Dissertation HS4101 1004740

Faculty of Health and Social Care
School of Health Science
BSc (Hons) Applied Sport and Exercise Science
May 2014
‘‘Investigation into the Influence of Fluid Restriction on Cognition
and Mood in University Level Basketball Players’’
By Amy Street (1004740)
Supervisor: Dr. Eimear Dolan

BSc (Hons) Applied Sport and Exercise Science
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Module number: HS4101
Module title: Research Project
Module leader: Dr Paul Swinton
Date of hand-in: 16/05/2014
Student number: 1004740
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HS4101 Research Project MatriculationNo:1004740
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Contents:
Pg No.
1. Acknowledgements
2. Abstract
3. Introduction
4. Literature Review
4a. Sweat Loss in Basketball and Intermittent Sport
4b. Basketball Specific Studies
4c. Sport Specific Studies
4d. Summary
5. Aims and Objectives
6. Hypothesis
7. Methods
7a. Study Design
7b. Population Sample
7c. Profile of Mood States Questionnaire (POMS)
7d. Ruler Drop Test
7e. Symbol Digit Modalities Test (SDMT)
7f. Test Procedures
8. Data Analysis
9. Results
9a. Physiological Data
9b. Reaction Time
9c. Symbol Digit Modalities Test
9d. Profile of Mood States Questionnaire
5
6
6-7
7-13
13-14
14
14-19
19
19-23

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10. Discussion
10a. Physiological Findings
10b. Cognition Findings
10c. Mood Findings
10d. Strengths of Study
10e. Limitations
10f. Practice and Future Implications
11. Conclusion
12. References
13. Appendices
24-32
32
33-44
45-70

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1. Acknowledgments
I would like to take this opportunity to first and foremost say a huge
thank you to my wonderful tutor Dr Eimear Dolan, for all her support,
guidance and encouragement throughout this project. She has been such
a role model.
Thank you to the basketball coach Donnie, for permitting me to
experiment on the basketball team, and to all the players who
participated.
Thank you so much to all the lecturers who have also supported me
throughout this final year.
I would also like to thank Craig Thain, for his constant motivation and for
being by my side throughout. He has been my rock.
Finally, thank you to all my friends and family, who have been so
supportive. I would also like to apologise to those who were appointed the
unfortunate job of proof reader.

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2. Abstract
This study examined the effects of fluid provision and restriction in a
simulated basketball game on cognitive function and mood. 5 members
(Male=4, Female=1) were recruited from the university basketball team.
Method: Participants took part dehydrated or hydrated during the initial session
and exposed to the opposite state in the second session. Subjective feelings
were measured pre and post-game and the cognitive functions of attentional
vigilance, visual scanning, working memory and reaction time were immediately
measured post-game in both fluid states. Results: Participants displayed a mean
body mass loss of 0.74±0.19% in the fluid restriction state and 0.00±0.25%in
the fluid provision state (P=0.01). Improvement in post-reaction time result was
identified in the fluid restricted state (P < 0.01), however results displayed
potential learning effect (P= 0.01). Fluid restriction was associated with
significant increase in subjective feelings of confusion after comparison of pre to
post game mood change between fluid states (P=0.03). Conclusion: Mild
dehydration of <1% after a 40 minute basketball game has been shown to
increase perceived confusion, however further research is required to develop a
more conclusive finding.
3. Introduction
It is evident according to literature that cognition and mood status are vital
determinants of performance within the majority of intermittent sports (Araujo
et al., 2006; Eysenck et al., 2007; Martin & Thomson 2011; Prapavessis 2000;
Totterdell 2000; Voss et al., 2010). Attention, visual search, working memory
and reaction time are some of the principal cognitive functions incorporated
within most intermittent sports alongside all aspects of mood (Burke 2007;
Moran, 2009; Moran, 2012; Abernethy et al, 2007). However, understanding of
the impact of fluid intake on these parameters for performance purposes is
limited regardless of the fact that sufficient fluid replacement is essential for
optimal metabolic, cardiovascular and thermoregulatory function during exercise
(Popkin, D’Anci & Rosenberg 2010; Buyckx 2007).
In highly severe cases (9% to 12% total weight loss), dehydration can
cause extreme deterioration in cognitive function and can lead to death

7
(Wilmore, Costill & Kenney 2007; Maughan & Murray 2001). With this in mind, it
can be theorized that naturally, mild and moderate dehydration will also be
associated with negative impacts on mood and cognitive function with regards to
sports performance. However, there is very little conclusive evidence of the
relationship between degree of dehydration and its effects on governing
cognitive functions and mood in sport (Armstrong et al. 2012; Burke, 2007;
Sawka 2004). Dehydration within Basketball in particular is a prime concern due
to heightened player susceptibility to dehydration, because of their physical
stature and the intense demands of the sport (Osterberg, Horswill and Baker
2009). However there is currently no evident literature assessing the effects of a
basketball specific inducement of dehydration on cognition and mood in players.
4. Literature Review
4a. Sweat Loss in Basketball and Intermittent sport
Basketball involves bursts of high-intensity activity incorporating power
and speed with intermittent rest periods, as well as cognitive functions such as
reaction time and decision making (Sharkey & Gaskill 2006). Exercise such as
this can be associated with heavy sweat losses (Burke and Hawley 1997). A
study by Osterberg, Horswill and Baker (2009) assessing fluid intake and urine
specific gravity of National Basketball Association players found that within the
first 20 minutes of game time, over 2 litres of sweat was lost for each player,
resulting in substantial losses by the end of the game. They state that basketball
players in particular are more susceptible to dehydration within their sport due
to their tendency to have taller and larger frames, increasing their fluid
requirement due to high sweat production (Osterberg, Horswill & Baker 2009).
This is supported by a study that found significant correlation between sweat
rate and body surface area, highlighting that the greater the skin surface area,
the greater the amount of sweat produced (Godek et al. 2006). It can be
proposed that basketball inflicts high physiological demand, resulting in
proportionally high levels of sweat loss in players (Dougherty et al. 2006). A
study by Casa et al. (2000) monitoring NBA players during a game found that
only 40% of sweat losses were replaced, resulting in 1-3% DEH (dehydration).

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This is reasoned by Burke (2007), stating that basketball players are more
susceptible to dehydration because team talks are the prime focus during pre-
game, half-time and post-game, overshadowing the importance of hydration and
opportunity to drink. Without sufficient awareness of fluid intake specific to an
individual’s sport, there is high probability of the onset of dehydration: a state of
excessive water loss within the body that has not been equally replaced
(Dougherty et al. 2006).
4b. Basketball Specific Studies
Regardless of the fact that basketball induces high sweat losses,
increasing risk of dehydration, current literature exploring the effects of
dehydration on primary determinants of performance within basketball is limited
and generally not valid within context of the sport.
A study by Baker, Conroy & Kenney (2007), analysed vigilance-related
attention in 11 male basketball players after 3 hours interval walking (50%
VO2max) on a treadmill in 40˚C heat, followed by a simulated basketball game
during euhydrated and dehydrated (1-4%) states. The study found vigilance-
related attention was impaired by dehydration. Another study by Dougherty et
al. (2006) determining the effect of heat (40°C) and exercise (50% VO2max)
induced dehydration on basketball skills in 15 year old males found significant
decreases in skill performance after 2% DEH. Both studies concluded that
basketball players were advised to remain euhydrated during game play to
maintain optimal performance.
Through evaluation of both studies it could be seen that inducement of
both hyperthermia and sweat production through exercise restricts analysis of
the effects of exercise induced dehydration alone. This is supported by studies
that have identified significant differences in cognitive outcome between induced
hyperthermia and dehydration associated with exercise (Cian et al. 2000;
Gonzalez-Alonso et al. 1997). Evidence suggests that exercise in the heat can
cause greater interference with brain neurotransmission, due to reduction in
cerebral blood flow, compared to exercise within neutral environments which can
increase cerebral blood flow (Ide & Secher, 2000; Nybo & Neilsen, 2001). It can
be suggested that disrupted brain neurotransmission can lead to increases in
dopamine levels; a key neurotransmitter responsible for fatigue (Maughan,

