Resea ch A icle
Associa ion be ween In o ma ion and Communica ion
Technology Usage and he Quali y o Sleep among School-Aged
Child en du ing a School Week
Sand a Ononogbu,1Ma ju Wallenius,2Raija-Leena Punamäki,2Lea Saa ni,3
Ha i Lindholm,4and Clas-Håkan Nygå d1
1School o Heal h Sciences, Uni e si y o Tampe e, Medisiina inka u 3, 33014 Tampe e, Finland
2School o Social Sciences and Humani ies/Psychology, Uni e si y o Tampe e, Kale anka u 5, 33014 Tampe e, Finland
3Tampe e Uni e si y o Applied Sciences, Kun oka u 3, 33520 Tampe e, Finland
4Cen e o Excellence o Heal h and Wo k Abili y, Finnish Ins i u e o Occupa ional Heal h, Topeliuksenka u 41 aA,
00250 Helsinki, Finland
Co espondence should be add essed o Clas-H˚
akan Nyg˚
a d; clas-hakan.nyga d@u a. i
Recei ed 30 Sep embe 2013; Re ised 10 Decembe 2013; Accep ed 20 Decembe 2013; Published 28 Janua y 2014
Academic Edi o : Gio a Pilla
Copy igh © 2014 Sand a Ononogbu e al. This is an open access a icle dis ibu ed unde he C ea i e Commons A ibu ion
License, which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly
ci ed.
Objec i e. To de e mine he associa ion be ween in ensi y o in o ma ion and communica ion echnology (ICT) usage and quali y
o sleep in school-aged child en du ing a school week. Me hods. In all 61 subjec s, 10–14 yea s o age, a quasiexpe imen al labo a o y
s udy whe e c i e ions o inclusion we e absence o p io medical condi ion and du a ion o ICT use. A po able de ice (Hol e
moni o )wasused omeasu ehea a e a iabili y(HRV)o e a24-hou pe iod,whileac i i ydia ywasused o eco din15-
minu e in e als ICT use and sleep and wake up ime. Low and high ICT use g oups we e o med acco ding o hei in ensi y o
ICT use. S a is ical analysis was done wi h wo independen samples es s and ac o ial ANCOVA. Resul s. The highe ICT use s
showed a lowe sleep ime s anda d de ia ion o no mal o no mal in e al (SDNN) measu es in compa ison o he low ICT use s.
Conclusion. The in ensi e ICT use was associa ed wi h poo e quali y o sleep indica ed by physiological measu es among child en
and adolescen s. Knowing he c ucial ole o heal hy sleep in his age, he esul s a e eason o conce n.
1. In oduc ion
The use o in o ma ion and communica ion echnology
(ICT) such as compu e use, in e ne su ing, and ideo
game playing enhances ce ain academic skills [1]. Howe e ,
he inc ease o in ense ICT usage among adolescen s [2]is
associa edwi had e see ec ssuchaspoo psychosocial
heal h s a us [3]. In addi ion, a educ ion in a e age sleep
du a ion due o delayed bed ime, ea ly waking up, sleep
dis up ion by nigh ma es, and sleep walking a e ela ed o
he use o ICT du ing he nigh ime [4]. The comp omise
o he es o a i e po en ial o sleep by a educ ion in i s
quan i y and quali y is ound o unde mine he day ime
unc ioning o adolescen s, mani es ed as i i abili y, day ime
sleepiness, and inabili y o concen a e o assimila e du ing
academic ac i i ies [5]. Long- e m ad e se heal h e ec s, like
poo sleep, a e ela ed o dep ession [6]. Sleeping pa e ns o
dep essed subjec s a e shown o be i egula compa ed wi h
he nondep essed subjec s [7]. In addi ion, he p obabili y
o de eloping anxie y o dep ession is much highe among
adolescen s wi h poo sleep [6]. Also an inc ease o body mass
index [8], abno mal glucose me abolism [9], p edisposi ion
o ce ain ca dio ascula diseases such as hype ension [10],
educ ion o immune esponsi eness o ce ain in ec ion [11],
inc eased isk o acciden s [12], and incidence o subs ance
abuse [13], agg a a ion o ce ain illnesses such as seizu e
diso de s [14], and psychia ic symp oms [15]a eassocia ed
wi h poo sleep among adolescen s. Violen gaming may
Hindawi Publishing Co po a ion
Sleep Diso de s
Volume 2014, A icle ID 315808, 6 pages
h p://dx.doi.o g/10.1155/2014/315808
2Sleep Diso de s
induce di e en au onomic esponses in boys compa ed o
non iolen gaming—du ing playing and du ing he ollowing
nigh —sugges ing di e en emo ional esponses [16].
