CHAPTER-IV
RESULT AND DISCUSSION
In the previous chapter present researcher elaborately discussed about the subjects,
parameters and the statistics. In this chapter the results from the collected data were
presented systematically with appropriate graphs and tables. Discussions were also made
accordingly. In the final study, the researcher presented results of all the data in three
different dimensions of Indian football players. The dimensions are as follows:
1. Age level of the players
2. Level of performance of the players.
3. Playing position of the players.
Explanation behind these different dimensions is that present researcher wanted to
prepare a Neurocognitive profile of the football players.
Apart from above mentioned dimension, present researcher also worked on the
identification of threshold level of brain function impairment after continuous heading in
football.
4.1 Result of the Pilot Study
In this study, present researcher measured neuropsychological status of the four (04),
district level Indian football players with the use of CNS Vital Sign software (Version:
2012). This software includes neuropsychological area like: Neurocognitive Index,
Composite Memory, Verbal Memory, Visual Memory, Processing Speed, Executive
Function, Psychomotor Speed, Reaction Time, Complex Attention, and Cognitive
Flexibility. Following are the results of the various domain of neuropsychological profile
recorded in the pilot study:
Result And Discussion
Sl. No.
Domain Name
Standard Score
(Mean)
Range
1.
Neurocognitive Index
70.5
Low
2.
Composite Memory
76.43
Low
3.
Verbal Memory
77.57
Low
4.
Visual Memory
82.29
Low-Average
5.
Processing Speed
76.43
Low
6.
Executive Function
60.43
Very Low
7.
Psychomotor Speed
83.23
Low-Average
8.
Reaction Time
72.29
Low
9.
Complex Attention
64.50
Very Low
10.
Cognitive Flexibility
56.07
Very Low
Table II: Pilot Study Result
Here to mention, above average domain score indicate a standard score in that
domain of greater than 109. Average is 90-109. Low average is 80-89. Below Average is
70-79. Very low are less than 70. According to the CNS Vital Sign Software
(version:2012) each and every neuropsychological domain high score is better but in case
of reaction time and complex attention low score is better. As per the score of the pilot
study footballers were better in reaction time and complex attention.
4.2 Final Study
4.2.1 Final Study-I: On Age Level
Present researcher divided total thirty eight (38) subjects in two different age level of
Indian football players : Under 21 years (U=21) of age group in which total number of
subject were eighteen (18) and other age group was Above 21 years (A=21) which was
consist of twenty (20) subjects. CNS Vital Sign software (version: 2012) was used to
measure the Neurocognitive abilities of the players. This software measured ten (10)
different areas of Neurocognition. Following are the results of different neurocognitive
areas separately.
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Result And Discussion
4.2.1.a Neurocognitive Index
Graph and Table no 1: Neurocognitive Index of Under 21 & Over 21 Football Players
The results indicated that Over 21 years aged players (89.45±9.34) recorded better
performance than the Under 21 players (76.00±22.26) in Neurocognitive Index (Graph&
Table no: 1). This result is also significant at 0.05 level. So from these results, it may be
concluded that Over 21 years football players express better neurocognitive index than
the Under 21 age level football players.
4.2.1.b Composite Memory
Graph and Table no 2: Composite Memory of Under 21 & Over 21 Football Players
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Result And Discussion
It was observed that Over 21 years football players (87.30±10.97) recorded better
performance than the Under 21 players (77.83±15.73) in composite memory. (Graph &
Table no: 2). This results also significant at 0.05 level. From this result it may be
concluded that Over 21 year aged football players are better in composite memory than
the Under 21 year’s football players.
4.2.1.c Verbal Memory
Graph and Table no3: Verbal Memory of Under 21 & Over 21 Football Players
Results indicated that Over 21 years aged football players (90.95±16.41) performed
better than the Under 21 years aged football player (82.78±23.21) in verbal memory
(Graph & Table no: 3). From this it may be concluded that in verbal memory domain,
Over 21 years aged players are reported better than the Under 21 years aged players.
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Result And Discussion
4.2.1.d Visual Memory
Graph and Table no 4: Visual Memory of Under 21 & Over 21 Football Players
In visual memory, it was observed that Over 21 years aged football players
(91.70±12.02) performed better than the Under 21 years aged football players
(82.89±14.00), which is also significant at 0.05 level (Graph and Table no- 4) . So from
the above, it may be concluded that Over 21 years football players possess better visual
memory than the Under 21 years aged football players.
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Result And Discussion
4.2.1.e Processing Speed
Graph and Table no 5: Processing Speed of Under 21 & Over 21 Football Players
In processing speed, it was observed that Over 21 years aged football players
(89.05±11.66) performed better than the Under 21 years aged football players
(80.50±15.79). So from this result, it may be concluded that Over21 years football
players possess better processing speed than the Under 21 years aged football
players.(Graph and Table no: 5)
4.2.1.f Executive Function
Graph and Table no 6: Executive Function of Under 21 & Over 21 Football Players
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Result And Discussion
Results indicated that Over 21 years aged football players (95.5±17.06) recorded
better performance than the Under 21 years aged football players (68.50±40.03) in
executive function and this result also significant at 0.05 level (Graph and Table no: 6).