9
Shirreffs & Watson 2007). Consequentially, it can be appreciated that exposure
to both hyperthermia and exercise induced dehydration may produce results that
do not reflect exercise dehydration alone, highlighting that study specificity with
regards to basketball may be limited.
A similar study by Baker et al. (2007) assessing basketball skill
performance in 15 skilled male basketball players after 15 minute bouts of
exercise in heat for 2 hours at 50% VO2max, found skill was impaired at 2%
DEH. The study concluded that players were advised to prevent ≥2% DEH
before and during the game to maximise performance. As well as heat, exercise
duration, intensity and type was not specific to that of a basketball game,
whereby the induced dehydration method may not typically reflect induced levels
within an actual game setting. For example, intensity of exercise is an important
determinant of cognitive function according to Easterbrook’s (1959) cue
utilization theory of arousal, whereby moderate exercise could improve cognitive
performance and high intensity could impair performance. All the mentioned
studies induced exercise intensity to 50% VO2max, which is classified as
moderate intensity (<70% VO2max) according to Brisswalter, Collardeau & Rene
(2002). Montgomery, Pyne & Minehan (2010), found that the average VO2max
within a basketball game is approximately 85% (High intensity). Therefore it can
be seen that the results of these studies may have potentially displayed an
inaccurate interpretation of results when compared to that achieved through
dehydration inducement within a basketball game.
Additionally, the location of induced dehydration can influence degree of
sweat loss according to Osterberg (2009), whereby basketball is usually played
within dry environments seen within sports halls or arenas, increasing sweat
evaporation. It can therefore be seen that amount of sweat loss within a
laboratory setting may not replicate the same amount lost within a game
situation, further highlighting the need for a sports specific study. Evidentially,
although the studies displayed detriments in cognitive and mood performance
and skill during approximately a 2% DEH state, they may not provide a valid
interpretation of specific dehydration effects in context to specific demands and
nature of a basketball game.

10
With such limited amount of studies referring to basketball, further
exploration of sport specific literature is required to develop a greater
understanding of the potential effects of dehydration on cognition and mood.
4c. Sport Specific Studies
Studies have established specific boundaries to determine dehydration
state of an individual, whereby 1 to 2% body weight loss is classed as mild, 2 to
5% is moderate and >5% is severe (Burke 2007; Maughan 1991; Tomporowski
2007). There is varied research assessing the effects of dehydration on cognition
and mood in relatively neutral temperatures. However it is evident that the
majority studies that have assessed dehydration have identified that an
inducement of >2% DEH solely through fluid restriction is usually associated
with detrimental effects on cognition and mood (Grandjean & Grandjean 2006;
Szinnai et al. 2005; Wilson & Morley 2003). This can be understood because
physiologically just 2% fluid loss of body weight reduces blood plasma volume,
which in turn decreases blood pressure and stroke volume, thus blood flow to
the muscles and skin (Wilmore, Costill & Kenney 2007). It can be appreciated
that these physiological changes will consequently reduce blood flow to the
skin’s surface, restricting dissipation of heat. Heart rate is increased in direct
proportion to decreases in stroke volume, which has a linear relationship with
rate of perceived exertion (Borg 1982). This could suggest that inducement of
2% dehydration could negatively impact perceived exertion, inducing mood
states such as fatigue, anxiety and tension which may decrease exercise
performance (Szinnai et al. 2005). However it can be questioned as to whether
exercise induced dehydration will have similar effects on cognition and mood due
to the fact that exercise has been shown to immediately enhance cognition and
mood (Lichtman & Poser, 1983; Tomporowski2003), which may outweigh the
impacts of mild dehydration.
The majority of studies using exercise have exacerbated dehydration with
the use of environmental conditions such as heat and humidity which have
displayed performance decrements in mood and cognition (Cian et al. 2001;
Gopinathan, Pichan & Sharma 1998; Maughan, Shirreffs & Watson 2007;
Sharma et al. 1986). However, as previously mentioned, by inducing
hyperthermia whilst exercising, the effects of solely dehydration cannot be

11
examined accurately, initiating a broader argument during analysis of results
and reducing study specificity (Ganio et al. 2011; Lieberman 2007). It can
therefore be questioned as to what extent solely exercise induced dehydration
affects brain function and mood, whereby currently relevant literature is limited.
A study by D’Anci et al. (2009) involved thirty one male college athletes
from both the rowing team and lacrosse team. The rowers engaged in a 60
minute high intensity rowing session, whilst the lacrosse team partook in 75
minutes of lacrosse specific drills, whilst either randomly dehydrated or
euhydrated. A series of cognitive tests including vigilance attention, visual
working memory, reaction time, visual perception and mathematical addition, as
well as a thirst and mood questionnaire were then completed. The study found
that reaction time was decremented and anger, depression and tension were
significantly ranked more negatively after a >2% decrease in body weight.
However visual working memory and search performance were enhanced within
the dehydrated session. Yet it was identified that these enhanced results
displayed potential learning effect between sessions, decreasing reliability and
validity of values. The positive results of visual working memory may be
explained by this learning effect or due to the fact that dehydration can elevate
cerebral arginine vasopressin, a hormone that has been shown to enhance
memory (Wilson & Morley, 2003). With regards to study validity, it is evident
that the induced dehydration would reflect the amounts achieved within the
sports, due to the fact that it incorporated sport specific exercise, thus making
results applicable for rowing and lacrosse. However, because the study
incorporated two different sports, the degree and duration of inducement of
dehydration between the exercises will be different. This may lead to increased
exposure to varied confounding variables that could influence cognitive
performance and mood independently of dehydration (Easterbrook 1959).
Specificity of results are therefore reduced, as physiologically, with relation to
Easterbrook’s (1959) cue utilization theory for example, rowing and lacrosse
impose extremely different demands upon the body inducing different exercise
intensities and therefore degrees of arousal.
Alternatively a study by Ganio et al. (2011) that initiated exercise induced
mild dehydration (>2%) during three sets of 40 minutes walking on a treadmill
(5.6km/h, 5% incline) with 26 male participants, found visual vigilance and

