (≤5).

CONCLUSION

These findings support the hypothesis that poor sleep quality might lead to impulsivity and add to the growing evidence that improving sleep quality may be a therapeutic target for patients with BD.

A bidirectional model of sleep and technology use: A theoretical review of How much, for whom, and which mechanisms

The link between technology and sleep is more complex than originally thought. In this updated theoretical review, we propose a new model informed by the growing body of evidence in the area over the past 10 years. The main theoretical change is the addition of bi-directional links between the use of technology and sleep problems. We begin by reviewing the evidence to date for the originally proposed mechanisms of bright light, arousal, nighttime sleep disruptions, and sleep displacement. Then, in support of the new direction of effect (sleep problems preceding technology use), we propose two new mechanisms: technology before sleep might be used as a time filler and/or as an emotional regulation strategy to facilitate the sleep-onset process. Finally, we present potential moderators of the association between technology and sleep, in recognition of protective and vulnerability factors that may mitigate or exacerbate the effects of technology on sleep and vice versa. The goal of this theoretical review is to update the field, guide future public health messages, and to prompt new research into how much technology and sleep affect each other, for whom it may be problematic, and which mechanisms may explain their association.

Development of evening sleep homeostatic pressure in early adolescent boys

The physiological processes governing sleep regulation show maturational changes during adolescent development. To date, data are available to specify when delays in circadian timing occur; however, no longitudinal data exist to characterize the maturation of the accumulation of sleep pressure across the evening. The aim of this longitudinal study was to test whether this change in evening sleep propensity can be identified during early adolescence. Twenty pre-pubescent boys' (Mage = 10.3, SD = 0.4 years) evening sleep homeostats were assessed using a series of sleep latency tests every hour (7:30 p.m. to 3:30 a.m.) at 6-month intervals across four waves. While results revealed shorter sleep onset latencies with increasing wakefulness (p < .001), this effect was not moderated by study wave (p = .79). Evening sleep propensity thus appears to remain stable in boys during early adolescence. Future studies should expand upon these findings by using larger samples of girls as well as boys across an extended age range during the teenage years.

What's "app"-ning to adolescent sleep? Links between device, app use, and sleep outcomes

This study investigated the associations between adolescent evening use of technology devices and apps, night time sleep, and daytime sleepiness. Participants were 711 adolescents aged 12-18 years old (46% Female, M_age = 15.1, SD = 1.2). Time spent using technology devices and apps in the hour before bed, and in bed before sleep onset, was self-reported. Participants additionally completed a questionnaire about their sleep on school nights and next day sleepiness. In the hour before bed, 30 min of phone use was associated with a 9-min delay in bedtimes. Thirty minutes spent using laptops, gaming consoles, and watching YouTube was associated with later lights out times of 9 min, ∼16 min and ∼11 min respectively, while watching TV was associated with a 9 min earlier lights out times. Using gaming consoles and watching YouTube were associated with greater odds of receiving insufficient sleep (≤7 h TST). In bed before sleep onset, 30 min spent using laptops, phones, iPad/tablets, and watching YouTube were linked with later lights out times of ∼7 min for phones and laptops, 9 min for iPad/tablets, and ∼13 min for YouTube. Watching Netflix was associated with greater daytime sleepiness. YouTube at this time point was associated with increased odds of sleeping ≤7 h on school nights. Adolescents are engaging with a wide range of technology devices and apps in the evenings. However, certain devices and apps (e.g., phones, laptops, gaming and YouTube) might lead to more negative sleep outcomes for adolescents on school nights compared to others.

Sleep’s role in the development and resolution of adolescent depression

Two adolescent mental health fields — sleep and depression — have advanced largely in parallel until about four years ago. Although sleep problems have been thought to be a symptom of adolescent depression, emerging evidence suggests that sleep difficulties arise before depression does. In this Review, we describe how the combination of adolescent sleep biology and psychology uniquely predispose adolescents to develop depression. We describe multiple pathways and contributors, including a delayed circadian rhythm, restricted sleep duration and greater opportunity for repetitive negative thinking while waiting for sleep. We match each contributor with evidence-based sleep interventions, including bright light therapy, exogenous melatonin and cognitive-behaviour therapy techniques. Such treatments improve sleep and alleviate depression symptoms, highlighting the utility of sleep treatment for comorbid disorders experienced by adolescents.

