artículo musicoterapia

Clinical Psychology Review 29 (2009) 193–207

Contents lists available at ScienceDirect

Clinical Psychology Review

Dose–response relationship in music therapy for people with serious mentaldisorders: Systematic review and meta-analysis

Christian Gold a,⁎, Hans Petter Solli b,c, Viggo Krüger b, Stein Atle Lie a

a Unifob Health, Bergen, Norwayb University of Bergen, Norwayc Lovisenberg Diakonale Hospital, Oslo, Norway

⁎ Corresponding author. Unifob Health, Grieg AcademE-mail address: [email protected] (C. Gold)

0272-7358/$ – see front matter © 2009 Elsevier Ltd. Aldoi:10.1016/j.cpr.2009.01.001

a b s t r a c t
a r t i c l e i n f o
Article history:
Serious mental disorders h Received 30 June 2008Received in revised form 6 January 2009Accepted 12 January 2009
Keywords:PsychosisDepressionPsychotherapyDose–effect relationshipMixed-effects meta-analysis

ave considerable individual and societal impact, and traditional treatments mayshow limited effects. Music therapy may be beneficial in psychosis and depression, including treatment-resistant cases. The aim of this review was to examine the benefits of music therapy for people with seriousmental disorders. All existing prospective studies were combined using mixed-effects meta-analysis models,allowing to examine the influence of study design (RCT vs. CCT vs. pre-post study), type of disorder(psychotic vs. non-psychotic), and number of sessions. Results showed that music therapy, when added tostandard care, has strong and significant effects on global state, general symptoms, negative symptoms,depression, anxiety, functioning, and musical engagement. Significant dose–effect relationships wereidentified for general, negative, and depressive symptoms, as well as functioning, with explained varianceranging from 73% to 78%. Small effect sizes for these outcomes are achieved after 3 to 10, large effects after 16to 51 sessions. The findings suggest that music therapy is an effective treatment which helps people withpsychotic and non-psychotic severe mental disorders to improve global state, symptoms, and functioning.Slight improvements can be seen with a few therapy sessions, but longer courses or more frequent sessionsare needed to achieve more substantial benefits.

© 2009 Elsevier Ltd. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1941.1. Music therapy in mental health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1941.2. Music therapy—the evidence to date . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1951.3. Research questions addressed in this review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

2. Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.1. Criteria for selecting studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

2.1.1. Study design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.1.2. Study quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.1.3. Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.1.4. Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.1.5. Outcomes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

2.2. Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.3. Selection of studies and data extraction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.4. Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196

2.4.1. Individual study results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1962.4.2. Combination of study results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

3. Description of studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1973.1. Selection process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1973.2. General study characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1973.3. Interventions: Music therapy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1973.4. Comparison conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1973.5. Data extraction and preprocessing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

y Music Therapy Research Centre, Lars Hilles gate 3, 5015 Bergen, Norway. Tel.: +47 97501757..

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194 C. Gold et al. / Clinical Psychology Review 29 (2009) 193–207

4. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2004.1. Comparison of music therapy versus standard care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

4.1.1. General mental state . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2004.1.2. Negative symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2004.1.3. Depressive symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2004.1.4. Other symptoms: Anxiety and positive symptoms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2004.1.5. Functioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2014.1.6. Musical engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2014.1.7. Other outcomes: Global state, leaving the study early, quality of life, satisfaction, and medication level . . . . . . . . . . . . 203

4.2. Other outcomes and comparisons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2035. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203

5.1. Summary of findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2035.2. The evidence base for music therapy in mental health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2045.3. The dose–response relationship in music therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2045.4. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2045.5. Implications for practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2055.6. Implications for future research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206. Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206

Conflict of interest . . .

1. Introduction

Serious mental disorders are common and often long-lasting condi-tions with considerable impact on society and the individual. Seriousnessmay be defined by specific states generally considered as severe, such aspsychosis or suicidal behavior, by low level of functioning or a severeglobal impression, or by chronicity and treatment resistance. In acomprehensive international mental health survey (Demyttenaere et al.,2004), serious mental disorders were found to be prevalent in between0.4% inNigeria and7.7% in theUnited States. Seriousness in that studywasdefined as severe role impairment, severe overall functional impairment,substance dependence, or suicidality in conjunction with a mentaldisorder, irrespective of the particular diagnosis. Treatment options forpeoplewith seriousmental disorders includepsychopharmacological andpsychotherapeutic approaches. Both have been shown to be efficacious inmany but not in all patients, and notwithout limits. Many patients do notshow satisfactory improvement with these traditional approaches andcontinue to show substantial symptom levels and impaired functioning.There is therefore a need for additional, innovative forms of therapy tohelp people with serious mental disorders.

1.1. Music therapy in mental health

Music therapy is a special type of psychotherapy where forms ofmusical interaction and communication are used alongside verbalcommunication. It has been defined as “a systematic process ofintervention wherein the therapist helps the client to promote health,using music experiences and the relationships developing through themas dynamic forces of change” (Bruscia, 1998). The types of ‘musicexperiences’ used in music therapy can include free and structuredimprovisation, other types of active music-making by patients, andlistening to music. Improvisation is perhaps the most prominent form ofmusical interaction in music therapy. It has been described as central inmanymusic therapymodels. Client(s) and therapist improvise onmusicalinstruments they have chosen, playing together freely or with a givenstructure or a musical or non-musical theme. Music therapists arespecifically trained to intervene therapeutically within the medium, forexample to support by providing rhythmical or tonal grounding, toclarify, to confront or to challenge the client's expression in the music(Bruscia, 1987; Wigram, 2004). Other modes of music experiences inmusic therapy include playing composedmusic on instruments, singingandwriting or improvising songs (Baker &Wigram, 2005), and listeningto music (Grocke & Wigram, 2006). Songs may be used by clients as a

safe, structuring and socially acceptable form inwhich they can expressfeelings which otherwisemight be too overwhelming to express. Musiclistening may be helpful to bring up and make available therapeuticallyrelevant issues (emotions, associations, memories, identity issues).

All these different modes of ‘music experiences’ become therapeuticby being used in the context of a therapeutic relationship. Verbaldiscussions, reflections, or interpretations connected to the music areimportant to help clients explore the potential meaning of an experience,and to relate a new experiencewithin therapy to situations in the client'slife. The degree to which the music experience itself, versus the verbalreflection connected to it, is seen as the active agent of change may varybetween models of music therapy (Garred, 2004), as well as betweenclients. However, treatments that rely solely on the direct effects of musicalone,whichdonot “involveordependuponaprocessof interventionandchange within a client–therapist relationship” (“auxiliary level”, Bruscia,1998, p. 195), are not music therapy. The term ‘music medicine’ issometimes used to distinguish such treatments from music therapy.

In the context of treatment options for people with serious mentaldisorders, music therapy may fill an important gap which traditionaltherapies donotfill. Previous clinical reports (Rolvsjord, 2001; Solli, 2008)as well as research studies (Hannibal, 2005; Hanser & Thompson, 1994;Meschede, Bender, & Pfeiffer, 1983) have reported that music therapy hashelped some patients who did not benefit—or not sufficiently—fromexclusively verbal psychotherapy. Particularly some of the most severelydisturbed patients may not be able to use verbal language for them tochange. This may obviously concern non-verbal patients, but equallyimportantly verbal patients who are, for whatever reasons, unable toaddress their problems verbally. Some music therapy models alsospeculate that the preverbal qualities of music (in particular of freeimprovisation) may help to address early childhood traumas (Wigram,Nygaard Pedersen, & Bonde, 2002, p. 155). Research on mother–infantcommunication supports the notion of music as a medium which is insome ways similar to language, but less laden with referential semanticmeaning and more rooted in the communication at early developmentalstages (Trevarthen & Malloch, 2000). These qualities may enable itseffective use by patients who are too severely disturbed for purely verbalpsychotherapy.