Ca dio ascula pa ame e s such as hea a e, R-R in e -
al, and blood p essu e a y wi h sleep quali y [17]and
changes o hea a e a iabili y (HRV) e lec he hy hm
o sleep [18]. Unde no mal physiological condi ions, sleep
pe iod is domina ed by pa asympa he ic au onomic ac i -
i y, which po en ia es adequa e eco e y om he day ime
s ess. Howe e , a se e e s ess dis up s eco e y by aising
sympa he icac i i ydu ingsleepandHRVcanbeusedas
an indica o o sleep quali y [19]Thesqua e oo o he
mean squa ed di e ence o successi e no mal o no mal R-R
in e als in ime domain analysis o HRV in ECG ( MSSD)
co ela es o he high equency bands (HF, 0.15–0.40 Hz)
[20] and e lec s he pa asympa he ic ac i i y, which inc eases
du ing sleep. On he o he hand, he low equency band
(LF, 0.04–0.15 Hz) is ela ed o hea a e and blood p essu e,
which inc ease wi h sympa he ic dominance du ing day ime
[21].Those a ia ionscouldbein luencedbyage,sex,li es yle
and heal h s a us [22].
The aim o his s udy was o in es iga e whe he and how
he in ensi y o ICT usage among school-aged child en is
associa ed wi h he quali y o sleep du ing a school week,
indica ed by blood p essu e and ca diac au onomic con ol
assessed by HRV.
2. Me hods
2.1. Subjec s. The s udy design is a quasiexpe imen al lab-
o a o y s udy. Pa icipan s we e selec ed om hose 222
(123 gi ls) ou h and 256 (137 gi ls) se en h g ade s om
se en schools in he Tampe e egion o Finland who had
ea lie comple ed a su ey ques ionnai e. The age g oups
we e chosen acco ding o he de elopmen al saliency in
ansi ion om middle childhood o adolescence [23]. In
he su ey ques ionnai e pa icipan s had desc ibed hei
ICT use (mobile phones, compu e games, in e ne su ing,
and communica ion) including equency (g aded om 0 =
ne e ,1=less hanonceaweek,2=1-2daysaweek,3=3–5
imes a week o 4 = almos daily) and daily du a ion (g aded
om0=no a all,1=less hananhou ,2=1-2hou s,3=
3-4 hou s o 4 = o e 4 hou s), bo h du ing school days and
he weekends. A subg oup o 88 pupils was de i ed om he
su ey ques ionnai e sample o a end he labo a o y s udy
using pu posi e sampling me hod. Subjec s we e s a i ied
in o ou h and se en h g ade s (10- and 13-yea -olds) and
boys and gi ls. To maximize he di e ences wi h espec o
ICT use pa icipan s ep esen ing bo h low ICT use (ne e
o 1 o 2 days a week and less han 1 hou a any ime) and
high ICT use ( h ee o ou hou s o mo e, almos daily) we e
selec ed on he basis o he ques ionnai e da a. Al oge he 74
s uden s pa icipa ed in his s udy. The d opou s we e due o
e usals and unwillingness o p o ide in o med consen on
he pa o ei he he schoolchild en o hei pa en s.
2.2. P ocedu e. Be o e da a collec ion he app o al o he
E hical Commi ee o Pi kanmaa Hospi al Dis ic (Code
numbe R04050) was acqui ed. Pe mission was also ob ained
om he school p incipals. A each school an in o ma-
ion mee ing was held, usually o each pa icipa ing class
sepa a ely, and an in o ma ion le e was deli e ed bo h
o hepupilsselec ed o hes udyand hei pa en s.
