Abstract
The aim of this study is to investigate the structure and complexity of emotional states experienced by young musicians before entering the stage and to explain the influence of emotional beliefs on their pre-performance emotions. Emotions were elicited with a guided imagery induction, where 222 students aged 9- to 12-years-old recalled their most recent concert memory. They described their emotions on the list of 18 emotions (nine pairs of contrary emotions) and answered three questions measuring music performance anxiety (MPA) beliefs: MPA utility beliefs, MPA regulation beliefs, and audience attitude beliefs. The cluster analysis results show the complexity and multiplicity of emotional states reported by young musicians. Five emotional profiles vary from negative emotions of fear and sadness (High MPA) through a mixture of positive and negative emotions (Moderate MPA, Hesitation, Ambivalence) to positive emotions of confidence, courage and happiness (Composure-Confidence). Beliefs that MPA has negative impact on performance, beliefs of inefficacy in managing MPA and perceived audience pressure rather than support were related to High and Moderate MPA profiles. Practical implications for music education are discussed.
Keywords
Introduction
A public performance is the culmination of a performer’s work on a piece of music. This significant, subjectively engaging, difficult situation, ambiguous in terms of profit and loss, may evoke mixed emotional experiences in music performers (Gabrielsson, 2001; Gabrielsson & Lindström Wik, 2003; Kaleńska-Rodzaj, 2018; Lamont, 2012). The aim of this study was to investigate the structure and complexity of the self-reported emotional states experienced by young music students and to explain the influence of emotional beliefs on their pre-performance emotions. The selected cognitive and emotional variables have been derived from a process model of emotion regulation (Gross, 2007), which highlights the mediating role of attentional deployment and cognitive appraisal in final emotional responses to situations. It means that the final pre-performance emotional state of musicians depends on how they perceive and evaluate experienced emotions in public performance contexts. These research results may be useful for musicians and music educators in understanding pre-performance emotions and regulating them more effectively.
Regulation advantages of perceiving pre-performance emotions’ complexity
The theoretical foundation of this study is the distinction between primary (basic) and secondary emotions (Ekman, 1984, 1999; Izard, 1992; Plutchik, 1982), also labelled as mixed emotions. Mixed emotions are often defined as co-occurrence of positive and negative affects (Larsen, McGraw, & Cacioppo, 2001), but a recent definition extends the scope of the concept as “co-occurrence of any two or more same-valence or opposite-valence emotions” (Larsen & McGraw, 2014, p. 263).
Mixed affective experiences are generally aversive unless people find a way to cope with the associated discomfort (Williams & Aaker, 2002). Some theories underline the importance of the verbal labelling of an emotional state as the first step to emotional regulation (Dolard & Miller, 1950; Mayer & Salovey, 1997; Schachter & Singer, 1962). The accuracy of the identification and description of emotions with discrete emotion words and the perception of their complexity indicate a high level of emotional development (R. D. Lane & Schwartz, 1987) and enable effective emotional regulation (L. F. Barrett & Gross, 2001). Research provides evidence that the ability to recognise mixed emotions emerges at the age of 5–6 years and develops over time (see Larsen, To, & Fireman, 2007; Zajdel, Myerow Bloom, Fireman, & Larsen, 2013), with differentiation of emotion dimensions in term of intensity, multiplicity, valence and ambivalence becoming more accurate in early adolescence (Donaldson & Westerman, 1986; Harter & Buddin, 1987).
According to a cognitive-developmental theory of emotional awareness (R. D. Lane & Schwartz, 1987), language indicates the person’s level of emotional awareness. In Polish, the most commonly used term to label the variety of pre-performance affective states is the word trema (tremor), which is the equivalent of the English terms stage fright or music performance anxiety. Trema refers mostly to the somatic symptoms of arousal associated with public performance, so it may be used to describe intense anxiety or more positive states such as excitement or enthusiasm. According to Lane’s theory, describing emotion in terms of somatic sensations indicates a low level of emotional awareness (awareness of bodily sensations). In English the term trema describes one dimension—the emotion of anxiety, which indicates a moderate level of emotional awareness (awareness of single emotions). Recognising the diversity of the experienced emotions (high-level awareness of multiple emotions) plays a crucial role in enhancing musicians’ coping resources. Such awareness, for example, may help musicians to redirect their attention to the positive outcomes of the performance situation (Folkman, 1997; Folkman & Moskowitz, 2000; Lazarus & Folkman, 1984; Tugade & Fredrickson, 2004).
