Original ArticleProtective and risk factors associated with adolescent sleep: findings from Australia, Canada, and The Netherlands
Introduction
Sleep is critical for adolescents' daily functioning [1], [2]. With longer sleep duration, adolescents have improved capabilities to learn, remember and perform well academically [3], [4], and decreased rates of motor vehicle accidents [5], whereas less than seven hours of sleep per night is associated with higher rates of delinquency and crime [6]. Poorer mental health is associated with adolescents who obtain less than seven hours sleep per night, compared to adolescents who sleep seven to nine hours per night [7]. Earlier bedtimes, shorter sleep latencies (ie, the time it takes to fall asleep) and longer sleep length are also related to lower anxiety, depressed mood, suicidal ideation, and fatigue scores [8], [9].
The transition from middle childhood to adolescence is marked, for some, by an increase in the time it takes for sleep pressure to accumulate, and a delay in the circadian rhythm [10]. Consequently, adolescents may struggle to fall asleep at a time which allows for an adequate sleep opportunity during the school week, when sleep may be constrained by school start times [10]. In addition to biological factors, extrinsic factors also play a part in delaying bedtimes, increasing sleep latency and decreasing sleep time, particularly on school days. As adolescents' sleep can be affected by a plethora of environmental factors, it is important to understand the relative influence of such factors so that appropriate interventions may minimise their impact. Whilst we review many influential factors here, it is important to note that most research studies investigate one-to-a-few factors without consideration of the majority of risk and protective factors [11]. Thus, the primary aim of the present study will be to analyse the relative importance of multiple risk and protective factors associated with adolescents' sleep, such as technology use, substance use, pre-sleep cognitive and emotional arousal, home environment, and after school sport, and to ascertain whether these factors pertain to adolescent sleep in a similar manner for different countries.
Age is a potential risk factor, with older adolescents sleeping less than younger adolescents – a phenomenon found across Australia, Europe, North America, and Asia [12], [13]. Gender is also influential on sleep, with girls sleeping more than boys, yet girls' time in bed decreasing at a larger rate than boys for each increasing year of age [13].
Concerning adolescents' “screen consumption,” multiple studies, particularly surveys, have found links between technology use and later bedtimes (eg, Gamble et al. [14]) and short sleep duration and longer sleep latency (eg, Hysing et al. [15]). However, some controlled laboratory experiments (eg, Heath et al. [16]; van der Lely et al. [17]; Weaver et al. [18]) have found little-to-no negative causal effects of pre-bed technology use on sleep. Indeed, a meta-analysis found, if anything, that technological devices are predominantly related to adolescents' later bedtimes [11].
The link between substance use and adolescent sleep remains unclear [11]. Although there seems to be no association between sleep latency and alcohol or tobacco use, links between these substances and sleep duration and bedtime are less distinct, with the potential for moderating or mediating factors, such as negative family interactions [11]. In terms of caffeine, its use is associated with less total sleep, especially when consumed in the evening [11,19]. However, links between caffeine use and sleep latency and bedtime are varied [19].
Sleep hygiene comprises multiple factors, such as pre-sleep cognitive and emotional arousal, physiological arousal, sleep environment, sleep stability, behavioural arousal, and daytime sleep (ie, napping [20]). Good sleep hygiene has typically benefitted adolescent sleep parameters (eg, Bartel et al. [11]; Storfer-Isser et al. [20]). Less pre-sleep worry in adolescents has shown to be related to decreased sleep latency [11], and less cognitive and emotional arousal prior to bed has been shown to relate to earlier bedtimes, a shorter sleep latency, and longer sleep time [20].
Adolescents' sleep has consistently shown to be enhanced when their home environment is positive [11], [21], [22], [23], [24]. A home environment encompasses many components, such as stress of demands [25], conflict [24] and disorganisation [22]. Sufficient sleep may be supported in a positive home environment, where a foundation is laid for health promoting behaviours [26], and less chaos is present [22]. Similarly, parent-set bedtimes are consistently linked with longer sleep durations, but not sleep latency [11], above the effects of age [27], thus improving adolescents' daytime wakefulness and decreasing their fatigue [28].
Activities outside of school (ie, extracurricular, work, study, sport) have been proposed to shorten sleep [29], [30]. Although a meta-analysis found a beneficial relationship between physical activity and bedtime, the association between other activities on bedtime, sleep latency or total sleep time was not found [11]. Moreover, access to indoor room lighting may also decrease adolescents' sleep, even at low lux [31].