12
visual working-memory were impaired in the dehydrated state compared to an
euhydrated state. Fatigue and tension were also rated more negatively. There
are potential benefits of testing within a laboratory setting, as seen within this
study, as confounding variables such as weather and environmental temperature
can be controlled to a greater extent than that of field based tests, increasing
study reliability. However the practicality of the results for future implications
can be questioned due to the fact that participants were also required to
consume a diuretic to enhance dehydration, preventing precise identification of
the effects of solely exercise induced dehydration (Armstrong, Costill & Fink,
1985).
Such conflicting evidence between the studies could be due to said
limitations of studies and the differing physiological demands of exercise, which
could expose separate confounding variables that may influence results
(Collardeau & Rene 2002). A potential explanation could be due to degree of
stimulation achieved during exercise, whereby the type of exercise may
determine participant arousal and susceptibility to dehydration effects. The
natural movement of walking may not be as mentally stimulating as sport
developed movements of cycling or rowing. This is supported by a study by
Lambourne & Tomporowski(2010) comparing the degree of arousal in cycling
and running and identified that cycling produced a greater arousal and
evidentially improved cognitive functions including reaction time and attentional
vigilance, however running on a treadmill reduced cognitive performance.
Theoretically, inducement of dehydration within an environment that lacks
stimulation could increase a participant’s awareness of becoming dehydrated and
resultantly could cause a potential placebo effect that may negatively impact
cognition and mood. Supporting this theory, Aarts, Dijksterhuis & Vries (2001)
suggest that to a certain extent mental stimulation could provide distraction to
negative associations of dehydration such as thirst and headaches. Furthermore,
fatigue was not affected by dehydration within the study by D’Anci et al. (2009),
however was negatively affected in the study by Ganio et al. (2011), suggesting
that rowing potentially may have induced greater arousal compared to walking,
counteracting sensation of fatigue.

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4d. Summary
According to Karslo (2011) with many studies it can be difficult to isolate
certain variables that affect physiology, which may lead to conclusions in
research that are lacking in strength. It is evident that the available studies
relevant to basketball do not provide an accurate sports specific interpretation of
dehydration and its effects on cognition and mood, primarily due to exacerbation
of exercise induced dehydration through hyperthermia. Although they provide
insight to the potential negative impacts of >2% dehydration on cognition and
mood, the lack of sport specific literature, with regards to a dehydration
susceptible sport such as basketball, emphasises the requirement for this study.
With regards to conflicting results of current studies mentioned, it could
be seen that the effects of mild dehydration may partially be influenced by the
type of sport and degree of arousal. The fast paced, varying nature of basketball
could potentially increase degree of arousal that may display decreases in
fatigue and improved working memory. However, with consideration of degree
of dehydration ranging from 1-3% in basketball players (Casa et al. 2000) and
relatively high intensity of the game (Montgomery, Pyne & Minehan 2010),
cognitive performance and mood are likely to differ from results of the
mentioned studies.
5. Aims and Objectives
Aim
To determine the effects of basketball specific exercise induced
dehydration on cognitive function and mood within university level basketball
players.
Objectives
1) Achieve sports specific level of %DEH through exercise and fluid
restriction during a basketball game
2) To assess the differences in cognitive function between hydrated and fluid
restricted test sessions through the completion of a ruler drop test and a

14
symbol digit modalities test to assess reaction time, visual scanning,
attention and motor speed between hydration and dehydration groups.
3) To compare participants’ change in perceived mood between hydration
and fluid restricted sessions using a self-reported profile of mood state
questionnaire.
6. Hypothesis
It can be hypothesised that a basketball induced dehydration of >2%
will be achieved during fluid restriction, whereby the measured aspects of
cognition and mood will be significantly decremented.
7. Methods
7a. Study design
The study was an experimental singular repeated measures cross over
design providing primarily quantitative results, whereby sessions were carried
out over two days with one week rest between each session. Procedures and
subject participation for each session remained the same, whilst variable
(Hydration level) was altered to assess data correlation between sessions. By
replicating test structure, test retest reliability is subsequently increased by
reducing exposure to external data-influencing variables (Piepho, Büchse &
Richter, 2004). With this in mind participants were allocated equally into either a
1) Hydration or 2) dehydration group on the initial testing session and exposed
to the opposite variable during the second test session, thus reducing the
confounding influence of individual variability. The implemented procedures
provided numerical data; the profile of mood states questionnaire, ruler drop
test, symbol digit modalities test, urine osmolality test and %DEH via weight
measurement. By incorporating a quantitative design results provide numerical
data which generally allows factual, non-biased results and therefore opportunity
for a proficient, accurate analysis of findings (Hopkins 2000).

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7b. Population Sample
9 university level regular basketball players (6 males, 3 females, age 19 to
25) were recruited to take part in the study. Initially participants were provided
information of all the test procedures and the requirements of the study
(Appendix 1-2). An informed consent form was completed to agree to
participation within the test (Appendix 4) and participants were then screened
prior to testing to ensure compatibility for participation in the study through
completion of a participant questionnaire (Appendix 3). Exclusion criteria
included significant health concerns or injuries that may influence test results or
pose a risk to health whilst partaking within the study. One week later
participants attended a familiarization session, whereby tests were demonstrated
and participants were allowed to complete each test once. This familiarization
session ensured participants fully understood each test procedure and its
requirements for test repeatability. It ensured reduced risk of participant error
during the official testing sessions that could otherwise affect result validity and
reliability (Altmann 2002). Each test during familiarisation was only completed
once to prevent the risk of learning effect that may occur through task repetition
which could influence results (Mosheiov 2001). Ethical approval for testing was
sought and achieved and permission to use the basketball team was granted
through RGU Sport and the basketball coach (Appendix 5-7).
7c. Profile of Mood States Questionnaire
The Profile of Mood States (POMS) (McNair, Lorr & Droppleman 1971) is a
self-examined rating system, whereby participants marked on a scale of 0-4 (0-
not at all, 4-extremely) how they were currently feeling in relation to the
provided emotions (Appendix 10). Participants were seated in a quiet
environment and there was no time limit for test completion. To ensure validity,
this test was completed immediately pre and post-game to identify overall
change in mood state induced by the game, preventing influence of external
confounding mood states that may be present regardless of hydration status. By
referring to guidelines (Mackenzie 2001) scoring of their overall degree of anger,
anxiety, depression, confusion, fatigue and vigor could be achieved. Pre and

16
post-game change in state of tension, depression, anger, vigor, fatigue and
confusion could then be compared between hydrated and fluid restricted states.
Several studies have praised the validity and reliability of the profile of
mood states in accurately interpreting mood (Covassin & Pero 2004; Gibson
1997, Gutman et al. 1984; Silva et al. 1985). Gutman et al. 1984 found that
athletes who displayed low anger, anxiety, depression, confusion and fatigue,
and high vigour scores within the profile of mood states were more successful in
performance than athletes that exhibited the opposite profile. The link between
performance and mood ratings highlights that the profile of moods states
questionnaire is a valid interpretation of an individual’s mood state and this is
supported by a study by Gibson (1997) assessing the reliability and validity of
the POMS in 479 participants and found that the POMS was able to accurately
and repeatedly discriminate between healthy individuals and those with known
mood disturbances.
7d. The Ruler Drop Test
Reaction-time was measured using the ruler drop test (Russ & Geller,
1968) whereby a 30cm ruler was held between the individual’s tip of their thumb
and index finger at 0cm and dropped, by which the participant caught it as
quickly as possible. To increase reliability of the test, the participant was seated,
with their dominant arm and wrist resting on a table and their fingers off the
edge of the table, to provide support and reduce movement that may affect
results. A parallel gap between the participant’s thumb and finger from the ruler
needed to be present to ensure that the same proportional distance between the
fingers and the ruler was consistent for all participants to increase test reliability.
The test was consecutively repeated three times to minimize random error. The
distance the ruler drops before the participant catches it is applied into an
equation which determines the subjects’ reaction time. The equation is based on
Newton’s formula (Lieberman & Goodman 2007).
Reaction Time= √ (2*distance (metres)/9.81 (gravity))
The test is deemed valid because results are determined by the speed at
which an individual reacts to the release of the ruler and subsequently displays

