This study explores listeners’ experience of music-evoked sadness. Sadness is typically assumed to be undesirable and is therefore usually avoided in everyday life. Yet the question remains: Why do people seek and appreciate sadness in music? We present findings from an online survey with both Western and Eastern participants (N = 772). The survey investigates the rewarding aspects of music-evoked sadness, as well as the relative contribution of listener characteristics and situational factors to the appreciation of sad music. The survey also examines the different principles through which sadness is evoked by music, and their interaction with personality traits. Results show 4 different rewards of music-evoked sadness: reward of imagination, emotion regulation, empathy, and no “real-life” implications. Moreover, appreciation of sad music follows a mood-congruent fashion and is greater among individuals with high empathy and low emotional stability. Surprisingly, nostalgia rather than sadness is the most frequent emotion evoked by sad music. Correspondingly, memory was rated as the most important principle through which sadness is evoked. Finally, the trait empathy contributes to the evocation of sadness via contagion, appraisal, and by engaging social functions. The present findings indicate that emotional responses to sad music are multifaceted, are modulated by empathy, and are linked with a multidimensional experience of pleasure. These results were corroborated by a follow-up survey on happy music, which indicated differences between the emotional experiences resulting from listening to sad versus happy music. This is the first comprehensive survey of music-evoked sadness, revealing that listening to sad music can lead to beneficial emotional effects such as regulation of negative emotion and mood as well as consolation. Such beneficial emotional effects constitute the prime motivations for engaging with sad music in everyday life.

Funding: The study was funded by the Cluster of Excellence “Languages of Emotion” of the Freie Universität Berlin. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and in the Supporting Information file labelled “ Dataset S1 ”.

Copyright: © 2014 Taruffi, Koelsch. This is an open-access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

The aim of this study was to provide a better understanding of why people engage with sad music. We collected responses from a large multi-ethnic sample of participants, covering diverse age groups, through means of an online survey. In particular, we focused on the rewarding aspects of music-evoked sadness suggested by Levinson [14] , as well as the relative contribution of listener characteristics (e.g., mood and personality) and situational factors to the appreciation of sad music. Because our knowledge of how many listeners experience sadness in response to sad music is largely based on very limited data, and because emotions other than sadness can also be elicited by sad music [17] , [20] , another purpose was to identify the most frequent emotions experienced in response to sad music. Furthermore, we also examined the role of the above-mentioned principles [39] , [40] in evoking sadness as well as their interaction with personality traits. Because we obtained responses from a multi-ethnic sample of participants, we further compared the Western and Eastern participants’ responses to investigate whether broad cultural differences influence the reward and/or the emotional experiences associated with listening to sad music. Finally, to further discriminate which uses and rewards are specific to sad music compared to other types of music (e.g., happy music), we distributed a second survey on happy music to another sample of participants.

Emotions can be evoked by music in different ways. Several researchers [38] – [40] theoretically introduced a number of principles through which music listening may evoke emotions. The principles underlying emotional responses to music encompass e.g., appraisal, evaluative conditioning, contagion, memory, expectancy, imagination or visual imagery, understanding, rhythmic entrainment, and social functions [39] , [40] . To date, no evidence has been published indicating the most relevant principles through which sadness is usually evoked. Moreover, it still needs to be established whether different personality types contribute to elicit sadness through specific principles.

With regard to the listener characteristics, individual differences in personality traits can help to clarify why some listeners strongly appreciate sad music while others avoid it. Surprisingly, relatively few studies have specifically assessed the contribution of personality to the inclination of listening to sad music [18] – [20] . Vuoskoski and colleagues [20] discovered that openness to experience, global empathy and its subscales, fantasy, and empathic concern significantly correlate with liking of sad music and intensity of emotional responses evoked by sad music. Moreover, Vuoskoski and Eerola [19] found that global empathy and its subscales, fantasy, and empathic concern contribute to sadness evoked by unfamiliar music, while only fantasy plays a role in the case of familiar music. On the other hand, Garrido and Schubert [18] showed that absorption and musical empathy predict enjoyment of negative emotions in response to music. Thus, although more empathic individuals seem to appreciate sad music more than less empathic individuals, further studies could help to specify the nature of the association between the trait empathy and the appreciation of sad music (e.g., whether it is due to a specific use of sad music in more empathic individuals). Another factor representing a good candidate for modulating the appreciation of sad music is mood. Moods are affective states lower in intensity and longer in duration than emotions, and usually not directed at any specific object [35] . A number of studies reported mood-congruent effects on liking of sad music [36] , [37] . For example, Schellenberg and colleagues [37] statistically eliminated the typical preference for happy music over sad music after a demanding distractor task (which aimed to induce a negative mood in the participants). Moreover, Hunter and colleagues [36] were able to attribute this effect to sad mood, by showing that liking of sad music increases when listeners are in a sad mood.

