Sleep-Wake Cycle, Daytime Sleepiness and Attention Components

MIND, BRAIN, AND EDUCATION

Sleep–Wake Cycle, Daytime Sleepiness, and Attention Components in Children Attending Preschool in the Morning and Afternoon Shifts Aline S. Belísio1, Fernanda F. Kolodiuk1, Fernando M. Louzada2, Pablo Valdez3, and Carolina V. M. Azevedo1

ABSTRACT— Children tend to sleep and wake up early and to exhibit daytime sleep episodes. To evaluate the impact of school start times on sleepiness and attention in preschool The sleep–wake cycle plays an important role in the cog- children, this study compared the temporal patterns of nitive processes of learning, such as attention (Gillberg sleep, daytime sleepiness, and the components of attention & Akerstedt, 1998; Thomas et al., 2000; Valdez, Reilly, & between children aged 4–6 years that study in the morning Waterhouse, 2008) and memory consolidation (Drosopou- (n = 66) and the afternoon (n = 144) shifts. The former get los, Schulze, Fischer, & Born, 2007; Wilhelm, Diekelmann, & up 1 hr and 30 min earlier on weekdays and show lower effi- Born, 2008), in addition to contributing to restoring phys- ciency on the sustained attention task than those who study iological and biochemical processes (Benington & Heller, intheafternoon.Thus,themorningshiftwasassociatedwith 1995; Ramm & Smith, 1990) and maintaining energy bal- a reduction in nighttime sleep, which might have a nega- ance (Spiegel, Tasali, Penev, & Van Cauter, 2004; Taheri, tive effect on children’s performance in the morning, causing Lin, Austin, Young, & Mignot, 2004; Taveras, Rifas-Shiman, higher levels of daytime sleepiness and a decline in sustained Oken, Gunderson, & Gillman, 2008). attention. Because only one parameter of one component of Sleephasanessentialfunctionincognitiveandmotor attention was negatively affected, further studies are needed development, especially in children, who are still maturing. to confirm this effect on cognition. A number of changes inherent to this age group occur in the sleep–wake cycle as a result of the maturation process of the nervous system. Children tend to go to bed and wake up early; that is, they have a tendency to morningness (Jenni & Carskadon, 2005). Total sleep duration declines progressively with age, along with an increase in nighttime 1Laboratório de Cronobiologia, Programa de Pós-Graduação em Psi- sleep and a decrease in daytime sleep episodes (naps), which cobiologia, Departmento de Fisiologia, Universidade Federal do Rio are frequent in young children (Acebo et al., 2005; Jenni & Grande do Norte 2Departmento de Fisiologia, Universidade Federal do Paraná Carskadon, 2005; Louzada, Orsoni, Mello, Benedito-Silva, 3Laboratório de Psicofisiologia, Departmento de Psicologia, Universi- & Menna-Barreto, 1996; Menna-Barreto, Isola, Louzada, dad Autónoma de Nuevo León Benedito-Silva, & Mello, 1996). Address correspondence to Carolina V.M. Azevedo, Caixa Postal 1511, The sleep–wake cycle is influenced by a series of peculiari- CEP 59078-970, Natal, RN, Brazil; e-mail: [email protected] ties in the child’s social environment, such as behavior before

