Applied Psychophysiology and Biofeedback

, Volume 37, Issue 2, pp 131–144

The Effect of Heart Rate Variability Biofeedback on Performance Psychology of Basketball Players

Authors

    • Department of Sports Medicine and PhysiotherapyGuru Nanak Dev University
  • Kanupriya Garg
    • Department of Sports Medicine and PhysiotherapyGuru Nanak Dev University
Article

DOI: 10.1007/s10484-012-9185-2

Cite this article as:
Paul, M. & Garg, K. Appl Psychophysiol Biofeedback (2012) 37: 131. doi:10.1007/s10484-012-9185-2

Abstract

Coping with pressure and anxiety is an ineluctable demand of sports performance. Heart rate variability (HRV) Biofeedback (BFB) shall be used as a tool for self regulating physiological responses resulting in improved psycho physiological interactions. For further analysis, the present study has been designed to examine the relationship between anxiety and performance and also effectiveness of biofeedback protocol to create stress-eliciting situation in basketball players. Thirty basketball players of university level and above (both male and female) aged 18–28 years, who scored a minimum of 20 in state trait anxiety inventory, were randomly divided into three equal groups- Experimental (Biofeedback) group, Placebo group and Control (No Treatment) group. The BFB group received HRV BFB training for 10 consecutive days for 20 min that included breathing at individual’s resonant frequency through a pacing stimulus; Placebo group was shown motivational video clips for 10 consecutive days for 10 min, whereas No Treatment Control group was not given any intervention. Two way repeated measure ANOVA was applied to analyze the differences within and between the groups. Anxiety, coping self-efficacy, heart rate variability, respiration rate, and performance (dribbling, passing and shooting) at session 1, 10 and 1 month follow up were statistically significant in each group along with interaction of group and time (p < 0.001). Also, all the measures showed statistically significant inter group difference (p < 0.05). The findings are harmonious with existing data on HRV BFB as a strategy for dealing with anxiety. The Placebo group showed improvement in self efficacy and performance post training. The Control group showed no change in any variable except performance. The results of the study support the idea that HRV BFB lowers the anxiety and thus there seems to be a potential association between HRV BFB and performance optimization.

Keywords

HRV BFBAnxietySelf-efficacyBasketballSTAIPerformance

Introduction

Heart Rate Variability

The term “Heart rate variability” (HRV) refers to the waveform of beat to beat changes in the duration of RR intervals (RRIs) (Lagos et al. 2008). Earlier HRV was analyzed by means of time and frequency domain techniques, referred to as spectral analysis. Time domain analysis provides measures such as standard deviation of Normal to Normal interval (SDNN). The frequency domain technique analyzes the frequency information obtained in the recording and result is shown on a power spectrum, which depicts a breakdown of all the frequencies (Very Low Frequency, Low Frequency and High Frequency). A new approach to HRV monitoring and feedback is the analysis of heart rhythm patterns which analyzes the varying shape of the HRV waveform (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996).

HRV analysis represents the most reliable and quantitative assessment of autonomic nervous system functioning (Sutarto et al. 2010). The heart rate may be increased by slow acting sympathetic activity or decreased by fast acting parasympathetic (vagal) activity. The balance between these systems produces an ongoing oscillation, an orderly increase and decrease in heart rate. Higher HRV indicates an optimal interplay between the sympathetic and parasympathetic nervous system and thus epitomize as an index of emotional expression (Lagos et al. 2008).

A healthy heart doesn’t beat with absolute regularity. A certain amount of variability is required so that it can adapt to life’s routine challenges. In recent years, potential prognostic value of HRV has been given forethought due to association between HRV parameters and several physical and psychological health problems. Reduced HRV is an indicator of cardiovascular problems, generalized anxiety disorder, panic disorder and post traumatic stress disorder (Wheat and Larkin 2010).

Techniques for Stress Management

A variety of relaxation techniques exist in the field of sport psychology for management of stress. When practiced regularly, techniques like deep breathing, visualization, progressive muscle relaxation, meditation and yoga negate the ill effects of stress and evokes a relaxation response, a state of deep rest and/or a functionally efficient relaxed state during performance. The psychophysiological symptoms of stress can also be relieved by cognitive training which includes positive self talk, mental rehearsal, mental imagery and visuo motor behavior rehearsal therapy (Lagos et al. 2008). Most of the methods focus on psychological symptoms of stress rather than addressing the imbalance of sympathetic and parasympathetic system in the body.

Training for psychological skills has become a widely accepted practice in the athletic setting now. Managing and improving performance of a player involves maintenance of systematic records and analysis of past performances through “evaluation” and “feedback” so as to discover his/her potential in pursuit of better performance.

