Listening to music for improving sleep in adults with insomnia

  • Protocol
  • Intervention


  • Kira V Jespersen,

    Corresponding author
    1. Aarhus University, Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus, Jylland, Denmark
    • Kira V Jespersen, Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Nørrebrogade 44, Building 10G, Aarhus, Jylland, 8000, Denmark.

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  • Julian Koenig,

    1. SRH University Heidelberg, School of Therapeutic Sciences, Heidelberg, Baden-Württemberg, Germany
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  • Poul Jennum,

    1. Department of Clinical Neurophysiology, Glostrup Hospital, Danish Centre of Sleep Medicine, Glostrup, Denmark
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  • Peter Vuust

    1. Aarhus University, Department of Clinical Medicine, Center of Functionally Integrative Neuroscience (CFIN), Aarhus, Jylland, Denmark
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This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the effects of music listening on sleep quality in adults with insomnia and to assess the influence of specific variables that may moderate the effect.


Description of the condition

Insomnia is the most common sleep disorder and affects millions of people worldwide. Insomnia can be defined as a complaint of disturbed sleep in the presence of adequate opportunity and circumstance for sleep (NIH 2005). The three main diagnostic manuals present varying approaches to diagnosing insomnia. The fourth edition of the American Psychiatric Association's Diagnostic and Statistical Manual (DSM-IV) defines primary insomnia as a subjective complaint of difficulty initiating or maintaining sleep, or non-restorative sleep, that lasts for at least one month (APA 1994). The sleep disturbance causes clinically significant distress or impairment in social, occupational or other important areas of functioning. The sleep disorder must not be due to the direct effects of a substance and must not occur exclusively during another general medical condition, mental disorder or specific sleep disorder (APA 1994). The World Health Organization's International Classification of Diseases (ICD-10) includes a frequency criteria and distinguishes between non-organic sleep disorders and sleep disturbances with a presumed organic basic (WHO 1992). The revised edition of the International Classification of Sleep Disorders (ICSD-2), produced by the American Academy of Sleep Medicine, has several insomnia subtypes based on specific descriptive, etiologic categories (AASM 2005).

Estimates of the prevalence of insomnia vary according to the definitions used. A review of epidemiological studies of insomnia found that about one third of the general population experiences insomnia symptoms, but when daytime consequences were included, the prevalence rate drops to 9 to 15% (Ohayon 2002). When looking at insomnia diagnoses according to the DSM-IV criteria, there was a prevalence of 6%, with primary insomnia as the most frequent diagnosis (2 to 4%) followed by insomnia related to another mental disorder (1 to 3%) (Ohayon 2002).

Insomnia is often comorbid with medical or psychiatric illness. Studies have found consistent associations between insomnia and depression, anxiety disorders and other psychological disorders, as well as substance abuse and dependence. Furthermore, insomnia is associated with a number of medical problems such as decreased immune functioning (Taylor 2003), cardiovascular disorders, hypertension, chronic pain, breathing difficulties and gastrointestinal and urinary problems (Taylor 2007). Insomnia it itself can have a number of negative daytime consequences, and it is well recognised that people with insomnia experience impairments in everyday life such as fatigue and irritability (Riedel 2000; Shekleton 2010). People with insomnia report significantly lower scores on quality of life than those without insomnia, and the reduction in quality of life is correlated with insomnia severity (Leger 2001). Important areas of life such as occupational function and social relations seem to be affected and insomnia is associated with higher work absenteeism and increased risk of accidents. As such, it is a condition with great costs for both the individual and society (Walsh 2004).

Description of the intervention

Treatments for insomnia include pharmacotherapy (medication), psychological and behavioral interventions, and a variety of complementary and alternative therapies. Basic education in sleep hygiene is commonly used to inform patients about lifestyle and environmental factors that may interfere with or promote sleep (Morin 2005). Although good sleep hygiene can be helpful, it is not considered sufficient for more severe and chronic insomnia. The most common treatment of insomnia is the use of pharmacotherapy either as over-the-counter or prescription medications (NIH 2005). Benzodiazepine receptor agonists have been approved for the treatment of insomnia by the U.S. Food and Drug Administration, and studies have reported beneficial short-term effects of these agents. With the exception of eszopiclone, approved use is limited to 35 days or less (NIH 2005). There is some concern about the long-term use of these medications due to risk of abuse, dependence and adverse effects such as residual daytime sedation, cognitive impairments and reduced motor co-ordination. Furthermore, use of hypnotics has been associated with increased mortality (Kripke 2012).

