hypothesis for music therapy

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• Published: 04 December 2023

Biological principles for music and mental health

• Daniel L. Bowling   ORCID: orcid.org/0000-0002-5303-5472 1 , 2  

Translational Psychiatry volume  13 , Article number:  374 ( 2023 ) Cite this article

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• Human behaviour
• Neuroscience
• Psychiatric disorders

Efforts to integrate music into healthcare systems and wellness practices are accelerating but the biological foundations supporting these initiatives remain underappreciated. As a result, music-based interventions are often sidelined in medicine. Here, I bring together advances in music research from neuroscience, psychology, and psychiatry to bridge music’s specific foundations in human biology with its specific therapeutic applications. The framework I propose organizes the neurophysiological effects of music around four core elements of human musicality: tonality, rhythm, reward, and sociality. For each, I review key concepts, biological bases, and evidence of clinical benefits. Within this framework, I outline a strategy to increase music’s impact on health based on standardizing treatments and their alignment with individual differences in responsivity to these musical elements. I propose that an integrated biological understanding of human musicality—describing each element’s functional origins, development, phylogeny, and neural bases—is critical to advancing rational applications of music in mental health and wellness.

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Introduction

Every day, hundreds of millions of people make or listen to music. This appetite is driven by music’s core effects on emotion [ 1 , 2 , 3 ], reward [ 4 ], and affiliation [ 5 ]. The value we place on these effects supports a 200 billion dollar per year industry in the US alone [ 6 ]. More and more, music’s core effects have come into focus for their alignment with core dimensions of mental health, e.g., mood, motivation, pleasure, and social functioning. Together with rapidly increasing awareness of mental health’s humanistic and financial importance, this alignment has sparked new investments in music-based interventions from government and industry [ 7 , 8 , 9 ]. This interest presents an opportunity for proponents of music’s therapeutic value to increase the specificity and rigor of its application and enhance our understanding of its clinical scope and efficacy.

Meeting this goal depends on a clear conception of music’s underlying biology as a source of principles for systematic applications towards specific clinical and subclinical goals. An awareness of such principles exists in music therapy [ 10 , 11 , 12 ], especially “neurologic” music therapies for motor rehabilitation [ 13 , 14 , 15 ], but applications in mental health remain highly variable, making it difficult to achieve a unified biologically-informed approach. Moreover, there are far too few music therapists to meet current mental health needs. In the US, for example, there are only about 10,000 board-certified music therapists, compared to about 58 million adults living with mental illness [ 16 , 17 ]. Assuming an average weekly caseload of 30 patients [ 18 ], total capacity to treat is therefore just 0.5%. Musicians represent another important source of insight, as they are ultimately the most skilled at titrating music’s neurophysiological impact. However, the inherently subjective nature of their “artistic” approach can preclude direct integration within a scientific model of health.

Given the uncertainty in defining the relationship between music and health, funders have sought to advance applications by casting a wide net. The National Institutes of Health, for example, has sponsored an extensive list of research topics involving music, including improving treatment response in cancer, stress and pain management in surgery, affect modulation in mood disorders, anxiolysis in anxiety disorders, social functioning in neurodevelopmental disorders, palliative care in advanced illness, neural rehabilitation after injury, and wellness through exercise [ 19 ]. This breadth is likely to puzzle many medical professionals and raise skepticism in more than a few. Can music really be such a panacea?

While skepticism is justified (as discussed in Section “Skepticism and need”), clear evidence of music’s effects on core mental health variables is readily apparent in our growing understanding of music’s biological foundations. Critically, these foundations provide a rational basis for standardizing and expanding music’s psychiatric applications and benefits. In this review, I outline a framework for music in human biology and describe some of its basic implications for standardized music-based interventions in mental health, with the goal of increasing biomedical integration and impact.

Developing a biological perspective

As far as we know, music has been with humans since our earliest existence. The first known evidence of human preoccupation with music comes from Stone Age flutes, carefully carved in wing bones and mammoth ivory some 40,000 years ago [ 20 ]. Over the course of recorded history, explanations of music and its power have been sought in terms of mythology, cosmology, mathematics, and physics, with many important insights along the way [ 21 , 22 ]. However, it was not until the 19th century that music came to be viewed in terms of human evolution. In 1871, based on observations of general similarity between human and animal vocalization, as well as the behavior of other “singing” mammals (like gibbons and howler monkeys), Darwin postulated a basis for music in sexual selection on social behavior. Specifically, he proposed that the vocalizations of our ancestors were likely more musical than linguistic, comprising greater regularity in pitch and time, and functioning mainly in signaling affect, attracting mates, and threatening rivals [ 23 ]. From this perspective, “music” provided the foundation for the evolution of human language, centering its underlying biology within the study of human cognition and communication more broadly [ 24 ].

Two aspects of this early account continue to shape modern biological music research or biomusicology (e.g. [ 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]). One is that music is, first and foremost, a form of social communication, with explicit origins in auditory-vocal interaction. The second is that singing and speaking—and thus, music and language—likely share a common origin in early hominids, as reflected by their many overlapping features, like being auditory-vocal by default, emotional expressive, and inherently social [ 25 ]. While many more specific details about the evolutionary origins of music remain under debate (cf [ 31 , 38 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ]), a general view of music as rooted in social communication, with close ties to speech and language, is consistent across most theories and also central here.

Before proceeding, it is important to clarify that biomusicology chiefly concerns musicality rather than music per se. Whereas music is a cultural phenomenon of infinite variety [ 46 ], musicality is the genetically constrained and reliably developing set of neural capacities on which music production and perception rests [ 33 ]. It should be noted that this view departs significantly from common conceptions of music that center specific cultural manifestations and individual variation in preferences. Instead, a biological perspective centers music’s basic features in relation to pressures to evolve and develop neural capacities that support social communication. The following sections define this perspective with respect to four core elements of musicality—tonality, rhythm, reward, and sociality—reviewing essential concepts, biological bases, and evidence of clinical benefits, towards a framework for rational clinical translation.

Musical terms and definitions

Tones are a special class of sound stimuli that evoke a strong sense of pitch. Physically, they comprise regularly spaced pressure waves that repeat at frequencies between approximately 30–4000 Hz [ 49 ]. All musical cultures and traditions use tones [ 50 , 51 ], making neural sensitivity to tonality— defined simply as the use of tones to make music—a core element of human musicality. Tonality has primarily been considered from three perspectives. Harmony is focused on the organization of tones with respect to frequency. Melody is focused on the sequential organization of tones over time. Timbre is focused on the quality imparted to tones by their source and manner of production (e.g., a voice or a synthesizer, sounded gently or harshly, etc.) [ 52 ].

Conserved aspects of tonality

The most significant source of tones in the human auditory environment is vocal fold vibration in the larynx [ 53 , 54 ]. In speech, the frequency of vocal fold vibration fluctuates rapidly, leading to dynamic and variable tones (Fig. 1A ). In contrast, during song, these vibrations are modulated to emphasize particular frequencies and frequency relationships [ 50 , 51 , 55 ]. Beyond these “universal” features, many key aspects of harmony, melody, and timbre are widely observed across richly differentiated musical cultures and traditions.

A The same phrase spoken and sung by the same person to highlight how tones in music are related to tones in speech (based on Diana Deustch’s speech-to-song illusion). Variation in sound pressure over time (black) is overlaid with variation in the fundamental frequency of vocal fold vibration (the physical correlate of voice pitch; red). B On the left, the frequency relationships defined by the Japanese ritsu scale are presented along a vertical axis. Each relationship is calculated with respect to the lowest tone in the set (labeled “1.000”). On the right, the melody of the American gospel song “Amazing Grace” is shown using the same relationships. Conventional note letter names are listed at the right. C Timbral similarity of vocal and instrumental tones with parallel affective qualities. Top row: sound pressure waveforms with temporal envelopes shown in red. Bottom row: corresponding Fourier transforms with spectral envelopes shown in blue. These examples were selected to show similarity in temporal and spectral features of vocal and instrumental tones with parallel affective qualities.

In harmony, music almost always emphasizes a small set of tones defined by specific relationships to each other [ 51 ]. The simplest of these relationships—e.g., octaves (2:1) and fifths (3:2)—feature prominently in music worldwide [ 21 , 56 , 57 ], and particular sets of ratios called scales (or modes) are strikingly popular across cultural boundaries [ 21 , 57 , 58 ]. For example, the Western minor mode corresponds to what South Indian musicians call the Keeravani raga [ 59 ]. Similarly, the Japanese ritsu scale is also found in traditional Western folk songs like “Auld Lang Syne” and “Amazing Grace” (Fig. 1B ) [ 60 ]. In melody, tones tend to be arranged in arched or descending contours [ 21 , 51 ], traced mainly by small steps in pitch, with larger steps typically rising (Fig. 1B ) [ 61 , 62 , 63 , 64 ].

In timbre, specific temporal and spectral characteristics of tones give rise to specific perceptions of anatomical and affective source parameters, e.g., the ratio of low- to high-frequency energy in a tone is associated with size, valence, and arousal [ 65 , 66 ], rapid tone onsets signal a higher commitment of energy [ 67 ], and “rough” growl-like tones often convey anger or aggression [ 68 , 69 ] (Fig. 1C ). There is also widespread conservation in the use of tones for specific purposes. For example, lullabies typically comprise tones with relatively more low-frequency energy, sorted into simple repeating patterns [ 70 , 71 , 72 ]. Likewise, flatter contours with narrower pitch steps are favored for conveying somber affect [ 63 , 73 ]. Together, these and other broadly conserved aspects of tonality indicate a strong foundation in our shared biology.

Biological foundations of tonality

To model the biology underlying tonality, music scientists have developed vocal similarity theory (VST), the central tenet of which is that we perceive tones according to their behavioral significance in vocal communication [ 22 , 30 , 53 , 58 , 74 , 75 , 76 , 77 , 78 ]. VST is based on the fact that our experience with tones is dominated by the voice at evolutionary and individual time scales. This implies that the neurobiology of tone perception has primarily been shaped by pressure to contend with tones in the voice and their significance for adaptive behavior [ 22 , 53 , 75 ].

Phylogenetically, sensitivity to “tone of voice” is likely to have emerged very early in tetrapod evolution [ 79 ]. In mammals, auditory-vocal interaction is often central to social behavior and cognition, placing this sensitivity under intense selective pressure. Developmentally, the fetal brain begins responding to mother’s voice around the 24th week of gestation [ 80 ]. Over the ensuing weeks, these responses develop to the point that infants strongly prefer their mother’s voice at birth [ 81 ], an orientation that scaffolds the formation of our prototypical social bond, the modulation of affect through sound, and the development of communication more broadly [ 82 ]. Mechanistically, neural specialization for responding to vocal tones is evident throughout the auditory system, from enhanced representations of periodicity in the brainstems of humans and rats [ 83 , 84 ], to harmonically sensitive neurons in marmoset cortex [ 85 ], and pitch contour neurons in human cortex [ 86 ].

The culmination of this underlying biology is a brain that responds to tones reflexively by supplying percepts of meaning and intent as guides for behavior and cognition. This works because the acoustics of laryngeal vocalization are linked to source parameters at a statistical level [ 87 , 88 ]. For music, the implication of VST is that conserved aspects of tonality can be understood as consequences of the auditory system’s biological tuning to voices.

Applications of tonality in mental health

VST roots tonality in the bioacoustics of vocal affect, providing a principled basis for the assessment and manipulation of reflexive responses to musical tones, and their translation to psychiatry. For any given clinical goal related to the modulation of patient affect, VST predicts that proper applications of tonality require alignment with the statistical regularities that identify vocal expressions as conveying the emotion required to effect the desired physiological change. For example, a musical intervention aimed at relieving high anxiety and agitated negative mood should have tonal properties that align with a positive calming voice, such as extended falling pitch contours and low-frequency weighted timbres. Similarly, an intervention for depression should possess a gentle affirming tone, captured by more articulated contours that rise towards their ends. This approach naturally imbues musical tonality with a capacity to modulate listener feelings that parallels the corresponding tone of voice. However, because musical tones are (often) freed from the constraints of vocal expression—e.g., by instrumental production or release from linguistic demands—key regularities can be distilled and exaggerated to yield tones with supernormal neurophysiological effects.

Importantly, guidance derived from VST on how to use tonality to modulate affect largely corresponds with what musicians and music therapists have learned to do through subjective exploration and experience [ 76 , 89 ]. This is reflected in the effects of current musical treatments on dysregulated anxiety and mood. For example, receptive treatments (based on listening) can effectively reduce acute anxiety in chemotherapy [ 90 ], childbirth [ 91 ], and surgery [ 92 ]. A 2018 meta-analysis of 81 randomized controlled studies, involving over 6000 patients, found that music listening before, during, or after surgery significantly reduced anxiety symptoms, with an effect size equal to 69% of one standard deviation (Standard Mean Difference [SMD] = 0.69) [ 92 ]. Other meta-analyses indicate that music therapy can also be an effective anxiolytic beyond these acute medical contexts. A 2021 meta-analysis of 32 controlled studies with over 1,900 patients with anxiety showed significant anxiety reduction after an average of 7.5 music therapy sessions (SMD = 0.36). This effect was stronger in the subset of 11 studies with >12 sessions (SMD = 0.59), suggesting a dose-response effect [ 93 ]. For context, consider that estimated summary SMDs for first-line psychotherapies and pharmacotherapies lie between 0.28–0.44 and 0.33–0.45 respectively (but note that these numbers are based on much larger samples) [ 94 ].

Similarly positive effects of music therapy have been reported for affect disorders. A 2017 meta-analysis of 9 controlled studies including 411 patients diagnosed with a depressive disorder found that adding 6–12 weeks of music therapy to antidepressants and/or psychotherapy significantly reduced clinician-rated and patient-rated symptoms (SMD = 0.98 and 0.85 respectively) [ 95 ]. A 2020 meta-analysis focused specifically on receptive musical treatments found an even stronger effect when looking at depressive symptoms across patients with a wider variety of primary diagnoses, like heart disease, dementia, insomnia (SMD = 1.33, 17 controlled studies, 1,284 patients) [ 96 ]. The same paper also reports a significant effect for interactive treatment (based on making music; SMD = 0.57, 20 controlled studies, 1,368 patients) [ 96 ]. Both effects were apparent across variable depression severity levels and treatment courses (mean dosage was approximately 14 h, SD = 18, range = 0.33–126) [ 95 , 96 ]. For context, overall SMDs for psychotherapy and pharmacotherapy in depressive disorders have been estimated at 0.31 and 0.30 respectively (again, based on larger samples) [ 94 ].

While success of this kind might suggest that music therapy can do without VST, it should be noted that none of the aforementioned meta-analyses (and few of the individual studies that they cite) provide any details on the parameters of the music employed. This is largely because musical decisions are made on intuition rather than principle. Thus, while subjectivity has proven an essential guide in discovering music’s therapeutic applications, it also complicates scientific efforts to understand music’s therapeutic effects and standardize their application. VST addresses this challenge by providing objective guidelines for musical tonality based on specific therapeutic goals. This is a necessary step towards standardization, which is in turn required for expanding access to musical treatment.

Rhythm is the temporal patterning of sounds in music. The dominant feature of rhythm is temporal predictability, focused at rates ranging from approximately 0.5 to 5 Hz (30–300 beats per minute [bpm]) [ 97 , 98 , 99 ]. All musical cultures and traditions exhibit some temporal predictability in this range, making neural sensitivity to rhythm a second core element of musicality (no ranking implied) [ 50 , 51 ]. Investigations of rhythm typically identify two core components [ 100 ]. Pulse is the main cycle of rhythmic repetition perceived in music; it is generally what we synchronize to when we move in time with music. Meter refers more broadly to other rhythmic cycles perceived in music [ 101 ]. These encompass repetition rates that are both faster and slower than the pulse, defined by subdivisions of the pulse and multi-pulse cycles, respectively.

Conserved aspects of rhythm

As with tonality, key elements of rhythm are widely conserved across musical cultures and traditions. In pulse, acceptable rates (or tempos ) are highly constrained, showing a peak between approximately 1.33 and 2.67 Hz (80–160 bpm) across a variety of different musical traditions (Fig. 2A ) [ 98 , 102 ]. Intriguingly, this peak corresponds closely with dominant rates of periodicity in full-body human motion (e.g., 1.35–2.5 Hz [81–150 bpm] in walking) [ 98 ]. A second widely conserved aspect of pulse is that individual pulses tend to be isochronous or equally spaced in time [ 50 , 51 ]. There are traditions that also use unequal pulse spacing [ 103 ], but only in ways that retain predictability and thus allow interpersonal synchrony [ 104 , 105 ].

A A histogram of tempos from a sample of over 74,000 pieces of music. “DJ lists” refers to lists of song tempos used by disk jockeys to match pulse rates between tracks; “Radio” refers to songs found by randomly tuning into radio stations circa 2002; “Hits” refers to popular music from 1960–1990; and “styles” refers to a selection of music from divergent styles (e.g., renaissance polyphony and modern jazz). B One cycle from each of three rhythms with different meters, increasing in complexity from top to bottom. Circle size and shading indicate level of accenting (large/dark = strong), red stars and horizontal black brackets mark subgroups, and ellipsis denote repetition. Tin, Na , and Dhin are specific tabla drum strokes; tone, slap, bass , and touch are specific djembe drum stokes. The suku rhythm is based on section 5.3 of Polak (2010), with a timing ratio of 11:17:22 for the short-medium-long pulse patterns. C Hypothesized information flow through the network of brain areas implicated in rhythm perception. Additionally relevant brain areas include the hypothalamus, insula, and orbitofrontal cortex (see Fig. 3 ). The rhythm network is mostly bilateral despite being visualized in the left hemisphere here. Numbers refer to Brodmann areas. Insets show implicated structures in situ. Panel A is adapted from Moelants (2002) with permission from the author.

In meter, rhythmic cycles that are faster than the pulse also exhibit characteristic rates, mostly in the range of 2–8 Hz (120–480 bpm; typical of finger or wrist motion), and involving subdivisions of the pulse rate by factors of two or three [ 99 , 101 ]. Faster cycle rates are found in some traditions, e.g., 10–15 Hz [600–900 bpm] in djembe [ 103 ] or death metal [ 106 ], but this is relatively rare. For cycles at rates slower than the pulse, rhythmic patterning is almost always marked by variations in acoustic emphasis called accenting [ 100 ] (Fig. 2B ). A simple example of accenting comes from the marching rhythm “ one , two , one , two , ”, a repeating two-pulse cycle in which the first pulse is accented. Increasing in complexity, the meter of rūpak tāl in North Indian music is defined by a repeating seven-pulse cycle with multiple levels of accent set into groups of three and two [ 107 ]. More complex still are the drum patterns of Malian djembe music. For example, in suku, a repeating twelve-pulse cycle with multiple levels of accent is set into groups of three, each of which has a non-isochronous “short-medium-long” pulse pattern [ 103 ]. In sum, despite impressive diversity, rhythms from around the world are characterized by a restricted tempo range, multi-layered patterning, accenting, and predictability.

Further evidence that rhythm relies on conserved biology comes from the fact that the acoustic stimulus, taken alone, is often an insufficient basis for direct derivations of pulse and meter. Instead, these core aspects of rhythm depend on the interaction of sonic events and the brain [ 100 , 101 ]. Multiple lines of evidence indicate that humans possess specialized neural mechanisms that reflexively identify and reinforce temporal regularity in sequential auditory stimuli. These mechanisms (described in greater detail below) are specialized in that they are common to most humans but apparently rare among other animals. Individuals from many species can be trained to move in reaction to a pulse, but human movements are shifted forwards in time to anticipate, rather than lag behind, upcoming events [ 108 ]. We also synchronize flexibly, easily adjusting to tempo changes that disrupt or defeat synchrony in experiments with other species (parrots represent an interesting exception) [ 40 ].

More evidence of specialization comes from our curious tendency to spontaneously impose accenting on acoustic sequences that lack it. For example, we are apt to hear alternation or triplets in sequences of physically identical events, a perceptual imposition that can be differentiated electroencephalographically [ 109 ]. A final piece of evidence for specialized neural mechanisms in human rhythm perception is the global popularity of syncopation , especially in dance music [ 110 , 111 , 112 ]. Syncopation balances anticipation, built from sounds occurring on-the-pulse, against its systematic violation by sounds occurring off-the-pulse [ 113 ]. Perceiving syncopation thus depends on a conserved ability to form an internal model of regular temporal structure that is strong enough to withstand substantial ill-fitting sonic data [ 111 ]. Together, these and other broadly conserved aspects of rhythm indicate a strong foundation in our shared biology.

Biological foundations of rhythm

To model the biology underlying rhythm, music scientists have developed Neural Resonance Theory (NRT), the central tenet of which is that rhythm perception depends on endogenous oscillations in neural circuitry [ 97 , 114 , 115 , 116 ]. NRT holds that such oscillations spontaneously entrain to stimulus-evoked neural responses to modulate receptivity, prediction, and motor reactivity, thus providing a mechanistic basis for pulse and meter. While this “resonant” capacity is maximally engaged by music, its primary utility appears to be in processing spoken language, which, despite being less temporally regular than music, is still sufficiently regular (between 2–8 Hz [120–480 bpm] [ 102 ]) for entrained oscillations to aid in parsing phonemes, syllables, and phrases [ 117 , 118 ]. This implies that rhythm perception is intimately linked to vocal communication, just like tone perception.

A related aspect of NRT is that neural activity in auditory cortices readily couples with neural activity in parts of the brain that regulate movement, especially cortical areas and subcortical structures involved in motor planning, such as the supplementary motor and premotor cortices, the dorsal striatum, and the cerebellum [ 119 , 120 , 121 , 122 , 123 ] (Fig. 2C ). Activity in these parts of the brain increases in response to rhythm, even in the absence of movement [ 122 ], suggesting that auditory-motor interaction may be essential to rhythm perception. The link between rhythm and movement has also been explored in studies of groove , a psychological concept defined by variation in the degree to which a musical stimulus inspires movement. People generally agree about degrees of groove in music [ 124 , 125 ], with research suggesting a basis in common acoustical and structural features of rhythm, such as emphasized low-frequency energy (“bass”) [ 126 , 127 ] and moderate levels of syncopation [ 111 , 112 , 127 , 128 ]. Notably, groove is broadly associated with positive affect [ 111 , 125 , 129 , 130 ], making it directly relevant to mental health.

Applications of rhythm in mental health

So far, the clinical value of NRT has mainly been studied in the context of music therapies aimed at improving sensory and motor functions [ 131 ] (including speech [ 132 ]). However, even in these contexts, mental health benefits are often apparent. For example, in a 2021 meta-analysis of 17 randomized controlled studies testing musical interventions in Parkinson’s disease, a sub-analysis of 8 studies with mental health measures found significant benefits for mood, motivation, and emotional well-being in music conditions compared to standard care (SMD = 0.38, N  = 273 patients) [ 133 ]. Positive mental health outcomes have also been observed in response to receptive music therapy after stroke [ 134 , 135 ]. For example, one widely-cited study found that listening to music for at least one hour per day over a two-month period significantly lowered self-reported depression at 3 months post-stroke, as compared to standard medical care and rehabilitation [ 136 ]. Intriguingly, this study also reported benefits of music listening for cognitive function (memory and attention) in a well-controlled comparison to audio-book listening [ 136 ].

The capacity of rhythm to entrain activity in broad auditory-motor networks and simultaneously increase positive affect can also be hypothesized to account for a significant proportion of the benefits of musical treatments for anxiety and depression (see Section “Applications of tonality in mental health”). Specifically, engaging these networks with high-groove rhythms may provide an efficient way to disrupt maladaptive patterns of brain activity associated with negative affect and self-focused negative rumination [ 137 , 138 , 139 ]. Related to this hypothesis, there is growing evidence that groove is important for understanding the effects of music on cognition, particularly in the context of repetitive effortful work, which can often generate negative affect [ 135 , 140 , 141 , 142 , 143 , 144 , 145 ]. For example, in one recent study, listening to a high-groove drum loop for just 3 min was found to be more effective than noise at improving performance on a subsequent repetitive behavioral task measuring context-dependent response inhibition (a “Stroop” test). This effect of rhythm was specific to participants who reported enjoying the drum loop and its groove. These participants also exhibited significantly greater (dorsolateral) prefrontal cortical activity during the Stroop test in the drum-loop condition, as measured using functional Near Infra-Red Spectroscopy [ 141 ].

Experimental evidence for positive effects of rhythm on certain types of cognition accords with longstanding evidence from ethnographic literature. Specifically, rhythmic music has often been used to positively transform the experience of work otherwise experienced as negative and draining (e.g., harvesting food, military drills, and moving cargo) [ 145 , 146 ]. Similarly, musicians commonly experience “being in the groove” as a pleasant state of focus that offsets burdens associated with extended periods of high level performance (e.g., on tour) [ 125 , 129 , 147 ]. Such effects can be understood as rhythmically-driven increases in motivation and effort [ 143 ], potentially reflecting increased engagement of key cortico-basal ganglia-thalamo-cortical loop circuitry (see Fig. 2B ). They are particularly well-characterized in the context of physical exercise, where music can increase enjoyment and reduce perceived exertion [ 148 ], but such benefits may also extend to less muscular tasks (see discussion of the Mozart effect in Section “Another crest in the music and health hype cycle?”). In sum, the biological foundations of rhythm provide insight into how music can be applied to address challenges in mental health associated with mood, cognition, and motivation.

