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Adolescents’ Electronic Media Use at Night, Sleep Disturbance, and Depressive Symptoms in the Smartphone Age

Authors:
  • University of Basel, Psychiatric Clinics (UPK)
  • University of Applied Science Fresenius, Germany

Abstract and Figures

Adolescence is a time of increasing vulnerability for poor mental health, including depression. Sleep disturbance is an important risk factor for the development of depression during adolescence. Excessive electronic media use at night is a risk factor for both adolescents' sleep disturbance and depression. To better understand the interplay between sleep, depressive symptoms, and electronic media use at night, this study examined changes in adolescents' electronic media use at night and sleep associated with smartphone ownership. Also examined was whether sleep disturbance mediated the relationship between electronic media use at night and depressive symptoms. 362 adolescents (12-17 year olds, M = 14.8, SD = 1.3; 44.8 % female) were included and completed questionnaires assessing sleep disturbance (short sleep duration and sleep difficulties) and depressive symptoms. Further, participants reported on their electronic media use in bed before sleep such as frequency of watching TV or movies, playing video games, talking or text messaging on the mobile phone, and spending time online. Smartphone ownership was related to more electronic media use in bed before sleep, particularly calling/sending messages and spending time online compared to adolescents with a conventional mobile phone. Smartphone ownership was also related to later bedtimes while it was unrelated to sleep disturbance and symptoms of depression. Sleep disturbance partially mediated the relationship between electronic media use in bed before sleep and symptoms of depression. Electronic media use was negatively related with sleep duration and positively with sleep difficulties, which in turn were related to depressive symptoms. Sleep difficulties were the more important mediator than sleep duration. The results of this study suggest that adolescents might benefit from education regarding sleep hygiene and the risks of electronic media use at night.
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EMPIRICAL RESEARCH
Adolescents’ Electronic Media Use at Night, Sleep Disturbance,
and Depressive Symptoms in the Smartphone Age
Sakari Lemola Nadine Perkinson-Gloor
Serge Brand Julia F. Dewald-Kaufmann
Alexander Grob
Received: 30 April 2014 / Accepted: 16 August 2014 / Published online: 10 September 2014
Springer Science+Business Media New York 2014
Abstract Adolescence is a time of increasing vulnera-
bility for poor mental health, including depression. Sleep
disturbance is an important risk factor for the development
of depression during adolescence. Excessive electronic
media use at night is a risk factor for both adolescents’
sleep disturbance and depression. To better understand the
interplay between sleep, depressive symptoms, and elec-
tronic media use at night, this study examined changes in
adolescents’ electronic media use at night and sleep asso-
ciated with smartphone ownership. Also examined was
whether sleep disturbance mediated the relationship
between electronic media use at night and depressive
symptoms. 362 adolescents (12–17 year olds, M =14.8,
SD =1.3; 44.8 % female) were included and completed
questionnaires assessing sleep disturbance (short sleep
duration and sleep difficulties) and depressive symptoms.
Further, participants reported on their electronic media use
in bed before sleep such as frequency of watching TV or
movies, playing video games, talking or text messaging on
the mobile phone, and spending time online. Smartphone
ownership was related to more electronic media use in bed
before sleep, particularly calling/sending messages and
spending time online compared to adolescents with a
conventional mobile phone. Smartphone ownership was
also related to later bedtimes while it was unrelated to sleep
disturbance and symptoms of depression. Sleep disturbance
partially mediated the relationship between electronic
media use in bed before sleep and symptoms of depression.
Electronic media use was negatively related with sleep
duration and positively with sleep difficulties, which in turn
were related to depressive symptoms. Sleep difficulties
were the more important mediator than sleep duration. The
results of this study suggest that adolescents might benefit
from education regarding sleep hygiene and the risks of
electronic media use at night.
Keywords Electronic media use in bed before sleep
Smartphone Sleep Sleep duration Sleep difficulties
Depressive symptoms Sleep hygiene Adolescence
Introduction
The aim of this study is to examine changes in electronic
media use in bed and adolescents’ sleep associated with
smartphone ownership. Moreover, we test whether elec-
tronic media use in bed before sleep is associated with
S. Lemola (&)N. Perkinson-Gloor A. Grob
Department of Psychology, University of Basel, Missionsstrasse
62, 4055 Basel, Switzerland
e-mail: sakari.lemola@unibas.ch
N. Perkinson-Gloor
e-mail: nadine.perkinson@unibas.ch
A. Grob
e-mail: alexander.grob@unibas.ch
S. Brand
Center for Affective, Stress and Sleep Disorders, Psychiatric
Clinics of the University of Basel, Wilhelm Klein-Strasse 27,
4012 Basel, Switzerland
e-mail: serge.brand@upkbs.ch
S. Brand
Division of Sport Science, Department of Sport, Exercise and
Health, Faculty of Medicine, University of Basel, Basel,
Switzerland
J. F. Dewald-Kaufmann
Department of Paediatric Endocrinology, Dr. von Hauner
Children’s Hospital, Ludwig Maximilian University,
Geschwister-Scholl-Platz 1, 80539 Munich, Germany
e-mail: Julia.Kaufmann@med.uni-muenchen.de
123
J Youth Adolescence (2015) 44:405–418
DOI 10.1007/s10964-014-0176-x
depressive symptoms and whether this relationship is
mediated by sleep disturbance including short sleep dura-
tion and sleep difficulties. To do so, we follow a theoretical
model proposed by Cain and Gradisar (2010) suggesting
that increased electronic media use—particularly in the
bedroom before sleep—is related to sleep disturbance.
Moreover this model suggests that sleep disturbance in turn
is associated with impaired daytime functioning. Despite
important work in this area, research has not kept pace with
changes in technology and the broad use of such electronic
devices as smartphones. Therefore, to the authors’ best
knowledge this study is the first that addresses changes in
adolescents’ electronic media use at night, sleep, and
mental health associated with the use of smartphones.
Electronic Media Use and Adolescents’ Sleep
Adolescence is a time of changing sleep patterns with a
pronounced shift of bedtimes to later in the evening. For
many adolescent students, this results in sleep deprivation
during the school week and sleeping in on weekends
(Crowley et al. 2007; National Sleep Foundation 2006;
Perkinson-Gloor et al. 2013; Lemola et al. 2012). The
delay of bedtime during adolescence is considered to be
due to both biological maturation and environmental fac-
tors (Crowley et al. 2007). Among the environmental fac-
tors that may delay bedtimes, electronic media use in the
evening has been suggested to play an outstanding role
(Cain and Gradisar 2010).
During the last several decades, there has been a par-
ticularly pronounced increase in the use of electronic media
during leisure time among children and adolescents.
Moreover, there is clear increase in media use from
childhood to adolescence (Rideout et al. 2010) and many
adolescents consider the various kinds of electronic media
use as their favorite leisure time activity (Willemse et al.
2012). Nowadays, more than half of adolescents from
technologically advanced countries report to consume
electronic media on most evenings during the last hour
before they go to bed (National Sleep Foundation 2011)
and for more than two thirds the last activity of the day was
related to electronic media use at least 3 times per week
(Kubiszewski et al. 2013).
