Chapter 1 Introduction
1.3 Organization of this dissertation
This dissertation is composed of five chapters. Figure 1-1 illustrates the hierarchy associating different chapters.
In the beginning, Chapter 1 introduces the background and the aims of this research. To investigate the meditation effects on stress manipulation in psychological aspects, Chapter 2 presents our survey study administrating questionnaires to evaluate the perceived stress (depression, anxiety and stress/tension) of a large pool of college students. How meditation practice affects the perceived stress was examined by comparing the three psychological factors between college students with and without meditation practice in their daily lives.
In the physiological aspects, Chapter 3 focuses on the heart rate variability which can reflect the autonomic function. A laboratory-controlled experiment was designed and carried out. The heart rate variability was analyzed both in time and frequency domains and compared between experimental and control groups. In Chapter 4, we explored the cardiorespiratory phase synchronization which may be an indicator of good coordination between cardiac and respiratory systems. The synchrogram scheme and corresponding quantification method for measuring synchronization degree are introduced. Three synchronization parameters were defined to examine how meditation affects the cardiorespiratory phase synchronization.
The last chapter discusses the results and summarizes the findings of this study. This chapter concludes with our anticipation of future work.
Chapter 2 Perceived Stress
Chapter 3 Heart Rate Variability
Chapter 4 Cardiorespiratory Phase Synchronization psychological factors physiological factors
Discussion and Conclusion Chapter 5
Introduction Chapter 1
Figure 1-1. Chapter hierarchical structure.
Chapter 2－
Investigation of Meditation Effects on Perceived Stress
The effectiveness of short-term meditation practice on stress management has been proved in different groups of subjects including students, teachers, patients, etc. In the study of Shapiro et al. (1998), premedical students accepted an eight-week meditation-based stress-reduction intervention could effectively reduce anxiety and depression levels as well as increase empathy level and spiritual experiences. Winzelberg and Luskin (1999) reported that a four-week meditation training for the secondary-school teachers could effectively reduce their certain manifestations of stress except for anxiety. The study of Majumdar et al. (2002) showed that an eight-week mindfulness meditation program could effectively reduce psychological distress and increase well-being and quality of life for participants with chronic physical, psychological, or psychosomatic illness.
Our study focused on the group of college students and extended to investigate the effects of long-term meditation practice. This survey study thus focuses on the group of college students and mainly examines the effects of Chan-meditation practice on their perceived stress. Our survey involved two groups of participants, totally 541 college students.
Experimental/control group included subjects with/without Chan-meditation practice in their daily lives. To evaluate the perceived stress of participants, DASS questionnaire was used to measure their negative emotional states.
2.1 Stress problems of college students
In an annual survey report, Leo (2000) found that increasing numbers of college students were reported to feel overwhelmed and stressful. This indicates that stress becomes a more and more important issue on college campuses. The stress of college students was primarily related to academic, personal, and negative life events (Archer and Lamnin 1985; Li and Lin 2005). This general pattern of stress-producing incidents has remained relatively constant over the past 15 years in American college students (Murphy and Archer 1996). Students may need a certain level of stress to improve their performance. However, excess stress will negatively affect health, personality, and even academic performance. Especially, the level of stress experienced by college students has been documented as a predictor of suicidal ideation and hopelessness (Dixon et al. 1992). Hence, an effective method for college students to manage their stress in daily lives is valuable. Since college students are at the age of fast development of personality and life viewpoint, the stress may cause long-term, substantial effects on future life.
2.2 Survey study
2.2.1 Participants
Participants of this study involved 541 students from four universities (National Taiwan University, National Tsing Hua University, National Chiao Tung University and Chung Yuan Christian University) in Taiwan. The participants in the experimental group were the students with Chan-meditation experience. The participants in the control group were the students without any meditation experience. Their information is listed in Table 2-1.
