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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

The study longitudinally tracked the relationship among challenge/skill balance, flow, and performance anxiety in 27 student musicians over the course of a semester as they worked toward a recital of a piece of music. Using hierarchical linear modeling, the balance between the challenge of a passage of music and the perceived skills necessary to play that music was found to be significantly and consistently correlated with optimal experience. Results of moderated multiple regression indicated that skill level moderated the relationship between challenge, flow, and performance anxiety. Results also indicated that flow and performance anxiety were antithetical experiences, such that when flow was highest, performance anxiety was lowest and vice versa. These findings are discussed in terms of the application of flow theory to understanding performance, and the practical implications for reducing task-specific anxiety.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Flow is an optimal and positive state of mind during which individuals are highly motivated and engrossed in an enjoyable activity. Such optimal experiences have been reported in a wide variety of domains, including leisure (Csikszentmihalyi & Csikszentmihalyi, 1988), sports (Jackson & Marsh, 1996), and work activities (Demerouti, 2006). The current research studied the experiences of flow in student musicians. Specifically the research addressed two issues. First it looked at whether the balance between the perceived challenges in a task and the skills necessary to perform it is conducive to flow. Second, it investigated the extent to which performance anxiety interferes with the experience of flow.

Flow and Challenge/Skill Balance

The construct of “flow” was first coined by Mihaly Csikszentmihalyi (1975) who found that individuals experiencing flow frequently used the metaphor of being carried along effortlessly on a current. Flow is a subjective state that is experienced when individuals are completely absorbed by an enjoyable activity. It is characterised by an exclusive and intense concentration on the task at hand, where there is an absence of distraction, a perception of time being distorted, and where action and awareness merge in the performance of the activity (Csikszentmihalyi, 1997; Nakamura & Csikszentmihalyi, 2002). Flow is an intrinsically motivated state of self-determination (Csikszentmihalyi, 1990), in that the flow activity is performed for its own sake and not for some extrinsic reward. These essential components of flow are also reflected in operationalisations of flow at work (e.g. Bakker, 2008; Demerouti, 2006; Nielsen & Cleal, 2010). This research identifies the core elements of the experience of flow as (1) absorption, or an intense concentration and involvement in the task, (2) enjoyment of the performance of the task, and (3) intrinsic motivation, which refers to the fact that the performance of the task is motivating in itself, and does not require any external regulation or reward.

Recently flow theory has begun to distinguish between the conditions that are necessary to elicit flow, and the psychological components that constitute the experience of flow (Nakamura & Csikszentmihalyi, 2009). The preconditions of flow are inherent in the task and include: (1) the perceived challenges of the task (action opportunities) matching the skills of the person performing the task (action capabilities); (2) the task having clear and proximal goals; and (3) the task providing the individual with feedback concerning how well they are doing and the extent to which they are achieving the goals of the task. It is these task conditions that facilitate the subjective experiences of the flow state described above (Nakamura & Csikszentmihalyi, 2009). Despite this distinction, research continues to confound the preconditions of flow with its subjective states (Fullagar & Kelloway, in press).

Of the conditions that induce flow, challenge/skill balance is the most documented. Right from the initial phenomenological framing of flow, the balance of perceived challenges and skills has held a central role in understanding optimal experience (Csikszentmihalyi, 1975; see Figure 1). Flow theory stipulates that there are two components of this precondition that must be satisfied in order for optimal experience to occur (Csikszentmihalyi, 1990, 1997). First, the perceived challenges, or opportunities for action, inherent in the task or activity must interact with, and match, the perceived skills of the person performing the task (Nakamura & Csikszentmihalyi, 2002). Second, both challenges and skills must be at a moderate to high level (Massimini & Carli, 1988) so that the challenges “stretch but do not overmatch existing skills” (Nakamura & Csikszentmihalyi, 2009, p. 195). Thus, activities that demand low skills and have low challenges (such as viewing television) may be enjoyable but are conducive to apathy (Csikszentmihalyi, 1990). On the other hand, anxiety is experienced when challenges far exceed skills.

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Figure 1. Challenge/Skill balance model. Adapted from Csikszentmihalyi, 1975.

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Despite the centrality of challenge/skill balance in flow theory, little research has empirically investigated the relationship between this task precondition and the experience of flow. There are two reasons for this. First, as we mention above, it is only recently that the distinction has been made between the preconditions to flow that are inherent in the task, and the subjective experience of flow (Nakamura & Csikszentmihalyi, 2009). Second, although flow has been conceptualised as a multi-factor variable it has been predominantly measured as a higher-order unidimensional construct (Fullagar & Kelloway, in press). Other research has tended to focus on isolated components of flow, such as enjoyment or task interest (Schmidt, Shernoff, & Csikszentmihalyi, 2007). Little effort has been made to understand the relationships between the different facets of flow. Furthermore, the global constructs that are used to assess flow obfuscate the distinction between the preconditions of flow and its affective and cognitive components (Fullagar & Kelloway, in press).