Sleep problems are both a symptom and precursor of adolescent depression. In this Review, Gradisar et al. describe how the combination of adolescent sleep biology and psychology predisposes adolescents to develop depression, and describe interventions that improve sleep and depression symptoms in this population.

Identifying electronic-sport athletes' sleep-wake cycle characteristics

Organized electronic-sport competitions (e-Sport) is related to several health problems, including sleep disorders. The objective of this study was to evaluate the characteristics of the sleep-wake cycle of League of Legends (LoL) athletes during their pre-training, training, pre-competition, and competition routines. Twenty male elite LoL players completed the questionnaires related to sleep pattern (Pittsburgh Sleep Quality Index), sleepiness (Epworth Sleepiness Scale), and chronotype (Morningness-Eveningness Questionnaire), and they wore an actigraph for 7 days. Pre-training and pre-competition assessments were carried out by questionnaires (n = 20) and training and competition assessments by actigraph (n = 16). The chronotype that most Eathletes presented was a moderately evening type. They presented a poor sleep quality and were borderline for excessive daytime sleepiness. Sleep onset and offset times were significantly prolonged during the competition condition (t = 2.11, p < .05; t = 2.51, p < .05). Correlations showed a relationship between PSQI and Sleepiness in the pre-training and pre-competition conditions (r = 0.50, p = .02) and chronotype with sleep onset (r = 0.61, p = .01), total sleep time (r = 0.55, p = .02), and time awake (r = 0.49, p = .04) in the competition condition. Linear regression analysis indicated associations between the PSQI and sleepiness (25%; p = .02) during pre-training and pre-competition. During the competition there were associations between chronotype and sleep onset (37%; p = .01), chronotype and time awake (24%; p = .04), and chronotype and TST (30%; p = .02). In general, the findings support the conclusion that LoL athletes presented an altered sleep pattern during their training routines.

Social Media Use and Sleep Disturbance among Adolescents: A Cross-Sectional Study

Objective: Recently, social media use has become prevalent in the daily lives of many adolescents. This study was performed to address adolescents' sleep quality and depression in relation to social media use. Method : This cross-sectional cluster-sampling study was directed on 576 high school students in 2019 in Hamadan, Iran. Three standard self-reported questionnaires were used for recording sleep patterns (Pittsburgh Sleep Questionnaire Index (PSQI)), depression (Beck), and Electronic Media Use. Data was analyzed using SPSS. P-values less than 0.05 were considered as being significant. Results: Among the adolescents 290 (50.3%) were female and the age median was 17. The average time of all Smart devices used was 7.5±4.4 hours per day. Among all students 62.3 % (359) said that they had their cell phone on in their bedroom when they sleep. In boys, the amount of social media use was significantly more than girls and poor sleep quality had a statically significant relationship with social media use (P-Value = 0.02). Additionally, there was a reverse correlation between the average use of electronic devices and sleep duration (Spearman's rho = 0.17; P-Value = 0.03), and a direct correlation between the average use in social media and depression (Spearman's rho = 0.171; P-Value < 0.001). Conclusion: In this important age group a high level of electronic devices use and its relationship with sleep quality, daily dysfunction, sleep duration and depression is worthy of issue awareness among health managers, parents and teachers for providing interventional programs, based on standard updated guidelines, in order to reduce the problem and familiarize adolescents and their parents, at home or school, with restrictions on using devices to view and participate in social media.

Quality of Sleep Among Bedtime Smartphone Users

Background

Exposure to light from viewing devices at night disturbs the circadian rhythm, especially sleep. The study aimed to assess (a) extent to which smart phones are used by medical undergraduate students during bedtime and to find their quality of sleep (b) the association of quality of sleep and cell phone variables.

Methods

A cross sectional observational study was conducted among 450 medical undergraduate students. The participants completed Pittsburgh Sleep Quality Index (PSQI) questionnaire and a validated semi structured questionnaire consisting of demographic details and cell phone variables.

Results

By dividing the subjects into three groups according to their usage (Group I <1 hour, Group II 1 to 2 hours, Group III >2 hours), Group III respondents had significant prolonged sleep latency, reduced sleep duration, sleep inefficiency and daytime sleep disturbances (P < 0.05). Lack of awareness about night shift mode, lying posture use while using phone during bedtime correlated with poor quality sleep (P < 0.05).

Conclusions

Awareness about the negative impact of evening exposure to viewing devices on sleep and health should be emphasized.

