Effects of physically active lessons and active breaks on cognitive performance and health indicators in elementary school children: A cluster randomized trial

Effects of physically active lessons and active breaks on cognitive performance and health indicators in elementary school children: A cluster randomized trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of physically active lessons and active breaks on cognitive performance and health indicators in elementary school children: A cluster randomized trial João Carlos Nascimento Melo, Julian Tejada, Ellen Caroline Mendes Silva, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5804150/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Jul, 2025 Read the published version in International Journal of Behavioral Nutrition and Physical Activity → Version 1 posted 9 You are reading this latest preprint version Abstract Background This cluster-randomized trial investigated the effects of active breaks and physically active lessons on cognitive function and health indicators in elementary school children in Aracaju, SE. Methods Six schools were randomly divided into three groups: 1) active breaks (n = 61), which consisted of short physical activity intervals during classes; 2) physically active lessons (n = 77), which combined physical activity with educational content; and 3) control (n = 46), which followed the traditional curriculum. The interventions were conducted over eight weeks. Cognitive function was assessed via reaction time and correct responses on five computerized tests: visual search, Go/NoGo, mental rotation, cueing positive, and digit span. Physical activity was measured by pedometers and the Web-CAAFE questionnaire. Quality of life, daytime sleepiness, and school perception were also evaluated as secondary outcomes. Generalized estimating equation models were used, with a significance level of 5%. Results The physically active lesson group showed significant improvements in inhibitory control on the Go/NoGo test (∆ = -104.5 ms; p < 0.001; d = 0.50) and in working memory on the DigitSpan test (∆ = 0.62 hits; p < 0.001; d = 0.44). The physically active lessons and active breaks groups showed significant improvements in spatial reasoning on the mental rotation test (∆ = -1967.5 ms; p < 0.001; d = 0.72, and ∆ = -1477.8; p < 0.001; d = 0.54, respectively). All groups demonstrated significant improvements in spatial orientation on the Cueing Posner test, with the largest effect in the physically active lessons group (∆ = -386.4 ms; p < 0.001; d = 0.69). Conclusion The study concluded that physically active lessons improved various cognitive functions, whereas active breaks, although less impactful, are still a beneficial strategy without adverse effects. Trial registration: Brazilian Clinical Trials Registry (REBEC trial: RBR-10zxwdrh, retrospectively registered on 2025-01-09, https://ensaiosclinicos.gov.br/rg/RBR-10zxwdrh ). Physically Active Learning Executive Function Health Indicator Classroom Physical Activity Figures Figure 1 Figure 2 Figure 3 Introduction The increase in the number of studies on sedentary behavior over the past few years reflects its recognition as a public health issue [ 1 ]. While the implications of this behavior are better understood in adults [ 2 – 6 ], there is growing evidence regarding the adverse effects of prolonged sitting in children, including obesity [ 7 ], elevated systolic and diastolic blood pressure [ 8 ], impaired vascular [ 9 , 10 ] and cerebrovascular [ 11 ] impaired motor abilities [ 12 , 13 ] and reduced sleep duration [ 14 ]. Such evidence has driven the implementation of policies and international recommendations to reduce sedentary behavior, particularly during childhood and adolescence [ 15 – 17 ], given that critical periods for establishing habits and lifestyles at this age are likely to persist throughout life [ 18 ]. In this context, schools have been the focus of research and interventions aimed at reducing sedentary behavior [ 1 ], largely because of the significant amount of daily time that this population spends in this setting [ 19 ] and because, in more traditional teaching models, classroom layouts tend to encourage prolonged periods of sitting among students [ 19 , 20 ]. Thus, strategies aimed at replacing sedentary behavior with physical activity and optimizing classroom time have been a focal point for researchers [ 21 , 22 ]. The integration of physical activity in the classroom can occur in various forms [ 21 ], including active breaks [ 23 ] (i.e., short intervals during class for physical activities that may or may not be related to the curricular content) and physically active learning [ 24 ] (i.e., integrating physical activity into curricular content, such as teaching mathematics via body movement). These strategies have been suggested due to their low-cost nature [ 25 , 26 ], potential to reduce sedentary behavior [ 23 , 24 ], increase physical activity levels [ 23 , 24 ], improve academic performance [ 24 ] and yield promising results in cognitive outcomes such as inhibitory control [ 27 – 30 ], working memory [ 31 – 33 ], attention [ 32 ] and fluid intelligence [ 34 ]. However, more specific data are still needed regarding certain types of cognitive processes related to problem-solving and decision-making. These processes encompass so-called executive functions [ 35 ], which control goal-directed behaviors, assist in impulse control, and help maintain a focus on tasks. These functions are particularly important because of their relationship with the development of the frontal cortex, a brain region involved in various higher-order cognitive functions (such as risk assessment, language production, visual processing, and working memory), which undergo late development during adolescence [ 36 ]. The study of these functions could help clarify the evidence on cognitive outcomes, given that previous reviews have failed to reach robust conclusions owing to the heterogeneity of results [ 23 , 24 , 26 ]. Moreover, most research has been conducted in high-income countries, which may limit the generalizability of the findings to other educational contexts [ 23 , 24 ]. For example, in Brazil, the existence of shorter school periods and poor infrastructure in schools, such as small classrooms and overcrowding [ 37 ], may pose critical limitations for the implementation of these interventions. Additionally, most studies have focused on a single type of intervention [ 25 , 26 ], with few comparisons of the effects of different approaches [ 38 – 40 ]. To the best of our knowledge, only two studies [ 40 , 41 ] have compared the effects of physically active lessons and active breaks in children. However, both studies were conducted in high-income countries and did not investigate cognitive outcomes; instead, they focused on children's mathematics performance. Thus, scientific gaps persist, particularly regarding the effects on executive functions, which have been suggested as an underlying mechanism to explain the positive effects on academic performance [ 42 , 43 ]. Additionally, further studies are needed to verify the transferability of the observed positive effects to other educational contexts, such as low- and middle-income countries, as well as studies comparing different types of interventions, particularly the differences between physically active lessons and active breaks. Therefore, the primary aim of the present study is to assess the effects of physically active lessons and active breaks on the executive functions of elementary school students, with the secondary objective of examining the effects on physical activity levels, quality of life, daytime sleepiness, and school perception. Methods The trial was reported in accordance with the CONSORT statement for cluster randomized trials [Supplementary Material 1] (Campbell et al., 2012) and the TIDieR Checklist for Reporting and Replicating Interventions [Supplementary Material 2]. Study design A three-arm cluster-randomized clinical trial was conducted in public schools in the city of Aracaju, Brazil. The data from this study are part of the first year of the Erguer project (second wave) during the year 2022. The study received approval from the Human Research Ethics Committee of the Federal University of Sergipe (Approval Number: 5.301.398). Figure 1 illustrates the experimental design of the study, summarizing the main stages. Evaluations took place at two time points: the baseline assessment, conducted between March and July 2022, and a follow-up assessment after the interventions, carried out between November and December 2022. The interventions lasted eight weeks, starting in September after the initial assessments and the return from vacation, and ended in November 2022. The interventions were implemented by the classroom teachers themselves, directly in their classrooms. Training and support for teachers were provided by the project team between July and October 2022, combining in-person and online sessions. [Insert Fig. 1] Figure 1. Schematic of the study design. (A) Schematic showing the study protocol timeline. (B) Description of the interventions. Participant schools One of the eight regions of the municipality of Aracaju [ 44 ] was randomly selected. All schools in this region, with at least two first-grade classes, were invited to participate. Six schools (100%) accepted the invitation and were randomly assigned to one of three groups: 1) an intervention group with physically active lessons (two schools); 2) an intervention group with active breaks (two schools); and 3) a control group (two schools). Participant students After primary consent was obtained from the school, all first-grade children were invited to participate in the study. The inclusion criteria required that children be regularly enrolled in the selected schools and return the informed consent form duly signed by their parents or guardians. Children with physical limitations (such as orthopedic problems, injuries, blindness, or debilitating chronic conditions) or cognitive/behavioral issues (such as hyperactivity or uncontrolled cognitive disorders) that would prevent participation in the planned activities or hinder comprehension of the assessments were excluded from the study. Sample size To determine the sample size for the study, the sample size required to detect a group-by-time interaction was calculated via the “pwrss” package in R. A small to moderate expected effect size (partial 𝜂² = 0.03), a statistical power of 80%, and a significance level of 5% were considered. The initial calculation indicated that 81 participants would be needed. The sample size was then adjusted to account for the design effect (DE) associated with cluster randomization (schools), using an intracluster correlation coefficient (ICC) of 0.05 [ 45 ]. The design effect calculation resulted in an adjusted sample size of 132 participants. Finally, after accounting for an expected dropout rate of 20%, the final sample size adjusted for dropout was 165 participants. Training and intervention support Teachers in the intervention schools were invited to participate in a 48-hour training course, divided into four modules, provided by the project team. The sessions took place between July and October 2022, were conducted both in person and online, and were tailored to the type of intervention (physically active lessons and active breaks). The training was structured into two modules before the interventions, covering both theoretical and practical sessions (concepts, definitions, organization, and planning), and two modules during the interventions (monitoring, discussing challenges, problem-solving, and sharing experiences). To support implementation, teachers were provided with educational materials, including ideas for activities, adapted lesson plans, and suggestions on how to modify the interventions to suit their specific contexts. Additionally, an intern was assigned to each school. The interns were undergraduate students, and their primary role was to conduct assessments and, in the case of intervention schools, to offer support to teachers whenever possible. All the interns underwent both in-person and remote training sessions on data collection procedures. Intervention All the students in the intervention classes participated in the activities, but only the students who were part of the sample were assessed. The interventions took place particularly on days without physical education classes (two days a week), as these are the days when children spend more time sitting during school. For schools with physically active lessons, the teachers replaced sedentary lessons with lessons that integrated physical activity into the pedagogical content [ 46 ]. Adapted lesson plans were provided to the teachers, including strategies for incorporating movement into portuguese language and math content (e.g., teaching content through folk games). The physically active lessons were designed to have the same duration as a typical daily lesson, ranging from 30–50 minutes. Initially, the teachers were instructed to conduct at least one physically active lesson per day, gradually increasing as they became more engaged and familiar with the interventions. For the schools assigned for active breaks, the teachers were instructed to interrupt classroom activities or tasks after extended periods where the children remained seated (approximately 60 minutes). These breaks were designed to disrupt prolonged sitting by incorporating short sessions of moderate-intensity physical activity within the class. Each session lasted 5 to 10 minutes and followed a structure consisting of three phases: preparation, physical activity, and relaxation. In the preparation phase, which lasted between 1 and 4 minutes, the students stood next to their desks while the teacher explained the activity, with the duration varying based on the time needed to explain the task. The physical activity phase, lasting 2 to 3 minutes, included various exercises, such as aerobics (e.g., jumping jacks), strength and resistance exercises (e.g., squats), and playful activities, such as simple choreographies, mimicking movements, and active games. To reduce arousal after physical activity and redirect attention back to the previous task, cool-down exercises (e.g., stretches, breathing exercises) were performed during the final relaxation phase, which