(drinking milk, going to the bathroom, listening to stories, tonic alertness, phasic alertness, selective attention, and sus- and use of favorite object) and during sleep (co-sleeping tained attention. Tonic alertness is the ability to respond to or bed-sharing). These sleep patterns change when chil- changes in the environment; phasic alertness is the ability to dren start school and the school start times modulate the respond to environmental changes preceded by a warning sleep–wake cycle, which may lead to daytime sleepiness and signal; selective attention is the ability to process a sensory compromise academic performance (Beltramini & Hertzig, event and ignore other events; and sustained attention is the 1983; Li et al., 2008; Reimão, Souza, Medeiros, & Almirão, ability to respond to the environment for a certain interval 1998; Reimão et al., 1999; Silva et al., 2005). of time. Despite exhibiting a tendency to morningness, children Attention may be modulated by time of day (Valdez, between 3 and 10 years of age who study in the morning and Ramírez, García, Talamantes, & Cortez, 2010) and sleep wake up and go to bed earlier sleep less during the week than deprivation (Rodríguez, 2011), which leads to a decline in on the weekend (Adam, Snell, & Pendry, 2007; Belísio, 2010; attention levels and may compromise school learning. With El-Sheikh, Buckhalt, Mize, & Acebo, 2006; Louzada et al., the changes in current lifestyles, children go to sleep late on 1996; Mello, Isola, Louzada, & Menna-Barreto, 1996; Silva weekdays and wake up early to go to school. This results et al., 2005). Moreover, children aged between 7 and 10 years in partial deprivation and irregular sleeping hours and, in who study in the morning show greater frequency of naps, in turn, daytime sleepiness, primarily in children who study in addition to sleeping approximately 1 hr more than children the morning. However, the relationship between the com- who study in the afternoon (Silva et al., 2005). Thus, children ponents of attention, sleep pattern, and daytime sleepiness who study in the morning experience acute sleep deprivation in children aged between 4 and 6 years remains unknown, on weekdays that is generally compensated for on weekends. as is the effect of school start times on these parameters. The An increase of around 26–29 min in time spent in bed during present study aimed to compare sleep habits, daytime sleepi- the weekend was observed in children aged between 4 and ness, and the components of attention in preschool children 6 (Belísio, 2010) and 8 and 10 years (Anacleto, 2011). This as a function of school shift (morning and afternoon). slight difference between school days and weekends is likely caused by a natural predisposition to go to sleep and wake up early, characteristic of this age group, and the influence METHODS of parents in determining the sleep–wake schedule of their children (Iglowstein, Jenni, Molinari, & Largo, 2003; Meijer, The study was approved by the Onofre Lopes University Habekothé, & Van Den Wittenboer, 2000). Hospital Research Ethics Committee (CEP/HUOL protocol The shorter nighttime sleep and irregular sleep times no. 554/11). The sample consisted of 210 children of both related to the morning shift would not be expected in chil- sexes from the morning (n = 66) and afternoon (n = 144) dren, who naturally wake up earlier. However, in addition to shifts, aged between 4 and 6 years, from the city of Natal, causing changes in sleep patterns, school start time may lead Brazil (Latitude: 5∘ 47′ 42″ S and longitude: 35∘ 12′ 34″ to high levels of daytime sleepiness (Silva et al., 2005) and low W). Seven private schools took part in the research. At all attention levels (Valdez et al., 2008), which may negatively schools, morning classes start at 7 a.m. and finish at 11 a.m., interfere with the child’s learning process. while afternoon classes are between 1 p.m. and 5 p.m. Among the cognitive processes affected by sleep depriva- The following inclusion criteria were adopted: preschool tion we highlight the attention, which is the ability to select children (1) of both sexes aged between 4 and 6 years, (2) and respond specifically to a stimulus in the environment for enrolled in private schools in Natal, who study in the morn- a certain period of time. This cognitive process can be stud- ing or afternoon shift, and (3) whose parents or guardians ied using neuropsychological models (Cohen & O’Donnell, gave their informed consent. 1993; Mirsky, Anthony, Duncan, Ahearn, & Kellam, 1991; The exclusion criteria were (1) sleep disturbance or any Posner & Rafal, 1987; Valdez et al., 2005), which makes it health problem, such as allergies, sinusitis, hypertension or possible to analyze the brain areas involved, as well as ver- neurological disorders, and (2) incomplete questionnaires. ify the presence of circadian rhythms in the different atten- Sleep habits were characterized using the sleep habits tion components and the impact of sleep deprivation in this questionnaire applied by Wey (2002), to which were added process. questions regarding bedtime rituals (Owens, Spirito, & The model used in the present study was proposed by McGuinn, 2000) and information about parents’ schooling Valdez et al. (2005) and is based on the Posner and Rafal level. (1987) model, with some changes, namely in defining atten- Economic level was characterized using a questionnaire tion components and assessing each component of the atten- adapted from the model proposed by the Brazilian Economic tion process. In the model proposed by Valdez et al. (2005), Classification Criterion (CCEB) of the National Association attention is divided into four components denominated of Research Companies (Associação Nacional de Empresas