From above mentioned result, it may be concluded that Over 21 years aged football
player better in executive functioning than the Under 21 years aged football players.
4.2.1.g Psychomotor Speed
Graph and Table no 7: Executive Function of Under 21 & Over 21 Football Players
In psychomotor speed measurement, Over 21 years aged football players
(97.40±13.93) recorded better than the Under 21 years aged football players (Graph &
Table no: 7). So it may be concluded that Over 21 years aged football players possess
better psychomotor speed than the Under 21 years aged football players.
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Result And Discussion
4.2.1.h Reaction Time
Graph and Table no 8: Reaction Time of Under 21 & Over 21 Football Players
Results indicated that Under 21 years aged football players (74.50±24.34) recorded
better in reaction time than the Over 21 years aged football players (78.20±10.99). So
this may concluded that Under 21 years football players were better in reaction time
(Graph & Table no: 8).
4.2.1.i Complex Attention
Graph and Table no 9: Complex Attention of Under 21 & Over 21 Football Players
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Result And Discussion
Results indicated that Under 21 years aged football players (71.44±32.64) performed
better in complex attention than the Over 21 years aged football players (88.70±15.29).
This results is also significant at 0.05 level. So from this results it may be concluded that
Under 21 years aged football players possess better complex attention than the Over 21
years aged football players(Graph & Table no : 9).
4.2.1.j Cognitive Flexibility
Graph and Table no 10: Cognitive Flexibility of Under 21 & Over 21 Football Players
In cognitive flexibility measurement, it was observed that Over 21 years aged
football player (94.00±17.55) recorded better than the Under 21 year’s football players
(64.83±40.08) which is also significant at 0.05 level (Graph & Table no: 10). So from
these results, it may be concluded that Over 21 years aged football players are more
cognitively flexible than the Under 21 years aged football players.
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Result And Discussion
4.2.2 Final Study-II: On Performance Level
Here, present researcher divided the total thirty eight (38) players in two different
groups on the basis of their performance level in football: District and University Level.
In district level, total eighteen (18) football players were included whereas from the
university level, twenty (20) football players were also included. Here also CNS Vital
Sign software (Version: 2012) was used to measure the neuropsychological profile of the
players. Ten (10) major domains were measured with this software. Following are the
results of all ten domain of neuropsychology in details:
4.2.2.a Neurocognitive Index
Graph and Table no 11: Neurocognitive Index of University & District Level Football Players
Results indicated that university level players (93.25±7.85) recorded better than the
district level players (71.78±19.18) in neurocognitive index measurement (Graph &Table
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Result And Discussion
no: 11), which was also significant at 0.05 levels. So from the result it may be concluded
that university level players possess better neurocognitive index than the district level
football players.
4.2.2.b Composite Memory
Graph and Table no 12: Composite Memory of University & District Level Football Players
It was observed that university level football players (88.00±10.85) recorded better
composite memory than the district level football players (77.06±15.29) (Graph & Table
no:12). This result was also significant at 0.05 level. So from the above, it may be
concluded that university level football players possess better composite memory than
the district level players.
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Result And Discussion
4.2.2.c Verbal Memory
Graph and Table no 13: Verbal Memory of University & District Level Football Players
In verbal memory measurement, it was observed that university level football players
(94.10±17.08) recorded better than the district level player (79.28±20.70) in verbal
memory and this results also significant at 0.05 level (Graph & Table no:13). So from
this result, it may be concluded that university level footballers holds higher form of
verbal memory than the district level football players.
4.2.2.d Visual Memory
Graph and Table no 14: Visual Memory of University & District Level Football Players
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Result And Discussion
It was recorded that in visual memory domain, university level football players
(91.95±12.98) better than the district level football players (82.61±12.80) and this results
was also significant at 0.05 level (Graph & Table no: 14). From these results it may be
concluded that university level football players possess better visual memory than the
district level football players.
4.2.2.e Processing Speed
Graph and Table no 15: Processing Speed of University & District Level Football Players
It was observed that in processing speed domain, measurement university
level football players (92.70±10.94) recorded better performance than the district
level football players (76.44±12.69) and this results was also significant at 0.05 level
(Graph & Table no:15). From this result it may be concluded that the university level
football player’s holds better processing speed in comparison to district level football
players.
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Result And Discussion
4.2.2.f Executive Function
Graph and Table no 16: Executive Function of University & District Level Football Players
Results indicated that in executive function domain, university level football players
(101.30±11.51) recorded better performance than the district level football players
(62.06±36.44) and this result was significant at 0.05 level (Graph & Table no: 16). From
this result, it may be concluded that university level football players possess better
executive functioning ability than the district level football players.