The principle of training specificity by Zupan et al. (2006) states that athletes’ should train themselves as if they are competing in an event. Athletes when train like as if they are competing, impact their psychological processes on autonomic states of their body. Wilmore and Costill (2004) expands this concept further, the training program must stress the physiological systems that are critical for optimal performance in the given sport. This statement highlights and characterizes the concept that body system specificity has a direct link with actual sport task. When athletes’ train while considering themselves in pseudo competitive situations, there is an impact on their psychological processes in cognizance to the changes occurring in the autonomic states of their bodies.

Heart Rate Variability Biofeedback Training and Resonant Frequency

Efforts to identify effective treatment that target HRV and baroreflex function therefore are warranted. Biofeedback (BF) has been implemented as a method for altering physiological activity which in turn results in improved psychology and performance (Babiloni et al. 2008; Hammond 2007; Strack 2003).

Resonant properties in cardiovascular system result from heart rate baroreflex activity. Resonance frequency of an individual can be estimated as the highest amplitude of heart rate oscillations elicited by breathing (Hassett et al. 2007). The resonant characteristic of HRV is generated by paced breathing at a frequency of about 0.1 Hz (six breaths per minute). The 0.1 Hz is in the lower frequency band which reflects the autonomic control and action of baroreflex (Lehrer et al. 2006). Thus, when individuals breathe at their resonant frequency, high-amplitude oscillations in heart rate are elicited and the closed loop system of the baroreflex modulates the respiratory effects on HRV (Lehrer et al. 2003).

Breathing at one’s resonant frequency aims at producing maximal increases in respiratory sinus arrhythmia (RSA) amplitude. Variation in heart rate is accompanied by breathing (RSA) which is controlled by parasympathetic reflexes (Lagos et al. 2008). RSA usually occur in the frequency range of 0.15–0.4 Hz in a healthy adult (Lehrer et al. 2000).

Heart Rate Variability and Psychological Stressors

A variety of factors can cause increase in specific rhythms of heart including anxious thinking, breathing, emotions, pressure sensors (baroreceptors) in the arteries, and other physiological and behavioral changes (Lagos et al. 2008). Anxiety is important especially in a sporting context and in a team game such as basketball; it may be the determining factor between winning and losing. Anxiety is highly complex phenomenon acting within both the central nervous system and autonomic nervous system (especially cardiovascular and respiratory systems). It comprises of two different components: State and Trait anxiety. State anxiety is situational in nature, characterized by heightened autonomic nervous system activity whereas trait anxiety is a world view that an individual uses when coping with situations in his or her environment (Spielberger 1966).

Dealing with anxiety is especially important for an athlete, as an anxious athlete has trouble concentrating, focusing and in decision making (Wilson and Pritchard 2005). This results in detrimental performance and they seldom reach the desired result. Reduction in anxiety will be facilitated if one’s self efficacy is reinforced as anxiety is associated with low self efficacy (Nicholls et al. 2010). Self-efficacy is a powerful predictor for sports performance which is associated with the perceived ability to cope with fear or with anxiety-arousing events. Self-efficacy expectations are beliefs that one can successfully organize and execute the action required to produce particular outcomes (Anyadubalu 2010). Different individuals have distinct efficacy-related beliefs. One such belief refers to a person’s ability to excogitate strategies that will assist him/her in coping with various fears and stressors, which is referred to as Coping Self Efficacy (Nicholls et al. 2010). Treating anxiety will be more difficult when evaluation of self efficacy is associated with poor results and self assessments (Dehdari et al. 2008).

Basketball is a sport that requires great amount of physical energy and does not solely rely on physical abilities for performance success. For a basketball player to deliver a winning performance there is a firm need to cultivate strong psyche. In a game like basketball, where players often run up and down the court, heart rate is driven by physical demands on the court and also by their emotional intensity. Sometimes, even before they begin the competition, their heart rate is unusually high. So the aim of athletic performance training is to improve the cardiorespiratory efficiency thus, saving cardiac and respiratory energy and helping athletes to train according to their resonant frequency (Lagos et al. 2008). The physical fitness of basketball players and, consequently, game performance can be influenced by the balance in autonomic nervous system.

Thus, the current study is an attempt to further explore the effectiveness of HRV BFB on performance skills of anxious basketball players.

Methodology

Participants and Study Design

Thirty basketball players (Male = 17, Female = 13) ranging in age from 18 to 28 years (21.13 ± 2.82 years) were recruited from Amritsar who met the following inclusion criteria: (a) scored 20 and above on Spielberger state trait anxiety inventory (STAI), (b) has not received any kind of psychological intervention previously. There was no known medical or psychiatric diagnoses reported from the participants. The subjects represented a wide range of skills from university (46.66%), state (20%) to national (33.33%) standards. Ethical clearance was obtained from the Institutional Ethics Committee of Faculty of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar, India.

