Naps Enhance Executive Attention in Preschool-Aged Children

Abstract

Objective

Executive attention is impaired following sleep loss in school-aged children, adolescents, and adults. Whether naps improve attention relative to nap deprivation in preschool-aged children is unknown. The aim of this study was to compare executive attention in preschool children following a nap and an interval of wake.

Method

Sixty-nine children, 35–70 months of age, completed a Flanker task to assess executive attention following a nap and an equivalent interval of wake.

Results

Overall, accuracy was greater after the nap compared with the wake interval. Reaction time(s) did not differ between the nap and wake intervals. Results did not differ between children who napped consistently and those who napped inconsistently, suggesting that naps benefit executive attention of preschoolers regardless of nap habituality.

Conclusions

These results indicate that naps enhance attention in preschool children. As executive attention supports executive functioning and learning, nap promotion may improve early education outcomes.

Sleep loss impairs attention in adults, adolescents, and school-aged children (Doran, Van Dongen, & Dinges, 2001; Fallone, Acebo, Arnedt, Seifer, & Carskadon, 2001). Specifically, executive attention, defined as the ability to regulate attention in the presence of conflicting information (Rueda, Posner, & Rothbart, 2005), is reduced following sleep loss (Durmer & Dinges, 2005; Goel, Rao, Durmer, & Dinges, 2009). Whether nap deprivation in preschool children is sufficient to reduce executive attention is unknown. Understanding relations between napping and attention in young children is particularly important, as the maturational trajectory of the attention networks coincides with a dramatic change in sleep patterns during early development (Fox & Calkins, 2003; Iglowstein, Jenni, Molinari, & Largo, 2003). Executive attention underlies the development and efficacy of executive functions (e.g., working memory, response inhibition, and set shifting) that emerge during the preschool years (Garon, Bryson, & Smith, 2008; Posner & Rothbart, 1998; Rothbart & Posner, 2001). Moreover, executive attention supports memory (Engle & Kane, 2003) and self-regulation (Rueda, Posner, & Rothbart, 2005), key cognitive processes that facilitate learning during early childhood.

As children age, the neural networks that facilitate executive attention develop rapidly (Rothbart, Sheese, Rueda, & Posner, 2011). Throughout infancy, attention is primarily mediated by the alerting system that directs attention to novel or salient stimuli. During the first year of life, the orienting network supports refined attention allocation via executive attention. Executive attention is further strengthened by functionality of the executive attention network (prefrontal cortex, cingulate cortex, frontal gyrus), which begins to develop during the preschool years and continues to mature through late childhood (Anderson, 2002; Rothbart, Sheese, Rueda, & Posner, 2011; Rueda, Checa, & Combita, 2012).

As the executive attention network develops, there are notable improvements in executive functioning (Posner & Rothbart, 1998; Rothbart & Posner, 2001). During the preschool years, top-down employment of executive attention facilitates response inhibition, the ability to suppress a particular behavior or motor response (Garon, Bryson, & Smith, 2008). Similarly, executive attention supports working memory and set shifting by promoting passive storage, rehearsal, and rule learning. Importantly, these executive functions improve learning and adaptive behavior throughout development (Rothbart & Posner, 2001). As such, it is important to identify factors that improve and diminish executive attention in early childhood.

Sleep patterns change dramatically during the preschool years. From 1.5 to 4 years of age, sleep is typically biphasic, composed of a single mid-day nap and an overnight sleep bout (Iglowstein, Jenni, Molinari, & Largo, 2003). By 4 years of age, many children transition from a biphasic sleep pattern to a monophasic sleep pattern, with sleep consolidated to a single, overnight sleep bout. This transition is variable; some children transition earlier in this period of development, whereas other children continue to nap past 5 years of age. Moreover, nap frequency varies during this transitional period, making both a nap condition and nap-deprived condition within the range of normative sleep patterns for this age-group. Given that the developmental trajectory of the executive attention network coincides with the typical biphasic to monophasic sleep transition, children who nap consistently (biphasic sleepers) may be more susceptible to attentional impairments when nap deprived.

