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Behavioral Sleep Medicine

ISSN: 1540-2002 (Print) 1540-2010 (Online) Journal homepage: http://www.tandfonline.com/loi/hbsm20

Mindfulness-Based Interventions for Insomnia: AMeta-Analysis of Randomized Controlled Trials

Yuan-Yuan Wang, Fei Wang, Wei Zheng, Ling Zhang, Chee H. Ng, Gabor S.Ungvari & Yu-Tao Xiang

To cite this article: Yuan-Yuan Wang, Fei Wang, Wei Zheng, Ling Zhang, Chee H. Ng, Gabor S.Ungvari & Yu-Tao Xiang (2018): Mindfulness-Based Interventions for Insomnia: A Meta-Analysis ofRandomized Controlled Trials, Behavioral Sleep Medicine, DOI: 10.1080/15402002.2018.1518228

To link to this article: https://doi.org/10.1080/15402002.2018.1518228

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Mindfulness-Based Interventions for Insomnia: A Meta-Analysis ofRandomized Controlled TrialsYuan-Yuan Wanga*, Fei Wangb*, Wei Zhengc*, Ling Zhangd*, Chee H. Nge, Gabor S. Ungvarif,and Yu-Tao Xianga

aFaculty of Health Sciences, University of Macau, Macao SAR, China; bGuangdong Mental Health Center, GuangdongGeneral Hospital & Guangdong Academy of Medical Sciences, Guangzhou, China; cThe Affiliated Brain Hospital ofGuangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, Guangdong, China; dThe National ClinicalResearch Center for Mental Disorders, China & Center of Depression, Beijing Institute for Brain Disorders & MoodDisorders Center, Beijing Anding Hospital, Capital Medical University, Beijing, China; eDepartment of Psychiatry,University of Melbourne, Melbourne, Victoria, Australia; fUniversity of Notre Dame Australia/Graylands Hospital,Perth, Australia

ABSTRACTObjective: Mindfulness-based interventions (MBIs) are clinically effective forinsomnia, but the research findings have been mixed. This meta-analysis ofrandomized controlled trials (RCTs) examined the effect of MBIs on insomnia.Method: Both English (PubMed, PsycINFO, Embase, and Cochrane Librarydatabases) and Chinese (WanFang and CNKI) databases were systematicallyand independently searched. Standardized mean differences (SMDs) and riskratio (RR) with their 95% confidence intervals (CIs) were calculated using therandom effects model. Results: Five RCTs (n = 520) comparing MBIs (n = 279)and control (n = 241) groups were identified and analyzed. Compared to thecontrol group, participants in the MBIs group showed significant improvementin insomnia as measured by the Pittsburgh Sleep Quality Index (n = 247; SMD:−1.01, 95% CI: −1.28 to −0.75, I2 = 0%, p < 0.00001) at post-MBIs assessment.Conclusion: In this comprehensive meta-analysis, MBIs appear to be effective inthe treatment of insomnia. Further studies to examine the long-term effects ofMBIs for insomnia are needed.

Insomnia is a common sleep disorder that is associated with increased risk of physical comorbidities,psychiatric disorders, impaired social function (Gong et al., 2016; Li et al., 2015; Ohayon & Bader,2010), and all-cause mortality (Araujo et al., 2017). Insomnia has been estimated to affect up to athird of the population globally based on different diagnoses (Ohayon, 2002). Common strategies fortreating insomnia include pharmacotherapy and psychosocial interventions, such as cognitivebehavioral therapy (CBT) and mindfulness-based interventions (MBIs). Both pharmacotherapyand psychosocial interventions are widely used to treat insomnia (Hohagen et al., 1994). CBT hasbeen regarded as a first-line treatment for chronic insomnia in many countries (Perlis & Smith,2008), with satisfactory effectiveness (Cheng & Dizon, 2012; Wang, Wang, & Tsai, 2005).