W i en consen s o he pa icipa ion we e ob ained om
all child en willing o pa icipa e and hei pa en /gua dian.
The esea che ga e di ec ions o an ac i i y dia y and he
subjec s had possibili y o ask ques ions.
A each school, in a peace ul oom, he pa icipan s we e
gi en he Hol e moni o and ac i i y dia y wi h e bal and
w i en ins uc ions. Nex day child en e u ned he Hol e
moni o and he ac i i y dia y o he esea che . Da a we e
collec ed du ing h ee weeks, om he end o Ap il o he
beginning o May. The sampling day was always an o dina y
school day. As a ewa d o aking pa in he s udy, he
subjec s ecei ed a cinema icke each.
2.3. Measu es
2.3.1. In ensi y o ICT Use. Exposu e o ICT was measu ed
by use o a 24-hou ac i i y dia y du ing Hol e ’s eco dings.
High subjec compliance a e and da a eliabili y ha e been
ob ained wi h dia y me hod using objec i e measu es as
c i e ion, bo h among child en and adolescen s [24]. The
pa icipan s we e ins uc ed o eco d in 15-minu e in e als
he ime spen on di e en ICT ac i i ies wi h al e na i es:
(a) using mobile phone, o example, o phone calls o ex
messages, (b) playing mobile phone games, (c) playing TV
o console games, (d) playing compu e o In e ne games,
(e) using compu e o homewo k, w i ing, and so o h, ( )
using compu e o communica ion, and (g) gene al su ing
on he In e ne . Pa icipan s also eco ded hei sleeping
hou s, om going o bed un il waking up he nex mo ning.
To al ime spen on di e en ICT ac i i ies was calcula ed
summing up he 15 min in e als o each ac i i y.
2.3.2. Physiological Measu es. Pa icipan s we e equi ed o
ha e he moni o o a 24-hou du a ion and asked o
eco d hei bed ime and wake up ime. ECG eco dings
we e pe o med by h ee-channel ECG eco de du ing one
wo kday and sampling a e was 128 Hz (B aema DL700
Hol e Moni o , Bu ns ille, USA). All eco dings we e i s
scanned by an expe ienced nu se specialized in he anal-
yses o Hol e ’s eco dings. The ea e e e y eco ding was
escanned by a physician and medical specialis in clinical
physiology (HL). The HRV pa ame e s we e calcula ed using
a alida edso wa e o long e mECG eco dings(Cen u y
2000, BMS Inc., S . Louis, USA). The s anda d ime domain
measu es we e ob ained: s anda d de ia ion o all no mal
sinus R-R in e al (SDNN, ms), oo mean squa e o he
successi e no mal sinus R-R in e al di e ence ( MSSD, ms),
pe cen age o successi e no mal sinus R-R in e al longe
han 50 ms (pNN50), and he hea a e compu ed om
he mean cycle leng h o R-R complexes. The ime domain
pa ame e s we e used in u he e alua ion, because hey
a e less sensi i e o scanning e o s and a e p e e ed o
be used in hou ly analyses o long- e m eco dings ins ead
Sleep Diso de s 3
Table 1: Cha ac e is ics o s udy pa icipan s.
Va iables 𝑁(%) ICT use, 𝑛(%) SDNN (ms) MSSD (ms) BMI (kg/m2) MSBP (mm/hg) MDBP(mm/hg)
Low use s High use s 𝑃 alue Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD)
Gende
Males 29(48) 19(65) 10(35) 0.143 108.35 (27.60) 80.45 (25.62) 17.72 (2.38) 114.81 (9.67) 75.45 (8.37)
Females 32 (52) 15 (47) 17 (53) 105.35 (28.10) 72.58 (27.14) 19.91 (3.25) 114.58 (7.87) 72.95 (6.31)
Age
10-11 yea s 31 (51) 18 (58) 13 (42) 0.710 105.80 (26.41) 78.10 (26.77) 17.89 (2.79) 114.20 (8.45) 75.95 (7.45)
13-14 yea s 30 (49) 16 (53) 14 (47) 107.77 (29.40) 74.28 (26.57) 19.94 (3.03) 115.21 (9.04) 72.16 (6.90)
ICT: in o ma ion and echnology use; 𝑃: signi ican le el; SDNN: S anda d de ia ion o NN in e al; MSSD: oo mean squa e o successi e di e ence; BMI:
body mass index; MSDP: mean sys olic blood p essu e; MDBP: mean dias olic blood p essu e.
