4 × 10 m Speed-Agility Test

Coordination, agility, and speed were evaluated with this test. The aim of the test was to run four repetitions of 10 m distance. Students had to run at a maximum speed, and they had two attempts. We recorded the best of the two attempts, and results were measured in seconds with a Casio handheld stopwatch (HS-3V-1).

#### Standing Broad Jump

This test has been successfully used for measuring lower limb explosive strength. Students jumped horizontally to achieve maximum distance (in centimeters). Participants performed the standing broad jump three times, with 20 s of recovery between attempts to minimize the effect of fatigue. The best jump was considered as the final outcome. The test was performed in the school gym to avoid falls caused by slipping [38].

#### 2.4.3. Rating of Perceived Exertion (RPE) *Biology* **2021**, *10*, x FOR PEER REVIEW 10 of 16

The RPE was measured with the Borg scale [39] immediately after the exercise in ABG and CG. The RPE scale ranged from 6 (no exertion) to 20 (maximal exertion).

#### 2.4.4. Cognitive Measurement: Psychomotor Vigilance Task iPhones 5s (iOS 12.4.5) were used to present the stimuli of the PVT. Performance in

2.4.4. Cognitive Measurement: Psychomotor Vigilance Task

iPhones 5s (iOS 12.4.5) were used to present the stimuli of the PVT. Performance in the PVT has been shown to be valid to control vigilance [18,40] and was linked to the control of cardiovascular fitness [41]. The devices were previously blocked to any other type of notification. The center of the mobile screen was placed about 50–80 cm from the participants' heads at eye level (aiming to help everyone feel as comfortable as possible during the duration of the task). The PVT presents a grey screen with a chronometer at the center, which begins the countdown at the speed of a real stopwatch and could be presented on the screen after a random time interval ranging between 2000 and 10,000 ms. Verbal and written instructions were given to the participant prior to the start of the PVT in every session, stressing that they had to fixate on the center of the screen, try not to move their eyes, and respond as quickly as possible (while avoiding anticipation errors) as soon as the chronometer starts. The task included a single block lasting 10 min. The exact number of trials of each participant depended on the latency of the individual's response. the PVT has been shown to be valid to control vigilance [18,40] and was linked to the control of cardiovascular fitness [41]. The devices were previously blocked to any other type of notification. The center of the mobile screen was placed about 50–80 cm from the participants' heads at eye level (aiming to help everyone feel as comfortable as possible during the duration of the task). The PVT presents a grey screen with a chronometer at the center, which begins the countdown at the speed of a real stopwatch and could be presented on the screen after a random time interval ranging between 2000 and 10,000 ms. Verbal and written instructions were given to the participant prior to the start of the PVT in every session, stressing that they had to fixate on the center of the screen, try not to move their eyes, and respond as quickly as possible (while avoiding anticipation errors) as soon as the chronometer starts. The task included a single block lasting 10 min. The exact number of trials of each participant depended on the latency of the individual's response.

The task duration in both preintervention and postintervention was a 10-min test [42]. Students completed the first PVT, and five trials were excluded from the analysis. In addition, these trials were considered as practice in the preintervention for both groups (See Figure 4, for more information). The task duration in both preintervention and postintervention was a 10-minute test [42]. Students completed the first PVT, and five trials were excluded from the analysis. In addition, these trials were considered as practice in the preintervention for both groups (See Figure 4, for more information).

**Figure 4.** Experimental Set. Student performing the PVT (see text for full description). addition, confidence intervals (95%) were calculated. **Figure 4.** Experimental Set. Student performing the PVT (see text for full description).

tistically significant differences between groups, ABG vs. CG, was used as the betweensubjects factor, and time of measurement, baseline vs. eight weeks, as a within-subject factor. We performed a paired‐sample t‐test in body composition characteristics (body weight, BMI) and physiological parameters (RPE). Effect size is indicated with Cohen's d for t-tests [0.2 (small); 0.5 (medium) and >0.8 (large)] and partial eta squared for Fs. In

*2.5. Data Analysis*

#### *2.5. Data Analysis*

For data processing and mean and standard deviation were used. Descriptive statistics were calculated for each variable. For the comparison of samples and to observe statistically significant differences between groups, ABG vs. CG, was used as the between-subjects factor, and time of measurement, baseline vs. eight weeks, as a within-subject factor. We performed a paired-sample *t*-test in body composition characteristics (body weight, BMI) and physiological parameters (RPE). Effect size is indicated with Cohen's d for *t*-tests [0.2 (small); 0.5 (medium) and >0.8 (large)] and partial eta squared for Fs. In addition, confidence intervals (95%) were calculated.

