Can Qigong improve non-motor symptoms in people with Parkinson’s disease - A pilot randomized controlled trial?

Abstract

Non-motor symptoms (NMS) including sleep disorders, anxiety, depression, fatigue, and cognitive decline can significantly impact quality of life in people with PD. Qigong exercise is a mind-body exercise that shows a wide range of benefits in various medical conditions. The purpose of this study was to investigate the effect of Qigong exercise on NMS with a focus on sleep quality. Seventeen participants completed a 12-week intervention of Qigong (n = 8) or sham Qigong (n = 9). Disease severity, anxiety and depression levels, fatigue, cognition, quality of life, and other NMS of the participants were evaluated prior to the intervention and at the end of the 12-week intervention. After the intervention, both Qigong and sham-Qigong group showed significant improvement in sleep quality (p < 0.05) and overall NMS (p < 0.05). No significant difference was found between groups. Qigong exercise has the potential as a rehabilitation method for people with PD, specifically alleviating NMS in PD. However, this finding needs to be carefully considered due to the small sample size and potentially low intervention fidelity of this study.

1. Introduction

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease in the United States [1]. Cardinal motor symptoms of PD, including bradykinesia, tremor, rigidity, and postural instability have been a primary focus of PD treatment [2]. Pharmacological treatments (e.g., levodopa, catechol-O-methyl transferase (COMT) inhibitors, dopamine agonists, monoamine oxidase B (MAO-B) inhibitors), surgical treatment (e.g., deep brain stimulation), and physical therapy have shown great benefits in alleviating and improving motor symptoms in people with PD [3].

However, non-motor symptoms (NMS) including sleep disorder, mood disorder, cognitive decline, and fatigue have not received much attention until recent years. Growing evidence has demonstrated that NMS can occur at any stage of PD progression and often precede the diagnosis of PD by many years [4]. Sleep disorders are common in people with PD. A study reported that up to 96% of people with PD experience at least one sleep-related dysfunction [5]. Another study estimated that 60%–90% of people with PD suffered from a disease-related or secondary sleep disorder [6]. Mood disorders such as anxiety and depression impact patients’ quality of life (QOL). Strong associations between mood disorders and QOL have been reported previously [7]. Moreover, it was demonstrated that depression is related to decreased QOL, with the association being stronger than for motor symptoms and physical disability [8]. Cognitive decline becomes worse as the disease progresses, resulting in restricted activities of daily living and decreased QOL [9]. Mild cognitive impairment is commonly reported in people with PD, which can often develop into PD dementia [10]. Fatigue can occur independently from the rest of the symptoms in PD, but is often associated with other NMS such as sleep and mood disorders [11]. A study reported that fatigue negatively impacts all QOL domains, including bodily discomfort, emotional well-being, mobility, and activities of daily living [12].

Mind-body practices such as Yoga, Tai Chi, and Qigong are becoming popular in the United States. According to Clarke and colleagues (2015), more than 10% of adults in the United States have used mind-body practices [13]. Qigong exercise is a mind-body exercise that consists of a harmonious series of meditation, deep breathing, and mild body movement. Past studies, including those from our laboratory, have shown feasibility in the PD population and benefits in NMS [14–16]. Our recent preliminary study showed that Qigong exercise may improve sleep disorders in people with PD [17]. However, a lack of evidence from rigorous randomized controlled trials makes clinicians hesitant to recommend Qigong exercise to people with PD.

In this randomized controlled pilot trial, we investigated the effect of Qigong exercise on NMS domains including sleep quality (primary measurement), anxiety, depression, fatigue, cognition, and QOL.

2. Methods

2.1. Participants

This study recruited a total of 32 people with mild to moderate PD (modified Hoehn and Yahr stage between 1 and 3). Participants were recruited from the Parkinson’s Disease and Movement Disorder Clinic at the University of Kansas Health System, the regional PD symposium, and the Healthcare Enterprise Repository for Ontological Narration (HERON) at the University of Kansas Medical Center. All enrolled participants were initially screened through a phone interview between October 2017 and November 2018. The inclusion criteria were (1) diagnosis of idiopathic PD, (2) 40–80 years of age, (3) no deep brain stimulation, and (4) no anticipated changes in PD medications. The exclusion criteria were (1) Mini Mental State Examination (MMSE) score below 24, (2) neurological conditions other than idiopathic PD, and (3) significant or uncontrolled cardiovascular diseases. Before participating in the study, all participants signed an informed consent approved by the Institutional Review Board of the University of Kansas Medical Center (#STUDY00140835). This study is registered at www.clinicaltrails.gov (NCT03463330).