The study was experimental in nature with double blind study design.

The participants were randomly assigned into three equal groups (N = 10):
  1. 1.

    Experimental Group received Heart rate variability (HRV) biofeedback training (Male = 8, Female = 2; Mean Age: 21.1 years; University: 0.4%; State: 0.2%; National: 0.4%)

     
  2. 2.

    Placebo Group was shown motivational basketball visual clips (Male = 2, Female = 8; Mean Age: 20.6 years; University: 0.2%; State: 0.3%; National: 0.5%)

     
  3. 3.

    Control Group (No Treatment) did not receive any training (Male = 7, Female = 3; Mean Age: 21.7 years; University: 0.3%; State: 0.3%; National: 0.4%).

     

During the initial visit, players selected according to the inclusion criteria completed an informed consent, a demographic questionnaire, STAI and coping self efficacy scale. After filling the questionnaires; dribbling, passing and 3-min shooting tests were performed. Players were then fitted with plethysmographic sensor on the finger and abdominal strain gauge for baseline measures of HRV and respiration rate respectively. The study was conducted at the Sports Psychology Lab, Department of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar, India.

Pre and post recording of the following measures were done.

Psychological Measures

Anxiety was measured by STAI: It is an instrument used for identifying anxiety in adults. This questionnaire consists of two sets of 20 items each that are answered on a 4-point Likert scale. The first subscale measures state anxiety, and the second measures trait anxiety. The test–retest correlations for A- Trait scale ranges from 0.73 to 0.86 and 0.16 to 0.54 for A- State scale. The reliability coefficient for A-trait ranges from 0.86 to 0.92 and 0.83 to 0.92 for A- state scale (Spielberger et al. 1970) (Fig. 1).
https://static-content.springer.com/image/art%3A10.1007%2Fs10484-012-9185-2/MediaObjects/10484_2012_9185_Fig1_HTML.gif
Fig. 1

Intergroup comparison of state and trait anxiety for experimental, placebo and control groups

Self-Efficacy was measured by coping self-efficacy scale (CSES): It is a 26-item measure, with three higher-order dimensions: use problem-focused coping, stop unpleasant emotions and thoughts, and get support from family and friends. It is measured on 11-point scale, rating the extent to which the participants feel that they can perform behaviour important to effective coping. The CSES assesses the athletes’ confidence with regard to their coping strategies. Thus, a higher CSES score would suggest that a person is more confident in his or her ability to cope. The scale has adequate reliability with a Cronbach alpha of 0.95 (Chesney et al. 2006) (Fig. 2).
https://static-content.springer.com/image/art%3A10.1007%2Fs10484-012-9185-2/MediaObjects/10484_2012_9185_Fig2_HTML.gif
Fig. 2

Intergroup comparison of self efficacy for experimental, placebo and control groups

Physiological Measures

Heart rate variability and respiration rate were measured with the utilization of electrodes and a respiration strap connected to an encoder. These measures were recorded into a computer and analyzed by a specialized BFB software program (Biograph Procomp Infiniti 5.0 Thought technology Ltd., Canada) (Figs. 3 and 4).
https://static-content.springer.com/image/art%3A10.1007%2Fs10484-012-9185-2/MediaObjects/10484_2012_9185_Fig3_HTML.gif
Fig. 3

Intergroup comparison of total HRV, LF HRV and HF HRV for experimental, placebo and control groups

https://static-content.springer.com/image/art%3A10.1007%2Fs10484-012-9185-2/MediaObjects/10484_2012_9185_Fig4_HTML.gif
Fig. 4

Intergroup comparison of respiration rate for experimental, placebo and control groups

Performance Measures (Fig. 5)

https://static-content.springer.com/image/art%3A10.1007%2Fs10484-012-9185-2/MediaObjects/10484_2012_9185_Fig5_HTML.gif
Fig. 5

Intergroup comparison of dribbling, passing and shooting for experimental, placebo and control groups

Dribbling Test

The dribbling test was part of the Harrison Basketball Battery. It involves weaving in and around cones continuously for 30 s while dribbling the ball. Each cone successfully passed earned one point. The test–retest reliability coefficient of battery is 0.95 (Barrow and McGee 1979).

