PLOS ONE

RESEARCH ARTICLE

Do both timing and duration of screen use

affect sleep patterns in adolescents?
Sarah Hartley ID1,2*, Sylvie Royant-Parola1, Ayla Zayoud3, Isabelle Gremy3,
Bobette Matulonga3
1 Réseau Morphée, Garches, France, 2 APHP Hôpital Raymond Poincaré, Sleep Center, Université de
Versailles Saint-Quentin en Yvelines, Garches, France, 3 Institut Paris Région, Observatoire Régional de
Santé, Paris, France

a1111111111 * sarah.hartley@reseau-morphee.fr
a1111111111
a1111111111
a1111111111 Abstract
a1111111111
Background
Sleep duration has declined in adolescents over the last 30 years and screen use has been
identified as a risk factor. Studies have examined the duration of screen use and screen-
OPEN ACCESS based activities but have not differentiated between evening and night-time use.
Citation: Hartley S, Royant-Parola S, Zayoud A,
Gremy I, Matulonga B (2022) Do both timing and Methods
duration of screen use affect sleep patterns in
adolescents? PLoS ONE 17(10): e0276226. https:// Cross sectional questionnaire survey of adolescents recruited in schools. Sleep habits on
doi.org/10.1371/journal.pone.0276226 school nights and weekends, symptoms of insomnia and daytime repercussions were
Editor: Manuel Spitschan, University of Oxford, recorded using an online questionnaire administered in the classroom setting. Sleep depri-
UNITED KINGDOM vation (<7 hours in bed /night), school night sleep restriction (�2 hours difference in sleep
Received: December 15, 2021 duration on school nights vs weekends), excessive sleepiness (score >6 on a visual ana-
Accepted: October 3, 2022
logue scale), duration of screen use and timing of screen use (evening vs after bedtime)
were determined.
Published: October 20, 2022

Peer Review History: PLOS recognizes the Results

benefits of transparency in the peer review
process; therefore, we enable the publication of 2513 students (53.4% female, median age 15 years) were included. 20% were sleep deprived
all of the content of peer review and author and 41% sleep restricted. A clear dose effect relationship in a model controlling for age, sex,
responses alongside final, published articles. The
school level and sociodemographic class was seen with all levels of night-time screen use on
editorial history of this article is available here:
https://doi.org/10.1371/journal.pone.0276226 sleep deprivation and sleep restriction (>2 hours use sleep deprivation OR 5.23[3.03–9.00].
sleep restriction OR 2.05[1.23–3.42]) and > 2 hours evening use (>2 hours use sleep depriva-
Copyright: © 2022 Hartley et al. This is an open
access article distributed under the terms of the tion OR 2.72[2.15–3.44] sleep restriction OR 1.69[1.36–2.11]) but not moderate evening use.
Creative Commons Attribution License, which All night-time use and > 2 hours evening use increased the risk of insomnia, non refreshing
permits unrestricted use, distribution, and sleep, and affected daytime function (daytime sleepiness, lack of energy and irritability).
reproduction in any medium, provided the original
author and source are credited.
Conclusions
Data Availability Statement: All relevant data are
within the paper and its Supporting Information Both duration of screen use and timing are associated with adverse effects on sleep and
files. daytime functioning in adolescents. More than 2 hours evening use and all night-time use
Funding: The authors received no specific funding should be avoided.
for this work.

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PLOS ONE Adolescent sleep and screen use

