Effects of Heart Rate Variability Biofeedback on Enhancing Self-Efficacy, Quality of Life and Six-Minute Walking Test in Patients with Chronic Obstructive Pulmonary Disease

doi:10.21203/rs.3.rs-5107134/v1

Objective

Heart rate variability biofeedback (HRVB) is a psychological intervention applied to patients with chronic obstructive pulmonary disease (COPD), and improves their autonomic activation and pulmonary function. This study explored the effects of HRVB on self-efficacy, quality of life, depression, anxiety, and heart rate variability (HRV) indices under the Six-Minute Walking Test (6MWT) in patients with COPD.

Methods

A total of 53 patients with COPD were assigned to either an HRVB group (n = 26) or a control group (n = 27), both received standard medical care. The HRVB group also participated in one hour weekly for six weeks. All participants completed assessments using the COPD Self-Efficacy Scale, St. George's Respiratory Questionnaire, Beck Depression Inventory-II, and Beck Anxiety Inventory pre-test and post-test. The 6MWT was administered to measure HRV during baseline, walking, and recovery stages.

Results

Significant improvements in self-efficacy and quality of life for the HRVB group, with a significant increase in post-test compared to pre-test and the control group. Additionally, the HRVB group exhibited a significant decrease in HRV reactivity and increased HRV recovery at the post-test compared to the pre-test.

Conclusion

These findings indicated that HRVB effectively enhances self-efficacy and quality of life in patients with COPD while improving autonomic function. Therefore, HRVB could be a valuable component of pulmonary rehabilitation for patients with COPD.

Chronic Obstruction Pulmonary Disease

Heart Rate Variability Biofeedback

Self-Efficacy

Quality of Life

Six-Minute Walking Test

Chronic obstructive pulmonary disease (COPD) is caused by various factors, including an increase in e-cigarettes, household or environmental air pollution, and exposure to inhalable dust in occupational settings (World Health Organization, 2024). Intervention programs for patients with COPD typically include routine medical care, pulmonary rehabilitation, physical activity, weather and environmental conditions monitoring, emotion regulation, and maintenance of a healthy lifestyle (Global Initiative for Chronic Obstructive Lung Disease, 2024).

Self-efficacy, a concept developed by the psychologist Albert Bandura, refers to an individual’s belief in their ability to perform a specific task or achieve a goal successfully. In patients with COPD, high self-efficacy indicates greater confidence in managing various aspects, such as shortness of breath, fatigue, flare-ups, seeking medical help, adhering to treatment plans, engaging in appropriate physical activities, and maintaining lifestyle changes. According to Bandura’s (1997) theory of self-efficacy, factors such as enactive mastery experiences, vicarious experiences, verbal persuasion, and physiological and affective states influence self-efficacy (Bandura, 1997). Therapists can enhance self-efficacy by providing education and building strong therapeutic alliances (Tsai & Chen, 2013). Previous studies have shown that high self-efficacy has fewer negative effects and a lower likelihood of experiencing dyspnea, exacerbations, or complications (Simpson & Jones, 2013). Yi et al. (2021) found that increased self-efficacy positively affected self-confidence, quality of life, and prognosis in patients with COPD. Moreover, self-efficacy acts as a moderating variable between pulmonary function (forced expiratory volume in one second, FEV1), symptoms, and quality of life. Poor pulmonary function, more severe symptoms, and lower self-efficacity are associated with poor quality of life (Kohler et al., 2002). Selzler et al. (2020) meta-analysis also found a positive relationship between health-related quality of life and self-efficacy, including exercise barrier self-efficacy, COPD symptoms, exercise tasks, and general self-efficacy.

Regarding negative emotions in patients with COPD, a systematic review and meta-analysis found the prevalence of depression in COPD (27.10%) was significantly higher than in non-COPD individuals (10.00%), with the incidence of depression among COPD patients being 3.74 times greater than that in the control group (Matte et al., 2016). A prevalence study based on the National Health Insurance Research Database in Taiwan reported that 4.10 % of patients with COPD experienced comorbid depression (Fu, 2015), and 9.13% suffered from anxiety disorders (Hsieh et al., 2016). The prevalence of anxiety among patients was 2.22 times higher than that in the control group (Hsieh et al., 2016). A systematic review found the prevalence of anxiety disorders among inpatients with COPD ranged from 10% to 55% (median, 17%), whereas it ranged from 13% to 46% among outpatients with COPD (Willgoss & Yohannes, 2013). Negative emotions can exacerbate dyspnea, hinder adherence to medical regimens, decrease exercise tolerance, cause acute exacerbation, and increase rates of hospitalization or mortality (Dua et al., 2018; Vikjord et al., 2020; Zareifopoulos et al., 2019). Our previous study found that anxiety mediates the relationship between autonomic nervous system activity and quality of life in patients with COPD, indicating that higher sympathetic activation and anxiety are associated with poor quality of life (Wu et al., 2022).