o spec al analyses [24]. The body mass index (BMI) was
calcula ed om he pa icipan ’s epo ed heigh and weigh
using weigh in kilog ams/heigh in me e s2 o mula. The
mean sys olic (MSBP) and mean dias olic (MDBP) blood
p essu e was measu ed. P io o commencemen o he s udy,
pa icipan s we e clinically checked by a specialized nu se
and by an expe ienced esea che o he au onomic ne ous
sys em o exclude any ca dio ascula o o he ch onic diso -
de s ha could con ound hea a e a iabili y eco ding.
2.4. S a is ical Analysis. To answe he esea ch ques ions,
he pa icipan s we e di ided in o wo g oups acco ding o
he in ensi y o ICT usage, ha is, he o al sum o hou s
spen in di e en ICT ac i i ies du ing Hol e ’s eco ding. Six
pa icipan s who had missing da a on some sleep hou s and
addi ional se en pa icipan s wi h Hol e ’s eco ding e o s
we e excluded om he analysis. In he inal sample he e
we e 61 pa icipan s, wi h 27 (44%) high ICT use s. In he
high use g oup, he o al ime o ICT usage o 16 pa icipan s
(62%) was one o less han 3 hou s, o six pa icipan s (21%) 3
o less han 6 hou s, and o i e pa icipan s (17%) 6–8 hou s.
The es o he pa icipan s (𝑁=34)we ecalledlowICT
use g oup who had no used ICT a all (72%) o had used
ICT only o less han one hou .
Di e ences by gende and age in quali y o sleep we e
es ed by chi squa ed es s. The ela ionship be ween he
in ensi y o ICT use and quali y o sleep was es ed wi h
independen samples 𝑡- es s among he g oups o high and
low ICT use s. Fu he analysis o he e ec s o gende , age,
and body mass index on he ou come a iables was done wi h
ac o ial ANCOVA. The da a analysis was ca ied ou wi h
SPSS 15.0 o Windows.
3. Resul s
O he pa icipan s 32 we e emales (53%). The numbe o
he pa icipan s in he younge age g oup (10-11 yea s) was
31 (51%), while in he olde g oup (13-14 yea s) he numbe
was 30 (49%) (Table 1). Among he high ICT use g oup, 52%
belonged o heolde ageg oup(13-14yea s).Pa icipan sin
he high ICT use g oup di e ed signi ican ly om he low
ICT use g oup bo h in he o al ime used ICT and in using
di e en o m o ICT excep o mobile phone use.
The mean sleep ime blood p essu e did no di e
be ween heICTuse g oups.Howe e , he ewasas a is-
ically signi ican di e ence in HRV be ween he ICT use
g oups, when assessed wi h mean sleep ime SDNN (𝑃=
0.035)(Table 2).Compa isono hemeandayandnigh
HRV alues be ween he ICT use g oups e ealed lowe
nigh alues, especially in olde (13-14 yea s) high ICT use s.
Ne e heless, analysis wi h MSSD (𝑃 = 0.07)showedno
s a is ically signi ican di e ence be ween he g oups. HRV
sleeppe iod oseslowe inhighICTuse sinbo hageg oups
compa ed o low ICT use s (Figu es 1and 2). Adjus men
o he in luence o body mass index, gende , and age wi h
ac o alANOVA esul edinnosigni ican e ec on he
ou come (Table 3).
4. Discussion
This s udy e ealed ha HRV o high ICT use s di e ed
om low use s du ing sleep on assessmen wi h SDNN.