Competing interests: The authors have declared Introduction

that no competing interests exist.
Sleep is a vital function that evolves throughout the human lifespan. Restorative sleep is essen-
tial for health, cognitive function, and mental health [1]. Sleep is regulated by homeostatic
sleep pressure and the circadian drive for sleep [2]. While the former depends on the time
spent awake (and is thus sensitive to sleep deprivation) the latter depends on external synchro-
nisers or zeitgebers [3]. These act on the central body clock in the suprachiasmatic nucleus
which controls the phase of peripheral clocks in individual cells via melatonin secretion from
the pineal gland during the night.
Both sleep duration and the phase of the circadian system are important for sleep timing,
sleep quality and daytime vigilance [4]. Sleep need in adolescents is often underestimated:
studies have shown that adolescents need on average 9 hours a night, but real life sleep times
are often much lower [5] and studies suggest that they been reducing over time [6] although
this is debated [7]. Many causes have been advanced for this reduction in sleep time including
social pressures linked to school work or friendship groups, the use of stimulants such as caf-
feine, and finally inappropriate stimulation of the central body clock due to evening light.
Light is the most powerful synchroniser of the central body clock and stimulates the mela-
nopsin receptors of intrinsically photosensitive retinal ganglion cells (ipRGCs) in the retina
which convey the signal to the suprachiasmatic nucleus. Melanopsin receptors are exquisitely
sensitive to blue light in the 446–477 nm range [8]. Modern screens in smartphones, laptops
and tablets have screens emit large quantities of blue light, and this has been shown to modu-
late the expression of circadian genes [9] and block the secretion of melatonin [10]. This trans-
lates to sleep disturbance: reading using a tablet clearly delays sleep onset compared to a book
[11], and this effect is blocked by wearing blue light blocking glasses [12]. Children and adoles-
cents are particularly sensitive to the effects of blue light [13], especially if they are little
exposed to morning bright light. An additional mechanism is likely to be the mental stimula-
tion provided by screen use: playing a video game or using social networks seem to contribute
to poor sleep [14].
The American Academy of Pediatrics, in 2016, recommended limiting screen activities to 2
hours a day, but this limit has been shown to be regularly exceeded [15]. Excessive screen use
is defined as >3 hours a day of screen use for social activities: ie those not related to school
work, but timing of screen use has not been defined. Studies have shown that excessive screen
use is linked to insufficient sleep in adolescents [16] although quantifying use is problematic. It
is possible that other consequences, such as obesity [17] and adverse mental health outcomes
[18] are mediated by reduced sleep time. Reduced sleep duration and poor quality sleep in
adolescents have been shown to lead to inattention in class [19] and poor academic perfor-
mance [20–22].
We hypothesized that in adolescents both the duration of screen use and the timing of
screen use (evening and night-time) would be associated with a reduction in both sleep time
and sleep quality with effects on daytime function (daytime sleepiness, lack of energy and irri-
tability). Our aim was to examine the associations between the duration and timing of screen
use, sleep and daytime function in healthy adolescents in the community.

Methods
The Morphee health network (Réseau Morphée) is funded by the regional health authority in
the Paris region. It aims to provide information about sleep disorders and improve the man-
agement of patients suffering from sleep disorders. We performed a transverse survey based
study in adolescents aged from 12–19. Participants were recruited within schools during edu-
cational sessions on sleep between 2015 and 2019. Prior to educational sessions led by trained

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PLOS ONE Adolescent sleep and screen use

class teachers, consent was sought from parents. Once consent was obtained, students com-
pleted an online questionnaire in class which formed one of the tools for the education ses-
sions. Inclusion criteria were belonging to a school participating in the programme and having
signed consent from a parent. No identifying data was available on the questionnaire apart
from sex, age to the nearest year, school class and school.
The study was approved by the scientific committee of the Réseau Morphée and by the edu-
cational authority in each school (Comité pédagogique et du Comité d’Education à la Santé et
la Citoyenneté, CESC). The study was approved by the Commission Nationale Informatique et
Liberté (CNIL), 8013081 19/12/2016.

Sleep related measures

The questionnaire had 50 questions including age (in years), sex, school year, the presence of a
screen in the bedroom, timing and duration of screen exposure, screen based activities, bed-
time and getting up time during the week and at the weekend, sleep quality and symptoms
associated with sleep disorders, anxiety and depression.
Sleep time was calculated from mean bedtime and getting up times both during the week
and at weekends, and represents the total available window for sleep, not necessarily the actual
sleep time which will be reduced by the time taken to fall asleep and wake periods during the
night. Adolescents with a sleep time <7 hours were considered to be sleep deprived, adoles-
cents with a difference of �2 hours between their sleep time on schooldays and at the weekend
were considered to be sleep restricted during the week. We compared sleep deprivation (sleep
time of <7 hours) with sleep restriction (a difference between sleep time at the weekend and
during the week of>2 hours) to attempt to compensate for adolescents whose sleep needs were
less than 9 hours following the definition of sleep restriction in the study by Lo et al [23].
Information on sleep quality was collected looking for difficulties in falling asleep (with a
time >60 minutes considered as abnormal [24]) and the presence of refreshing sleep: on a
scale of 1–10, sleep was considered non refreshing if the score was �6. Insomnia was defined
as difficulties falling asleep or maintaining sleep accompanied by daytime consequences (lack
of energy, irritability or daytime sleepiness).

Daytime functioning
Daytime sleepiness was defined as a score >6 on a visual analogue scale of 1–10 concerning
the likelihood of falling asleep in class with a maximum score of 10 (extremely sleepy in class).
Students were asked about lack of energy and irritability with a yes/no response.

