Flow in music performance and music-listening: Differences in intensity,predictors,and the relationship between flow and subjective well-being

Abstract

Flow describes a state of total absorption in an activity. This optimal experience has received much attention in research on music-playing and performing, but not on interindividual differences in music-listening. We expect differences in the intensity of flow between performing music and listening to music and in the relationships with subjective well-being. In Study 1 (N = 207; questionnaire study), we investigated differences in flow between performing and listening to music in three dimensions of flow. We analyzed correlations between flow, previous musical training, music experience, and subjective well-being. Participants reported a more intense flow experience while listening to music than while performing music. Flow was significantly associated with subjective well-being and music experience. For performing music, flow was positively correlated with previous musical practice. Study 2 (N = 383; questionnaire study) focused on flow while listening to music and subjective well-being, and on the role a flexible self-concept plays in this phenomenon. Stronger relationships between flow and subjective well-being were obtained for individuals with a highly flexible self-concept. Flow was positively correlated with music experience. The results provided evidence for relationships between flow, previous musical practice, and music experience. Correlations with subjective well-being depend on processes of self-regulation.

Keywords

flow music-listening well-being musical engagement performing music

Common descriptions of the feeling of complete absorption in musical activities, referred to as flow (Nakamura & Csikszentmihalyi, 2002), include forgetting about time when playing an instrument, not caring about anything else but the music one is listening to and feeling extremely good about playing music. Previous research concerning flow and musical activities examined this state mostly in terms of situational and/or individual factors that facilitate its experience and its effects on various psychological processes (Manzano, de Theorell, Harmat, & Ullén, 2010; Pates, Karageorghis, Fryer, & Maynard, 2003; Sinnett, Jäger, Singer, & Antonini Philippe, 2020; Valenzuela, Codina, & Pestana, 2018). Most studies focused on music-playing, either in private or in performance or examination settings, but only a few on listening to music (Chirico, Serino, Cipresso, Gaggioli, & Riva, 2015; Pates et al., 2003). This paper therefore intends to take a first step, using self-reports comparing flow in music-playing with flow in music-listening, with a special emphasis on performing music. Broadening the focus to aspects of music-listening is important, especially when one considers the relevance of listening to music in everyday life. Another major line of research investigated flow experienced in musical activities in relation to subjective well-being (Croom, 2015; Georgi, von Bötsch, & Fedorov, 2016; Heller, Bullerjahn, & von Georgi, 2015; Smolej Fritz & Avsec, 2007). This line of research repeatedly showed a relationship between flow and subjective well-being. Again, previous research examined mostly music-playing, although listening to music could also be a potential source of well-being, possibly to a larger number of people. In this paper, we report two studies that investigated (1) differences in flow between performing music and music-listening and (2) the relationships between flow and well-being, especially for music-listening.

Flow and musical activity

Flow is described as a state of total absorption in an activity (Nakamura & Csikszentmihalyi, 2002), resulting from a perceived match of the challenges of an activity and personal skills. The experience of flow occurs when an individual is challenged by a given task that requires skills that are available. According to Csikszentmihalyi and LeFevre (1989), in order to evoke flow, an activity also needs to exceed the weekly average of challenges met and skills needed (see also Moneta, 2012). Furthermore, other affective states resulting from engagement in a given task can be distinguished from flow on this challenge-skill dimension. For example, if a situation is very challenging but one does not have the required skills, anxiety is more likely to be experienced –rather than flow; on the other hand, a situation may lead to apathy if both challenges and available skills are low. In addition to being challenging and requiring available skills, the task needs to be interesting and relevant for the person to not result in boredom (Moneta, 2012). Numerous studies on musical activities indicate that playing an instrument is a flow-evoking activity: it complies with the aforementioned prerequisites by challenging one’s skills and being a relevant task for instrumentalists (Chirico et al., 2015; Gaggioli, Chirico, Mazzoni, Milani, & Riva, 2017; Hart & Di Blasi, 2015; Manzano et al., 2010; O’Neill, 1999; Smolej Fritz & Avsec, 2007; Valenzuela et al., 2018).

