The Relationship Among Flow, Performance Anxiety and Performance Satisfaction in Musicians
Bachelor thesis Social Psychology
Noor Wielaart (10534165) University of Amsterdam Supervisor: Dr. Svenja A. Wolf Submission date: June 2nd, 2017 Words: 5063
Abstract
The present study aimed to investigate the relationships among dispositional flow, music performance anxiety, and music performance (defined as performance satisfaction) in musicians. Dispositional flow, music performance anxiety, and performance satisfaction were measured among 89 musicians who played in various Dutch orchestras and who had just performed. Results indicated that neither dispositional flow nor the experience of music performance anxiety predicted performance satisfaction. On a subscale level a higher predisposition to experience flow in the form of skill-challenge balance predicted greater performance satisfaction. Dispositional flow was found to be negatively related to music performance anxiety. To improve performance, musicians could choose situations in which their skills are appropriately challenged. In addition, teachers and conductors should help creating environments in which the skill-challenge balance is fostered.
The Relationship Among Flow, Anxiety and Performance Satisfaction in Musicians How do you achieve optimal performance? This is an interesting question; all
musicians strive for a good performance outcome (Chaffin & Lemieux, 2004). Being able to describe what musicians need to do to perform optimally would enable people to work directly towards excellence. There are many potential influences on optimal performance. One possibility to optimise a performance is completely losing yourself in a performance (Jackson & Roberts, 1992; Jackson, Thomas, March, & Smethurst, 2001). That is, not noticing anything that happens in the surrounding environment and not paying attention to inner feelings (e.g. hunger or thirst). This is called a flow state, and once you experience this, all you do is focus on the task (Csikszentmihalyi, 1990). This focus might help you improve your performance. Conversely, some musicians experience anxiety regarding performing publicly (Fehm & Schmidt, 2006). Just thinking of the audience that might be evaluating them while they are doing their best could be frightening. Hence, performance anxiety might lead to a decline in performance. Both flow and performance anxiety are potential factors that might influence music performance.
Measuring musical performance is complex because of its subjective nature. People differ in what they classify as a good performance. So, in order to measure performance and guide people in the right direction to optimize their performance, the construct needs to be specified. One way of operationalising performance is by measuring the satisfaction
musicians feel after performing. Musicians are experts in their field, and therefore able to tell a good performance from a bad performance. In this regard, musicians will be more satisfied with their performance when they performed well rather than when they did not. Moreover, performance satisfaction has been used in other domains to measure performance (e.g. outcomes in sport; Pensgaard & Duda, 2003, and customer satisfaction as a proxy for marketing success; Eccles & Pyburn, 1992)
However, simply measuring to what extent people are satisfied with their performance is not very informative. To understand how the optimal performance comes about, it is useful to investigate its predictors. Knowing what factors predict a good performance enables
musicians to seek and create circumstances which foster those factors. As for predictors, there are a lot of factors that could influence performance outcomes, e.g. skill level (Beilock & Gray, 2012), attention (Castanada & Gray, 2007), and motivation and effort (Yeo & Neal, 2004). In addition, especially practice-related aspects have been found to influence
performance. Williamon and Valentine (2000) found the quality of practice rather than its quantity to be influential for the level of performance outcome. Furthermore, according to a meta-analysis, deliberate practice explained 21% of the variance in performance in domains such as sports and professions (Macnamara, Hambrick, & Oswald, 2014).
Besides behavioural aspects such as practice, affective aspects are important too in influencing performance. To illustrate, positive affective states have been associated with an increase in creativity (Schwarz & Bless, 1991), and creativity has been linked to better performances in music (Clarke, 2005). Furthermore, emotional characteristics (which could be seen as affective processes; Clore & Ortonoy, 2008) have been found to directly relate to better performances in nursing students (Beauvais, Brady, O’Shae, & Griffin, 2010). To further investigate the effect of affective states on music performances, this study looks at flow.
Besides motivational and concentrative components, flow is a state that encompasses positive affect in the form of pleasure (Csikszentmihalyi, 1990; Jackson & Csikszentmihalyi, 1999). The term flow was introduced in the seventies by Csikszentmihalyi, who, after
extensive research, described flow as a state of mind in which people are immensely involved in an activity, even much so that nothing else seems to matter (Csikszentmihalyi, 1990). In addition, he placed pleasure in participating in the activity as a key element of flow; people
engage in it just for the sake of doing it. Furthermore, flow can be described as the experience of working at full capacity (Nakamura & Csikszentmihalyi, 2002). Jackson and
Csikszentmihalyi (1999) translated all findings on flow into the following nine fundamental dimensions that give an extensive idea about what flow entails: challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration on the task at hand, sense of control, loss of self-consciousness, time transformation, and autotelic
experience.
The experience of flow is quite common in musicians. Sinnamon, Moran, and O’Connell (2012) found that 95% of elite music students experienced flow frequently or always. In amateur students, this percentage was 87%. Additionally, Frits and Avsec (2007) demonstrated that most music students experienced flow in a performance setting.
Flow is expected to affect music performance because people in flow are very concentrated and put everything they have into their task, which would most likely facilitate their performance (Beal, Weiss, Barros, & MacDermid, 2005). Furthermore, Engeser and Rheinberg (2008) described the association between flow and better performances because of the following arguments. Firstly, flow in itself is a highly functional state that fosters a performance. Secondly, individuals known to the feeling of flow are more motivated to execute further activities that allow them to experience flow again, and in order to do so, they choose activities that are challenging. In this sense, flow could be seen as a continuous motivation to achieve excellence.
Correlational support for a relationship between flow and performance in other domains has been documented by Jackson and Roberts (1992), who found characteristics of flow to be linked to collegiate athletes’ reflections on their best performances. More evidence in a sport setting was found by Jackson et al. (2001) who demonstrated a positive link
surfers, and orienteers. Furthermore, it has been shown that the experience of flow in individuals indirectly contributes to a better team performance in an organizational setting (Aubé, Brunelle, & Rousseau, 2014). Based on these findings and previous arguments, it is expected that flow influences performance in a musical setting too.
Nonetheless, not everyone is capable of experiencing flow. Csikszentmihalyi (1990) states that people differ in their ability to control and center their attention, and therefore differ in their skill to focus their psychic energy. Consequently, some people are better
psychologically equipped to experience flow, independent of the situation. In this regard, flow seems to be a trait; a relatively stable characteristic that is generally difficult to change
(Watson & Clark, 1984). With this in mind, it is interesting to look whether the possession of the flow trait is linked to performance (satisfaction).