There is a growing body of evidence that electronic
media use during adolescence is related to later bedtimes,
shorter sleep duration, and sleep disturbance (Cain and
Gradisar 2010, for a systematic review). The greatest
attention had been addressed towards the relationship
between TV-consumption and sleep; of 20 studies exam-
ining this link, which were identified by Cain and Gradisar
(2010), 17 have found a significant relationship between
the amount of watching TV and poor sleep. With regard to
the use of computers, internet, or video game playing, 15
studies have been identified which consistently reported
later bed times, shorter sleep duration, and longer sleep
latency to be related to greater use of these electronic
media. Two out of three studies also reported more daytime
sleepiness/tiredness (Van den Bulck 2004; Eggermont and
Van den Bulck 2006), while one study could not confirm
this relationship (Li et al. 2007). With regard to mobile
phone use and sleep, seven studies had been conducted till
2010 (Cain and Gradisar 2010). Two studies found shorter
sleep duration being related to greater mobile phone use
(Harada et al. 2002; Punama
¨ki et al. 2007), while one study
could not confirm this link (Yen et al. 2008); three studies
found that greater mobile phone use was associated with
increased daytime sleepiness/tiredness (Van den Bulck
2003,2007;So
¨derqvist et al. 2008), while no relationship
was found with sleep latency (Gaina et al. 2005) or sleep
difficulties (So
¨derqvist et al. 2008; Yen et al. 2008).
More recent studies regarding adolescents’ bedtime
mobile phone use include two surveys conducted in Japan
examining the relation of mobile phone communication
after lights out with sleep (Munezawa et al. 2011; Oshima
et al. 2012). Munezawa et al. (2011) found both texting and
calling after lights were turned off to be related with more
sleep disturbance (including short sleep duration, sub-
jective poor sleep quality, excessive daytime sleepiness,
and insomnia symptoms) controlling several confounders
(including gender, grade-level, alcohol-drinking, smoking,
eating breakfast, extracurricular activities, and mental
health). Oshima et al. (2012) reported mobile phone use
after lights were turned off to be negatively related to sleep
duration only in younger adolescents ages 13–15 years,
while no such relation was found in 16–18 year olds.
Taken together, there is a large body of evidence that
electronic media use is related to disturbed sleep. However,
the published studies to date have all been conducted
before the latest electronic revolution affecting adoles-
cents’ lives has taken place.
The Possible Role of Smartphones for Adolescents’
Electronic Media Use
The availability of smartphones may change adolescents’
patterns of electronic media consumption profoundly. First,
when having access to wireless Internet, smartphones allow
communication with peers without charge, by using for
instance Internet based messenger applications such as
WhatsApp. Particularly the cost of calling and sending text
messages was a limiting factor of adolescents’ mobile
phone communication before smartphones became easily
available. During that time adolescents applied various
tricks to avoid charges related to calling or texting (Prezza
et al. 2004). For instance, ‘‘ringing’’ was a procedure
involving one adolescent dialing a friend but interrupting
406 J Youth Adolescence (2015) 44:405–418
123
the call before the other person could take the phone.
Hence,—and without charge—the other mobile phone
displayed who was calling, whereby telling that person ‘‘I
was thinking of you.’’ Another more elaborate trick was to
answer ‘‘yes’’ or ‘‘no’’ questions by the number of phone
ring signals (e.g., one signal meant ‘‘yes’’ and two signals
meant ‘‘no’’). The availability of smartphones and wireless
Internet access, however, make such practices obsolete.
Beyond replying to simple questions, smartphones and the
access to wireless Internet offer several new opportunities
to communicate free of charge such as, for instance,
sharing pictures and short movies with a predefined group
of friends. Beside the decrease of costs related to com-
munication, smartphones are also more convenient to use
while lying in bed to surf the Internet or to watch videos
from Youtube as smartphones have the advantage of being
lighter and handier than for instance notebook computers.
Their superior handiness compared to other electronic
media thus make smartphones particularly practical to use
when already lying in bed. While being convenient, these
points also bear the risk that adolescents increase their use
of the mobile phone in general and when lying in the bed.
The rate of smartphone ownership varies by Nation and
age group, and is currently rapidly increasing. In the United
States, for instance, the percentage of the population who
owned a smartphone increased from 35 % in 2011 to 56 %
in 2013 (Smith 2013). In Switzerland, the number of the
12–19 year olds who owned a smartphone increased from
47 % in 2010 to 79 % in 2012 (Willemse et al. 2012); the
same representative survey study revealed that the number
of adolescents using the mobile phone to surf the Internet
increased from 16 % in 2010 to 66 % in 2012. Similar rates
have been reported for Germany, where 25 % of the
12–19 year olds owned a smartphone in 2011 while this
number has increased to 72 % in 2013 (Medienpa
¨dagogi-
scher Forschungsverbund Su
¨dwest 2013); 60 % of the
adolescents in Germany also reported to subscribe to a flat-
rate data plan for their mobile phones. However, scientific
knowledge whether smartphone ownership affects adoles-
cents’ electronic media use in the bed before sleep, and
whether it increases the risk of poor sleep and daytime
functioning, is still missing.
Possible Mechanisms Linking Electronic Media Use
with Poor Sleep
Cain and Gradisar (2010) propose several mechanisms
through which electronic media use in the evening may
reduce sleep duration and interfere with sleep quality. As a
first mechanism, electronic media use may displace sleep.
As an unstructured leisure activity with no fixed starting
and stopping point, it involves an increased risk of
expanding and taking up more time, and thus displacing
other possible activities and sleep (Kubey 1986; Van den
Bulck 2004).
As a second mechanism, it has been proposed that
electronic media use before sleep may increase mental,
emotional, or physiological arousal. This possible mecha-
nism has been examined by six experimental studies that
all examined the effects of playing video games. In a first
study, Higuchi et al. (2005) studied young male adults who
played an exciting video game late at night or performed
simple tasks with low mental load in front of a screen as a
control condition. Playing video games slightly increased
sleep latency and heart rate, and it decreased subjective
sleepiness compared to a control condition. In a similar
vein, Dworak et al. (2007) found that video game playing
resulted in longer sleep latency and poorer memory per-
formance on the following day in adolescent boys. More-
over, an Australian study found that playing video games in
the evening as compared to more passive watching of a
movie decreased male adolescents’ sleepiness and
increased sleep latency (although only to a slight degree;
Weaver et al. 2010). However, physiological arousal was
not affected in this study. A second Australian study also
found moderately reduced sleep quality but no effect on
heart rate among adolescents with previous video game
experience (King et al. 2013). Finally, in two Swedish
studies, violent video game playing was compared with
non-violent video game playing. The first study, which
included male adolescents with rather low experience with
violent video games, revealed that violent video game
playing induced stronger autonomic responses than non-
violent gaming (while not affecting subjective sleep quality
or cortisol secretion; Ivarsson et al. 2009a,b). The second
experiment found differential effects of experimental
exposure to violent versus non-violent video games
according to the previous gaming experience such that
adolescents with low gaming experience showed more
negative effects related to heart rate variability, sleep
quality, and mood after the violent game pointing to the
importance of the previous experience with video games
(Ivarsson et al. 2013). Taken together, experimental studies
are in line with a causal role of playing video games for
poor sleep. However, physiological arousal (including
heart rate variability) and neuroendocrine responses
(including cortisol secretion) were not confirmed as the
mediators of this effect—at least not in experienced video
game players. It is possible that mental and/or emotional
arousal which was not assessed in these studies mediated
the effects on sleep. With regard to other types of elec-
tronic media use, electromagnetic radiation emitted by
mobile phones has been reported to delay melatonin pro-
duction and could therefore be related to later sleep onset
(Wood et al. 2006). Moreover, communication via mobile
phone when lying in the bed before sleep has also been
J Youth Adolescence (2015) 44:405–418 407
123
suggested to increase emotional and/or cognitive arousal
and might therefore affect sleep (Munezawa et al. 2011).
