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Understanding the Influence of Music on Emotions: A Historical Review

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Kimberly Sena Moore, Understanding the Influence of Music on Emotions: A Historical Review, Music Therapy Perspectives , Volume 35, Issue 2, October 2017, Pages 131–143, https://doi.org/10.1093/mtp/miw026

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Music has long been thought to influence human emotions. There is significant interest among researchers and the public in understanding music-induced emotions; in fact, a common motive for engaging with music is its emotion-inducing capabilities ( Juslin & Sloboda, 2010). Traditionally, the influence of music on emotions has been described as dichotomous. The Greeks viewed it as either mimesis , a representation of an external reality, or catharsis , a purification of the soul through an emotional experience ( Cook & Dibben, 2010). This type of dichotomous viewpoint has persisted under various labels, such as formalist versus absolutist, and referential versus expressionist ( Meyer, 1956). However, these perspectives all emerged from musicology. Outside musicology, the scientific study of emotions was intermittent and, until recently, references to music’s effect on emotions were rare ( Sloboda & Juslin, 2010). Since the 1990s, there has been increased interest in studying music-induced emotions, particularly in psychology ( Juslin & Sloboda, 2010). This interest extends to the music therapy profession as well. For example, a professional music therapist in the United States is required to be able to develop and implement music therapy experiences designed to focus on emotion-related treatment goals, such as the ability to empathize, and the client’s overall affect, mood, and emotions ( Certification Board for Music Therapists [CBMT], 2015), and must apply knowledge of music-based emotional responses ( American Music Therapy Association [AMTA], 2013). Given the increased interest in psychology and the clinical implications for the music therapist, it seems timely to analyze and reflect on how the understanding of music-induced emotions has evolved in order to support current and future research and clinical practice. As current understanding is built upon prior knowledge, a historical review can serve to examine previous directions and help inform future study ( Hanson-Abromeit & Davis, 2007). Thus, the purpose of this inquiry was to provide a historical overview of prominent theories of music and emotion and connect them to current understanding. More specifically, the objectives were:

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ORIGINAL RESEARCH article

Emotional responses to music: shifts in frontal brain asymmetry mark periods of musical change.

• 1 School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
• 2 Institute for Systematic Musicology, University of Hamburg, Hamburg, Germany
• 3 Monash Biomedical Imaging, Monash University, University of Newcastle, Newcastle, NSW, Australia
• 4 Centre for Positive Psychology, Graduate School of Education, University of Melbourne, Melbourne, VIC, Australia

Recent studies have demonstrated increased activity in brain regions associated with emotion and reward when listening to pleasurable music. Unexpected change in musical features intensity and tempo – and thereby enhanced tension and anticipation – is proposed to be one of the primary mechanisms by which music induces a strong emotional response in listeners. Whether such musical features coincide with central measures of emotional response has not, however, been extensively examined. In this study, subjective and physiological measures of experienced emotion were obtained continuously from 18 participants (12 females, 6 males; 18–38 years) who listened to four stimuli—pleasant music, unpleasant music (dissonant manipulations of their own music), neutral music, and no music, in a counter-balanced order. Each stimulus was presented twice: electroencephalograph (EEG) data were collected during the first, while participants continuously subjectively rated the stimuli during the second presentation. Frontal asymmetry (FA) indices from frontal and temporal sites were calculated, and peak periods of bias toward the left (indicating a shift toward positive affect) were identified across the sample. The music pieces were also examined to define the temporal onset of key musical features. Subjective reports of emotional experience averaged across the condition confirmed participants rated their music selection as very positive, the scrambled music as negative, and the neutral music and silence as neither positive nor negative. Significant effects in FA were observed in the frontal electrode pair FC3–FC4, and the greatest increase in left bias from baseline was observed in response to pleasurable music. These results are consistent with findings from previous research. Peak FA responses at this site were also found to co-occur with key musical events relating to change, for instance, the introduction of a new motif, or an instrument change, or a change in low level acoustic factors such as pitch, dynamics or texture. These findings provide empirical support for the proposal that change in basic musical features is a fundamental trigger of emotional responses in listeners.

Introduction

One of the most intriguing debates in music psychology research is whether the emotions people report when listening to music are ‘real.’ Various authorities have argued that music is one of the most powerful means of inducing emotions, from Tolstoy’s mantra that “music is the shorthand of emotion,” to the deeply researched and influential reference texts of Leonard Meyer (“Emotion and meaning in music”; Meyer, 1956 ) and Juslin and Sloboda (“The Handbook of music and emotion”; Juslin and Sloboda, 2010 ). Emotions evolved as a response to events in the environment which are potentially significant for the organism’s survival. Key features of these ‘utilitarian’ emotions include goal relevance, action readiness and multicomponentiality ( Frijda and Scherer, 2009 ). Emotions are therefore triggered by events that are appraised as relevant to one’s survival, and help prepare us to respond, for instance via fight or flight. In addition to the cognitive appraisal, emotions are also widely acknowledged to be multidimensional, yielding changes in subjective feeling, physiological arousal, and behavioral response ( Scherer, 2009 ). The absence of clear goal implications of music listening, or any need to become ‘action ready,’ however, challenges the claim that music-induced emotions are real ( Kivy, 1990 ; Konecni, 2013 ).

A growing body of ‘emotivist’ music psychology research has nonetheless demonstrated that music does elicit a response in multiple components, as observed with non-aesthetic (or ‘utilitarian’) emotions. The generation of an emotion in subcortical regions of the brain (such as the amygdala) lead to hypothalamic and autonomic nervous system activation and release of arousal hormones, such as noradrenaline and cortisol. Sympathetic nervous system changes associated with physiological arousal, such as increased heart rate and reduced skin conductance, are most commonly measured as peripheral indices of emotion. A large body of work now illustrates, under a range of conditions and with a variety of music genres, that emotionally exciting or powerful music impacts on these autonomic measures of emotion (see Bartlett, 1996 ; Panksepp and Bernatzky, 2002 ; Hodges, 2010 ; Rickard, 2012 for reviews). For example, Krumhansl (1997) recorded physiological (heart rate, blood pressure, transit time and amplitude, respiration, skin conductance, and skin temperature) and subjective measures of emotion in real time while participants listened to music. The observed changes in these measures differed according to the emotion category of the music, and was similar (although not identical) to that observed for non-musical stimuli. Rickard (2004) also observed coherent subjective and physiological (chills and skin conductance) responses to music selected by participants as emotionally powerful, which was interpreted as support for the emotivist perspective on music-induced emotions.

It appears then that the evidence supporting music evoked emotions being ‘real’ is substantive, despite no obvious goal implications, or need for action, of this primarily aesthetic stimulus. Scherer and Coutinho (2013) have argued that music may induce a particular ‘kind’ of emotion – aesthetic emotions – that are triggered by novelty and complexity, rather than direct relevance to one’s survival. Novelty and complexity are nonetheless features of goal relevant stimuli, even though in the case of music, there is no significance to the listener’s survival. In the same way that secondary reinforcers appropriate the physiological systems of primary reinforcers via association, it is possible then that music may also hijack the emotion system by sharing some key features of goal relevant stimuli.

Multiple mechanisms have been proposed to explain how music is capable of inducing emotions (e.g., Juslin et al., 2010 ; Scherer and Coutinho, 2013 ). Common to most theories is an almost primal response elicited by psychoacoustic features of music (but also shared by other auditory stimuli). Juslin et al. (2010) describe how the ‘brain stem reflex’ (from their ‘BRECVEMA’ theory) is activated by changes in basic acoustic events – such as sudden loudness or fast rhythms – by tapping into an evolutionarily ancient survival system. This is because these acoustic events are associated with events that do in fact signal relevance for survival for real events (such as a nearby loud noise, or a rapidly approaching predator). Any unexpected change in acoustic feature, whether it be in pitch, timbre, loudness, or tempo, in music could therefore fundamentally be worthy of special attention, and therefore trigger an arousal response ( Gabrielsson and Lindstrom, 2010 ; Juslin et al., 2010 ). Huron (2006) has elaborated on how music exploits this response by using extended anticipation and violation of expectations to intensify an emotional response. Higher level music events – such as motifs, or instrumental changes – may therefore also induce emotions via expectancy. In seminal work in this field, Sloboda (1991) asked participants to identify music passages which evoked strong, physical emotional responses in them, such as tears or chills. The most frequent musical events coded within these passages were new or unexpected harmonies, or appoggiaturas (which delay an expected principal note), supporting the proposal that unexpected musical events, or substantial changes in music features, were associated with physiological responses. Interestingly, a survey by Scherer et al. (2002) rated musical structure and acoustic features as more important in determining emotional reactions than the listener’s mood, affective involvement, personality or contextual factors. Importantly, because music events can elicit emotions via both expectation of an upcoming event and experience of that event, physiological markers of peak emotional responses may occur prior to, during or after a music event.

This proposal has received some empirical support via research demonstrating physiological peak responses to psychoacoustic ‘events’ in music (see Table 1 ). On the whole, changes in physiological arousal – primarily, chills, heart rate or skin conductance changes – coincided with sudden changes in acoustic features (such as changes in volume or tempo), or novel musical events (such as entry of new voices, or harmonic changes).

TABLE 1. Music features identified in the literature to be associated with various physiological markers of emotion.

Supporting evidence for the similarity between music-evoked emotions and ‘real’ emotions has also emerged from research using central measures of emotional response. Importantly, brain regions associated with emotion and reward have been shown to also respond to emotionally powerful music. For instance, Blood and Zatorre (2001) found that pleasant music activated the dorsal amygdala (which connects to the ‘positive emotion’ network comprising the ventral striatum and orbitofrontal cortex), while reducing activity in central regions of the amygdala (which appear to be associated with unpleasant or aversive stimuli). Listening to pleasant music was also found to release dopamine in the striatum ( Salimpoor et al., 2011 , 2013 ). Further, the release was higher in the dorsal striatum during the anticipation of the peak emotional period of the music, but higher in the ventral striatum during the actual peak experience of the music. This is entirely consistent with the differentiated pattern of dopamine release during craving and consummation of other rewarding stimuli, e.g., amphetamines. Only one group to date has, however, attempted to identify musical features associated with central measures of emotional response. Koelsch et al. (2008a) performed a functional MRI study with musicians and non-musicians. While musicians tended to perceive syntactically irregular music events (single irregular chords) as slightly more pleasant than non-musicians, these generally perceived unpleasant events induced increased blood oxygen levels in the emotion-related brain region, the amygdala. Unexpected chords were also found to elicit specific event related potentials (ERAN and N5) as well as changes in skin conductance ( Koelsch et al., 2008b ). Specific music events associated with pleasurable emotions have not yet been examined using central measures of emotion.

Davidson and Irwin (1999) , Davidson (2000 , 2004 ), and Davidson et al. (2000) , have demonstrated that a left bias in frontal cortical activity is associated with positive affect. Broadly, a left bias frontal asymmetry (FA) in the alpha band (8–13 Hz) has been associated with a positive affective style, higher levels of wellbeing and effective emotion regulation ( Tomarken et al., 1992 ; Jackson et al., 2000 ). Interventions have been demonstrated to shift frontal electroencephalograph (EEG) activity to the left. An 8-week meditation training program significantly increased left sided FA when compared to wait list controls ( Davidson et al., 2003 ). Blood et al. (1999) observed that left frontal brain areas were more likely to be activated by pleasant music than by unpleasant music. The amygdala appears to demonstrate valence-specific lateralization with pleasant music increasing responses in the left amygdala and unpleasant music increasing responses in the right amygdala ( Brattico, 2015 ; Bogert et al., 2016 ). Positively valenced music has also been found to elicit greater frontal EEG activity in the left hemisphere, while negatively valenced music elicits greater frontal activity in the right hemisphere ( Schmidt and Trainor, 2001 ; Altenmüller et al., 2002 ; Flores-Gutierrez et al., 2007 ). The pattern of data in these studies suggests that this frontal lateralization is mediated by the emotions induced by the music, rather than just the emotional valence they perceive in the music. Hausmann et al. (2013) provided support for this conclusion via mood induction through a musical procedure using happy or sad music, which reduced the right lateralization bias typically observed for emotional faces and visual tasks, and increased the left lateralization bias typically observed for language tasks. A right FA pattern associated with depression was found to be shifted by a music intervention (listening to 15 min of ‘uplifting’ popular music previously selected by another group of adolescents) in a group of adolescents ( Jones and Field, 1999 ). This measure therefore provides a useful objective marker of emotional response to further identify whether specific music events are associated with physiological measures of emotion.