Few studies have examined flow while listening to music. In an interview-study, Lamont (2011) found that participants, while listening to music, experienced flow-like states which they described as being absorbed by the music and losing a sense of the surroundings. In addition, the interviewees stated that flow often occurs in situations in which they were concentrating on the music. Diaz (2011) found that flow was a common reaction after listening to music but can be decreased by a previous mindfulness training. Analyzing participant’s description of the flow-experience, Diaz found that participants were focussing more on the cognitive aspect of flow, which might have decreased its affective component and thus the overall intensity of the flow-experience. Another explanation could be that music-listening may lose its autotelic character (finding pleasure in the act of music-listening itself), when combined with another, potentially conflicting activity. Both studies demonstrated that concentrating on the music increases the likelihood of experiencing flow and stress the importance of an intense engagement with the music to experience flow while listening. A high level of concentration and engagement in music-listening is also seen to be an important prerequisite for music-listening to evoke flow, as otherwise one can hardly experience a state of absorption (Csikszentmihalyi, 2009). Ruth, Spangardt, and Schramm (2016) provided empirical evidence for the influence of a concentrated form of music-listening (analytical music-listening) on flow, that is, lower levels of analytical listening reduce flow when listening to complex music. Bernardi, Bellemare-Pepin, and Peretz (2018) investigated the occurrence of flow while either listening and dancing to music or listening to music without moving. The results here showed that music listening does evoke flow, depending on the music listened to.

In sum, research on flow resulting from listening to music is scarce, which also was apparent in a systematic review of research on flow and musical activities (Chirico et al., 2015). Here, the authors report only one study that investigated flow while listening to music. Furthermore, no research investigated whether the experience of flow while playing music, especially in a concert performance with an audience, differs from the experience while listening to music.

Differences in flow between performing and listening to music

Performing music pertains to situations of performing in public and, thus, social evaluation. These public situations might evoke negative emotions that reflect the social nature of the performance (LeBlanc et al., 1997). Supporting this, Wrigley and Emmerson (2013) found that during performance exams, in which individuals are probably focusing mainly on the accuracy of their performance, the majority of music students experience low amounts of flow or even none at all. As negative emotions can lead to an increased focus on oneself, they can prevent the individual from experiencing flow (Fullagar, Knight, & Sovern, 2013). Congruent with this assumption, S. Cohen and Bodner (2019) found a significant negative relationship between flow and performance anxiety among classical orchestral musicians. In contrast, music-listening often takes place in solitude and, thus, without social evaluation. Even in situations of listening to music where others are present, it is not likely that these “others” evaluate the listener’s performance; this reduces the probability of negative emotions resulting from social evaluative processes. Hence, emotions like shame or anxiety are unlikely to be evoked. Without these negative emotions, it may be easier to lose oneself in the activity of listening to music, which may in turn increase the probability and intensity of experiencing flow. In sum, we assume that flow also occurs while listening to music, provided listening is done with concentration. We furthermore expect differences between flow in performing and flow in listening to music, with a higher likelihood for flow to occur with the latter activity due to the social and evaluative nature of music performances.

Flow, previous musical training, and musical reception

Flow has been defined as a state of total absorption in certain actions, and it is sensitive to any kind of distraction. In the case of musical activities, this means that a musician is less likely to experience flow when she needs to concentrate on the movements necessary to play the piece (Wrigley & Emmerson, 2013). Given this detrimental effect on flow in playing and performing, we assume higher levels of previous musical training (PMT) could counteract this and enhance the experience of flow.

In the sections above, we described the necessity of focussing on the present activity to experience flow. With regard to PMT, a further clarification is necessary. During performance, a musician might also be distracted by cognitions not even related to the music being played (e.g., trouble in social relationships). The same holds true for music-listening. If one listens to music in the background, concentration is divided to a degree that could impede entering a state of flow. We therefore assume that those situations in which music is the major activity and the listener is thus intensely engaged with the music are likely to facilitate a state of total absorption. The terms music experience (Behne, 1997) or music reception generally describe how and for what purposes individuals listen to music, that is, the kind of music-related situations they regularly seek and/or create (Gardikiotis & Baltzis, 2012; Leipold & Loepthien, 2015). We use the term musical reception (MR) to denote listening habits or interindividual differences in the use of music. Previous research has shown these differences in MR to covary with personality, general affect, and uses of music-listening (Chamorro-Premuzic & Furnham, 2007; Getz, Chamorro-Premuzic, Roy, & Devroop, 2012). However, these studies refer mainly to cognitive (attentive-analytical music-listening) and affective (emotional music-listening) facets of MR. As listening to music also takes place in social situations (North, Hargreaves, & Hargreaves, 2004), the present research includes social aspects of MR. In sum, a heightened involvement in listening to music has been discussed as an antecedent of flow in music-listening (Csikszentmihalyi, 2009) and we therefore expect that MR is positively correlated with flow.