Psychological and behavioral treatments have been found to have good efficiency for persistent insomnia (Morin 2006a). These treatments include cognitive behavioral therapy, stimulus control therapy, sleep restriction therapy and relaxation training, often combined in multi-component approaches. In spite of good results, the psychological and behavioral treatments appear to be under-utilised, perhaps because they require considerable time and effort for the patient (Krystal 2004). Furthermore, there is a problem of availability with relatively few well-trained professionals in the field (Wilson 2010).

Due to the current limitations of psychological and pharmachological treatments of insomnia, different alternative and complementary interventions are used by people with insomnia, and music is one of them. Studies show that listening to music is often used by adults as a self-help intervention to improve sleep (Urponen 1988; Morin 2006; Aritake-Okada 2009), and a simple Google search on 'music' and 'sleep' also reveals a huge market of music promoted for its sleep-inducing properties. However, the efficiency of music as intervention for insomnia remains unclear. Music is used as a therapeutic intervention in a number of areas, including pain relief (Cepeda 2006), psychiatry (Maratos 2008; Mössler 2011), neuro-rehabilitation (Bradt 2010) and for improving psychological outcomes in medical conditions such as cancer and heart disease (Bradt 2009; Bradt 2011). Research on the impact of music on sleep has evolved during the last 20 years, and methods for applying music listening to improve sleep quality vary across studies. Generally, the intervention involves the use of pre-recorded music in relation to sleep initiation. Music listening can be used passively, or it can be used actively with specific instructions. The duration of the intervention period and the time spent listening to the music may vary. The choice of music may be determined by the experimenter or by the participants themselves. Relatively few of the studies on music and insomnia are randomized controlled trials, and since the impact of the music intervention may differ depending on the design of the intervention, there is a need to evaluate the results of both randomized and quasi-randomized trials in order to retain valuable information.

How the intervention might work

The impact of music listening on sleep has been attributed to different mechanisms. Several authors argue that improvement of sleep is obtained because slow, soothing music enhances relaxation (Hernandez-Ruiz 2005; Lai 2005; Deshmukh 2009; Jespersen 2012). This suggestion is substantiated by studies showing reduced levels of cortisol as an effect of music listening (Nilsson 2009; Koelsch 2011), as well as changes in heart-rate and blood pressure (Trappe 2010; Korhan 2011; Su 2012). These studies show that music can affect various physiological measures that reflect autonomic nervous system responses, and, as such, slow, soothing music may lead to a decrease in sympathetic arousal and thus improve sleep (Su 2012). On a psychological level, studies have found that listening to music can reduce anxiety and stress responses (Dileo 2007; Zhang 2012), which can lead to greater relaxation and improvement of sleep. Another possible mechanism in the effect of music on sleep is the distracting properties of music. Hernandez-Ruiz 2005 suggests that music can function as a focal point of attention that distracts from stressful thoughts and thereby improves sleep. A number of individual factors are also likely to influence the music experience, such as age and gender (Juslin 2011; Nieminen 2012), music preference (Vuust 2010), musical training (Vuust 2006, Brattico 2009) and culture (Hargreaves 1997). Differences in effect may therefore be found depending on the type of music, the etiology of the insomnia symptoms and the length of the intervention.

Why it is important to do this review

Music is commonly used to relieve sleep problems and the use of music as a non-pharmacological intervention offers potential advantages of easy administration, low cost and safety. Clinical trials have been performed to investigate the effect of music on sleep, but it remains unclear if the existing evidence is rigorous enough to reach a conclusion about whether it improves sleep. A systematic review is needed to establish the efficacy of music listening for improvement of sleep quality and thereby refute or validate the popular belief that music is helpful for sleep.