Screen exposure
Participants were prompted to supply data on the presence of a screen in the bedroom including
computer, television and smartphone. Data on the duration of screen use (computers, smartphones,
and games consoles) was collated to provide the total duration of screen exposure. Simultaneous use
of several screens was not recorded. Mean duration of screen exposure was estimated by students
both after dinner before bedtime and during the night (in bed, after lights out) with 5 possible
responses (0 minutes, <30 minutes, <1 hour, 1–2 hours, <2 hours). The type of activity in the even-
ing and during the night was recorded (sending texts, social networks, films/series and video games)

Statistical analysis
Quantitative variables (sleep duration, bedtime and getting up time) were described by median
and interquartile range (IQR) and were compared using the Kruskal-Wallis test. Qualitative

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PLOS ONE Adolescent sleep and screen use

variables such as sex, evening screen use, night-time screen use and symptoms of sleep pathol-
ogy were described by percentage and analysed by Chi2 tests. For multivariant analysis, even-
ing screen use with 5 possible responses from 0 minutes to >120 minutes were collapsed into
3 groups (<60 minutes, 60–120 minutes and >120 minutes). For night-time screen use, the
original 5 groups (0 minutes to >120 minutes) were retained as we considered it possible that
lower duration screen exposure during the night was physiologically important.
Logistic regression was used to evaluate the associations between sleep duration, sleep dis-
orders evening screen use and night-time screen use. The analysis was adjusted for sociodemo-
graphic variables: age, sex and sociodemographic status, evaluated via school location, as
previous studies have shown that these are important [25]. Missing variables were excluded
from the analysis. Analysis was performed using SAS version 9.4.

Results
Population
The online questionnaire could not be uploaded if data was not complete, 6 participants were
excluded for incoherent responses. 2513 students were included: 53.4% were girls with a mean
age of 14.3 years (median: 15 years, IQR: [12, 16]). All were in secondary education: 45.7%
were in middle school (aged 11–15) and 54.3% in high school (aged >15).

Sleep habits
Mean sleep time over the entire population was 7.8 hours (median 8 hours; IQR: [7, 9]; SD
1:52) during the school week and 9.75 hours (median 10 hours; IQR: [9, 11]; SD 2:17) at the
weekend: students aged <12 years slept longer than the 12–15 and >15 years groups
(p<0.0001), and middle school students slept longer than high school students (p<0.0001),
see Table 1.
Nearly half of all students took >30 minutes to fall asleep and 10% more than 2 hours.
Large differences were noted between school days and weekends, both in mean getting up
time (07:05 vs 10:38) and in bedtimes (21:52 vs 00:46). 95% got up between 06:00 and 08:00 on
school days, whereas 94% got up after 08:00 at the weekends (with 36,3% after 11H00 and 10%
after 13:00). A bedtime after midnight was much more common at the weekend (62% vs 14%).

Sleep and age

Sleep restriction, defined as a reduction of >2 hours in sleep time on schooldays vs weekends
increased significantly with age: 30% in <12, 45% in 12–15 and 46% in >15 (p<0.0001), as did
sleep deprivation defined as a sleep time <7 hours: 9% <12, 21% 12–15, 31% >15 (p<0.0001).

Table 1. Age, sleep time, sleep pathology, and daytime sleepiness.

<12 years n = 847 12–15 years n = 842 >15 years n = 816 Total n = 2513 p P tendance
Median Sleep time on school days; hours: minutes (SD) 9:00(1:51) 8:00 (1:42) 7:00 (1:36) 8:00 (1:52) <0.0001 <0.0001
Median sleep time on weekends; hours: minutes (SD) 10:05 (2:35) 10:04 (1:58) 9: 57(2:11) 10:00 (2:17) <0.0001 <0.0001
Sleep deprivation on schooldays 9% 21% 31% 20% < .0001 < .0001
Sleep restriction 30% 45% 46% 41% < .0001 < .0001
Insomnia 19% 17% 18% 18% 0.45 0.87
Difficulty falling asleep 20% 14% 16% 16% 0.004 0.02
Daytime sleepiness 3% 2% 1% 2% 0.043 0.012
Poor quality sleep 36% 48% 52% 45% < .0001 < .0001
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PLOS ONE Adolescent sleep and screen use

Non refreshing sleep also increased with age affected 36% <12, 48% 12–15 and 45% of >15
(p<0.0001). As expected sleep duration also decreased with age whereas no age difference was
found for insomnia or for daytime sleepiness.

Screen use (Table 2)

65% had at least one screen in their bedroom (computer, television, game console or mobile
telephone). Before bedtime 11% read or listened to music, 30% did passive screen based acti-
vites (ex. watching a film) 32% did active screen based activities (social networks, video games)
and 27% did none of the above. 22% used their smartphone and 40% used other screens before
going to bed. 27% reported using screens during the night: see Table 2.
82% woke up at least once during the night and in 33% this was due to a message on their
smartphone (text or social network). Owning a smartphone was more common in girls (94.4% vs
90.3% p = 0.0002), but excessive screen use (>2 hours) after dinner was more common in boys
(26% vs 18% p<0.0001) as was > 2 hours screen use during the night (4.5% vs 2.6% p = 0.0009).