However, this latter mechanism has not yet been tested
experimentally.
As a third mechanism, Cain and Gradisar (2010) sug-
gested that light emission of the screens of electronic media
devices might affect sleep. In line with this notion, there is
evidence from an experimental study with young adults
that particularly light emission of modern flat screens with
LED back light technology may interfere with sleep. LED
back light screens emit an increased amount of light in the
short wave length spectrum of around 460 nm which
suppresses melatonin secretion in the evening and reduces
subjective and objective signs of sleepiness (Cajochen et al.
2011). However, one recent study comparing the impact of
the three conditions (a) 1 hour of bright tablet screen
exposure, (b) 1 h of short-wavelength filtered tablet screen
exposure, and (c) 1 h of dim tablet screen exposure on
adolescents’ pre-bedtime alertness, sleep, and daytime
functioning found only minimal differences (Heath et al.
2014). No evidence is yet available indicating whether
more than 1 h of exposure to a tablet screen might have a
stronger effect on adolescents’ sleep.
A fourth mechanism by which particularly mobile
phones in the bedroom may disturb sleep is that incoming
messages may wake adolescents up at night. Recently, a
representative survey of the US population revealed that
18 % of adolescents aged between 13 and 18 years are
woken up by text messages after sleep onset at least few
times per week compared to only 10 % of individuals aged
between 30 and 45 years (National Sleep Foundation
2011). Similar rates of being woken up by incoming text
messages and calls after lights out have been reported by
adolescents in Belgium (Van den Bulck 2007). In this latter
study, the odds of being very tired during the day strongly
increased with the frequency of mobile phone use after
lights out. Moreover, also a nation-wide study with Japa-
nese adolescents showed that the use of mobile phones
after lights out was associated with poor sleep and exces-
sive daytime sleepiness (Munezawa et al. 2011).
The Role of Sleep for Depression in Adolescence
While severe cases of depression are comparably rare
before puberty, the prevalence rate drastically increases
until the end of adolescence (Hankin et al. 1998; Kessler
et al. 2001). Around 20 % of the population has experi-
enced a depressive episode when turning 18 years old,
which also involves a highly increased risk for further
depressive episodes in adulthood (Lewinsohn et al. 1993).
It is therefore of major interest to understand why this rate
is increasing during adolescence, to identify possible risk
and protective factors, and to develop efficacious treatment
and prevention approaches.
The comorbidity of depression with sleep problems is
very high with 73 % of adolescents with depressive dis-
order also suffering from a sleep disorder (Lui et al. 2007).
Moreover, most studies examining correlations between
sleep disturbance and depressive symptoms in adolescents
found significant correlations (e.g., Short et al. 2013, Le-
mola et al. 2011). Often researchers assumed a bi-direc-
tional relationship between the sleep disturbance and
mental health (e.g., Cortese et al. 2013). However, in a
recent meta-analysis summarizing longitudinal and treat-
ment studies that examined the prospective role of sleep
disturbance in the development of depression and vice
versa during adolescence, Lovato and Gradisar (2014)
concluded that sleep disturbance rather acts as a precursor
to the development of depression while little support was
found for a predictive role of depressive symptoms in the
development of sleep disturbance. These findings point to
the importance of sleep disturbance in the etiology of
depression during adolescence.
In a related vein, experimental studies have tested the
causal role of sleep restriction for vulnerability factors that
are known to be related to depression. A recent experi-
mental study showed that restricted sleep to 6.5 h for
5 days—a regimen mimicking common sleep curtailment
during a school week—resulted in increased self-reports of
tension, anxiety, and fatigue as well as greater parent rated
oppositionality/irritability and poorer emotional regulation
in adolescents aged 12–17 years (Baum et al. 2014).
Likewise, curtailing sleep to 6.5 h on a first night and to
\2 h on a second night showed similar effects involving
increased negative affect and decreased positive affect in
adolescents aged 10–16 years (Dagys et al. 2012; McG-
linchey et al. 2011; Talbot et al. 2010). In a computerized
analysis of emotional markers in speech, adolescents
appeared to be even more vulnerable to the effects of sleep
deprivation compared to adults (McGlinchey et al. 2011).
The mechanism through which short sleep has an impact
on emotional and behavioral functioning in adolescents
may involve an increase in negative mood and a decrease
in the ability to regulate emotions (Baum et al. 2014). In
adulthood, a neuroimaging study showed increased amyg-
dala activity in sleep deprived individuals as well as
decreased connectivity between the prefrontal cortex and
the amygdala (Yoo et al. 2007). Amygdala activity is
known to reflect processes related to negative affectivity
including anxiety. The increase in amygdala activity and
decrease in prefrontal control of the amygdala related to
sleep deprivation may indicate proneness to negative affect
and lower ability to regulate negative feelings (Yoo et al.
2007).
408 J Youth Adolescence (2015) 44:405–418
123
The Role of Sleep Disturbance for the Relationship
Between Electronic Media Use and Depression
While it is generally accepted that electronic media use
during adolescence has a predictive role in the devel-
opment of depression (Primack et al. 2009) and that
electronic media use is related to sleep disturbance (Cain
and Gradisar 2010), studies that explicitly examine the
mediating role of sleep disturbance for the relationship
between electronic media use and depressive symptoms
are rare. Most studies analyzing relationships between
electronic media use, sleep disturbance, and depressive
symptoms simultaneously in adolescents (Munezawa
et al. 2011; Oshima et al. 2012) or in young adults
(Brunborg et al. 2011) defined one of these variables as a
covariate rather than a mediator. One study treated
depressive symptoms as a covariate when studying the
relationship between mobile phone use after lights out
and sleep disturbance finding that the raw association
was attenuated when the covariates (including depressive
symptoms) were controlled (Munezawa et al. 2011). A
second study treated sleep duration as a covariate when
studying the relationship between mobile phone use after
lights out and poor mental health, suicidal ideation, and
self-injury (Oshima et al. 2012). Similarly as in the
former study, the raw associations were attenuated when
controlling for covariates. Furthermore, also Brunborg
et al. (2011) controlled for depressive symptoms when
assessing the relationship between using the mobile
phone in the bedroom at night and sleep disturbance in
young adults. A formal test of the mediation hypothesis
that sleep disturbance may mediate the relationship
between electronic media use and depressive symptoms
was conducted by two studies (Adams and Kisler 2013;
Lemola et al. 2011). Results from Adams and Kisler
(2013) support the mediation hypothesis in a sample of
college students. In contrast, Lemola et al. (2011) could
not find mediation of the relationship between habitual
video game playing at night and depressive symptoms by
sleep disturbance in a sample of adolescents and young
adults who played the online multiplayer role play game
World of Warcraft.
Taken together, there is a wealth of evidence that
electronic media use before bedtime, sleep disturbance, and
depressive symptoms in adolescence are interrelated.
However, studies assessing how the availability of smart-
phones—including the opportunity to cheaply and conve-
niently communicate with peers when already lying in the
bed—changes the use of electronic media in adolescents’
bedrooms are missing. Moreover, there is only little
research studying the hypothesis that disturbed sleep acts
as a mediator of the relationship between electronic media
use and depressive symptoms in adolescence.
The Current Study
In the current study, we examine whether adolescents who
own a smartphone differ from their peers who do not own a
smartphone regarding their electronic media use in bed
before sleep. Moreover, we examine whether electronic
media use in the bed is related to sleep disturbance (including
short sleep duration and sleep difficulties), and whether short
sleep duration and sleep difficulties mediate the relationship
between electronic media use in bed and depressive symp-
toms. In particular we test the following hypotheses.