Previous studies have shown that patients with COPD experience autonomic nervous system (ANS) dysregulation and reduced heart rate variability (HRV; Carvalho et al., 2011; Gunduz et al., 2009; Rossi et al., 2014; Vanzella et al., 2018; Wu et al., 2022; Zupanic et al., 2014). Heart rate variability biofeedback (HRVB) is a non-pharmacological treatment that includes resonance frequency, slow diaphragmatic, and pursed lip breathing (Lehrer et al., 2000, 2013). Previous studies have confirmed that HRVB alleviates dyspnea (Wu et al., 2024; de Souto Barbosa et al., 2023) and increases HRV indices (Giardino et al., 2004; Huang, 2015). Furthermore, it enhances exercise tolerance (Giardino et al., 2004; Huang, 2015) and improves the quality of life (de Souto Barbosa et al., 2023; Giardino et al., 2004; Huang, 2015) in patients with COPD. Giardino et al. (2004) conducted a pilot study with 20 stable patients with COPD. They found significant improvements in exercise tolerance as measured by the six-minute walking test (6MWT), COPD Self-Efficacy Scale scores, and dyspnea assessed by the Borg Scale. In Taiwan, Huang (2015) conducted a randomized controlled trial involving eight HRVB sessions in 36 patients with COPD. After HRVB training, patients showed significant improvements in quality of life, as measured by the 12-item Short Form Health Survey-Mental Health Component Summary (SF 12- MCS), exercise tolerance via the 6MWT, HRV indices, and a decrease in depression, as assessed by the Hospital Anxiety and Depression Scale. More recently, de Souto Barbosa et al. (2023) applied the HRVB to nine patients with COPD in Brazil, and their results also showed significant improvements in quality of life, dyspnea, depression (BDI-II), and anxiety (BAI). Although these results confirmed positive outcomes after HRVB in patients with COPD, Giardino et al. (2004) and de Souto Barbosa et al. (2023) had small sample sizes and signal-group designs, limiting their findings' generalizability. A randomized controlled trial with two active control groups was conducted in Huang's study. However, it is an unpublished master's thesis without peer review, which may limit its applicability. This study aimed to address these limitations by increasing the sample size, including a control group, and examining the effects of the HRVB on self-efficacy, quality of life, depression, and anxiety, as well as autonomic function during the 6MWT in patients with COPD.

Participants

Patients with COPD were diagnosed and referred by a physician from the Department of Thoracic Medicine of Kaohsiung Municipal Siaogang Hospital, Kaohsiung City, Taiwan. The inclusion criteria based on the Global Initiative for Chronic Obstructive Lung Disease (2024) were: (1) Exposure to risk factors for COPD. (2) Presence of respiratory symptoms such as difficulty breathing, coughing, or sputum production. (3) A forced expiratory volume in the first second (FEV1) to forced vital capacity (FVC) ratio (FEV1/FVC ratio) < 70%. (4) Age between 40 and 80 years.

The exclusion criteria were as follows: (1) Presence of other lung diseases (e.g., asthma or lung cancer), heart disease (e.g., arrhythmia or pacemaker), cognitive impairment, seizures, or severe mental disorders. (2) Employment with shifts. (3) Unstable vital signs at rest, defined as systolic blood pressure ≥ 150 mmHg, heart rate ≥ 110 bpm, and oxygen saturation (SpO2) < 90%.

This study included 65 patients with COPD who completed the pre-test and were assigned to the HRVB (n = 30) and control groups (n = 35), with participants matched by age and sex. A total of 53 participants completed the post-test (26 in the HRVB group and 27 in the control group). A total of 12 participants were excluded from data analysis because of electrocardiogram (ECG) artifacts (n = 8) or dropout (n = 4). Detailed participant information has been published in our previous study (please see Wu et al., 2024).

The institutional review board of Kaohsiung Medical University Hospital, Kaohsiung City, Taiwan, approved this study (Approval No.: KMUHIRB-F(II)-20200060). Informed consent was obtained from all participants before the study began. After completing all study procedures, the participants received a gift card (approximately USD 20) for six visits in the HRVB group and a gift card (approximately USD 7) for the pre-test and post-test measurements in the control group.

Measurements

Demographic data (age and sex), smoking years and status, Global Initiative for Chronic Obstructive Lung Disease (GOLD) ABE Assessment Tool, COPD Self-Efficacy Scale (CSES), St. George's Respiratory Questionnaire (SGRQ), Beck Depression Inventory-II (BDI-II), and Beck Anxiety Inventory (BAI) were collected at both pre-test and post-test. After completed the psychological questionnaires, the 6MWT was conducted under baseline, walking, and recovery stages, and Borg Rate of Perceived Exertion Scale (Borg Scale) was measured under these three stages.

(1) GOLD ABE Assessment Tool was classified participants into three subgroups using the Modified Medical Research Council Dyspnea Scale (mMRC) and exacerbation history. Group A: mMRC score < 2, and 0 or 1 moderate exacerbation not leading to hospitalization in the past year. Group B: mMRC score ≥ 2, and 0 or 1 of moderate exacerbations, and not leading to hospitalization in the past year. Group E: mMRC score ≥ 2, and moderate exacerbations or ≥ 1 leading to hospitalization in the past year (Global Initiative for Chronic Obstructive Lung Disease, 2024).

(2) Chronic Obstructive Pulmonary Disease Self-Efficacy Scale was developed by Wigal et al. (1991) and was used to assess self-efficacy in patients with COPD. The CSES comprises 34 items rated on a Likert scale and includes five subscales: 12-item for negative affect, 8-item for intense emotional arousal, five-item for physical exertion, 6-item for weather/environment, and three-item for behavioral risk factors. The total score ranged from 34 to 170, with higher scores indicating greater self-efficacy.

Chiang et al. (2011) translated the Chinese version of CSES and used in Hong Kong. Its internal consistency reliability (Cronbach’s alpha) was .95, with a two-week rest-retest reliability of .91 (p < .001). In a sample of 30 COPD patients, the criterion-related validity between the CSES and the SGRQ was − .66 (p < .001). In this study, the CSES was translated into traditional Chinese and examined for internal consistency and reliability (Cronbach’s alpha) in 53 patients with COPD. Cronbach’s alpha was .98 for total scores, .95 for negative affect, .93 for intense emotional arousal, .90 for physical exertion, .88 for weather/environment, and .87 for behavioral risk factors. The six-week test-retest reliabilities were .93 (p < .001) for the total score, .91 (p < .001) for negative affect, .90 (p < .001) for intense emotional arousal, .94 (p < .001) for physical exertion, .92 (p < .001) for weather/environment, and .82 (p < .001) for behavioral risk factors. The criterion-related validity between CSES and SGRQ was r = − .30 (p = .031). These results indicate strong psychometric properties of the CSES.