Passing Test

The Stubbs’ Ball Handling Test was utilized. On a vertical flat wall, three adjacent circles each one 30 cm in diameter were drawn at a distance of 160 cm from each other. The first circle was drawn at 151 cm above the floor, the second at 121 cm, and the third circle at 136 cm above the floor. The athlete stood behind a painted line located at 450 cm away from the wall. On the verbal signal “Ready, … Go” the athlete threw the ball towards the first circle using a chest pass, retrieved the ball and passed to the second circle, retrieved the ball and passed to the third circle, then retrieved the ball and passed to the second circle again, then to the first, second, third, etc. The athlete continued passing the ball to the three circles for 30 s consecutively. Each bounce, either inside the painted circle or on its perimeter, earns one point. According to Stubb, a validity coefficient of 0.74 was achieved when the ratings were correlated with best of two trials on the test (Barrow and McGee 1979).

Shooting Test

A 3-min shooting test was used. The participant was asked to execute as many shots as possible from any position on a marked perimeter of 366 cm radius from the hoop for 90 s. The participant was responsible for shooting and retrieving the ball himself. Each successful shot earned one point. Test–retest reliability has been reported at 0.91 (Weinberg et al. 1991).

Protocol

Group A: Experimental Group

The protocol designed by Lehrer et al. (2000) for HRV BFB training was implemented with the participants. Following the pre-test measurements, the subject sat with closed eyes in a chair for 5 min with hands resting on arm rest in a peaceful room before commencement of HRV biofeedback training. In the first session, the subject was asked to breathe at variable respiratory rates for about 2 min each (6.5, 6, 5.5, 5, 4.5 breaths/minute) for determination of resonant frequency. A “pacing stimulus”: a light display that moved up and down on the computer screen at the target respiratory rate was provided. The subject was instructed to breathe at that particular rate of stimulus. The resonant frequency was determined as the maximum point in the peak amplitude signal of the resonant frequency detection monitor on the biofeedback equipment. The subject was then asked to breathe at his resonant frequency and relax. The BFB sessions were given for 10 consecutive days for 20 min each. Throughout the training, the subject was instructed for natural shallow breathing, to avoid hyperventilation, as can be provoked by this technique. The feedback to the subject was given in the form of beat-to-beat heart rate and respiratory rate on the screen. In addition, the subject was taught breathing through pursed lips abdominal procedure to elicit high amplitude oscillations in heart rate at his resonant frequency to achieve a relaxed state.

Group B: Placebo Group

Subjects were shown motivational basketball video clips for 10 min daily for 10 days.

Group C: No Treatment Control Group

This group did not receive any training.

Players in all the three groups were allowed to continue with normal practice schedule.

Statistical Analyses

The data was statistically analysed using the Statistical Package for Social Sciences (SPSS)/16.0 (Copyright© SPSS Inc.). For examining the changes in the dependent variables on day one, day ten and 1 month follow-up along with inter-group comparison Two-way Repeated Measure ANOVA was used. Statistical significance was accepted at p ≤ 0.05. Tukey’s HSD post hoc comparison was conducted to study the intergroup differences and to provide specific information on associated variables (Table 1).
Table 1

Univariate ANOVA for pre experimental, placebo and no treatment control group

Measures

Pre

Sum of squares

df

Mean square

F

State anxiety

97.067

2

48.533

0.984NS

Trait anxiety

85.400

2

42.700

0.786NS

Self efficacy

1,955.400

2

977.700

1.878NS

Total HRV

731,752.958

2

365,876.479

1.045NS

LF HRV

5,945.262

2

2,972.631

0.074NS

HF HRV

335,268.092

2

167,634.046

2.074NS

Respiration rate

2.651

2

1.326

0.337NS

Dribbling

471.800

2

235.900

3.628**

Passing

8.267

2

4.133

0.467NS

Shooting

0.067

2

0.033

0.007NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

Results

Psychological Measures

The means and standard deviation for pre, post and follow up state anxiety for the three groups is shown in Table 2. Variation in state anxiety measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 66.503, p < 0.001). The inter-group difference in state anxiety was also statistically significant (F = 10.767, p < 0.001). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1(Experimental) and 2(Placebo) and group 1 and 3(Control); whereas no significant difference was found between group 2 and 3 (Table 2).
Table 2

Showing state anxiety in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

40.90 ± 7.66

21.40 ± 1.43

20.10 ± 1.28

2. Placebo

38.90 ± 5.95

38.70 ± 6.12

38.60 ± 6.15

3. Control

36.50 ± 7.33

36.40 ± 7.38

36.30 ± 7.34

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for state anxiety

 Time

942.200

2

471.100

70.652

<0.001*

 Time × group

1,773.733

4

443.433

66.503

<0.001*

 Error

360.067

54

6.668

  