Likewise, music therapy may be effective in an area of outcome inwhich psychopharmacological treatments show limited success—namelyin the area of negative symptoms, including affective flattening orblunting, poor social relationships, and low motivation, among others(Andreasen, 1982; Buckley & Stahl, 2007; Buchanan et al., 2007). Apreviousmeta-analysis of RCTs comparingmusic therapy as an additional

195C. Gold et al. / Clinical Psychology Review 29 (2009) 193–207

treatment to standard care alone for people with psychotic disorders,showed large effects on negative symptoms (Gold, Heldal, Dahle, &Wigram, 2005). This finding is also interesting because it may show somehints as towhatmay be regarded as the effective factors ofmusic therapy(or its ‘mechanisms of change’). First, music as a medium for emotionalexpression may help patients to improve their expressive range anddiminish affective flattening. Second, making music together is always asocial endeavor, inherently connected to forming and building socialrelationships, andmay therefore help patients to overcomedeficits in thisarea. And third, the possibility tomakemusic in therapymay be a centralmotivating factor, especially for patients who otherwise show little or nomotivation (Rolvsjord, 2001; Solli, 2008), which may then generalize toother situations. These domains, summarized as negative symptoms,were first described for schizophrenia but have been shown to be atransdiagnostic phenomenon which is relevant in non-psychotic mentaldisorders as well, particularly major depression (Winograd-Gurvich,Fitzgerald, Georgiou-Karistianis, Bradshaw, & White, 2006).

Generally, it can be said that music therapy is usually tailored to anindividual patient and his/her specific needs more than to a specificclinical diagnosis. There is usually no direct link between a patient'sclinical diagnosis and the specific techniques used in therapy,although the type of disorder will, as part of a larger picture, certainlyplay a role in forming the therapist's choices, attitudes and behaviorsduring a therapy. (Little research has been conducted to address thislink, but findings to date are that diagnosis explains only a smallfraction of the variation in techniques, e.g., Drieschner & Pioch, 2002.)Similarly, indications for music therapy in mental health may betransdiagnostic, and decisions to offer music therapy to an individualpatient in a given clinical setting may be based on many aspects ofwhich the primary clinical diagnosis is only one.

Many researchers have argued that dimensional concepts aremorevalid to describe psychopathology than categorical systems (Maser &Akiskal, 2002; Kendell & Jablensky, 2003; Krueger, Watson, & Barlow,2005). Continuities exist between healthy and disordered states aswell as between different disorders, and notably also betweenpsychotic and non-psychotic states (Cullberg, 2007; Maser & Akiskal,2002). The existing evidence for a continuum of mental healththerefore justifies the combination of psychotic with non-psychoticdisorders in a meta-analysis (as will be done here). The notion of sucha continuum also fits well with the practice of music therapy beingadapted more to a patient's needs than to his diagnosis.

1.2. Music therapy—the evidence to date

Several systematic reviews and meta-analyses have been con-ducted to examine the effects of music therapy in the field of mentalhealth (e.g., Dileo & Bradt, 2005; Gold, Heldal, et al., 2005; Gold,Voracek, & Wigram, 2004; Gold, Wigram, & Elefant, 2006; Koger,Chapin, & Brotons, 1999; Maratos, Gold, Wang, & Crawford, 2008;Pesek, 2007; Silverman, 2003; Vink, Birks, Bruinsma, & Scholten,2003). Many of these have found promising results; however, thequality of the included studies varied. Promising results, applyingrigorous study selection criteria, have been found in two recentCochrane reviews for psychotic disorders (Gold, Heldal et al., 2005)and for depression (Maratos et al., 2008). Both reviews suggested thatmusic therapy has a number of beneficial effects for these peoplewhen added to standard care. The review on schizophrenia alsosuggested some hints towards a ‘dose–effect’ relationship: Globalstate, general and negative symptoms and functioning improvedsignificantly and by large effect sizes in those studies where asufficiently large number of sessions were offered. However, bothreviews were limited by their very narrow inclusion criteria. Theschizophrenia reviewmeta-analyzed only four studies; the depressionreview did not include any meta-analysis and relied solely on anarrative summary. Therefore an analysis of dose–effect relationshipwas well beyond the scope of the previous Cochrane reviews.

In psychotherapeutic methods such as music therapy, the term‘dose’ or ‘dosage’ clearly must be understood metaphorically,not literally. Howard, Kopta, Krause, & Orlinsky (1986) have arguedthat although a therapymodel's proposed active ingredients (such asinterpretations, empathic reflections, etc.) might be consideredas the most theoretically coherent ‘unit of treatment’, these arenot easy to measure. However, the number of therapy sessions apatient has received is most likely correlated to a patient's exposureto those ingredients and can therefore be used as a readily availableproxy measure. The number of therapy sessions has been widelyaccepted as a measure of ‘dose’ in psychotherapy since this seminalpaper. The same paper also brought up a discussion on whether thedose–response relationship in psychotherapy is linear, or whetherthe first sessions have a greater influence than subsequent sessions.This discussion is still ongoing today, and therefore the presentreview aims at examining both possibilities for the field of musictherapy.

The previous Cochrane reviews of the effects of music therapy onschizophrenia (Gold, Heldal, et al., 2005) and depression (Maratos etal., 2008) chose very narrow inclusion criteria because they wereaimed at selecting only the most reliable evidence for one particularmental disorder. This narrow focus, while helping to achieve highreliability, also necessarily limited the generalizability of its findings inseveral ways:

• Focus on only one mental disorder: As described above, musictherapy is not usually targeted at a specific diagnosis, but ratherbroad in its goals and methods. This is reflected in some studies thatused a mixed patient sample (e.g., de l'Etoile, 2002; Thaut, 1989),which would consequently have to be excluded in any reviewfocusing on one selected diagnosis. A transdiagnostic focus alsoseems appropriate given the relevance of dimensional concepts inmental health as summarized above.

• Exclusion of non-randomized studies: While ensuring that the mostreliable evidence is used, an exclusive focus on randomized studiesalso has its drawbacks. For example, external validity—the extent towhich studies are generalizable to everyday clinical practice—maybe higher in some of the non-randomized studies. RCTs on complexinterventions are difficult to conduct, so that clinically desirablefeatures may in some cases be given too little attention. This may forexample concern the selection of subjects, the contents of therapy,and the duration of therapy and follow-up. Excluding non-randomized studies also implies that there is less evidence todraw on, which will often make advanced statistical proceduressuch as meta-regression impossible to apply.

The present review attempted to overcome these weaknesses byapplying a wider focus, in the hope of enabling broader and clinicallymore useful generalizations.

1.3. Research questions addressed in this review

The aim of this reviewwas to examine the effects of music therapyfor people with serious mental disorders, based on all prospectivestudies (randomized studies, other controlled studies, uncontrolledpre-post studies). The main research questions addressed were asfollows:

1. Can the previously hypothesized influence of the number ofsessions on the effects of music therapy be confirmed andquantified? What shape does this ‘dose–response’ relationshiptake in music therapy? Is it possible to predict the numberofsessions needed for a small, medium, or large effect, respectively?

2. Does the type of mental disorder predict the effect of musictherapy? Does music therapy have a different impact on patientsthat are either psychotic or non-psychotic? Where would musictherapy be most indicated?

http://www.musictherapyworld.net/modules/mmmagazine/issues/20021018120155/20021018120645/DrieschnerMTT.pdf


In addition we also aimed to address how the type of study designmay be related to the estimated effect of music therapy. In contrast tothe main research questions above, the inclusion of study design as apotential predictor was less directly of clinical importance, but wasmainly related to examining the robustness of findings whenincluding ‘weaker’ study designs than RCTs.

2. Method

2.1. Criteria for selecting studies

2.1.1. Study designStudies with any prospective group design (RCTs, CCTs, and studies

without control groups) were considered relevant. Randomizedcontrolled trials (RCTs) were defined, according to the strict criteriaof the Cochrane Collaboration (Higgins & Green, 2008), as studieswhere participants were allocated to conditions through truerandomization (e.g., using lots, dice, or computer-generated rando-mization lists), as opposed to quasi-randomization (e.g., using patientnumbers or date of intake). Controlled clinical trials (CCTs) weredefinedmore loosely as any study using a control group intended to beequivalent in terms of patient characteristics (including quasi-randomization as well as matching techniques). Finally, an uncon-trolled study was defined as any other prospective design where allparticipants received the same interventions and baseline values wereavailable so that participants could be used as their own controls (e.g.,case series, pre-post design).

2.1.2. Study qualityStudies with more than 30% attrition rate were excluded. As other

important study quality characteristics, allocation concealment (inRCTs) and blindness were assessed and reported. Outcomes wereincluded if they were either adequately blinded or a self-report. Theywere also included if they were possibly blinded but the actual use ofblinding was uncertain. Outcomes that are definitely non-blindedpresent a high risk of bias and were excluded. This is in accordancewith the Cochrane Handbook (Higgins & Green, 2008).