It is only recently that controlled, laboratory experiments have been used to induce the state of flow by manipulating challenge/skill balance (Engeser & Rheinberg, 2008; Keller & Bless, 2008; Keller & Blomann, 2008; Moller, Meier, & Wall, 2010). This research has confirmed the core tenet of flow theory that the compatibility of skills and demands is associated with the emergence of flow. However, although such experimental methods enable the manipulation and control of variables and thus increase the internal validity of the research, they compromise the external validity of the findings. The research cited above has focused on the performance of simple video games such as Pac-Man® (Engeser & Rheinberg, 2008) and Tetris® (Keller & Bless, 2008; Keller & Blomann, 2008). Such tasks lack the cognitive realism and meaningfulness of more complex and dynamic task environments found in the “real world” (DiFonzo, Hantula, & Bordia, 1998). Consequently the first purpose of the current study was to investigate the relationship between challenge/skill balance and flow in a sample of participants performing tasks requiring distinct and personally relevant skills. Specifically, we studied flow among musicians engaged in the performance of a passage of music of varying complexity on which their ability was to be assessed.

Flow and Performance

Flow is a concept that is particularly important to the performance of artistic activities in that the goal-directed, focused attention inherent in such tasks is believed to be conducive to high levels of performance (Csikszentmihalyi, Abuhamdeh, & Nakamura, 2005; Perry, 1999; Sawyer, 1992). Flow also seems to have important implications for the development of learning. When individuals develop the skills necessary to perform an activity, they also begin to master the challenges inherent in the activity. As skills are acquired, new challenges have to be identified so that the balance between challenges and capabilities can be maintained. This cycle increases motivation, enhances competence, fosters growth, and extends the individual's capacities (Csikszentmihalyi et al., 2005). It would appear then that flow theory can provide a theoretical framework that not only enables an understanding of task engagement, in music and other endeavors, but also suggests successful strategies for practice in music education (Custodero, 2002) and other deliberate efforts at skill enhancement.

Research on flow at work has shown that flow is positively related to performance on activities that have high intrinsic motivating potential (that is high in autonomy, meaningfulness, feedback, and challenge) (Demerouti, 2006; Eisenberger, Jones, Stinglhamber, Shanock, & Randall, 2005). Although there is a paucity of published studies linking flow to musical activities, the literature that exists is consistent with the relationships found in work settings. Flow experiences have been associated with time spent practicing and musical performance (O'Neill, 1999), as well as the creativity and quality of musical compositions (Byrne, Carlton, & MacDonald, 2006). Various conditions, such as autonomy, performance feedback, social support, and supervisory coaching, have also been found to contribute to the experience of musical flow (Bakker, 2005).

Flow theory would suggest that it is at the point when the practiced skills are appropriate for the challenges posed by the task that the individual will become absorbed in the task, lose track of both time and self, and experience a state where action and awareness merge (Csikszentmihalyi, 1997; Moneta & Csikszentmihalyi, 1996; see Figure 1).

Hypothesis 1: The balance between the perceived challenge of playing a passage of music and the perceived skills of the performer will be positively associated with the subjective experience of flow.

Flow and Task-Specific Anxiety

Although there is a growing amount of research that has investigated the conditions that facilitate flow (e.g. Demerouti, 2006; Eisenberger et al., 2005; Fullagar & Kelloway, 2009; Keller & Bless, 2008; Nielsen & Cleal, 2010), no research has been undertaken to understand what prevents flow. Allison and Duncan (1988) were the first to introduce the term “antiflow”, which is the experience of either boredom or anxiety. Antiflow has been described as a demotivational state characterised by tedium and a lack of autonomy and control (Sorrentino, Walker, Hodson, & Roney, 2001). Consistent with the notion that anxiety is an important component of the antiflow state, we propose that felt anxiety during performance of a task may suppress the experience of flow.

According to flow theory, anxiety is the antithesis of flow (Csikszentmihalyi, 1975, 1990). Physiologically, the state of extreme arousal generated by anxiety has been found to be associated with “disintegrated” attention rather than the focused attention that is characteristic of flow (Izard, 1977). Music performance anxiety (MPA) is a state of distressful apprehension that has been shown to impair performance, regardless of the musician's age, aptitude, or level of training (Kenny & Osborne, 2006; Osborne & Franklin, 2002), and provides a relevant, task-appropriate construct for examining the relationship between anxiety and flow in the current research. Despite the reported pervasiveness of MPA, very little research has been published on it in the psychology literature (Kenny & Osborne, 2006).

Csikszentmihalyi's (1975, 1990) theory of flow has several implications for predicting task-specific or performance anxiety and its effect on flow. When the challenge of a task is perceived to be far in excess of the capabilities of the performer, then the prevailing psychological state of the individual will be one of anxiety. This anxiety shifts attention from the focused activity to the self and one's task-related shortcomings, and creates a state of mind that is extremely self-conscious and prevents the performer from experiencing flow (Nakamura & Csikszentmihalyi, 2002).

Hypothesis 2a: When the perceived challenge of a passage of music far exceeds the perceived skills necessary to perform the music the performer will experience performance anxiety.

Hypothesis 2b: Performance anxiety will suppress the experience of flow during the performance of a passage of music.

In summary, this study used an experience sampling method (ESM) to track student musicians as they worked toward a music recital. Specifically, the research had two aims: (1) to determine the relationship between the balance of perceived challenge and the skills necessary to perform a task (i.e. play a passage of music) and the experience of flow; and (2) to ascertain whether the relationships between challenge, flow, and anxiety were moderated by skill level.

