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Journal of Exercise Physiologyonline
June 2017
Volume 20 Number 3
Editor-in-Chief
Official Research Journal of
Tommy
the American
Boone, PhD,
Society
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Exercise
Physiologists
Todd Astorino, PhD
Julien Baker,
ISSN 1097-9751
PhD
Steve Brock, PhD
Lance Dalleck, PhD
Eric Goulet, PhD
Robert Gotshall, PhD
Alexander Hutchison, PhD
M. Knight-Maloney, PhD
Len Kravitz, PhD
James Laskin, PhD
Yit Aun Lim, PhD
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Derek Marks, PhD
Cristine Mermier, PhD
Robert Robergs, PhD
Chantal Vella, PhD
Dale Wagner, PhD
Frank Wyatt, PhD
Ben Zhou, PhD
Official Research Journal
of the American Society of
Exercise Physiologists
ISSN 1097-9751
JEPonline
Association of BRAMS with Physiological Variables
during a Maximum Test in High Performance Kayak
Athletes
Pamela Gill Ferreira1, Heros Ribeiro Ferreira2, Joice Mara Facco
Stefanello 1
1Laboratory
of Sport Psychology of Federal University of Parana,
Curitiba, PR, Brazil, 2Laboratory of Physiology of Faculty of Medical
Sciences of Santa Casa of Sao Paulo, Sao Paulo, SP, Brazil
ABSTRACT
Ferreira PG, Ferreira HR, Stefanello JMF. Association of BRAMS
with Physiological Variables during a Maximum Test in High
Performance Kayak Athletes. JEPonline 2017;20(3):184-193. The
purpose of this study was to determine the association of the
Brazilian Mood Scale (BRAMS) with specific physiological variables
prior to a 4-min maximum effort test in Olympic kayak athletes. The
subjects consisted of 54 high performance canoeing athletes with
more >3 yrs of international competitive experience. Their mean age
was 21.76 ± 6.43 yrs. The Kolmogorov Smirnov test was applied for
normality. The Spearman correlation test was used to determine the
correlation between variables. Analysis of Variance was used to
determine statistical differences with the alpha level set at P<0.05.
The results indicate significant correlations for the following
variables, BRUMS subscale: Tension (r = .41; P=0.01), Depression
(r = .34; P=0.05), Fatigue (r = .46; P=0.01), Confusion (r = .40;
P=0.02), and Anger (r = .42; P=0.01) with Lactate and Anger (r = .37;
P=0.03) with Heart Rate and Stroke Rate (r = .40; P=0.02). These
findings are in agreement with the association of metabolic
responses in different high intensity sports. Search results for
BRUMS with regards to blood lactate and heart rate in the 4-min
maximum effort test confirm the diagnostic effects for the high
performance sport in the pre-competitive phase. This analysis should
help in promoting success in kayak athletes.
Key Words: Fatigue, Kayak, Mood, Performance
185
INTRODUCTION
The studies about relationship between emotional variables and sports performance (1) have
received a lot of attention, especially the studies with mood states (18,22,37). The changes in
mood states can compromise an athletic performance since as they do not provide the
athlete with the performance conditions to be successful or even indicate training overload
(23,32). Hence, mood states are a decisive factor in the performance of athletes (39). Initially,
the research involving mood states in sport was performed with athletes of individual
modalities (e.g., running and swimming) (14,32). Currently, researchers have investigated
this variable in the most sports (20,23,30), particularly in association with metabolic or
physiological parameters in order to validate a modification.
Generally, when athletes present positive mood states with high levels of energy and low
levels of fatigue, anger, tension, depression, and mental confusion (17,27,42), their
perception of the actual experience can impact positively or negatively their performance
(25). Athletes who are depressed or who feel that it is hopeless to continue face a very
frustrating situation. Their feelings of sadness are often associated with the behavior of “why
try”. On the other hand, when athletes feel strong, vigorous, and cheerful, they tend to exhibit
coping behaviors that allow for the handling of frustrating situations. They feel encouraged,
which helps to produce the appropriate physiological responses.