An affective state that is in stark contrast with flow is anxiety (Fullagar, Knight, & Sovern, 2012). Anxiety is an important component of the experience of antiflow, which is a demotivational state in which an individual lacks autonomy and control (Allison & Duncan, 1988; Sorrentino, Walker, Hodson, Roney, 2011). This is supported by the physiological finding that the extreme state of arousal generated by anxiety is linked to disintegrated attention, which in turn, is in contrast with the focused attention that is needed to experience flow (Izard, 1977). It is interesting to see whether antiflow’s component anxiety negatively affects performance satisfaction in music.
According to Salmon (1990) music performance anxiety denotes “the experience of persisting, distressful apprehension about and/or actual impairment of performance skills in a public context, to a degree unwarranted given the individual’s musical aptitude, training and level of preparation” (p. 3). The prevalence of music performance anxiety is relatively high. Fehm and Schmidt (2006) found that one third of adolescent students at a music conservatory were impaired by their anxiety. Not only young people seem to be affected by anxiety whilst
playing music. Performances of more than one third of students and faculty members of a university’s music department were negatively affected by anxious feelings, varying from completely impairing their act to feeling uncomfortably distressed while playing (Wesner, Noyes and Davis (1990). A small percentage even indicated that their professional music careers were negatively influenced by their anxiety. Finally, self-reported music performance anxiety was found to be more severe in solo performances, compared to group and practice performances (Nicholson, Cody, & Beck, 2015).
Music performance anxiety expresses itself on three levels: the behavioural level (Clark & Agras, 1991; van Kemenade, van Son, & van Heesch, 1995), the cognitive level (Steptoe & Fidler, 1987; Tobacyk & Downs, 1986), and the physiological level (James, 1988; Lehrer, 1987). Each of these dimensions could link to music performance. Behaviour (e.g. avoiding performance opportunities; Gross & Hen, 2004) directly affect performance outcome because there is no performance. Furthermore, irregular cognitions, e.g. thinking that one mistake could ruin an entire career, only feeds feelings of anxiety (Hovey & Maganã, 2002). Lastly, feelings of anxiety are expressed via sweaty hands, heavy breathing, irregular or a fastened heartbeat, which increase chances of actual mistakes during performances (Sarason, 1984).
Performance anxiety has previously been found to contribute to performances in various contexts. For example, Kouchaki and Desai (2015) demonstrated anxious individuals to perform worse in hypothetical work-situations compared to non-anxious individuals. Another extensively researched context is sports. Wilson, Wood, and Vine (2009) found a relation between anxiety and performance detoriation in soccer players. Furthermore, athletes have been observed to feel like they are chocking while being in stressful and
anxiety-provoking situations, which resulted in a decrease in their performance (Craft, Magyar, Becker, & Feltz, 2003).
Similar to flow, individuals differ in their propensity to experience music performance anxiety. Moreover, music performance anxiety seems to not be just a state of mind; general trait-anxiety was found to positively correlate with music performance anxiety in music students (Cox & Kenardy, 1993) as well as professional orchestra musicians (Steptoe & Fidler, 1987). Barlow (2000) found that early interactions in life play a role in someone propensity to experience anxiety. Furthermore, Kenny (2009) reckons there is a general factor that indicates if an individual is psychologically vulnerable to experience music performance anxiety, as well as a specific vulnerability factor that is provoked by performance situations. Following this thought, some people are more prone to experience music performance anxiety than others. Similar to flow, this begs the question how this trait relates to music performance.
The present study will aim to investigate the relationships among both flow and performance anxiety and music performance, defined as performance satisfaction. First, it is expected that the more likely musicians are to experience flow, the better they will perform (i.e. the more satisfied they will be with their music performance). Second, it is expected that the more likely musicians are to experience music performance anxiety, the worse their performance will be (i.e. the less satisfied they will be with their music performance). Furthermore, due to findings suggesting that the shift in attention between flow and anxiety prevents one from happening simultaneously with the other (Nakamura & Csikszentmihalyi, 2002), dispositional flow and performance anxiety are expected to correlate negatively (i.e. the more propensity to experience flow, the less propensity to experience music performance anxiety).
Methods Participants
To estimate the sample size, a statistical power analysis was run in G-power. Based on an expected medium effect size, α = .05 and power = .95, the projected sample size is N =
184. The actual study sample who provided responses for all relevant measures consisted of N = 89 musicians that participated in various Dutch music group (e.g. Sint Joris Orkest,
Symfonish Orkest Rijnmond). Among the participants, 46.1% identified as men and 53.9% as women. The mean age of the participants was 56.04 years (SD = 17.78). Their mean musical experience was 27.15 years (SD = 16.90), with 15.7% of participants indicating that they followed or had ever followed a musical education and the other 84.3% indicating they had not.
Materials
Dispositional Flow Scale-2. To measure dispositional flow, the Dispositional Flow Scale-2 (DFS-2; Jackson & Ecklund, 2002) was used. The questionnaire measures all nine dimensions described by Csikszentmihalyi (1990). The DFS-2 consists of 36 items that are rated on a 5-point Likert-type scale, ranging from 1 (not at all) to 5 (very much). Example items are “My attention is focused entirely on what I am doing” and “Time seems to alter (either slowing down or speeding up)”. High scores correspond with a higher propensity to experience flow in a certain activity. We translated the original English items to Dutch and adapted them to a musical setting (see Appendix A1). Internal consistency tests on the
subscales showed an acceptable to good structure: skill-challenge balance Cronbach’s α = .77, action awareness α = .86, goals α = .64, feedback α = .77, concentration α = .79, sense of control α = .84, loss of self-consciousness α = .85, time transformation α = .90, and autotelic experience α = .82.
Kenny Music Performance Anxiety Inventory. To measure music performance anxiety, the Kenny Music Performance Anxiety Inventory (K-MPAI; Kenny, Davis, Oates, 2004) was used. The questionnaire measures the biological vulnerability, general
psychological vulnerability, and specific psychological vulnerability for music performance anxiety. The K-MPAI consists of 26 items that are rated on a 6-point scale ranging from -3
(strongly disagree) to +3 (strongly agree). Example items are “I worry that one bad performance will ruin my career” and “My parents were mostly responsive to my needs”. High scores on the K-MPAI correspond with high levels of music performance anxiety. We translated the original English items to Dutch (see Appendix A2). Internal consistency tests on the subscales showed an acceptable to good structure: biological vulnerability Cronbach’s α = .63, general psychological vulnerability α = .83, and specific psychological vulnerability α = .69.