The aim in this study was to examine whether: (1) music perceived as ‘emotionally powerful’ and pleasant by listeners also elicited a response in a central marker of emotional response (frontal alpha asymmetry), as found in previous research; and (2) peaks in frontal alpha asymmetry were associated with changes in key musical or psychoacoustic events associated with emotion. To optimize the likelihood that emotions were induced (that is, felt rather than just perceived), participants listened to their own selections of highly pleasurable music. Two validation hypotheses were proposed to confirm the methodology was consistent with previous research. It was hypothesized that: (1) emotionally powerful and pleasant music selected by participants would be rated as more positive than silence, neutral music or a dissonant (unpleasant) version of their music; and (2) emotionally powerful pleasant music would elicit greater shifts in frontal alpha asymmetry than control auditory stimuli or silence. The primary novel hypothesis was that peak alpha periods would coincide with changes in basic psychoacoustic features, reflecting unexpected or anticipatory musical events. Since music-induced emotions can occur both before and after key music events, FA peaks were considered associated with music events if the music event occurred within 5 s before to 5 s after the FA event. Music background and affective style were also taken into account as potential confounds.

Materials and Methods

Participants.

The sample for this study consisted of 18 participants (6 males, 12 females) recruited from tertiary institutions located in Melbourne, Australia. Participants’ ages ranged between 18 and 38 years ( M = 22.22, SD = 5.00). Participants were excluded if they were younger than 17 years of age, had an uncorrected hearing loss, were taking medication that may impact on mood or concentration, were left-handed, or had a history of severe head injuries or seizure-related disorder. Despite clearly stated exclusion criteria, two left handed participants attended the lab, although as the pattern of their hemispheric activity did not appear to differ to right-handed participants, their data were retained. Informed consent was obtained through an online questionnaire that participants completed prior to the laboratory session.

Online Survey

The online survey consisted of questions pertaining to demographic information (gender, age, a left-handedness question, education, employment status and income), music background (MUSE questionnaire; Chin and Rickard, 2012 ) and affective style (PANAS; Watson and Tellegen, 1988 ). The survey also provided an anonymous code to allow matching with laboratory data, instructions for attending the laboratory and music choices, and explanatory information about the study and a consent form.

Peak Frontal Asymmetry in Alpha EEG Frequency Band

The physiological index of emotion was measured using electroencephalography (EEG). EEG data were recorded using a 64-electrode silver-silver chloride (Ag-AgCl) EEG elastic Quik-cap (Compumedics) in accordance with the international 10–20 system. Data are, however, analyzed and reported from midfrontal sites (F3/F4 and FC3/FC4) only, as hemispheric asymmetry associated with positive and negative affect has been observed primarily in frontal cortex ( Davidson et al., 1990 ; Tomarken et al., 1992 ; Dennis and Solomon, 2010 ). Further spatial exploration of data for structural mapping purposes was beyond of the scope of this paper. In addition, analyses were performed for the P3–P4 sites as a negative control ( Schmidt and Trainor, 2001 ; Dennis and Solomon, 2010 ). All channels were referenced to the mastoid electrodes (M1–M2). The ground electrode was situated between FPZ and FZ and impedances were kept below 10 kOhms. Data were collected and analyzed offline using the Compumedics Neuroscan 4.5 software.

Subjective Emotional Response

The subjective feeling component of emotion was measured using ‘EmuJoy’ software ( Nagel et al., 2007 ). This software allows participants to indicate how they feel in real time as they listen to the stimulus by moving the cursor along the screen. The Emujoy program utilizes the circumplex model of affect ( Russell, 1980 ) where emotion is measured in a two dimensional affective space, with axes of arousal and valence. Previous studies have shown that valence and arousal account for a large portion of the variation observed in the emotional labeling of musical (e.g., Thayer, 1986 ), as well as linguistic ( Russell, 1980 ) and picture-oriented ( Bradley and Lang, 1994 ) experimental stimuli. The sampling rate was 20 Hz (one sample every 50 ms), which is consistent with recommendations for continuous monitoring of subjective ratings of emotion ( Schubert, 2010 ). Consistent with Nagel et al. (2007) , the visual scale was quantified as an interval scale from -10 to +10.

Music Stimuli

Four music stimuli—practice, pleasant, unpleasant, and neutral—were presented throughout the experiment. Each stimulus lasted between 3 and 5 min in duration. The practice stimulus was presented to familiarize participants with the Emujoy program and to acclimatize participants to the sound and the onset and offset of the music stimulus (fading in at the start and fading out at the end). The song was selected on the basis that it was likely to be familiar to participants, positive in affective valence, and containing segments of both arousing and calming music—The Lion King musical theme song, “ The circle of life. ”

The pleasant music stimulus was participant-selected. This option was preferred over experimenter-selected music as participant-selected music was considered more likely to induce robust emotions ( Thaut and Davis, 1993 ; Panksepp, 1995 ; Blood and Zatorre, 2001 ; Rickard, 2004 ). Participants were instructed to select a music piece that made them, “experience positive emotions (happy, joyful, excited, etc.) – like those songs you absolutely love or make you get goose bumps.” This song selection also had to be one that would be considered a happy song by the general public. That is, it could not be sad music that participants enjoyed. While previous research has used both positively and negatively valenced music to elicit strong experiences with music, in the current study, we limited the music choices to those that expressed positive emotions. This decision was made to reduce variability in EEG responses arising from perception of negative emotions and experience of positive emotions, as EEG can be sensitive to differences in both perception and experience of emotional valence. The music also had to be alyrical 1 —music with unintelligible words, for example in another language or skat singing, were permitted—as language processing might conceivably elicit different patterns of hemisphere activation solely as a function of the processing of vocabulary included in the song. [It should be noted that there are numerous mechanisms by which a piece of music might induce an emotion (see Juslin and Vastfjall, 2008 ), including associations with autobiographical events, visual imagery and brain stem reflexes. Differentiating between these various causes of emotion was, however, beyond the scope of the current study.]

The unpleasant music stimulus was intended to induce negative emotions. This was a dissonant piece produced by manipulating the participant’s pleasant music stimulus and was achieved using Sony Sound Forge© 8 software. This stimulus consisted of three versions of the song played simultaneously— one shifted a tritone down, one pitch shifted a whole tone up, and one played in reverse (adapted from Koelsch et al., 2006 ). The neutral condition was an operatic track, La Traviata, chosen based upon its neutrality observed in previous research ( Mitterschiffthaler et al., 2007 ).

The presentation of music stimuli was controlled by the experimenter via the EmuJoy program. The music volume was set to a comfortable listening level, and participants listened to all stimuli via bud earphones (to avoid interference with the EEG cap).

Prior to attending the laboratory session, participants completed the anonymously coded online survey. Within 2 weeks, participants attended the EEG laboratory at the Monash Biomedical Imaging Centre. Participants were tested individually during a 3 h session. An identification code was requested in order to match questionnaire data with laboratory session data.

Participants were seated in a comfortable chair and were prepared for fitting of the EEG cap. The participant’s forehead was cleaned using medical grade alcohol swabs and exfoliated using NuPrep exfoliant gel. Participants were fitted with the EEG cap according to the standardized international 10/20 system ( Jasper, 1958 ). Blinks and vertical/horizontal movements were recorded by attaching loose electrodes from the cap above and below the left eye, as well as laterally on the outer canthi of each eye. The structure of the testing was explained to participants and was as follows (see Figure 1 ):

FIGURE 1. Example of testing structure with conditions ordered; pleasant, unpleasant, neutral, and control. B, baseline; P, physiological recording; and S, subjective rating. ∗ These stimuli were presented to participants in a counter balanced order.

The testing comprised four within-subjects conditions: pleasant, unpleasant, neutral, and control. Differing only in the type of auditory stimulus presented, each condition consisted of:

(a) Baseline recording (B)—no stimulus was presented during the baseline recordings. These lasted 3 min in duration and participants were asked to close their eyes and relax.

(b) Physiological recording (P)—the stimulus (depending on what condition) was played and participants were asked to have their eyes closed and to just experience the sounds.

(c) Subjective rating (S)—the stimulus was repeated, however, this time participants were asked to indicate, with eyes open, how they felt as they listened to the same music on the computer screen using the cursor and the EmuJoy software.

At every step of each condition, participants were guided by the experimenter (e.g., “I’m going to present a stimulus to you now, it may be music, something that sounds like music, or it could be nothing at all. All I would like you to do is to close your eyes and just experience the sounds”). Before the official testing began, the participant was asked to practice using the EmuJoy program in response to the practice stimulus. Participants were asked about their level of comfort and understanding with regards to using the EmuJoy software; experimentation did not begin until participants felt comfortable and understood the use of EmuJoy. Participants were reminded of the distinction between rating emotions felt vs. emotions perceived in the music; the former was encouraged throughout relevant sections of the experiment. After this, the experimental procedure began with each condition being presented to participants in a counterbalanced fashion. All procedures in this study were approved by the Monash University Human Research Ethics Committee.

EEG Data Analysis for Frontal Asymmetry

Electroencephalograph data from each participant was visually inspected for artifacts (eye movements and muscle artifacts were manually removed prior to any analyses). EEG data were also digitally filtered with a low-pass zero phase-shift filter set to 30 Hz and 96 dB/oct. All data were re-referenced to mastoid processes. The sampling rate was 1250 Hz and eye movements were controlled for with automatic artifact rejection of >50 μV in reference to VEO. Data were baseline corrected to 100 ms pre-stimulus period. EEG data were aggregated for all artifact-free periods within a condition to form a set of data for the positive music, negative music, neutral, and the control.

Chunks of 1024 ms were extracted for analyses using a Cosine window. A Fast Fourier Transform (FFT) was applied to each chunk of EEG permitting the computation of the amount of power at different frequencies. Power values from all chunks within an epoch were averaged (see Dumermuth and Molinari, 1987 ). The dependent measure that was extracted from this analysis was power density (μV 2 /Hz) in the alpha band (8–13 Hz). The data were log transformed to normalize their distribution because power values are positively skewed ( Davidson, 1988 ). Power in the alpha band is inversely related to activation (e.g., Lindsley and Wicke, 1974 ) and has been the measure most consistently obtained in studies of EEG asymmetry ( Davidson, 1988 ). Cortical asymmetry [ln(right)–ln(left)] was computed for the alpha band. This FA score provides a simple unidimensional scale representing relative activity of the right and left hemispheres for an electrode pair (e.g., F3 [left]/F4 [right]). FA scores of 0 indicate no asymmetry, while scores greater than 0 putatively are indicative of greater left frontal activity (positive affective response) and scores below 0 are indicative of greater right frontal activity (negative affective response), assuming that alpha is inversely related to activity ( Allen et al., 2004 ). Peak FA periods at the FC3/FC4 site were also identified across each participant’s pleasant music piece for purposes of music event analysis. FA (difference between left and right power densities) values were ranked from highest (most asymmetric, left biased) to lowest using spectrograms (see Figure 2 for an example). Due to considerable inter-individual variability in asymmetry ranges, descriptive ranking was used as a selection criterion instead of an absolute threshold or statistical difference criterion. The ranked FA differences were inspected and those that were clearly separated from the others (on average six peaks were clearly more asymmetric than the rest of the record) were selected for each individual as their greatest moments of FA. This process was performed by two raters (authors H-AA and NR), with 100% interrater reliability, so no further analysis was performed/considered necessary required to rank the FA peaks.

FIGURE 2. Sample data for participant 4 – music selection: The Four Seasons: Spring; Antonio Vivaldi. Recording: Karoly Botvay, Budapest Strings, Cobra Entertainment). (A) EEG alpha band spectrogram; (B) subjective valence and arousal ratings; and (C) music feature analysis.

Music Event Data Coding

A subjective method of annotating each pleasant music piece with temporal onsets and types of all notable changes in musical features was utilized in this study. Coding was performed by a music performer and producer with postgraduate qualifications in systematic musicology. A decision was made to use subjective coding as it has been successfully used previously to identify significant changes in a broad range of music features associated with emotional induction by music ( Sloboda, 1991 ). This method was framed within a hierarchical category model which contained both low-level and high-level factors of important changes. First, each participant’s music piece was described by annotating the audiogram, noting the types of music changes at respective times. Secondly, the low-level factor model utilized by Coutinho and Cangelosi (2011) was applied to assign the identified music features deductively to changes within six low-level factors: loudness, pitch level, pitch contour, tempo, texture, and sharpness. Each low-level factor change was coded as a change toward one of the two anchors of the feature. For example, if a modification was marked in terms of loudness with ‘loud,’ it described an increase in loudness of the current part compared to the part before (see Table 2 ).