Screen use and sleep duration

The presence of a screen in the bedroom (computer, television, game console or mobile tele-
phone) was associated with an increase in sleep deprivation (p<0.0001) (Table 2). Multivariate
analysis using logistic regression (Table 3), showed that having a screen in the bedroom and
owning a smartphone were both associated with an increased risk of sleep deprivation and
sleep restriction (p<0.0001) however this was no longer apparent after adjusting for age, sex,
school class and sociodemographic class.
Evening screen use was associated with sleep deprivation: bivariate analysis (Table 2)
showed that of participants with a sleep time of <7 hours, 51% used screens for >120 minutes
in the evening vs 11% of students with no screen use. Multivariate analysis (Table 4) showed a
clear dose effect relationship between the duration of evening screen use, sleep deprivation
and sleep restriction compared to the group who used screens for <1 hours (all data in bold
are significant with p < 0.0001). After adjustment for age, sex, school class and sociodemo-
graphic class moderate evening screen use (60–120 minutes) was only significantly associated
with sleep restriction, but > 2 hours of evening screen use was significantly associated with
both sleep deprivation OR 2.72 [2.15–3.44] and sleep restriction OR 1.69 [1.36–2.11] (Table 4).
Night-time screen use also showed a significant dose effect relationship both before and
after adjustment, with > 2 hours of use being strongly associated with both sleep deprivation
OR 5.23 [3.03–9.00] and sleep restriction OR 2.05 [1.23–3.42].

Table 2. The association between screens and sleep time.

Sleep duration on school nights
<7 hours n = 505 7–9 hours n = 1183 �9 hours n = 825 Total p
Computer in the bedroom 64% 58% 41% 46% < .0001
Duration of screen time in the evening 0 minutes 11% 12% 18% 14% < .0001
<30 minutes 9% 17% 26% 18%
30–60 minutes 11% 19% 17% 17%
60–120 minutes 18% 25% 17% 21%
>120 minutes 51% 25% 21% 30%
Owns a mobile telephone 96% 95% 87% 92% < .0001
Nighttime users of screen 10% 11.8% 5.4% 26.7% < .0001
Owns a smartphone 94% 94% 88% 92% < .0001
Television in the bedroom 44% 35% 26% 34% < .0001
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PLOS ONE Adolescent sleep and screen use

Table 3. The association between the presence of screens in the bedroom or owning a smartphone on sleep and daytime function adjusted for age, sex and sociode-
mographic class.
Presence of a screen in the bedroom� N = 1632 (64.9%) Owning a smartphone�� N = 2324 (92.5%)
Crude OR [IC95%] Adjusted OR [IC95%] Crude OR [IC95%] Adjusted OR [IC95%]
Sleep deprivation on schooldays 2.71 [1.75–4.19] 1.19 [0.73–1.91] 1.96 [1.50–2.54] 1.19 [0.87–1.62]
Sleep restriction 2.25 [1.42–3.57] 1.57 [0.97–2.55] 1.54 [1.16–2.04] 1.19 [0.87–1.62]
Insomnia 0.83 [0.52–1.30] 0.97 [0.60–1.57] 0.94 [0.69–1.29] 0.99 [0.71–1.39]
Lack of energy 1.09 [0.75–1.59] 0.80 [0.54–1.20] 1.49 [1.15–1.92] 1.21 [0.92–1.60]
Irritability 1.05 [0.66–1.66] 1.12 [0.69–1.82] 1.18 [0.86–1.61] 1.21 [0.86–1.69]
Daytime sleepiness 1.67 [1.12–2.48] 1.13 [0.75–1.71] 1.89 [1.45–2.45] 1.47 [1.11–1.96]
Poor quality sleep 1.64 [1.12–2.42] 1.17 [0.78–1.75] 1.39 [1.09–1.78] 1.09 [0.83–1.43]

Significant data (p < 0.0001) are shown in bold

�
Adolescents having at least one screen il their bedroom are compared with those who do not have a screen in their bedroom considered as the reference class (with
OR = 1)
��
Adolescents who have a smartphone are compared with those who don’t have a smartphone considered as the reference class (with OR = 1)
OR ratio are adjusted for age, school department as a proxy of socio economic level and gender.

https://doi.org/10.1371/journal.pone.0276226.t003

Screens, sleep complaints and daytime functioning

Multivariate analysis showed that the presence of a screen in the bedroom was associated with
an increase in daytime sleepiness OR1.67 [CI:1.12–2.48] and non refreshing sleep OR1.64
[CI1.12–2.42], but these were no longer significant once corrected for age, sex, school class
and sociodemographic class (Table 3). Owning a smartphone was associated with decreased
sleep quality OR1.39 [CI:1.09–1.78] and an increase in daytime sleepiness OR1.89 [CI:1.45–
2.45] but only daytime sleepiness OR1.47 [1.11–1.96] remained significant once the analysis
was adjusted (Table 3). No association was seen with insomnia or irritability.
Evening screen use showed a clear dose effect relationship (Fig 1 and Table 4) persisting
after adjustment for age, sex, school class and sociodemographic class with certain elements of
daytime function. Both moderate (60–120 minutes) and > 2 hours of evening screen use
increased daytime sleepiness OR 2.17 [CI1.75–2.69]. More than 2 hours of evening screen use
but not moderate screen use (60–120 minutes) was associated with non refreshing sleep OR
1.60 [1.29–1.98] insomnia 1.60 [1.23–2.00], irritability OR 1.64 [1.28–2.09], and lack of energy
OR1.54 [1.24–1.90]. When adolescents who used screens during the night were excluded from
the analysis the association with >2 hours of evening screen use, but not moderate screen use