Few studies have approached pre-performance emotions as mixed emotions (Gabrielsson, 2001; Gabrielsson & Lindström Wik, 2003; Lamont, 2012). Considerably more attention has been paid to the emotional states of high intensity and definite valence—music performance anxiety (MPA, Kenny, 2004, 2006; Kenny & Osborne, 2006; Papageorgi, Hallam, & Welch, 2007).
To my knowledge only one study to date has shown the impact of mixed emotional experience on music performance quality and musician well-being (Kaleńska-Rodzaj, 2018). In that study I identified the type, complexity and function of emotions experienced by adolescent musicians before giving a solo music performance. The frequency analysis results showed that musicians’ pre-performance emotional state was dominated by ambivalent emotions of hope, sadness and anxiety. A cluster analysis produced six pre-performance emotional profiles: high MPA, moderate MPA, calm, impatience with mixed emotions, joy with background fatigue, and excitement (enthusiasm). Compared with the MPA profiles, participants who experienced positive emotions of moderate and high intensity or mixed emotions (including anxiety) demonstrated quite similar higher levels of performance quality, measured by referees’ assessment and self-assessment (including level of satisfaction with performance).
Meta-emotion beliefs and pre-performance emotions in young musicians
Musicians’ beliefs about emotions are also crucial for effective emotional regulation (meta-emotion, Gottman, Katz, & Hooven, 1996). Offering an extended process model of meta-emotion and emotion regulation during media use, Bartsch, Vorderer, Mangold, and Viehoff (2008) propose the following definition: “We understand meta-emotion as a process that monitors and appraises emotions and recruits affective responses toward them, which results in a motivation to maintain and approach emotions, or to control and avoid them” (p. 7).
Public performance requires the ability to regulate one’s emotions adequately. Performers monitor and evaluate their pre-performance emotional state to apply appropriate self-regulation strategies in order to maintain or change their emotions to desirable levels (Carver, 2004; Tamir, 2009). Contra-hedonic regulation strategies, when a person perceives the benefits of experiencing negative emotional states and tries to sustain them, are often used in sports psychological skills training (Hanin, 1997, 2007). However, the research results show that it is not always easy to change our valence-related beliefs: only 15% of runners believed that anxiety and anger would enhance performance. They used strategies to increase unpleasant emotions such as intensifying anger and decreasing anxiety before competing (A. M. Lane, Beedie, Devonport, & Stanley, 2011). Simoens, Puttonen, and Tervaniemi’s (2015) study of musicians found that the proportion of participants strongly believing that MPA has a positive influence on performance was higher—about 28% (34% strongly believed in its negative impact), however the functional effect of the belief was not analysed.
MPA utility beliefs
Beliefs about MPA utility were the basis for distinguishing between adaptive and maladaptive MPA in Wolfe’s studies (1989, 1990). Adaptive anxiety may enhance performance by stimulating a musician’s alertness and concentration on the task at hand, instead of focusing on the self (Gates & Montalbo, 1987; Hamann, 1982; Mor, Day, Flett, & Hewitt, 1995). The facilitating role of anxiety is found in more experienced performers (Kemp, 1996; Kokotsaki & Davidson, 2003).
Positive emotional beliefs about worrying and stress prevent maladaptive coping, helping a person to deal with negative emotions (Beer & Moneta, 2012). Positive beliefs about stress have an impact on physiological functioning of both body and mind under stress, such as decreasing cortisol reactivity (Crum, Salovey, & Achor, 2013). Moreover, training participants to reappraise their stress response as helpful, and to interpret the symptoms of stress in terms of the body’s mobilisation or excitation, improve their well-being and reduce stress symptoms (Brooks, 2014; McGonigal, 2015).
