Music therapy improves sleep quality in acute and chronic sleep disorders: A meta-analysis of 10 randomized studies

International Journal of Nursing Studies 51 (2014) 51–62

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Music therapy improves sleep quality in acute and chronic sleep disorders: A meta-analysis of 10 randomized studies Chun-Fang Wang *, Ying-Li Sun, Hong-Xin Zang Department of Cardiovascular Surgery, Center for Cardiovascular Disease, Pingjin Hospital, Logistics University of Chinese People’s Armed Police Forces, Tianjin, PR China

A R T I C L E I N F O

A B S T R A C T

Article history: Received 14 November 2012 Received in revised form 5 March 2013 Accepted 16 March 2013

Objective: To evaluate the efficacy of music therapy for acute and chronic sleep disorders in adults. Design: Systematic review and meta-analysis. Data sources: A systematic search of publications in PubMed, Embase, and the Cochrane Library without language restriction was performed. Review methods: Studies with randomized controlled design and adult participants were included if music was applied in a passive way to improve sleep quality. Subgroup analysis was conducted to explore the sources of heterogeneity. Results: Ten studies involving 557 participants were identified. The sleep quality was improved significantly by music (standard mean difference: 0.63; 95% CI: 0.92 to 0.34; p < 0.001), with significant heterogeneity across studies. Subgroup analysis found heterogeneity between subgroups with objective or subjective assessing methods of sleep quality, and between subgroups with difference follow-up durations. No evidence of publication bias was observed. Conclusion: Music can assist in improving sleep quality of patients with acute and chronic sleep disorders. For chronic sleep disorders, music showed a cumulative dose effect and a follow-up duration more than three weeks is necessary for assessing its efficacy. ß 2013 Elsevier Ltd. All rights reserved.

Keywords: Music Sleep disorders Sleep quality Meta-analysis

What is already known about the topic?  Chronic sleep disorders are associated with adverse health outcomes.  Acute sleep disorders of patients after operation or patients in intensive care unit are associated with worse prognosis.  Music has been used to improve the sleep quality from an ancient time, but prospective clinical trials presented conflicting results.

What this paper adds  Music can assist in treating both acute and chronic sleep disorders.  For chronic sleep disorders, music therapy shows a cumulative dose effect.  A follow-up duration more than three weeks is necessary for assessing the efficacy of music for chronic sleep disorders. 1. Introduction

* Corresponding author at: Department of Cardiovascular Surgery, Pingjin Hospital, No. 220 Chenglin Street, 300126 Tianjin, China. Tel.: +86 022 60577599; fax: +86 022 60577600. E-mail address: [email protected] (C.-F. Wang). 0020-7489/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijnurstu.2013.03.008

Sleep is a primitive behavior of humans. Unfortunately, according to epidemiological studies, about one third of adults reported sleep disorders (Krueger and Friedman, 2009), especially in older and shift-workers (Kronholm

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et al., 2008; Rowshan Ravan et al., 2010). As to in-hospital patients, duo to the change of environments and the noise of medical equipments, acute sleep deprivation is common, especially in peri-operative patients or patients in intensive care unit (Hardin, 2009; Kamdar et al., 2012). Chronic sleep disorders have proved to be associated with adverse health outcomes, including cardiovascular disorders (Cappuccio et al., 2011; Chien et al., 2010), total mortality (Cappuccio et al., 2010a, 2010b; Castro-Costa et al., 2011; Kronholm et al., 2011), type 2 diabetes (Cappuccio et al., 2010a, 2010b), respiratory disorders (Penzel et al., 2007), and obesity (Cappuccio et al., 2008). In addition, acute sleep deprivation can also worsen the prognosis. Pharmacological therapy has been wildly used to treat sleep disorders, but the potential side effects limit a longterm intervention. Realizing that sleep is affected by both physiological and psychological factors, people resorted to kinds of mind-body interventions such as music therapy, which indeed have been used from a very ancient time (Cervellin and Lippi, 2011). In fact, music is the most welcomed method used by nurses to improve the patients’ sleep quality (Bouhairie et al., 2006). Some earlier studies succeeded to prove the efficacy of music in improving sleep quality (Kullich et al., 2003; Lai and Good, 2005; Renzi et al., 2000; Zimmerman et al., 1996). Although a previous meta-analysis (de Niet et al., 2009) recommended the music-assisted relaxation to patients with sleep disorders, the evidence was limited because only 5 studies were available at that time. The result was challenged by several recent studies with negative results (Chan et al., 2010; Chang et al., 2012), and we noticed that only one study included in that mateanalysis showed negative result (Hernandez-Ruiz, 2005). With accumulating evidence, our goal was to evaluate the efficacy of music for sleep disorders by conducting a metaanalysis of prospective cohort studies. 2. Methods 2.1. Search strategy and study selection We attempted to follow the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guideline to report the present meta-analysis (Moher et al., 2009). We systematically searched the electronic databases PubMed, Embase, and the Cochrane Library without language restriction. The following search terms were used: sleep, sleep quality, insomnia, music, music intervention, music relaxation, music therapy. The reference lists of original and review articles were reviewed to identify any additional relevant studies. Studies were included in the meta analysis if they met the following criteria: (1) a randomized controlled design, (2) adult population over 18 years of age were involved, (3) music was applied in a passive way to improve sleep quality, (4) the sleep quality was assessed using a subjective or objective method. Studies were excluded if: (1) participants suffering neurological or severe cognitive disorders were enrolled, (2) active use of music was used as intervention, such as playing instruments. If