To assess the effects of music listening on sleep quality in adults with insomnia and to assess the influence of specific variables that may moderate the effect.


Criteria for considering studies for this review

Types of studies

We will consider randomized controlled trials (RCTs) and quasi-randomized trials (qRCTs) (in which participants are allocated to groups on the basis of a quasi-random process such as date of birth or alternate numbers for inclusion). Since blinding a participant to the treatment (music) is not possible, we will include unblinded or single-blinded trials.

Types of participants

We will include studies that evaluate the effect of music on sleep in:

  • adults with insomnia as documented by standardized measures (for example, the Pittsburgh Sleep Quality Index (Buysse 1989), objective measures (for example, polysomnography or actigraphy) or by reports/diaries kept by participants, relatives or other informants;


  • people diagnosed with a sleep disorder by standard diagnostic criteria such as International Classification of Diseases (WHO 1992), Diagnostic and Statistical Manual of Mental Disorders (APA 1994) or International Classification of Sleep Disorders (AASM 2005), or with a complaint of sleep problems.

Types of interventions

The intervention to be studied is listening to music with or without relaxation instructions. The intervention can be self-administered or administered by research personnel. We will investigate two comparisons: 1) the effect of music intervention compared with a no music control group; 2) the effect of music intervention adjunctive to other treatment versus other treatment alone. The other treatment can be pharmacological, psychological or alternative complementary treatment as long as the intervention and control group receive the same treatment.

Types of outcome measures

Primary outcomes

The outcomes of interest are sleep and insomnia symptoms as measured by sleep diary, polysomnography and actigraphy or by standardized scales related to sleep (for example, Pittsburgh Sleep Quality Index (PQSI) or Insomnia Severity Index (ISI)). Furthermore, adverse events are considered primary outcomes to establish the safety of the intervention.

  1. Sleep quality

  2. Sleep onset latency

  3. Total sleep time

  4. Sleep interruption (number of awakenings and wake after sleep onset)

  5. Sleep efficiency (per cent of time in bed spent asleep)

  6. Adverse events (as reported by trialists; for example, discomfort or hearing loss)

These primary outcomes will be presented in a 'Summary of findings' table.

Secondary outcomes

The outcomes of interest are the waking correlates and consequences of insomnia. The relevant measures include the following.

  1. Psychological outcomes

    1. depression

    2. anxiety

    3. quality of life

  2. Physical outcomes

    1. fatigue

    2. daytime sleepiness

    3. pain

  3. Physiological outcomes

    1. heart rate

    2. heart rate variability

    3. blood pressure

The psychological outcomes will be measured by standardized questionnaires with established reliability and validity (for example, Beck Depression Inventory (Beck 1996), State-Trait Anxiety Inventory (Spielberger 1983), SF-36 (Ware 1992)). Physical outcomes need to be measured with standardized procedures such as the multiple sleep latency test (MSLT) or validated rating scales. Physiological outcomes need to be measured with standardized procedures, such as electrocardiogram.

We will take into consideration the study period and follow-up as described in the included studies. When assessing the outcomes in relation to time points, we will group the data as follows: immediate post-intervention, short term (post-intervention to one month), medium term (between one and three months follow-up) and long term (more than three months follow-up).

Search methods for identification of studies

We will attempt to identify all relevant studies irrespective of language. There will be no language restrictions for either searching or trial inclusion. Non-English articles will be assessed and translated.

Electronic searches

To identify the relevant studies, we will search the following electronic databases.

  1. Cochrane Central Register of Controlled Trials (CENTRAL) part of The Cochrane Library




  5. PsycINFO

  6. Web Of Science (Science Citation Index Expanded, Social Sciences Citation Index, Arts and Humanities Citation Index, Conference Proceedings Citation Index - Science and Conference Proceedings Citation Index - Social Science and Humanities)



  9. Current Controlled Trials (

  10. RILM Abstracts of Music Literature

We will use the following search strategy to search MEDLINE (PubMed format).