MPA regulation beliefs
The pre-performance emotional state may also be determined by musicians’ beliefs regarding their ability to cope with pre-performance emotions, particularly MPA. A person’s inability to cope with MPA and feelings of inadequacy in managing negative emotions have been associated with anxiety, depressive symptoms and shyness (Caprara et al., 2008). Self-efficacy beliefs, in contrast, influence thoughts and feelings that may prevent negative emotions and help a person to remain calm when dealing with challenging tasks (for a review, see Bandura, 1997). Self-efficacy and outcome expectations have been found to be the key variables for predicting test anxiety (Zeidner & Matthews, 2007) and music performance quality (McCormick & McPherson, 2003; McPherson & McCormick, 1998, 2006).
Audience attitude beliefs – perceived pressure and support
Previous research shows the significance of family, friends and institutional support for the development of musical abilities (Burland & Davidson, 2002; Manturzewska, 1969; Papageorgi et al., 2010). On the base of significant others’ reactions children develop their own concept of self (beliefs about self in different areas of functioning). Parents’ and teacher’s reactions to children’s actions resulting in success or failure are also generalised as a concept of others, which in music performance contexts takes the form of concept of audience (audience attitude beliefs). In their research, Simoens et al. (2013) linked audience attitude beliefs with the kinds of pre-performance emotions experienced by musicians and showed that perceived social pressure was a key contributing factor in debilitating MPA, whereas perceived social support was the main predictor for performance boost.
All the above-mentioned findings highlight the importance of investigating the structure of pre-performance emotions in association with key musicians’ beliefs about pre-performance emotions, and allow the formulation of the following hypotheses:
(H1) The structure of young musicians’ pre-performance emotional states is complex and includes emotions of different modalities.
(H2) Musicians who believe in the negative impact of MPA on performance report experiencing negative pre-performance emotions more often than musicians who believe in the positive impact of MPA on performance.
(H3) Musicians with negative beliefs about their ability to manage MPA report experiencing negative pre-performance emotions more often than musicians with positive beliefs about their ability to manage MPA.
(H4) Musicians with negative beliefs about audience attitude report negative pre-performance emotions more often than musicians with positive audience attitude beliefs.
Method
Participants
The participants were 222 children (136 girls and 86 boys), ranging in age from 9 to 12 (X = 10.44; SD = 1.13), recruited in elementary music schools in Cracow (Poland) for the Successful Performer Workshop Programme. After obtaining the Music School Educational Director’s approval, parental and child consents for child participation in the workshops and in research were collected. Coding of children’s names on research sheets helped to maintain anonymity and confidentiality of personal information. Children were in the third to sixth grades. Data was divided and analysed according to four age groups comprising 63 children aged 9 years (23 boys, 40 girls), 49 children aged 10 years (16 boys, 33 girls), 60 children aged 11 years (30 boys, 30 girls), and 50 children aged 12 years (17 boys, 33 girls). The whole sample was Caucasian. Nearly 56% of the musicians were pianists, 28% violinists, and 16% other instrument players.
Instruments and procedure
Data was collected at the first meeting organised for each grade as part of a Successful Performer Workshop Programme. All of the children had participated in an instrumental audition prepared by the music school for family, friends and school community one or two weeks prior. After a brief introduction and an explanation of the aim of the meeting, the participants were asked to recall this most recent audition performance. To help the children retrieve more details from memory, a visualisation exercise about going on stage was prompted with the following instruction:
Sit comfortably, close your eyes, and take a few deep breaths. I will guide you through a situation. Try to imagine it using your previous experiences. Imagine that it is the day of your performance. You have waited for it for a very long time, you have been practising and finally the day has come. You have dressed nicely for the performance. In your classroom, you have warmed up on your instrument and played the piece that you are going to perform today. You wait for a while in your classroom and then move to the concert room. You are behind the door and hear the previous performer finish their performance. The audience claps. The door opens, the student goes out, and you hear yourself being announced. In a moment, you will enter the stage …
To design the guided imagery induction procedure, the typical location and process of a performance in the school were identified. The instruction was written according to the PETTLEP model of motor imagery 1 (Holmes & Collins, 2001), which helps adapt visualisation procedures to real experience. The information included in the instruction was expected to trigger the memory of the recent school audition performance and to evoke the associated emotions.