Music and brain reward circuitry

While the framework described so far is based on an analytic separation of tonality and rhythm, the health applications of several other core elements of musicality are better considered in terms of music as a whole. Perhaps the best example is our fundamental attraction to music, as reflected in its marked capacities to stimulate wanting, liking, and learning. Over the past several decades, neuroimaging studies have demonstrated that taking pleasure in music is closely associated with activity in classical brain reward circuitry [ 26 , 149 ], including the mesolimbic dopamine pathway between the ventral tegmental area (VTA) and the nucleus accumbens (NAc) [ 4 ]. Early studies used positron emission tomography with the radiolabeled dopamine D 2 receptor ligand, [ 11 C]raclopride, to show that musical frisson [ 150 ] — moments of peak neural excitement, piloerection, and “chills” that occur during music listening—are associated with surges in dopamine binding within the NAc [ 151 , 152 ]. Additional evidence that music stimulates mesolimbic reward comes from functional magnetic resonance imaging studies showing, for example, that the magnitude of an individual’s NAc response to music correlates with their subjective liking for it [ 153 ].

At the level of brain networks, functional neuroimaging studies have also found that the time-course of musically-stimulated NAc activity is tightly coupled with that of activity in the VTA and hypothalamus [ 154 ]. This has led to the proposal of a “tripartite network” at the core of musical reward, with the hypothalamic node linking desire and pleasure to autonomic and neuroendocrine effects (Fig. 3A ) [ 128 , 154 , 155 ]. Beyond this core, musical reward also engages an extended network of brain areas including the auditory, frontal, and insular cortices, as well as the amygdala and hippocampus, all of which also exhibit temporal coupling with the NAc during music listening [ 149 , 153 , 154 ]. These extended connections are presumed to situate musical reward with respect to sensory, integrative, somatic, affective, and memory-based aspects of musical responding, respectively.

A A model of the extended musical reward network including the tripartite core (red outline) and associated cortical areas and subcortical structures (gray outline). Arrows indicate significant positive temporal correlation in blood-oxygenation-level-dependent activity between the indicated areas during pleasurable music listening. Numbers refer to Brodmann areas ( B ) A close-up of the tripartite core showing dopaminergic (blue), opioideric (green), and oxytocinergic (red) circuitry hypothesized to underpin music’s capacity to stimulate social connection. In rodent models (on which this panel is based) the derivation of reward from positive social interaction requires the oxytocinergic projections from the PVN to the NAc and VTA. C Interactions within the PVN between oxytocin and CRF. Oxytocin decreases the excitability of CRF neurons in mouse hypothalamic slices, and may further inhibit CRF release by modulating CRFR1-positive neurons. Note that music may also have effects on CRF that are independent of oxytocin. ARC arcuate nucleus, CRFR1 CRF receptor type 1, NAc nucleus accumbens, POMC proopiomelanocortin, PVN paraventricular nucleus, VTA ventral tegmental area.

Lastly, as in the processing of other rewarding stimuli like food, sex, and drugs, the hedonic aspects of musical reward are partially dependent on opioidergic mechanisms. This has been shown pharmacologically, as treatment with the (predominantly μ-) opioid receptor antagonists naloxone and naltrexone significantly reduces pleasure in response to musical stimuli [ 156 , 157 ]. Thus, although the work described in this section has been carried out almost entirely with “Western” listeners, the results, taken together with the widespread enjoyment of music around the world, strongly support the sensitivity of brain reward circuitry to musical stimulation as a third core element of musicality.

Applications of musical reward in mental health

In keeping with the central importance of reward in our everyday lives, this element of musicality has extremely broad implications for mental health. Dysfunction in brain reward circuitry contributes to a wide range of psychopathology, including mood disorders, anxiety disorders, substance use disorders, eating disorders, obsessive-compulsive disorders, attention-deficit/hyperactivity disorder, autism spectrum disorders, conduct disorder, Tourette’s syndrome [ 158 ], and schizophrenia. This suggests that the benefits of many current musical treatments may be attributable to normalizing effects of tonality and rhythm on otherwise aberrant activity in brain reward circuitry. Thus, in addition to effects on core dimensions of mental health (e.g., anxiety, mood, cognition, and motivation), musical treatments have also been found efficacious in more specific cases of psychopathology that specifically feature reward dysfunction. Some examples include: substance-use disorder, where adding music therapy to standard treatment can improve motivation to rehabilitate and abstinence [ 159 ]; anorexia nervosa, where interactive music therapy can stimulate reductions in post-meal anxiety that exceed those of other treatments [ 160 ]; and Tourette’s syndrome, where music listening, performance, and even imagined performance, can be an effective tic suppressant [ 161 ].

Further evidence of music’s efficacy against reward-related dysfunction comes from treatments applied to prominent transdiagnostic symptoms, like fatigue [ 162 ], apathy [ 163 , 164 ], and anhedonia [ 165 ]. For example, in a study of nursing home residents age 60+ with mild-to-moderate dementia, a twelve-week interactive music therapy intervention significantly reduced apathy and improved communication, in comparison with a treatment-as-usual control [ 163 ]. The effect sizes were relatively small (SMD = 0.32 and 0.15 respectively), but given the central importance of apathy in dementia and other psychopathology [ 166 , 167 , 168 ], they represent an important starting point for further investigation. In sum, the capacity of music to modulate brain reward circuitry provides a strong mechanistic basis for its benefits across a wide variety of functional disorders in mental health. A better understanding of how and when music stimulates reward is thus critical to advancing music’s therapeutic benefits for mental health.

Converging evidence indicates that engaging in music with other people is an effective way to stimulate interpersonal affiliation and social connection [ 44 ]. Psychological experiments, for example, have repeatedly shown that interpersonal temporal coordination (or “synchrony”) in behavior—a defining feature of musical interaction—strengthens social bonds between participants. This has been measured in terms of increased feelings of affiliation and self-other similarity [ 169 , 170 ], trust behaviors in economic games [ 171 , 172 ], and real-world cooperation [ 173 , 174 , 175 , 176 , 177 ] (reviewed in [ 178 ]). Another line of evidence comes from physiological experiments showing that recreational forms of behavioral synchrony—e.g., in group singing, drumming, or exercise—can upregulate oxytocin secretion [ 155 , 179 , 180 , 181 , 182 ], downregulate cortisol secretion [ 155 , 181 , 183 , 184 , 185 ], modulate immune reactivity [ 182 , 184 , 185 ], and decrease pain [ 186 , 187 ].

In addition to behavioral synchrony, music almost certainly facilitates affiliation and social connection through inducing synchrony in affect. This is perhaps best illustrated by the Iso Principle for mood management in music therapy, one of a few core methods that remains consistent across diverse approaches and therapeutic goals [ 188 ]. Iso Principle is the practice of initiating treatment sessions with music that is parameterized to match the patient’s current mood, creating a basis of shared affect that can then be leveraged to shift mood through musical changes. While the neural basis of synchrony’s effects on social neurobiology has yet to be studied in detail (see [ 189 ] for leading hypotheses), at a psychological level it appears to work through empathetic processes that increase trust and promote openness to further interaction and direction [ 190 ].

A final line of evidence comes from ethnographic and historical observations indicating that music (and dance) are commonly associated with contexts involving high levels of social cohesion. Major examples include religious rituals, cooperative labor, and military drill, as well as overt expressions of group solidarity like political chants, football songs, and national anthems [ 145 , 146 ]. Taken together, these findings strongly support the sensitivity of neural mechanisms supporting affiliation and social connection to musical stimulation as a fourth core element of musicality.

Oxytocin and social reward

Although many artistic and aesthetic experiences are capable of eliciting intense pleasure, music stands out for the regularity with which it does so [ 157 ]. Research suggests that frisson, for example, are induced by music at about four times the rate that they are induced by other stimuli, including the visual arts and literature combined [ 191 ]. This begs the question of why music is so rewarding.

A potential hint comes from the fact that frisson are also induced at high rates by inspirational speech [ 191 , 192 ]. From a mechanistic perspective, this can be taken as support for the hypothesis that the reward potency of music (and speech) reflects high temporal predictability relative to other artistic stimuli [ 150 , 153 ], which is particularly well-suited to anticipatory aspects of reward processing [ 193 ]. At the same time, phylogenetic and developmental perspectives have given rise to the hypothesis that the reward potency of music reflects its basis in social communication [ 149 ]. In this non-mutually exclusive view, music’s capacity to stimulate reward processing also reflects the activity of evolved neural mechanisms that develop to afford the voice with major modulatory control over the rewards of social interaction.

Interest in the link between music and social reward has led many researchers to posit a role for the hypothalamic neuropeptide oxytocin in musicality [ 5 , 44 , 149 , 194 , 195 ], following on its essential functions in affiliative behavior and social bonding (Fig. 3B ) [ 196 , 197 , 198 , 199 , 200 ]. More specifically, music can be hypothesized to stimulate endogenous oxytocin mechanisms that upregulate dopaminergic (and related opioidergic) aspects of reward processing [ 198 ], thereby increasing sensitivity to musical rewards in social context. An important corollary of this hypothesis also addresses the anti-stress effects of music [ 201 ], as music-induced oxytocin release in the hypothalamus may also modulate local corticotropin releasing factor (CRF) circuitry to downregulate activity in the hypothalamic-pituitary-adrenal axis and the sympathetic division of the autonomic nervous system (Fig. 3C ) [ 202 , 203 , 204 , 205 , 206 ].

Applications of sociality in mental health

Social functioning—as reflected in the structure, function, and quality of an individual’s social connections—is a critical determinant of mental health in patients across prominent psychiatric disorders [ 207 , 208 ] as well as the general public [ 209 , 210 ]. This implies that effects of musical treatment of the neurobiology of social functioning may be of even broader significance than closely related effects on brain reward circuitry. However, before describing the clinical evidence supporting such effects, it should be noted that the extent to which musical treatment must involve live interaction to impact social neurobiology is presently unclear. Sound recording is only 160 years old, which implies that the vast majority of our collective experience with music has occurred in social contexts. Accordingly, there is an important sense in which listening to recorded music, even alone, may remain inherently social in neurobiological terms. Our attribution of recorded music to a person (or people) with communicative intent is essentially reflexive [ 211 ], particularly when it comprises vocals. It is also clear that recorded music is often a potent stimulus for behavioral and affective synchrony. Thus, listening to music alone may stimulate social neurobiology in many of the same ways as live musical interaction. Nevertheless, until shown otherwise, it seems reasonable to assume that live interaction is the more potent stimulus for leveraging music’s effect on sociality (e.g., see [ 212 , 213 , 214 ]).

Operationally, social functioning is targeted by interactive approaches to music therapy designed to support interpersonal responding, coordination, and synchrony [ 11 , 215 ]. A large body of evidence supports the benefits of such approaches in autism spectrum disorders [ 216 , 217 , 218 , 219 , 220 , 221 ]. Some of this evidence is summarized in a 2022 meta-analysis of 26 controlled studies including 1,165 children with diagnoses of an autism spectrum disorder (ranging from mild to severe). This analysis compared music therapy to non-musical standard care or a “placebo” therapy over an average duration of 2.5 months (SD = 2.0), with session frequency varying from daily to weekly in shorter and longer studies respectively [ 216 ]. Directly after the intervention, significant benefits associated with music therapy included improvement in clinical global impression (risk ratio=1.22, 8 studies, 583 patients), reduced total autism symptom severity (SMD = 0.83, 9 studies, 575 patients), and better quality of life for clients and/or their families (SMD = 0.28, 3 studies, 340 patients). During the intervention, music therapy was also associated with significant improvements in non-verbal communication (SMD = 1.06, 3 studies, 50 patients) and behavioral adaptation (SMD = 1.19, 4 studies, 52 patients); in the 1–5 months following the intervention, music therapy was associated with reduced total autism symptom severity (SMD = 0.93, 2 studies, 69 patients) and improved self-esteem (SMD = 0.86, 1 study, 35 patients) [ 216 ]. For context, the overall SMD for autism interventions based on Applied Behavior Analysis (a common non-musical behavioral therapy) has been estimated at 0.36 for treating general autism symptoms (based on 14 studies with 555 patients) [ 222 ].

Further evidence supporting the benefits of music therapy for social functioning comes from studies on schizophrenia [ 223 ]. A 2020 meta-analysis of 15 controlled studies involving 964 adults diagnosed with schizophrenia or a schizophrenia-like disorder highlighted significant improvements in negative symptoms (such as flat affect, poor social interactions, and apathy) when adjunct interactive and/or receptive music therapy was compared to standard care (SMD = 0.56) [ 164 ]. This aligns with an earlier 2017 meta-analysis that more specifically investigated social functioning, reporting benefits from two controlled studies involving adults with schizophrenia in which music therapy was compared to antipsychotic medication (SMD = 0.72, N  = 160 patients) [ 224 ]. For context, the SMD of antipsychotic medications for treating negative symptoms in schizophrenia has been estimated at 0.35, based on 167 studies with 28,102 patients [ 225 ].

There is also some evidence that musical interventions can impact social functioning in Alzheimer’s disease and related dementias. For example, individual studies have reported significant benefits of interactive music therapy on language functioning [ 226 ] and receptive music therapy on social engagement [ 227 ]. However, reviews and meta-analyses suggest that such social effects are mainly derivative from primary benefits that reduce agitation, anxiety, and depression [ 228 , 229 ].

Finally, outside of the clinic, musical therapy has long been valued as a non-verbal path to social connection in children with special needs [ 215 , 221 ], as well as a way to combat social isolation and loneliness, particularly in older adults living alone and/or with serious disease [ 184 , 230 ]. In sum, music’s capacity to stimulate the neurobiology of affiliation and social connection is associated with benefits in multiple major mental health disorders and across the lifespan.

Individual differences in musicality

Despite strong foundations in our shared biology, there is also substantial individual variation in neural sensitivity to the core elements of musicality. At the low end of the spectrum are individuals who cannot carry a tune or dance in time, some of whom find music irritating and actively avoid it [ 231 ]. Conversely, at the high end are individuals who find it difficult to live without music, some of whom create works of art that transcend their geographic and temporal horizons [ 232 ]. This high degree of individual variation in musical appreciation and engagement implies that there may also be substantial variation in individual capacity to benefit from musical treatment. In this section and the next I review research on understanding individual variation in musicality, outlining how its measurement may be used to increase the precision with which musical treatments are applied. Accordingly, I argue that better applications of music in mental health depend not only on aligning the neurophysiological effects of music’s core elements with specific clinical targets, but also on matching treatment content to individual differences in musicality.

Psychoacoustic testing

Tests of tone and rhythm perception have long served as the primary way to measure individual differences in musicality. Performance on the most basic of these tests—e.g., measuring sensitivity to harmony and pulse—tends to be positively skewed [ 233 ], reflecting a commonplace competency for music similar to that which we possess for language [ 41 ]. Nevertheless, there is still considerable variation in basic test scores, and this is increased for tests that probe more sophisticated musical abilities [ 234 ].

Environmental factors

Researchers have traditionally sought explanations for individual differences in musicality based on environmental factors. One of the most important environmental factors is formal training , a process by which individuals explicitly learn specific motor skills and rules for music performance and composition [ 235 ]. Formal training is particularly important for explaining sophisticated musical abilities, e.g., as assessed by Goldsmith’s Musical Sophistication Index (Gold-MSI) [ 234 ]. Another important environmental factor is musical enculturation , i.e., the process of implicitly learning the statistical properties of the music to which one is developmentally exposed. Many studies have demonstrated effects of training and enculturation on psychoacoustic tests (e.g. [ 236 , 237 ]). Though sometimes framed as evidence against biological constraints, such effects may be better considered in terms of how biological constraints manifest in the face of environmental variation [ 56 , 78 ].

Biological factors

Progress is also being made towards understanding the genetic basis of musicality [ 27 ]. Early work provided evidence that genetic factors explain surprising amounts of phenotypic variability in psychoacoustic test performance (e.g., 70–80% in tone perception [ 238 ]), as well as time spent practicing music (e.g., 40–70% [ 239 ]; see also [ 240 ]). More recently, genome-wide association (GWA) techniques have been applied to musicality [ 241 , 242 , 243 ]. The largest of these GWA studies to date has focused on rhythm perception [ 243 ]—assessed via the question “can you clap in time with a musical beat?”—in a sample of over 606,825 individuals, accessed via an academic collaboration with 23andMe, Inc. The results indicated that beat perception and synchronization depend on many genes, with variation at 69 loci spread across 20 chromosomes being significantly associated with survey responses after linkage disequilibrium pruning. Additional analyses found enriched expression of genes implicated by these loci in brain-specific regulatory elements as well as fetal brain tissue, indicating potential roles in regulating neurodevelopment. Similar analyses focused on the adult brain found enriched expression in structures implicated in rhythm and reward, including the frontal and temporal cortices, cerebellum, basal ganglia, nucleus accumbens, and hypothalamus (see Figs. 2 C and 3B ).

Although complex traits like our sensitivity to rhythm are expected to be polygenic [ 243 ], some studies have also focused on associations between musicality and individual genes. One of the best studied genes in this context is AVPR1A , which encodes the vasopressin 1A receptor, a major component of the arginine vasopressin and oxytocin signaling pathways [ 196 , 244 ]. Genetic variation in the promotor region of AVPR1A has been associated with phenotypic variation in psychoacoustic test scores [ 245 , 246 ], time spent attentively listening to music [ 247 ], and being a dancer as opposed to another type of athlete [ 248 ]. Variation in AVPRA1 has also been associated with verbal memory [ 249 ], acoustic startle [ 250 ], amygdala activity [ 251 ], prosocial behavior [ 252 ], pair-bonding [ 253 ], and autism [ 254 ]. As intriguing as these associations are, however, it should also be noted that several studies have looked and failed to find associations between musical ability/behavior and AVPR1A polymorphism [ 242 , 255 ]. Other genes of particular interest include VRK2 , FANCL , MAPT , MAPK3 , GATA2 , GBE1 , GPM6A , PCDH7, SCL64A , and UGT8 among others (see [ 27 ] and [ 243 ]).

Lastly, progress in understanding the biology underlying individual differences in musicality has also come from studies of disordered music perception. Congenital amusia [ 256 ] is an umbrella term for lifelong deficits in music perception that prevent people from singing in tune [ 257 ], dancing in time [ 258 ], or deriving pleasure from music [ 259 ]. Deficits in tone perception (or tone deafness ) is the best studied form of congenital amusia: it runs in families [ 238 , 260 ] and is associated with decreased connectivity between the auditory cortices and the inferior frontal gyrus [ 261 , 262 ], potentially reflecting abnormal frontotemporal cortical development [ 263 ]. The prevalence of tone deafness is approximately 1.5%, with as many as 4.2% of people exhibiting a lesser form of impairment [ 264 ]. Deficits in rhythms perception (or beat deafness ) appears to be at least as common [ 264 ]. Finally the prevalence of music-specific anhedonia , which, as the name implies, occurs despite otherwise normal hedonic functioning, is estimated at about 5% [ 265 ].

Hypotheses for precision medicine

Faced with questions about whether a patient is sufficiently musical to engage in treatment, many music therapists provide reassurance, as a significant part of their practice is dedicated to finding adaptive ways to leverage music’s capacities to align with individual strengths [ 266 , 267 ]. While this resource-oriented approach has the benefit of allowing music therapists to work with almost anyone, the framework proposed here can potentially offer more systematic guidelines for determining whether a patient is likely to benefit from musical treatment. Fundamentally, patients with a history of strong engagement with music and keen sensitivity to its tonal, rhythmic, rewarding, and social elements would appear to be good candidates for musical treatment, especially if neurophysiological systems influenced by one or more core elements of musicality are implicated by their symptoms. Conversely, those patients who report disliking music, find it unrewarding, or otherwise qualify for congenital amusia, would seem to have a lower likelihood of benefiting.

In between these extremes are individuals whose specific musicality profiles —conceived as a series of measurements describing sensitivity to each core element of musicality—have important potential to inform decisions about treatment content. As an example, treatment for a patient with below-average tone perception, but normal sensitivity to musical reward, rhythm, and sociality could be personalized to align with their musicality profile by focusing on the neurophysiological effects of rhythm in an affiliative interactive context in which tonal elements are minimized or omitted.

Defining musicality profiles

While measurements of underlying biology may improve assessments of individual differences in musicality in the future, current efforts must rely on psychoacoustic tests and surveys. Among the most promising for determining suitability for musical treatment is the Barcelona Music Reward Questionnaire (BMRQ) [ 265 ], a survey of 20 self-reported items that assess the degree to which an individual takes pleasure in different aspects of music. For individuals with normal scores on the BMRQ, further insight may be gained through a series of basic psychoacoustic tests, like the scale test and out-of-key test (for evaluating tone perception) and the off-beat test (for evaluating rhythm perception) from the Montreal Battery of Evaluation of Amusia (MBEA [ 233 , 268 ]; see MBEMA for testing children aged 6 to 10 [ 269 ]). If a more comprehensive assessment is desired, clinicians can deploy the Gold-MSI (for musical sophistication) [ 234 ] or the computerized beat alignment test (for rhythm) [ 270 ].

Although not explicitly focused on music, it may also be useful to assess a patient’s level of social functioning and anxiety (e.g., with the Social Responsivity Scale [SRS] [ 271 ] and Liebowitz Social Anxiety Scale [LSAS] [ 272 ] respectively), as the results could inform decisions about the extent to which a musical intervention should target social functioning. Interactive music therapy can be hypothesized to be most effective in cases where social functioning and social anxiety are both low. By contrast, in cases where social anxiety (or anxiety more generally) is high, the most effective approach may instead require limiting social interaction, at least at first. In keeping with this hypothesis, interactive approaches to music therapy in dementia (where anxiety is often high) are significantly less effective than receptive approaches at reducing agitation and behavioral problems [ 229 ]. Similarly, in music therapy for autism—which is predominantly interactive—high comorbidity with anxiety disorders may help explain some of the heterogeneity in trial results (cf [ 273 , 274 ].). Lastly, in cases where a patient is unable to complete surveys or perform perceptual tests due to developmental delay or cognitive impairment, interviewing caregivers about the patient’s history of music engagement and social functioning can offer valuable insights into their potential sensitivity to musical treatment.

Idiosyncratic preferences

Beyond tailoring musical treatments to align neurophysiological effects with clinical targets and individual musicality profiles, treatments may also be customized based on individual music preferences or “taste” [ 275 , 276 ]. In receptive music therapy, for example, it’s common for patients to nominate songs they like, with therapists providing oversight for alignment with therapeutic goals [ 89 ]. One major advantage of this approach is that listening to preferred music can be especially rewarding [ 151 , 277 ]. This is often attributed to the familiarity of preferred music, which facilitates expectations, their fulfillment, and associated memories and emotions [ 150 , 278 , 279 ]. Other potential benefits of preferred music include fostering a sense of safety, enhancing engagement, and reducing stress [ 280 , 281 , 282 ]. However, personal memories and associations can also make the therapeutic value of preferred music difficult to control, especially if not carefully reviewed [ 283 ]. This is because what a person likes is not necessarily aligned with their therapeutic goals. A prime example is that people with depression often prefer music that maintains or exacerbates their sadness [ 284 , 285 , 286 ] (but see [ 285 , 287 , 288 ]). Accordingly, despite the benefits of preferred music, using novel or unknown music is advisable in some contexts.

Having already changed how people discover new music, algorithmic music recommendation systems may also find applications in mental health. However, the issue of mismatch between what a person likes and their treatment goals remains significant here as well. For example, listening to strongly preferred or popular music while attempting to focus tends to decrease task performance [ 140 , 142 ]. In the extreme, the lifestyle associated with many forms of popular music is linked to substance abuse, risk-taking, suicide, homicide, and accidental death among practitioners [ 289 ]. This highlights the fact that engagement with music is not necessarily health-positive (cf [ 290 , 291 , 292 ].). In therapeutic contexts, though, there are still many cases in which tailoring musical interventions to idiosyncratic preferences can be beneficial. For example, in receptive music therapy for Alzheimer’s disease, listening to familiar, preferred music appears to carry benefits for self-awareness [ 293 ]. Similarly, in depression, preferred music is likely to be the most effective stimulus for normalizing brain affect and reward functions, provided that it has been properly vetted to avoid stimulating negative affect. Finally, when a patient has normal sensitivity to musical reward but only within a very restricted genre (e.g., from their youth [ 294 ]), or, reports enjoying music despite poor tone and rhythm perception [ 295 ], understanding their idiosyncratic preferences may be necessary to design effective treatment.

In sum, determining the therapeutic value of aligning musical treatment with idiosyncratic preferences is of central importance for musical applications in mental health. That said, progress in this kind of preference matching should be incorporated within a broader precision paradigm as advocated here, which aims to align the specific neurophysiological effects of musicality’s core elements with specific clinical targets and individual differences in associated responsivity.

Skepticism and need

In this final section, I address several important points of skepticism regarding the premise of the biological framework presented here, i.e., the hypothesis that music can do more for mental health.

Benefits from music to mental health are already at saturation

In addition to the effects of musical treatment described above (see Sections “Applications of tonality in mental health.”, “Applications of rhythm in mental health”, “Applications of musical reward in mental health”, & “Applications of sociality in mental health”.), there is strong evidence that people derive mental health benefits from more casual engagement with music. During the height of the COVID-19 pandemic, for example, more than half of 4,206 survey respondents reported engaging with music as a coping strategy, using it to derive reward, modulate mood, and/or reduce stress and anxiety [ 296 ]. Similar positive functions are apparent in pre-pandemic research as well (alongside more social functions) [ 2 , 297 , 298 , 299 ]. Associations between music and healing have also been found in many cultures throughout human history, suggesting a potentially ancient relationship [ 300 , 301 ]. Thus, even though music lies outside the mainstream of mental health care, many people are already using music to improve their condition.