lasted 2–3 minutes. Teachers were instructed to implement at least one break per lesson or after 60 consecutive minutes of prolonged sitting (approximately two breaks per day), which gradually increased as they became more engaged and familiar with the interventions. Control For the control schools, the teachers did not participate in any training sessions and were instructed to maintain their usual lessons without any changes to their routines. Data collection procedures Data collection took place at the schools and was conducted by the project interns. The children were taken out of the classroom one at a time and led to the assessment area. To minimize the time spent away from class, the tests were divided into sessions of approximately 30 minutes. Therefore, children had to return multiple times on different days during the data collection weeks to complete all the study assessments. Both the cognitive performance tests and questionnaires were administered on computers/laptops. Primary outcome assessment Cognitive performance Five executive functions were assessed: inhibitory control via the Go/NoGo paradigm [ 51 ]; working memory, which was evaluated via the nonverbal digit span forward test paradigm [ 52 ]; selective attention, which was assessed via the visual search test paradigm [ 53 ]; spatial orientation, which was evaluated via the Posner Cueing test [ 54 , 55 ]; and spatial reasoning, which was assessed via the mental rotation test paradigm [ 56 ]. For all the tests, computerized versions were used, programmed with a Psytoolkit [ 47 , 48 ], and made available via JATOS [ 49 ]. The number of correct responses and reaction time (in milliseconds) for each test were used as indicators of cognitive performance. [for more details, see Additional File 3]. Secondary outcomes assessed Steps daily For the objective assessment of physical activity, Omron HJA-310 pedometers were used for seven consecutive days. The participants received information sheets with instructions before wearing the pedometer. Data were recorded on the total number of steps during the week (including weekdays and weekends) as well as the number of steps taken when the children arrived at school and before leaving (number of steps taken during school hours). For this study, valid information for total weekly steps was defined as at least two weekdays and one weekend day. Additionally, daily values ranging from a minimum of 1,000 steps to a maximum of 30,000 steps were considered valid [ 50 ]. For steps at school, at least two days of use were needed, and to ensure that the device was used during school hours, daily values ​​of fewer than 100 steps were not considered valid. Physical activity and screen-based activity As a subjective measure, the daily frequency of physical activity (DFPA) and screen-based activity (DFSA) was assessed via the electronic School-Aged Children’s Dietary and Physical Activity Questionnaire (WEB-CAAFE), a web-based questionnaire in which the child recalls the type, frequency and intensity of the physical activities performed in the morning, afternoon and evening of the previous day [ 51 ]. For this study, the self-reported frequency of physical activity was obtained by summing the reports of active play (i.e., play involving at least moderate physical activity, such as playing a ball), structured physical activity (i.e., physical activities monitored by a teacher or coach, such as swimming), and household chores (i.e., physical activities considered household tasks, such as sweeping). For example, if a participant reported playing in the park in the morning, playing tag in the afternoon, and playing with a dog in the evening, their total count for active play was 3. The frequency of screen-based activity was obtained by summing reports of screen use (smartphone, tablet, TV, laptop) across the three time periods (morning, afternoon, and evening). Quality of Life To assess the children's quality of life, the Autoquestionnaire Qualité de Vie Enfant Imagé (AUQEI) [ 52 ], validated for Brazilian children [ 53 ], was used. The questionnaire consists of 26 questions and generates a score ranging from zero to 78 points, with a higher score indicating a better perception of quality of life. Daytime Sleepiness To evaluate daytime sleepiness, the Pediatric Daytime Sleepiness Scale (PDSS) [ 54 ], translated and validated into Brazilian Portuguese [ 55 ], was used. The questionnaire consists of eight questions and generates a score ranging from zero to 32 points, with a higher score indicating greater daytime sleepiness. School Perception To assess students' perceptions of school, a questionnaire was used to gauge the child's satisfaction with the school, teacher, and classroom tasks. Responses were given on a five-point visual analog scale, where facial expressions 1 and 2 were negative, 4 and 5 were positive, and 3 was neutral. For the analysis, responses were considered continuous values, where a higher score indicated greater satisfaction. Demographics and anthropometrics During baseline, information on sex (male or female) and age (date of birth) was collected. Additionally, measurements of body weight (Seca® scale; accuracy of 0.1 kg) and height (accuracy of 0.1 cm) were taken via standardized procedures at each assessment point. Based on these measurements, body mass index was calculated via the following equation: kg/m². Statistical analyses All analyses employed the intention-to-treat (ITT) method without data imputation, considering the information of all children regardless of missing data at any time point. The outliers were addressed via the winsorization technique [ 56 ], which prevents the permanent loss of extreme values by adjusting them to acceptable limits. A limit of three standard deviations was used for the minimum and maximum values. Descriptive analyses are presented as relative and absolute frequencies, means, and standard deviations. Data normality was verified via the Shapiro‒Wilk test. To compare baseline measurements between groups, one-way ANOVA or Kruskal‒Wallis test was used for continuous variables, and Pearson's chi‒square test was used for categorical variables. Generalized estimating equation (GEE) models with Gamma distributions (Poisson for count outcomes), and exchangeable working correlations were implemented via the glmgee function from the glmtoolsbox package to assess the effects of interventions (CTL, PAL, and AB) over time (baseline and follow-up) on the outcomes. The choice of GEE was made because of its advantages: it does not require normality of distributions, allows for the analysis of correlated observations, and accommodates missing data over time in the model [ 57 ]. For models with significant group-by-time interactions, post hoc comparisons were performed via contrast functions from the emmeans package. Additionally, partial eta squared (𝜂²) was calculated for the effect size of the group-by-time interaction in the GEE models. Cohen's d, as suggested by Becker [ 58 ], was calculated to determine the effect size of the mean differences between baseline and follow-up for each group in the post hoc comparisons. Furthermore, intracluster correlation coefficients (ICCs) of schools were reported, obtained from unadjusted follow-up raw scores via the clus.rho function from the FishMethods package, adjusted for clusters with unequal sample sizes. All analyses were conducted via R version 4.4.0 within the RStudio integrated development environment. A significance level of p < 0.05 was adopted for all analyses. Results Baseline characteristics of the participants The recruitment and data collection flowcharts are presented in Fig. 2. Out of the 345 first-grade children eligible across the six schools, 184 children (53.3%) returned with a signed informed consent form from their parents. The active lessons group included 77 children, the active breaks group included 61 children, and the control group included 46 children. The characteristics of the children in the groups are presented in Table 1 , with participants having an average age of 6.9 ± 0.6 years and 52.7% being girls. Differences at baseline between groups were observed for height (p < 0.001), school shift (p < 0.001), mental rotation test (number of hits: p = 0.012; reaction time: p < 0.001), steps at school (p = 0.003), frequency of physical activity, and screen-based activity (p < 0.001). Further details are available in Supplementary Table 1 of Supplementary Material 4. [Insert Fig. 2] Figure 2. Flow diagram - CONSORT. Table 1 Characteristics of participating children at baseline (N = 184). CTL (n = 46) PAL (n = 77) AB (n = 61) p All Demographic Age, years 7.2 ± 0.9 6.8 ± 0.4 6.9 ± 0.3 .106 6.9 ± 0.6 Sex (%) Boys 25 (54.3) 34 (44.2) 28 (45.9) .530 87 (47.3) Girls 21 (45.7) 43 (55.8) 33 (54.1) 97 (52.70 Anthropometric Height, m 1.21 ± 0.09 1.16 ± 0.07 1.16 ± 0.08 < .001 1.17 ± 0.08 Weight, kg 25.5 ± 6.6 23.8 ± 5.4 24.2 ± 6.3 .235 24.4 ± 6.0 BMI, kg/m 2 17.3 ± 2.9 17.7 ± 3.1 17.9 ± 3.9 .718 17.6 ± 3.3 School additional information School shift (%) Morning 12 (26.1) 51 (66.2) 38 (62.3) < .001 101 (54.9) Afternoon 34 (73.9) 26 (33.8) 23 (37.7) 83 (45.1) [Insert Table 1 ] Main outcome Significant interactions between group and time were observed in four out of the five tests conducted (Table 2 ). For the test Go/NoGo (reaction time: p = 0.045; partial 𝜂² = 0.02), DigitSpan (correct responses: p = 0.020; partial 𝜂² = 0.01), Mental Rotation (reaction time: p = 0.049; partial 𝜂² = 0.02), and Cueing Posner (reaction time: p = 0.012; partial 𝜂² = 0.03). Table 2 Estimated marginal means for the primary outcomes of each group and results from the generalized estimating equation (GEE) models. Outcome Estimated marginal means GEE (group by time) N Baseline Follow-up P Partial 𝜂² ICC Go/NoGo Correct responses (hits) a,b CTL 44 23.7 (0.2) 24.3 (0.2) .218 .01 .03 PAL 77 23.1 (0.2) 23.9 (0.1) AB 60 23.4 (0.2) 23.8 (0.2) Time reaction (milliseconds) a,b CTL 44 913.4 (33.4) 875.2 (41.6) .045 .02 .16 PAL 77 833.9 (23.6) 729.5(22.7) AB 60 886.1 (31.0) 886.2 (31.0) DigitSpan Correct responses (hits) CTL 46 2.2 (0.2) 2.1 (0.2) . 020 .01 .07 PAL 77 2.3 (0.2) 2.9 (0.2) AB 59 2.3 (0.2) 2.2 (0.2) Mental Rotation Correct responses (hits) CTL 44 12.7 (0.4) 12.0 (0.4) .242 .01 < .001 PAL 77 11.8 (0.3) 12.1 (0.2) AB 60 12.1 (0.3) 12.4 (0.2) CTL 44 5887.6 (365.2) 5314.1 (335.1) .049 Time reaction (milliseconds) a,b PAL 77 7068.0 (310.6) 5100.5 (173.4) .02 .03 AB 60 7354.4 (353.2) 5876.6 (183.6) Cueing Posner Correct responses (hits) CTL 39 23.6 (0.3) 23.5 (0.3) .260 .01 .01 PAL 77 23.3 (0.2) 23.9 (0.2) AB 60 23.9 (0.2) 24.3 (0.2) Time reaction (milliseconds) b CTL 39 1788.9 (102.8) 1606.1 (54.6) .017 .03 .01 PAL 77 1889.6 (64.1) 1503.2 (36.7) AB 60 1655.8(56.6) 1497.8 (48.8) Visual Search Correct responses (hits) CTL 44 6.5 (0.2) 6.7 (0.3) .988 .00 .07 PAL 77 6.8 (0.2) 6.9 (0.2) AB 60 6.9 (0.2) 7.1 (0.2) Time reaction (milliseconds) b CTL 44 3941.1 (201.9) 3137.6 (188.7) .076 .02 .08 PAL 77 3943.8 (132.1) 3088.2 (108.9) AB 60 3932.5 (189.9) 3590.4 (140.0) Note : The estimated marginal means and standard errors are based on generalized estimating equation (GEE) models and their respective adjustments. The GEE models were adjusted for age and sex. The interpretation of the partial 𝜂² effect size is as follows: small if < 0.06, medium if between 0.06 and 0.14, and large if ≥ 0.14. CTL, control PAL, physically active lesson AB, active break a, statistically significant for the main effect of group b, statistically significant for the main effect of time p < .05, statistically significant. [Insert Table 2 ] Changes over time (follow-up minus baseline) for the main outcomes that showed significant interactions between groups and time are shown in Fig. 3. For inhibitory control (Fig. 3A), a significant reduction in the average reaction time on the Go/NoGo test was observed in the physically active lesson group (∆ = -104.5 ms; p < 0.001; d = 0.50). No significant difference was found in the active breaks (∆ = 0.1 ms; p = 0.996; d = 0.00) or control groups (∆ = -38.2 ms; p = 0.372; d = 0.17). For working memory (Fig. 3B), a significant increase in the average number of correct responses on the DigitSpan test was observed in the physically active lesson group (∆ = 0.62 hits; p < 0.001; d = 0.44), whereas the active breaks (∆ = -0.08 hits; p = 0.698; d = 0.06) and control groups (∆ = -0.11 hits; p = 0.683; d = 0.08) did not significantly differ. For spatial reasoning (Fig. 3C), significant changes in reaction time on the mental rotation test were identified for the physically active lesson group (∆ = -1967.5 ms; p < 0.001; d = 0.72) and the active break group (∆ = -1477.8 ms; p < 0.001; d = 0.54), whereas no significant differences were observed in the control group (∆ = -573.5 ms; p = 0.186; d = 0.24). For spatial orientation (Fig. 3D), significant changes in reaction time on the Cueing Posner test were identified in all groups: physically active lessons (∆ = -386.4 ms; p < 0.001; d = 0.69), active breaks (∆ = -157.9 ms; p = 0.007; d = 0.36), and control (∆ = -182.8 ms; p = 0.20; d = 0.28), with a greater effect in the active lessons group. No significant changes in other cognitive indicators were observed. Further details can be found in Supplementary Table 2 of Supplementary Material 4. [Insert Fig. 3] Figure 3. Boxplot and effect size for post hoc comparisons between baseline and follow-up data by group. The boxplots display the median and the 25th and 75th percentiles without adjustment (raw score). Circles and squares represent the results of each child according to their school. The point ranges represent the difference (∆) and their respective confidence intervals. Cohen's effect size was based on GEE models, with the following interpretation: small if < 0.50, medium if between 0.50 and 0.80, and large if ≥ 0.80. Secondary outcomes Most secondary outcomes did not show statistical significance for the interaction between group and time (Table 3 ), except for the DFPA (p = 0.002; partial 𝜂² = 0.04) and daytime sleepiness (p = 0.004; partial 𝜂² = 0.04). Since the school shift was significant in the models for these two outcomes (p < 0.001), we repeated the analyses by adding the interaction term group vs. time vs. shift to examine any potential moderating effect of the school shift. However, the interaction term was not significant [daily frequency of physical