High ICT use s had lowe le el o nigh changes in hea
a e a iabili y. SDNN ep esen s me ely he o e all cyclic
a ia iono HRVandisco ela ed odiu naloscilla iono
HRV. Low SDNN du ing he ea ly nigh e lec s he delayed
eadiness o he au onomic egula ion o sleep. The esul
hus con ibu es o ea lie indings showing ha in ensi e
ICT use has a nega i e impac on sleep pa e n in adul s
[25]. Ou ea lie esul s e ealed ha long pe iods o ICT
use we e ela ed o de e io a ed s ess egula ion, indica ed
by la ened co isol awakening esponse [26], which is in
conco dance wi h he cu en esul s. I can be also o sugges
ha among heal hy child en he in ensi y o agal eco e y is
good a e he sympa he ic o e d i e a enua ing he cyclic
componen o HRV is blun ed. Howe e , simila o o he
s udies [27], we did no ind associa ion be ween ICT and
sleep quali y when HRV is assessed wi h MSSD. Taking
accoun o he ac ha MSSD is epo edly a mo e sensi i e
indica o o pa asympa he ic ac i i y [19], he in luence o
he small sample size on his ou come canno be o e uled.
Some mechanisms ha e been sugges ed o explain how
o whyICTusageisassocia edwi hpoo sleep.Theyinclude
di ec enc oachmen o sleep ime by ICT use h ough i s
inc eased accessibili y, a o dabili y, addic i e endencies [28,
29], physiological changes induced by emo ional eac ion o
ac i i ies [27], supp ession o mela onin sec e ion [8]and
4Sleep Diso de s
Table 2: Unadjus ed means o SDNN (ms) and MSSD (ms) by ICT use.
Va iables ICT use Mean di e ence (95% CI) 𝑃 alue
Low use s
Mean (SD)
High use s
Mean (SD)
SDNN 114.12 (27.12) 99.05 (27.23) 15.07 (1.06–29.09) 0.035
MSSD 82.61 (27.14) 69.87 (25.27) 12.73 (−0.85–26.32) 0.066
SDNN: S anda d de ia ion o NN in e al; MSSD: oo mean squa e o successi e di e ence; ICT: in o ma ion and echnology use; 𝑃:signi ican le el.
Bold means s a is ically signi ican .
Table 3: Means o SDNN (ms) and MSSD (ms) by ICT use, adjus ed o gende , age and BMI.
Va iables 𝑁SDNN MSSD
Mean (SD) 𝐹s a is ic 𝑃 alue Mean (SD) 𝐹s a is ic 𝑃 alue
ICT use
Low use s 34 114.12 (27.12) 11.17 0.002 82.61 (27.14) 7.84 0.008
High use s 27 99.05 (27.23) 69.87 (25.27)
SDNN: S anda d de ia ion o NN in e al; MSSD: oo mean squa e o successi e di e ence; ICT: in o ma ion and echnology use; BMI: body mass index;
𝑃:signi ican le el.
Bold means s a is ically signi ican .
09: 00D1
11:00D1
13: 00D1
15:00D1
17: 00D1
19: 00D1
21: 00D1
23: 00D1
01:00D2
03: 00D2
05:00D2
07:00D2
1000
900
800
700
600
500
400
300
200
100
0
Age 2L=13-14 yea s
Age 2H=13-14 yea s
Age 1L=10-11 yea s
Age 1H=10-11 yea s
Low ICT use s (n=16)
High ICT use s (n=14)
Low ICT use s (n=18)
High ICT use s (n=13)
Figu e 1: Mean HRV (SDNN, ms) du ing a school day and a nigh .
educ ion in physical ac i i y [30]. Ne e heless, physical
ac i i y has also been shown o be insigni ican in ce ain
s udies [30]. Fu he , ICT usage has been ound o inc ease
weigh among adolescen s as he displacemen o physical
ac i i y wi h ICT usage is associa ed wi h a aise in body
mass index [22]. In his s udy, we con olled he BMI in he
analysis, and i was no associa ed wi h he quali y o sleep,
i espec i e o gende and age.
The c oss-sec ional design o his s udy limi s he abili y
o make causal in e ences. I is di icul o ule ou sleep
dis u bance as an ac ual p ecipi a o o high ICT usage.