17
their capability to catch it quickly (Molnar et al. 2007). Fong, Shamay & Chung
(2013) indicate that the ruler-drop test is the best determinant of simple
reaction time when without the availability of more complex and expensive
equipment that monitors reaction time.
7e. Symbol Digit Modalities Test
The Symbol Digit Modalities Test (SDMT) (Smith 1968; Smith 1982)
(Appendix 8) measures key neurocognitive functions including attentional
vigilance, visual scanning, working memory and motor speed and has previously
been used as a measure of cognitive impairment (Zuri et al., 2013 and Sheridan
et al., 2006).
Using a reference key, participants were required to pair as many specific
numbers with given geometric figures using a pen as quickly as they can in 90
seconds. When 90 seconds was reached the test was terminated and
participants were required to stop writing immediately. Their score depicted the
correct amount of numbers paired with the geometric figures in the 90 second
time span (Benedict, 2012). For the second testing session, the numbers
associated with a symbolwere swapped and replaced to become associated with
a different symbol. Also the order of symbols provided on the grid was changed.
By changing the symbol-number association and grid order, the risk of learning
effect is minimised for the second session, increasing the validity of the test.
According to several studies, the SDMT is one of the most valid and
reliable tests of neurocognitive function (Benedict & Zivadinov 2007; Morrow et
al. 2010; Nocentini et al. 2006; Sonder et al. 2014). Moreover the test is easy to
administer and can be completed simultaneously by all participants, reducing
waiting time that could otherwise increase influence of the confounding
physiological variables of exercise recovery, that may influence results (Piepho,
Büchse & Richter 2004). It can be seen that the SDMT is a valid test with
regards to basketball because it measures cognitive functions such as attentional
vigilance, motor speed and visual scanning, all specific components required to
excel as a basketball player (Millslagle 2002).

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7f. Test Procedures
On the morning of the initial test session, subjects reported to the sports
hall at 07.00 hours and were randomly allocated into either the hydration or
dehydration group. The hydrated participants were provided with a two liter
bottle of water, labeled with their corresponding number. Each bottle had been
marked at different fluid levels labeled with time periods; ‘before game’ (340ml),
‘half-time’ (+230ml) and ‘after game’ (+500ml), in accordance with the
recommended fluid intake guidelines by Simpson and Howard (2011) (Appendix
9). Participants were required to consume at least to the minimum marked
amount of fluid at each time period in order to maintain hydration and were
permitted to drink beyond the minimum if required. The dehydrated participants
were notified that they would not have access to any fluids until completion of
the session. All participants completed an initial profile of mood states
questionnaire and provided a urine sample. Participants were then weighed on
scales. They were required to remove all clothing except their shorts and (for
females) sports bra to ensure readings depicted a relatively accurate
interpretation of body mass. Hydrated participants were required to consume
their initial 340ml of water prior to measurement to identify their initial hydrated
weight measurement. 1 volunteer team member took part within the game to
make teams equal, therefore the game consisted of 6 players. However, the
volunteer was not included within testing. Participants took part in a 5 minute
sport specific warm up followed by a standard full court 40 minute basketball
game, with a 2 minute half-time break after 20 minutes of the game. During the
break, the hydrated participants were required to have consumed to at least the
‘half-time’ mark on their bottle (+230ml) prior to initiation of the second half of
the game.
After the game, hydrated participants were required to consume up to or
past the ‘after game’ mark (+500ml). Participants were then immediately seated
and requested to complete a second POMS questionnaire, with reminder to score
accurately to that of their perceived emotions. Mood is a variable that can be
influenced relatively easily (Lieberman 2005); therefore immediate completion of
the questionnaire after the game reduces the influence of external variables that
could affect results. Once completed, participants were then required to provide
another urine sample, followed by a weight measurement. Participants were

19
encouraged to empty their bladders prior to weighing to enable a more accurate
depiction of body weight. Following on from this, participants took part in the
reaction time test. Finally the SDMT test was completed.
In addition, a 24 hour dietary recall was taken prior to the initial test
session. This required participants to record everything they ate and drank in the
24 hours prior to testing to ensure control of confounding variables such as
carbohydrate consumption that has been found to enhance performance in high
intensity intermittent basketball games (Dougherty et al. 2006; Welsh et al.
2002; Burke 2007). Participants were encouraged not to consume or drink
anything for four hours prior to testing. This dietary consumption was then
repeated 24 hours prior to the second session.
The second session was carried out 1 week after the initial session to
allow for complete recovery. The session was initiated at the same time as the
previous session. A study by Lieberman (2005), declared that time of day was
found to influence mood level and performance, as well as urine osmolality.
Therefore it was evident to repeat measures at the same time of day as the
previous session, to reduce potential time influence on outcome measures.
Procedures were repeated in the same order as the initial session to increase
reliability of test results, however participants were exposed the opposite state
to ensure that they provided both fluid restricted and fluid included results.
8. Data Analysis
All data was analysed via the SPSS programme version 21. The Shapiro-Wilk
test was used to identify whether results were parametric (normally distributed)
or non-parametrically distributed in order to determine the test best suited for
analysis of data. Results were deemed parametrically distributed; therefore the
paired-samples T-test was deemed the most suited test for data analysis. Data
was deemed significant if significance displayed a p value of <0.05.
10. Results
3 participants were excluded from data analysis as attendance was not fully
completed for both test sessions, whilst 1 participant withdrew their participation

20
*P = 0.01
*P=0.01
Graph 1. Mean change of body weight pre and post-game for fluid
restricted and fluid included states
due to injury. Therefore data analysis depicts the results of 5 participants (n=5)
that provided results for both fluid restricted and fluid included sessions.
9a. Physiological Data
Change in mean body weight pre and post-game for participants during
the dehydrated state (Table 1) was deemed significant (P=0.01) whilst
hydrated participants displayed no significant weight change (Graph 1). Overall
there was an average percentage body weight loss of 0.93±0.18% and
0.64±0.21% for fluid restricted participants and fluid inclusion participants
respectively. No significance was found in urine osmolality pre/post-game or
between sessions.
Fluid Inclusion Fluid Restriction
BW Pre (Kg) 79.08 ±10.99 78.76 ± 9.8
BW Post (Kg) 79.08 ± 10.79 78.02 ± 9.64
Weight Difference (Kg) 0.00 ± 0.25 0.74 ± 0.19*
UO Pre mOsm/Kg 654 ± 227.29 850 ± 122.15
UO Post mOsm/Kg 548 ± 183.45 798 ± 106.85
UO Difference mOsm/Kg 106 ± 149.75 52 ± 208.37
Table 1. Body weight and urine osmolality mean results of pre and post -game for both
fluid restricted and fluid included sessions.
Body Weight (BW), Urine Osmolality (UO), *P=0.01

21
9b. Reaction Time
Results for each particpant were derived by the mean of the 3 attempts,
whereby overall mean results of all particpants were 0.167±0.015s and
0.175±0.037s for fluid restriction and fluid inclusion states respectively (Graph
2). Difference in overall mean post-game reaction time between fluid restriction
and fluid inclusion states was deemed significant (P=0.003), whereby reaction
time was reduced in the dehydrated state.
Graph 2. Mean reaction time for both fluid inclusion and fluid restriction states
Fluid Inclusion (FI), Fluid Restriction (FR), *P= 0.003