Mindfulness-based interventions (MBIs) are often used in treating insomnia (Wong et al.,2017; Zhang et al., 2015) and could improve insomnia and sleep quality (Black, O’Reilly,Olmstead, Breen, & Irwin, 2015; Bowden, Gaudry, An, & Gruzelier, 2012; Crain, Schonert-Reichl, & Roeser, 2017; Rao, Metri, Raghuram, & Hongasandra, 2017; Wong et al., 2017).

CONTACT Yu-Tao Xiang xyutly@gmail.com 3/F, Building E12, Faculty of Health Sciences, University of Macau, Avenida daUniversidade, Taipa, Macau SAR, China.

*These authors contributed equally to the work.Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/hbsm.

Supplemental data for this article can be accessed here.© 2018 Taylor & Francis Group, LLC

BEHAVIORAL SLEEP MEDICINEhttps://doi.org/10.1080/15402002.2018.1518228

Mindfulness emphasizes the awareness that emerges through purposeful attention to the presentmoment, with an accepting and nonjudgmental attitude (Kabat-Zinn, 2003). MBIs aim to reduceworry about the past or the future, and focus on everyday activities (Kanen, Nazir, Sedky, &Pradhan, 2015). MBIs consist of a number of brief interventions that incorporate mindfulness asa principle (Strauss, Cavanagh, Oliver, & Pettman, 2014), including the Mindfulness-BasedCognitive Therapy (MBCT), Mindfulness-Based Stress Reduction (MBSR) and other approacheswith modified or integrated mindfulness components. Of them, MBCT and MBSR are the mostwidely used in treating psychiatric disorders and related problems (Strauss et al., 2014). MBSRwas developed from the ancient tradition of mindfulness mediation established by Kabat-Zinnet al in 1970s, and was used as a method of healing (Kabat-Zinn, 2003). In contrast, MBCT wasdeveloped in the 1990s by integrating MBSR with cognitive therapy elements, which is now usedin the maintenance treatment for depression and insomnia (Kuyken et al., 2016; Segal, Williams,& Teasdale, 2012; Wong et al., 2017). Studies of insomnia treatments have compared MBIs andpharmacotherapy (Gross et al., 2011; Cohen’s d = −0.64 in sleep efficiency), CBT and pharma-cotherapy (Jacobs, Pace-Schott, Stickgold, & Otto, 2004; Cohen’s d = 1.1 in sleep efficiency), andMBIs and CBT (Garland et al., 2014; Cohen’s d = −2.76 in sleep efficiency), but the findingshave been mixed.

Several meta-analyses (Gong et al., 2016; Kanen et al., 2015) were conducted to examine the effect ofMBIs on sleep problems, but studies involving subjects with major medical conditions, such as cancerand osteoarthritis, were not excluded. Major medical conditions, including physical and psychiatriccomorbidities and medication-caused side effects, could influence the effect of MBIs on insomnia andlimit the generalizability of the findings (O’Donnell, 2004). In addition, several recent RCTs ofMBIs havebeen published and not been included in previous meta-analyses (Wei et al., 2017; Wong et al., 2017).

Thus, we performed a comprehensive meta-analysis of RCTs on MBIs for insomnia. We hypothe-sized that compared to control groups, MBIs would be more effective for improving insomnia.

Methods

Selection criteria

According to the PICOS acronym, the following inclusion criteria were used: Participants (P):participants with insomnia according to standardized diagnostic criteria, such as the ChineseClassification and Diagnostic Criteria for Mental Disorders, third edition (CCMD-3; Chen, 2002),the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; AmericanPsychiatric Association, 1994), and the International Statistical Classification of Diseases andRelated Health Problems, 10th revision (ICD-10; World Health Organization, 1992). Intervention(I): MBIs group including MBIs alone or MBIs plus other treatments (e.g., health education).Comparison (C): control group; that is, receiving other intervention (i.e., pharmacotherapy orsleep hygiene education) and blank control or waitlist control. Outcomes (O): the primary outcomemeasure was insomnia at post-MBI assessment as measured using standardized rating scales, such asthe Pittsburgh Sleep Quality Index (PSQI) (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989). Keysecondary outcome measures included other sleep-related data, such as sleep efficacy, total sleeptime, total wake time, and sleep quality. Study design (S): RCTs with meta-analyzable data. Casereports or series, qualitative reports, observational trials, nonrandomized studies, reviews, and meta-analyses were excluded. Studies conducted in patients with major medical conditions (e.g., cancer)were excluded.

