The effects of equine‐assisted activities on execution function in children aged 7–8 years: A randomized controlled trial

Abstract Background : This study examines the effects of equine‐assisted activity (EAA) training on executive functioning (EF) (inhibitory control, working memory, and cognitive flexibility) in children aged 7–8 years. Methods : Twenty‐Four healthy children aged 7–8 years with a 1:1 ratio of boys to girls were randomly divided into EAA group (EAAG) or control group (CG). The subjects in EAAG were trained for 12 weeks, and CG participated in normal daily activities. All subjects conducted the Flanker, 1‐Back, and More‐odd shifting tasks at rest and recorded the average reaction times (RTs) and accuracy data of each task. Results : After 12 weeks of EAA intervention, EAAG showed a highly significant increase (p < .01) in mean RTs and accuracy in the Flanker and More‐odd shifting tasks and a highly significant increase (p < .01) in accuracy only in 1‐Back. Conclusion : These findings suggest that 12‐week EAA training can be effective in improving EF and promoting cognitive performance in children aged 7–8 years.

significant improvements in WM and CF by setting up high-frequency, low-frequency, and control groups (CGs) in a basketball intervention.
Similarly, the Ishihara et al. (2017) study showed that tennis game instruction had a positive effect on IC and fitness levels, and that longer coordination training was associated with better WM. In addition, Alesi et al. (2016) suggested that the football group at post-test showed significantly larger gains than the sedentary group on measures of agility, visuospatial WM, attention, planning, and IC. In general, both team sports and individual sports can be effective in improving EF. Therefore, monitoring EF development during childhood is essential.
But scarce studies have examined the link between equine-assisted activities (EAAs) and EF performance because few studies to date have attempted to assess EF performance using specific EF assessment tasks. However, studies did imply such a link between EAA and cognitive processes associated with EF. For example,  found improvements in attention skills and distractibility, one of the key skills of EF, when they examined 7-year-old children with autism who participated in a therapeutic equine program. Similarly, Kaiser et al. (2006) found that child-reported levels of inattention, as well as parent-reported levels of inattention and impulsivity, improved following participation in an equine program for sixth-and eighth-grade boys enrolled in a school-based special education program. Recent findings show that children diagnosed with psychiatric disorders have improved general intelligence as measured by the Ravens Progressive Matrices after completing an 8-week equine program (Hession et al., 2014). Such correlational studies provide preliminary support for an association between EAA and EF performances. Unfortunately, most studies have been conducted on children with atypical development, and no studies have been found to correlate with normal children aged 7-8 years.
Given that physical activity is associated with the performance of EF, EAA as a physical activity should show a similar association.
In summary, there is a paucity of research on the effects of EAA on EF in normal children. So, the primary hypothesis of this study was a positive effect of 12 weeks of EAA on three sub-components of EFs (IC, WM, and CF) in normal children aged 7-8 years. The testing and training timeline are shown in Figure 1. Importantly, during the monitoring process, the room lights were dimmed, and the room environment was quiet. Furthermore, during the test, subjects were asked to keep their posture stable and remain as still as possible.

Intervention
This experimental protocol was selected from Cook and Frederick's

Measures
The IC, WM, and CF were evaluated by Flanker task (Zhan et al., 2020), 1-Back (Ji & Wang, 2018), and More-odd shifting (Tian et al., 2021), respectively. The Flanker task, 1-Back, and More-odd shifting were designed using E-Prime 2.0 (Psychology Software Tools Inc.). This task was exhibited on a 15.6-in. monitor that was 80 cm away from the subjects. The congruent and incongruent reaction times (RTs) and accuracy statistics were performed on the test results at the end of the Flanker task and More-odd shifting tests. However, the RTs and accuracy were recorded at the end of the 1-Back test.