TABLE 2. Operational definitions of high and low level musical features investigated in the current study.

Due to the high variability of the analyzed musical pieces from a musicological perspective – including the genre, which ranged from classical and jazz to pop and electronica – every song had a different frequency of changes in terms of these six factors. Hence, we applied a third step of categorization which led to a more abstract layer of changes in musical features that included two higher-level factors: motif changes and instrument changes. A time point in the music is marked with ‘motif change’ if the theme, movement or motif of the leading melody change from one part to the next one. The factor ‘instrument change’ can be defined as an increase or decrease of the number of playing instruments or as a change of instruments used within the current part.

Data were scored and entered into PASW Statistics 18 for analyses. No missing data or outliers were observed in the survey data. Bivariate correlations were run between potential confounding variables – Positive affect negative affect schedule (PANAS), and the Music use questionnaire (MUSE) – and FA to determine if they were potential confounds, but no correlations were observed.

A sample of data obtained for each participant is shown in Figure 2 . For this participant, five peak alpha periods were identified (shown in blue arrows at top). Changes in subjective valence and arousal across the piece are shown in the second panel, and then the musicological analysis in the final section of the figure.

Subjective Ratings of Emotion – Averaged Emotional Responses

A one-way analysis of variance (ANOVA) was conducted to compare mean subjective ratings of emotional valence. Kolmogorov–Smirnov tests of normality indicated that distributions were normal for each condition except the subjective ratings of the control condition D (9) = 0.35, p < 0.001. Nonetheless, as ANOVAs are robust to violations of normality when group sizes are equal ( Howell, 2002 ), parametric tests were retained. No missing data or outliers were observed in the subjective rating data. Figure 3 below shows the mean ratings of each condition.

FIGURE 3. Mean subjective emotion ratings (valence and arousal) for control (silence), unpleasant (dissonant), neutral, and pleasant (self-selected) music conditions.

Figure 3 shows that both the direction and magnitude of subjective emotional valence differed across conditions, with the pleasant condition rated very positively, the unpleasant condition rated negatively, and the control and neutral conditions rated as neutral. Arousal ratings appeared to be reduced in response to unpleasant and pleasant music. (Anecdotal reports from participants indicated that in addition to being very familiar with their own music, participants recognized the unpleasant piece as a dissonant manipulation of their own music selection, and were therefore familiar with it also. Several participants noted that this made the piece even more unpleasant to listen to for them.)

Sphericity was met for the arousal ratings, but not for valence ratings, so a Greenhouse-Geisser correction was made for analyses on valence ratings. A one-way repeated measures ANOVA revealed a significant effect of stimulus condition on valence ratings, F (1.6,27.07) = 23.442, p < 0.001, η p 2 = 0.58. Post hoc contrasts revealed that the mean subjective valence rating for the unpleasant music was significantly lower than for the control F (1,17) = 5.59, p = 0.030, η p 2 = 0.25, and the mean subjective valence rating for the pleasant music was significantly higher than for the control condition, F (1,17) = 112.42, p < 0.001, η p 2 = 0.87. The one-way repeated measures ANOVA for arousal ratings also showed a significant effect for stimulus condition, F (3,51) = 5.20, p = 0.003, η p 2 = 0.23. Post hoc contrasts revealed that arousal ratings were significant reduced by both unpleasant, F (1,17) = 10.11, p = 0.005, η p 2 = 0.37, and pleasant music, F (1,17) = 6.88, p = 0.018, η p 2 = 0.29, when compared with ratings for the control.

Aim 1: Can Emotionally Pleasant Music Be Detected by a Central Marker of Emotion (FA)?

Two-way repeated measures ANOVAs were conducted on the FA scores (averaged across baseline period, and averaged across condition) for each of the two frontal electrode pairs, and the control parietal site pair. The within-subjects factor included the music condition (positive, negative, neutral, and control) and time (baseline and stimulus). Despite the robustness of ANOVA to assumptions, caution should be taken in interpreting results as both the normality and sphericity assumptions were violated across each electrode pair. Where sphericity was violated, a Greenhouse–Geisser correction was applied. Asymmetry scores above two were considered likely a result of noisy or damaged electrodes (62 points out of 864) and were omitted as missing data which were excluded pairwise. Two outliers were identified in the data and were replaced with a score ±3.29 standard deviations from the mean.

A signification time by condition interaction effect was observed at the FC3/FC4 site, F (2.09,27.17) = 3.45, p = 0.045, η p 2 = 0.210, and a significant condition main effect was observed at the F3/F4 site, F (2.58,21.59) = 3.22, p = 0.039, η p 2 = 0.168. No significant effects were observed at the P3/P4 site [time by condition effect, F (1.98,23.76) = 2.27, p = 0.126]. The significant interaction at FC3/FC4 is shown in Figure 4 .

FIGURE 4. FC3/FC4 (A) and P3/P4 (B) (control) asymmetry score at baseline and during condition, for each condition. Asymmetry scores of 0 indicate no asymmetry. Scores >0 indicate left bias asymmetry (and positive affect), while scores <0 indicate right bias asymmetry (and negative affect). ∗ p < 0.05.

The greatest difference between baseline and during condition FA scores was for the pleasant music, representative of a positive shift in asymmetry from the right hemisphere to the left when comparing the baseline period to the stimulus period. Planned simple contrasts revealed that when compared with the unpleasant music condition, only the pleasant music condition showed a significant positive shift in FA score, F (1,13) = 6.27, p = 0.026. Positive shifts in FA were also apparent for control and neutral music conditions, although not significantly greater than for the unpleasant music condition [ F (1,13) = 2.60, p = 0.131, and F (1,13) = 3.28, p = 0.093], respectively.

Aim 2: Are Peak FA Periods Associated with Particular Musical Events?

Peak periods of FA were identified for each participant, and the sum varied between 2 and 9 ( M = 6.5, SD = 2.0). The music event description was then examined for presence or absence of coded musical events within a 10 s time window of (5 s before to 5 s after) the peak FA time-points. Across all participants, 106 peak alpha periods were identified, 78 of which (74%) were associated with particular music events. The type of music event coinciding with peak alpha periods is shown in Table 3 . A two-step cluster analysis was also performed to explore natural groupings of peak alpha asymmetry events that coincided with distinct combinations (2 or more) of musical features. A musical feature was to be deemed a salient characteristic of a cluster if present in at least 70% of the peak alpha events within the same cluster.

TABLE 3. Frequency and percentages of musical features associated with a physiological marker of emotion (peak alpha FA). High level, low level, and clusters of music features are distinguished.

Table 3 shows that, considered independently, the most frequent music features associated with peak alpha periods were primarily high level factors (changes in motif and instruments), with the addition of one low level factor (pitch). In exploring the data for clusters of peak alpha events associated with combinations of musical features, a four cluster solution was found to successfully group approximately half (53%) of the events into groups with identifiable patterns. This equated to 3 separate clusters characterized by distinct combinations of musical features, with the remaining half (47%) deemed unclassifiable as higher factor solutions provided no further differentiation.

In the current study, a central physiological marker (alpha FA) was used to investigate the emotional response of music selected by participants to be ‘emotionally powerful’ and pleasant. Musical features of these pieces were also examined to explore associations between key musical events and central physiological markers of emotional responding. The first aim of this study was to examine whether pleasant music elicited physiological reactions in this central marker of emotional responding. As hypothesized, pleasant musical stimuli elicited greater shifts in FA than did the control auditory stimulus, silence or an unpleasant dissonant version of each participant’s music. This finding confirmed previous research findings and demonstrated that the methodology was robust and appropriate for further investigation. The second aim was to examine associations between key musical features (affiliated with emotion), contained within participant-selected musical pieces, and peaks in FA. FA peaks were commonly associated with changes in both high and low level music features, including changes in motif, instrument, loudness and pitch, supporting the hypothesis that key events in music are marked by significant physiological changes in the listener. Further, specific combinations of individual musical features were identified that tended to predict FA peaks.

Central Physiological Measures of Responding to Musical Stimuli

Participants’ subjective valence ratings of music were consistent with expectations; control and neutral music were both rated neutrally, while unpleasant music was rated negatively and pleasant music was rated very positively. These findings are consistent with previous research indicating that music is capable of eliciting strong felt positive affective reports ( Panksepp, 1995 ; Rickard, 2004 ; Juslin et al., 2008 ; Zenter et al., 2008 ; Eerola and Vuoskoski, 2011 ). The current findings were also consistent with previous negative subjective ratings (unpleasantness) by participants listening to the dissonant manipulation of musical stimuli ( Koelsch et al., 2006 ). It is not entirely clear why arousal ratings were reduced by both the unpleasant and pleasant music. The variety of pieces selected by participants means that both relaxing and stimulating pieces were present in these conditions, although overall, the findings suggest that listening to music (regardless of whether pleasant or unpleasant) was more calming than silence for this sample. In addition, as both pieces were likely to be familiar (as participants reported that they recognized the dissonant manipulations of their own piece), familiarity could have reduced the arousal response expected for unpleasant music.

As hypothesized, FA responses from the FC3/FC4 site were consistent with subjective valence ratings, with the largest shift to the left hemisphere observed for the pleasant music condition. While not statistically significant, the small shifts to the left hemisphere during both control and neutral music conditions, and the small shift to the right hemisphere during the unpleasant music condition, indicate the trends in FA were also consistent with subjective valence reports. These findings support previous research findings on the involvement of the left frontal lobe in positive emotional experiences, and the right frontal lobe in negative emotional experiences ( Davidson et al., 1979 , 1990 ; Fox and Davidson, 1986 ; Davidson and Fox, 1989 ; Tomarken et al., 1990 ). The demonstration of these effects in the FC3/FC4 site is consistent with previous findings ( Davidson et al., 1990 ; Jackson et al., 2003 ; Travis and Arenander, 2006 ; Kline and Allen, 2008 ; Dennis and Solomon, 2010 ), although meaningful findings are also commonly obtained from data collected from the F3/F4 site (see Schmidt and Trainor, 2001 ; Thibodeau et al., 2006 ), which was not observed in the current study. The asymmetry findings also verify findings observed in response to positive and negative emotion induction by music ( Schmidt and Trainor, 2001 ; Altenmüller et al., 2002 ; Flores-Gutierrez et al., 2007 ; Hausmann et al., 2013 ). Importantly, no significant FA effect was observed in the control P3/P4 sites, which is an area not implicated in emotional responding.

Associations between Musical Features and Peak Periods of Frontal Asymmetry

Individual musical features.

Several individual musical features coincided with peak FA events. Each of these musical features occurred in over 40% of the total peak alpha asymmetry events identified throughout the sample and appear to be closely related to changes in musical structure. These included changes in motif and instruments (high level factors), as well as pitch (low level factor). Such findings are in line with previous studies measuring non-central physiological measures of affective responding. For example, high level factor musical features such as instrument change, specifically changes and alternations between orchestra and solo piece instruments have been cited to coincide with chill responses ( Grewe et al., 2007b ; Guhn et al., 2007 ). Similarly, pitch events have been observed in previous research to coincide with various physiological measures of emotional responding including skin conductance and heart rate ( Coutinho and Cangelosi, 2011 ; Egermann et al., 2013 ). In the current study, instances of high pitch were most closely associated with physiological reactions. These findings can be explained through Juslin and Sloboda’s (2010 ) description of the activation of a ‘brain stem reflex’ in response to changes in basic acoustic events. Changes in loudness and high pitch levels may trigger physiological reactions on account of being psychoacoustic features of music that are shared with more primitive auditory stimuli that signal relevance for survival to real events.