Search methods

Both English (PubMed, PsycINFO, Embase, and Cochrane Library databases) and Chinese(WanFang, and CNKI) databases were systematically and independently searched by two

2 Y.-Y. WANG ET AL.

reviewers (YYW and FW), from their inception until August 16, 2017. The following searchterms were used: (“insomnia” OR “sleep” OR “early morning awakening” OR “maintenancedisorder” OR “dyssomnia” OR “sleepless”) AND (“mindfulness” OR “Mindfulness-BasedCognitive Therapy” OR “Mindfulness-Based Stress Reduction” OR “MBCT” OR “MBSR”)AND (“Random*” OR “control” OR “Randomized controlled trial”). Moreover, reference listsof the relevant reviews were hand-searched in order to avoid missing studies.

Data extraction

Two reviewers (YYW and FW) independently extracted the relevant data. Any inconsistency arisingin the process was discussed to reach an agreement or was resolved by referring to a third reviewer(YTX). Two studies reported both actigraphy and sleep diary data (Gross et al., 2011; Ong et al.,2014); in order to avoid interdependence, only actigraphy data were extracted. There was one study(Ong et al., 2014) with three treatment arms that compared the control group with two differentMBIs groups. Half of the participants in the control group were assigned to each MBIs arm to avoidinflating the number of participants in the control group.

Quality assessment

The quality of the included studies were assessed by the Cochrane risk of bias (Higgins &Green, 2014) and Jadad scale (Jadad et al., 1996), both of which are widely used qualityassessment tools for meta-analyses of RCTs. The Cochrane risk of bias assesses the aspectsof selection bias (random sequence generation and allocation concealment), reporting bias(selective reporting), blinding, attribution bias, and other sources of bias; while the Jadad scaleassesses the randomization, blinding, and withdrawals and dropouts of participants with thetotal score ranging from 3 to 4. Jadad total score < 3 was rated as low-quality; otherwise, it wasconsidered as high-quality (Jadad et al., 1996). The grading of recommendations assessment,development, and evaluation (GRADE) system (Atkins et al., 2004; Balshem et al., 2011) wasused to judge the evidence level of outcomes.

Data synthesis and statistical analyses

The Review Manager Version 5.3 (http://www.cochrane.org) and Comprehensive Meta-AnalysisV2.0 (www.meta-analysis.com) were used to synthesize data and conduct additional analyses.Considering the discrepancies in sampling methods, measurements, and demographic characteristicsbetween studies, the random effects model was used in all meta-analytic outcomes because it is moreconservative than the fixed-effects model (DerSimonian & Laird, 1986). Standardized mean differ-ence (SMD) with 95% confidence intervals (CIs) was used for continuous outcomes. Risk ratio (RR)± 95% CI was calculated for dichotomous data. Study heterogeneity was measured using I2, with I2

values greater than 50% indicating significant heterogeneity (Higgins, Thompson, Deeks, & Altman,2003). All meta-analytic outcomes were two-tailed, with significance level set at 0.05.

Results

Literature search and study characteristics

A total of 527 relevant hits were identified in the initial search. As shown in Figure 1, 5 RCTs with 11MBT treatment arms were included in the analyses. In Table 1, the pooled sample size was 520, with279 patients in the MBIs group and 241 in the control group. Study sites included China (3 RCTs,n = 436), the United States (2 RCTs, n = 84). The MBIs treatment duration ranged from 6 to8 weeks. One study in China used the CCMD-3 (Psychiatry Branch of the Chinese Medical

BEHAVIORAL SLEEP MEDICINE 3

Association, 2001), one study in China used DSM-IV (American Psychiatric Association, 1994),another study in Hong Kong used both DSM-IV (American Psychiatric Association, 1994) and ICD-10 (World Health Organization, 1992), and two U.S. studies used DSM-IV (American PsychiatricAssociation, 1994) and DSM-IV-TR (American Psychiatric Association, 2000). MBIs treatmentfrequency varied from 50 min per week for 6 weeks, to 2.5 hr per day for 8 weeks.

