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Exploring the intersection of occupational engagement and well-being in student musicians: A multi-method study

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Exploring the intersection of occupational engagement and well-being in student musicians: A multi-method study

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Content Exploring the intersection of occupational engagement and well-being in student musicians: A
multi-method study
by
Yoko Ellie Fukumura
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfilment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(OCCUPATIONAL SCIENCE)
December 2024
Copyright 2024 Yoko Ellie Fukumura

ii
ACKNOWLEDGEMENTS
I would like to express my deepest gratitude to my mentor, Dr. Shawn C. Roll, for the
exceptional guidance and support throughout this process. Thank you for believing in me from
my early days in the lab and giving me the space to grow.
To my dissertation committee members, Dr. Aviva Wolff, Dr. Beth Pyatak, and Dr. John Sideris,
thank you for your valuable feedback and ongoing support. Your expertise and insight were
invaluable to the completion of this dissertation.
Thank you to the current and past members of the Musculoskeletal Sonography and
Occupational Performance Lab for your support and encouragement. To the students I had the
pleasure of working with, thank you for all your hard work and support. It was an absolute joy
working together and I could not have done this without you.
And finally, to my friends, family, and my cat Miku, thank you for your unwavering love and
encouragement.

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TABLE OF CONTENTS
ACKNOWLEDGEMENTS............................................................................................................ ii
LIST OF TABLES......................................................................................................................... vi
LIST OF FIGURES ...................................................................................................................... vii
ABBREVIATIONS ..................................................................................................................... viii
ABSTRACT................................................................................................................................... ix
CHAPTER 1 General Introduction................................................................................................. 1
1.1 Musician Health & Well-being ............................................................................................. 1
1.1.1 Injury and Intervention ................................................................................................... 1
1.1.2 Challenges and Complexities of Musician Well-being .................................................. 3
1.2 Occupational Identity of a Musician ..................................................................................... 5
1.2.1 Musician as an Athlete ................................................................................................... 6
1.2.2 Musician as a Worker..................................................................................................... 8
1.2.3 Musician as a Performing Artist................................................................................... 11
1.3 Musician Health and Well-Being Frameworks................................................................... 12
1.3.1 Critical Considerations Based on Occupational Identities ........................................... 12
1.3.2 Ecology of Musical Performance (EMP) Model.......................................................... 14
1.4 Dissertation Overview......................................................................................................... 16
1.5 References........................................................................................................................... 19
CHAPTER 2 Mapping Review of Musician Well-being Literature............................................. 26
2.1 Introduction. ........................................................................................................................ 26
2.2 Methods............................................................................................................................... 28
2.2.1 Study Design................................................................................................................. 28
2.2.2 Article Review Process................................................................................................. 29
2.2.3 Data Extraction and Analysis....................................................................................... 33
2.3 Results................................................................................................................................. 34
2.3.1 Search Results............................................................................................................... 34
2.3.2 Descriptive characteristics............................................................................................ 36
2.3.3 Well-being constructs................................................................................................... 39
2.4 Discussion ........................................................................................................................... 43

iv
2.5 Conclusion........................................................................................................................... 47
2.6 References........................................................................................................................... 48
CHAPTER 3 National Musician Well-being Survey ................................................................... 54
3.1 Introduction ......................................................................................................................... 54
3.2 Methods............................................................................................................................... 56
3.2.1 Study Design................................................................................................................. 56
3.2.2 Subjects and Recruitment ............................................................................................. 56
3.2.3 Survey Components...................................................................................................... 57
3.2.4 Data Management & Analysis...................................................................................... 60
3.3 Results................................................................................................................................. 62
3.3.1 Sample Description....................................................................................................... 62
3.3.2 Distribution of Well-being Contributors and Outcomes .............................................. 66
3.3.3 Multiple Linear Regression Analysis........................................................................... 74
3.4 Discussion ........................................................................................................................... 76
3.5 Conclusion........................................................................................................................... 79
3.6 References........................................................................................................................... 81
CHAPTER 4 Intersection of Daily Activity Patterns and Well-being in Music Students ........... 84
4.1 Introduction ......................................................................................................................... 84
4.2 Methods............................................................................................................................... 86
4.2.1 Study Design Overview................................................................................................ 86
4.2.2 Subjects and Recruitment ............................................................................................. 87
4.2.3 Modified Day Reconstruction Method ......................................................................... 88
4.2.4 Semi-structured Interviews........................................................................................... 90
4.2.5 Investigator Positionality.............................................................................................. 91
4.3 Results................................................................................................................................. 92
4.3.1 Sample Description....................................................................................................... 92
4.3.2 DRM Results ................................................................................................................ 93
4.3.3 Interview Results........................................................................................................ 100
4.4 Discussion ......................................................................................................................... 103
4.5 Conclusion......................................................................................................................... 106
4.6 References......................................................................................................................... 108
CHAPTER 5 Discussion and Synthesis...................................................................................... 111