Changes in instruments and motif, however, may be less related to primitive auditory stimuli and stimulate physiological reactions differently. Motif changes have not been observed in previous studies yet appeared most frequently throughout the peak alpha asymmetry events identified in the sample. In music, motif has been described as “...the smallest structural unit possessing thematic identity” ( White, 1976 , p. 26–27) and exists as a salient and recurring characteristic musical fragment throughout a musical piece. Within the descriptive analysis of the current study, however, a motif can be understood in a much broader sense (see definitions in Table 2 ). Due to the broad musical diversity of the songs selected by participants, the term motif change emerged as most appropriate description to cover high level structural changes in all the different musical pieces (e.g., changes from one small unit to another in a classic piece and changes from a long repetitive pattern to a chorus in an electronic dance piece). Changes in such a fundamental musical feature, as well as changes in instrument, are likely to stimulate a sense of novelty and add complexity, and possibly unexpectedness (i.e., features of goal oriented stimuli), to a musical piece. This may therefore also recruit the same neural system which has evolved to yield an emotional response, which in this study, is manifest in the greater activation in the left frontal hemisphere compared to the right frontal hemisphere. Many of the other musical features identified, however, did not coincide frequently with peak FA events. While peripheral markers of emotion, such as skin conductance and heart rate changes, are likely to respond strongly to basic psychoacoustic events associated with arousal, it is likely that central markers such as FA are more sensitive to higher level musical events associated with positive affect. This may explain why motif changes were a particularly frequent event associated with FA peaks. Alternatively, some musical features may evoke emotional and physiological reactions only when present in conjunction with other musical features. It is recognized that an objective method of low level music feature identification would also be useful in future research to validate the current findings relating to low level psychoacoustic events. A limitation of the current study, however, was that the coding of both peak FA events and music events was subjective, which limits both replicability and objectivity. It is recommended future research utilize more objective coding techniques including statistical identification of peak FA events, and formal psychoacoustic analysis (such as achieved using software tools such as MIR Toolbox or PsySound). While an objective method of detecting FA events occurring within a specific time period after a music event is also appealing, the current methodology operationalized synchrony of FA and music events within a 10 s time window to include mechanisms of anticipation as well as experience of the event. Future research may be able to provide further distinction between these emotion induction mechanisms by applying different time windows to such analyses.

Feature Clusters of Musical Feature Combinations

Several clusters comprising combinations of musical features were identified in the current study. A number of musical events which on their own did not coincide with FA peaks did nonetheless appear in music event clusters that were associated with FA peaks. For example, feature cluster 1 consists of motif and instrument changes—both individually considered to coincide frequently with peak alpha asymmetry events—as well as texture (multi) and sharpness (dull). Changes in texture and sharpness, individually, were observed to occur in only 24.3 and 19.2% of the total peak alpha asymmetry events, respectively. After exploring the data for natural groupings of musical events that occurred during peak alpha asymmetry scores, however, texture and sharpness changes appeared to occur frequently in conjunction with motif changes and instrument changes. Within feature cluster 1, texture and sharpness occurred in 86 and 93% of the peak alpha asymmetry periods. This suggests that certain musical features, like texture and sharpness, may lead to stronger emotional responses in central markers of physiological functioning when presented concurrently with specific musical events as compared to instances where they are present in isolation.

An interesting related observation is the specificity with which these musical events can combine to form a cluster. While motif and instrument changes occurred often in conjunction with texture (multi) and sharpness (dull) during peak alpha asymmetry events, both also occurred distinctly in conjunction with dynamic changes in volume (high level factor) and softness (low level factor) in a separate feature cluster. While both the texture/sharpness and loudness change/softness combinations frequently occur with motif and instrument changes, they appear to do so in a mutually exclusive manner. This suggests a high level of complexity and specificity with which musical features may complement one another to stimulate physiological reactions during musical pieces.

The current findings extend previous research which has demonstrated that emotionally powerful music elicits changes in physiological, as well as subjective, measures of emotion. This study provides further empirical support for the emotivist theory of music and emotion which proposes that if emotional responses to music are ‘real,’ then they should be observable in physiological indices of emotion ( Krumhansl, 1997 ; Rickard, 2004 ). The pattern of FA observed in this study is consistent with that observed in previous research in response to positive and negative music ( Blood et al., 1999 ; Schmidt and Trainor, 2001 ), and non-musical stimuli ( Fox, 1991 ; Davidson, 1993 , 2000 ). However, the current study utilized music which expressed and induced positive emotions only, whereas previous research has also included powerful emotions induced by music expressing negative emotions. It would be of interest to replicate the current study with a broader range of powerful music to determine whether FA is indeed a marker of emotional experience, or a mixture of emotion perception and experience.

The findings also extend those obtained in studies which have examined musical features associated with strong emotional responses. Consistent with the broad consensus in this research, strong emotional responses often coincide with music events that signal change, novelty or violated expectations ( Sloboda, 1991 ; Huron, 2006 ; Steinbeis et al., 2006 ; Egermann et al., 2013 ). In particular, FA peaks were found to be associated in the current sample’s music selections with motif changes, instrument changes, dynamic changes in volume, and pitch, or specific clusters of music events. Importantly, however, these conclusions are limited by the modest sample size, and consequently by the music pieces selected. Further research utilizing a different set of music pieces may identify a quite distinct pattern of music features associated with FA peaks. In sum, these findings provide empirical support for anticipation/expectation as a fundamental mechanism underlying music’s capacity to evoke strong emotional responses in listeners.

Ethics Statement

This study was carried out in accordance with the recommendations of the National Statement on Ethical Conduct in Human Research, National Health and Medical Research Council, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Monash University Standing Committee for Ethical Research on Humans.

Author Contributions

H-AA conducted the experiments, contributed to the design and methods of the study, analysis of data and preparation of all sections of the manuscript. NR contributed to the design and methods of the study, analysis of data and preparation of all sections the manuscript, and provided oversight of this study. JH conducted the musicological analyses of the music selections, and contributed to the methods and results sections of the manuscript. BP performed the analyses of the EEG recordings and contributed to the methods and results sections of the manuscript.

Conflict of Interest Statement

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.

• ^ One participant only chose music with lyrical content; the experimenter confirmed with this participant that the language (Italian) was unknown to them.

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Keywords : frontal asymmetry, subjective emotions, pleasurable music, musicology, positive and negative affect

Citation: Arjmand H-A, Hohagen J, Paton B and Rickard NS (2017) Emotional Responses to Music: Shifts in Frontal Brain Asymmetry Mark Periods of Musical Change. Front. Psychol. 8:2044. doi: 10.3389/fpsyg.2017.02044

Received: 08 November 2016; Accepted: 08 November 2017; Published: 04 December 2017.

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Copyright © 2017 Arjmand, Hohagen, Paton and Rickard. 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) or licensor 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: Nikki S. Rickard, [email protected]

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.

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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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Blasco-Magraner, J.S., Bernabé-Valero, G., Marín-Liébana, P. et al. Changing positive and negative affects through music experiences: a study with university students. BMC Psychol 11 , 76 (2023). https://doi.org/10.1186/s40359-023-01110-9

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Theoretical and empirical advances in understanding musical rhythm, beat and metre

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The rhythmic elements of music are integral to experiences such as singing, musical emotions, the urge to dance and playing a musical instrument. Thus, studies of musical rhythm are an especially fertile ground for the development of innovative theories of complex naturalistic behaviour. In this Review, we first synthesize behavioural and neural studies of musical rhythm, beat and metre perception. Then, we describe key theories and models of these abilities, including nonlinear oscillator models and predictive-coding models, to clarify the extent to which they overlap in their mechanistic proposals and make distinct testable predictions. Next, we review studies of development and genetics to shed further light on the psychological and neural basis of rhythmic abilities and provide insight into the evolutionary and cultural origins of music. Last, we outline future research opportunities to integrate behavioural and genetics studies with computational modelling and neuroscience studies to better understand musical behaviour.

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Snyder, J.S., Gordon, R.L. & Hannon, E.E. Theoretical and empirical advances in understanding musical rhythm, beat and metre. Nat Rev Psychol (2024). https://doi.org/10.1038/s44159-024-00315-y

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Music and Empathy

How could music improve empathy.

Posted May 17, 2024 | Reviewed by Ray Parker

• The Importance of Empathy
• Find counselling near me
• Empathy allows for the perception of another’s thoughts and feelings.
• Music can increase our ability to be more empathetic individuals.
• Music is thought to be the social glue that strengthens feelings of unity.

Empathy is the ability to imagine how others are feeling. It allows an individual to share the same emotions observed in another person. Music can nonverbally channel empathy between people. People who demonstrate empathy can better interpret emotions conveyed through music (Tabak, 2022). They tend to be more accurate in understanding what musicians intend to convey through music.

Empathy levels influence people’s preferences for music (Clark 2015). Research has shown that empathy is positively linked to preferences for sad and tender music (R&B/soul, adult contemporary, soft rock genres) and negatively correlated with preferences for intense music (punk, heavy metal, and hard rock genres).

Evidence has shown that highly emphatic people experience more intense sadness after listening to sad instrumental music (Clarke 2015). Highly empathic people also find listening to music more pleasurable than people low in empathy. This evidence suggests the possibility that empathy can be cultivated via music. Music with emotional depth may increase empathy, whereas music with more strong and tense features may decrease it.

Even listening to music could help us be more empathic toward others. For instance, listening to love songs enhances our romantic feelings, and marching bands intensify our feelings for the home team.

For some people, music can represent a virtual person with whom to empathize. For example, we listen to sad music when we feel sad. We experience the music as empathizing with our feelings and making us feel less alone.

Evidence has also shown that long-term musical training (rhythmic coordination) has a positive influence on children’s empathy and social competence. For instance, musically trained children tend to be more sensitive to emotions expressed in music, and adults with professional musical training have heightened sensitivity to emotions in speech compared to non-musicians (Juslin 2019).

The social hormone oxytocin plays a role in facilitating empathy. Music triggers the hormones oxytocin and serotonin, responsible for bonding , trust, and intimacy . Sharing rhythmic behaviors such as singing, dancing, chanting, smiling to a smile, or talking together can increase social bonding.

The power of music to arouse brain oxytocin was at the center of the 2004 film entitled The Story of Weeping Camel . In the movie about a family of nomads in Mongolia, one camel had just given birth, but with great difficulty. Consequently, the mother camel showed little interest in her baby and refused to let it nurse. Tradition holds that the playing of the violin can motivate a camel and reunite her with her calf. This is exactly what the family did. They brought a musician to the village and played for the mother and baby camels. After a while the mother camel began to weep and gradually moved closer to her baby, in the end allowing it to suckle.

In sum, empathy is the capacity to share what someone else is feeling, resulting in compassionate behavior. Even if empathy doesn’t come naturally, research suggests people can cultivate it. Music has some special power to motivate our empathy and help us connect with others. Listening to music that contains reflective, thoughtful, and gentle attributes may increase empathy and improve reflective functioning. In fact, a possible evolutionary benefit of music is to improve group cohesion. Singing in choruses and sharing rhythms and melodies could have brought people together, whether as a community or in preparation for a battle.

Clark S., Giacomantonio S. (2015). Toward predicting prosocial behavior: Music preference and empathy differences between adolescents and adults. Empirical Musicology Review , 10(1–2), 50–65.

Juslin, P. N. (2019). Musical emotions explained: Unlocking the secrets of musical affect . Oxford University Press

Tabak, B. A., Wallmark, Z., Nghiem, L. H., Alvi, T., Sunahara, C. S., Lee, J., & Cao, J. (2023). Initial evidence for a relation between behaviorally assessed empathic accuracy and affect sharing for people and music. Emotion, 23 (2), 437–449.

Shahram Heshmat, Ph.D., is an associate professor emeritus of health economics of addiction at the University of Illinois at Springfield.

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How do emotions help construct our cultural identity in music festivals?

2022 was a record year for music festivals in Spain, hitting historic highs just two years after the entire country was locked down due to the pandemic. Spain boasts close to a thousand music festivals and a live music industry that earned 459 million euros in ticket revenue alone in 2022. This is almost 200% more than the previous year, according to figures from the Anuario de la Música en Vivo 2023 (2023 Live Music Yearbook) produced by the country's Music Promoters' Association.

Festival attendance keeps on growing. This is a phenomenon that sets the cultural and social agenda for thousands of people, and which also raises many questions. What mark might by left on society by this music festival culture? How are festivalgoers influenced by their experiences there?

Research published in Empirical Studies of the Arts has sought to understand how emotions stirred by music festivals trigger, shape, bolster and influence cultural identification processes.