2.1.3. ParticipantsStudy participants eligible for this review were adults with serious

mental disorders diagnosed by an international classification system.This included psychotic disorders as well as some non-psychoticdisorders such as borderline personality disorder, depression, bipolardisorder, and suicidality connected to a mental disorder. Seriousmental disorders are characterized by significant role disability(Demyttenaere et al., 2004), which could be indicated by low GAFscores or by admittance to in-patient treatment.

2.1.4. InterventionsStudies were included only if participants were offered music

therapy, according to the definition above. Most importantly, thisexcluded interventions of the ‘music medicine’ type, where musicalone is provided as a treatment, rather than using music asa medium within a psychotherapeutic process and relation-ship. Secondly, it had to be possible to disentangle musictherapy from other therapies. Comparison conditions could be notreatment, standard care, or an active control condition (i.e., adifferent therapy, a ‘placebo’ therapy, or a different type of musictherapy).

2.1.5. OutcomesAll outcomes of clinical relevance were considered, including

measures of general mental state, symptoms, and functioning, but alsooutcomes related to music and other patient- or service-relevantoutcomes such as quality of life, medication level, or satisfaction withcare. Continuous outcomes had to be assessed by a standardized

(preferably published) rating scale. They had to be assessed either as aself-report or by an independent (preferably blinded) rater. Ratings doneby therapists were excluded as they were definitely not blinded and atserious risk of being biased.

2.2. Search strategy

A comprehensive search strategy was applied to identify allrelevant studies. To avoid the pitfalls of publication bias and Englishlanguage publication bias, published as well as unpublished reports inany language were considered. Highly sensitive search strategies wereemployed in previous related reviews on music therapy for psychoticdisorders (Gold, Heldal, et al., 2005), for depression (Maratos, Gold,Wang, & Crawford, 2008), and for all mental disorders (Heldal & Dahle,2006), and the results from these searches were used for this review.Each of those previous searches included searching in relevantdatabases as well as hand searching. To identify any later trials, weused the following search strategies (May 2006):

(a) The trial database PsiTri, which contains structured informationon published and unpublished clinical trials in mental health,based on multiple database searches as well as hand searchesby several Cochrane groups, was searched for entries contain-ing the word “music” in any field.

(b) PubMed was searched using its “Clinical Queries” searchstrategy designed to identify scientifically strong studies oftherapy outcome, which was expanded with the MedicalSubject Headings (MeSH) term “Evaluation Studies”, andcrossed with the MeSH terms “Music Therapy” and “MentallyIll Persons” or “Mental Disorders”.

2.3. Selection of studies and data extraction

At least two reviewers independently assessed each potentiallyrelevant study for inclusion and extracted data from the includedstudies. Cases of disagreement were resolved by discussion.

2.4. Data analysis

2.4.1. Individual study resultsFor each study, odds ratios (OR) were calculated for dichotomous

outcomes and standardized mean differences (Hedges' g) forcontinuous outcomes. For continuous outcomes we first checked ifthere was evidence for skewness (floor or ceiling effects), which wethen attempted to remove by log-transformation if possible (i.e., if rawdata were available for that study). The effect size index Hedges' g issimilar to Cohen's d (and can be interpreted similarly), but corrects forsmall-sample bias and is therefore more conservative in smallsamples. For dichotomous outcomes with missing data, we assumedthe negative outcome for the missing cases. Effect estimates werecalculated in such a way that a beneficial effect of music therapy isalways represented by a positive effect size (for continuous outcomes)or by an odds ratio smaller than 1 (for dichotomous outcomes).

The different types of research designs were handled as follows inthe calculation: For RCTs, only post-test means were used, as thepretest was assumed to be equal in the populations due to therandomization. For CCTs, we used the post-test mean of theexperimental group, but subtracted the pretest difference betweengroups from the post-test mean of the control group in order to adjustfor existing pretest differences. For the studies without separatecontrol groups, we used the baseline values as control, thereby simplycomparing post-test versus pretest. There is some discussion in themeta-analytical literature on whether or not the correlation betweenpretest and post-test values should be taken into account. However,such a procedure would give relatively larger weight to the studieswith the weakest designs. We therefore decided not to make use of


these correlations in order not to give undue weight to those studies(see the related discussion in the appendix of Gold et al., 2004).

2.4.2. Combination of study resultsResults for the same type of outcome were combined across

studies in a meta-analysis. Results of different outcomes were notcombined. If the same outcome was measured with different scales inthe same study, both using equally valid methods (in terms of raterblinding and standardization and validity of instrument), the averageeffect size of these measures was used.

For the outcomes where data were available from at least fivestudies, we used mixed-effects meta-analysis, an extension of meta-regression, to examine simultaneously the following three predictors:study design (as a 3-level factor: RCT, CCT, uncontrolled), type ofdisorder (as a linear predictor: percentage of participants withpsychotic vs. non-psychotic disorders), and number of sessionsprovided (as a linear predictor; alternatively the square root ofsessions if this improved the model fit). Model fits using differentcombinations of predictors were compared using adjusted R2 (asrecommended by Tabachnick & Fidell, 2001, p. 147), and the modelyielding the best fit was selected. This was done in order to fit the databest to the figures and for the prediction of effect sizes.

Mixed-effectsmodels are usually preferred overfixed-effectsmodelsin the literature on meta-analysis and meta-regression (Everitt &Hothorn, 2006; Sutton, Abrams, Jones, Sheldon, & Song, 2000;Thompson & Higgins, 2002). In contrast to the simpler fixed-effectsmodels, mixed-effects models take into account possible randomvariation between the true effects of each study (between-studyheterogeneity not captured by the predictors) and are essentially moreconservative and less prone to bias. The appropriate study weights forthe mixed-effects models were calculated iteratively until theyconverged, as recommended and described in Sutton et al. (2000,p. 98). The open-source statistical software environment R, Version 2.6.1(R Development Core Team, 2007), was used for the statistical analyses.

For outcomes where data were available from at least two but lessthan five studies, traditionalmeta-analytic summarieswere calculated(as described in Cooper & Hedges, 1994). Study results were pooledusing a fixed effects model. When a substantial amount of statisticalheterogeneity (when I2N50%; Higgins & Green, 2008, p. 278) wasfound and could not be explained, we subsequently considered arandom effects model. We used R package meta, Version 0.8-2(Schwarzer, 2007), for these analyses, which replicates the proceduresin the Cochrane Collaboration's meta-analysis software.

3. Description of studies

3.1. Selection process

The various searches yielded initially 166 potentially relevantstudies for any mental disorder (Heldal & Dahle, 2006), 34 forschizophrenia (Gold, Heldal, et al., 2005), and 16 for depression(Maratos et al., 2008). The updated database searches did not identifyany newer studies. Studies were excluded if the design, participants,interventions, or outcomes, as assessed by two reviewers indepen-dently, did not meet the inclusion criteria for this review. In addition,some potentially relevant studies had to be excluded where we wereunable to retrieve the full text of the study report (Castilla-Puentes etal., 2002), where no usable outcome data were reported and attemptsto retrieve additional data directly from authors failed (Meschede etal., 1983; Schmuttermayer,1983), or where the drop-out rate exceeded30% (Steinberg et al., 1991).

3.2. General study characteristics

In result, fifteen studies were retained and included in the meta-analysis (Table 1). These included eight RCTs, three CCTs, and four

studies without control groups. Assessor blinding was adequate in sixstudies and uncertain in nine studies. Definitely non-blindedoutcomes in one study (Radulovic, 1996) were excluded from theanalysis. Nine countries and three continents are represented in theincluded studies, with six studies from Europe (Denmark, Germany,Italy, Serbia, UK), five from North and Central America (Mexico, USA),and four fromAsia (China, Japan). Together, the studies enrolled a totalof N=691 patients. In terms of their primary diagnosis, about twothirds (n=456) were diagnosed with a psychotic disorder and theremaining third (n=235) with a non-psychotic disorder, most oftendepression. There were three studies (de l'Etoile, 2002; Radulovic,1996; Thaut, 1989) that included both types of disorders; however,there were several further studies that included the various forms ofoverlaps such as schizoaffective or schizotypal disorder. Severity wasindicated in various ways, including psychoticism (11 studies),institutionalization (10 studies), classification as ‘chronic’ (6 studies),lack of response to other therapy (2 studies), and/or suicidality(1 study; see Table 1).