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5.1 Summary of Key Findings ................................................................................................ 111
5.1.1 Conclusions from Chapter 2: Mapping Review ......................................................... 111
5.1.2 Conclusions from Chapter 3: National Survey........................................................... 112
5.1.3 Conclusions from Chapter 4: Intersection of Daily Activity and Well-being............ 113
5.2 Synthesis of Knowledge Gained ....................................................................................... 114
5.2.1 Advancing understanding of the EMP Model ............................................................ 114
5.2.2 Emerging Themes on Intersection of Occupational Identities and Well-being in
Musicians............................................................................................................................. 115
5.3 Future Directions for Musician Well-being and Occupational Science Research ............ 119
5.3.1 Future directions for further development of the EMP model ................................... 119
5.3.2 Next steps for musician well-being research.............................................................. 122
5.3.3 Opportunities for Occupational Science (OS)............................................................ 123
5.4 References......................................................................................................................... 125
BIBLIOGRAPHY....................................................................................................................... 127
APPENDIX A National Well-being Survey............................................................................... 141
APPENDIX B Multiple Imputation Analysis............................................................................. 171
B.1 Methods............................................................................................................................ 172
B.2 Limitations........................................................................................................................ 177
B.3 References ........................................................................................................................ 180
APPENDIX C Modified Daily Reconstruction Method............................................................. 181
APPENDIX D List of all Reported Activities and Occupational Therapy Practice Framework
(OTPF) Categorization................................................................................................................ 188

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LIST OF TABLES
Table 2.1 Search terms.................................................................................................................. 30
Table 2.2 Frequency and percentage of articles, sorted within variable by frequency................. 38
Table 3.1. Survey construction ..................................................................................................... 59
Table 3.2 Distribution and comparison of incomplete and complete respondent demographics,
descriptive factors, and general health outcome variables............................................................ 65
Table 3.3. Well-being contributor satisfaction, importance, and quality/ability responses.......... 68
Table 3.4. Distribution of well-being outcome variables. ............................................................ 70
Table 3.5. Parameter estimates and significance of regression models with three well-being
outcome variables. ........................................................................................................................ 75
Table 4.1. Intended sample demographics.................................................................................... 88
Table 4.2. Sample demographics.................................................................................................. 92
Table 4.3. Within individual correlation of hedonic and eudemonic well-being. ........................ 94
Table B.1. Distribution of physical and mental health ratings between complete and
incomplete survey responses....................................................................................................... 174
Table B.2. Survey item description............................................................................................. 176
Table D.1. Reported activities and OTPF categorization. .......................................................... 189