METHOD

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Participants

Participants in the study were 27 music students (14 males, 13 females; Mean Age = 21.71 years) in a music department of a Midwest American university. Students volunteered to participate in the study and either played one of a variety of instruments including trumpet, flute, and percussion, or majored in vocal music. Each student was preparing to give a juried recital at the end of the semester. Most students had had some experience giving juried recitals at the college level (Mean number of recitals given = 3.59, SD= 3.32). The mean number of recitals indicates that most of the participants were advanced students, nearing the completion of their programs. All of the students were preparing for professional careers in music, either as performers (those pursuing a Bachelor's in Music) or as music educators (pursuing a Bachelor's in Music Education).

Procedure

At the beginning of the semester each student was asked to identify the piece of music that he/she would be playing at the juried recital. In consultation with their music instructor, this piece of music was then broken down into several passages that were compositionally coherent. The number of passages varied across the sample (Minimum = 3; Maximum = 7). At the beginning of each week for a 10-week period, a survey form was distributed to the participants. Even though students may have had multiple practice sessions during the week, they were instructed to complete the survey form once following a single practice session if that session satisfied two conditions. First, students had to have practiced the piece of music in its entirety without interruption. Second, the survey instrument had to be completed immediately following the rehearsal of the entire piece of music. This was to ensure that there was minimum distortion due to recall delay. Survey questions had to be responded to for each of the multiple passages of the piece that had been practiced. As a check, students had to state the time and date that they practiced the music as well as the time and date that they completed the survey (Mean response lag= 2.19 minutes). Each week the completed survey forms were collected at the same time and location that the next week's surveys were distributed. This process was continued for 10 weeks with the final survey being completed after the juried recital. So, if a student had selected a piece of music that consisted of five musical passages, over the 10-week period there would be 50 momentary assessments of their experience of playing the passages in that piece of music. Overall there were 1,031 momentary assessments with an average of 38.19 musical passages assessed per participant.

Measures

Each week, after practicing the entire piece of music, students answered a series of questions that assessed the perceived challenge/skill balance, experiences of flow, and felt anxiety while playing each passage of the piece of music.

Perceived Challenge.  The perceived challenge of playing each passage of the musical piece was assessed by two questions: “How much challenge was there in playing this passage of music?” and “How difficult was this passage of music to play?” Each question was responded to using a 10-point response format (1 =“Not at all challenging/Very easy”, 10 =“Extremely challenging/Extremely difficult”). The overall perceived challenge score was calculated by summing the scores on these two items. The internal consistency coefficient of these two items (computed on within-individual mean item ratings) was satisfactory (α= 0.93).

Perceived Skill.  Student musicians' perceptions of their capabilities to play each passage of music were assessed by two items: “How much more do you need to rehearse this passage?” (reverse coded) and “How well prepared were you to play this passage of music?” Again a 10-point response format was used (1 =“No more rehearsal/Extremely unprepared”, 10 =“Much more rehearsal/Extremely well prepared”). The overall score for perceived capabilities or skills to perform the passage of music was calculated by summing the item scores. The internal reliability of these two items was good (α= 0.95).

Challenge/Skill Balance.  This was calculated by the absolute difference between the perceived challenges and perceived skills or capability scores with regard to playing each passage of music. Consequently lower scores indicated greater balance between challenges and skills.

Flow.  Optimal experience or flow was assessed with six items adapted from the Flow State Scale (FSS-2; Jackson & Eklund, 2004; Jackson & Marsh, 1996). The six items with the highest factor loadings from Jackson and Eklund's (2004) scale were used to measure enjoyment, concentration, action/awareness merging, loss of self-consciousness, time transformation, and a sense of control. The items were adapted to be appropriate for musical performance rather than athletic performance. The scale was theoretically grounded in Csikszentmihalyi's (1990) operationalisation of flow and assessed the six core components of the flow experience (Nakamura & Csikszentmihalyi, 2009). The scale did not assess challenge/skill balance, goal clarity, or feedback as these are considered preconditions to flow and inherent in the task. They were not regarded as elements or components of the state (Nakamura & Csikszentmihalyi, 2002, 2009). Students were asked to think about how they felt while playing a particular passage of music and to respond to the various statements on a 7-point scale (1 =“Strongly Disagree”, 4 =“Neither Agree nor Disagree”, 7 =“Strongly Agree”). A composite flow score was calculated for each passage of music played by summing the scores on each of the six components. The dimensions of flow have been found to be highly correlated, thereby justifying a composite measure (Jackson & Eklund, 2004). The internal consistency of these six items was satisfactory (α= 0.83).

Momentary performance anxiety while playing each passage of music was measured using a single-item scale: “How anxious were you feeling while playing this passage of music?” Respondents answered on a 10-point response format (1 =“Not at all anxious/extremely relaxed”, 10 =“Very anxious/extremely tense”). As with the above variables, momentary performance anxiety was assessed each time the musician played or rehearsed a passage of music.

