research paper on the effects of music

EDITORIAL article

Editorial: the impact of music on human development and well-being.

• 1 Department of Culture, Communication and Media, University College London, London, United Kingdom
• 2 Department of Philosophy, Sociology, Education and Applied Psychology, University of Padua, Padua, Italy
• 3 School of Humanities and Communication Arts, Western Sydney University, Penrith, NSW, Australia
• 4 Melbourne Conservatorium of Music, University of Melbourne, Melbourne, VIC, Australia

Editorial on the Research Topic The Impact of Music on Human Development and Well-Being

Music is one of the most universal ways of expression and communication for humankind and is present in the everyday lives of people of all ages and from all cultures around the world ( Mehr et al., 2019 ). Hence, it seems more appropriate to talk about musics (plural) rather than in the singular ( Goble, 2015 ). Furthermore, research by anthropologists as well as ethnomusicologists suggests that music has been a characteristic of the human condition for millennia (cf. Blacking, 1976 ; Brown, 1999 ; Mithen, 2005 ; Dissanayake, 2012 ; Higham et al., 2012 ; Cross, 2016 ). Nevertheless, whilst the potential for musical behavior is a characteristic of all human beings, its realization is shaped by the environment and the experiences of individuals, often within groups ( North and Hargreaves, 2008 ; Welch and McPherson, 2018 ). Listening to music, singing, playing (informally, formally), creating (exploring, composing, improvising), whether individually and collectively, are common activities for the vast majority of people. Music represents an enjoyable activity in and of itself, but its influence goes beyond simple amusement.

These activities not only allow the expression of personal inner states and feelings, but also can bring about many positive effects in those who engage in them. There is an increasing body of empirical and experimental studies concerning the wider benefits of musical activity, and research in the sciences associated with music suggests that there are many dimensions of human life—including physical, social, educational, psychological (cognitive and emotional)—which can be affected positively by successful engagement in music ( Biasutti and Concina, 2013 ). Learning in and through music is something that can happen formally (such as part of structured lessons in school), as well as in other-than-formal situations, such as in the home with family and friends, often non-sequentially and not necessarily intentional, and where participation in music learning is voluntary, rather than mandated, such as in a community setting (cf. Green, 2002 ; Folkestad, 2006 ; Saether, 2016 ; Welch and McPherson, 2018 ).

Such benefits are evidenced across the lifespan, including early childhood ( Gerry et al., 2012 ; Williams et al., 2015 ; Linnavalli et al., 2018 ), adolescence ( McFerran et al., 2018 ), and older adulthood ( Lindblad and de Boise, 2020 ). Within these lifespan perspectives, research into music's contribution to health and well-being provides evidence of physical and psychological impacts ( MacDonald et al., 2013 ; Fancourt and Finn, 2019 ; van den Elzen et al., 2019 ). Benefits are also reported in terms of young people's educational outcomes ( Guhn et al., 2019 ), and successful musical activity can enhance an individual's sense of social inclusion ( Welch et al., 2014 ) and social cohesion ( Elvers et al., 2017 ).

This special issue provides a collection of 21, new research articles that deepen and develop our understanding of the ways and means that music can impact positively on human development and well-being. The collection draws on the work of 88 researchers from 17 different countries across the world, with each article offering an illustration of how music can relate to other important aspects of human functioning. In addition, the articles collectively illustrate a wide range of contemporary research approaches. These provide evidence of how different research aims concerning the wider benefits of music require sensitive and appropriate methodologies.

In terms of childhood and adolescence, for example, Putkinen et al. demonstrate how musical training is likely to foster enhanced sound encoding in 9 to 15-year-olds and thus be related to reading skills. A separate Finnish study by Saarikallio et al. provides evidence of how musical listening influences adolescents' perceived sense of agency and emotional well-being, whilst demonstrating how this impact is particularly nuanced by context and individuality. Aspects of mental health are the focus for an Australian study by Stewart et al. of young people with tendencies to depression. The article explores how, despite existing literature on the positive use of music for mood regulation, music listening can be double-edged and could actually sustain or intensify a negative mood.

A Portuguese study by Martins et al. shifts the center of attention from mental to physical benefits in their study of how learning music can support children's coordination. They provide empirical data on how a sustained, 24-week programme of Orff-based music education, which included the playing of simple tuned percussion instruments, significantly enhanced the manual dexterity and bimanual coordination in participant 8-year-olds compared to their active control (sports) and passive control peers. A related study by Loui et al. in the USA offers insights into the neurological impact of sustained musical instrument practice. Eight-year-old children who play one or more musical instruments for at least 0.5 h per week had higher scores on verbal ability and intellectual ability, and these correlated with greater measurable connections between particular regions of the brain related to both auditory-motor and bi-hemispheric connectivity.

Younger, pre-school children can also benefit from musical activities, with associations being reported between informal musical experiences in the home and specific aspects of language development. A UK-led study by Politimou et al. found that rhythm perception and production were the best predictors of young children's phonological awareness, whilst melody perception was the best predictor of grammar acquisition, a novel association not previously observed in developmental research. In another pre-school study, Barrett et al. explored the beliefs and values held by Australian early childhood and care practitioners concerning the value of music in young children's learning. Despite having limited formal qualifications and experience of personal music learning, practitioners tended overall to have positive attitudes to music, although this was biased toward music as a recreational and fun activity, with limited support for the notion of how music might be used to support wider aspects of children's learning and development.

Engaging in music to support a positive sense of personal agency is an integral feature of several articles in the collection. In addition to the Saarikallio team's research mentioned above, Moors et al. provide a novel example of how engaging in collective beatboxing can be life-enhancing for throat cancer patients in the UK who have undergone laryngectomy, both in terms of supporting their voice rehabilitation and alaryngeal phonation, as well as patients' sense of social inclusion and emotional well-being.

One potential reason for these positive findings is examined in an Australian study by Krause et al. . They apply the lens of self-determination theory to examine musical participation and well-being in a large group of 17 to 85-year-olds. Respondents to an online questionnaire signaled the importance of active music making in their lives in meeting three basic psychological needs embracing a sense of competency, relatedness and autonomy.

The use of public performance in music therapy is the subject of a US study by Vaudreuil et al. concerning the social transformation and reintegration of US military service members. Two example case studies are reported of service members who received music therapy as part of their treatment for post-traumatic stress disorder, traumatic brain injury, and other psychological health concerns. The participants wrote, learned, and refined songs over multiple music therapy sessions and created song introductions to share with audiences. Subsequent interviews provide positive evidence of the beneficial psychological effects of this programme of audience-focused musical activity.

Relatedly, McFerran et al. in Australia examined the ways in which music and trauma have been reported in selected music therapy literature from the past 10 years. The team's critical interpretive synthesis of 36 related articles led them to identify four different ways in which music has been used beneficially to support those who have experienced trauma. These approaches embrace the use of music for stabilizing (the modulation of physiological processes) and entrainment (the synchronization of music and movement), as well as for expressive and performative purposes—the fostering of emotional and social well-being.

The therapeutic potential of music is also explored in a detailed case study by Fachner et al. . Their research focuses on the nature of critical moments in a guided imagery and music session between a music therapist and a client, and evidences how these moments relate to underlying neurological function in the mechanics of music therapy.

At the other end of the age span, and also related to therapy, an Australian study by Brancatisano et al. reports on a new Music, Mind, and Movement programme for people in their eighties with mild to moderate dementia. Participants involved in the programme tended to show an improvement in aspects of cognition, particularly verbal fluency and attention. Similarly, Wilson and MacDonald report on a 10-week group music programme for young Scottish adults with learning difficulties. The research data suggest that participants enjoyed the programme and tended to sustain participation, with benefits evidenced in increased social engagement, interaction and communication.

The role of technology in facilitating access to music and supporting a sense of agency in older people is the focus for a major literature review by Creech , now based in Canada. Although this is a relatively under-researched field, the available evidence suggests that that older people, even those with complex needs, are capable of engaging with and using technology in a variety of ways that support their musical perception, learning and participation and wider quality of life.

Related to the particular needs of the young, children's general behavior can also improve through music, as exampled in an innovative, school-based, intensive 3-month orchestral programme in Italy with 8 to 10-year-olds. Fasano et al. report that the programme was particularly beneficial in reducing hyperactivity, inattention and impulsivity, whilst enhancing inhibitory control. These benefits are in line with research findings concerning successful music education with specific cases of young people with ADHD whose behavior is characterized by these same disruptive symptoms (hyperactivity, inattention, and impulsivity).

Extra-musical benefits are also reported in a study of college students (Bachelors and Masters) and amateur musicians in a joint Swiss-UK study. Antonini Philippe et al. suggest that, whilst music making can offer some health protective effects, there is a need for greater health awareness and promotion among advanced music students. Compared to the amateur musicians, the college music students evaluated their overall quality of life and general and physical health more negatively, as did females in terms of their psychological health. Somewhat paradoxically, the college students who had taken part in judged performances reported higher psychological health ratings. This may have been because this sub-group were slightly older and more experienced musicians.

Music appears to be a common accompaniment to exercise, whether in the gym, park or street. Nikol et al. in South East Asia explore the potential physical benefits of synchronous exercise to music, especially in hot and humid conditions. Their randomized cross-over study (2019) reports that “time-to-exhaustion” under the synchronous music condition was 2/3 longer compared to the no-music condition for the same participants. In addition, perceived exertion was significantly lower, by an average of 22% during the synchronous condition.

Comparisons between music and sport are often evidenced in the body of existing Frontiers research literature related to performance and group behaviors. Our new collection contains a contribution to this literature in a study by Habe et al. . The authors investigated elite musicians and top athletes in Slovenia in terms of their perceptions of flow in performance and satisfaction with life. The questionnaire data analyses suggest that the experience of flow appears to influence satisfaction with life in these high-functioning individuals, albeit with some variations related to discipline, participant sex and whether considering team or individual performance.

A more formal link between music and movement is the focus of an exploratory case study by Cirelli and Trehub . They investigated a 19-month-old infant's dance-like, motorically-complex responses to familiar and unfamiliar songs, presented at different speeds. Movements were faster for the more familiar items at their original tempo. The child had been observed previously as moving to music at the age of 6 months.