Considering that perceptions, judgments, behaviors, and memories always associate with an
affective resonance and change in the mood state present in an individual (2,3,5,6,28,31,44),
professionals who work with the high performance athletes are interested in understanding
the psychological demands associated with sports performance. In this way, they are in a
better position to detect and optimize the athletes’ training sessions by intervening when
necessary to help guide them in a fast and precise way to help ensure their best performance
(26,27)
While athletes who engage in competitive performances must have high levels of strength,
muscular endurance, balance, coordination, and agility (7-12) to perform well, they must also
have a strong and balanced emotional state of mind. Also, in addition to the physiological
variables and the athletes’ mood state profile, the ideal condition for the best athletic
performance is made possible by ideal environmental factors. This is a primary concern for
the kayak athletes whereby the environment can interfere with the competitive performance
due to wind and water actions. The athletes’ quick decisions and concentration in the face of
unstable environmental conditions require attention equal to their physical abilities.
Cognitive mechanisms that allow for exercise to effectively decrease the athletes’ anxiety
remain to be completely understood. The experimental methods used in various studies
cannot effectively explain whether the mood changes observed in the participants were due
to the exercise itself or were influenced by artifacts from the experiment that may have led
participants to self-assess more positively after the session (25,28-31,33,34,44). Thus, the
purpose of this study was to determine the association of the Brunel Mood Scale (BRUMS)
with specific physiological variables prior to a 4-min maximum effort test in Olympic kayak
athletes.
186
METHODS
Subjects
The study consisted of 54 male athletes with a mean age of 21.76 ± 6.43 yrs, height of
182.46 ± 3.42 cm, and body weight of 78.73 ± 4.19 kg. All subjects presented with more than
3 yrs of high performance training and international competitive results. The subjects were
analyzed during the strength training period of the general training plan established by the
Brazilian Confederation of Canoeing (CBCa) in order to have greater control of all sports
activities and nutritional status. The subjects were informed about the objectives and
procedures of the study and, after agreement, they signed a free and informed consent form,
which was approved by the Ethics Committee of the School of Medical Sciences of Santa
Casa de Sao Paulo (FCMSCSP) under number 518,993 of 01/29/2014.
Procedures
The present study has cross-sectional, descriptive, and correlational characteristics, where all
subjects maintained their training programs during the month preceding the research. The
evaluation of mood states was performed immediately before the maximal effort of 4-min in
an ergometer. The questionnaire was read item by item by the evaluator so that all the
subjects could mark their answer. The subjects did not consume any dietary or ergogenic
supplements before or during the study.
Brazilian Mood Scale (BRAMS)
To evaluate the subjects’ mood states, the Brazilian Mood Scale (BRAMS) (4,15,40,41) was
used, which was adapted from the Profile of Moods States (POMS). The Brazilian version
(BRAMS) has six subscales with four indicators each: (a) Tension (items 1, 13, 14, 18); (b)
Depression (items 5, 6, 12, 16); (c) Vigor (items 2, 15, 20, 23); (d) Fatigue (items 4, 8, 10,
21); (e) Confusion (items 3, 9, 17, 2); and (f) Anger (items 7, 11, 19, 22). Responses are
recorded using a 5-point Likert scale, where ‘0’ = ‘Not at all’, ‘1’ = ‘A little’, ‘2’ = ‘Moderately’, 3
= ‘Quite a bit’, and ‘4’ = ‘Extremely’. The standard reference timeframe used is “How you feel
right now”, although a variety of other reference time periods can be used. The BRAMS has
been shown to be a valid and reliable measure of mood in several scientific studies. The
average completion time of the BRAMS is 1 to 2 min (35,36,43,45).
4-Min Maximum Kayak Ergometer Test
The specific ergometer for canoeing was the Kayakpro® Speedstroke GYM, which has been
used in recent years by countless countries for indoor training and championships. The kayak
ergometer (KE) allows the athlete to use the same posture as when in the kayak. It is
configured to allow the athlete the same movement that is carried out when in the water. The
rowing axis is fixed by cables at the ends are connected to force and speed transducers that
allow for the resistance to be altered, calibrated, and controlled by computer, which provides
the simulated variables to the in loco test (10,12).
The purpose of the 4-min test using the KE was for each subject to perform a maximum
physical effort specific to the sport of kayaking. Each subject performed a complete joint
warm-up for 5 min followed by a 40 W load for 5 min on the ergometer, which was followed
by a 2 min passive interval. Then, the KE test was initiated (10,12). The variables analyzed
were determined by the components of the force-time curve: (a) Average Relative Power
(ARP) in watts·kg-1; (b) Stroke Rate (SR) in RPM; and (c) Distance Travelled (DD) in meters
(m). The impulse loads determined the ARP by the time ratio and the SR were determined by
187
the number of complete stroke cycles per minute, which were averaged. The maximum
distance travelled (MDT) variable was measured in meters, and it was the final product of the
4-min maximum test (9).