Performance satisfaction. Performance satisfaction was measured via three single items (See Appendix A3). First, to measure general performance satisfaction, participants were asked to rate their performance on a scale from 0 (totally dissatisfied) to 100 (totally satisfied; as used by Pensgaard & Duda, 2003).
Second, to set a reference framework that allows comparing the present performance to similar performances, participants answered “I think my performance was” by choosing one of the following options: much worse than usual, slightly worse than usual, the same as usual, slightly better than usual, much better than usual.
Finally, to get an idea of how participants thought about the amount of mistakes they made during the performance, participants answered “I made” by choosing one of the
following options: a lot more mistakes than usual, slightly more mistakes than usual, the same amount of mistakes as usual, slightly less mistakes than usual, a lot less mistakes than usual. Internal consistency test on these three items showed an extremely low value of Cronbach’s α = .089. Deletion of item 1 substantially improved the internal consistency to α = .72. Hence. all analyses in this study were done with a scale that included only items 2 and 3.
Procedure
Previous to this study, the research design as well as the letter of consent were submitted to the Ethics Committee of the University of Amsterdam. After approval, data
collection started. For participants to be included, they had to have had a music performance. Various heads of orchestras and music schools were contacted via e-mail or by phone and asked if they allowed us to visit an upcoming public performance in order to recruit participants. Once appointments were made, we visited the orchestras on the day of their performance. Musicians were individually approached just before their performance, and were asked to participate. Those who agreed read and signed the letter of informed consent (appendix B) and proceeded with their performance. As soon as possible after their
performance, the participants completed the DFS-2, the K-MPAI, and the satisfaction items. Finally, participants were thanked and those who were interested were reassured they would receive a summary of this study’s most important findings. Participants did not receive a reward for participating.
Results
Means, standard deviations, and correlations for subscales of dispositional flow and performance anxiety, as well as performance satisfaction can be found in Table 1.
First, to test our expectations and investigate to what extent flow and performance anxiety predicted performance satisfaction, we calculated two multiple regression analyses. In order to prepare the data for these analyses, we first checked them for possible outliers. In this context, one score on each of the flow subscales skill-challenge balance and action awareness were removed because these were substantially lower than the -2.96 limit given in Field (2013).
Second, the distribution of the data was examined. Histograms showed that the sample was normally distributed on the following subscales: skill-challenge balance, goals, feedback, concentration, and sense of control, as well as on performance satisfaction. The distribution was slightly negatively skewed for the flow subscales action awareness, loss of
self-consciousness, time transformation, and autotelic experience. The distribution was slightly positively skewed for all subscales of performance anxiety. Most of the distributions showed a normal bell shaped curve. Nonetheless, the flow subscale goals and concentration seemed slightly platykurtic, whereas the flow subscale autotelic experience and the performance satisfaction scale seemed slightly leptokurtic. These violations could be neglected, however, because regression analyses are usually robust (Field, 2013).
Third, the assumption of multicollinearity was checked looking at tolerance values. The subscales of flow showed values between VIF = 1.40 and VIF = 3.47. Performance anxiety’s subscale biological vulnerability showed VIF = 1.35, general vulnerability VIF = 1.82, and specific vulnerability VIF = 1.52. All VIF values are greater than 1, which means results might be slightly biased (Field, 2013) However, all tolerance values lie between 0.2 and 10, which is acceptable (Field, 2013).
After having checked these assumptions, we proceeded with our main analyses. During data processing, missing cases were excluded pairwise to make sure participants were used on all scales they provided data for. The first regression model tested hypothesis 1 and included mean scores on all nine subscales of flow as predictors and mean performance satisfaction as the criterion. Overall, this model did not predict a significant amount of variance in performance satisfaction, R2 = .176, F(9,67) = 1.59, p = .137. However, on a subscale level, skill-challenge balance was found to be a significant predictor of performance satisfaction, see Table 2. Musicians who scored higher on skill-challenge balance reported higher performance satisfaction compared to musicians who reported lower skill-challenge balance. These findings are partly in line with hypothesis 1, because only one aspect of dispositional flow seemed to contribute to predicting performance satisfaction.
Table 1.
The Mean Scores, Standard Deviations, Range, and Correlations for the Subscales of the DFS-2 and the KMPAI.
Correlations Subscale M (SD) n Scale 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 1. Skill-challenge balance 4.01 (.58) 88 1-5 1.00 .54** .68** .62** .52** .65** .35** .28** .56** -.01 -.18 -.27* .05 2. Action-awareness 3.79 (.78) 88 1-5 1.00 .47** .42** .31** .60** .48** .26* .30** -.31** -.17 -.24* -.17 3. Goals 4.16 (.55) 88 1-5 1.00 .78** .49** .62** .31** .23* .53** -.13 -.20 -.31** -.15 4. Feedback 4.13 (.56) 89 1-5 1.00 .38** .65** .24* .11 .39** -.09 -.19 -.28* -.09 5. Concentration 4.24 (.55) 89 1-.5 1.00 .53** .34** .33** .42** -.01 -.20 -.33** -.08 6. Sense of control 3.92 (.69) 88 1-5 1.00 .53** .22** .41** -.15 -.26* -.39** -.17 7. Loss of self-consiousness 3.70 (.92) 88 1-5 1.00 .16 .40** -.08 -.31** -.31** -.07 8. Time transformation 3.83 (.94) 88 1-5 1.00 .46** -.23* -.16 -.05 .15 9. Autotelic experience 4.34 (.51) 88 1-5 1.00 -.01 -.13 -.26* -.00 10. Biological PV -1.14 (1.1) 86 -3–3 1.00 .51** .30** .17 11. General PV -1.44 (.91) 86 -3–3 1.00 .60** .14 12. Specific PV -1.61 (.90) 86 -3–3 1.00 .16 13. Perf. Satisfaction 3.33 (.70) 78 1-5 1.00
Note. PV = DFS-2 subscales: 1-9. KMPAI subscales: 10-12. PV = Psychological Vulnerability.
Likewise, the second regression model tested hypothesis 2. Here, mean scores on all three subscales of performance satisfaction were added as predictors and mean performance satisfaction again was entered as criterion. Overall, this model did not predict a significant amount of variance in performance satisfaction, R2 = .040, F(3,72) = 0.981, p = .406. On a subscale level, too, none of the subscales of performance anxiety were found to be significant predictors of performance satisfaction, see Table 3. This was counter to hypothesis 2 and means that higher scores on music performance anxiety did not correspond with lower scores on performance satisfaction.