22
Data also displayed a significant improvement in reaction time (P=0.01)
for all participants in session 2 when compared to session 1 (Graph 3).
9c. Symbol Digit Modalities Test
There were no significant differences between performance of the symbol
digit modalities test between hydrated and dehydrated states of participants
(P=1.0).
Graph 3. Mean reaction time performance of each participant of session 1 and
session 2, P=0.01
5

23
9d. Profile of Mood States Questionnaire
No significant changes were identified for total mood state, tension,
depression, vigour and fatigue. Difference was identified through subtraction of
post-game score from pre-game score, whereby the higher the score the more
negative the mood state. Confusion was deemed to have a significant pre to post
game difference (P=0.03) between states. Graph 4 highlights that the negative
difference in confusion is due to a significantly increased post-game confusion
rating during the fluid restriction state (-4±3.52) compared to the fluid inclusion
(2.8±3.27).
Graph 4. Overall mean pre to post game change comparison between
fluid inclusion and fluid restriction states for confusion
*P=0.03
*

24
9. Discussion
The aim of this study was to identify the effects of fluid restriction on
aspects of cognition and mood in university level basketball players with the
hypothesis that at least 1% dehydration would be induced and cognition and
mood tests would show deterioration in performance. The results of this study
highlight that fluid restriction within a standardised 40 minute basketball game
on university level basketball players caused significant decreases in body mass
of 0.93 % resulting in exercise inducement of very mild dehydration.
Predominant findings of test results from fluid restricted participants for
cognition displayed significant improvements in reaction time; however the
SDMT displayed no change. Furthermore, no change was identified in the mood
test between fluid inclusion and fluid restricted states except for a significant
increase in perceived confusion in the fluid restricted state.
10a. Physiological Findings
With regards to hydrated and fluid restricted participant results, it is likely
that fluid loss due to perspiration and breathing rate would have accounted for
the significant change in body mass loss of 0.93±0.18% (p=0.01) within the
fluid restricted participants, whilst hydrated participants’ body mass remained
relatively unchanged due to the ability to replace fluid lost through fluid
replacement. This 0.93% loss of body mass can be seen as an inducement of
extremely mild dehydration whereby very few studies have observed such mild
dehydration and its related affects. This relatively small loss of weight to what
was expected of approximately 2% may be due to the fact that there were only
6 players within the game, potentially reducing competitive edge or challenge,
thus reducing exercise intensity. Observation in change of urine osmolality from
pre to post game in fluid inclusion and fluid restriction sessions highlight no
change in urine concentration. It could potentially be seen that the degree of
exercise induced dehydration was not extensive enough to display significant
effects in urine concentration.
Comparison of the 24 hour dietary recall sheets between session 1 and
session 2 using WinDiets software displayed no change in dietary consumption

25
between the two sessions for each participant. This suggests that the
confounding aspects of diet were reduced, due to the fact that diet remained
relatively the same before participation within both sessions, increasing the
probability that the results obtained were determined by dehydration.
10b. Cognition Findings
Reaction time comparisons of post participant results between hydrated
and fluid restricted sessions displayed a significant performance enhancement
during the fluid restricted session (p=0.003), whereby overall time to catch the
ruler decreased by 10.27±2.67%. This finding is interesting because it
contradicts the majority of findings displayed by similar studies assessing the
effects of fluid restriction on reaction time performance (D’anchi et al. 2009;
Neave et al. 2001; Leibowitz et al. 1972; Serwah & Marino 2006). It could be
wholly or partially explained by the fact that analysis of results displayed
significant reductions in reaction time (p=0.01) during the second session for all
participants regardless of fluid state when compared with performance during
the initial session. This may be due to a learning effect because the majority of
the participants within the study who attended the second session had already
experienced the fluid restricted state, leading to an increase in performance
during the fluid restricted state. This is supported by a study by Sanders (1988)
that found that individuals that were new to a reaction time task, significantly
became more efficient at the task after several attempts.
Although potential learning effect is the most likely explanation for the
outcome of these findings, there are other theories that may have potentially
contributed to such a significant performance improvement during fluid
restricted state. A study by D’anci et al. (2009) assessing the effects of fluid
restriction and fluid inclusion on college athletes after a high intensity rowing
session lasting 60 minutes found a significant increase in reaction time results
after 1.5-2% weight loss in the fluid restricted state. It can be seen that a
greater number of participants (n=31, 16 males, 15 females) were used
compared to this study, indicating that reliability of results may indicate a more
accurate interpretation of the effects of fluid restriction on reaction time, due to
the reduced risk of random error (Hopkins, 2000). Additionally, there are
relatively equal numbers of males to females within the study by D’anci et al.

26
(2009) which may also explain the difference in performance outcome of
reaction time compared to this study which incorporated just 1 female. A few
studies have identified a significant difference in reaction time performance
between males and females, whereby females generally displayed a slower
reaction time compared to males (Adan 2012; Der & Deary 2006). It could be
seen that the increased incorporation of female participants may have influenced
a more negative performance outcome within mean results. However the most
predominant explanation for such a difference in reaction time compared to this
study could be due to achievement of a higher weight loss % potentially caused
by the longer duration of exercise and/or difference in physiological
requirements of rowing compared with basketball.
On the other hand, Szinnai et al. (2005) also displayed performance
enhancements within male participants after a gradual loss of 2.6% dehydration
over a 7 day period when performing a computerised reactive response task,
whilst female performance remained unaffected (men: -36 ms, women: +26 ms,
p = 0.01). The study theorized that the performance difference in gender may
have been due to low oestrogen levels in men being linked to greater visual-
spacial awareness (Szinnai et al. 2005). This theory is supported by a study by
Der & Deary (2006) that used 7400 participants, whereby male participants had
significantly faster reaction-times than females. However Szinnai et al. (2005)
failed to provide a theory as to why there was a performance improvement in
males during their dehydrated state compared to their hydrated state,
regardless of gender difference. A second study with similar findings by Heuvel
et al. (2013) found that 5% dehydration induced faster reaction times compared
to that of a euhydrated or 3% dehydrated state, during heat induced
dehydration via thermo regulated water immersion. However this study
theorised that the increase in reaction time performance was directly related to
core temperature rather than due to inducement of dehydration.
Although there is no conclusive explanation for the reported findings of
the improved reaction time results for this study and the similar studies
mentioned, D’Anci, Constant & Rosenberg (2006) state that initiation of mild
dehydration could potentially activate cognitive compensating mechanisms in an
attempt to inhibit dehydration stressors. Heinrichs & Koob (2004) and Kloet,