activity (p = 0.979); daytime sleepiness (p = 0.494)]. Table 3 Estimated marginal means for the secondary outcomes of each group and results from the generalized estimating equation (GEE) models. Outcome Estimated marginal means GEE (group by time) N Baseline Follow-up P Partial 𝜂² ICC Steps At school (step/day) a CTL 41 1724.5 (146.3) 1746.3 (148.4) 0.383 .01 .40 PAL 73 1330.2 (105.9) 1137.4 (55.5) AB 58 1767.4 (116.7) 1621.8 (110.4) In the week (step/day) b CTL 40 7089.5 (455.0) 6244.7 (469.2) 0.564 .00 − .02 PAL 61 6816.3 (320.5) 6605.3 (377.6) AB 55 7044.9 (388.8) 6395.8 (399.9) Web-CAAFE (self-reported) Physical activity (frequency) a CTL 46 3.8 (0.4) 4.0 (0.6) 0.002 0.04 .12 PAL 77 2.4 (0.2) 2.3 (0.2) AB 61 4.8 (0.3) 3.2 (0.3) Screen-based activity (frequency) a CTL 46 1.3 (0.2) 1.9 (0.3) 0.071 0.02 .10 PAL 77 2.1 (0.1) 1.8 (0.1) AB 61 1.7 (0.1) 1.5 (0.2) Quality of life AUQEI Score (0–78 points) CTL 45 56.2 (1.3) 53.4 (2.1) 0.129 0.01 .12 PAL 77 53.7 (0.9) 54.0 (0.9) AB 60 52.1 (1.1) 53.9 (1.2) Daytime Sleepiness PDSS Score (0–32 points) CTL 43 14.0 (1.0) 11.8 (0.9) 0.004 0.04 .32 PAL 77 9.9 (0.6) 12.0 (0.7) AB 59 10.5 (1.0) 12.8 (0.9) School perception School (Likert Scale 1–5) a, b CTL 43 4.8 (0.1) 4.8 (0.1) 0.082 0.02 .12 PAL 77 4.8 (0.1) 4.7 (0.1) AB 60 4.7 (0.1) 4.1 (0.2 Teacher (Likert Scale 1–5) CTL 43 4.5 (0.2) 4.6 (0.1) 0.095 0.01 − .02 PAL 77 4.5 (0.1) 4.6 (0.1) AB 60 4.8 (0.1) 4.6 (0.1) Task in the classroom (Likert Scale 1–5) b CTL 43 4.3 (0.2) 4.1 (0.2) 0.124 0.01 .11 PAL 77 4.4 (0.1) 4.4 (0.1) AB 60 4.3 (0.2) 3.8 (0.2) Note : The estimated marginal means and standard errors are based on generalized estimating equation (GEE) models and their respective adjustments. The GEE models were adjusted for age, sex and school shift. The interpretation of the partial 𝜂² effect size is as follows: small if < 0.06, medium if between 0.06 and 0.14, and large if ≥ 0.14. CTL, control PAL, physically active lesson AB, active break a, statistically significant for the main effect of group b, statistically significant for the main effect of time p < .05, statistically significant. [Insert Table 3 ] For the DFPA (Fig. 3E), the active breaks group showed a reduction in the total self-reported physical activity frequency during the previous day (∆ = -1.5 frequency; p < 0.001; d = 0.60), whereas no differences were observed for the physically active lessons group (∆ = -0.1 frequency; p = 0.643; d = 0.05) or the control group (∆ = 0.2 frequency; p = 0.761; d = 0.07). With respect to daytime sleepiness (Fig. 3F), children in the physically active lessons and active breaks groups reported increased feelings of excessive sleepiness during the day [(∆ = +2.2 score; p = 0.045; d = 0.45); (∆ = 2.3 score; p = 0.006; d = 0.31), respectively], whereas no significant differences were found for the control group (∆ = − 2.2 score; p = 0.067; d = 0.34). Further details can be found in Supplementary Table 2 of Supplementary Material 4. Discussion Our primary objective was to investigate the effects of physically active lessons and active breaks on executive functions and health indicators in elementary school children. To the best of our knowledge, this is the first study to examine these two different strategies of school-based physical activity interventions on the executive functions of first-grade children from a low socioeconomic status region in a middle-income country. The results of the cognitive tests revealed positive effects of physically active lessons on various executive functions. In inhibitory control, as measured by the Go/NoGo test, a significant reduction in reaction time was observed in the physically active lesson group, suggesting an improvement in the ability to inhibit impulsive responses. In working memory, as assessed through the DigitSpan test, the physically active lesson group presented a significant increase in the number of correct responses, indicating a better ability to maintain and manipulate information mentally. Inhibitory control and working memory are cognitive functions associated with the prefrontal cortex [ 35 ]. The importance of these executive functions for academic performance is well established, as these skills are essential for complex tasks, problem solving, and effective learning [ 59 ]. Our findings align with evidence reported in the literature, with recent studies identifying positive effects of physically active lessons on cognitive functions such as inhibitory control [ 27 , 28 ] and working memory [ 31 , 32 ]. Notably, studies [ 27 , 28 ] were conducted with Brazilian children. However, the present study advances the field by increasing the sample size and randomizing the schools. With respect to spatial reasoning, as assessed with the mental rotation test, significant improvements were found in both the physically active lessons and the active breaks groups, with the effects being more pronounced in the physically active lessons group. Spatial reasoning plays a crucial role in learning disciplines such as science, technology, engineering, arts, and mathematics, as it involves skills in visualizing and manipulating shapes and spaces, which are essential for understanding these concepts [ 60 ]. However, it is important to exercise caution when interpreting these results, as both the physically active lesson group and the active break group started with performance levels significantly below those of the control group. Thus, the significant improvement may have been influenced by the large margin for growth, meaning that there was more room for substantial improvement. Finally, in spatial orientation, as measured by the Cueing Posner test, significant improvements were observed in all three groups, with the effect being more pronounced in the physically active lesson group for the time of reaction. The Cueing Posner test evaluates the ability to voluntarily and quickly direct attention to a specific location in space on the basis of visual cues [ 61 , 62 ]. This skill is crucial for learning, as it allows students to focus their attention on relevant information and ignore distractions, thereby facilitating efficient and effective information processing. One of the mechanisms that explains how physical activity can improve cognitive functions is increased activation of the prefrontal cortex when physical activity is performed at moderate to vigorous intensity levels [ 35 , 63 , 64 ]. This increase in brain activity is associated with improvements in executive functions [ 65 ]. Studies on isotemporal substitutions suggest that replacing prolonged sitting time with light physical activity can contribute to the enhancement of cognitive functions [ 66 ]. Although the intensity of the interventions in the present study was not measured, replacing sedentary time with light physical activity may have played a crucial role in improving executive functions, particularly in the group with physically active lessons. The activities suggested in the materials provided and the planning discussed during the training sessions included movements during the learning process (for example, when teaching syllables, children formed words through popular games such as 'hopscotch'). Thus, the implementation of a more dynamic and playful lesson structure, where students spend less time sitting and more time engaging in light physical activity, may explain the positive results found in the group with physically active lessons. Furthermore, physically active lessons provide learning through movement, meaning that movement is integrated into one or more partial processes of learning a specific knowledge or skill. This could be another factor that enhances the positive effects on cognitive abilities, as learning through movement not only increases task engagement but also promotes socialization and makes the learning environment more dynamic, providing a more interactive and engaging context. The simultaneous activation of multiple brain areas during learning through movement may favor information retention and effective learning [ 67 ]. On the other hand, the active breaks in this study focused primarily on interrupting prolonged sitting time without involving pedagogical content or cognitive engagement. Consequently, the results for cognitive functions were less pronounced. A possible explanation seems to be related to the type of activity performed, as activities with more cognitively engaging components [ 29 , 38 ] or those combined with the curriculum [ 23 ] have shown improvements in cognitive functions compared with active breaks with purely physical activity components [ 39 , 68 ]. Some unexpected results were observed in this study regarding self-reported daily total physical activity frequency during the previous day and daytime sleepiness. The active breaks group showed a reduction in self-reported total physical activity frequency during the previous day. Initially, children in the active breaks group reported a greater frequency of self-reported physical activity during the previous day than did those in the physically active lessons and control groups. Therefore, this change should be interpreted with caution. Additionally, the number of steps taken during the week did not differ between the groups over time, indicating that the level of physical activity performed during the breaks may not have been compensated by less activity throughout the day. However, a more detailed investigation, such as the use of accelerometers, could help researchers better understand these results. With respect to daytime sleepiness, children in the physically active lessons and active break groups reported an increase in daytime sleepiness. This increase was unexpected; however, owing to the nature of the interventions, other unmeasured factors may have influenced the children's daytime sleepiness. Although the school shift did not moderate the observed effects, it did explain part of the observed changes. Information such as sleep duration, use of electronics before bedtime, and bed and wake-up times, among others, would help us better understand these changes, given that previous evidence has associated daytime sleepiness with the number of hours of sleep [ 69 ] and the use of electronics before bedtime [ 70 ]. Limitations and strengths The study had limitations that should be considered. First, to allow for greater external validity of the interventions, some decisions were made to ensure implementation primarily within the educational reality of each school. For example, teachers were instructed to implement the interventions as frequently as possible autonomously. Unlike other studies where teachers are directed to include a fixed number of interventions, in the present study, teachers had the freedom to schedule the activities as they wished. The implementation of the interventions gradually increased in frequency over the weeks. However, as there was no daily control of how often the activities were implemented, it is possible that the activities were carried out at various frequencies and times. We also note that some uncollected information, such as sitting time, hours of sleep, and socioeconomic information, could have provided additional context for the participants. On the other hand, the study had strengths such as being a cluster-randomized clinical trial, which allows for more robust inferences about causality. Additionally, this was the first study to compare the effectiveness of two physical activity interventions in the classroom in a middle-income country in South America, thus expanding the knowledge in this area. Cognitive functions were assessed via standardized tests, which increases the reliability of the results and allows comparisons with other studies. Furthermore, information was collected on behaviors outside the school context, providing a comprehensive view of the reach of the interventions. Practical implications The positive results associated with physically active lessons indicate that more dynamic and engaging strategies implemented in the classrooms of elementary schools can effectively promote children's cognitive development. Promoting activities that involve physical movement may offer an effective approach to stimulating specific brain areas associated with executive functions. However, when implementing these interventions, it is important to consider the diverse nature of the activities, aiming for those that not only provide physical activity for children but also offer cognitive stimulation. This suggests a shift in the educational paradigm, encouraging methods that integrate movement and learning synergistically. Conclusion These results indicate that physically active lessons can improve inhibitory control, working memory, spatial orientation, and spatial reasoning in elementary school children. While less effective, active breaks still represent a viable strategy with no harmful effects. However, further research is needed on long-term effects to determine best practices for implementing these interventions in schools. Abbreviations DFPA: Daily frequency of physical activity; PAL: Physically active lesssons; AB: Active Break; CTL: Control Declarations Acknowledgement The authors thank the children, principals, coordinators, and teachers from the schools that participated in the study. Also, thanks to the Municipal Department of Education of Aracaju for their support and for facilitating scholarships for the interns. The authors acknowledge all the interns who assisted in data collection, especially Alana Cerqueira, Amanda Vasconcelos, Bianca Ivo, Camile Souza, Felipe Rocha, Guilherme Santos, Isis Correia, and Luana Silveira. The authors also thank Beatriz Nóia and Marcel Belitardo for their assistance in teacher training. Additionally, the authors express their gratitude to Professor Dra. Thayse Gomes and Dra. Heike Schmitz, for their collaboration on the conceptualization and design of the study. We also thank Professors Dra. Clarice Martins and Dr. Diogo Araújo for their contributions to the initial draft. Authors’ contributions JCNM, JT, and DRPS conceived the study design and concept. JCNM conducted the study as part of their master's degree under the supervision of JT and DRPS. JCNM analyzed the data and prepared the results with review by JT and DRPS. JCNM prepared the first draft under the supervision of DRPS. JT, ECMS, JYVN, DNO, LG, and DRPS critically revised and improved the manuscript. All authors reviewed and approved the final manuscript. Funding The information and opinions contained in this Article do not necessarily reflect the views or policies of the supporting organizations. JCNM and ECMS were supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) with PhD scholarships (Process numbers: 88887.950448/2024-00 and 88887.605029/2021-00, respectively). JY, DNO, and LG were supported by CAPES with master's degree scholarships (Process numbers: 88887.808021/2023-00, 88887.947469/2024-00, and 88887.829680/2023-00, respectively). This study was financed in part by the Foundation for the Support of Research and Technological Innovation of the State of Sergipe (FAPITEC/SE: 019203.00717/2020-8) and the National Council for Scientific and Technological Development (CNPq: 404791/2023-9). The funding bodies had no role in the design of the study, the collection, analysis, or interpretation of data, or in writing the manuscript. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was carried out in accordance with the principles of the Declaration of Helsinki. The study received approval from the Human Research Ethics Committee of the Federal University of Sergipe (Approval Number: 5.301.398). Written informed consent from parents or legal guardians was obtained, and all participants provided written consent before the baseline data collection. Consent for publication As part of the informed consent process, parents or legal guardians provided written consent for their child’s data to be used in this research study, including the publication of findings in scientific journals. 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Supplementary Files SupplementaryMaterial1.docx SupplementaryMaterial2.docx SupplementaryMaterial3.docx SupplementaryMaterial4.docx Cite Share Download PDF Status: Published Journal Publication published 09 Jul, 2025 Read the published version in International Journal of Behavioral Nutrition and Physical Activity → Version 1 posted Editorial decision: Revision requested 13 Mar, 2025 Reviews received at journal 06 Mar, 2025 Reviews received at journal 28 Feb, 2025 Reviewers agreed at journal 05 Feb, 2025 Reviewers agreed at journal 29 Jan, 2025 Reviewers invited by journal 27 Jan, 2025 Editor assigned by journal 13 Jan, 2025 Submission checks completed at journal 13 Jan, 2025 First submitted to journal 10 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5804150","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":401812102,"identity":"3ae1c873-77bf-4c1d-88e2-ed2b9d1c4ed3","order_by":0,"name":"João Carlos Nascimento Melo","email":"","orcid":"","institution":"Programa de Pós-Graduação em Ciências da Saúde, Universidade Estadual de Londrina (UEL)","correspondingAuthor":false,"prefix":"","firstName":"João","middleName":"Carlos Nascimento","lastName":"Melo","suffix":""},{"id":401812103,"identity":"9d06f16a-ad4e-4d7a-979f-4cfb4ab2252e","order_by":1,"name":"Julian Tejada","email":"","orcid":"","institution":"Departamento de Psicologia, Universidade Federal de Sergipe (UFS)","correspondingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Tejada","suffix":""},{"id":401812104,"identity":"85ea6c5b-b584-4f33-9e76-03a841666557","order_by":2,"name":"Ellen Caroline Mendes Silva","email":"","orcid":"","institution":"Programa de Pós-Graduação em Ciências da Saúde, Universidade Estadual de Londrina (UEL)","correspondingAuthor":false,"prefix":"","firstName":"Ellen","middleName":"Caroline Mendes","lastName":"Silva","suffix":""},{"id":401812105,"identity":"7b93bba0-faf8-4684-8bc9-136af495a956","order_by":3,"name":"José Ywgne Vieira do Nascimento","email":"","orcid":"","institution":"Programa de Pós-Graduação em Educação Física, Universidade Federal de Sergipe (UFS)","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"Ywgne Vieira do","lastName":"Nascimento","suffix":""},{"id":401812106,"identity":"8d27b782-4247-4c6e-ad30-2350f662d648","order_by":4,"name":"David Nunes Oliveira","email":"","orcid":"","institution":"Programa de Pós-Graduação em Educação Física, Universidade Federal de Sergipe (UFS)","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"Nunes","lastName":"Oliveira","suffix":""},{"id":401812107,"identity":"e827eeb9-377a-48e2-bc65-9d00e496f0ca","order_by":5,"name":"Larissa Gandarela","email":"","orcid":"","institution":"Programa de Pós-Graduação em Educação Física, Universidade Federal de Sergipe (UFS)","correspondingAuthor":false,"prefix":"","firstName":"Larissa","middleName":"","lastName":"Gandarela","suffix":""},{"id":401812108,"identity":"9f24439a-bbe8-49cd-b637-54350a9582fb","order_by":6,"name":"Danilo Rodrigues Pereira da Silva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDCCA0D0AMRgZm5gYKiAMQhpSQBrYQSqPANjENDCANbCAFTJ2AZl4AN8x88ePJBQcS9Pvp2xTeLnvNpo/naglh8V23BqkTyTl3Ag4UxxscFhxjbJ3m3Hc2ccZmxg7DlzG6cWgwM5BgcS2xISNzAzNhvwbjuW2wDUwszYhkfL+TcQLfObGZsN/845ljufoJYbUFuAhjc+5m2oyd1ASIvkDaAtCWcSQH5pfCxz7EDuRqCWg/j8wnc+x/jDh4qEPPn+wwcOvqmpy513/vDBBz8qcGuBgQQofRhMHiCoHklLHTGKR8EoGAWjYIQBAMLtZmTy9s0YAAAAAElFTkSuQmCC","orcid":"","institution":"Departamento de Educação Física, Universidade Federal de Sergipe (UFS)","correspondingAuthor":true,"prefix":"","firstName":"Danilo","middleName":"Rodrigues Pereira da","lastName":"Silva","suffix":""}],"badges":[],"createdAt":"2025-01-10 13:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5804150/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5804150/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12966-025-01789-6","type":"published","date":"2025-07-09T15:58:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":73871623,"identity":"c648d959-488c-4456-b23d-8aa7b0d3b05f","added_by":"auto","created_at":"2025-01-15 12:24:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":617912,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the study design. (A) Schematic showing the study protocol timeline. (B) Description of the interventions.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/dc4d459d2dda4c134facadce.png"},{"id":73871662,"identity":"b3c0c772-5fb0-4993-b4a7-6e8c5e9abc4c","added_by":"auto","created_at":"2025-01-15 12:24:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":424205,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram - CONSORT.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/c643a317433cb4fc6c06ca83.png"},{"id":73871673,"identity":"836c1dc3-6a61-4f86-93b5-21490f699f80","added_by":"auto","created_at":"2025-01-15 12:24:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":728657,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplot and effect size for post hoc comparisons between baseline and follow-up data by group. The boxplots display the median and the 25th and 75th percentiles without adjustment (raw score). Circles and squares represent the results of each child according to their school. The point ranges represent the difference (∆) and their respective confidence intervals. Cohen's effect size was based on GEE models, with the following interpretation: small if \u0026lt; 0.50, medium if between 0.50 and 0.80, and large if ≥ 0.80.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/3805b41be775cd40919eef49.png"},{"id":86699656,"identity":"98a1e678-dae5-476f-916e-5ebf96fd79e1","added_by":"auto","created_at":"2025-07-14 16:11:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3048573,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/23eefe52-82fa-4610-aab5-f8c732a5b1e7.pdf"},{"id":73872934,"identity":"82051c3e-8a02-4c39-85f1-bbe83ef8327a","added_by":"auto","created_at":"2025-01-15 12:32:09","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":42360,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/f898221b716571a804517c90.docx"},{"id":73872936,"identity":"6dc495d1-6183-4ec5-beef-04a8774a6fdd","added_by":"auto","created_at":"2025-01-15 12:32:11","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":30316,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/2f213665cd7c74056216754f.docx"},{"id":73871661,"identity":"0691e412-a788-4aad-bc67-15b3bc1e650c","added_by":"auto","created_at":"2025-01-15 12:24:11","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":425904,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/bee2ee8641ea35fe77a051f3.docx"},{"id":73871621,"identity":"ffa921b9-e2a9-486c-acb8-a9cb5297553d","added_by":"auto","created_at":"2025-01-15 12:24:09","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":23862,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial4.docx","url":"https://assets-eu.researchsquare.com/files/rs-5804150/v1/e9a7f167d18eeb7dc6241f0e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of physically active lessons and active breaks on cognitive performance and health indicators in elementary school children: A cluster randomized trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe increase in the number of studies on sedentary behavior over the past few years reflects its recognition as a public health issue [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While the implications of this behavior are better understood in adults [\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], there is growing evidence regarding the adverse effects of prolonged sitting in children, including obesity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], elevated systolic and diastolic blood pressure [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], impaired vascular [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and cerebrovascular [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] impaired motor abilities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and reduced sleep duration [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Such evidence has driven the implementation of policies and international recommendations to reduce sedentary behavior, particularly during childhood and adolescence [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], given that critical periods for establishing habits and lifestyles at this age are likely to persist throughout life [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, schools have been the focus of research and interventions aimed at reducing sedentary behavior [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], largely because of the significant amount of daily time that this population spends in this setting [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and because, in more traditional teaching models, classroom layouts tend to encourage prolonged periods of sitting among students [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Thus, strategies aimed at replacing sedentary behavior with physical activity and optimizing classroom time have been a focal point for researchers [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The integration of physical activity in the classroom can occur in various forms [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], including active breaks [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (i.e., short intervals during class for physical activities that may or may not be related to the curricular content) and physically active learning [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] (i.e., integrating physical activity into curricular content, such as teaching mathematics via body movement). These strategies have been suggested due to their low-cost nature [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], potential to reduce sedentary behavior [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], increase physical activity levels [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], improve academic performance [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and yield promising results in cognitive outcomes such as inhibitory control [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], working memory [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], attention [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and fluid intelligence [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, more specific data are still needed regarding certain types of cognitive processes related to problem-solving and decision-making. These processes encompass so-called executive functions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], which control goal-directed behaviors, assist in impulse control, and help maintain a focus on tasks. These functions are particularly important because of their relationship with the development of the frontal cortex, a brain region involved in various higher-order cognitive functions (such as risk assessment, language production, visual processing, and working memory), which undergo late development during adolescence [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The study of these functions could help clarify the evidence on cognitive outcomes, given that previous reviews have failed to reach robust conclusions owing to the heterogeneity of results [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, most research has been conducted in high-income countries, which may limit the generalizability of the findings to other educational contexts [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. For example, in Brazil, the existence of shorter school periods and poor infrastructure in schools, such as small classrooms and overcrowding [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], may pose critical limitations for the implementation of these interventions. Additionally, most studies have focused on a single type of intervention [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with few comparisons of the effects of different approaches [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. To the best of our knowledge, only two studies [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] have compared the effects of physically active lessons and active breaks in children. However, both studies were conducted in high-income countries and did not investigate cognitive outcomes; instead, they focused on children's mathematics performance.