Nonetheless, there are multiple ways in which music’s mental health benefits may be increased. First, expanding access to musical treatment is essential [ 302 ]; as stated in the introduction, music therapists in the US only have the capacity to treat 0.5% of adults with mental illness. I have argued that this necessitates standardizing and applying treatments within a biological framework. Second, the popular perception of music as entertainment needs to evolve to encompass its therapeutic benefits. Explaining musical treatments in biomedical terms and normalizing therapeutic modes of listening can facilitate this shift. Third, the balance in music education needs to pivot away from individual performance and back towards widespread attainment of basic skills (e.g., social singing and dancing, listening, reflecting, curating, etc.), with an explicit focus on developing lifelong tools for mental health and wellness [ 303 ].

Another crest in the music and health hype cycle?

Even if one accepts that music has expandable mental health benefits, the importance of music’s potential might still seem overblown, here and elsewhere. It is worth revisiting the Mozart effect in this context, as an example of music’s real effects and associated hyperbolic overinterpretation. In 1993, a study published in the journal Nature reported that 10 min of listening to a spirited Mozart sonata, versus speech-based relaxation, or silence, improved performance on a subsequent spatial reasoning task [ 144 ]. After being picked up by popular press, this finding was transformed into the notion that “listening to Mozart actually makes you smarter” [ 304 ], which was subsequently used to market books and other media for benefits purportedly backed by science [ 305 ]. Backlash from the scientific community in the form of criticism and further investigation eventually came to show that the Mozart effect amounts to a relatively small but replicable performance boost that generalizes to other types of music (and speech) which stimulate enjoyment and arousal (SMD = 0.37 in meta-analyses) [ 143 , 305 , 306 ]. Thus, while we should remain guarded against hype surrounding claims about music’s potential benefits, the example of the Mozart effect should also remind us not to counter hype with dismissal.

Low quality studies undermine claims of clinical value

The randomized double-blind placebo-controlled trial remains the gold standard for evidence in clinical medicine. However, this approach was primarily designed to test the efficacy of drug therapies, a history that creates problems for using it to test behavioral interventions, such as music therapy or psychotherapy [ 307 , 308 ]. Central problems include: difficultly blinding patients and therapists to their assigned condition (treatment or control), designing appropriate “placebo” treatments, and perceived difficulty in standardizing treatment without jeopardizing therapeutic integrity [ 308 , 309 ]. These problems are compounded in trials that rely on self- and/or clinician-reported outcomes (which is standard in much mental health research [ 309 ]). Consequently, concerns over study quality have often been cited in expressions of doubt over music’s clinical value (e.g. [ 302 , 308 ]).

A quick survey of modern clinical research in music therapy shows that such criticism has been well-received. Improvements in control conditions and blinded outcome assessments have been gradually implemented and evidence from more carefully conducted trials has begun to accumulate. Over the last decade, there has also been a surge in meta-analytic syntheses of this work, most of which explicitly assess risk-of-bias alongside their conclusions, although they do not typically take the next step of adjusting effect size estimates accordingly (cf [ 96 , 310 ].). Overall, bias assessments suggest that the certainty of evidence supporting benefits from musical treatment in mental health is moderate to low. Nonetheless, this level of certainty is consistent with many treatments in psychiatry [ 94 ]. The assertion that studies of musical treatment are especially suspect is thus poorly substantiated. Interested readers should consult bias assessments in these meta-analyses [ 93 , 95 , 96 , 133 , 164 , 216 , 224 , 229 ], and review individual studies that exemplify high-quality research on musical treatments for conditions such as anxiety [ 311 , 312 ], depression [ 313 , 314 ], autism [ 274 , 315 ], psychosis [ 316 , 317 ], and dementia [ 318 , 319 ].

Mental health needs

In concluding this section, it is useful to briefly consider musical treatment in the context of current mental health needs. In 2007, mental health disorders were estimated to account for 14% of global disease burden [ 320 ]. In 2021, an estimated 22.8% of adults in the United States had a diagnosable mental illness, with 12.7% of adolescents having serious thoughts of suicide [ 17 ]. In opposition to this growing psychopathology, first-line treatments in psychiatry are often criticized for their limited effectiveness [ 94 , 320 , 321 ]. Quantifying this point, a 2022 meta-analytic evaluation of 3,782 clinical trials examining the most common adult mental health disorders across a total sample size of 650,514 patients estimated summary effect sizes of just 0.34 SMD for psychotherapy and 0.36 SMD for pharmacotherapy [ 94 ]. In depression, SMDs <0.88 represent changes in a patient’s presentation that are typically too small to be detected by a clinician, suggesting that the effects of standard treatments for depression commonly lack clinical significance [ 94 , 322 , 323 ]. A similar SMD threshold in schizophrenia is 0.73 [ 94 , 324 ]. It is crucial to note that small summary effect sizes in meta-analyses are averages, and thus obscure the reality that a minority of patients have experienced clinically significant benefits under current treatments (due to poorly understood individual differences in treatment response). Nevertheless, the data at hand clearly indicate that new treatments are urgently needed [ 94 ].

It is in this context that advancing new standardized music-based interventions is important, not only because music affects core dimensions of mental health through the biology of tonality, rhythm, reward, and sociality, but because these avenues present an accessible, easy-entry, and low-risk approach to addressing problems for which we need solutions. Music is poorly conceived as a panacea. Instead, it has real effects on human neurobiological functions that feature prominently in mental illness, and thus has important potential in treating their disorder.

The effects of music on mental health and wellness are drawing more attention now than ever before. Efforts to better understand music’s benefits and increase their integration into medicine are complicated by their impressive diversity and a lack of clarity regarding underlying biology. This review has addressed these challenges by synthesizing progress in music research from psychology, neuroscience, and psychiatry to create a framework for defining music’s neurophysiological effects and their clinical scope in biological terms. This framework includes four core elements of human musicality: tonality , based on tone perception and the bioacoustics of vocal emotional expression, with applications targeting mood and anxiety; rhythm , based on neural resonance, anticipation, and auditory-motor entrainment, with applications targeting mood, cognition, and motivation; reward , based on engagement of classic brain reward circuitry and the reinforcement of successful communication, with broad applications in stimulating positive affect and normalizing reward function; and sociality , based on synchrony and the neurobiology of affiliation, with broad applications in treating social dysfunction and increasing social connectedness. This framework rationalizes many observed benefits of musical treatment and provides a path towards a precision approach to increasing their impact. As the world continues to change and we face new challenges to mental health and wellness, music will continue to provide real biologically mediated relief. Understanding and leveraging this fact towards better treatments and interventions in psychiatry presents an important opportunity to diversify and improve care during times of pressing need.

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The author would like to thank Drs. Dale Purves, Concetta Tomaino, and Karen Parker for comments on drafts of this manuscript, as well as Drs. Daniel Levitin, Patrick Savage, and two anonymous reviewers for constructive feedback during peer review. This work was supported by NIMH grant K01MH122730.

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Bowling, D.L. Biological principles for music and mental health. Transl Psychiatry 13 , 374 (2023). https://doi.org/10.1038/s41398-023-02671-4

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38 Music Therapy Research: Context, Methodology, and Current and Future Developments

Jane Edwards, Deakin University

• Published: 09 June 2015
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Music therapy is an evidence-based profession. Music therapy research aims to provide information about outcomes that support music therapy practice including contributing to theoretical perspectives that can explain why changes occur during treatment. Music therapy research has been conducted in a range of health, education, and community contexts throughout the world. Initially many music therapy developments in the university sector occurred through the establishment of training programmes that were developed and delivered by music therapists with professional experience in leading services in education and health care. Now many music therapy training programmes are led by people with practice experience along with research qualifications, and some universities offer music therapy doctoral pathways. Music therapy research capacity has expanded through a notable increase in PhD graduates as well as an increase in funded research in music therapy. This chapter covers: (1) traditions, (2) trends, and (3) contexts for music therapy research.

Introduction

Research is the process by which new knowledge is developed, existing knowledge is extended, and new theoretical frameworks are founded. In health care, research provides evidence for effective ways of working with patients or clients to achieve positive change; maintaining or improving optimal health and well-being. Research methods in health and education are characterized by a guiding research question or hypothesis, a theoretical or epistemological 1 orientation adopted by the researcher, a data source, and a selected method of data collection and analysis that is agreed in advance of the research commencing. All research is bound by an ethical code which is assured by approval from an Institutional Review Board, or an ethics committee. This process confirms that the processes of the research will cause no harm or discomfort to the participants, and will add value to existing knowledge.

Music therapy research is usually undertaken within the context of a university with outreach to recruit patients or students in health care or education. Initially music therapy in the university sector was built up through training programmes that were developed and delivered by people with professional experience in developing and leading music therapy services in education and health care. As higher education institutions across the world have become increasingly invested in all academic staff being research active including attaining PhDs and regularly applying for competitive research funding this has influenced the landscape of music therapy within the higher education environment. Increasingly it is unusual to find a course leader who does not either have a PhD or is working towards a PhD. Full-time permanent academic positions across the university context internationally usually require that the person has a PhD and a substantial body of work that has contributed to knowledge development in their specialist field.

Traditions of research in music therapy

In the fledgling years of music therapy research a commitment to quantitative methods within a strict positivist epistemology can be observed, especially in research publications within the USA. This was partly because of the influence of behavior modification as a technique in therapy practice ( Madsen et al. 1968 ). Modifying behavior that could be observed and measured was the goal of music therapy. Many researchers used randomized controlled trials (RCT) to examine the effects of music therapy on behaviors of clients. RCTs are studies in which participants are randomly assigned to either a music therapy treatment group, or to a control group which does not receive the treatment. The RCT is considered a gold standard within medical research ( Greenhalgh 2014 ). It is a highly effective method by which to test the effects and benefit of pharmacological medications. It can also show treatment outcomes when groups are compared where one group receives a treatment and another group, matched with the treatment group, do not (see Robb and Burns , this volume). Because of the alignment of music therapy with allied health, and the delivery of many music therapy services within medical contexts, the use of the RCT has been common in music therapy research ( Bradt 2012 ).

The most important historical development in this type of research was the introduction of randomization, where participants or subjects are randomly assigned to one of the groups, whether treatment, control, or placebo (see Robb and Burns , this volume). This random allocation to groups minimizes bias and increases the likelihood that the results of the research will be trustworthy.

In the later part of the twentieth century music therapy research reports using new methods entered the published literature, and references to new methods can be observed (for example, Aigen 1993 ; Amir 1993a , b ; Comeau 1991 ; Forinash 1992 ; Forinash and Gonzalez 1989 ; Langenberg et al. 1993 ). The early years of qualitative methods followed along the same route as other allied health research where qualitative inquiry or qualitative research became a commonly used descriptor ( Edwards 2012 ). Although qualitative is a useful description for many research methods it is not in and of itself a method. Distinctions between methods and epistemologies within qualitative traditions have not always been well defined in music therapy research reports ( Aigen 2008 ), and also in other allied health research writings ( Carter and Little 2007 ). In the maturation of music therapy research a wider range of methods and traditions have been engaged, and knowledge about different methods has become more elaborated and differentiated. It is now agreed that all methods have an underlying epistemology, and in using qualitative method research it is essential to be able to state ones position in relation to the theory of knowledge creation to which one subscribes ( Edwards 2012 ). Frequently used qualitative research methods in music therapy are grounded theory (see Daveson this volume; O’Callaghan 1996b ; 2012 ), and phenomenology ( Ghetti this volume).

An important distinction between research methods is whether they use inductive or deductive processes. Inductive refers to the way in which the researcher allows the information to be induced from the data during analysis ( O’Callaghan and McDermott 2004 ; O’Callaghan 1996a ). The researcher looks closely at the data, usually text or arts based, and reflects on the materials allowing meanings to emerge. Research which is deductive uses a pre-defined criteria to examine the data. For example, looking for particular incidences of a word in text or measuring a baseline behavior then providing treatment and following up with a further measure. Deductive might also refer to research in which the themes to be examined are decided in advance even when a qualitative method is used.

Research is published in journals following a process of anonymous peer review. A paper is submitted to just one journal and then the editor sends an anonymized version of the paper for review to at least two professionals with expertise in the area of the paper’s content. The reviewers read the paper and provide feedback to the editor about their opinion of the paper. Reviewers can recommend the paper should be published, or they can request revisions, or they can recommend that the paper be rejected. It is not unusual that articles are rejected. It can be because the editor or reviewers do not think the topic of the paper is relevant to the journal, or there can be issues of quality with the research that deem it unsuitable for publication. Many researchers make revisions to rejected papers and then submit them to another journal. It is unacceptable to submit to more than one journal at a time, and authors must sign a declaration at submission that the work has not been published elsewhere or been submitted for review to another journal.

Peer reviewed articles appear in the following English language journals of music therapy: Australian Journal of Music Therapy, British Journal of Music Therapy, Canadian Journal of Music Therapy, Journal of Music Therapy, Music Therapy Perspectives, Nordic Journal of Music Therapy , the New Zealand Journal of Music Therapy , and Voices . There are also related journals which publish music therapy research papers including: Psychology of Music, Music and Medicine , and The Arts in Psychotherapy . Music therapy research also appears in medical and therapy journals (for example, Loewy et al. 2013 , O’Callaghan et al. 2014 ). Therefore when students are researching projects or writing papers are encouraged to search the journal literature as well as reading relevant books and book chapters.

Trends in music therapy research

In this part of the chapter three trends in music therapy research will be discussed: (1) music therapy and evidence-based medicine, (2) arts-based research, and (3) mechanisms of change in music therapy.

Music therapy and evidence-based medicine

A number of music therapists have considered the ways that the profession can respond to the imperative of evidence-based medicine (EBM). EBM can be traced back to the 1960s but it more formally entered the lexicon of health care practice through the 1990s ( Smith and Rennie 2014 ). As a PhD researcher in a department of Paediatrics and Child Health in the 1990s the author observed firsthand the shift in thinking about practice and services that occurred when EBM began to be a main point of interest for researchers, not just in medicine but also through nursing and allied health departments. In order to consider the implications for music therapy she gave a series of presentations which were then worked into scholarly papers for publication. After initial rejection some of the ideas were eventually published ( Edwards 2005 , 2004 , 2002 ). Since that time others have also written about EBM and music therapy (for example Abrams 2010 , and Standley 2012 ).

Rather than relying on the outcome of a single RCT to develop new practices in health care, EBM proposed an evidence hierarchy founded on single cases (weak evidence) through to meta-analyses (strong evidence). In a meta-analysis the research findings from a number of studies with patients who have similar characteristics are analyzed statistically to show whether the changes that have occurred across all of the studies are convincing enough to warrant inclusion of the treatment in standard care. Dileo and Bradt concluded that “Overall, EBP [practice] intends to assure that patient treatment is safe, effective, and cost-effective.”(2009, p. 170)

Abrams has positioned evidence-based music therapy having multiple benefits for the profession:

The virtues of an integral understanding of evidence-based music therapy practice are numerous. It can help promote clarity of the different roles, purposes, strengths, and limits of each domain of evidence. It provides accountability to core values, standards of integrity, and standards of rigor, all internally consistent within a given perspective in any given instance. Moreover, it encourages an awareness of the applicability and relevance of evidence to clinical work in any given case. Abrams 2010 , p. 374

Earlier conceptualizations of EBM pointed out that music therapists are often referred clients or patients for whom other therapeutic supports or treatments have not been effective ( Edwards 2005 ). Therefore because of the complexity of the client’s situation and their unique needs traditional processes of matching of clients in control and treatment groups in the traditional RCT might not be possible.

Concepts used in evidence are now turning towards music therapy participants’ views to be a better accessed and utilized form of evidence (for example, Ansdell and Meehan 2010 ). Although initially this author’s concerns about EBM focused on inappropriate application by managers to limit innovation and cut services, in practice EBM has some but not complete influence on service leaders’ decisions to support or close programmes. At the same time it has produced an outstanding number of music therapy meta-analyses published in the most important medical evidence database in the world, the Cochrane Library (for example Mössler et al. 2011 ).

Arts-based research

The arts are increasingly being used in health care and related research to learn about the experiences of care workers and recipients, to gain access to marginalized voices, and to communicate research findings to a wider audience. Ledger and Edwards 2011 , p. 313

Arts-based research is a movement that has developed internationally with minimal input from creative arts therapists. Ledger and Edwards (2011) provided a number of examples in which music therapists appeared reluctant to describe their research methods as arts based . This reluctance was hypothesized as emerging from anxiety about seeming scientific enough, especially when conducting research in health and medical contexts.

As artistic processes within music are central to music therapy practice, the use of music making or other creative arts processes could be considered compatible with the goals of music therapy inquiry. It is therefore puzzling why arts based processes are not more widely used in music therapy research.

Arts-based research was included in the main research textbook to date in music therapy ( Wheeler 2005 ). Dianne Austin and Michele Forinash make a distinction between arts based research and the studies that have analyzed music created in music therapy sessions. They have shown that the arts can be used at every step in the research process to develop rich and expressive findings. Arts-based research is explained as offering a valuable way to gain insights that might not otherwise be discoverable ( Austin and Forinash 2005 ).

Mechanisms of change in music therapy

Research contributes to knowledge about change, but researchers also have a responsibility to theorize why the change occurs. Research relevant to music therapy from the fields of psychology and neuroscience are key to understanding the mechanisms of change in music therapy. For example, music therapy relies on the evocative potentials of music to develop a way of relating between the therapist and the client that is helpful in meeting the client’s needs and contributing to their well-being. Some of these evocative capacities include the ability of music to influence affect. In order to be able to interact and support clients in a way that is helpful and informed, understanding how music influences emotional states is key. Music therapists have extensive experience and expertise in observation of musical responses. As an experienced music therapy practitioner the following mechanism as to how emotional response to music might occur makes sense to the author. Julin and Västfjäll have proposed that when humans listen to music all of the following psychological processes happen, not separately but concurrently, and this is why an emotional response occurs:

(1) brain stem reflexes, (2) evaluative conditioning, (3) emotional contagion, (4) visual imagery, (5) episodic memory, and (6) musical expectancy. Juslin and Västfjäll 2008 , p. 563

Their proposition is interesting for music therapy practitioners to engage in order to understand the instantaneous aspects of response over which an individual has no control, and to confirm that there is no one piece of music that has the same effect on every listener. However, many psychological theories such as these that are relevant to music therapy are silent on the core interpersonal and relational aspects of music therapy. Therefore neuropsychological and physiological theories need to be accessed in order to further understanding of music therapy as a relational practice.

Developing theories about brain growth indicate that infant brains develop in collaboration and interaction with other brains ( Schore 2010 ). Loving, predictable responsiveness from the adult care giver is essential for an infant’s healthy start in life. The failure of the infant-parental bond to coalesce and attachment to be formed is disastrous for the child’s ongoing development. This can occur because of maltreatment and/or neglect, or because of demands on the carer’s own resources result in them being unavailable to the infant’s needs. This has lifelong consequences on development, particularly the skills needed for social interaction with others, and the resilience to deal with stressful experiences and events. Neurosequential modelling proposes that the infant brain develops in stages.

The brain is organized in a hierarchical fashion with four main anatomically distinct regions: brainstem, diencephalon, limbic system, and cortex. During development the brain organizes itself from the bottom up, from the least (brainstem) to the most complex (limbic, cortical) areas. While significantly interconnected, each of these regions mediates distinct functions, with the lower, structurally simpler areas mediating basic regulatory functions and the highest, most complex structures (cortical) mediating the most complex functions. Each of these main regions develops, organizes, and becomes fully functional at different times during childhood… Perry 2009 , p. 243

This theory is important for music therapy because it provides information to explain why children who have not developed self-regulatory processes due to severe early relational trauma, for example what Perry described as the “overanxious, impulsive, dysregulated child” (p. 243), might behave differently in the regulating holding environment of music therapy where predictable structure can contain and support the child’s actions and spontaneity (for relevant case examples, see Drake 2011 ).

The therapeutic opportunities in music therapy lie not only in the client’s responses to music but equally and sometimes more importantly in the therapist-client relating. Porges’ Polyvagal Theory is so named because it associates two physiological systems with feelings of safety and security and explains how these function in interpersonal relating. These are:

(a) the commonly known fight-or-flight system that is associated with activation of the sympathetic nervous system… and (b) a less-known system of immobilization and dissociation that is associated with activation of a phylogenetically more ancient vagal pathway. Geller and Porges 2014 , p. 180

Using the Polyvagal Theory ( Porges 2011 ) Geller and Porges (2014) have illuminated therapeutic presence as a salient factor reliant on neurophysiological processes by which safety, security, and trust are experienced in the therapeutic relationship. Given that many people who seek or are referred to psychological services have experienced a breakdown of their capacity to cope, or to relate successfully with others, the ability to provide safety and security in the interpersonal space is crucial to providing opportunities for capacity building towards growth and change.

Expert therapists have reported that the experience of therapeutic presence involves concurrently (a) being grounded and in contact with one’s integrated and healthy self; (b) being open, receptive to, and immersed in what is poignant in the moment; and (c) having a larger sense of spaciousness and expansion of awareness and perception. This grounded, immersed, and expanded awareness also occurs with (d) the intention of being with and for the client in service of their healing process. By being grounded, immersed, and spacious, with the intention of being with and for the other, the therapist invites the client into a deeper and shared state of relational therapeutic presence. Geller and Porges 2014 , p. 180

Polyvagal theory has contributed to the development of new ways of working as well as supporting existing practices in music therapy. As Loewy (2011) noted:

… [Polyvagal Theory] contributes to the theoretical justification for the role that music therapy can play in activating neural circuits that regulate reactivity. Porges’ rationale for and description of feeding and rocking as primal attachment behaviors which influence vagal afferent pathways is an essential contributor to the current thinking about the importance of the quality of care in the first stage of life. Music therapy practices that activate somatomotor components which trigger visceral change influence attachment practices which are critically important in the early years. Loewy 2011 , p. 182

The relational dimensions of music therapy practice are underpinned by multiple psychobiological principles including those encapsulated in communicative musicality initially developed by Stephen Malloch in his postdoctoral work at Edinburgh University, which was then further elaborated ( Malloch and Trevarthen 2009 ). Malloch and Trevarthen (2009) documented how the development of the theory and observation of the presence of communicative musicality occurred through many decades of research in the last century. Importantly multiple theorists and researchers from a range of fields, whether during field observations or in laboratory based experimental work, noted the expressive, dance and song like interactions between infants and the adults who share loving relationships with them. These multiple perspectives result in the conclusion that:

… we are evolved to know, think, communicate, create new things and care for one another in movement—through a sense of being in rhythmic time with motives and in tune with feelings to share the energy and harmony of meaning and of relating. Malloch and Trevarthen 2009 , p. 8

Contexts for research

All research conducted with service users in music therapy involves a context. This may be a single site such as a school or a hospital (see Colwell , this volume), or multiple sites. It may involve a service such as an oncology department, or additionally it may involve participants who access multiple services, for example children with cerebral palsy. Each context differs as to how service users or students can be approached to be involved in the research, and who will act as formal or informal gate-keepers. Researchers planning projects need to factor in how the people who will contribute to managing the data collection of the project will be sorced, and how these potential gate-keepers will assist in managing the recruitment and involvement of service users. Often people who are crucial to the research such as gate-keepers receive little acknowledgement either in research reports, or in international publications. This can make it difficult for novice researchers to understand how crucial they are to conducting research which relies on data collection from service users or students ( Porter et al. 2014 ).

Clinicians working within a service are often the referring point for participation in a music therapy project. The clinician can decide whether a person who meets the criteria for the project is able to manage the requirements of the project participation, and would potentially benefit from being a research participant. Clinicians are protective of their clients or patients. Therefore the researcher must take care to ensure that the clinician has confidence in the researcher and the research processes, that participants will not be taxed or made demands of in any problematic way. The gatekeeper may also be encoraged to note that the client may end up receiving music therapy, and that this participation may be highly enjoyable and potentially therapeutically beneficial.

One contextual dimension that has received limited attention in the literature is the role of the researcher and how this differs from the role of music therapist. Ledger (2010a) has reflected on her experiences as a music therapy researcher undertaking an ethnographic research project in a hospital that was developing a new music therapy service. She wrote:

Returning to the familiar setting of a hospital brought to the fore a set of previously held positions and behaviors. I needed to manage not only the boundary between researcher and music therapist but also the boundaries between researcher and colleague, researcher and friend, and experienced music therapist and student. These boundaries needed to be negotiated and renegotiated throughout the duration of my ethnography. There were times when it was helpful to cross boundaries in order to build rapport and to show appreciation to the staff who contributed to my research. However, there were also times when I needed to establish clear boundaries and to reiterate my research intentions. Ledger 2010a , p. 300

Ledger’s further reflection reveals some of the dilemmas that can arise when conducting qualitative methods research ( Ledger 2010b ). Unlike other types of research where one might collect data through testing or questionnaires, ethnography involves participation and observation. Being aware of the need to manage and negotiate role identity is an important part of undertaking this work.