Neuroimaging studies in adults indicate that overnight sleep deprivation alters activation of the frontal networks that support executive attention (Drummond, Gillin, & Brown, 2001). Consistent with this, cognitive processes that depend on executive attention are reduced following overnight sleep deprivation in adults (Durmer & Dinges, 2005; van der Helm, Gujar, & Walker, 2010). Similar behavioral findings are observed in children following nap deprivation. Nap deprivation impairs memory (Desrochers, Kurdziel, & Spencer, 2016; Kurdziel, Dulcos, & Spencer, 2013) and self-regulation (Berger, Miller, Seifer, Cares, & LeBourgeois, 2012; Miller, Seifer, Crossin, & LeBourgeois, 2015) in preschool children. Conversely, these capacities are improved following a nap. Taken together, these findings suggest that nap deprivation may impair executive attention during early childhood.

The aim of the present study was to directly assess the role of napping on executive attention during early childhood. To test this, preschool-aged children completed a Flanker task following a mid-day nap and an equivalent interval of time spent awake. As the attention networks underlying executive attention mature during the preschool years (Fox & Calkins, 2003; Rothbart, Sheese, Rueda, & Posner, 2011) and are less efficient following sleep loss (Drummond, Gillin, & Brown, 2001), we hypothesized that executive attention would be reduced following nap deprivation, marked by decreased accuracy and slower reaction time (RT) on a Flanker task, compared with a mid-day nap. Alternatively, the loss of mid-day sleep may not have the same impact as overnight sleep deprivation, as naps are short and become less consistent at this age. Moreover, we evaluated the effect of nap habituality on task performance following the nap and wake intervals. As the transition from napping overlaps with the development of the executive attention network, children who nap consistently may be particularly sensitive to nap deprivation. Thus, we hypothesized that attentional differences following nap and wake would emerge between children who nap consistently versus those who do not.

Methods

Participants

Sixty-nine children (38 females), 35–70 months of age (M_age = 55.33, SD = 9.90 months), were recruited from preschools in Western Massachusetts as part of a larger study. Demographic information for this sample is provided in Table I. An additional sample of 41 children was tested but was excluded for noncompliance (n = 1), recording error (n = 3), missing school on either testing day (n = 6), failing to sleep in the nap condition (n = 3) or stay awake during the wake condition (n = 4), or failing to reach the >50% accuracy criterion (to omit children performing at or below chance level) on the Flanker task following the nap (n = 7) or wake condition (n = 9) or both the nap and wake conditions (n = 8). Consistent with other studies (see Rothbart & Rueda, 2005), children who met accuracy criteria were significantly older (M_age = 55.33, SD = 9.90 months) than those who were excluded from analyses for failing to meet accuracy criteria (M_age = 49.42, SD = 9.97 months; t(91) = 2.52, p = .014, 95% CI [1.25, 10.58]). Males were excluded for failing to meet accuracy criteria more often than females (χ²(1, N = 93) = 4.79, p = .029). Children who were included or excluded based on accuracy criteria did not differ in race (x²(4, N = 86) = 3.58, p = .466) or average household income (χ²(8, N = 77) = 10.48, p = .233).

Table I.

Demographic Information for Sample Tested

Variable	%
Child race
White/Caucasian	47.8
Black/African American	23.3
Chinese	1.4
Multiracial	20.3
Other	2.9
Missing	4.3
Caregiver race
White/Caucasian	44.9
Black/African American	11.6
Chinese	1.4
Multiracial	17.4
Other	5.8
Missing	18.8
Household income
$5,000 or less/year	1.4
$5,001–$10,000/year	4.3
$10,001–$20,000/year	15.9
$20,001–$40,000/year	26.1
$40,001–$70,000/year	10.1
$70,001–$100,000/year	13.0
$100,001–$150,000/year	7.2
More than $150,000/year	4.3
Missing	14.5

To recruit this sample, information regarding the study and consent forms were distributed to caregivers of children in local preschools. Children were eligible to participate in this study if they had normal or corrected-to-normal vision and no history of a diagnosed sleep disorder (e.g., no current diagnosis or history of sleep apnea, sleep disordered breathing, or restless leg syndrome), parasomnias, or learning or developmental disability, as reported by caregivers. Caregivers also completed the Children’s Sleep Habits Questionnaire (a reliable assessment of disordered sleep in young children; Owens, Spirito, & McGuinn, 2000) to confirm that the children in our sample had healthy sleep habits (average total score = 38 ± 9). We also confirmed that enrolled children had not traveled beyond 1 time zone within 1 month of testing and were not taking sleep-altering medications.