4.2.2.g Psychomotor Speed
Graph and Table no 17: Psychomotor Speed of University & District Level Football Players
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Result And Discussion
Results indicated that in psychomotor speed domain assessment, University level
football players (102.65±9.30) significantly (at 0.05 levels) better than the district level
football players (82.78±13.89) (Graph & Table no: 17). So from the above, it may be
concluded that university level football players possesses better psychomotor speed than
the district level football players.
4.2.2.h Reaction Time
Graph and Table no 18: Reaction Time of University & District Level Football Players
In reaction time measurement it was observed that district level football players
(73.89±25.19) slightly better than the university level football players (78.75±8.84). So
from the above mentioned results it may be concluded, in reaction time district level
players were better than the university level football players (Graph & Table no: 18).
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Result And Discussion
4.2.2.i Complex Attention
Graph and Table no 19: Complex Attention of University & District Level Football Players
Results indicated that in complex attention, district level football players
(67.28±30.88) recorded better performance than the university level football players
(92.45±12.92) which was also significant at 0.05 level.(Graph & Table no: 19). So from
the above mentioned results it may be concluded that district level football players
possess better complex attention ability than the university level football players.
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Result And Discussion
4.2.2.j Cognitive Flexibility
Graph and Table no 20: Cognitive Flexibility of University & District Level Football Players
It was observed that in cognitive flexibility measurement, university level football
players (98.65±13.01) significantly performed better than the district level football
players (61.33±39.40) and the level of significance was 0.05 level (Graph & Table no:
20). So from the above mentioned results, it may be concluded that university level
football players possess better cognitive flexibility than the district level football players.
4.2.3 Final Study-III: On Playing Position
Here, present researcher conducted his study on different playing position in
football. Accordingly he picked up subjects from different playing position like defender,
midfielder and striker. Total thirty eight (38) subjects voluntarily participated in this
study. Among them sixteen (16) players played in defense position, thirteen (13) players
played in midfield position and remaining nine (9) players were from striking position.
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Result And Discussion
Here also CNS Vital Sign software (Version: 2012) was used to measure the
neurocognitive abilities of the Indian players. This software measured ten (10) different
domain of neurocognition. Results of the entire domain are explained below separately:
4.2.3.a Neurocognitive Index
Graph and Table no 21: Neurocognitive Index of Various Playing Position of Football Players
It was observed in neurocognitive index domain measurement, the players who
played in the striking position (88.78±7.17) performed better than the players who played
in the position of defense (80.69±20.17) and midfield (82.08±19.12) respectively
(Graph& Table no: 21). So from the above mentioned result, it may be concluded that the
players playing in a striking position possess better neurocognitive index than the player
playing in midfield and defense position.
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Result And Discussion
4.2.3.b Composite Memory
Graph and Table no 22: Composite Memory of Various Playing Position of Football Players
It was observed that the players playing in defense position (83.19±16.46) recorded
better than the players played in midfield (83.15±11.81) and striker (81.67±14.10)
position in composite memory domain measurement (Graph &Table no: 22). So from the
above mentioned result, it may be concluded that defenders possess better composite
memory in comparison to the players playing in midfield and striking zone.
4.2.3.c Verbal Memory
Graph and Table no 23: Verbal Memory of Various Playing Position of Football Players
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Result And Discussion
It was observed that, the players playing in midfield position (89.62±13.02) recorded
better than the players played in defense (86.44±25.71) and striker (84.56±18.75)
position in verbal memory domain measurement (Graph & Table no: 23). So from the
above mentioned result it may be concluded that midfielder in football possess better
verbal memory in respect of the player playing in defense and striker position
respectively.
4.2.3.d Visual Memory
Graph and Table no 24: Visual Memory of Various Playing Position of Football Players
Results indicated that the players playing in defense position (89.69±13.58) recorded
better performance of visual memory than the players playing in midfield (82.15±15.53)
and striker (87.78±14.37) position (Graph & Table no: 24). So from the above mentioned
result it may be concluded that players playing in defense position possess better visual
memory in comparison to the players playing in midfield and striker position
respectively.
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Result And Discussion
4.2.3.e Processing Speed
Graph and Table no 25: Processing Speed of Various Playing Position of Football Players
Results indicated that the players playing in the striker position (87.00±14.30)
reported better performance than the players playing in the defense (84.88±13.30) and
midfield (83.77±16.25) position in processing speed (Graph & Table no: 25). So from the
above mentioned result it may be concluded that the players who are playing in striker
position possess better processing speed in respect of players playing in defense and
midfield position.