Table 2-1. Participant information for experimental group and control group
Control Group Experimental Group
Number of participants 456 85
Sex (male : female) 350 : 106 57 : 28
Age (Mean ± SD years) 22.7 ± 2.3 23.1 ± 2.8
Education degree (under-graduates : graduates) 327 : 129 54 : 31
2.2.2 Intervention
The experimental-group participants all have learned the Chan-Buddhist meditation (see Appendix B) in the Chan club of their university. They attended a 90-minute weekly Chan-meditation program over an 8-week period, and afterwards continue the meditation practice in their daily life. In the Chan-Buddhist meditation, meditators sit in the full-lotus, half lotus, or free-style position with eyes closed. Two major techniques for a beginner to get into good-quality meditation are: (1) switching the breathing habit from chest to abdominal breathing so that the breathing becomes smoother, deeper, and quieter, and (2) focusing on some important spots like the Chan Chakra (inside the third ventricle), the Wisdom Chakra (corpora quadrigemina), or the Dharma-eye Chakra (hypophysis). They normally concentrate their mind on particular Chakra(s) in the beginning to release themselves from uncontrollable wild thoughts. Through Chan-Buddhist meditation, a practitioner seeks to attain the enlightened state of disclosing the internal spiritual power and wisdom.
2.2.3 Measures
Participants in both groups were requested to complete a Chinese version of the DASS (Depression Anxiety Stress Scales) questionnaire sheet (see Appendix C). The DASS (Lovibond and Lovibond 1995b) is a set of 42 items classified into three self-report scales capable of measuring the negative emotional states of depression, anxiety and stress/tension, respectively.
The DASS evenly distributes 42 items for these three negative emotional states, that is, 14 items for evaluating each state. As the scales of DASS have been shown to have high internal consistency and to yield meaningful discrimination both in clinical and non-clinical samples (Lovibond and Lovibond 1995a; Brown et al. 1997; Antony et al. 1998; Clara et al. 2001;
Crawford and Henry 2003), the scales should meet the needs of measuring current state of participants in three dimensions of depression, anxiety and stress/tension. However, it must be noted that the DASS Stress scale, originally labeled "tension/stress", measures the syndrome that is factorially (via confirmatory factor analysis) distinct from depression and anxiety characterized by nervous tension, difficulty in relaxing and irritability. It is narrower than the conventional conception of stress in terms of environmental events triggering a wide variety of emotional symptoms which probably incorporates all three DASS scales. Therefore, in most cases all three DASS scales are relevant to the assessment of stress in the broader sense.
Participants were asked to use 4-point scale (1: not at all, 2: some of the time, 3: a good part of time, and 4: most of the time) to rate the extent to which they had experienced the state described by each item over the past week. The recommended cutoffs for conventional severity labels (normal, mild, moderate, severe, and extremely severe) of each negative emotional state are provided in the DASS manual (Lovibond and Lovibond 1995b). It is helpful to characterize degree of severity relative to the reported statistics of general population.
On the questionnaire, experimental subjects were also requested to fill in (1) number of
continuously practicing years after their 8-week Chan-meditation training, (2) averaging duration (in minutes) of each meditation practice during the past three months, and (3) averaging number of meditation practices per week during the past three months.
2.2.4 Procedure
The DASS questionnaires were administrated to the participants in the beginning of the semester (in March, 2005). Participants in the experimental group filled out the DASS questionnaires in their club congregation. Control group included the students attending the speech held by Chan club in the beginning of the semester, and the DASS questionnaires were administrated to them before the speech began. Figure 2-1 illustrates the flowchart of applying the DASS questionnaires.
Filling out the DASS Questionnaire (15 minutes)
Getting back the questionnaires Explaining how to fill out the
DASS Questionnaire
Figure 2-1. Flowchart of applying the DASS questionnaires.
2.3 Results
The percentage of participants with respect to different severity labels of three DASS scales, according to the DASS scale cutoffs (see Appendix C) provided in the DASS manual, are presented in Table 2-2 for respectively the experimental group and control group.
Considering the Depression scale, 23% in the control group showed a depression level higher than “moderate”, which was only 2% in the experimental group. As regards the Anxiety scale, 38% of the control subjects had anxiety level higher than “moderate”, but only 19% of the meditation practitioners indicated their anxiety level higher than “moderate”. Finally, the Stress scale with level higher than “moderate” was declared by 17% of the control subjects and only 7% of the meditation practitioners. The results show that, in consideration of negative emotion, college students in Taiwan encounter the anxiety problem more than the depression and the stress. In addition, percentages of the students with all the three DASS scales at the level of “moderate” to “extremely severe” are all much lower in the experimental group than in the control group.