3.3. Interventions: Music therapy

Music therapywas offered between one and six times perweek overa period of one to six months. Themaximum number of sessions offeredin each study varied from six to 78 (if not specified directly in a report,this was calculated bymultiplying frequencywith duration—a potentialoverestimate as it doesnot take into account cancellations andholidays).Some of the studies (Troice & Sosa, 2003; Hayashi et al., 2002; Talwaret al., 2006; Zerhusen et al., 1995) also reported how many of thismaximum number actually were received by the patient, ranging from59% to 90% with a median of 73%. In the further calculations we usedsessions received if reported, and assumed 75% otherwise.

Music therapy was provided in group settings in two thirds of thestudies. Three studies (Hanser & Thompson, 1994; Pavlicevic, 1994;Talwar et al., 2006) used exclusively individual sessions; two studies(Thaut, 1989; Yang et al., 1998) combined group and individual sessions.Most studies used a combination of different working modes, such asimprovisation (described in 8, central in 4 studies), other forms ofplayingmusic on instruments (described in 8, central in 1 study), singingand/or writing songs (described in 6 studies), listening to music(described in 10, central in 6 studies), and verbal reflection around themusic experiences (described in 11, central in 4 studies; Table 1). In allstudies, music therapy was provided with some degree of process-orientation as well as some degree of structure; there seemed to be anagreement that both elements were necessary in working with thispopulation. Although there may have been some variation along thisdimension, we did not find an example that was extreme on either endof the scale (either extremely open or very rigidly structured). One study(Ceccato et al., 2006) compared approaches with more versus lessstructure.

Information concerning the theoretical background which informedthe approach was sparse. Some studies described a psychodynamic(Moe et al., 2000; Radulovic, 1996) or cognitive background (Hanser& Thompson, 1994), but most studies were less explicit in this respectand appeared to be eclectic in their theoretical orientation. Similarly,information concerning the qualification level of the music therapistwas infrequent, although this may reflect the different state ofdevelopment of the profession across countries. Studies from countrieswhere formalized registration requirements exist reported such boardor state registration (Hanser & Thompson, 1994; Talwar et al., 2006;Troice & Sosa, 2003); in other studies, therapists were more generallydescribed as trained, skilled, or experienced.

3.4. Comparison conditions

The most basic comparison, where music therapy is added tostandard care or minimal therapeutic contact, was available in all

Table 1Characteristics of included studies

Study Design and study quality Duration(months)

Participants

Clinical condition and setting Proportionof psychoticdisorders

Demographicsc Interventionsa Comparisonb,c Outcome scalesd

Typec No. of sessions

a) Randomized studiesChen(1992)

Design: ParallelAllocation concealment:UnknownBlindness: Not reported

2 Diagnosis: DepressionSetting: InpatientsCountry: China

0% N=68Age: 60-77 (M=64)Sex: 46% male

MT (P⁎, S), 6sessions pr. wk. of60 min., plusantidepressants.N=34

Offered: 48 Antidepressants. N=34 C) HAMDD) HARSG) Global state: Overall improvement

Unable to use: Confinement in bed

Hanser &Thompson(1994)

Design: ParallelAllocation concealment:UnknownBlindness: Not reported

2 Diagnosis: Major or minordepressive disorderHistory: 90% were insufficientlyimproved after previouspsychotherapySetting: OutpatientsCountry: USA

0% N=32Age: 61-86 (M=68)Sex: 23% male

MT (L⁎, V⁎, O), 1session pr. wk. of60 min. N=11

Offered: 8 1.) Minimaltherapeutic contact,consisting of weeklyphone talks of20 min. N=102.) No treatment.N=11

A) BSI GSIC) Geriatric Depression Scale, GDS

Not used (secondary measure):Depressed mood scale on Profile ofMood States, POMS

Not used (data not reported): BDID) Anxiety, Profile of Mood States,POMS; Hostility, POMSG) Rosenberg Self-Esteem Scale, RSE

Radulovic(1996)

Design: ParallelAllocation concealment:UnknownBlindness: Inadequate intherapist ratings (self-reports usable)

1.5 Diagnosis: Mood disorders,adjustment disorder,schizoaffective disorderSetting: InpatientsCountry: Serbia

2% N=60Age: 21-62Sex: 33% male

MT (L⁎, V⁎), 2sessions pr wk. of20 min., plusstandard care.N=30

Offered: 12 Standard care. N=30 C) BDINot used (non-blindedtherapist ratings): HAMDD) Not used (non-blinded therapistratings): HARS

Talwaret al.(2006)

Design: ParallelAllocation concealment:AdequateBlindness: Adequate(assessors blinded)

3 Diagnosis: SchizophreniaSetting: InpatientsCountry: UK

100% N=81Age: 18-64 (M=37)Sex: 74% male

MT (I⁎, V), 1 sessionpr. wk. of 50 min.,plus standard care.N=33

Offered:12; Attended:MdN=8

Standard care. N=48 A) PANSSB) PANSSD) Positive symptoms, PANSSE) GAFG) Quality of Life, SFQ Satisfactionwith care, CSQ Engagement withservices, HAS Unable to use: EPEX

Tanget al.(1994)

Design: ParallelAllocation concealment:UnknownBlindness: Adequate(assessor blinded)

1 Diagnosis: SchizophreniaHistory: Chronic (residualsubtype)Setting: InpatientsCountry: China

100% N=76Age: UnknownSex: Unknown

MT (L⁎, P, S, V), 5sessions pr. wk. of1 hr., plus standardcare. N=38

Offered: 19 Standard care. N=38 B) SANSE) Unable to use: Disability, DAS

Ulrichet al.(2007)

Design: ParallelAllocation concealment:AdequateBlindness: Adequate(assessors blinded)

1 Diagnosis: Schizophrenia,schizoaffective psychosis,schizotypal disorder, drug-induced psychosis, depressionwith psychotic symptomsSetting: InpatientsCountry: Germany

100% N=37Age: 22-58 (M=38)Sex: 54% male

MT (I, P, S, V), 2sessions pr. wk. of60-105 min., plusstandard care.N=21

Attended: 7.5 Standard care. N=16 B) SANSE) Social functioning, Giessen Test(self-report and observer rating)G) Quality of life, SPG

Satisfaction with care, unpublishedscale

Yang et al.(1998)

Design: ParallelAllocation concealment:UnknownBlindness: Unknown

3 Diagnosis: SchizophreniaHistory: Chronic (mean durationof illness 13 yrs.)Setting: InpatientsCountry: China

100% N=72Age: 21-55Sex: 59% male

MT (I, P, S, L, V), 6sessions pr. wk. of 2hrs., plus standardcare. N=41

Offered: 78(6 per week over3 months)

Standard care. N=31 A) BPRSB) SANSE) Social functioning, SDSIG) Global state: Clinically importantimprovement

Zerhusenet al.(1995)

Design: ParallelAllocation concealment:UnknownBlindness: Unknown

2.5 Diagnosis: DepressionSetting: Nursing home residentsCountry: USA

0% N=60Age: 70-82 (M=77)Sex: ca. 25% male

MT (L⁎, P), biweeklysessions of unknownlength. N=20

Offered: 20;Attended: 11.8(59% of 20)

1.) Cognitive therapy.N=20;2.) Standard care.N=20

C) BDI

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b) Other controlled studiesCeccatoet al.(2006)

Design: ParallelMatching: Age, sex,education, clinical history,cognitive deficitsBlindness: Unknown

4 Diagnosis: SchizophreniaSetting: Day patientsCountry: Italy

100% N=16Age: M=34(SD = 10)Sex: 81% male

1.) MT (L⁎), 1 sessionpr. wk. of 55 min.N=8. 2.) MT (I⁎),1 session pr. wk. of55 min. N=8.

