Association between Information and Communication Technology Usage and the Quality of Sleep among School-Aged Children during a School Week

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). 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