The total enrollment rate (the number of children who enrolled in the study as a percent of the number of eligible children in all classrooms) for the larger study was 63.42%. Mean enrollment rate (mean number of children enrolled in each classroom as a percent of eligible children in the classroom) across the 15 classrooms (six different schools) was 63.85%. Common reasons for nonenrollment were concern regarding the effect the nap/wake manipulation would have on overnight sleep; no time (referring to caregiver questionnaires collected as part of the larger study); part-time preschool enrollment; or lack of interest.

Measures

Flanker Task

The Flanker task used in the current study was similar to that described elsewhere (McDermott, Perez-Edgar, & Fox, 2007) and has been used in children as young as 3.5 years of age (Rothbart & Rueda, 2005). Stimuli were images of five fish. Fish were each 1 inch in height and 1.25 inches in width and were horizontally aligned in the middle of a 14-inch computer screen positioned approximately 15 inches from the child. Trials were “congruent” if the center, target fish was oriented in the same direction (leftward or rightward facing) as the flanking fish. Trials were “incongruent” if the center, target fish was oriented in the direction opposite of the flanking fish (Figure 1). There were an equal number of congruent and incongruent trials presented during each block, and the presentation of these trial types was randomized throughout blocks.

Figure 1.

This figure illustrates the order of stimulus presentation during the Flanker task.

Each trial began with the presentation of a central fixation mark (500 ms) followed by the fish stimuli (700 ms). Children were instructed to indicate the orientation of the center fish, via button press on a mouse (left vs. right), as quickly and accurately as possible. Children were required to respond within 1,300 ms of the stimuli presentation (responses made outside of that time frame were marked as omitted responses). To maintain engagement and ensure that children understood task instructions, feedback was presented on the screen following each trial. Following a correct response, a smiley face (1.5 inches in height and 1.5 inches in width) was displayed for 850 ms. A frowning face was displayed following an incorrect or omitted response. A blank screen was presented for 190 ms between trials.

The task consisted of 10 practice trials and 80 experimental trials, presented in two blocks of 40 trials each. Participants were randomly assigned to one of two pseudo-random trial orders, counterbalanced across participants. The task took approximately 10–15 min to complete (accounting for time spent on practice trials and a short break between the two blocks).

Nap Diary

Classroom teachers were given nap diaries to indicate the number of naps children took in the classroom over the 2-week testing period that included the two experimental conditions (i.e., nap and wake). Teachers noted whether the child napped and the start/end times of the classroom nap opportunity.

Procedure

All procedures were approved by the institutional review board at the University of Massachusetts Amherst. Data were collected by trained postdoctoral research associates, graduate students, and undergraduate research assistants. Testing took place in the preschool classrooms over the course of one calendar year. No testing was performed the week following Daylight Savings Time changes. In most cases, experimental procedures were performed on Wednesdays to control for changes in sleep drive that may accrue across the week. Caregivers consented to their child’s participation, and child assent was sought before commencing with the experimental procedures.

Children completed two conditions, a nap and a wake condition, separated by approximately 1 week, with the order counterbalanced across participants. In the nap condition, children were encouraged to sleep during the typical afternoon nap opportunity (∼1–3 p.m.). Experimenters noted the duration of time each child spent asleep during the nap opportunity (experimental nap length). In the wake condition, children participated in quiet activities (i.e., reading books or coloring) to maintain a wake state during same interval of time. To control for other potential environmental factors, in both conditions, children remained on their cots with the lights dimmed and the room was kept quiet. Following the nap/wake interval, children completed a Flanker task to assess executive attention.

Data Analyses

All statistical analyses were performed using SPSS Version 20.0. A linear regression model was used to evaluate the role of child age, sex, race, and household income in predicting the change in accuracy and RT between conditions (nap vs. wake). These variables did not significantly predict change in accuracy or RT between the nap and wake conditions. As such, they were not included in subsequent statistical analyses.

Repeated-measures analyses of variance (RM-ANOVAs) were used to compare executive attention, measured by accuracy (the number of correct trials divided by the total number of trials administered) and RT on congruent and incongruent trials, between the nap and wake conditions. Accuracy and RT for correct trials were entered as outcome variables in two separate RM-ANOVAs with trial type (congruent and incongruent) and condition (nap and wake) as within-subject factors. Additionally, we examined the correlation between experimental nap length and postnap accuracy and RT to determine whether nap duration altered the behavioral outcomes. The results of the RM-ANOVAs evaluating accuracy motivated post hoc t-tests comparing errors of commission and errors of omission between the nap and wake conditions.