In previous research (Kaleńska-Rodzaj, 2018) the pre-performance emotional state was assessed using the UMACL Mood Adjective List, so adjectives describing other intense pre-performance emotions, such as anger or courage, could not be included. That is why a new list of emotions accommodating the specifics of pre-performance emotions and adapted to the age of the participants was constructed. After the visualisation session, the children completed a list of 18 pre-performance emotions (nine pairs of opposite emotions) derived from theory: four basic emotions (happy–sad, afraid–brave, angry–cheerful, curious–bored) (Ekman, 1984, 1999; Izard, 1992); one pair of adjectives describing the level of energetic arousal (full of energy–tired) and two pairs describing the level of tense arousal (relaxed–uptight, worried–calm) (Matthews, Jones, & Chamberlain, 1990); one pair of adjectives referring to self-confidence (sure–unsure), and one pair of adjectives referring to performance anticipation (pleased–gloomy). In the experts’ opinion (three elementary music school teachers with over 10 years of experience in teaching children) the adjectives were understandable for children aged between 9 and 12. The participants indicated their emotions by marking the emotions which they felt during the visualisation procedure, or by adding their own, if relevant adjectives were unavailable.
After completing the list of emotions, the participants were asked to answer three multiple-choice questions measuring MPA susceptibility: MPA utility beliefs, MPA regulation beliefs, and audience attitude beliefs; choosing one, the most relevant option (the questions are presented in Tables 2, 3, and 4). This data was gathered to examine the children’s beliefs about the external and internal factors which contribute to MPA, and to establish the relationships between these beliefs and the participants’ pre-performance emotions.
Results
Frequency analysis
Frequency analysis was performed in order to examine the distribution of emotions marked by the participants. The results are shown in Figure 1.
Distribution of pre-performance emotions marked by young musicians (N = 222).
The participants most frequently described their pre-performance emotional state with the adjectives unsure (69%), uptight and worried (approximately 60%, indicating tense arousal), and afraid (45%). Approximately 30% of the students reported positive emotions (sure, brave, cheerful, pleased). The least frequently marked items were angry (12%) and bored (14%). Emotional adjectives added by two participants were excited and irritated. Due to the limited representativeness of these emotions, they were excluded from further analyses.
In order to determine whether any participants experienced mixed emotions (positive and negative), and to distinguish pre-performance emotional profiles, a cluster analysis was performed.
Cluster analysis
A hierarchical cluster analysis using Ward’s (1963) clustering algorithm was carried out to determine whether it was possible to distinguish different profiles for the children on the basis of the pre-performance emotions they had chosen. The analyses were performed using IBM SPSS Statistics 21.0 software.
Profiles of pre-performance emotions
Since the items pleased and happy were highly correlated (r = 0.60), only happy was included in the analyses, as it is more specific to pre-performance emotions. The adjective pleased was excluded to avoid information redundancy. The remaining 17 adjectives with choice frequencies ranging from 12% (angry) to 69% (unsure) were entered.
The number of configurations to be retained was decided by examining the scree plot of distance coefficients as a function of the number of configurations at each agglomerative step (Aldenderfer & Blashfield, 1984). Five configurations were retained, as the scree plot indicated that the presence of additional configurations (more than five) did not reduce distance coefficients significantly (Figure 2).
The dendrogram for hierarchical cluster analysis results – five configurations obtained.
The number and percentage of children who marked each emotion in each configuration are shown in Table 1.
Proportion of children reporting different emotions in each cluster.
Note. *Although the adjective pleased was included in the cluster analysis, it had no effect on the distinction of the profiles. The percentages indicate the proportion of children who have chosen an affective adjective in particular cluster.