Flow and subjective well-being

Research on flow resulting from playing music has repeatedly shown it to be related to greater subjective well-being (Ascenso, Perkins, Atkins, Fancourt, & Williamon, 2018; Croom, 2015; Georgi et al., 2016; Habe, Biasutti, & Kajtna, 2019; Heller et al., 2015; Smolej Fritz & Avsec, 2007). Surprisingly though, to our knowledge the relationship between subjective well-being and flow from listening to music has not been investigated, although this musical activity is much more prominent in everyday-life and may thus be a possible source of well-being for many people. Given the evidence for a positive relationship between flow and well-being in playing music, one could assume a comparable pattern for music-listening. On the other hand, we assume playing a musical instrument to be more central to one’s self-definition than music-listening. A direct and substantial effect on overall well-being therefore appears less plausible for music-listening, and makes it necessary to investigate underlying processes. To date, research aimed at a thorough understanding of the causality or mechanisms of the possible relationship between flow and well-being is scarce. We argue that a flexible self-concept (FSC; Brandtstädter & Rothermund, 2002; Martin & Anderson, 1998) can serve as a moderator between flow and general well-being. FSC describes an individual’s ability to adjust to unforeseen events and to regard a given situation from different perspectives. Several studies have demonstrated that accommodative processes (positive reappraisal, downward comparison, reorientation) are associated with subjective well-being (Brandtstädter & Rothermund, 2002) because individuals are able to adjust their standards flexibly in the face of difficulties (stress, age-related losses). One goal of the present study is to examine whether the emotion-regulating functions of accommodation unfold particularly well in individuals who report a high degree of flow. We assume this because, similar to positive emotions, flow broadens the attentional focus and thus information processing. These in turn are a prerequisite for FSC and well-being (Fredrickson, 2002). On the other hand, one could also argue that an accommodative self-concept enhances the link between music-induced flow and general well-being, possibly because this interconnected self-concept could serve as prerequisite, enabling individuals to apply domain-specific emotions to general well-being.

Hypotheses

The following hypotheses will be tested:

Flow differs in intensity between performing and listening to music. In contrast to performing, music-listening does not involve social evaluations. We therefore expect a more intense experience of flow while listening to music.

More pronounced engagement in music-listening (MR, hypothesis 2a) and previous musical practice and training (PMT, hypothesis 2b) are positively correlated with flow during musical activity. Both low levels of MR and PMT prevent the individual from getting absorbed by the musical activity.

Flow while performing or listening to music is positively correlated with subjective well-being.

Flow is positively correlated with a flexible self-concept (FSC).

The relationship between flow while listening to music and subjective well-being is moderated by FSC. High levels of FSC increase the relationship between flow and subjective well-being.

Hypotheses 1, 2, and 3 were examined by comparing the information from questionnaires from two groups who were asked about flow either when performing or when listening to music (Study 1). Hypothesis 4 and 5 result from Study 2, investigating solely music-listening.

Study 1

Participants

Participants were recruited via personal networks, German-speaking online chatrooms for musicians, and online-platforms for social research in Germany. We aimed at a sample consisting of individuals who were interested in music and recruited participants who either actively played an instrument (and performed regularly, e.g., in public or in a band) or participants who were interested in and regularly listened to music. Since no study yet compares flow when performing and listening, we first focused in a self-report study on whether any differences between music performing and listening were reported at all. Criterion for inclusion to participate in the study was a specific level of music education on the basis of the subscale “musical training” (Schaal, Bauer, & Müllensiefen, 2014, see below for details). To make both groups somewhat comparable, we used a score of at least 2.5, which meant that almost all had learned or played an instrument.