Flanker task
In the experimental task, subjects were required to focus on the "+" sign in the middle of the screen to indicate the start of the task. This is followed by a sequence of five letter combinations according to the letters that appear on the screen for 1000 ms, with the gaze point being the position where the middle arrow is located and the stimulus interval being 1 s. This string of letters may appear as follows: congruent conditions, such as "FFFFFF" and "LLLLLL"; incongruent conditions, such as "LLFLL" and "FFLLFF." The experiment required the subjects to respond to the middle letter as quickly and correctly as possible by pressing the "F" key on the keyboard with the index finger if it was an "F" and the "L" key if it was an "L." The two conditions were presented equally and randomly, and the formal test consisted of 2 sections, each of which required 60 judgments and 12 practice sessions before the formal test.

1-Back
During an experimental task, a prompt sign "+" is displayed in the center of the screen to signal the start of that task. In the experimental task, the five letters of the alphabet "B, D, L, Y, and P" were presented as stimuli, and each letter would appear separately in the center of the display, with a stimulus presentation time of 2 s and a stimulus interval of 2 s. Subjects were asked to look at the letters carefully and press the "F" key if the letter presented was the same as the previous one presented, or the "L" key if different. The formal test was divided into 2 segments; each segment had to be completed 24 times and practiced 12 times before the formal test.

More-odd shifting
Subjects focused their attention on the computer screen, and subjects judged the numbers 1-9 (but not 5), as required, with a numerical duration of 1-and a 2-s interval between two numbers. The task is divided into three parts: the first part, "large/small" judgment: The screen presents a black number, if the number is less than 5, press the "F" key; if the number is greater than 5, press the "L" key. The second part, "odd/even" judgment: The middle of the screen shows green numbers; if it is an odd number, press the "F" key to react; if it is an even number, press the "L" key to react. The third type is "large/small-odd/even" shifting judgment: If the presented numbers are black, "large/small" judgment; if they are green, "odd/even" judgment. Subjects were asked to press the key response as soon as possible while ensuring accuracy. Note: All data were normally distributed (p > .05) with chi-squared (p > .05) before independent samples t-tests were performed. In the test of difference between the two groups, height (cm), 127.6 ± 6.2 in EAAG and 128.6 ± 7.2 in CG, t = −.95, p = .35 > .05; weight (kg), 27.7 ± 3.6 in EAAG and 27.5 ± 3.5 in CG, t = .35, p = .96 > .05; BMI (kg/m 2 ), 16.5 ± 1.5 in EAAG and 16.2 ± 1.6 in CG, t = .31, p = .82 > .05. The data results showed no differences in demographic variables between EAAG and CG pre-test. Abbreviations: CG, control group; EAAG, equine-assisted activity group.
The formal test was divided into six subsections, using the sequence ABCCBA. The A and B sections do not require shifting, 16 times each; the C section requires 32 shifts, which includes 16 shifts. Before the formal start of the exercise, the A and B segments were practiced 8 times each, and the C segment was practiced 16 times.

Statistics and analysis
Descriptive results are reported as means ± standard deviations. All statistical analyses were performed using the statistical package SPSS 26.0; significant differences are indicated by different letters (*p < .05; **p < .01).

Demographic variables difference examination
Data were investigated and analyzed on individuals in the EAAG and CG samples, where demographic variables included age, height, weight, and BMI, with the purpose of reducing the effect of experimental results due to demographic differences between the two groups, as shown in Table 2.

IC
In this study, the Flanker task data before and after the experimental intervention were statistically analyzed using a 2 (group: EAAG, CG)×2 (time: pre-test, post-test) repeated measures ANOVA to analyze the changes of EAA on IC in children aged 7-8 years (see Table 3).
A simple effects analysis showed that in the EAAG, there was a highly significant difference (p < .01) pre-and-post test. In addition, in the EAAG, the congruent task accuracies before and after the experiment were 0.84 ± 0.07 and 0.88 ± 0.06, respectively, whereas in the CG, the congruent task accuracies before and after the experiment were 0.85 ± 0.06 and 0.87 ± 0.05, respectively (see Table 4).
In the EAAG, the congruent task RTs before and after the experiment were 725.27 ± 105.34 and 682.42 ± 72.55, respectively, whereas in the CG, the congruent task RTs before and after the experiment were 718.63 ± 89.45 and 705.23 ± 71.67, respectively (see Table 4).