The interpretation of results was based only on the most differentiating items, and the profiles were labelled as follows:
1. High MPA dominated by negative emotions: afraid and unsure, marked by over 90% of the group, and sad, reported by 65%. High tense arousal (worried, uptight) was experienced by a large proportion of the group. The frequency of choice of positive emotional adjectives ranged from 2% to 8%.
2. Moderate MPA dominated by tense arousal (worried, uptight) and negative emotions (unsure), marked by over 90% of the group, and afraid reported by 63%. Positive emotional adjectives (brave, cheerful, sure) and energetic arousal adjectives (full of energy) accounted for 20–30% of the reported affective states. Although pairs of ambivalent emotions were observed in 30% of participants (afraid–brave, unsure–sure), negative emotional adjectives were considerably more frequent.
3. Hesitation grouped students who labelled their emotional state as unsure (73%), and reported tense arousal (worried and uptight, approximately 45%). Other emotions included calm (approximately 35%) and curious or bored (approximately 30%). A smaller proportion (approximately 20%) used other emotional adjectives (afraid, angry). This profile is closer to the MPA clusters, but the difference between them is the low frequency of fear—a determinant of MPA.
4. Composure-Confidence dominated by positive emotions, ranging from calm to happiness. The choice of adjectives indicated lack of tense arousal with energetic arousal instead (full of energy, 57%). The most frequently marked emotional adjective was sure (93%). The occurrence of negative emotions ranged from 2% to 13%.
5. Ambivalent Emotions grouped participants who reported contrasting emotions. Relatively few children in this cluster felt sad (18%), gloomy (27%), bored (27%), or angry (45%). The frequency of choice of the remaining adjectives ranged from 63% to 100%. The entire group described themselves as cheerful or happy, and 90% as sure and tired. It was considered whether this cluster should be incorporated into Cluster 4, however since Ambivalent Emotions grouped pupils with very distinctive characteristics, it was included in the results.
Music performance anxiety beliefs
In order to investigate the relationships between the beliefs about factors contributing to MPA and pre-performance emotional profiles (PE profiles), three Chi-squared analyses were performed. Due to the small sample size and empty cells in contingency tables approximations of the exact test results were obtained through a Monte Carlo simulation (with 1,000,000 samples).
MPA utility beliefs
A 3 (MPA utility beliefs) × 5 (PE profiles) Chi-square analysis revealed significant relationships between MPA utility beliefs and emotional profiles: χ2 (8) = 51.69, p < .001. The belief in the debilitating effect of MPA on performance was most frequently observed in the High MPA (30%) and Moderate MPA (36%) profiles. The belief in the adaptive function of MPA was most frequent in the Hesitation profile (33%). Responses indicating lack of pre-performance anxiety were most frequent in the Composure-Confidence profile (70%). The results are detailed in Table 2.
Proportion of children expressing MPA utility beliefs in each emotional profile.
The analysis of the whole sample showed that significantly more participants believed in the adaptive (n = 129, 58%) as opposed to debilitating function of MPA (n = 70, 32%). The reports of 10% of the children indicated a lack of pre-performance anxiety.
MPA regulation beliefs
A 3 (MPA regulation beliefs) × 5 (PE profiles) Chi-square analysis revealed significant relationships between MPA regulation beliefs and emotional profile: χ2 (12) = 50.69, p < .001. The sense of the uncontrollability of pre-performance anxiety was prevalent in both MPA profiles and diminished with the decrease in the frequency of negative emotions. The majority of participants who were familiar with MPA coping techniques were found in the Hesitation cluster (33%). Expressions of well-being and no need for coping techniques were most characteristic of the Composure-Confidence profile (51%). The results are presented in Table 3.
Proportion of children expressing MPA regulation beliefs in each emotional profile.
When divided according to MPA regulation beliefs, the results of the whole sample showed a prevalence of the belief in the controllability of MPA (n = 130; 59%) over the belief that controlling it is unnecessary (n = 49; 23%). The reports of 18% of the children (n = 39) indicated a sense of helplessness over MPA.