(3) St. George’s Respiratory Questionnaire was developed by Jones et al. (1992), and was used to assess the impact of COPD-related dyspnea on daily life. The SGRQ contains 50-item on a Likert scale and three subscales: eight-item assessing respiratory symptoms, 16-item measuring activity limitations in daily life, and 26-item evaluating the impact of illness. The total SGRQ score ranges from 0–100%, with higher scores indicating a poor quality of life and lower scores indicating a better quality of life. A score higher than 25% is considered the cutoff for poor quality of life (Global Initiative for Chronic Obstructive Lung Disease, 2024). The Chinese version of the SGRQ was translated by David et al. (2004) for use in Hong Kong. The two-week rest-retest reliability ranged from .70 to .86, and the internal consistency reliability ranged from .74 to .98. The SGRQ and 36-item Short Form Health Survey (SF-36) validity ranged from .33 to .92.

In this study, the SGRQ was translated into traditional Chinese, and its internal consistency reliability (Cronbach’s alpha) was assessed in 53 patients with COPD. Cronbach’s alpha was .91 for the total score, .76 for symptoms, .87 for activity, and .85 for impact. The six-week rest-retest reliability (n = 27) was .88 (p < .001) for the total score, .88 (p < .001) for symptoms, .92 (p < .001) for activity, and .83 (p < .001) for impact. The validity of the SGRQ and BODE index in this study was r = .51 (p < .001). These results confirmed the strong psychometric properties of the SGRQ.

(4) Beck Depression Inventory-II comprises 21 items on a Likert scale designed to evaluate depressive symptoms, including somatic and cognitive depression subscales. The total BDI-II score ranges from 0 to 63, with higher BDI-II scores indicating more severe depressive symptoms. A total score below 13 indicated normal depression, 14–19 indicated mild depression, 20–28 indicated moderate depression, and ≥ 29 indicated severe depression (Beck et al., 1996). The Chinese version of the BDI-II, translated by Chen (2000), has demonstrated strong psychometric properties, including a Cronbach’s alpha of 0.94, split-half reliability of 0.91, and a correlation of 0.69 with the Chinese Health Questionnaire of 0.69 (Lu et al., 2002).

(5) Beck Anxiety Inventory comprises 21-item on a Likert scale to evaluate anxiety symptoms. It includes subscales assessing somatic and cognitive anxieties. The total BAI score ranges from 0 to 63, with higher scores indicating more severe anxiety symptoms. A total score below 7 indicated normal anxiety, 8–15 indicated mild anxiety, 16–25 indicated moderate anxiety, and ≥ 26 indicated severe anxiety (Beck et al., 1988). The Chinese version of BAI, translated by Lin (2000), has shown good psychometric properties, with a Cronbach’s alpha of .95, split-half reliability of .91, and a correlation of .72 with the Hamilton Anxiety Scale of 0.72 (Che et al., 2006).

(6) Six-Minute Walking Test was used to measure the exercise capacity for patients with COPD. Based on the guidelines and manual of the American Thoracic Society (ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories, 2002), participants were asked to walk at a fast pace for 6 minutes along a flat corridor. This study based on the Vagal tank theory (Laborde et al., 2018) to examine the HRV changes from resting baseline to walking (HRV reactivity), and from walking to recovery (HRV recovery). Therefore, ECG data was collected under resting baseline, walking, and recovery using the ProComp Infiniti version 6.0 with ECG sensor with 2048 Hz/s sampling rate (Thought Technology, Montreal, QC, Canada) at baseline and recovery stages. The Zephyr BioHarness™ with 250 Hz/s sampling rate (Zephyr Technology Corp., Annapolis, Maryland, USA) attached to chest strap and transfer to smartphone via Bluetooth during walking stage.

(7) The Borg Rate of Perceived Exertion Scale was developed by Dr. Gunnar Borg and is used to rate how hard individuals feel they are exerting themselves during baseline, walking, and recovery stages of the 6MWT (Borg, 1982). The Borg Scale typically ranges from 0 (nothing at all) to 10 (maximum exertion).

Heart Rate Variability Biofeedback Training Equipment

During the HRVB training, a ProComp Infiniti version 6.0 (Thought Technology, Montreal, QC, Canada) with a lead II ECG sensor (sampling rate: 2048 Hz/s) and a respiration sensor (sampling rate: 256 Hz/s) were placed on the participants’ chests to collect raw ECG and respiration signals. During the home practice, a wearable Eureka device with a photoplethysmography (PPG) sensor (Finesse Lifecare Co., Ltd., Taiwan) was placed on participants’ earlobes and connected to a smartphone via Bluetooth. The accompanying breathing app guided patients to slow their breathing rate and provided feedback after the home training.

Research Design and Experimental Procedure

A two-factor mixed design encompassing a between-participants design (comparing the HRVB and control groups) and a within-subjects design (pre-test and post-test). Patients completed the psychological questionnaires, and a research assistant ensured that patients’ vital signs were stable (SBP < 150 mmHg, heart rate < 110 bpm, and SpO2 ≥ 90%). Raw ECG signals and breathing rates were recorded using a lead II ECG and respiration sensor under the resting baseline at pre-test and post-test, during the 6MWT, and during the HRVB training period. This study primarily focused on the effects of the HRVB on psychological characteristics.

Heart Rate Variability Biofeedback Protocol

This study implemented Lehrer's HRVB protocol (Lehrer et al., 2000, 2013), with modifications based on our prior clinical studies: (1) To accommodate the aging patients and their dyspnea symptoms, breathing rates were gradually reduced until reaching each individual’s resonance frequency, as some patients found slower breathing intolerable during the initial session. (2) In the first session, patients were introduced to self-guided muscle relaxation through an audiotape and were guided to breathe in a relaxed manner. (3) Based on our previous studies, the HRVB training was structured into six weekly sessions over six consecutive weeks (Lin et al., 2015).

The patients’ optimal resonance frequency was determined during the first session by assessing the highest low frequency (LF) power across five breathing rates (6.5, 6, 5.5, 5, and 4.5 breaths per minute), followed by self-guided relaxation training. In sessions 2–6, the patients were trained in the abdominal and pursed lip-breathing techniques, gradually adjusting their breathing rates from baseline to achieve their target resonance frequency. In the third session, the Eureka (Finesse Technology Ltd., Zhubei, Hsinchu, Taiwan) were instructed to engage in home practice sessions twice daily for 5 min, 5 days a week. After each home practice session, the patients emailed their raw data to the researchers and received feedback in the following session. Psychoeducation on breathing techniques was provided through a brochure as part of the HRVB training.