Analysis

To investigate the effects of trait anxiety and challenge/skill balance on flow and performance anxiety, hierarchical linear modeling was used (HLM; Bryk & Raudenbush, 1992). One of the assumptions of regression analysis is that residual effects are independent. Obviously time-series data violate this assumption of residual independence at level 1 (Hofmann, Griffin, & Gavin, 2000). Consequently level-1 models were developed that accounted for the residual autocorrelation in the data. This was accomplished by controlling for lagged flow and lagged performance anxiety in the level-1 equations (Bryk & Raudenbush, 1992).

To examine within-individual (level-1) relationships between challenge/skill balance, flow, and performance anxiety, flow and performance anxiety were separately regressed onto challenge/skill balance. Although we felt that a difference score was the best way to operationalise challenge/skill balance, we were aware of some of the statistical problems associated with the use of a global difference score to denote balance (see Edwards, 2001, for a summary). Consequently, in order to further test our hypotheses and to ascertain more precisely the interaction between the perceived challenge of the task and the perceived skill of performing the task, we used moderated multiple regression analyses (Aiken & West, 1993; Preacher, Curran, & Bauer, 2006). Two models were calculated using momentary flow and performance anxiety as separate outcome variables, and including challenge, skill, and the interaction term (challenge × skill) as predictors. Both challenge and skill were standardised. Asymptotic variances and covariances were then used to calculate the simple slopes and determine the nature of the interactions (Bauer & Curran, 2005; Preacher et al., 2006).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

Means, standard deviations, and intercorrelations across individuals for all study variables are presented in Table 1. The distributional qualities of the measures of perceived challenge and perceived skill necessary to capably play the passage of music were assessed. The overall mean of the composite sum of the two perceived challenge items was 13.98 (SD= 3.99, median = 14.43) and that of the two perceived skills items was 10.81 (SD= 3.36, median = 11.22). Consequently, the challenge and skills inherent in performing the passages of music was generally perceived by all participants to be above average and to be negatively skewed in the moderate to high level.

Table 1. Means (M), Standard Deviations (SD), and Intercorrelations across Individuals for all Study Variables (N= 27)
 MSD 1 2 3 4
  1. * p < .05; ** p < .01.

1. Flow30.025.99    
2. Performance Anxiety4.661.77−.57**   
3. Challenge/Skill Balance6.222.79−.62**.52**  
4. Perceived Challenge13.983.99.59**−.53**−.85** 
5. Perceived Skill10.813.36.03−.02−.27.12

Before proceeding with the tests of the hypotheses, we analyzed the systematic within- and between-individual variance in momentary flow and performance anxiety. The results of the null models that were used to test these statistical assumptions are presented in Table 2. The results indicated that there was substantial within- and between-individual variance for both momentary flow and anxiety (Flow: σ2= 30.95, τ00= 5.14; Anxiety: σ2= 4.47, τ00= 0.26). Chi-square tests indicated that the between-individual variance was significant for both flow and anxiety (Flow: τ00= 5.14, χ2(26) = 204.07, p < .01; Anxiety: τ00= 0.26, χ2(26) = 80.96, p < .01). The intraclass correlation (ICC=τ00 /(σ2+τ00)) for the flow measure was .14, indicating that between-individual variance accounts for 14 per cent of the total variance in flow. This would suggest that 86 per cent of the overall variance (both systematic and error) is attributable to within-individual variation. For anxiety, 5 per cent of the total variance was accounted for by between-individual variance, indicating that 95 per cent of the variance was due to within-individual variation in momentary performance anxiety. These results suggest that both flow and anxiety vary considerably from situation to situation.

Table 2. Parameter Estimates and Variance Components of the Null and Serial Dependent Models
Model equations γ00γ10 σ 2 τ 00 τ 11
  • a

    β 0 j is the average level of flow/performance anxiety for individual; j: γ00 is the grand mean of flow/performance anxiety scores; σ2= var(rij) the within-individual variance in flow/performance anxiety (computed as the average squared distance from individual momentary scores and the individual's mean score); and τ00= var(U0j) the between-individual variance in flow/performance anxiety (the variance of the 27 average flow/performance anxiety scores).

  • b

    γ00= intercept of level-2 regression predicting β0j, γ10= intercept of level-2 regression predicting β1j, σ2= variance in level-1 residual (i.e. variance in rij), τ00= variance in level-2 residual for models predicting β0j (i.e. variance in U0j), τ11= variance in level-2 residual for models predicting β1j (i.e. variance in U1j).

  • * p < .05; ** p < .01.

Null models a
Flowij=β0j+rij29.7230.955.14** 
Perf. Anxietyij=β0j+rij4.664.470.26** 
β0j00+U0j
Serial Dependent Models (Random-coefficient regression) b
L1: Flowij=β0j+β1j (Flowij.t-1) +rij
L2: β0j00+U0j29.910.37**25.861.550.03
L2: β1j10+U1j
L1: Perf. Anxietyij=β0j+β1j (Perf. Anxietyij.t−1) +rij
L2: β0j00+U0j4.630.32**3.950.090.03
L2: β1j10+U1j

We also tested whether individuals' flow and anxiety ratings were randomly distributed or serially dependent (Ilies & Judge, 2002; see Table 2). Lagged flow was found to be a significant predictor of momentary flow (Flow: γ10= .37, p < .01), and anxiety was also serially dependent on its lagged effect (Anxiety: γ10= .32, p < .01). All subsequent models controlled for lagged effects.