Audience attitude beliefs – perceived pressure and support
A 3 (audience attitude) × 5 (PE profiles) Chi-square analysis revealed significant relationships between audience attitude and emotional profile: χ2 (8) = 16.80, p < .05. The belief in negative audience attitude prevailed in MPA profiles and increased with the frequency of negative emotions. The majority of students expressing a belief in a mostly positive audience attitude could be observed in the Moderate MPA cluster (35%). The belief in a definitely positive audience attitude was most characteristic of the Hesitation profile (32%). The results are shown in Table 4.
Proportion of children expressing audience attitude beliefs in each emotional profile.
The division of the sample according to audience attitude beliefs shows the prevalence of the belief in a definitely positive audience attitude (n = 87; 54.4%) over the belief in a predominantly positive audience attitude (n = 49; 30.6%). Only 15% of the children (n = 24) harboured a negative image of the audience.
Discussion
The results of this study reveal the complexity of pre-performance emotions reported by young musicians after their entering the stage visualisation, supporting hypothesis H1. The young musicians’ emotional attitude to performance was dominated by tension and lack of confidence in over 60% of the group, with 45% reporting feeling fear. This combination of emotional adjectives reflected a negative mood and tension (Matthews et al., 1990). A relatively small number of participants reported feeling sadness—18% as compared to 93% in previous research (Kaleńska-Rodzaj, 2018). This difference may have been the result of the development stage of each group: in the previous research the majority of the participants were in middle and late adolescence phases (D. Barrett, 1996), but in the current study the group consisted of children and early adolescents. The depressed mood in the older group might result not only from the participants’ appraisal of the challenge and their limited capacity to handle it, but also from the confluence of developmental changes (physical, psychological and social), which they were undergoing. The rarer occurrence of sadness in the younger participants may indicate either their lesser performance experience, or their better adaptation to the situation, because sadness felt before performance may foster feelings of helplessness, resignation, passivity, and self-focus (Lazarus, 1991).
It is worth noting that 30% of the present study’s participants reported feeling positive pre-performance emotions such as confidence, courage, satisfaction and cheerfulness, compared with 70% in adolescent groups in previous research by the author (Kaleńska-Rodzaj, 2018). Both reported results are in line with the conclusions of research conducted wuth adults: public performance may evoke both positive and negative emotions (Gabrielsson, 2001; Gabrielsson & Lindström Wik, 2003; Lamont, 2012).
The pre-performance emotional profiles identified in students in late childhood and early adolescent musicians in this study were to some extent similar to those observed in the population of musicians in early and late adolescence (Kaleńska-Rodzaj, 2018). In both studies, High MPA profiles were dominated by negative emotions, mainly fear and sadness, and feelings of helplessness. This combination revealed a depressed mood, and these musicians may potentially require psychological help to prevent long-term professional and health implications (Hildebrandt, Nübling, & Candia, 2012; Kenny, 2011; Wristen, 2013).
Previously, the Moderate MPA profile comprised emotions similar to those observed in the High MPA profile (Kaleńska-Rodzaj, 2018). In the present study, the Moderate MPA profile comprised mixed feelings, both positive (courage) and negative (lack of confidence, fear and feeling tense). Courage is defined as the capacity to move ahead in spite of despair (May, 1975), to be persistent in danger: it does not mean fearlessness, in fact, fear is considered as a prerequisite for courage (Rachman, 1990). In the performance context, courage seems to be the “fight” response to tension felt in the situation. This feeling derives from personal values, goals and ambitions and helps to manage fear. Because the “development of psychological courage is essential to the well-being of many people” (Puttman, 1997, p. 1), teaching children how to build courage considering their values and goals may help them to cope with MPA.
In both the present study and my previous research (Kaleńska-Rodzaj, 2018), the mixed emotions profiles (Hesitation and Impatience) were associated with tense arousal, which make them closer to MPA profiles. However, in the current research, respondents in the Hesitation group rarely reported fear and often reported other emotions, including curiosity, indifference and calm. This state of lack of confidence with a background of different emotions may be interpreted as a state of mobilisation: enhanced concentration and readiness to complete an important task despite the uncertainty and limited control over the environment.