Table 2-2. Percentage of participants with respect to different severity labels of three DASS scales for the experimental group and control group
Control Group
(n=456) Experimental Group
(n=85)
Normal Mild Moderate Severe Extremely
Severe Normal Mild Moderate Severe Extremely Severe
Depression 55% 22% 17% 4% 2% 92% 6% 1% 1% 0%
Anxiety 52% 10% 26% 7% 5% 70% 11% 14% 4% 1%
Stress 50% 33% 12% 5% 0% 88% 5% 7% 0% 0%
Means and standard deviations of three DASS scales and their summation are presented in Table 2-3 for both groups. The summation of three DASS scales is labeled as “Total” which may present the stress level in the boarder sense. Student’s t test of the difference in means between two groups indicates that for all the three DASS scales and their summation, experimental-group means are significantly lower than those of the control group (Depression:
t(194)=9.14, p<0.001; Anxiety: t(132)=5.39, p<0.001; Stress: t(539)=9.92, p<0.001; Total:
t(138)=9.18, p<0.001). As a consequence, experimental group reveals significantly lower mean values on negative emotion than control group does.
Table 2-3. Means and standard deviations for DASS scales of experimental group and control group
Control Group (n=456)
Experimental Group (n=85)
M SD M SD
p-Value
Depression 9.26 6.75 4.45 3.88 0.000*
Anxiety 8.35 5.57 5.26 4.71 0.000*
Stress 14.28 6.06 7.25 5.65 0.000*
Total 31.88 16.47 16.95 13.19 0.000*
*Significantly different (p<0.001)
We further investigated the effect of three meditation factors (meditation experience, duration, and frequency) on the values of DASS scales. Table 2-4 lists the results of correlation coefficients between DASS scales and three meditation factors, respectively.
Except for the Depression scale, all the DASS scales are significantly negatively related to meditation experience, meditation duration, and meditation frequency. Under (p-value) statistical significance, the Depression scale only negatively correlates with meditation experience. Generally, more meditation experience, longer meditation duration, and higher meditation frequency allow the negative emotional level perceived by subjects to drop further.
Table 2-4. Correlation coefficients between DASS scales and three meditation factors Meditation experience
(years)
Meditation duration (minutes)
Meditation frequency (times/week)
Depression -0.224* -0.144 -0.193
Anxiety -0.241* -0.240* -0.227*
Stress -0.225* -0.222* -0.274*
Total -0.248* -0.223* -0.255*
*Significantly related (p<0.05)
To further study the effect of meditation experience, the experimental subjects were divided into four groups of four ranges of practicing years, 0.2-0.5 years, 0.5-1 years, 1-2 years, and above 2 years. Figure 2-2 illustrates the mean values of DASS scales for each group. Practitioners with 0.2-0.5yr meditation experience have smaller mean values of DASS Stress scale than that of control subjects (Depression: t(473)=1.51, p>0.05; Anxiety:
t(473)=0.23, p>0.05; Stress: t(473)=2.76, p<0.005; Total: t(473)=1.71, p<0.05). Accordingly, short-term meditation experience can be effective in reducing the level of stress/tension in
college students. As regards the DASS Depression and Anxiety scales, mean values of the practitioners with 0.5-1yr meditation experience are significantly smaller than that of control subjects (Depression: t(37)=6.15, p<0.001; Anxiety: t(481)=2.66, p<0.001). This results show that long-term meditation experience is necessary for reducing depression and anxiety.
0.00 10.00 20.00 30.00 40.00 50.00 60.00
Scale mean
control group 9.26 8.35 14.28 31.88
0.2-0.5(years) 6.89 8.05 10.37 25.32
0.5-1(years) 4.48 5.44 7.85 17.78
1-2(years) 3.28 4.06 6.11 13.44
2(years)- 3.19 3.52 4.62 11.33
Depression Anxiety Stress Total
*
**
***
***
Figure 2-2. Mean values of DASS scales with respect to different meditation experience (years) range of participants in experimental group. There are 19 participants for 0.2-0.5 years, 27 participants for 0.5-1 years, 18 participants for 1-2 years, and 21 participants for above 2 year. The Mean values of DASS scales of control group are also shown here. Significant difference are noted by * for p<0.05, ** for p<0.005, and *** for p<0.001.