In order to test if there was a relationship between challenge/skill balance and the experience of flow while performing a passage of music (Hypothesis 1), we ran a random coefficient regression model controlling for the lagged effects of flow. The results of this analysis are presented in Table 3. The regression coefficient for challenge/skill balance was significantly different from zero (β21=−0.60, t(1028) =−18.30, p < .01). The direction of the regression coefficient indicates that lower discrepancy or greater balance between perceived challenges and skills is associated with higher levels of flow. Challenge/skill balance accounted for 35 percent of the within-individual variance in flow, after controlling for the lagged effects of flow. In sum, results supported Hypothesis 1 by indicating that challenge/skill balance was significantly related to the experience of flow.

Table 3. Results for the Random-Coefficient Regression Models for Flow and Performance Anxiety Controlling for Lagged Effects
Model equations β 1j β 2j γ00γ10γ20 σ 2
  • a

    γ00 is the mean of the intercepts across groups; γ10 is the mean of the slopes across groups; σ2 (rij) is the level-1 residual variance.

  • * p < .05; ** p < .01.

Random-coefficient regression models a
L1: Flowij=β0j+β1j (Flowij.t−1) +β2j (Challenge/Skill Balanceij) +rij
L2: β0j00+U0j
L2: β1j10+U1j
L2: β2j20+U2j0.30**−0.60**29.75**0.15**−0.76**16.92
L1: Perf. Anxietyij=β0j+β1j (Perf. Anxietyij.t-1) +β2j (Challenge/Skill Balanceij) +rij
L2: β0j00+U0j
L2: β1j10+U1j
L2: β2j20+U2j0.15**0.26**4.71**0.060.35**2.11

A similar random regression model was used to assess the relationship between challenge/skill balance and performance anxiety (Hypothesis 2a). The results of the hierarchical linear model that was tested are presented in Table 3. T-tests indicated that the level-1 regression coefficient was significantly different from zero (β21= 0.26, t(1028) = 22.15, p < .01). This indicates that the larger the discrepancy between perceived challenges and the skills necessary to perform a piece of music the greater the experience of performance anxiety. Forty-seven per cent of the within-individual variance in performance anxiety was accounted for by challenge/skill balance, after controlling for lagged anxiety. This would appear to support Hypothesis 2a.

To test Hypothesis 2b and to better understand the relationship between challenge/skill balance and the experiences of flow and performance anxiety, we used moderator multiple regression analyses on the level-1 variables (Aiken & West, 1993). The results of the moderated random-coefficient regression analyses are presented in Table 4. The interaction effect between perceived challenge and perceived skill was found to be significant for flow (γ40= 1.35, t = 8.48, p < .001) and performance anxiety (γ40=−0.75, t = 12.77, p < .001) after controlling for autocorrelational effects. The effect sizes of the challenge × skill interaction effect were significant for both flow (R2= .07) and anxiety (R2= .15).

Table 4. Results for the Moderator Random-Coefficient Regression Analyses
Model parameters a γ 00 γ 10 γ 20 γ 30 γ 40
  • Note: The regression coefficients presented in the table are not standardised.

  • a

    Lagged flow (Flowij.t−1) and lagged anxiety (Perf. Anxietyij.t−1) were centered at the grand mean, whereas challenge and skill were standardised.

  • * 

    p < .001

Random-coefficient regression model a
L1: Flow =γ0010 (Flowt−1) +γ20 (Challenge) +γ30 (Skill) +γ40 (Challenge × Skill) + r
 29.84*0.23*1.93*−1.29*1.35*
L1: Perf. Anxiety =γ0010 (Perf. Anxietyt−1) +γ20 (Challenge) +γ30 (Skill) +γ40 (Challenge × Skill) + r
 4.61*0.12*−0.73*0.59*−0.75*

Using asymptotic variances and covariances, we plotted the simple slopes in order to understand the nature of the interaction effects (Bauer & Curran, 2005) (see Figures 2 and 3). The perceived challenge of the task was not related to flow among those musicians who perceived their skills to be low. For low-skilled performers, flow was uniformly high regardless of the challenge of the piece of music they were playing (Figure 2). However, as skill level increased, the relationship between challenge and skill was stronger and more positive. Among moderate to highly skilled musicians, flow levels were highest when challenge was high, and lowest when the piece of music being played was not challenging (Figure 2). These results would again appear to support Hypothesis 1. The converse was found for performance anxiety as the outcome variable. Low-skilled performers uniformly experienced low levels of anxiety and this was independent of the degree of challenge in the music being played (Figure 3). On the other hand, among moderate to highly skilled musicians, the amount of anxiety experienced increased as the challenge of the task decreased (Figure 3). Anxiety was highest when playing not particularly challenging music, and lowest in the high challenge situation, that is when flow was at its highest level. Consequently, analysis of the data using moderator multiple regression rather than difference scores yields results that are not supportive of Hypothesis 2a. However, our data do suggest that flow and anxiety are incompatible states, in that among moderately to highly skilled musicians anxiety was lowest when flow was highest and vice versa. Therefore Hypothesis 2b was supported.

image

Figure 2. Simple slopes analysis with flow as the outcome variable.