Finally, a novel UK-based study by Waddington-Jones et al. evaluated the impact of two professional composers who were tasked, individually, to lead a 4-month programme of group composing in two separate and diverse community settings—one with a choral group and the other in a residential home, both funded as part of a music programme for the Hull City of Culture in 2017. In addition to the two composers, the participants were older adults, with the residential group being joined by schoolchildren from a local Primary school to collaborate in a final performance. Qualitative data analyses provide evidence of multi-dimensional psychological benefits arising from the successful, group-focused music-making activities.

In summary, these studies demonstrate that engaging in musical activity can have a positive impact on health and well-being in a variety of ways and in a diverse range of contexts across the lifespan. Musical activities, whether focused on listening, being creative or re-creative, individual or collective, are infused with the potential to be therapeutic, developmental, enriching, and educational, with the caveat provided that such musical experiences are perceived to be engaging, meaningful and successful by those who participate.

Collectively, these studies also celebrate the multiplicity of ways in which music can be experienced. Reading across the articles might raise a question as to whether or not any particular type of musical experience is seen to be more beneficial compared with another. The answer, at least in part, is that the empirical evidence suggests that musical engagement comes in myriad forms along a continuum of more or less overt activity, embracing learning, performing, composing and improvising, as well as listening and appreciating. Furthermore, given the multidimensional neurological processing of musical experience, it seems reasonable to hypothesize that it is perhaps the level of emotional engagement in the activity that drives its degree of health and well-being efficacy as much as the activity's overt musical features. And therein are opportunities for further research!

Author Contributions

The editorial was drafted by GW and approved by the topic Co-editors. All authors listed have made a substantial, direct and intellectual contribution to the Edited Collection, and have approved this editorial for publication.

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

We are very grateful to all the contributing authors and their participants for their positive engagement with this Frontiers Research Topic, and also for the Frontiers staff for their commitment and support in bringing this topic to press.

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Keywords: music, wider benefits, lifespan, health, well-being

Citation: Welch GF, Biasutti M, MacRitchie J, McPherson GE and Himonides E (2020) Editorial: The Impact of Music on Human Development and Well-Being. Front. Psychol. 11:1246. doi: 10.3389/fpsyg.2020.01246

Received: 12 January 2020; Accepted: 13 May 2020; Published: 17 June 2020.

Reviewed by:

Copyright © 2020 Welch, Biasutti, MacRitchie, McPherson and Himonides. 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: Graham F. Welch, graham.welch@ucl.ac.uk ; Michele Biasutti, michele.biasutti@unipd.it

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• Open access
• Published: 21 March 2023

Changing positive and negative affects through music experiences: a study with university students

• José Salvador Blasco-Magraner 1 ,
• Gloria Bernabé-Valero 2 ,
• Pablo Marín-Liébana 1 &
• Ana María Botella-Nicolás 1  

BMC Psychology volume  11 , Article number:  76 ( 2023 ) Cite this article

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Currently, there are few empirical studies that demonstrate the effects of music on specific emotions, especially in the educational context. For this reason, this study was carried out to examine the impact of music to identify affective changes after exposure to three musical stimuli.

The participants were 71 university students engaged in a music education course and none of them were musicians. Changes in the affective state of non-musical student teachers were studied after listening to three pieces of music. An inter-subject repeated measures ANOVA test was carried out using the Positive and Negative Affect Schedule (PANAS) to measure their affective state.

The results revealed that: (i) the three musical experiences were beneficial in increasing positive affects and reducing negative affects, with significant differences between the interaction of Music Experiences × Moment (pre-post); (ii) listening to Mahler’s sad fifth symphony reduced more negative affects than the other experimental conditions; (iii) performing the blues had the highest positive effects.

Conclusions

These findings provide applied keys aspects for music education and research, as they show empirical evidence on how music can modify specific affects of personal experience.

Peer Review reports

Introduction

The studies published on the benefits of music have been on the increase in the last two decades [ 1 , 2 , 3 ] and have branched out into different areas of research such as psychology [ 4 , 5 , 6 , 7 , 8 ], education [ 1 , 9 , 10 ] and health [ 11 , 12 ] providing ways of using music as a resource for people’s improvement.

The publication in 1996 of the famous report “Education Hides a Treasure” submitted to the UNESCO by the International Commission was an important landmark in the educational field. This report pointed out the four basic pillars of twenty-first century education: learning to know, learning to do, learning to live together, and learning to be [ 13 ]. The two last ones clearly refer to emotional education. This document posed a challenge to Education in terms of both academically and emotionally development at all levels from kindergarten to university. In this regard, there has been a notable increase in the number of studies that have shown the strong impact of music on the emotions in the different stages of education and our lives. For example, from childhood to adolescence, involving primary, secondary and university education, music is especially relevant for its beneficial effects on developing students’ emotional intelligence and prosocial skills [ 1 , 14 ]. In adults, music benefits emotional self-regulation [ 15 ], while in old age it helps to maintain emotional welfare and to experience and express spirituality [ 16 ]. This underlines the importance of providing empirical evidence on the emotional influence of music.

Influence of music on positive affects

Numerous studies have used the Positive and Negative Affect Schedule (PANAS) to evaluate the emotional impact of music [ 17 ]. This scale is valid and effective for measuring the influence of positive and negative effects of music on listeners and performers [ 10 , 18 , 19 ]. Thus, for example, empirical evidence shows that exposure to a musical stimulus favours the increase of positive affects [ 20 , 21 ] found a significant increase in three positive affects in secondary school students after listening to music, and the same results has been found after listening to diverse musical styles. These results are consistent with Schubert [ 22 ], who demonstrated that music seems to improve or maintain well-being by means of positive valence emotions (e. g. happiness, joy and calm). Other research studied extreme metal fans aged between 18 and 34 years old and found statements of physiological excitement together with increased positive affects [ 21 ]. Positive outcomes after listening to sad music have also been found [ 23 ], who played Samuel Barbers’ Adagio for Strings , described by the BBC as the world’s saddest piece of classical music, to 20 advanced music students and 20 advanced psychology students with no musical background and subsequently found that the music only had positive affects on both groups.

Several experimental designs that used sad music on university students noticed that they experienced both sadness and positive affects [ 24 , 25 ] and also found that music labeled as “happy” increased positive affects while the one labeled as “sad” reduced both positive and negative affects [ 26 ]. For other authors the strongest and most pleasant responses to sad music are associated with empathy [ 27 ]. Moreover, listening to sad music had benefits since attributes of empathy were intensified [ 27 , 28 ]. In relation to musical performances, empirical evidence found a significant increase in positive affects [ 29 ]. Thus, music induces listeners to experience positive affects, which could turn music into an instrument for personal development.

Following on from Fredrickson’s ‘broaden‐and‐build’ framework of positive emotions [ 30 ], positive affects cause changes in cognitive activities which, in turn, can cause behaviour changes. They can also expand the possibilities for action and improve physical resources. According to Fredrickson [ 30 ], positive affects trigger three sequential effects: (1) amplification of the scope for thought and action; (2) construction of personal resources to deal with difficult simplifications; (3) personal transformation by making one more creative, with a better understanding of situations, better able to face up to difficulties and better socially integrated. This leads to an “upward spiral” in which even more positive affects are experienced. A resource such as music that can increase positive affects, can therefore be considered as a step forward in personal transformation. Thus, music teachers could have a powerful tool to help students enhance their personal development.

Influence of music on negative affects

There is a great deal of controversy as regards the influence of music on negative affects. Blasco and Calatrava [ 20 ] found a significant reduction of five negative affects in secondary school students after listening to Arturo Marquez’s typically happy Danzón N O 2. Different results were found in an experiment in which the change in participants ‘affects was assessed after listening the happy "Eye of the Tiger" by Survivor and the sad "Everybody Hurts" by REM [ 26 ]. They found that the happy piece only increased the positive affects but did not reduce the negative ones, while the sad piece reduced both positive and negative affects. However, neither of these findings agree with Miller and Au [ 31 ], who carried out an experiment to compare the influence of sad and happy music on undergraduates ‘mood arousal and found that listening to both types had no significant changes on negative affects. Shulte [ 32 ] conducted a study with 30 university students to examine the impact that nostalgic music has on affects, and found that after listening to different songs, negative affects decreased. Matsumoto [ 33 ] found that sad music reduced sad feelings in deeply sad university students, while Vuoskoski and Eerola [ 34 ] showed that sad music could produce changes in memory and emotional judgements related to emotions and that experiencing music-induced sadness is intrinsically more pleasant than sad memories. It therefore seems that reducing negative affects has mostly been studied with sad and nostalgic musical stimuli. In this way, if music can reduce negative affects, it can also be involved in educational and psychological interventions focused on improving the emotional-affective sphere. Thus, for example, one study examined the effects of a wide range of music activities and found that it would be necessary to specify exactly what types of music activity lead to what types of outcomes [ 2 ]. Moore [ 3 ] also found that certain music experiences and characteristics had both desirable and undesirable effects on the neural activation patterns involved in emotion regulation. Furthermore, recent research on university students shows that music could be used to assess mood congruence effects, since these effects are reactions to the emotions evoked by music [ 35 ].

These studies demonstrate that emotional experience can be actively driven by music. Moreover, they synthesize the efforts to find ways in which music can enhance affective emotional experience by increasing positive affects and reducing the negative ones (e. g. hostility, nervousness and irritability). Although negative emotions have a great value for personal development and are necessary for psychological adjustment, coping with them and self-regulation capacities are issues that have concerned psychology. For example, Emotional Intelligence [ 36 ], which has currently been established in the educational field, constitutes a fundamental conceptual framework to increase well-being when facing negative emotions, providing keys for greater control and management of emotional reactions. It also establishes how to decrease the intensity and frequency of negative emotional states [ 37 ], providing techniques such as mindfulness meditation that have proven their effectiveness in reducing negative emotional experiences and increasing the positive ones [ 38 ]. The purpose of this research is to find whether music can be part of the varied set of resources that can be used by a teacher to modify students’ emotional experience.