The future of music therapy research

As music therapy matures and grows as a field of practice it is developing its depth and breadth of research engagement. Contemporary research is immensely inspiring, especially for increasingly sounding the voices of service users ( Ansdell and Meehan 2010 ; Solli et al. 2013 ), and the careful development of research procedures which ensure the complexity of musical experiences are not lost in the need for research rigor ( Erkkilä et al. 2011 ). The development of greater sophistication in mixed methods research (see Erkkilä , this volume) will ensure that the outcomes of psychological testing or observation of the therapist will not be privileged over the lived experience of participants. The increasing harnessing of the capacities of technology in conducting systematic evaluation of music therapy services show promising developments ( Streeter et al. 2012 ). More robust theoretical engagement with neuroscience and psychophysiology (for example Loewy 2011 ) and social theories ( Baines 2013 ) will ensure that music therapy has strong theoretical bones upon which the flesh and sinew of competent practice can continue to grow.

Epistemology refers to theory of knowledge. All research has an epistemological foundation whether or not it is made explicit. For further information see Edwards (2012) .

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Peer-reviewed

Research Article

Effects of music therapy on depression: A meta-analysis of randomized controlled trials

Roles Conceptualization, Writing – original draft

Affiliation Bengbu Medical University, Bengbu, Anhui, China

Roles Methodology, Software

Affiliation Anhui Provincial Center for Women and Child Health, Hefei, Anhui, China

Roles Writing – review & editing

Affiliations Bengbu Medical University, Bengbu, Anhui, China, National Drug Clinical Trial Institution, The First Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui, China

Roles Conceptualization, Writing – review & editing

* E-mail: [email protected]

• Qishou Tang, 
• Zhaohui Huang, 
• Huan Zhou, 

• Published: November 18, 2020
• https://doi.org/10.1371/journal.pone.0240862
• Peer Review
• Reader Comments

We aimed to determine and compare the effects of music therapy and music medicine on depression, and explore the potential factors associated with the effect.

PubMed (MEDLINE), Ovid-Embase, the Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, and Clinical Evidence were searched to identify studies evaluating the effectiveness of music-based intervention on depression from inception to May 2020. Standardized mean differences (SMDs) were estimated with random-effect model and fixed-effect model.

A total of 55 RCTs were included in our meta-analysis. Music therapy exhibited a significant reduction in depressive symptom (SMD = −0.66; 95% CI = -0.86 to -0.46; P <0.001) compared with the control group; while, music medicine exhibited a stronger effect in reducing depressive symptom (SMD = −1.33; 95% CI = -1.96 to -0.70; P <0.001). Among the specific music therapy methods, recreative music therapy (SMD = -1.41; 95% CI = -2.63 to -0.20; P <0.001), guided imagery and music (SMD = -1.08; 95% CI = -1.72 to -0.43; P <0.001), music-assisted relaxation (SMD = -0.81; 95% CI = -1.24 to -0.38; P <0.001), music and imagery (SMD = -0.38; 95% CI = -0.81 to 0.06; P = 0.312), improvisational music therapy (SMD = -0.27; 95% CI = -0.49 to -0.05; P = 0.001), music and discuss (SMD = -0.26; 95% CI = -1.12 to 0.60; P = 0.225) exhibited a different effect respectively. Music therapy and music medicine both exhibited a stronger effects of short and medium length compared with long intervention periods.

Conclusions

A different effect of music therapy and music medicine on depression was observed in our present meta-analysis, and the effect might be affected by the therapy process.

Citation: Tang Q, Huang Z, Zhou H, Ye P (2020) Effects of music therapy on depression: A meta-analysis of randomized controlled trials. PLoS ONE 15(11): e0240862. https://doi.org/10.1371/journal.pone.0240862

Editor: Sukru Torun, Anadolu University, TURKEY

Received: June 10, 2020; Accepted: October 4, 2020; Published: November 18, 2020

Copyright: © 2020 Tang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The Key Project of University Humanities and Social Science Research in Anhui Province (SK2017A0191) was granted by Education Department of Anhui Province; the Research Project of Anhui Province Social Science Innovation Development (2018XF155) was granted by Anhui Provincial Federation of Social Sciences; the Ministry of Education Humanities and Social Sciences Research Youth fund Project (17YJC840033) was granted by Ministry of Education of the People’s Republic of China. These funders had a role in study design, text editing, interpretation of results, decision to publish and preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Depression was reported to be a common mental disorders and affected more than 300 million people worldwide, and long-lasting depression with moderate or severe intensity may result in serious health problems [ 1 ]. Depression has become the leading causes of disability worldwide according to the recent World Health Organization (WHO) report. Even worse, depression was closely associated with suicide and became the second leading cause of death, and nearly 800 000 die of depression every year worldwide [ 1 , 2 ]. Although it is known that treatments for depression, more than 3/4 of people in low and middle-income income countries receive no treatment due to a lack of medical resources and the social stigma of mental disorders [ 3 ]. Considering the continuously increased disease burden of depression, a convenient effective therapeutic measures was needed at community level.

Music-based interventions is an important nonpharmacological intervention used in the treatment of psychiatric and behavioral disorders, and the obvious curative effect on depression has been observed. Prior meta-analyses have reported an obvious effect of music therapy on improving depression [ 4 , 5 ]. Today, it is widely accepted that the music-based interventions are divided into two major categories, namely music therapy and music medicine. According to the American Music Therapy Association (AMTA), “music therapy is the clinical and evidence-based use of music interventions to accomplish individualized goals within a therapeutic relationship by a credentialed professional who has completed an approved music therapy program” [ 6 ]. Therefore, music therapy is an established health profession in which music is used within a therapeutic relationship to address physical, emotional, cognitive, and social needs of individuals, and includes the triad of music, clients and qualified music therapists. While, music medicine is defined as mainly listening to prerecorded music provided by medical personnel or rarely listening to live music. In other words, music medicine aims to use music like medicines. It is often managed by a medical professional other than a music therapist, and it doesn’t need a therapeutic relationship with the patients. Therefore, the essential difference between music therapy and music medicine is about whether a therapeutic relationship is developed between a trained music therapist and the client [ 7 – 9 ]. In the context of the clear distinction between these two major categories, it is clear that to evaluate the effects of music therapy and other music-based intervention studies on depression can be misleading. While, the distinction was not always clear in most of prior papers, and no meta-analysis comparing the effects of music therapy and music medicine was conducted. Just a few studies made a comparison of music-based interventions on psychological outcomes between music therapy and music medicine. We aimed to (1) compare the effect between music therapy and music medicine on depression; (2) compare the effect between different specific methods used in music therapy; (3) compare the effect of music-based interventions on depression among different population [ 7 , 8 ].

Materials and methods

Search strategy and selection criteria.

PubMed (MEDLINE), Ovid-Embase, the Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, and Clinical Evidence were searched to identify studies assessing the effectiveness of music therapy on depression from inception to May 2020. The combination of “depress*” and “music*” was used to search potential papers from these databases. Besides searching for electronic databases, we also searched potential papers from the reference lists of included papers, relevant reviews, and previous meta-analyses. The criteria for selecting the papers were as follows:(1) randomised or quasi-randomised controlled trials; (2) music therapy at a hospital or community, whereas the control group not receiving any type of music therapy; (3) depression rating scale was used. The exclusive criteria were as follows: (1) non-human studies; (2) studies with a very small sample size (n<20); (3) studies not providing usable data (including sample size, mean, standard deviation, etc.); (4) reviews, letters, protocols, etc. Two authors independently (YPJ, HZH) searched and screened the relevant papers. EndNote X7 software was utilized to delete the duplicates. The titles and abstracts of all searched papers were checked for eligibility. The relevant papers were selected, and then the full-text papers were subsequently assessed by the same two authors. In the last, a panel meeting was convened for resolving the disagreements about the inclusion of the papers.

Data extraction

We developed a data abstraction form to extract the useful data: (1) the characteristics of papers (authors, publish year, country); (2) the characteristics of participators (sample size, mean age, sex ratio, pre-treatment diagnosis, study period); (3) study design (random allocation, allocation concealment, masking, selection process of participators, loss to follow-up); (4) music therapy process (music therapy method, music therapy period, music therapy frequency, minutes per session, and the treatment measures in the control group); (5) outcome measures (depression score). Two authors independently (TQS, ZH) abstracted the data, and disagreements were resolved by discussing with the third author (YPJ).

Assessment of risk of bias in included studies

Two authors independently (TQS, ZH) assessed the risk of bias of included studies using Cochrane Collaboration’s risk of bias assessment tool, and disagreements were resolved by discussing with the third author (YPJ) [ 10 ].

Music therapy and music medicine

Music Therapy is defined as the clinical and evidence-based use of music interventions to accomplish individualized goals within a therapeutic relationship by a credentialed professional who has completed an approved music therapy program. Music medicine is defined as mainly listening to prerecorded music provided by medical personnel or rarely listening to live music. In other words, music medicine aims to use music like medicines.

Music therapy mainly divided into active music therapy and receptive music therapy. Active music therapy, including improvisational, re-creative, and compositional, is defined as playing musical instruments, singing, improvisation, and lyrics of adaptation. Receptive music therapy, including music-assisted relaxation, music and imagery, guided imagery and music, lyrics analysis, and so on, is defined as music listening, lyrics analysis, and drawing with musing. In other words, in active methods participants are making music, and in receptive music therapy participants are receiving music [ 6 , 7 , 9 , 11 – 13 ].

Evaluation of depression

Depression was evaluated by the common psychological scales, including Beck Depression Inventory (BDI), Children’s Depression Inventory (CDI), Center for Epidemiologic Studies Depression (CES-D), Cornell Scale (CS), Depression Mood Self-Report Inventory for Adolescence (DMSRIA), Geriatric Depression Scale-15 (GDS-15); Geriatric Depression Scale-30 (GDS-30), Hospital Anxiety and Depression Scale (HADS), Hamilton Rating Scale for Depression (HRSD/HAMD), Montgomery-sberg Depression Rating Scale (MADRS), Patient Reported Outcomes Measurement Information System (PROMIS), Self-Rating Depression Scale (SDS), Short Version of Profile of Mood States (SV-POMS).

Statistical analysis

The pooled effect were estimated by using the standardized mean differences (SMDs) and its 95% confidence interval (95% CI) due to the different depression rate scales were used in the included papers. Heterogeneity between studies was assessed by I-square ( I 2 ) and Q-statistic (P<0.10), and a high I 2 (>50%) was recognized as heterogeneity and a random-effect model was used [ 14 – 16 ]. We performed subgroup analyses and meta-regression analyses to study the potential heterogeneity between studies. The subgroup variables included music intervention categories (music therapy and music medicine), music therapy methods (active music therapy, receptive music therapy), specific receptive music therapy methods (music-assisted relaxation, music and imagery, and guided imagery and music (Bonny Method), specific active music therapy methods (recreative music therapy and improvisational music therapy), music therapy mode (group therapy, individual therapy), music therapy period (weeks) (2–4, 5–12, ≥13), music therapy frequency (once weekly, twice weekly, ≥3 times weekly), total music therapy sessions (1–4, 5–8, 9–12, 13–16, >16), time per session (minutes) (15–40, 41–60, >60), inpatient settings (secure [locked] unit at a mental health facility versus outpatient settings), sample size (20–50, ≥50 and <100, ≥100), female predominance(>80%) (no, yes), mean age (years) (<50, 50–65, >65), country having music therapy profession (no, yes), pre-treatment diagnosis (mental health, depression, severe mental disease/psychiatric disorder). We also performed sensitivity analyses to test the robustness of the results by re-estimating the pooled effects using fixed effect model, using trim and fill analysis, excluding the paper without information on music therapy, excluding the papers with more high biases, excluding the papers with small sample size (20< n<30), excluding the papers using an infrequently used scale, excluding the studies focused on the people with a severe mental disease. We investigated the publication biases by a funnel plot as well as Egger’s linear regression test [ 17 ]. The analyses were performed using Stata, version 11.0. All P-values were two-sided. A P-value of less than 0.05 was considered to be statistically significant.

Characteristics of the eligible studies

Fig 1 depicts the study profile, and a total of 55 RCTs were included in our meta-analysis [ 18 – 72 ]. Of the 55 studies, 10 studies from America, 22 studies from Europe, 22 studies from Asia, and 1 study from Australia. The mean age of the participators ranged from 12 to 86; the sample size ranged from 20 to 242. A total of 16 different scales were used to evaluate the depression level of the participators. A total of 25 studies were conducted in impatient setting and 28 studies were in outpatients setting; 32 used a certified music therapist, 15 not used a certified music therapist (for example researcher, nurse), and 10 not reported relevent information. A total of 16 different depression rating scales were used in the included studies, and HADS, GDS, and BDI were the most frequently used scales ( Table 1 ).

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PRISMA diagram showing the different steps of systematic review, starting from literature search to study selection and exclusion. At each step, the reasons for exclusion are indicated. Doi: 10.1371/journal.pone.0052562.g001.

https://doi.org/10.1371/journal.pone.0240862.g001

https://doi.org/10.1371/journal.pone.0240862.t001

Of the 55 studies, only 2 studies had high risks of selection bias, and almost all of the included studies had high risks of performance bias ( Fig 2 ).

https://doi.org/10.1371/journal.pone.0240862.g002

The overall effects of music therapy

Of the included 55 studies, 39 studies evaluated the music therapy, 17 evaluated the music medicine. Using a random-effects model, music therapy was associated with a significant reduction in depressive symptoms with a moderate-sized mean effect (SMD = −0.66; 95% CI = -0.86 to -0.46; P <0.001), with a high heterogeneity across studies ( I 2 = 83%, P <0.001); while, music medicine exhibited a stronger effect in reducing depressive symptom (SMD = −1.33; 95% CI = -1.96 to -0.70; P <0.001) ( Fig 3 ).

https://doi.org/10.1371/journal.pone.0240862.g003

Twenty studies evaluated the active music therapy using a random-effects model, and a moderate-sized mean effect (SMD = −0.57; 95% CI = -0.90 to -0.25; P <0.001) was observed with a high heterogeneity across studies ( I 2 = 86.3%, P <0.001). Fourteen studies evaluated the receptive music therapy using a random-effects model, and a moderate-sized mean effect (SMD = −0.73; 95% CI = -1.01 to -0.44; P <0.001) was observed with a high heterogeneity across studies ( I 2 = 76.3%, P <0.001). Five studies evaluated the combined effect of active and receptive music therapy using a random-effects model, and a moderate-sized mean effect (SMD = −0.88; 95% CI = -1.32 to -0.44; P <0.001) was observed with a high heterogeneity across studies ( I 2 = 70.5%, P <0.001) ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0240862.g004

Among specific music therapy methods, recreative music therapy (SMD = -1.41; 95% CI = -2.63 to -0.20; P <0.001), guided imagery and music (SMD = -1.08; 95% CI = -1.72 to -0.43; P <0.001), music-assisted relaxation (SMD = -0.81; 95% CI = -1.24 to -0.38; P <0.001), music and imagery (SMD = -0.38; 95% CI = -0.81 to 0.06; P = 0.312), improvisational music therapy (SMD = -0.27; 95% CI = -0.49 to -0.05; P = 0.001), and music and discuss (SMD = -0.26; 95% CI = -1.12 to 0.60; P = 0.225) exhibited a different effect respectively ( Fig 5 ).

https://doi.org/10.1371/journal.pone.0240862.g005

Sub-group analyses and meta-regression analyses

We performed sub-group analyses and meta-regression analyses to study the homogeneity. We found that music therapy yielded a superior effect on reducing depression in the studies with a small sample size (20–50), with a mean age of 50–65 years old, with medium intervention frequency (<3 times weekly), with more minutes per session (>60 minutes). We also found that music therapy exhibited a superior effect on reducing depression among people with severe mental disease /psychiatric disorder and depression compared with mental health people. While, whether the country have the music therapy profession, whether the study used group therapy or individual therapy, whether the study was in the outpatients setting or the inpatient setting, and whether the study used a certified music therapist all did not exhibit a remarkable different effect ( Table 2 ). Table 2 also presents the subgroup analysis of music medicine on reducing depression.

https://doi.org/10.1371/journal.pone.0240862.t002

In the subgroup analysis by total session, music therapy and music medicine both exhibited a stronger effects of short (1–4 sessions) and medium length (5–12 sessions) compared with long intervention periods (>13sessions) ( Fig 6 ). Meta-regression demonstrated that total music intervention session was significantly associated with the homogeneity between studies ( P = 0.004) ( Table 3 ).

A, evaluating the effect of music therapy; B, evaluating the effect of music medicine.

https://doi.org/10.1371/journal.pone.0240862.g006

https://doi.org/10.1371/journal.pone.0240862.t003

Sensitivity analyses

We performed sensitivity analyses and found that re-estimating the pooled effects using fixed effect model, using trim and fill analysis, excluding the paper without information regarding music therapy, excluding the papers with more high biases, excluding the papers with small sample size (20< n<30), excluding the studies focused on the people with a severe mental disease, and excluding the papers using an infrequently used scale yielded the similar results, which indicated that the primary results was robust ( Table 4 ).

https://doi.org/10.1371/journal.pone.0240862.t004

Evaluation of publication bias

We assessed publication bias using Egger’s linear regression test and funnel plot, and the results are presented in Fig 7 . For the main result, the observed asymmetry indicated that either the absence of papers with negative results or publication bias.

A, evaluating the publication bias of music therapy; B, evaluating the publication bias of music medicine; BDI = Beck Depression Inventory; CDI = Children’s Depression Inventory; CDSS = depression scale for schizophrenia; CES-D = Center for Epidemiologic Studies Depression; CS = Cornell Scale; DMSRIA = Depression Mood Self-Report Inventory for Adolescence; EPDS = Edinburgh Postnatal Depression Scale; GDS-15 = Geriatric Depression Scale-15; GDS-30 = Geriatric Depression Scale-30; HADS = Hospital Anxiety and Depression Scale; HRSD (HAMD) = Hamilton Rating Scale for Depression; MADRS = Montgomery-sberg Depression Rating Scale; PROMIS = Patient Reported Outcomes Measurement Information System; SDS = Self-Rating Depression Scale; State-Trait Depression Questionnaire = ST/DEP; SV-POMS = short version of Profile of Mood Stat.

https://doi.org/10.1371/journal.pone.0240862.g007

Our present meta-analysis exhibited a different effect of music therapy and music medicine on reducing depression. Different music therapy methods also exhibited a different effect, and the recreative music therapy and guided imagery and music yielded a superior effect on reducing depression compared with other music therapy methods. Furthermore, music therapy and music medicine both exhibited a stronger effects of short and medium length compared with long intervention periods. The strength of this meta-analysis was the stable and high-quality result. Firstly, the sensitivity analyses performed in this meta-analysis yielded similar results, which indicated that the primary results were robust. Secondly, considering the insufficient statistical power of small sample size, we excluded studies with a very small sample size (n<20).

Some prior reviews have evaluated the effects of music therapy for reducing depression. These reviews found a significant effectiveness of music therapy on reducing depression among older adults with depressive symptoms, people with dementia, puerpera, and people with cancers [ 4 , 5 , 73 – 76 ]. However, these reviews did not differentiate music therapy from music medicine. Another paper reviewed the effectiveness of music interventions in treating depression. The authors included 26 studies and found a signifiant reduction in depression in the music intervention group compared with the control group. The authors made a clear distinction on the definition of music therapy and music medicine; however, they did not include all relevant data from the most recent trials and did not conduct a meta-analysis [ 77 ]. A recent meta-analysis compared the effects of music therapy and music medicine for reducing depression in people with cancer with seven RCTs; the authors found a moderately strong, positive impact of music intervention on depression, but found no difference between music therapy and music medicine [ 78 ]. However, our present meta-analysis exhibited a different effect of music therapy and music medicine on reducing depression, and the music medicine yielded a superior effect on reducing depression compared with music therapy. The different effect of music therapy and music medicine might be explained by the different participators, and nine studies used music therapy to reduce the depression among people with severe mental disease /psychiatric disorder, while no study used music medicine. Furthermore, the studies evaluating music therapy used more clinical diagnostic scale for depressive symptoms.

A meta-analysis by Li et al. [ 74 ] suggested that medium-term music therapy (6–12 weeks) was significantly associated with improved depression in people with dementia, but not short-term music therapy (3 or 4 weeks). On the contrary, our present meta-analysis found a stronger effect of short-term (1–4 weeks) and medium-term (5–12 weeks) music therapy on reducing depression compared with long-term (≥13 weeks) music therapy. Consistent with the prior meta-analysis by Li et al., no significant effect on depression was observed for the follow-up of one or three months after music therapy was completed in our present meta-analysis. Only five studies analyzed the therapeutic effect for the follow-up periods after music therapy intervention therapy was completed, and the rather limited sample size may have resulted in this insignificant difference. Therefore, whether the therapeutic effect was maintained in reducing depression when music therapy was discontinued should be explored in further studies. In our present meta-analysis, meta-regression results demonstrated that no variables (including period, frequency, method, populations, and so on) were significantly associated with the effect of music therapy. Because meta-regression does not provide sufficient statistical power to detect small associations, the non-significant results do not completely exclude the potential effects of the analyzed variables. Therefore, meta-regression results should be interpreted with caution.

Our meta-analysis has limitations. First, the included studies rarely used masked methodology due to the nature of music therapy, therefore the performance bias and the detection bias was common in music intervention study. Second, a total of 13 different scales were used to evaluate the depression level of the participators, which may account for the high heterogeneity among the trials. Third, more than half of those included studies had small sample sizes (<50), therefore the result should be explicated with caution.

Our present meta-analysis of 55 RCTs revealed a different effect of music therapy and music medicine, and different music therapy methods also exhibited a different effect. The results of subgroup analyses revealed that the characters of music therapy were associated with the therapeutic effect, for example specific music therapy methods, short and medium-term therapy, and therapy with more time per session may yield stronger therapeutic effect. Therefore, our present meta-analysis could provide suggestion for clinicians and policymakers to design therapeutic schedule of appropriate lengths to reduce depression.

Supporting information

S1 checklist. prisma checklist..

https://doi.org/10.1371/journal.pone.0240862.s001

S1 Dataset.

https://doi.org/10.1371/journal.pone.0240862.s002

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• Introduction
• Conclusions
• Article Information

IV indicates inverse variance; MT, music therapy. Box size corresponds to the weighting of each study in the meta-analysis. Diamonds provided for each subgroup as well as the overall analysis indicate the aggregated mean (middle of the diamond) and 95% CIs (points of the diamonds) of results from appropriate included studies. Total refers to the total number of participants included in analyses at preintervention and postintervention time points.

IV indicates inverse variance; MT, music therapy. Total refers to the total number of participants included in analyses at preintervention and postintervention time points.

IV indicates inverse variance. Total refers to the total number of participants included in analyses at preintervention and postintervention time points.

eTable 1. Articles Excluded After Full-text Review, With Reasons

eTable 2. Reviews Searched for Additional Records in This Meta-analysis

eTable 3. GRADE Quality of Evidence Ratings for Included Studies

eFigure 1. PRISMA Flow Diagram

eFigure 2. Funnel Plot Detailing Distribution of MCS Pre-post Changes

eFigure 3. Funnel Plot Detailing Distribution of PCS Pre-post Changes

eFigure 4. Funnel Plot Detailing Distribution of MCS Changes in Music Plus TAU vs TAU Interventions

eFigure 5. Funnel Plot Detailing Distribution of PCS Changes in Music Plus TAU vs TAU Interventions

eFigure 6. Meta-analysis of Pre-post Changes in MCS Scores, Stratified by Music Plus TAU vs All Other Interventions

eFigure 7. Meta-analysis of Pre-post Changes in PCS Scores, Stratified by Music Plus TAU vs All Other Interventions

eFigure 8. Meta-analysis of MCS Scores in Music vs Meditation Interventions

eFigure 9. Meta-analysis of PCS Scores in Music vs Meditation Interventions

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McCrary JM , Altenmüller E , Kretschmer C , Scholz DS. Association of Music Interventions With Health-Related Quality of Life : A Systematic Review and Meta-analysis . JAMA Netw Open. 2022;5(3):e223236. doi:10.1001/jamanetworkopen.2022.3236

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Association of Music Interventions With Health-Related Quality of Life : A Systematic Review and Meta-analysis

• 1 Institute of Music Physiology and Musicians’ Medicine, Hannover University of Music, Drama and Media, Hannover, Germany
• 2 Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia

Question   Are music-making and listening interventions associated with positive changes in health-related quality of life?

Findings   This systematic review and meta-analysis of 26 studies comprising 779 individuals found that music interventions were associated with statistically and clinically significant changes in mental HRQOL, both preintervention to postintervention as well as when music interventions were added to treatment as usual vs treatment as usual control groups.

Meaning   These results suggest that associations between music interventions and clinically significant changes in HRQOL are demonstrable in comprehensive reviews of previous studies.

Importance   Increasing evidence supports the ability of music to broadly promote well-being and health-related quality of life (HRQOL). However, the magnitude of music’s positive association with HRQOL is still unclear, particularly relative to established interventions, limiting inclusion of music interventions in health policy and care.

Objective   To synthesize results of studies investigating outcomes of music interventions in terms of HRQOL, as assessed by the 36- and 12-Item Health Survey Short Forms (SF-36 and SF-12).

Data Sources   MEDLINE, Embase, Web of Science, PsycINFO, ClinicalTrials.gov, and International Clinical Trials Registry Platform (searched July 30, 2021, with no restrictions).