\u003c/p\u003e \u003cp\u003eThus, scientific gaps persist, particularly regarding the effects on executive functions, which have been suggested as an underlying mechanism to explain the positive effects on academic performance [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Additionally, further studies are needed to verify the transferability of the observed positive effects to other educational contexts, such as low- and middle-income countries, as well as studies comparing different types of interventions, particularly the differences between physically active lessons and active breaks. Therefore, the primary aim of the present study is to assess the effects of physically active lessons and active breaks on the executive functions of elementary school students, with the secondary objective of examining the effects on physical activity levels, quality of life, daytime sleepiness, and school perception.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe trial was reported in accordance with the CONSORT statement for cluster randomized trials [Supplementary Material 1] (Campbell et al., 2012) and the TIDieR Checklist for Reporting and Replicating Interventions [Supplementary Material 2].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA three-arm cluster-randomized clinical trial was conducted in public schools in the city of Aracaju, Brazil. The data from this study are part of the first year of the Erguer project (second wave) during the year 2022. The study received approval from the Human Research Ethics Committee of the Federal University of Sergipe (Approval Number: 5.301.398). Figure\u0026nbsp;1 illustrates the experimental design of the study, summarizing the main stages. Evaluations took place at two time points: the baseline assessment, conducted between March and July 2022, and a follow-up assessment after the interventions, carried out between November and December 2022. The interventions lasted eight weeks, starting in September after the initial assessments and the return from vacation, and ended in November 2022. The interventions were implemented by the classroom teachers themselves, directly in their classrooms. Training and support for teachers were provided by the project team between July and October 2022, combining in-person and online sessions.\u003c/p\u003e \u003cp\u003e[Insert Fig.\u0026nbsp;1]\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1.\u003c/b\u003e Schematic of the study design. (A) Schematic showing the study protocol timeline. (B) Description of the interventions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipant schools\u003c/h3\u003e\n\u003cp\u003eOne of the eight regions of the municipality of Aracaju [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] was randomly selected. All schools in this region, with at least two first-grade classes, were invited to participate. Six schools (100%) accepted the invitation and were randomly assigned to one of three groups: 1) an intervention group with physically active lessons (two schools); 2) an intervention group with active breaks (two schools); and 3) a control group (two schools).\u003c/p\u003e\n\u003ch3\u003eParticipant students\u003c/h3\u003e\n\u003cp\u003e After primary consent was obtained from the school, all first-grade children were invited to participate in the study. The inclusion criteria required that children be regularly enrolled in the selected schools and return the informed consent form duly signed by their parents or guardians. Children with physical limitations (such as orthopedic problems, injuries, blindness, or debilitating chronic conditions) or cognitive/behavioral issues (such as hyperactivity or uncontrolled cognitive disorders) that would prevent participation in the planned activities or hinder comprehension of the assessments were excluded from the study.\u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eTo determine the sample size for the study, the sample size required to detect a group-by-time interaction was calculated via the \u0026ldquo;pwrss\u0026rdquo; package in R. A small to moderate expected effect size (partial \u0026#120578;\u0026sup2; = 0.03), a statistical power of 80%, and a significance level of 5% were considered. The initial calculation indicated that 81 participants would be needed. The sample size was then adjusted to account for the design effect (DE) associated with cluster randomization (schools), using an intracluster correlation coefficient (ICC) of 0.05 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The design effect calculation resulted in an adjusted sample size of 132 participants. Finally, after accounting for an expected dropout rate of 20%, the final sample size adjusted for dropout was 165 participants.\u003c/p\u003e\n\u003ch3\u003eTraining and intervention support\u003c/h3\u003e\n\u003cp\u003eTeachers in the intervention schools were invited to participate in a 48-hour training course, divided into four modules, provided by the project team. The sessions took place between July and October 2022, were conducted both in person and online, and were tailored to the type of intervention (physically active lessons and active breaks). The training was structured into two modules before the interventions, covering both theoretical and practical sessions (concepts, definitions, organization, and planning), and two modules during the interventions (monitoring, discussing challenges, problem-solving, and sharing experiences). To support implementation, teachers were provided with educational materials, including ideas for activities, adapted lesson plans, and suggestions on how to modify the interventions to suit their specific contexts.\u003c/p\u003e \u003cp\u003eAdditionally, an intern was assigned to each school. The interns were undergraduate students, and their primary role was to conduct assessments and, in the case of intervention schools, to offer support to teachers whenever possible. All the interns underwent both in-person and remote training sessions on data collection procedures.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIntervention\u003c/h2\u003e \u003cp\u003eAll the students in the intervention classes participated in the activities, but only the students who were part of the sample were assessed. The interventions took place particularly on days without physical education classes (two days a week), as these are the days when children spend more time sitting during school.\u003c/p\u003e \u003cp\u003eFor schools with physically active lessons, the teachers replaced sedentary lessons with lessons that integrated physical activity into the pedagogical content [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Adapted lesson plans were provided to the teachers, including strategies for incorporating movement into portuguese language and math content (e.g., teaching content through folk games). The physically active lessons were designed to have the same duration as a typical daily lesson, ranging from 30\u0026ndash;50 minutes. Initially, the teachers were instructed to conduct at least one physically active lesson per day, gradually increasing as they became more engaged and familiar with the interventions.\u003c/p\u003e \u003cp\u003eFor the schools assigned for active breaks, the teachers were instructed to interrupt classroom activities or tasks after extended periods where the children remained seated (approximately 60 minutes). These breaks were designed to disrupt prolonged sitting by incorporating short sessions of moderate-intensity physical activity within the class. Each session lasted 5 to 10 minutes and followed a structure consisting of three phases: preparation, physical activity, and relaxation. In the preparation phase, which lasted between 1 and 4 minutes, the students stood next to their desks while the teacher explained the activity, with the duration varying based on the time needed to explain the task. The physical activity phase, lasting 2 to 3 minutes, included various exercises, such as aerobics (e.g., jumping jacks), strength and resistance exercises (e.g., squats), and playful activities, such as simple choreographies, mimicking movements, and active games. To reduce arousal after physical activity and redirect attention back to the previous task, cool-down exercises (e.g., stretches, breathing exercises) were performed during the final relaxation phase, which lasted 2\u0026ndash;3 minutes. Teachers were instructed to implement at least one break per lesson or after 60 consecutive minutes of prolonged sitting (approximately two breaks per day), which gradually increased as they became more engaged and familiar with the interventions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eControl\u003c/h3\u003e\n\u003cp\u003eFor the control schools, the teachers did not participate in any training sessions and were instructed to maintain their usual lessons without any changes to their routines.\u003c/p\u003e\n\u003ch3\u003eData collection procedures\u003c/h3\u003e\n\u003cp\u003eData collection took place at the schools and was conducted by the project interns. The children were taken out of the classroom one at a time and led to the assessment area. To minimize the time spent away from class, the tests were divided into sessions of approximately 30 minutes. Therefore, children had to return multiple times on different days during the data collection weeks to complete all the study assessments. Both the cognitive performance tests and questionnaires were administered on computers/laptops.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrimary outcome assessment\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eCognitive performance\u003c/h2\u003e \u003cp\u003eFive executive functions were assessed: inhibitory control via the Go/NoGo paradigm [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]; working memory, which was evaluated via the nonverbal digit span forward test paradigm [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]; selective attention, which was assessed via the visual search test paradigm [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]; spatial orientation, which was evaluated via the Posner Cueing test [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]; and spatial reasoning, which was assessed via the mental rotation test paradigm [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. For all the tests, computerized versions were used, programmed with a Psytoolkit [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and made available via JATOS [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The number of correct responses and reaction time (in milliseconds) for each test were used as indicators of cognitive performance. [for more details, see Additional File 3].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcomes assessed\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eSteps daily\u003c/h2\u003e \u003cp\u003eFor the objective assessment of physical activity, Omron HJA-310 pedometers were used for seven consecutive days. The participants received information sheets with instructions before wearing the pedometer. Data were recorded on the total number of steps during the week (including weekdays and weekends) as well as the number of steps taken when the children arrived at school and before leaving (number of steps taken during school hours). For this study, valid information for total weekly steps was defined as at least two weekdays and one weekend day. Additionally, daily values ranging from a minimum of 1,000 steps to a maximum of 30,000 steps were considered valid [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. For steps at school, at least two days of use were needed, and to ensure that the device was used during school hours, daily values ​​of fewer than 100 steps were not considered valid.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePhysical activity and screen-based activity\u003c/h2\u003e \u003cp\u003eAs a subjective measure, the daily frequency of physical activity (DFPA) and screen-based activity (DFSA) was assessed via the electronic School-Aged Children\u0026rsquo;s Dietary and Physical Activity Questionnaire (WEB-CAAFE), a web-based questionnaire in which the child recalls the type, frequency and intensity of the physical activities performed in the morning, afternoon and evening of the previous day [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. For this study, the self-reported frequency of physical activity was obtained by summing the reports of active play (i.e., play involving at least moderate physical activity, such as playing a ball), structured physical activity (i.e., physical activities monitored by a teacher or coach, such as swimming), and household chores (i.e., physical activities considered household tasks, such as sweeping). For example, if a participant reported playing in the park in the morning, playing tag in the afternoon, and playing with a dog in the evening, their total count for active play was 3. The frequency of screen-based activity was obtained by summing reports of screen use (smartphone, tablet, TV, laptop) across the three time periods (morning, afternoon, and evening).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eQuality of Life\u003c/h2\u003e \u003cp\u003eTo assess the children's quality of life, the \u003cem\u003eAutoquestionnaire Qualit\u0026eacute; de Vie Enfant Imag\u0026eacute;\u003c/em\u003e (AUQEI) [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], validated for Brazilian children [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], was used. The questionnaire consists of 26 questions and generates a score ranging from zero to 78 points, with a higher score indicating a better perception of quality of life.