None of the emotional profiles found in this study included excitement (enthusiasm) as found in the previous study (Kaleńska-Rodzaj, 2018), even in the Composure-Confidence profile, despite its univalence and predominance of positive emotions. In the present study this group gathered students who reported positive emotions of confidence, calm, courage and happiness.
The Ambivalence profile, which was found only in the present study, combined happiness, satisfaction, courage, fear and curiosity (marked by more than 70% of the participants). This may represent a unique group reporting mixed (ambivalent) emotions. On the other hand, the results must be treated with caution due to the small size of the group and the high number of adjectives selected by the students. It is also possible that these 11 children may have struggled to label their pre-performance emotions, especially when they became very intense. To control children’s level of emotion labelling skills and intensity of emotional experience variables, further research is needed.
The results support hypotheses H2, H3 and H4, which stated that factors contributing to MPA (MPA utility, MPA regulation and audience attitude beliefs) are associated with pre-performance emotional profiles. Students who believed that MPA debilitates their performance, felt that their MPA coping skills were inadequate, and perceived the audience as unfavourable reported the negative pre-performance emotions typical of the High and Moderate MPA profiles (fear and tension, lack of confidence) more often than students harbouring positive beliefs (Composure-Confidence, Ambivalent Emotions, Hesitation). In the case of the Ambivalent Emotions group, it would follow that musicians experiencing ambivalent emotions may have considerable capacity to cope with MPA, despite the fear and potential tension caused by ambiguous feelings.
These findings support the results of previous studies on meta-emotional beliefs (Beer & Moneta, 2012), self-efficacy beliefs (McCormick & McPherson, 2003; McPherson & McCormick, 1998, 2006; Zeidner & Matthews, 2007), and perceived social-support (Simoens et al., 2013; Wolfe, 1989) and show their linkage with musicians’ pre-performance emotional states. Moreover, the results give us some ideas as to how to develop emotional knowledge and skills in young musicians to support MPA prevention.
Practical implications for music education
The findings of this study indicate the need for psychological help in MPA prevention and treatment at an early stage of music education: 45% of the participants belonged to MPA profiles, 31% believed MPA had a negative impact on their performance, 18% reported helplessness in coping with MPA and 15% perceived pressure rather than support from music audition listeners (family and school community). These results highlight an important message for educators: not to throw young musicians in at the deep end, forcing them to perform in competitive situations whatever the personal cost, but to carefully develop their emotional awareness and emotional regulation skills.
The idea of an emotional education programme for musicians based on this research has a three-step structure according to Gross’s (2007) model. First, we can help children to gain insight into their pre-performance emotions (attentional deployment), to perceive their complexity in the performing situation, and then to stop labelling them all as MPA. Recognising fear co-occurring with positive emotions may help focus the attention on the benefits of performing and mobilising to do their best on stage (see Brooks, 2014).
Second, we can help children to develop their meta-emotional knowledge (cognitive change), teaching them how to recognise and differentiate precisely between their emotions, how to evaluate the arousal increase in the case of mobilisation. Building a new, personal method of categorising emotions as helpful or unhelpful for a certain individual, in a certain situation and a certain task (Hanin’s idea of optimal emotions in sport, IZOF, Hanin, 1997, 2007) can help to change the traditional way of evaluating negative and positive emotions as bad or good, and to build emotion beliefs based on personal experience. Decentration exercises can help performers to understand the audience’s emotional perspective and to treat listeners as a source of social support.
Third, we can teach children some strategies for changing experienced emotions (response modulation), such as developing confidence, hope and courage by referring to individual values, goals and ambitions (Osborne, Greene, & Immel, 2014). Learning relaxation techniques to lower tension arousal Clark & Williamon, 2011; Khalsa, Shorter, Cope, Wyshak, & Sklar, 2009) and cognitive techniques to focus the mind (Clark & Agras, 1991; Kenny, 2005, 2011) can be helpful. The above-mentioned knowledge and skills can help students in developing their emotional intelligence, building a positive performance attitude and achieving peak performance (Marin & Bhattacharya, 2013; Srinivasan & Gingras, 2014).
