Abstract: This was performed pre and post a

Abstract:

Objectives: This
study investigated the effect of moderate to vigorous aerobic physical activity
on the cognitive functioning of children. The aim was to attempt to identify a
positive relationship between physical activity and cognitive functioning. This
was done by testing the cognitive functioning of a group of thirty-nine
children before and after exercise, as well as before and after a sedentary
period of the same length.

Methods: The cognitive
functioning of the participants was measured using the Trail Making Test. This
test is made up of two parts, A and B, which measure different elements of
cognitive functioning. This was performed pre and post a moderate to vigorous
forty minute session of aerobic physical activity. The Trail Making Test was
also carried out pre and post a forty minute sedentary period in order to
compare results and to investigate the effects, if any physical activity had on
the performance of the test.

Results: Physical activity
appeared to have an effect on the performance of Part A of the Trail Making
Test. This was due to a significant difference in the change in Part A times
post physical activity when compared with post sedentary. Physical activity was
not found to have a significantly different effect on the performance of Part B
of the test when compared with the sedentary times recorded.

Conclusion: Our
results indicate that acute bouts of moderate to vigorous physical activity
have a positive effect on the areas of cognitive functioning involved in visual
search and motor response.

 

Introduction:

Cognitive functioning (C.F.) can be defined as any “intellectual process by which one becomes
aware of, perceives, or comprehends ideas.
It involves all aspects of perception, thinking, reasoning,
and remembering”(Mosby’s Medical Dictionary, 2009). Physical activity
(P.A.) refers to bodily movements performed by muscles in the body which result
in the expenditure of energy (Bouchard et al, 1993).

The benefits of P.A. on general health and well-being
has been well documented and researched. It has been proven to reduce the risk
of illnesses such as cardiovascular disease, types of cancer, diabetes, and
depression (Bouchard & Shephard, 1994). While the benefits of P.A. on
health have been long accepted, its relationship with C.F. has been debated.
Despite some disagreement over the effect that exercise has on the C.F. of
individuals, a huge amount of research in this field has produced positive
results. An example of such a study is that conducted by the California
Department of Education in 2001. In a study of over 900,000 children between
the ages of 10 and 14, a positive relationship was found between P.A. level and
academic achievement (CDE, 2001).

Another study conducted in 2011 suggested that P.A.
may influence the manner in which the brain organises its attentional resources
(Hillman et al, 2011). They found that exercise could have an impact on the
manner in which the brain responds to external stimuli, allowing individuals to
be more efficient in terms of attention span. This would have a major impact on
learning, as it would increase the brains capacity for informational input,
while reducing the energy expenditure.

Though large numbers of studies have been conducted in
this area, it remains unclear as to which types of P.A. cause the greatest
effect, if any, on C.F. In a 2009 study carried out by Pesce et al, the effect
of different forms of exercise on recall memory in children were investigated.
This study reported that acute bouts of vigorous P.A. promoted the storing of
new information into the long-term memory of the subjects, while bouts of
low-moderate exercise did not (Pesce et al, 2009).

The area of fitness which appears to have the greatest
impact on C.F. from reviewing relevant literature is aerobic fitness. Children
with high levels of aerobic fitness were found to be more successful than their
less-fit counterparts when tested on their abilities to process and learn new
information. This was done by providing information for the children to study
alone, before being asked to recall the information later (Raine et al, 2013).

It is without question that executive function plays a
key role in academic performance. A study of 51 school children found that
those with poor levels of executive function consistently produced lower grades
than those with higher levels (St Clair-Thompson et al, 2006). Although the
importance of intellectual strengths of students clearly effect academic
performance, it can equally be argued that non-intellectual strengths such as
motivation and discipline play an integral role (Duckworth & Seligman,
2006). If true, P.A. may play a major role in improving the academic
performances of students in schools, due to its ability to develop
self-discipline, teamwork, and potentially self-esteem (McCauley et al, 2005).