Assessment quality and quality of evidence

The risk of bias of the included studies is summarized in Supplemental Figure 1. Two RCTs weresingle blinded and all the others did not report blinding. Five RCTs described the random allocationsequence generation, and none mentioned allocation concealment. All studies were rated as low-riskin terms of attrition and reporting bias. Jadad scores ranged from 3 to 4 (Table 1). Of the 5 RCTs, allwere rated as high-quality. The quality of evidence of 5 outcome measures ranged from low-quality(80%) to moderate-quality (20%) according to the GRADE approach (Table 2).

Figure 1. PRISMA flow diagram.

4 Y.-Y. WANG ET AL.

Table1.

Characteristicsof

includ

edRC

Ts. Participants

Interventio

n

FirstAu

thor

(cou

ntry)

na

M(%

)aAg

e(y)a

Diagn

ostic

criteria

Design:

-Settin

g-Blinding

Type of MBIs

Duration

(wks)

Type

ofinterventio

ns;

nFrequencyof

MBIs

Follow-up

time

Outcomes

(Sleep

measures)

Dropo

utrate

(MBIs,

%)

Jadad

scorec

Wei

2017,

China(W

eiet

al.,2017)

160

43;

69/160

57.7

CCMD-3

-Hospital

-NR

MBSR

61.

MBSR+regu

lar

health

education;

n=80

2.Regu

larhealth

education;

n=80

50min/w

k6×

/wk

NR

PSQI

0; 0/80

3

Gross

2011,U

S(Gross

etal.,

2011)

3027;

8/30

NR

DSM

-IV-TR

-University

health

center

-NR

MBSR

81.

MBSR;

n=20

2.ph

armacotherapy;

n=10

2.5hclass/wk

+45

min

practiceat

least6days

aweek,

8×/w

k(+

aday-long

retreat)

3mon

thPSQI;actig

raph

y(TST

&SE)

5; 1/20

3

Ong

2014,U

S(Ong

etal.,

2014)

5426;

9/35

43.77

DSM

-IV-University

Medical

Center

-NR

MBSR

MBTI

81.

MBSR;

n=19

2.MBTI;n=19

3.Self-mon

itorin

g(SM)

cond

ition

;n=16

2.5h/d,

8×/w

k(+

one6-hretreat)

3&

6mon

thsb

actig

raph

y(TWT,

TST,SE)

MBSR

21;

4/19;

MBTI

0; 0/19

MBSR:

31;6

/19;

MBTU:

21;

4/19

3

Won

g2017,

China(HK)

(Won

get

al.,2017)

216

22;

47/216

56.1

DSM

-IVandICD-10

combined

-com

mun

ity&primary

care

-Singleblind

MBC

T8

1.MBC

T;n=111

2.Sleeppsycho

-educationwith

exercise

control(PEEC);n=105

2.5h/d,

8×/w

k3&

6mon

ths

Insomnia

severityIndex;

sleepdairy

(TST

&SE)

18;

18/101

4

Zhang2015,

China

(Zhang

etal.,2015)

6058;

35/60

78.1

DSM

-IV-hospital

-Singleblind

MBSR

81.

MBSR;

n=30

2.wait-listcontrol;

n=30

45min/d,8

×/w

kNR

PSQI

3; 1/30

4

Note.

a The

samplesize

was

derived

attherand

omizationassessment;gend

erprop

ortio

nandagewerederived

from

extractableinform

ation.

bOnly6mon

thsof

data

wereavailableforactig

raph

y.c Jadad

totalscore

<3was

ratedas

low-quality;otherwise,itwas

considered

ashigh

-quality.