Test of between subject effect

 Group

2,121.867

2

1,060.933

10.767

<0.001*

 Error

2,660.533

27

98.538

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

11.27

<0.001*

 Group 1 versus 3

8.93

<0.05**

 Group 2 versus 3

2.33

0.639NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

Similarly the means and SD for pre, post and follow up trait anxiety for the three groups is shown in Table 3. Variation in trait anxiety measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 157.573, p < 0.001). The inter-group difference in trait anxiety was statistically significant (F = 6.628, p < 0.05). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 3).
Table 3

Showing trait anxiety in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

45.30 ± 5.88

26.20 ± 2.89

25.40 ± 2.67

2. Placebo

41.30 ± 7.18

41.20 ± 7.13

41.10 ± 6.95

3. Control

42.40 ± 8.75

42.50 ± 8.84

42.40 ± 8.66

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for trait anxiety

 Time

855.356

2

427.678

160.157

<0.001*

 Time × group

1,683.111

4

420.778

157.573

<0.001*

 Error

144.200

54

2.670

  

Test of between subject effect

 Group

1,834.156

2

917.078

6.628

<0.05**

 Error

3,735.800

27

138.363

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

8.90

<0.05**

 Group 1 versus 3

10.13

<0.05**

 Group 2 versus 3

1.23

0.913NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

The means and SD for pre, post and follow up coping self efficacy for the three groups is shown in Table 4. Variation in coping self efficacy measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 79.688, p < 0.001). The inter-group difference in coping self efficacy was statistically non significant (F = 2.269, p = 0.123). Post hoc analysis using Tukey’s-HSD revealed statistically no significant difference between group 1 and 2, group 1 and 3 and group 2 and 3 (Table 4).
Table 4

Showing coping self efficacy in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

176.30 ± 31.67

223.30 ± 24.74

224.80 ± 25.71

2. Placebo

195.80 ± 14.14

196.40 ± 14.11

196.30 ± 14.15

3. Control

188.90 ± 18.93

188.80 ± 18.91

188.80 ± 19.01

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for coping self efficacy

 Time

5,166.022

2

2,583.011

81.943

<0.001*

 Time × group

10,047.778

4

2,511.944

79.688

<0.001*

 Error

1,702.200

54

31.522

  

Test of between subject effect

 Group

5,694.689

2

2,847.344

2.269

0.123NS

 Error

33,887.800

27

1,255.104

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

11.97

0.403NS

 Group 1 versus 3

19.30

0.107NS

 Group 2 versus 3

7.33

0.705NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

Physiological Measures

Paced stimulus breathing in response to rhythmical simulation of individual’s resonant frequency elicits high amplitude heart rate oscillations during HRV BFB training. When the participant breathes at or close to resonant frequency, the respiratory component is most prominent. Also, HRV and respiration are in phase with each other, that is, heart rate increases with inhalation and decreases with exhalation.

The means and SD for pre, post and follow up Total HRV for the three groups is shown in Table 5. Variation in Total HRV measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 20.850, p < 0.001). The inter-group difference in Total HRV was statistically significant (F = 6.610, p < 0.05). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 5).
Table 5

Showing total HRV in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

808.89 ± 817.73

2,224.11 ± 1,624.81

2,287.21 ± 1,641.80

2. Placebo

760.10 ± 482.32

760.05 ± 482.04

760.17 ± 482.16

3. Control

455.89 ± 386.51

455.75 ± 386.68

455.88 ± 386.47

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for total HRV

 Time

4,657,710.465

2

2,328,855.232

20.847

<0.001*

 Time × group

9,316,509.147

4

2,329,127.287

20.850

<0.001*

 Error

6,032,317.874

54

111,709.590

  

Test of between subject effect

 Group

2.855E7

2

1.428E7

6.610

<0.05**

 Error

5.832E7

27

2,159,910.664

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

1,013.29

<0.05**

 Group 1 versus 3

1,317.56

<0.05**

 Group 2 versus 3

304.26

0.705NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

The means and SD for pre, post and follow up LF HRV for the three groups is shown in Table 6. Variation in LF HRV measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 12.707, p < 0.001). The inter-group difference in LF HRV was statistically significant (F = 6.969, p < 0.05). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 6).
Table 6

Showing LF HRV in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

253.40 ± 219.30

1,220.10 ± 1,010.92

1,263.41 ± 1,027.79

2. Placebo

277.98 ± 140.97

277.86 ± 141.00

277.97 ± 140.90

3. Control

244.75 ± 227.45

244.78 ± 227.15

244.78 ± 227.16

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for LF HRV

 Time

2,173,803.014

2

1,086,901.507

12.706

<0.001*

 Time × group

4,347,964.257

4

1,086,991.064

12.707

<0.001*

 Error

4,619,404.576

54

85,544.529

  