Data reduction and statistical analysis

During data processing, a research assistant visually inspected R spike from ECG raw signals and peak wave from PPG signals, removed arrhythmia and movement artifacts, and then converted into HRV indices using Kubios-Premium version 3.5 (Kubios Co., Kuopio, Finland). ECG artifacts or arrhythmias that occurred in more than 20% of a 5-minute period were excluded from the statistical analysis (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996). The HRV indices included the time and frequency domains of HRV: (1) Standard deviation of the normal-to-normal intervals (SDNN), representing total HRV; (2) Root mean square of successive differences (RMSSD), reflecting parasympathetic activation; (3) low-frequency power (LF, 0.04–0.15 Hz, influenced by both sympathetic and parasympathetic activation or baroreceptor gain); (4) high-frequency power (HF, 0.15–0.4 Hz, indicative of parasympathetic activation; (5) low-frequency/high-frequency ratio (LF/HF ratio, reflecting sympathetic activation); (6) total power (TP, representing total HRV). To meet the homogeneity assumption of HRV, the HRV indices were transformed using the natural logarithms of lnSDNN, lnRMSSD, lnLF, lnHF, and lnTP.

To assess the accuracy and consistency from three devices, we collected simultaneously from 15 healthy students using the ProComp Infiniti, Zephyr BioHarness™ and Eureka for five-minute resting baseline. We explore interbeat interval (IBI) with 256 Hz/s sampling rate from the ProComp Infiniti, IBI with 250 Hz/s sampling rate from the Zephyr BioHarness™, and peak to peak interval with 256 Hz/s sampling rate from the Eureka, and then analyzed using Kubios-Premium version 3.5 (Kubios Co., Kuopio, Finland) to derive HRV indices.

Due to Food and Drug Administration approval of ProComp Infiniti, this study analyzed the correlations between ProComp Infiniti and Zephyr BioHarness™ to confirm the, finding r = 1.000 (p < .001) for mean IBI, low frequency (LF), high frequency (HF), and low frequency/high frequency ratio (LF/HF ratio). High correlations were observed between ProComp Infiniti and Eureka: r = .998 (p < .001) for mean IBI, r = .990 (p < .001) for SDNN, r = .943 (p < .001) for the root mean square of successive heartbeat interval differences, r = .999 (p < .001) for LF, r = .998 (p < .001) for HF, and r = .992 (p < .001) for LF/HF ratio. These findings indicate a high level of consistency between the ProComp Infiniti, Zephyr BioHarness™, and Eureka devices.

All statistical analyses were conducted using SPSS Windows software version 24.0; IBM Corp., Armonk, NY). A t-test and chi-square test were employed to compare the pre-test demographic data and psychological questionnaires between the HRVB and control groups. Two-way analysis of variance (ANOVA) was used to examine the interaction effects of Group (HRVB vs. control) × Time (pre-test and post-test) on the psychological questionnaires (CSES, SGRQ, BDI-II, BAI, and HRV indices). When a significant Group × Time interaction effect was found, a simple main effects analysis with a Bonferroni post hoc comparison was conducted to examine the differences between groups or across time points in the psychological questionnaires. If the Group × Time interaction effect was not significant, a main effect analysis was conducted to examine the differences between groups or across time points in the psychological questionnaires. Additionally, the Mauchly sphericity test was applied, and the Greenhouse-Geisser correction was used to adjust for any violation of sphericity in the repeated-measures ANOVA.

Partial eta squared (np²) was used to calculate the effect size. Effect size (np²) were interpreted as follows: 0.01 ≤ np² < 0.58 for a small effect size, .058 ≤ np² < 0.138 for a medium effect size, and np² ≥ 0.138 for a large effect size (Cohen, 1988).

Participants Characteristics

There were 26 participants in the HRVB group (mean age: 61.88 ± 9.35 years, 76.90% male) and 27 participants in the control group (mean age: 61.78 ± 11.42 years, 59.30% male). No significant differences were found in demographic data (age and sex), smoking history and behavior, or psychological questionnaires (CSES, SGRQ, BDI-II, and BAI) between the HRVB and control groups at pre-test (Table 1).

Table 1

*Demographic data, psychological questionnaires, and HRV indices between the HRVB and control groups*
Variables, mean (SD)		HRVB group (n = 26) M (SD)	Control group (n = 27) M (SD)	t/ χ2	p	Cohen’s d / Phi
Age		61.88 (9.35)	61.78 (11.42)	0.037	.970	− .010
Sex, n (%)	Men	20 (76.90%)	16 (59.30%)	1.897	.168	.189
	Women	6 (23.10%)	11 (40.70%)
Smoking years		23.26 (32.57)	22.70 (31.06)	0.063	.950	− .018
Smoking, n (%)	No smoking	11 (42.30%)	13 (48.15%)	3.482	.603	.256
	Quit smoking	10 (38.50%)	10 (37.05%)
	Smoking occasionally	2 (7.70%)	0 (0.00%)
	Smoking less than half pack per day	2 (7.70%)	1 (3.70%)
	Smoking 1–2 packs per day	1 (3.80%)	3 (11.10%)
Pulmonary function	FEV1 (L)	1.93 (0.57)	2.06 (0.63)	-0.753	.455	.216
	FEV1 prediction (%)	68.91 (14.97)	77.06 (14.70)	-2.000	.051	.549
	FEV1/FVC (%)	67.89 (9.00)	72.73 (10.25)	-1.823	.074	.395
COPD severity, n (%)	Group A	8 (30.80%)	12 (44.44%)	3.237	.198	.247
	Group B	8 (30.80%)	3 (11.12%)
	Group E	10 (38.40%)	12 (44.44%)
Self-efficacy	Total score of CSES	111.42 (25.90)	116.74 (27.83)	-0.719	.475	.193
	Negative affect	40.73 (9.48)	41.78 (9.75)	-0.396	.694	.109
	Intense emotional arousal	26.65 (6.47)	27.78 (6.45)	-0.633	.529	.175
	Physical exertion	14.88 (4.42)	16.41 (4.73)	-1.210	.232	.334
	Weather/Environment	19.19 (4.56)	20.63 (5.57)	-1.026	.310	.282
	Behavioral risk factors	9.96 (2.54)	10.15 (2.77)	-0.255	.799	.071
Quality of life	Total score of SGRQ	25.27 (16.18)	30.74 (17.56)	-1.178	.244	.324
	Symptoms	32.21 (20.91)	34.56 (24.99)	-0.371	.712	.102
	Activity	38.31 (26.13)	39.97 (23.37)	-0.244	.808	.067
	Impact	15.65 (13.89)	24.27 (19.56)	-1.843	.071	.507
Depression	Total score of BDI-II	5.15 (5.13)	7.26 (7.45)	-1.195	.238	.567
	Somatic depression	2.12 (1.95)	2.74 (2.09)	-1.127	.265	.113
	Cognitive depression	3.04 (3.86)	4.52 (5.81)	-1.088	.282	.229
Anxiety	Total score of BAI	4.00 (3.77)	5.19 (6.96)	-0.766	.447	.211
	Somatic anxiety	2.19 (2.19)	2.30 (3.53)	-0.128	.898	.037
	Cognitive anxiety	1.81 (2.38)	2.89 (3.63)	-1.276	.208	.351