Despite the multiple factors which have been proposed to positively or negatively affect adolescents' sleep, these variables have not been studied simultaneously or in multiple countries, to determine the strength of their influence, when accounting for the presence of each other. Considering sleep broadly impacts daily functioning [1], [2], [3], [5], [29], it is within the best interests of the scientific community to determine which extrinsic factors provide the largest contribution in assisting, and hindering, the chances of a teenager getting to bed early, falling asleep quickly, and sleeping for longer. Such knowledge can direct healthcare professionals, parents, and adolescents themselves in achieving these sleep goals. In line with this, we created an online survey to collect data on adolescents' technology use, substance use, home environment, parent-set bedtime, and physical activity, at a single time point. In doing so, all factors could be analysed together, thus assessing which variables were more highly associated with adolescent bedtime, sleep latency, and total sleep than others. The added benefit of sampling across multiple countries was to assess the generalisability of findings to various adolescent populations across the globe.
Section snippets
Participants
A total of 460 588, and 354 adolescents commenced the survey from Australia, Canada, and The Netherlands, respectively. Of those, 325 (137 male), 193 (28 male), and 150 (55 male) contributed to data from the 178-item questionnaire battery, respectively. See Table 1 for descriptive statistics and frequencies for each sample.
Materials
All variables, other than caffeine, alcohol, and tobacco use, pre-sleep cognitive-emotional arousal, and sleep reduction, asked adolescents about their school day and weekend
Behavioural protective and risk factors
Hierarchical regression analyses were performed to assess the impact of protective and risk factors on BT, SOL, and TST. Different predictive factors for each sleep variable were chosen based on the results from a previous meta-analysis on the protective and risk factors on adolescents' sleep [11], such that factors previously found to have no relationship with a specific sleep variable were not included in regression models for that sleep variable.
Discussion
Overall, although the magnitude of effect varied slightly between countries, many similarities also arose, with a large portion of variance attributed to extrinsic factors. For each country the time adolescents stopped using their mobile phone and/or the Internet, was associated with sleep, with later stop times related to later bedtimes and shorter sleep duration. In general, substance use was not related to sleep. Lower pre-sleep cognitive and emotional arousal decreased sleep latency across
Conclusion
In conclusion, behavioural factors share a small-to-large portion of variance on sleep parameters. In terms of individual protective factors, less pre-sleep cognitive emotional arousal is related to shorter sleep latencies, and is beneficially related to total sleep. Later use of a mobile and/or Internet is associated with later bedtimes and short sleep duration, with the strength of the association differing for each device between countries. Internet stop time had higher associations for
Funding sources
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Conflict of interest
None.
The ICMJE Uniform Disclosure Form for Potential Conflicts of Interest associated with this article can be viewed by clicking on the following link: http://dx.doi.org/10.1016/j.sleep.2016.07.007.
Acknowledgments
The Australian authors would like to thank the international collaborators, as well as Ben Maddock (Adelaide, Australia) for assisting with technical support for the online survey, and Michelle Short (Adelaide, Australia) for assisting with analyses.
References (55)
- et al.
Sleepless in adolescence: prospective data on sleep deprivation, health and functioning
J Adolesc
(2009) - et al.
Functional consequences of inadequate sleep in adolescents: a systematic review
Sleep Med Rev
(2014) - et al.
Sleep loss, learning capacity and academic performance
Sleep Med Rev
(2006) - et al.
The influence of sleep quality, sleep duration and sleepiness on school performance in children and adolescents: a meta-analytic review
Sleep Med Rev
(2010) - et al.
The sleep patterns and well-being of Australian adolescents
J Adolesc
(2013) Sleep in adolescents: the perfect storm
Pediatr Clin North Am
(2011)- et al.
Protective and risk factors for adolescent sleep: a meta-analytic review
Sleep Med Rev
(2015) - et al.
Recent worldwide sleep patterns and problems during adolescence: a review and meta-analysis of age, region, and sleep
Sleep Med
(2011) - et al.
The relationships between sex, age, geography and time in bed in adolescents: a meta-analysis of data from 23 countries
Sleep Med Rev
(2010) - et al.
Blue blocker glasses as a countermeasure for alerting effects of evening light-emitting diode screen exposure in male teenagers
J Adolesc Health
(2015)
Sleep patterns and psychological functioning in families in northeastern Iran; evidence for similarities between adolescent children and their parents
J Adolesc
The relation of objective sleep patterns, depressive symptoms, and sleep disturbances in adolescent children and their parents: a sleep-EEG study with 47 families
J Psychiatr Res
Bringing order out of chaos: psychometric characteristics of the confusion, hubbub, and order scale
J Appl Dev Psychol
Holiday and school-term sleep patterns of Australian adolescents
J Adolesc
Effects of caffeine on sleep and cognition
Sleep and exercise: a reciprocal issue?