The work has been headed by Jordi Oliva Codina, holder of a doctoral degree from the UOC (Universitat Oberta de Catalunya) and course instructor at its Faculty of Arts and Humanities. Oliva analyzed, from different standpoints and together with Alba Colombo, member of the same Faculty and of the Language, culture and identity in a global era (IdentiCat) research group, the impact that music festivals have on society.

Colombo has coordinated the UOC's participation in the Festivals, Events and Inclusive Public Space ( FESTPACE ) project, which looks at the use of public spaces for different types of events in Europe.

Events designed to create emotions

Oliva and Colombo's work stems from the following premise: festivals play with the emotions to attract their audience and provide a unique experience. Based on this theory, it has sought to understand how this affects attendees' sense of identity.

"If someone goes to a festival and hears their favorite group or any other they like, they'll feel intense positive emotions and will identify with their way of playing, of making music, of dressing, as well as the people around them.

"If this happens once, it may well not be important, but if it happens often or repeatedly in a lot of festivals, it gives rise to identification processes that can determine one's cultural identity," explained Oliva.

"Larger or more mainstream festivals, for example, sell themselves as a happy place, where you can find like-minded people, where you can feel like you were at Woodstock in 1968. These emotions lead to the creation of a very appealing process that makes you want to be a part of it," he added.

These emotions have an impact. Music festivals are designed to create a unique experience for their attendees and therefore have a significant impact on a number of cultural identification processes. This can find form in an influence on musical tastes, in bolstering a regional identity or in an increase in a sense of community. Oliva's conclusions note that this influence increases when the emotions felt during a festival are more intense.

The importance of classical music festivals

Oliva's research has confirmed that festivals are able to determine cultural identities based on the content they offer. Mass participation, mainstream events have financial motives and seek to make consumers identify with the brand. This brings together vast numbers of people, which has an impact that is both cultural and felt in the live music sector.

"The festival craze is on the rise but, at the same time, concert venues are dying out, people consume music based on playlists and many producers set their goals based on what festivals are asking for. In the world of mainstream music, it's all very calculated," explained Oliva.

"Classical music festivals are different; a range of intentions underlie them because they have the mission of culturally enriching their audience. They don't focus solely on financial gain, in great part due to the fact that they receive more funding," he explained.

The future of the study

This study concludes Oliva's research project, which brings together three perspectives: that of sociology, which aims to gain an understanding of social behavior in music festivals; that of psychology, which comprises an analysis of the emotions of music; and, lastly, that of event studies, to ascertain organizers' intentions and provide an assessment of the impact of music festivals.

The UOC's research provides a tool that could be used to measure festivals' emotional impact. A resource that, according to the researcher, can be of great long-term use, making it particularly appealing to public administrations.

"Festival companies have a short-term view, with goals more focused on the upcoming event's financial return. Interest should, in any case, come from public administrations, to be able to understand what we are leaving for society with this boom in festivals," concluded the UOC researcher.

More intense emotions mean a bigger impact

To reach these conclusions, the researcher focused on the San Sebastián Quincena Musical classical music festival. After every concert, he carried out surveys gauging which emotions had been awakened by the music, how intense they were and how this affected the cultural identity of the festivalgoers.

"My main conclusion is that positive emotions and cultural identity have a positive correlation. The more intense the emotion stemming from the music, the greater the growth in a sense of cultural identity," explained the UOC researcher.

The second part of the methodological process consisted of interviewing both festivalgoers and organizers to gain an understanding of what they felt during the concerts and how this affected them in terms of culture and identity.

"In the case of Quincena Musical, after the concerts, many members of the public go for a drink with the artists or others they have met at the festival. This is a way of creating bonds and a sense of community, which, in this case, has occurred time and time again over the course of 80 years.

"What's more, enjoying the festival affects its public's relationship with culture. For example, it increases their understanding of and love for music. These are highly significant, positive impacts," added Oliva.

More information: Jordi Oliva et al, Perceived Intense Emotions and Their Influence on Cultural Identification Processes: A Mixed-Method Study of a Classical Music Festival, Empirical Studies of the Arts (2023). DOI: 10.1177/02762374231176192

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Sad Girl Playlists Aren’t Just Trendy—Study Finds Sad Music Can Boost Your Mental Health

• New research suggests that listening to sad music can positively impact a person’s mood based on the sense of connectedness it provides.
• Experts cite three responses to sad music: grief, melancholia, and sweet sorrow.
• Experts agree that music of all kinds can play a role in people’s mental health and mood, but music is a personal, unique experience for each listener.

A new study found that listening to sad music can impact a person’s mood positively, based on a revived sense of connectedness.

When you’re at a party or social gathering you may queue an upbeat song, such as “That’s What I Like” by Bruno Mars. On other days, you might just want to listen to something that’s a bit more gloomy and relatable like Taylor Swift’s “Anti-Hero.”

Whatever music you enjoy listening to most, whether that be hip-hop, country, rock, or jazz, it can oftentimes influence your mood and feelings.

This is especially true when it comes to sad music. Various features of a song, including tempo, mode, instrument choice, and dynamics, can prompt negative emotions in listeners, Tara Venkatesan, PhD, a cognitive scientist at Oxford University and an operatic soprano, told Health.

However, a new study published in the Journal of Aesthetic Education , which Venkatesan was a part of, suggests that while listening to sad music can certainly make people feel sad, doing so may also impact a person’s mood positively and allow them to feel a sense of connectedness.

“Our main point is that the value of sad music lies in its ability to create a sense of connection, regardless of whether it actually evokes sadness in the listener,” Venkatesan clarified. “And it’s that sense of connection, not necessarily the experience of sadness itself, which is what makes listening to sad music really great!”

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Why Do People Love Sad Music?

The researchers hypothesized that people value sad music for the same reasons they might value sad conversations—a sense of genuine connection.

For example, when someone tells you about their horrible break up, you might feel sad yourself because of how genuinely devastated and lonely they are feeling, Venkatesan explained. However, as you continue talking, you might feel like there’s something meaningful about that interaction and connected with this person in a unique way.

The research team demonstrated sad music’s ability to provide a sense of connection in two parts.

In the first part, the researchers wanted to show that emotional expression is a characteristic value of what music is all about. They gave nearly 400 participants a description of four different songs including:

• A song that “conveys deep and complex emotions” but is “technically very flawed”
• A song that is “technically flawless” but “does not convey deep or complex emotions”
• A song that is “deeply emotional” and “technically flawless”
• A song that is both unemotional and “technically flawed”

Participants were asked to rank songs based on which pieces embodied “what music is all about.”

They found that participants valued emotional expression more than technical proficiency when reviewing their song choices. Highly emotional songs, even of lesser technical value, were chosen at a much higher rate.

For the second part of their experiment, the authors asked 450 new participants to rate how connected they felt when listening to music or participating in conversations that expressed 72 different emotions, including inspiration, love, sadness, contempt, etc.

They found that the emotions that make people feel connected in conversation are also the emotions whose expression in music matched the “what music is all about” highly rated songs: sadness, love, joy, loneliness , and sorrow.

Furthermore, participants said that songs expressing sad emotions like suffering and despair are unpleasant to listen to but still capture the essence of what music is all about and make for high-connection conversations.

“In other words, regardless of whether we enjoy sad music, we value sad music because it creates a sense of connection,” Venkatesan explained.

Other research has suggested that people listen to sad music for no particular motivation other than the fact that they like this music or band. In fact, a 2014 study highlights that nearly a third of participants listened to sad music when they were in a positive mood.

Does Listening to Sad Music Evoke Sadness? 

Whether or not sad music makes a person feel sad depends on each individual and their experience, Shannon Bennett, PhD , site clinical director for NewYork-Presbyterian’s Center for Youth Mental Health, told Health .

For example, a person might feel sad when they hear a certain song because that song might be connected to a particular memory. Since our emotions and memories are very connected, when we listen to a song that evokes a certain memory, it can cause us to feel sad.

“If a piece of music is connected to either of those experiences that could then bring on a real feeling of sadness,” Bennett explained. “But that to me is a more personal experience in terms of how intense that feeling is, how long it lasts, and then importantly what we do with it.”

This aligns with a 2016 study that found people who listen to sad music can perpetuate cycles of negative thinking and often prompts them to think about sad memories or negative thoughts.

Music, and our response to it, is a unique and personal experience.

While sad music can generally make people feel sad, depending on the mental health state of an individual, it can evoke other emotions as well, added Venkatesan. She cited previous research on people’s experience of sad music and noted three main categories expressed: grief, melancholia, and sweet sorrow.

“While grief consisted mainly of negative emotions like despair, both melancholia and sweet sorrow consisted of more mixed emotions like longing and nostalgia and even positive emotions like comfort and pleasure,” she said.

Music and Mental Health

Bennett clarified that sad music does not automatically indicate sad emotion for the listener—it can actually impact the listener’s mental health positively.

“Music can be a way to practice just sitting with a feeling that sometimes is harder to sit with and that is actually emotionally very helpful,” she added. “We call that an emotional exposure that in fact is used in some very well-researched therapy protocols to help us to sit with emotions that we sometimes don’t want to sit with.”

Sad music can also make people feel connected in the same way a heartfelt conversation makes us feel connected, said Venkatesan. “It is very likely that the sense of connection we experience when listening to sad music has positive health benefits.”

Some studies suggest that listening to sad music creates a feeling of “emotional communion” where you share feelings of sadness with the singer or composer. Venkatesan explained that in this case, listening to sad songs may act as a form of virtual contact which can help people feel accepted, understood, and less lonely.

She added that other studies suggest that listening to sad songs allows us to connect with ourselves and reflect on our own emotional experiences which can help with mood regulation.

Venkatesan noted that music, in general, has a profound effect on our brains and physiology and therefore can also impact our mood.

For example, some research suggests that relaxing music can decrease levels of salivary cortisol and psychological stress, which is an indicator of decreased stress and better regulation when responding to a stressor.

Bennett noted in the same way that a sad song might evoke a sad emotional state, there are ways to use music to evoke a positive emotional state. There are also ways that people can choose positive behaviors that might move them in the direction of positive emotion.

Bennett concluded, “My hope is that this research will help people just recognize that feeling sad is okay and also that there are things that we can do to help us move out of that feeling.”

Attie-Picker M, Venkatesan T, Newman GE, Knobe J. On the value of sad music . J Aesthet Educ . Published online April 18, 2023.

Tallahassee Memorial Healthcare. How music affects your mind, mood and body. 

Taruffi L, Koelsch S. The paradox of music-evoked sadness: an online survey . PLoS One . 2014;9(10):e110490. doi:10.1371/journal.pone.0110490

Garrido S, Schubert E, Bangert D. Musical prescriptions for mood improvement: an experimental study . Arts Psychother . 2016;51:46-53. doi:10.1016/j.aip.2016.09.002

Van den Tol AJM, Edwards J, Heflick NA. Sad music as a means for acceptance-based coping . Music Sci . 2016;20(1):68-83. doi:10.1177/1029864915627844

Ooishi Y, Mukai H, Watanabe K, Kawato S, Kashino M. Increase in salivary oxytocin and decrease in salivary cortisol after listening to relaxing slow-tempo and exciting fast-tempo music . PLoS One . 2017;12(12):e0189075. doi:10.1371/journal.pone.0189075

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Music Use for Mood Regulation: Self-Awareness and Conscious Listening Choices in Young People With Tendencies to Depression

Joanna stewart.

1 MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Penrith, NSW, Australia

Sandra Garrido

Cherry hense.

2 Department of Music Therapy, Faculty of Fine Arts and Music, The University of Melbourne, Melbourne, VIC, Australia

Katrina McFerran

The current study explored the circumstances in which seven young people with a tendency to depression chose different styles of music to listen to, and their level of awareness of the impact of their music listening habits on mood and wellbeing. A model of various pathways through music use was developed that may explain why music listening intentions in young people do not always align with their wellbeing outcomes. We suggest that the relationship between intentions and outcomes are mediated by differing levels of self-awareness and insight into the mood regulation processes occurring during music listening.

Introduction

Depression is responsible for the deaths of many people globally each year, with suicide being the leading cause of death around the world in 15–29 year-olds ( WHO, 2017 ). Many more young people experience depression at highly debilitating levels, around 8% in Australia meeting the DSM criteria for Major Depressive Disorder (MDD) ( Lawrence et al., 2015 ), and 13% in the United States ( National Institute of Mental Health, 2017 ). The early onset of depression is a critical factor in terms of projected quality of life ( Sullivan et al., 2012 ), and if left untreated, depression can become a lifelong disability ( Meade and Dowsell, 2016 ). Depression also has an impact on the social and intellectual development of young people as well as reducing engagement with education at a crucial developmental stage. It is therefore imperative to address depression in young people before its impact on their lives increases.