[Insert Table 1 here]

Effects of Heart Rate Variability Biofeedback in Self-Efficacy

There were significant Group × Time interaction effects for a total score of CSES and its subscales. These include negative affect, intense emotional arousal, physical exertion, and weather/environment (F_{(1, 51)} = 14.526, p < .001, np2 = .222; F_{(1, 51)} = 6.299, p = .015, np2 = .110; F_{(1, 51)} = 10.131, p = .002, np2 = .166; F_{(1, 51)} = 18.835, p < .001, np2 = .270; F_{(1, 51)} = 19.071, p < .001, np2 = .272). However, there was no significant interaction effect of Group × Time in behavior risk factors (F_{(1, 51)} = 3.59, p > .001, np2 = .065; Table 2 and Fig. 1).

A simple main effect analysis for Time revealed that participants in the HRVB group had a significantly higher total score of CSES (F_{(1, 51)} = 17.122, p < .001, np2 = .251), and subscale score for negative affect (F_{(1, 51)} = 4.874, p = .32, np2 = .087), intense emotional arousal (F_{(1, 51)} = 10.197, p =. 002, np2 = .167), physical exertion (F_{(1, 51)} = 25.916, p < .001, np2 = .337), and weather/environment (F_{(1, 51)} = 26.342, p < .001, np2 = .341) at post-test compared to pre-test. In the control group, there were no significant differences in total score and subscales of the CSES at post-test and pre-test (total score: F_{(1, 51)} = 1.501, p = .226, np2 = .029; negative affect: F_{(1, 51)} = 1.777, p = .189, np2 = .034; intense emotional arousal: F_{(1, 51)} = 1.683, p = .200, np2 = .032; physical exertion: F_{(1, 51)} = 1.023, p = .317, np2 = .020; and weather/environment: F_{(1, 51)} = 1.020, p = .317, np2 = .020).

A simple main effect of the Group revealed a significant increase in total score and subscales of CSES at post-test for the HRVB group compared to the control group (F_{(1, 102)} = 4.023, p = .048, np2 = .038). The post hoc comparisons revealed that the HRVB group had higher CSES scores at the post-test (127.08 ± 22.29) compared to the pre-test (111.42 ± 25.90), as well as higher post-test scores compared to the control group (112.19 ± 31.11).

Table 2

*The interaction effects at the pre-test and post-test between the HRVB and control groups in psychological questionnaires*
Variables	HRVB group (n = 26)		Control group (n = 27)			F		np²
	Pre-test M (SD)	Post-test M (SD)	Pre-test M (SD)	Post-test M (SD)	Time	Group	Time × Group	Time × Group
Total score of BDI-II	5.15 (5.13)	4.08 (5.02)	7.26 (7.45)	7.30 (8.67)	1.000	2.217	1.147	.022
Somatic depression	2.12 (1.95)	1.73 (1.93)	2.74 (2.09)	2.89 (2.21)	0.358	2.866	1.816	.034
Cognitive depression	3.04 (3.86)	2.35 (3.60)	4.52 (5.81)	4.41 (7.00)	0.825	1.640	0.432	.008
Total score of BAI	4.00 (3.77)	2.73 (3.41)	5.19 (6.96)	4.96 (7.39)	2.031	1.334	1.001	.019
Somatic anxiety	2.19 (2.19)	1.54 (2.20)	2.30 (3.53)	2.11 (3.30)	3.171	0.200	0.989	.019
Cognitive anxiety	1.81 (2.38)	1.19 (1.55)	2.89 (3.63)	2.85 (4.52)	0.801	2.830	0.629	.012
Total score of SGRQ	25.27(16.18)	18.94 (13.83)	30.74 (17.56)	26.80 (18.91)	23.912***	2.212	1.301	.025
Symptoms	32.21 (20.91)	22.81 (20.57)	34.56 (24.99)	32.35 (24.15)	9.455**	0.993	3.622	.066
Activity	38.31 (26.13)	29.82 (21.68)	39.97 (23.37)	36.84 (24.84)	17.147***	0.451	3.645	.067
Impact	15.65 (13.89)	11.51 (11.72)	24.27 (19.56)	19.34 (20.95)	12.306**	3.338	0.094	.002
Total score of CSES	111.42 (25.90)	127.08 (22.29)	116.74 (27.83)	112.19 (31.11)	4.381*	0.476	14.526***	.222
Negative affect	40.73 (9.48)	43.92 (8.88)	41.78 (9.75)	39.89 (10.79)	0.414	0.362	6.299*	.110
Intense emotional arousal	26.65 (6.47)	29.81 (6.08)	27.78 (6.45)	26.52 (7.54)	1.867	0.408	10.131**	.166
Physical exertion	14.88 (4.42)	18.88 (4.09)	16.41 (4.73)	15.63 (5.01)	8.567**	0.586	18.835***	.270
Weather/Environment	19.19 (4.56)	23.23 (4.40)	20.63 (5.57)	19.85 (6.39)	8.741**	0.517	19.071***	.272
Behavioral risk factors	9.96 (2.54)	11.23 (2.20)	10.15 (2.77)	10.30 (2.74)	5.689*	0.339	3.559	.065