The esul o his s udy will need u he e alua ion wi h a
p ospec i e s udy wi h a andomized con olled design in
which child en a e andomized o ei he a high ICT g oup
o a con ol g oup, and also hei sleep quan i y and quali y
500
450
400
350
300
250
200
150
100
50
0
09: 00D1
11:00D1
13: 00D1
15:00D1
17: 00D1
19: 00D1
21: 00D1
23: 00D1
01:00D2
03: 00D2
05:00D2
07:00D2
Age 2L=13-14 yea s
Age 2H=13-14 yea s
Age 1L=10-11 yea s
Age 1H=10-11 yea s
Low ICT use s (n=16)
High ICT use s (n=14)
Low ICT use s (n=18)
High ICT use s (n=13)
Figu e 2: Mean HRV ( MSSD, ms) du ing a school day and a nigh .
should be analyzed. In addi ion, po en ial con ounde s such
as sleep en i onmen , die , pa en al socioeconomic s a us,
physical ac i i y, and o he ac o s ha could a ec he s a e o
he au onomic ne ous sys em du ing sleep should be mea-
su ed and adjus ed o mo e e ec i ely. Ano he limi a ion is
he sel - epo s ega ding in ensi y o ICT use, sleep du a ion,
and wake up ime, which wa an s he eliabili y o he da a.
The accu acy o he da a can be imp o ed by employing a
mo e comp ehensi e me hod in ob aining his in o ma ion.
5. Conclusion
Thiss udyshows ha hein ensi yo in o ma ionand
communica ion echnology use by child en and adolescen s
seems o in e e e wi h he quali y o sleep du ing a school
Sleep Diso de s 5
week. The pa icipan s wi h low ICT use seem o sleep
be e han he high use s. High amoun o ICT use by
child en and adolescen s may des oy good sleep pa e n.
In pa icula he sympa he ic o e d i e may con inue o
heea lysleepandcauseadelayinpa asympa he ic eco -
e y. The leng h o es o a i e sleep migh sho en, which
is a heal h isk o physical and cogni i e heal h among
child en. In expe imen al condi ions p olonged ideo game
playing caused dis up ion o adolescen sleep [31]. Because
sleep is e y impo an o adolescence g ow h, cogni i e
unc ioning, and physical heal h [32], he esul s a e o
conce n. Fu he s udies a e needed wi h la ge numbe
o pa icipan s, comp ehensi e accoun o o he o ms o
ICT use beyond compu e use, in e ne su ing, and ideo
game playing o enhance a mo e conclusi e esul o he
e ec s o ICT use on child en’s and adolescen s’ sleep. The
use o ac i i y moni o s would inc ease he possibili y o
assess he ac ual sleeping ime. Resea ch is also needed o
explo e whe he he amoun o ICT usage h ough in e e ing
es o a i e sleep is ela ed o adolescen s’ school pe o mance
(such as a en ion, pe sis ence, o memo y) o beha iou
p oblems.
Con lic o In e es s
The au ho s decla e ha he e is no con lic o in e es s
ega ding he publica ion o his pape .
Acknowledgmen s
This esea ch was suppo ed by he G an s om he Academy
o Finland (201669) and he In o ma ion Socie y Ins i u e o
he Uni e si y o Tampe e and he Tampe e Uni e si y o
Technology (16-01). The au ho s a e g a e ul o he schools o
coope a ion and o he child en and adolescen s who pa ic-
ipa ed in he s udy. They hank Heli Sis onen, Jukka Koskelo,
and Ma ja a Radecki o assis ance in da a collec ion.
Re e ences
[1]K.Sub ahmanyam,P.G een ield,R.K au ,andE.G oss,
“The impac o compu e use on child en’s and adolescen s’
de elopmen ,” Jou nal o Applied De elopmen al Psychology, ol.
22,no.1,pp.7–30,2001.
[2] S a is ics Finland, F om Ci izen o Eci izen: Resul s om S a is-
ical Su eys abou Finns’ Use o ICT in 1996–2005,Re iews,no.
3, S a is ics Finland, 2006.