Study Selection   Inclusion criteria were randomized and single-group studies of music interventions reporting SF-36 data at time points before and after the intervention. Observational studies were excluded. Studies were reviewed independently by 2 authors.

Data Extraction and Synthesis   Data were independently extracted and appraised using GRADE criteria (Grading of Recommendations, Assessment, Development, and Evaluations) by multiple authors. Inverse-variance random-effects meta-analyses quantified changes in SF-36 mental and physical component summary (respectively, MCS and PCS) scores from preintervention to postintervention and vs common control groups.

Main Outcomes and Measures   SF-36 or SF-12 MCS and PCS scores, defined a priori.

Results   Analyses included 779 participants from 26 studies (mean [SD] age, 60 [11] years). Music interventions (music listening, 10 studies; music therapy, 7 studies; singing, 8 studies; gospel music, 1 study) were associated with significant improvements in MCS scores (total mean difference, 2.95 points; 95% CI, 1.39-4.51 points; P  < .001) and PCS scores (total mean difference, 1.09 points; 95% CI, 0.15-2.03 points; P  = .02). In subgroup analysis (8 studies), the addition of music to standard treatment for a range of conditions was associated with significant improvements in MCS scores vs standard treatment alone (mean difference, 3.72 points; 95% CI, 0.40-7.05 points; P  = .03). Effect sizes did not vary between music intervention types or doses; no evidence of small study or publication biases was present in any analysis. Mean difference in MCS scores met SF-36 minimum important difference thresholds (mean difference 3 or greater).

Conclusions and Relevance   In this systematic review and meta-analysis, music interventions were associated with clinically meaningful improvements in HRQOL; however, substantial individual variation in intervention outcomes precluded conclusions regarding optimal music interventions and doses for distinct clinical and public health scenarios.

Health-related quality of life (HRQOL) is a broad concept capturing “an individual’s or group’s perceived physical and mental health over time.” 1 HRQOL is closely related to and frequently used interchangeably with well-being, 1 with the importance of these broad health concepts reflected in their prominence in United Nations Sustainable Development goals: “To ensure healthy lives and promote well-being for all at all ages.” 2

Listening to and making music (eg, by singing or playing instruments) is increasingly advocated, including in a recent World Health Organization report, as a means of improving HRQOL as well as various domains of well-being in clinical and healthy populations. 3 - 7 However, a lack of clarity regarding the magnitude of music effects on HRQOL, particularly compared with other established health interventions, presents clear challenges to the inclusion of music in health policies and care at local, national, and international levels. 8 Additionally, optimal music intervention types and doses for specific scenarios are still unclear, precluding the formulation of evidence-based music prescriptions. 3 , 8

The 36-item Health Survey Short Form (SF-36) HRQOL questionnaire is the most widely used patient-reported outcome instrument in health research, demonstrating strong validity, sensitivity, and reliability across a range of languages, versions (eg, RAND, 9 Medical Outcomes Study 10 ), interventions, and clinical and healthy populations. 9 - 12 Additionally, summary scores from the SF-36 and the reduced 12-item Health Survey Short Form (SF-12) have demonstrated good consistency. 13 - 15 The SF-36 has also been frequently used in studies of music interventions, 3 , 4 providing a means of both quantifying and easily contextualizing the magnitude of music’s association with HRQOL using a broadly valid and applicable instrument. Accordingly, the aim of this study is to quantitatively synthesize and contextualize the associations of music interventions and changes in HRQOL assessed by the SF-36 and SF-12. A secondary study aim is to evaluate these associations relative to specific music intervention types and doses.

The protocol for this systematic review and meta-analysis was prospectively registered with PROSPERO ( CRD42021276204 ) and written following the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA ) reporting guideline. This study was exempted from ethics review by the central ethics committee of Leibniz University Hannover because it was a secondary synthesis of deidentified data.

Four databases—MEDLINE, EMBASE, Web of Science, and PsycINFO—and 3 clinical trials registries—Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and International Clinical Trials Registry Platform (ICTRP)—were searched for peer-reviewed articles, clinical trial registrations, and gray literature reports on July 30, 2021, using the following query: (Music* OR singing OR listening) AND (SF12 OR SF36 OR SF-12 OR SF-36 OR “short form 36” OR “short form 12”) . All related subject headings were included where possible and no limitations on study date or language were imposed. The reference lists of included studies and relevant systematic reviews were also hand searched for additional relevant studies.

Following removal of duplicate records, titles and abstracts of database search results were screened, followed by full-text review of potentially relevant abstracts against inclusion and exclusion criteria. Screening and full-text review were performed independently in duplicate by 2 study authors (J.M.M. and C.K.), with disagreements resolved through discussion.

Inclusion criteria were randomized and nonrandomized studies investigating the association of music-making (eg, instrumental music, singing, active music therapy) and/or music listening (eg, to recorded or live music, receptive music therapy) interventions with HRQOL in adults using the SF-36 or SF-12 (reduced version) questionnaires. No restrictions were made on eligible control groups. Studies that investigated the association of music with HRQOL as either a primary or secondary objective were both eligible for inclusion. Additionally, studies must have reported the SF-36 or SF-12 Mental Component Summary (MCS) score and/or Physical Component Summary (PCS) score, or data enabling the calculation of a MCS and/or PCS score (eg, data from all 8 subscales included in both the SF-36 and SF-12 10 , 13 ), at both preintervention and immediate postintervention time points. Higher MCS and PCS scores indicated better mental and physical HRQOL, respectively. MCS and PCS from the SF-12 and SF-36 have demonstrated good consistency across a range of populations. 15 , 16

MCS and PCS scores are both calculated using norm-based scoring methods including all 8 subscales of the SF-36 and SF-12: physical functioning, role physical, bodily pain, general health, vitality, social functioning, role-emotional, and mental health. In calculations of MCS scores, vitality, social functioning, role-emotional, and mental health subscale scores are given the most weight. Conversely, in calculations of PCS scores, physical functioning, role-physical, bodily pain, and general health subscale scores are given the most weight. 17 Ware, Kosinsky, and Keller 17 described MCS and PCS score calculations in further detail, including precise scoring procedures and algorithms. Exclusion criteria were observational and cross-sectional studies and studies that investigated other music-related activities that do not focus on music-making or listening (eg, songwriting).

The quality of evidence supporting review conclusions was appraised using the GRADE system. GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) provides a framework for evaluating the risk of bias of individual studies, as well as the level of certainty supporting specific review results. 18 GRADE was selected for this review because of its broad applicability to different study types and because it has been “designed for reviews…that examine alternative management strategies.” 18

The risk of bias of individual studies was evaluated using the following standard criteria: allocation concealment, masking (of assessors and data analysts), percentage lost to follow-up, intention-to-treat analysis, selective outcome reporting, use of individual randomization, and control for carryover effects (crossover study design). 19 Based on these criteria, an evidence quality rating of high, moderate, low, or very low was assigned to each study using established procedures. 19 All studies were appraised independently by 2 study authors (J.M.M. and C.K.), with any disagreements resolved through discussion. The overall quality and certainty of evidence supporting the results of each meta-analysis was then appraised by the primary author in consultation with the authorship team using the same rating scale. 19

Demographic, music and control intervention, and SF-36 or SF-12 data before and after the intervention were extracted in duplicate by 2 study authors (J.M.M. and C.K.). Data from all available SF-36 and SF-12 subscales were extracted, as well as MCS and PCS summary scores. To maximize consistency of data across studies, MCS and PCS scores were recalculated where possible from underlying subscale data using the methodology of Ware, Kosinsky, and Keller. 17 Missing MCS and PCS standard deviations were imputed from mental health and physical function subscale scores, respectively, or as medians with minimum and maximum or interquartile range data as per established methods. 20 , 21 Authors of studies meeting inclusion criteria but reporting unclear or incomplete SF-36 or SF-12 data were contacted to retrieve compatible MCS and/or PCS data.

Weighted inverse-variance random-effects meta-analyses were conducted to determine the aggregate pre- to postintervention change in MCS and PCS scores. Additionally, inverse-variance random-effects meta-analyses were performed on postintervention MCS and PCS scores in music vs control groups common to at least 3 studies. The presence of statistical heterogeneity, indicating significant variation in the overall effects of music interventions on MCS and PCS scores, was evaluated using the χ 2 test and I 2 statistic. Potential small study or publication biases were evaluated using the Egger test. 22 Sensitivity analyses were performed where possible according to music intervention types (eg, music therapy, singing, music listening) and quality of study evidence (very low and low vs moderate and high). Additionally, exploratory nonparametric Spearman correlation analyses were performed to evaluate potential links between key characteristics of the music intervention “dose” (ie, intervention duration, music session frequency and length) and MCS and PCS scores. Significance was set at α = .05 for all statistical tests except meta-analysis main effects; α = .033 was used for meta-analysis main effects to control for multiplicity of related MCS and PCS outcomes, as per recommendations for meta-analyses aiming to best balance Type I and II error risk. 23 Analyses were conducted in RevMan version 5.4 (Cochrane Collaboration) and SPSS version 26 (IBM Corp).

Finally, published meta-analyses of MCS and PCS scores from established non–pharmaceutical or medical health interventions were retrieved to serve as a basis for comparison with results of the present study. Additionally, changes in MCS and PCS scores were evaluated against a 3-point minimum clinically important difference threshold established by the SF-36 developers. 24 This threshold was designed to be a general benchmark for meaningful change based on a range of longitudinal and cross-sectional data sets from both clinical and healthy populations; accordingly, this threshold was deemed particularly appropriate for the broad scope and heterogeneous literature included in this review. 24

Data from 26 eligible studies and 779 total participants (mean [SD] age, 60 [11] years) were included in the present study (eFigure 1, eTables 1 and 2 in the Supplement ). Included studies were conducted in Australia, 25 Brazil, 26 - 28 China (Hong Kong SAR), 29 Germany, 30 India, 31 Italy, 32 - 34 The Netherlands, 35 , 36 Spain, 37 Sweden, 38 Thailand, 39 Turkey, 40 the United Kingdom, 41 - 45 and the US. 46 - 50 Included studies comprised 22 investigations of clinical populations and 4 of healthy populations (10 investigations examined music listening, 7 music therapy, 8 singing, and 1 gospel music intervention) and 20 randomized clinical trials (RCTs) and 6 single-group studies (8 RCTs included comparisons with a usual treatment control group, 3 RCTs used meditation control groups, and 9 RCTs used a range of other disparate control groups). MCS and PCS scores were available for 25 studies; only MCS data was available in 1 additional study. 49 Evidence quality was high in 5 studies (19%), moderate in 11 studies (42%), low in 7 studies (27%), and very low in 3 studies (12%) (eTable 3 in the Supplement ).

Music interventions were associated with significant increases in both MCS (total mean difference, 2.95 points; 95% CI, 1.39-4.51 points; P  < .001) and PCS scores (total mean difference, 1.09 points; 95% CI, 0.15-2.03 points; P  =.02) from preintervention values ( Figure 1 and Figure 2 ). Standardized mean differences were 0.25 (95% CI, 0.15-0.36) for MCS scores and 0.15 (95% CI, 0.05-0.26) for PCS scores. MCS scores (including 779 participants) were significantly greater in moderate-quality and high-quality vs very low–quality and low-quality studies and varied significantly across intervention types (χ 2  = 4.56; I 2  = 78.1%; P  = .03) ( Figure 1 ). However, changes in MCS scores did not significantly vary across intervention types when the 1 gospel music intervention study 46 was excluded. PCS scores (including 763 participants) did not significantly vary according to study quality or intervention type.

No key characteristics of the music intervention dose (ie, intervention duration, music session frequency and length), nor any combination of these characteristics, were associated with changes in MCS or PCS scores. No significant statistical heterogeneity or evidence of small study or publication bias (eFigures 2 and 3 in the Supplement ) was present in either analysis. Results of these meta-analyses were also judged to be minimally affected by individual study biases but limited by the imprecision of relatively wide confidence intervals. Accordingly, results were appraised to provide moderate-quality evidence, indicating that “the true effect is probably close to the estimated effect.” 18

Adding music interventions to treatment as usual (TAU) was associated with significant increases in MCS scores vs TAU alone (total mean difference, 3.72 points; 95% CI, 0.40-7.05 points) (standardized mean difference, 0.24; 95% CI, 0.02-0.45) ( P  = .03) ( Figure 3 ). Differences for PCS scores were not significant ( Figure 4 ). Improved MCS in music plus TAU vs TAU groups did not vary significantly with study quality or music intervention type, and no significant statistical heterogeneity or evidence of small study or publication biases was present in either analysis (eFigures 4 and 5 in the Supplement ). Pre-post intervention changes in MCS and PCS scores associated with music plus TAU interventions did not significantly differ from changes in MCS and PCS scores associated with all other included music interventions (eFigures 6 and 7 in the Supplement ). Results of these meta-analyses were judged to be minimally affected by individual study biases but limited by the imprecision of wide confidence intervals across studies. Accordingly, results were appraised to provide moderate-quality evidence.

No significant differences in MCS or PCS scores in music listening vs meditation intervention studies were present across 3 included studies (eFigures 8 and 9 in the Supplement ). Once again, no significant statistical heterogeneity or evidence of small study or publication biases was present in either analysis. However, results were limited by the small number of studies and wide confidence intervals, and judged to provide low-quality evidence (ie, “the true effect might be markedly different from the estimated effect”). 18

Changes in MCS scores, both pre-post intervention and vs TAU, met or exceeded the proposed 3-point minimum important difference threshold for MCS and PCS scores. 17 Pre-post changes in PCS scores (1.1-point improvement) fell below this threshold.

Changes in MCS scores (pre-post and vs TAU) were similar to changes in PCS scores reported for weight loss in studies of adults with obesity (2.8-point improvement; no significant MCS change). 51 However, mean differences in MCS and PCS scores (pre-post and vs TAU) associated with music interventions were substantially smaller than differences in MCS and PCS scores associated with resistance exercise (ie, strength training) in older adults from mixed clinical and healthy populations vs mixed control groups (standardized mean difference: MCS, 0.54; PCS, 0.50) 52 and mixed modes of exercise in participants with knee osteoarthritis vs inactive or psycho-educational control groups (standardized mean difference: MCS, 0.44; PCS, 0.52). 53

This meta-analysis of 26 studies of music interventions provided clear and quantitative moderate-quality evidence that music interventions are associated with clinically significant changes in mental HRQOL. Additionally, a subset of 8 studies demonstrated that adding music interventions to usual treatment was associated with clinically significant changes to mental HRQOL in a range of conditions. Music interventions were associated with substantially smaller changes in physical HRQOL, which are of potentially equivocal practical importance. 17 The substantial individual variation in responses to music interventions across included studies should be emphasized; this analysis must only be used as a general guide to the associations between music interventions and HRQOL changes.

Included studies presented considerable heterogeneity in study populations and geographic locations, music intervention types and doses, and TAU control groups. However, no statistical heterogeneity or evidence of small study or publication bias was present in any analyses. This suggests that results approximate the true, albeit general, association between music interventions and changes in HRQOL. Further research is still needed to provide guidance regarding optimal music interventions and doses in distinct clinical and public health scenarios.

Associations between music interventions and changes in MCS scores (pre-post and music plus TAU vs TAU) are within the range, albeit on the low end, of changes in MCS and PCS scores associated with established non–pharmaceutical/medical, 51 - 54 as well as pharmaceutical/medical, 55 - 57 health interventions, and thus are likely to be clinically significant. 17 Accordingly, this review quantitatively confirmed narrative syntheses from prior systematic reviews asserting that music interventions are linked to meaningful improvements in well-being and HRQOL. 3 - 6 Of particular interest for future study and health policy is the fact that these benefits are associated with participation in a broadly rewarding activity. 58 While uptake and adherence challenges persist with other non–pharmaceutical/medical interventions (eg, weight loss, exercise), 59 , 60 music is “reliably ranked as one of life’s greatest pleasures.” 61 As such, music interventions may present a more attractive and effective nonpharmaceutical alternative to other health interventions. Further study is required to investigate this hypothesis and clarify the specific utility of music vs other established interventions.

Additionally, targeted research is also needed to provide insights into the mechanisms of music interventions’ association with positive changes in HRQOL—ie, the who, what, when, where, and how underpinning their effectiveness. The absence of any significant differences between music intervention types and doses in the present analyses is intriguing but not definitive; these results could also be simply explained by the diversity of included populations and interventions, even within specific intervention types (particularly clearly demonstrated for music listening interventions in the Table ). Broad confidence intervals of both main and intervention type–specific results in this meta-analysis likely also reflect the diversity of interventions. A 2021 analysis 62 indicated that the mechanisms of music’s impact on health are complex and specific to distinct settings, suggesting that targeted study is required to determine optimal music intervention characteristics in each setting. However, other analyses propose that such targeted research may be able to be rapidly generalized to other settings if foundational physiological mechanisms of music intervention effects can be identified and targeted. 63

This study had several limitations. Review was limited by its broad inclusion criteria that limited conclusions regarding the associations of specific music interventions in particular scenarios with specific HRQOL changes, especially given the diversity of included interventions. Despite this limitation, which would preclude the conduct of many meta-analyses, we contend that our meta-analysis was justified by the demonstrated need for even general quantitative syntheses, which allow music effects to be clearly contextualized. 8 Additionally, standardized mean differences describing the magnitude of pre-post intervention effects have been shown to be prone to bias and must be interpreted with caution. 64 However, the similar effect sizes of changes in MCS scores in pre-post and music plus TAU vs TAU analyses provided additional confidence in the average magnitude of pre-post MCS changes. Finally, this review was ultimately limited to studies evaluating the association of music interventions HRQOL using the SF-36 or SF-12 instruments, a possibly skewed subset of music intervention studies. Statistical homogeneity, the absence of apparent publication or small study biases, and the broad psychometric rigor of the SF-36 and SF-12 15 , 16 suggest that results of this review approximated the true associations between music interventions and HRQOL changes. However, the possibility remains that this subset of studies was not representative of music’s general effects on HRQOL or that the SF-36 and SF-12 instruments do not completely capture the impact of music on HRQOL. This uncertainty is reflected in the moderate quality rating of key review results, indicating that “the true effect is probably close to the estimated effect.” 18

This study provided moderate-quality quantitative evidence of associations between music interventions and clinically significant changes in mental HRQOL. Mean differences in physical HRQOL associated with music interventions were potentially equivocal. Changes in mental HRQOL associated with music interventions were within the range, albeit at the low end, of average effects of established non–pharmaceutical and medical interventions (eg, exercise, weight loss). Substantial individual variation in music intervention effects precluded conclusions regarding music use in specific scenarios. Future research is needed to clarify optimal music interventions and doses for use in specific clinical and public health scenarios.

Accepted for Publication: January 31, 2022.

Published: March 22, 2022. doi:10.1001/jamanetworkopen.2022.3236

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2022 McCrary JM et al. JAMA Network Open .

Corresponding Author: J. Matt McCrary, Institute of Music Physiology and Musicians’ Medicine, Hannover University of Music, Drama and Media, Neues Haus 1, 30175 Hannover, Germany ( [email protected] ).

Author Contributions : Dr McCrary had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: McCrary, Altenmuller.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: McCrary, Altenmuller, Scholz.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: McCrary, Scholz.

Obtained funding: McCrary, Altenmuller.

Administrative, technical, or material support: Altenmuller, Kretschmer.

Supervision: McCrary, Altenmuller, Scholz.

Conflict of Interest Disclosures: None reported.

Funding/Support: Dr McCrary holds a postdoctoral fellowship from the Alexander von Humboldt Foundation, which directly supported this study.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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ORIGINAL RESEARCH article

Music therapy for depression enhanced with listening homework and slow paced breathing: a randomised controlled trial.

• 1 Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland
• 2 NORCE Norwegian Research Centre AS, Bergen, Norway
• 3 Department of Clinical and Health Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria

Introduction: There is evidence from earlier trials for the efficacy of music therapy in the treatment of depression among working-age people. Starting therapy sessions with relaxation and revisiting therapeutic themes outside therapy have been deemed promising for outcome enhancement. However, previous music therapy trials have not investigated this issue.

Objective: To investigate the efficacy of two enhancers, resonance frequency breathing (RFB) and listening homework (LH), when combined with an established music therapy model (trial registration number ISRCTN11618310).

Methods: In a 2 × 2 factorial randomised controlled trial, working-age individuals with depression were allocated into groups based on four conditions derived from either the presence or absence of two enhancers (RFB and LH). All received music therapy over 6 weeks. Outcomes were observed at 6 weeks and 6 months. The primary outcome was the Montgomery Åsberg Depression Rating Scale (MADRS) score.

Results: There was a significant overall effect of treatment for the primary outcome favouring the breathing group ( d = 0.50, 95% CI 0.07 to 0.93, p = 0.02). The effect was larger after adjustment for potential confounders ( d = 0.62, 95% CI 0.16 to 1.08, p = 0.009). Treatment effects for secondary outcomes, including anxiety (anxiety scale of Hospital Anxiety and Depression Scale) and quality of life (RAND-36), were also significant, favouring the breathing group. The homework enhancer did not reach significant treatment effects.

Conclusion: We found that the addition of RFB to a music therapy intervention resulted in enhanced therapeutic outcome for clients with depression.

Introduction

Impact of depression.

Depression is one of the most disabling of diseases, causing a serious individual and societal burden ( Sobocki et al., 2006 ). In Europe, major depression and specific phobia are the most common psychiatric disorders ( Alonso et al., 2004 ). Almost 13% of the population report a lifetime history of major depressive disorder, with around 4% having experienced major depression in the past 12 months. Depression is often connected to other disabling disorders, such as generalised anxiety disorder and somatoform disorder, all of which show an excess comorbidity leading to higher psychosocial disability, increased suicidality, and worse clinical outcome and treatment response ( Maier and Falkai, 1999 ). According to Turunen (2020) , the prevalence of mental problems in Finland has been growing continuously in recent years; the number of anxiety diagnoses, for instance, was 25% higher in 2019 compared to the year before. Also the effect of COVID-19 can be clearly seen in the use of mental health services, the number of short-term psychotherapy referrals across countries having increased four times at the beginning of 2020, compared to the same period one year before ( Khan et al., 2020 ). In the light of these trends, offering the best possible evidence-based treatments and improving existing therapeutic approaches has become more important than ever. The aim of this study was to investigate whether an effective form of music therapy could be further enhanced in terms of clinical outcomes.

Treatments for Depression

Pharmacotherapy and psychotherapy—used alone or in combination—are currently the main treatments for depression ( Masennus: Käypä hoito-suositus, 2020 ), and both have been found equally efficacious ( De Maat et al., 2006 ). However, when including risk of relapse, long-term outcomes, and suicidal risks in the evaluation, pharmacotherapy has been associated with higher relapse ( De Maat et al., 2006 ), poorer long-term outcomes ( Hengartner et al., 2018 ), and increased suicidal risks ( Baldessarini et al., 2017 ), making psychotherapy an appealing and valuable option among the treatment modalities. Interestingly, a recent meta-analysis ( Weitz et al., 2018 ) reports that psychotherapy is almost as effective at reducing comorbid anxiety symptoms as it is at reducing depressive symptoms. Furthermore, besides the reduction in depressive symptoms, psychotherapy also has a positive impact on quality of life (QoL), especially its mental health component ( Kolovos et al., 2016 ).

Forms of Psychotherapy

When comparing the most common forms of verbal psychotherapy used in the treatment of depression, Cuijpers et al. (2014) found no significant difference in terms of response and remission rate, which suggests that the various forms of verbal psychotherapy might be largely interchangeable. A common challenge for verbal psychotherapy is the fact that major depression typically leads to psychomotor regression in the area of speech ( Flint et al., 1993 ), noticeable in the form of retardation of speech and prolongation of quiet episodes ( Hoffman et al., 1985 ). Consequently, verbal expression and processing during therapy may be difficult or insufficient for some individuals with depression. Psychotherapy forms that allow non-verbal expression – such as arts therapies – may offer a potential alternative. For instance, there is an increasing number of randomised controlled trials (RCT) and two Cochrane systematic reviews ( Maratos et al., 2008 ; Aalbers et al., 2017 ) on the effect of music therapy for depression. According to Aalbers et al. (2017) , music therapy provides short-term beneficial effects for people with depression. More specifically, music therapy added to treatment as usual (TAU) appears to be more efficacious than TAU alone. Furthermore, music therapy is not associated with more or fewer adverse events than TAU alone. Similarly, a systematic review on the effectiveness of dance and movement therapy (DMT) in the treatment of adults with depression also concludes that DMT is an effective intervention ( Karkou et al., 2019 ).