Analyses of variance (ANOVA) were used to analyze the RTs. Trials with RTs below 100 ms in the experimental group (preintervention = 11.38% and postintervention = 7.79%) were assumed to represent anticipation errors and were discarded from the analysis [18].

Statistically significant effects were further analyzed with paired-sample *t*-tests corrected by Holm-Bonferroni for multiple comparisons. The Greenhouse–Geisser correction was applied when sphericity was violated. Data were analyzed using Statistical software (version 10.0; Statsoft, Inc., Tulsa, OK, USA). For all analyses, significance was accepted at *p* < 0.05.

#### **3. Results**

#### *3.1. Anthropometrical Characteristics*

A paired sample *t*-test with body weight between CG (66.79 ± 9.59; CI 95%: 4.68) and ABG (67.40 ± 17.07; CI 95%: 8.38) was not significant [t(21) = 0.05, *p* > 0.05, d = 0.04]. Another *t*-test with BMI between CG (22.90 ± 3.74; CI 95%: 1.25) and ABG (22.41 ± 3.74; CI 95%: 1.83) also was not significant [t(21) = 0.40, *p* > 0.05, d = −0.13]. These results confirmed that there was no statistically significant difference between the groups, therefore, both groups were equal.

#### *3.2. Physical Fitness Assessment*

The level of physical fitness was assessed by means of the ALPHA-Fitness test battery. A paired sample *t*-test with *Standing broad jump* between ABG (172.71 ± 35.84; CI 95%: 14.28) and CG (177.38 ± 43.96; CI 95%: 21.09) was not significant [t(21) = 0.05, *p* > 0.05, d= −0.09]. Another *t*-test with 4 × 10m speed-agility test between ABG (10.55 ± 2.2; CI 95%: 0.58) and CG (10.98 ± 1.23; CI 95%: 1.05) also was not significant [t(21) = 0.05, *p* > 0.05, d= −0.24]. Finally, a *t*-test with 20-m shuttle run test between ABG (43.91 ± 6.75; CI 95%: 3.41) and CG (43.08 ± 7.25; CI 95%: 2.99) also was not significant [t(21) = 0.05, *p* > 0.05, d = 0.12]. As was the case in anthropometrical characteristics, results confirmed both groups were equal at the start.

### *3.3. Rating of Perceived Exertion (RPE)*

A paired sample *t*-test with RPE scale showed higher values in the ABG (16.10 ± 1.21; CI 95%: 0.52) than in CG (6.29 ± 0.42; CI 95%: 0.18) [t(21) = 35, 35, *p* < 0.001, d = −10.83]. Previous results confirmed that effort (CG vs. ABG) was different in terms of physical demands.

#### *3.4. Psychomotor Vigilance Task*

A different analysis of variance of repeated measures (ANOVA) was performed with the average of the participants' RTs with the groups (CG vs. ABG) and time-on-task (10 min). First, an ANOVA with participants' mean RT [Pre-CG (380.08 ± 59.41 ms; CI 95%: 17.27) and Pre-ABG (375.97 ± 57.09 ms; CI 95%: 14.56)] and time-on-task, was not significant in any effects or interactions [*F* < 1 in all cases]. Second, an ANOVA with participants' mean RT [Pre-CG (380.08 ± 59.41 ms; CI 95%: 17.27) and Post-CG (382.05 ± 53.21 ms; CI 95%: 20.33)] also was not significant in any effects or interactions [*F* < 1 in all cases]. Finally, a new ANOVA with participants' mean RT [(Post-CG (382.05 ± 53.21 ms; CI 95%: 20.33) and Post-ABG (359.76 ± 62.89 ms; CI 95%: 22.91)] revealed a significant main effect of group

condition [F = 4.89, *p* = 0.03, η2 = 0.19]. Participants responded faster in the ABG than in the CG. The effect of time-on-task and interaction between the control condition and time-on-task was insignificant (*F* < 1). More information is in Figure 5. *Biology* **2021**, *10*, x FOR PEER REVIEW 12 of 16

**Figure 5.** Mean RT (± SE) as a function of Group Condition, time-on-task and Group x time-on-task. **Figure 5.** Mean RT (±SE) as a function of Group Condition, time-on-task and Group x time-on-task.