 

Based on the most effective previous research carried
out in this area, we decided to test the effects of an acute bout of
moderate-vigorous, aerobic physical activity on cognitive functioning in children.
Cognitive functioning was measured using the Trail-Making Test. This test was
chosen as it provides a measure of two domains C.F. separately, with visual
search and motor-speed skills being tested in Part A, while mental flexibility
and set-switching are measured in Part B (Bowie & Harvey, 2006).

The hypothesis for the study was that an acute bout of
moderate-vigorous, aerobic P.A. would have a positive effect on C.F. in
children.

 

Methodology:

 

Participants
Thirty-nine (22 females and 17 males) fourth class students with a mean age of
9.6 years and standard deviation of 0.8 participated in the study. The students
were from the West Dublin area. The participants were from a co-educational
school which allowed for mixed gender testing. Participants were selected from
the two fourth classes within the school. None of the students in either of the
classes reported any forms of learning disabilities. The students were provided
with consent forms, which were to be signed by their parents or guardians to
allow them to take part in the study. Students were also required to sign an
assent form to acknowledge their own willingness to take part in the study.
Participating students were all assigned a number. This allowed for ease of
recording results and only the testers were aware of which numbers correspond
to each student. No initial cognitive or fitness testing was carried out on the
students to allow for an unbiased selection

Trail
Making Test
For
our study, we used the Trail Making Test (TMT) in order to test cognitive
function. The TMT has been shown
to be a reliable and valid neuropsychological test (Tombaugh, 2004). The
most widely used version of the TMT comprises parts A and B. In part A, the
subject uses a pencil to connect a series of 25 encircled numbers in numerical
order. In part B, the subject connects 25 encircled numbers and letters in
numerical and alphabetical order, alternating between the numbers and letters.
For example, the first number ”1” is followed by the first letter ”A,”
followed by the second number ”2” then second letter ”B” and so on. This
continues up to the number “13”, ensuring there are 25 encircled characters in
each test. The numbers and letters are placed in a semi-random fixed order, in
such a manner as to avoid overlapping lines being drawn by the examinee.
Each participant was given a “practice” Test A and Test B directly before
carrying out the corresponding tests. These practise tests were a good
representation of the actual TMT. The TMT measures a variety of cognitive
functions within the person being tested. Test A is generally presumed to be a
test of visual search and motor speed skills, whereas Test B is considered also
to be a test of higher level cognitive skills such as mental flexibility and
set shifting. We tested the effect of physical activity on the performance
levels on the TMT.

 

System
for Observing Fitness Instruction Time (SOFIT)
To
measure the intensity of the exercise we used the System for Observing Fitness
Instruction Time (SOFIT) observation tool. The SOFIT observation tool has been shown to be a reliable and valid
means of measuring physical activity levels (Rowe et al., 2004). This involved monitoring a specific student’s
activity levels at specific intervals, for a determined amount of time, e.g.
Student 1 is monitored every minute for 5 minutes. Activity levels were given a
rating between 1 to 5 with each number indicating a different level of
intensity as outlined below:
1.         Lying down
2.         Sitting
3.         Standing
4.         Walking
5.         Vigorous.
While one tester led the lesson, the other three were observing and recording
the intensity level of a participant. After 5 minutes of observing we would
select a different participant from the group and repeat the process. We did
this throughout the lesson.

 

Exercise
Physical
activity in this study was considered to be any aerobic exercise performed at a
moderate to vigorous intensity. For this study, we wanted the participants to
perform physical activity at a moderate to vigorous intensity for forty minutes
in order to ensure the students were utilising their aerobic fitness. In order
to achieve this we compiled a lesson which consisted of three sections, a
warm-up, circuit and a cool down.
Warm-Up: The warm-up started with the participants running around in a square
and performing instructions given to them by the teacher. The instructions
included high knees, heel flicks, touching the ground with both hands, jumping
up as high as they could. Circuit: The circuit was 25 minutes long and was made
up of six sections: Interval sprints (half basketball court), jumping jacks,
high knees, heel flicks, repeated standing jump (both feet together) and
distance running (80% of full basketball court repeated). The participants were
divided amongst the stations and performed the task for thirty seconds with a
thirty second rest period between each station. Once all participants had
completed all the stations they were given a two-minute rest period. This was
repeated three times.
Cool-Down: Consisted of a light jog the full length of a basketball court
followed by a number of various dynamic stretches.