Volume 11—Number 1 11 Sleep, Sleepiness, and Attention in Children

de Pesquisa, 2008). This classification stratifies the popula- computer screen for 200 ms. There were a total of 100 stim- tion into eight economic classes (A1, A2, B1, B2, C1, C2, D, uli: 70 green hearts, 20 red circles, and 10 blue stars (each andE),basedonresponsesrelatedtopossessionofgoods blue star was preceded by an arrow). The images were dis- and the head of the family’s schooling level. Classification in played randomly. Responses were recorded on a keyboard. points makes it possible to infer mean family income. The child had to press key 1 when a green heart appeared, An adapted version of the sleep diary (Wey, 2002) was key 2 when a red circle appeared, and key 3 when a blue used to characterize sleep pattern for 9 consecutive days star appeared. Each key was covered with an image sticker (from Friday night to Monday morning). The following out- related to the requested response: key 1 with a green heart, comes were obtained from the sleep diary: (1) sleep at night key 2 with a red circle, and key 3 with a blue star. A 100-ms (bedtimes, wake up times, and time in bed), (2) daytime naps feedback sound (beep) was presented after each correct (frequency of children who doze during the week and week- response. end, duration, and times of start and end); (3) the activity According to the attention model proposed by Pos- before bedtime (options: watching TV, playing, homework, ner and Rafal (1987) and Valdez et al. (2005), responses or other); (4) parent regulation of bedtime (options: the par- to the green heart (a frequent stimulus) indicated tonic ents regulated the bedtime, or the child goes to bed sponta- alertness, the red circle (a different, infrequent, specific neously); (5) the way of waking up (options: spontaneously, stimulus) indicated selective attention, the blue star (a stim- by an alarm clock, or called by someone); and (6) the rea- ulus preceded by an arrow that acted as a warning signal) son for wake up time (options: school starting time, physical indicated phasic alertness, while changes in performance activities or sports, travel, promenade, or other). Parents or during the task indicated sustained attention. Task duration guardians completed the questionnaires on sleep habits, eco- was 5 min. nomic classification, and the sleep diary with information on Training sessions were held on Monday and Tuesday, the children’s sleep habits. during which the task was explained to the children as a In order to assess the sleepiness levels, an adapted version game in which they would have to press certain keys corre- (Belísio, 2014) of the Pictorial Sleepiness Scale Based on Car- sponding to the figures displayed on the screen. Data from toon Faces of Maldonado (Maldonado, Bentley, & Mitchell, this training were excluded from the analysis. The task was 2004) was applied during 6 days, from Monday to Friday applied on three weekdays (Wednesday, Friday, and Mon- and the next Monday, consecutively. The data collected on day) between 8 a.m. and 9 a.m. to children of the morning the first Monday were excluded from analysis to reduce the shift and between 2 p.m. and 3 p.m. to their afternoon coun- effects of a new person in the school environment. Dur- terparts. The children responded to the Maldonado daytime ing questionnaire application children were asked how they sleepiness scale before the task was applied. were feeling at that moment, that is, whether they felt sleepy or not. Next, the children indicated the face on the scale that best represented how they were feeling at the time. The scale DATA ANALYSIS was applied between 8 a.m. and 9 a.m. and 2 p.m. and 3 p.m. to children of the morning and afternoon shifts, respectively. Sleep habits (co-sleeping, room sharing, and bedtime ritu- A continuous performance task (CPT) was used to assess als) and economic classification of children in the morning the components of attention in the children. The CPT and afternoon shifts were compared using the chi-square uses frequent stimuli to track the child’s attention, but test (χ2). also requires responses to infrequent and specific stimuli The sleep parameters obtained from the sleep diary (the that occur at random intervals (Riccio, Reynolds, Lowe, & bed and wake up times, time spent in bed at night, and total Moore, 2002). A CPT, a simple task that continuously mon- time spent in bed every 24 hr, the latter obtained from the itors behavior, is sensitive to sleep deprivation and circa- sum of the time spent in bed at night and the duration of dian rhythms (Gill, Haerich, Westcott, Godenick, & Tucker, nap) were compared between shifts by analysis of variance 2006; Mullaney, Kripke, Fleck, & Johnson, 1983; Valdez et al., (ANOVA) for repeated measures and Bonferroni’s posttest. 2005). It has been demonstrated that this task measures each Daytime sleepiness, irregularity of bed and wake up times component of attention and the indices of sustained atten- (calculated from the standard deviation in bed and wake tion (Smith, Valentino, & Arruda, 2002; Valdez et al., 2005, up times, respectively), and the parameters related to naps 2010). (start time, end time, and duration) were compared between The CPT used in the present study was an adapted ver- shifts using the Mann–Whitney test. Comparative analysis sion for preschool children (Belísio, 2014) of that applied of nap-related parameters between week and weekend days on university students by Valdez et al. (2005). In this task, was conducted using the Wilcoxon test. three images familiar to children (a green heart, a red circle, In relation to attention task data, the Mann–Whitney and a blue star) were used. Each image was displayed on a test was applied to compare the percentage and reaction