Possession of a smartphone is related to more electronic
media use in general and particularly in bed before sleep
(Hypothesis 1). We expect that adolescents with a smart-
phone more often use electronic media as smartphones allow
to communicate with peers without charge (e.g., by using
smartphone applications such as WhatsApp or the Facebook
application for smartphones). Moreover, due to their small
size smartphones are more convenient to use than for
instance notebook computers when lying in the bed. Due to
these reasons, we assume that the advent of smartphones in
adolescents’ bedrooms profoundly change electronic media
use in the bed and thus might also affect sleep.
Electronic media use in bed before sleep is related to
higher levels of depressive symptoms (Hypothesis 2). In
line with previous research (Brunborg et al. 2011; Lemola
et al. 2011; Oshima et al. 2012) we expect that higher
levels of depressive symptoms in adolescents who more
often use electronic media in bed before sleep.
Electronic media use in bed before sleep is related to
shorter sleep on weekday nights and/or sleep difficulties on
weekday nights (Hypothesis 3). We expect electronic media
use in bed before sleep to be related to shorter sleep and/or
sleep difficulties in line with previous research (Cain and
Gradisar 2010 for a review; Brunborg et al. 2011; Dworak
et al. 2007; Eggermont and Van den Bulck 2006; Fossum
et al. 2014; Higuchi et al. 2005; King et al. 2013; Munezawa
et al. 2011; Oshima et al. 2012; Van den Bulck 2007).
Several factors may lead to less sleep in adolescents who use
electronic media in bed before sleep, including that it may
replace the time for sleep and it may increase arousal due to
the media contents or due to alerting features of the screens
including brightness and the specific wave-length of LED-
backlight screens (Cain and Gradisar 2010).
The relationship between electronic media use in bed
before sleep and depressive symptoms is partly mediated
by sleep duration and/or sleep difficulties (Hypothesis 4).
We expect that the relationship between electronic media
use in bed and depressive symptoms is at least partly due to
sleep disturbance. This expectation is based on the theo-
retical model proposed by Cain and Gradisar (2010) sug-
gesting that electronic media use has an impact on daytime
functioning via sleep disturbance. Moreover, there is now a
J Youth Adolescence (2015) 44:405–418 409
123
large body of evidence indicating that sleep disturbance in
adolescence predicts the development of depressive
symptoms (Lovato and Gradisar 2014).
In further analyses, we explore whether the relations
between electronic media use in bed before sleep, sleep
duration, sleep difficulties, and depressive symptoms are
moderated by age (Additional Research Question 1).
Moreover, we explore (Additional Research Question 2)
which type of electronic media use is most strongly related
with sleep duration, sleep difficulties, and depressive
symptoms. We do not propose hypotheses regarding which
media device would be most strongly related to sleep dis-
turbance and depressive symptoms.
Method
Procedure
Participants were recruited from public high schools in
northwestern Switzerland. Principals of all 42 high schools
within the area received a letter with information on the
study aims and procedures. Approximately 1 week later,
the principals of the 42 high schools were contacted by
phone to ask if they were interested in participation. Seven
high school principals agreed that school classes of their
school participated in the study. In total, the seven partic-
ipating schools consisted of 82 school classes and teachers
of 32 of those agreed to participate. The 32 school classes
consisted of 646 students, of which 390 agreed to partici-
pate and if underage, had consent from their parents.
Trained study personnel visited the school classes and
administered questionnaires on sleep, media consumption
before going to sleep, and psychological health. Complet-
ing the questionnaire took approximately 25 min. After
completing the questionnaires students either received an
interventional lesson on sleep hygiene or general infor-
mation on sleep related topics such as dreaming. One
month later, students were visited a second time and
completed the same questionnaires. The present paper
reports data collected at the first school visit and from all
participating students. Data for the present study was
gathered between October 2012 and February 2013. Stu-
dents and parents of underage students gave written
informed consent to participate in the study. The study was
approved by the Ethics Committee of Basel and performed
in accordance with the ethical standards laid down in the
Declaration of Helsinki.
Participants
In total, 390 adolescents aged 12–20 years completed the
questionnaires at the first data assessment time of whom
362 (92.8 %) were underage, i.e. between 12 and 17 years
old. Young adults (ages 18–20; n =28; 7.2 %) were
excluded from the analyses of the current study in order to
address the research questions within underage adoles-
cents. Among the remaining 362 students, 200 (55.2 %)
were male and 162 (44.8 %) were female. A majority
indicated to speak only German/Swiss German at home
(55.8 %), 21.3 % indicated to speak German/Swiss Ger-
man and another language at home, and 22.9 % indicated
to speak only another language at home.
Measures
Sleep Duration
To assess sleep duration, students were asked to indicate
the time they turn off the lights to go to sleep on regular
school nights (Monday to Thursday night) and the time
they get up in the morning of regular school days (Monday
to Friday morning). Sleep duration was defined as the time
between the indicated ‘‘lights off’’-time and rise time.
Sleep Difficulties
Sleep difficulties were assessed with five items from the
German translation of the Insomnia Severity Index (ISI;
Bastien et al. 2001; translated by the 3rd author of the
present article). Reliability and validity of the German
version were established in a previous study (Gerber et al.
2010). The items were answered on a 5-point Likert scale
(0 =not at all/very satisfied and 4 =very much/very dis-
satisfied) and assessed difficulties falling asleep and
maintaining sleep, satisfaction with the current sleep pat-
tern and feeling rested after awakening (e.g. ‘‘In the last
2 weeks, did you have difficulties falling asleep?’’). A
higher mean score represents more sleep difficulties
(Cronbach’s alpha =.71).
Electronic Media Use in Bed Before Sleep
To assess electronic media use in bed before sleep stu-
dents were asked about their behavior regarding media
consumption in bed before going to sleep on a regular
school night. Media consumption in bed was assessed
with four items assessing how often participants watch
TV or movies, play video games, talk on the phone or
text, and spend time online on Facebook or in chat rooms
or surf the Internet before going to sleep and while
already in bed. Answer categories ranged from 1 (never)
to 5 (most of the time to always; at 57 days per week). A
higher sum score represents more electronic media con-
sumption in bed before going to sleep (Cronbach’s
alpha =.70).
410 J Youth Adolescence (2015) 44:405–418
123
Daily Duration of Electronic Media Use in General
To assess the duration of electronic media use in general
the students indicated on four items how many minutes and
hours they (1) watch TV, (2) play video games, (3) spend
time online on Facebook, (4) spend time on the Internet in
total on an ordinary school day. Moreover, they indicated
how many text messages they send per day (including short
messages, WhatsApp messages etc.).
Depressive Symptoms
Depressive symptoms were assessed with six items taken
from the short version of the ‘‘Allgemeine Depressionss-
kala’’ (ADS-K; Hautzinger and Bailer 1993), the German
version of the Center of Epidemiological Studies Depres-
sion Scale (CES-D; Radloff 1977), including ‘‘feeling
depressed’’, ‘‘feeling everything one does is an effort’’,
‘feeling fearful’’, ‘‘feeling sad’’, ‘‘that one could not get
going’’, and ‘‘that one enjoyed life’’ (reverse coded). Thus,
no item assessing sleep disturbance was included. The
items were answered on a 4-point Likert scale ranging from
0(occurred never or rarely)to3(occurred most of the time
or always) reflecting how often the symptoms were expe-
rienced during the preceding week. Higher scale mean
scores reflect higher levels of depressive symptoms
(Cronbach’s alpha =.73).
