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.

Technology use as a sleep-onset aid: are adolescents using apps to distract themselves from negative thoughts?

Study Objectives: The aim of this study was to; (1) explore whether adolescents use technology as distraction from negative thoughts before sleep, (2) assess whether adolescents who perceive having a sleep problem use technology as distraction more compared to adolescents without sleep complaints, and (3) collect qualitative information about which devices and apps adolescents use as a distraction. Methods: This study used a mixed-methods cross-sectional design, where 684 adolescents (M = 15.1, SD = 1.2, 46% female) answered both quantitative and qualitative questions about their sleep (perceived sleep problem, sleep onset time (SOT), and sleep onset latency [SOL]) and technology use as distraction from negative thoughts. Results: The majority of adolescents answered "yes" or "sometimes" using technology as a distraction from negative thoughts (23.6% and 38.4%). Adolescents who answered "yes" to using technology as distraction were more likely to report having a sleep problem, longer SOL, and later SOT, compared to adolescents who answered "no". The most popular device to distract was the phone, because of its availability, and the most common apps used for distraction included YouTube, Snapchat, and music apps. Conclusions: This study shows that many adolescents use technology to distract themselves from negative thoughts, which may help them manage the sleep-onset process. Thus, distraction may be one mechanism explaining how sleep affects technology use, rather than vice versa.

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, Mage = 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.

A randomised controlled dismantling trial of sleep restriction therapies for chronic insomnia disorder in middle childhood: effects on sleep and anxiety, and possible contraindications.

Sleep restriction therapies likely drive improvement in insomnia in middle childhood via increases in homeostatic sleep pressure (e.g., evening sleepiness). Increased evening sleepiness may also dampen comorbid anxiety symptoms; and reduced wakefulness in bed may reduce worry. However, sleep restriction therapies have never been evaluated as a standalone intervention in this population. The mechanism of action needs testing, as do effects on anxiety, and cognitive performance and parasomnias (possible contraindications). This randomised controlled trial evaluated the efficacy of two "doses" of sleep restriction therapy (sleep restriction therapy, bedtime restriction therapy), compared to a control condition (time in bed regularisation). A total of 61 children (mean [SD, range] age 9.1 [2.1, 6-14] years; 54% female) with chronic insomnia disorder received two weekly 60-min treatment sessions with a psychologist. Sleep, sleepiness, anxiety, worry, cognitive performance, and parasomnias were measured pre-treatment, across treatment, and at 4-weeks post-treatment. Both the sleep and bedtime restriction groups experienced reductions in total sleep time (d = 1.38-2.27) and increases in evening sleepiness (d = 1.01-1.47) during the 2-week treatment, and improvements in insomnia (i.e., sleep onset latency; d = 1.10-1.21), relative to the control group. All groups reported improved anxiety and worry, yet there were no differences between the control and restriction groups (all p > 0.658). Time in bed increased at the 1-month follow-up, and benefits to sleep and insomnia were maintained. There were no adverse effects on cognitive functioning (all p > 0.259), nor parasomnia occurrence (all p > 0.740). These results suggest that sleep restriction therapies are brief, yet effective, standalone interventions for insomnia in middle childhood, and improvements are likely due to increased sleepiness, not sleep regularisation.

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.

Wi-Fi off, devices out: do parent-set technology rules play a role in adolescent sleep?

There is limited evidence surrounding the relationship between parent-set technology rules and adolescent sleep. This study had two aims: 1) to investigate the relationship between presence of and compliance to parent-set technology rules and adolescent sleep outcomes and daytime sleepiness; 2) to investigate if compliance, non-compliance, or the absence of rules could moderate the relationship between Fear of Missing Out (FoMO) and Bedtime Procrastination (BtP) on sleep outcomes and daytime sleepiness. A total of 711 adolescents aged 12-18 years old (46% Female, M age  = 15.1, SD = 1.2) were recruited through secondary schools in South Australia. Participants completed a survey containing self-report measures about their sleep, daytime sleepiness, FoMO, BtP, the presence/absence of technology rules in their house, and their compliance to these rules. The study design was cross sectional. Results indicated that the presence of a parent-set technology rule was associated with earlier bedtimes regardless of compliance. Earlier lights out times and increased sleep duration were observed in adolescents who always complied to their rules compared to those who did not comply or did not have parent-set technology rules. BtP and FoMO were associated with later bedtimes, later lights out times, longer sleep onset latency, shorter sleep duration, and more daytime sleepiness. However, parent-set rules did not moderate the links between BtP/FoMO and adolescent sleep. Whilst longitudinal investigations are warranted to examine the directionality of these relationships, the present study suggests that parent-set technology rules may play an important role in protecting adolescent sleep.