To assess developmental differences in our sample, post hoc RM-ANOVAs were performed to address behavioral differences among consistent and inconsistent nappers. In these models, accuracy and RT for correct trials were entered as outcome variables, condition and trial type as within-subject factors, and nap habituality status (consistent or inconsistent napper) as a between-subjects factor. To measure nap habituality, we calculated the number of days in which the child napped (as recorded by classroom teachers) as a percentage of the total number of days the child was in the classroom (i.e., not absent) during the 2-week testing period (Cremone, Kurdziel, Fraticelli-Torres, McDermott, & Spencer, 2016; Spencer et al., 2016). A median split was used to separate “consistent” and “inconsistent” nappers (Cremone, Kurdziel, Fraticelli-Torres, McDermott, & Spencer, 2016). Based on this distinction, children who napped 100% of the recorded days were considered “consistent nappers,” whereas those who napped less than that (range: 0–90%; M = 53.28, SD = 7.15%) were considered “inconsistent nappers.”

Results

Accuracy

In the RM-ANOVA predicting accuracy, the main effects of trial type and condition were significant (see Table II). As expected, accuracy on congruent trials was significantly greater than accuracy on incongruent trials (F(1,68) = 81.62, p ≤ .001, η_p²=.546; Figure 2). Children had greater accuracy overall following the nap condition relative to the wake condition (F(1,68) = 6.16, p = .016, η_p²=.083; Figure 2). The interaction between condition and trial type was not significant (F(1,68) = 0.383, p = .538). The correlation between nap length (as recorded by the experimenter on the day of the nap condition) and accuracy was not significant for congruent or incongruent trials (p’s ≥ .437).

Table II.

Average Accuracy and RT on Correct Trials Assessed by the Flanker Task

Variable	Nap condition		Wake condition		p-value
	Mean	SD	Mean	SD
Accuracy (%)
Congruent	81.15	14.55	76.90	15.11	≤.001a
Incongruent	64.43	19.67	61.64	18.22
				0.016b
RT (ms)
Congruent	756.90	221.31	724.16	181.46	.055a
Incongruent	783.86	220.30	761.57	194.03
				0.192b

Note. ^a,bp-values from the repeated-measures analyses of variance representing the main effects of trial type and condition, respectively.

Figure 2.

Accuracy for congruent and incongruent trials during the nap and wake conditions. Note. Means represent those from the repeated-measures analysis of variance; error bars represent standard error.

To explore factors driving differences in accuracy, errors of commission and omission were compared between the nap and wake conditions. Children made fewer errors of commission following the nap condition (M = 18.19, SD = 9.51) compared with the wake condition (M = 20.29, SD = 9.33; t(68) = 2.02, p = .047, 95% CI [0.24, 4.18]). Errors of omission did not differ between conditions (t(68) = 1.39, p = .170).

Reaction Time

In the RM-ANOVA predicting RT, the main effect of trial type was not significant. Although the difference was not significant, children tended to respond to congruent trials faster than incongruent trials (F(1,68) = 3.81, p = .055, η_p²=.053; see Table II andFigure 3). The main effect of condition (F(1,68) = 1.74, p = .192) and the interaction between condition and trial type (F(1,68) = 0.10, p = 0.755) were not significant. The correlation between nap length and RT to congruent trials following the nap opportunity was not significant (r = −.018, p = .883). RT to incongruent trials tended to be faster following a longer nap (r = −.232, p = .055); however, this difference was not significant and should be interpreted with caution.

Figure 3.

Reaction time for correctly answered congruent and incongruent trials during the nap and wake conditions. Note. Means represent those from the repeated-measures analysis of variance; error bars represent standard error.

Nap Habituality

Of the 69 children with complete data sets, information regarding nap habituality was available for 61 children (not all teachers provided this information). Of the children with nap habituality data, 7 children napped 0–25% of days recorded, 4 children napped 26−50% of days recorded, 4 children napped 51–75% of days recorded, 10 children napped 76–99% of days recorded, and 36 children napped 100% of days recorded. As such, based on the median split approach (Cremone, Kurdziel, Fraticelli-Torres, McDermott, & Spencer, 2016), 36 children (19 females; M_age = 56.14, SD = 9.27 months) were classified as consistent nappers and 25 (16 females; M_age = 56.96, SD = 9.39 months) as inconsistent nappers. Consistent and inconsistent nappers did not differ in age (t(59) = 0.34, p = .736) or sex (x²(1, N = 61) = 0.760, p = .383).