Table 2
Summary of Regression Analysis for Flow Variables Predicting Performance Satisfaction (n=78)
Note. S-C Balance = Skill-challenge balance, Loss of S-C = loss of self-consciousness.
Criterion: performance satisfaction.
ß 95% CI [,] S-C Balance .45 [0.11, 0.97] Action Awareness -.24 [-0.49, 0.06] Goals -.30 [-0.91, 0.14] Feedback .16 [-0.30, 0.69] Concentration -.10 [-0.49, 0.24] Control -.25 [-0.64, 0.14] Loss of S-C .11 [-0.13, 0.30] Time transformation .25 [-0.01, 0.38] Autotelic experience -.10 [-0.56, 0.30]
Lastly, Pearson’s correlations were inspected to estimate whether there was a relationship between the subscales of flow and music performance anxiety. As displayed in Table 1, the performance anxiety subscale biological vulnerability correlated negatively with the flow subscales action awareness and time transformation. Additionally, the performance anxiety subscale general psychological vulnerability correlated negatively with the flow subscales sense of control and loss of self-consciousness. Finally, the performance anxiety subscale specific psychological vulnerability correlated negatively with all flow subscales, except for time transformation. These findings support hypothesis 3 as higher dispositional flow related to lower performance anxiety.
Table 3
Summary Regression Analysis for Music Performance Anxiety Variables Predicting Performance Satisfaction (n=78)
Note. PV = psychological vulnerability.
Criterion: performance satisfaction
Discussion
This study aimed to investigate the relationship between both dispositional flow and music performance anxiety and music performance, defined as performance satisfaction.
ß t 95% CI
Biological P V .13 0.96 [-0.09, 0.25]
General P V -.01 0.06 [-0.23, 0.25]
Results indicated that generally neither dispositional flow nor music performance anxiety predicted music performance satisfaction. Nonetheless, on a subscale level a higher predisposition to experience flow in the form of skill-challenge balance predicted greater performance satisfaction. In addition, dispositional flow was negatively related to music performance anxiety.
Firstly, it seems as though there is no relationship between dispositional flow and music performance. The likelihood of experiencing flow did not contribute to performance satisfaction. This finding is in contrast with hypothesis 1, which stated that more disposition to experience flow would positively affect performance satisfaction. The current finding suggests that musicians who are dispositioned to experience flow do not perform better than those who are not dispositioned to experience flow. Additionally, it is not in line with previous findings within flow research. Flow characteristics were previously linked to better performances in a sport domain (Jackson & Roberts, 1992; Jackson, Thomas, March, & Smethurst, 2001). Interestingly, musicians in the current sample all scored relatively high on all flow scales, whereas the sport research showed more variation in the experience of flow. Because the current sample did show little variation in dispositional flow, it could not
accurately predict performance satisfaction (Field, 2013). The high flow scores could perhaps be explained by a heuristic response bias (i.e. they report memories that match their current mood; Fiedler, Nickel, Muehlfriedel, & Unkelbach, 2001). Musicians might be nervous before a performance, and feel happy and relieved once it is over. Because they completed the questionnaire right after their performance, their positive feelings could bias their memory of how they felt during the actual performance. Therefore, they generally could have responded more positively than they would have at a more neutral time and place.
Secondly, it seemed as though there is no relationship between music performance anxiety and performance satisfaction. The likelihood of experiencing musical performance
anxiety did not influence the extent of performance satisfaction. The findings are not in line with hypothesis 2, which stated that music performance anxiety would negatively affect performance satisfaction. The current findings suggest that people who experience music performance anxiety did not perform worse than those wo did not.
This goes against previous discoveries in sports, where anxiety reduced athletic performance (Wilson et al., 2009). However, Wilson et al. (2009) looked at individual performances (i.e. shooting penalties) whereas the current study investigated individual performances within a group performance. As Nicholson et al. (2015) demonstrated, solo performances provoke more severe anxiety compared to group performances. Accordingly, the means on music performance anxiety in this study were surprisingly low, indicating that musicians did not experience music performance anxiety. Additionally, previous research suggested that approximately one third of young music pupils and university students
experiences performance anxiety in such a way that it negatively influences their performance (Fehm & Schmidt, 2006; Wesner et al., 1990).
Again, the overall low scores on music performance anxiety contradict those finding. The absence of performance anxiety could perhaps be explained by the high mean age of our participants, whereas previous mentioned studies focused on younger musicians. Jorm (2000) found the risk of experiencing anxiety to decrease with age, meaning that older people
generally are less prone to suffer from anxiety compared to young people. Furthermore, the visited performances were possibly not comparable to the performances used in other studies. For example, one of our performances was at a senior orchestra festival, where the social aspects of the event seemed to be the focus instead of the performance itself.
Lastly, flow negatively correlated with music performance anxiety. This is in line with hypothesis 3. Musicians with low biological vulnerability seemed to experience more action awareness and time transformation aspects of flow compared to those with high biological
vulnerability. Furthermore, musician with lower general psychological vulnerability for anxiety experienced more sense of control and loss of self-consciousness compared to those with high general psychological vulnerability. Lastly, musicians with high specific
psychological vulnerability for performance anxiety did not significantly experience less time transformation compared to those with low specific psychological vulnerability, but did experience all other dimensions of flow to a lesser extent than those that do not have a specific psychological vulnerability. These are in line with findings by Kirchner (2008), who demonstrated a connection between flow and anxiety in music students. Whether this
connection is due to the shift in attention, as proposed by Nakamura and Csikszentmihalyi (2002). has to be studied in more detail.
Despite not finding all expected relationships, this study did give some interesting insights. As this is one of the first studies that looked at dispositional flow and anxiety in this specific music context (i.e. recreational orchestras), it creates a basis for future research to build upon. Furthermore, it seems as though flow and music performance anxiety as traits do not necessarily relate to music performance. Maybe situational factors that enable a flow state and music performance anxiety to happen are more relevant than predisposition in predicting performance. Also, experienced flow in musicians in recreational orchestras is relatively high. Conversely, there is little to no music performance anxiety present before performing.
A positive relationship between flow and performance would inform musicians that possess the flow trait to focus on flow-fostering environments in order to deliver their best performance. Furthermore, a negative relationship music performance anxiety and better performances would inform musicians with a propensity to experience anxiety that working on their anxiety would actually lead to better performances. However, the current findings indicate that traits are not that relevant in predicting performance. Instead, care should be taken to set up situations in which flow could foster and performance anxiety could be
reduced, independently of predisposition, e.g. environments where they receive direct feedback on progress (Nakamura & Csikszentmihalyi, 2009) or starting with group performances before diving into performing solo (Nicholson et al., 2015).