TA B L E 5
In the EAAG, 1-Back accuracies before and after the experiment were 0.83 ± 0.05 and 0.85 ± 0.06, respectively, whereas in the CG, 1-Back accuracy before and after the experiment were 0.83 ± 0.05 and 0.83 ± 0.06, respectively (see Table 6). Abbreviations: CG, control group; EAAG, equine-assisted activity group; RTs, reaction times.

WM
In this study, the 1-Back data before and after the experimental intervention were statistically analyzed using a 2 (group: EAAG, CG)×2 (time: pre-test, post-test) repeated measures ANOVA to analyze the changes of EAA on WM in children aged 7-8 years (see Table 5).

CF
In this study, the More-odd shifting data before and after the experimental intervention were statistically analyzed using a 2 (group: EAAG, CG)×2 (time: pre-test, post-test) repeated measures ANOVA to analyze the changes of EAA on CF in children aged 7-8 years (see Table 7).

TA B L E 7
Statistical results of More-odd shifting variance before and after experimental intervention.

DISCUSSION
In our study, changes in EF in children aged 7-8 years were explored primarily through a 12-week EAA intervention. To our great surprise, 12 weeks of EAA were effective in improving three cognitive tests: Flanker task, 1-Back, and More-odd shifting. That is, 12 weeks of EAA improved IC, WM, and CF significantly.
In our research, 12 weeks of EAA were effective in reducing RTs and increasing the accuracy of IC, which is consistent with studies by others (Contreras-Osorio et al., 2021). Previous studies have shown that the rate of IC development varies at different stages. Anderson et al. (1991) found that 6-7 years old is the sensitive period of development; after 7 years old slow growth, after 10 years old tends to level off. In addition, the subjects in this study belonged to this age group. However, exercise intensity is an important factor in improving postexercise cognitive performance (Chang et al., 2012), further manifested by improved IC performance (Browne et al., 2016). For example, in a meta-analysis, exercise intensity had a significant effect; the results were positive at 64%-76% or 77%-93% of heart rate max for the prescribed exercise (Chang et al., 2012). Although heart rate was not monitored in this study for riding during exercise, the actual exercise heart rate intensity may be consistent with this intensity. It is important to note that the type of exercise also positively affects IC: chronic exercise (Amatriain- study days over an 8-week period and was shown to enhance IC in adolescents (Ludyga et al., 2018). In terms of overall duration, EAA can also be considered chronic exercise. In addition, we found supportive evidence in a study on open-and closed-skill sports (Formenti et al., 2021). It is commonly recognized that closed-skill motor activities are performed in a relatively stable and predictable environment in which motor actions are repetitive and unrelated to the external environment; open-skill physical activity is a dynamic and changing environment, the main feature of which is the motor actions that must be constantly adapted to external stimuli (Di Russo et al., 2010). This change in the context of open-skill movement, in which inappropriate movements must be inhibited, may be associated with greater challenges in motor skills and activation of brain systems involved in EF (particularly the prefrontal cortex) (Lin et al., 2013). This would imply that the cognitive demands in open skills movements (such as EAA), which are characterized by complex motor movements, may contribute to the explanation of the positive effects of exercise on cognitive function (Best, 2010). It is also important to add that EAA can be effective in improving a rider's concentration Ward et al., 2013) and, to some extent, aid in the improvement of IC performance.
The results of the study showed an increasing trend in accuracy and a significant decrease in response time in the 1-Back task. Related studies have shown some improvement in WM and EF in complex sports, such as martial arts (Giordano et al., 2021), gymnastics (Hsieh et al., 2017), basketball (Xu et al., 2022), and soccer (Wen et al., 2021), and EAA also have more complex technical requirements, so the effect is significant. Furthermore, Krejci et al. (2015) reported an intervention in hippotherapy for children with cerebral palsy and showed some improvement in the attention and memory of the subjects. This in some way suggests that equestrian sports are known to improve children's attention and memory consistent with the present study. In fact, studies have shown that elementary school students are still in a stage of continuous brain development and their nervous system shows plasticity in both micro and macro aspects, which quietly emerges