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LIST OF FIGURES
Figure 1.1. Ecology of Musical Performance (EMP) Model reproduced with permission
(Bastepe-Gray et al., 2021)........................................................................................................... 16
Figure 2.1 Review process adapted from Focused Mapping Review and Synthesis (FMRS)
Approach (Bradbury-Jones et al., 2019)....................................................................................... 29
Figure 2.2. Flow diagram of study review and inclusion process. ............................................... 35
Figure 2.3 Histogram of publication years of included articles.................................................... 37
Figure 2.4. Frequency of included articles covering EMP constructs and subcomponents ......... 41
Figure 2.5 Nested bar chart of distribution of articles by study design across EMP model
constructs and study population.................................................................................................... 42
Figure 3.1 Survey drop-off flowchart ........................................................................................... 64
Figure 3.2. Distribution of PERMA well-being sub scores (n=124). ........................................... 73
Figure 4.1. Number of activities reported each day by 8 participants. ......................................... 94
Figure 4.2. Boxplot of hedonic and eudemonic well-being distribution across OTPF activity
categories. ..................................................................................................................................... 96
Figure 4.3. Activity pattern visuals mapping out OTPF activity categories on hedonic and
eudemonic scales by participant. ................................................................................................ 100
Figure B.1. Survey attrition number by content section. ............................................................ 173
Figure B.2. Distribution of quality and satisfaction ratings of physical and mental health........ 175

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ABBREVIATIONS
DRM Day Reconstruction Method
EMP Ecology of Musical Performance
FMRS Focused Mapping Review and Synthesis
MIRC Musician-Instrument-Repertoire Complex
OS Occupational Science
OTPF Occupational Therapy Practice Framework
PERMA Positive Emotion, Engagement, Relationships,
Meaning, and Accomplishment
PI Principal Investigator
PRMD Playing-related Musculoskeletal Disorder

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ABSTRACT
Since its inception, occupational science has theorized the role of occupational
engagement in health and well-being outcomes. While different schools of thought have
emerged, engaging in meaningful occupations that contribute to one’s identity is generally seen
as beneficial. Much of the existing literature on the intersection of occupation and health has
focused on instances where obstacles exist to engagement in important occupations (e.g., health
conditions or environmental constraints), demonstrating the importance of supporting
engagement to facilitate health and well-being. Given this knowledge, one may assume that an
occupational group such as musicians who engage in a creative and fulfilling occupation would
experience abundant health and wellness. However, on the contrary, musicians are at risk for
many health impairments that are directly associated with their career occupation. A plethora of
occupation-related health impairments have been identified within musicians, including playingrelated musculoskeletal disorders (PRMD), performance anxiety, and hearing loss, among others.
While extensive literature exists on the biomechanics of PRMD development or the high
prevalence and impacts of performance anxiety, there has been limited focus on interventions to
support musician well-being. Overall, despite many wide-scale initiatives to support musician
health, occupation-related health impairments remain highly prevalent in musicians.
One component currently missing in the literature is an understanding of musicians as a
unique occupational group. Research studies have adopted one of three theoretical foundations to
apply to musicians: musician as athlete, musician as worker, or musician as performing artist.
Similarly, clinicians often approach musician injury with occupational health frameworks (i.e.,
worker wellness) or performance-based frameworks (i.e., athlete performance, performing artist),
resulting in musicians feeling that practitioners fail to understand their unique needs as

x
performing artists. To better promote health and well-being in musicians, there is a need for a
foundational understanding of musicians as a unique occupational group.
While there is no validated foundational framework to understand musician well-being
and address the unique physical and mental health concerns in musicians, a recent study used a
single case study to develop the Ecology of Musical Performance (EMP) model to understand
and more effectively treat a musician with PRMD. Using the EMP model as a foundational
framework, this dissertation examined musician health using three perspectives: existing
literature, national trends, and daily lived experiences. In Chapter 2, a mapping review was
conducted to create a topography of existing musician well-being articles, using EMP model
well-being determinants to categorize articles. Next, in Chapter 3, a national survey was
conducted to quantitatively examine the associations of EMP well-being determinants with
various well-being outcomes. Building on the survey findings, in Chapter 4, the lived
experiences of a small group of music students were explored using daily activity logs and
interviews.
This dissertation was the first study to apply the EMP model as a foundational
framework; much was uncovered about the model’s current usefulness and potential areas for
modification. Although the survey illustrated the importance of all five model constructs as wellbeing determinants, the literature review identified many gaps in the existing literature. There is
also an opportunity for further development in the theoretical framework to facilitate musician
well-being, as the model was developed to support clinicians’ understanding of musicians for
evaluation and treatment and was not designed in a way that translates to empirical measurement
in research studies easily. Finally, preliminary interview findings highlighted the impact of
multi-faceted occupational identities of musicians on their health behaviors and well-being

xi
outcomes. The knowledge gaps within musician well-being literature are a call to action to
occupational scientists and other scholars, as this study demonstrated the need for more
theoretical development in understanding the occupational identities of musicians and how they
transact with well-being.