Offered: 16 – B) (Attention: Paced Auditory SerialAddition Test, PASAT) (Memory:Wechsler Memory Scale, WMS)E) Social functioning: LifeSkills Profile, LSP

Hayashiet al.(2002)

Design: ParallelMatching: Age,education, marital status,clinical history, workstatus, medication doseBlindness: Not reported

4 (plus8-monthfollow-up inexperimentalgrouponly)

Diagnosis: Schizophrenia orschizoaffective psychosisHistory: Chronic (ward forlong-stay patients)Setting: InpatientsCountry: Japan

100% N=66Age: 43-84Sex: 0% male

MT (P, S, L, V),1 session pr. wk of1 hr., plus standardcare. N=34

Offered: 15;Attended:M=11.8, range3-15

Standard care.N=32

A) PANSSB) PANSSD) Positive symptoms, PANSSE) Unable to use (incompletelyreported): Ward life activity andadjustment, unpublished scaleF) Musical experiences,unpublished scaleG) Quality of Life Scale,QLS; Medication level

Pavlicevicet al.(1994)

Design: ParallelMatching: Age, sex,social class, clinical history,severity, musical experienceBlindness: Adequate(assessor blinded)

2.5 Diagnosis: SchizophreniaHistory: ChronicSetting: Day patientsCountry: UK

100% N=41Age: M=38 (SD = 9)Sex: 80% male

MT (I⁎), 1 session pr.wk. of 30 min., plusstandard care.N=21

Offered: 10 Minimaltherapeuticcontact (2sessions) plusstandardcare. N=20

A) BPRSB) SANSC) HAMDF) Music Interaction Rating forSchizophrenia, MIR(S)

c) Studies without control groupsde l'Etoile(2002)

Design: Pre-postBlindness: Not reported

1.5 Diagnosis: Schizophrenia,bipolar disorderHistory: All had previoustherapy, 63% (5/8) had a clinicalhistory of 10-20 yearsSetting: Day patientsCountry: USA

88% N=8Age: 30-45Sex: 75% male

MT (I, P, S, L, V, O),weekly sessions of60 min. N=8

Offered: 6 Baseline A) SCL-90R GSIC) Depression subscale of SCL-90RD) Obsessive-compulsive, Hostility,Paranoid deation, all SCL-90RsubscalesG) Not used: Attitude to seekinghelp (4 factors), Fisher & TurnerAttitude ScaleNot used: Helpfulness oftherapeutic factors(10 factors), unpublished scale

Moe et al.(2000)


6 Diagnosis: Schizotypal disorder,schizophrenia, schizoaffectivedisorderSetting: 89% (8/9)inpatients/day patientsCountry: Denmark

100% N=9Age: 23-40(M=29)Sex: 78% male

MT (L⁎, V⁎), 1session pr. wk. of90 min. N=9

Attended:Range 23-32

Baseline E) GAFG) Unable to use: Qualitativerating of therapy contents

Thaut(1989)

Design: Pre-postBlindness: Not applicable(self-reported outcomes only)

3 Diagnosis: Schizophrenia,bipolar disorder, depression,adjustment disorder,suicidal tendenciesSetting: Forensic patientsCountry: USA

70% N=50Age: 18-45Sex: 100% male

MT (I, P, L, V, O),3 weekly sessionsof 60-90 min. N=50

Offered: 39(3 per weekover 13 weeks)

Baseline C) (Mood, 1-item rating)G) Relaxation, 1-item rating;Positive thoughts, 1-item rating

Troice & Sosa(2003)


6 Diagnosis: SchizophreniaHistory: Chronic(mean duration of illness 8 yrs.)Setting: OutpatientsCountry: Mexico

100% N=15Age: M=32(SD = 8)Sex: 67% male

MT (I⁎, V⁎),biweekly sessionsof 1 hour. N=15

Offered: 40;mean 35.8

Baseline A) PANSSB) PANSSD) Positive symptoms, PANSSF) Unable to use (incompletely reported):Experiences with musicG) Unable to use (incompletelyreported): Subjective well-being

a Including all music therapy interventions. MT –music therapy; working modes in MT: I – improvisation, P – playing music on instruments (excl. improvisation), S – singing songs, L –music listening, V – verbal reflection, O – other. Centralworking modes are marked with ⁎.

b Including all non-music therapy interventions.c N=participants included in the study (including any who may have dropped out after inclusion).d Outcomes were categorized as follows: A) General mental state; B) Negative symptoms; C) Depressive symptoms; D) Other symptoms; E) Functioning and related; F) Music-related; G) Other. Outcomes partly related to a category are listed

in brackets. Abbreviations of common outcome measures are explained in the text.

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studies (Table 1). Standard care, in whatever specific way this wasdefined by the authors, included any form of treatment as usual whichwas provided to all participants (i.e. both experimental and controlgroup). Only two studies included other comparisons: One studycompared to cognitive behavior therapy (Zerhusen et al., 1995), onestudy compared two types of music therapy approaches (Ceccato et al.,2006). Meta-analyses were therefore only calculated for the compar-ison between music therapy and standard care.

When various types of music therapywere provided simultaneously(Thaut, 1989), so that this prevented separation of the effects of each ofthese types, the studywas included as an uncontrolled (pre-post) study,although it may have originally been described as a CCT. When a CCTcomparing different types of music therapy also allowed for a pre-postcomparison, but not a controlled comparison, of music therapy versusstandard care (Ceccato et al., 2006), it was included as a CCT but treatedas an uncontrolled study for the respective comparison.

3.5. Data extraction and preprocessing

Data were reported in varying ways in the studies. Whennecessary, study authors were contacted to retrieve additional data.For some studies, we received from the study authors either individualpatient data (Ceccato et al., 2006; Talwar et al., 2006; Ulrich et al.,2007) or unpublished summary data (Radulovic, 1996) whichwewereable to use. Log-transformation to remove skewness, based onindividual patient data, was performed in one instance (negativesymptoms in Ulrich et al., 2007). In two instances (negative symptomsin Ceccato et al., 2006, functioning in Ulrich et al., 2007), we calculatedand used the average effect size of two equally valid measures for thesame outcome category. In one instance (global state in Yang et al.,1998) we encountered missing values in a dichotomous outcome andinserted the negative event.

4. Results

4.1. Comparison of music therapy versus standard care

For the comparison of music therapy versus standard care, therewere four outcomes where we were able to estimate a dose–responserelationship. In addition, there was a range of other outcomes wheresimple meta-analysis was performed.

4.1.1. General mental stateSeven studies (Table 1), including 315 participants, measured

general mental state on a continuous scale, using one of thefollowing standardized measures: The Symptom Checklist SCL-90RGeneral Severity Index (SCL-90R GSI), the Brief Symptom InventoryGeneral Severity Index (BSI GSI), the Brief Psychiatric Rating Scale(BPRS), or the Positive and Negative Syndrome Scale (PANSS). Themodel selection process for this outcome is shown in Table 2. Itcan be seen that the number of sessions alone explained 78%of the variance in this outcome (pb .01). Design and disorder alonewere not useful predictors. We also examined a full model adjusting

Table 2The model selection process—explained variance (adjusted R2) for all possible mixed-effect

Outcome N ofstudies

N ofparticipants

Varia

Desig

General symptoms 7 315 .23Negative symptoms 8 404 .03Depressive symptoms 7 319 .00Level of functioning 5 215 .00

Note. The table shows explained variance (adjusted R2) and significance levels (⁎pb .05, ⁎⁎pmodels including all predictors simultaneously were also examined but not presented as theones with the highest explained variance, if significant) are highlighted in bold font.aNot available (the predictor was constant for this outcome).

for all predictors simultaneously, which yielded no additionalinformation (data not presented). Therefore, the number of sessionswas selected as the only predictor for this outcome. The dose–response relationship is illustrated graphically in Fig. 1. An increasingtrend can be seen in the symbols for the individual studies, as well asin the regression line from the mixed-effects model. From theregression model, it can be predicted how many sessions will beneeded on average to achieve a certain effect. Table 3 shows that asmall effect on general symptomswill be expected after ten sessions, alarge effect after 39 sessions.

4.1.2. Negative symptomsEight studies, with a total of 404 participants, measured negative

symptoms on a continuous scale, typically using either the Scale forthe Assessment of Negative Symptoms (SANS) or the negativesymptoms subscale of the PANSS. One study (Ceccato et al., 2006)measured sub-domains of negative symptoms (attention and mem-ory) using other scales (Table 1). Again, Table 2 shows the modelselection process. As all studies involved exclusively participants withpsychotic disorders, only design and dosage could be examined aspotential predictors. As in the previous outcome, design was not auseful predictor, whereas dosage was highly significant and explaineda large proportion of the variance. In this outcome, the square root ofsessions turned out to be a better predictor than the untransformednumber of sessions, andwas therefore selected as the only predictor inthe model. Fig. 2 illustrates the dose–response relationship fornegative symptoms. Here, the regression line is curvilinear, showinga steep increase of effect for the first sessions and a moderate butcontinuing increase for later sessions. This is also reflected in Table 3,which shows that a small effect on negative symptoms can beexpected already after as little as three sessions, whereas it takes 42sessions to produce a large effect.