Thus, although empirical evidence of the effects of music on the emotional sphere is still incipient. It seems that they can increase positive effects, but it is not clear their impact on the negative ones, since diverse and contradictory results (no change and reduction of negative affects after listening to music) were found. In addition, the effects of the type of musical piece (e.g. happy or sad music) need further investigation as different effects were found. Moreover, previous studies do not compare between the effects of listening to versus performing music. Such an approach could provide keys to highlight the importance of performing within music education. Therefore, this study aims to contribute to this scientific field, providing experimental evidence on the effects of listening to music as compared to performing music, as well as determining the effects of different types of music on positive and negative affects.

To this end, the effects of three different types of music experiences were compared: (1) listening to a sad piece, (2) listening to an epic and solemn piece, and (3) performing of a rhythm and a blues piece, to determine whether positive and negative affects were modified after exposure to these experimental situations. In particular, two hypotheses guided this study: (1) After exposure to each musical experience (listening to a sad piece; listening to a solemn piece and playing a blues), all participants will improve their emotional experience, increasing their positive affects and reducing their negative ones; and (2) the music performance will induce a greater change as compared to the listening conditions.

Participants

A total of 71 students were involved in this study, 6 men and 65 women between the ages of 20 and 40, who were studying a Teaching Grade. These students were enrolled in the "Music Education" program as part of their university degree’s syllabus. None of them had special music studies from conservatories, academies or were self-taught; thus, all had similar musical knowledge. None of them had previously listened to music in an instructional context nor had performed music with their fellow students. In addition, none of them had listening before to the musical pieces selected for this experiment.

All signed an informed consent form before participating and no payment was given for taking part in the study. As the experiment was carried out in the context of a university course, they were assured that their participation and responses would be anonymous and would have no impact on their qualifications. The research was approved by the ethical committee at the Universidad Católica de Valencia San Vicente Mártir: UCV2017- 18-28 code.

Questionnaire

To assess emotional states, the Positive and Negative Affective States scales (PANAS), was administered [ 39 ]. In particular, the Spanish version of the scale [ 17 ], whose study shows a high degree of internal consistency; in males 0.89 in positive affects and 0.91 in negative affects; in women 0.87 in positive affects and 0.89 in negative affects. In this study, good reliability level in each experimental condition was obtained (0.836–0.913 for positive affects and 0.805–0.917 for negative affects (see Table 1 for more information on Cronbach’s α for each experimental condition).

The PANAS consists of 20 items which describe different dimensions of emotional experience. Participants must answer them regarding to their current affective state. The scale is composed of 20 items; 10 positive affects (PA) and 10 negative affects (NA). Answers are graded in a 5-options (Likert scale), with reversed items, ranging from extremely (1) to very slightly or not at all (5).

Musical pieces

The musical pieces choice stemmed from the analysis of some of the music elements that most influence the perception of emotions: mode, melody and intervals. Within the melody, range and melodic direction were distinguished. The range or amplitude of the melodic line is commonly divided into wide or narrow, while the melodic direction is often classified as ascending or descending. Chang and Hoffman [ 10 ] associated narrow amplitude melodies with sadness, while Schimmark and Grob [ 40 ] related melodic amplitude with highly activated emotions. Regarding the melodic direction, Gerardi and Gerken [ 41 ] found a relationship between ascending direction and happiness and heroism, and between descending direction and sadness.

In relation to the mode, Tizón [ 42 ] stated that the major one is completely happy, while the minor one represents sadness. Thompson and Robitaille [ 43 ] considered that, in order to cause emotions such as happiness, solemnity or joy, composers use tonal melodies, while to obtain negative emotions, they use atonality and chromaticism.

In this research, the selected pieces (“Adagietto” from Gustav Mahler's Fifth Symphony, MML; and “Titans” from Alexander The Great from Vangelis, VML) are representative examples of the melodic, intervallic and modal characteristics previously exposed. Mahler's and Vangelis's pieces completely differ in modes and melodic amplitude (sad vs. heroism). Likewise, Mahler's piece is much more chromatic than Vangelis' one, which has a broader melody made up of third, fourth and fifth intervals, often representative of heroism. Those features justify the fact that they have been used as soundtracks in two films belonging to the epic genre (Alexander The Great, 2004) and drama (Death in Venice, 1971).

The musical piece that was performed by the students was chosen in order to be easy to learn in a few sessions, since they were not musicians. So, three musical pieces were used for the experimental conditions, the first two musical pieces were recordings in a CD, while the third one was performed by the subjects.

The three chosen pieces are described below:

Condition 1 (MML): “Adagietto” from Gustav Mahler’s Fifth Symphony (9:01 min), performed by the Berlin Philharmonic conducted by Claudio Abbado [ 44 ]. This is a sad, melancholic and dramatic piece that Luchino Visconti used in the film Death in Venice, made in 1971 and based on the book by Thomas Mann.

Condition 2 (VML): “Titans Theme” from Alexander the Great (3:59 min), directed by Oliver Stone and premiered in 2004, whose music was composed, produced and performed by Vangelis [ 45 ]. It has a markedly epic character with large doses of heroism and solemnity.

Condition 3 (BP): “Rhythm’s Blues” composed and played by Ana Bort (4:00 min). This is a popular African-American piece of music with an insistent rhythm and harmonically sustained by tonal degrees. This piece was performed by the participants using percussion instruments (carillons and a range of xylophones and metallophones).

The sample was divided into two groups (N 1  = 36 and N 2  = 35) that participated separately in all the phases of the study. The first two conditions (MML and VML) were carried out in each group's classroom, while the performance (BP) was developed in the musical instruments room. This room had 52 percussion instruments, including different types of chimes, xylophones and metallophones (soprano, alto and bass). It is a large space where there are only chairs and musical instruments and stands. The first group was distributed as follows: 6 chimes (3 soprano and 3 alto), 5 soprano xylophones, 5 alto xylophones, 5 bass xylophones, 5 soprano metallophones, 5 alto metallophones and 5 bass metallophones. The distribution of the second group was similar, but with one less alto metallophone.

Prior to the experiment, participants received two practical lessons in order to learn how to collectively perform the music score (third experimental condition). After the two practical lessons, during the next three sessions (leaving two weeks between each session), the experiment was carried out. In each session, an experimental condition was applied and PANAS was on-line administered online beforehand and afterwards (Pre-Post design). All participants were exposed to the three experimental conditions and completed the scale before and after listening to music.

In each of these three sessions, a different music condition was applied: MML in the first one, VML in the second one and BP in the third one.

As conditions VML and MML were listening to pieces of music, the instructions received by the subjects were: “You are going to listen to a musical piece, you ought to listen actively, avoiding distractions. You can close your eyes if you feel like to”. For the BP condition, they were said to play the musical sheet all together.

The aim of the study was to examine the effect of the music experience variable (with three levels: MML, VML and BP) in the Positive and Negative Affects subscales from the PANAS scale. The variable Moment was also studied to control biases and to analyze differences between the Pre and Post conditions.

The experiment was designed as a two-way repeated measure (RM) ANOVA with two dependent variables: Positive Affects and Negative Affects, one for each PANAS’ subscales.

The two repeated measures used in the experiment were the variables Musical Experience (ME), with three levels (MML, VML and BP) and the variable Moment, with two levels (PRE and POST). All participants were exposed to the three experimental conditions.

The design did not include a control group, similar to many other studies in the field of music psychology [ 27 , 30 ]. The control was carried out from the intra-subject pre-post measurement of all the participants. The rationale for this design lies in the complexity of the control condition (or placebo) design in psychology [ 46 ]. While placebos in pharmacological trials are sugar pills, in psychology it is difficult to establish an equivalent period of time similar to the musical pieces (e. g. 9 min) without activity, so that cognitive activity occurred during this period of time (e. g. daydreaming, reading a story, etc.) could bias and limit the generalization of results.

Additionally, one of the goals of this study was to compare the effects of listening to music compared to performance on affects. For this reason, two music listening experiences (MML and VML) and a musical performance experience (BP) were designed. In order to control potential biases, participants did not know the musical pieces in the experimental conditions and they had a low level of musical performance competence (musicians were excluded).

It was used SPSS statistics v.26 for the statistical analyzes.

Two ANOVA were performed. The first one, analyzed two dependent variables at the same time: Positive Affects (PA) and Negative Affects (NA).

In the second ANOVA, the 20 items of the PANAS scale were taken as dependent variables. The rest of the experimental design was similar to the first one, a two-way RM ANOVA with variables Musical Experience (ME) and Moment as repeated measures.

Examination of frequency distributions, histograms, and tests of homogeneity of variance and normality for the criterion measures indicated that the assumptions for the use of parametric statistics were met. Normality was met in all tests except for one, but the ANOVA is robust against this assumption violation. All the analyses presented were performed with the significance level (alpha) set at 0.05, two-tailed tests. Means and standard deviations for the 6 experimental conditions for both subscales, Positive Affects and Negative Affects, are presented in Table 1 .

Mauchly’s test of sphericity was statistically significant for Musical Experience and Musical Experience*Moment focusing on NA as the dependent variable ( p  < 0.05). The test only was significant for Musical Experience for PA as dependent variable ( p  < 0.05). The rest of the W’s Mauchly were not significant ( p  > 0.05), so we assumed sphericity for the non-mentioned variables and worked with the assumed sphericity univariate solution. For the variables which the W’s Mauchly was significant, the univariate solution was also taken, but choosing the corrected Greenhouse–Geisser epsilon approximation due to its conservativeness.

A significant principal effect of the Musical Experience variable F(1.710,119.691) = 22.505, p  < 0.05, η 2  = 0.243; the Moment variable F(1,70) = 45.291, p  < 0.05, η 2  = 0.393; and the Musical Experience*Moment interaction F(2,140) = 32.502, p  < 0.05, η 2  = 0.317 were found for PA.

Statistically significance was found for Moment F(1, 70) = 70.729, p  < 0.05, η 2  = 0.503 and Musical Experience*Moment interaction F(1.822, 127.555) = 8.594, p  < 0.05, η 2  = 0.109, but not for Musical Experience F(1.593, 111.540) = 2.713, p  < 0.05, η 2  = 0.037, for the other dependent variable, NA.

Table 2 shows pairwise comparisons between Musical Experience levels. Bonferroni’s correction was applied in order to control type I error. We only interpret the results for the Positive Affects because the Musical Experience effect was not statistically significant for Negative Affects. Results show that condition VML presents a significant higher punctuation in Positive Affects than the other two conditions ( p  < 0.05). It also shows that the musical condition MML is significantly above BP in Positive Affects ( p  < 0.05).