The total sample consisted of N = 207 participants that matched these criteria. Overall, the participants’ age was between 19 and 80 years (M = 49.1, SD = 15.5); 44% were female and 56% male (one participant did not answer this question). Seven percent of the participants had a low level of education, with nine or fewer years of schooling, 19% had a medium level of education with 10 years of schooling, and 73% had a high level of education with 12 or more years of education (German equivalent to university entrance level or A-levels). The questionnaire study was distributed online. Participants were assigned to one of the two conditions, based on whether they played an instrument or frequently listened to music. Participants were assigned to Group 1 (performing music; n = 105) if they actively and regularly played an instrument and currently performed. They were asked about their flow when they perform musically. Participants were assigned to Group 2 (listening group; n = 102) if they regularly listened to music. This group also included participants who played an instrument, but have no regular performance practice. They were asked about flow while listening to music (see below for detailed instructions). Participants in the music-performance condition were, on an average, slightly older (M = 51.5, SD = 14.2) than those in the music-listening condition (M = 46.6, SD = 16.4), t(205) = 2.28, p = .02. No differences were found for sex, χ²(1) = .02, p = .90, and musical training, t(205) = 0.40, p = .69. Participation was voluntary. Participants were informed about the general topic of the research prior to the survey, and they received a detailed description of the research question at the end of the survey questionnaire. The study is part of a larger research project on music-listening, perceived resources, and subjective well-being. The ethical review board of the Universität der Bundeswehr München provided ethical approval for the research project.

Materials and procedure

Flow

To assess the experience of flow while either performing or listening to music we used an adapted version of the Flow-State-Scale (FSS, Jackson & Marsh, 1996). The original version of the FSS consists of 9 subscales, of which only those that were expected to play a role both for music playing and music listening were used, namely, Action-Awareness-Merging (e.g., “Things just seemed to be happening automatically.”), Concentration on Task (e.g., “It was no effort to keep my mind on what was happening.”), and Autotelic Experience (e.g., “I really enjoyed the experience.”). Due to time restrictions in the online assessment, we excluded the scales: Challenge-Skill Balance, and Paradox of Control because of their limited applicability to listening situations. We did not use the Transformation of Time scale because it was not clear whether speeded or slowed experience would be measured and aspects of losing track of time and surroundings are implicitly included in other scales (e.g., concentration on task). We also used the subscales Clear Goals, Unambiguous Feedback, and Loss of Self-Consciousness but because these scales refer to a performance situation, some adjustments were necessary to make the items applicable for listening situations. In fact, the 8-item version that we used was a good approximation for the 24 items. Control analyses revealed that both scales were highly correlated (rs > . 90) in both groups and the differences in the mean values were not significant. Because the statements in many of the FSS-items refer to activities that cannot be applied to listening situations (e.g., “I made the correct movements without thinking about trying to do so.”), we only used those items that are suitable for both music-playing and listening (e.g., “The experience left me feeling great.”), resulting in a total of 8 items with good reliability (α = .91). As flow is more likely to occur in situations that exceed the average music-playing or listening situations, participants were instructed to think of concrete situations that match this prerequisite. Both groups were instructed to think of a musical situation that they would call something special, in which they were focused on the music and that was a little more demanding than casual listening or playing. Participants in the music-performance group were instructed to think of a performance situation in which they played a piece that was challenging and/or ambitious for them. Music listeners had to think of a situation in which they concentratedly listened to a piece of music. Participants had to indicate the extent to which the item-statements described their experience while performing or listening to music on a 5-point Likert-type scale (1 = does not apply at all to 5 = applies very much).

Well-being

Well-being was measured using the positive-affect subscale of the Job-Affect-Scale (JAS, Burke, Brief, George, Roberson, & Webster, 1989). The JAS has been shown to be a reliable instrument for measuring affect (Huelsman, Furr, & Nemanick, 2016). As this instrument assesses job-related affect, we adapted the instructions to gain a measure of overall well-being, asking participants to state how they felt in general during the past 2 weeks, using 10 items describing positive affective states (e.g., active, enthusiastic). Statements were made on a 5-point Likert-type scale (1 = does not apply at all to 5 = applies very much); reliability of the resultant scale was good (α = .85).

Musical reception

To assess the amount of MR, we measured attentive-analytical (e.g., “I try to understand the formal structure of a piece.”), emotional (e.g., “Music often touches me emotionally.”), and social aspects of music-listening (e.g., “I like to talk to friends about music.”) with an instrument by Leipold and Loepthien (2009). This scale measures the mentioned facets of musical experience; previous studies conducted confirmatory factor analyses on this instrument, showing good model-fit parameters and intercorrelations among the three facets (Leipold & Loepthien, 2009; Loepthien, 2015). The overall scale consists of 13 items with good reliability (α = .89).