Physiological Variables
During all test, gas exchange was analyzed using a metabolic system K4b 2 (Cosmed, Rome,
Italy) that was calibrated using a 3 L syringe and gases of known concentrations. The
physiological variables of interest included peak VO2, SPO2 and heart rate (HR). Prior to and
immediately after the KE, blood was collected from the earlobe to determine [Lac], using
disposable microspears (Roche®, Soflix®) and reagent strips for lactate (Roche®, lactate test
strip) in a portable Accusport analyzer (Roche®). The HR data were collected and recorded
using a Polar® system of information transmission. All data were stored in the equipment and
subsequently filtered and analyzed using specific software. Body composition was collected
the previous day using the metod Multi-frequency Direct Segmentation Bioimpedance DSMBIA, Tetrapolar, using an equipment model 120 for InBody®.
Statistical Analyses
The results are presented as mean ± SD. The normality was verified using the Kolmogorov
Smirnov test. Spearman test was use to establish correlation and the statistical comparison
of the groups was carried out using the One-Way Analysis of Variance (ANOVA) test and the
Tukey HSD (Honestly Significant Difference) test. The significance level was set an alpha
level of 5%. The Statistical package SPSS 17 was used to analyzed the data.
RESULTS
The descriptive results (mean ± SD) are shown in Table 1 (body composition, levels of sports
performance about data of metabolic characterization, attesting the high level of the athletes.
Table 2 presents the results of the correlation analysis of the variables in the BRAMS
subscale, which indicate significant correlations for the following variables: Tension (r = .41;
P=0.01), Depression (r = .34; P=0.05), Fatigue (r = .46; P=0.01), Confusion (r = .40; P=0.02),
and Anger (r = .42; P=0.01) with Lactate and Anger (r = .37; P=0.03) with Heart Rate and
Stroke Rate (r = .40; P=0.02).
Table 1. Characterization of the Sample.
Weight (kg)
Height (cm)
HR Rest (beats·min-1)
VO2 Peak (L·min-1)
SPO2 (%)
Lactate Rest (mmol)
% Fat (%)
Minimum
Maximum
Average ± SD
73.4
177.0
54.0
3.2
98.0
1.5
7.7
91.6
198.0
79.0
3.9
99.0
3.9
10.4
78.73 ± 4.19
182.46 ± 3.42
74.52 ± 9.52
3.54 ± 0.43
98.82 ± 0.38
2.88 ± 0.55
9.22 ± 1.88
188
Table 2. Correlation between BRAMS Subscales and 4-Min Test Variables.
Tension
Depression
Vigor
Fatigue
Confusion
Anger
r
P
r
P
r
P
r
P
r
P
r
P
Δ Lac
Δ HR
ΔSBP
Δ DBP
Δ SPO2
ARP
SR
MDT
(mmol)
(bpm)
(mmHg)
(mmHg)
(%)
(W·kg-1)
(spm)
(m)
.41*
.01
.34*
.05
-.26
.14
.46**
.01
.40*
.02
.42*
.01
.31
.08
.06
.74
.32
.07
.30
.08
.31
.08
.37*
.03
-.06
.73
-.12
.49
.30
.08
-.03
.87
-.14
.42
-.17
.35
.20
.27
-.22
.22
.19
.28
-.07
.68
-.05
.79
.04
.83
.14
.42
-.28
.11
.13
.47
.13
.46
-.04
.83
-.10
.58
-.34
.05
-.02
.93
.07
.67
-.13
.47
.04
.81
-.07
.71
-.04
.80
.11
.53
.24
.18
.10
.57
.31
.07
.40*
.02
-.11
.53
.12
.51
.24
.18
.04
.84
.32
.06
.26
.13
Δ = variation; Lac = Lactate; HR = Heart Rate; SAP = Systolic Blood Pressure; DAP = Diastolic Blood Pressure;
ARP = Average Relative Power; SR = Stroke Rate; MDT = Maximum Distance Travelled; bpm = beats per
minute; mmHg = millimeter Mercury; W·kg-1 = Watt per kilogram; spm = stroke per minute; m = meter; r =
correlation value and P = significant; *Significant correlation for P<0.05 and **Significant correlation for P<0.01
DISCUSSION
It was observed that there were significant differences when the highest loads were reached,
thus indicating the sensitivity of the instrument associated with the intensity of the sports
stimulus. Thus, it is suggested the sensitivity of the BRAMS test is a way to detect a change
in mood states at different levels. In the state of calm and stability, training with moderate
loads may show few changes in mood states.