#### **4. Discussion 4. Discussion**

The present study investigated the chronic effects of an eight-week training program on vigilance performance in high school students. The results revealed faster RTs in the experimental group than in the CG. However, the effect of time-on-task and interaction between the control condition and time-on-task was not significant (*F* < 1). Crucially, our results showed a significant main effect of the group with faster RTs in the ABG than in the CG. This result suggests a facilitation effect on vigilance in the ABG and provides support to previous research that showed moderate aerobic exercise had a selective impact on cognitive processing [43,44]. Therefore, the inclusion of uncertainty regarding the appearance of the target in the PVT makes it different from simple RT tasks and provides a reliable instrument to measure vigilance. Thus, in our study, the PE not only improved the nonspecific response speed but rather improved participants' vigilance. The present study investigated the chronic effects of an eight-week training program on vigilance performance in high school students. The results revealed faster RTs in the experimental group than in the CG. However, the effect of time-on-task and interaction between the control condition and time-on-task was not significant (*F* < 1). Crucially, our results showed a significant main effect of the group with faster RTs in the ABG than in the CG. This result suggests a facilitation effect on vigilance in the ABG and provides support to previous research that showed moderate aerobic exercise had a selective impact on cognitive processing [43,44]. Therefore, the inclusion of uncertainty regarding the appearance of the target in the PVT makes it different from simple RT tasks and provides a reliable instrument to measure vigilance. Thus, in our study, the PE not only improved the nonspecific response speed but rather improved participants' vigilance.

As previously noted, practicing regular PE has been shown to produce changes to structural and functional levels of the brain [3,44,45]. Chronic PE produces lasting physiological adaptations [46]. Therefore, the body will naturally adjust, finally producing different anthropometric and physiological changes, thus causing an increase in the individual functional level (improved capacity and effectiveness in exercise). Considering the above, the conclusion from the literature is that physical fitness is one of the moderators between the effect of PE and cognitive function [40]. In this respect, we can explain the changes produced by chronic PE in the present experiment, based on the "cardiovascular As previously noted, practicing regular PE has been shown to produce changes to structural and functional levels of the brain [3,44,45]. Chronic PE produces lasting physiological adaptations [46]. Therefore, the body will naturally adjust, finally producing different anthropometric and physiological changes, thus causing an increase in the individual functional level (improved capacity and effectiveness in exercise). Considering the above, the conclusion from the literature is that physical fitness is one of the moderators between the effect of PE and cognitive function [40]. In this respect, we can explain the changes produced by chronic PE in the present experiment, based on the "cardiovascular

hypothesis". Significantly, based on our results, the benefits found for cognitive functions

physical fitness [3,47,48]. In addition, physiological adaptations at the cardiovascular level, which we suggest occurred due to improvement in vigilance values, are associated

hypothesis". Significantly, based on our results, the benefits found for cognitive functions usually associated with the regular practice of PE are moderated by the improvement of physical fitness [3,47,48]. In addition, physiological adaptations at the cardiovascular level, which we suggest occurred due to improvement in vigilance values, are associated with regular PE and have also been associated with adaptation at the brain level, which have been related to improvements in cognitive performance [47,48]. This could be considered a potential limitation of our study since the healthy lifestyle questionnaire and the level of physical fitness of the ALPHA-Fitness test battery were only applied in the preintervention. Consequently, we can only suggest the facilitation effect on vigilance in the ABG.

In the same context, we found interesting studies suggesting that regular aerobic PE is a good stimulus for triggering structural changes at the neural level [3,49] and therefore appears to positively impact cognitive performance [50,51]. Within this specific framework, the new research performed with magnetic resonance techniques [9,14,44,45,47,48] has been linked to adaptations at the brain level, which seem to have a positive impact on cognitive performance. In this respect, the literature revealed that chronic exercise leads to maintenance and neuronal proliferation in different brain areas (especially the hippocampus) and causes the growth of new blood capillaries through the action of brain-derived neurotrophic factor (BDNF) and insulin-like growth type 1 or somatomedin (IGF-1) in the hippocampus, cortex, and cerebellum, which has consequently been shown to have repercussions at the level of cognitive function [52]. Both proteins have shown a permanent increase in their production with the lasting intervention of regular physical exercise [15,53] and could be decisive preventive factors for brain degeneration, long-term enhancers and the development and protein for new neurons.