The roles of repetitive negative thinking and perfectionism in explaining the relationship between sleep onset difficulties and depressed mood in adolescents.

OBJECTIVE: The present study investigated the relationship between difficulty initiating sleep and depressed mood and whether it is mediated by repetitive negative thinking. A moderating role of perfectionism was also examined. METHODS: We surveyed 393 adolescents aged 14 to 20 years (M = 17.32, SD = 1.90) via an online questionnaire that assessed difficulty initiating sleep, repetitive negative thinking, perfectionism, and depressed mood. RESULTS: Results indicated that repetitive negative thinking fully mediated the relationship between difficulty initiating sleep and depressed mood. In addition, this relationship was moderated by perfectionism, specifically, the relationship between repetitive negative thinking and depressed mood was stronger among more perfectionistic adolescents. CONCLUSIONS: These findings highlight that repetitive negative thinking is significantly associated with both difficulty initiating sleep and depressed mood, supporting the conceptualization of repetitive negative thinking as a transdiagnostic process. Further, individual differences in perfectionism may amplify the relationship between repetitive negative thinking and mood. The role of repetitive negative thinking and perfectionism in explaining the link between sleep onset problems and depressed mood has important clinical implications through providing possible treatment targets.

Readiness to change and commitment as predictors of therapy compliance in adolescents with Delayed Sleep-Wake Phase Disorder.

OBJECTIVES: Recent evidence indicates that adolescents' motivation to change sleep-wake patterns is low, despite significant impact of adolescent sleep problems on many areas of daytime functioning. The aim of the present study is to evaluate components of adolescents' motivation, and subsequent changes in behaviour. METHODS: Fifty-six adolescents, aged 13-23 (M = 15.8 ± 2.3 y; 38% m) diagnosed with Delayed Sleep-Wake Phase Disorder (DSWPD) underwent three therapy sessions involving bright light therapy to phase advance sleep patterns. Adolescents were instructed to advance wake-up times by 30-min daily. Motivation ratings of desire, ability, reason, need and commitment to change sleep patterns were taken at baseline. Sleep diaries were taken at the end of treatment session 1, with sequentially earlier wake-up times in 30-min intervals indicating compliance. RESULTS: At the outset of therapy, adolescents indicated strong desire, reasons and need, yet moderate ability and commitment to advance their sleep-wake patterns. Following therapy, sleep-onset times were significantly advanced, total sleep time increased and sleep latency decreased (all p < 0.05). Therapy lasted 6-27 days (M = 13.9 ± 4.5) and clients complied for approximately half the time (between 3 and 15 days; M = 8.8 ± 2.7). Commitment was associated with ability (r = 0.66, p < 0.001) but not desire, reason or need (all p > 0.05). Adolescents' desire to change (r = 0.30, p = 0.03) and commitment (r = 0.30, p = 0.03) were positively correlated with behaviour change, but their need, ability and reasons were not. A mediation analysis showed that ability and desire were important in predicting behaviour change, by total effects through commitment (ie, indirectly and directly). CONCLUSION: Our findings suggest that the total effects of ability (ie, confidence) and desire to change are the best predictors of behavioural changes, thus clinicians should focus on these components of the readiness to change model when undertaking treatments with sleep-disordered adolescents.

Cognitive "insomnia" processes in delayed sleep-wake phase disorder: Do they exist and are they responsive to chronobiological treatment?

OBJECTIVE: To systematically investigate whether cognitive "insomnia" processes are implicated in adolescent Delayed Sleep-Wake Phase Disorder (DSWPD) and to examine whether these processes are responsive to chronobiological treatment. METHOD: Sixty-three adolescents (M = 15.8 ± 2.2 years, 63.5% f) diagnosed with DSWPD and 40 good sleeping adolescents (M = 15.9 ± 2.4 years, 75% f) completed baseline measures of sleep, daytime functioning and cognitive "insomnia" processes (i.e., repetitive negative thinking, physiological hyperarousal, distress, sleep-related attention and monitoring, sleep misperception). Sixty DSWPD adolescents (M = 15.9 ± 2.2 y, 63% f) entered a treatment trial and received 3 weeks of light therapy. Sleep, daytime functioning, and insomnia were measured again post-treatment and at 3-month follow-up. RESULTS: Adolescents with DSWPD had significantly later sleep timing (d = 0.99-1.50), longer sleep latency (d = 1.14), and shorter total sleep time (d = 0.85) on school nights, compared with the good sleeping adolescents. There was evidence of cognitive "insomnia" symptoms, with the DSWPD group reporting more repetitive negative thinking (d = 0.70-1.02), trait hyperarousal (d = 0.55), distress (d = 2.19), sleep associated monitoring (d = 0.76), and sleep onset misperception (d = 1.29). Across treatment and follow-up, adolescents with DSWPD reported advanced sleep timing (d = 0.54-0.62), reduced sleep latency (d = 0.53), increased total sleep time (d = 0.49), and improved daytime functioning (d = 0.46-1.00). Repetitive negative thinking (d = 0.64-0.96), physiological arousal (d = 0.69), distress (d = 0.87), and sleep onset misperception (d = 0.37) also showed improvement. CONCLUSIONS: Cognitive "insomnia" processes may be implicated in the development and maintenance of DSWPD in adolescents. Many of these processes are amendable to chronobiological treatment; however, residual symptoms may place adolescents at risk of poor treatment outcome or relapse. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Brief school-based interventions to assist adolescents' sleep-onset latency: Comparing mindfulness and constructive worry versus controls.