Improvisational Music Therapy

We previously conducted an RCT on the effectiveness of music therapy for working-age people with depression ( Erkkilä et al., 2011 ). In that trial, only one specific music therapy technique was used, called improvisational psychodynamic music therapy (IPMT) ( Erkkilä et al., 2012 ). This decision was influenced by the first systematic review on music therapy for depression ( Maratos et al., 2008 ), which concluded that one weakness of the existing RCTs was the variety of music therapy methods included in the same study, making it difficult to draw any conclusions on the effect of a single method, such as clinical improvisation. In that RCT, based on 20 bi-weekly music therapy sessions of 60 min each, we found that the clients in the IPMT + TAU group improved significantly more in terms of depression, anxiety, and general functioning, compared to the TAU group. Furthermore, the treatment response of the IPMT + TAU group was almost twice as high as in the TAU group, based on the primary outcome measure (depression). We concluded that IPMT is an effective treatment for depression when added to TAU, with the added benefit of significantly reducing comorbid anxiety and improving general functioning. The core element of IPMT, free improvisation, can be described as a means of “self-projection and free association” and may enable clients thereby “to connect with emotional memories and images” ( Erkkilä et al., 2011 , p. 132). Emphasising the creative process rather than the end product, it has also been described as “playing around with sounds until they form whatever patterns, shapes or textures one wants them to have, or until they mean whatever one wants them to mean” ( Bruscia, 1998 , p. 5). In the present study, we aimed to build on the positive results of our previous RCT, and investigate whether the effectiveness of integrative improvisational music therapy (IIMT; based on IPMT with certain modifications, as described in “Methods”) can be further enhanced through the addition of carefully selected elements. The two elements we chose were a slow-breathing technique called resonance frequency breathing (RFB), and a homework task where clients were encouraged to listen to the improvisations created during therapy.

Enhancement 1: Resonance frequency breathing (RFB)

Resonance frequency breathing is the core element of a method called heart rate variability biofeedback (HRVB). With the help of biofeedback equipment displaying heart and respiration patterns in real-time, clients learn to breathe at their resonance frequency, which corresponds to a specific breathing speed that is unique to each person, and is typically located between 4.5 and 6.5 breaths/min in adults ( Vaschillo et al., 2006 ). When breathing at resonance frequency, heart, respiratory, and blood pressure rhythms become highly synchronised, and heart rate variability (HRV) substantially increases ( Lehrer and Gevirtz, 2014 ). Within a very short time, the autonomic nervous system shifts to parasympathetic dominance (rest-and-digest), resulting in relaxation and lower stress levels. RFB is a simplified form of HRVB, as it does not involve any biofeedback equipment. In RFB, the resonance frequency is determined beforehand through a single breathing assessment. Subsequently, clients are doing paced breathing at their previously determined resonance frequency, using a breath pacer set at the right speed, according to the results of the breathing assessment. In terms of application, HRVB has proven beneficial for a wide range of physical and psychological conditions ( Gevirtz, 2013 ; Moss and Shaffer, 2017 ), as well as for the enhancement of artistic creativity ( Gruzelier et al., 2014 ) and sport performance ( Jiménez Morgan and Molina Mora, 2017 ). More relevant to the topic of the present trial, a recent meta-analysis, based on 24 studies and 484 participants, revealed that HRVB was associated with a large reduction in stress and anxiety ( Goessl et al., 2017 ). HRVB has also been found beneficial for the treatment of depression, both in open-label studies ( Karavidas et al., 2007 ; Siepmann et al., 2008 ) and in controlled studies ( Caldwell and Steffen, 2018 ; Lin et al., 2019 ). In a systematic review and meta-analysis investigating the effect sizes of HRVB for specific health conditions, the authors conclude that HRVB would be a useful addition to clinicians’ existing skill-sets, because of its proven efficacy and the ease with which it can be used alongside other forms of therapy ( Lehrer et al., 2020 ). However, to date, very few attempts have been made to fully integrate HRVB into an existing form of (psycho)therapy, so as to create a synergy effect in support of the latter. In most studies we have come across, HRVB is used as an additional and separate treatment modality, for example alongside cognitive behavioural therapy or acceptance and commitment therapy ( Reiner, 2008 ; Caldwell and Steffen, 2018 ). At the Music Therapy Clinic for Research and Training (University of Jyväskylä, Finland), we have developed and tested our own therapy format, whereby each session of IIMT begins with 10 min of RFB. Our pilot studies suggest that the inclusion of RFB helps clients upregulate and downregulate their emotions during music therapy, depending on their clinical status and current needs ( Brabant and Erkkilä, 2018 ). These preliminary findings require follow-up with a between-group study such as the present one, to determine whether the observed effects on therapy processes also lead to better outcomes. Generally, it should be noted that RFB is an active field of research. The mechanisms behind RFB are incompletely understood, but may include baroreflex gains ( Shaffer and Meehan, 2020 ); vagal nerve stimulation ( Gerritsen and Band, 2018 ); enhancement of functional connectivity in brain areas associated with emotion regulation ( Mather and Thayer, 2018 ); and the complex interplay of several neurophysiological processes ( Noble and Hochman, 2019 ). However, there is consensus that the resonance frequency is stable in adults, around 0.1 Hz or 6 bpm, and that breathing at a frequency near 0.1 Hz promotes relaxation and other physical and mental benefits ( Mather and Thayer, 2018 ; Noble and Hochman, 2019 ; Shaffer and Meehan, 2020 ). Slow-placed breathing may provide a parsimonious explanation of the physical and mental benefits of a number of contemplative activities such as meditation or yoga ( Gerritsen and Band, 2018 ), but it is less clear whether breathing at the individual’s precise resonance frequency is more effective than breathing at 6 bpm ( Shaffer and Meehan, 2020 ). Procedures for frequency assessment have been reviewed recently ( Shaffer and Meehan, 2020 ), based on previous work by Lehrer and colleagues ( Lehrer and Gevirtz, 2014 ; Lehrer et al., 2020 ).

Enhancement 2: Listening homework (LH)

The idea of the LH task arose from our earlier clinical observations, where some clients seemed to benefit from listening back to the recorded music improvisations, both during the sessions and at home. We hypothesise that, because music improvisations evoke emotions and imagery with specific therapeutic meanings, providing clients with the chance to further process these emotions at home may improve the effect of therapy. The therapeutic potential of homework is already known in the context of verbal psychotherapy ( Kazantzis et al., 2000 ; Kazantzis et al., 2010 ; Mausbach et al., 2010 ), where it has been used for the treatment of depression ( Thase and Callan, 2006 ). According to the meta-analysis by Mausbach et al. (2010) , clients’ compliance to homework is a crucial factor, with higher compliance being associated with better therapeutic outcomes. While this body of research supports the plausibility of homework in psychotherapy in general, it is not directly related to LH in this study. First, the previous research involved predominantly cognitive and behavioural therapy (CBT), which is quite distant from IIMT. Second, LH is rather different from the types of homework assignments typically given in these other types of psychotherapies. However, the idea of LH is closely connected to a category of music therapy methods called receptive music therapy. In receptive music therapy, listening to music is used to stimulate the verbal dialogue between client and therapist, and to evoke emotions, memories, images, associations, and so on. The music is often precomposed, but can also be improvised by a therapist in a given situation. In this context, music is often seen as a catalyst and enhancer. In one of the best-known examples of receptive methods – the Bonny Method of Guided Imagery and Music (BMGIM) ( Grocke and Bruscia, 2002 )– pre-designed programmes of Western classical music are used to shape and support the client in experiencing unfolding imagery. The client listens to the programme while in an altered state of consciousness and simultaneously dialogues with the therapist. From a therapeutic perspective, the BMGIM approach and the experiences in altered state as an essential element of it have been found beneficial and effective ( Hammer, 1996 ; McKinney et al., 1997 ; McKinney and Honig, 2017 ). In contrast to BMGIM, however, in our study there was no therapeutic guidance during the home listening, although there were opportunities to discuss the listening experiences when being back in the therapy room.

In this RCT, we examined two hypotheses concerning the efficacy of RFB and LH when combined with IIMT to enhance therapeutic outcome. Hypothesis 1 suggested that RFB would reduce depressive symptoms and that we would observe a significant overall treatment effect over time for RFB, together with significant treatment effects post-intervention and at follow-up. Hypothesis 2 suggested that LH would similarly reduce depressive symptoms and yield significant treatment effects. These hypotheses are rationalised by the aforementioned findings, which indicate positive treatment effects of both HRVB and psychotherapeutic homework assignments in depressed clients. In addition to this, we were interested in exploring potential interaction effects between the RFB and LH interventions, although due to insufficient literature we did not have an a priori hypothesis on the efficacy of this combination for the treatment of depression.

Materials and Methods

We conducted a 2 × 2 factorial randomised controlled trial in which all clients received IIMT ( Erkkilä et al., 2019 ). The trial was registered (ISRCTN11618310) before recruitment. Clients were randomly allocated to one of four groups (IIMT alone, IIMT + LH, IIMT + RFB, IIMT + LH + RFB) following a 2 × 2 factorial design. Conditions were derived from either the presence or absence of LH (LH yes , LH no ) and RFB (RFB yes , RFB no ).

Participants

Eligible participants were adults with a primary diagnosis of major depressive disorder (F32/F33, ICD-10 criteria). The diagnosis was made by a psychiatric nurse with an MA degree in nursing science and assessment qualification. Musical skills were not required from participants. Exclusion criteria were a known history of psychosis, bipolar disorder, personality disorder, other combined psychiatric disorders in which depression cannot be defined as primary disorder, acute and severe substance misuse, and depression severity impeding clinical measurements or verbal conversation.

Randomisation and Blinding

After screening and diagnosis, a computerised block randomisation with randomly varying block sizes of 4 and 8 was conducted by an external person (C.G.) who had no direct contact with the patients. To ensure group allocation concealment, randomisation was conducted at another site (NORCE Norwegian Research Centre). Thus, assessor, therapists, and participants were unaware of allocation until therapy started. As this was a single-blind trial, only the outcome assessor remained blinded to allocation throughout the trial.

Assessment Procedure

Outcome measures were collected by a specialist in psychiatric assessment at three measurement points: (1) baseline, i.e., during recruitment (T0); (2) post-intervention, i.e., 6 weeks after randomisation (T1); (3) and follow-up, i.e., 6 months after randomisation (T2). The time point of primary interest was post-intervention. Demographic information was obtained at the beginning of the intervention.

Interventions

All participants were offered 12 bi-weekly sessions of IIMT over a period of 6 weeks. Each session lasted one hour. The therapeutic approach and its additional components (LH and RFB) are described in the following sections.

Integrative Improvisational Music Therapy (IIMT)

In music therapy, music experiences are used to enrich and enhance a client’s expression and interaction. Essential to music therapy is the client-therapist relationship, in contrast with music and medicine, where music can be used without that relationship. IIMT, developed at the Music Therapy Clinic for Research and Training (University of Jyväskylä, Finland), is based on clinical improvisation, which is one of the major methods of music therapy ( Bruscia, 1987 ). IIMT is based on the interplay and alternation between free music improvisation and verbal discussion ( Erkkilä et al., 2011 , 2012 ). It was originally anchored in the psychodynamic music therapy tradition ( Priestley, 1994 ; Bruscia, 1998 ), and later on, adopted elements from the integrative psychotherapy tradition ( Norcross and Goldfried, 2005 ) as well. The fundamental aim of IIMT is to encourage clients to engage in expressive musical interaction with the therapist. The experiences arising from this interaction are then conceptualised and further processed in the verbal domain ( Erkkilä et al., 2011 ). In IIMT, improvising is primarily understood both as a symbolic representation of abstract mental content, and as an expressive medium able to evoke emotions, images, and memories ( Erkkilä et al., 2012 ), but other human processes–such as cognitive, behavioural, and physiological–may be involved as well.

We standardised the clinical setting so that every therapy process involved identical instruments and a similar arrangement of the two music therapy clinics. Two identical digital pianos placed opposite each other (one for the client, another one for the therapist) were used for melodic and harmonic improvisations. Two identical djembe drums placed next to the pianos were used for non-melodic, rhythmic improvisations. No other instruments or music therapy methods were used. The improvisations were digitally recorded, which made it possible to listen back to them anytime afterwards. Eleven qualified and clinically experienced music therapists (five female, six male) were responsible for conducting the therapy sessions.

Added Component: Resonance Frequency Breathing (RFB)

Each client’s resonance frequency was determined through a breathing assessment conducted before the beginning of therapy. We opted for a single assessment for the sake of simplicity, relying on the finding that adults’ resonance frequency appears to be very stable ( Vaschillo et al., 2006 ). The assessment followed the protocol developed by Lehrer (2007) , and consisted of two parts. First, the client was instructed in how to perform RFB (abdominal breathing, inhalation through the nose and exhalation through the mouth, no holds or pauses, and breathing slower without breathing deeper). Once the technique was sufficiently mastered, the client was asked to breathe at six different rates for 3 min each, while wearing a heart rate monitor. The breathing rates ranged from 7 to 4.5 breaths/min, starting from the fastest until the slowest, in 0.5 steps. Heart rate data for each breathing segment was then analysed using Kubios HRV 3.1 ( Tarvainen et al., 2014 ). The optimal breathing rate was defined as the rate producing the highest peak in the low frequency (LF) component of the power spectrum (0.04–0.15 Hz), as obtained through a fast Fourier transform analysis of the heart beat intervals.

Following the assessment, each client’s optimal breathing speed was communicated to their respective therapist, who used this information for the RFB task. At the beginning of each therapy session, clients assigned to RFB yes performed 10 min of RFB at an inhalation/exhalation ratio of 40/60 in a seated position, while following visual cues provided by a breathing app called Kardia ( Tache, 2017 ), installed on a tablet computer placed in front of the client. Longer exhalations are known to promote parasympathetic activation ( Strauss-Blasche et al., 2000 ) and, in a slow-breathing scenario, a 40/60 ratio has been shown to induce higher levels of relaxation than its opposite ratio ( Diest et al., 2014 ).

Added Component: Listening Homework (LH)

Listening homework was conducted outside the therapy context, in the client’s own time, based on the clinical improvisations created in music therapy sessions using two digital pianos and two djembes. These improvisations were recorded by the therapists using Pro Tools 11.3.1. Each client had personal access through their personal computers to all of their improvisation recordings. Recordings were stored on a University server and automatically synchronized with the clients’ home computers using the continuous file synchronization program Syncthing ( The Syncthing Foundation, 2017 ) in order to be available for listening immediately after the music therapy session. All improvisations created during the music therapy process were available to the client for listening throughout the therapy process. Clients were instructed to use headphones to listen, whenever they felt like doing so and as many times as they wished, to any of the available improvisations and could decide when and how many times they wanted to listen to the improvisations. A dedicated music player, Cantata (2017) , which automatically displayed all available improvisations to clients, was installed in clients’ computers for this purpose. Software installation and guidance to clients on how to use the music player was performed shortly before the first music therapy session. Client’s mean total listening time was 02h:28m:59s (SD = 03:03:34; median = 01:10:32; Q1 = 00:26:20; Q3 = 03:34:29; range 0 to 12:11:21).

At the beginning of the trial, the clinicians were advised to encourage clients to listen to the improvisations after each session. In addition, the therapists were advised to recommend particular improvisations to be listened to at home when they were connected to specific, clinically important themes. Clients’ experiences while listening back to improvisations could be discussed and reflected upon with the therapist in subsequent therapy sessions.

Treatment Fidelity

To ensure treatment fidelity, the selected clinicians were offered intensive training in the music therapy model and in the two added components. All the clinicians were qualified music therapists. Regular clinical supervision was used for monitoring and maintaining the quality of the clinical work.

Primary Outcome

The Montgomery-Åsberg Depression Rating Scale (MADRS) ( Montgomery and Åsberg, 1979 ) was the primary outcome of the study. At the beginning of the study, MADRS was used to determine participant eligibility. The MADRS has high joint-reliability, has been shown to be sensitive to change, and has been demonstrated to have predictive validity for major depressive disorder ( Rush et al., 2008 ).

Secondary Outcomes

The anxiety subscale (HADS-A) of the Hospital Anxiety and Depression Scale (HADS) ( Aro et al., 2004 ) was used to assess anxiety. QoL was assessed using the RAND-36 ( Aalto et al., 1999 ), whose results were aggregated into two summary scales, physical component sum (PCS) and mental component sum (MCS) ( Ware and Kosinski, 1994 ). A detailed explanation of this procedure can be found in the Supplementary Material . The Global Assessment of Functioning (GAF) ( Jones et al., 1995 ) was used for assessing how mental health symptoms affected the clients’ daily life and general functioning. The measures of general functioning and QoL were chosen based on widespread use in psychological intervention studies concerning people with mental health problems.

Sample Size

Following a previous IIMT intervention, we assumed that no more than 10% of clients would leave the study early. We aimed to recruit 68 participants and allocate them into 4 conditions in a factorial design ( n = 34 in each condition; n = 17 in each group) ( Erkkilä et al., 2019 ). For each condition, the selected sample size provided statistical power of 0.80 for detecting a medium standardised effect size of Cohen’s d = 0.60 in a mixed-model analysis (see Twisk, 2013 , p. 281, equation 13.3), with a 2-tailed significance level of p < 0.05 and intra-participant correlation of ρ = 0.6.

Statistical Analysis

An intention-to-treat (ITT) approach was followed, using all available data regardless of whether the treatment was received as intended. Clients who left the study before completion of the intervention were considered dropouts. All tests used two-tailed 5% significance level, with no adjustments for multiplicity. Baseline, post-intervention and follow-up outcome measures served as continuous dependent variables. Repeated-measures linear mixed-effects models (see Supplementary Material ) were used to assess RFB and LH effects for each continuous outcome. An advantage of the utilised repeated measures design is that clients with missing data can be retained in the model, and thus all clients were used in the analysis. RFB and LH were entered as predictors and a random intercept term grouped by client was added to adjust for the dependency of repeated observations within each client. To adjust for baseline differences between conditions, the treatment terms were removed from the model ( Twisk et al., 2018 ). Hence, the effects of RFB and LH were calculated from the interaction between each factor and time. As an exploratory investigation to examine potential interaction effects between RFB and LH interventions, the repeated-measures linear mixed-effects models were subsequently expanded by adding an RFB x LH interaction.

Besides treatment effect post-intervention and follow-up, we obtained an overall treatment effect over time B as an estimate of the raw mean difference between presence and absence of each factor; B was calculated as the sum of the regression coefficients between each condition and time points ( Erkkilä et al., 2019 ). To estimate effect sizes for a given outcome, its overall treatment effect over time was divided by the standard deviation of the measure across all clients at baseline.

For each client, a dichotomous treatment response variable was calculated, defined as a reduction in MADRS of at least 50% between the pre- and post-intervention measurements. For dichotomous variables (leaving the study early, treatment response), missing data were imputed and a negative outcome was assumed for those clients (left the study early, no-response) for a conservative estimate. Fisher’s exact test and odds ratio were calculated separately for RFB and LH. To determine clinical significance, risk difference and number needed to treat (NNT) were calculated for effects that were statistically significant.

Besides the crude efficacy analysis, an adjusted efficacy analysis and two sensitivity analyses were carried out. The repeated-measures linear mixed-effects model of each continuous outcome was adjusted for prognostic covariates by adding them as random effects (random slopes) in the model: age group (i.e., grouped every 10 years), gender, medication (use of antidepressants, anxiolytic or hypnotic medication), and therapist. Two sensitivity analyses were conducted for the primary outcome: a single imputation method (Last Observation Carried Forward) that assumes no change for missing data, and a per-protocol approach (treatment as received). All statistical analyses were performed in Matlab 2019b (MathWorks, Natick, Massachusetts).

Data Sharing

The study’s data-set, except for the data that could compromise the privacy of research participants, is available from the corresponding author upon request.

The study was conducted at the Music Therapy Clinic for Research and Training (University of Jyväskylä, Finland). Figure 1 shows the patient flow during the trial.

Figure 1. Flow of participants through the trial.

Recruitment started on February 1, 2018 and ended on October 31, 2018. Participants were recruited in central Finland through newspaper announcements. Of 102 people who were initially invited for screening, 14 declined, 11 were no-shows and 7 met an exclusion criterion. This left 70 eligible participants (74% female), their age ranging from 19 to 57 years ( M = 39). Baseline characteristics in each condition are shown in Table 1 .

Table 1. Demographic and clinical characteristics of 70 clients at baseline.

According to the results of the treatment effect analysis, there was a significant main effect of time both post-intervention and at follow-up in the expected direction (i.e., improvement of clients’ condition) on all outcome measures (see Table 2 ).

Table 2. Effects of music therapy with or without resonance frequency breathing or listening homework.

Figures 2 , 3 show mean outcome scores across time points, separately for presence and absence of RFB and LH. An overall improvement over time for all secondary measures can be observed, regardless of condition.

Figure 2. Mean scores of continuous outcome for presence and absence of RFB across timepoints. Error bars denote confidence intervals at 95%. T0: baseline; T1: post-intervention (6 weeks after the beginning of the intervention); T2: follow-up (6 months after the beginning of the intervention).

Figure 3. Mean outcome measure scores for presence and absence of LH across timepoints. Error bars denote confidence intervals at 95%. T0: baseline; T1: post-intervention (6 weeks after the beginning of the intervention); T2: follow-up (6 months after the beginning of the intervention).

Table 2 shows the results of crude and adjusted treatment efficacy analyses post-intervention and at follow-up. The crude treatment efficacy analyses revealed significant differences between RFB yes and RFB no for all outcome measures, in all cases favouring RFB yes . The differences between most outcome measures both post-intervention and at follow-up reached statistical significance. Regarding LH, although the results for most outcome measures favoured LH yes (with the exception of HADS), none of them reached significance. Adjusted treatment efficacy analyses yielded similar results to those obtained in the crude analyses, except that the adjusted analyses for RFB reached significance at both time points for all outcome measures. Potential interactions between RFB and LH were examined by subsequently adding an RFB x LH interaction. This factor interaction, however, did not yield significance at any time point for any outcome measure, neither in the crude nor in the adjusted analysis.

Crude and adjusted overall treatment effect over time and resulting effect sizes are presented in Table 3 . According to the crude treatment efficacy analysis, the overall effect of treatment for RFB was significant for all measures except GAF, with RFB yes clients invariably improving more than RFB no clients. The adjusted treatment efficacy analysis yielded similar results, except for two differences. First, while the overall effect of treatment for GAF did not reach significance for RFB in the crude analysis, all outcome measures yielded significant differences for RFB in the adjusted analysis. Second, differences between RFB yes and RFB no increased after covariate adjustment of the treatment efficacy analysis, especially for MADRS.

Table 3. Effect sizes of music therapy with or without resonance frequency breathing for continuous outcomes.

Montgomery-Åsberg Depression Rating Scale scores decreased in all conditions post-intervention, as shown in Figures 2 , 3 . An overall improvement in MADRS from moderate (20-34 points) to mild depression (7-19 points) can be observed for all conditions. Overall, the post-intervention remission rate (defined as MADRS ≤ 9) was 31%, and the post-intervention response rate (defined as a MADRS reduction of 50% or more) was 39%.

Regarding treatment effect post-intervention and follow-up for the RFB factor (see Table 2 ), there was no significant difference between conditions in MADRS ( p = 0.103) post-intervention (6 weeks). However, at follow-up (6 months), the decrease in MADRS score was significantly larger in the RFB yes condition than in the RFB no condition ( p = 0.04). No significant differences were found between the LH factor levels, neither at post-intervention ( p = 0.485) nor follow-up ( p = 0.297).

Overall treatment effect analyses [3] (see Table 3 ) showed a significantly higher decrease in MADRS for RFB yes than for RFB no (Crude B [SE] = −3.55 [1.53], p = 0.02 ∗ ). These differences increased after adjustment for potential confounders (Adjusted B [SE] = −4.35 [1.64], p = 0.009 ∗∗ ). No significant differences were found between LH factor levels (Crude B [SE] = −1.70 [1.53], p = 0.27; adjusted B [SE] = −1.42 [1.76], p = 0.42). Medium effect sizes for RFB were observed in both crude and adjusted analysis, although they were higher in the adjusted analysis ( d [95% CI] = 0.62 [0.16−1.08]) than in the crude analysis ( d [95% CI] = 0.50 [0.07−0.93]). For LH, small effect sizes (Crude d [95% CI] = 0.24 [−0.19−0.67]; Adjusted d [95% CI] = 0.20 [−0.29−0.70]) were observed.

Results for dichotomous variables are presented in Table 4 . There were fewer dropouts in RFB yes compared to RFB no but the odds ratio was not significant. MADRS response rates were significantly greater in RFB yes ( p < 0.05) post-intervention (6 weeks), but were not significant at follow-up (6 months). A risk difference of 0.26 and NNT of 3.9 were observed, favouring RFB yes condition. There were no significant differences between the LH factor levels in any of the dichotomous variables.

Table 4. Attrition and response rates in 70 participants randomised to music therapy with or without resonance frequency breathing or listening homework.

The crude treatment efficacy analyses resulted in a significant improvement in secondary measures for RFB yes either at follow-up, post-intervention, or both time points (see Table 2 ). HADS scores decreased in all conditions during the intervention. In regards to RFB, there was a significant difference between conditions in HADS ( p = 0.027) post-intervention. At follow-up, differences did not reach significance ( p = 0.054). No significant differences were found between the LH factor levels neither at post-intervention nor follow-up; similar results regarding LH were observed for the other three secondary measures (RAND-36 MCS, RAND-36 PSY and GAF). Adjusted treatment effect analyses yielded comparable results, albeit of higher significance; this was also observed for the rest of the secondary outcomes. Also, in the adjusted analysis there was a significant difference in HADS ( p = 0.017) between RFB no and RFB yes at follow-up.

For all conditions, both RAND-36 MCS and RAND-36 PCS decreased during intervention. For RAND-36 MCS, RFB results showed a significant difference between conditions, both post-intervention ( p = 0.027) and at follow-up ( p = 0.012), in favour of RFB yes . Significant differences were also observed between RFB yes and RFB no for RAND-36 PCS, both post-intervention ( p = 0.012) and at follow-up ( p = 0.01).