As regards Moment variable (Table 3 ), all but one Pre-Post differences were statistically significant ( p  < 0.05) for all the three conditions for both Positive and Negative Affects dependent variables. The Pre-Post difference found in Positive Affects for the VML Musical Experience did not reach the statistical level ( p  = 0.319).

Focusing on these statistically significant differences, we observe that conditions MML and BP, for PA, decreased from Pre to Post condition, indicating that positive emotions increased significantly between pre and post measures. On the other hand, for NA, all conditions increased from Pre to Post conditions, indicating that negative affects were decreased between pre and post conditions. Once again, one should bear in mind that items were reversed, thus, a higher scores in NA means a decrease in affects.

In order to measure the interaction effect, significant differences between simple effects were analysed.

The simple effect of Moment (level2-level1) in the first Music Experience condition (MML) in PA was compared with the simple effect of Moment (level2-level1) in the second Musical Experience condition (VML). Music Experience conditions 2–3 (VML-BP) and 1–3 (MML-BP) were compared in the same way. Thus, taking into account PA and NA variables, a total of 6 comparisons, 3 per dependent variable, were made.

The results of these comparisons are shown in Table 4 . Comparisons for PA range from T1 to T3 and comparisons for NA range from T4 to T6. All of them are significant ( p  < 0.05) which means that there are statistically significant differences between all the Musical Experience conditions when comparing the Moment (pre/post) simple effects.

In Table 5 , we can look at the differences’ values. As we said before the differences between Pre and Post conditions are significant when comparing the three musical conditions. The biggest difference for positive affects is between MML and BP (T3 = 8.443), and between VML and MML (T4 = − 6.887) for negative affects.

In this second part, the results obtained from the second two-way RM ANOVA with the 20 items as dependent variables are considered. Results of the descriptive analysis of each item: Interested, Excited, Strong, Enthusiastic, Proud, Alert, Inspired, Determined, Attentive, Active, Distressed, Upset, Guilty, Afraid, Hostile, Irritable, Ashamed, Nervous, Jittery, Scared ; in each musical condition: MML, VML and BP; and for the PRE and POST measurements, can be found in the Additional file 1 (Appendix A).

As regards the ANOVA test that compares the three experimental conditions in each mood, Mauchly’s Sphericity Test indicates that sphericity cannot be assumed for the musical experience in most of the variables of the items of effects, except for Interested, Alert, Inspired, Active and Irritable . For these items, the highest observed power index among Greenhouse–Geisser, Huynh–Feldt and Lower-bound epsilon corrections was taken for each variable. For the interaction Musical Experience*Moment, sphericity was not assumed for Distressed, Guilty, Hostile and Scared . For these items, the same above-cited criterion was followed.

Musical experience has a principal effect on all the positive affects, but only has it for 5 negative affects ( Nervous, Jittery, Scared, Hostile and Upset ) ( p  < 0.05). For more detail see Table S1 from Additional file 1 : Appendix B.

The principal effect of Moment is also statistically significant ( p  < 0.05) for all (positive and negative), but two items: Guilty ( p  = 0.073) and Hostile ( p  = 0.123). All the differences between Pre and Post for positive affects are positive, which means that scores in conditions Pre were significantly higher than in condition Post. The other way around occurs for negative affects, all the differences Pre-Post are negative, meaning that the Post condition is significantly higher than the Pre condition. For more detail, see Table S2 from Additional file 1 : Appendix B. In this way, Pre-post changes (Moment) improve affective states; the positive affects increase while the negative are reduced, except for Guilty ( p  = 0.073) and Hostile ( p  = 0.123).

Comparing the proportion of variance explained by the musical experienced and Moment (Tables s1 and s2 from the Additional file 1 : Appendix B), it is observed that most of the η 2 scores in musical experience are below 0.170, except Active and Alert , which are higher. On the other hand, the η 2 scores for Moment are close to 0.300. From these results we can state that, taking only one of the variables at a time, the proportion of the dependent variable’s variance explained by Moment is higher than the proportion of the dependent variable’s variance explained by Musical Experience.

The effect of interaction, shown in Table S3 from the Additional file 1 : Appendix B is significant in 7 positive moods ( Interested, Excited, Enthusiastic, Alert, Determined, Active and Proud ) and 4 negative moods ( Hostile , Irritable, Nervous , and Jittery ).

The pairwise comparisons of Musical Experience’s levels show a wide variety of patterns. Looking at Positive Affects, there is only one item ( Active ) which present significant differences between the three musical conditions. Items Concentrated and Decided do not present any significant difference between any musical conditions. The rest of the Positive items show at least one significant difference between conditions VML and BP. All differences are positive when comparing VML-MML, VML-BP MML-BP, except for Alert and Proud. So, in general, scores are higher for the first two conditions in relation to the third one, meaning that third musical condition presents the biggest increase for Positive Affects (remember items where reversed). For more detail see Additional file 1 : Appendix C.

As regard pairwise comparisons of Musical Experience’s for negative affects, only the items which had a significant principal effect of the variable Musical Experience are shown here. There is a significant difference between conditions VML and MML in item Nervous ; between VML and BP for Scared ( p  < 0.05). For Jittery ; all three conditions differed significantly from each other ( p  < 0.05). Conditions MML and BP differed significantly for Hostile ( p  < 0.05) and conditions VML and BP almost differed significantly for Upset item, but null hypothesis cannot be rejected as p  = 0.056. For more detail see Additional file 1 : Appendix C. All differences were negative when comparing VML-MML, VML-BP MML-BP, except for Nervous and Jittery . So, in general, scores are lower for the first and second condition in relation to the third one.

Positive effects increased significantly during the post phase of all the music experiences, showing that exposure to any of the three music stimuli improved positive affectivity. There were also significant differences between the three experiences in this phase, according to the following order of improvements in positive affectivity: (1) the rhythm and blues performance (BP), (2) listening to Mahler (MML) and (3) listening to Vangelis (VML). As regards the effects of the musical experience x Moment interaction , all the comparisons were significant, with bigger differences in the interpretation of the blues (BP) than in listening to Mahler (MML) and Vangelis (VML). However, the comparison between both experiences, although significant, was smaller. These results indicate that performing music is significantly effective in increasing positive effects. We will explain these results in greater detail below as regards the specific affective states.

As regards Negative Affects, the comparison of the simple effects showed that these decreased after the musical experiences, although in this first analysis the VML musical experience did not differ from the other two. However, the results of the effects of the interaction between musical experiencie x Moment showed that all the comparisons were significant, with a larger difference between MML and VML than the one between BP and each of the other experiences. Listening to Mahler (MML) was more effective in reducing negative affects, compared to both listening to Vangelis and interpreting the blues (BP). These results agree with previous studies [ 26 , 32 ], in which listening to sad music helped to reduce negative affectivity. In this study, it was the most effective condition, although exposure to all three musical experiences reduced negative affects.

The analysis of the specific affective states shows that most items that belong to Positive Affect scale are the most sensitive ones to the PRE-POST change, the different musical conditions and the interpretation of both effects. However, some items of the Negative Affect scale did not differ in the different music conditions or in the music experience × Moment interaction . For example, there were two items (Guilty and Hostile) that did not obtain significance. These results are consistent with the fact that music has certain limits as regards its impact on people’s affects and does not influence all equally. For example, Guilty has profound psychological implications that cannot be affected by simple exposure to certain musical experiences. This means we should be cautious in inferring that music alone can have therapeutical effects on complex emotional states whose treatment should include empirically validated methods. Also, emotional experiences are widely diverse so that any instrument used to measure them is limited as regards the affective/emotional state under study. These results suggest the importance of reviewing the items that compose the PANAS scale in musical studies to adapt it in order to include affective states more sensitive to musical experiences and eliminate the least relevant items.

The analysis of the results in the specific affective states, allows us to delve deeper into each experimental condition. Thus, regarding the results obtained in the complete scale of PANAS, listening to Mahler (MML), causes desirable changes by raising two positive affects ( Inspired and Attentive ) and reducing 10 negative affects ( Distressed, Upset, Afraid, Hostile, Irritable, Ashamed, Nervous, Jittery, and Scared ). This shows that this music condition had a greater effect on the negative affects than the other ones. These results agree with previous studies [ 26 , 32 ], which found that sad music could effectively reduce negative affects, although other studies came to the opposite conclusion. For instance, Miller and Au [ 31 ] found that sad music did not significantly change negative affects. Some authors [ 47 , 48 ] have argued that adults prefer to listen to sad music to regulate their feelings after a negative psychological experience in order to feel better. Taruffi and Koelsch [ 49 ] concluded that sad music could induce listeners to a wide range of positive effects, after a study with 772 participants. In order to contribute to this debate. It would be interesting to control personality variables that might explain these differences on the specific emotions evoked by sad music. In this study, it has been shown that a sad piece of music can be more effective in reducing negative affects than in increasing positive ones. Although the results come from undergraduate students, similar outcomes could be obtained from children and adolescents, although further research is required. In fact, Borella et al. [ 50 ] studied the influence of age on the effects of music and found that the emotional effects influenced cognitive performance (working memory) in such a way that the type of music (Mozart vs. Albinoni) had a stronger influence on young people than on adults. Kawakami and Hatahira [ 28 ], in a study on 84 primary schoolchildren, also found that exposure to sad music pleased them and their level of empathy correlated with their taste for sad music.

Listening to Vangelis (VML) increased 3 positive affects ( Excited, Inspired and Attentive ) and reduced 8 negative affects ( Distressed, Upset, Afraid, Irritable, Ashamed, Nervous, Jittery , and Scared ). Surprisingly, two positive affects were reduced in this experimental condition ( Alert and Attentive ). It could be explained due to the characteristic ostinato rhythm of this piece of music. It was found a similar effect in the study by Campbell et al., [ 26 ] in which sad music reduced both positive and negative affects. This musical condition also managed to modify negative affects more than positive ones.

Performing the blues (BP) increased all 10 positive affects, indicating that performing is more effective in increasing positive affects than listening. These results agree with the study by Dunbar et al. [ 29 ], who found that music performance significantly increased positive affects.