[3] M.Ma he s,L.Can e o d,T.Olds,K.Heske h,K.Ridley,and
M. Wake, “Elec onic media use and adolescen heal h and well-
being: c oss-sec ional communi y s udy,” Academic Pedia ics,
ol. 9, no. 5, pp. 307–314, 2009.
[4] G. Mesqui a and R. Reim˜
ao, “Nigh ly use o compu e by
adolescen s: i s e ec on quali y o sleep,” A qui os de Neu o-
Psiquia ia, ol.65,no.2,pp.428–432,2007.
[5] R. E. Dahl, “The impac o inadequa e sleep on child en’s
day ime cogni i e unc ion,” Semina s in Pedia ic Neu ology,
ol.3,no.1,pp.44–50,1996.
[6] E.O.Johnson,H.D.Chilcoa ,andN.B eslau,“T oublesleeping
and anxie y/dep ession in childhood,” Psychia y Resea ch, ol.
94, no. 2, pp. 93–102, 2000.
[7]E.Heins,C.Sei z,J.Sch
¨
uz e al., “Bed ime, ele ision and
compu e habi s o p ima y school child en in Ge many,”
Gesundhei swesen, ol.69,no.3,pp.151–157,2007.
[8] S. Higuchi, Y. Mo ohashi, Y. Liu, M. Aha a, and Y. Kaneko,
“E ec s o VDT asks wi h a b igh display a nigh on mela-
onin, co e empe a u e, hea a e, and sleepiness,” Jou nal o
Applied Physiology, ol.94,no.5,pp.1773–1776,2003.
[9] K. Spiegel, R. Lep oul , and E. an Cau e , “Impac o sleep deb
on me abolic and endoc ine unc ion,” The Lance , ol.354,no.
9188,pp.1435–1439,1999.
[10] S.Ja ahe i,A.S o e -Isse ,C.L.Rosen,andS.Redline,“Sleep
quali y and ele a ed blood p essu e in adolescen s,” Ci cula ion,
ol. 118, no. 10, pp. 1034–1040, 2008.
[11] Y. Ma sui, K. Sai o, T. Nakakuma, and K. Michi, “S udies on
he hos ac o s in he ou b eak o odon ogenic in ec ion— he
backg ound ac o so pa ien sand hee ec o se uma e sleep
dep i a ion on PMN chemo axis,” Kansenshogaku Zasshi, ol.
65, no. 1, pp. 47–53, 1991.
[12] M. M. Ohayon, M. Caule , P. Philip, C. Guilleminaul , and
R. G. P ies , “How sleep and men al diso de s a e ela ed o
complain s o day ime sleepiness,” A chi es o In e nal Medicine,
ol. 157, no. 22, pp. 2645–2652, 1997.
[13]E.O.JohnsonandN.B eslau,“Sleepp oblemsandsubs ance
use in adolescence,” D ug and Alcohol Dependence, ol.64,no.
1,pp.1–7,2001.
[14] S. Liamsuwan, P. G a an-Smi h, E. Fagan, A. Bleasel, and J.
An ony, “The alue o pa ial sleep dep i a ion as a ou ine
measu e in pedia ic elec oencephalog aphy,” Jou nal o Child
Neu ology, ol.15,no.1,pp.26–29,2000.
[15] E. J. Paa onen, F. Almq is , T. Tamminen e al., “Poo sleep
and psychia ic symp oms a school: an epidemiological s udy,”
Eu opean Child and Adolescen Psychia y, ol. 11, no. 1, pp. 10–
17, 2002.
[16] M. I a sson, M. Ande son, T. ˚
Ake s ed , and F. Lindblad,
“Playing a iolen ele ision game a ec s hea a e a iabili y,”
Ac a Paedia ica, ol. 98, no. 1, pp. 166–172, 2009.
[17] A. Mon i, C. Medigue, H. Nedelcoux, and P. Escou ou, “Au o-
nomic con ol o he ca dio ascula sys em du ing sleep in
no mal subjec s,” Eu opean Jou nal o Applied Physiology, ol.
87, no. 2, pp. 174–181, 2002.
[18] Z. Zhuang, X. Gao, and S. Gao, “The ela ionship o HRV
o sleep EEG and sleep hy hm,” In e na ional Jou nal o
Neu oscience, ol. 115, no. 3, pp. 315–327, 2005.