Test of between subject effect

 Group

8,491,253.184

2

4,245,626.592

6.969

<0.05**

 Error

1.645E7

27

609,234.514

  

 Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

634.36

<0.05**

 Group 1 versus 3

667.53

<0.05**

 Group 2 versus 3

33.16

0.985NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

High frequency HRV decreases after the BFB training whereas it increases across the sessions. The means and SD for pre, post and follow up HF HRV for the three groups is shown in Table 7. Variation in HF HRV measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 17.193, p < 0.001). The inter-group difference in LF HRV was also statistically significant (F = 6.176, p < 0.05). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 7).
Table 7

Showing HF HRV in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

385.73 ± 463.24

669.29 ± 523.28

686.68 ± 534.86

2. Placebo

223.14 ± 113.76

222.89 ± 113.96

222.75 ± 113.92

3. Control

129.90 ± 122.29

129.88 ± 122.36

129.80 ± 122.12

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for HF HRV

 Time

189,807.883

2

94,903.942

17.125

<0.001*

 Time × group

381,115.324

4

95,278.831

17.193

<0.001*

 Error

299,258.986

54

5,541.833

  

Test of between subject effect

 Group

3,397,030.388

2

1,698,515.194

6.176

<0.05**

 Error

7,425,026.910

27

275,000.997

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

357.63

<0.05**

 Group 1 versus 3

450.70

<0.05**

 Group 2 versus 3

93.06

0.773NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

The means and SD for pre, post and follow up Respiration Rate for the three groups is shown in Table 8. Variation in Respiration Rate measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 202.989, p < 0.001). The inter-group difference in Respiration Rate was statistically significant (F = 41.874, p < 0.001). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 8).
Table 8

Showing respiration rate in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

15.30 ± 2.00

6.26 ± 0.26

6.00 ± 0.16

2. Placebo

15.23 ± 2.12

15.25 ± 2.09

15.33 ± 2.17

3. Control

14.64 ± 1.81

14.64 ± 1.75

14.83 ± 1.72

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for respiration rate

 Time

180.741

2

90.370

192.734

<0.001*

 Time × group

380.715

4

95.179

202.989

<0.001*

 Error

25.320

54

.469

  

Test of between subject effect

 Group

678.204

2

339.102

41.874

<0.001*

 Error

218.651

27

8.098

  

Comparison

Mean difference

p value

Post hoc analysis

Group 1 versus 2

6.08

<0.001*

Group 1 versus 3

5.51

<0.001*

Group 2 versus 3

0.56

0.721NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

Sport Performance Measures

The means and SD for pre, post and follow up dribbling for the three groups is shown in Table 9. Variation in dribbling measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 20.444, p < 0.001). The inter-group difference in shooting was also statistically significant (F = 14.181, p < 0.001). The post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 9).
Table 9

Showing dribbling in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

40.30 ± 10.75

50.40 ± 8.60

56.60 ± 8.24

2. Placebo

35.90 ± 6.35

37.00 ± 6.34

33.20 ± 12.40

3. Control

30.60 ± 6.25

32.60 ± 6.51

31.70 ± 6.12

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for dribbling

 Time

436.200

2

218.100

17.587

<0.001*

 Time × group

1,014.133

4

253.533

20.444

<0.001*

 Error

669.667

54

12.401

  

Test of between subject effect

 Group

5,076.267

2

2,538.133

14.181

<0.001*

 Error

4,832.633

27

178.986

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

13.73

<0.001*

 Group 1 versus 3

17.47

<0.001*

 Group 2 versus 3

3.73

0.534NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

The means and SD for pre, post and follow up passing for the three groups is shown in Table 10. Variation in passing measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 115.739, p < 0.001). The inter-group difference in shooting was also statistically significant (F = 9.860, p < 0.001). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 10).
Table 10

Showing passing in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

9.40 ± 3.02

16.60 ± 2.27

22.10 ± 2.13

2. Placebo

9.60 ± 3.62

11.90 ± 3.75

10.80 ± 4.07

3. Control

10.60 ± 2.06

12.00 ± 2.35

11.90 ± 2.72

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for passing

 Time

409.267

2

204.633

214.984

<0.001*

 Time × group

440.667

4

110.167

115.739

<0.001*

 Error

51.400

54

0.952

  