4.2.3.f Executive Function
Graph and Table no 26: Executive Function of Various Playing Position of Football Players
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Result And Discussion
It was observed that the player playing in the striker position (92.89±16.53) reported
better performance than the players playing in the defense (78.38±38.86) and midfield
(81.00±33.63) position in executive function (Graph & Table no-26). So from the above
mentioned result it may be concluded that the players who are playing in striker position
possess higher level of executive function ability in respect to the players playing in
defense and midfield position.
4.2.3.g Psychomotor Speed
Graph and Table no 27: Psychomotor Speed of Various Playing Position of Football Players
It was observed that the players playing in the striking position (96.44±11.64)
recorded better performance in psychomotor speed domain than the players playing in
defense(94.25±17.08) and midfield (89.77±19.03) position (Graph & Table no: 27). So
from the above mentioned result it may be concluded that striker in football possess
better psychomotor speed than the players playing in defense and midfield position
respectively.
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Result And Discussion
4.2.3.h Reaction Time
Graph and Table no 28: Reaction Time of Various Playing Position of Football Players
It was observed that the players playing in the midfield position (73.15±14.73)
recorded better reaction time than the player playing in the defense (77.63±23.00) and
striker (79.11±14.69) position(Graph & Table no: 28). So from above mentioned result, it
may be concluded that the midfielder was having better reaction time in comparison to
defender and striker.
4.2.3.i Complex Attention
Graph and Table no 29: Complex Attention of Various Playing Position of Football Players
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Result And Discussion
The result of complex attention domain show that, the players playing in the defense
position (75.00±29.60) were better than the players playing in midfield (80.54±25.91)
and striker (90.33±18.80) position respectively (Graph & Table no: 29). So from the
above mentioned result it may be concluded that defenders holds better complex attention
level in comparison to the midfielder and striker.
4.2.3.j Cognitive Flexibility
Graph and Table no 30: Cognitive Flexibility of Various Playing Position of Football Players
The result of cognitive flexibility domain showed that, the players playing in the
striker position (94.44±17.07) recorded better in cognitive flexibility than the players
playing in defense (74.88±38.75) and midfield (76.85±34.10) position respectively
(Graph & Table no: 30). So from the above mentioned result it may be concluded that,
striker position players possess better cognitive flexibility in comparison to the defender
and midfielder.
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Result And Discussion
4.3 Final Study-IV: Impairment after Heading
The unique area of this study is the identification of threshold level of
neuropsychological impairment after heading. In football heading is one of the major
skill which applied frequently by the player. Specially defensive player uses heading to
clear the ball and offensive player uses heading to get a goal. Earlier heading was not
used in football, but now a day it becomes a very useful skill for the purpose of defense
as well as offense. In 1970’s first time some researcher raised a question on heading and
brain injury. But the momentum of research was started after 80’s. In recent decades it is
a major research area of heading and brain function impairment. Many researchers
engaged themselves to locate the impairment. There are also other types of research
report those proved no impairment after heading. The present researcher after thoroughly
reviewing all the available scientific literature within his limit observed that no research
group was tried for identification of threshold level of neuropsychological impairment
after continuous heading. Hence, this unique research area was organized. In this study
(Final Study IV) the researcher used CNS vital sign software version 2013. There were
16 parameters. Total 20 subjects were divided 5 each in 4 groups: 10 minutes; 15
minutes; 20 minutes and 25 minutes as per the duration of heading concern.
In the ideal laboratory setup all the subjects were given rest then following a proper
protocol initial data was collected in the different days as per their schedule. Then 10
minutes group started heading for 10 minutes in the outside lawn of the laboratory. After
finishing 10 minutes continuous heading again the neuropsychological test was
conducted individually on all the 10 minutes group. The same procedure was followed on
the other groups. But the date and time of the test was different for each individual
subjects. In the following the result of this unique study is presented with graphs and
tables.
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Result And Discussion
4.3.a Neurocognitive Index
Graph and Table no 31: Neurocognitive Index Impairment after Heading
Neurocognitive Index is an average or means score derived from the domain score or
a general assessment of the overall neurocognitive status of the subject. It was observed
that after 10 minutes and 15 minutes heading there is no such changes but after 20
minutes of continuous heading the mean score deteriorate. After 25 minutes of
continuous heading the means scores of neurocognitive index significantly (at 0.05
levels) deteriorated from the initial resting score (Graph & Table no: 31).
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Result And Discussion
4.3.b Composite Memory
Graph and Table no 32: Composite Memory Impairment after Heading
The composite memory is the ability to recognize remember and retrieves words and
geometric figures. It identifies problems with the storage, manipulation and retrieval
information. Composite memory score was decreased slightly after 10 minutes and 15
minutes of heading but after 20 minutes of continuous heading it decreased sharply.
However after 25 minutes of heading the composite memory score was decreased
significantly from the pre- test score (Graph & Table no: 32).