 

Procedure

The
data for this research paper was collected over two days. The testing for was carried out as follows:

Active
group: Each student was brought to the designated testing room in groups of 4
and completed the TMT. Once completed they returned to their classroom and the
next 4 students were brought to the same room. Once the whole class had
completed the TMT, the class as a whole were brought outside and performed 40
minutes of vigorous aerobic PA. SOFIT observation sheets were filled in during
active time using method above. Following the exercise, the class were again
tested with the TMT using the same procedure.

Sedentary
group: Each student was brought to the designated testing room in groups of 4
and completed the TMT. Once the student completed the TMT they returned to
their classroom for 40 minutes. This 40-minute period was defined as sedentary
time where they engaged in the normal class routine. After each student had
spent the allocated time in the classroom, they were brought back to the
testing room to complete the TMT again. This procedure was repeated for each
student.

Day
1

Active
group: Class A

Sedentary
group: Class B

Day
2

Active
group: Class B

Sedentary
group: Class A

 

 

Statistical
Analyses

Data
analysis was performed using the software Statistical Package for the Social
Sciences (SPSS).

The
principal modes of data analysis were one-way repeated measures analysis of
variance (ANOVA) and paired sample t-tests.

The
one-way repeated measures ANOVA was used to analyse the effect of physical
activity (pre and post) on the TMT scores of each participant twice during the
study. This provided us with descriptive statistics, a Wilk’s Lambda value of
significance, as well as pairwise comparisons.

The
paired sample t-tests were used to analyse the difference in times between the
Pre and Post scores for Active and Sedentary times. This was carried out for
each of Parts A and B of the TMT separately. The total time taken to complete
parts A and B was also analysed using this method.

 

 

Results:

 

Results
from SOFIT averaged for the group as 4.5, which falls between walking and
vigorous category.

 

A one-way repeated measures ANOVA
was conducted to compare scores on the effect of physical activity on Part A of
the TMT at Time 1 (pre activity), Time 2 (post activity), Time 3 (pre
sedentary), and Time 4 (post sedentary). The means and standard deviations are
presented in Table 1. There was a significant effect for time, Wilks’ Lambda =
.432, F (3, 36) = 15.8, p < .0005, multivariate partial eta squared = .57.   Table 2 below shows the differences between each of the Times for TMT Part A outlined above using the Bonferroni Post-Hoc test. Significant differences were found between Times 1 and 2, Times 1 and 4, and Times 3 and 4 (all p<0.05). All other comparisons were found to be insignificant.                 Table 1 Descriptive statistics for the effect of physical activity on TMT Parts A&B at Time 1, Time 2, Time 3 and Time 4 Descriptive Statistics   Test A Test B Pre Active Post Active Pre Sedentary Post Sedentary Pre Active Post Active Pre Sedentary Post Sedentary Mean (t) 48.3079 35.0718 43.3582 37.1582 118.8895 97.1151 105.3964 91.5626 Standard Deviation 21.48137 16.62194 15.73948 17.56802 51.43195 44.61589 40.00113 49.21863 Number of Participants 39 39 39 39 39 39 39 39     Table 2 Pairwise comparisons for the effect of physical activity on TMT Parts A&B at Time 1, Time 2, Time 3 and Time 4 Pairwise Comparisons (significant values) Test A Pre Active Post Active Pre Sedentary Post Sedentary Test B   Pre Active Post Active Pre Sedentary Post Sedentary   Pre Active   0.000 1.000 0.036 Pre Active   0.000 0.789 0.059   Post Active 0.000   0.059 1.000 Post Active 0.000   1.000 1.000   Pre Sedentary 1.000 0.059   0.005 Pre Sedentary 0.789 1.000   0.041   Post Sedentary 0.036 1.000 0.005   Post Sedentary 0.059 1.000 0.041                               Figure 1   A one-way repeated measures ANOVA was conducted to compare scores on the effect of physical activity on Part B of the TMT at Time 1 (pre activity), Time 2 (post activity), Time 3 (pre sedentary), and Time 4 (post sedentary). The means and standard deviations are presented in Table 1 above. There was a significant effect for time, Wilks' Lambda = .553, F (3, 36) = 9.68, p < .0005, multivariate partial eta squared = .48.   Table 2 above shows the differences between each of the Times for TMT Part B outlined above using the Bonferroni Post-Hoc test. Significant differences were found between Times 1 and 2, and Times 3 and 4 (all p<0.05). All other comparisons were found to be insignificant.                     Figure 2     A paired-samples t-test was conducted to evaluate the effect of physical activity on students' scores in TMT part A. There was a statistically significant decrease in TMT part A scores from Pre – Post Active Part A (M = 13.24, SD = 14.71) to Pre – Post Sedentary Part A (M = 6.2, SD = 10.61), t (38) = 2.39, p <. 05 (two-tailed). The mean decrease in Pre – Post Part A scores was 7.04 with a 95% confidence interval ranging from 1.09 to 12.99. The eta squared statistic (0.131) indicated a moderate effect size.   A paired-samples t-test was conducted to evaluate the effect of physical activity on students' scores in TMT part B. There was not a statistically significant decrease in TMT part B scores from Pre – Post Active Part B (M = 21.77, SD = 28.88) to Pre – Post Sedentary Part B (M = 13.83, SD = 30.17), t (38) = 1.21, p >. 05 (two-tailed). The
mean decrease in Pre – Post Part B scores was 7.94 with a 95% confidence
interval ranging from -5.39 to 21.27. The eta squared statistic (0.04)
indicated a small effect size.