In the RM-ANOVA predicting accuracy, the main effect of nap habituality status (F(1,59) = 0.28, p = .600) was not significant. The interaction between trial type and nap habituality status was also not significant. However, compared with consistent nappers, inconsistent nappers had greater accuracy on incongruent trials (F(1,59) = 3.14, p = .082, η_p²=.051). All other interactions with nap habituality status (p’s ≥ .785) were not significant. Consistent with results of the larger sample, the main effects of trial type (F(1,59) = 64.70, p ≤ .001, η_p²=.523) and condition (F(1,59) = 7.68, p = .007, η_p²=.115) were significant such that accuracy was greater for congruent trials and after the nap interval. The interaction between trial type and condition was not significant (F(1,59) = 0.24, p = .628).

In the RM-ANOVA predicting RT, the main effect of nap habituality status (F(1,59) = 0.54, p = .464) and related interactions (p’s ≥ .290) were not significant. The main effects of trial type (F(1,59) = 2.92, p = .093, η_p²=.047) and condition (F(1,59) = 3.68, p = .060, η_p²=.059) were also not significant; however, RT tended to be faster for congruent trials and after the nap interval. The interaction between trial type and condition was not significant (F(1,59) = 0.00, p = .988).

Discussion

A growing body of literature indicates that napping improves learning and memory during the preschool years (Desrochers, Kurdziel, & Spencer, 2016; Kurdziel, Dulcos, & Spencer, 2013). The results of the current study extend these findings by demonstrating a role of naps in enhancing attention, particularly in the face of conflicting information, which requires executive attention (Posner & Rothbart, 1998). As executive attention supports the development of other core executive functions (Garon, Bryson, & Smith, 2008; Posner & Rothbart, 1998; Rothbart & Posner, 2001) and is strongly associated with memory capacities (Engle & Kane, 2003) and self-regulation (Rueda, Posner, & Rothbart, 2005), enhanced attention following a nap may support early cognitive development in young children.

Consistent with our hypothesis and the results of other studies (Davies, Segalowitz, & Gavin, 2004; McDermott, Perez-Edgar, & Fox, 2007; Pailing, Segalowitz, Dywan, & Davies, 2002), typical interference effects emerged such that accuracy was greater and RT faster for congruent versus incongruent trials across conditions. Interference was low during congruent trials, when the target stimulus and flanking stimuli were oriented in the same direction. Interference was high, on the other hand, during incongruent trials, when the target stimulus was oriented in the direction opposite of the flanking stimuli. During these high interference trials, executive attention was needed to ignore the mismatched, flanking stimuli and attend to the target stimulus to make the correct response. Consequently, and consistent with prior studies, accuracy was lower and RT slower on incongruent versus congruent trials.

In accordance with our primary hypothesis, accuracy on both congruent and incongruent trials was greater following the nap relative to the wake interval. Although these results suggest a general enhancement of attention following mid-day sleep, the sleep-dependent improvement on high interference, incongruent trials demonstrates that naps are also beneficial for executive attention. In other words, following a nap, children are better able to use attentional resources to differentiate between the flanking and target stimuli to respond to incongruent trials accurately. Although the magnitude of change in accuracy between the nap and wake conditions is of medium effect size (η_p²=.083), this nap-dependent improvement is functionally relevant, as executive attention supports memory (Engle & Kane, 2003) and self-regulation (Rueda, Posner, & Rothbart, 2005) during early childhood.

Drummond and colleagues (2001) showed increased activation in the prefrontal cortex and parietal lobes during a divided attention task following sleep deprivation in young adults, suggesting that more attentional resources were needed to engage executive attention following sleep loss (Drummond, Gillin, & Brown, 2001). Given that accuracy on incongruent trials was poor following wake compared with an afternoon nap, results from the current study lend support to the hypothesis that the neural structures underlying executive attention are similarly taxed following nap deprivation in young children. We posit that naps reduce the cognitive load on the neural structures supporting executive attention, thereby increasing their efficacy following the nap opportunity. However, given the lack of a significant interaction between condition and trial type, this interpretation should be approached with caution.