Depression and Media Use

Access to online media has increased exponentially with the onset of digitisation and technological advancement ( Brown and Bobkowski, 2011 ). Research has demonstrated that young people are even more likely to turn to media when they are in a negative mood ( Dillman Carpentier et al., 2008 ). In fact, withdrawal from socialization and normal daily activity has been identified as a behavior consistent with clinical depression and this often involves an increase in general media use ( O’Keeffe and Clarke-Pearson, 2011 ). This increased engagement with media includes music listening, with emotional dependency on music also tending to increase during periods of depression ( McFerran, 2016 ).

However, research has demonstrated that this increased reliance on music during episodes of psychological distress does not always have positive mental health outcomes for the young people involved. For example, Garrido and Schubert (2015a , b ) have demonstrated that people with a ruminative coping style, which is highly predictive of clinical depression, tend to be attracted to music that can intensify symptoms of depression. Similarly, in a study by McFerran et al. (2015) the authors discovered that having high levels of distress while listening to music was associated with more intense, negative moods afterward. Other studies confirm the fact that people with depression are not always able to effectively select music that helps them to feel better ( Wilhelm et al., 2013 ; Hense et al., 2014 ). They may also use music as part of generally unhealthy coping strategies such as emotion-focused coping ( Miranda et al., 2012 ), rumination ( Garrido and Schubert, 2013 ), or social withdrawal ( McFerran and Saarikallio, 2014 ).

Self-Awareness and Depression

Self-awareness can be described as clear awareness of one’s own feelings, emotions, and behaviors ( Blakemore and Frith, 2003 ). Such awareness is generally regarded as an adaptive function that can result in identification of aspects of the self that would benefit from modification. Experiencing feelings of sadness can often provide the motivation for self-scrutiny and behavioral modification, even increasing detail oriented thinking and realistic thinking that is useful for problem solving behaviors ( Keedwell, 2008 ). However, in depression, the adaptive function of sadness tends to malfunction, with depression being associated with increased pessimism and reduced motivation to engage in problem solving ( Bianco et al., 2013 ).

In general, individuals differ as to their levels of cognitive insight, or their capacity to understand their own thoughts, behaviors and affective states ( Riggs et al., 2012 ). However, research has demonstrated that low emotional awareness is highly predictive of depression and anxiety in young people ( Kranzler et al., 2016 ). Emotional awareness, or the ability to identify emotional experiences, can be a protective factor against psychopathology by allowing an individual to recognize the need to activate appropriate emotion regulation strategies ( Barrett et al., 2001 ). On the other hand, young people with low emotional awareness tend to have reduced access to effective strategies for coping with negative affect and interpersonal difficulties ( Flynn and Rudolph, 2014 ).

This lack of awareness may also play into music listening choices in young people with depression. This is implied by one study conducted by Garrido and Schubert (2015b) in which participants with high levels of rumination reported having benefited from listening to sad music while at the same time reporting an increase in depressive symptoms. Similarly, in a study on listening to nostalgic music, Garrido (2018) found that implicit mood measures (in which participants are unaware that their mood is being assessed) indicated a much higher level of negative mood responses after listening to nostalgic music than participants reported in response to direct questioning. The issue of the discrepancy between perceived and real mood changes was also discussed by McFerran et al. (2016) in a systematic review of 33 articles about music and mental health. Their review revealed that while direct questioning usually suggested positive mood effects from listening to music, non-direct mood indicators suggested results were not always so positive. At times this appeared to be because researchers worded questions in such a way as to suggest positive effects. In other cases study participants demonstrated a tendency to construe music listening positively regardless of its effect on their mood. This reveals issues both with demand characteristics in study design as well as a degree of positive bias in participants.

In exploring the concept of awareness further, McFerran and Saarikallio (2014) identified three different response styles with regards to music choices. They found that some people can recognize that the music they listen to is not beneficial to their mood and then be proactive in changing their listening habits. The second response style is when a person can be made aware of deteriorations in their mood by others and change their habits. This has been shown to be possible, for example, with young people who are seeking help for depression and who work with a music therapist to identify more helpful ways of listening to their preferred music ( McFerran et al., 2018 ). The third response style is when a person may either recognize or be made aware of the negative impact but is not inclined to modify their listening behaviors. Alternatively, if an individual’s mental health is very poor, they may not be able to focus on therapeutic interventions that demand high cognitive function such as this level of meta-reflection on intentional music listening ( Hense et al., 2018 ). Thus, it appears that there is a need to develop nuanced strategies for increasing awareness of the effect that music listening can have on young people’s mood and wellbeing. Given the central role that music plays in the lives of young people, increasing such awareness has the potential for positive benefits through increased understanding of adaptive and maladaptive behaviors more generally. There is a need to further understand how young people are enabled to increase their awareness about the effects of music on their wellbeing.

The current study uses a grounded theory approach to explore the following research question through interviews with seven young people: To what degree are young people with symptoms of depression aware of the effect their music-listening has on mood and wellbeing, and how do they reach a state of awareness?

The research question lends itself to an inductive approach in which a topic is explored with no prior hypothesis. Grounded theory is one qualitative method that is often used to investigate the ways in which various conditions interact with an individual’s experience of a given phenomenon, with an emphasis on analyzing people’s actions and integrating what they do as well as what they say ( Charmaz and Bryand, 2007 ) This method enables theoretical notions to be extrapolated from qualitative data, rather than generating a rich description ( Dey, 2007 ). In grounded theory, the researchers endeavor to approach the data without being influenced by a priori knowledge. Through processes of coding, constant comparison and abstraction of concepts from data categories, a conceptual hypothesis or theory can be developed ( Chun Tie et al., 2019 ).

Participants

Participants were recruited from among people who had taken part in an online survey and had indicated their interest in being involved in further research ( Garrido et al., 2017 ). Initially, 615 people participated in the survey and were asked to complete the Depression and Anxiety Stress Scale (DASS; Henry and Crawford, 2005 ) and the Rumination-Reflection Questionnaire (RRQ; Trapnell, 1997 ). Purposive sampling was used, and potential participants with DASS scores above 15 and rumination scores above four were approached, as these are indicative of severe symptoms of depression and ongoing ruminative coping styles. This generated a list of 27 potential participants, 4 of whom were not approached because they had indicated being negatively affected by participating in the survey. The participants on the inclusion list were contacted by email, with 7 young people aged from 19 to 28 years (mostly female) responding and being interviewed. Participant demographics are included in Table 1 . As the previous study had been conducted online the participants lived in a number of different countries.

Demographic information of interview participants.

Materials and Procedure

Ethics approval was granted by the Human Research Committee (#1443393.1) at the University of Melbourne. Potential participants were contacted via email and if they responded with interest were sent a Plain Language Statement and Consent form. Written informed consent was obtained from all participants prior to conduct of the interviews. Due to the diverse locations of participants, all but one interview was conducted via the video call function on Skype using Version 7.39.0.102. Audio of the interviews was recorded using MP3 Skype Recorder 4.32 Free Edition. Since all participants were fluent English speakers interviews were conducted in English and took approximately 45 min to 1 h. Participants were offered a $15 iTunes voucher for participating in the study.

Interviews were conducted by the first two authors and memos were created after each interview to record the impressions of the interviewers about participants’ demeanor, body language, tone of voice and time taken to respond as well as the interviewers’ reflections on how their own personal biases may have influenced their conduct of the interview ( Finlay, 2002 ). Discussions between the first two authors took place after each interview to determine the direction of the subsequent interview. An interview guide was used, however, interviews proceeded freely based on participant responses (see Appendix ). In general, the interviewer sought to prompt participants to discuss their use of music to regulate their moods, and in particular negative moods. In order to determine the level of awareness and responsiveness to the idea that music does not always have positive effects on mood, and to avoid the positive bias that has limited some previous studies, the interviewers deliberately introduced the topic of negative effects toward the end of the interview if participants had not raised the issue themselves.

Interviews were transcribed verbatim. A preliminary analysis of each interview was conducted using open coding in accordance with Strauss and Corbin (2008) . The initial in vivo codes related primarily to the ways the young people described using music to regulate mood and included codes such as “for comfort,” “music is used as a distraction” and “to keep fighting.” This initial coding allowed the first author to immerse herself in the data and revealed new questions for consideration in subsequent interviews to enable deeper exploration of new issues. For example, themes of anxiety began to emerge as common around the fourth interview, and so additional questions in relation to this were added to the interview guide for subsequent interviews.

Once open coding of the interviews had been completed a second wave of analysis was conducted independently by two pairs of researchers (the first two and last two authors) who each identified themes and central categories that connected the various ideas that were emerging from the data. Axial coding as described by Charmaz (2006) was then used to discern possible relationships between the various categories and codes, with constant return to the data to better understand whether similar coding was representative of shared ideas. The codes were examined to assess the motivations participants gave for adopting particular mood regulation strategies with music and the factors influencing the relative success of these strategies. This informed the generation of sub-categories within the larger concepts that had been identified across participants. The properties and dimensions of the categories and sub-categories were then delineated with a focus on the central code of awareness and, where present, how this awareness was described as developing. Memos were used as a way of noting impressions from the data, with statements such as “It seems like…” The analysts would then return to the raw data to see whether these impressions could be sustained by what had actually been said. This process allowed for a constant attention to the possibility of the researchers’ pre-assumptions influencing interpretation of the data, rather than allowing details about the phenomenon to emerge from the participants’ experiences, which was the focus of this study. The two research teams then compared their analyses and used selective coding to integrate and further refine the central category, it’s properties and dimensions and to develop a theoretical proposition.

Reflexivity

Since researchers who have worked in a particular field for some time may already be familiar with previous findings in this area and be somewhat influenced by their knowledge, reflexivity was considered an important part of the research process ( Finlay, 2002 ). Qualitative analysis is an inherently subjective process and two of the authors (SG and KM) have undertaken a number of studies of this topic previously. It was therefore critical to ensure that analysis was not used to simply confirm our existing beliefs (confirmation bias). Undertaking two separate analyses was our primary strategy for testing our ability to focus on what was being said by the seven participants and we frequently returned to the data to scrutinize our emerging ideas and test how closely it matched the raw data. This allowed us to rigorously debate and refine our presentation of the findings. Throughout the interviews and analysis process, the researchers also engaged in personal and shared reflections and debate about potential meanings inherent in the data.

Strategies for Music Choice

Our analysis suggested that the strategies participants described for using music to manage negative moods fell into two broad categories: (i) selecting music that differed from the negative mood in an effort to shift a negative mood, and (ii) selecting music that mirrored the negative mood in an effort to cope with negative feelings. These strategies are depicted in Figure 1 following the model of Biasutti (2013 , 2018 ). Both strategies appeared to have negative outcomes at times and positive outcomes at other times.

Phases of awareness and their influence on music listening strategies.

Music That Differed From Current Mood

Many (5 of 7) of the participants described listening to music that differed from the mood they were experiencing in order to try to alter a negative mood. For example, Participant 3 described listening to classical music when angry to help her calm down: “If I’m listening to classical music because I’m trying to calm myself down, it’s soothing. It helps me relax. It’s more like trying to relax, that I’m feeling the music and trying to absorb every note.” Similarly, several participants identified using calming music to reduce feelings of anxiety. Participant 5 stated “I have anxiety issues so I find it quite a nice way to settle myself,” while Participant 7 described using music to “get out of my head” when feeling anxious. Participant 2 also reported sometimes using music to “block out things that are bothering me.” Participant 5 also described successfully listening to upbeat music when feeling down. She stated: “If I’m feeling depressed I tend to put on happy music like cheesy pop and things to try and cheer myself up almost. Something with a fast tempo to kind of boost my mood.” These strategies were considered to represent conscious processes adopted by participants to change their mood. In contrast, Participant 4 reported that listening to music that didn’t match her negative mood gave her “the impression that everyone else is having fun except for me.”