With regard to situational factors, music-evoked emotions are strongly influenced by the situational conditions of exposure to music [29] – [31] , as well as by the purpose that music serves in a given situation [32] . Thus, the investigation of the situational factors underlying engaging with sad music is important to understand why sad music is appreciated (if individuals actively choose to listen to sad music, then we can assume that they appreciate such music). Although no direct evidence has been published concerning the situations in which people engage with sad music, two qualitative studies identified a number of explicit functions achieved by listening to sad music, such as re-experiencing affect, cognitive, social, retrieving memories, friend, distraction, and mood enhancement [33] , [34] . However, because these studies are limited by their small sample sizes (for example, only five participants were recruited by Garrido and Schubert [33] ), further research should extend their findings to a broader population.

Although the existing literature reports a wide range of responses to sad music, varying from “like” to “dislike” or even “hate” [18] , [20] , [28] , very little is known about which factors modulate the appreciation of sad music. Nevertheless, situational factors and listener characteristics might explain a significant portion of the variance in the emotional and aesthetic responses evoked by sad music.

In addition to Levinson’s theory, Panksepp [26] found that sad music is more effective for arousing “chills” (i.e., intensely pleasurable responses to music) than happy music. Consequently, he argued that the neural substrate of social loss might entail similar neurochemicals (e.g., oxytocin or opioids) involved also in the “chill” response [26] , [27] . Furthermore, Huron proposed that the pleasure experienced through sad music is due to the consoling effects of prolactin, a hormone usually released when people are sad or weeping [28] . However, no direct evidence is yet available for a role of prolactin, and there is a lack of empirical data supporting any of the proposed theories [14] , [26] , [28] .

Preliminary evidence for the rewards of music-evoked sadness can be found in studies which showed that pleasant emotions, such as blitheness and wonder, are elicited in response to sad music [17] , [20] , [22] , [23] . Because it is well established that pleasure refers to the subjective hedonic component of reward [24] , [25] , the pleasant emotions evoked in these studies may be, for instance, the outcome of any combination of the above-mentioned rewards of music-evoked sadness.

If music-evoked sadness is, at least for some individuals, a rewarding or valuable experience, what, then, are the rewarding aspects of such an experience? In the field of philosophy, Levinson [14] investigated this problem, suggesting reward as a key concept to explain the attraction to negative emotions, and in particular to sadness, in music. He proposed that eight types of reward contribute to the appreciation of music-evoked sadness. Two are external contributions: The first, apprehending expression, is linked to the observation that negatively valenced responses to music facilitate our grasp of the expression in a musical work [21] . The second consists of the Aristotelian theory of catharsis [11] applied to the musical domain. According to this theory, the negative emotional tone of sad music offers listeners the possibility of a controlled purification from a certain amount of a negative emotion afflicting them. The other six rewards are divided into two groups. The first group includes the following rewards: savoring feeling (i.e., savoring the qualitative aspects of sadness for its own sake); understanding feeling (i.e., sadness is perceived and appraised more clearly); and emotional assurance (i.e., music-evoked sadness allows listeners to reassure themselves about their ability to feel intense emotions). These rewards share the characteristic of being detached from contextual implications. This means that music-evoked sadness is not directed at any extra-musical (“real-life”) circumstance that could evoke sadness, and, therefore, is deprived of its aversive aspects (e.g., grieving due to the loss of a loved one). The second group includes three other rewards: emotional resolution (i.e., a sense of mastery and control listeners derive from identifying themselves with sad music resolving happily); expressive potency (i.e., identifying with the music to the point of imagining oneself to have the same richness and spontaneity of the sadness expressed by music); and emotional communion (i.e., sharing the sadness of another human being such as the composer). These last rewards are closely connected to the ability to imagine oneself in the emotional condition portrayed by the music. According to Levinson’s theory, imagination and freedom from “real-life” implications mediate the passage from music-evoked sadness to music-evoked reward. However, such rewards have not yet been empirically investigated.