 

A paired-samples t-test was
conducted to evaluate the effect of physical activity on students’ overall
scores in TMT. There was not a statistically significant decrease in TMT scores
from Pre – Post Active Total (M = 35.01, SD = 35.08) to Pre – Post Sedentary
Total (M = 20.03, SD = 32.11), t (38) = 1.9, p >. 05 (two-tailed). The mean
decrease in Pre – Post scores was 14.98 with a 95% confidence interval ranging
from -0.95 to 30.9. The eta squared statistic (0.09) indicated a moderate
effect size.

All results above can be seen in
table 3 and 4 below.

 

Table 3

Paired Sample Statistics

 

Mean

Standard Deviation

Pair
1

Difference between Pre and Post
Active Test A
 

13.2362

14.70758

Difference between Pre and Post
Sedentary Test A

6.2000

10.60885

Pair
2

Difference between Pre and Post
Active Test B
 

21.7744

28.88280

Difference between Pre and Post
Sedentary Test B

13.8338

30.17413

Pair
3

Total Pre – Total Post (Active)
 

35.0105

35.08191

Total Pre – Total Post (Sedentary)
 

20.0338

32.11204

Paired sample statistics for Pre –
Post Active and Sedentary Parts A and B, and Total Pre –

Total Post

 

 

 

 

 

 

Table 4

Paired sample t-tests for Pre – Post
Active and Sedentary Parts A and B, and Total Pre –

Total Post

Paired Sample T-Tests

 

 
Mean

 
Standard
Deviation

95% Confidence
Interval of the Difference
Lower

95% Confidence
Interval of the Difference
Upper

 
t

 
df

 
Sig. (2-tailed)

 

Pair 1

 
7.03615

 
18.35357

 
1.08661

 
12.98569

 
2.394

 
38

 
.022

 

Pair 2

 
7.94051

 
41.12293

 
-5.39000

 
21.27103

 
1.206

 
38

 
.235

 

Pair 3

 
14.97667

 
49.12639

 
-.94827

 
30.90160

 
1.904

 
38

 
.065

 

Pair 1

Difference
between Pre and Post Active Test A–Difference between Pre and Post Sedentary
Test A

Pair 2

Difference
between Pre and Post Active Test B–Difference between Pre and Post Sedentary
Test B

Pair 3

Total
Post Active – Total Post Sedentary
 

 

Discussion:

The results of the study do not definitively support
the hypothesis. The post scores were significantly lower in Parts A and B of
the TMT after both exercise and sedentary time. This indicates that although
the participants improved every time they completed the test, it was not
necessarily due to P.A.