Music That Mirrored Current Mood

The other prevalent theme we perceived across most (6 of 7) participants was the use of music to mirror mood in an attempt to cope with feelings of sadness and depression. While the term ‘cope’ can cover a wide range of strategies for dealing with undesirable situations and affective states including problem-solving and attempting to change one’s mood, in the context of this data the term is used to describe strategies designed to mitigate or lessen the intensity or unpleasantness of an undesirable mood without actually shifting it’s valence. Different participants described selecting music that mirrored their current mood in relation to a diverse range of intentions or aims, and outcomes. However, our interpretation was that these strategies often appeared to be designed to help participants cope with affective states, rather than to change them.

Some participants expressed the desire to be “comforted” when listening to music, gaining understanding that “I’m not the only one going through problems” (Participant 3). This strategy provided a feeling of “validation” of the experience for Participant 4, and Participant 6 described something similar saying, “I’m tired and I’m still sad but it’s less heavy and it’s like someone understands.” Participant 3 also reported that sometimes it was just a matter of changing the degree of sadness being felt, describing how in the past she found it useful to listen to music that was “at a level that is just a little bit above what I’m feeling, to maybe bring me up a little bit but not so much that it would bother me.” In this case, even a small improvement in mood was perceived as a positive change.

Others listened to mood-matching music with the express aim of intensifying their negative emotions. Several participants reported listening to slow, acoustic, classical pieces to reflect and emphasize a sad or low mood state. For example, Participant 1 described deliberately choosing songs that conveyed “extreme manifestations” of the sad mood she was in. Two participants described their motivation as being to “drown in” (Participant 3) or “wallow in” the negative emotions (Participant 4). Participant 3 described how this had a positive effect, and how it “gets me to the highest point and then I come down,” suggesting that she experienced some relief once the more intense emotions diminished. For Participant 1, the effect was less clear and she reported listening to music with suicidal lyrics when depressed, stating that this “probably just intensified the emotion, which [may] or [may not] be beneficial.” Participant 4 similarly reported that this could leave her not even feeling “motivated enough to change the music.”

In contrast to the others, Participant 2 reported that she preferred to avoid music that could make her feel more depressed. This did not necessarily entail listening to music that was upbeat and happy, which she tended to listen to when having a “better day,” but she said: “If I’m not feeling so good I’ll listen to a classical piece, something slow.” She also made the following statement.

“I try not to listen to depressing music if I’m already feeling down because it’s not going to do anything to help really. Sometimes I kind of need it to know that other people feel the same way, but a lot of time its just going to make me feel worse and so then I don’t want to do that… Usually I listen to more positive things.”

Factors Influencing the Outcomes

Our analysis of the properties and dimensions of the strategies presenting in the data revealed that both positive and negative effects were experienced from both strategies for managing moods with music. This was determined during axial coding, where we examined the circumstances surrounding these strategies in order to determine some of the factors that contributed to a positive or negative outcome. We identified three properties: (i) the messages conveyed by the lyrics, (ii) the frequency and duration of listening to certain music, (iii) the nature and intensity of the prior affective state of the listener.

The Messages Conveyed by the Lyrics

Some participants described particularly being attracted to music with lyrics that have special meaning for them when feeling down. When Participant 1 described the kind of music she was drawn to in a depressed mood, she said “It’s both the music and the lyrics as well, and I think that what the singer’s expressing is a sort of frustration and I’ll think, ‘Oh yes, that’s exactly what we feel here’.” Participant 6 described how music with lyrics was especially important to her when she was feeling sad: “When I’m really, really sad that’s the only time I’ll listen to music where I care more about the lyrics.”

However, the outcomes weren’t necessarily positive for participants when they listened to music with lyrics that closely related to how they felt. Participant 1 stated: “I started thinking about the lyrics and stuff and it’s not pleasant stuff and I began to think, well maybe it’s listening to this stuff which is really contributing to my being in a very low mood.” Participant 6 similarly said: “I was just getting really perturbed because I was listening to the lyrics too much and I could relate and then I could go and watch TV or something but I kept thinking about the song.”

More positive effects were noted when listening to songs that were considered “emotional but” also inspired “some optimism,” or had an “uplifting message” (Participant 6). Participant 2 stated that “If the music has a positive outlook on life, I’m likely to kind of adopt that somewhat.” Thus, several participants demonstrated how the differing messages in music, even music that mirrored their mood, could have differing effects on their mood.

Frequency and Duration of Music Listening

Participant 1 explained how she had experienced a phase in her life when she was listening intensely to music with very negative, suicidal lyrics. She made the following statement.

“I was listening for hours a day…to be hearing people talking about drug problems, how much they don’t like themselves, that they were locked up in the mental hospital etc. On a daily basis that probably isn’t the world’s best for mental health.”

Participant 2 similarly described that the amount of time she spent listening to sad music needed to be limited. “Sometimes I kind of need it to know that other people feel the same way… But there does come a point when you are feeling bad enough and then that would make you feel worse and it’s something you have to stay away from.” Participant 6 also mentioned a time when she had been listening to songs about suicide “quite a few times…too much” with negative results. Thus, there was a recognition that intense or frequent listening to music that reflected negative thinking was likely to have a more negative impact on wellbeing.

Nature and Intensity of the Prior Affective State

Being in a low negative mood state was frequently mentioned as a factor that would result in music listening having a negative or neutral effect on mood. For example, Participant 4 said: “If I am having a really bad day then nothing I do will really change that.” She also stated that, “When I’m in a more neutral mood I can change my emotions according to what I’m listening to but when I’m really sad nothing helps.” Similarly, Participant 7 commented that it’s the strength of his mood that influences how easy it is to modify with music: “Some moods are harder to shake.”

A number of participants described using music to distract from, or mask unpleasant emotional states. For example, Participant 6 described herself as having “an anxiety disorder” and being able to use music to “distract” herself or “calm” herself down. Although this strategy was sometimes described as helpful in alleviating the intensity of emotional experiences, some participants also acknowledged the temporary nature of this solution. For example, Participant 7 stated that music could not remove anxious feelings altogether, but that it would just “temporarily mask the depression” and then he would “be back to square one” when the music finished. Similarly, Participant 6 stated that “on the spot it’s useful because I’m just thinking about the music, I’m forcing myself not to think about what’s making me anxious but when I stop everything comes back.” Thus, some participants identified that ‘covering up’ emotions were a short-term and somewhat limited solution.

Strategies also appeared to differ depending on the individual’s mood. Participant 3 said that when she was feeling sad she usually chose music that matched her mood because she found it “comforting” and “reassuring.” However, when angry she would listen to music that she hoped would change her mood.

In examining some of the factors that influenced the outcome of music listening for people with symptoms of depression, it seemed possible that a key factor was the level of awareness and consciousness with which individuals selected music. Selective coding allowed us to explore the data in order to further test this theory. In order to overcome previous study limitations which have demonstrated that individuals do not always directly report negative effects of listening to music, coding strategies here looked not only at clear statements relating to awareness, but at other indications such as inconsistent responses or signs of ambiguity or confusion. Upon direct request, most participants were able to list a song or a type of music that had previously caused a deterioration in mood for them. For example, Participant 4 reported that listening to “emo” music had previously had a negative effect on her mood. Participant 1 similarly described listening to Elliott Smith and realizing that her mood was “continually low.”

It was evident that for several participants their insight into the potential for music to have negative effects was something they had gained over time, usually after some negative experiences. For example, Participant 5 stated:

“It’s something I’ve developed over time. It’s like a mechanism I’ve developed as I got more used to having mental health problems…I used to listen to a lot of punk rock stuff and all that kind of emo stuff nonsense and it just used to make me much more worked up because it’s so intense that it does not help. But it took me quite a long time to realize what was happening.”

Awareness was obtained in several ways. Some participants were made more aware by the comments of friends and family. Participant 5 made the following statement.

“My family members were like, ‘This is too intense. Why are you listening to this? You are obviously struggling.’ There is a history of mental illness in my family so they are quite good at knowing how to deal with it. And I was like, ‘No it is helping’… until I heard a few people my own age say that it’s not working. She similarly said: “Some of my friends had some of the same issues and they said how they listened to some music that made them feel worse and I was like “oh maybe they have figured out what’s wrong with me too” and I sort of realized that.”

Of note in Participant 5’s comments is the fact that she had at first believed that the music was helping her, but she ultimately identified with the experience of friends who noted that it was not always as helpful as it could be.

For Participant 6 it was therapy that had helped her to become more aware of her listening habits. She made the following statement:

“When I was younger I did have a tendency to just listen to songs more, especially if they made me sad and they emphasized my mood. Now, I would take a break from them and listen to something different because I’m trying, well not trying to control my mood but it was one of the things I discussed with my therapist. I was not trying not to hurt myself more, but trying to not feel worse about things.”

For Participant 1, the realization appears to have come to her personally without prompting from other people. “I began to think, ‘Well maybe it’s listening to this stuff which is really contributing to my being in a very low mood, so I had to stop then.” She reported realizing that listening to particular music with suicidal lyrics had “brought [her] into a more negative mood.”

However, there was some evidence that despite a recognition of the negative effects of past experiences, this did not always translate into an awareness of the potential impact of current listening behaviors. Several participants seemed to lack clarity in their own mind about whether particular listening was useful or not. This was evidenced by some inconsistent statements within the interviews. For example, when Participant 4 was asked what she listens to when she is in a low mood she said: “emo music.” However, when asked to describe a situation where music had made her feel worse she described how in high school emo music had made her “feel worse.” When asked again whether she would do the same thing now, she said: “Probably not.” In this case, the participant recognized some negative effects in the past but still reported the same listening choices. However, asking the participant to reflect on the past negative experience caused her to change her answer about current listening choices. Whether or not this reflected an actual change in opinion is unclear.

Participant 6 was similarly somewhat ambiguous about whether her listening choices made her feel worse. As cited above, this participant reported discussing with her therapist about avoiding music that made her feel “worse about things.” She seemed to have some useful strategies for regulating her mood such as listening to music that is “sad” but that gives her “some optimism,” or music that gave her some relief in that after listening she was “still sad but less heavy.” However, when speaking about a previous experience she made the following statement.

“I don’t know if it made me feel worse…but there was this one song about suicide that I remember listening to…the song itself kind of hit close to home at that moment… I was just getting really perturbed because I was listening to the lyrics too much.”

When asked if she would listen to the same song again she said “sometimes I do,” but preferred not to listen to it when in a good mood because it “brings back memories.” Thus, while this participant appeared to have some awareness of her complex responses to certain music in the past, she sometimes seemed to revert to unhealthy patterns in periods of depression. Of note with this participant was a recognition that the message in the lyrics – whether suicidal or optimistic – was an important factor even when the music was “sad” overall, with the former tending to make her feel worse, while the latter helped her to feel “like someone understands.”

Similarly, Participant 1 gave some conflicting statements in reference to her preference for listening to Elliott Smith and his music with suicidal themes when feeling depressed. At first when describing her response to this music she stated, “I just kind of think, ‘Oh God, this is just so sad and so depressing.’ I kind of sit there and think ‘oh woe is me’.” She also reported having had to stop listening to this music at one stage because she had been getting too depressed, and stated that the music “probably just intensified the emotion.” However, when the interviewer introduced the question of whether some other listening choices might be more helpful, the participant was quick to justify her preferences stating, “If I listen to depressing music when I’m depressed it does have some benefits.” Music was intensely important to this participant. She reported listening to music much of each day and spending a lot of time reading about musicians and their lives. The type of music she listened to appeared to be closely connected to her sense of identity, and her attraction to music that was meaningful and musically “masterful,” something which she associated with singer-songwriters such as Elliott Smith. Thus, for this participant there appeared to be some resistance to the idea that such music choices could have a negative influence on mental health despite a recognition of past negative experiences.

Participant 2’s approach contrasted with the other participants. She described herself as having been better in recent years, but even when going through a period of depression, her music listening choices did not necessarily have a negative outcome. She described using music as a temporary thing to escape from her difficulties. “I remember there were times when I would find a 12 min piece and just put my headphones on, turn it up, probably too loud, and then sit there and enjoy it for 12 min and that was 12 min that I didn’t have to deal with everything else.” This demonstrated some intentionality of music use, but not necessarily an ability to sustain the wellbeing benefits with music. Participant 4 similarly described her approach to music listening when depressed as “a way of soothing my emotions rather than solving them.”