Test of between subject effect

 Group

488.267

2

244.133

9.860

<0.001*

 Error

668.500

27

24.759

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

5.27

<0.001*

 Group 1 versus 3

4.53

<0.001*

 Group 2 versus 3

0.73

0.837NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

The means and SD for the parameter of shooting at pre, post and follow up for the three groups is shown in Table 11. Variation in shooting measured over time (i.e. pre, post and follow up) was statistically significant in each group along with interaction of group and time (F = 82.620, p < 0.001). The inter-group difference in shooting was statistically significant (F = 15.206, p < 0.001). However the post hoc analysis using Tukey’s-HSD revealed statistically significant difference between group 1 and 2 and group 1 and 3; whereas no significant difference was found between group 2 and 3 (Table 11).
Table 11

Showing shooting in three groups

Group

Time of measurement

Pre

Post

Follow up

1. Experimental

5.30 ± 2.66

10.80 ± 2.34

14.70 ± 2.90

2. Placebo

5.20 ± 1.68

6.70 ± 2.11

6.00 ± 1.82

3. Control

5.30 ± 2.00

5.80 ± 2.04

5.70 ± 2.16

Test of within subject effect

Source

Sum of squares

df

Mean square

F value

p value

Two-way repeated measure ANOVA for shooting

 Time

198.022

2

99.011

125.507

<0.001*

 Time × group

260.711

4

65.178

82.620

<0.001*

 Error

42.600

54

0.789

  

Test of between subject effect

 Group

404.022

2

202.011

15.206

<0.001*

 Error

358.700

27

13.285

  

Comparison

Mean difference

p value

Post hoc analysis

 Group 1 versus 2

4.30

<0.001*

 Group 1 versus 3

4.67

<0.001*

 Group 2 versus 3

0.37

0.920NS

NS p > 0.05: not significant; * p < 0.001: highly significant; ** p < 0.05: significant

Discussion and Future Directions

The primary objective of the present study was to examine the oppugn of heart rate variability biofeedback (HRV BFB) as a stress coping tool. Application of biofeedback is pragmatic in helping an individual modulate his/her emotions. Biofeedback also monitors nervous system activation level to ascertain psychophysiological readiness of the body imperative for supreme performance (Jordanova and Demerdzieva 2010). The results of the present study indicate that the BFB group exhibited considerable reduction in state and trait anxiety post training as compared to placebo and no treatment control groups, this mitigation in psychological stress effect persisted at 1 month follow up also. The effect of reduction in anxiety could be attributed to regulation and stimulation of baroreflexes by breathing at one’s resonant frequency through HRV BFB technique.

The psychological states and processes can cause dramatic impact on autonomic control of the heart. Psychological stressors such as anxiety are often associated with an increase in sympathetic cardiac control, decrease in parasympathetic control, or both. Biofeedback induced effects on HRV indices and respiration rate helps to moderate the heightened sympathetic activity. Total and LF HRV increased post training and at follow up whereas decrease in HF HRV was observed post BFB training while it increased across the sessions for experimental group. Statistically non significant results were acknowledged for HRV parameters and respiration rate in placebo and no treatment control groups. The desired respiration rate of six breaths per minute was achieved in the experimental group after biofeedback training. The subject was trained to produce the smooth sinusoidal wave form (RSA) in which respiration rate and heart rate varies in phase with each other, that is, heart rate rises with inhalation and decreases with exhalation. Findings of physiological measures in the present study fortifies that the cardiovascular system has the property of resonance at a frequency near 0.1 Hz (six breaths per minute) consistent with preliminary studies (Lagos et al. 2008; Lehrer et al. 2003, 2006; Hassett et al. 2007).

Breathing at or near resonance frequency help subjects to change their tonic level of physiological arousal by increasing HRV amplitude, hence directly resulting in training and exercising the bodies’ own physiological control mechanisms (Sutarto et al. 2010). The HRV BFB training helps to restore the autonomic balance and improves autonomic control that supports emotional regulation and performance coordination (Lagos et al. 2008; Lehrer et al. 2003). The high amplitude oscillations stimulate and exercises autonomic reflexes, particularly the baroreflexes, thus restoring and regulating the balance between sympathetic and parasympathetic systems (Lehrer et al. 2003).

Sport psychologists suggest that motivational sphere of an athlete is a nucleus of his/her personality which should be given equal importance. However, an athlete’s performance suffers when their tension exceeds the capacity for maximal functioning. The potential interaction of specific stress responses like anxiety with performance has a debilitative effect. Thus, it is important for athletes to be able to control their anxiety to accomplish peak performance during training and competition. According to Humara (1999), athletes who score high on self efficacy interpret their anxiety as being facilitative instead of debilitative and they also achieve success more easily. The significantly improved scores of self efficacy suggest interesting finding as it indicates the fostering of self confidence in subjects of the experimental group. The potential interdependence between raised levels of self efficacy and self confidence with ability to cope with diverse threats and stressors may help the subject negate the deteriorating consequences of anxiety. Thus according to Anyadubalu (2010), it can be considered meaningful and impulsive for regulation of motivation.