Previous musical training

Because music education has been shown to affect emotional reactions resulting from the experience of playing and listening to music, we suspected differences in the experience of flow due to previous musical training (PMT). Especially in the case of performing music, more music education may facilitate flow because less attentional resources are invested in the actual playing. PMT was measured with the subscale “musical training” of the German version of the Gold-MSI (Schaal et al., 2014). This subscale assesses seven facets of musical education (e.g., number of instruments played, years of practice etc.) in an open-answer format. Values are then converted on a 7-point Likert-type scale with high values indicating higher musical education (α = .69).

Results

To test hypothesis 1, we first conducted a t-test for independent samples, (i.e., differences in flow between music-listening and -performing). As expected, the mean differences were significant with t(205) = -3.47, p < .01, d = 0.48. Figure 1 shows that participants thinking about listening to music reported more flow than those thinking about music performances.

Figure 1.

Mean Differences in the Intensity of Flow between Performing Music and Music-Listening. Error Bars Indicate 95% Confidence Interval of Mean Values.

To investigate the relationship between flow, MR, and PMT (hypothesis 2), as well as possible moderating effects of PMT and MR on the differences in flow between performing or listening to music, an analysis of covariance (ANCOVA) was conducted. Assumptions of ANCOVA (absence of outliers, linearity of covariates, homogeneity of variance) were tested prior to the analysis. The assumption of homogeneity of covariates’ regression slopes was violated. However, with a large sample size and nearly equal cell sizes, as in this study, ANCOVA is expected to be robust against this violation (Bortz & Schuster, 2010). Because this violation is a marker of interactions, we tested the interaction terms. Musical activity (Group 1: thinking about a musical performance, or Group 2: concentrated listening to music) served as an independent variable. Covariates were PMT and MR (z-transformed values). We computed the interactions between the group factor and the covariates for heuristical purposes, because we were interested in whether there would be differences in flow after performing and listening that were associated with PMT or with MR. Table 1 shows the main effect of musical activity on flow, which remained significant after inserting the covariates. As expected in hypotheses 2a and 2b, both covariates (PMT and MR) significantly predicted the amount of experienced flow. Finally, both interaction terms of musical activity and PMT as well as MR were statistically significant.

Table 1.

Analysis of covariance of flow.

Source of variance (adj.)	Adjusted SS	df	MS	F	η ²
Music group: 1 = performing, 2 = listening	11.12	1	11.12	18.38***	.08
Covariates
PMT	7.77	1	7.77	12.85***	.06
MR	24.23	1	24.23	40.06***	.17
Interactions
Group x PMT	7.58	1	7.58	12.52***	.06
Group x MR	3.29	1	3.29	5.44*	.03
Error	121.58	201	0.61

Note: N = 207. PMT: previous musical training; MR: musical reception; SS: sum of squares; MS: mean squares.

p < .05 ***p < .001.

In order to further illustrate the significant interactions, we conducted two correlation analyses separately for each musical activity group. The results show an interesting pattern: While PMT is positively correlated with flow when performing music, r = .44, p < .001, no significant relationship can be found for music-listening, r = .01, p > .05. For MR, a significant relationship with flow can be found in both musical activity groups, albeit these relationships differ in their effect size. Although medium in size for performing, r = .33, p < .001, for music-listening there is a large correlation between flow and MR, r = .62, p < .001.

For hypothesis 3, we examined the bivariate correlations between flow and overall well-being. As expected, this analysis revealed a significant relationship for the full sample, r = .18, p < .01. However, when this relationship was examined for the two subsamples separately, flow and overall well-being were significantly related only in the performing sample, r = .25, p < .01; the association between listening and well-being showed only a statistical trend, r = .18, p = .08. We therefore also compared both correlation coefficients via the cocor online-script (Diedenhofen & Musch, 2015), which examines two correlation coefficients from independent groups. The result did not show a significant difference between the correlation coefficients found in both musical activity groups, z = .52, p > .05. As participants in the music-performance group were significantly older than those in the music-listening group, all analyses were also conducted controlling for age. None of the results differed substantially from those reported in the text.

