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JEPonline
Autonomous Modulations and Self-Confidence of High Performance Athletes
Pamela Gill Ferreira1, Heros Ribeiro Ferreira2, João Paulo Loures3, 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, 3Laboratory of Physiology Exercise of State University of Sao Paulo, Sao Paulo, SP, Brazil
ABSTRACT
Ferreira PG, Ferreira HR, Loures JP, Stefanello JMF. Autonomous Modulations and Self-Confidence of High Performance Athletes. JEPonline 2017;20(4):1-10. The purpose of this study was to determine the correlation of the self-confidence inventory (SCI) with heart rate variability (HRV) in Olympic slalom canoeist. The subjects consisted of 34 high performance slalom canoeing athletes with more than 3 yrs of international competitive experience. Their mean age was 20.11 ± 4.82 yrs. The Kolmogorov Smirnov test was applied for normality. The Pearson correlation test was used to determine the correlation between variables with the alpha level set at P<0.05. The results indicate significant correlations for the following variables, self-confidence in physical skills and training (SPST) with index corresponds to the square root of the mean of the successive squared differences, between consecutive R-R intervals (rMSSD) r=0.40 (P=0.018) and SPST with high frequency domain (HF) r=0.39 (P=0.02). These findings are in agreement with the association of HRV of athletes who present a vagal predominance before the beginning of the training and the canoeing was related to HRV indicators of parasympathetic domain during rest. This analysis should help in promoting success in canoeing athletes.
Key Words: HRV, Kayak, Performance, Self-Confidence
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INTRODUCTION
Control of the cardiovascular system is performed in part by the autonomic nervous system (ANS), which provides afferent and efferent nerves to the heart in the form of sympathetic endings throughout the myocardium and parasympathetic to the sinus node, the atrial myocardium, and the atrioventricular node (18). The influence of the ANS on the heart is dependent on information from the baroceptors, chemoceptors, atrial receptors, ventricular receptors, respiratory system modifications, vasomotor system, renin-angiotensin-aldosterone system, and thermoregulatory system (20,31).
This neural control is closely linked to heart rate (HR) and baroreceptor reflex activity (28). From the afferent information, through a complex interaction of stimulation and inhibition, responses of the sympathetic and parasympathetic pathways modify HR to adapt it to the needs of each moment. The increase in HR is the consequence of the greater action of the sympathetic pathway and the lower parasympathetic activity (i.e., vagal inhibition) while the decrease in HR depends primarily on the predominance of vagal activity (18,28).
The heart is not a metronome and its beats lack the regularity of a clock, thus HR changes defined as heart rate variability (HRV) are normal. The HR changes indicate the heart's ability to respond to multiple physiological stimuli and environmental factors of which among them are breathing, physical exercise, mental stress, hemodynamic and metabolic alterations, sleep, and orthostatism (3,6). The regulation of the autonomic nervous system is directly related to the release of catecholamines, which is sensitive to different training stimuli and presents itself as an interesting tool in the identification of acute and chronic responses that result from different training stimuli.
The data obtained from the heart rate transcribe the physical and mental state from rest even at the end of the exercises. In this context, the analysis of heart rate variability, which consists of the oscillations of the intervals between consecutive heart beats (9), can be an efficient tool to understand the relationship between cardiovascular risk factors and the autonomic response. It is known that the parasympathetic activity may be suppressed and closely related to positive stress due to cardiometabolic complications (20,29).
Interestingly, this same activity can be stimulated by increased cardiorespiratory capacity and physical training (18). The HRV has been shown to be a useful tool for monitoring individual adaptations to a training program as well as for the treatment of disorders such as stress and anxiety (9). Psychological factors such as anxiety, mood, and self-confidence have a direct relationship with the performance of athletes and their inability to cope with sports situations, especially during the pre-competition in which the psychological reactions may occur that lead the athlete to failure. Thus, the purpose of this study was to correlate the HR variability and the state of self-confidence in elite canoeing athletes.
METHODS
Subjects
The study consisted of 34 male athletes with a mean age of 20.11 ± 4.82 yrs, height of 172.41 ± 9.12 cm, and body weight of 68.64 ± 10.1 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 an 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
This study was cross-sectional, descriptive, and correlational. The subjects maintained their training programs during the month preceding the research. The evaluation of self-confidence states was performed immediately before the heart rate variability test. The inventory 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.