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Result And Discussion
4.3.c Verbal Memory
Graph and Table no 33: Verbal Memory Impairment after Heading
Verbal memory is the ability to recognized, remember and retrieved words that is
exploit or attained literal representation or attributes. In verbal memory after 10 minutes,
20 minutes and 25 minutes of continuous heading the mean scores decreased
significantly from the initial level. However the 15 minutes group also decreased but the
mean difference was not significant (Graph & Table no: 33).
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Result And Discussion
4.3.d Visual Memory
Graph and Table no 34: Visual Memory Impairment after Heading
The visual memory is the ability to recognize, remember and retrieve a geometric
figure that is exploiting or attain symbolic or spatial representation. After 10 and 15
minutes of continuous heading visual memory decreased. But after 20 minutes and 25
minutes of continuous heading the mean visual memory score was decreased
significantly (Graph & Table no: 34).
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Result And Discussion
4.3.e Processing Speed
Graph and Table no 35: Processing Speed Impairment after Heading
Processing speed is how well a subject can automatically and fluently perform
relatively lazy or over learned cognitive tasks, especially when high mental efficiency is
required that is attention and focused concentration. After 10 minutes and 15 minutes of
heading there was no such changes in processing speed but after 20 minutes of
continuous heading processing speed decreased abruptly and after 25 minutes of heading
the processing speed decreased significantly from the pre-test score (Graph & Table no:
35)
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Result And Discussion
4.3.f Executive Function
Graph and Table no 36: Executive Function Impairment after Heading
The executive function is how well a subject recognizes set shifting (Mental
flexibility) and obstruction (rules & categories) and manages multiple tasks
simultaneously. After 10 minutes, 20 minutes and 25 minutes of continuous heading, the
executive function decreased significantly from the initial value however slight changes
was observed in the 15 minutes heading group (Graph & Table no-36).
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Result And Discussion
4.3.g Psychomotor Speed
Graph and Table no 37: Psychomotor Speed Impairment after Heading
The psychomotor speed is how well a subject recognizes and process information
that is perceiving, attending / responding to incoming information, motor speed, fine
motor coordination and visual perceptual ability. After 10 and 15 minutes of heading the
mean score of psychomotor speed was decreased. But after 20 and 25 minutes of heading
the psychomotor speed deteriorated significantly (Graph & Table no: 37).
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Result And Discussion
4.3.h Reaction Time
Graph and Table no 38: Reaction Time Impairment after Heading
The reaction time is how fast the subject can react to a simple and increasingly
complex direction set. In reaction time lower score means better performance. It was
observed that, after 10 minutes of heading the mean score of reaction time was higher
than the pre-test value. But after 15, 20 and 25 minutes of continuous heading the
reaction time score were significantly higher than the pre-test value. In reaction time low
score is better. It means reaction time performances deteriorate after continuous heading
(Graph & Table no: 38).
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Result And Discussion
4.3.i Complex Attention
Graph and Table no 39: Complex Attention Impairment after Heading
Complex attention is the ability to maintain focus and performance quickly and
accurately that is problem attending to multiple stimuli at the same time like reaction
time low scoring in complex attention means better performance. It was observed that
after 10 minutes, 15 minutes and 25 minutes of heading complex attention score
increased and in 20 minutes group it was increased significantly. In complex attention is
low score is better, which means complex attention deteriorates after continuous heading
(Graph & Table no: 39).
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Result And Discussion
4.3.j Cognitive Flexibility
Graph and Table no 40: Cognitive Flexibility Impairment after Heading
Cognitive flexibility is how well subject is able to adapt to rapidly changing and
increasingly complex set of directions and / or to manipulate the information. It was
observed that, after 15 minutes of heading cognitive flexibility was decrease but
after
10,20 and 25 minutes of continuous heading the cognitive flexibility was significantly
decreased from the pre-test value(Graph & Table no: 40).
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Result And Discussion
4.3.k Social Acuity
Graph and Table no 41: Social Acuity Impairment after Heading
Social acuity is the ability and inclination to perceive the psychological state of
others and act accordingly. All the heading groups (10, 15, 20, 25 minutes) mean score of
social acuity was decreased. But the mean difference of all the groups was not
significant. However the trends are clear after continuous heading social acuity quality
was decreased (Graph & Table no: 41).
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Result And Discussion
4.3.l Reasoning
Graph and Table no 42: Reasoning Impairment after Heading
Reasoning is the processes of thinking about something in a logical way in order to
form a conclusion or judgment. It was observed that after 15 minutes of heading the
mean reasoning score was decreased however after 10, 20 and 25 minutes of continuous
heading the mean reasoning score decreased significantly (at 0.05 levels) from the pretest value(Graph & Table no: 42).