Bidirectional associations between adolescents' sleep problems and impulsive behavior over time

Objective/Background

Adolescents who experience sleep problems are less able to resist impulses. Furthermore, youths who show more impulsive behaviors are, in turn, assumed to have more sleep problems, which sets the stage for a negative cycle over time. Empirical research has shown some evidence that sleep problems affect impulse control, but the bidirectional link has previously not been tested. Therefore, the aim of this study was to test this assumption.

Methods

In this study, we used cross-lagged models to investigate the bidirectional association between sleep problems (ie, insomnia and sleep duration) and impulsive behaviors over two years in a cohort of young adolescents (n = 2767, mean age ∼13.7, 47.6% girls). We also investigated the moderating role of age and gender.

Results

The results showed that the links between sleep duration/insomnia and impulsive behavior are bidirectional. Youths who experienced sleep problems also experienced increased difficulties with impulse control, and problems regulating impulses were also linked with increases in sleep problems, and these effects were systematic over two years. Moreover, age did not moderate these associations but impulsive behaviors had a larger impact on girls’ insomnia as compared to boys.

Conclusions

By confirming the bi-directionality of this association, this study supports the importance of developing interventions to promote sleep health in adolescents but also the need to tailor such programs to adolescents’ development because adolescents might not be able to prioritize sleep if they cannot control their impulses.

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Poor sleep and impulsive behavior were bidirectionally linked over three years.

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Girls might be at higher risk of insomnia when displaying impulsive behavior.

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Sleep interventions should take into account adolescents' lack of impulse control.

How internal and external cues for bedtime affect sleep and adaptive functioning in adolescents

OBJECTIVE

To determine whether the main reason for bedtime is associated with sleep and adaptive functioning in adolescents.

METHODS

Participants were 1374 adolescents (X age = 16.8 years, SD = 0.58; 33.6% male) from Helsinki, Finland. Adolescents completed a questionnaire battery including the Munich Chronotype Questionnaire, Strengths and Difficulties Questionnaire, Beck Depression Inventory, and items drawn from the School Sleep Habits Survey, and the Pittsburgh Sleep Quality Index.

RESULTS

On school nights, adolescents whose parents set their bedtime, and those who went to bed when they were tired went to bed earlier, obtained more sleep and had earlier midpoint of sleep than adolescents who went to bed when they have finished messaging/socializing or when their television show had finished. Adolescents who went to bed when they had finished their homework had sleep that fell in between these groups. On weekends, adolescents whose parents set their bedtime went to bed earlier and had an earlier midpoint of sleep. However, there were no differences between groups in terms of sleep duration once the need to rise for school in the morning was removed. Adolescents who went to bed on school nights when they were tired or once their homework was finished had better adaptive functioning.

CONCLUSIONS

These results provide support for two very different approaches to help optimize the sleep of adolescents: either by implementing parental regulation of bedtimes across adolescence, or by encouraging adolescents to use their bodily cues to indicate when it is time for bed, rather than relying on an external cue.

Sleep spindles in adolescence: a comparison across sleep restriction and sleep extension

BACKGROUND

The tendency for adolescents to have restricted sleep has been examined in numerous studies; however, the impact of sleep restriction on adolescents' neural activity during sleep (measured by electroencephalography (EEG)) is less extensively researched, particularly regarding sleep spindles.

METHODS

In this experimental study, 34 adolescents attended a 10-day laboratory study where they received five consecutive nights of either 5 h, 7.5 h or 10 h of sleep opportunity, with one adaptation, one baseline and two recovery nights of 10 h of sleep opportunity before and after the experimental phase.

RESULTS

Both within- and between-subjects effects were observed for fast sleep spindle characteristics of density, duration and amplitude. Overall, when experiencing severe sleep restriction, fast spindles in adolescents were lower in amplitude and longer in duration. Sex differences were also seen for fast spindle amplitude.

CONCLUSIONS

This investigation adds to the knowledge in this field by investigating specific sleep spindle characteristics in the context of experimentally manipulated sleep. Sleep restriction is highly prevalent among adolescents. These findings indicate that chronic sleep restriction has an impact on brain activity related to sleep spindles.