4.1.3. Depressive symptomsData for depressive symptoms, measured on a continuous scale,

were available from seven studies (319 participants). Measures usedincluded the Hamilton Rating Scale for Depression (HAMD), the BeckDepression Inventory (BDI), and other related measures (Table 1). Asfor the previous outcomes, design and disorder showed no relation tothe effect size, but dosage was a highly significant predictor, with thenumber of sessions explaining 73% of the variance in effects (Table 2).The steep linear relationship is shown in Fig. 3. Although there is onepositive outlier (from an RCT—Hanser & Thompson, 1994), moststudies fall into the confidence range of the prediction line, whichappears to be equally valid for psychotic (white boxes) and non-psychotic disorders (black boxes). Table 3 reflects the steep regressionline, showing that small effects on depressive symptoms are expectedafter four sessions, and even large effects may occur after relativelyfew (16) sessions.

4.1.4. Other symptoms: Anxiety and positive symptomsSimple meta-analyses were applied for other symptom domains

which were measured on continuous scales in less than five studies.

models

nce explained by each model (Adjusted R2)

n Disorder Sessions Square root of sessions

.00 .78⁎⁎ .70⁎⁎NAa .69⁎⁎ .77⁎⁎.16 .73⁎⁎ .66⁎⁎NAa .66⁎ .74⁎

b .01, ⁎⁎⁎pb .001) for each model. Negative values of adjusted R2 were set to zero. Fully did not improve the prediction for any of the outcomes. The selected models (i.e. the

Fig. 1. Dose–effect relationship of music therapy for general symptoms. Note. Each individual study is plotted at the position indicated by the number of sessions provided and theeffect size found in that study. The box symbol for each study is filled white if themajority of participants had a psychotic disorder, and black otherwise. The size of the box representseach study's weight in the analysis. The vertical line added to each individual study indicates the 95% confidence interval (CI) of the observed effect; the line type (solid, dashed, ordotted) indicates the strength of the study's design. Finally, the dashed regression line shows the result of a mixed-effects meta-regression analysis, indicating the relationshipbetween the number of sessions provided and the predicted effect size. The 95% CI of the regression is shown by the dotted lines around the regression line.


Anxiety was measured in three studies (108 participants) with theHamilton Anxiety Rating Scale (HARS) or other related scales(Table 1). An initial meta-analysis of the three studies suggested alarge and significant effect size, but also a high amount of statisticalheterogeneity (Table 4). Visual inspection of the results revealed thatthe study with the weakest design (de l'Etoile, 2002, an uncontrolledstudy) was responsible for the heterogeneity. Therefore, the analysiswas repeated with this study excluded. Meta-analysis of the tworemaining, methodologically strong studies (Chen, 1992; Hanser &Thompson, 1994, both RCTs) yielded a large and significant effect(g=1.31, pb .001) and no statistical heterogeneity (I2=0%). It should benoted that both studies included in this meta-analysis concernedpeople with depression.

Positive symptoms were measured in four studies (170 partici-pants), using the respective subscale of the PANSS or a related scale(Table 1). A meta-analysis of these studies did not reveal a significanteffect; however, the confidence interval was wide enough to includepotential effects of clinically meaningful size (Table 3).

Table 3Model formulae and prediction of numbers of sessions needed to achieve relevant effects

Outcome Regression model N

Sm

General symptoms .02×sessions 10Negative symptoms .12×√ (sessions) 3Depressive symptoms .05×sessions 4Functioning .11×√ (sessions) 3

Note. This table shows the regression parameters of the previously described mixed-effects mand large effects are defined according to Cohen's (1988) guidelines for the interpretation ocalculation is comparable but corrected for small-sample bias (i.e., it is more conservative w

4.1.5. FunctioningFive studies (215 participants) had usable data on the effects ofmusic

therapy on functioning, using the Global Assessment of Functioning(GAF) or related scales (Table 1). The mixed-effects meta-analyticmodels shown in Table 2 suggested that design was not related to theeffect. Type of disorder could not be examined as a predictor because allstudies concerned people with psychotic disorders only. As for theprevious outcomes, therapy “dosage”was theonly strongand significantpredictor of the effect of music therapy compared to standard care. Thesquare-root model explained 74% of the variance (pb .05) and wasselected as the best model. Fig. 4 shows that effects increase with thenumber of therapy sessions provided, most steeply during the firstsessions. Table 3 shows the estimated number of sessions necessary foreach effect size.

4.1.6. Musical engagementTwo studies (107 participants) had usable data on music-related

outcomes, measured on continuous scales (Table 1). These form a

umber of sessions needed

all effect Medium effect Large effect

24 3916 4210 1620 51

eta-regression models and predicted values based on these parameters. Small, medium,f the effect size index Cohen's d. The effect size index Hedges' g which was used in thehen studies are small, but asymptotically identical to Cohen's d).

Fig. 2. Dose–effect relationship of music therapy for negative symptoms. Note. Explanations see under Fig. 1.


relatively heterogeneous category which might be summarized as“musical engagement”. One study (Pavlicevic, 1994) assessed musicalinteraction in a music therapy assessment session, the other study

Fig. 3. Dose–effect relationship of music therapy for depr

(Hayashi et al., 2002) assessed musical experiences in daily life. Meta-analysis of these studies (Table 4) showed a medium-sized effect(g=0.49, pb .05) with no heterogeneity (I2=0%), suggesting that music

essive symptoms. Note. Explanations see under Fig. 1.

Table 4Meta-analyses for outcomes measured in less than five studies

Outcome N of studies N of participants Effect sizea Heterogeneityb

a) Dichotomous outcomes Odds ratio (95% CI) I2

Global state 2 (Chen 1992; Yang et al., 1998) 140 0.03 (0.01 to 0.09)⁎⁎⁎ 0%NNT=1.59

Leaving the study earlyc 4 (Hanser & Thompson, 1994; Pavlicevic et al., 1994;Talwar et al. 2006; Yang et al., 1998)

226 1.11 (.42 to 2.92) 0%

b) Continuous outcomes Hedges' g (95% CI) I2

Anxiety (initial analysis) 3 (Chen 1992, de l'Etoile 2002, Hanser & Thompson, 1994) 108 1.05 (0.63 to 1.48)⁎⁎⁎ 73.8%⁎

Anxiety (excludingweak design)

2 (Chen 1992; Hanser & Thompson, 1994) 100 1.31 (0.85 to 1.78)⁎⁎⁎ 0%

Positive symptoms 4 (de l'Etoile 2002; Hayashi et al., 2002; Talwar et al. 2006; Troice & Sosa, 2003) 170 0.18 (−0.12 to 0.48) 0%

Musical engagement 2 (Hayashi et al., 2002, Pavlicevic 1994) 107 0.49 (0.09 to 0.88)⁎ 0%

Quality of life 2 (Hayashi et al., 2002; Ulrich et al., 2007) 103 0.16 (−0.24 to 0.56) 0%

Satisfaction 2 (Talwar et al. 2006; Ulrich et al., 2007) 118 Fixed: 0.13 (−0.28 to 0.53) 52%Random: 0.06 (−0.57 to 0.68)

Medication level 2 (Hayashi et al., 2002; Tang, 1994) 142 −0.25 (−0.58 to 0.08) 41%

a Effect sizes are shown for the fixed-effects models where no unexplained heterogeneity was found, and for both fixed and random-effects models where unexplainedheterogeneity was found. For dichotomous outcomes where a significant effect was found, the number-needed-to-treat statistic (NNT) is also shown. All effect sizes were coded suchthat ORb1 and gN0 represent a positive effect.

b I2 describes the percentage of variability in effect estimates that is due to heterogeneity, rather than sampling error (Higgins & Green, 2008). Significance of heterogeneity isshown for the Q test.

c Only calculated for controlled studies (RCTs and CCTs) with at least one drop-out in any group.


therapy improved the musical engagement of those receiving musictherapy, compared to standard care. Rather than as a clinical endpoint initself, the outcome might best be understood as an indicator ofmechanisms of change in music therapy.

4.1.7. Other outcomes: Global state, leaving the study early, quality of life,satisfaction, and medication level

Five further outcomes, two dichotomous and three continuousones, were available from at least two but less than five studies. Meta-analyses for each of these outcomes are shown in Table 4.

Global state (2 studies, 140 participants) was rated as a dichot-omous outcome (no overall improvement as rated by a psychiatrist).The results were clearly in favor of music therapy, with a very low andsignificant odds ratio (OR=0.03, pb .001) and no statistical hetero-geneity (I2=0%). To improve interpretability, the result was alsotranslated into the number needed to treat (NNT), which indicatedthat less than two patients need to be referred tomusic therapy so thatone will benefit. It should be noted that this result was based on RCTs,that it concerned psychotic as well as depressed patients, and that(although dose–response relationship was not addressed for thisoutcome) both included studies provided a large number of sessions.