Fig 1. Duration of evening screen time use and effects.

https://doi.org/10.1371/journal.pone.0276226.g001

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Table 4. The association between the duration of screen exposure in the evening and during the night on sleep and daytime function adjusted for age, sex and sociodemographic class.

Evening screen exposure compared to students Night time screen exposure compared to students not using screens at night��
using screens for <1 hour�
1–2 hours screen use >2 hours screen use 30 minutes N = 327 30–60 minutes N = 154 60–120 minutes N = 82 >120 minutes N = 86
N = 641 N = 549
Crude OR Adjusted Crude OR Adjusted Crude OR Adjusted OR Crude OR Adjusted OR Crude OR Adjusted OR Crude OR Adjusted OR
[IC95%] OR [IC95%] OR [IC95%] [IC95%] [IC95%] [IC95%] [IC95%] [IC95%] [IC95%] [IC95%]
[IC95%] [IC95%]
Sleep 1.27 1.16 [0.93– 2.47 2.72 [2.15– 2,51 [1,97 2,72 2,26 2,90 3,55 5,98 [3,52– 3,81 5,23
deprivation on [1.05– 1.44] [2.01– 3.44] 3,19] [2,6 – 3,59] [1,62 – 3,15] [1,77 – 3,82] [2,21 – 5,68] 10,15] [2,39 – 6,6] [3,3 – 9,00]
schooldays 1.54] 3.03]
Sleep 1.32 1.27 [1.0– 1.73 1.69 [1.36– 1,76 1,72 1,82 1,92 2,54 3,17 1,91 2,05
restriction [1.07– 1.58] [1.39– 2.11] [1,37 – 2,27] [1,31 – 2,25] [1,27 – 2,61] [1,31 – 2,80] [1,54 – 4,18] [1,88 – 5,35] [1,19 – 3,4] [1,23 – 3,42]
1.62] 2.14]
Insomnia 0.88 0.84 [0.63– 1.57 1.60 [1.23– 2,36 2,38 2,78 2,82 4,31 4,23 5,85 5,48
[0.68– 1.11] [1.23– 2.00] [1,78 – 3,13] [1,77 – 3,21] [1,91 – 3,13] [1,91 – 4,16] [2,71 – 6,85] [2,61 – 6,83] [3,75 – 9,14] [3,39 – 8,84]
1.47] 2.00]
Lack of energy 1.25 1.19 [0.97– 1.46 1.54 [1.24– 1,72 1,60 2,11 2,12 3,41 3,89 2,44 2,84

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[1.03– 1.46] [1.03– 1.90] [1,36 – 2,18] [1,24 – 2,5] [1,52 – 2,95] [1,50 – 3,00] [2,13 – 5,46] [2,38 – 6,35] [1,57 – 3,79] [1,75 – 4,60]
1.52] 1.52]
Irritability 1.08 1.10 [0.85– 1.52 1.64 [1.28– 1,71 1,75 2,99 2,76 1,70 1,66 3,92 3,56
[0.85– 1.41] [1.20– 2.09] [1,30 – 2,26] [1,31 – 2,33] [2,11 – 4,24] [1,92 – 3,96] [1,2 – 2,84] [0,98 – 2,82] [2,52 – 6,11] [2,21 – 5,75]
1.37] 1.93]
Daytime 1.41 1.35 [1.10– 2.15 2.17 [1.75– 1,80 1,67 2,43 2,59 3,16 3,81 2,92 3,05
sleepiness [1.16– 1.65] [1.76– 2.69] [1,42 – 2,28] [1,30 – 2,15] [1,74 – 3,39] [1,82 – 3,68] [1,99 – 5,1] [2,34 – 6,21] [1,86 – 4,56] [1,87 – 4,95]
1.71] 2.64]
Poor quality 1.24 1.22 [0.99– 1.54 1.60 [1.29– 1,92 1,73 2,28 2,30 2,53 2,98 1,84 2,99
sleep [1.02– 1.49] [1.26– 1.98] [1,52 – 2,44] [1,34 – 2,22] [1,63 – 3,20] [1,62 – 3,28] [1,60 – 4,00] [1,84 – 4,82] [1,19 – 2,85] [0,94 – 3,45]
1.50] 1.88]