Transient sadness is a so-called basic emotion that can be observed in people, independent of cultural background [1] . Sadness is characterized by low physiological and physical activity, tiredness, decreased interest in the outer world, low mood, rumination, decreased linguistic communication, and a withdrawal from social settings [2] – [5] . Moreover, sadness is particularly associated with the awareness of an irrevocable separation, the loss of an attachment figure or of a valued aspect of the self, as well as the breaking of social bonds [6] – [10] . Thus, the experience of sadness is typically assumed to be undesirable and is therefore usually avoided in everyday life. Hence, the question arises as to why people seek and appreciate sadness in music. The appeal of sad music has always been a crucial issue in aesthetics from ancient [11] to modern times [12] – [15] . It is remarkable that, despite so much philosophical debate, there is still broad disagreement about this fundamental aspect of the aesthetic experience. Nevertheless, both the scientific and the philosophical literature have consistently reported that, in addition to sadness, sad music also elicits pleasurable emotions, ranging from a sense of relief to a state of profound beauty [13] , [16] , [17] . However, it is difficult to draw conclusions concerning the nature of the pleasure experienced in response to sad music (e.g., whether this is due to the appraisal of musical and acoustic features or to other types of cognitive or emotional processes) due to the lack of empirical research on the topic. The study of the relationship between sadness and pleasure has been largely neglected by psychological research on music and emotion, which predominantly has focused on other aspects of the problem such as the role of individual differences [18] – [20] or the relationship between felt and perceived emotion in response to sad music [17] .

The final part of the survey included two measures of individual differences in trait empathy and personality factors. Empathy was assessed via the Interpersonal Reactivity Index (IRI) [45] . The IRI includes 28 items, divided in four sub-scales measuring the following related aspect of emotional empathy: fantasy; perspective-taking; empathic concern; and personal distress. As a means of limiting the experimental procedure to a maximum of 20 minutes, personality traits were assessed by the Ten-Item Personality Inventory (TIPI) [46] . This is a brief version of the Big Five Inventory (BFI) [47] and it covers the following five personality domains: extraversion; agreeableness; conscientiousness; emotional stability; and openness to experience.

In the sixth section participants were asked to provide one or more example(s) of their favourite sad music (either instrumental or with lyrics). This question was included because respondents were provided with neither a definition of sad music nor examples of sad music in the survey, but were instead instructed to focus on “self-identified sad music” (as in Van den Tol and Edwards [34] ). Given that “self-identified sad music” may represent music that does not sound “sad” to any other listener (for example, because of personal associations with the music, such as the break up of a relationship), we examined the examples of sad music provided by participants to determine whether they are consistent with the Western cultural conventions of representing sadness in music. Specifically, we made use of the tagging system supported by the online music database www.last.fm . In addition, we retrieved a number of acoustic and musical features of the instrumental pieces named by the participants (for details see the Results section).

Participants were then presented with 13 items devised to explore possible rewarding aspects of music-evoked sadness. These items (see Table S3 ) were designed on the basis of Levinson’s theory on negative emotions [14] and integrated with three items indicated by previous studies on sad music and emotion regulation [28] , [34] , [42] – [44] . All ratings were provided on a 7-point Likert scale (1 = strongly disagree and 7 = strongly agree).

The fourth section consisted of a 7-item questionnaire designed to evaluate the role of different principles underlying the evocation of sadness in listeners [39] , [40] . However, not all of these principles were suitable to be translated into clear statements. Thus, the present study used only those which could have been reasonably operationalized by the use of self-reports (i.e., memory, imagination, contagion, appraisal, and social functions; see Table S2 for the list of items). Ratings were given on a 7-point Likert scale (1 = strongly disagree and 7 = strongly agree).