Statistical Analysis
First, mean value comparisons and frequency comparisons
of the study variables between smartphone owners and
owners of a conventional mobile phone were conducted by
analysis of variance (ANOVA) and v
2
statistics (test of
Hypothesis 1). Second, Pearson correlations were calcu-
lated. The Pearson correlations represent preliminary
analyses to present the zero-order relations between the
study variables. Third, regression analyses were conducted
as suggested by Baron and Kenny (1986) to test mediation.
This included the following steps: (a) Prediction of the
dependent variable (depressive symptoms) by the inde-
pendent variable (electronic media use in bed; test of
Hypothesis 2). (b) Prediction of the mediators (sleep
duration and sleep difficulties) by the independent variable
(electronic media use in bed; test of Hypothesis 3).
(c) Prediction of the dependent variable (depressive
symptoms) by both the independent variable (electronic
media use in bed) and the mediators (sleep duration and
sleep difficulties; test of Hypothesis 4; for partial mediation
it is required that the direct relation between the indepen-
dent variable and the dependent variable is reduced by
inclusion of the mediator to the model). In order to also
formally test the significance of the indirect effects we then
additionally employed the SPSS procedure Indirect by
Preacher and Hayes (2008), assessing the models with both
mediators simultaneously via bootstrapping. All regression
models controlled adolescents’ age and gender. Fourth, we
tested whether any of the regression models of the previous
steps were moderated by adolescents’ age (test of Addi-
tional Research Question 1) following the procedure sug-
gested by Aiken and West (1991). Finally, further
regression models specified simultaneous entry of the four
different types of electronic media consumption in bed
before sleep and the variable whether the mobile phone
was switched off during the night according to the ‘‘step-
wise’ algorithm (probability-of-F-to-enter: 0.05; prob-
ability-of-F-to-remove: 0.10; test of Additional Research
Question 2). Again all regression models controlled ado-
lescents’ age and gender.
Results
Table 1shows descriptive statistics of the study variables
and the comparisons of the electronic media use between
the group owning a smartphone (n =299; 82.6 % of the
sample) and the group owning a conventional mobile
phone (n =51; 14.4 % of the sample) (test of Hypothesis
1). Only a minority of 10 adolescents (2.8 %) indicated not
to own a mobile phone and were therefore excluded from
this comparison. Adolescents owning a smartphone were
somewhat older and more often spoke a different language
than German at their homes than their peers who had a
conventional mobile phone. With regard to their electronic
media consumption in general, they spent more time on the
Internet and on Facebook, and they sent several times more
text messages per day, while they did not spend more time
watching TV or playing video games. Regarding their
electronic media use in bed before sleep, they more often
watched videos, communicated by phone or text message,
more often spent time online, and more often had their
phones switched on during the night, while they did not
significantly differ regarding video game playing in the
bed. Furthermore, smartphone owners switched off the
lights later at night than their peers with conventional
mobile phones, while they did not differ significantly
regarding sleep duration, sleep difficulties, and symptoms
of depression.
Table 2presents Pearson correlations for participants’
age, gender, sleep, depressive symptoms, and variables of
electronic media use at night. Age was negatively related to
sleep duration and it was positively related to depressive
symptoms and all types of electronic media use at night
except for playing video games. Girls had higher levels of
depressive symptoms and reported more calling and/or text
messaging in bed before sleep, while they also reported less
J Youth Adolescence (2015) 44:405–418 411
123
Table 1 Description of the study variables and comparisons between adolescents with a smartphone and with a conventional mobile phone
Total sample
(N=362)
Adolescents with a
smartphone (n=299)
Adolescents with a
conventional mobile phone
(n=51)
Statistics
a
n/mean (%/SD) n/mean (%/SD) n/mean (%/SD)
Age (years), mean (SD) 14.82 (1.26) 14.9 (1.2) 14.3 (1.3) F=12.57, p\0.001
Gender (female) n(%) 162 (44.8) 136 (45.5) 23 (44.2) v
2
=0.03, p=0.87
Language spoken at home (German only) n(%) 202 (55.8) 155 (51.8) 37 (71.2) v
2
=6.67, p=0.01
Sleep on weekdays
Time of switching lights off, mean (SD) 10:26 (0:55) 10:30 (0:55) 10:10 (0:48) F=5.75, p=0.02
Time of getting up, mean (SD) 06:30 (0:23) 06:31 (0:24) 06:25 (0:20) F=3.32, p=0.07
Sleep duration (hours), mean (SD) 8:04 (0:54) 8:01 (0:55) 8:14 (0:52) F=2.54, p=0.11
Sleep difficulties, mean (SD) 2.20 (0.68) 2.21 (0.68) 2.13 (0.61) F=0.73, p=0.39
Depressive symptoms, mean (SD) 1.58 (0.48) 1.59 (0.48) 1.53 (0.44) F=0.79, p=0.37
Amount of media use on weekdays, hours, mean (SD)
Watching TV 1:41 (1:22) 1:44 (1:23) 1:32 (1:22) F=0.83, p=0.36
Playing video games 0:53 (1:00) 0:54 (1:01) 0:46 (0:46) F=0.79, p=0.37
To be on the Internet (total) 1:52 (1:39) 2:00 (1:42) 1:08 (0:59) F=12.36, p\0.001
To be on Facebook 0:48 (1:07) 0:54 (1:11) 0:17 (0:28) F=13.54, p\0.001
Number of text messages sent per day, mean (SD) 71.11 (89.53) 84.63 (92.89) 7.06 (10.49) F=36.10, p\0.001
During the night mobile phone is
b
n(%)
Switched on and at the bed 204 (57.6) 181 (60.5) 21 (41.2) v
2
=24.28, p\0.001
Switched on but not at the bed 75 (21.2) 68 (22.7) 6 (11.8)
Switched off or not in bedroom 75 (21.2) 50 (16.7) 24 (47.1)
Media use in bed before sleep, mean (SD) 9.49 (4.18) 10.10 (4.18) 6.76 (2.76) F =30.20, p\0.001
Media use in bed before sleep n(%)
Watching TV/videos
Never 183 (50.8) 144 (48.3) 34 (66.7) U=6,004.5, p=0.01
Once a week or less 61 (16.9) 49 (16.4) 7 (13.7)
Twice a week 43 (11.9) 37 (12.4) 5 (9.8)
3–4 times a week 29 (8.1) 27 (9.1) 2 (3.9)
5–7 times a week 44 (12.2) 41 (13.8) 3 (5.9)
Playing video games
Never 245 (68.1) 200 (67.1) 36 (70.6) U=7,225.5, p=0.50
Once a week or less 47 (13.1) 40 (13.4) 6 (11.8)
Twice a week 36 (10.0) 27 (9.1) 8 (15.7)
3–4 times a week 22 (6.1) 21 (7.0) 1 (2.0)
5–7 times a week 10 (2.8) 10 (3.4) 0 (0.0)
Communication by phone or text message
Never 92 (25.6) 57 (19.1) 26 (51.0) U=3,743.0, p\0.001
Once a week or less 48 (13.3) 39 (13.1) 9 (17.6)
Twice a week 42 (11.7) 31 (10.4) 10 (19.6)
3–4 times a week 64 (17.8) 60 (20.1) 3 (5.9)
5–7 times a week 114 (31.7) 111 (37.2) 3 (5.9)
To be online (on Facebook, Chatroom, etc.)