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDaytime Sleepiness\u003c/h2\u003e \u003cp\u003eTo evaluate daytime sleepiness, the Pediatric Daytime Sleepiness Scale (PDSS) [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], translated and validated into Brazilian Portuguese [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], was used. The questionnaire consists of eight questions and generates a score ranging from zero to 32 points, with a higher score indicating greater daytime sleepiness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSchool Perception\u003c/h2\u003e \u003cp\u003eTo assess students' perceptions of school, a questionnaire was used to gauge the child's satisfaction with the school, teacher, and classroom tasks. Responses were given on a five-point visual analog scale, where facial expressions 1 and 2 were negative, 4 and 5 were positive, and 3 was neutral. For the analysis, responses were considered continuous values, where a higher score indicated greater satisfaction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDemographics and anthropometrics\u003c/h2\u003e \u003cp\u003eDuring baseline, information on sex (male or female) and age (date of birth) was collected. Additionally, measurements of body weight (Seca\u0026reg; scale; accuracy of 0.1 kg) and height (accuracy of 0.1 cm) were taken via standardized procedures at each assessment point. Based on these measurements, body mass index was calculated via the following equation: kg/m\u0026sup2;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eAll analyses employed the intention-to-treat (ITT) method without data imputation, considering the information of all children regardless of missing data at any time point. The outliers were addressed via the winsorization technique [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], which prevents the permanent loss of extreme values by adjusting them to acceptable limits. A limit of three standard deviations was used for the minimum and maximum values.\u003c/p\u003e \u003cp\u003eDescriptive analyses are presented as relative and absolute frequencies, means, and standard deviations. Data normality was verified via the Shapiro‒Wilk test. To compare baseline measurements between groups, one-way ANOVA or Kruskal‒Wallis test was used for continuous variables, and Pearson's chi‒square test was used for categorical variables. Generalized estimating equation (GEE) models with Gamma distributions (Poisson for count outcomes), and exchangeable working correlations were implemented via the glmgee function from the \u003cem\u003eglmtoolsbox\u003c/em\u003e package to assess the effects of interventions (CTL, PAL, and AB) over time (baseline and follow-up) on the outcomes. The choice of GEE was made because of its advantages: it does not require normality of distributions, allows for the analysis of correlated observations, and accommodates missing data over time in the model [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. For models with significant group-by-time interactions, post hoc comparisons were performed via contrast functions from the \u003cem\u003eemmeans\u003c/em\u003e package.\u003c/p\u003e \u003cp\u003eAdditionally, partial eta squared (\u0026#120578;\u0026sup2;) was calculated for the effect size of the group-by-time interaction in the GEE models. Cohen's d, as suggested by Becker [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], was calculated to determine the effect size of the mean differences between baseline and follow-up for each group in the post hoc comparisons. Furthermore, intracluster correlation coefficients (ICCs) of schools were reported, obtained from unadjusted follow-up raw scores via the clus.rho function from the \u003cem\u003eFishMethods\u003c/em\u003e package, adjusted for clusters with unequal sample sizes.\u003c/p\u003e \u003cp\u003eAll analyses were conducted via R version 4.4.0 within the RStudio integrated development environment. A significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was adopted for all analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics of the participants\u003c/h2\u003e \u003cp\u003eThe recruitment and data collection flowcharts are presented in Fig.\u0026nbsp;2. Out of the 345 first-grade children eligible across the six schools, 184 children (53.3%) returned with a signed informed consent form from their parents. The active lessons group included 77 children, the active breaks group included 61 children, and the control group included 46 children. The characteristics of the children in the groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with participants having an average age of 6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 years and 52.7% being girls. Differences at baseline between groups were observed for height (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), school shift (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mental rotation test (number of hits: p\u0026thinsp;=\u0026thinsp;0.012; reaction time: p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), steps at school (p\u0026thinsp;=\u0026thinsp;0.003), frequency of physical activity, and screen-based activity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Further details are available in Supplementary Table\u0026nbsp;1 of Supplementary Material 4.\u003c/p\u003e \u003cp\u003e[Insert Fig.\u0026nbsp;2]\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2.\u003c/b\u003e Flow diagram - CONSORT.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of participating children at baseline (N\u0026thinsp;=\u0026thinsp;184).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL (n\u0026thinsp;=\u0026thinsp;46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePAL (n\u0026thinsp;=\u0026thinsp;77)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAB (n\u0026thinsp;=\u0026thinsp;61)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAll\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87 (47.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97 (52.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometric\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight, m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchool additional information\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchool shift (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMorning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (66.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (62.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101 (54.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfternoon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (73.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (33.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83 (45.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eMain outcome\u003c/h2\u003e \u003cp\u003eSignificant interactions between group and time were observed in four out of the five tests conducted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For the test Go/NoGo (reaction time: p\u0026thinsp;=\u0026thinsp;0.045; partial \u0026#120578;\u0026sup2; = 0.02), DigitSpan (correct responses: p\u0026thinsp;=\u0026thinsp;0.020; partial \u0026#120578;\u0026sup2; = 0.01), Mental Rotation (reaction time: p\u0026thinsp;=\u0026thinsp;0.049; partial \u0026#120578;\u0026sup2; = 0.02), and Cueing Posner (reaction time: p\u0026thinsp;=\u0026thinsp;0.012; partial \u0026#120578;\u0026sup2; = 0.03).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimated marginal means for the primary outcomes of each group and results from the generalized estimating equation (GEE) models.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEstimated marginal means\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eGEE (group by time)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePartial \u0026#120578;\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGo/NoGo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCorrect responses\u003c/p\u003e \u003cp\u003e(hits) \u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.7 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.9 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.4 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.8 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTime reaction\u003c/p\u003e \u003cp\u003e(milliseconds) \u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e913.4 (33.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e875.2 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e.045\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e833.9 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e729.5(22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e886.1 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e886.2 (31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDigitSpan\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCorrect responses\u003c/p\u003e \u003cp\u003e(hits)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.2 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.\u003cb\u003e020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.2 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMental Rotation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCorrect responses\u003c/p\u003e \u003cp\u003e(hits)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.7 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.0 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.8 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.4 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5887.6 (365.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5314.1 (335.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e.049\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime reaction\u003c/p\u003e \u003cp\u003e(milliseconds) \u003csup\u003ea,b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7068.0 (310.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5100.5 (173.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7354.4 (353.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5876.6 (183.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCueing Posner\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCorrect responses (hits)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.6 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.5 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTime reaction\u003c/p\u003e \u003cp\u003e(milliseconds) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1788.9 (102.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1606.1 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1889.6 (64.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1503.2 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1655.8(56.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1497.8 (48.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVisual Search\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCorrect responses (hits)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.5 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.7 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.8 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTime reaction\u003c/p\u003e \u003cp\u003e(milliseconds) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3941.1 (201.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3137.6 (188.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3943.8 (132.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3088.2 (108.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3932.5 (189.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3590.4 (140.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eNote\u003c/b\u003e: The estimated marginal means and standard errors are based on generalized estimating equation (GEE) models and their respective adjustments. The GEE models were adjusted for age and sex. The interpretation of the partial \u0026#120578;\u0026sup2; effect size is as follows: small if\u0026thinsp;\u0026lt;\u0026thinsp;0.06, medium if between 0.06 and 0.14, and large if\u0026thinsp;\u0026ge;\u0026thinsp;0.14.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eCTL, control\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ePAL, physically active lesson\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAB, active break\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ea, statistically significant for the main effect of group\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eb, statistically significant for the main effect of time\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.05, statistically significant.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eChanges over time (follow-up minus baseline) for the main outcomes that showed significant interactions between groups and time are shown in Fig.\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eFor inhibitory control (Fig.\u0026nbsp;3A), a significant reduction in the average reaction time on the Go/NoGo test was observed in the physically active lesson group (∆ = -104.5 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.50). No significant difference was found in the active breaks (∆ = 0.1 ms; p\u0026thinsp;=\u0026thinsp;0.996; d\u0026thinsp;=\u0026thinsp;0.00) or control groups (∆ = -38.2 ms; p\u0026thinsp;=\u0026thinsp;0.372; d\u0026thinsp;=\u0026thinsp;0.17).\u003c/p\u003e \u003cp\u003eFor working memory (Fig.\u0026nbsp;3B), a significant increase in the average number of correct responses on the DigitSpan test was observed in the physically active lesson group (∆ = 0.62 hits; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.44), whereas the active breaks (∆ = -0.08 hits; p\u0026thinsp;=\u0026thinsp;0.698; d\u0026thinsp;=\u0026thinsp;0.06) and control groups (∆ = -0.11 hits; p\u0026thinsp;=\u0026thinsp;0.683; d\u0026thinsp;=\u0026thinsp;0.08) did not significantly differ.\u003c/p\u003e \u003cp\u003eFor spatial reasoning (Fig.\u0026nbsp;3C), significant changes in reaction time on the mental rotation test were identified for the physically active lesson group (∆ = -1967.5 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.72) and the active break group (∆ = -1477.8 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.54), whereas no significant differences were observed in the control group (∆ = -573.5 ms; p\u0026thinsp;=\u0026thinsp;0.186; d\u0026thinsp;=\u0026thinsp;0.24).\u003c/p\u003e \u003cp\u003eFor spatial orientation (Fig.\u0026nbsp;3D), significant changes in reaction time on the Cueing Posner test were identified in all groups: physically active lessons (∆ = -386.4 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.69), active breaks (∆ = -157.9 ms; p\u0026thinsp;=\u0026thinsp;0.007; d\u0026thinsp;=\u0026thinsp;0.36), and control (∆ = -182.8 ms; p\u0026thinsp;=\u0026thinsp;0.20; d\u0026thinsp;=\u0026thinsp;0.28), with a greater effect in the active lessons group. No significant changes in other cognitive indicators were observed. Further details can be found in Supplementary Table\u0026nbsp;2 of Supplementary Material 4.\u003c/p\u003e \u003cp\u003e[Insert Fig.\u0026nbsp;3]\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3.