when the individual's own abilities cannot meet the requirements imposed by the environment (Lövdén et al., 2010). As in this study, the rider's pre-and-post test accuracy scores on the 1-Back task were above the standard of 0.8, but to a certain extent, they also showed a mismatch between their own ability and the difficulty of the task, so the subjects kept improving their WM processing efficiency to try to reach the matching state. In addition, general intelligence gains undergo a similar process, increasing with WM efficiency, and recent brain research has provided some evidence that this may be the result of changes in neural network activity within the brain following WM training (Nęcka et al., 2021). In addition, there is also some evidence that physical activity may improve white matter integrity in these brain regions (Chaddock-Heyman et al., 2014), which in part facilitates improvements in WM.
A systematic review and meta-analysis (Contreras-Osorio et al., 2021) showed that the frequency of the intervention training was effective in improving WM capacity while being consistent in other sports as well (Xu et al., 2022). The frequency of training one to two times per week in this study was consistent with that of previous researchers.
Exercise as a stressor promotes physiological and psychological arousal (Stork et al., 2018) and increases oxygen and blood flow to the brain (Wheeler et al., 2019), optimizing the allocation of cognitive resources and improving the efficiency of cognitive processing . This study showed that EAAG performed better on a More-odd shifting after an EAA intervention compared to a CG. The results are consistent with previous studies (Kujach et al., 2020). There is also evidence that studies in both open and closed skills movement show lower switching costs in the experimental group compared to the CG, suggesting that the open skill movement pattern helps motorists be better prepared for upcoming movement, temporal and spatial transitions and can better switch from one task to another (Tsai & Wang, 2015 (Borgi et al., 2016). Finally, the immediate feedback the rider receives from the horse allows for physical and mental selfregulation (So et al., 2017). It provides different reinforcement for the successful performance of a task and reinforces the learning of the "checking" part of the cognitive strategy. Furthermore, this result can be explained that the improvement of EF by physical activity seems to be related to the physiological changes it causes in the brain. Regular physical activity has been linked to positive changes in brain structure and volume, including increases in white matter, parietal gray matter, the hippocampus, and basal ganglia volume (Benedict et al., 2013;Erickson et al., 2009). In addition, physical activity is thought to affect brain neuroplasticity because it increases BDNF synthesis in the hippocampus, which promotes neuronal and synaptic growth and differentiation and protects against neuronal and synaptic transmission (Lista & Sorrentino, 2010). Moreover, studies show that exercise improves blood circulation to the brain and that aggregation in exercise plasma reduces inflammation and improves memory (De Miguel et al., 2021). The influence may be more pronounced in children aged 6-12, when their brains are rapidly developing, especially in the dorsolateral prefrontal cortex, anterior cingulate cortex, parietal cortex, and subcortical structures like the thalamus, caudate nucleus, nucleus accumbent, and cerebellum (Bidzan-Bluma & Lipowska, 2018). Therefore, we recommend an increase in EAA for children in this age group to achieve better motor cognition.
Although our findings show some significant effects of EAA on the improvement of EF in children aged 7-8 years, some limitations should be acknowledged. First, our EAAG of subjects were mostly active enthusiasts, and there may be uncontrollable effects of preexisting preferences. Second, the age range was chosen at the stage of 7-8 years old, which is a critical period for cognitive development and has a significant effect; if the age range is increased, this result is not universal. Finally, all our studies have produced behavioral results that do not allow for a deeper explanation of brain neural mechanisms, and useful tools are needed to confirm that cognitive engagement in movement is supporting the development of EF in children.

CONCLUSION
These findings suggest that a 12-week EAA intervention can be effective in improving EF (IC, WM, and CF) and promoting cognitive performance in children aged 7-8 years, as well as being a worthwhile physical activity program.

CONFLICT OF INTEREST STATEMENT
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the first author upon reasonable request.