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Figure 3. Simple slopes analysis with performance anxiety as the outcome variable.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES

The current research set out to test the relationship between an important precondition to flow, the balance between action opportunities and action capabilities, and the subjective experience of flow. Recently this relationship has been studied in participants engaging in relatively simple videogame tasks in laboratory settings (Engeser & Rheinberg, 2008; Keller & Bless, 2008; Keller & Blomann, 2008). We wanted to ascertain whether the relationship between challenge/skill balance and optimal experience generalised to a more complex, meaningful, and dynamic task that consisted of moderate to high levels of both perceived challenge and skill.

Using the absolute difference between skill and challenge measures, we found that both flow and performance anxiety were associated with the balance between the perceived skills necessary to perform a task and the perceived challenges inherent in the task. Flow was more likely to occur for tasks where challenges and skills were balanced, whereas performance anxiety was associated with tasks where the challenge did not match the skills of the performer. These results confirm Csikszentmihalyi's theory that the balance between challenge and perceived skills is an essential precursor to flow, even in the performance of a complex task such as playing a passage of music.

However, it must be noted that there has been some controversy about the use of difference scores (Edwards, 2001; Peter, Churchill, & Brown, 1993). One of the main problems is that difference scores are typically less reliable than their component variables (Peter et al., 1993). We felt justified in using difference scores for two reasons. First, the reliability coefficients for challenge (α= .93) and skill (α= .95) were satisfactory and the attenuation in reliability for the difference term was minimal. Second, the correlation between the components was small (r=−.001). A second issue with difference scores is the possible restriction in variance in the difference variable (Peter et al., 1993). This did not seem to be a problem in the current study. Further, such a restriction in variance would have truncated the correlations between challenge/skill balance and both flow and performance anxiety, resulting in a more conservative test of the hypotheses. However, using absolute difference scores confounds the experiences of boredom and anxiety proposed by Csikszentmihalyi's channel theory (1975). Consequently the procedure we used may have caused artificial dichotomies in our data and a loss of fidelity. To avoid these kinds of problems we further analyzed our data using interactive regression analysis (Edwards, 2001) to determine whether the relationship between flow and challenge was moderated by the perceived skill level of the person performing the task.

The results of moderated multiple regression provided a more detailed analysis of the relationship between challenge and flow that is both consistent and contrary to flow theory. The literature on optimal experience suggests that challenges and skills have to be at relatively high levels to experience flow (Massimini & Carli, 1988). Our results found that there was no relationship between the challenge of the task and flow for low-skilled performers, whereas there was a significant positive relationship when skill levels were perceived to be moderate to high. Among moderate to highly skilled performers, flow levels were highest when the piece of music being played was challenging. A similar finding was found with momentary performance anxiety as the outcome variable. Specifically, when skill levels were perceived to be low, there was no relationship between the perceived challenge of the music and task-specific anxiety. In this circumstance anxiety was uniformly low. However, for performers who perceived their musical skills to be moderate to high, the perceived challenge of the task was significantly and negatively related to performance anxiety. Skilled performers experienced the highest level of task-specific anxiety when playing relatively easy pieces of music. This contradicts the eight-channel theory of challenge/skill balance (Csikszentmihalyi, 1988, 1990; Massimini & Carli, 1988) that stipulates that when the challenge of a task is low and the skills required to perform the task are moderate to high, then the resulting state should be one of either boredom or relaxation (Massimini & Carli, 1988) rather than anxiety. Anxiety is proposed to be experienced when the challenge of the task is perceived to be high and skills low (Csikszentmihalyi, 1975). We also found partial support for the notion that flow and performance anxiety are mutually exclusive experiences. When flow was highest, anxiety was lowest, and vice versa. However, this relationship was moderated by the perceived skill level of the person performing the task. Low-skilled performers experienced relatively high levels of flow and low levels of anxiety regardless of the difficulty of the task, unlike the moderate- to high-skilled performers.

These findings are consistent with recent theory and research on the physiological and cognitive anatomy of flow. For example, Dietrich (2006; Dietrich & Stoll, 2010) has proposed that flow is a state of “transient hypofrontality” in that there is a temporary suspension of some higher cognitive functions thereby disabling their interference with the more implicit and automatic cognitive processes that are characteristic of flow. This would explain why participants experienced more anxiety when performing less challenging tasks. It is in such tasks that analytic cognitive processes have more opportunity to interfere with the focused attention of flow and facilitate a more disintegrated or distracted attention that is characteristic of anxiety. This explanation is also consistent with distraction theory, which proposes that when an individual's attention is diverted from the execution of the task by task-irrelevant thoughts, performance is impaired and there is a greater likelihood of anxiety (Beilock & Carr, 2001; Lewis & Linder, 1997).

The finding that flow and task-specific anxiety are incompatible states is corroborated by recent research on the physiology of flow (see Ullén, de Manzano, Theorell, & Harmat, 2010). In a study of professional pianists, flow was shown to correlate with decreased heart period, increased cardiac output, increased respiratory rate and depth, an activation of facial muscles associated with the expression of positive emotions, and a deactivation of muscles implied in negative emotional expression (de Manzano, Theorell, Harmat, & Ullén, 2010). Furthermore, there is evidence that suggests that flow is associated with the activation of parasympathetic systems that have been shown to counteract the catabolic sympathetic activity that is associated with stress (Grape, Sandgren, Hansson, Ericson, & Theorell, 2003).