2.2. Study design

This study was a 12-week, randomized, controlled pilot trial. All participants were randomly assigned into either an experimental or a control group. For allocation of the participants, a single sequence of computer-generated random numbers was utilized. A set of sealed envelopes containing group assignment were prepared based on the random sequence. A participant was given an envelope and assigned to either Qigong or sham-Qigong group. Participants in the experimental group practiced a Qigong exercise (Qigong Group = QG, n = 8) whereas those in the control group practiced a sham Qigong exercise (sham Qigong Group = SQG, n = 9). The participants and assessors were blinded to the group allocation.

Overall, the study consisted of two assessment sessions (baseline and post-intervention) and a 12-week intervention (daily exercise at home and weekly group exercise sessions). During the baseline assessment session, the informed consent and demographic and medical information were collected. The session included neuropsychological tests and questionnaires assessing NMS. During the 12-week intervention, both QG and SQG practiced the assigned exercise twice a day at home and attended one weekly group session for 12 weeks throughout the exercise period. After the completion of the exercise period, the post-intervention assessment was conducted, in which the assessment procedure was identical to the baseline assessment. Further details about the study design were previously published [18].

2.3. Intervention

A ‘six healing sounds’ Qigong exercise was used in this study. Participants in QG learned and performed this Qigong exercise. Research team members who were trained by an experienced Qigong practitioner provided three training sessions to the QG participants during the first three weeks of intervention. A full cycle of Qigong exercise usually takes 15–20 min. The QG was asked to practice Qigong exercise twice a day at home, in the morning and at night before going to bed. They were also asked to attend weekly group exercise sessions (45 min–1 h) throughout the study. During the group exercise session, they learned and practiced Qigong exercise, and the instructors and participants discussed issues related to PD and the exercise practice. For the SQG, every procedure was identical except the assigned exercise. To provide an equal level of physical activities, they learned and practiced sham Qigong exercise. The sham Qigong exercise includes the same series of mild body movements, but meditation and deep breathing with six healing sounds were excluded. Participants in both QG and SQG maintained a daily exercise journal provided by the research team.

2.4. Measurements

To measure the quality of sleep, the Parkinson’s Disease Sleep Scale 2 (PDSS-2) was administered [19,20]. This scale consists of a total of 15 items (minimum (min) = 0, maximum (max) = 60) that assess motor problems at night, PD symptoms at night, and disturbed sleep [20]. The validity and reliability of the PDSS-2 has been demonstrated by various studies [21–23]. A wearable activity monitor, Actigraph (wGT3X-BT, Actigraph, LLC. Pensacola, FL, USA), was also utilized to track movement during sleep. Outcomes from Actigraph included sleep efficiency, total time in bed, total sleep time, wake after sleep onset, awakenings, and average awakening.

Mood disorders, anxiety, and depression were assessed by the 20-item Geriatric Anxiety Inventory (GAI) (min = 0, max = 20) and 15-item Geriatric Depression Scale (GDS) (min = 0, max = 15) [24,25]. Fatigue was assessed by the 16-item Parkinson Fatigue Scale (min = 16, max = 80) [26]. Cognitive functions were assessed by the Frontal Assessment Battery (FAB) (min = 0, max = 18) [27], 10-point Clock Drawing Test (CDT) [28], and Trail Making Test A and B (TMT A and B) [29]. Comprehensive NMS and QOL were assessed by the Parkinson’s Disease Non-Motor Symptom Questionnaire (NMSQ) (min = 0, max = 30) [30] and 39-item Parkinson’s Disease Questionnaire (PDQ) (min = 0, max = 100) [31]. To measure the severity of PD symptoms, the Unified Parkinson’s Disease Rating Scale (UPDRS) was utilized (min = 0, max = 199) [32]. Further details about the measurements utilized in the study were found in a previously published protocol [18].

2.5. Statistical analysis

Both the Shapiro-Wilk test and visual evaluation were carried out with the study variables for testing/inspecting data normality. Variables that were not normally distributed with the p-value less than 0.05 were visually evaluated for the symmetry and peakness/kurtosis of the distribution using the histogram and cumulative frequency distribution. A total of 8 variables including MMSE, FAB, CDT, TMT A and B, GAI, GDS, and Hoehn and Yahr stage, were not normally distributed. Paired and independent t-tests were used to compare measurements for QG and SQG if normally distributed. Chi-square tests were used for categorical variables. Otherwise, Wilcoxon Signed-Rank test and Mann-Whitney tests was utilized to compare measurements for QG and SQG. For the sub-analysis of PDSS-2, mean changes (post-intervention – baseline) were calculated for the total PDSS-2 score and sub-scores, which were compared between QG and SQG using independent t-tests. Data from the Actigraph was processed using the ActiLife version 6.13.4 software provided by the manufacturer (Actigraph, LLC. Pensacola, FL, USA). The Cole-Kripke algorithm was utilized for the Actigraph data analysis [33]. Pearson’s correlation coefficients were calculated to examine the relationships between changes in PDSS-2 and Actigraph variables. The significance level was set at p = 0.05. Statistical analyses were conducted using Python 3.7.