Youth Screen Media Habits and Sleep: Sleep-Friendly Screen Behavior Recommendations for Clinicians, Educators, and Parents

With the widespread use of portable electronic devices and the normalization of screen media devices in the bedroom, insufficient sleep has become commonplace. In a recent literature review, 90% of included studies found an association between screen media use and delayed bedtime and/or decreased total sleep time. This pervasive phenomenon of pediatric sleep loss has widespread implications. There is a need for basic, translational, and clinical research examining the effects of screen media on sleep loss and health consequences in children and adolescents to educate and motivate clinicians, teachers, parents and youth themselves to foster healthy sleep habits.

High and low use of electronic media during nighttime before going to sleep: A comparative study between adolescents attending a morning or afternoon school shift

This study compared the effects of time spent on electronic media devices during nighttime before going to sleep on the sleep-wake cycle, daytime sleepiness, and chronotype in 568 Mexican students (288 girls, mean age = 14.08) attending a double school shift system (287 from morning shift and 281 from afternoon shift). Students completed anonymous self-report questionnaires. Results suggest that high exposure to an electronic media device may have an impact on their sleep-wake cycle, regardless of their school shift. Adolescents from the afternoon shift reported more time spent on devices. Those from the morning shift reported daytime sleepiness with the use of MP3 player, and from the afternoon shift with the use of computer, MP3 player, and television. Both school shifts reported an intermediate chronotype with all electronic media devices, but the afternoon shift with a tendency towards eveningness with the use of the computer, smartphone, and MP3 player.

Adolescents' future orientation and nonmedical use of prescription drugs

INTRODUCTION

How adolescents think about their future (i.e., future orientation) impacts their risk-taking behavior. The purpose of the present analysis was to explore whether future orientation (future planning, perceived risk to future goals, and positive future expectations) was associated with nonmedical use of stimulants and analgesics in a sample of high school students.

METHODS

Information on future orientation and nonmedical use of prescription drugs (NMUPD) were collected using a paper-and-pencil survey from a sample of 9th-12th grade students in a Midwestern school.

RESULTS

Higher perceived risk to future goals and positive future expectations were associated with a lower likelihood of self-reported nonmedical use of stimulants (n=250; OR=0.46, 95% CI: 0.26, 0.83; OR=0.15, 95% CI: 0.05, 0.47, respectively). Only higher perceived risk to future goals was associated with a lower likelihood of self-reported nonmedical use of analgesics (n=250; OR=0.40, 95% CI: 0.24, 0.68). In a follow-up analysis limited to students who endorsed alcohol or marijuana use, perceived risk to future goals remained associated with a lower likelihood of nonmedical use of stimulants and analgesics.

CONCLUSIONS

Results suggest that risk perception might be a salient protective factor against both nonmedical use of stimulants and analgesics. Overall, the differential impact of conceptualizations of future orientation might depend on the class of prescription drug used, demonstrating a need to consider prescription drugs individually in the development of future studies and interventions.

Bedtime mobile phone use and sleep in adults

BACKGROUND

The few studies that have investigated the relationship between mobile phone use and sleep have mainly been conducted among children and adolescents. In adults, very little is known about mobile phone usage in bed our after lights out. This cross-sectional study set out to examine the association between bedtime mobile phone use and sleep among adults.

METHODS

A sample of 844 Flemish adults (18-94 years old) participated in a survey about electronic media use and sleep habits. Self-reported sleep quality, daytime fatigue and insomnia were measured using the Pittsburgh Sleep Quality Index (PSQI), the Fatigue Assessment Scale (FAS) and the Bergen Insomnia Scale (BIS), respectively. Data were analyzed using hierarchical and multinomial regression analyses.

RESULTS

Half of the respondents owned a smartphone, and six out of ten took their mobile phone with them to the bedroom. Sending/receiving text messages and/or phone calls after lights out significantly predicted respondents' scores on the PSQI, particularly longer sleep latency, worse sleep efficiency, more sleep disturbance and more daytime dysfunction. Bedtime mobile phone use predicted respondents' later self-reported rise time, higher insomnia score and increased fatigue. Age significantly moderated the relationship between bedtime mobile phone use and fatigue, rise time, and sleep duration. An increase in bedtime mobile phone use was associated with more fatigue and later rise times among younger respondents (≤ 41.5 years old and ≤ 40.8 years old respectively); but it was related to an earlier rise time and shorter sleep duration among older respondents (≥ 60.15 years old and ≥ 66.4 years old respectively).

CONCLUSION

Findings suggest that bedtime mobile phone use is negatively related to sleep outcomes in adults, too. It warrants continued scholarly attention as the functionalities of mobile phones evolve rapidly and exponentially.