multiple published articles from the same study were available, only the article with the most detailed information was included. 2.2. Data extraction and study quality Our primary outcome was the sleep quality which was assessed using subjective methods such as questionnaire, or objective methods such as polysomnography. All literature search results were screened independently by two authors (W-CF and S-YL) for potentially relevant articles, and uncertainty or disagreement were resolved by discussion and consensus. Data extraction was performed using a standardized protocol and data-collection form. Extracted data included the first author’s name, year of publication, study population, the sample size, participants’ age and gender, duration of follow-up, the intervention for each group, method to assess the sleep quality, and result in each group. Studies were assessed for quality by randomization, blinding, reporting of withdrawals, generation of random numbers, and concealment of allocation. Trials scored one point for each area addressed, with a possible score between 0 and 5 (Moher et al., 1998). 2.3. Statistical analysis Since continuous data from different scales were extracted, the standardized mean difference (SMD) was used as the measure of effect and the results were expressed as a SMD with 95% confidence intervals (CIs). SMD is calculated by dividing the mean difference in each study by the study’s deviation, which makes the results comparable across studies. It should be noted that SMD is an index without unit, and the results of 0.2 are usually interpreted as small, those of 0.5 as moderate and from 0.8 as large. The heterogeneity among studies was tested by Qstatistic (significance level at p < 0.10) and I-statistic (Higgins et al., 2003). The result of I-statistic is I2, which describes the percentage of total variation across studies that is due to heterogeneity rather than due to chance, where high values of the index (I2 > 50%) indicate the existence of heterogeneity. The combined SMD were computed using fixed-effects models with no evidence of significant heterogeneity. In the presence of heterogeneity, random-effects models are more appropriate because they assume that the effect being estimated in the different studies are not identical. Publication bias was assessed with funnel plots and Egger regression test (Egger et al., 1997). Sensitivity analysis was performed to explore the influence of individual studies by deleting 1 study in each turn. Subgroup analysis was conducted to assess possible sources of heterogeneity by checking the heterogeneity between subgroups with different average ages, geographical locations, or follow-up durations, with acute or chronic sleep disorders, and with subjective or objective sleep quality assessing methods. Significant heterogeneity between subgroups indicates that the subgroup factor may explain part of the total heterogeneity. A p-value < 0.05 was considered to be statistically significant. All statistical analyses were performed using Stata software (version 11.0; Stata Corporation, College

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Fig. 1. Flow chart of study selection.

Richards-Campbell Sleep Questionnaire (RCSQ), five studies used the Pittsburgh Sleep Quality Index (PSQI), another one study used the Verran and Synder-Halpern (VSH) sleeping scale, and the remaining study used a visual analog scale (VAS). Two studies used polysomnography to measure the quality of sleep. Among the objective sleep measures that polysomnography supplied, we selected the sleep efficiency (total sleep time/total recording time) as our primary outcome.

Station, TX) and REVMAN software (version 5.0; Cochrane Collaboration, Oxford, United Kingdom). 3. Results 3.1. Main features of included studies Two hundred and twenty-seven articles were obtained from the initial search. Ten studies involving 557 participants were identified based on our criteria (Chan et al., 2010; Chang et al., 2012; Harmat et al., 2008; Hernandez-Ruiz, 2005; Kullich et al., 2003; Lai and Good, 2005; Renzi et al., 2000; Richards, 1998; Ryu et al., 2012; Zimmerman et al., 1996) (Fig. 1). The excluded studies are listed in the Appendix. All articles were in English except one in German. Two studies were found to be published twice in separate articles (Chan, 2011; Chan et al., 2010; Lai and Good, 2005, 2006), and the most detailed one was selected. The characteristics of these studies are presented in Table 1. Four studies focused on post-operative acute sleep disorders in hospital with the follow-up durations less than 4 days. The other 6 studies focused on chronic sleep disorders, 2 of them with the follow-up durations between 4 and 5 days and the remaining 4 studies with the durations between 3 and 4 weeks. Eight studies used subjective, self-rating scale to measure the quality of sleep. One study used the