Heart Rate Variability (HRV)
For heart rate variability (HRV) analysis, resting heart rate was recorded beat-to-beat by means of a heart rate monitor (Polar®, model RS800, Kempele, Finland), validated for the purpose of this study to determine R-R intervals (13). While the subjects breathed normally in the 30-min supine position, the electrode tape was positioned at the height of the xiphoid process of the sternum. The clock for capturing the information was fixed on the wrist, which kept the arms extended at the side of the body. All athletes were instructed to abstain from caffeine and physical activity for 24 hrs before the test and assessments were made in the morning to avoid possible circadian rhythm influences in an acclimatized room with a temperature of 25°C ± 1°C (13).
The data were recorded in the beat-to-beat mode in milliseconds, which was downloaded by infrared transmission to a portable computer from Polar Pro Trainer software (version 5.41.002). The method of data filtering followed two steps: (a) digital filtering through software used to download the data; and (b) manual filtering to visually check for variations between heart rate ranges that allowed for removing abnormal intervals (9,12). One thousand R-R intervals were used to analyze the data, which was calculated by the Kubios HRV software, version 2.0, the mean R-R (M-iRR) intervals and the heart rate variability index using the linear method, and in the time domain: rMSSD.
The rMSSD index corresponds to the square root of the mean of the successive squared differences between consecutive R-R intervals, in which it represents the predominance of the activity of the autonomic parasympathetic nervous system (18). The SDNN index reflects the participation of both branches of the autonomic nervous system (ANS), and represents the standard deviation of the mean of all normal R-R intervals, expressed in milliseconds (3). HRV undergoes transformations in fundamental oscillatory components in the frequency domain where the low frequency components (LF - 0.04 to 0.15 Hz) are analyzed, which is linked to the joint action of the vagal and sympathetic components with predominance of the sympathetic over the heart, high frequency components (HF - 0.15 to 0.4 Hz). The latter is an indication of the action of the vagus nerve on the heart. In addition, the LF/HF ratio is characterized by the sympathetic-vagal balance over the heart.
The spectral analysis is calculated using the Fourier. All measurements were taken with athletes wearing lightweight and barefoot clothing. The body weight was measured on a digital reading scale (Filizola®, Personal Line 200 model, Brazil) with an accuracy of 0.1 kg. The subjects’ stature was determined by a stadiometer fixed on the wall (Sanny®, Professional model, Brazil) with an accuracy of 0.1 cm.
Sport Self-Confidence Inventory
The Sport Self-Confidence Inventory (SCI) was used to evaluate the subjects’ level of self-confidence. The SCI (4,14) is composed of 14 items distributed in three subscales: (a) Self-Confidence in Physical Skills and Training (SPST); (b) Self-Confidence in Cognitive Efficiency (SCE); and (C) Resilience Self-Confidence (RS). The scale is composed of the following classifications:
7. Absolutely certain (absolute certainty that yes);
6. Practically right (almost certainly so);
5. Quite right (I think so);
4. Maybe (I have doubts);
3. Quite uncertain (I think not);
2. Practically uncertain (almost certainly not); and
1. I cannot do it at all (absolutely not).
Statistical Analyses
The results are presented as mean ± SD. Normality of the data was verified using the Kolmogorov Smirnov test. For the multivariate model, the rMSSD index underwent logarithmic adjustment (log10). Due to the use of some variables of parametric origin, Pearson's correlation was used to verify the relationship between the self-confidence inventory (SCI) and heart rate variability (HRV). Statistical significance was set at a P value less than 5% using the software SPSS 17 (SPSS Inc., Chicago, IL).
RESULTS
The descriptive results (mean ± SD) are shown in Table 1, which also includes the minimum and maximal body composition and levels of metabolic performance that characterize the athletes. Table 2 presents the variables of the Heart Rate Variability. Table 3 presents the results of the correlation analysis of the variables in the SCI with a heart rate variability of which there were significant correlations for the following variables: SPST with rMSSD (r=0.40; P=0.018) and SPST with HF (r= 0.39; P=0.02).
Table 1. Characterization of the Subjects.
Minimum / Maximum / Mean ± SDWeight (kg) / 71.9 / 87.2 / 68.64 ± 10.1
Height (cm) / 176.3 / 189.0 / 172.41 ± 9.12
HR Rest (beats·min-1) / 51.0 / 68.0 / 54.2 ± 6.72
VO2 Peak (L·min-1) / 3.8 / 4.8 / 4.19 ± 0.87
SPO2 (%) / 98.0 / 99.0 / 98.88 ± 0.21
Lactate Rest (mmol) / 1.2 / 2.7 / 1.98 ± 0.41
% Fat (%) / 10.7 / 10.4 / 9.22 ± 1.88
Table 2. Descriptive Data about Heart Rate Variability (HRV).