Prior studies have demonstrated the negative impact of sleep deprivation on attention (Doran, Van Dongen, & Dinges, 2001; Fallone, Acebo, Arnedt, Seifer, & Carskadon, 2001), which may make the present findings unsurprising. However, given that naps are relatively brief (based on experimental nap length, M = 94.68, SD = 28.16 minutes) and transitional, nap deprivation is unique from overnight sleep deprivation. Importantly, we found that executive attention was improved following a nap for both consistent and inconsistent nappers. The executive attention network has a protracted period of development (Anderson, 2002; Rothbart, Sheese, Rueda, & Posner, 2011; Rueda, Checa, & Combita, 2012), which may have contributed to sleep-dependent enhancement of executive attention in both groups of children. Thus, although inconsistent nappers may have advanced brain development (Lam, Mahone, Mason, & Scharf, 2011; Spencer et al., 2016), the efficacy of the executive attention network can still be improved by mid-day sleep. Additional studies evaluating the effects of nap habituality on other measures of executive attention and earlier attentional capacities, such as those mediated by the alerting and orienting systems, are needed to better understand the role of napping on attention in consistent and inconsistent nappers.

Limitations and Future Directions

Overall the current study supports the importance of mid-day naps for attention regulation during early childhood. However, there are a number of limitations to be addressed in future studies. First, younger children found the task extremely challenging. There was also substantial variability in both accuracy and RT across the nap and wake conditions (see Table II). As our goal was to assess the relations between mid-day sleep and attention across the preschool age range (2.9–5.11 years of age), we recruited broadly. The failure of many younger participants to meet the performance criterion is consistent with prior work showing that approximately half of 3.5-year-old children tested on a Flanker task were unable to perform the task (see Rothbart & Rueda, 2005). Interestingly, 50% (14 of 28) of the 3-year-old children in the present study met the accuracy criteria required to be included in analyses. These patterns suggest that individual differences in Flanker task performance are evident even among young children. Furthermore, age was not associated with change in performance, suggesting a stable role of sleep on executive attention in preschool-aged children. Nonetheless, results regarding young children should be taken with caution given that 50% of the 3-year-old children tested were excluded for low accuracy on the Flanker task.

Second, we did not observe a condition by trial type interaction in our sample. That is, performance on both congruent and incongruent trials was improved following the nap, suggesting that the effects of sleep on attention may not be specific to executive attention per se. Rather, sleep may provide a general benefit to attention, as evidenced by increased accuracy and slower RT on both congruent and incongruent trials. Other cognitive tasks, such as the Attention Network Task (see Rueda et al., 2004), which gauge all attention networks (i.e., alerting, orienting, and executive attention), may be used in future studies to better understand the role of sleep on different attentional processes in this age-group.

Third, we did not observe beneficial effects of napping on RT, despite nap-dependent enhancement of accuracy. The attention mechanisms underlying accuracy and RT differ (Prinzmetal, McCool, & Park, 2005): executive attention, which is voluntary, is gauged by measures of both accuracy and RT, whereas involuntary attention (attention mediated by the orienting and alerting system) is measured in RT but not accuracy. Our results suggest that mid-day sleep improves accuracy but not RT in young children. However, RT to correct incongruent trials tended to be faster the longer children had napped, suggesting that sleep improves attention to more difficult trials. Taken together, these findings suggest that sleep may increase the efficacy of voluntary attention (i.e., executive attention) but not involuntary attention.

Additionally, accumulating evidence indicates that tasks used to probe executive attention map on to a single latent factor that reflects executive functioning rather than an independent or exclusive capacity (Wiebe, Espy, & Charak, 2008). As executive attention supports the subsequent development of other executive functions (Garon, Bryson, & Smith, 2008; Posner & Rothbart, 1998; Rothbart & Posner, 2001), the nap-dependent enhancement of attention reported in this study may be indicative of a global benefit of sleep on executive functioning in preschoolers. Thus, additional studies assessing the role of napping on other executive functions, or executive function as a whole, are needed.

Conclusions

To make time for increasing demands in curriculum, there is currently reduced emphasis and time allotted to nap opportunities in the preschool classroom. The results of our study indicate that attention is reduced when children are kept awake during this nap opportunity and improved when children are able to nap. As executive attention supports memory and self-regulation, our data suggest that mid-day naps enhance attentional capacities that support cognitive development and early education.

Funding

This work was supported by the National Institutes of Health [HL111695] awarded to Rebecca M. C. Spencer.

Conflicts of interest: None declared.