3.2. Music and sleep quality The outcomes with different methods were not directly comparable. A high PSQI value means a lower sleep quality, while a high RCSQ, VSH or SE value means the opposite. The scores of RCSQ, VSH or SE were converted by subtracting the real score from the maximum score. The quality of sleep was improved significantly by music (SMD: 0.63; 95% CI: 0.92 to 0.34; Z = 4.24, p < 0.001; Fig. 2) using random-effect model, with significant heterogeneity (I2 = 64%; X2 = 24.88, p = 0.003). Similar effects were shown between subgroups with acute or chronic sleep disorders ((I2 = 0%; X2 = 0.40, p = 0.53). The funnel plot was inspected and found to be roughly symmetrical, and the Egger regression test also showed no evidence of significant publication bias (p = 0.42).

Table 1 Characteristics of included studies. Author

Year

Age (mean)

Male (%)

Simple size

Country

Followup duration

Participants’ characteristics

Measure

Quality score

Zimmerman Richards Renzi

1996 1998 2000

67 66 46

68 100 60

96 69 86

USA USA Italy

2 days 1 day 1 day

RCSQ PSG VAS

2 2 3

Kullich Hernandez-Ruiz Lai Harmat Chan Chang Ryu

2003 2005 2005 2008 2010 2012 2012

48 35 67 23 76 32 61

65 28 60 94 42 50 58

Austria USA Taiwan Hungary Hong Kong Taiwan South Korea

3 5 3 3 4 4 1

In hospital, post-CABG In hospital, CCU In hospital, post-anorectal operation In stationary rehabilitation Abused women in shelter In community Students in university In community Volunteer In hospital, post-coronary angiography

PSQI PSQI PSQI PSQI PSQI PSG VSH

2 2 4 4 4 4 4

63 0 /* 22 45 6 66

weeks days weeks weeks weeks days day

CABG = Coronary artery bypass grafting; CCU = Coronary care unit; RCSQ = Richards-Campbell Sleep Questionnaire; PSG = Polysomnography; VAS = Visual analog scale; PAQI = Pittsburgh Sleep Quality Index; VSH = Verran and Synder-Halpern sleeping scale. * Data were not reported.

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Fig. 2. Forest plot shows difference of sleep quality between participants with music therapy and control group, expressed as standardized mean difference (SMD).

3.3. Sensitivity and subgroup analysis

4. Discussion

Exclusion of any single study did not materially alter the overall SMD, with a range from 0.55 (95% CI: 0.83 to 0.28) to 0.72(95% CI: 0.98 to 0.47). No heterogeneity was found between subgroups with different average ages, participants from hospital or not, or different geographical locations. Significant heterogeneity was presented between studies with different follow-up durations, and with subjective or objective sleep quality assessing methods. Significant pooled effect was only shown in studies with follow-up duration shorter than 4 days or longer than 2 weeks, and with subjective methods (Table 2).

This study shows music can help to improve the quality of sleep in a wild range of populations, including patients after operation with acute sleep disorders, as well as students in university and elders in community with chronic sleep disorders. Similar results were shown in subgroups with different ages or geographical locations. Substantial heterogeneity was observed among all studies. Subgroup analysis found heterogeneity between subgroups with objective or subjective methods, and with different follow-up durations, but not between inpatients and participants out of hospital. The heterogeneity could mostly be explained by the negative results in studies which focused on chronic sleep disorders but with the follow-up durations less than 3 weeks. Actually, a cumulative dose effect was showed in four of the included studies (Chan et al., 2010; Harmat et al., 2008; Kullich et al., 2003; Lai and Good, 2005), and the effect reached no plateau after 3 weeks. Previous studies also pointed out that 3 weeks is a recommended period of time for observing chronic changes of sleep patterns and the effects of a new intervention on sleep quality (Chan et al., 2010). It is a follow-up duration less than 3 weeks that resulted in the absence of positive efficacy of music therapy for chronic sleep disorders. Although the results of objective methods have proved to be closely related to subjective sleep quality, especially the index of sleep efficiency (Akerstedt et al., 1994; Kushida et al., 2001), no tool is available for a comprehensive assessment of sleep quality with varied objective indices like the subjective questionnaires, which may explains the slight heterogeneity between them. The consistence of results between participants from different geographical locations implies that music is a