Difficulties falling asleep are common among adolescents, especially during times of stress. Adolescents may thus benefit from brief techniques (15 min) that decrease pre-sleep cognitive-emotional arousal and sleep-onset latency. The present study used a 3 (intervention: mindfulness bodyscan mp3, constructive worry, control) by 3 (time: baseline, week 1, week 2) mixed-model design on a school-based sample of adolescents (N = 232; Mage  = 15.9 ± 0.8 years, range = 14-18 years; 19% male), and a sub-sample of adolescents with prolonged sleep-onset latency (i.e. ≥30 min; N = 119; Mage  = 16.9 ± 0.9 years; 21% male). It was expected that the 15-min pre-recorded breath-based mindfulness bodyscan, and constructive worry, would decrease sleep-onset latency and pre-sleep arousal similarly over time, relative to the control condition. A significant interaction was observed among adolescents with prolonged sleep-onset latency, who completed ≥3 days for at least 1 week (p = .001), where mindfulness decreased sleep-onset latency relative to constructive worry and the control. Neither technique changed pre-sleep worry or cognitive-emotional arousal, or associated daytime functioning (both the whole sample and sub-sample). A pre-recorded mp3 breath-based mindfulness bodyscan technique is a promising means by which adolescents with prolonged sleep-onset latency can decrease sleep-onset latency. This simple tool has potential for scalable dissemination by stakeholders (e.g. teachers), unqualified to treat adolescent sleep difficulties. Future studies are needed to determine whether benefits may extend to academic performance and mental health, if performed for a longer time period with increased compliance.

Sleep Interventions Designed to Improve Athletic Performance and Recovery: A Systematic Review of Current Approaches.

BACKGROUND: Athletes experience various situations and conditions that can interfere with their sleep, which is crucial for optimal psychological and physiological recovery as well as subsequent performance. Conventional sleep screening and intervention approaches may not be efficacious for athletes given their lifestyle, the demands of training and travel associated with interstate/international competition. OBJECTIVES: The present systematic review aimed to summarize and evaluate sleep intervention studies targeting subsequent performance and recovery in competitive athletes. Based on the findings, a secondary aim was to outline a possible sleep intervention for athletes, including recommendations for content, mode of delivery and evaluation. METHODS: A systematic review was conducted based on the PRISMA guidelines in May 2016 with an update completed in September 2017. Ten studies met our inclusion criteria comprising a total of 218 participants in the age range of 18-24 years with athletes from various sports (e.g., swimming, soccer, basketball, tennis). A modified version of the quality assessment scale developed by Abernethy and Bleakley was used to evaluate the quality of the studies. RESULTS: The included studies implemented several sleep interventions, including sleep extension and napping, sleep hygiene, and post-exercise recovery strategies. Evidence suggests that sleep extension had the most beneficial effects on subsequent performance. Consistent with previous research, these results suggest that sleep plays an important role in some, but not all, aspects of athletes' performance and recovery. CONCLUSION: Future researchers should aim to conduct sleep interventions among different athlete populations, compare results, and further establish guidelines and intervention tools for athletes to address their specific sleep demands and disturbances.

The short and long of adolescent sleep: the unique impact of day length.

STUDY OBJECTIVES: Variation in day length is proposed to impact sleep, yet it is unknown whether this is above the influence of behavioural factors. Day length, sleep hygiene, and parent-set bedtime were simultaneously explored, to investigate the relative importance of each on adolescents' sleep. METHODS: An online survey was distributed in four countries at varying latitudes/longitudes (Australia, The Netherlands, Canada, Norway). RESULTS: Overall, 711 (242 male; age M = 15.7 ± 1.6, range = 12-19 yrs) adolescents contributed data. Hierarchical regression analyses showed good sleep hygiene was associated with earlier bedtime, shorter sleep latency, and longer sleep (ß = -0.34; -0.30; 0.32, p < 0.05, respectively). Shorter day length predicted later bedtime (ß = 0.11, p = 0.009), decreased sleep latency (ß = -0.21, p < 0.001), and total sleep (ß = -0.14, p = 0.001). Longer day length predicted earlier bedtimes (ß = -0.11, p = 0.004), and longer sleep (ß = 0.10, p = 0.011). CONCLUSIONS: Sleep hygiene had the most clinical relevance for improving sleep, thus should be considered when implementing adolescent sleep interventions, particularly as small negative effects of shorter day length may be minimised through sleep hygiene techniques.