Significant data (p < 0.0001) are shown in bold

�
Adolescent who use screens for more than 1 hour are compared with those who have an evening screen exposure of less than 1 hour considered as the reference class (N = 1323, OR = 1)
��
Adolescent who have nighttime screen exposure are compared with those who never use screen during the night considered as the reference class (N = 1841, OR = 1)
OR ratio are adjusted for age, gender and geographic area of the school as a proxy of socio economic level

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Adolescent sleep and screen use
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Fig 2. Duration of night time screen time use and effects.

https://doi.org/10.1371/journal.pone.0276226.g002

was confirmed for sleep restriction OR 1.54 [0.78–1.70], poor quality sleep OR 1.61 [1.23–
2.12], insomnia OR 1.54 [1.06–2.23], lack of energy OR 1.21 [0.92–1.60] irritability OR 1.71
[1.23–2.40] and increased daytime sleepiness OR 1.94 [1.47–2.57].
Night-time screen use (Fig 2 and Table 4) showed a clear dose effect across all domains in
the fully adjusted model. More than 2 hours of night-time screen use was associated with
insomnia OR 5.48 [3.39–8.84], daytime sleepiness OR 3.05 [1.87–4.95], irritability OR 3.56
[2.21–5.75], and lack of energy OR 2.84 [1.75–4.60]. The association with non-refreshing sleep
was borderline significant (adjusted OR 2.99 [0.94–3.45]). To examine the possibility that the
association with daytime sleepiness was limited to participants with long sleep time (>9 hours
per day) the analysis was repeated having excluded long sleepers and showed that the associa-
tion was reinforced with significant adjusted ORs of 2,00 [1.16–3.46] for 30 minutes use, 3.13
[1.56–6.27] for 30–60 minutes and 6.25 [2.06–18.9] for >120 minutes. The OR in the 60–120
minutes group was not significant but we note low numbers in this group. The analysis was
further adjusted for the possession of a screen and for the presence of a screen in the bedroom
(see Table 5).

Discussion
Our study shows a clear association between subjective estimates of evening and night-time
screen use, reduced sleep duration, poor sleep and elements affecting daytime functioning
(daytime sleepiness, a lack of energy and irritability) in an adolescent population recruited in
an educational setting. These effects persisted, especially in the case of night-time screen use,
after adjusting for age, sex, school class and sociodemographic status and demonstrated a clear
dose effect relationship.
Our findings confirm the results of earlier studies. Insufficient sleep is common in adoles-
cents [21] and multiple studies have confirmed an association not only with screen use but
also with the content accessed [26]. A metanalysis [27] of 17 studies in children and adoles-
cents showed a clear association between screen use and inadequate sleep time. A dose
response effect between self reported screen use at bedtime and sleep duration was found by
Hysing [24] but although screen use during the night is known to be frequent in adolescents in
France [28] this is the first study to distinguish the effects of both duration and timing of
screen use and to demonstrate a clear dose response relationship.
Nearly all adolescents have access to a screen, and having a screen (not including a smart-
phone) in the bedroom was frequent: 65% in our study compared to 97% in the USA (NSF

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Table 5. The association between the duration of screen exposure during the evening and at night on sleep and
daytime function adjusted for age, sex and sociodemographic class adjusted for screen possession and presence of
a screen in the bedroom (adjusted OR only).
Evening screen exposure Night time screen exposure compared to students not
compared to students using using screens at night ��
screens for <1 hour�
1–2 hours >2 hours 30 minutes 30–60 60–120 >120
screen use screen use N = 327 minutes minutes minutes
N = 641 N = 549 N = 154 N = 82 N = 86
Adjusted OR Adjusted OR Adjusted OR Adjusted OR Adjusted OR Adjusted OR
[IC95%] [IC95%] [IC95%] [IC95%] [IC95%] [IC95%]
Sleep deprivation 0.87(0.649 2.62 (2.01– 2.21 (1.61– 3.07 (2.02– 5.93 (3.44– 7.79 (4.48–
on schooldays 1.17) 3.42) 3.03) 4.66) 10.21) 13.52)
Sleep restriction 1,22 (0.99– 1.60 (1.27– 1.61 (1.23– 1.80 (1.23– 2.90 (1.72– 1.93 (1.15–
1.52) 2.02) 2.11) 2.64) 4.91) 3.24)
Insomnia 0.84 (0.63– 1.63 (1.25– 2.42 (1.78– 2.92 (1.97– 4.48 (2.75– 5.62 (3.44–
1.12) 2.12) 3.29) 4.32) 7.29) 9.17)
Lack of energy 1.62 (0.94– 1.48 (1.19– 1.54 (1.19– 2.10 (1.49– 3.98 (2.42– 2.70 (1.66–
1.43) 1.84) 1.99) 2.98) 6.56) 4.40)
Irritability 1.11 (0.86– 1.65 (1.28– 1.69 (1.27– 2.69 (1.87– 1.65 (0.97– 3.56 (2.19–
1.43) 2.12) 2.27) 3.88) 2.80) 5.80)
Daytime 1.32 (1.07– 2.11 (1.69– 1.63 (1.27– 2.49 (1.75– 3.79 (2.31– 3.05 (1.86–
sleepiness 1.62) 2.63) 2.11) 3.54) 6.22) 5.00)
Poor quality 1.25 (1.01– 1.61 (1.29– 1.73 (1.34– 2.36 (1.65– 3.02 (1.86– 2.14 (1.32–
sleep 1.53) 2.00) 2.23) 3.37) 4.92) 3.48)