#1 music [mh]
#2 music therapy [mh]
#3 music*
#4 #1 or #2 or #3
#5 sleep [mh]
#6 sleep disorders [mh]
#7 sleep*
#8 insomnia*
#9 wakeful*
#10 sleepless*
#11 dyssomn*
#12 #5 or #6 or #7 or #8 or #9 or #10 or #11
#13 randomized controlled trial [pt]
#14 controlled clinical trial [pt]
#15 clinical trial [pt]
#16 clinical trial as topic [mh]
#17 randomized [tiab]
#18 placebo [tiab]
#19 randomly [tiab]
#20 trial [tiab]
#21 #13 or #14 or #15 or #16 or #17 or #18 or #19 or #20
#22 #4 and #12 and #21

The search strategies for the other databases will be based on this search strategy and modified where necessary.

Searching other resources

We will handsearch the following journals.

  1. Australian Journal of Music Therapy (1990 to present)

  2. British Journal of Music Therapy (1987 to present)

  3. Canadian Journal of Music Therapy (1993 to present)

  4. New Zealand Journal of Music Therapy (2010 to present)

  5. Nordic Journal of Music Therapy (1992 to present)

  6. Music and Medicine (2009 to present)

  7. Music Therapy Perspectives (2004 to present)

  8. Music Therapy Today (online) (2001 to present)

  9. Voices (online) (2001 to present)

  10. The International Journal of Arts Medicine (1991 to 1999)

  11. Journal of Music Therapy (1980 to present)

  12. The Arts in Psychotherapy (1980 to present)

  13. Musik-,Tanz- und Kunsttherapie (German) (1995 to present)

  14. Musiktherapeutische Umschau (German) (1980 to present)

  15. Musik und Gesundsein (German) (2011 to present)

We will search the bibliographies of retrieved articles and relevant reviews to identify potential trials missed by the electronic searches. We will also perform a citation search in ISI Web of Science and identify studies that have cited any of the relevant studies retrieved by the search, and thereby discover more recent studies that may have been missed.

For the identification of unpublished trials, we will contact experts in the field and search conference proceedings databases and trials registers.

Data collection and analysis

Selection of studies

Two authors (KVJ and JK) will independently screen all titles and abstracts. All papers where title or abstract refer to a trial on music and sleep will be retrieved in full. In cases of insufficient information in title or abstract to decide the relevance of the paper, it will be retrieved in full. The two authors will independently review the full texts and use a previously prepared inclusion criteria form to assess the trial's eligibility for inclusion. Disagreements will be discussed and a third review author (PV) will be involved in making the final decision. We will keep a record of excluded articles and the reason for their exclusion.

Data extraction and management

Data will be extracted using a standardized coding form by the first two review authors who will be blinded to each other’s assessment. Disagreements will be solved by consensus. If outcome data is not available, we will contact the authors of the study.

From each trial, we will extract the following information.

1. General information

  • author

  • year of publication

  • title

  • journal (title, volume, pages) or if unpublished source

  • country

  • language of publication

2. Study design

  • design (for example, parallel or cross-over design)

  • method of randomization (and concealment)

  • nature of the control group (for example, no treatment or treatment as usual)

  • losses to follow-up

  • blinding of study evaluators

  • washout period in cross-over design

  • inclusion criteria

  • exclusion criteria

3. Participants

  • total sample size

  • number of experimental group

  • number of control group

  • age

  • gender

  • ethnicity

  • diagnosis

  • comorbidities

  • sleep quality (and reason for poor sleep)

  • duration of disorder

  • previous or additional treatments

4. Intervention

  • type of music employed (characteristics)

  • music selection (selected by participant or researcher)

  • who provided the music (participant or research personal)

  • length and frequency of intervention sessions

  • Intervention period (duration of intervention)

  • how participants were exposed to music (for example, headphones or loudspeakers)

  • listening instructions

5. Outcomes

  • methods of sleep assessment

  • secondary outcome measures

  • pre-test means and post-test means or change scores and standard deviations, for all groups for all outcomes specified above

  • baseline differences

  • follow-up period

Assessment of risk of bias in included studies

The risk of bias will be assessed by two authors independently (KVJ and JK), using the tool described (and the criteria outlined) in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). Disagreements will be solved by discussion with the fourth author (PV). If information is absent for evaluation of the methodological criteria, authors will be contacted to obtain further information.