Protective and risk factors associated with adolescent sleep: findings from Australia, Canada, and The Netherlands.

BACKGROUND: Sleep is vital for adolescent functioning. Those with optimal sleep duration have shown improved capacity to learn and decreased rate of motor vehicle accidents. This study explored the influence of numerous protective and risk factors on adolescents' school night sleep (bedtime, sleep latency, total sleep time) simultaneously to assess the importance of each one and compare within three countries. METHOD: Online survey data were collected from Australia, Canada, and The Netherlands. Overall, 325 (137 male), 193 (28 male), and 150 (55 male) contributed to data from Australia, Canada, and The Netherlands, respectively (age range 12-19 years). RESULTS: Regression analyses showed mixed results, when comparing protective and risk factors for sleep parameters within different countries, with combined behavioural factors contributing to small to large shared portions of variance in each regression (9-50%). One consistent finding between countries was found, with increased pre-sleep cognitive emotional sleep hygiene related to decreased sleep latency (beta = -0.25 to -0.33, p < 0.05). Technology use (mobile phone/Internet stop time) was associated with later bedtime, or less total sleep, with the strength of association varying between device and country. CONCLUSION: Results indicate that when designing interventions for adolescent sleep, multiple lifestyle factors need to be considered, whereas country of residence may play a lesser role.

Protective and risk factors for adolescent sleep: a meta-analytic review.

Teenagers need sufficient sleep to function well daily, yet consolidated evidence advising which factors protect, or harm, adolescents' sleep is lacking. Forty-one studies, published between 2003 and February, 2014, were meta-analysed. Mean weighted r values were calculated to better understand the strength of protective and risk factors for 85,561 adolescents' (age range = 12-18 y) bedtime, sleep onset latency (SOL) and total sleep time (TST). Results showed good sleep hygiene and physical activity were associated with earlier bedtimes. Video gaming, phone, computer and internet use, and evening light related to delayed bedtimes. Good sleep hygiene negatively correlated with sleep latency. Alternatively, sleep latency lengthened as a negative family environment increased. Tobacco, computer use, evening light, a negative family environment and caffeine were associated with decreased total sleep, whereas good sleep hygiene and parent-set bedtimes related to longer sleep length. Good sleep hygiene appears to be protective, whereas a negative home environment and evening light appear to be risk factors. Cautious use of technology (other than television), caffeine, tobacco and alcohol should be considered. These factors, along with pre-sleep worry, are likely to have some negative impact on sleep. Parent-set bedtimes and physical activity may be beneficial. Future research directions are discussed.

Does one hour of bright or short-wavelength filtered tablet screenlight have a meaningful effect on adolescents' pre-bedtime alertness, sleep, and daytime functioning?

Electronic media use is prevalent among adolescent populations, as is the frequency of sleeplessness. One mechanism proposed for technology affecting adolescents' sleep is the alerting effects from bright screens. Two explanations are provided. First, screens emit significant amounts of short-wavelength light (i.e. blue), which produces acute alertness and alters sleep timing. Second, later chronotypes are hypothesised to be hypersensitive to evening light. This study analysed the pre-sleep alertness (GO/NOGO task speed, accuracy; subjective sleepiness), sleep (sleep diary, polysomnography), and morning functioning of 16 healthy adolescents (M = 17.4 ± 1.9 yrs, 56% f) who used a bright tablet screen (80 lux), dim screen (1 lux) and a filtered short-wavelength screen (f.lux; 50 lux) for 1 hr before their usual bedtime in a within-subjects protocol. Chronotype was analysed as a continuous between-subjects factor; however, no significant interactions occurred. Significant effects occurred between bright and dim screens for GO/NOGO speed and accuracy. However, the magnitude of these differences was small (e.g. GO/NOGO speed = 23 ms, accuracy = 13%), suggesting minimal clinical significance. No significant effects were found for sleep onset latency, slow-rolling eye movements, or the number of SWS and REM minutes in the first two sleep cycles. Future independent studies are needed to test short (1 hr) vs longer (>2 hrs) screen usage to provide evidence for safe-to-harmful levels of screenlight exposure before adolescents' usual bedtime.