Significant data (p < 0.0001) are shown in bold

�
Adolescent who use screens for more than 1 hour are compared with those who have an evening screen exposure of
less than 1 hour considered as the reference class (N = 1323, OR = 1)
��
Adolescent who have a nighttime screen exposure are compared with those who never use screen during the night
considered a the reference class (N = 1841, OR = 1)
OR ratio are adjusted for age, gender and geographic area of the school as a proxy of socio economic level screen
possession and presence of a screen in the bedroom

https://doi.org/10.1371/journal.pone.0276226.t005

sleep in America 2014) and this is increasing over time [29]. Our adjusted model showed that
simply having access to a computer or television screen in the bedroom did not increase the
risk of negative effects on sleep: it is the duration of screen use and notably the timing of use
which determines the effect. Our data enabled us to distinguish evening screen use (after the
evening meal but before lights out) and night-time screen use (after lights out). Evening screen
use (computer, television or smartphone) was found in 86%, slightly lower than Hysing et als
study in 2015 in a population of 16–18 year olds [24], but we note that our population was
younger with a mean age of 14.3 years. 27% of our participants regularly used screens during
the night and 33% were woken at least once a night by an alert on their mobile phones.
A reduction in sleep time linked to the intensity of screen use during the night reflects the
fact that time spent on screens directly reduces sleep time. However, this cannot fully explain
the reduction in sleep time observed by those using screens in the evening. Evening screen
based activities can be mentally stimulating (for example playing games or interacting on
social networks) but screens also expose users to bright, blue enriched light. Evening light
exposure has two effects: a directly stimulating effect on the wake systems reducing sleepiness
[30] and a potential reduction or abolition of melatonin secretion which shifts the phase of the
body clock, leading to later bedtimes and wake times [31]. However this depends on the spec-
trum of the light exposure (blue light specifically stimulating the melanopsin receptors in the

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PLOS ONE Adolescent sleep and screen use

retina) [10], and also daytime light exposure as bright light exposure during the day can signif-
icantly reduce the suppressing effect of evening light on melatonin secretion [32]. It is sug-
gested that the combination of evening light exposure and stimulating screen based activity
may explain the later bedtimes noted in evening screen users [26]. All our participants were
under 18 and in school and thus obliged to get up early in the school week (mean getting up
time was 07:05): early school start times are known to be associated with reduced weekday
sleep times in adolescents [33]. A later bedtime in the context of a fixed wake time would
reduce total sleep time. At the weekend, high sleep pressure due to reduced sleep on school
nights and phase shifted circadian rhythms leading to delayed melatonin offset will lead to
later wake times and a difference in sleep duration between the school week and the weekend.
This is what we observed, with a clear dose effect relationship between evening screen use and
sleep restriction (defined as �2 hours more sleep per night on average at the weekend). Sleep
deprivation, defined as a sleep time in the week of <7 hours was linked to all night-time screen
use and >2 hours of evening screen use.
Screen use has also been shown to impact sleep quality [34]. Increased sleep latency is com-
mon in adolescents due to physiological circadian delay [35], so we retained a definition of
sleep onset insomnia combining a delay of >60 minutes [24] associated with daytime conse-
quences. We found sleep onset insomnia in 18% of participants and a clear increase in risk
with 2 hours evening screen use, confirming the findings of Hysing, Yen and Varghese [24, 36,
37]. Non refreshing sleep affected 45% of our sample and we found a strong association with
both >2 hours evening screen use and all night time use. The feeling that sleep is not refresh-
ing has been shown to be linked to inadequate sleep duration [38], but also to sleep fragmenta-
tion and difficulties waking in the morning which are linked to circadian phase. Circadian
phase shifting with delayed melatonin offset induced by evening/nighttime screen use would
lead to being woken up to go to school in the week before melatonin offset. This delayed mela-
tonin offset would cause difficulties waking, which would be exacerbated by the effects of
reduced sleep time. We also note that 33% of our population reported being regularly woken
at night by telephone alerts which could further fragment sleep.
Evening and night-time screen use also affected daytime functioning. Insufficient sleep is
the major cause of excessive daytime sleepiness in adolescents [39, 40]. Daytime sleepiness was
measured in our study by the likelihood of falling asleep in class, which represents severe sleep-
iness, and this was found in 2% of our population. We showed a clear increase in daytime
sleepiness linked to both moderate and > 2 hours evening and night-time screen use. More
than 2 hours evening use and all levels of night-time screen use were associated with lack of
energy during the day and with irritability. Sleepiness has been shown to interfere with learn-
ing [40], and irritability reflects difficulties with emotional control in the face of social chal-
lenge. Our study was not designed to demonstrate a link between screen use and educational
performance, but this has been shown by other studies [22].
Our study was limited by the fact that both sleep habits and screen use depended on self
report. However studies using actigraphy have shown broad correlation between subjective
and objective reports of sleep timing [41] with higher accuracy in adolescents for sleep onset
latency [42]. A more complex problem is that of subjective vs objective screen use. Firstly, as
discussed by Kaye et al, there is a clear need for theoretically valid and practically useful con-
ceptualisations of screen time [43]. Estimations of use are affected by the time frame of refer-
ence, media multitasking (the number of screens used simultaneously), developmental age
[44] and the differentiation between screen time as a numerical measurement (e.g., minutes
per day) or “screen use” (number of connections),. Andrew et als study of smartphone use in
adults found a reasonable correlation in estimated vs objective use time although a consider-
able underestimate in the number of brief uses [45] while other studies show only a modest