Each study will be graded for risk of bias in each of the following domains.

Random sequence generation (checking for possible selection bias)

We will describe the method used to generate the allocation sequence for each included study in sufficient detail to allow an assessment of whether it produces comparable groups.

We will assess the risk of bias as:

  • low risk of bias (adequate method of random sequence generation: for example, any truly random process such as random number table; computer random number generator);

  • high risk of bias (inadequate method of random sequence generation: for example, any non-random process such as odd or even date of birth; hospital or clinic record number);

  • unclear risk of bias (insufficient information about the method of random sequence generation to permit judgement of ‘low risk’ or ‘high risk’).

Allocation concealment (checking for possible selection bias)

We will describe the method used to conceal the allocation sequence for each included study and determine whether intervention allocation could have been foreseen in advance of or during recruitment or changed after assignment.

We will assess the risk of bias as:

  • low risk of bias (adequate method of allocation concealment: for example, telephone or central randomization; consecutively numbered sealed opaque envelopes);

  • high risk of bias (inadequate method of allocation concealment: for example, open random allocation; unsealed or non-opaque envelopes, alternation; date of birth);

  • unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk’).

Blinding of participants and personnel (checking for possible performance bias)

We will describe the different methods used to blind personnel from knowledge of which intervention a participant received for each included study. Since blinding a participant to the treatment (music) is not possible we will judge studies at low risk of bias if we judge that the lack of blinding is not affecting the results. We will assess blinding of participants and personnel separately for different outcomes or classes of outcomes, since we expect certain outcomes (for example lab measurements and physiological data such as heart rate or blood pressure) to be unaffected by blinding of participants and personnel.

We will assess the risk of bias of blinding personnel as:

  • low risk of bias (adequate method of blinding or outcome is not likely to be influenced by lack of blinding);

  • high risk of bias (inadequate method of blinding or outcome is likely to be influenced by lack of blinding);

  • unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk’).

Blinding of outcome assessment

We will describe the methods used to blind outcome assessment for each included study. We will assess blinding separately for different outcomes or classes of outcomes, as stated in (3).

We will assess the risk of bias as:

  • low risk of bias (adequate method of blinding or outcome is not likely to be influenced by lack of blinding);

  • high risk of bias (inadequate method of blinding or outcome is likely to be influenced by lack of blinding);

  • unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk’).

Incomplete outcome data (checking for possible attrition bias through withdrawals, dropouts, protocol deviations)

We will assess data on attrition, exclusions and reasons to determine whether they would introduce bias. We will describe the completeness of data for each included study, and for each outcome or class of outcomes. We will report whether attrition and exclusions are reported, the numbers of participants included at each stage of the analysis (compared with the total participants randomized), whether reasons for attrition or exclusion are reported, and whether missing data are balanced across groups or are likely to be related to outcomes.

We will judged whether incomplete data is dealt with adequately and assess the risk of bias as:

  • low risk of bias (no missing outcome data or balanced missing outcome data or appropriate methods of imputing missing data);

  • high risk of bias (missing outcome data or unbalanced missing outcome data or inappropriate methods of imputing missing data);

  • unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk’).

Selective reporting bias

We will investigate the possibility of selective outcome reporting bias for each included study. We will try to access study protocols of respective studies as source to judge selective reporting.

We will assess the risk of bias as:

  • low risk of bias (all pre-specified and expected outcomes are reported);

  • high risk of bias (not all pre-specified and expected outcomes are reported, outcome that was not pre-specified is reported, outcome is reported incompletely);

  • unclear risk of bias (insufficient information to permit judgement of ‘low risk’ or ‘high risk’).

Other bias

We will investigate other risks of bias, specifically risk of bias from baseline differences and risk of bias from carry-over or period effect for cross-over trials.