Study 2

Study 1 revealed ambiguous results, mainly for experiencing flow when listening to music. On the one hand, listening to music appeared to be a source of flow, but the picture of the relationship between the positive affective experience of music-listening, and overall well-being was not clear. In Study 2, we considered the role of a flexible self-concept, which has been shown to predict well-being in several studies. We assumed that a low degree of flexibility is not only associated with less flow (hypothesis 4), but also moderates the effect of a task-specific reaction (flow) on general well-being (hypothesis 5). In addition, as Study 1 had revealed a substantial relationship between flow, PMT and MR for music-listening, Study 2 explored hypothesis 2 in more detail for music-listening.

Participants

Participants were recruited via personal network, German-speaking online chatrooms for musicians, and online-platforms for social research in Germany. The questionnaire was distributed online. The sample consisted of 386 participants. Due to missing values on several items, three participants were eliminated, resulting in a total of N = 383. Participants’ ages ranged from 18 to 82 years (M = 46.0, SD = 17.1); 50 % were female and 49 % male (2 participants did not answer this question). According to the answers given, 10% of the participants had a low level of education, with nine or fewer years of schooling; 31% had a medium educational level with 10 years of schooling; and 57% had a high level of education with 12 or more years of education (German Abitur). Participants were informed about the general topic of the research prior to the survey and then received a detailed description of the research question at the end of the questionnaire. Participation was voluntary. The study is part of a larger research project on listening to music, perceived resources, and subjective well-being. The ethics review board of the Universität der Bundeswehr München provided ethical approval for the research project.

Materials and procedure

Flow

Flow was assessed similarly to Study 1, yet only with respect to flow experienced while listening to music. The resultant scale with 8 items showed good reliability (α = .90).

Well-being

Well-being was measured with the positive affect scale of the JAS (Burke et al., 1989; for details see Study 1). Cronbach’s alpha was .88.

Flexibility of self-concept

To measure FSC, we used the ACCO-5 scale (Loidl & Leipold, 2019), which is a questionnaire encompassing several facets of flexible goal adjustment. The items relate to how people deal with situations in which goals or plans can no longer be realized. The subscales—positive reappraisal/personal growth, lowering of aspirations/acceptance, and reorientation—consist of 16 items and assess the general tendency to adjust one’s goals in the face of threats to self-concept. Participants were asked to rate how well each item applied to themselves on a seven-point Likert-type scale (1 = not at all, 7 = exactly; α = .94).

Musical reception

The overall variable for MR was the same as in Study 1, using an instrument by Leipold and Loepthien (2015). The resulting variable containing 13 items showed satisfactory reliability (α = .91).

Previous musical practice

To assess the participants’ musical education, we used the subscale “musical education” of the German version of the Gold-MSI (Schaal et al., 2014, see Study 1). The scale consists of 7 items with good reliability (α = .86).

Results

Overall associations between variables

Table 2 presents descriptive statistics and relationships between the assessed variables. Participants with a higher MR experienced flow in a more pronounced manner when listening to music, which confirmed hypothesis 2. PMT is related to flow and MR, yet it does not show any relationship to FSC and well-being. In accordance with hypotheses 3 and 4, experiencing flow when listening to music is significantly related to well-being, and flow is related to FSC. We then tested the hypotheses in controlled analyses.

Table 2.

Descriptive statistics and intercorrelations of assessed variables.

		M	SD	1.	2.	3.	4.	5.	6.
1.	Age	45.99	17.13
2.	Sex (0 = female; 1 = male)			.20***
3.	PMT	2.80	1.44	−.22***	.00
4.	Flow	3.71	0.91	−.07	−.05	.20***
5.	MR	4.52	1.23	−.05	−.08	.22***	.65***
6.	FSC	5.06	1.01	.18***	.02	.07	.35***	.36***
7.	Well-being	3.27	0.73	.12*	.13**	.02	.13**	.19***	.46***

Note: N = 383. SD: standard deviation; PMT: previous musical training; MR: musical reception; FSC: flexible self-concept.

p < .05 **p < .01 ***p < .001.

We used a regression analysis to test whether music-specific effects on flow (hypothesis 2) are unique effects. As expected, and similar to the results of Study 1, MR significantly predicted flow (β = .64, p < .001), whereas the predictive value of PMT was not significant (β = .06, p = .17).