The odds of leaving the study early (as a proxy measure oftolerability) were calculated from four controlled studies. The meta-analysis suggested no difference, indicating good tolerability of musictherapy as well as of standard care. Quality of life, satisfaction with care,and medication level were each available from two studies. Nosignificant effects were found for these outcomes.

4.2. Other outcomes and comparisons

All outcomes with usable data from at least two studies wereincluded in the analyses presented above, but we chose not to meta-analyze non-replicated outcomes with usable data from only onestudy. For the comparison of music therapy versus standard care,these included hostility, self-esteem (Hanser & Thompson, 1994), andengagement with services (Talwar et al., 2006). Non-replicated resultsconcerning other comparisons included structured versus improvisa-

tional music therapy (Ceccato et al., 2006) and music therapy versuscognitive behavior therapy (Zerhusen et al., 1995). Later follow-ups(some months after termination of therapy) or intermediate assess-ments (during therapy) were included in some studies (Hanser &Thompson, 1994, Hayashi et al., 2002), but not frequently andconsistently enough across studies to be included in a meta-analysis.

5. Discussion

5.1. Summary of findings

This study is themost comprehensive systematic review andmeta-analysis of the effects of music therapy in adult mental health to date.It showed thatmusic therapy, when added to standard care, has strongand significant effects on global state, level of general symptoms,negative symptoms, depression, anxiety, functioning, and musicalengagement. It showed further that the effects do not depend ondiagnosis, which confirmsmusic therapy's broad applicability. Neitherdid the results depend on study design, confirming the robustness ofour findings. In contrast, effects do depend strongly on the number ofsessions provided.

For all outcomes where data were available from sufficientlymany studies (i.e., for general symptoms, negative symptoms,depressive symptoms, and functioning), the results of the reviewsuggest that the ‘dosage’ of music therapy was the best predictor ofits effects, explaining more than 70% of the variance. This indicatesclearly that the effects of music therapy are related to the number ofsessions provided. For two of the outcomes, the square root of thenumber of sessions seemed to be a better predictor than theuntransformed number of sessions, indicating that the dose–response relationship may be non-linear (increasing more steeplywith the first few sessions) for negative symptoms and functioning.However, a linear dose–response relationship also fitted the datarelatively well for all of these outcomes. From the findings it wasestimated that between 16 sessions (for depressive symptoms) and51 sessions (for functioning) will be needed until large effects areseen.

Fig. 4. Dose–effect relationship of music therapy for functioning. Note. Explanations see under Fig. 1.


5.2. The evidence base for music therapy in mental health

The findings of this review demonstrate that music therapy is aneffective treatment for serious mental disorders with a clear dose–effect relationship. This extends the more basic knowledge fromprevious related reviews demonstrating music therapy's effectivenessfor schizophrenia (Gold, Heldal, et al., 2005) and depression (Maratoset al., 2008). The fact that the size of music therapy's effect was notsignificantly related to the type of diagnosis for any of the outcomesexamined makes most sense in the context of a dimensional model ofmental health, which emphasizes the commonalities of the differentmental disorders rather than conceptualizing them as distinct entities.This does not imply that no differences exist—but differences may bemore likely to show on other than diagnoses-related dimensions. Thiswill be discussed further under implications for practice. The samefinding lends support to a contextual model of therapy which focuseson encounter, relationship, and therapeutic process, as opposed to amedical model where specific techniques are applied to treat specificdiseases or symptoms (Wampold, 2001). Music therapy appears to beindicated for a broad range of serious mental disorders.

The fact that the effect sizes found in this review were also notrelated to the type of study design justifies and underlines theappropriateness of the range of study designs included. Although non-randomized study designs may bear a greater risk of bias and cautionis warranted, such caution was applied in the analysis and noindication of bias was found. Overall, the fact that all study designsand all types of serious mental disorder included showed the sameresults strengthens the confidence with which conclusions can bedrawn from this review.

5.3. The dose–response relationship in music therapy

The one predictor that was significant consistently across alloutcomes was the ‘dosage’ of music therapy. In line with previous

findings from research in verbal psychotherapy (Howard et al., 1986),our findings indicate that the effects of music therapy increase withthe number of sessions provided. The number of sessions explainedhigh proportions of the variance in effects (between 73% and 78%),indicating a clear and strong relationship. With the findings from thisreview, it is now possible to predict the expected effect size from thenumber of sessions, or to predict the number of sessions needed toachieve a given effect size. The results indicate that small effects areseen after 3 to 10 sessions; medium effects are achieved after 10 to 24sessions and large effects after 16 to 51 sessions. This facilitates theplanning of future research in the field and may also have directimplications for practice and policy. As others have noted, “thepresence of a dose–response gradient may also increase ourconfidence in the findings of observational studies and therebyenhance the assigned quality of evidence” (Higgins & Green, 2008,p. 367). The findings of this review therefore confirm the effectivenessof music therapy and underline the strength of causal inference fromthe existing evidence.

5.4. Limitations

The results of a meta-analysis depend firstly on the results of theindividual studies included. Therefore, their limitations should bementioned here first. We excluded studies with very high risk of bias(e.g. with very high drop-out rates) from the review. However, we didinclude studies with ‘weaker’ designs than the strongest ones thatexist. This was done to enhance external validity, and the choice wasaccompanied by a clear strategy to statistically identify the impact of apotential bias. The results showed no impact of study design,indicating that their inclusion was justified in this sample of studies.However, other limitations of the primary studies' quality, as well asthe quality of their reporting, should also be mentioned. In more thanhalf of the studies it was uncertain whether or not outcomeassessment was adequately blinded. Similarly, concealment of


allocation (relevant in RCTs) was only rarely reported and oftenuncertain. It was not possible to assess the impact of methodologicalquality in greater detail in this meta-analysis, both due to the lack ofmethodological transparency and due to the need for parsimony inselecting predictor variables in meta-regression models. For example,it would have been desirable to assess the impact of adequate blindingas a further methodological predictor in addition to study design.

Likewise, greater transparency had also been desirable for manyclinical aspects, particularly for the kind of music therapy that wasapplied in the studies.While someaspects, such as duration, setting, andgeneral working modalities were fairly clear from the study reports, itsometimes proved difficult to identify clearly the theoretical orientationand the formal qualification level of the music therapist(s) who appliedthe therapy. This may in part be related to the stage of development ofmusic therapy as an academic discipline and as a regulated profession,both ofwhichvaryacross countries. The implication of this limitation forthe present review is that conclusions can only be about music therapyin general (within the definition provided in the beginning of thisarticle), rather than about more specific theoretical or methodologicalapproaches within music therapy. Relatedly, as the vast majority ofstudies comparedmusic therapy to standard care and did not include anactive control intervention, it is not possible at this stage to make anystatements about the specificity of music therapy's effects. The currentevidence suggests that music therapy has an effect. Based on that, alogical and useful next step in this field of researchwould be to examineto what extent this effect is due to its specific ingredients—the use ofmusic—or due to other, more general factors.

Thepotential impact of researcher allegiancehas beenmuchdebatedin psychotherapy research (e.g., Luborsky et al., 1999). Although it wasnot the focus of this review, it should be mentioned here as a potentiallimitation. It is plausible to assume thatmost studies in this reviewwerecarried out by researchers who have a somewhat positive allegiancetowards music therapy. One notable exception is the Zerhusen et al.(1995) study, where music therapy was used as a comparison conditiononly, whichmight indicate neutral or negative allegiance towardsmusictherapy. However, the high consistency of the dose–response relation-ship identified in this review makes bias from researcher allegianceseemunlikely here. Researcher allegiance is presumably independent ofthe number of sessions in a study; we can see no plausible reason whythe impact of researcher allegiance should be greater in studies wheremany sessions were provided. Therefore, researcher allegiance can beruled out as a potential threat to the validity of our findings. Tosummarize, the existence of a clear dose–response relationshipstrengthens the conclusion that the results reflect the true effects oftherapy rather than methodological artifacts.