Abbreviatio

ns:C

CMD-3,C

hinese

ClassificationandDiagn

ostic

Criteria

forMentalD

isorders,third

edition

;DSM

-IV,D

iagnostic

andStatisticalManualofMentalD

isorders,fourth

edition

;DSM

-IV-TR,

Diagnostic

andStatisticalManualofM

entalD

isorders,fourth

edition

,textrevision;d,day;ICD-10,theInternationalStatisticalClassificationof

DiseasesandRelatedHealth

Prob

lems,10th

revision

;M,male;

min,minute;

MBI,Mindfulness-Based

Interventio

n;MBC

T,Mindfulness-Based

Cogn

itive

Therapy;

MBSR,

Mindfulness-Based

Stress

Redu

ction;

MBTI,Mindfulness-Based

Therapyfor

Insomnia;PSQI,Pittsburgh

SleepQualityIndex;n,

numberof

patients;NR,

notrepo

rt;SE,sleepefficiency;TST,totalsleep

time;TW

T,totalw

aketim

e;wk,week.

BEHAVIORAL SLEEP MEDICINE 5

Insomnia assessed by PSQI at post-MBI assessment

Three RCTs with 3 treatment arms reported data on insomnia assessed by the PSQI at the post-MBIsassessment. Compared to the control group, the MBIs group showed significant improvement inpost-MBIs insomnia (n = 247; SMD: −1.01, 95% CI: −1.28 to −0.75, I2 = 0%, p < 0.00001, Figure 2).

Sleep efficiency at post-MBIs assessment

Three RCTs with 4 treatment arms provided data on sleep efficiency, with 3 arms using actigraphy(Gross et al., 2011; Ong et al., 2014), and 1 arm using sleep diary (Wong et al., 2017). There was nosignificant group difference in terms of sleep efficiency at post-MBIs assessment (n = 274; SMD:−0.07, 95% CI: −0.31 to 0.17, I2 = 0%, p = 0.58).

Sleep time at post-MBIs assessment

Three RCTs with 4 treatment arms reported data on total sleep time (TST), with 3 arms using actigraphy(Gross et al., 2011; Ong et al., 2014), and 1 arm using sleep diary (Wong et al., 2017). There was nosignificant group difference in terms of total sleep time at post-MBIs assessment (n = 274; SMD: −0.14,95% CI: −0.51 to 0.24, I2 = 29%, p = 0.47). One RCT with 2 treatment arms also reported total wake timeat post-MBIs using actigraphy (Ong et al., 2014), and there was no significant group difference in termsof total wake time at post-MBIs assessment (n = 54; SMD: 0.03, 95% CI: −0.55 to 0.61, I2 = 0%, p = 0.92).

Table 2. GRADE analyses.

Primary/secondaryoutcome

Studyarms (N)

Risk ofbias Inconsistency Indirectness Imprecision

Publicationbias

Largeeffect

Overall quality ofevidencea

Pittsburgh SleepQuality Index

3 (247) Seriousb No No No Seriousc No +/±/-/; Low

Sleep Efficacy 4 (274) Seriousb No No No Seriousc No +/+/-/-/; LowTotal Sleep Time 4 (274) Seriousb No No No Seriousc No +/+/-/-/; LowTotal Wake Time 2 (54) Seriousb No No No Seriousc No +/+/-/-/; LowDiscontinuation rate 6 (536) Seriousb No No No No No +/+/+/-/;

Moderate

Note. GRADE = grading of recommendations assessment, development, and evaluation.aGRADE Working Group grades of evidence: High-quality = further research is very unlikely to change our confidence in theestimate of effect. Moderate-quality = further research is likely to have an important impact on our confidence in the estimate ofeffect and may change the estimate. Low-quality = further research is very likely to have an important impact on our confidencein the estimate of effect and is likely to change the estimate. Very low-quality = we are very uncertain about the estimate.

bMeta-analytic studies (more than 50%) were open label studies or only mentioned random allocation without describing the method.cFor continuous outcomes, N < 400. For dichotomous outcomes, N < 300.

Figure 2. Effect of MBIs on PSQI at post-MBIs assessment.

6 Y.-Y. WANG ET AL.

All cause discontinuation

The discontinuation rate was not significantly different between the MBIs and control groups(n = 536, RR = 3.74, 95% CI: 0.74 to 18.90, I2 = 35%, p = 0.11). Only 5 RCTs with 6 treatmentarms were included for primary and secondary outcomes, thus we cannot assess publication bias byperforming a funnel plot or Egger’s test (Egger, Davey Smith, Schneider, & Minder, 1997).