Flow, FSC, and the moderating effect of FSC on the relationship between flow and well-being

To examine the correlations between flow and well-being (hypothesis 3), flow and FSC (hypothesis 4), and the moderating effect of FSC on the relationship between flow and well-being (hypothesis 5), we conducted a hierarchical regression analysis. Well-being served as criterion, while flow and FSC were predictors (Step 1). In the second step, the interaction term between both predictors was added, using z-standardized variables to compute the interaction term (J. Cohen, Cohen, West, & Aiken, 2003). As age and gender showed significant correlations with FSC and well-being (see Table 2), both variables were entered as control variables in Step 1. The results are presented in Table 3.

Table 3.

Hierarchical regression analysis for variables predicting well-being.

	B	SE B	β
Step 1
Age	0.00	.03	.00
Sex	0.09	.03	.12**
Flow	−0.02	.04	−.03
FSC	0.34	.04	.47***
R	.48
R ²	.23
Step 2
Age	0.00	.03	.00
Sex	0.08	.03	.11**
Flow	−0.02	.04	−.02
FSC	0.36	.04	.50***
Flow x FSC	0.07	.03	.12**
R	.49
R ²	.24
ΔR ²	.01**

Note: N = 383. B: unstandardized beta coefficient, SE B: standard error of B, β: standardized beta coefficient; FSC: flexibility of self-concept.

p < .01 ***p < .001.

In Step 1, only FSC and sex remained significant predictors of well-being; in Step 2, as predicted, the interaction between flow and FSC also significantly predicted well-being. Figure 2 illustrates the results of this analysis. Only participants with a highly flexible self-concept showed significantly higher overall well-being when intense flow was reported following music-listening. Participants with medium and low values in FSC showed no covariation between flow and well-being.

Figure 2.

Well-Being as a Function of Flow and Self-Concept Flexibility. We Used Standard Deviations to Categorize FSC. Indicated Here are the Correlation-Coefficients r for Each FSC—Sub-Group.

Discussion

Music-psychological research on flow has largely focused on situations in which music is played but has given little attention to situations involving listening to music. The present studies extend this research by investigating differences in flow between music-playing, especially in performing and music-listening. The first study showed a more pronounced experience of flow for listening to music as compared to performing music. These differences in flow between performance and listening may reflect the different nature of the two activities. Music performances occur in public. The results found here reflect exactly this social aspect of performing music. In contrast, listening to music does not necessarily involve other people and, even when others are present, they do not act as an audience that evaluates the listener’s “performance.” Hence, music-listening involves fewer social evaluations: One does not need to reflect on one’s performance, the right movements, and the notes to play, and this may altogether facilitate losing oneself in this activity (Csikszentmihalyi, 2014). This interpretation is in accordance with the findings concerning PMT: Whereas musicians with lower levels of musical education show lower values of experienced flow in a performance situation, those with higher levels of music education experience an equal intensity of flow as music listeners. Well-trained musicians might be more experienced in public performances, which can reduce the amount of negative emotions occurring in these situations. Furthermore, a higher musical education increases the self-confidence of a musician and also reduces the amount of concentration needed to execute basic movements (Papageorgi, Hallam, & Welch, 2007). These aspects may altogether increase the likelihood of experiencing flow in a performance situation as they shift the attentional focus away from the distracting aspects to the actual playing-experience. The difference between the two groups in the flow experienced may also be due to the different instructions for performing music and listening to music. In particular, asking music-listeners to think of a situation in which they listened to music attentively and with concentration may imply flow. We have controlled for interindividual differences in the tendency to listen attentively and emotionally to music. Although the main effect of group remained significant, we cannot rule out confounding factors (see limitation section).

In addition, the results of both studies support our second hypothesis: The higher the overall engagement with music, the more intense the experienced flow. This result is in line with theoretical assumptions of Csikszentmihalyi (2009) who claimed that a certain amount of concentration is needed to experience flow when listening to music (see also Lamont, 2011). Hence, merely having music playing in the background does not evoke flow, but listening to music as the main activity so that attention can be focused on the music is an important precondition for getting into and staying in flow (Csikszentmihalyi, 2014). The results for MR found here are also in line with Ruth et al. (2016) findings. In this study, the authors showed a negative effect of low analytical listening on flow when listening to complex music.