The third section comprised items on sad music listening habits, including: frequency of listening to sad music; situation-related factors and their importance for listening to sad music; liking of sad music according to the listener’s mood (positive and negative); and emotions evoked by sad music (see Table S1 for the list of items). Participants provided quantitative ratings on 7-point Likert scales for the first three items. In addition to the ratings, the item related to the situational factors was designed as an open-ended response where participants were asked to provide one or more examples of situations in which they engage with sad music. The explanatory nature of the open response was adopted to be able to draw conclusions on the motivations for selecting sad music with regard to the situational factors. For the last item, “emotions evoked by sad music”, participants were asked to indicate the emotions that they frequently experience when listening to sad music. They could select either one or more emotions from the nine emotions listed in the Geneva Emotional Music Scale (GEMS-9) [23] , or add their own alternative responses. Furthermore, participants were given the opportunity to answer that sad music does not evoke any particular emotion in them. The GEMS was selected as ideal instrument to measure the subjective emotional experience of participants, because it provides a nuanced assessment of music-evoked emotions [23] , [41] . It comprises nine categories (wonder, transcendence, tenderness, nostalgia, peacefulness, power, joyful activation, tension, and sadness), which condense into three main factors: sublimity; vitality; and unease.

The survey was divided into seven sections (further details are explained below): (1) Core Details; (2) Musical Training and Musical Engagement; (3) Sad Music; (4) Principles Underlying the Evocation of Sadness by Music; (5) Rewarding Aspects of Music-Evoked Sadness; (6) Favourite Sad Music; and (7) Personality Questionnaires. Items were randomised among each section.

Data were collected using an online survey. In total, the survey featured 76 items. Participants were instructed to complete the survey individually, and in a quiet environment without listening to any music. The survey was programmed and administered online between the 3 rd of February and the 3 rd of June 2013, using the software Unipark (Unipark, Germany; www.unipark.info ). The average duration to survey completion was 20 minutes.

Data were obtained from 772 individuals: 495 females (64.1%) aged 16–78 years (M = 28.3, SD = 9.0) and 277 males (35.9%) aged 16–68 years (M = 28.6, SD = 8.1). 408 participants grew up in Europe (52.8%, 266 females), 224 (29.1%, 128 females) in Asia, 122 (15.8%, 88 females) in North America, 10 (1.3%, 7 females) in South America, 6 (0.8%, 5 females) in Australia, and 2 (0.2%, 1 female) in Africa. With respect to their musical training, 40 (5.2%, 31 females) respondents reported to be professional musicians, 66 (8.5%, 31 females) semi-professional musicians, 230 (29.8%, 143 females) amateur musicians, and 436 (56.5%, 290 females) non-musicians. With regard to their musical engagement, 500 (64.8%, 319 females) participants reported being music lovers, 262 (33.9%, 168 females) liking music, and 10 (1.3%, 8 females) not being music lovers.

The present study was an online survey which was completely voluntary and anonymous, i.e. no personal data were collected except age, gender, and nationality. Moreover, no financial compensation was provided. We obtained informed consent from all participants through an online form with which the survey started. However, it was not possible to obtain an additional informed consent from the guardians on behalf of the under-aged subjects (6 subjects with minimum age 16). Obtaining such an informed consent from a guardian wouldn’t have been possible, given that the survey was completely anonymous. Informing under-aged participants that they could not take part, would still have left the opportunity that they might take part without their guardians approval by entering an incorrect (older) age. These issues can thus be considered as a general problem that applies to web-based anonymous surveys. Nevertheless, we made sure that the survey did not feature any material/question that could have posed any negative influence or risk on minors. In addition, participants were informed that they could withdraw at any time without giving a reason and without any negative consequence. Participants were recruited through electronic mailing lists of students and through the newsletter of the Cluster Languages of Emotion. The study was conducted according to the Declaration of Helsinki and approved by the ethics committee of the Psychology Department of the Freie Universität Berlin. Because in the ethics application nothing was stated about the age of participants, we therefore assume that the ethics committee did not see anything critical about the questions being answered by minors.