Performing the blues (BP) reduced 6 negative affects, although it was more effective in increasing positive affective states. Vigorous rhythmic music was also found to be positively associated with the use of all the forms of regulating emotions, which suggests that this type of music is especially useful for emotion modulation [ 51 ]. It was found an exception, since Jittery increased after the blues performance. It could be explained by the negative experience that is sometimes associated with music performance. Therefore, it should be taken into account that music performance could increase some negative effects. For example, Dimsdale et al. [ 52 ] found that a strong negative emotional response to a certain type of music in adolescents was related to risk behaviour, indicating that research into the repertory of music experiences needs to be broadened to diverse styles in different age groups to identify all the types of emotional response and their psychological consequences. However, this result should be taken with caution and further research should focus on whether the effect of increased agitation is usual after music performances.

To sum up, this study contributes to the scientific field on the following points: (1) all the musical experiences had significant effects on improving emotional states, increasing positive affects and decreasing the negative ones, which shows the importance of musical experiences on improving the affective sphere; (2) the specific affects that increased, decreased or did not change for each musical experience were identified, providing specific and useful keys for the design of future interventions; and (3) the differences between various types of musical experiences were analyzed, finding more improvements in the performing conditions than in the listening ones.

Limitations and future directions

Limitations.

The sample, made up of university students with a very homogeneous profile in terms of age and sociodemographic characteristics, could limit the generalization of the results. In addition, the low percentage of men in the sample could also affect the generalizability of the results, although no previous studies have reported gender-based differential effects on the positive and negative affects after musical experiences.

Besides, the choice of the pieces of music was based on theoretical criteria and students’ music preferences were not taken into account. This will be included in future research, since the specific choice of the pieces could affect the positive or negative valence of participants’ emotions. However, the goal of using pieces of music not chosen by participants was to elicit new musical experiences for them. Furthermore, no participant was a musician and none of them had previous knowledge of any of the pieces, which may lead to a bias in the results.

In relation to this, the huge amount of available pieces of music, all of them influenced by their cultural and historical context, make it difficult to generalize that certain music parameters correlate with specific emotions. It would be necessary a cross-cultural approach to reach that conclusion.

Future directions

It is recommended to introduce the variables of music preferences and music history to control their effect on the results and to be able to compare the different musical parameters of the pieces together with participants’ preferences.

Likewise, it would be interesting to identify the affects with a greater or lesser degree of influence by music, to adjust the psychological evaluation instrument to the characteristics of the experiment, including items of emotions that can be modified after exposure to a music experience.

The PANAS manual [ 39 ] indicates that a wide variety of affective states (60) and eight different temporal instructions were included in its construction, showing its great versatility. In further research, this instrument should be adapted to for a more specific application to music studies. For instance, by including other emotional states that could be related with the influence of music (e.g. Tranquility , Gratitude , Elevation ), in order to measure more exactly the effects of music on people’s affective experiences.

Accordingly, it would be interesting to evaluate participants' affective traits to establish a baseline and control personality variables, helping to delve into the different levels of the hierarchical structure of affectivity and its relationship with the various music parameters.

Finally, it is recommended that the psychology of music include objective psychophysiological measurements together with self-report evaluations, so that conclusions arising from the experiments have greater robustness and can increase the impact of the contribution to the scientific community.

This study have shown how different music experiences, such as listening and performing, influence the changes in positive and negative affects in student teachers. The results show that the three musical experiences studied are effective in improving the affects by comparing the emotional states before and after the music experiences. It was also showed that there are differences between the effects obtained in each of the music experiences. Besides, improving both types of affects will depend largely on the selected music for the purpose. Although further evidence is required, the results support the importance of music in education, since it provides tools to increase positive affects and to decrease the negative ones, which is important for emotional intelligence development [ 53 , 54 ].

The three music experiences studied are more effective in reducing negative emotional states than in increasing the positive ones. This finding provides useful clues for music teachers to provide strategies that favor emotional regulation. For instance, in order to reduce hostility, irritability and nervousness, students could be exposed to musical auditions of both sad and solemn pieces, choosing musical pieces with similar characteristics to those described in this study. These auditions will be a resource for stress management in the classroom, as well as a tool that students can adopt and generalize to other contexts. Moreover, it is highly likely that students have not heard this type of music before and this experience could increase their repertoire of musical preferences, enhancing their emotional regulation.

The blues performance had a greater impact on participants' positive affects than listening to the other two pieces so, if any teacher wants to increase them (e.g., enthusiasm, interest, etc.), students could be asked to perform simple pieces such as Rhythm's Blues. In this way, musical performance could increase students' resources, contributing to higher levels of motivation, concentration and interest, which promotes learning [ 55 , 56 , 57 , 58 ]. Likewise, it could be very useful for elementary and secondary music teachers, who will be able to contribute to socio-emotional improvement and personal development of their students. Particularly, musical experiences could be a valuable resource for secondary teachers, since music is important in adolescents' lives and can be an interesting tool for meeting their emotional needs [ 59 ]. This is supported by Kokotsaki and Hallam [ 60 ], who consider that performing music helps students feel like active agents of a group, develop a strong sense of belonging, gain popularity, make "like-minded" relationships, improve their social skills and foster a strong sense of self-esteem and satisfaction.

This study shows that experiencing with various unknown musical pieces can have positive effects on emotions. According to this finding, university professors of Teaching grade in music education should encourage future teachers to experience various musical styles, rhythms and tonalities, avoiding prejudices. Thereby, future music teachers will be able to use a diversity of musical experiences that broaden the emotional effects and fulfill the socio-emotional function of music education. In relation to Fredrickson's 'broaden‐and‐build' framework of positive emotions [ 30 ], music can become a mean of widening other positive emotional states, constructing personal resources and transforming people, and contribute to an upward spiral of positive emotions. Taking into account the underlying psychological mechanisms of the impact of music on the emotional states it will be possible to use it to improve emotional area and other aspects of the personal sphere, as Chang et al., [ 10 ] maintain. Therefore, music education is an important resource to improve the emotional development of students.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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We should like to express our gratitude to the Valencia University student teachers for their disinterested and valuable contribution to this study.

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José Salvador Blasco-Magraner, Pablo Marín-Liébana & Ana María Botella-Nicolás

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• Published: 24 June 2019

Effects of Relaxing Music on Healthy Sleep

• Maren Jasmin Cordi 1 , 2 ,
• Sandra Ackermann 1 &
• Björn Rasch   ORCID: orcid.org/0000-0001-7607-3415 1 , 2  

Scientific Reports volume  9 , Article number:  9079 ( 2019 ) Cite this article

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• Human behaviour
• Quality of life

Sleep is vital for human health and wellbeing, and sleep disturbances are comorbid to many mental and physiological disorders. Music consistently improves subjective sleep quality, whereas results for objective sleep parameters diverge. These inconsistencies might be due to inter-individual differences. Here, 27 female subjects listened to either music or a control text before a 90 minutes nap in a within-subjects design. We show that music improved subjective sleep quality as compared to the text condition. In all participants, music resulted in a reduced amount of sleep stage N1 during the nap. In addition, music significantly increased the amount of slow-wave sleep (SWS) and increased the low/high frequency power ratio. However, these effects occurred only in participants with a low suggestibility index. We conclude that listening to music before a nap can improve subjective and objective sleep parameters in some participants.

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Introduction.

Sleep plays an important role for maintaining physical and mental health 1 , 2 , 3 , 4 , 5 , and is critical for general well-being 6 , 7 . However, sleep disturbances are highly common in our society 8 , with increased prevalence in ageing 9 as well as among people at risk of or suffering from a psychiatric disorder 10 . The use of sleep enhancing medicine is problematic, as its effectiveness decreases across time and may lead to addiction. Consequently, researchers need to empirically validate the effectiveness of non-pharmacological and easy to implement tools to support healthy sleep.

Listening to music is a widely used tool to improve sleep. In an online survey in a general population 62% (out of n = 651 respondents) stated to have at least once used music to help them sleep 11 . In a survey in over 500 patients with sleep disorders, over 50% reported to use music as sleep aid 12 . In a meta-analysis based on six included studies in a total of 314 patients, Jespersen and colleagues reported that music helped to improve subjective sleep quality in insomnia patients 13 . Similarly, sedative music while resting could effectively improve subjectively rated sleep in patients with sleep complaints 14 . In 20 included trials, another meta-analysis showed positive effects of music based interventions before bedtime on PSQI scores, sleep onset latency and sleep efficiency in patients suffering from primary insomnia 15 . Positive effects of listening to music on subjectively evaluated sleep were found in toddlers when listening throughout the naptime, preschool children and young adults listening 45 minutes at naptime and/or bedtime 16 , 17 , 18 . Also in older women, two further studies reported shorter sleep onset time, less nocturnal awakenings and better sleep quality and satisfaction as measured with a questionnaire and sleep logs when listening to music when going to bed 19 , 20 . In sum, the positive effects of listening to music on subjective ratings of sleep quality are well established across different age groups including both healthy participants and patients.

In contrast to subjective sleep quality, empirical findings on the effects of music on objectively measured sleep are scarce and inconsistent. For example, Lazic and Ogilvie 21 did not find differences in polysomnographic measures when subjects in a within design either listened to music, tones or neither tones nor music after lights off until continuous sleep was observed. Similarly, Chang et al . 22 did not observe any positive effects of music playing when lying in bed on objective measures of sleep onset, total sleep time, sleep interruption and sleep efficiency, in spite of positive effects of music on subjective sleep quality. Only Chen et al . 23 reported effects of music on objective sleep parameters: One hour of listening to music after subjects went to bed significantly decreased the amount of stage N2 sleep, and increased deep SWS only in a subgroup of participants with long sleep latencies. However, further, more fine grained analyses of sleep-related oscillations are missing in this study. This paper points towards the possibilities that the effects of music on objective sleep parameters might depend on certain individual differences.