[19] N. Michels, E. Clays, M. de Buyze e, B. Vanaels , S. de Henauw,
and I. Sioen, “Child en’s sleep and au onomic unc ion: low
sleep quali y has an impac on hea a e a iabili y,” Sleep, ol.
36, no. 12, pp. 1939–1946, 2013.
[20] Task Fo ce, “Hea a e a iabili y: s anda ds o measu emen ,
physiological in e p e a ion, and clinical use. Task o ce o he
Eu opean socie y o ca diology and he No h Ame ican socie y
o pacing and elec ophysiology,” Ci cula ion, ol.93,no.5,pp.
1043–1065, 1996.
[21] M. Ca ing on, M. Walsh, T. S ambas, J. Kleiman, and J. T inde ,
“The in luence o sleep onse on he diu nal a ia ion in ca diac
ac i i y and ca diac con ol,” Jou nal o Sleep Resea ch, ol.12,
no.3,pp.213–221,2003.
[22] R. B. Singh, G. Co n´
elissen, A. Weydahl e al., “Ci cadian hea
a e and blood p essu e a iabili y conside ed o esea ch and
pa ien ca e,” In e na ional Jou nal o Ca diology, ol.87,no.1,
pp. 9–28, 2003.
[23] L. S einbe g and A. S. Mo is, “Adolescen de elopmen ,”
Annual Re iew o Psychology, ol.52,pp.83–110,2001.

6Sleep Diso de s
[24] F. Lomba di and P. S ein, “O igin o hea a e a iabili y and
u bulence: an app aisal o au onomic ca dio ascula unc ion,”
F on ie s in Physiology, ol.2,a icle95,2011.
[25] L. G. P. M. an Amels oo , E. G. Schou en, A. C. Maan,
C. A. Swenne, and F. J. Kok, “Occupa ional de e minan s o
hea a e a iabili y,” In e na ional A chi es o Occupa ional and
En i onmen al Heal h, ol. 73, no. 4, pp. 255–262, 2000.
[26] M. Wallenius, A. Hi onen, H. Lindholm e al., “Sali a y co -
isol in ela ion o he use o in o ma ion and communica ion
echnology (ICT) in school-aged child en,” Psychology, ol.1,
pp. 88–95, 2010.
[27] A. H. Ga de, B. Lau sen, A. H. Jø gensen, and B. R. Jensen,
“E ec s o men al and physical demands on hea a e a i-
abili y du ing compu e wo k,” Eu opean Jou nal o Applied
Physiology, ol.87,no.4-5,pp.456–461,2002.
[28] J. Owens, R. Maxim, M. McGuinn, C. Nobile, M. Msall, and
A. Ala io, “Tele ision- iewing habi s and sleep dis u bance in
school child en,” Pedia ics, ol.104,no.3,a iclee27,1999.
[29] J. G. Johnson, P. Cohen, S. Kasen, M. B. Fi s , and J. S. B ook,
“Associa ion be ween ele ision iewing and sleep p oblems
du ing adolescence and ea ly adul hood,” A chi es o Pedia ics
and Adolescen Medicine, ol.158,no.6,pp.562–568,2004.
[30]S.J.Ma shall,S.J.H.Biddle,T.Go ely,N.Came on,and
I. Mu dey, “Rela ionships be ween media use, body a ness
andphysicalac i i yinchild enandyou h:ame a-analysis,”
In e na ional Jou nal o Obesi y, ol.28,no.10,pp.1238–1246,
2004.
[31] D. L. King, M. G adisa , A. D ummond e al., “The impac
o p olonged iolen ideo-gaming on adolescen sleep: an
expe imen al s udy,” Jou nal o Sleep Resea ch, ol.22,no.2,pp.
137–143, 2013.
[32] R. G ube , “Making oom o sleep: he ele ance o sleep o
psychology and he a ionale o de elopmen o p e en a i e
sleep educa ion p og ams o child en and adolescen s in he
communi y,” Canadian Psychology, ol.54,no.1,pp.62–71,2013.