Results

Which are the rewarding aspects of music-evoked sadness? A principal component analysis (PCA) with oblique rotation (direct oblimin) was carried out on the ten items describing the rewarding aspects of music-evoked sadness (in the preliminary analysis three items were excluded because of their low correlations). The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = .83, and all KMO values for individual items were >.76, which is well above the acceptable limit of .5 [48]. Bartlett’s test of sphericity showed that correlations between items were sufficiently large for a PCA (χ2 (45) = 3402.65, p<.001). An initial analysis was computed to obtain eigenvalues for each dimension in the data. Four dimensions had eigenvalues over Jolliffe’s criterion of 0.7 and, in combination, explained 76.6% of the variance. Given the large sample size, and the convergence of the scree plot and Jolliffe’s criterion on four dimensions, these four dimensions were retained in the final analysis. Table 1 shows the factor loadings after rotation. The items that cluster on the same dimensions suggest to interpret dimension 1 as the reward of imagination, where music-evoked sadness has pleasurable effects due to the engagement of imaginative processes (e.g., “I imagine I have the same rich expressive ability as present in the music”). Dimension 2 represents the reward of emotion regulation, which includes statements about the rewarding effects derived from regulation of negative moods and emotions (e.g., “Experiencing sadness through music makes me feel better after listening to it, and thus has a positive impact on my emotional well-being”). Dimension 3 represents the reward of empathy, which includes statements about the pleasurable effects of music-evoked sadness due to mood-sharing and virtual social contact through the music (e.g., “I like to empathise with the sadness expressed in the music, as if it were another individual”). Dimension 4 represents the reward of no “real-life” implications, which includes statements about the pleasure listeners can take in music-evoked sadness due to its lack of contextual implications (e.g., “I can enjoy the pure feeling of sadness in a balanced fashion, neither too violent, nor as intense as in real-life”). With regard to the consistency of the extracted factors, imagination had high reliability (Cronbach’s α>.92) and no “real-life” implications, emotion regulation and empathy had good reliability (Cronbach’s α>.7). PPT PowerPoint slide

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larger image TIFF original image Download: Table 1. Factor loadings for explanatory factor analysis with direct oblimin rotation of the items describing the rewarding aspects of music-evoked sadness (N = 772). https://doi.org/10.1371/journal.pone.0110490.t001 A repeated-measures ANOVA, with type of reward (four levels) as within-subjects factor, was conducted to identify the most important rewards for the listeners. A significant main effect of type of reward was found, F(2.65, 2041.97) = 37.28, p<. 0001, ω2 = .99. Bonferroni pairwise comparisons showed that there were significant differences between the mean ratings for all four factors. Figure 1 shows that no “real-life” implications turned out to be the most important source of reward for the listeners. PPT PowerPoint slide

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larger image TIFF original image Download: Figure 1. Mean ratings for each of the four dimensions of reward identified. Error bars indicate standard error of the mean, ***a p-level of <.001, and *a p-level of <.05. https://doi.org/10.1371/journal.pone.0110490.g001 Only 31 participants (4% of all participants) took the opportunity to add their own alternative responses concerning other possible rewards that were not included in the list provided by the questionnaire. Due to the low number of responses, these answers did not provide representative information, and were therefore not further analyzed. However, to generate hypotheses for future studies, these answers are reported in the Table S4.