3. Results

3.1. Descriptive statistics

We obtained the contact information of 275 people diagnosed with PD collected from the HERON database, PD symposium, and PD clinic (Fig. 1). At the phone screening, 54 individuals qualified and indicated verbal interest in study participation (Fig. 1). Among those 54 people, 32 participated in the study while 22 individuals did not due primarily to loss of contact. A total of 17 participants (8 in QG and 9 in SQG) completed the study and their data were included in the final data analysis (Fig. 1). Demographics of study participants are shown in Table 1. No group differences at baseline were found. The compliance levels to the daily home exercise program in participants who completed the study were 81.6 ± 12.1% in QG and 80.1 ± 10.5% in SQG. During the study, 15 participants withdrew from the study for various reasons (Fig. 1).

Fig. 1.

Flow chart of the study participants.

Table 1.

Demographics of the participants who completed the study.

	Qigong group (n = 8)	Sham Qigong group (n = 9)	p-value
Age (year)	66.4 (8.1)	65.9 (5.4)	0.88
Sex (F/M)	4/4	3/6	0.49
Education (year)	16.4 (3.7)	14.67 (2.9)	0.30
Disease duration (year)	4.25 (2.1)	5.33 (3.3)	0.44
HY Stage	2 (2–2)	2 (2–2)	0.87
LEDD (mg)	682.6 (301.1)	712.6 (332.4)	0.87

Values are presented as mean (standard deviation) or median (Q1-Q3) except sex variable.

Abbreviations: HY = Hoehn and Yahr, LEDD = levodopa equivalent daily dose.

3.2. Non-motor symptoms

The total scores of the PDSS-2 were significantly improved from 19.3 ± 12.5 to 11.0 ± 6.7 in QG (p < 0.05) and from 19.9 ± 9.4 to 14.6 ± 3.7 in SQG (p < 0.05) between pre- and post-assessment (Table 2). The PDSS-2 sub-scores show that motor symptoms at night were significantly improved from 4.3 ± 3.7 to 1.7 ± 2.0 in QG (p < 0.05) and PD symptoms at night and disturbed sleep were approaching significance in QG (p = 0.10 and p = 0.06, respectively). In SQG, disturbed sleep was significantly improved from 9.9 ± 4.7 to 7.6 ± 3.5 (p < 0.05). The scores of the comprehensive NMS measured by NMSQ were significantly improved from 10.38 ± 5.7 to 8.0 ± 5.3 in QG (p < 0.05) and from 10.4 ± 6.9 to 8.0 ± 4.6 in SQG (p < 0.05). The UPDRS 1 score (evaluation of mentation, hallucinations, depression and apathy) was improved in QG approaching significance (p = 0.06). The GDS and PDQ scores were improved and showed statistically significant differences in SQG (p < 0.05). While the within-group analyses revealed significant improvement in several measurements as described in Table 2, no significant difference was found in between-group analyses after the 12-week interventions for any variables in the study.

Table 2.

Non-motor symptoms after the intervention in QG and SQG.