Finally, regarding the relationship between the chronic practice of PE or the level of physical fitness and general cognitive functioning, it should be noted that practically all of the literature explains the association between these variables based on the premise of the cardiovascular hypothesis, and mainly shows studies in children and older adults. According to this hypothesis, the cognitive function benefits associated with regular exercise are mediated by improving physical fitness. In addition, physiological adaptations attributed to chronic PE have also been linked to adaptations at the brain level, which seem to have a positive impact on cognitive performance [47,48].

Regarding the absence of fitness improvements, such a fact can be determined by the limited volume and intensity of practice [54–56]. Some fitness tests are also strength and power-dependent, such as sprinting, jumping and change-of-direction [57,58]. The program provided was based on strength endurance; however, intensity and intention were not controlled, which may cause a bias in the results as intensity may be critical for improvements [59]. Additionally, extra activities performed outside were not controlled, which may constrain the effects of parallel stimulus on the final outcomes.

This study has some limitations. One of the limitations is the absence of a counterbalanced intervention aiming to test different AB effects for the same target group. An additional study limitation is not controlling the extra activities and the effects of baseline levels of students. Baseline levels may play an important role in the progression since being a good or bad responder can be constrained by the starting point and trainability. Despite these limitations, this study provides an important and innovative approach to a micro-dose strategy for improving the quality of life and health of populations. This is one of the few studies dedicated to active break effects in a programmed approach that may help better understand the minimal effective dose that can be applied in students. Future research may compare different micro-doses and intensities while extending the approach to working, elderly and other populations).

#### **5. Conclusions**

The outcome of the present study suggests that an eight-week PE program based on AB of 16.10 ± 1.21 of the RPE scale improves vigilance performance. The importance of these findings is partly due to the sample of adolescent participants since most previous

research has been done on children and adults. In addition, our study highlights a potential finding that locates the basis of dose-response on AB studies. Taken together, the current dataset extends this topic of research and contributes to demonstrating the evidence of the effect of chronic exercise on cognition. It is suggested, however, that future research should systematize greater monitoring of training, not just pre and postintervention. Consequently, another important factor is to analyze the characteristic of ABs (physical exercise, technical exercise, mindfulness, integration in the classroom contents, etc.), as they must be understood in order to assess the best impact on vigilance during the class. In addition, it is recommended that training interventions be carried out for more extended periods of time so that it will be possible to investigate the behavior of vigilance capacity as training time increases. It also contributes to the extant research on cognitive performance during the PA performed in the classroom and opens up exciting avenues for future research.

**Author Contributions:** Conceptualization, F.T.G.-F. and S.G.-V.; methodology, F.T.G.-F. and J.C.P.-V.; formal analysis, S.B.-M. and F.T.G.-F.; investigation, F.T.G.-F. and S.G.-V.; resources, F.T.G.-F.; writing original draft preparation, S.B.-M., F.M.C. and G.B.; writing—review and editing, E.M.-C.; project administration, J.C.P.-V. and S.G.-V.; funding acquisition, E.M.-C. All authors have read and agreed to the published version of the manuscript.

**Funding:** The research was supported by the Consejería de Educación, Cultura y Deportes de Castilla-La Mancha, co-financed with European Union ERDF funds, under Grant number: SB-PLY/19/1805001/000147). This work is part of a two-year project entitled "Active Breaks Influence on Attentional Primary School Students".

**Institutional Review Board Statement:** The study was conducted in accordance with the ethical principles of the 1964 Helsinki declaration for human research and was approved by the Research Ethics Committee of the University of Castilla-La Mancha (Hospital Universitario de Albacete, Record 04/2020, and internal project n◦ 2020/05/052).

**Informed Consent Statement:** The participants' parents were informed about the objectives of the investigation and signed consent forms detailing their possible benefits and risks. Families were informed that they could revoke the participation agreement at any time. All participants were verbally informed and asked to provide consent prior to the intervention. The participants were fully debriefed about the purpose of the study at the end of the experiments.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** We thank the schoolchildren, teachers, schools, and families for their collaboration in the study.

**Conflicts of Interest:** The authors declare no conflict of interest.

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