CHAPTER 1 General Introduction
1.1 Musician Health & Well-being
Career musicians engage in a single occupation over many years, often starting during
their developmental years, and becoming professional working musicians after spending many
thousands of hours engaging in the craft. It is said that a musician typically practices for 10,000
hours before becoming an “expert” (Lehmann & Ericsson, 1997). Part of the reason for this
daunting number is that the musician must become extremely proficient at the physical aspects of
playing to be mentally freed from the technicalities of music-making to allow for full creative
expression while performing. Practice becomes a daily ritual to sustain a high level of
performance and continually polish their craft. On this journey to becoming a career musician,
many musicians develop health impairments related to their occupation. Playing-related
musculoskeletal disorders (PRMD) are one such identified concern, with a lifetime prevalence
reported to be between 62-93% (Kok, Huisstede, et al., 2016). The time musicians spend
engaging in their occupation, the depth of their expertise, and the implications of becoming a
career musician all contribute to the complexity of musicians and the difficulty in addressing
musician health.
1.1.1 Injury and Intervention
Literature on musician health has grown exponentially in the past three decades. Study
after study replicates findings of high injury prevalence amongst musicians, and numerous
studies have been conducted on injury prevalence and treatment. A significant portion of current
literature on musicians focuses on the phenomena of various repetitive-strain injuries. Beyond
the high prevalence, there may be good reason for this focus, as a medically non-fatal

2
musculoskeletal disorder can become a debilitating obstacle for a musician. PRMDs often have
immense physical, social, emotional, and financial consequences for the musician (Zaza et al.,
1998). Even a relatively minor injury that doesn’t hinder other activities of daily living can cause
discomfort and pain that changes the way the musician interacts with their occupation of music
making, distracting them from the artistic or technical demands and causing psychological
distress (Guptill, 2012). With music-making as a key component of identity for many musicians,
not being able to play at the same level, or at all, can risk the musician for occupational
alienation, occupational deprivation, underemployment, and more (Guptill, 2012). It is no
wonder that musculoskeletal injuries have been associated with depression in professional
musicians (Kenny & Ackermann, 2015). Conversely, performance anxiety, another common
work-related stressor in musicians, has been found to be a significant risk factor for
musculoskeletal injuries (Baadjou et al., 2016; Jabusch & Altenmüller, 2004). With the high
stakes on health maintenance, many musicians are keenly aware of the importance of the health
of their bodies and try to find a balance between their body and their performance (Schoeb &
Zosso, 2012).
College musicians are one subgroup of musicians at high risk for injuries and other
occupation-related health detriments. Studies have suggested that music students have a lower
awareness of health behaviors and hesitate to seek help when experiencing pain (Britsch, 2005;
Spahn et al., 2002). Similar to professional musicians, a national survey in the U.S. found that
two-thirds of music students reported a musculoskeletal disorder during their years of study
(Spahn et al., 2002). To be admitted to a college music program, music students must pass
through a rigorous screening and audition process, followed by a continued high-level demand of
performance and musical development throughout their years of study. Most college music