[Insert Table 2 here]

[Insert Fig. 1 here]

Effects of Heart Rate Variability Biofeedback in Quality of Life

There were no significant Group × Time interaction effects for a total score of SGRQ or its subscales-symptoms, activity, and impact F_{(1, 51)} = 1.301, p = .259, np2 = .025; F_{(1, 51)} = 3.622, p = .063, np2 = .066; F_{(1, 51)} = 3.645, p = .062, np2 = .067; F_{(1, 51)} = 0.094, p = .761, np2 = .002; Table 2). However, the main effect of Time revealed significantly decreased from pre-test to post-test in both groups for SGRQ total score (F_{(1, 51)} = 23.912, p < .001, np2 = .319), as well as the subscales of symptoms (F_{(1, 51)} = 9.455, p = .003, np2 = .156), activity (F_{(1, 51)} = 17.147, p < .001, np2 = .252), and impact (F_{(1, 51)} = 12.306, p = .001, np2 = .194). In the HRVB group, the t-test revealed there were significant reductions from the pre-test (25.27 ± 16.18) to the post-test (18.94 ± 13.83) for total score of SGRQ, as well as for its subscales: symptoms from 32.21 ± 20.91 to 22.81 ± 20.57; activity from 38.31 ± 26.13 to 29.82 ± 21.68; and impact from 15.65 ± 13.89 to 11.51 ± 11.72 (Table 3).

Table 3

*The time effects at pre-test and post-test in total score and subscales of the SGRQ for the HRVB and control groups*
Variables	HRVB group (n = 26)
	Pre-test M (SD)	Post-test M (SD)	t	p	Cohen’s d	Pre-test M (SD)	Post-test M (SD)	t	p	Cohen’s d
Total score of SGRQ	25.27 (16.18)	18.94 (13.83)	5.549***	< .001	1.088	30.74 (17.56)	26.80 (18.91)	2.259*	.033	.435
Symptoms	32.21 (20.91)	22.81 (20.57)	3.164**	.004	.621	34.56 (24.99)	32.35 (24.15)	0.939	.356	.181
Activity	38.31 (26.13)	29.82 (21.68)	4.055***	< .001	.795	39.97 (23.37)	36.84 (24.84)	1.669	.107	.321
Impact	15.65 (13.89)	11.51 (11.72)	3.845**	.001	.754	24.27 (19.56)	19.34 (20.95)	2.130*	.043	.410

[Insert Table 3 here]

Effects of Heart Rate Variability Biofeedback in Depression and Anxiety

There was no significant Group × Time interaction effects for total scores of BDI-II, somatic depression, cognitive depression, total scores of BAI, somatic anxiety, and cognitive anxiety (F_{(1, 51)} = 1.147, p = .289, np2 = .022; F(_{(1, 51)} = 1.816, p = .184, np2 = .034; F_{(1, 51)} = 0.432, p = .514, np2 = .008; F_{(1, 51)} = 1.001, p = .322, np2 = .019; F_{(1, 51)} = 0.989, p = .325, np2 = .019; F_{(1, 51)} = 0.629, p = .431, np2 = .012 (Table 2 and Fig. 2).

[Insert Fig. 2 here]

Effects of Heart Rate Variability Biofeedback on Changes in HRV Reactivity and HRV Recovery

HRV data from one patient in each group who experienced arrhythmia during the walking and recovery stages were excluded from the analysis. There were 25 patients in the HRVB group and 26 in the control group. Significant Group × Time interaction effects were found in HRV reactivity (from baseline to walking), including lnSDNN (F_{(1, 49)} = 10.179, p = .002, np2 = .172) and lnTP (F_{(1, 49)} = 8.790, p = .005, np2 = .152). However, no significant Group × Time interaction effect were observed for lnRMSSD, lnLF, and lnHF between baseline and walking stages in either group. Post hoc comparisons revealed a significantly decreased in HRV reactivity for lnSDNN and lnTP from baseline to walking (F_{(1, 49)} = 11.255, p = .002, np2 = .187; and F_{(1, 49)} = 10.515, p = .002, np2 = .177) (Table 4 and Fig. 3). Moreover, no significant Group × Time interaction effect was found in Borg Scale between baseline and walking for the two groups.

Significant Group × Time interaction effects were found in HRV recovery (from walking to recovery), including lnSDNN (F_{(1, 49)} = 7.396, p = .009, np2 = .131), lnHF (F_{(1, 49)} = 4.149, p = .047, np2 = .078), and lnTP (F_{(1, 49)} = 7.433, p = .009, np2 = .132). Post hoc comparisons showed significant increases in HRV recovery for lnSDNN and lnTP from walking to recovery (F_{(1, 49)} = 5.862, p = .019, np2 = .107; F_{(1, 49)} = 4.594, p = .037, np2 = .086) in the HRVB group. However, no significantly differences were observed between baseline and walking stages in the HRVB group. Additionally, there were no significant of Group × Time interaction effect for lnRMSSD and lnLF (Table 4 and Fig. 3). Moreover, no significant Group × Time interaction effect was found in Borg Scale between walking and recovery for the two groups.