We will assess the risk of bias as:

  • low risk of bias (the study appears to be free of other sources of bias);

  • high risk of bias (there is at least one important risk of bias);

  • unclear risk of bias (insufficient information to permit judgement).

With reference to domains (1) to (6) above, we will assess the likely magnitude and direction of the bias and whether we consider it is likely to impact on the findings. We will explore the impact of the level of bias through undertaking sensitivity analyses – see Sensitivity analysis.

Measures of treatment effect

Two authors independently will extract data from the studies identified for inclusion to ensure accuracy. We will use Review Manager 5 (RevMan 2011) for data entry and analysis.

Dichotomous data

For dichotomous data, we will present the results as summary odd ratios with 95% confidence intervals (CI).

Continuous data

Continuous outcomes will be analyzed using mean difference (MD) if outcomes are measured on the same scale (for example, PSQI) between trials. We will use the standardized mean difference (SMD) to combine trials that measured the same outcome, but used different scales. All outcome will be presented using 95% confidence intervals. If a study provides multiple, interchangeable measures of the same construct at the same time point, we will calculate the average standard mean difference (SMD) across these outcomes, and the average of their estimated variances. Where studies report the same outcomes using continuous and dichotomous measures, we will re-express odds ratios as standardized mean differences allowing dichotomous and continuous data to be pooled together as described in section nine of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011).

Ordinal data

Ordinal data measured on scales (for example, sleep quality on visual analogue scales) we will analyze as continuous data and the intervention effect will be expressed as a difference in means. Ordinal data measured on shorter scales will be analyzed as dichotomous data by combining categories and the intervention effect will be expressed using OR.

Unit of analysis issues

Cluster-randomized trials

We anticipate that trials using clustered randomization will have controlled for clustering effects. In case of doubt, we will contact the first authors to ask for individual participant data to calculate an estimate of the intracluster correlation coefficient (ICC). If this is not possible, we will obtain external estimates of the ICC from a similar trial or from a study of a similar population or as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). When the ICC is established, we will use it to re-analyze the trial data. If ICCs from other sources are used, we will report this and conduct sensitivity analyses to investigate the effect of variation in the ICC.

Cross-over trials

Cross-over trials will be analyzed using combined data from all study periods, or using first period data if combined data is not available.

Studies with more than two treatment arms

If a study has multiple treatment arms, we will only use comparisons between the music intervention and the control/treatment as usual group. If more than one of the interventions is a music intervention and there is sufficient information in the trial to assess the similarity of the interventions, we will combine similar music interventions to allow for a single pair-wise comparison.

Dealing with missing data

For included studies, we will note levels of attrition. Where information or clarification about the presented data set is missing in the study reports, or there is a lack of detail or a discrepancy between different reports, we will try to retrieve relevant information by contacting the authors of the study. In case of missing data due to loss to follow-up or drop-out, we will attempt to obtain complete outcome data from authors, to include all participants randomized to each group in the analyses. If any outcome data remains missing or if authors do not respond within a reasonable time, we will analyze data on an available case basis, based on the numbers of participants for whom outcome data (continuous and dichotomous) is known. We will not impute missing data. We will explore the impact of including studies with high levels of missing data by performing sensitivity analyses based on consideration of best case and worst case scenarios. The potential impact of missing data on the findings of the review will be adressed in the 'Discussion' section of the review.

Assessment of heterogeneity

We will assess clinical and methodological heterogeneity by examining the characteristics of the studies. The similarity between interventions (for example, dose, frequency), participants (for example, age) and trial design (for example, allocation concealment, blinding, losses to follow-up) and the outcomes will be reported. Heterogeneity of treatment response will be assessed visually from the forest plot of the risk ratio and using the Chi² test. In addition, heterogeneity will be assessed statistically according to the standard method using the I² statistic, calculated for each comparison on each outcome. Substantial heterogeneity will be assumed if I² is greater than 50%, indicating that 50% of the variability in the outcome cannot be explained by sampling variation. Where significant heterogeneity is present, we intend to investigate it by subgroup analysis based on the participant clinical characteristics and interventions of the included studies as mentioned below.