Some research has identified situational characteristics associated with flow, such as the amount of autonomy and skill variety inherent in the task (Demerouti, 2006; Fullagar & Kelloway, 2009). However no research has investigated the task-specific characteristics that may inhibit flow and induce its opposite state, antiflow. Our research indicated that task-specific anxiety and flow are incompatible states. Specifically, when performance anxiety was highest, flow was lowest, and vice versa. We would argue that flow and anxiety are not antipodal states (in that they are not the opposite ends of the same continuum), but that they are antithetical (in that they are negatively related). Antipodal constructs suggest that the absence of one construct indicates the presence of the other construct, and that both can be measured using the same scale. Our findings indicate that flow and performance anxiety can exist simultaneously, but that the presence of one minimises the magnitude of the other. Also, we would not suggest that flow and performance anxiety be measured using the same scale. As mentioned above, an antithetical state to flow has been briefly referred to in the literature and termed “antiflow” (Allison & Duncan, 1988). Antiflow has been described as a demotivational state characterised by tedium and a lack of autonomy and control (Sorrentino et al., 2001). However, very little empirical research has addressed the nature of antiflow. Our research would suggest that task-specific anxiety may be an important component of the antiflow state that suppresses optimal experience.

Our multilevel analyses of the variance components of flow and performance anxiety indicate that most of the variation in both constructs is due to situational characteristics, even taking into account that some of this variance could be attributable to error. This suggests that both constructs demonstrate state-like rather than trait-like properties, and further supports evidence that flow is a situational or momentary state, rather than a trait (Fullagar & Kelloway, 2009). This has important theoretical implications. The clarification of key concepts and distinguishing between traits and states is important in the construction of theory in psychology (Mischel, 1969). Luthans (2002) has emphasised that a crucial criterion for the inclusion of constructs in positive organisational scholarship should be that they are manageable and capable of being effectively changed to improve performance. Our research adds further evidence that both flow and performance anxiety are responsive to changes in situational contingencies, specifically the degree of balance between the challenge of the task and the skills necessary to meet that challenge.

We do not wish to suggest that there are no trait aspects to either task-specific anxiety or flow. One model that has been used to understand music performance anxiety is Barlow's theory of emotion (2000). This model conceives performance anxiety as consisting of the interplay between inherited biological predispositions and learned environmental contingencies. Our methodology focused predominantly on assessing momentary anxiety and flow, and even though our findings support that of Fullagar and Kelloway (2009) in documenting state-like aspects of flow, there is evidence of trait components to optimal experience. Several studies have indicated that self-motivated individuals who have a high need for achievement exhibit a greater predisposition to experience flow, and are more likely to seek out situations of challenge/skill balance than those who are lower on these characteristics (Asakawa, 2004; Eisenberger et al., 2005). Our research did show that the relationships between flow and challenge, and between flow and task-specific anxiety, were moderated by perceived level of skill. It is conceivable that skill levels are at least partially determined by such dispositional characteristics as intrinsic motivation and need for achievement.

Our findings have several important practical implications. First, the finding that both flow and performance anxiety are predominantly state constructs suggests that there are situational factors that can be managed to facilitate the experience of flow and to reduce performance anxiety. The treatments for performance anxiety fall into two broad categories (Kenny, 2005). First, there are various combinations of cognitive and behavioral approaches (e.g. behavioral rehearsal, systematic desensitisation, stress inoculation, relaxation, meditation, and biofeedback). Second, there are psychopharmacological or drug interventions that reduce the effects of adrenaline (e.g. the use of beta-blockers, selective serotonin reuptake inhibitors, and anti-depressants). However, there are few well-conducted studies that have assessed the effectiveness of these treatments. Kenny (2005), in a review of treatments for music performance anxiety, concludes that “the literature on treatment approaches for MPA is fragmented, inconsistent, and methodologically weak. These limitations make it difficult to reach any firm conclusions about the effectiveness of the various treatment approaches reviewed” (p. 206). Our research suggests that generating a flow state would appear to be one effective way to reduce performance anxiety.

Among moderately to highly skilled performers, we found that the highest levels of task-specific anxiety occurred when the task was perceived to be relatively easy. Our results further indicated that if the performer was anxious, it was much less likely for him/her to experience flow. Conversely, when performers experienced high levels of flow, their anxiety was the lowest. Apparently, being “in flow” enables performers to focus on the task, enjoy their performance, and feel less anxious. This suggests that one way to prevent performance anxiety is to encourage flow. For more skilled individuals, it is even more important that the perceived challenge of the task match their perceived skill level in order to facilitate flow and reduce performance anxiety.

Several factors have been identified as facilitators of flow. Csikszentmihalyi et al. (2005) specifically outline three conditions that are important for encouraging optimal experience or flow. These include having clear goals, the provision of specific feedback concerning task performance, and having the skills necessary to perform the task. We see these three conditions as being dynamically related. Our research suggests that optimal levels of flow are achieved through two interrelated processes. First, individuals should, when possible, choose moderately challenging tasks that are commensurate with their ability. Second, a practice regime should be established that has clear goals and specific feedback, enabling the individual to develop the skills necessary to perform the task. In addition to these factors, Bakker (2005), drawing upon emotional contagion theory, found that flow spilled over from music teachers to their students. Consequently, another way of increasing flow and decreasing performance anxiety is for teachers to model the state both in their own performances and in their instruction.