Chapter 3－
Heart Rate Variability in Chan Meditation
In regard to the significance of heart rate variability (HRV) in cardiovascular and autonomic functions, various interventions were studied to discover the way to regulate it.
White (1999) studied the effects of relaxing music on HRV and found relaxing music could decrease the heart rate and increase the high-frequency HRV. Lehrer et al. (2000) developed a biofeedback system which could help practitioners to induce a resonant RSA (respiratory sinus arrhythmia) by slow breathing. Tiller et al. (1996) found that positive emotions could alter the HRV and lead to either the entrainment or internal coherence mode of heart function.
Other mechanisms like yoga (Raghuraj et al. 1998), qigong (Lee et al. 2002) and meditation were also studied.
As introduced in Section 1.2, phenomenon of the HRV during various meditation techniques has been reported. However, most of these techniques emphasized the skill of slow breathing (<0.15Hz). This chapter reports our study on HRV during Chan-meditation which emphasizes inward attention. We analyzed the HRV both in time and frequency domains.
3.1 Introduction to ECG signal
Heart can beat by itself at a regular rhythm due to a specialized conducting system. The system comprises four parts, as shown in Fig. 3-1, SA node (sinoatrial node), AV node (atrioventricular node), Bundle of His, and Purkinje fibers. The SA node, locating in the right
Figure 3-1. The conducting system of the human heart. (Modified from Shepherd 1988).
atrium of the heart, is the pacemaker that controls the heart rate. Depolarization waves are generated by SA node and propagate to atria, AV node, and ventricles. When depolarization waves propagate to atria, they make the atria contract. These waves afterwards spread to AV node that connects with Bundle of His. Purkinje fibers are the extended parts of Bundle of His.
The networking of Purkinje fibers appears to be a threadlike net on subendocardial surface.
Therefore, through Bundle of His, depolarization waves spread to entire ventricles and make two ventricles contract at the same time. In sum, the pathway of cardiac electrical conduction is: SA node → atria → AV node → Bundle of His → Bundle branches of His → Purkinje fibers → ventricles (Shepherd 1988).
The depolarization waves not only spread throughout the whole heart, but also induce the electrical current change that can be non-invasively recorded on the body surface as the
electrocardiogram (ECG) signal. Without stimulation, the heart cells are in the quiescent state (approximate -80 mV) with negative potential (so-called polarization). Once being stimulated, they bear positive potential and the systole reaction is induced. Hence, ECG reflects the potential variation of cardiac cycle of the heart. The typical wave complex of ECG is shown in Fig. 3-2. Each ECG complex correlates to the particular task of the cardiac cycle as described below:
1. P wave: The wave is due to the depolarization of atria. Atria contract at this time.
2. Q wave: The wave is caused by the depolarization of ventricles, and the R wave follows. Atria relax at this time.
3. R wave: The period of the depolarization of ventricles. Atria relax gradually, and ventricles start to contract at this moment.
4. S wave: The period of the depolarization of ventricles. Atria completely expand, and ventricles completely contract.
5. T wave: This wave is due to the repolarization of ventricles. Ventricles expand gradually.
Figure 3-2. The typical wave complex of ECG.
3.2 Introduction to heart rate variability
3.2.1 Autonomic nervous system and heart rate variability
The autonomic nervous system (ANS) is a control system responsible for maintaining the homeostasis in the body. Autonomic nervous system involves the sympathetic nervous system and parasympathetic nervous system. They are distributed to smooth muscles, cardiac muscles, and glands (see Fig. 3-3). The ANS affects bodily involuntary functions such as heart rate, blood pressure, respiratory rate, and digestion, etc. Most autonomic functions are controlled through the interaction between sympathetic and parasympathetic nerves in a counterbalance way, few (e.g., adrenal medulla) are controlled by only one of these two branches of ANS. In general, the sympathetic nervous system is responsible for the stress response when you encounter a stressor, and the parasympathetic nervous system is responsible for the relaxation response when the stressor has disappeared.