Strengths and limitations
One of the most valuable contributions of this study is that it highlights the complexity of pre-performance emotional states. If we accept a broader definition of mixed emotions as a blend of basic emotions (secondary), we may conclude that even univalent emotional states comprise different emotions; for example, High MPA involves a combination of lack of confidence, fear and sadness, whereas Composure-Confidence is a mixture of happiness, courage and cheerfulness. According to a narrow definition (mixed emotions as the co-occurrence of negative and positive emotions), we indicated mixed emotions in Moderate MPA, Hesitation and Ambivalence profiles.
The second important finding of this study is the heterogeneity of pre-performance emotional states, which vary from negative emotions of fear and sadness (High MPA) through to a mixture of positive and negative emotions (Moderate MPA, Hesitation, Ambivalence) and finally to positive emotions of confidence, courage and happiness (Composure-Confidence). The differences in emotional contents between two types of MPA have also been shown. The results of the present and previous research (Kaleńska-Rodzaj, 2018) have confirmed my assumptions that MPA may be interpreted as a secondary emotion; a complex emotional state including emotions of different modalities.
The third finding addresses the relationship between pre-performance emotional states and MPA beliefs (MPA utility beliefs, MPA regulation beliefs, audience attitude beliefs). Negative MPA beliefs are related to negative emotions experienced in performance settings (High and Moderate MPA profiles). On the other hand, the children with positive beliefs about MPA seemed to be less vulnerable to music performance anxiety as they experienced more positive emotions (Composure-Confidence, Ambivalent Emotions, Hesitation profiles).
All of the findings presented provide a new look at a structure of pre-performance emotional states, including MPA. They also show the prevention perspective (described in the above section: Practical implications for music education) in regulation of negative pre-performance emotions.
The limitations of the study must be acknowledged. Inducing emotions with memory retrieval may be considered as a limitation of the research design. However, the use of guided imagery is supported by a large body of research on imagination and perception (Herholz, Lappe, Knief, & Pantev, 2008; Zatorre & Halpern, 2005), including studies evaluating the effectiveness of visualisation techniques in various areas of performance (review meta-analysis by Schuster et al. 2011), and studies on eliciting mixed emotions (Ersner-Hershfield, Mikels, Sullivan, & Carstensen, 2008).
The list of emotions used to assess pre-performance emotions might also be refined. Although the list was based on established theory and the suggestions of experts, it should be expanded to incorporate self-conscious emotions triggered by social exposure (Lewis, 2008), such as pride, shame and guilt. Work on the tool measuring pre-performance emotions is in progress.
Although my hypotheses, based on the theory, predict a causal relationship between musicians’ beliefs and pre-performance emotional states, in practice this impact can be reciprocal: the feeling of pleasure or displeasure associated with experienced emotions has an impact on musicians’ evaluation of emotion and then on their emotional beliefs. A small number of participants in every cluster make generalisation of results difficult, however the results presented here are mostly in line with previous research (Kaleńska-Rodzaj, 2018), except the lower occurrence of sadness in the studied age group.
The present study is among the first few attempts to examine the structure of pre-performance emotions in the music performance psychology field. The findings may help to generate new ideas and theories, and inspire further extensive research on structure, functions, and correlates of pre-performance emotions. Future research should consider variables determining the ability to recognise and label emotions, which creates a basis for emotional awareness (R. D. Lane & Schwartz, 1987) and emotional intelligence (Mayer & Salovey, 1997). It could also be useful to include personality variables (self-esteem, motivation), ability-related variables (sense of efficacy as a performer), self-regulation capacity (MPA coping strategies), and the effectiveness of performing in public (performance quality). In addition, the way in which emotions mix could be addressed with a process-oriented study design, as this would allow the monitoring of temporal changes in emotional responses to the performance situation.
Footnotes
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author received financial support from the Pedagogical University of Cracow.