\u003c/b\u003e Boxplot and effect size for post hoc comparisons between baseline and follow-up data by group. The boxplots display the median and the 25th and 75th percentiles without adjustment (raw score). Circles and squares represent the results of each child according to their school. The point ranges represent the difference (∆) and their respective confidence intervals. Cohen's effect size was based on GEE models, with the following interpretation: small if\u0026thinsp;\u0026lt;\u0026thinsp;0.50, medium if between 0.50 and 0.80, and large if\u0026thinsp;\u0026ge;\u0026thinsp;0.80.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcomes\u003c/h2\u003e \u003cp\u003eMost secondary outcomes did not show statistical significance for the interaction between group and time (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), except for the DFPA (p\u0026thinsp;=\u0026thinsp;0.002; partial \u0026#120578;\u0026sup2; = 0.04) and daytime sleepiness (p\u0026thinsp;=\u0026thinsp;0.004; partial \u0026#120578;\u0026sup2; = 0.04). Since the school shift was significant in the models for these two outcomes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), we repeated the analyses by adding the interaction term group vs. time vs. shift to examine any potential moderating effect of the school shift. However, the interaction term was not significant [daily frequency of physical activity (p\u0026thinsp;=\u0026thinsp;0.979); daytime sleepiness (p\u0026thinsp;=\u0026thinsp;0.494)].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimated marginal means for the secondary outcomes of each group and results from the generalized estimating equation (GEE) models.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eEstimated marginal means\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eGEE (group by time)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFollow-up\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePartial \u0026#120578;\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteps\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAt school\u003c/p\u003e \u003cp\u003e(step/day) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1724.5 (146.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1746.3 (148.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1330.2 (105.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1137.4 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1767.4 (116.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1621.8 (110.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIn the week\u003c/p\u003e \u003cp\u003e(step/day) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7089.5 (455.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6244.7 (469.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6816.3 (320.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6605.3 (377.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7044.9 (388.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6395.8 (399.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeb-CAAFE (self-reported)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003cp\u003e(frequency) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.0 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eScreen-based activity\u003c/p\u003e \u003cp\u003e(frequency) \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.9 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of life\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAUQEI Score\u003c/p\u003e \u003cp\u003e(0\u0026ndash;78 points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.2 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.4 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.0 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.1 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.9 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDaytime Sleepiness\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePDSS Score\u003c/p\u003e \u003cp\u003e(0\u0026ndash;32 points)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.8 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.9 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.0 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.8 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSchool perception\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSchool\u003c/p\u003e \u003cp\u003e(Likert Scale 1\u0026ndash;5) \u003csup\u003ea, b\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.7 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.1 (0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTeacher\u003c/p\u003e \u003cp\u003e(Likert Scale 1\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.6 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eTask in the classroom\u003c/p\u003e \u003cp\u003e(Likert Scale 1\u0026ndash;5) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.4 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.8 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cb\u003eNote\u003c/b\u003e: The estimated marginal means and standard errors are based on generalized estimating equation (GEE) models and their respective adjustments. The GEE models were adjusted for age, sex and school shift. The interpretation of the partial \u0026#120578;\u0026sup2; effect size is as follows: small if\u0026thinsp;\u0026lt;\u0026thinsp;0.06, medium if between 0.06 and 0.14, and large if\u0026thinsp;\u0026ge;\u0026thinsp;0.14.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eCTL, control\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ePAL, physically active lesson\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAB, active break\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ea, statistically significant for the main effect of group\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eb, statistically significant for the main effect of time\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.05, statistically significant.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Insert Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFor the DFPA (Fig.\u0026nbsp;3E), the active breaks group showed a reduction in the total self-reported physical activity frequency during the previous day (∆ = -1.5 frequency; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.60), whereas no differences were observed for the physically active lessons group (∆ = -0.1 frequency; p\u0026thinsp;=\u0026thinsp;0.643; d\u0026thinsp;=\u0026thinsp;0.05) or the control group (∆ = 0.2 frequency; p\u0026thinsp;=\u0026thinsp;0.761; d\u0026thinsp;=\u0026thinsp;0.07). With respect to daytime sleepiness (Fig.\u0026nbsp;3F), children in the physically active lessons and active breaks groups reported increased feelings of excessive sleepiness during the day [(∆ = +2.2 score; p\u0026thinsp;=\u0026thinsp;0.045; d\u0026thinsp;=\u0026thinsp;0.45); (∆ = 2.3 score; p\u0026thinsp;=\u0026thinsp;0.006; d\u0026thinsp;=\u0026thinsp;0.31), respectively], whereas no significant differences were found for the control group (∆\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.2 score; p\u0026thinsp;=\u0026thinsp;0.067; d\u0026thinsp;=\u0026thinsp;0.34). Further details can be found in Supplementary Table\u0026nbsp;2 of Supplementary Material 4.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur primary objective was to investigate the effects of physically active lessons and active breaks on executive functions and health indicators in elementary school children. To the best of our knowledge, this is the first study to examine these two different strategies of school-based physical activity interventions on the executive functions of first-grade children from a low socioeconomic status region in a middle-income country.\u003c/p\u003e \u003cp\u003eThe results of the cognitive tests revealed positive effects of physically active lessons on various executive functions. In inhibitory control, as measured by the Go/NoGo test, a significant reduction in reaction time was observed in the physically active lesson group, suggesting an improvement in the ability to inhibit impulsive responses. In working memory, as assessed through the DigitSpan test, the physically active lesson group presented a significant increase in the number of correct responses, indicating a better ability to maintain and manipulate information mentally. Inhibitory control and working memory are cognitive functions associated with the prefrontal cortex [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The importance of these executive functions for academic performance is well established, as these skills are essential for complex tasks, problem solving, and effective learning [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Our findings align with evidence reported in the literature, with recent studies identifying positive effects of physically active lessons on cognitive functions such as inhibitory control [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and working memory [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Notably, studies [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] were conducted with Brazilian children. However, the present study advances the field by increasing the sample size and randomizing the schools.\u003c/p\u003e \u003cp\u003eWith respect to spatial reasoning, as assessed with the mental rotation test, significant improvements were found in both the physically active lessons and the active breaks groups, with the effects being more pronounced in the physically active lessons group. Spatial reasoning plays a crucial role in learning disciplines such as science, technology, engineering, arts, and mathematics, as it involves skills in visualizing and manipulating shapes and spaces, which are essential for understanding these concepts [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However, it is important to exercise caution when interpreting these results, as both the physically active lesson group and the active break group started with performance levels significantly below those of the control group. Thus, the significant improvement may have been influenced by the large margin for growth, meaning that there was more room for substantial improvement.\u003c/p\u003e \u003cp\u003eFinally, in spatial orientation, as measured by the Cueing Posner test, significant improvements were observed in all three groups, with the effect being more pronounced in the physically active lesson group for the time of reaction. The Cueing Posner test evaluates the ability to voluntarily and quickly direct attention to a specific location in space on the basis of visual cues [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This skill is crucial for learning, as it allows students to focus their attention on relevant information and ignore distractions, thereby facilitating efficient and effective information processing.\u003c/p\u003e \u003cp\u003eOne of the mechanisms that explains how physical activity can improve cognitive functions is increased activation of the prefrontal cortex when physical activity is performed at moderate to vigorous intensity levels [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. This increase in brain activity is associated with improvements in executive functions [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Studies on isotemporal substitutions suggest that replacing prolonged sitting time with light physical activity can contribute to the enhancement of cognitive functions [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Although the intensity of the interventions in the present study was not measured, replacing sedentary time with light physical activity may have played a crucial role in improving executive functions, particularly in the group with physically active lessons. The activities suggested in the materials provided and the planning discussed during the training sessions included movements during the learning process (for example, when teaching syllables, children formed words through popular games such as 'hopscotch'). Thus, the implementation of a more dynamic and playful lesson structure, where students spend less time sitting and more time engaging in light physical activity, may explain the positive results found in the group with physically active lessons.\u003c/p\u003e \u003cp\u003eFurthermore, physically active lessons provide learning through movement, meaning that movement is integrated into one or more partial processes of learning a specific knowledge or skill. This could be another factor that enhances the positive effects on cognitive abilities, as learning through movement not only increases task engagement but also promotes socialization and makes the learning environment more dynamic, providing a more interactive and engaging context. The simultaneous activation of multiple brain areas during learning through movement may favor information retention and effective learning [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. On the other hand, the active breaks in this study focused primarily on interrupting prolonged sitting time without involving pedagogical content or cognitive engagement. Consequently, the results for cognitive functions were less pronounced. A possible explanation seems to be related to the type of activity performed, as activities with more cognitively engaging components [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] or those combined with the curriculum [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] have shown improvements in cognitive functions compared with active breaks with purely physical activity components [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSome unexpected results were observed in this study regarding self-reported daily total physical activity frequency during the previous day and daytime sleepiness. The active breaks group showed a reduction in self-reported total physical activity frequency during the previous day. Initially, children in the active breaks group reported a greater frequency of self-reported physical activity during the previous day than did those in the physically active lessons and control groups. Therefore, this change should be interpreted with caution. Additionally, the number of steps taken during the week did not differ between the groups over time, indicating that the level of physical activity performed during the breaks may not have been compensated by less activity throughout the day. However, a more detailed investigation, such as the use of accelerometers, could help researchers better understand these results.