Thus the participants in general described unconscious listening that worsened their mood as a past way of using music when they had little to no insight about their emerging mental health problems. This suggests that when participants were not aware of how poor their mental health was becoming, they used music in ways that contributed to their deterioration and stopped once something challenged them – the realization of depression, comments by family or friends, or therapy. However, the same listening behaviors sometimes seemed to continue or re-occur in current circumstances especially when there was a deterioration in wellbeing.

Pathways to More Conscious Music Use

The emphasis placed by grounded theory analysts on actions and interactions encourages modeling of diverse pathways through a phenomenon ( Strauss, 1987 ; Morse et al., 2016 ). For this study, the findings suggested a model of the pathways young people with symptoms of depression take through music use that reflect differing strategies for dealing with undesirable moods (see Figure 2 ). The model demonstrates how listeners may have the intention to either cope with or to change an undesirable mood, but outcomes vary depending on the strategy used, which in turn is influenced by the individuals’ fluctuating level of awareness. In this model, individuals have the antecedent condition of depression and are influenced in their music listening selections by the central condition, which is the state of being in an undesirable mood. They then exercise their intention to either cope with their mood or change their mood through strategies that involve selecting either mood matching music or music that is different to their mood. These selections are influenced by their own changing levels of awareness which in turn, are influenced by intervening conditions such as negative experiences or discussions with family, friends, or a therapist. These differing strategies can have varying outcomes, with mood matching music generally leading to either maintenance of mood or feeling worse, and listening to music that is different to the initial undesirable mood generally resulting in mood repair or a temporary change to mood.

Model of the pathways young people with depression take in using music to deal with negative affective states.

This study focused on exploring the degree to which young people with symptoms of depression are aware of the effect their music listening choices have on mood and wellbeing, and how they reach that state of awareness. Our findings demonstrated that most young people in our study reported past behaviors reflecting limited awareness and unconscious motivations, often with undesirable outcomes. However, intervening conditions including insights gained from friends, family, a therapist or through self-reflection, resulted in some increased awareness. Previous research has demonstrated that increased awareness of the effect of music listening choices can be deliberately influenced, such as through use of the Healthy-Unhealthy Music Scale as an awareness raising tool ( Saarikallio et al., 2015 ; McFerran et al., 2018 ).

However, in the current study, some young people demonstrated an initial resistance to increased awareness, or a reversion to previous unhelpful patterns of music listening even after reaching a level of awareness, particularly during depressive episodes. Thus, the pathways young people took through music listening and awareness of the effects of their music listening choices were not always linear. Skill building appeared to be a gradual process of discovery by continual cycling through varying intentions, strategies and outcomes, with new levels of consciousness being reached as new events and experiences challenged old behaviors.

Of note in the current study was that some participants described being more able to use music to change states such as anxiety or anger even when these were quite severe, but were less inclined to use this strategy when feeling depressed. When seeking to change an anxious mood, for example, participants reported listening to calming music – music that did not match their current mood. In contrast, when dealing with depression, many of the participants reported using music that maintained their current mood in order to feel validated and to have their feelings acknowledged.

While the intention of participants was to use music to help them cope with their depressed mood, this sometimes resulted in intensifying the state. It may be that the different interactional strategies used in each case contributed to the differing outcomes since research suggests that listening to mood shifting music is often more effective than listening to sad music when feeling depressed ( Garrido and Schubert, 2015b ). Alternately, it may be that anxiety is more amenable to influence by music listening. In a systematic review of studies relating to music and people with dementia, for example, it was found that music can reliably reduce agitation in patients, while the effects of music on symptoms of depression are less consistent ( Garrido et al., 2018 ). Anxiety is often exacerbated by a fear of the symptoms of anxiety themselves ( Dugas et al., 2012 ), but calming music can reduce physiological symptoms of anxiety thereby inducing a relaxation response ( Hamel, 2001 ). On the other hand, depression is often closely related to thought patterns which may be less likely to be altered when listening to music, particularly if the music echoes the existing negative thoughts.

It may be this relationship between thought patterns and depression that can help explain why the benefits of listening to distracting music was sometimes time-limited, ceasing as soon as the song was over. This has further been noted in Cheong-Clinch’s study of adolescents with mental illness ( Cheong-Clinch and McFerran, 2016 ), where music was found to mediate mood momentarily, but it was more difficult for young people to achieve sustained benefits. As reflected in our findings, the content of the lyrics often had an influence on whether positive benefits were achieved. When participants listened to music that mirrored their current circumstances this appeared to have less desirable mood outcomes, possibly because listening to such music is akin to ruminating. In contrast, outcomes were more positive for participants in the current study when they listened to music with optimistic messages. Previous research has similarly demonstrated that the thoughts triggered by music have a greater impact on mood outcomes than features of the music itself ( Garrido et al., 2016 ). Thus, listening to music that is distracting as opposed to music that alters mood via shifting thought patterns, may be only of temporary benefit.

Nevertheless it is important not to ignore momentary benefits for people struggling with depression. Some theorists suggest that the cumulative benefits of positive moments can serve as protective factors that eventually lead to improved wellbeing ( Rutter, 2012 ). More pragmatically, young people who are struggling with suicidal thoughts appreciate even small periods of escape ( Cheong-Clinch and McFerran, 2016 ). Such brief distractions are helpful in that they reduce time spent ruminating and can reduce the incidence of self-harm and suicide attempts ( Polanco-Roman et al., 2015 ). Furthermore, studies in music therapy have indicated that selecting music that matches one’s mood as the beginning point of a process that gradually shifts toward more positive music – a strategy known as the iso-principle – can produce a more enduring repair of mood ( Davis et al., 2008 ). The participants in the current study did report experiencing some lessening of the intensity of their negative moods after listening to mood-matching music. It is possible that for some, the reduced intensity of their negative moods was the beginning of a process of recovery. However, the data in this study did not reveal this clearly, and it is likely that the long-term outcomes of this process differ from individual to individual particularly in situations where the person has a high level of unawareness about the thinking patterns and emotions being triggered by the music.

Clinical Implications

While some participants in this study described reaching awareness of their strategies for music use on their own, external input such as from friends, family or a therapist was also described and has been categorized as intervening conditions in Figure 2 . Although this may suggest that telling young people to be more careful about their music listening could be beneficial, a broader cultural context is also at play. Young people report feeling resentful of the judgments made about their music choices, and one function of music is often described as being to assert an independent identity, beyond parental authority ( Laiho, 2004 ). In a previous study, we were able to encourage young people seeking support for depression to contemplate their music listening habits, but this occurred within a respectful conversation that involved both validating music preferences as well as dialoguing about consequences ( McFerran et al., 2018 ).

It is also common for caring adults to mistake the mechanism of action in this scenario and to blame the qualities of the music itself, rather than focusing on how music choices reflect mental health. This has historically been a point of contention between fans of heavier genres, such as Rock and Rap, and correlations are frequently found with antisocial behaviors ( Lozon and Bensimon, 2014 ). Nevertheless, a causal relationship between particular music genres and mental illness or problem behaviors has never been established ( North and Hargreaves, 2006 ). Rather, complex interactions between an array of personal and social mechanisms underlie our emotional reactions to music ( Juslin et al., 2015 ). Interventions that focus on self-reflection and raising awareness of the interaction between thoughts and feelings triggered by our music listening choices are likely to be more successful than those targeting particular music genres or styles.

There is ample evidence to demonstrate that people use music to improve their mood on a daily basis, both in everyday life ( DeNora, 2000 ; Saarikallio, 2007 ; McFerran et al., 2015 ; Papinczak et al., 2015 ) and in music therapy ( Maratos et al., 2009 ; Cheong-Clinch, 2013 ; Bibb and Skwews McFerran, 2018 ). There is also an emerging body of research which seeks to qualify these findings, since it is clear that music is not a magic pill that can immediately resolve a negative mood and nor is it always helpful. This research contributes to this second discourse, highlighting how individual’s uses of music can result in various outcomes depending on a range of factors. Individuals can use music listening to improve, maintain or intensify a mood, and may do any of these things at various times. Although it appears that people with depression are most likely to use music to intensify a negative mood, they are also the least aware of this tendency. This is further complicated by the finding that an individual can become aware of unhelpful listening habits, but can lose that awareness when in a depressive state and revert to intensifying strategies.

The current study is limited by the fact that the sample was primarily female. This gender imbalance is not unusual in studies relating to mental health (see for e.g., Lindner et al., 2016 ), and is likely a reflection of the higher rates of depression among females ( Freeman and Freeman, 2013 ). Nevertheless, future studies could benefit from recruitment of a more balanced sample so as to explore gender differences in strategy selection and outcomes of music use. Future research should also consider the influence of cultural context. The current study included at least one participant from a non-English speaking background. While music tastes among young people are becoming increasingly globalized ( Cicchelli and Octobre, 2017 ), culture nevertheless has an impact not only on music selections, but on the way individuals value particular emotional experiences ( Oishi et al., 2007 ).

Using music to influence mood is likely to continue to be a popular strategy for many people, both in their everyday life and through music therapy or other therapeutic contexts. Therefore, our ability to predict when this is likely to be more or less helpful and to develop strategies for supporting people during the most difficult moods is critical. However, the nuances of the pathways through music listening and toward an improved mood are complex and need to be individually identified and negotiated. The findings from this research indicate that promoting awareness of the power of music to enhance any mood is helpful, but that we should be prepared for circuitous pathways and open to change in all directions when people engage with their preferred music.

Ethics Statement

The study was approved by the Human Ethics Committee of the University of Melbourne. Written consent was provided by all participants.

Author Contributions

SG and KM developed the initial project design. JS and SG undertook the data collection. All authors contributed substantially to data analysis, write up, and development of the conceptual model.

Conflict of Interest Statement

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.

Appendix: Interview Guide

• simple (1) Could you start by telling me what kind of music you like?
• simple (2) How important is music to you in your life?
• simple (3) Is it something you listen to every day?
• simple (4) Do you tend to focus on it most of the time or is it just in the background?
• simple (5) How important are the lyrics in the music?
• simple (6) Do you ever find yourself listening to music to try to influence your mood one way or another?
• simple (7) What sort of effect would it have on you when you do that?
• simple (8) Would you find it annoying to listen to something upbeat when you are feeling low?
• simple (9) Have you ever listened to music that made you feel worse?
• simple (10) Do you think its possible that sometimes music could make you feel worse? If so, what kind? When and how?
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Life-long music and dance relationships inform impressions of music- and dance-based movement therapies in individuals with and without mild cognitive impairment

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Background No effective therapies exist to prevent degeneration from Mild Cognitive Impairment (MCI) to Alzheimer’s disease. Therapies integrating music and/or dance are promising as effective, non-pharmacological options to mitigate cognitive decline.

Objective To deepen our understanding of individuals’ relationships (i.e., histories, experiences and attitudes) with music and dance that are not often incorporated into music- and dance-based therapeutic design, yet may affect therapeutic outcomes.

Methods Eleven older adults with MCI and five of their care partners/spouses participated (4M/12F; Black: n=4, White: n=10, Hispanic/Latino: n=2; Age: 71.4±9.6). We conducted focus groups and administered questionnaires that captured aspects of participants’ music and dance relationships. We extracted emergent themes from four major topics, including: (1) experience and history, (2) enjoyment and preferences, (3) confidence and barriers, and (4) impressions of music and dance as therapeutic tools.

Results Thematic analysis revealed participants’ positive impressions of music and dance as potential therapeutic tools, citing perceived neuropsychological, emotional, and physical benefits. Participants viewed music and dance as integral to their lives, histories, and identities within a culture, family, and/or community. Participants also identified lifelong engagement barriers that, in conjunction with negative feedback, instilled persistent low self-efficacy regarding dancing and active music engagement. Questionnaires verified individuals’ moderately-strong music and dance relationships, strongest in passive forms of music engagement (e.g., listening).

Conclusions Our findings support that individuals’ music and dance relationships and the associated perceptions toward music and dance therapy may be valuable considerations in enhancing therapy efficacy, participant engagement and satisfaction for individuals with MCI.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study was supported by the National Institute of Child Health and Human Development under award number F32HD108927. This research was also supported by Emory University through a Goizueta Alzheimer's Disease Research Center CEP Innovation Accelerator Seed Grant, and an award from the Emory University Senior Vice President of Research Intersection Fund.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Institutional Review Board at Emory University (STUDY#:00003507) approved this study. All participants provided written, informed consent prior to study participation.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

All data produced in the present study are available upon reasonable request to the authors.

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