3
programs require annual jury performances to faculty members and a graduating recital, on top
of other performance requirements (e.g., ensemble rehearsals and performances). Despite the
high-performance demands on student musicians and implications for their future careers, there
is currently a lack of adequate health-promoting measures for student musicians (Clark et al.,
2013).
Several studies have investigated preventive interventions in the student musician
population with some success. One randomized controlled trial demonstrated the feasibility and
effectiveness of a workshop intervention in student musicians at an 8-week summer music
festival program to decrease injury incidence (Wolff et al., 2021). Additionally, a longitudinal
study of university students found that a preventive curriculum over the first two semesters had a
preventive effect on students’ psychological health but did not have a significant impact on
physical symptoms (Zander et al., 2010). An educational course for student musicians in health
promotion and injury prevention was shown to increase knowledge 6 weeks later but did not
improve self-reported application of the health promotion and injury prevention strategies,
demonstrating the complexity of behavior change within daily routines (Barton & Feinberg,
2008). Several other intervention studies of musculoskeletal injury prevention, including student
musicians within their sample, have demonstrated short-term effectiveness in lowering injury
risk but failed to demonstrate long-term effectiveness (Roos & Roy, 2018).
1.1.2 Challenges and Complexities of Musician Well-being
While performance-related musculoskeletal injury is a significant concern for musicians
and undoubtedly a contributor to overall well-being, there is a need to consider musicians’ wellbeing more holistically to effectively promote both injury prevention and general well-being.

4
Most of current musician health literature focuses on musicians’ bodily functions and structures,
and less on the interplay of personal, environmental, and occupational factors (Guptill, 2008).
Health and well-being in musicians are often more complex than the biomechanics of injury. For
example, musicians are generally aware of the high risk of performance-related injury, but
musicians often do not engage in preventive health behaviors or address signs of injury early.
The social dynamics and financial pressures play a large role, as many feel the need to hide their
injury from colleagues and avoid seeking help: musicians have reported hesitating to disclose
their injury to their peers due to fears of employability as well as past history of negative
experiences of injury disclosure such as being stigmatized by peers and losing social support
(Guptill, 2011a; Guptill, 2011b).
To better promote health and well-being in musicians, there is a need for a better
foundational understanding of musicians as a unique occupational group; there is a lack of
foundational understanding of the musician (Clark et al., 2013; Hansen & Reed, 2006). Musician
health involves not just concerns for siloed health impairments but also concerns for artistry,
future career, sense of identity, and more. Qualitative articles demonstrate some of the complex
relations between a musician’s health and their music (Guptill, 2012). While the occupation of
music in career musicians can be theorized as a unique intersection of athleticism, work, and
artistry, no foundational framework has been developed to understand this unique occupational
group. Instead, many studies have adopted one of three theoretical foundations to apply to
musicians: musician as athlete, musician as worker, or musician as performing artist. Similarly,
clinicians often approach musician injury with occupational health frameworks (i.e., worker
wellness) or performance-based frameworks (i.e., athlete performance, performing artist). This

5
leaves musicians often feeling that practitioners fail to understand their unique needs as
performing artists (Guptill & Golem, 2008).

1.2 Occupational Identity of a Musician
Within occupational science literature, there is an understanding of occupations as being
a primary foundation for identity (Christiansen, 1999). Occupation has been described as a
synthesis of doing, being, becoming, and belonging (Hammell, 2004; Rebeiro et al., 2001;
Wilcock, 1998), all of which are necessary ingredients to survival and health (Wilcock, 2007).
While occupational identity in musicians has not been studied explicitly, aspects of identity,
especially during injury experiences, have emerged from multiple qualitative studies. In one
phenomenological study of orchestra musicians with injury, the theme of “identity and voice”
emerged, as musicians spoke of the loss of their identity as a musician and their outlet for
expression (Bourne et al., 2019). Another qualitative study explored the role of passion
throughout the occupational life course. Passion in this study was described by participants as the
value placed on their life in their performing art, their love for their performing art, and the allconsuming nature of music. Passion was found to fuel competence development in the
occupation, leading to the addition of the occupation of music to their occupational repertoire
(Christine et al., 2012). The three descriptions of passion within this study are all components
related to occupational identity: the value placed on the occupation, the love and choice for the
occupation, and the time component leading to an increased sense of meaning associated with
the occupation. Given the importance of occupational identity, advancing injury prevention and