27
Joëls & Holsboer (2005) both highlight that organisms exposed to stressors that
alter normal functioning of the body, produce a coping response as a survival
mechanism to ensure that homeostasis is preserved. They state that
corticotropin-releasing factor (CRF)/urocortin is up regulated, increasing
production of adrenal glucocorticoid production which enhances sensitivity and
arousal; a prime determinant of reaction time performance (Eason & Harter
1969). The majority of studies that identified increases in reaction time induced
>2% dehydration (Grandjean & Grandjean 2007; Gopinathan Pichan & Sharma
1988). This could suggest that an initial increase in CRF may eventually be
overruled by gradual increases in severity of dehydration, which has been
observed by Aguillera et al. (1992), stating that inducement of dehydration
through consumption of 2% saline solution decreases CRF secretion. It could
therefore be suggested that the improvement in reaction times seen during mild
dehydration of 0.93% potentially could be due to enhanced levels of arousal
through release of CRF. It can be theorised that exercise inducement of <1%
dehydration may initially enhance reaction time of basketball players, but
greater inducement of dehydration may induce negative performance outcomes.
However the most likely explanation for improved performance was due to a
learning effect and it is therefore evident that further basketball related research
is required with regards to reaction time and <1% dehydration to establish a
strong conclusive finding.
Analysis of the SDMT test identified that results displayed no change
between fluid inclusion and restricted states. This potentially indicates that >1%
DEH may not have a significant impact on the measured attributes of the SDMT
test; divided attention, visual scanning, tracking and motor speed. Currently
there is no evident literature identifying the effects of >1% dehydration on
cognition through the use of the symbol digit modalities test. A study by Zuri et
al. (2013) is the only study at present that has incorporated the SDMT test to
measure cognition after dehydration. The study induced a dehydration state of
3.27% through a combination of heat and exercise within a humid environment,
whereby the SDMT test revealed significant performance detriment compared to
the control group (hydrated). However, because Zuri et al. (2013) incorporated
both heat and exercise variables for inducement of dehydration, cognition may
have been affected more extremely due to the added stressor of heat, than just

28
exercise alone (Leiberman 2007). It can therefore be seen that comparability of
the study’s outcome to the findings of this study cannot be solely depended
upon to determine a valid explanation.
The majority of studies have found that significant deterioration of the
outcome variables of visual scanning, attentional vigilance and motor speed
occur at >2% DEH (Baker, Conroy & Kenney 2007; Cian et al. 2001; D’Anci et
al. 2009; Gopinathan Pichan &Sharma 1988). This is supported by a study by
Szinnai et al. 2005 that measured aspects of cognition including visual scanning
and attentional vigilance after water deprivation and found that deterioration in
performance was only evident after 2.6% DEH, whereby it was theorised these
aspects of cognition could potentially be preserved until this level of dehydration.
10c. Mood Findings
In contrast to several studies observing dehydration and its negative
effects on mood (Armstrong et al. 2012; D’Anci et al. 2009; Ganio et al. 2011;
Lieberman et al. 2005), this study surprisingly displayed no change of pre to
post difference between hydrated and fluid restricted states for total mood state,
tension, depression, vigour and fatigue. However analysis of confusion scores
highlighted a significant increase of perceived confusion of participants during
their fluid restricted state (p=0.03) between pre and post-game results when
compared with their fluid inclusion session.
The fact that no change was seen for the majority of the mood states
between fluid included and restricted states may be due to the fact that an
induced dehydration of <1% was not sufficient enough to cause mood
degradation. This theory is supported by several studies that have failed to find
detriments in mood at dehydration levels of lower than 1% (D’anci et al. 2009;
Szinnai et al. 2005; Ganio et al. 2011; Kempton et al. 2011) A further potential
explanation may be due to lack of thirst sensation whereby Adolph et al. (1947)
found perceived thirst after >2% DEH had significant negative alterations in
mood. This may explain why the majority of studies displaying significant
negative associations of dehydration with mood in different settings have
attained it through inducement of at least >2% DEH (Armstrong et al. 2012;

29
Armstrong et al. 2010; Ganio et al. 2011; Lieberman 2005). Other studies have
also found a link between mood and level of perceived thirst indicating that a
higher perception of thirst could have detriments in perception of mood (D’Anci
et al. 2009; Guelinckx et al. 2013; Pross et al. 2013) Potentially it could be seen
that the sensation of thirst and the requirement to drink may be less apparent at
such a mild level of dehydration, resulting in the insignificant findings, or simply
due to the fact that dehydration level was not high enough to have a significant
impact on results.
According to the results of this study, confusion may be affected at
dehydration levels as mild as <1% induced after a 40 minute basketball game.
Currently there is very little evidence to neither support nor contradict this
finding or propose any valid reasoning behind it with regards to such a low level
of induced dehydration specifically for exercise. However the reason for such a
significant effect on solely one mood state is interesting, and may simply be due
to random error and coincidence, based on the fact that results have been
derived from a limited amount of participants. However, a study by Shirreffs et
al. (2004) monitoring the effects of fluid restriction over a 37h period, noticed a
significant increase in confusion and decrease in alertness 13 hours into testing
at 1% DEH, whilst subjective feelings of tiredness only became present after 24h
after 1.7% DEH. It can be seen that this study displayed earlier signs of
confusion decrements, whilst increased fatigue was delayed until a more
elevated level of dehydration, which potentially supports this study’s finding. It
could be theorised that confusion may be more susceptible to early negative
effects of dehydration compared to other mood states and could potentially be
the first mood state to deteriorate. Further exploration is required in relevant
research in order to provide a clearer explanation as to whether these findings
are due to valid physiological reasoning or simply a display of random error.
10d. Strengths of the study
A significant strength of the study was the recruitment of individual’s with
relatively similar fitness levels, when considering that fitness level could
potentially have an impact on the effect of exercise intensity on cognitive
function. This is supported by a study by Gutin & DiGennaro (1968) that

30
observed that after a treadmill run to voluntary exhaustion individuals classified
as being extremely fit performed the mathematical tasks significantly better than
those that were classified as being less physically fit. By recruiting individuals
with similar levels of fitness, overall implications of results are more specific
towards a particular population of athletes, in this case, university level
basketball players. Additionally it can be seen the repeated cross-over design of
the study decreases the contribution of individual variability that could cause
greater dispersion of results, leading to insignificant findings (Adan 2012). This
study design allows
Following on from this, a second strength of this study is its specificity
with regards to basketball related dehydration. As a field based research project,
it provides sport specific information that could potentially reflect results
displayed in a real game scenario, providing beneficial implications for teams.
10e. Limitations
With regards to outcomeof the study, test reliability cannot be
guaranteed due to the limited number of subjects, whereby at least 50
participants should be used to justify results and reduce random error according
to Hopkins (2000). This limited number of participants may have partially been
due to inconvenience with regards to time of day or due to university
commitments. Due to practicability of assessing a basketball team, population
sample would generally remain limited in order to increase specificity of results
with regards to the sport and team fitness levels (Burke, 2007) and this is a
generalised limitation for studies assessing team sports.
The limited change in urine osmolality pre to post may be explained the
fact that both sessions were carried out on early mornings, making it likely that
the pre-game urine sample provided would have been the participants’ first urine
void of the day. Eberman, Minton & Cleary (2009) highlight that the first urine
void of the day may not accurately depict an individual’s hydration status,
because its osmolality is usually stronger due to increased fluid preservation
during sleep. It could be seen that the stronger osmolality reading for pre-game
samples may not have accurately depicted the true hydration status of

31
participants, therefore potentially reducing the difference between pre and post-
game osmolality reading for fluid restricted state results. This can be seen as a
potential limitation within the study, however due to limited team availability;
early mornings were the only opportunity for carrying out this research.
Potential limitations with the profile of mood states questionnaire that
may have affected accuracy results could be due to the subjective nature of its
assessment. It can be seen that qualitative tests may induce socially desired
expectations and fear of judgement which can influence participant ratings and
therefore cause variation between presented results and actual perceived
feelings (Smit & Rogers 2002). Additionally the POMS is sensitive to alterations
in mental state induced by various environmental stressors, sleep loss, drugs,
and nutritional manipulations (Banderet & Lieberman 1989) To reduce the
effects of external stressors, the test was carried out pre and post-game and the
difference between the two was the participant’s score. Furthermore the 24
dietary recall sheets encouraged repeatability of diet to minimise nutritional
manipulation. However, at present, there are no alternative tests that are
capable of measuring an individual’s mood qualitatively and the profile of mood
states questionnaire is currently one of the most accurate tests for observation
of mood status (Terry, Lane & Fogarty 2003). Similarly the 24 hour dietary recall
procedure poses as a potential limitation within the study due to the fact that
information is based upon subjective input. It cannot be guaranteed that the
information provided replicates the participant’s actual dietary consumption,
whereby failure to repeat the recorded diet may occur, however this may not be
highlighted due to fear of scrutiny. In an attempt to minimise this limitation,
participants were clearly reminded and encouraged to provide accurate
information on every item they consumed within the 24 hours leading up to each
session.
Finally, with regards to reaction time, learning effect was a potential
limitation within the study. Results displayed that all participants improved their
reaction time scores within the second session, regardless of hydration status.
However, this was a potential risk within the study and effort to minimise
learning effect was applied within the familiarisation session, whereby
participants were only allowed one practice attempt during the ruler drop test.