Never 146 (40.6) 100 (33.6) 37 (72.5) U=4,359.0 p\0.001
Once a week or less 52 (14.4) 49 (16.4) 3 (5.9)
Twice a week 41 (11.4) 34 (11.4) 5 (9.8)
3–4 times a week 55 (15.3) 50 (16.8) 5 (9.8)
5–7 times a week 66 (18.3) 65 (21.8) 1 (2.0)
a
Statistics refer to the comparison between adolescents who own a smartphone versus adolescents who own a conventional mobile phone
b
The question whether the mobile phone was switched on during the night was also replied by three of the individuals who indicated not to own a mobile phone
412 J Youth Adolescence (2015) 44:405–418
123
watching of TV and videos and less often played video
games in bed compared to boys. Sleep duration on week-
days was negatively related to depressive symptoms and all
types of electronic media use at night, while sleep diffi-
culties were positively related to these variables (except for
a non-significant relation to video game playing in bed).
Depressive symptoms were positively related to all types of
electronic media use at night.
Figure 1represents the regression models testing the
relations between electronic media use in bed before sleep
(independent variable), sleep duration (mediator), and
depressive symptoms (dependent variable), while Fig. 2
shows the same model with sleep difficulties as the medi-
ator. The regression models revealed that electronic media
use in bed before sleep was related to higher levels of
depressive symptoms (b=.26, t=4.84, p\0.001; test
of Hypothesis 2). Moreover, regression models revealed
that electronic media use in bed before sleep was also
related to shorter sleep on weekday nights (b=-.29,
t=-6.00, p\0.001) and sleep difficulties (b=.21,
t=3.91, p\0.001; test of Hypothesis 3) controlling for
age and gender. The direct effect of electronic media use in
bed on depressive symptoms remained significant after
inclusion of the mediator to the regression model, but was
substantially reduced when sleep difficulties as the medi-
ator came to the model (from b=.26, t=4.84,
DR
2
=0.060; p\0.001 to b=.17, t=3.49, DR
2
=
0.026; p\0.001) and somewhat reduced when sleep
duration as the mediator came to the model (from b=.26,
t=4.84, DR
2
=0.060; p\0.001 to b=.23, t=4.10,
DR
2
=0.043; p\0.001) indicating partial mediation (test
of Hypothesis 4). Testing the indirect effect with both
mediators in the model revealed only significance of the
indirect path via sleep difficulties (B =0.08, SE =0.02,
bias corrected CI 0.04–0.13 based on 3,000 bootstrap
samples) but not sleep duration (B =0.02, SE =0.02, bias
corrected CI -0.01 to 0.05).
Testing the age-moderation of the associations between
electronic media use in bed before sleep, sleep duration,
sleep difficulties, and depressive symptoms showed no
significant interactions with age (all pvalues C0.10;
additional Research Question 1).
Table 2 Pearson correlations between study variables
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
1. Age
2. Gender 2.14
3. Sleep duration on weekdays 2.42 2.05
4. Sleep difficulties .01 .08 2.16
5. Depressive symptoms .13 .12 2.22 .44
6. Mobile switched on after lights out .42 2.07 2.39 .14 .15
7. Media use in bed (scale) .31 2.02 2.40 .20 .28 .44
8. Watching TV/videos in bed .19 -.14 2.24 .12 .19 .25 .70
9. Playing video games in bed .07 2.21 2.13 .02 .16 .16 .55 .38
10. Calling/text messaging in bed .34 .13 2.37 .18 .19 .45 .81 .33 .23
11. To be online (Facebook, Chat etc.) in bed .27 .08 2.37 .22 .25 .39 .81 .36 .21 .68
Pairwise exclusion of missing values. Gender coding: male =1, female =2. Coding of ‘‘Mobile switched on after lights out’’: mobile switched
off after lights out (or not in the bedroom) =1, mobile switched on but not at the bed =2, mobile switched on and at the bed =3. Media use in
bed (scale) represents the mean score of the four variables watching TV/videos in bed, playing video games in bed, calling/text messaging in bed,
and to be online (Facebook, Chat etc.) in bed
Italics p \0.05; italics and bold p \0.01; italics, bold, and underlined p \0.001
Fig. 1 Mediation of the relationship between electronic media use in
bed before sleep and depressive symptoms by sleep duration.
Coefficients are standardized regression coefficients that are
controlled for age and gender. The coefficient in brackets represents
the standardized regression coefficient when the mediator (sleep
duration) is also in the model. **p\0.01; ***p\0.001
J Youth Adolescence (2015) 44:405–418 413
123
Testing which type of electronic media use in bed was
most strongly associated with sleep duration, sleep diffi-
culties, and depressive symptoms stepwise regression was
conducted (additional Research Question 2). Being online
(Facebook, Chat etc.) in bed (b=-.21, t=-4.13,
p\0.001) and having the mobile phone switched on at
night (b=.20, t=3.71, p\0.001) (but not watching TV,
playing video games, and calling/text messaging in bed)
were related with sleep duration on weekdays. Being online
(Facebook, Chat etc.) in bed before sleep (b=.22,
t=4.10, p\0.001) (but not watching TV, playing video
games, calling/text messaging in bed, and having the
mobile switched on at night) was related with sleep diffi-
culties. Moreover, being online (Facebook, Chat etc.) in
bed (b=.19, t=3.43, p\0.001) and playing video
games (b=.15, t=2.86, p=0.005) (but not watching
TV, calling/text messaging in bed, and having the mobile
switched on at night) were related with depressive
symptoms.
Discussion
Adolescence is a time of increasing vulnerability for
severe mental health disorders such as depression. Epi-
demiological studies show that the incidence of new
cases of depression drastically increases with puberty
(Hankin et al. 1998; Kessler et al. 2001). As the recur-
rence rate during adulthood is high, prevention of
depression with onset during adolescence is of major
importance (Lewinsohn et al. 1993). During adolescence,
sleep patterns change with a pronounced shift of bed-
times to later in the evening, increasing sleep deprivation
during the school week and sleeping in on weekends
(Crowley et al. 2007). Importantly, there is growing
evidence that sleep disturbance in adolescence may pre-
dict the development of depression (Lovato and Gradisar
2014). In order to prevent the burden of depression with
onset during adolescence, it appears to be a promising
venue to identify and address sleep disturbance (Lovato
and Gradisar 2014).
In addition to the increase in the prevalence of depres-
sion with the transition from childhood to adolescence,
there is also a secular trend of an increasing incidence of
depression during adolescence since the 1960s (Kessler
et al. 2001). A similar but decreasing secular trend has been
reported for adolescents’ sleep duration (Dollman et al.
2007; Iglowstein et al. 2003). Although speculative, it is
possible that these secular trends have a common cause.
One such possible cause is the increasing availability of
electronic devices that has changed adolescents’ every day
lives profoundly since the 1960s. There is now a large body
of evidence confirming that electronic media use particu-
larly is related and may cause sleep disturbance (Cain and
Gradisar 2010). Moreover, there is also evidence of a
predictive role of media use for the development of
depression (Primack et al. 2009). A theoretical model
proposed by Cain and Gradisar (2010) suggests that elec-
tronic media use may cause sleep disturbance, which in
turn may cause daytime dysfunction such as increased
depressive symptoms. One aim of the current study was to
test whether adolescents’ sleep disturbance mediates the
relationship between electronic media use at night and
symptoms of depression. A further aim of the current study
was to examine how smartphones have changed adoles-
cents’ electronic media use at night as during the latest
years the prevalence of smartphones has escalated among
adolescents in Switzerland (Willemse et al. 2012). Due to
the large functional range of smartphones, their handiness,
and the inexpensiveness of accessing the Internet, we
hypothesized that owning a smartphone would change
electronic media use at night and increase sleep disturbance
in adolescents.