Minimum / Maximum / Average ± SDSPST (a.u.) / 19.0 / 35.0 / 29.42 ± 5.04
SCE (a.u.) / 16.0 / 28.0 / 23.57 ± 4.03
SR (a.u.) / 20.0 / 33.0 / 27.23 ± 4.18
SDNN (ms) / 30.2 / 130.6 / 87.43 ± 23.27
rMSSD (ms) / 16.9 / 94.40 / 53.64 ± 20.28
LF (Hz) / 10.5 / 65.20 / 35.20 ± 15.95
HF (Hz) / 34.4 / 89.20 / 64.48 ± 15.93
LF/HF (Hz) / 0.11 / 1.89 / 0.65 ± 0.49
SPST = Self-Confidence in Physical Skills and Training; SCE = Self-Confidence in Cognitive Efficiency; SR = Self-Confidence on Resilience; rMSSD = Square Root of the Mean of the Successive Squared Differences; LF = Low Frequency Components; HF = High Frequency Components; LF/HF = Ratio is characterized by the Sympathetic-Vagal Balance over the heart.
Table 3. Pearson Correlation between Heart Rate Variability (HRV) and Self-Confidence Inventory (SCI) Responses.
SDNN / rMSSD / LF / HF / LF/HFSPST (a.u.) / r=0.16 P=0.36 / r=0.40 P=0.01* / r=0.12 P=0.47 / r=0.39 P=0.02* / r=-0.27 P=0.12
SCE (a.u.) / r=0.04 P=0.81 / r=0.15 P=0.38 / r=0.07 P=0.68 / r=0.13 P=0.46 / r=-0.15 P=0.38
SR (a.u.) / r=0.06 P=0.70 / r=0.26 P=0.13 / r=-0.03 P=0.83 / r=0.28 P=0.09 / r=-0.13 P=0.43
SPST = Self-Confidence in Physical Skills and Training; SCE = Self-Confidence in Cognitive Efficiency; SR = Self-Confidence on Resilience; r = Correlation Value; and P = Significant; *Significant correlation for P<0.05; and **Significant correlation for P<0.01
DISCUSSION
The purpose of this study was to verify the possible correlations between a self-confidence inventory (SCI) and the heart rate variability (HRV) of Olympic slalom athletes. The main correlations were observed between self-confidence in physical skills and training (SPST, r=0.39; P=0.02) and HRV variables related to parasympathetic activity. The vagus nerve acting on the heart seems to help athletes control elevated levels of anxiety, which increases their expectations of achieving a high level of performance. Similarly, the rMSSD variable that indicates the predominance of the activity of the autonomic parasympathetic nervous system also showed a correlation between self-confidence in physical abilities and training (r=0.40; P=0.018).
It is known that with advancing age there is the tendency to decrease the vagal response with a decrease in HRV (12), but this behavior does not seem to be the case among young athletes (18,29,31). Numerous authors (1,15,22-25) have determined values associated with HRV normality, and they suggested reference values of 27 ± 12 ms and 8 to 24% for rMSSD and pNN50, respectively. In the present study, when the obtained indexes were analyzed, the canoeists presented higher values of rMSSD (53.64 ± 20.28 ms) compared to the reference values. The higher values are consistent with the athletes’ high level of conditioning that is linked to a predominant parasympathetic activity.
It should be noted that physical exercise has a modulatory role in cardiorespiratory capacity and, therefore, can delay the reduction in parasympathetic activity (1,5,6,10,19, 21,24,27). Physically active individuals have a lower resting HR that suggests a greater parasympathetic activity attributed to intrinsic adaptations of the sinus node itself or also due to other physiological changes such as an increased venous return and systolic volume as well as positive changes in myocardial contractility (10,16,17,26).
Training characterized by high intensities are extremely important components in the improvement of athletic performance (2,7,8,11). However, the choice of the highest percentage of the type of training is characterized by the specificity that the modality requires or even by the periodization training. In this way, physical and physiological adaptations are differentiated according to the type of training chosen (i.e., high intensity training and short duration training) that results in acute responses such as the production of blood lactate and hormonal activity of catecholamine’s and cortisol (32). Conversely, low intensity and long duration training tend to increase mitochondrial content and respiratory capacity of muscle fibers (25,30).