12 Volume 11—Number 1 Aline S. Belísio et al.

time for correct responses in each attention component Economic Classiﬁcation (tonic alertness, selective attention, phasic alertness, and Most of the morning shift children belonged to classes A2 sustained attention—concentration); sequences of hits and (24%) and B1 (44%), whereas those from the afternoon errors during the attention task (obtained by a sequence shift were in B1 (22%) and B2 (40%) (X2 = 37.32, of hits and errors over the course of the test; e.g., 1 hit, 2 p < .0001). hits, 3 hits, until achieving 100 hits, which refers to the total number of stimuli in the task), and omissions (no response Children’s Activity Before Bedtime to the stimulus) between children who study in the morning A higher percentage of children who studied in the morning and afternoon. watch TV on Monday (51%; χ2 = 30.74; p < .0001), Tuesday Furthermore, the time on task stability, which is an index (51%; χ2 = 13.72; p = .0174), and Friday (72%; χ2 = 37.13; of sustained attention, was obtained from a linear regres- p < .0001), whereas a greater percentage of those who sion of the percentage of correct responses and reaction studied in the afternoon watch TV on Wednesday (60%; time in all attention components throughout the task (tonic χ2 = 11.73; p = .0386), Thursday (51%; χ2 = 27.47; p < .0001), alertness, selective attention, and phasic alertness). Nega- and Saturday (50%; χ2 = 31.40; p < .0001). tive values represent a decrease in correct answers/reaction time over the task. On the other hand, positive values represent an increase in these parameters across the task. Parent Regulation of Children’s Bedtime The Mann–Whitney test was used to compare the indices A greater percentage of morning shift students have their between the shifts. A signiﬁcance level of 5% was set in all bedtime regulated by their parents on Tuesday (52%; 2 2 tests applied. χ = 8.48; p = .0035), Wednesday (50%; χ = 17.36; p < .0001), Thursday (50%; χ2 = 1107; p = .0008), and Saturday (49%; X2 = 10.55; p = .0011), whereas this occurred only on Friday (43%; χ2 = 6.55; p = .0104) for children who study in the afternoon. RESULTS

Co-Sleeping, Room Sharing and Bedtime Ritual Reason for Wake Up Time There was no diﬀerence in the frequency of co-sleeping, A higher percentage of parents of children who study room sharing, or bedtime rituals between children who in the morning report school as the reason for wake up study in the morning and afternoon (χ2, p > .05) (Table 1). time on weekdays (Monday: 97%; χ2 = 401.20; Tuesday:

Table 1 Frequency of Co-Sleeping, Room-Sharing, and Bedtime Rituals During the Week in Children Who Study in the Morning and Afternoon Shifts (χ2 test, p > .05).

Morning Afternoon Frequently Sometimes Rarely Frequently Sometimes Rarely Behaviors % % % % % % χ2 p Co-sleeping and room-sharing Co-sleeping with brother/sister 5.0 4.0 91.0 7.0 7.0 86.0 2.06 .3561 Co-sleeping with parents/guardians 41.0 27.0 33.0 41.0 27.0 32.0 0.40 .9799 Room-sharing with brother/sister 20.0 3.0 76.0 20.0 5.0 75.0 0.52 .7694 Room-sharing with parents/guardians 29.0 10.0 59.0 26.0 12.0 61.0 0.67 .7126 Sleeping alone 31.0 17.0 53.0 30.0 16.0 54.0 0.09 .9520 Bedtime rituals Drinking milk 44.0 22.0 33.0 40.0 24.0 35.0 .73 .6914 Listening to stories 17.0 51.0 32.0 18.0 50.0 32.0 0.09 .9531 Going to the bathroom 64.0 27.0 9.0 58.0 32.0 10.0 1.26 .5319 Requires the parents in the room 57.0 25.0 18.0 61.0 23.0 17.0 0.55 .7577 Sleeping with the lights on 25.0 14.0 62.0 23.0 19.0 59.0 1.48 .4752 Using a special object 40.0 15.0 45.0 32.0 18.0 50.0 3.38 .1836 Others 29.0 19.0 50.0 38.0 15.0 46.0 3.73 .1543

Note: Frequently = behavior occurs 5 or more times during the week; Sometimes = behavior occurs 2–4 times during the week; rarely = behavior occurs once or never during the week.

Volume 11—Number 1 13 Sleep, Sleepiness, and Attention in Children

Fig. 1. Mean and standard deviation of bedtime, wake up time, and time in bed at night, and total time in bed (night and daytime nap) during the week in children of morning and afternoon shifts (ANOVA, *p < .05).