Our results show that adolescents who owned a smart-
phone sent a lot more text messages and spent more time
on the Internet and on Facebook per day than their peers
with conventional mobile phones, while they did not watch
more TV or play video games. At night when lying in the
bed, adolescents who owned a smartphone were a lot more
likely to communicate by calling or text messaging or to be
online (e.g., on Facebook or chat), and somewhat more
likely to watch TV or videos (which may also be done on
Fig. 2 Mediation of the relationship between electronic media use in
bed before sleep and depressive symptoms by sleep difficulties.
Coefficients are standardized regression coefficients that are
controlled for age and gender. The coefficient in brackets represents
the standardized regression coefficient when the mediator (sleep
difficulties) is also in the model. ***p\0.001
414 J Youth Adolescence (2015) 44:405–418
123
the smartphone screen), while they were not more likely to
play video games. Furthermore, adolescents who owned a
smartphone were more likely to go to bed later, although
their sleep duration was not shorter on average, and they
did not report more sleep difficulties or symptoms of
depression than their peers who owned a conventional
mobile phone. These findings are in line with our first
hypothesis that adolescents with smartphones report more
electronic media use when lying in the bed and are con-
sistent with the interpretation that the availability of new
electronic devices may strongly change adolescents’ habits.
However and interestingly, the effect did not generalize to
more sleep disturbance or symptoms of depression. This
points to the interpretation that it is more important when,
how much, and how often adolescents use their electronic
devices than whether they use a smartphone or a conven-
tional mobile phone.
Consistent with our second hypothesis, we found that
electronic media use in the bed before sleep was related to
higher levels of depressive symptoms. This is in line with
several studies showing that electronic media use in gen-
eral (e.g., Primack et al. 2009) and at night are related to
depressive symptoms in adolescents (Lemola et al. 2011;
Oshima et al. 2012). Moreover, these results are thus also
in line with similar reports concerning young adults
(Brunborg et al. 2011; Thome
´e et al. 2011). Consistent with
our third hypothesis and in line with a large body of evi-
dence (e.g., Cain and Gradisar 2010), we found that elec-
tronic media use in the bed before sleep was related to
shorter sleep duration and more sleep difficulties. More-
over, consistent with our fourth hypothesis our findings are
in line with the theoretical model involving the mediation
of the relationship between electronic media use and
depressive symptoms by sleep disturbance (Cain and
Gradisar 2010). Particularly sleep difficulties substantially
decreased the relationship between electronic media use
and depressive symptoms when added to the regression
model (the reduction of the criterion variance explained by
electronic media use was from 6 to 2.6 % when entering
sleep difficulties to the regression model indicating that
more than half of the effect was mediated by sleep diffi-
culties). Less strong was the mediating role of sleep
duration, which even disappeared when tested in a model
simultaneously with sleep difficulties. The relationships
between electronic media use, sleep disturbance, and
depressive symptoms appeared relatively consistent across
the studied age range as no moderation by age was found.
All types of electronic media use in the bed before sleep
were moderately to strongly correlated with each other.
Moreover, they were correlated with shorter sleep and
more symptoms of depression, which is consistent with
earlier reports (e.g., Cain and Gradisar 2010). Also con-
sistent with earlier studies watching TV or videos, calling
or text messaging, and spending time online were corre-
lated with sleep difficulties. However, no such correlation
was found between playing video games in bed before
sleep and sleep difficulties. The latter finding is surprising,
although there are also other reports that adolescents who
are experienced in playing video games may not neces-
sarily have poor sleep when playing before sleep (Lemola
et al. 2011). The electronic media use type that was most
strongly related with sleep disturbance and depressive
symptoms was spending time online (e.g., on Facebook or
chatrooms) when lying in the bed before sleep.
Depression during adolescence is a severe condition
involving a high recurrence rate during young adulthood
(Lewinsohn et al. 1993). As the incidence is drastically
increasing during adolescence and prevalence rates have
also risen across the last few decades (Kessler et al. 2001)
it is of major interest to provide ways of prevention during
adolescence. A promising venue for prevention of depres-
sion during adolescence is by improving adolescents’ sleep
quality as there is evidence that disturbed sleep is a vul-
nerability factor for the development of depressive symp-
toms during adolescence (Lovato and Gradisar 2014).
Recommendations to prevent sleep disturbance in ado-
lescents might involve the following. First, as electronic
media use before sleep is related with sleep disturbance and
depressive symptoms many adolescents might benefit from
improved sleep hygiene involving a reduction in electronic
media use before and at bedtime. In our study, more than
80 % of the adolescents owned a smartphone and more
than a third of these adolescents reported to write text
messages or were still online most of the nights when they
were already in bed before sleep. This reflects the endemic
of electronic media use among adolescents nowadays and
the decrease of parental control of their children’s media
consumption. Sleep hygiene education for adolescents
might be taught in classrooms and parents could be
informed regarding the risk and possible strategies to
reduce adolescents’ electronic media use at night. Second,
and in addition to sleep hygiene education, adolescents’
smartphones might feature specific applications supporting
adolescents to maintain sleep hygiene. For instance, such
applications might track the time when adolescents use
their phone (or other electronic media), at what time there
is noise in their bedroom, and at what time they go to sleep
and when they get up. Such sleep hygiene applications for
smartphones might also actively provide reminders when
sleep hygiene rules are violated. Finally, adolescents suf-
fering from excessive media use and a sleep disorder
should be identified by school psychologists and referred to
cognitive behavioral treatment of insomnia in adolescence
as there is now evidence that maintaining healthy sleep
patterns in adolescents might possibly reduce the incidence
of depression in adolescence (Lovato and Gradisar 2014).
J Youth Adolescence (2015) 44:405–418 415
123
Our study also has limitations. First, media use, sleep
disturbance, and depressive symptoms were self-reported
by adolescents using questionnaires. This may involve bias
due to common method (for a discussion of this issue
related to the link between subjective sleep disturbance and
mental health problems see e.g., Lemola et al. 2013).
Moreover, questionnaire measures of behavior may be
biased by memory difficulties. While sleep could be
assessed objectively with actigraphy in future studies, sleep
hygiene and electronic media use could be measured by
experience sampling methods in order to achieve higher
validity of measurement. Second, the correlational nature
of the present study precludes causal conclusions regarding
the relationship between electronic media use, sleep dis-
turbance, and depressive symptoms. While experimental
work with adolescents has convincingly shown that sleep
restriction compromises emotional regulation (e.g., Baum
et al. 2014), future studies might also try to experimentally
restrict electronic media use at night to test whether ado-
lescents are willing and able to reduce their electronic
media use for a certain time for research purposes and
whether sleep and psychological adjustment could be
positively influenced by such a procedure. Finally, our
study cannot advance our knowledge which mechanisms
might be involved in possible effects of electronic media
use on sleep disturbance.
Conclusion
Our findings suggest that the availability of smartphones is
related to increased electronic media use of adolescents at
night. Further, our findings confirm earlier reports that
electronic media use at night is related to sleep disturbance.
Sleep disturbance in turn appears to be a partial mediator of
the relationship between electronic media use at night and
depressive symptoms. Adolescents might benefit from
education regarding sleep hygiene and the risk of electronic
media use at night as improving sleep quality may be a key
factor in the prevention of depression.