In sum, we suggest that flow from music performance and music listening differs in its intensity, possibly due to the more intimate and non-evaluative character of listening to music. In contrast, the social-evaluative aspects of performing may hinder musicians from experiencing flow, as they need to focus on their performance and may even experience negative emotions. A high level of music education (PMT) can, however, moderate this detrimental effect in performing music, enabling the musician to focus solely on the playing itself and, thus, enjoy it. It is important to note that the results of Study 1 do not show that flow is per se more intense when listening to music but rather that the public nature of a performance situation may impede the experience of flow. The significant interaction—that PMT is associated with flow in the performance group, but not in the listening group—supports this interpretation. The results reported here do not imply more pronounced experiences of flow when listening to music as compared to playing music in general as we investigated solely the public aspect of making music, namely performing. Flow is more intense when MR is high, and the focus is more on the music while listening.

We also investigated the relationship between flow and overall well-being. In Study 1, we found a relationship between flow following performing music and well-being, replicating findings from previous studies investigating music performance in general (Croom, 2015; Georgi et al., 2016; Habe et al., 2019). To our knowledge, both studies presented here are the first steps to also investigate the relationship between overall well-being and flow while listening to music. Here, although significantly correlated, the effect-sizes were low. We therefore investigated how the relationship between flow following music-listening and overall well-being varies, dependent on the level of FSC. In previous studies, FSC was found to buffer stress- or age-related impairment in general well-being (Brandtstädter, 2017; Brandtstädter & Greve, 1994). Study 2 shows that a flexible self-concept moderates the relationship between flow and well-being in that only participants with a highly flexible self-concept showed a significant relationship between flow and well-being. The underlying process here might lie in the effects that positive affective reactions, like flow, have on the cognitive system. A broad attentional focus during positive affective states possibly facilitates flexible processes (e.g., reorganization and reinterpretation) and thus enhances the flexibility of one’s self-concept, which in turn positively affects overall well-being (Fredrickson, 2002). Given this result, flow when listening to music is a domain-specific affective state, which alone cannot account for higher subjective well-being, but requires moderating cognitive factors as well. Music-listening can evoke flow and may, in combination with a highly flexible self-concept, be a source of well-being for a large number of people as flow while listening to music does not require high amounts of PMT.

Limitations and further research

We interpreted the differences in the intensity of experienced flow while performing or listening to music to reflect the social, and thus, the evaluative component in performing music. Yet, as music-listening and music-playing occur in both private and public settings, more research is needed to examine differences between other combinations of these contexts in order to achieve a comprehensive picture of differences in flow between music-playing and music-listening. For example: Do musicians experience more intense flow when playing privately then in performance situations? Can the differences in flow found in Study 1 also be found when listening privately and playing music in a private setting are compared? These considerations further suggest the use of within-study designs for future investigations. As this study was a first step to investigate differences in flow between music-playing and music-listening, more research is needed to achieve a broader picture.

Another limitation was the use of only three facets of flow. As stated before, this was necessary due to time restrictions as well as to enhance the comparability of the results between flow during music performances and listening to music. In fact, we have examined six facets of flow and the significant results remained stable in both studies. However, because many items refer to movements of the performers and could not simply be applied to listening situations without adjustments to the items, we decided to report the results of the shortened version. Future research investigating flow in private versus public situations within the same musical activity (playing or listening) should therefore consider developing scales that would be appropriate for the various situations. The present results are based on self-report questionnaires. It would be interesting to examine whether the differences hold true during the actual listening and playing of music.

We interpreted the moderating effect of FSC on the relationship between flow and well-being as stemming from the effects that flow has on flexible cognitive processes. Both studies conducted were cross-sectional and provide no evidence for a specific causal direction. It may also be possible that highly flexible individuals experience flow more often and intensely, and the positive relationship between flow and well-being may indicate a cumulative effect that is based on FSC. Longitudinal studies are needed to further explore the complex relationship between these three variables.

Conclusion

Musical activities are potential sources of flow. This seems to hold true for both performing and listening to music. In the case of music-listening, experiencing flow does not depend on music education. Hence, music-listening might be a flow-evoking activity for many people. These findings on musical activity and flow are particularly important because experiencing flow is related to general well-being, yet in the case of music-listening, additional cognitive factors are important for this relationship. The results of both studies suggest that musical activities are potential sources to experience flow and may thus, in the long-term, contribute to a happy and fulfilled life.

Footnotes

Acknowledgements

The authors would like to thank Amy Michéle-Malkowsky for many discussions and two anonymous reviewers for their comments on a draft of the manuscript.

Funding

The author(s) received no financial support for the research authorship and/or publication of this article.

ORCID iD

Tim Loepthien

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