92%; χ2 = 600.61; Wednesday: 94%; χ2 = 947.41; Thurs- earlier on Monday, Tuesday, and Thursday than on Saturday 2 2 < day: 86%; χ = 342.08; Friday: 80%; χ = 358.96; p < .0001) (F(6.462) = 8.47; Bonferroni, p .0001) (Figure 1). compared to those who study in the afternoon (Monday: Children from the morning shift woke up about 1 hr 18%; χ2 = 401.20; Tuesday: 12%; χ2 = 600.61; Wednesday: and 30 min earlier from Monday to Friday compared to 8%; χ2 = 947.41; Thursday: 17%; χ2 = 342.08; Friday: 14%; those who studied in the afternoon, with no difference on 2 < χ = 358.96; p < .0001). weekends (F(6.450) = 7.06; Bonferroni, p .0001). Children in the morning shift woke up earlier during the week than on Saturday and Sunday (F = 11.34; Bonferroni, p < .0001), Way of Waking Up (6.450) whereas those in the afternoon shift showed no difference A greater number of children who study in the morn- between weekdays and weekends (F = 11.34; Bonfer- ing are woken up by someone on weekdays (Monday: (6.450) roni, p < .0001) (Figure 1). 76%; χ2 = 180.28; Tuesday: 76%; χ2 = 128.92; Wednesday: Morning shift students spent 1 hr less in bed on Monday 68%; χ2 = 140.76; Thursday: 76%; χ2 = 123.17; Friday: 63%; and Sunday nights than their afternoon shift counterparts χ2 = 193.39, p < .0001), whereas more children who study (ANOVA F = 7.01; Bonferroni, p < .0001). Time spent in the afternoon wake up spontaneously on these days (6.456) in bed for children who studied in the morning was shorter (Monday: 78%; χ2 = 180.28; Tuesday: 73%; χ2 = 128.92; on Tuesday, Thursday, and Sunday than on Saturday. On Wednesday: 79%; χ2 = 140.76; Thursday (72%; χ2 = 123.17; the other hand, children who studied in the afternoon spent Friday: 82%; χ2 = 193.39, p < .0001). more time in bed from Monday to Friday than on Saturday < (ANOVA F(6.456) = 1.10; Bonferroni, p .0001) (Figure 1). Temporal Sleep Patterns There was no difference in the irregularity of bed-

Bedtimes did not diﬀer between shifts (F(6.462) = 0.97, times (Mann–Whitney, p = .9588) and wake up times p = .4438). Nevertheless, children in the morning shift usu- (Mann–Whitney, p = .4067) between the shifts (Table 2). ally went to bed 40 min earlier than those who studied in Children who studied in the morning napped more fre- the afternoon. Children who studied in the morning went quently on weekdays and weekends (χ2, p < .0001) and to bed earlier on Monday and Wednesday than on Saturday, naps were longer on weekdays (Mann–Whitney, p = .008) whereas those who studied in the afternoon went to bed (Table 2). It is important to underscore that the children

14 Volume 11—Number 1 Aline S. Belísio et al.

Table 2 Irregularity in Bedtime and Wake Up Times, Frequency of Children Who Nap, Times of Start, End, and Duration of Naps in Children of the Morning and Afternoon Shifts (χ2, Mann–Whitney, p < .05).

Morning Afternoon Characteristics (n = 44) (n = 39) p Nap Weekdays frequency 68% 26% <.0001 of children Start 13:40 ± 01:18 13:38 ± 03:05 .3121 End 15:48 ± 01:30 15:04 ± 03:29 .4238 Duration 02:08 ± 00:54 01:25 ± 00:50 .0001 Weekend frequency 44% 31% .0080 of children Start 14:26 ± 00:59 14:36 ± 01:37 .4062 End 16:19 ± 01:12 16:16 ± 01:50 .5022 Fig. 2. Mean and standard deviation of daytime sleepiness level Duration 01:52 ± 00:46 01:44 ± 00:51 .4356 during the week in children of morning and afternoon shifts. The Irregularity Bedtime 00:43 ± 00:22 00:43 ± 00:20 .9588 daytime sleepiness was measured by an adapted version of the Wake up time 00:50 ± 00:55 00:42 ± 00:24 .4067 Pictorial Sleepiness Scale Based on Cartoon Faces of Maldonado et al. (2004) (Mann–Whitney, p < .05). napped at home. In children who studied in the morning, time increased less in this group (Mann–Whitney, p = .05) the naps occurred after they returned from school; while (Figure 4). Nevertheless, there was no diﬀerence between those in the afternoon shift napped, for example, when they shifts in relation to omissions (Figure 5) and the sequence missed school to go to the dentist or to accompany their of hits and errors across the test (Mann–Whitney, p > .1777) parents to solve personal problems. (Figure 6).