Table 2 Subgroup analyses to explore sources of heterogeneity. Subgroups

Sleep quality Studies

SMD (95% CI), p for heterogeneity

Geographic location USA and Europe Asia

6 4

0.65( 0.91 to 0.38) 0.61( 1.03 to 0.08) p = 0.91

Average age (years) 35 35–65 >65

3 3 4

0.47( 1.41 to 0.48) 0.81( 1.29 to 0.33) 0.60( 0.91 to 0.29) p = 0.72

Follow-up duration <4 days 4 days to 2 weeks 3 weeks to 4 weeks

4 2 4

0.74( 1.13 to 0.34) 0.02( 0.44 to 0.48) 0.79( 1.21 to 0.37) p = 0.02

Sleep quality assessing methods Objective 2 Subjective 8 SMD = standardized mean difference.

0.06( 0.60 to 0.48) 0.77( 1.04 to 0.50) p = 0.02

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fundamental aspect of human experience and deeply ingrained in all cultures. Although some studies in Asia used traditional music other than western classic music which was mostly used in other studies, these music pieces are all characterized by a tempo of 60–80 beats per minute, slow stable rhythm, low-frequency tones, and soothing and relaxing melodies. Familiarity to the selected music may improve the compliance which should be considered when implying the music therapy (Chi and Young, 2011). The possible underlying mechanisms are not fully understood. As to acute sleep disorders, previous evidence showed that music was effective for pre-operative anxiety (Beccaloni, 2011; Pittman and Kridli, 2011), as well as postoperative pain (Engwall and Duppils, 2009). The improvement of sleep quality presented in the studies with postoperative patients can be obviously attributed to the music-induced relief of anxiety and pain, which may cause acute sleep disorders. Music acts upon the central nervous system, especially the deeper, more ancient parts of the brain such as limbic system. In addition, music also has an effect on the modulation of endogenous opioids and oxytocin (Bernatzky et al., 2011), which may contribute to the efficacy of music therapy for chronic sleep disorders. However, more researches are needed to explore the mechanisms of kinds of sleep disorders and how music affects them in different ways. Music therapy is low cost and safe, is easy to learn, and could be used readily by nurses in hospital as well as health-care professionals in community. For peri-operative patients, nurses can offer sleep-inducing music to help them sleep and relax. The accidence of chronic sleep disorders is high in elderly people. Health-care professionals can encourage them to listen to appropriate music as an alternative self-care skill and provide them with adequate advice, which may help to improve their quality of sleep and life. It should be noted that our results were limited because of the relatively small size of each included study, and the efficacy of music for sleep disorders should be tested in larger studies involving populations with acute or chronic sleep disorders separately. When music is used to improve sleep quality, the key issues are the selection of music and the protocol to conduct the intervention. Although the pieces of music selected in previous studies shared in some common characteristics, some studies identified that the efficacy of music is affected by the listeners’ enjoyment of music (Nilsson, 2011) and preferred music has the most beneficial effects (Lai, 2004). There is a need to compare the different types of music on sleep and investigate how the music affects sleep in a different way. A comprehensive list of recommended pieces of music should be developed in the future research, which can offer a wide range of selection to meet various preferences. Standard protocol or guideline to conduct the music therapy has not been established. Future researches are needed to determine the preferred duration of music playing, the appropriate time to play the music before bedtime, and how to make a comfortable condition which is necessary to ensure the participants paying all their attention on listening to the music.

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4.1. Limitations There are several limitations to our analysis. First, the nature of this intervention makes a double-blinding design impossible. Secondly, the sample size in each study is relatively small. Thirdly, the quality of some studies is relatively low. Some earlier studies did not detail the methods to generate the random numbers and/or declare the concealment of allocation, which got quality scores 2 or 3. Fourthly, substantial heterogeneity was presented. Although the major source of heterogeneity was detected through subgroup analysis, uncontrolled or unmeasured factors potentially produce bias. Fifthly, the longest followup duration was no more than 4 weeks which left it unclear that whether the efficacy of music can maintain or even be better after a longer follow-up. Sixthly, although SMD was used to pool the results, the difference between various subjective methods used in studies could still induce a significant heterogeneity and bias. Finally, various objective indices were presented by polysomnography, but we only assessed the sleep efficiency which may miss some other useful information.