This study did have a few limitations, the main one being the size and characteristics of the study sample. According to a power analysis in G-power, a projected sample size of N = 184 was needed. Because the actual number of participants was substantially lower (N=89), there is a possibility that existing effects were not detected. In addition, our sample consisted of recreational musicians, which explains the generally high flow scores and low music performance anxiety scores. This limited amount of variance could have prevented existing relationships from appearing (i.e. if there is no variability, it cannot predict anything). In future research, enough time should be scheduled to recruit more participants and care should be taken in selecting various sorts of musicians (i.e. not only recreational but professionals too).
Secondly, the questionnaire took long to complete because it was part of a bigger investigation. The KMPAI was put at the very end, and people did not seem well-focused on answering questions truthfully once they got to this part. This was noticeable in their
responses (i.e. giving the same option for each question, even when response-options were reversed) and their behavior (e.g. sighing and complaining about the length). Future research should create a shorter questionnaire with just the measurements of flow, music performance anxiety, and performance satisfaction.
Thirdly, the choice to look at flow as a trait could be discussed. Trait-flow was chosen because of the impractically to measure flow experience during the performance itself.
However, having participants fill in flow questions afterwards could bias their answers. As mentioned before, musicians could have used heuristics when completing the questionnaire and responded more positively than they actually felt during the performance. Furthermore,
looking at flow as a trait indicates looking at flow in all aspects of life. However, musicians who just performed are likely to place themselves in a music or performance context and do not think about other domains of life (e.g. work, art, hobbies). Therefore, their answers might not represent their everyday flow experiences. Future research could use the Experience Sampling Method (Larson & Csikzentmihalyi, 1978) where participants are stopped at random times and asked to describe their experience of flow in that moment. This results in a general idea of flow instead of flow in the music performance setting.
To conclude, this study is one of the first to investigate flow, perfomance anxiety, and performance in a recreational music context. Musicians that are dispositioned to experience flow and music performance anxiety, do not differ in their performance satisfaction. However, experiencing a balance between challenge and personal skill does seem to positively affect performance satisfaction. Teachers and conductors should play a part in fostering this balance in their musicians. Furthermore, musicians themselves should focus on placing themselves in environments that are challenging, but appropriate to their personal skills.
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Appendix A
Dutch Versions of Questionnaires
A1. Nederlandse versie van de Dispositional Flow Questionnaire (DFS-2)
Beantwoord alstublieft de volgende stellingen met betrekking tot uw ervaring met muziek. Deze stellingen hebben betrekking op de gedachten en gevoelens die u kunt ervaren tijdens het musiceren. U kunt de onderstaande kenmerken soms, altijd of nooit ervaren. Er zijn geen goede of foute antwoorden. Denk na over hoe vaak u ieder kenmerk heeft ervaren tijdens het musiceren en omcirkel het nummer dat het beste past bij uw ervaring.
Helemaal mee oneens 1 Mee oneens 2 Niet eens, niet oneens 3 Mee eens 4 Helemaal mee eens 5 1.
Wanneer ik deelneem aan een muzikaal optreden...
...voel ik me uitgedaagd, maar geloof ik dat mijn vaardigheden mij in staat stellen de uitdaging aan te gaan.
1 2 3 4 5
2. ...voer ik de juiste handelingen uit zonder na te denken over hoe dit moet.
1 2 3 4 5
3. ...weet ik precies wat ik wil doen.
1 2 3 4 5
4. ... is het voor mij duidelijk hoe het met mijn prestatie gesteld staat.
1 2 3 4 5
1 2 3 4 5 6. ...heb ik een gevoel van controle over wat ik doe.
1 2 3 4 5
7. .... ben ik niet bezorgd over wat anderen over mij denken.
1 2 3 4 5
8. ...lijkt de tijd te veranderen (of te vertragen of te versnellen).
1 2 3 4 5
9. ...geniet ik met volle teugen van de ervaring.
1 2 3 4 5
10. ...komen mijn vaardigheden overeen met de grote uitdaging van het musiceren.
1 2 3 4 5
11. ...lijken de handelingen automatisch te gebeuren.
1 2 3 4 5
12. ...ben ik sterk bewustzijn van wat ik doe.
1 2 3 4 5
13. ...ben ik me bewust van hoe goed ik presteer.
1 2 3 4 5
14. ...kost het mij geen moeite om mijn gedachten bij het musiceren te houden.
1 2 3 4 5
15. ...voel ik mij in controle over wat ik doe.
1 2 3 4 5
1 2 3 4 5 17. ...lijkt de manier waarop de tijd verstrijkt anders dan normaal.
1 2 3 4 5
18. ...hou ik van het gevoel van musiceren en wil het opnieuw ervaren.
1 2 3 4 5
s 19. ... voel ik me bekwaam genoeg om aan de hoge eisen van het musiceren te voldoen.
1 2 3 4 5
20. ... presteer ik automatisch zonder hier teveel over na te denken.
1 2 3 4 5
21. ...weet ik wat ik wil bereiken.
1 2 3 4 5
22. ... heb ik een goed beeld over hoe ik presteer terwijl ik musiceer.
1 2 3 4 5
23. ...ben ik volledig geconcentreerd.
1 2 3 4 5
24. ...heb ik een gevoel van totale controle.
1 2 3 4 5
25. ...ben ik niet bezig met hoe ik mezelf presenteer.
1 2 3 4 5
26. ...lijkt de tijd snel voorbij te gaan.
1 2 3 4 5
1 2 3 4 5 28. ...de uitdaging en mijn vaardigheden bevinden zich op hetzelfde niveau.
1 2 3 4 5
29. ...doe ik dingen spontaan en automatisch, zonder erover na te hoeven te denken.
1 2 3 4 5
30. ...zijn mijn doelen duidelijk gedefinieerd.
1 2 3 4 5
31. ...kan ik door de manier waarop ik musiceer vaststellen hoe goed ik het doe.
1 2 3 4 5
32. ...ben ik volledig gefocust op de desbetreffende taak.
1 2 3 4 5
33. ...voel ik totale controle over mijn lichaam.
1 2 3 4 5
34. ...ben ik niet bezorgd over wat anderen van mij denken.
1 2 3 4 5
35. ...verlies ik mijn normale tijdsbesef.
1 2 3 4 5
36. ...is de ervaring erg bevredigend.