Discussion

This updated and comprehensivemeta-analysis of RCTs on the effect ofMBIs on insomnia found thatMBIssignificantly improved insomnia symptoms, as measured by the PSQI, compared to control groups. Inaddition, the discontinuation rate was not different between the MBIs and control groups, which indicatesthat the treatment adherence to MBIs was satisfactory.

Several meta-analyses have examined the effect ofMBIs on sleep. Onemeta-analysis (Kanen et al., 2015)evaluated the effect of MBIs on sleep disturbances in the general population. Two earlier meta-analysesincluded participants with major medical conditions, such as cancer and osteoarthritis (Gong et al., 2016;Kanen et al., 2015). In order to increase the homogeneity of included studies, we excluded studies thatincluded participants with major medical conditions and only synthesized studies that used insomniadiagnostic criteria. In addition, we included recently published RCTs in both English andChinese databasesthatwere not previously included. Similar to an earliermeta-analysis (Gong et al., 2016), we found thatMBIscould significantly improve insomnia symptomsmeasured by the PSQI. Themechanism of the therapeuticeffects of MBIs on insomnia is not clear, although it is recognized that MBIs could improve emotionalregulation and reduce stress level (Zhang et al., 2015), which could in turn alleviate insomnia. Furthermore,another meta-analysis (Kanen et al., 2015) reported that the significant effects of MBIs on insomnia werefound only in subjective (i.e., the PSQI) but not in objective assessments (i.e., actigraphy). In this study, nosignificant group difference was found in terms of actigraphy data as well as sleep efficacy and sleep time atthe post-MBIs. Instead of assessing individual sleep parameters, the PSQI covers multiple aspects of sleepincluding sleep efficacy, sleep time, sleep latency, and daytime dysfunction, which therefore may be moresensitive in detecting the minor changes in insomnia symptoms.

The advantages of this meta-analysis are the inclusion of recently published RCTs (Wei et al., 2017;Wong et al., 2017) and the exclusion of those involving major medical conditions, which provide a morehomogeneous sample and avoid the confounding effects caused by major medical conditions. However,there are also several methodological limitations. First, the duration and frequency of MBIs varied acrossstudies; the dose-response ofMBIs for insomnia was thus difficult tomeasure. Second, the follow-up periodranged from 3 to 6 months, but insufficient data were available to analyze the long-term MBIs effect oninsomnia. Third, both theMBIs and control groups were heterogeneous: theMBIs groups includedMBCT,MBSR, and mindfulness-based therapy for insomnia, while the control groups included wait-list control,pharmacotherapy, self-monitoring condition and regular health education, all of which increased theheterogeneity of the outcomes. Fourth, although all included studies were rated as high-quality, the qualityof evidence of 5 outcomemeasures ranged from low-quality (80%) to moderate-quality (20%) according tothe GRADE approach. Fifth, three of the five included studies were from China and two from the UnitedStates, which limits the generalization of the findings to other populations. Finally, theMBIs group includedMBIs alone or MBIs plus other treatments. Other treatments, such as health education, may haveaugmentation effect and bias the efficacy of MBIs in insomnia.

Conclusions

This comprehensive meta-analysis of RCTs on MBIs for insomnia found that MBIs appear to have apositive effect on insomnia as measured by the PSQI. Further RCTs with larger samples and longerfollow-up are needed to confirm the findings.

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Acknowledgments

The study was supported by the University of Macau (SRG2014-00019-FHS; MYRG2015-00230-FHS; MYRG2016-00005-FHS). The University of Macau had no role in the study design, generating or interpreting the results andpublication of the study.

Conflict of interest

We declare that the authors have no competing interests.

Statement

All co-authors have seen and approved the manuscript. There is no conflict of interest concerning the authors inconducting this study and preparing the manuscript.

Funding

This work was supported by the University of Macau [SRG2014-00019-FHS; MYRG2015-00230-FHS; MYRG2016-00].

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