One possible factor being involved in individual differences in the effects of non-pharmacological interventions on objective sleep may be suggestibility. Suggestibility describes the ability of a person to respond to suggestions in terms of perceptual, cognitive, neural and bodily processes 24 . Suggestibility accounts for strong individual differences in the effects of hypnotic interventions, but also outside of hypnosis, like for instance “placebo” effects 25 (but see 26 ). Also, a suggestion to not attribute meaning to Stroop words reduced the Stroop effect in highly suggestible subjects irrespective of whether a hypnotic state was established before or not 27 . It was even shown that suggestions impact on memories, beliefs and behaviors 28 . In a series of studies 29 , we have shown that hypnotic suggestion to sleep deeper increases deep SWS and slow wave activity (SWA) in high suggestible healthy participants. No enhancement of SWS was observed for low suggestible females. A similar pattern of results occurred in a conceptual replication of this study in elderly women 30 . As we here applied the same study design as in those previous experiments, we were interested if the effect of music on sleep also depends on expectations and self-suggestions. We expect that the effect of music on objective sleep parameters and sleep related oscillations in the electroencephalogram (EEG) is stronger in high vs. low suggestible participants.

In the current study we tested if listening to music as compared to a spoken text before a midday nap improves sleep quality in high vs. low suggestible females. We measured sleep objectively using polysomnography. The experimental design was identical to our previous studies on the effects of hypnotic suggestions on sleep, except that a musical piece instead of the standardized hypnotic suggestion was used. The musical piece was composed by Dr. Lee Bartel for promoting sleep, called “Drifting into Delta”track 2 , 31 . It was pre-selected in a pilot study due to its best effects on subjective ratings of sleep quality. As it is supposed to induce deep sleep through its frequencies of 0.01–2 Hz we also analyzed brain activity during listening to the sound. To foster the role of subjective expectations and beliefs, subjects were explicitly informed that the music composition used was specifically designed to deepen sleep. Consequently we also assumed to find increased low and reduced high frequency EEG activity during the nap following the music condition. In order to test possible consequences of altered sleep on cognitive performance, we additionally introduced memory tests before and after the nap.

Subjective sleep measures

As expected from previous studies, subjects reported better subjective sleep after music (3.69 ± 0.16, scale from 1 to 5) as compared to the control text (3.28 ± 0.18) as indicated by a significant main effect of sound on the dependent variable subjective sleep quality ( F (1, 24) = 4.36, p  = 0.048, eta 2  = 0.15). The interaction with suggestibility did not reach significance ( p  = 0.15).

Objective sleep measures

For objective measures of sleep architecture, only one parameter revealed a significant effect: Listening to music before the 90 min nap decreased the time spent in N1 sleep (6.13 ± 0.73 min) as compared to the control condition (8.00 ± 0.78 min, main effect sound: F (1, 25) = 5.39, p  = 0.029, eta 2  = 0.18, see Fig.  1A ). In all other sleep stages, the main effect of sound was non-significant (all p  ≥ 0.15 see Table  1 ). Additionally, we observed a significant interaction between the type of sound and suggestibility on SWS increase (where the amount of SWS in the control condition was set to 100%): In low suggestibles, music increased the percentage of SWS by +46.18% ( p  = 0.035), whereas a non-significant reduction of SWS (−9.84%, p  = 0.60) occurred in high suggestible participants (interaction F (1, 25) = 4.37, p  = 0.047, eta 2  = 0.15), See Fig.  1B . In absolute values, low suggestibles spent 31.35 ± 3.83 min in SWS after listening to music as compared to 20.58 ± 3.58 min after listening to the control text ( p  = 0.027). In contrast, no difference in time spent in SWS occurred for high suggestible participants (23.11 ± 3.50 min vs. 23.86 ± 4.27 min, for music vs. control condition, p  = 0.89). Both results were not affected when considering that during listening to music, 9 low and 11 high suggestible subjects fell asleep while 4 low and 3 high suggestibles did not (all p  ≥ 0.25 for this factor).A chi-square test comparing the number of subjects falling asleep and suggestibility was non-significant (Chi 2 (1) = 0.31, p  = 0.58). During listening to the text, 11 low and 11 high suggestibles fell asleep, while 2 low and 3 high suggestibles did not (Chi 2 (1) = 0.69, p  = 0.16).

Effect of music on sleep stages. ( A ) Both groups benefitted from reduced minutes spent in N1 after music compared to text condition. The within-group comparison was significant only for low suggestible subjects. ( B ) The interaction between sound and suggestibility in SWS increase was driven by low suggestibles showing a higher increase in SWS after music compared to text while high suggestibles did not benefit from music. The x-axes distinguish low (LS) and high suggestible (HS) subjects. The graphs show the values for N1 minutes and SWS increase in percent in the text (black bar) and music condition (grey bar). Asterisks indicate p values ≤ 0.05. Mean + /− standard errors of the mean (SEM) are displayed.

Additionally, the interaction between sound and suggestibility for REM sleep was significant ( F (1, 25) = 6.39, p  = 0.018, eta 2  = 0.20), as demonstrated in Table  1 . However, only few participants had actually reached REM sleep (high suggestible: 9 vs. 4 participants after music vs. text, low suggestibles: 3 vs. 5 participants). Although the Chi-square for a difference from an equal distribution was not significant ( p  > 0.15), we refrained from further analyses of this finding due to the very low sample size in this analysis.

Please note that differences in total sleep time (see Table  1 ) might rather be a product of divergent sleep latencies as time in bed was limited to 90 minutes. In general, high suggestible participants spent more time in N2 sleep and were less time awake after sleep onset as compared to low suggestibles (both p  = 0.05, see Table  1 ).

Poweranalyses during non-REM (NREM) sleep

For a more fine grained analysis of the effects of music on sleep, we compared power of sleep-related brain oscillations during NREM sleep stages N2 and SWS between the music and the control condition. The analyses were conducted using repeated measure ANOVAs with within-subject factors FCP (frontal, central, parietal), hemisphere (right vs. left) and type of sound (music vs. text) and between-subjects factor suggestibility (high vs. low). Total power (i.e., 0.5–50 Hz) did not differ significantly between the two experimental sessions ( p  > 0.16). Therefore, the poweranalyses are based on the absolute muV values in the single frequency bands.

We focused on the ratio between low and high frequencies during NREM sleep, as this marker has been discussed as indicator for restorative sleep (SWA divided by beta activity, see 32 and 33 ). Higher values thus mean a higher proportion of low than high frequency power in the signal during NREM sleep and might be associated with more restorative sleep. Music significantly increased the low/high frequency ratio during sleep as compared to the control text only in low suggestible subjects (interaction: F (1, 25) = 5.72, p  = 0.025, eta 2  = 0.19). The post-hoc t-test showed a significantly higher ratio after music (154.07 ± 32.69) than after text (89.67 ± 15.46), t (12) = −2.45, p  = 0.031), while this difference was non-significant in high suggestible subjects ( p  = 0.65). The effects were wide-spread across the whole scalp, see Fig.  2 , upper panel, although the ANOVA indicated that this interaction was dependent on localization (three-way interaction between sound, suggestibility and FCP F (2, 50) = 3.90, p  = 0.027, eta 2  = 0.14). Following up on this revealed that in high suggestibles, FCP * sound was non-significant ( p  = 0.64), while the interaction was significant in low suggestible subjects ( F (2, 24) = 3.40, p  = 0.05, eta 2  = 0.22. Here, all post-hoc tests were significant and showed a higher ratio in frontal ( t (12) = 2.25, p  = 0.044), central ( t (12) = 2.57, p  = 0.024) and parietal electrodes ( t (12) = 2.71), p  = 0.019). All other effects with sound or suggestibility in this ANOVA were non-significant ( p  > 0.06).

Power analyses during NREM sleep. Displays t-values of the analyses on SWA/beta Ratio (upper panel) and Sigma power (lower panel). The 1 st column shows comparisons on music versus text in low suggestibles, while higher values indicate higher power after music. The 2 nd column shows the results of the same analysis for high suggestibles. The 3 rd column indicates results of the group comparison high versus low suggestibles on the difference music – text. Positive values mean higher power value differences in low compared to high suggestibles. Significant electrodes (non-corrected for multiple comparisons) are indicated with white dots.

Analyzing SWA alone revealed a trend in the interaction between suggestibility and sound ( F (1, 25) = 3.37, p  = 0.08, eta 2  = 0.12). No other main effects or interaction with those two factors were significant (all p  > 0.10). When only investigating SWA in SWS this pattern remained. Please note however, that in this analysis 2 low suggestible subjects had to be excluded as they did not show SWS in one of the sessions. Examining beta power alone revealed a significant three-way interaction between sound, suggestibility and FCP ( F (2, 50) = 6.55, p  = 0.003, eta 2  = 0.21). While in high suggestibles, beta power did not differ depending on sound ( p  > 0.80) or FCP* sound ( p  > 0.10), a main effect of sound ( F (1, 12) = 5.46, p  = 0.038, eta 2  = 0.31) and its interaction with FCP ( F (2, 24) = 4.56, p  = 0.021, eta 2  = 0.28) were found in low suggestibles. After listening to music, beta power was lower in low suggestibles (0.59 ± 0.09) than after text (0.67 ± 0.08). This difference was most pronounced in frontal electrodes ( t (12) = −2.55, p  = 0.026)) and central electrodes ( t (12) = −2.26, p  = 0.043) and not significant in parietal area ( t (12) = −1.99, p  = 0.070)).

We did neither find effects of sound in theta nor in alpha power (all p  > 0.20).

Interestingly, power in the sigma band was reduced after music (1.19 ± 0.09) compared to the text condition (1.26 ± 0.10), F (1, 25) = 6.06, p  = 0.02, eta 2  = 0.20. The interaction between sound and suggestibility was a trend ( F (1, 25) = 3.90, p  = 0.06, eta 2  = 0.14) and further specified by the three-way interaction between sound, FCP and suggestibility ( F (2, 50) = 6.20, p  = 0.004, eta 2  = 0.20). In low suggestibles, sigma band power was higher in frontal and central electrodes after text compared to music ( t (12) = −2.69, p  = 0.02 and t (12) = −2.31, p  = 0.04, respectively), while in high suggestibles, all direct comparisons were non-significant (all p  > 0.20), see Fig.  2 , lower panel. All other effects were non-significant (all p  > 0.20). Due to significant effects in the power range of spindle activity, we analyzed number and density of spindles during NREM sleep. All effects were however non-significant (all p  > 0.20, see Table  1 ). When restricting the analysis to frontal slow spindles, low suggestibles had descriptively reduced spindle density after music listening (3.02 ± 0.49) as compared to the control text (3.37 ± 0.60). However, the interaction between sound and suggestibility was not significant ( p  > 0.20). Also no significant main effects occurred ( p  > 0.07, see Table  1 ). The number of slow spindles also revealed no significant results ( p  > 0.50). All effects of density and number of parietal fast spindles were p  > 0.50.