Time Spent in Bed There was no difference between shiftsF ( (6.480) = 4.05, DISCUSSION p = .3828) or weekdays (F(6.480) = 1.62, p = .1388) for time spent in bed every 24 hr (nighttime sleep and naps) This is a pioneering investigation on comparing the habits (Figure 1). and temporal patterns of sleep, daytime sleepiness, and the components of attention in preschool children enrolled in the morning and afternoon shifts. Sleep habits did not differ Daytime Sleepiness between shifts, but there were differences in temporal sleep The level of daytime sleepiness in children who study in the patterns, daytime sleepiness, and some components of atten- morning was higher on Monday (Mann–Whitney, p = .05) tion between children who studied in these shifts. and Friday (Mann–Whitney, p = .004) compared to those Itwasobservedthatmostofthechildrenco-sleptand who studied in the afternoon (Figure 2). engaged in bedtime rituals regardless of the shift in which they studied. Thus, school start time did not change these Components of Attention behaviors, probably because they are part of family dynam- Children in the morning shift exhibited a higher percentage ics that increase child–parent interactions (Beltramini & of correct answers for phasic alertness than those from the Hertzig, 1983; Buckley, Rigda, Mundy, & McMillen, 2002; afternoon shift (Mann–Whitney, p = .05) (Figure 3). How- Silva et al., 2005). ever, over the course of the test children who studied in the With respect to temporal sleep patterns according to morning had fewer correct answers and a lower increase in school start time, it was observed that during the week chil- reaction time than those who studied in the afternoon. This dren who studied in the morning woke up 1 hr and 30 min can be visualized in the time on task stability in Figure 4. earlier than those who studied in the afternoon. Thus, they The negative values observed represent a decrease in correct spent 1 hr less in bed at night and tended to be sleepier on answers throughout the task. On the other hand, the positive Monday and Friday than their afternoon shift counterparts. valuesrepresentanincreaseinreactiontimeduringthetask. Furthermore, a higher frequency of children from the morn- The decrease in the percentage of correct answers across the ing shift napped with longer episodes than those who studied task was higher in morning shift children. However, reaction in the afternoon.

Volume 11—Number 1 15 Sleep, Sleepiness, and Attention in Children

Fig. 3. Mean and standard error of the percentages and reaction time of correct answers for the components of attention during the continuous performance task in children who study in the morning and the afternoon shifts (Mann–Whitney, p = .05).

Fig. 4. Mean and standard error of indices of time on task stability Fig. 5. Mean and standard error of omissions during the attention in relation to the percentage and reaction time of correct answers task for children who study in the morning and the afternoon > during the performance task in children who study in the morning (Mann–Whitney, p .05). and afternoon shifts (Mann–Whitney, p < .05).

and the stronger influence of parents in determining their In more sleep deprived teenagers, this corresponds to a sleep–wake times (Iglowstein et al., 2003; Meijer et al., 2000) difference of nearly 2 hr of sleep between school days and This difference in temporal sleep patterns between week- weekends (Carskadon, 2002; Carskadon, Acebo, & Jenni, days and weekend in children who studied in the morn- 2004; Sousa, Araújo, & Azevedo, 2007). The difference ing may be due to acute sleep deprivation associated with between children and teenagers may be due to the natural a shorter time in bed at night in consequence to the school predisposition of children to go to bed and wake up earlier, starting time in the morning, which may contribute to a