32
10f. Practice and Future Implications
With regards to the results of this study and consideration of previous
studies, potential future recommendations for basketball players are to remain
hydrated pre-game and throughout game play, to maximise cognitive
performance and mood. It is evident that there is greater need to emphasize the
importance of hydration, therefore by ensuring rehydration is the primary focus
during half-time, players are more likely to replace their sweat losses effectively
(Burke 2007).
Due to the limited number of recruited subjects within this study, it can be
recommended that further research with a greater population sample is required
to attain more conclusive findings with regards to dehydration and its impact on
aspects of cognition and mood in basketball. It should be emphasised that future
studies should incorporate a similar sports specific approach to dehydration, to
ensure findings are valid and can be implemented.
11. Conclusion
This study aimed to identify the effects of fluid restriction on cognition
and mood in university level basketball players. The main finding within this
study was that fluid restriction during a 40 minute basketball game resulted in
an average dehydration of 0.93% in participants, whereby a significant increase
in confusion was evident within this state. A second predominant finding was a
significant improvement in reaction time within the fluid restricted state.
However it has been established that this improvement was predominantly due
to a learning effect and cannot be considered for future implication until verified
by further research. It can be concluded that although confusion was increased
by dehydration, reliability of all test results can not be guaranteed due to limited
subject participation, whereby at least 50 participants should be present
(Hopkins 2000). Evidentially it is advised that basketball players remain
hydrated during practice and competitions to potentially prevent confusion
during performance, however further research is recommended with a larger
population sample to attain more conclusive findings.

33
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45
Appendix 1
Recruitment Material
Dear Sir/Madam
We would like to invite you to take part in a study that explores the effects of
mild dehydration on cognitive function (memory, mood and reaction time) and
skill performance in basketball.
The study will take place over three weeks and will be during your scheduled
training sessions so you will not need to give up any additional time.
To assess your suitability for the test you will be required to complete a Physical
Activity Readiness Questionnaire (PARQ) and an informed consent form. From
these the researcher will determine if you surpass the exclusion criteria.
Below is a detailed account of the test procedures for you to read:
Three test days will be carried out over three weeks, each on the basketball
teams scheduled training days. The first will be an initial control trail to
familiarise participants with all test procedures. The second day of testing will
involve the team being hydrated by following the exercise hydration guidelines
provided by ASCM (2011). Immediately after game play, you will be weighed
and a urine sample will be taken to monitor your level of hydration and then the
tests will be carried out. The third day of testing will involve all participants to be
dehydrated and restricted access to water, followed by execution of all the tests.
All results obtained will be recorded and analysed.
The participants will complete each of the tests after a 40 minute game. The
Illinois agility test (physical performance) will be completed first with the
participants being separated between two stations. The mood, memory and
reaction time tests (cognitive function) will be completed second with the
participants being split between the three for speed of completion so the results
will be more accurate. For more detailed information on the tests involved see
the attached participant information sheet.
The result from the tests will be shared and could benefit your game as you will
able to see the potential merits of remaining fully hydrated throughout a game.
Attached is a copy of the PARQ and the informed consent sheet for you to fill in.
Thank You
Yours Sincerely
Amy, Simon, Lewis

46
Appendix 2
Participant Information Sheet for Competent Adults (PISCA)
Generic Information
SRRG Ref No: SHS 13 42
Title (short): Fluid restriction in basketball players.
Date: 11.11.13
Introduction:
We are applied sport and exercise students currently undertaking our fourth year
research projects. This letter is an invitation for you to participate in our study
which would be very much appreciated.
The study:
The purpose of the study is to look at the effect of fluid restriction on cognitive
function and skill performance in basketball players. To be included in the study
you need to play basketball for RGU, training at least once a week and competing in
games. For the study you will be required to take part in a basketball session, be
weighed both before and after the session and provide a urine sample. The study
also requires you to carry out a performance test as well as a memory, mood and
reaction time test at the end of the session. Your participation in the study is
completely voluntary and you can withdraw from the study at any point.
Taking part:
The study will take place at RGU sport in the hall during a normal basketball
training session. There will be a familiarisation session and two testing sessions
and these will take place on a weekly basis during the normal basketball training
sessions at RGU sport. The familiarisation will be a practice session where you will
find out what the tests are and be able to have a practice of each test so you know
exactly what you will be doing within the testing sessions. There are two testing
conditions, a hydrated one where you will be encouraged to drink water throughout
the session and the second is a fluid restricted session where you would not be
allowed access to water until the end of the session. The sessions will be
approximately two hours long. As a participant you will be required to be weighed
and give a urine sample at the start then take part in a basketball game. You will
then be weighed after the session and required to give a urine sample. You would
also have to carry out an Illinois agility test which is a simple speed and change of
direction test where you will be timed when carrying out the course. A simple
reaction speed test which involves catching a falling ruler, a written test to assess
cognitive function such as motor speed, short term memory, scanning ability and
attention and a current mood status questionnaire to assess your mood after the
session. You will be asked to provide a 24 hour dietary recall before the first
session and to avoid any major changes to your diet and activity patterns between
testing sessions. If you are injured or have been injured in the past six months you

47
will be unable to take part in the study.
Expenses and payment:
This is a voluntary study and therefore no payment will be received for
participation.
Advantages and disadvantages of taking part:
Taking part will give data on how effectively you manage to stay hydrated when
playing basketball and the effect it can have on your performance when you are not
properly hydrated. The disadvantage is that some discomfort may be felt during
the fluid restriction session causing you to be very thirsty by the end of the session.
However you have the right to withdraw from the tests at any point.
Confidentiality, data protection and anonymity:
All your data will be kept completely confidential and saved in a secure database
that will be password encrypted. It will only be available for the research team and
anonymity will make it impossible to link the data to you the individual.
Data Protection: all data will be collected and stored within the requirements of the
Data Protection Act (1998). Data will be stored in a locked cabinet/password
protected computer/memory stick/ hard drive and accessible only to the research
team (student researcher and supervisor)
What happens if there is a problem?
If you have any problems then you can contact the research team via the
information provided at the end of the sheet.
Complaints may be made to the SRRG convenor Dr Lyndsay Alexander
l.alexander@rgu.ac.uk.
What will happen to my research data?
The data will be used to write up the research paper which may be published within
academic journals and then it will be destroyed at the end of the study.