Table 4

*The interaction effects in HRV reactivity and HRV recovery at pre-test and post-test between the HRVB and control groups*
Variables	HRVB group (n = 25)		Control group (n = 26)			F		np²
	Pre-test M (SD)	Post-test M (SD)	Pre-test M (SD)	Post-test M (SD)	Time	Group	Time × Group	Time × Group
HRV reactivity from walking HRV subtract baseline HRV
lnSDNN(ms)	-0.21 (0.62)	-0.58 (0.63)	-0.49 (0.53)	-0.37 (0.47)	2.577	0.057	10.179**	.172
lnRMSSD (ms)	-0.52 (0.57)	-0.77 (0.73)	-0.65 (0.97)	-0.58 (0.67)	0.768	0.032	2.287	.045
lnLF (ms²)	-1.49 (1.47)	-2.06 (1.62)	-1.23 (1.32)	-1.45 (1.52)	3.265	1.509	0.626	.013
lnHF (ms²)	-1.66 (1.50)	-2.33 (1.82)	-2.17 (1.84)	-1.87 (1.77)	0.554	0.003	3.692	.070
lnTP (ms²)	-0.95 (1.16)	-1.70 (1.32)	-1.37 (0.99)	-1.16 (1.19)	2.776	0.045	8.790*	.152
Borg Scale	0.18 (0.90)	0.34 (0.51)	0.54 (0.97)	0.67 (1.51)	0.826	2.034	0.006	.000
HRV recovery from recovery HRV subtract walking HRV
lnSDNN(ms)	0.34 (0.53)	0.64 (0.62)	0.62 (0.46)	0.45 (0.45)	0.543	0.134	7.396**	.131
lnRMSSD (ms)	0.45 (0.57)	0.71 (0.65)	0.59 (0.82)	0.48 (0.55)	0.397	0.089	2.743	.053
lnLF (ms²)	1.20 (1.20)	1.80 (1.41)	1.57 (1.15)	1.47 (1.41)	1.535	0.005	3.012	.058
lnHF (ms²)	1.56 (1.52)	2.05 (1.51)	1.87 (1.60)	1.41 (1.38)	0.005	0.217	4.149*	.078
lnTP (ms²)	0.99 (1.09)	1.61 (1.18)	1.64 (0.95)	1.16 (1.20)	0.112	0.187	7.433**	.132
Borg Scale	-0.30 (0.76)	− 0.52 (0.67)	-0.60 (0.80)	-0.83 (1.20)	2.182	2.384	0.001	.000

[Insert Table 4 here]

[Insert Fig. 3 here]

The most significant finding of this study was that participants in the HRVB group showed a significant increase in COPD self-efficacy and quality of life at the post-test compared to both their pre-test scores and the post-test scores of the control group. However, there was no significant decrease in depression or anxiety in post-test scores in the HRVB and control groups.

This improvement in COPD self-efficacy was consistent with the findings of Giardino et al. (2004), who reported a 13-point increase in COPD self-efficacy (from 49 to 62) following HRVB training. In the present study, self-efficacy increased by 15.66 points. This increase is associated with the self-efficacy theory (Bandura, 1997), which includes the following components: (1) Enactive mastery experiences: patients learn breathing skills using visual feedback and apply them to their daily lives and physical activities. (2) Vicarious experience: Through therapist demonstrations, disease education, and case sharing, patients realized that COPD and symptom control were more manageable than initially believed. (3) Verbal persuasion: therapists provide positive reinforcement, mental support, and feedback during each training session and homework assignment. (4) Physiological and emotional states: The patients were trained in breathing techniques to reduce dyspnea and anxiety. They also learn muscle relaxation techniques to manage emotional and physiological activity (Neşe & Bağlama, 2022). Consequently, patients in the HRVB group were better equipped to manage dyspnea and improve their self-efficacy than those in the control group. Additionally, this study found significant decreases in the post-test in the four subscales of the CSES-negative affect, intense emotional arousal, physical exertion, weather or environment compared to the pre-test. Patients gained greater confidence in handling dyspnea caused by emotional and physical activity, including weather or environmental challenges across different situations.

Huang (2015) used the Exercise Self-Regulatory Efficacy Scale (Ex-SRES) to measure self-efficacy in patients performing 30-minute exercise thrice weekly. However, Huang’s result did not show a significant increase in exercise self-efficacy. Possible reasons could be that their patients had higher pre-test scores, leading to a ceiling effect, or that while pulmonary rehabilitation improved exercise tolerance, it did not significantly improve physical activity levels or sedentary lifestyles. Previous studies have also emphasized the importance of psychological intervention and behavior modification in enhancing self-efficacy (Egan et al., 2012; Probst et al., 2011).

Regarding quality of life, both groups showed a decrease in the total SGRQ score in the post-test compared to the pre-test. These findings are consistent with previous studies (de Souto Barbosa et al., 2023; Giardino et al., 2004). In our study, SGRQ scores decreased by 6.33 points (from 25.27 to 18.94), which is similar to Giardino et al. (2024), who reported a decrease of 8.2 points (from 50.1 to 41.9). However, de Souto Barbosa et al. (2023) found a much larger reduction of 31.93 points (from 53.26 to 21.23). Several factors could account for these differences: (1) de Souto Barbosa et al. (2023) had a smaller sample size (n = 9), which may have led to the presence of outliers at both pre-test and post-test, affecting the results. (2) High dropout rate: de Souto Barbosa et al. (2023) reported a higher dropout rate (31.00%) compared to our study (6.67%). This may have resulted in only the most responsive participants remaining in the final analysis, potentially affecting the treatment effects. (3) Baseline SGRQ scores: The baseline SGRQ scores in our study (25.27 ± 16.18 at pre-test and 18.94 ± 13.83 at post-test of the HRVB group) were lower than those reported in de Souto Barbosa et al. (53.26, 95% confidence interval [CI]: 40.02–66.49 at pre-test; 21.23, 95% CI was 13.85–28.61 at post-test) and Giardino et al. (2004) (50.10 ± 15.4 at pre-test and 41.9 ± 14.10 at post-test). Additionally, the 95% CI of SGRQ in de Souto Barbosa et al. (2023) was wider than the standard deviations in both Giardino et al. (2004) and our study, suggesting greater validity in their sample, which could have affected their results.