Nicholls et al. (2010) suggested that Coping self efficacy beliefs undoubtedly put forth strong influences on situational appraisals and the manner in which any personage retort to these appraisals such as anxiety. The lowered state and trait anxiety could be attributed to restructuring of cognitive processes and lowered sympathetic arousal accomplished through HRV BFB training. This finding is also concluded by Dahlbeck and Lightsey (2008), who showed that high self efficacy, predicts lower anxiety and better psychological adjustment in an individual. Reduction in anxiety could also be ascribed to the attention and importance given to the subject during the HRV BFB procedure. During follow up interactions, the subjects appeared to be emotionally composed and felt greater control over their apprehensions. Placebo group also demonstrated statistically significant improvement in self efficacy due to visualization of motivational basketball videos.

Within the last decade, biofeedback practitioners have suggested that HRV BFB may be useful in increasing the performance of wrestlers, dancers, baseball players and golfers (Lagos et al. 2008; Raymond et al. 2005; Strack 2003). The improved sport performance in the experimental group, as indicated by the findings of the present study, could be attributed to the HRV BFB procedure eliciting resonance in the cardiovascular system. The HRV BFB training monitors autonomic nervous system homeostasis and reflects a positive psycho physiological shift. Basketball performance tests including dribbling and passing were established to be statistically significant for all the involved three groups post training. Shooting skill was significant for experimental and placebo groups post training while non significant for no treatment control group. At 1 month follow up, significant results were noticeable for experimental group for dribbling, passing and shooting. Improvement in performance for placebo and no treatment control groups could be due to the regular and consistent practice of their game during the study period.

It is apparent from the findings of the present study that HRV BFB training is a self regulatory intervention aimed at reducing psychophysiological stressors resulting in optimal performance. The cumulative effects of the psychosocial processes directly target the elevated sympathetic arousal, ultimately achieving the “flow state” of the mind which is imperative for peak performance (Jordanova and Demerdzieva 2010).

Future Directions

Different individuals gain knowledge of their specific game skills at different pace, and thus some players may not acquire and gain self-regulatory skills in ten sessions. Further research is warranted to assess the effects of HRV BFB over durations that would include more than ten sessions. Secondly, as individual biofeedback sessions were used in this study, it would be helpful to investigate the effects of the same intervention using group training sessions. The intervention may be more practical to implement if athletes learn the self-regulation skills in a group setting as it could be of great help to players involved in team sports. Third, the resonant frequency BFB procedure may be combined with relaxation imagery intervention so as to generate physiological and psychological domains more consistently and extensively. Also, future studies may aim at exploring the role of BFB relative to the advanced skills of the basketball players like rebounding, moving with and without the ball, position specific skills to bring into focus the necessary transition in the performance of the player.

Strength and Limitation of the Study

A major strength of the current study was inclusion of placebo group to compare and evaluate the efficacy of HRV BFB more specifically on the trained players. Previous studies which examined the effect of HRV BFB on sport performance did not incorporate the placebo conditions. Placebo group in this study helped in minimizing possible Hawthorne effects. Further, potential threats to the internal validity of the current study were addressed through random distribution of players into three equal groups. Inclusion of both male and female players with skills ranging from university, state to national standards ensures that findings are generalized for both gender and different levels of the game. Recording of the tested measures after a period of 1 month helped in the assessment of long term effects of HRV BFB on sports performance and predicted whether training effects remain consistent over time. Limitation of the present study was the small sample size and retrieving the ball himself/herself during shooting test that might influence the player’s performance during pre and post recording.

Conclusion

The existing study was sufficiently powered to examine the effect of HRV BFB on performance skills of anxious basketball players.

In spite of the limitations inherent in the present study, the findings of the study suggest that cardiac variability biofeedback (HRV BFB) training focalizes on simulating physiological requirements with psychological thus, helping athletes find their “zone of excellence”. An interesting finding which emerged from results of the present study was the improvement in the construct of self efficacy after the biofeedback training which was persistent even after a month. This suggests the profound influence of biofeedback on psychosocial processes which may serve as an index of sports performance. Thus, HRV BFB may serve as a powerful strategy in the area of sports psychophysiology for emotional and cognitive restructuring.

Continued research is required in the emerging field of HRV BFB as it may be incorporated with physical training to become an integral part of performance and rehabilitation psychology in contemporary sports medicine.

Copyright information

© Springer Science+Business Media, LLC 2012