The correlation with “tension” was positively correlated with the variables: depression (r =
0.39, P = 0.02); anger (r = 0.63, P < 0.01); confusion (r = 0.57, P <0.01); and fatigue (r =
0.67, P<0.01). In addition, depression was positively correlated with tension, pre-test with
anger (r = 0.34, P = 0.04), fatigue (r = 0.58, P<0.01), and confusion (r = 0.53, P<0.01). Rage
was positively correlated with fatigue (r = 0.59, P<0.01), confusion (r = 0.55, P<0.01), and
with tension and depression. The force factor did not present a correlation. These findings
are in agreement with the findings of Terry and Lane (37), which indicate that the force factor
correlated only with depression and fatigue.
In the pre-test, the subjects’ fatigue presented a correlation with the previously highlighted
items, tension, depression, and anger, and also with confusion (r = 0.73, P<0.01). Here, it is
important to note that although these relationships can be observed to guarantee the
sensitivity of the instrument, they should not be a correlation coefficient (r) very close to 1 or
-1. This should not happen because a perfect correlation may indicate that the instrument is
not capturing the nuances that differentiate mood states, but rather measures a general
stress trend.
189
Regarding the physiological responses and biomechanics of the maximum 4-min test applied
to the canoeing athletes. The lactate variation variable presented a greater number of
positive associations, corroborating with Filho et al. (13) and Stevenson et al. (35) that
suggest mood states can detect signs of fatigue and excessive training. The BRAMS
questionnaire presented a significant predictive value of the stroke rate, although there was a
correlation with the anger subscale only (r = 0.55, P = 0.02). Finally, it was shown that the
tension variable, as it refers to the high musculoskeletal tension, which can be observed
through psychomotor manifestations such as restlessness (38,39) leaves the athlete tense
and/or trembling (19,21,30). High tension can be useful for sports performance. It is
suggested that high levels may contribute to the generation of energy and the reduction of
fatigue (5,22), which agrees with the findings in the present study.
Likewise, the variable depression at high levels may reflect dissatisfaction with a particular
event or situation (24-26). Also, anger is an emotional state that varies from feelings on a
scale of mild irritation to cholera associated with autonomic nervous system stimuli (34,36,39,
44). Conversely, the variable vigor is characterized by the state of energy, animation, and
activity, essential elements for the good performance of an athlete since it indicates a positive
aspect of mood. Finally the variable, fatigue is described as a factor that can gradually
change attention, concentration, and memory; also in mood disorders, irritability, and
subsequently changes in sleep, physical tiredness, and inattention. Thus, it has
repercussions in the process of initiation of problems of psychosomatic, physiological, and
psychic order (5,13,16,29,31,32).
CONCLUSIONS
The discussion presented in this present study corroborates the literature (vigor, fatigue,
tension, depression, confusion, and rage) that fits adequately with high-performance
canoists, especially at 4-min maximum test. However, during competitions, the moderate
increase in tension and anger can be considered positive, aiming at a better performance of
these athletes at that specific time. In competitions, the guidelines should be related to the
goals of the athlete, the concentration for the task to be performed, the feeling of control of
the situation, and the autotelic experiences. These aspects can help keep the mood at
appropriate levels to produce a better sports performance. Hence, with regards to the
canoeing athlete and factors that influence their performance, the findings in this study
indicate that the athletes’ mood state profile has a close relationship with their sports practice.
This information can be viewed as an important tool that can be used by sports psychologists
and exercise physiologists interested in producing the best sports performance. Future
research should highlight these differences by discussing mood states of athletes in training
and competition, providing a new perspective on data interpretation, as well as professional
intervention.
ACKNOWLEDGMENTS
The authors would like to thank all the participating athletes who were essential for this study
and finally the UFPR.
Address for correspondence: Pamela Gill Ferreira, Federal University of Parana, Curitiba,
Parana, Brazil, 80010-100. Email: [email protected]
190
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