While our study found a significant improvement in total SGRG scores for both groups, it provides more detailed information on the subscale analysis than previous studies (de Souto Barbosa et al., 2023; Giardino et al., 2004). Our study offers a more in-depth understanding of quality of life by analyzing its subscales. In the HRVB group, significant improvements were observed in the SGRQ subscales of symptoms, activity, and impact at the post-test compared to the pre-test. In contrast, the control group showed improvement only in the total SGRQ and impact subscale scores. HRVB training helped patients with COPD improve their dyspnea, COPD symptoms, physical limitations, activities, and overall impact on daily life. Moreover, neither de Souto Barbosa et al. (2023) nor Giardino et al. (2004) included a control group in their studies. By including a control group, our study allowed a direct comparison of changes from pre-to post-tests following HRVB training, providing a more robust comparison of its effects.

The depression and anxiety scores in this study showed a reduction in the post-test compared to the pre-test. However, these changes were not statistically significant. Their results differ from those of de Souto Barbosa et al. (2023), who reported a decrease in depression from 19.22 to 6.44 and anxiety scores from 22.44 to 8.33. A possible explanation for this discrepancy is that the depression and anxiety scores in our study were within the normal range at pre-test (HRVB group: 5.15 for depression and 4.00 for anxiety; control group: 7.26 for depression and 5.19for anxiety), and remained low at post-test (HRVB group: 4.08 for depression, 2.73 for anxiety; control group: 7.30 for depression, 4.96 for anxiety). This suggests a potential floor effect in our study, in which the scores were too low for significant reductions. In contrast, de Souto Barbosa et al. (2023) had participants with higher baseline anxiety with anxiety scores (BAI) falling within the mild anxiety range (8–15), even though their depression scores (BDI-II) were also within the normal range. Two other studies (Giardino et al., 2004; Huang, 2015) used the Hospital Anxiety and Depression Scale (HADS) to assess depression. While Giardino et al. (2004) found no significant changes in depression scores, Huang (2015) reported a decrease in depression but not anxiety. Another factor could be sex differences in emotional distress among patients with COPD. Previous research has indicated that female patients with COPD tend to experience higher levels of emotional distress than male patients with COPD (Hsieh et al., 2016; Tsai et al., 2013). In de Souto Barbosa et al. (2023), a higher percentage of COPD patients were female (88.89%) compared to our study (23.08%). Additionally, 33.30% of COPD patients in de Souto Barbosa’s study had comorbid COPD and depression (n = 3), whereas only 2.7% of participants in our study had comorbid COPD and generalized anxiety disorder, n = 1). The prevalence of depression and anxiety in our study was lower than that of Fu (2015), who reported 4.10% for depression and 9.13% for anxiety disorders in the Taiwanese population. However, only 2.7% (n = 1) of patients with COPD were comorbid with generalized anxiety disorder, and none had comorbid with COPD or depression. The prevalence of depression and anxiety was lower than previous studies, such as 27.10% for depression (Matte et al., 2016) and 3–46% for anxiety in patients with COPD (Willgoss & Yohannes, 2013). Possibly, patients who chose to participate in our study had depression and anxiety levels within the normal range at pre-test and remained within that range after HRVB training, making it difficult to observe significant changes.

This study had several limitations. First, this was not a randomized controlled trial, making it difficult to rule out potential confounding factors that might have influenced the results and limited the efficacy of the study. Second, this study only presented the short-term effectiveness of HRVB on self-efficacy and quality of life; there was no long-term follow-up to confirm the sustained effects of HRVB on patients with COPD over time. Third, self-efficacy and quality of life were measured using self-report questionnaires, which may have introduced response bias among patients with COPD. Fourth, this study did not include an active control group. The placebo effect could have contributed to the more positive outcomes observed in the self-report measures.

Six sessions of HRVB showed promise as a non-pharmacological intervention for alleviating dyspnea and enhancing self-efficacy and quality of life in patients with COPD. Further randomized controlled trials with larger sample sizes and active control groups are necessary to confirm their efficacy in this population. The HRVB has the potential to become an evidence-based component of pulmonary rehabilitation programs for patients with COPD.

The study protocol was approved by the ethics committee of Kaohsiung Medical University Hospital (KMUHIRB-F(II)-20200060). Informed consent was obtained from all participants involved in the study. All authors have agreed to publish in this journal.

Conflicts of Interest:

The authors declare no conflict of interest.

Author Contribution

P.C.Y. collected data from patients with COPD and conducted formal analysis and investigation. D.W.W. secured funding, diagnosed, and referred participants with COPD. I.M.L. designed the research and experimental procedures, provided supervision, prepared the original draft, and contributed to writing, reviewing, and editing the manuscript.

Acknowledgement

This study was supported by the Kaohsiung Municipal Siaogang Hospital (S110-05). We thank the patients with COPD who attended and participated in our study.

Data Availability Statement:

Data are available from the corresponding author upon reasonable request.

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No competing interests reported.

Effects of Heart Rate Variability Biofeedback on Enhancing Self-Efficacy, Quality of Life and Six-Minute Walking Test in Patients with Chronic Obstructive Pulmonary Disease

Status:

Journal Publication

Version 1

Abstract

Objective

Methods

Results

Conclusion

Figures

Introduction

Methods

Participants

Measurements

Heart Rate Variability Biofeedback Training Equipment

Research Design and Experimental Procedure

Heart Rate Variability Biofeedback Protocol

Data reduction and statistical analysis

Results

Participants Characteristics

Effects of Heart Rate Variability Biofeedback in Self-Efficacy

Effects of Heart Rate Variability Biofeedback in Quality of Life

Effects of Heart Rate Variability Biofeedback in Depression and Anxiety

Effects of Heart Rate Variability Biofeedback on Changes in HRV Reactivity and HRV Recovery

Discussion

Conclusions

Declarations

Conflicts of Interest:

Author Contribution

Acknowledgement

Data Availability Statement:

References

Additional Declarations

Status:

Journal Publication

Version 1