In which situations do listeners engage with sad music? Results indicate that situation-related factors play a significant role in the engagement with sad music. With regard to the following item, “How much do specific situations influence your choice to listen to sad music?”, ratings showed that situational factors are highly relevant to the choice to listen to sad music (M = 4.74, SD = 1.84, on a 7-point Likert scale ranging from 1 = not at all to 7 = a lot). 61.7% of participants (477 out of 772) provided ratings ≥5. To examine this issue further, an open-ended follow-up question asked participants to provide one or more examples of circumstances in which they engage with sad music, and to describe the function that sad music serves in those situations. A content analysis of the free responses revealed that there are several situations in which listeners engage with sad music, which are intrinsically linked to a wide spectrum of functions (i.e., emotional, social, cognitive, and aesthetic) that listening to sad music may potentially fulfill. Based on the previous literature [33], [34], the responses concerning the situational factors were grouped into the following categories (Table 2): emotional distress; social; memory; relaxation and arousal; nature; musical features; introspection; background; fantasy; avoiding sad music; intense emotion; positive mood; and cognitive. The category emotional distress includes situations in which the listeners are in a negative emotional state due to different reasons such as, for example, the loss of a loved one. In these circumstances, sad music is used as a tool for mood-enhancement (achieved, for example, through venting of negative emotion or cognitive reappraisal), consolation, or simply because it reflects the current mood. The category social comprises statements on social attachment and social bonding (e.g., people engage with sad music when they feel lonely or when they need to be accepted or understood), and is therefore linked to a consolatory use of sad music (achieved through mood-sharing or virtual social contact through the music). The category memory refers to situations in which sad music is chosen to retrieve autobiographical memories of valued past events or people. The category relaxation and arousal represents situations in which sad music is used as a tool to regulate arousal (e.g., quieting down before going to bed). The category nature refers to situations such as travelling, and being in contact with nature as well as to specific times of the day (i.e., evening) or of the year (i.e., winter). The category musical features is related to the aesthetic appreciation of sad music focused on the formal properties of the music, rather than on perceptions of emotional content. The categories fantasy, cognitive, and introspection represent situations in which sad music is chosen because of cognitive as well as self-related functions: Sad music is used respectively to engage creativity, to improve focus during work or while studying, and to cope with a personal problem by organizing thoughts and feelings. The category background refers to situations such as driving, reading or working, where sad music represents an optimal musical background. The category avoiding sad music comprises all the answers that stress a clear dislike for sad music, regardless of the different situational factors. The category intense emotion includes a number of situations in which listeners engage with sad music to experience intense emotions. Finally, the category positive mood includes the answers of the participants who reported to engage with sad music only when being in a positive emotional state, and, consequently, to avoid sad music when being in a negative emotional state. According to these respondents, sad music does not have any positive effect on emotional distress, but it rather contributes to perpetuate this negative affective state. PPT PowerPoint slide

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larger image TIFF original image Download: Table 2. Summary of the situations in which participants engage with sad music, and functions of listening to sad music in those circumstances. https://doi.org/10.1371/journal.pone.0110490.t002 The number of nominations for the different situational-categories is provided in Figure 2. As can be seen, listeners reported to engage with sad music especially when experiencing emotional distress. For instance, there is a striking difference between the frequency with which participants reported the situation-related category emotional distress (470 nominations) and the reported frequencies of all other categories (all fewer than 184 nominations). Emotional distress is a broad concept that refers to a variety of situations. To specify this concept, we reported the most popular examples given by the participants for emotional distress: “when feeling sad” (109 nominations); “when experiencing lovesickness or a break up” (108); “when grieving for a loss” (51); “when experiencing stress at work/university” (48); “when feeling angry after an argument” (44); “when experiencing frustration and being disappointed with myself” (41); “when needing to release negative feelings” (29); “when feeling melancholic” (22); and “when feeling like crying” (17). Furthermore, a considerable number of participants (184 out of 772) reported engaging with sad music when they feel lonely (i.e., category social), whereas a small number (16) reported engaging with sad music only while experiencing a positive emotional state (i.e., category positive mood). PPT PowerPoint slide

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larger image TIFF original image Download: Figure 2. The amount of nominations for each situation-related factor underlying listening to sad music. https://doi.org/10.1371/journal.pone.0110490.g002

Do mood and personality modulate the liking of sad music? Both the engagement with, and the liking of sad music occur more frequently in a mood-congruent fashion. For instance, 54.4% of participants (420 out of 772) provided ratings ≥5 on a 7-point Likert scale (1 = never, 7 = always) in response to the statement “When I am in a sad mood I like to listen to sad music” (M = 4.44, SD = 1.80). On the other hand, 32.7% of participants (253 out of 772) provided ratings ≥5 on a 7-point Likert scale (1 = never, 7 = always) in response to the statement “When I am in a positive mood I like to listen to sad music” (M = 3.60, SD = 1.56). A paired-samples t-test revealed that the difference between the ratings for the two items is significant (t(771) = 10.141, p<.0001, r = .34). A correlation analysis between the personality factors and the subscales of empathy with the variables of liking of sad music was performed to evaluate whether personality traits can modulate the liking of sad music. A Bonferroni correction for multiple tests was applied. Because significant correlations were weak (r<.2), the results (summarized in Table 3) should be interpreted with caution. However, to generate hypotheses for future studies, we also report these results. The mood-congruent liking of sad music positively correlated with global empathy (r = .114, p<.01) and its subscales, fantasy (r = .160, p<.01), and personal distress (r = .108, p<.01). A similar pattern was observed for the mood-incongruent liking of sad music, which positively correlated with global empathy (r = .109, p<.01) and its subscales, fantasy (r = .116, p<.01), and perspective taking (r = .142, p<.01), but not with personal distress (r = −.052, p>.05). Moreover, the mood-congruent liking of sad music negatively correlated with emotional stability (r = −.123, p<.01). PPT PowerPoint slide