1 2 3 4 5
Hieronder vindt u enkele uitspraken over hoe u zich over het algemeen voelt en hoe u zich voelt voor of tijdens een optreden. Omcirkel één nummer om aan te geven in hoeverre u het eens of oneens bent met iedere stelling.
Helemaal mee oneens -3 Mee oneens -2 Een beetje mee oneens -1 Niet eens, niet oneens 0 Een beetje mee eens 1 Mee eens 2 Helemaal mee eens 3
1. Ik voel me soms terneergeslagen zonder dat ik weet waarom.
-3 -2 -1 0 1 2 3
2. Ik vind het gemakkelijk om anderen te vertrouwen.
-3 -2 -1 0 1 2 3
3. Ik heb zelden het gevoel in controle te zijn over mijn leven.
-3 -2 -1 0 1 2 3
4. Ik heb er vaak moeite mee mezelf ertoe te zetten om dingen te doen.
-3 -2 -1 0 1 2 3
5. Overmatig zorgen maken is een karaktereigenschap die voorkomt in mijn familie.
-3 -2 -1 0 1 2 3
6. Ik heb vaak het gevoel dat het leven mij niet veel te bieden heeft.
-3 -2 -1 0 1 2 3
7.
Hoe harder ik werk ter voorbereiding van een optreden, hoe groter de kans dat ik een ernstige fout maak.
-3 -2 -1 0 1 2 3
8. Ik vind het moeilijk van anderen afhankelijk te zijn.
-3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3 10. Voorafgaand aan een optreden weet ik nooit of ik goed zal gaan presteren.
-3 -2 -1 0 1 2 3
11. Ik heb vaak het gevoel dat ik als persoon niet veel waard ben.
-3 -2 -1 0 1 2 3
12. Tijdens een optreden twijfel ik of ik het optreden wel goed doorkom.
-3 -2 -1 0 1 2 3
13. Nadenken over een mogelijk evaluatie heeft invloed op mijn optreden.
-3 -2 -1 0 1 2 3
14. Zelfs in de meest stressvolle optredens, ben ik er zeker van dat ik goed zal presteren.
-3 -2 -1 0 1 2 3
15. Ik maak me zorgen over een negatieve reactie van het publiek.
-3 -2 -1 0 1 2 3
16. Ik voel me soms angstig zonder dat daar een specifieke reden voor is.
-3 -2 -1 0 1 2 3
17. Vanaf het begin van mijn muzikale opleiding, ben ik al angstig om op te treden.
-3 -2 -1 0 1 2 3
18. Ik maak me zorgen dat één slecht optreden mijn carrière zal verpesten.
-3 -2 -1 0 1 2 3
19. Mijn ouders luisterden bijna altijd naar mij.
-3 -2 -1 0 1 2 3
20. Optredens die de moeite waard zijn laat ik lopen doordat ik angstig ben.
-3 -2 -1 0 1 2 3
-3 -2 -1 0 1 2 3
22.
Tijdens het voorbereiden van een optreden, doe ik dit vaak met tegenzin en het gevoel dat het optreden waarschijnlijk mis zal gaan.
-3 -2 -1 0 1 2 3
23. Ik heb vaak het gevoel dat ik niets heb om naar uit te kijken.
-3 -2 -1 0 1 2 3
24. Mijn ouders hebben mij altijd aangemoedigd nieuwe dingen te proberen.
-3 -2 -1 0 1 2 3
25. Ik maak me voor een optreden zoveel zorgen, dat ik er niet van kan slapen.
-3 -2 -1 0 1 2 3
26. Mijn geheugen is meestal zeer betrouwbaar.
-3 -2 -1 0 1 2 3
A3. Tevredenheid na het muziekoptreden
Beantwoord alstublieft de volgende vragen en stellingen met betrekking de tevredenheid die u voelt over het optreden dat u zojuist heeft gegeven. Er zijn geen goede of foute antwoorden. Denk goed na over de vragen en omcirkel het nummer dat het best past bij uw ervaring.
1. Hoe tevreden bent u over het optreden van vandaag?
Zet een kruisje op de lijn hieronder tussen 0 (helemaal niet tevreden) en 100 (ontzettend tevreden)
0 100
2. Ik vind mijn muziekprestatie …
1. Veel slechter dan dat ik gemiddeld presteer op deze muziekprestatie, 2. Iets slechter dan hoe ik gemiddeld presteer op deze muziek prestatie, 3. Hetzelfde als hoe ik gemiddeld presteer op deze muziekprestatie,
4. Iets beter dan hoe ik gemiddeld presteer op deze muziekprestatie, 5. Veel beter dan hoe ik gemiddeld presteer op deze muziekprestatie.
3. Ik maakte …
1. Veel meer fouten dan dat ik gemiddeld maak bij deze muziekprestatie 2. Iets meer fouten dan dat ik gemiddeld maak bij deze muziekprestatie
3. Hetzelfde aantal fouten dan dat ik gemiddeld maak bij deze muziekprestatie 4. Iets minder fouten dan dat ik gemiddeld maak bij deze muziekprestatie 5. Veel minder fouten dan dat ik gemiddeld maak bij deze muziekprestatie
Appendix B
Letter of Informed Consent
INFORMATIE BROCHURE VOOR DEELNEMERS
EMOTIE, WELZIJN EN PRESTATIE BIJ MUZIEKGROEPEN Hoofdonderzoeker: Dr. Svenja A. Wolf (S.A.Wolf2@uva.nl)
Bachelor Studenten: Adine Teillers, Janine Cornelissen, Irene van Amersfoort, Noor Wielaart, Terence Watson
Beste deelnemer,
Voordat het onderzoek begint, is het belangrijk dat u op de hoogte bent van de procedure die in dit onderzoek wordt gevolgd. Lees daarom onderstaande tekst zorgvuldig door en aarzel niet om opheldering te vragen over deze tekst, mocht deze niet duidelijk zijn. De
onderzoeksleider zal eventuele vragen graag beantwoorden.
DOEL VAN HET ONDERZOEK
Het doel van het onderzoek is te onderzoeken hoe de emoties, welzijn en prestatie van muzikanten in muziekgroepen zijn.
GANG VAN ZAKEN TIJDENS HET ONDERZOEK
Het onderzoek bestaat uit meerdere vragenlijsten die we je vragen in te vullen. Als eerste zal er een vragenlijst komen die maximaal 15 minuten kost om in te vullen. Aan het begin van de
uitvoering zal een vragenlijst aangeboden worden die maximaal 5 minuten kost om in te vullen. Na de uitvoering zal dan nog een laatste vragenlijst komen. Deze vragenlijst kost maximaal 10 minuten om in te vullen. In de vragenlijsten zullen we u vragen naar wat algemene informatie over uzelf en uw achtergrond in muziek en er zal worden vastgesteld welke emoties u ervaart, wat uw staat van welzijn is, en uw tevredenheid met de prestatie in muziek is.