Assessment of reporting biases

If we suspect reporting bias, we will contact study authors asking them to provide missing outcome data. If sufficient study data are available for individual outcomes, funnel plots will be inspected for evidence of reporting or publication bias. We will assess funnel plot asymmetry visually and statistically by means of the Bee and Mazumdar (Begg 1994) and the Egger et al tests (Egger 1997), if sufficient studies are available. If asymmetry is suggested by visual assessment or detected in any of these tests, we will perform exploratory analyses to investigate if it reflects a publication bias or a true relationship between trial size and effect size. We attempt to minimize the potential for publication bias by our comprehensive search strategy that includes evaluating published and unpublished literature.

Data synthesis

We will enter all trials included in the systematic review into Review Manager 5 (RevMan 2011) and will check for data entry errors. A meta-analysis will be conducted when there are data from at least two included studies and in the absence of substantial heterogeneity. We will undertake meta-analyses using both fixed-effect and random-effects models. In case of agreement between the results of both analyses (with confidence intervals of fixed-effect analyses being included in that of the random-effects analysis), the results from random-effects models will be reported, as it conveys better the variability. If fixed-effect and random-effect models give different results, possible sources of heterogeneity or inconsistency among trials in the magnitude or direction of effects will be investigated.

Subgroup analysis and investigation of heterogeneity

Depending on the data reported and where heterogeneity is found, we will carry out the following subgroup analyses (ranked for importance).

  1. Duration and dosage of the intervention (dosage as 15, 30, 45 or 60 minutes listening time, and duration as number of days of intervention: short, 1 to 4 days; medium, 5 to 20 days; and long, 21 days or more).

  2. Etiology of insomnia (for example, psychological disorders, medical conditions or age-related sleep problems).

  3. Subjective versus objective measure of sleep quality.

  4. Participant-selected music versus researcher-selected music.

  5. Music listening alone versus music listening with relaxation instructions.

The subgroup analyses are exploratory and will be conducted as recommended in the Cochrane Handbook for Systematic Reviews of Interventions, section 9.6 (Higgins 2011).

Sensitivity analysis

Where possible, we will conduct sensitivity analyses to determine the impact of study quality and risk of bias on the results of meta-analyses. Planned analyses include (1) excluding studies with inadequate method of random sequence generation, (2) excluding studies using inadequate methods of allocation concealment, (3) excluding studies using inadequate methods of blinding personnel or (4) excluding studies using inadequate methods of blinding outcome assessment.


We would like to thank the editorial team of the Cochrane Developmental, Psychosocial and Learning Problems Group (CDPLPG) for their assistance.

Contributions of authors

Co-ordinate the review: Kira Vibe Jespersen
Draft the protocol: Kira Vibe Jespersen, Julian Koenig, Poul Jennum and Peter Vuust
Develop a search strategy: Peter Vuust and Kira Vibe Jespersen
Select which trials to include: Kira Vibe Jespersen and Julian Koenig
Arbitrate in the event of dispute: Peter Vuust
Extract data from trials: Julian Koenig and Kira Vibe Jespersen
Enter data into RevMan software: Kira Vibe Jespersen
Carry out the analysis: Julian Koenig and Kira Vibe Jespersen
Interpret the analysis: Peter Vuust, Julian Koenig, Poul Jennum and Kira Vibe Jespersen
Draft the final review: Kira Vibe Jespersen and Julian Koenig
Keep the review up to date: Kira Vibe Jespersen and Julian Koenig

Declarations of interest

Kira Jespersen - none known
Julian Koenig - none known
Peter Vuust - none known

Sources of support

Internal sources

  • Kira Vibe Jespersen: Clinic for Traumatized Refugees, Central Denmark Region, Denmark.

    Salary support

  • Peter Vuust: Center of Functionally Integrative Neurosciences, Aarhus University and the Royal Academy of Music, Aarhus, Denmark.

    Salary support

  • Julian Koenig: School of Therapeutic Sciences, SRH University Heidelberg, Germany.

    Salary support

External sources

  • No sources of support supplied