16 Volume 11—Number 1 Aline S. Belísio et al.

selective attention, although an increase in the percentage of correct answers for phasic alertness was observed in children enrolled in the morning shift. The decrease in one of the sustained attention indices (percentage of correct answers across the task) in children from the morning shift may have been caused by acute sleep deprivation associated to the shorter time they spent in bed at night due to the school start time. In the school context, this negative effect might compromise learning. However, both groups of children showed an increase in reaction time across the task, but this increase was less marked in children who studied in the morning. This increase across the task was expected in cognitive assessment tests due to the fatigue effect. The lower increase Fig. 6. Average and standard error of the sequence of hits and in morning shift students may be due to a motivational error runs during the continuous performance task in children effect (Valdez et al., 2008), as a consequence of a higher who study in the morning and the afternoon shifts. No significant diferences were found between the groups in hits or error runs. activity level associated with methodological differences (Mann–Whitney, p > .05). in school tasks. Motivation and the higher activity level might have stimulating effects on cognitive development (Wojtczak-Jaroszowa & Jarosz, 1987). higher level of daytime sleepiness. It is important to under- The absence of intershift differences in some attention score that most of the children who studied in the morning parameters may result from the level of daily sleep depri- were woken up by their parents during the week and most vation observed in children (about 1 hr), which might not who studied in the afternoon woke up spontaneously, reaf- have been sufficient to interfere in attention levels. Further- firming the signs of acute sleep deprivation in the former more, the time the tasks were applied could have influ- group. Thus, the increase in sleepiness on Monday may be enced the responses obtained. Children from each shift a consequence of the shorter time in bed from Sunday to answered the tasks at different circadian moments (morn- Monday, whereas on Friday it may result from accumulated ing or afternoon). Additionally, those who studied in the tiredness during the week. This sleepiness pattern may lead morning should have exhibited a higher homeostatic pres- to the long nap episodes observed in the children enrolled in sure level since they had less nighttime sleep, but afternoon the morning shift. shift students displayed a higher number of previous waking With regard to naps and the shorter time spent in bed, hours. These factors may lead to more rapid fatigue in both it was observed that after adding time spent in bed at night groups and might have influenced the results obtained for and the daytime nap, the total sleep time of morning shift attention. students was similar to that of afternoon students. This In other studies, it was observed that university students shows that children who studied in the morning slept less at had increased attention levels during the day and a decline night than those from the afternoon shift, but they seemed between 4 a.m. and 6 a.m. (Valdez et al., 2005, 2010). The to compensate this deprivation by taking daily naps. These continuous application task presented in this study was results corroborate those observed by Silva et al. (2005), who applied between 8 a.m. and 9 a.m. to the morning group and reported that 7- to 10-year-old children who studied in the 2 p.m. and 3 p.m. to the afternoon group. Based on the study morning took more naps than those who studied in the with university students, it was expected that both shifts afternoon. These sleeping patterns demonstrate acute sleep would exhibit high attention levels, while sleep-deprived deprivation during the week that is compensated by taking children would not perform well on the task. However, chil- daily naps. Thus, school start time influenced the children’s dren are characterized by an advanced circadian phase in sleeping patterns, given that they spent less time in bed and relation to college students. Thus, circadian variation in woke up earlier to go to school in the morning. attention should be assessed considering the ontogenetic dif- In addition, morning shift students had fewer correct ferences that could cause different results in each age group. answers, even though they exhibited a shorter increase in The reduction in sustained attention efficiency observed reaction time during the CPT compared to their after- in this study is similar to the levels identified in previous noon shift counterparts. Nevertheless, in this investigation research with children starting at 7 years of age that sought no intershift differences were observed in omissions, the to identify cognitive development. Shorter sleep duration sequence of hits and errors during the test, or the number and poorer sleep quality have been associated with low per- of correct answers and reaction time for tonic alertness and formance (Paavonen et al., 2009; Sadeh, Gruber, & Raviv,