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larger image TIFF original image Download: Table 3. Correlations between the mean ratings for the liking of sad music and personality traits as measured by the TIPI and IRI. https://doi.org/10.1371/journal.pone.0110490.t003

Which emotions are most frequently experienced in response to sad music? The survey featured an item in response to which participants indicated the most frequent emotions evoked by sad music. They could select more than one option and/or add their response alternatives (free responses are reported in Table S5). Figure 3 reports the number of nominations for each emotion. Surprisingly, nostalgia (76% of nominations), and not sadness (44.9%), was indicated as the most frequent emotion evoked by sad music. Moreover, participants also reported experiencing positive emotions, such as peacefulness (57.5%), tenderness (51.6%), and wonder (38.3%). Conversely, the percentage of nominations for joyful activation (6.1%) was low compared to the other emotions. PPT PowerPoint slide

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larger image TIFF original image Download: Figure 3. The most frequent emotions, as measured by the GEMS, evoked in response to sad music. https://doi.org/10.1371/journal.pone.0110490.g003 Interestingly, the average number of emotions that participants reported to have experienced in response to sad music (M = 3.33, SD = 1.56) correlated positively with both variables of mood-incongruent liking of sad music (r = .323, p<.01) and mood-congruent liking of sad music (r = .273, p<.01).

What is the importance of the theoretically discussed principles underlying the evocation of sadness? Participants who reported frequently experiencing sadness in response to sad music (N = 347) also rated to what extent they agreed/disagreed with each of the seven items (see Table S2) describing five of the principles underlying the evocation of sadness through music (i.e., memory, imagination, contagion, appraisal, and social functions). First, ratings were averaged across different items describing the same principle. Second, a repeated-measures ANOVA was conducted on the mean ratings for each principle, with principle type represented as a within-subjects factor, to establish which principles are most important in evoking sadness. A significant main effect of the type of principle was found, F(3.37, 1165.01) = 39.41, p<.0001, ω2 = .22. Bonferroni pairwise comparisons showed that there were significant differences between mean ratings for all five principles, with the exception of three non-significant differences between the mean ratings given on imagination and social functions, imagination and appraisal, as well as appraisal and contagion. Memory was rated as the most important principle underlying the evocation of sadness. However, all the principles were judged to be relevant (all means >4.5, on a 7-point Likert scale from 1 = strongly disagree to 7 = strongly agree). Figure 4 shows the mean ratings given to each of the five principles ranked in descending order. PPT PowerPoint slide

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larger image TIFF original image Download: Figure 4. Mean ratings for each principle underlying music-evoked sadness. Error bars indicate standard error of the mean, ***a p-level of <.001, and **a p-level of <.01. https://doi.org/10.1371/journal.pone.0110490.g004 The data also revealed gender differences for contagion. On average, contagion was rated higher by females (M = 5.40, SE = 0.74) than by males (M = 4.92, SE = 0.14), with this difference being significant (t(167.12) = −3.004, p = .003, r = .24, Bonferroni-corrected). To investigate whether differences in sadness-evocation styles might be associated with personality traits, a Pearson correlation analysis of the subscales’ scores of IRI and TIPI with the principles’ ratings was conducted. A Bonferroni correction for multiple tests was applied. The results (summarized in Table 4, only r>.2 are reported) reveal an association between empathy (total score plus all subscales) and sadness induced via contagion (r = .348, p<.001), via engagement in social functions (r = .399, p<.001), as well as via appraisal (r = .262, p<.001). Note that, although not reported in Table 4 (because r<.2), global empathy also significantly correlated with sadness induced via imagination (r = .184, p<.005) and via memory (r = .187, p<.001). Finally, contagion negatively correlated with emotional stability (r = −.296, p<.001). PPT PowerPoint slide