All conditions exhibited a decrease in GAF scores. There was no significant difference between conditions in GAF for RFB ( p = 0.257) post-intervention (6 weeks). However, GAF scores at follow-up (6 months) were significantly higher in RFB yes than in RFB no ( p = 0.042).

Regarding the overall crude treatment effect of secondary measures (see Table 3 ), we observed significant differences between RFB conditions for HADS (B [SE]: −1.68 [0.67], p = 0.01 ∗ ), RAND-36 MCS (B [SE]: 1.63 [0.56], p = 0.004 ∗∗ ) and RAND-36 PCS (B [SE]: 1.41 [0.46], p = 0.003 ∗∗ ). No significant differences in GAF were observed for RFB. With respect to LH, overall treatment effect analyses did not yield significant differences for any of the secondary measures. The adjusted overall treatment effect analysis yielded similar findings, although the differences between RFB yes and RFB no were larger, and GAF results reached significance. Crude effect sizes for RFB were medium or above medium for RAND-36 MCS and RAND-36 PCS, and close to medium for HADS and GAF. Adjusted effect sizes for RFB were close to large for RAND-36 MCS and above medium for HADS, RAND-36 PCS, and GAF. Regarding the LH factor, crude and adjusted effect sizes were trivial (d ≤ 0.2) for all outcome measures except GAF, which yielded higher effect sizes (Crude d [95% CI] = 0.41 [−0.07−0.89], Adjusted d [95% CI] = 0.37 [−0.17−0.92]).

Sensitivity Analyses

Two sensitivity analyses were conducted. The first assumed no change in MADRS scores for missing observations, thus providing a conservative estimate for dropouts. Overall treatment effect for RFB was still significant in both crude ( p = 0.003 ∗∗ ) and adjusted analysis ( p = 0.002 ∗∗ ). Furthermore, a per-protocol analysis reclassified three clients from LH yes to LH no , as they did not engage in any form of listening homework. There were still no significant differences between the LH factor levels in any of the outcome measures. Reclassification of clients for the RFB factor was not needed, since they all followed protocol.

Adverse Events and Reasons for Drop-Out

Adverse events were rare, transient, and mostly unrelated to the trial interventions. Two participants (one IIMT + RFB, one IIMT + LH) experienced a worsening of problems (sleep problems) following a change in their medication. One (IIMT) had to stop therapy due to a pre-existing comorbid condition which necessitated surgery and subsequent recovery time. One (IIMT + LH) stopped therapy because a therapeutic alliance (agreement on goals and methods of therapy) could not be established. Finally, two participants (one IIMT, one IIMT + LH) stopped therapy due to scheduling issues.

In this study, we investigated whether a music therapy model called IIMT could be further enhanced by introducing additional components known to favour emotional processing and/or stress regulation (listening homework – LH, and resonance frequency breathing – RFB). In line with our previous RCT ( Erkkilä et al., 2011 ), we found that 12 bi-weekly sessions of music therapy were able to significantly improve MADRS scores in all four conditions. Furthermore, our results indicate that IIMT can indeed be further enhanced, at least with RFB. More specifically, the overall effect of treatment for RFB was statistically significant for all measures except GAF, with RFB clients consistently improving more than non-RFB clients (see Table 3 ). We also observed significant differences in all outcome measures—either post-intervention, at follow-up, or both—favouring clients allocated to RFB (see Table 2 ). In contrast, the LH factor did not yield significant differences in any of our analyses. However, for all outcome measures besides HADS, the observed changes did favour LH yes . In sum, these results strongly support the hypothesis of RFB as an enhancer of therapeutic outcome and speak for its inclusion in music therapy, and possibly in other forms of psychotherapy.

Interestingly, for RFB yes , the treatment effect at T2 was larger than at T1 for all outcome measures except HADS, and the mean improvement in RFB yes was monotonic (i.e., continued to increase between post-intervention and follow-up). Although we did not monitor whether clients kept using RFB on their own after the end of therapy, it is possible that an independent practice of RFB might have contributed to maintaining and reinforcing these positive outcomes.

In terms of clinical significance, the addition of RFB resulted in a near doubling of the MADRS post-intervention response rate, which went from 26% (RFB no ) to 51% (RFB yes ). To put these results into perspective, in our previous depression study (consisting of 20 bi-weekly sessions of music therapy without enhancers), the post-intervention response rate was 45% ( Erkkilä et al., 2011 ). It is not surprising that 12 sessions of music therapy without RFB would result in a lower response rate than 20 sessions. However, the truly interesting finding is that, in terms of response rate, 12 sessions of music therapy with RFB were equivalent to 20 sessions without enhancers. Although this is a post hoc comparison of two different trials, it suggests that integrating RBF into music therapy might allow similar results to be achieved with fewer sessions.

These results point to the existence of qualities specific to RFB and music therapy which, when combined, can create a synergy effect. In our experience ( Brabant and Erkkilä, 2018 ), clients who are starting their therapy sessions with RFB tend to have deeper and more productive sessions, which we attribute to RFB’s ability to rebalance the autonomic nervous system, reduce stress, and increase emotional resilience ( Goessl et al., 2017 ). As to improvisational music therapy, three of its unique characteristics are to offer a non-verbal way of expressing emotions, to provide an absorbing experience anchored in the present, and to allow the emergence of unconscious material ( MacDonald and Wilson, 2014 ). Thus, it stands to reason that combining the two methods would greatly facilitate the emergence of themes and emotions that usually remain unexpressed, while making it easier for the client to face these emotions and process them.

On a more general level, these findings highlight the benefits that can be derived from integrating RFB into an existing therapy method, instead of simply using it as an adjunct or complementary exercise, as is still largely the case when RFB or HRVB are being used. While searching the literature, we only found a few instances where such integration took place (e.g., Polak et al., 2015 ) or was being advocated (e.g., Gevirtz, 2020 ). Studies employing HRVB as a stand-alone intervention could serve as a baseline to determine the magnitude of possible synergy effects obtained in studies such as ours, by comparing effect sizes.

In contrast to RFB, our second added component (LH) did not yield any significant effect, in any of the analyses or comparisons that we performed. However, the changes observed at T1 and T2 were, nonetheless, always in favour of LH yes , except for HADS. In other words, the clients in the LH yes condition benefited more from therapy than the clients in the LH no condition. A more detailed analysis which is beyond the present paper will address the question whether listening duration correlated with clinical change. For such an analysis it will be important to separate extended, likely intentional listening from very short listening such as in searching for a piece.

Lastly, it should be noted that our results are in line with the existing evidence presented in the Introduction, regarding the positive effect of psychotherapy on comorbid anxiety ( Weitz et al., 2018 ) and QoL ( Kolovos et al., 2016 ). Interestingly, in this case, although the addition of RFB had a positive impact on both the physical and mental health component of QoL, the effect was more pronounced for physical health. We speculate that this was due to the nature of RFB and the regular practice thereof, which might have led to a sustained increase in autonomic flexibility and HRV, thus allowing clients to better regulate their stress levels in daily life and reduce unpleasant physical sensations.

Limitations

The main limitations of this trial include limited sample size and lack of a no-treatment or placebo control group. Although the sample was large enough to detect a significant effect of breathing added to IIMT, it was not large enough to exclude a clinically meaningful effect of listening homework. Further research with a larger sample would be required to confirm or disconfirm any effects of this component. The sample was also restricted to a single site, so that conclusions generalising to other settings or world regions cannot be drawn with confidence. Second, the study did not use a no-treatment or placebo control group. However, robust effects of IIMT compared to standard care were already demonstrated in the previous study on which the present study was built ( Erkkilä et al., 2011 ).

An issue surrounding LH is the absence of prior studies making use of this specific activity, which might have led to an incorrect estimation of the expected effect size. Although the use of homework has a long history in CBT, the kind of task given in CBT is arguably not directly comparable to what was required from the clients in the present trial. Thus, it is possible that our sample size was too small to detect a significant effect for the LH factor.

Another issue with LH might have been its possible inadequacy for the client population under investigation. Indeed, in contrast to RFB, LH was unsupervised, meaning that clients were free to perform the task or not, which led to lower task adherence compared to RFB. This raises the question of whether clients presenting with symptoms of depression should be given voluntary and unsupervised tasks in between therapy sessions, since depression typically includes a lack of initiative.

Future studies would benefit from having a larger sample size for studying LH, and being multi-centre. Furthermore, the results presented here are purely outcome-oriented, meaning it is not possible at this point to explain the results by establishing a relationship between what happened during therapy and the observed affective or behavioural changes.

Lastly, one question that remains unanswered is the extent to which the enhancement effect achieved with RFB in music therapy could be generalised to the larger field of psychotherapy. Based on our results, we presume that other forms of therapy would similarly benefit from the inclusion of RFB, especially if their approach and principles are similar to the ones used in music therapy (e.g., being emotion-focused, experiential, and integrative). Should this be the case, it would open the door to shorter and more cost-effective forms of therapy.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human subjects/patients were approved by the Ethical board of Central Finland health care district, 07/09/2017, ref.: 17 U/2017. Written informed consent was obtained from every participant.

Author Contributions

JE did the project leadership, contribution to the study design, development and implementation of the clinical music therapy model, writing parts of abstract, introduction, methods and discussion, and finalizing the manuscript. OB did the contribution to the study design, development and implementation of the RFB component, and writing parts of the methods and discussion sections. MH did the development and implementation of the LH component, statistical analysis, and writing parts of the methods, results, and discussion sections. AM did the statistical analysis, writing parts of the methods and results sections. EA-R developed and implemented the clinical music therapy model, wrote parts of the intervention, and commented the manuscript. NS did the development of LH component and implementation of the RFB component, helping to revise the methods and discussion section. SS did the contribution to the study design, helping to draft the results section and revise the manuscript. CG did the contribution to the study design, randomisation procedure, supervision of statistical analyses and revision of the manuscript text. All authors contributed to the article and approved the submitted version.

This work was supported by funding from the Academy of Finland (project numbers 298678, 314651, and 316912).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The study team acknowledges the support from the Academy of Finland and University of Jyväskylä. The authors would like to thank Inga Pöntiö for the psychiatric assessments, Markku Pöyhönen for providing support in administrative, practical, and logistical matters, Mikko Leimu for setting up the music recording platform, Jos Twisk for statistical advice and Monika Geretsegger for her support with the study.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2021.613821/full#supplementary-material

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Keywords : depression, anxiety, music therapy, randomised controlled trial, resonance frequency breathing, homework

Citation: Erkkilä J, Brabant O, Hartmann M, Mavrolampados A, Ala-Ruona E, Snape N, Saarikallio S and Gold C (2021) Music Therapy for Depression Enhanced With Listening Homework and Slow Paced Breathing: A Randomised Controlled Trial. Front. Psychol. 12:613821. doi: 10.3389/fpsyg.2021.613821

Received: 03 October 2020; Accepted: 22 January 2021; Published: 16 February 2021.

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Copyright © 2021 Erkkilä, Brabant, Hartmann, Mavrolampados, Ala-Ruona, Snape, Saarikallio and Gold. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Christian Gold, [email protected]

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• Open access
• Published: 27 March 2023

The effect of music therapy on cognitive functions in patients with Alzheimer’s disease: a systematic review of randomized controlled trials

• Malak Bleibel 1 ,
• Ali El Cheikh 2 ,
• Najwane Said Sadier 1 , 3 &
• Linda Abou-Abbas   ORCID: orcid.org/0000-0001-9185-3831 1 , 4  

Alzheimer's Research & Therapy volume  15 , Article number:  65 ( 2023 ) Cite this article

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The use of music interventions as a non-pharmacological therapy to improve cognitive and behavioral symptoms in Alzheimer’s disease (AD) patients has gained popularity in recent years, but the evidence for their effectiveness remains inconsistent.

To summarize the evidence of the effect of music therapy (alone or in combination with pharmacological therapies) on cognitive functions in AD patients compared to those without the intervention.

A systematic literature search was performed in PubMed, Cochrane library, and HINARI for papers published from 1 January 2012 to 25 June 2022. All randomized controlled trials that compared music therapy with standard care or other non-musical intervention and evaluation of cognitive functions are included. Cognitive outcomes included: global cognition, memory, language, speed of information processing, verbal fluency, and attention. Quality assessment and narrative synthesis of the studies were performed.

A total of 8 studies out of 144 met the inclusion criteria (689 participants, mean age range 60.47–87.1). Of the total studies, 4 were conducted in Europe (2 in France, 2 in Spain), 3 in Asia (2 in China, 1 in Japan), and 1 in the USA. Quality assessment of the retrieved studies revealed that 6 out of 8 studies were of high quality. The results showed that compared to different control groups, there is an improvement in cognitive functions after music therapy application. A greater effect was shown when patients are involved in the music making when using active music intervention (AMI).

The results of this review highlight the potential benefits of music therapy as a complementary treatment option for individuals with AD and the importance of continued investigation in this field. More research is needed to fully understand the effects of music therapy, to determine the optimal intervention strategy, and to assess the long-term effects of music therapy on cognitive functions.

Introduction

Alzheimer’s disease (AD) is a progressive, incurable neurological illness that is the most common cause of dementia, affecting an estimated 5% of men and 6% of women over the age of 60 worldwide [ 1 ]. The prevalence of AD increases exponentially with age, with 1% of those aged 60 to 64 years old and 24% to 33% of those aged 85 years or older affected [ 2 ]. As the global population ages, it is anticipated that the number of individuals with Alzheimer’s disease will increase.

Neuropsychiatric symptoms, such as apathy, depression, and agitation, are commonly observed in individuals with AD, in addition to the more well-known cognitive symptoms such as memory loss, visuospatial problems, and difficulties with executive functions [ 3 , 4 ]. These symptoms can cause a significant burden to patients, caregivers, and society as a whole [ 5 ]. While pharmacological therapies have been used to manage these symptoms, they have not always been effective in achieving long-term clinical efficacy [ 6 ]. As a result, non-pharmacological interventions have gained increasing attention as a complementary treatment option for managing neuropsychiatric symptoms in AD. Such therapies include cognitive training and music therapy which have been used for decades to improve symptoms of dementia [ 7 ].

Music Therapy is the use of music to address the physical, emotional, cognitive, and social needs of individuals [ 8 ]. The American Music Therapy Association describes music therapy as the use of music interventions in a clinical and evidence-based manner to achieve specific goals, which are tailored to the individual, by a professional who is credentialed and has completed an approved music therapy program [ 8 ]. Music therapy incorporates a crucial aspect of the interaction between the client and therapist through an evidence-based model [ 9 ]. It can include both active techniques, such as improvisation, singing, clapping, or dancing, and receptive techniques, where the client listens to music with the intention of identifying its emotional content [ 9 ]. In music listening approaches, the therapist creates a personalized playlist for the client, which can either be an individualized program or chosen by the therapist [ 9 , 10 ]. Generalized music interventions use music without a therapist present, with the goal of enhancing the patient’s well-being, and can include both active and music listening protocols. Music listening is used to stimulate memories, verbalization, or encourage relaxation [ 9 ].

For many years, music therapy has been used to help manage symptoms of dementia [ 9 , 11 ]. Music therapy can improve mood, cognitive functions, memory, and provide a sense of connection and socialization for patients who may be isolated [ 12 , 13 ]. Studies have found that musical training may help mitigate the effects of age-related cognitive impairments, and the capacity of persons to remember music makes it a good stimulus that engages AD patients [ 7 , 14 , 15 ]. After listening to music, AD patients showed improvement in categorical word fluency [ 16 ], autobiographical memory [ 17 , 18 ], and the memory of the lyrics [ 15 ]. Additionally, it can provide an opportunity for caregivers to participate in therapy sessions, which can improve the overall caregiving experience by giving them the opportunity for self-expression allowing them to depict their thoughts and emotions [ 19 ].

The specific mechanisms by which music therapy is beneficial are not fully understood. In 2003, research indicates that music may activate neural networks that remain intact in individuals with AD [ 20 ]. A recent study by Jacobsen et al. [ 21 ] used 7 T functional magnetic resonance imaging to examine the brain’s response to music and identify regions involved in encoding long-term musical memory. When these regions were evaluated for Alzheimer’s biomarkers, such as amyloid accumulation, hypometabolism, and cortical atrophy, the results showed that, although amyloid disposition was not significantly lower in the AD group compared to the control group, there was a substantial reduction in cortical atrophy and glucose metabolism disruption in AD patients [ 21 ]. These findings suggest that musical memory regions are largely spared and well-preserved in AD, which could help explain why music therapy is so effective in retrieving verbal and musical memories in individuals with the disease [ 21 ].

One experimental paradigm used to study the effects of music therapy in AD is the use of live music performances, in which a music therapist plays live music for individuals with the disease in a group setting [ 22 ]. Another paradigm is the use of individualized music, in which a music therapist creates a playlist of personalized music for an individual with the disease to listen to at home [ 23 ]. Both paradigms have been shown to be effective in improving mood and reducing agitation in individuals with AD [ 22 , 23 ].

The advantages of music therapy for AD patients include its non-invasive nature and lack of side effects, its ability to address multiple symptoms at once, and its cost-effectiveness and ease of implementation [ 9 , 18 , 24 , 25 ]. However, there are also some limitations to its application. Music therapy may not be suitable for patients with severe dementia [ 26 ] as their cognitive and physical abilities may be too impaired to fully participate in therapy sessions. Additionally, it requires trained therapists [ 8 , 9 ], who may not be easily accessible in some areas. In this review, we aimed to summarize the evidence of the effect of music therapy (alone or in combination with pharmacological therapies) on cognitive functions in AD patients compared to those without the intervention.

This systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2009) guidelines [ 27 ]. The protocol of this study was registered in PROSPERO. A statement of ethics was not required.

We used the PICO framework (population, intervention, comparator, and outcome) as follows:

P: Alzheimer patients

I: Music therapy (alone or in combination with pharmacological therapies)

C: Alzheimer patients with and without the intervention

O: Cognitive functions

Search strategy and databases

A systematic literature search of PubMed, Cochrane, and HINARI was performed for studies published in peer-reviewed journals from 1 January 2012 up to 25 June 2022. The databases were searched using the keywords of “Alzheimer’s Disease,” “AD,” “music therapy,” “music intervention,” “cognitive functions,” and “cognition.” Keywords were combined using the Boolean operators “OR” and “AND.”

Study selection and eligibility criteria

All randomized controlled trials (RCTs) published between 2012 and 2022 in the English language and providing quantitative measures of the association between AD and music therapy and its effect on cognitive functions were included in our review. Studies that assess the effect of music therapy on patients with a probable diagnosis of AD or studies where the music therapy was combined with another non-pharmacological therapy are excluded.

Data extraction

Search and identification of eligibility according to inclusion criteria and extraction of data were performed by the two reviewers MB and AC. For each paper, detailed information was collected on: study information (author’s name, publication year, and location), sample characteristics (sample size, age, and gender), study design, intervention details (description, duration) the control group, and the cognitive outcome measures.

Methodological quality assessment

A methodological quality assessment of all included studies was performed by two independent reviewers (MB and AC) using the Jadad scale for RCTs [ 28 ]. Although not used as a criterion for study inclusion or exclusion. Jadad scale is developed to assess randomized controlled trials on the bases of 3 essential items: (1) randomization, 1 point if randomization is mentioned 1 additional point if the method of randomization is appropriate and deduct 1 point if the method of randomization is inappropriate,(2) blinding 1 point if blinding is mentioned, 1 additional point if the method of blinding is appropriate, deduct 1 point if the method of blinding is inappropriate; (3) an account of all patients, the fate of all patients in the trial is known. If there are no data, the reason is stated. It is commonly considered that a study is of “high quality” if it scores 3 points or more.

Study selection

The flowchart of the study selection process is presented in Fig.  1 . The literature search identified a total of 144 records. After the exclusion of duplicate records and non-relevant abstracts, 57 studies were retained. After reviewing the full text, 49 studies were excluded according to our inclusion and exclusion criteria. In the end, a total of 8 full-text studies were included in the qualitative synthesis.

PRISMA flow diagram of the selection procedure

Study characteristics

Characteristics of included studies are presented in Table 1 . The final sample was composed of 8 RCTs, 4 studies were conducted in Europe (2 in France, 2 in Spain), 3 studies in Asia (2 in China, 1 in Japan), and one in the USA. All these studies were published in the English language in peer-reviewed journals. Included trials showed a total of 689 participants (300 females, 43.54%). Sample sizes ranged from 39 [ 29 ] to 298 [ 30 ]. Mean ages ranged from 60.47 [ 31 ] to 87.1 [ 26 ]. Participants’ stages of AD dementia varied from mild to severe. Mean Mini-Mental State Examination (MMSE) [ 32 ] at baseline is assessed in 7 trials out of 8 and varied from 4.65 [ 29 ] to 25.07 [ 33 ].

Intervention characteristics

Music therapy approach.

Music therapy methods were heterogeneous across the included studies. In one study, the active music therapy approach used was singing with the played songs [ 33 ]. Two other studies used the receptive (passive) music therapy approach which consists in listening to music and songs played on a CD player [ 31 , 35 ]. The remaining five studies were based on a combination of both active and receptive music approaches [ 26 , 29 , 30 , 34 , 36 ].

Comparators

In four studies, music therapy intervention was compared to standard care [ 29 , 30 , 34 , 35 , 36 ], while in the four remaining studies, different interventions other than music therapy were used as comparators such as: watching nature videos [ 36 ], painting [ 33 ], cooking [ 26 ], and practicing meditation [ 31 ].

Application of the intervention

Only three trials were conducted by a music therapist [ 29 , 34 , 36 ], 1 trial was conducted by a professional choir conductor [ 33 ], 1 by musicians [ 30 ] and the 3 remaining trials were conducted with facilitators with no musical expertise [ 26 , 31 , 35 ].

Types of applied music

Seven trials out of 8 were based on individualized songs (chosen according to patient’s preferences or songs that are used to evoke positive emotions in them) [ 29 , 30 , 31 , 33 , 34 , 35 , 36 ]. The remaining trial was based on familiar songs chosen without considering the patient’s preferences [ 26 ].

Outcome characteristics

The included studies assessed different outcomes, but we focused on domains directly related to outcome inclusion criteria: global cognition, memory, language, speed of information processing, verbal fluency, and attention. All cognitive outcomes and measurement tools used across studies are listed in Table 1 .

Risk of bias

The quality of trials was assessed by Jadad scales [ 28 ]. Studies with scores ≥ 3 were classified as high-quality studies and those of ≤ 2 were classified as “low-quality” studies. [ 26 , 29 , 30 , 31 , 33 , 36 ] studies were considered high-quality studies while [ 34 , 35 ] studies were considered of low-quality. Blinding of participants was not possible due to the nature of the intervention considered in this review. Randomization was mentioned in all studies except one study [ 34 ]. Results of the quality assessment of all studies using the Jadad scales are summarized in Table 2 .

Results of individual studies

Sakamoto et al. [ 29 ] studied the effect of music intervention (active and passive) on patients with severe dementia. Results showed that there is a short-term improvement in emotional state assessed by the facial scale which is a tool commonly used by psychologists and healthcare professionals to assess and code facial expressions, both positive and negative, to determine a patient’s emotional state [ 37 , 38 ]. In addition to eliciting positive emotions, music therapy has been shown to have long-term benefits in reducing behavioral and psychological symptoms of dementia assessed by the Behavioral Pathology in Alzheimer’s Disease (BEHAVE-AD) Rating Scale, a well-established instrument to assess and evaluate behavioral symptoms in AD patients, as well as to evaluate treatment outcomes and identify potentially remediable symptoms [ 39 ].

The study by Narme et al. [ 26 ] was conducted to evaluate the effectiveness of music and cooking interventions in improving the emotional, cognitive, and behavioral well-being of AD and mixed dementia patients. The study lasted 4 weeks and involved 48 patients, who received two 1-h sessions of either music or cooking interventions per week. Both interventions showed positive results, such as improved emotional state and reduced the severity of behavioral disorders, as well as reduced caregiver distress. However, there was no improvement in the cognitive status of the patients. Although the study did not find any specific benefits of music interventions, it suggests that these non-pharmacological treatments can improve the quality of life for patients with moderate to severe dementia and help to ease caregiver stress [ 26 ].

The study by Gómez Gallego and Gómez García [ 34 ] showed a significant increase in MMSE scores, especially in the domains of orientation, language and memory [ 34 ]. Subsequent study from the same author aiming to compare the benefits from active music therapy versus receptive music therapy or usual care on 90 AD patients showed impressive results of active music intervention improving cognitive deficits and behavioral symptoms [ 36 ]. Other supportive data revealed an increase of MMSE and MoCA scores over the study duration in the intervention group, in comparison to the control group [ 35 ].

The study by Pongan et al. [ 33 ] examined the effects of singing versus painting on 50 AD patients over a period of 12 weeks. Results showed that both therapies elicited benefits in reducing depression, anxiety, and pain. The only advantage that the singing group had over the painting group is the stabilization of verbal memory (assessed using FCRT) over time [ 33 ].

Lyu et al. [ 30 ] study aimed to investigate the effects of music therapy on cognitive functions and mental well-being in AD patients. The study utilized the World Health Organization University of California-Los Angeles Auditory Verbal Learning Test (WHO-UCLA AVLT) to assess the short-term and long-term memory of the participants. Subjects were tested on their ability to recall 15 verbal words immediately and after a delay of 30 min. The results showed that music therapy was more effective in improving verbal fluency and alleviating psychiatric symptoms and caregiver distress than lyric reading in AD patients. The stratified analysis revealed that music therapy improved memory and language ability in mild AD patients and reduced psychiatric symptoms (delusions, hallucinations, agitation/aggression, dysphoria, anxiety, euphoria, apathy, disinhibition, irritability/lability, and aberrant motor activity) and caregiver distress in moderate or severe AD patients. However, no significant effect was found on daily activities in any group of patients [ 30 ].