Cardiac responses and poweranalyses during listening

As low suggestible participants profited more from relaxing music, it might have been possible that music induced stronger responses on the autonomic and central nervous system already during the listening period. In the ANOVA with sound and suggestibility on heart rate during listening, the interaction was not significant ( p  > 0.80). Also, neither the main effect of sound nor suggestibility reached significance (both p  > 0.60). Similarly, during subsequent sleep, heart rate did neither differ depending on sound ( p  = 0.44), suggestibility ( p  > 0.70) nor sound * suggestibility ( p  > 0.60).

With respect to the power analysis of EEG activity during listening, we restricted our analysis to epochs during listening, in which the subjects were awake. Thus, all epochs containing stage N1 or stage N2 were excluded.

In this analysis, we observed a significant three-way interaction between sound, suggestibility and hemisphere for the SWA/beta ratio ( F (1, 25) = 4.79, p  = 0.038, eta 2  = 0.16). In low suggestibles, the main effect of sound and all its interactions were p  > 0.08 with non-significantly higher values during music than sound. In high suggestibles all follow-up tests were p  > 0.20. The same pattern was true for the four-way interaction with FCP ( F (2, 50) = 4.21, p  = 0.020, eta 2  = 0.14) and its follow-up tests (all p  > 0.06 in low and p  > 0.30 in high suggestibles). All main effects and interactions with sound or suggestibility were p  ≥ 0.09 in the alpha and p  > 0.10 in the theta and sigma band (see the Supplementary Material for the results of the power analyses of the entire listening period).

Cognitive tasks

To investigate effects of altered sleep pattern on post-nap cognitive performance, we included vigilance task after sleep. Here, performance was equal in both groups and after both conditions concerning reaction times, number of reactions and error rate ( p  > 0.09). Thus, attentional processes after sleep did not differ dependent on condition.

Also, we measured memory consolidation across sleep by presenting paired associate learning task (PAL) before and after the nap. For this parameter, a main effect of sound ( F (1, 24) = 4.45, p  = 0.05, eta 2  = 0.16) demonstrated that maintenance of memory performance across sleep was higher after listening to the text (99.89% ± 1.24) than across sleep after listening to music (94.95% ± 1.61). The other effects were p  > 0.10. PAL performance across sleep with presleep memory set to 100% were 96.00 ± 1.87% after music and 101.25 ± 2.09% after text in low suggestibles and 94.04 ± 2.56% after music and 98.72 ± 1.46% after text in high suggestibles. Both differences were p  > 0.10. The difference between PAL performance across nap after listening to music vs. text did not correlate with the difference in any sleep stage (all p  > 0.15, uncorrected) nor subjective sleep quality ( p  > 0.20), nor the difference in any power band (all p  > 0.10, uncorrected).

Here we tested if listening to relaxing music before a nap helps improving subjective and objective sleep quality of a nap in young healthy females. Our results showed a generally improving effect of listening to music on subjectively rated sleep quality. Subjects reported better sleep quality after having listened to music compared to listening to a control text. This is in line with previous studies showing beneficial effects of music on sleep ratings 14 , 18 . While subjective sleep is highly relevant for experienced wellbeing and the diagnosis of for instance insomnia, it does not necessarily correspond to objective sleep measures. We hence additionally measured sleep with polysomnography and compared sleep patterns after listening to music to sleep patterns after listening to a control text. Objectively, subjects spent less time in the sleep/wake transition phase N1 after music compared to the text condition. More fine-grained analyses showed that power in the sigma band (11–15 Hz) was also reduced during NREM sleep in the nap after listening to music versus listening to a text. Thus, overall, it can be concluded that listening to relaxing music before a nap can reduce time spent in N1 and the power of high frequency bands.

As we have seen in previous studies on the effect of hypnotic suggestions on a nap in healthy young and older females, it was important to consider subjects’ suggestibility. This measure indicates how sensitive subjects react to suggestions given externally. Concerning hypnosis, only those who were responsive for suggestions benefitted from the verbal, hypnotic intervention. To investigate whether suggestibility is also a relevant factor when testing the effect of music on sleep, we included this additional factor. We found that low suggestible subjects benefited from an increase in the amount of SWS of about 46% compared to their sleep after listening to the text. Whether this increase was to the detriment of the amount of REM sleep cannot be answered in this study due to a very limited amount of subjects reaching REM sleep at all during this nap. Additionally, as this was only a nap study we cannot make substantiated statements concerning REM sleep which usually takes place late in a sleep epoch. To confirm a possible trade-off between SWS and REM sleep the study should follow a nighttime design.

Also in a more fine grained analysis of oscillatory power bands during sleep, the level suggestibility significantly altered the effects of music. As studies have shown that insomniacs often experience low sleep quality when a high amount of high frequency penetrates their sleep 33 , 34 , we expected reduced high and increased low frequency power after listening to the relaxing music before sleep. A ratio quantifying the proportion of high and low frequency power in the NREM signal was calculated by dividing SWA power by beta power. Thus, higher values indicate a higher proportion of low compared to high frequencies in the signal. Low values had been referred to as an indication of worse sleep quality 32 , 34 and less restorative sleep 35 . Here we found higher SWA/beta ratios during sleep after listening to music than after listening to the text in low suggestible subjects. No changes were observed in high suggestible participants. These results using objective sleep data suggest that low suggestibles might have experienced a more restorative sleep after listening to music.

In spite of more restorative sleep, sigma power in frontal and central brain regions during sleep was significantly reduced in low suggestibles after listening to music. However, we did not observe a reduction in sleep spindles in this condition, in spite of the reduction in sigma power. Previous studies have reported changes in spindle density without changes in sigma power (e.g. 36 ), while here we report the opposite case. A possible explanation is that music reduces more long-lasting sigma power in low suggestible which might be unrelated to discrete sleep spindles (lasting maximal 3 seconds).

Interestingly, memory consolidation across the sleep interval was significantly reduced after listening to music as compared to the control text in the entire sample. The reduction in memory is particularly puzzling, because listening to non-verbal music after learning should induce less interference than the verbal control text. As SWS has been implicated in processes of memory consolidation during sleep 37 , 38 , increases in SWS and SWA /beta ratios in low suggestible participants should have led to improvements in declarative memory consolidation during sleep in low suggestible participants. It might be possible that the impairment in memory consolidation is related to the general reduction in sigma power in the music condition, as sleep spindles have suggested to be a critical factor for successful consolidation of memories during sleep 39 . However, as discrete sleep spindles were not altered by music in our study and changes in sigma power did not correlate with changes in memory performance, this possibility remains highly speculative and requires further examination. Note that memory consolidation was also not improved in spite of increases in SWS and SWA after hypnotic suggestions in high suggestibles in our previous studies 29 , 30 . In sum, low suggestibles benefitted more from relaxing music for their nap than high suggestibles. This is contrary to what we expected, as usually, a high level of suggestibility indicates more pronounced behavioral reactions to suggestions or expectations. Here we briefed the subjects about our expectations to find improved sleep after music compared to text. High suggestibles would have rather expected to be positively influenced by this information. However, also mere expectations without hypnotic induction did not lead to SWS increase in our nap study 29 . This suggests that high suggestibles show greater effects when the procedure is framed as hypnosis and a hypnotic induction actually takes place. On the contrary, low suggestibles seem to prefer non-verbal relaxation to hypnotic suggestions. This might result from a concern of being manipulated by direct and concrete instruction when being confronted with a spoken text. Under this assumption it could be even more effective to increase self-control by for instance letting subjects choose their own music. Trahan et al . (2018) discussed that familiar, self-chosen in contrast to given music might be less analgesic and anxiolytic 11 . These authors showed that particularly subjects with musical engagement use music to improve sleep. In our data, the distribution of subjects playing an instrument did not differ between high and low suggestible subjects. However, it might have possibly required a more precise measure of familiarity with music to test this assumption. Besides, effectiveness of a sleep-related intervention depends on whether sleep destabilization is triggered by psychological (i.e. mood, thoughts) or physical (i.e. arousal) factors. Being explicitly and verbally guided by hypnotic suggestions could thus be more expedient when rumination must be stopped while reducing physical tension could be better achieved by a more indirect and open form of relaxation intervention. Unfortunately, we did not measure those aspects in our sample to test group differences in this respect. Cardiac responses during the listening period and brain activity during wakeful listening remained unaffected. Probably, a combination of both, suggestions shaded with relaxing music could be beneficial for both needs and thus, all subjects could improve their sleep.

The importance of focusing on subjective and objective measures when investigating effects of any intervention on sleep was demonstrated by the fact that in neither of the groups the ratio or the amount of SWS was correlated with subjective sleep quality rating. Possibly separate mechanisms affect subjective and objective measures leading to converging results.

In sum, here we show that subjective sleep quality in young healthy females’ naps can be improved by relaxing music to some extent. Music reduced time spent in N1 and arousing high frequency power during following NREM sleep while leading to improved subjective sleep quality. This method seemed to be particularly beneficial for subjects low in suggestibility, although this conclusion should be tested critically in further studies and possible other confounding factors should be considered. Taken together, our results support the conclusion that music is a non-pharmacological, low-risk and low– cost tool to improve sleep on a subjective and objective level. To what extent this is applicable to sleep disturbances cannot yet be answered.

Thirty-two healthy, right-handed women (19–35 years, mean age 23.81, SD = 4.28) participated. To avoid gender effects we excluded males. Three subjects had to be excluded due to lacking sleep in one of the sessions, reporting naps in the week before the experiment or heavy cough during the session. In two subjects suggestibility could not be measured, one subject did not correctly understand the declarative memory test and was excluded in that analysis. The final sample consisted of 27 subjects (aged 23.22 ± 3.85 years). Ten of them indicated to play an instrument (equally distributed between high and low suggestibles, Chi squared p  = 0.29), four indicated to practice any kind of relaxation exercise. The subjects were German natives or had advanced German skills. They did neither regularly take naps, nor suffer from a diagnosed sleep disorder nor consume drugs. Hormonal contraceptives were allowed. None did shift work or intercontinental flights within 6 weeks before participation. For the experimental days they were asked to refrain from caffeine and alcohol, get up between 7 and 8 a.m. and to not do any sports until the session. Subjects received oral and written study information and gave their written informed consent before participation. They were paid 140 CHF for full participation. The Ethic Committee of the University of Zurich approved the study and the experiment was performed in accordance with the existing regulations.