Our findings have broader implications for the world of work in general. We have argued that both flow and work-related anxiety are predominantly determined by situational factors. Specifically, our results would suggest that organisations may be able to increase the amount of flow experienced at work, and simultaneously decrease work-related anxiety, by increasing the level of challenge in the task so that it is commensurate with the skill level of the worker. However, this effect may only be significant for workers with moderate to high skill levels. Such manipulations of the challenge of the task may not be effective for increasing flow and decreasing work-related anxiety in workers with low skill levels.

Our findings may also help us better understand how subjective worker experiences are related to objective performance outcomes. The factors described by Csikszentmihalyi et al. (2005) as facilitators of flow are remarkably similar to the prescriptions of goal setting theory. Clear goals that are matched to ability levels and accompanied by task feedback have been found to be related to increased performance in a wide range of settings (Locke & Latham, 2002). It is possible that following the prescriptions of goal setting encourages the development of flow, and thereby contributes to reduced stress and anxiety, as well as improved performance. If so, the experience of flow might help explain the positive effects associated with goal setting, as well as suggesting positive emotional outcomes that have not traditionally been studied in goal setting research.

Finally, our results have broader practical implications for individuals who wish to achieve optimal experience. Faced with a discrepancy between challenges and skills, the individual can respond in two ways (Csikszentmihalyi, 1990). First, he or she can increase the perception of challenge in the task. Csikszentmihalyi (1990) points out that this is relatively easy once the individual is aware that challenges exist. The other response is to increase one's skills through practice or training. Which of these strategies is used is dependent on the situation. Increasing perception of the task challenge is more likely when the individual believes that they are over-skilled, while increasing skills through practice is more relevant when the individual believes that they are under-skilled to perform the task. The goal is to achieve a balance between perceived skill and perceived challenge. It is at this point that the individual will become absorbed in the task and experience flow. However, simply balancing challenges and skills is not sufficient to produce optimal experience. Challenges have to be at a level that is the above average for the individual so that there is the opportunity for skill development, as demonstrated by the low levels of flow, and high levels of anxiety, in our data when high skill was matched with low challenge. Task-specific anxiety can be effectively reduced by ensuring a balance between perceived, moderate, task challenge and the skill level required to perform the task, thereby inducing flow.

There are several limitations to the current study that suggest directions for future research. First, we studied a very select sample of music students. It would be interesting to see if the antithetical relationship between flow and performance anxiety generalised to other disciplines, including and beyond the performing arts and athletic activities. Even though MPA appears to be independent of ability and experience (Kenny & Osborne, 2006), future research should investigate whether the mutually exclusive relationship between flow and performance anxiety maintains itself with experience. Second, one of the limitations of the Experience Sampling Method is that it necessitates the use of short scales that are minimally disruptive and require minimal effort. Our research used short composite scales to assess flow, perceived challenge, skill level, and performance anxiety. Such scales have yet to have their psychometric properties confirmed. With flow in particular, there is some debate as to whether it should be assessed as a multi-dimensional or unidimensional construct (Marsh & Jackson, 1999). Although our research utilised a specific composite measure, there are other operationalisations of flow (e.g. Bakker's work-related flow inventory (2008)). Future research would do well to use more extensive, multi-faceted operationalisations, as well as alternative definitions of flow to establish the general validity of the effects found in the current research. Finally, it could be argued that there was not much variation in the musical tasks that were studied, and that any within-subject variance could be due to variations in dispositional anxiety rather than fluctuations in momentary performance characteristics. However, our participants played several instruments and performed a wide variety of musical compositions that were each divided into several musical passages of varying difficulty. We are therefore confident that the variances in challenge/skill balance, momentary flow, and performance anxiety were sufficiently large.

There is growing evidence that the experience of flow is significantly and positively related to performance (Demerouti, 2006; Eisenberger et al., 2005). Flow has also been associated with positive mood (Fullagar & Kelloway, 2009). Fredrickson (1998, 2001) has made compelling theoretical arguments based on empirical evidence that positive emotions broaden individual resources and thought–action repertories such that individuals experiencing such emotions function at an optimal level. This is corroborated by research that has correlated psychological well-being with employee performance and turnover (Wright, Cropanzano, & Bonett, 2007). Our research did not assess students' performance in their final recital. It would be interesting to ascertain whether the relationship between flow and performance is robust, and transfers to a wider range of tasks, including musical performance.

In conclusion, this study aimed to understand the relationship between an important precondition of flow, namely challenge/skill balance, and the experience of flow while performing an applied, complex, task. Although this relationship has been established for simple tasks, such as playing videogames, we found that it translated into a more complex and dynamic musical task where participants were motivated to perform well. Specifically, we found that the experience of flow can be promoted by ensuring a balance between the challenges inherent in a task and the perceived skills necessary to perform that task, particularly among individuals who already perceive their task-related skills to be moderate to high. Our study suggests that understanding the processes that generate the flow state provides both a theoretical and practical framework for reducing performance anxiety.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. METHOD
  5. RESULTS
  6. DISCUSSION
  7. REFERENCES
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