Innes et al. [ 31 ] study consisted of testing music listening therapy over a period of 12 weeks. Cognitive functions were assessed through various measures, including memory (using the Memory Functioning Questionnaire MFQ), executive function (using the Trail Making Test (TMT) Parts A and B), and psychomotor speed, attention, and working memory (using the 90-s Wechsler Digit-Symbol Substitution Test). The scores assessed at baseline, 3 months, and 6 months after therapy showed an improvement in measures of memory function, psychological status, and cognitive performance including executive functions, working memory, processing speed, and attention [ 31 ].

Neurodegenerative diseases, such as dementia, pose a major challenge to global health and will continue to increase in impact with the aging population. AD is a widespread form of dementia affecting a large number of elderly individuals globally and may contribute to 60–70% of cases [ 40 ]. Despite efforts to find effective treatments through pharmacological means, the results have been disappointing in recent decades. As a result, non-pharmacological therapies have gained more attention as a way to improve cognitive, behavioral, social, and emotional functions in AD patients.

Music therapy has been shown to induce plastic changes in some brain networks [ 41 ], facilitate brain recovery processes, modulate emotions, and promote social communication [ 42 ], making it a promising rehabilitation approach. Thus, the present systematic review aimed to systematically synthesize the impact of music therapy on cognitive functions in AD patients. Out of the eight studies reviewed, totaling 689 subjects, seven studies found a significant and positive effect of music therapy on enhancing cognitive functions in individuals with AD. However, one study by Narme et al. [ 26 ] did not find evidence of the efficacy of music therapy on cognitive functions [ 26 ]. This result may be due to the use of music that was chosen by the therapist, rather than being based on the patient’s preferences, and the use of cooking as a control group rather than a standard group to test the efficacy of the intervention. Furthermore, Narme et al. [ 26 ] suggested that a larger sample size would be beneficial in conducting parametric analysis, which could provide more robust results [ 26 ]. These findings highlight the potential benefits of music therapy as a non-pharmacological intervention for AD patients.

Six out of eight studies revealed that patients who underwent Active Music Intervention (AMI) had better outcomes compared to those who underwent Receptive Music Intervention (RMI) [ 29 , 30 , 33 , 34 , 35 , 36 ]. On the other hand, the findings of the studies by Innes et al. [ 31 ] and Wang et al. [ 35 ] that used only the RMI approach, showed a positive impact on cognitive functions in AD patients [ 31 , 35 ].

In the study by Innes et al. [ 31 ], both the meditation and music listening groups showed significant improvements in cognitive functions, without a significant difference between the two groups. In the study by Wang et al. [ 35 ], music therapy was found to be an effective adjuvant to support pharmacological interventions in AD, leading to significant improvements in the MMSE and MoCA scores. It is worth noting that AMI and RMI differ in terms of the level of patient involvement and the objectives of the therapy. AMI involves the direct participation of patients in musical activities such as singing, playing an instrument, or moving to the beat, whereas RMI consists of passive listening to music. From a functional and physiological perspective, AMI may have a greater impact on cognitive and emotional processes due to the increased level of engagement and interaction with the music [ 36 ]. AMI has been shown to activate brain regions involved in auditory processing, motor control, and emotional regulation, leading to improved cognitive functions and reduced agitation and anxiety [ 41 ]. On the other hand, RMI may have a more relaxing effect, as it can induce changes in heart rate and breathing, reducing stress levels and improving sleep quality [ 42 ]. Based on our systematic review, it is not possible to draw conclusions about the optimal music types (classic music, familiar songs, individualized songs…) for music therapy in patients with AD. This is due to the heterogeneity of the studies included in our review, including differences in the types of music used and the methods of exposure. Therefore, it is not possible to determine with certainty which type of music is most effective for improving cognitive functions in AD patients. Further research is needed to establish the optimal music types and optimal duration of music therapy in this population. Our findings also revealed that individualized music playlists, consisting of songs chosen based on the patient’s preferences, showed improvement in cognitive functions, particularly in memory. A study by [ 31 ] used relaxing music in the intervention group, chosen according to patients’ preferences. The music listening CD to be heard by patients in this study contained selections from Bach, Beethoven, Debussy, Mozart, Pachelbel, and Vivaldi, which resulted in an improvement in cognitive functions. This is consistent with the [ 43 ] study which showed that listening to classical music, specifically selections from Mozart, could result in a temporary improvement in certain cognitive tasks such as abstract/spatial reasoning tests. While the “Mozart Effect” has been linked more to the acute arousal brought on by the pleasure of listening to music, rather than a direct impact on cognitive ability [ 44 ], both studies highlight the potential for listening to classical music to have a positive impact on cognitive functions.

The improvement in orientation, language, and memory domains in individuals with AD, as reported in the studies by [ 34 , 36 ], can be attributed to several factors such as the use of an individualized playlist or the presence of a music therapist to perform the sessions. The study by [ 30 ] suggests that music intervention has a positive effect on verbal fluency, memory, and language in individuals with AD. The rhythmic and repetitive elements of music regulate brain function, and musical activities such as singing and playing instruments can activate neural networks involved in memory and language processing.

Further beneficial effects other than improved cognitive behaviors, memory, language, and orientation, the study by [ 29 ] showed a positive impact on the emotional state of the patients. This is consistent with the idea that several cognitive processes such as perception, attention, learning, memory, reasoning, and problem-solving, are all influenced by emotions [ 45 ]. However, the positive effects observed in the emotional state of the patients disappeared 3 weeks after the intervention period. The effects of the intervention lasted after the follow-up for a period that varied between studies [ 29 , 30 , 31 , 33 , 35 ], from 1 month [ 33 ] to 6 months [ 30 , 31 ]. Further research is needed to determine the most effective and optimal duration for music therapy interventions.

Our review has some limitations including differences in participant characteristics (participant age/severity of illness/cognitive ability…), outcome measures, and intervention methods, that may have influenced the results. Additionally, the music therapy interventions used in the studies differed, with activities ranging from singing to playing instruments. These factors, combined with the small number of studies included in the review, limit the power of our findings. Furthermore, the heterogeneity of the interventions and outcome measures used in the studies makes it difficult to perform a meta-analysis and combine the data in a meaningful way. The varying methods of music selection and exposure also pose challenges in synthesizing the results.

The findings of this review suggest that music therapy could have a positive impact on cognitive functions in patients with AD. This supports the growing body of evidence that targets music therapy as a promising cognitive rehabilitating process aiming to improve cognitive functions in individuals with AD dementia like memory, executive functions, or attention. Improvements in these cognitive functions can, in turn, enhance the quality of life of both the patients and their caregivers. However, more research is needed to fully understand the mechanisms behind these effects and to determine the optimal approach to music therapy for this population, including the time frame for follow-up evaluations. Nevertheless, the results of this review highlight the potential benefits of music therapy as a treatment option for individuals with AD and the importance of continued investigation in this field, including long-term follow-up assessments to determine the sustained impact of music therapy on cognitive functions.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Abbreviations

• Alzheimer’s disease

Active music therapy

Behavior Pathology in Alzheimer’s Disease

Digit Symbol Substitution Test

Frontal assessment battery

Free and Cued Recall Test

Memory Functioning Questionnaire

Mini-Mental State Examination

Montreal Cognitive Assessment

Positron emission tomography

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Randomized controlled trials

Receptive music therapy

Severe impairment battery

Trail Making Test

United States of America

World Health Organization University of California-Los Angeles Auditory Verbal Learning test

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Malak Bleibel, Najwane Said Sadier & Linda Abou-Abbas

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Ali El Cheikh

College of Health Sciences, Abu Dhabi University, Abu Dhabi, United Arab Emirates

Najwane Said Sadier

INSPECT-LB (Institut National de Santé Publique Epidémiologie Clinique Et Toxicologie-Liban), Beirut, Lebanon

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Conception or design of the work: MB and LAA, Data collection, extraction, and quality assessment MB and AC, supervision, LAA, writing—original draft preparation, MB; Critical revision of the article: LAA and NSS; all authors read and approved the final manuscript.

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Bleibel, M., El Cheikh, A., Sadier, N.S. et al. The effect of music therapy on cognitive functions in patients with Alzheimer’s disease: a systematic review of randomized controlled trials. Alz Res Therapy 15 , 65 (2023). https://doi.org/10.1186/s13195-023-01214-9

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Psychology in Action

Is music the new medicine exploring the benefits of music therapy.

Written By: Noe Villavicencio-Ramirez

Mentored By: Suzanna Donato, M.A.

If you were asked to make a playlist of your life, what would it consist of? Would it contain songs from your childhood or beats from your teens? How about tracks that bring you to tears or melodies that brighten your day? We cannot deny the influence that music has on our lives, but have you ever wondered why that is?

The origins of music date back to way before anything you or I could remember. Recently, archeologists in Germany discovered a flute, carved from the bone of a bird, estimated to be about 42,000 years old. It is considered to be the oldest evidence of music-making to date. Another excavation in modern-day Syria unveiled many cuneiform scripts (i.e., clay tablets that detailed the daily life of Mesopotamian civilizations) from 1750 BCE. Within these scripts were depictions of musicians as important parts of daily life. Performing at religious ceremonies, communal festivities, and during celebrations for the King returning from battle, the musicians were a cornerstone of the lively cities and remained a staple of society for centuries. In addition to its celebratory contributions, the therapeutic value of music was also explored as far back as Ancient Greece. Aristotle, in his famous “De Anima”, wrote about the emotional impact and soul purification that was believed to take place as a result of simply listening to the sounds of a flute.

Music has a presence and the unique ability to demand excitement as it gets a crowd moving, but we cannot overlook the status music holds in its ability to remedy a hurting soul.

In today’s modern practices, music is continuously explored for its benefits and remedial contributions. It has been an intervention in a vast array of different procedures and settings becauses of its often soothing nature, along with the positive emotions it can elicit in the listener.

When a child undergoes a clinical procedure, naturally they are hit with a sea of emotions; fear and anxiety being the most noteworthy. In order to mitigate the stress that is brought upon by different procedures, oftentimes pharmacotherapy is the chosen remedy. Unfortunately, as effective as these medications may be, they are each also associated with long-term risks of their own (e.g. dry mouth, gastrointestinal discomfort, or more severe issues). That’s where music comes in. According to Klassen (2008), music has the potential to replace these interventions, thus reducing the risk for lasting negative effects. By pulling one’s attention away from painful symptoms, music offers an outlet to escape and get lost in a world of one’s choosing. To test this hypothesis, Klassen et. al (2008) decided to implement Music Therapy into the preparation phase of children undergoing medical or dental procedures. The children were observed either undergoing Music Therapy with a music therapist present (i.e., the active music therapy condition), without a therapist (i.e., the passive music therapy condition), or without any music at all (i.e., no music therapy condition). The results showed that, regardless of whether the therapy was active or passive, music was successful in reducing the levels of pain and anxiety as compared with the no music therapy condition. In this context, music was able to sooth the worrisome children and ease their transition into the operation phase, which is quite a feat for a tool we can so easily take for granted.

In addition to the impact that music has on pain and anxiety, it has also been suggested that music can influence one’s mood and emotions. A number of different experiments where music was used to induce mood changes in various samples were reviewed to further explore this idea. Across the varying studies, music remained consistent in its ability to influence the mood of the listener, either inciting a more positive or a more negative mood. In addition, researchers realized the role of cognitive processes that seemed to be paired to the induction of emotions via music. Participants that underwent changes in mood attributed these changes to the memories they recalled while listening to particular songs. Whether it was picturing their parents, remembering a special night out with their significant other, or reliving their state championship game from their high school days, the participants that interacted with the music felt a certain connection between the music and their memory recall. When reminded of their valued past experiences, participants were able to reconnect with their emotional state of that particular time period. This connection was reflected by the changes in mood and emotion of their present self. These studies suggest that music has the ability to trigger emotions that go beyond the ordinary “day-to-day” emotions and deal more with emotions that aren’t as easily labelled verbally. With this in mind, further research is currently exploring how to distinguish between the degree of complexity regarding the emotional responses as well as determining whether responses are a result of induction (how the music makes you feel) or perception (how the music sounds) (e.g., “I am feeling happy” versus “The music sounds happy”).

Another promising avenue for musical intervention is its role in regulating hormonal responses that can facilitate changes in different physiological functions. An example of this is demonstrated in Sutoo’s (2004) article on the effects of music on blood pressure regulation. This study used classical music to identify responses in the hormone levels of hypertensive rats in order to track the effect on their systolic blood pressure. The levels of calcium release and dopamine production were measured in order to study their association, as well as dopamine’s role in reducing blood pressure. Sutoo’s experiment used the work of a famous composer that you most likely have heard of, Wolfgang Mozart. Through the musical innervation, the researchers discovered that the music induced the synthesis of dopamine via calcium release, an effect that was halted when this pathway was manually blocked. As a result of the increased dopamine, the rats displayed a decrease in blood pressure and experienced a more efficient cardiac output. Wow, when people say that music could touch their heart, they aren’t kidding! Further research is being conducted on these mechanisms in order to test other regulatory functions attributed to the dopamine release, which may help in counteracting symptoms of other diseases that follow similar patterns of dopamine transmission.

Though we have undoubtedly made great strides in our exploration of music as a viable intervention, further research is necessary to better understand the mechanisms behind the power that music holds. Currently, researchers are expanding on studies that have shown great promise by fine tuning previous methods and approaches, such as those that we’ve looked into. One of the most critical additions to previous research is ensuring a thorough double blind approach. With frontline faculty usually taking the lead on data collection and even analysis of patients participating in the study, some of the results may be interpreted in a certain way given the assessors knowledge of the setting and experimental conditions. In future procedures, we hope to fully blind the assessors who will analyze the collected data, ensure full discretion of participant allocation, and implement controls that mirror the condition of the experimental groups (i.e., the active or passive music therapy conditions) through headsets that receive no input or by playing pre-recorded sounds/stories in place of music.

Most of the time, we don’t think twice about the extent to which music is influencing our daily lives so hearing about all of these different discoveries and experiments can be a lot to take in. If that’s the case, maybe try listening to some music on your own to help you relax a bit and hopefully you too will add to the list of great songs you associate with even greater memories!

Music therapy effectiveness by duration in patients with cancer: a meta-regression

Affiliations.

• 1 Yale School of Public Health, Yale University, New Haven, Connecticut, USA.
• 2 Yale New Haven Hospital, Yale University, New Haven, Connecticut, USA.
• 3 Volunteer Services, Yale New Haven Hospital, Yale University, New Haven, Connecticut, USA.
• 4 Yale New Haven Hospital, Yale University, New Haven, Connecticut, USA [email protected].
• 5 Department of Medicine, Yale University, New Haven, Connecticut, USA.
• PMID: 36810298
• DOI: 10.1136/bmjspcare-2021-003163

Objectives: Several reviews and meta-analyses have reported on music therapy for physical and emotional well-being among patients with cancer. However, the duration of music therapy offered may range from less than 1 hour to several hours. The aim of this study is to assess whether longer duration of music therapy is associated with different levels of improvement in physical and mental well-being.

Methods: Ten studies were included in this paper, reporting on the endpoints of quality of life and pain. A meta-regression, using an inverse-variance model, was performed to assess the impact of total music therapy time. A sensitivity analysis was conducted for the outcome of pain, among low risk of bias trials.

Results: Our meta-regression found a trend for positive association between greater total music therapy time and improved better pain control, but it was not statistically significant.

Conclusion: There is a need for more high-quality studies examining music therapy for patients with cancer, with a focus on total music therapy time and patient-related outcomes including quality of life and pain.

Keywords: cancer; pain; quality of life.

© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.

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A Trailblazing Journey in Music Therapy

Dr. carlene j. brown ‘80 stands as a pioneering figure in the field of music therapy and research..

A double major in music therapy and music education, she was among the first cohort of graduates of Emmanuel College's music therapy program. This milestone, one of many, set the stage for a distinguished career studying physiological and psychological responses to music.

A recent milestone includes her role as the sole music therapist on the University of Washington/National Institutes of Health-sponsored research team that’s studying the influence of music on pain management. Specifically, they are investigating how patients with chronic lower back pain  respond to live and recorded sessions of the Body Tambura, a German stringed instrument, performed by Dr. Brown while monitoring their EEG readings.  While data isn’t yet available, participants have reported reduced pain intensity and improved well-being, with some achieving states of relaxation previously unattainable. The study is a pilot and given the results, Dr. Brown expects the study will continue on a larger scale.

Dr. Brown presented her work using music for pain management at the December 2023 Sound Health Initiative workshop on " Music as Medicine: The Science and Clinical Practice ," co-sponsored by the National Institutes of Health, National Endowment for the Arts, Renée Fleming Foundation and John F. Kennedy Center for the Performing Arts. 

Emmanuel Laid the Groundwork for Success

Dr. Brown expressed gratitude for the pivotal role the College played in shaping her career and instilling in her a deep sense of purpose and commitment to serving diverse communities through music. 

“ Emmanuel provided me with a well-rounded musical education and philosophy of music therapy that I carry into all aspects of my work. The foundation I received at Emmanuel allowed me to embark on many different career paths. Dr. Carlene J. Brown

After graduation, Dr. Brown quickly found success as a music educator in Brookline, Mass., and later expanded her impact by leading a summer program for middle school youth at Tanglewood organized by the Boston Symphony Orchestra. The program, Days in the Arts, brings together students from Boston and other cities in Massachusetts to build confidence, develope leadership skills, foster cultural connections and empower youth through the arts.

“We used the arts to break down cultural barriers, and it was a stunning success. The students arrived on a Monday and left on Friday, and they were trying to figure out how to use public transportation to see each other. These are kids who would never have necessarily crossed paths,” she recalled. 

Expanding Access to Music Therapy

Dr. Brown earned a doctoral degree in the psychology of music in 1991 from the University of Washington in Seattle. She explored the physiological and psychological responses to music with a focus on its therapeutic aspects. “I asked, ‘Why was I seeing these reactions in a therapeutic setting? Is it me? Is it the person? Is it the music? What is music actually doing to influence a reaction?’”

She was also involved in a program to diversify the faculty at the university. “Part of my passion is to model the way for first generation and students of color to not only get through undergraduate, but also to consider a doctorate degree,” she said.

Dr. Brown's commitment to diversity and inclusion extend beyond academia. She was part of a team that established a community music school in Seattle and spearheaded a music therapy program within it. The endeavor brought music therapy into a broader educational context, emphasizing accessibility and inclusivity in the arts.

“This was an amazing opportunity to bring my musician side and my administrative side together to serve the community,” she said.

Dr. Brown joined the faculty of Seattle Pacific University (SPU) in 2005 as a professor of music and a one-year position turned into a tenured role and she eventually became the chair of the Music Department. In 2009, she launched a music therapy program at SPU — the first such program in the state. 

As Dr. Brown continues to break new ground in the field of music therapy and research, Emmanuel College is honored to say her journey began in the heart of Boston. 

The first Northern Music Awards will help fund a music therapy centre in Greater Manchester

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ITV Granada Reports correspondent Elaine Willcox explores the power of music therapy

Some of the artists nominated for the first-ever Northern Music Awards have been taking part in music therapy sessions for those living with dementia. They are run by the charity Nordoff and Robbins who want to create a dedicated therapy centre in Salford - using music to help make vital connections for those socially isolated, or with disabilities.

Every week, residents living with dementia at The Fed Heathlands Village in Prestwich have a specialist music therapy session.

Joanne Selig's late father and now her mother in law live there and she said it is a joy to see how the therapy transforms people's moods and provokes memories.

"It’s wonderful to see them smiling along and joining in and something we could do together as well, but hold hands and sing together."

The residents also enjoy petting her dog, Sherlock Bones who she takes on her visits.

David Robinson, Music Therapist and Head of Music Services (Delivery) at the charity, said: “It has to be tailored to where that person is in that moment. We use improvisation and go where the memory takes people."

"The music therefore has to change and flex to be with that person, to help bridge and support that connection moment by moment.”

Nine of our granada introducing acts are nominated at the Northern Music Awards, including soul and jazz artist Mica Millar, whose grandad had dementia.

Mica said: " In the session it was actually quite emotional because, gradually you can see maybe them singing along, coming up with a couple of lyrics."

"And we did do a lot of that with my grandad, he'd love to have a sing along."

"When I was writing, he had a habit of going round and turning all the plug switches off in the house, so the computer would just turn off and I lost a few hit songs probably."

It also brought back powerful memories too for pop poet Antony Smzierek who joined in the singing.

The spoken word, indie hip hop artist from Hyde, will open the awards with a specially commissioned piece about the power of music therapy.

“It was really, really beautiful. It was nice to see immediately how it helped.”

“But it's lovely to see that when those chords come in for Singing in the Rain - they're right back.

It's the same my grandmother and Nat King Cole. It was for us. So we play "Unforgettable". And she'll be back right away."

The staff at Beach house says the sessions have a calming effect ... which lasts all day.

Team leader Sally Williams said: "We have one resident who that that's the highlight of a week she absolutely loves it."

The charity hopes to be able to share the power of music with more people when it builds a dedicated centre earmarked for Salford.

Liam Fray from indie rock royalty Courteeners will take to the stage at the inaugural Nordoff and Robbins Northern Music Awards with a special live acoustic performance.

They will be joined by Manchester legend Lisa Stansfield, Warrington’s rising stars The K’s and the up-and-coming Leeds quartet, English Teacher.

Tickets are now on sale for the Awards taking place on Tuesday 23 April 2024 at Manchester’s iconic Albert Hall.

Resurrected in 2013 after being closed for over 40 years, the Grade II listed Wesleyan chapel has been restored into a stunning purpose-built music hall and is one of the most atmospheric music and events venues in the UK.

The awards will be hosted by BBC Radio Six Music Presenter Chris Hawkins who champions new music on his show.

"I'm very proud to be hosting the Northern Music Awards 2024. It's an incredible line up."

The charity said: "The performance-packed show will help to fundraise for Nordoff and Robbins’ vision to open a dedicated state of the art music therapy centre for Greater Manchester – and will kickstart a new chapter in celebrating the diverse talent of the North of England year after year. "

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Music therapy, artificial intelligence to be highlighted at St. Olaf Lutheran Church

Published 5:54 pm Tuesday, April 16, 2024

By Daily Herald

St. Olaf Lutheran Church in Austin invites everyone to a Continuing Education Day in its Fellowship Hall from 9-11:30 a.m. on Thursday, April 25. 

The program is free, and will cover topics of special interest in an ever-changing world. Here is the schedule for this informative morning:

• 9-10 a.m.: What’s New in IT, AI, Scams and Other Tech Topics, presented by Dick Flisrand

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• 10-10:30 a.m.: Coffee and Rolls

• 10:30-11:30 a.m.: The Power of Music Therapy, presented by Emma Evans-Peck, board-certified music therapist and neurologic music therapist from the MacPhail Center for Music in Austin

The first session will cover a wide range of tech topics, but of special interest will be a discussion of artificial intelligence (AI), a topic which has dominated headlines these days. This should help people better understand the debate surrounding this new technology.

The second session on music therapy will cover the dramatic changes that have occurred in this area in recent years with a focus on its neurologic underpinnings. It is a growing body of research has shown how music and arts therapies can be effective tools for addressing health and wellness issues.

MacPhail Center for Music – Austin has recently added music therapy to its programs.

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Jack Antonoff Mocks Ye During Impromptu Therapy Session With Jimmy Kimmel: ‘Your Diaper Is So Full’

"I prefer to sort of up the trolling," the producer said.

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Hannah Dailey

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Jack Antonoff is bringing his distaste for Ye (formerly known as Kanye West) to national television. Speaking to Jimmy Kimmel Tuesday night (April 16), the producer took shots at the rapper while indulging in a mock-therapy session with the late-night host, likening the “Donda” musician to a fussy baby with an overly full diaper. 

A Timeline of the Consequences Kanye West Has Faced for His ‘WLM’ Shirts & Antisemitic…

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It’s not the first time Antonoff, who is Jewish, has poked fun at Ye. In fact, it’s not even the first time he’s implied that the controversial figure is suffering from a loaded pull-up. In a February interview with the Los Angeles Times , the “Don’t Take the Money” singer quipped that the rapper “just needs his diaper changed so badly.” 

“It’s been a long time since I would’ve taken Kanye’s call,” he added at the time when asked whether he’d ever work with Ye in the future. “I’m so incredibly bored when someone doesn’t have the sauce anymore, so they go elsewhere to shock. It’s just a remarkable waste of space.” 

Aside from Ye’s hate speech, Antonoff has another big reason to oppose the hip-hop titan. The former Fun band member is a longtime friend and collaborator to Taylor Swift, whose tumultuous feud with Ye has been highly publicized over the years. 

A Timeline of Kanye West & Taylor Swift’s Relationship

Antonoff is fresh off his performance with Bleachers at the opening weekend of Coachella 2024, which was attended by Swift and Travis Kelce. The guitarist will take the Mojave Stage once again Saturday (April 20), when the festival resumes for a second weekend.  

Watch Antonoff’s Jimmy Kimmel Live! interview above. 

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