\u003c/p\u003e \u003cp\u003eWith respect to daytime sleepiness, children in the physically active lessons and active break groups reported an increase in daytime sleepiness. This increase was unexpected; however, owing to the nature of the interventions, other unmeasured factors may have influenced the children's daytime sleepiness. Although the school shift did not moderate the observed effects, it did explain part of the observed changes. Information such as sleep duration, use of electronics before bedtime, and bed and wake-up times, among others, would help us better understand these changes, given that previous evidence has associated daytime sleepiness with the number of hours of sleep [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and the use of electronics before bedtime [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and strengths\u003c/h2\u003e \u003cp\u003eThe study had limitations that should be considered. First, to allow for greater external validity of the interventions, some decisions were made to ensure implementation primarily within the educational reality of each school. For example, teachers were instructed to implement the interventions as frequently as possible autonomously. Unlike other studies where teachers are directed to include a fixed number of interventions, in the present study, teachers had the freedom to schedule the activities as they wished. The implementation of the interventions gradually increased in frequency over the weeks. However, as there was no daily control of how often the activities were implemented, it is possible that the activities were carried out at various frequencies and times. We also note that some uncollected information, such as sitting time, hours of sleep, and socioeconomic information, could have provided additional context for the participants.\u003c/p\u003e \u003cp\u003eOn the other hand, the study had strengths such as being a cluster-randomized clinical trial, which allows for more robust inferences about causality. Additionally, this was the first study to compare the effectiveness of two physical activity interventions in the classroom in a middle-income country in South America, thus expanding the knowledge in this area. Cognitive functions were assessed via standardized tests, which increases the reliability of the results and allows comparisons with other studies. Furthermore, information was collected on behaviors outside the school context, providing a comprehensive view of the reach of the interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003ePractical implications\u003c/h2\u003e \u003cp\u003eThe positive results associated with physically active lessons indicate that more dynamic and engaging strategies implemented in the classrooms of elementary schools can effectively promote children's cognitive development. Promoting activities that involve physical movement may offer an effective approach to stimulating specific brain areas associated with executive functions. However, when implementing these interventions, it is important to consider the diverse nature of the activities, aiming for those that not only provide physical activity for children but also offer cognitive stimulation. This suggests a shift in the educational paradigm, encouraging methods that integrate movement and learning synergistically.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese results indicate that physically active lessons can improve inhibitory control, working memory, spatial orientation, and spatial reasoning in elementary school children. While less effective, active breaks still represent a viable strategy with no harmful effects. However, further research is needed on long-term effects to determine best practices for implementing these interventions in schools.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDFPA: Daily frequency of physical activity; PAL: Physically active lesssons; AB: Active Break; CTL: Control\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the children, principals, coordinators, and teachers from the schools that participated in the study. Also, thanks to the Municipal Department of Education of Aracaju for their support and for facilitating scholarships for the interns. The authors acknowledge all the interns who assisted in data collection, especially Alana Cerqueira, Amanda Vasconcelos, Bianca Ivo, Camile Souza, Felipe Rocha, Guilherme Santos, Isis Correia, and Luana Silveira. The authors also thank Beatriz N\u0026oacute;ia and Marcel Belitardo for their assistance in teacher training. Additionally, the authors express their gratitude to Professor Dra. Thayse Gomes and Dra. Heike Schmitz, for their collaboration on the conceptualization and design of the study. We also thank Professors Dra. Clarice Martins and Dr. Diogo Ara\u0026uacute;jo for their contributions to the initial draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJCNM, JT, and DRPS conceived the study design and concept. JCNM conducted the study as part of their master\u0026apos;s degree under the supervision of JT and DRPS. JCNM analyzed the data and prepared the results with review by JT and DRPS. JCNM prepared the first draft under the supervision of DRPS. JT, ECMS, JYVN, DNO, LG, and DRPS critically revised and improved the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe information and opinions contained in this Article do not necessarily reflect the views or policies of the supporting organizations. JCNM and ECMS were supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) with PhD scholarships (Process numbers: 88887.950448/2024-00 and 88887.605029/2021-00, respectively). JY, DNO, and LG were supported by CAPES with master\u0026apos;s degree scholarships (Process numbers: 88887.808021/2023-00, 88887.947469/2024-00, and 88887.829680/2023-00, respectively). This study was financed in part by the Foundation for the Support of Research and Technological Innovation of the State of Sergipe (FAPITEC/SE: 019203.00717/2020-8) and the National Council for Scientific and Technological Development (CNPq: 404791/2023-9). The funding bodies had no role in the design of the study, the collection, analysis, or interpretation of data, or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was carried out in accordance with the principles of the Declaration of Helsinki. The study received approval from the Human Research Ethics Committee of the Federal University of Sergipe (Approval Number: 5.301.398). Written informed consent from parents or legal guardians was obtained, and all participants provided written consent before the baseline data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs part of the informed consent process, parents or legal guardians provided written consent for their child\u0026rsquo;s data to be used in this research study, including the publication of findings in scientific journals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOwen N, Healy GN, Dempsey PC, Salmon J, Timperio A, Clark BK, et al. Sedentary Behavior and Public Health: Integrating the Evidence and Identifying Potential Solutions. 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Effects of physically active maths lessons on children\u0026rsquo;s maths performance and maths-related affective factors: Multi-arm cluster randomized controlled trial. Br J Educ Psychol. 2024;94:839\u0026ndash;61. \u003c/li\u003e\n\u003cli\u003eGathercole SE, Pickering SJ, Knight C, Stegmann Z. Working memory skills and educational attainment: evidence from national curriculum assessments at 7 and 14 years of age. Appl Cogn Psychol. 2004;18:1\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eBlair C, Razza RP. Relating effortful control, executive function, and false belief understanding to emerging math and literacy ability in kindergarten. Child Dev. 2007;78:647\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003eSantos JAC. Secret\u0026aacute;ria Municipal da Sa\u0026uacute;de (Decreto de11 de julho de 2017). 2018;79. \u003c/li\u003e\n\u003cli\u003eParker K, Nunns M, Xiao Z, Ford T, Ukoumunne OC. 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Learning while multitasking: short and long-term benefits of brain stimulation. Ergonomics. 2018;61:1454\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003evan den Berg V, Saliasi E, de Groot RHM, Chinapaw MJM, Singh AS. Improving Cognitive Performance of 9-12 Years Old Children: Just Dance? A Randomized Controlled Trial. Front Psychol. 2019;10:174. \u003c/li\u003e\n\u003cli\u003eBub KL, Buckhalt JA, El-Sheikh M. Children\u0026rsquo;s sleep and cognitive performance: a cross-domain analysis of change over time. Dev Psychol. 2011;47:1504\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eBuheji M, Jahrami H, Cunha K, Ebrahim A. Children and Coping During COVID-19: A Scoping Review of Bio-Psycho-Social Factors. Int J Appl Psychol. 2020;10:8\u0026ndash;15.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbn","sideBox":"Learn more about [International Journal of Behavioral Nutrition and Physical Activity](http://ijbnpa.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ijbn/default.aspx","title":"International Journal of Behavioral Nutrition and Physical Activity","twitterHandle":"@IJBNPA","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Physically Active Learning, Executive Function, Health Indicator, Classroom Physical Activity","lastPublishedDoi":"10.21203/rs.3.rs-5804150/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5804150/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis cluster-randomized trial investigated the effects of active breaks and physically active lessons on cognitive function and health indicators in elementary school children in Aracaju, SE.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSix schools were randomly divided into three groups: 1) active breaks (n\u0026thinsp;=\u0026thinsp;61), which consisted of short physical activity intervals during classes; 2) physically active lessons (n\u0026thinsp;=\u0026thinsp;77), which combined physical activity with educational content; and 3) control (n\u0026thinsp;=\u0026thinsp;46), which followed the traditional curriculum. The interventions were conducted over eight weeks. Cognitive function was assessed via reaction time and correct responses on five computerized tests: visual search, Go/NoGo, mental rotation, cueing positive, and digit span. Physical activity was measured by pedometers and the Web-CAAFE questionnaire. Quality of life, daytime sleepiness, and school perception were also evaluated as secondary outcomes. Generalized estimating equation models were used, with a significance level of 5%.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe physically active lesson group showed significant improvements in inhibitory control on the Go/NoGo test (∆ = -104.5 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.50) and in working memory on the DigitSpan test (∆ = 0.62 hits; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.44). The physically active lessons and active breaks groups showed significant improvements in spatial reasoning on the mental rotation test (∆ = -1967.5 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.72, and ∆ = -1477.8; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.54, respectively). All groups demonstrated significant improvements in spatial orientation on the Cueing Posner test, with the largest effect in the physically active lessons group (∆ = -386.4 ms; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.69).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study concluded that physically active lessons improved various cognitive functions, whereas active breaks, although less impactful, are still a beneficial strategy without adverse effects.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e \u003cp\u003eBrazilian Clinical Trials Registry (REBEC trial: RBR-10zxwdrh, retrospectively registered on 2025-01-09, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ensaiosclinicos.gov.br/rg/RBR-10zxwdrh\u003c/span\u003e\u003cspan address=\"https://ensaiosclinicos.gov.br/rg/RBR-10zxwdrh\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e","manuscriptTitle":"Effects of physically active lessons and active breaks on cognitive performance and health indicators in elementary school children: A cluster randomized trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-15 12:23:38","doi":"10.21203/rs.3.rs-5804150/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-13T21:59:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-06T22:59:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-28T14:03:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315217980532737362948949134914326754131","date":"2025-02-05T08:24:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277119255028701372282456606351637560905","date":"2025-01-29T09:05:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-28T04:27:16+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-14T04:44:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-14T04:42:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Behavioral Nutrition and Physical Activity","date":"2025-01-10T13:24:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbn","sideBox":"Learn more about [International Journal of Behavioral Nutrition and Physical Activity](http://ijbnpa.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ijbn/default.aspx","title":"International Journal of Behavioral Nutrition and Physical Activity","twitterHandle":"@IJBNPA","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bbd2da43-7b0a-4f5c-9b91-c02c263a55eb","owner":[],"postedDate":"January 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T16:07:17+00:00","versionOfRecord":{"articleIdentity":"rs-5804150","link":"https://doi.org/10.1186/s12966-025-01789-6","journal":{"identity":"international-journal-of-behavioral-nutrition-and-physical-activity","isVorOnly":false,"title":"International Journal of Behavioral Nutrition and Physical Activity"},"publishedOn":"2025-07-09 15:58:00","publishedOnDateReadable":"July 9th, 2025"},"versionCreatedAt":"2025-01-15 12:23:38","video":"","vorDoi":"10.1186/s12966-025-01789-6","vorDoiUrl":"https://doi.org/10.1186/s12966-025-01789-6","workflowStages":[]},"version":"v1","identity":"rs-5804150","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5804150","identity":"rs-5804150","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}