The study consisted of four sessions. In the introduction group session, the study flow and its purpose were explained. We explicitly mentioned the expectation that music should improve sleep quality. Besides, questionnaires assessed sleep quality, demographic data and suggestibility. In the second session, subjects took a nap in the sleep laboratory to become familiar with the setup and sleep environment. The sleep diary was handed out to record sleep behavior in the week before the first experimental session. The experimental sessions took place at the same day of the week, separated by one week and started at 1 p.m. After performing the paired associate task and the finger tapping task, subjects went to bed. Depending on randomization, either music or the control text was presented via loudspeakers from the bedside cabinet when subjects lay in bed directly after switching the lights off. Participants were allowed to fall asleep at any time, but asked to listen to the sound. Listening and nap were recorded for a total of 90 minutes with polysomnography (PSG). Subjects were awakened 90 minutes after switching the lights off and asked to fill out the sleep quality questionnaire and perform again on the memory tasks. After each session, the sleep diary for the upcoming week was handed out.

Audio recordings

Music: Before the experimental naps, subjects either listened to a music tape or a spoken text. The selection of the musical piece was performed in a pilot study: Five 15 minutes-pieces of music, composed to induce sleep, were selected according to internet evaluations (google, youtube, amazon). Fifteen subjects listened to this selection before falling asleep and rated the tapes the next morning. According to subjectively reported enhancement of sleep quality, shortened sleep latency and better recovery, the best rated tape was chosen for the study. It was a piece composed by Dr. Lee Bartel for promoting sleep, called “Drifting into Delta”track 2 , 31 . It is supposed to induce deep sleep through its frequencies of 0.01–2 Hz, based on treatises on the influence of auditory pulsing of 0.25 to 2 Hz frequencies on oscillatory coherence 40 . Please find the spectrogram displaying the contained frequencies in the Supplementary Material. The series “Music to Promote Sleep” out of which we took this piece was tested before in patients suffering from fibromyalgia and showed positive effects on subjective sleep quality 41 .

Text: The text in the control condition was taken from Cordi et al . 29 and was a documentary about mineral deposits. A text was chosen as control to exclude a simple effect of listening. It was spoken by a male voice in normal speed and intonation.

Both tapes played for about 14 minutes. They were presented at a volume of 45–50 dB through loudspeakers before falling asleep. The order was determined randomly across subjects. Before playing the sound we instructed the subjects to relax and to get themselves into the tape, trying to let pass any thoughts that might come up and to not stuck on them. Subjects were allowed to fall asleep whenever possible.

Questionnaires

Standardized Sleep Inventory for the Assessment of Sleep – Revised Version, SFA – R: It assesses subjectively reported sleep behavior within the last sleep period (adapted to a nap here) on several dimensions 42 . As a measure for subjective sleep quality we analyzed the mean of an item asking to rate the previous sleep on 7 adjectives. We excluded the adjective “extensive” as the nap was limited in time by protocol. Higher values indicate better ratings. Data of one subject is missing.

Pittsburg Sleep Quality Index, PSQI: The PSQI measures general subjective sleep quality within the last month 43 . The global score ranges from 0 to 21, while 5 is the cutoff value for sleep difficulties. Overall, the sample scored 4.41 ± 2.26 ranging from 1 to 10 (5 subjects scoring >5). High and low suggestible subjects did not differ on this score ( p  = 0.83).

Sleep diary: To control sleep behavior one week before each of the experimental sessions, a sleep diary was used. We used the information about the wake up time to verify that subjects got up between 7 and 8 a.m. on experimental days.

Harvard Group Scale of Hypnotic Susceptibility, Form A, HGSHS: A: This is a widely used, standardized tool to determine hypnotic suggestibility 44 . After listening to a tape with a recorded hypnosis, subjects are confronted with a questionnaire on their experiences during listening. According to their rating about how strongly they had reacted to the given suggestions, they were grouped as high (score 7 or higher, mean = 8.50 ± SD = 1.23, n = 14) or low suggestible (scores 0–6, mean = 4.85 ± 1.21, n = 13). The groups differed significantly on those means, t (25) = −7.78, p  < 0.001, but not on age ( p  > 0.50).

Memory measures

Word pair associate learning task, PAL: In this episodic memory task, subjects are asked to remember as many of the presented word pairs as possible for a later cued recall 45 . The words are presented consecutively in EPrime in black font on a white computer screen. After a 500 ms fixation cross, the first word of the pair was presented for 1000 ms, followed by a blank interval of 200 ms separating it from the according second word of the pair. Another blank interval of 500 ms was displayed before the next fixation cross separating the previous from the following word pair. During cued recall, the first word of the pair was displayed until the subject remembered the according second word or indicated that it was forgotten. No feedback was given. The order during recall was different from the order during learning, but stable across subjects. Recall was tested directly before the nap and afterwards in the same order. Memory performance was defined as the number of correctly recalled words after sleep relative to the presleep performance which was set to 100%.

The procedural memory task and its results are reported in the Supplementary Material.

Psychomotor vigilance task (PVT): To overcome sleep inertia and to control for possible attentional differences before the memory tests after the nap, a vigilance task was applied. Subjects were confronted with a black screen on which a timer started to count upwards at unforeseen times. As soon as this was recognized, subjects were asked to press the space bar. Error rate and reaction time were analyzed.

Sleep recordings, scoring and EEG data processing

Sleep was measured with the Geodesic EEG System 400 series (Electrical Geodesics, Inc.) including high density electroencephalogram (EEG) with 128 electrodes, electromyogram (EMG), electrooculogram (EOG) and electrocardiogram (ECG). Data was collected with a sampling rate of 500 Hz, impedances were kept below 50 kΩ. Data was filtered and scored according to the criteria of the American Association of Sleep Medicine (AASM) (i.e., 0.1 Hz lowpassfilter, 35 Hz highpassfilter). Three coworkers blind to condition scored the data at the electrodes F4, C4, P4, O2, HEOG, VEOG and EMG. In case of disagreement, a forth blind scorer was consulted.

Power analyses were based on Fast Fourier Transformations (FFT). During data preprocessing we excluded the electrodes on the outer edge of the EEG cap (i.e. electrode numbers 17, 48, 49, 56, 63, 68, 73, 81, 88, 94, 99, 107, 113, 119, 125), filtered the data between 0.1 and 50 Hz and applied a 50 Hz Notch Filter. We re-referenced data to the average of both mastoids. The signal that was recorded while the music and the control file were presented was segmented into epochs of 4096 data points (~8 seconds) with an overlap of 409 points to account for the later applied Hamming-window of 10% and semi-automatically corrected for artefacts within the wake periods in the 14 minutes in which subjects listened to the tape. The same was done for segments scored as NREM sleep. Afterwards, the FFT was calculated with a Hamming-window of 10% and a resolution of 0.2 Hz. From this analysis, we exported the power in the respective areas (muV*Hz) for slow-wave activity, SWA (0.5–4.5 Hz), theta (4.5–8 Hz), alpha (8–11 Hz), sigma (11–15 Hz), beta (15–30 Hz) and the total power (0.5–50 Hz). Similarly to Krystal 32 and Maes et al . 33 we focused on the ratio between low and high frequencies during NREM sleep as an indicator for restorative sleep. SWA power was divided by beta power and hence higher values would indicate slowing of the EEG activity.

For the analyses on spindle density, we selected the derivations Fz, Cz and Pz for the analysis of the spindles across all sleep stages. On those, we performed a frequency extraction for frequency power of 11–15 Hz and added Spindle on and off markers to identify its on- and offset. Before automatic artifact correction detecting a maximal allowed difference of 200 muV within 200 ms in the EMG channel, we segmented the data into 1024 data point wide epochs (~2 seconds). Spindle events were counted for which the power signal exceeded a fixed threshold (±10 muV) for an interval lasting 0.5–3 sec. We extracted the amount of detected spindles (=spindle count) in those epochs separately for each sleep stage and separately for fast (13–15 Hz) and slow spindles (11–13 Hz). We then calculated spindle density per 1 minute within each sleep stage, also within NREM sleep (N2 + N3).

Heart rate: We analyzed electrocardial data with Kubios HRV Version 3.1 2. We first ran an automatic artifact correction on the unfiltered data that eliminated ectopic beats and artifacts based in dRR series. Afterwards, we excluded further visually detectable artifacts resulting from e.g. movements. Mean heart rate (HR) was measured for the time in which the subjects listened to the tapes and the following sleep episode separately. We could include all except 2 subjects for who the signal was too bad in one of the two sessions (1 low, 1 high suggestible).

Statistical analysis

The study followed a crossover design with a within-subjects comparison of the two naps. Data was analyzed using SPSS 23. The repeated measures analysis of variance (ANOVA) included the within subjects factor “sound” (music versus text) and the between subjects factor “suggestibility” (high versus low). When the Mauchly-Test was significant, we adapted values with Greenhouse-Geisser. We also adapted values when the Levene Test indicated uneven variances. Only the significant main effects and interactions were further investigated using paired samples t-tests according to Fisher’s protected LSD test. The level of significance was set to p  = 0.05.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Loredana Lucartuorto for helping to setup and design the study and to lead the pilot study. We thank Carmen Hättenschwiler, Noemi Marti Georg Rahn and Raphael Zeltner for helping to collect data. Grant information: This study was supported by a grant from University of Zurich Clinical research priority project “Sleep and Health” and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 677875).

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All authors designed the experiment, S.A. led data collection, M.C. analyzed the data, all authors wrote the manuscript.

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Correspondence to Björn Rasch .

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Cordi, M.J., Ackermann, S. & Rasch, B. Effects of Relaxing Music on Healthy Sleep. Sci Rep 9 , 9079 (2019). https://doi.org/10.1038/s41598-019-45608-y

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DOI : https://doi.org/10.1038/s41598-019-45608-y

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