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Result And Discussion
4.3.m Working Memory
Graph and Table no 43: Working Memory Impairment after Heading
Working memory refers to brain system that provides temporary storage and
manipulation of the information necessary for such complex cognitive tasks as language
comprehension, learning and reasoning. After 10, 15, 20 and 25 minutes of continuous
heading the working memory reduced. However after 15 and 25 minutes groups,
observed significant deterioration of working memory from the resting level (Graph &
Table no: 43).
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Result And Discussion
4.3.n Sustained Attention
Graph and Table no 44: Sustained Attention Impairment after Heading
The sustained attention is the ability to direct and focus cognitive activity on specific
stimuli. In order to complete any cognitively plane activity, any sequenced action or any
thought are must use sustained attention. It was observed that after 10, 15, 20 and 25
minutes of continuous heading practice the sustained attention scored was significantly
decreased in all the groups(Graph & Table no: 44).
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Result And Discussion
4.3.o Simple Attention
Graph and Table no 45: Simple Attention Impairment after Heading
Simple attention is the ability or power to keep the mind on something; the ability to
concentrate. After 10 and 15 minutes of heading the simple attention scored decreased.
But after 20 and 25 minutes of continuous heading the simple attention scored was
decreased significantly (Graph & Table no: 45).
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Result And Discussion
4.3.p Motor Speed
Graph and Table no 46: Motor Speed Impairment after Heading
Motor speed is relating to nerves or neurons that carry impulses which causes
muscles to contract. The motor cortex, motor nerve and motor end plate are directly
involve in the process of motor speed. It was observed that, after 10, 20 and 25 minutes
of continuous heading, the mean score of motor speed was decreased. But in the case of
25 minutes heading it was decrease significantly (at 0.05 levels). However, no such
changes were observed in the 15 minutes heading group.(Graph & Table no: 46).
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Result And Discussion
4.4 Discussion
Football is currently the most popular and fastest growing sports worldwide.
Due to the nature of the sport, soccer players are particularly vulnerable to various
types of head and neck injuries, including laceration, abrasions, contusion, fractures
and concussions (Mild traumatic brain injury). Most of the time, these types of
injuries occur as a result of unintentional or unexpected contact, for example, when a
player collide with teammates, opponents or the playing surface. The sport is also
unique in its purposeful use of the head – referred to as ‘heading’ – a technique to
advance or control the ball during game play (Maher et al., 2014).
There is significant concern about the potential long term cognitive and
behavioral consequences for athlete with respect to acute concussion, repetitive
concussion as well as cumulative sub-concussive head impacts, which are blow not
causing symptoms of concussion. While it is known that concussive injuries
frequently result in a clinical constellation of symptoms, the practice of heading –
which might occur thousands of times over a players carrier – carries unknown risk;
but heading may uniquely contribute to cognitive decline or impairment in short or
long term. Increased understanding and concern for concussion in all sport has
resulted in the recent implementation of a number of strategies to help or address the
issue of concussions in sports. Such initiatives have included; education of players,
coaches, athletic therapist, trainers and parents; development of standardized
assessment tool; consensus statement to provide guidelines for management and
legislation. In addition, a number of sport organizations have implemented specific
rules and policies – the National Hockey League, National Football League, Hockey
Canada and Soccer Shots. Connecticut – aim to reduce the number of head injury in
their respective sports. Despite these actions there are still a number of outstanding
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Result And Discussion
questions that have the potential to influence future prevention strategies. In
particular for football (soccer), and understanding of the incidents and mechanism of
injury, the identification of risk factors and insight into neurocognitive outcomes
could provide evidence for recommendations specific to possible rule changes
inform equipment manufacturers and contributing to management guidelines all
level of play (Maher et al., 2014).
Incidents of concussion in soccer; some study investigated the incident rate in
terms of Athletic Exposure (AE), where AE is consider a single practice for game.
An Epidemiological study of injuries in National Collegiate Association (NCAA)
man’s soccer over a fifteen years period was conducted using data collected by the
NCAA injury surveillance system and this study reported the incidents of concussion
in terms of male player to be 1.08 concussions per 1000 AE (Agal et al., 2007).
Further analysis by this roof of the NCAA, ISS man’s data showed that concussion
accounted of 5.8% of total injuries sustained during games, with player being 13
times of more like to receive a concussion during a game than practice. Concussion
frequency by either sex indicated that males had a higher incident and it was also
determined that the overall incident in soccer was 0.9 per team per session and that
69% of concussion occurred during game (Boden et al., 1998).
Most of studies identified player-to-player contact as the mechanism
responsible for the greatest proportion of concussion in both male and female soccer
athlete. Anderson et al. (2004) examined 192 head injury incidence involving playerto-player contact and found that 41% concussion resulted from contact by an elbow,
armor hand to the head. With respect to the playing situation, 58.3% head injuries
were sustained while the player was engaged in a heading dual. Marar et al., (2012)
reported concussion accounted for 60% of all injuries sustained while heading the
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ball, while another study reported that percentage was 64.1% (Gessel et al., 2007). In
two of these studies, concussion mechanism was differentiated by sex and while
player-to-player contact was the leading cause of concussion in both males and
females, a greater proportion of females sustained concussions from player to surface
and player to ball contact compared to male players. In contrast, males sustained a
greater proportion of concussion from player to player contact then females. It was
suggested that sex differences in style of play and more aggressive play in males
might account for this disparity.