VERTROUWELIJKHEID VAN GEGEVENS
Alle onderzoeksgegevens blijven volstrekt vertrouwelijk en worden anoniem verwerkt. De onderzoeksgegevens worden niet ter beschikking gesteld aan derden zonder uw uitdrukkelijke toestemming en alleen in anonieme gecodeerde vorm. De sleutel voor deze gegevens is in het bezit van de onderzoekers en zal niet uit handen worden gegeven.
VRIJWILLIGHEID
Als u nu besluit af te zien van deelname aan dit experiment, zal dit op geen enkele wijze gevolgen voor u hebben. Als u tijdens het onderzoek zelf besluit uw medewerking te staken, zal dat eveneens op geen enkele wijze gevolg voor u hebben. Tevens kunt u 24 uur na dit onderzoek alsnog uw toestemming om gebruik te maken van uw gegevens intrekken. U kunt ervoor kiezen alle gegevens in te trekken, een bepaalde vragenlijst, of een specifieke vraag. U kunt uw medewerking dus te allen tijde staken zonder opgave van redenen. Mocht u uw medewerking staken, of achteraf, zij het binnen 24 uur, uw toestemming intrekken, dan zullen uw gegevens worden verwijderd uit onze bestanden en vernietigd.
Omdat dit onderzoek geen risico’s voor uw gezondheid of veiligheid met zich meebrengt, gelden de voorwaarden van de reguliere aansprakelijkheidsverzekering van de UvA.
NADERE INLICHTINGEN
Mocht u vragen hebben over dit onderzoek, vooraf of achteraf, dan kunt u zich wenden tot de verantwoordelijke onderzoeker, Dr. Svenja A. Wolf, tel.: 020-5256890, email:
S.A.Wolf2@uva.nl, adres: Nieuwe Achtergracht 129 B, 1018 WT Amsterdam, kamer: G2.33. Voor eventuele klachten over dit onderzoek kunt u zich wenden tot het lid van de Commissie Ethiek, Dr. M. Rotteveel, tel.: 020-5256713, email: m.rotteveel@uva.nl, adres: Achtergracht 129 B, 1018 WT Amsterdam. Dit project staat geregistreerd onder nummer 2017-COP-7882.
TOESTEMMINGSVERKLARING
Dit formulier hoort bij de schriftelijke informatie die u heeft ontvangen over het onderzoek waar u aan deelneemt. Met ondertekening van dit formulier verklaart u dat u de
deelnemersinformatie heeft gelezen en begrepen. Verder geeft u met de ondertekening te kennen dat u akkoord gaat met de gang van zaken zoals deze staat beschreven in deze brief. Als u nog verdere informatie over het onderzoek zou willen krijgen kunt u zich wenden tot de verantwoordelijke onderzoeker, Dr. Svenja A. Wolf, tel.: 020-5256890, email:
S.A.Wolf2@uva.nl, adres: Nieuwe Achtergracht 129 B, 1018 WT Amsterdam, kamer: G2.33. Voor eventuele klachten over dit onderzoek kunt u zich wenden tot het lid van de Commissie Ethiek, Dr. M. Rotteveel, tel.: 020-5256713, email: m.rotteveel@uva.nl, adres: Achtergracht 129 B, 1018 WT Amsterdam.
[DEELNEMER]
onderzoek en gebruik van de daarmee verkregen gegevens. Ik behoud daarbij het recht om zonder opgaaf van reden deze instemming weer in te trekken. Tevens behoud ik het recht op ieder door mij gewenst moment te stoppen met het experiment.”
Aldus in tweevoud getekend: Datum:
………... ………
naam proefpersoon handtekening
[ONDERZOEKER]
“Ik heb toelichting verstrekt op het onderzoek. Ik verklaar mij bereid nog opkomende vragen over het onderzoek naar vermogen te beantwoorden.”
Reflectieverslag
Noor Wielaart (10534165) University of Amsterdam Supervisor: Dr. Svenja A. Wolf Submission date: June 2nd, 2017
In dit verslag zal ik terugblikken op het bachelorproject ‘Happy Together?! Emotions and group dynamics in muical performance groups’. Ik zal ingaan op de verwerking van feedback die verkregen is gedurende het project, de positieve en negatieve aspecten van het proces, de sterke en minder sterke kanten van het uiteindelijke onderzoeksverslag en ten slotte hoe we zijn omgegaan met ethische aspecten van wetenschappelijk onderzoek. Hiermee hoop ik inzicht te geven in het verloop van het bachelorproject
Feedback verwerking. Allereerst wil ik benadrukken dat ik de manier van feedback krijgen enorm heb gewaardeerd. We kregen over het algemeen binnen korte tijd onze feedback en Svenja was altijd in staat om extra vragen te beantwoorden. Wat betreft de feedback zelf zal ik kort ingaan op de belangrijkste punten. Een belangrijk feedback punt op de eerste versie van de inleiding was het beargumenteren waarom ik gekozen heb voor flow en muzikale prestatie angst. Dit vond ik lastig, omdat ik vooral uit interesse gekozen heb voor deze
constructen en niet op basis van een theorie waar vanuit ik de keuze kon beargumenteren. Een tip was om eerst algemeen in te gaan op mogelijke voorspellers voor prestatie, en vervolgens in te zoomen op de emotionele/psychologische staten ‘flow’ en ‘muzikale prestatieangst’. Ik ben op zoek gegaan naar artikelen over voorspellers van prestatie, en vervolgens op het effect van affectieve staten op prestatie. Ik heb geprobeerd dit te linken aan flow (wat ook een affectief component bevat). Op basis van later gevonden artikelen heb ik muzikale
deze manier redelijk aan elkaar gekoppeld heb. Andere belangrijke feedback voor de inleiding ging over de volgorde waarin ik mijn alinea’s presenteerde. Toen ik het teruglas, vond ik mijn structuur inderdaad een rotzooitje. Ik heb allereerst de stukken voor flow en muzikale
prestatieangst op dezelfde manier behandeld: definitie, prevalentie in de gekozen context, waarom er een effect verwacht wordt, etc. Ik hoop op deze manier meer structuur te hebben aangebracht in dit deel van mijn verslag. Op het resultaten stuk kregen we allen tegelijk mondelinge feedback. Dit vond ik fijn, want op deze manier kon je naast je eigen feedback, ook leren van de feedback voor anderen uit je groepje. Belangrijke punten hier waren het indelen van de tabellen en in mijn geval focussen op betrouwbaarheidsintervallen in plaats van p-waarden. Daarnaast kwamen er nog algemene kleine puntjes aan bod (bijv. percentages noemen bij man/vrouw verdeling ipv. aantal) die ik allemaal goed heb kunnen verwerken. De laatste feedback ronde was ontzettend fijn, hier heb ik erg veel aan gehad. Sommige puntjes vond ik wat lastiger aan te passen, omdat ze voor mijn gevoel tegen eerdere feedback
ingingen (bijv. de vertaling van de tevredenheidsitems en het introduceren van flow). Hier heb ik vervolgens goed over nagedacht, en geprobeerd er mee te doen wat mij het best leek voor m’n scriptie.