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larger image TIFF original image Download: Table 4. Correlations between the mean ratings for the principles underlying the evocation of sadness and personality traits as measured by the TIPI and IRI. https://doi.org/10.1371/journal.pone.0110490.t004

Are emotional responses to sad music the same across cultures? Eastern respondents provided lower overall ratings compared to Western respondents for all items featured in the survey, with the exception of ratings for the principle of social functions. The following significant difference was found: Western participants reported significantly (t(143.49) = 3.061, p = .003, r = .25, Bonferroni-corrected) higher ratings for the principle of memory (M = 6.00, SE = .08) compared to Eastern participants (M = 5.41, SE = .17). According to Eastern participants, the most frequent emotion evoked in response to sad music was peacefulness (117 of 219 nominations) followed by nostalgia (115 nominations). By contrast, the ranking of these two emotions for the Western participants was reversed, with nostalgia being the most frequent emotion (451 of 530 nominations) followed by peacefulness as the second most reported emotion (316 nominations).

Is “self-identified sad music” consistent with the cultural standards of representing sadness in music? We made use of the tagging system supported by the online music database www.last.fm to verify that the musical pieces named by the respondents can be considered culturally valid examples of sad music. Tags are keywords or labels that listeners can use to classify music. Musical platforms, such as last.fm, are used by millions of listeners and thus offer behavioural ratings from a sufficiently large sample of user tags. We examined the tags provided for the music examples nominated by participants in the survey. First, we inspected all musical pieces nominated more than once and second, all pieces nominated only one time. Participants reported 52 musical pieces (26 with lyrics and 26 instrumental) more than once, in a total of 165 nominations (see Table S7). Among these 52 pieces, 36 were tagged “sad” or “sadness” by last.fm users, and nine were assigned a “sadness-related” tag (e.g., “melancholic”). Three pieces received either very few or no tags and two were not found in the last.fm database. Only two musical pieces were not labeled “sad” or with a “sadness-related” tag. A total of 380 musical pieces (233 with lyrics and 147 instrumental) were mentioned only once by the participants (see Table S8). Forty pieces were not considered in the analysis because the title provided was too general (i.e., it referred to an album rather than a song or to a symphony rather than a movement). Moreover, 71 pieces received either very few or no tags and 18 were not found in the last.fm database. Among the remaining 251 musical examples, 168 were tagged “sad” or “sadness”, and 53 were labeled with a “sadness-related” tag. Only 30 musical pieces were not assigned either a “sad” or a “sadness-related” tag. Furthermore, through a large database of more than 30 million songs (see http://the.echonest.com/) we retrieved a number of acoustic and musical features of the instrumental pieces named by the participants, including tempo, loudness, mode, energy, dance ability, and “valence” (note that the term valence is used here to refer exclusively to the database’s musical attribute, which is derived from acoustic-driven information, not user tags; as indicated by the present data sad music can have a positive valence for listeners in certain circumstances). This was done in order to determine whether the example pieces contain musical parameters that have been consistently linked with sadness in Western music (e.g., slow tempo, low sound level, minor mode, low pitch, small intervals, legato, micro-structural irregularity, etc.; see [49]). Nominated songs with lyrics were excluded because lyrics may differ semantically from music-perceived emotion and may play a crucial role in evoking sadness [50]. Out of 142 instrumental pieces, 124 were retrievable in the database. Table 5 reports the descriptive statistics for the overall estimated tempo in BPM (M = 86.92, SD = 21.05), loudness in dB (M = −20.92, SD = 7.18), energy (M = 0.16, SD = 0.17), dance ability (M = 0.26, SD = 0.14), and valence (M = 0.13, SD = 0.14). Moreover, 52.41% of the musical pieces were written in a major mode and 47.58% in a minor mode. In addition, the energy and valence values of each piece were plotted onto a two-dimensional plane, according to the affective circumplex model of emotion [51]. Figure S1 shows that a large majority of the retrieved instrumental pieces nominated by our respondents (113 out of 124) fell into the low energy/negative valence quadrant. PPT PowerPoint slide

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larger image TIFF original image Download: Table 5. Descriptive statistics for the acoustic and musical features of the musical pieces nominated by the participants (N = 124). https://doi.org/10.1371/journal.pone.0110490.t005