5. Conclusion Music appears to be effective in treating acute and chronic sleep disorders. It is low cost and safe, and could be used to improve sleep quality in various populations with different ages and culture backgrounds, in hospital or in community. Our study also gives an indication that music shows a cumulative dose effect for chronic sleep disorders. A follow-up duration more than three weeks is necessary for assessing the efficacy of music, which have an implication for the design of trial evaluating the efficacy of music therapy for chronic sleep disorders. Conflict of interest: None declared. Funding: None. Ethical approval: None.

Appendix 1. List of the excluded articles and the reasons for exclusion Wrong exposure Ansfield, M.E., Wegner, D.M., Bowser, R., 1996. Ironic effects of sleep urgency. Behav. Res. Ther. 34 (7), 523–531. (The effects of low mental load music and high mental load music were compared.) Gitanjali, B., 1998. Effect of the Karnatic music raga ‘‘Neelambari’’ on sleep architecture. Indian J. Physiol. Pharmacol. 42 (1), 119–122. (Neelambai rage and Kalyani rage (rage is a kind of classic Indian Karnatic system of music) were compared.) Lai, H.L., Li, Y.M., Lee, L.H., 2012. Effects of music intervention with nursing presence and recorded music on psycho-physiological indices of cancer patient caregivers. J. Clin. Nurs. 21 (5–6), 745–756. (Two music interventions (music with and without nursing presence) were compared.)

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Levin Ia, I., 1997. [‘‘Music of the Brain’’ in the treatment of insomnia patients]. Zh. Nevrol. Psikhiatr. Im. S S Korsakova 97 (4), 39–43. Levin Ya, I., 1998. ‘‘Brain music’’ in the treatment of patients with insomnia. Neurosci. Behav. Physiol. 28 (3), 330–335. (The ‘brain music’ was investigated in these two studies, which was created by a program that could transform the spontaneous bioelectrical activity of the brain to music. The participants in the exprimental group was treated with their individual ‘brain music’, while the participants in the control group with other one’s music.) Robinson, S.B., Weitzel, T., Henderson, L., 2005. The Sh-hh-h Project: nonpharmacological interventions. Holist. Nurs. Pract. 19 (6), 263–266. (A complex intervention was assessed, and music was only a little part of this intervention.) Wrong outcome Bonnet, M.H., Arand, D.L., 2000. The impact of music upon sleep tendency as measured by the multiple sleep latency test and maintenance of wakefulness test. Physiol. Behav. 71 (5), 485–492. (The ability to remain awake was used as the outcome.) Bozcuk, H., Artac, M., Kara, A., Ozdogan, M., Sualp, Y., Topcu, Z., Karaagacli, A., Yildiz, M., Savas, B., 2006. Does music exposure during chemotherapy improve quality of life in early breast cancer patients? A pilot study. Med. Sci. Monit. 12 (5), CR200–205. (The outcome was the quality of life.) de Niet, G., Tiemens, B., van Achterberg, T., Hutschemaekers, G., 2011. Applicability of two brief evidence-based interventions to improve sleep quality in inpatient mental health care. Int. J. Ment. Health Nurs. 20 (5), 319–327. (The appliability of music therapy was assessed.) Diaz, M., Larsen, B., 2005. Preparing for successful surgery: an implementation study. Perm. J. 9 (3), 23–27. (Postoperative pain and perioperative anxity but not the qulity of sleep were evaluated.) Iwaki, T., Tanaka, H., Hori, T., 2003. The effects of preferred familiar music on falling asleep. J. Music Ther. 40 (1), 15–26. (The purpose of this study was to examine whether or not listening to music promotes falling sleep. The quality of sleep was not assessed.) Wrong population de Niet, G., Tiemens, B., Hutschemaekers, G., 2010. Can mental healthcare nurses improve sleep quality for inpatients? Br. J. Nurs. 19 (17), 1100–1105. (The participants were all with severe mental health problems and in psychiatric admission ward.) Tan, L.P., 2004. The effects of background music on quality of sleep in elementary school children. J. Music Ther. 41 (2), 128–150. (Elementary school children were involved in this study.) Self-control design Bloch, B., Reshef, A., Vadas, L., Haliba, Y., Ziv, N., Kremer, I., Haimov, I., 2010. The effects of music relaxation on sleep quality and emotional measures in people living with schizophrenia. J. Music Ther. 47 (1), 27–52. Hughes, C.M., McCullough, C.A., Bradbury, I., Boyde, C., Hume, D., Yuan, J., Quinn, F., McDonough, S.M., 2009. Acupuncture and reflexology for insomnia: a feasibility study. Acupunct. Med. 27 (4), 163–168.

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