	Qigong group			Sham Qigong group			Group
	Pre	Post	p	Pre	Post	p	p
PDSS-2
Total score	19.3 (12.5)	11.0 (6.7)	0.01*	19.9 (9.4)	14.6 (3.7)	0.04*	0.38
Motor symptoms	4.3 (3.7)	1.75 (2.0)	0.04*	5.1 (3.6)	3.7 (4.2)	0.21	0.26
PD symptoms	4. (5.5)	1.6 (1.8)	0.10	4.9 (3.9)	3.3 (3.2)	0.12	0.21
Disturbed sleep	10.6 (5.3)	7.6 (3.7)	0.06	9.9 (4.7)	7.6 (3.5)	0.03*	0.97
Actigraph
Sleep efficiency (%)	93.6 (3.7)	91.6 (6.5)	0.21	94.6 (2.0)	94.7 (2.1)	0.86	0.29
Total time in bed (min)	445 (72)	454 (54)	0.91	481 (96)	493 (85)	0.32	0.40
Total sleep time (min)	419 (65)	414 (26)	0.90	455 (93)	466 (80)	0.29	0.20
Wake after sleep onset	29.5 (19.7)	39.4 (33.1)	0.29	25.9 (9.8)	26.6 (12.0)	0.85	0.40
Awakenings (#)	7.1 (5.0)	10.4 (7.9)	0.13	7.1 (4.6)	6.7 (4.1)	0.59	0.34
Avg. Awakening (min)	5.0 (2.9)	4.1 (1.8)	0.21	5.0 (3.1)	5.2 (2.9)	0.59	0.47
Other non-motor symptom measurements
PFS	41.0 (17.5)	41.0 (15.8)	1.00	38.3 (15.2)	39.2 (15.8)	0.82	0.82
GAI	4.0 (6.0)	3.1 (5.0)	0.24	3.0 (5.1)	1.7 (4.3)	0.16	0.28
GDS	3.3 (3.3)	3.0 (2.8)	0.59	3.1 (3.1)	2.0 (2.8)	0.03*	0.30
MMSE	28.9 (1.4)	29.3 (0.7)	0.70	28.9 (1.2)	28.7 (1.9)	1.00	0.96
FAB	13.8 (1.7)	14.3 (1.2)	0.33	13.1 (1.5)	13.0 (1.8)	0.71	0.08
CDT	10.0 (0)	10.0 (0)	1.00	9.7 (1.0)	9.6 (1.3)	0.65	0.20
TMTA	32.1 (7.9)	31.6 (7.4)	0.73	38.9 (17.7)	54.8 (54.3)	0.14	0.13
TMTB	84.9 (69.2)	86.6 (53.3)	1.00	107.2 (99.3)	125.9 (149.7)	0.37	0.60
NMSQ	10.4 (5.7)	8.0 (5.3)	0.04*	10.4 (5.7)	8.0 (4.6)	0.01*	1.00
PDQ	29.9 (23.0)	26.0 (23.3)	0.18	40.6 (24.5)	28.8 (25.3)	0.05*	0.82
UPDRS
Part I	12.0 (7.1)	10.0 (8.3)	0.06	10.4 (6.9)	7.7 (6.3)	0.12	0.52
Part II	8.0 (5.7)	8.6 (5.3)	0.49	10.0 (11.1)	11.1 (10.6)	0.49	0.56
Part III	19.6 (8.6)	19.7 (9.6)	0.93	22.6 (9.2)	22.9 (16.3)	0.94	0.64

^*p < 0.05.

Values are presented as mean (standard deviation).

Abbreviations: CDT = Clock drawing test, FAB = Frontal assessment battery, GAI = Geriatric anxiety index, GDS = Geriatric depression scale, MMSE = Mini mental state examination, NMSQ = Non-motor symptom questionnaire, PD = Parkinson’s disease, PDQ = Parkinson’s disease questionnaire, PDSS-2 = Parkinson’s disease sleep scale-2, PFS = Parkinson fatigue scale, TMTA and B = Trail making test A and B, UPDRS = Unified Parkinson’s disease rating scale.

Further analysis of changes in PDSS-2 total score and sub-scores were performed after removing the data of participants who did not have any sleep disorders at baseline (two from QG and two from SQG excluded). Since these participants already had good sleep quality, there was no or little room to improve their sleep quality (ceiling effect). The cut-off PDSS-2 total score (<10) was introduced based on a previous study [34]. Although not statistically significant, the mean values of changes in PDSS-2 total and all sub-scores were greater in QG than SQG, with the difference between the two groups in PDSS-2 total score approaching a statistical significance (p = 0.15), in which the mean changes of PDSS-2 total scores were −10.7 ± 6.0 in QG and −6.9 ± 6.5 in SQG (p = 0.15); motor symptoms at night sub-scores were −3.2 ± 3.1 in QG and −1.9 ± 3.3 in SQG (p = 0.24); PD symptoms at night sub-scores were −3.7 ± 4.3 in QG and −1.9 ± 3.3 in SQG (p = 0.25); and disturbed sleep sub-scores were −3.8 ± 4.1 in QG and −2.7 ± 3.0 in SQG (p = 0.29).

Because sleep quality was the focus of this study, an additional correlation analysis was explored between subjective and objective measurements of sleep quality. Pearson’s correlation coefficients were calculated to examine the relationships between changes in PDSS-2 and Actigraph variables in all participants. Changes in PD symptoms at night were strongly or moderately strongly correlated with Actigraph variables including sleep efficiency (r = −0.52), wake after sleep onset (r = 0.60), and average awakenings (r = 0.50) (Fig. 2).

Fig. 2.