6
health promotion for musicians requires considering how musicians are viewed as athletes,
workers, and performing artists in the current literature and clinical practice.
1.2.1 Musician as an Athlete
Musicians have been likened to athletes for many reasons. Musicians are expected to
perform using their bodies at a high level with consistency (Clark & Lisboa, 2013), and the
physical exertions required are comparable to high-level athletes (Baadjou et al., 2015). To meet
the physical demands, both groups perform repetitive motions to improve their abilities and
maximize performance. For example, a performance of Handel’s Messiah lasts 3 hours, and one
3-minute aria within the piece requires a cellist to move their bowing arm up and down 740
times (Horvath, 2001). Physiological measurements have demonstrated that musicians exert
heavily after just 10 minutes of playing (Drinkwater & Klopper, 2010).
Despite similar physicality to athletes, significant differences exist in the occupational
performance of musicians. While aspects of practicing for a solo recital may be similar to an
athlete training for a race, how a musician practices has not been understood and organized in the
same way as that of an athlete training. Although both have physical demands on their bodies,
unlike athletes who often train their whole body, musicians only use particular muscle groups
and rarely work on whole-body athleticism (Baadjou et al., 2015; Bird & Macdonald, 2013). In
fact, some have called musicians athletes of the upper body, as most instruments do not require
the use of the lower extremities (Bird, 2009). Similarly to team sport athletes during training
activities, musicians are often unable to pace their rehearsals and performances the way athletes
can pace themselves during training and events, as the musicians must respond to the demands of
the composer, artistic direction, and others (Bird & Macdonald, 2013). An additional
complicating factor that has not been studied empirically is the psychological demands for the

7
performing musician. Stage fright and performance anxiety are major concerns for many
musicians (Britsch, 2005; Rife et al., 2000). When healthcare professionals equate musicians
with athletes, these differences can lead to a failure to understand the unique challenges of being
a musician, hinder the relationship between clinician and musician (Guptill & Golem, 2008), and
negatively impact treatment outcomes.
Although explicitly viewing musicians as athletes may not be the most useful approach,
multiple frameworks from athlete literature may inform advances in musician health and wellbeing care. One study suggested a specific sports medicine model to musicians toward a longterm musician development, adapted from the existing long-term athlete development models
(Clark & Lisboa, 2013). Unlike sports, where the athlete’s longevity is often a core part of their
training, most music programs focus on developing the musician as a performer from a very
early age. In the original long-term athlete development model, there are 7 stages of developing
an athlete, corresponding to the approximate age of the athlete (Balyi & Hamilton, 2004).
Considering how a staged model of development may be appropriate for musicians, especially in
early music education, may be an effective way of addressing injury prevention from the very
start of music training. However, there needs to be an understanding of how best to translate the
model to musicians. Especially with the extensive hours of practice required of musicians,
implementation of a model similar to the long-term athlete development model would require
something that is feasible for musicians (Clark & Lisboa, 2013). Similarly, adherence barriers
experienced within sports medicine may inform the components of implementation barriers
within musician injury prevention. Indeed, there have been recent calls for more implementation
science within musician injury to translate evidence into practice (Clark & Lisboa, 2013; Yang et

8
al., 2021), and adherence frameworks within sports injury prevention may be beneficial for
musician injury prevention.
The historical progression of frameworks within sports medicine literature can help
foreshadow and guide the future of musician health literature. Within sports medicine literature,
frameworks such as the original sequence of prevention model offered a very rudimentary
understanding of the biomechanical process of injury to prevent injury (van Mechelen et al.,
1992). However, while interventions have been shown to reduce injury prevalence, severity, or
costs, these interventions have not translated well in real life (Bolling et al., 2018). Recognizing
the complexity in effectively reducing the impact of injury in a population in real life, more
recently, complex systems theory has been offered as an alternative paradigm to van Mechelen’s
cyclical sequence of prevention (Bittencourt et al., 2016). There is an emphasis on not just
identifying a singular intervention that works for all athletes but on applying complex systems
theory and understanding what works, for whom, when, where, and why (Bekker & Clark,
2016). Following the trend within public health, applied human factors and ergonomics, and
injury epidemiological literature, sports medicine moved towards using a socioecological
paradigm to better understand sports injury (Hulme & Finch, 2015). In this way, sports medicine
frameworks are continually revised to better understand and support athletes.
1.2.2 Musician as a Worker
Another common framing within musician injury prevention is the musician as a worker
(Costa Lima et al., 2015), as most career musicians are full-time workers. In the U.S.,
approximately 500,000 musicians earn their living from music, with as high as 87% of these
professionals developing PRMD during their careers (Raymond et al., 2012; Zaza, 1998). As
with any other workplace, the environment and organization at the workplace may contribute to