Sleep Med Rev
Cross-national comparison of adolescent drinking and cannabis use in the United States, Canada, and the Netherlands
Int J Drug Policy
Socio-demographic factors as correlates of active commuting to school in Rotterdam, the Netherlands
Prev Med
Sleep-deprived young drivers and the risk for crash: the DRIVE prospective cohort study
JAMA Pediatr
Are qualitative and quantitative sleep problems associated with delinquency when controlling for psychopathic features and parental supervision?
J Sleep Res
Association between mental health status and sleep status among adolescents in Japan: a nationwide cross-sectional survey
J Clin Psychiatry
Earlier parental set bedtimes as a protective factor against depression and suicidal ideation
Sleep
Adolescent sleep patterns and night-time technology use: results of the Australian Broadcasting Corporation's big sleep survey
PLoS ONE
Sleep and use of electronic devices in adolescence: results from a large population-based study
BMJ Open
Does one hour of bright or short-wavelength filtered tablet screenlight have a meaningful effect on adolescents' pre-bedtime alertness, sleep, and daytime functioning?
Chronobiol Int
The effect of presleep video-game playing on adolescent sleep
J Clin Sleep Med
Caffeine use and sleep in adolescents: a systematic review
J Caffeine Res
Cited by (35)
Digital media use and sleep in late adolescence and young adulthood: A systematic review
2023, Sleep Medicine ReviewsCitation Excerpt :Another study investigated associations between text messaging frequency, awareness of mobile phone notifications at nighttime, compulsion to check notifications at nighttime, and sleep across a seven-day period and found that awareness of nighttime notifications was the only predictor for sleep disruptions and for women only [46]. A total of 23 studies investigated the relationship between the use of digital media and sleep duration [36–38,40–44,47–61], of which three studies have longitudinal design [36,50,61]. Most studies (n = 16) found an association between digital media use and short sleep duration [38,41–44,47–52,55,57–60].
The association of amygdala-insula functional connectivity and adolescent e-cigarette use via sleep problems and depressive symptoms
2022, Addictive BehaviorsCitation Excerpt :Given the YSR-derived sleep problems score possessed low internal consistency (Cronbach’s α = 0.47), we conducted ancillary analyses utilizing an alternative measure (i.e., Adolescent Sleep Hygiene Scale; Storfer-Isser et al., 2013) which was collected only at W2. Specifically, the ASHS’s cognitive/emotional subscale was used as prior work has demonstrated that less pre-sleep cognitive/emotional arousal among adolescents is linked with earlier bedtime routines, decreased sleep latency, and longer sleep (Bartel et al., 2016). We arrived at similar outcomes and interpretations as those described above for the YSR-derived variable (Supplemental Information Figure S2, Tables S2 and S3).
Smartphone addiction and victimization predicts sleep problems and depression among children
2022, Journal of Pediatric NursingEstimated all-day and evening whole-brain radiofrequency electromagnetic fields doses, and sleep in preadolescents
2022, Environmental ResearchCitation Excerpt :They found that higher all-day device use was related to excessive daytime sleepiness (Brunetti et al., 2016; Liu et al., 2019; Mak et al., 2014) and higher symptoms of sleep disturbances (Jiang et al., 2015; Kenney and Gortmaker, 2017; Liu et al., 2019; Söderqvist et al., 2008) in adolescents and young adults at 10–24 years old. Moreover, the use of screen devices in the evening has been related to more symptoms of sleep disturbances and less objective sleep efficiency at ages between 3 and 21 years old (Akçay and Akçay, 2018; Amra et al., 2017; Bartel et al., 2016; Bruni et al., 2015; Dube et al., 2017; Fobian et al., 2016; Johansson et al., 2016; Lemola et al., 2015; Murugesan et al., 2018; Nathanson and Beyens, 2018; Olorunmoteni et al., 2018). In our study we did not include the assessment of other factors related to the use of mobile communication devices beyond RF-EMF exposure, including light exposure or excitement based on the content watched or activity performed, that might affect sleep.
Relationships between sleep and internalizing problems in early adolescence: Results from Canadian National Longitudinal Survey of Children and Youth
2020, Journal of Psychosomatic Research