Boden et al., (1998) highlighted that concussion more often were a result of
being struck in the head by balls kick at close range, as opposed to the playing action
of heading the ball. These results are supported by a biomechanical study by Henlon
and Bir (2012) which showed that non heading impacts from the ball resulted in
greater head acceleration and subsequent head injury compared to impacts received
from heading. Player to player surface injuries included players who fall and struck
their head on the playing surface – which included the ground or the goal post. Other
mechanisms included collision with objects around the field of play such as fences,
benches or bleachers (Barness et al., 1998; Giannotti et al., 2010; Delaney et al.,
2006; Cusimano et al., 2013).
Players position appears to be an important factor in considering potential
risk factors associated with concussion while playing soccer. Especially defense man
and goal keeper are the greatest risk, sustaining more concussive injuries than
forwards and midfielders. Delaney et al., (2002) conducted a study using medical
history questionnaires completed 201 soccer players competing in the 1998 Canadian
Inter University Athletics Union Seasons. They reported that 70.2% of defenders and
78.9% of goal keepers had sustained a concussive head injury during the previous
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seasons. In a study assessing injuries sustained by both collegiate and high school
athletes, it was determined that 21.7% of all injuries sustained by soccer goal keepers
were concussions, while they represented only 11.1% of total injuries to soccer
players in other positions (Gessel et al., 2003).
Some studies have employed neuropsychological screening batteries to assess
soccer player cognitive functioning and found that soccer players exhibit significant
cognitive deficits following concussion (Ellemberg et al., 2007; Colvin et al., 2009).
Using the ImPACT computer based testing battery (Colvin et al., 2009) found
concuss soccer player of 9 days post injury displayed significant impairments in
memory, reaction time and visual processing speed and impairments were more
pronounced for females. Conversely, Zuckerman et al. (2012) used the ImPACT test
battery at base line and within 10 days of injury and reported no statistically
significant differences from base line scores. Ellemberg et al., (2007) examined 22
female university level soccer players at 6-8 months following their first medically
diagnosed concussion. The author reported chronic phase (months after the injury)
impairments – specifically, concussed players exhibited significantly, poorer
executive functions compared with controls for test of inhibition, playing and
decision making. Guskiewiez et al., (2002) examined soccer players pre-season
neurocognitive performance scores and reported no significant differences in
performance between (a) player’s with and without a history of concussion or (b)
between soccer player and non-athlete populations.
4.4.1 Effects of Heading
Many studies were investigating the short term effects of heading on
neurocognitive performance. Kontos et al., (2011) examined a group of youth soccer
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players and recorded the number of heads, each player executed during two
randomly selected games. However they did not find any differences between low,
moderate and high heading players and ImPACT scores. Similarly, Janda et al.,
(2002) observed youth soccer players and found no significance differences in
players pre and post season cognitive testing scores. The authors concluded that
there was no cumulative effect of heading on neurocognitive performance. Putukian
et al., (2000) also investigated the acute effects of heading by conducting testing
before and after two collegiate soccer practices – with the soccer players surviving as
their own controls and found that there were no significant differences between
baseline and post heading test scores. Webbe and Ochs (2003) conducted a study of
64 male score players competing in high school college or profession soccer, it was
found that frequency of ball heading and how recently they had participated in
heading exercises interacted and caused deficits in attention and visuo-spatial
capacity, suggesting that perhaps some transient cognitive problem may result from
heading. Stephens et al., (2005) evaluated male soccer players aged 13-16 on thirteen
neuropsychological test and recorded heading frequency during 1-3 games in a
preliminary study and found that heading frequency did not significantly predict
testing performance. A second identical study by this group found that there were
differences between the groups (Kaminski et al., 2008; Stephens et al., 2010;
evaluated 393 female high school soccer players pre and post season using the
Automated Neuropsychological Assessment Metric and had a designated individual
from each team record the number of heading each player perform in each game.
They did not find any significant correlation between test performance and the
number of heading executed.
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Many studies examining long term effects of heading, head impacts and / or
exposure to soccer. Included samples of elite collegiate and / or professional level
soccer players which represent population of athlete with longer and more intensive
carriers and subsequently greater heading exposure than younger athletes. Matser et
al., (1998) looked at Dutch professional players and found greater memory, planning
and perceptual deficits in forwards and defenders, players deemed to execute more
headers in a season. Matser et al., (1999) also squad a group of amateur soccer
players to determine whether deficits were evident in this population in addition to
professional players. The authors reported amateur soccer player were significantly
impaired in attention and memory. It was also determined that the lifetime exposure
to heading was related to cognitive deficit were in the professional players reporting
the highest prevailing of heading over the course of their carrier were most adversely
affected in test of verbal and visual memory as well as attention (Matser., 2001).