Relationships between changes in PDSS-2 total scores and sub-scores and Actigraph variables.

4. Discussion

Our findings indicate that Qigong exercise may improve sleep quality in people with PD, as shown by the significant difference in PDSS-2 total scores between pre- and post-assessments and approaching significance when compared to the control group after excluding participants without sleep disturbance. This result is in accordance with two previous studies in our laboratory that demonstrated improved sleep quality after Qigong exercise in people with PD [15,17]. In the recent pilot study, the amounts of averaged change between pre- and post-intervention in PDSS-2 total score was −7.3, which is less than the change (−10.7) observed in the current study. This result may be induced by a longer duration of the intervention from 8 weeks in our previous study to 12 weeks in the current study. Our results also show that the effect of Qigong exercise generated clinically significant improvement, since the established minimally clinically important difference of PDSS-2 is −3.44 [21]. In the current study, we also observed a significant sleep improvement in SQG. The exercise performed by the SQG participants was only the smooth body movements without deep breathing or meditation. Of relevance, a meta-analysis of the effect of physical activities on sleep suggested that the use of low-intensity exercises may improve sleep quality [35].

Although PDSS-2 is a reliable and valid questionnaire to assess sleep disorders in people with PD [21], it is still primarily based on subjective answers from the participants. We introduced an activity and sleep monitoring device (Actigraph) in the current study to measure sleep quality in people with PD. Stavitsky and colleagues (2010) reported a significant relationship between actigraphy measurements and PDSS-2 scores [36]. Although our study did not find strong correlations in all measured variables, the significant correlations between PD symptoms at night and Actigraphy variables of sleep efficiency, wake after sleep onset, and average awakenings were in accordance with the previous finding [36].

Comprehensive NMS evaluated by NMSQ was improved in both QG and SQG. NMSQ is widely utilized in clinics, and its validity and reliability in identifying NMS have been demonstrated in previous studies [30,37]. Results of the current study suggest that both Qigong and sham Qigong exercises may alleviate NMS in people with PD. Qigong exercise did not show any significant improvement in anxiety, depression fatigue, cognitive decline, and QOL, whereas sham Qigong exercise significantly improved depression measured by GDS and QOL measured by PDQ. Further studies with a larger sample size are needed to confirm these results.

This study has several limitations. The current study is underpowered due to the small sample size (n = 17). Post hoc power analyses using the changes (baseline vs. post-intervention) between groups revealed that the study has 10% power based on PDSS-2 total scores, 17% power based on PDSS-2 total scores excluding those who did not have sleep issue, and 5% power based on NMSQ. In addition, to achieve 80% power based on PDSS-2 total scores (sub-analysis result), the current study would need 88 people in total (44 for each group). Thus, the findings in this study should be interpreted with caution. A lack of statistical power and large variability due to small sample size may have affected the results, potentially causing a lack of significant group differences in sleep quality and comprehensive NMS. A larger sample size in future studies will increase statistical power and may show group differences, since our results showed trends that QG may generate greater improvement in sleep quality and comprehensive NMS compared with SQG.

The dropout rate was high (47%). The most common reason for dropouts was ‘lost interest’ (n = 7; 4 QG and 3 SQG) that happened during the first 6 weeks of the study. However, it is unclear why those participants lost interest. Possibly, those participants in both QG and SQG might have felt the intervention was not helpful since they could not see the benefits within the first 6 weeks. Intervention fidelity has been a concern in the current study. Intervention fidelity is the degree to which the intervention is delivered properly as the researcher originally intended [38,39]. In the current study, we did not have any formal evaluation and documentation of intervention fidelity. To enhance the intervention fidelity, future studies may consider suggestions (e.g., online signing in before practice at home, development of consistent treatment fidelity plan) proposed by a recent review on intervention fidelity in Qigong studies [40].

In this study, we evaluated mood disorder in the study participants using two measurements of GAI and GDS that were initially designed for mood assessment in older adults [24,25]. Among 17 participants, 10 participants were older than 65, while the ages of the rest of participants ranged between 56 and 64 years old. A previous study reported good diagnostic sensitivity and specificity of GDS for adults aged 18 and older [41]. However, the reliability and validity of GAI for adults younger than 65 years old has not been investigated. Future studies may need to consider this limitation.

In conclusion, Qigong exercise may alleviate sleep disorders and NMS in people with PD. However, the results of this pilot study should be carefully interpreted due to limitations. NMS are an important aspect of PD, which can significantly impact QOL. It is essential to understand NMS and develop an effective treatment for NMS. Qigong exercise may have potential as a treatment option for NMS in people with PD, but more rigorous studies are needed to provide definitive evidence.