Volume 11—Number 1 17 Sleep, Sleepiness, and Attention in Children

2002; Touchette et al., 2007). However, these studies mea- Psicobiologia and the Universidade Federal do Rio Grande suredperformanceusingscoresontestsortasksthatonly do Norte for financial support. assessed sustained attention. This study had a number of limitations: (1) sleep–wake REFERENCES cycle analysis using questionnaires completed by parents may have contained inaccuracies regarding their child’s Acebo, C., Sadeh, A., Seifer, R., Tzischinsky, O., Hafer, A., & habits (according to Lam, Mahone, Mason, and Scharf Carskadon, M. A. (2005). Sleep/wake patterns derived from [2011], because parents tend to overestimate the sleep time activity monitoring and maternal report for healthy 1- to of children, actigraphy is one of the best ways to evaluate 5-year-old children. Sleep, 28, 1568–1577. sleep patterns); (2) the different task application times could Adam, E. K., Snell, E. K., & Pendry, P. (2007). Sleep timing and quantity in ecological and family context: A nationally repre- have influenced intershift results; (3) some participants sentative time-diary study. JournalofFamilyPsychology, 21, abandoned the study at different stages, contributing to a 4–19. decrease in the number of participants; and (4) the absence Anacleto, A. S. (2011). Ciclo vigília/sono e atividade motora em of chronotype evaluation due to the lack of an instrument crianças de 8 a 10 anos (Doctoral dissertation). Universidade validated for Portuguese that could have been applied to the Federal do Paraná, Curitiba, Brazil. children. Finally, an actigraphic assessment of sleeping pat- Andrade, M. (1997). Padrões temporais das expressões da sonolên- terns, using sleepiness variables, such as sleep–wake times to cia em adolescentes (Doctoral thesis). Universidade de São classify the chronotypes of children younger than 8 years old, Paulo, São Paulo, Brazil. Associação Nacional de Empresas de Pesquisa. (2008), Critério de is suggested for future studies. The attention components in Classificação Econômica Brasil. Retrieved from http://www this age group should be analyzed more often throughout .anep.org.br the day to verify whether the findings of the present investi- Belísio, A. S. (2010). Influência de fatores sociais sobre o ciclo sono e gation really had an influence on daily sleep compensation, vigíliadecriançasnaeducaçãoinfantil(Masters dissertation). and motivation or were due to a circadian effect. Universidade Federal do Rio Grande do Norte, Natal, Brazil. It is suggested that school start time influences tem- Belísio, A.S. (2014). Padrões temporais de sono, sonolência diurna poral sleep patterns and daytime sleepiness in preschool e os componentes da atenção em crianças que estudam nos children. Changes in sleeping patterns due to the morn- turnos da manhã e da tarde na educação infantil (Doctoral thesis). Universidade Federal do Rio Grande do Norte, Natal ing start time have been assessed in teenagers (Andrade, Brazil. 1997; Carskadon, 2002; Carskadon et al., 2004; Sousa et al., Beltramini, A. U., & Hertzig, M. E. (1983). Sleep and bedtime 2007) and preteenagers aged 10–12 years (Epstein, Chillag, behavior in preschool-aged children. Pediatrics, 71, 153–158. & Lavie, 1998), but we observed that school start time also Benington, J. H., & Heller, H. C. (1995). Restoration of brain energy influences younger children, despite their natural tendency metabolism as the function of sleep. Progress in Neurobiology, to morningness. In addition to the negative impact on sleep 45, 347–360. patterns, there were signs of negative effects on sustained Buckley, P., Rigda, R. S., Mundy, L., & McMillen, I. C. (2002). Inter- attention, which may compromise learning. Since only one action between bed sharing and other sleep environments during the first six months of life. Early Human Development, 66, parameter of one component of attention was negatively 123–132. affected, further studies evaluating the attention compo- Carskadon, M. (2002). Factors influencing sleep patterns of adoles- nents in this age group at different times of the day are cents. In M. Carskadon (Ed.), Adolescent sleep patterns (pp. needed to confirm this effect on cognition. Nevertheless, the 4–26). Cambridge, UK: Cambridge University Press. results obtained reinforce the importance of broadening the Carskadon, M. A., Acebo, C., & Jenni, O. G. (2004). Regulation of discussion regarding changing school start times, which is adolescent sleep. Annals of the New York Academy of Sciences, focused on teenagers, to other age groups, such as preschool 1021, 276–291. children. To that end, it is essential to take into account the Cohen, R. A., & O’Donnell, B. F. (1993). Models and mecha- nisms of attention. In R. A. Cohen, I. A. Sparling-Cohen, & biological characteristics of each age group. l. F. O’Donne (Eds.), The neuropsychology of attention (pp. 177–186). New York, NY: Plenum Press. Acknowledgments—We thank Dr. John Araüjo, Dr. Luiz Drosopoulos, S., Schulze, C., Fischer, S., & Born, J. (2007). Sleep’s Menna-Barreto, and Dra. Katie Almondes for suggestions function in the spontaneous recovery and consolidation of throughout this study. We also thank the students Diana memories. Journal of Experimental Psychology: General, 136, Juárez, Ana-hi Flores, Mariana Reyna, Gabriela Iracheta, 169–183. El-Sheikh, M., Buckhalt, J. A., Mize, J., & Acebo, C. (2006). Marital Susana Hernandez, Galileu Borges, Maria Luiza Oliveira, conflict and disruption of children’s sleep. Child Development, Sabinne Galina, Jackleyde Silva, Icemária Felipe, and Kar- 77, 31–43. lyne dos Anjos for their help in data collection and analysis; Epstein, R., Chillag, N., & Lavie, P. (1998). Starting times of school: Dra. Candelária Ramírez and Dra. Aida García for analysis Effects on daytime functioning of fifth-grade children in Israel. support; and CAPES, Programa de Pós-Graduação em Sleep, 21, 250–256.

18 Volume 11—Number 1 Aline S. Belísio et al.

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Valdez, P., Ramírez, C., García, A., Talamantes, J., & Cortez, J. Wilhelm, I., Diekelmann, S., & Born, J. (2008). Sleep in children (2010). Circadian and homeostatic variation in sustained improves memory performance on declarative but not proce- attention. Chronobiology International, 27, 393–416. dural tasks. Learning and Memory, 15, 373–377. Valdez, P., Reilly, T., & Waterhouse, J. (2008). Rhythms of mental Wojtczak-Jaroszowa, J., & Jarosz, D. (1987). Chronohygienic and performance. Mind, Brain, and Education, 2, 7–16. chronosocial aspects of industrial accidents. In J. E. Pauly & Wey, D. (2002). Ciclovigília-sonodecrianças:transiçãodaedu- L. E. Scheving (Eds.), Advances in chronobiology B cação infantil para o ensino fundamental (Doctoral disserta- (pp. 415–426). New York, NY: Alan R. Liss. tion). Universidade de São Paulo, São Paulo, Brazil.

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