9
injury development in professional musicians (Lima et al., 2015). Importantly, musicians have
been compared to other workers who do not have the direct ability to minimize their
occupational hazards (Raymond et al., 2012; Zaza et al., 1998). Mirroring worker wellness
research, many musician injury prevention studies have investigated the contextual factors of
injury development, such as the ergonomics of instrument playing and the issue with the need to
move away from a one-size-fits-all approach (Chi et al., 2020). Moreover, being a worker can
complicate musician injury development due to the intersection of overlapping identities
(Guptill, 2011a). While musicians are already prone to performance anxiety, the added stress
from work and struggle for financial security may add to psychological stress and injury risk
(Lima et al., 2015). Full time professional musicians experience the difficulty of balancing their
need to sustain a career and seeking medical attention early in the injury development process
(Lima et al., 2015). Within professional orchestral musicians, there has been an underutilization
of worker’s compensation. This may be due to the financial pressure to stay employed, or the
lack of formal education and training on occupational health risks (Chimenti et al., 2013;
Raymond et al., 2012).
While worker wellness frameworks can add a layer of understanding of professional
musicians, there are many additional challenges specific to musicians that interact with existing
work-related challenges. One worker wellness framework that has been applied to musician
wellness is the job demands-resources model. Originally the job demands-control-support model
(Karasek, 1990), this model considers the job demands, such as physical and psychological effort
associated with strain, and the job resources, such as job control and feedback, as creating a net
impact on the health and well-being of workers (Bakker, 2011; Demerouti et al., 2001).
Musicians have been shown to be exposed to more psychosocially demanding workplaces than

10
the general workforce, potentially creating a higher job demand on the musician (Holst et al.,
2012). Additionally, work-related factors such as job demands and social support have been
associated with distress in musicians (Aalberg et al., 2019). However, existing questionnaires for
the general workforce to assess job demands and resources may not translate well to musicians.
For musicians, part of their core identity is being a musician, and even off work hours, they often
have to practice and rehearse to maintain their level of performance. As such, musicians find that
work and non-work as separate entities is an unfamiliar concept (Vaag et al., 2014). To ensure
the effective application of worker wellness perspectives to musicians, there is a need to
understand the musician’s perspective of their occupation of music, what boundaries may or may
not exist between their work and nonwork identities, and how this impacts the applicability of
worker wellness frameworks.
Recent development of worker wellness theories to address both health protection and
promotion may contribute to a more proactive framework for musician health. Worker wellness
frameworks such as Total Worker Health highlight the need to address multiple areas of a
complex work system to create workplaces that foster health and well-being for workers (Schill
& Chosewood, 2013). Additionally, new insights on the relationship of work and well-being
during the COVID-19 pandemic have led to frameworks such as the Surgeon General’s
Framework for Workplace Mental Health and Well-Being that highlight the significant mental
health and well-being impacts of the workplace (The U.S. Surgeon General's Framework for
Workplace Mental Health & Well-Being, 2022). Implementing features of frameworks that
consider the holistic needs of workers with an aim of health promotion may help shift the focus
within musician well-being away from injury prevention and towards promoting health and wellbeing.