As mentioned in Section 3.1, the heart rate is controlled by the SA node. The SA node has an inherent constant firing rate of about 100 times per minute (Vander et al. 1994). This firing rate is modulated by the ANS that is mediated by the sympathetic and parasympathetic nerves innervated onto the SA node (see Fig. 3-4). The autonomic control over SA node may increase (via the sympathetic nerves) or decrease (via the parasympathetic nerves) the heart rate, according, causing fluctuations in heart rate. This fluctuation (change of beat-to-beat intervals) in heart rate is named as HRV. It reflects the modulation of ANS on heart rate.
Clinical application of HRV was first reported in 1965 by Hon and Lee. The reduction in HRV has been found to be correlated with several diseases (Hon and Lee 1965; Ewing et al. 1985;
Kleiger et al. 1987; Singh et al. 1998; Bilchick et al. 2002).
Sympathetic nerves Parasympathetic nerves
Spinal cord Brainstem
Spinal cord Brainstem
Figure 3-3. Organization of the autonomic nervous system: the sympathetic (left) and parasympathetic (right) branches. (Modified from Shepherd 1988).
Figure 3-4. The autonomic innervations of the heart. (Modified from Shepherd 1988).
3.2.2 Methods for analyzing heart rate variability
A number of methods have been developed for analyzing the HRV. These methods can be grouped into two categories: linear and nonlinear. Linear methods involve time domain analysis and frequency domain analysis. In the time domain analysis, the intervals between successive normal heartbeats should be determined. In the ECG signal, each R peaks is detected, and the so-called normal-to-normal (NN) intervals (that is all intervals between adjacent R peaks of heartbeats resulted from sinus node depolarization) are determined. Then the time domain parameters such as the mean of NN intervals, the standard deviation of NN intervals (SDNN), the root-mean-square of differences between adjacent NN intervals (RMSSD), etc (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996) can be calculated. These parameters are generally derived over 24-hour long-term recordings, or over short-term recordings using a 5-minute window. In the frequency domain analysis, constructed sequences of the NN intervals can be analyzed by Fast Fourier Transform (FFT) or autoregressive model. Similar to the time domain analysis, frequency domain analysis can be applied to either 24-hour long-term recordings or 5-minute short-term epochs extracted from the entire recordings. In the short-term analysis, three main spectral components have been found to reveal physiological correlation: very low frequency (VLF, 0.003-0.04 Hz), low frequency (LF, 0.04-0.15 Hz), and high frequency (HF, 0.15-0.4 Hz), as shown in Fig. 3-5(a). In the long-term analysis, researchers have been also interested in an ultra-low-frequency (ULF) component slower than 0.003 Hz (Fig. 3-5(b)), in addition to VLF, LF, and HF components.
Methods based on the nonlinear model or hypothesis include Poincaré plot (Brennan et al. 1998; D’Addio et al. 1999), Lyapounov exponents measurement (Pierro et al. 1998), 1/f behavior (Lessard et al. 1999), approximate entropy measurement (Gu et al. 2000), and Geometrical methods (Woo et al. 1992), etc. Nonlinear methods provide a feasible tool to
explore the nonlinear mechanisms underlying the HRV. However, nonlinear methods for HRV analysis still require further studies to obtain meaningful interpretation and reliable application in medicine.
(a) (b)
Figure 3-5. Power spectral examples of NN-interval sequences derived from (a) a 5-minute ECG and (b) a 24-hour ECG (The Y axis is power in log). (Modified from Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996).
3.2.3 Physiological correlates of HRV spectral components
With power spectrum analysis, the fluctuations of heart rate are divided into four frequency bands (ULF, VLF, LF, and HF) which correspond to different physiological phenomena (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996). The high-frequency (HF, 0.15-0.4 Hz) and low-frequency (LF, 0.04-0.15 Hz) components are the two that are better understood and
With power spectrum analysis, the fluctuations of heart rate are divided into four frequency bands (ULF, VLF, LF, and HF) which correspond to different physiological phenomena (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996). The high-frequency (HF, 0.15-0.4 Hz) and low-frequency (LF, 0.04-0.15 Hz) components are the two that are better understood and