Finally, the small number of studies deserve mentioning as alimitation. Specifically, one might ask how conclusive the resultsconcerning the dose–effect relationship are, given that they are basedon only 15 studies. Concerning this possible criticism, it is first importantto note that these 15 studies reflect information from almost 700patients, who were offered a widely ranging number of music therapysessions. Secondly, one should recall the unusually high proportion ofexplained variance that was found in this meta-analysis. According toCohen's (1988, pp. 413–414) guidelines for interpretation of effects in thebehavioral sciences, an effect expressed as explained variance is “large”when R-squared is .26. The dose–effect relationship we discovered, withanR-squared of around .75 for all outcomes examined, by far exceeds theconventions of a large effect. This lends credibility to its interpretation asa true dose–effect relationship and makes alternative explanationsunlikely (Higgins&Green, 2008). Nevertheless, there is a need for furtherstudies, as is discussed further below.

5.5. Implications for practice

The findings of this review have several implications for practice.First, they underline the value of music therapy as an effective

treatment in mental health care. Music therapy helps patients withserious mental disorders to improve their general mental state,symptom levels, and level of functioning. This has been known beforefor patients with schizophrenia (Gold, Heldal, et al., 2005); the currentreview both confirms and extends the findings from that previousreview. The current review extended from the previous meta-analysisby including not only schizophrenic, but also non-psychotic seriousmental disorders. Compared to the previous review, the currentreview was also based on a broader selection of studies, includingpractice-based studies, which likely improved the generalizability andclinical applicability of the findings. Particular mention should bemade of the important group of patients with depression where nometa-analysis existed previously (only a narrative review of depres-sion studies was provided by Maratos et al., 2008). This broad range ofpatients will benefit if music therapy is added to their usual care.

Second, the findings imply that the number of sessions is animportant factor for music therapy to be beneficial. Small benefits ofmusic therapy can be seen already after a few sessions, as may bemosttypical on an acute inpatient ward. However, for stronger, clinicallymore meaningful—and potentially more lasting—effects, a consider-able number of sessions will be required. The findings therefore alsounderline the value of either intensive or long-term engagement ofpatients in music therapy, the latter of which may be most typical inoutpatient settings or in private practice. Mood changes seem to occurmore quickly than improvements in general symptom levels. It has tobe noted, however, that the extent of individual benefit from musictherapy will necessarily vary from patient to patient. Some mayrespond rapidly after few sessions, whereas others may need moretime than expected and predicted by the model. Further, the results ofthis review do not tell us if, the total number of sessions being equal, ahigher frequency of sessions over a shorter time or a lower frequencyover a longer time will be more beneficial. This may also vary acrossclient groups.

As a third implication for practice, the lack of difference of effectbetween psychotic and non-psychotic disorders raises the question ofdifferential indication for music therapy. If diagnosis is not the maindeterminant of music therapy's effect, then what other criteria mightbe more fruitful in determining who should receive music therapy?Psychotherapy researchers have argued that factors such as the matchbetween therapist and client and the client's motivation for a specifictype of therapy should be recognizedmore (Wampold, 2001). That theuse of such “soft” indications can often be more fruitful than anuncritical ‘prescription’ based on diagnosis alone, is very much inaccordance with our clinical experience as music therapists. Forexample, clients are often referred to music therapy because they aredeemed unsuitable or unmotivated for verbal psychotherapy (Hanni-bal, 2005; Hanser & Thompson,1994; Meschede et al., 1983; Rolvsjord,2001; Solli, 2008). An international multicenter RCT is currentlyinvestigating the effects of music therapy for this specific population(Gold, Rolvsjord, et al., 2005). It is important to be aware that referralbased on such types of indications requires referrers to think morecarefully about the individual patient and necessitates more andbetter communication between referrers and therapists than referralbased on diagnosis.

For policy makers, it will be important to know how easily musictherapy can be implemented into the care of seriously mentallydisordered patients. Inmany countries, qualifiedmusic therapists withan appropriate level of training are available; in other countries, theremay be an insufficient level of training, an insufficient numberof qualified music therapists, or an insufficient focus of the musictherapy training on mental health care. The findings of this reviewsuggest thatmusic therapists in this field need to be clinically skilled toenable a range of music experiences, as well as a fruitful reflection ofthese experiences, in a framework that offers both sufficient structureand openness towards the patient's individual therapeutic process.This requires extensive and adequate clinical training.


5.6. Implications for future research

This review has established the efficacy and dose–responserelationship of music therapy for people with serious mentaldisorders. This is an important, but still fairly general finding.Studies will be needed to fill gaps in client populations and toextend our knowledge on the effects of therapy variables otherthan dosage. Concerning client populations, the findings of thisreview indicate that not all mental disorders have been coveredequally well. Most of the studies identified focused on eitherpsychotic disorders or on depression. Some important disorderswhere music therapy is applied, including for example borderlinepersonality disorder and eating disorders, have not received specificattention in music therapy outcome research to date. Furthermore, asnoted in the previous section, there seem to be specific subgroupsacross diagnoses that warrant closer investigation, such as patientswith low therapy motivation. Future research should attempt to closethese gaps.

Concerning the further specification of the treatment, effects ofmusic therapy approaches may vary not only by the treatment “dose”(number of sessions), but also according to theoretical background,qualification of the therapist, therapeutic setting, and workingmodalities within therapy. Another wide area for more specific futurestudies on differences in types of music therapy will be related toindividual therapist variables, which may be at least as important asthe more formal characteristics of therapy (Wampold, 2001). As arelated but different issue, it would also be useful to compare musictherapy to active control conditions in order to establish to whatextent the effect of music therapy is due to using music in therapy ordue to other factors.

To improve the methodological quality of future outcome researchin the field, researchers should adhere to guidelines such as theCONSORT statement for RCTs (Moher, Schulz, & Altman, 2001) andrelated statements for other study designs (as listed onwww.consort-statement.org). Many of the methodological weaknesses identified inthe available research to date—from design aspects such as allocationconcealment and blinding through to the adequate reporting ofstatistics—are related to transparency of reporting, which can easily beimproved by using those guidelines.

Specifically and concretely, the numeric results of the meta-regression models can be used directly in the planning of futureresearch. Power calculation, an issue which was long ignored—notonly—in music therapy research (Gold, 2004), is now increasinglybeing used by music therapy researchers to identify the requiredsample size for their study hypotheses. One central assumptionin power calculation is the expected effect size. The results of thisreview are a strong reminder that this effect size again dependsto the number of sessions. Researchers planning an outcomestudy in the field should make use of this knowledge. One can usethe model formulae and predicted values (Table 3) to make aninformed decision on the expected effect size, based on thenumber of music therapy sessions to be provided. For example,in a study with general symptoms as the primary outcome, onecan see from the table that a medium effect size is expectedafter 24 sessions, and a large effect size after 39 sessions. Powercalculation then shows that the required sample size will decreaseconsiderably (from 64 to 26 participants per group) if the highernumber of sessions is chosen.1 Our findings therefore enableresearchers to make more informed decisions in planning researchby using the number of therapy sessions as a parameter in powercalculation.

1 Calculated for an independent samples t-test comparing two groups of equal size,with significance level α= .05 and test power 1−β= .80, using the function power.t.testin R. The same results can be found in the sample size tables in Cohen (1988).

6. Conclusion

This review has shown that music therapy is an effective therapyfor serious mental disorders, which helps patients to improve globalstate, symptoms, and functioning. This adds to the knowledge oneffective therapy for a populationwhich often does not respond easilyto traditional approaches. Music therapy appears to contributesomething unique to this field, with music helping in at least threedifferent ways—as a motivating factor, as a medium for emotionalexpression, and as a social endeavor. At the same time, this research isrooted in the wider field of psychotherapy research, and its findingscontribute to research on contextual models in psychotherapy(Wampold, 2001) as well as to research on dose–response relationshipin psychotherapy (Howard et al., 1986). It is hoped that the findings ofthe present review will also be fruitful for those related fields, as wellas furthering the knowledge and application of music therapy as atreatment that is rooted in good clinical practice, guided by adequatetheory and supported by reliable evidence.

Conflict of interest

Christian Gold, Hans Petter Solli, and Viggo Kruger are clinicallytrained music therapists.

Acknowledgements

The authors would like to thank Zulian Liu and Huo LiHua for helpwith the translation and Tor Olav Heldal and Trond Dahle for help withthe data extraction. Johan Cullberg provided valuable comments on anearlier version of this article. This review was enabled by intramuralsupport by Sogn og Fjorde University College, Sandane, Norway, andexternal funding from the Research Council of Norway. Parts of thisarticle were written at Café Museum, Vienna, Austria.

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