48
Assurance of research rigour:
This research has been approved by the School Research Review Group at the
School of Health Sciences, Robert Gordon University, Aberdeen.
What happens now?
If after reading this information sheet you are interested in taking part in this
research project please contact the researcher at the address/email/phone number
below.
Further information and contacts:
Researchers: Lewis Kerr, Amy Street,
Simon Gilmour
Supervisor: Eimear Dolan
HS3 Applied Sport and Exercise Science
School of Health Sciences
Robert Gordon University
Garthdee Road
Aberdeen AB10 7QG
l.r.kerr2@rgu.ac.uk
1004740@rgu.ac.uk
1007779@rgu.ac.uk
HS3 Applied Sport and Exercise Science
School of Health Sciences
Robert Gordon University
Garthdee Road
Aberdeen AB10 7QG
e.dolan @rgu.ac.uk
01224 263258

49
Appendix 3
PARQ
Participant Questionnaire
If you wish to participate in the study, it is important that you complete this
quick questionnaire to ensure that test procedures will be appropriate for you to
participate in.
Please carefully read each question below and circle ‘Yes’ or ‘No’ depending on
your answer. Please answer each question honestly and to the best of your
knowledge.
1. Has your doctor ever said that you have a heart condition and that
you can only do physical activity recommended by a doctor?
2. Do you experience a tightness or pain in your chest when you do
physical activity?
3. In the past month have you ever experienced pain in the chest
when NOT doing physical activity?
4. Do you ever feel faint, experience dizziness or lose consciousness?
5. Do you have a bone or joint problem (for example back, hip, and
knee) that could be made worse as a result of physical activity?
6. Have you had any injuries in the past 6 months?
7. Have you been unwell in the past month? If yes please explain.
………………………………………………………………………………………………………
8. Is your doctor currently prescribing you drugs for blood pressure or
a heart condition?
9. Do you know of any other reason as to why you should NOT
engage in physical activity?
If you answered ‘Yes’ to one or more questions:
If not already done so, please consult your doctor either by telephone or in
person before participating in physical activity and inform them of the questions
Yes / No
Yes / No
Yes / No
Yes / No
Yes / No
Yes / No
Yes / No
Yes / No
Yes / No

50
that you answered ‘Yes’ to on the PAR-Q. After medical evaluation, please seek
advice from your doctor as to whether it is appropriate for you to take part
within the study.
If you answered ‘No’ to all of the questions:
If you answered the PAR-Q accurately and honestly you have reasonable
assurance that you will be able to take part within the test.
I hereby state that I have read, understood and answered the above questions
honestly and to the best of my knowledge. I also state that I wish to take part
within the study which will involve aerobic exercise, agility tests and stretching. I
understand that my participation within this study involves the risk of injury or
even the possibility of death. I hereby confirm that I agree to take part within
the study at my own risk.
Name of participant ………………………………………………………………………
Signature ………………………………………… Date ………/………/………
Name of Researcher ……………………………………………………………………
Signature ………………………………………… Date ………/………/………

51
Appendix 4
Informed Consent Form
Generic Information
Please
initial
each box
1. I confirm that I have read and understand the participant
information sheet dated 11/11/2013 for the above study. I have
had the opportunity to consider the information, ask questions
and have had these answered satisfactorily.
2. I understand that my participation is voluntary and that I am free
to withdraw at any time without giving any reason.
3. I understand that data collected during the study will be looked at
by individuals from Robert Gordon University where it is relevant
to my taking part in this research. I give permission for these
individuals to have access to the data.
4. I agree to providing urine samples and being weighed prior to and
after playing basketball.
5. I agree to take part in testing after each session as outlined in the
information sheet.
6. I agree to take part in the above study.
Participant:
Name:
Signature:
Date:
Person taking consent:
Name: Amy Street, Lewis Kerr & Simon Gilmour
Signature:
Date: 11/11/2013

52
Appendix 5
Research Proposal
Generic Information
Title (full):
The effect of fluid restriction on cognitive function and skill
performance in basketball players.
Researcher’s name: Amy Street, Lewis Kerr, Simon Gilmour
Signature: Amy Street, Lewis Kerr, Simon Gilmour
Date: 11.11.13
Supervisor’s name: Eimear Dolan
Signature: Eimear Dolan
Date: 11.11.13
Background to the Research Topic
Introduction:
Water is a vital component required in order to survive, whereby it has been
found that in severe cases (9% to 12% total weight loss due to dehydration) can
cause serious deterioration in cognitive and physiological functions and could
lead to death (Wilmore, Costill and Kenney 2007). This study aims to find out
whether cognitive function and skill performance deteriorates as a result of mild
exercise induced dehydration (DEH) of a minimum of 2% DEH in university level
in basketball players. A basketball team was chosen due to basketball involving
bursts of high intensity exercise (Dougherty et al 2006) where quick decision
making, reaction time and skill execution can change the whole dynamic of the
game making it essential to maintain optimum performance for as long as
possible. It is important to assess the impact of dehydration on these variables
to emphasise its importance in relation to basketball performance as well as
other high intensity sports.
Literature Review:
Literature highlights that it is essential during sport to maintain the body’s
hydration levels as a loss of just 2% of body water could affect physical and
cognitive performance. Dehydration of 5% and 7% can have a serious effect on
decision making and awareness and as water loss increases, individuals begin to
experience symptoms such as tiredness, sore heads and dizziness (Latzka and
Montain 1999). It can therefore be questioned as to whether these effects would
be present at a more subtle induced dehydration state of 2% and to what

53
degree.
Studies by Gopinathan, Pichan and Sharma (1988) and Cian et al (2000)to
induce DEH of 2% have shown that mood was rated more negatively and
memory and reaction time performance diminished when exercising in heat and
restricting fluid. Interestingly a study involving college athletes during a training
session without access to fluids found that mood was ranked more negatively
after a >2% decrease in body weight, yet memory was actually enhanced
(D’anchi et al 2009). With such conflicting results it can be concluded that it is
necessary to carry out tests to further analyse the effects of 2% DEH on
cognitive functions in a basketball related setting within a neutral temperature.
A study by Lion et al (2010) found that cycling on an ergometer for forty five
minutes in a room (22-24◦C, room temperature) induced sweat loss sufficient
enough to induce a state of 2% dehydration which in turn negatively affected
the participants sensory perception directly after the cycle however sensory
organisation tests highlighted that the participant regained efficiency after 30
minutes. It can therefore be questioned that if sensory perception is affected at
2% DEH during a closed environment test would results show similar findings in
a test within a sports specific setting?
Research Question and/or Hypothesis:
Will fluid restriction leading to a minimum of 2% DEH impact on the cognitive
functions of memory, mood and reaction time and the dribbling ability of
basketball players?
It is predicted that there will be a significant relationship between cognitive
function and skill performance with fluid loss, whereby performance quality will
decline as percentage of DEH increases.
Aim(s) and Objectives
Aim(s):
1. To determine the effects of ≥2% DEH on university level basketball
players’ ability to perform a sports specific skill.
2. To determine the effect of ≥2% DEH on university level basketball
players’ cognitive functions.
Objectives:
1. Induce a level of ≥2% DEH during a basketball game and then carry out an
Illinois agility test incorporating dribbling and a free throw shot to determine the
effect on skill performance.
2. To monitor their cognitive function through the completion of a reaction time
test and a written test to assess their visual scanning, attention and motor
speed.
3. To obtain a player’s perceived feelings due to both hydration and dehydration
after the game using a valid profile of mood state.

Dissertation HS4101 1004740

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