The most obvious positive correlation between P.A. and
C.F. from our research was the effect P.A. appeared to have on the scores
obtained in Part A of the TMT. The average time taken to complete Part A was reduced
to a greater extent after physical activity when compared with the post
sedentary test. This can be seen from the pairwise comparisons in Table 1, as
well as in Pair 1 of the paired sample tests in Table 4. This indicates that
the exercise bout improved the participant’s visual-search and motor speed
skills. This is in keeping with previous studies carried out on the effects of
acute P.A. on C.F. It has been found that acute exercise increases the speed
with which the body can physically respond during cognitive testing
(Tomporowski, 2003). This is potentially due to the discovery that exercise
causes an increase in the production of neurotransmitters, which aid in
processing speed (McMorris et al, 2011). The intensity of the P.A. in our study
may also have played a role in the observed effect on Part A times. On average
the participants scored a 4.5 out of 5 on the SOFIT observation tool,
indicating students remained between walking and vigorous activity throughout
the lesson. High intensity bouts of exercise such as this have been shown to
improve basic C.F. such as choice-reaction times post-exercise due to increased
adrenaline levels in the blood (Brisswalter et al, 2002). The exercise
performed, though quite high in intensity, did not take any of the participants
to exhaustion. This may also have benefited the performance of the
participants, as prolonged moderate to vigorous exercise of up to 40 minutes
without reaching exhaustion has been found to provide the optimum arousal for
contingent negative variation. This has been found to be involved with C.F’s
such as expectancy and attention (Kamijo et al, 2004).

Despite the apparent benefits of high intensity P.A.
on simple C.F. tasks, it has been found to be less effective on the performance
of more complex tests (Hogervorst et al, 1996). This is in keeping with the
results obtained in our study in relation to Part B of the TMT, which measures
mental flexibility and set-shifting. Our results showed no significant
difference in the effects of P.A. on the times for Part B when compared with
the sedentary scores, as can be seen above in Pair 2 of the paired sample tests
in Table 4. This is in keeping with previous research carried out, which
suggested that P.A. had little or no effect on the set-shifting component of
executive function (Coles & Tomporowski, 2008).

Although our results do not indicate a clear positive
relationship between P.A. and C.F., the study contained several limitations.
Population size was one of these limitations, as only thirty-nine participants
took part in the study. This may not have provided a full representation of the
effects of P.A. on C.F. for the age being tested. Another limitation was the
apparent effect of trial familiarisation on the study. Upon completing the
study, each participant had completed the TMT four times. Although these tests
were done across two days, the participants may have displayed improvements due
to repetition, and not necessarily as a result of P.A.

 

 

Conclusion

The results of our study indicate that P.A. appears to
effect certain aspects of C.F., specifically visual search and motor response,
while being ineffective to others such as set-shifting and mental flexibility.

Although our results and previous studies provide
little support for a positive effect of acute P.A. on complex C.F., it is
possible long term P.A. programs could provide different findings. Long term
exposure to P.A. has been found to improve C.F. in elderly sufferers of
Parkinson’s disease over time (Tanaka et al, 2009). Also, in a meta-analytical
study of 134 case studies based on the effects of P.A. on C.F., the effects of
both acute and long term P.A. were investigated. It was found that acute P.A.
provided in general small, short term improvements on C.F. However, long term
exercise programs could potentially provide more significant, longer lasting
effects on C.F. (Etnier et al, 1997). Also, the effects of both acute and long
term P.A. on C.F. may vary with the ages of the participants being tested.

As a result, further research must be carried out on
the long term effects of P.A. on C.F. Also, a wide range of ages must be tested
to provide a more complete picture of the potential relationship. If a
definitively positive relationship were to be established, the repercussions on
both health and academic achievement in children could be enormous. It would
also put an onus on schools to improve activity levels, as no other institution
has as much influence on the lives of children, irrespective of their economic
background or family life (Resaland et al, 2015). 

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