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PLOS ONE Adolescent sleep and screen use

association between self report and logged screen time and a possible tendency to over report
[46]. To our knowledge no study has been able to evaluate objective vs subjective screen time
in the context of media multitasking especially in adolescents. Developing objective measures
of screen time across multiple devices is necessary but technically challenging. Given the
known difficulties in time estimation in the younger population it is likely that adolescents
underestimate their screen use.
Our screen use questions were limited to an upper limit of more than 2 hours: given the
high number of students (30%) using screens for more than 2 hours in the evening, it would
have been useful to have had further detail on high duration screen users: future studies should
seek details of upper limit use and we suggest asking about use of 180–240 minutes and >240
minutes. Opticians have started to offer blue light filters on glasses but we did not ask about
this, and so cannot identify a subpopulation potentially protected from the adverse effects of
blue light on circadian rhythms. The nature of screen based activity may add to the stimulating
effect of screens, but our study did not examine content or whether screen use was related to
school work or leisure activities, although telephone use is unlikely to be directly related to
school work.
Our definition of sleep deprivation as a sleep time <7 hours is less than the 9 hours recom-
mended sleep time for teenagers [47] although this ignores individual variations in sleep
needs. It is possible that students who need less that nine hours sleep or who have sleep diffi-
culties use screens when they cannot sleep leading to an association with reduced sleep time.
We cannot determine the direction of the effect, but students who need little sleep would not
suffer adverse effects on daytime functioning which would potentially reduce the strength of
the association. We did not examine potential confounders such as anxiety and depression as
the questionnaire was completed online in the classroom setting. Finally our population was
not selected randomly as we recruited from schools where teachers had chosen to implement a
sleep focussed teaching module. However, within school classes we had an excellent participa-
tion rate, ensuring good representation among children and data was adjusted for sociodemo-
graphic status estimated by geographical location of the school.

Conclusion
Our study aimed to explore the role of both duration and timing of screen exposure in adoles-
cents and is first to highlight a dose effect relationship between duration of screen use in a
teenage population both in the evening and during the night. Screen use is associated with
reduced sleep time, insomnia, non refreshing sleep and daytime consequences such as sleepi-
ness and irritability. Our data suggests that all night-time screen use should be avoided. Mod-
erate evening use of less than 2 hours is not associated with reduced sleep but may still be
associated with daytime sleepiness. We suggest that guidelines for the safe use of screens in
adolescents should recommend less than 2 hours of screen use in the evening and no screen
use at all during the night.

Supporting information
S1 Data.
(XLS)

Author Contributions
Conceptualization: Sarah Hartley, Sylvie Royant-Parola.
Data curation: Sarah Hartley, Sylvie Royant-Parola, Bobette Matulonga.

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PLOS ONE Adolescent sleep and screen use

Formal analysis: Ayla Zayoud, Bobette Matulonga.

Investigation: Sarah Hartley, Sylvie Royant-Parola, Ayla Zayoud, Bobette Matulonga.
Methodology: Sarah Hartley, Sylvie Royant-Parola, Bobette Matulonga.
Project administration: Sylvie Royant-Parola, Isabelle Gremy.
Resources: Sylvie Royant-Parola, Isabelle Gremy.
Supervision: Isabelle Gremy, Bobette Matulonga.
Validation: Sarah Hartley, Sylvie Royant-Parola, Isabelle Gremy, Bobette Matulonga.
Visualization: Sarah Hartley, Sylvie Royant-Parola, Ayla Zayoud.
Writing – original draft: Sarah Hartley.
Writing – review & editing: Sarah Hartley, Sylvie Royant-Parola, Ayla Zayoud, Isabelle
Gremy, Bobette Matulonga.

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