Goede en minder goede kanten van het project. Ik ben over het algemeen zeer tevreden met het verloop van het project. In eerste instantie was ik enigszins teleurgesteld dat ik niet was ingedeeld bij mijn nummer 1 of 2 keuze wat betreft onderwerpen, maar uiteindelijk was ik toch erg blij met het onderwerp ‘Happy Together’. Hoe meer ik me in las in het onderwerp, hoe enthousiaster ik werd. Ik kijk zeer positief terug op de samenwerking tijdens het project, zowel de samenwerking onderling in ons groepje als de samenwerking met Svenja. Wat betreft Svenja: ik had het gevoel alles te kunnen/durven vragen, we kregen snel antwoord op mailtjes en ik vond dat ze heel betrokken was bij al onze individuele onderzoeksvragen. Wat
betreft het groepje: er werd goed samengewerkt bij het vinden van deelnemers en we hebben elkaar geholpen waar nodig gedurende het proces. Wat echter wat minder goed liep was het werven van deelnemers. Het was lastig om in het beperkt aantal weken die we ervoor hadden orkesten te vinden die én wilden meedoen, én een optreden gepland hadden staan in die tijd. Hierdoor hebben we uiteindelijk minder deelnemers dan we nodig hadden om effecten te detecteren. Ondanks dat we hard ons best hebben gedaan en het niet persé onze schuld is, is het wel jammer. Hierdoor voelde het onderzoek af en toe ietwat nutteloos. Gelukkig bleef Svenja erg positief; ze vond dat we het goed gedaan hadden gezien de tijd die we hadden en benadrukten dat onze onderzoeken desondanks zeer informatief kunnen zijn. Dit nam mijn zorgen deels weg.
Sterke en minder sterke punten verslag. Ik vind het lastig om aan te geven wat sterke en minder sterke kanten van mijn verslag zijn. Ik ben van mening dat mijn inleiding niet super goed theoretisch onderbouwd is. Vooral door, zoals eerder aangegeven, het beargumenteren waarom gekozen is voor flow en muzikale prestatieangst. Ik zou in het vervolg (bijv. bij mijn masterthese) eerst onderzoeken welke overkoepelende theorieën er bestaan binnen het
onderwerp, en daar vanuit kiezen waar ik onderzoek naar wil doen. Op deze manier kan ik mijn onderzoek hoogstwaarschijnlijk wetenschappelijker onderbouwen. Waar ik tevreden over is het resultaten stuk. Van te voren zag ik op tegen het statistische deel omdat ik hier geen ster in ben. Uiteindelijk denk ik dat het goed gelukt is en dat ik ook redelijk goed begrijp wat we precies gedaan hebben en wat de gevonden resultaten betekenen. Wat betreft het beschrijven van de resultaten heb ik goed gekeken naar hoe andere artikelen dit doen en wat er precies gerapporteerd moet worden. Ondanks dat er naar aanleiding van de laatste feedback ronde nog wel wat aanpassingen aan mijn resultaten zijn gedaan, ben ik van mening dat ik een goed stuk heb kunnen schrijven voor een bachelorthese. Verder ben ik tevreden over de
discussie. Ik vond dat ik een duidelijke structuur had, waarbij ik per hypothese heb beschreven wat de gevonden resultaten betekenen en hoe deze bevindingen mogelijk verklaard kunnen worden. Ik heb naar aanleiding van feedback wat extra koppelingen naar eerder onderzoek moeten toevoegen, waardoor ik van mening ben dat mijn uiteindelijke discussie best goed gelukt is. Ten slotte ben ik op de grote tabel in mijn verslag. Dit is
natuurlijk een minder belangrijk detail dan de inhoudelijke stukken, maar ik vond het een hele klus om de tabel op 1 pagina te krijgen en het overzichtelijk te houden en ben hier lang mee bezig geweest.
Ethische aspecten onderzoek. Ons onderzoek was niet dermate fysiek of psychologisch gevaarlijk dat er twijfel bestond of het zou mogen worden uitgevoerd wat betreft ethiek. We hebben hier dan ook niet te lang bij stil gestaan. Wel hebben we nagedacht over hoe we deelnemers konden anonimiseren. Voor een aantal van ons groepje was het van belang om op meerdere momenten metingen af te nemen bij dezelfde proefpersonen. Het was de bedoeling dat we achteraf de verschillende ingevulde vragenlijsten van dezelfde persoon aan elkaar konden matchen. Hiervoor moesten we een codering bedenken om vragenlijsten aan elkaar te matchen zonder dat we de naam van de proefpersonen hoefden te weten. De code moest zodanig worden samengesteld dat proefpersonen deze makkelijk een tweede keer in konden vullen. Daarnaast moest de code uniek zijn, zodat we niet twee proefpersonen met dezelfde code zouden hebben. We hebben toen gekozen voor het volgende: code = het aantal zussen dat je hebt – het aantal broers dat je hebt – de maand van je eigen verjaardag – de eerste letter van je moeders voornaam (bv. 1-1-02-P). Op deze manier hoopten we zodanige variatie in codes te creëren dat de codes uniek waren voor de persoon, maar door de persoonlijke onderdelen maakten we het voor de proefpersoon makkelijk dezelfde code in te vullen op de tweede meting. Achteraf ontdekte ik dat, ondanks dat we iedereen verzekerde dat het
onderzoek anoniem zou zijn, er op de letter of consent wel een naam werd gevraagd. Wanneer hier ophef over ontstond tijdens het invullen, hebben we uitgelegd dat een naam niet nodig was, maar dat een datum en handtekening volstonden.