Acknowledgments The study was supported by the Stiftung
Suzanne und Hans Bia
¨sch zur Fo
¨rderung der Angewandten Psy-
chologie. The authors would like to thank all the participating
schools, parents, and adolescents who agreed to participate in the
present study.
Author contributions SL conceived of the study, participated in its
design and coordination, performed the statistical analysis, and
drafted the manuscript; NPG participated in the design and coordi-
nation of the study, performed the measurement, and helped to draft
the manuscript; SB participated in the design and interpretation of the
data; JKD participated in the design and interpretation of the data; AG
participated in the design and interpretation of the data. All authors
read and approved the final manuscript.
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Sakari Lemola, PhD is an Assistant Professor at the University of
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Nadine Perkinson-Gloor, MSc is a PhD student at the University of
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perinatal adversities, and consequences of insufficient and poor sleep,
particularly during adolescence.
Serge Brand, PhD is a research psychologist and psychotherapist at
the Center for Affective, Stress and Sleep Disorders, Psychiatric
Clinics of the University of Basel, Switzerland and a research
assistant at the Department of Sport, Exercise and Health, Division of
Sport Science at the University of Basel, Switzerland. He received his
doctorate in Psychology from the University of Basel, Switzerland in
2006. His major research interests include relations of sleep and
psychological health from infancy to adulthood and the interaction of
well-being, sleep, psychophysiology, and physical exercise.
Julia F. Dewald-Kaufmann, PhD works at the Dr. von Hauner
Children’s Hospital of the Ludwig Maximilian University, Munich,
Germany. She received her doctorate in psychology at the University
of Amsterdam in 2012. Her major research interests include outcomes
of chronic sleep reduction in adolescents and the role of sleep
hygiene.
Alexander Grob, PhD is a professor for Personality and Develop-
mental Psychology at the University of Basel, Switzerland. He
received his doctorate in psychology at the University of Berne,
Switzerland in 1990. His major research interests include develop-
mental and intelligence diagnostics in childhood and adolescence,
early intervention for disadvantaged children and adolescents, and
personality development in close relationships across the life-span.
418 J Youth Adolescence (2015) 44:405–418
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Cell phones have transitioned quickly from being a luxury to a necessity and today, it is hard to find someone who is not enjoying the amazing power of cell phones. However, with great powers come great responsibilities; most of the users are unaware of the harmful effects of mobile overuse. Today, we are on the brink of being a victim of technology-addiction and in this regard, psychiatrists, educationists, and psychologists have emphasized upon the physical, social, and mental health problems caused by cell phone overuse leading towards addiction. Addiction to mobile phone usage reportedly results in physical as well as mental impairment and has emerged as the subject of extensive discussion and debate among sociologists and psychologists. This technology-addiction needs to be addressed and managed thoughtfully or it may become the second most serious pandemic of this century.
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This prospective, longitudinal study examined associations between whether and when children first acquire a mobile phone and their adjustment measures, among low‐income Latinx children. Children (N = 263; 55% female; baseline Mage = 9.5) and their parents were assessed annually for 5 years from 2012. Children first acquired a mobile phone at a mean (SD) age of 11.62 (1.41) years. Pre‐registered multilevel models tested associations linking phone ownership, phone acquisition age, and the interaction between ownership and acquisition age to levels and changing trends of depressive symptoms, school grades, and reported and objectively assessed sleep. Results showed no statistically significant associations, controlling the False Discovery Rate. Findings suggest an absence of meaningful links from mobile phone ownership and acquisition age to child adjustment.
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Adolescent screen usage is ubiquitous and influences development and behavior. Longitudinal screen usage data coupled with psychometrically valid constructs of problematic behaviors can provide insights into these relationships. We describe methods by which the screen usage questionnaire was developed in the Adolescent Brain Cognitive Development (ABCD) Study, demonstrate longitudinal changes in screen usage via child report and describe data harmonization baseline-year 2. We further include psychometric analyses of adapted social media and video game addiction scales completed by youth. Nearly 12,000 children ages 9-10 years at baseline and their parents were included in the analyses. The social media addiction questionnaire (SMAQ) showed similar factor structure and item loadings across sex and race/ethnicities, but that item intercepts varied across both sex and race/ethnicity. The videogame addiction questionnaire (VGAQ) demonstrated the same configural, metric and scalar invariance across racial and ethnic groups, however differed across sex. Video gaming and online social activity increased over ages 9/10-11/12 (p’s <.001). Compared with boys, girls engaged in greater social media use (p<.001) and demonstrated higher ratings on the SMAQ (p<.001). Compared with girls, boys played more video games (p<.001) and demonstrated higher ratings on the VGAQ (p<.001). Time spent playing video games increased more steeply for boys than girls from age 9/10-11/12 years (p <.001). Black youth demonstrated significantly higher SMAQ and VGAQ scores compared to all other racial/ethnic groups. These data show the importance of considering different screen modalities beyond total screen use and point towards clear demographic differences in use patterns. With these comprehensive data, ABCD is poised to address critical questions about screen usage changes across adolescence.
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In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators. (46 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Background The relationship between inadequate sleep and mood has been well-established in adults and is supported primarily by correlational data in younger populations. Given that adolescents often experience shortened sleep on school nights, we sought to better understand the effect of experimentally induced chronic sleep restriction on adolescents' mood and mood regulation. Methods Fifty healthy adolescents, ages 14-17, completed a 3-week sleep manipulation protocol involving a baseline week, followed by a sleep restriction (SR) condition (6.5hr in bed per night for five nights) and healthy sleep duration (HS) condition (10hr in bed per night for five nights). The study used a randomized, counterbalanced, crossover experimental design. Participants' sleep was monitored at home via self-report and actigraphy. At the end of each condition, participants and their parents completed questionnaires of mood and mood regulation. To assess for expectancy effects, we also analyzed parent and teen ratings of hyperactivity/impulsivity, which prior research suggests is not sensitive to SR in adolescents. Wilcoxon Signed Rank tests compared questionnaire outcomes across the two conditions. ResultsParticipants averaged 2.5 more hours of sleep per night during HS relative to SR. Compared with HS, adolescents rated themselves as significantly more tense/anxious, angry/hostile, confused, and fatigued, and as less vigorous (p=.001-.01) during SR. Parents and adolescents also reported greater oppositionality/irritability and poorer emotional regulation during SR compared with HS (p<.05). There were no cross-condition differences in depression or hyperactivity/impulsivity (p>.05). Conclusions Findings complement prior correlational study results to show that after only a few days of shortened sleep, at a level of severity that is experienced regularly by millions of adolescents on school nights, adolescents have worsened mood and decreased ability to regulate negative emotions.
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This study investigated whether the use of a television, computer, gaming console, tablet, mobile phone, or audio player in bed before going to sleep was associated with insomnia, daytime sleepiness, morningness, or chronotype. 532 students aged 18-39 were recruited from lectures or via e-mail. Respondents reported the frequency and average duration of their in-bed media use, as well as insomnia symptoms, daytime sleepiness, morningness-eveningness preference and bedtime/rise time on days off. Mean time of media use per night was 46.6 minutes. The results showed that computer usage for playing/surfing/reading was positively associated with insomnia, and negatively associated with morningness. Mobile phone usage for playing/surfing/texting was positively associated with insomnia and chronotype, and negatively associated with morningness. None of the other media devices were related to either of these variables, and no type of media use was related to daytime sleepiness.
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