Downs and Abwender (2002) evaluated the long term cognitive effect of repetitive,
sub concussive contact as a result of heading. In their study cognitive testing
performance of current collegiate, professional, older professional or retired soccer
players were compared to healthy controls. The control consist of swimmers those
who have similar physical abilities and training schedules but without the risk of
head injury. They observe swimmers perform better than soccer player in test of
conceptual thinking, while it was demonstrated that older or retired soccer players
were significantly impair in conceptual thinking, reaction time and concentration
compared with all other groups, including the current younger soccer players.
Tysvaer and Lochen (1991) examined neuropsychological performance of retire
soccer players and found that they displayed significantly poorer verbal and
performance IQ and were impaired on the trail making test part A and part B as
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compared to the control group. Rutherford et al., (2005, 2009) sound significant
differences between soccer players and controls in divided attention and that the
number of head injuries sustained interacted significantly with heading frequency to
predict scores on alertness, working memory and language.
Straume-Naesheim et al., (2005) reported no significant interaction of both
self-reported heading exposure and previous concussions with neuropsychological
testing performance; however their scores were not compared with any control
group. Similarly Kaminski et al., (2007) found no significant differences in terms of
cognitive performance between female collegiate and high school soccer players and
non-playing collegiate controls.
Some studies investigated the presence of bio-chemical markers of brain
injury within the blood and / or cerebrospinal fluid of soccer players after
participation in heading exercises (Mussack et al., 2003; Stalnacke et al., 2004;
Stalnacke et al., 2006; Zetterberg et al., 2007; Stalnacke et al., 2008). The most
frequently investigated biomarker of the studies reviewed includes S-100B and
neurocon-specific-enolase (NSE) of these five papers, they indicated elevated levels
of S-100B after either soccer games where heading and / or head impacts occurred or
after a heading session. Specifically Stalnacke et al., (2006, 2008) found that S-100B
elevations co-related significantly with both the number of headers a player
performed and the number of head trauma events (including collisions and falls) that
a player experienced. These results were evident in both female and male soccer
players with respect to NES none of the studied indicated that NES increased in
response to heading exercise or head trauma.
Some studies have applied advanced neuroimaging techniques to examine the
effects of heading in soccer players. Adams et al., (2007) had a sample (N=10) of
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active male inter-collegiate soccer players complete a magnetic resonance imaging
(MRI) scan to determine whether head impacts during soccer play resulted in
structural brain changes. It was reported that compared with non-playing controls,
the ten (10) soccer playing participants had significantly decrease gray matter
density bi-laterally across the anterior-temporal cortex attributed to repeated subclinical injury. These college level player reported heading the ball anywhere from
2-20 times per game, in addition to the headers executed during training session,
suggesting that the minor head impacts from heading that are inherent to soccer play
can result in structural damage. However Jordon et al., (1996) did not found any
significant MRI finding in members of the US men’s national soccer team.
Sortland and Tysvaer (1989) used Computed Tomography (CT) to evaluate
the brain of former members of Norway’s National Team and found that of the 33
players recruited, 9 had significantly enlarge ventricles and 11 had significant
cortical atrophy and 3 had significant cerebellar atrophy compared with normative
measurements. In a recent original research by Koerte et al., (2012), elite male
soccer player in Germany without a history of concussion were evaluated using
Diffusion Tensor Imaging (DTI) with a group of age, handedness a sex matched
swimmers. They found significantly increase radial and axial diffusivity in soccer
players, indicating myelin pathology and decreased white matter integrity.
Tysvaer et al., (1989) conducted a neurophysiological study by using
electroencephalography (EEG) with former national team player in Norway to
quantify long term abnormality due to heading. They found that 12 of the 37 players
displayed slightly abnormal to EEG results. Tysvaer and Storli (1989) conducted a
similar study on 69 active players competing within the Norwegian first division
league and 69 age matched control, 38 players reported acute symptoms of
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Result And Discussion
concussion in relation to heading. Their result showed that 65% age of the current
players had normal EEG results compared with 87% of controls.
In the present study the researcher collected data on neuropsychology before
and after continuous heading. It was observed that after continuous 20 minutes of
heading, all the neuropsychological parameters started reflecting poorer score and
after 25 minutes of continuous heading all the parameter significantly decreased. In
the above discussion the present researcher reported with any supporting documents
and scientific mechanisms which may further strengthen the present research report.
However, there were many limitations of the study and methodological boundary;
the present research work uniquely identified the threshold level of starting brain
function impairment after continuous heading practice.
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