11
1.2.3 Musician as a Performing Artist
While musicians feel that one of their roles as a professional musician is being a worker
(Guptill, 2011a), the meaning derived from music may be greater than the meaning felt from the
work outputs of other professions. That is, the task of performing music is unique from winning
a sports game or finishing a work task. The musician is a performing artist, creating art that
happens in real-time. Performances can be more personal and exposing in nature, as it is a
representation of the musician, their personality, and the message they are communicating
through the music (Schoeb & Zosso, 2012). At the core, musicians are artists - they must connect
with their audience through their performance (Currey et al., 2020). With a core objective of
music-making being the emotional impact on the audience, music practice and performance can
be a more elusive and creative process compared to athletes or workers. Qualitative inquiry has
begun to demonstrate a need to shift the framing of musicians away from athletes or workers
toward this self-identification as artists (Guptill & Golem, 2008) in both clinical practice and
research.
While viewing the musician as a performing artist is a meaningful step towards a better
understanding of this unique occupational group, current performing arts and creative art
literature are less extensive than sports medicine or worker health literature. Although medical
concerns of artists have been recorded for centuries, performing art medicine originated recently
in the 1980s, with its first annual symposium in 1983 and associated journal, Medical Problems
of Performing Artists, beginning publication in 1986. This difference in knowledge and
resources is felt in real life applications, as athletes have access to an abundance of trainers,
medical support, sport psychologists, and other care team members, while most performing
artists do not have the same support. In 2019, Athletes and the Arts was established as an

12
initiative for collaborative exchange between sports medicine and performing arts knowledge, as
artists can benefit from established training and research in sports medicine (Dick, 2019).
Despite recent initiatives and the exponential growth in performing arts medicine
research, the work has yet to be substantiated in practical applications. Many specialized clinics
were established to address performing artists’ health, but the majority of these institutions were
discontinued due to a lack of resources. Furthermore, many healthcare professionals remain
unaware of the unique needs of performing artists. To be able to effectively translate the
increased research efforts into practice, there is a need for a more developed knowledge base
from clinical and basic research within performing arts medicine (Lee et al., 2020).
1.3 Musician Health and Well-Being Frameworks
Despite growing research on musicians’ well-being, little improvements have been made,
with a lack of fundamental understanding of this unique occupational group. While there are
arguably many overlaps in perspectives of viewing musicians as athletes, workers, and artists,
this population may be unique enough to merit a distinct health and well-being framework. All
three perspectives contribute to a partial understanding of the musician that may support such a
framework.
1.3.1 Critical Considerations Based on Occupational Identities
• Understanding the musician as an athlete has unique strengths. The current trends within
sports medicine to complexity and systems theory may be beneficial to musician injury
frameworks, as injury development is a fluid, cyclical, complex phenomenon. On the
other hand, the biomechanical aspects of music playing, practice, and high level of

13
performance is comparable to athletes. There is much that can be learned from sports
medicine literature from the perspective of tissue stress and strain, as well as the
associated risk factors for injury. The application of biomechanical sports injury
prevention into musician intervention will require more research into the similarities and
differences in sports training and music practice, as well as translational research into
how sports interventions to decrease tissue stress/strain can be applied to musicians.
While these biomechanical frameworks have helped inform training regimens for
athletes, simply transferring these training regimens to musician practice sessions may
not be effective, as musicians’ goals with practice are often more iterative and creative in
nature.
• Worker wellness frameworks help provide insight into the complexity of multiple
extrinsic factors that can contribute to the well-being of working musicians. However,
several potential differences must be understood better, such as the differences in the
distinction of work vs. nonwork boundaries in musicians. Many musicians are also
freelancers who have very different extrinsic work structures. Exploration of how
concepts of general workplaces may or may not apply to musicians would help to
understand how these frameworks can best be applied to career musicians who are
simultaneously musicians and workers. Recent trends within worker wellness initiatives
to focus on health promotion rather than safety and injury prevention may also inform the
development of more wide-scale intervention within musician health initiatives.

14
• Considering a musician as a creative, performing artist requires that a framework
incorporates the core fundamental nature of the occupation of music-making, perhaps
more intentionally than the former two perspectives. Unfortunately, there is not enough
research or literature in this area to adequately support framework development or
validation to directly inform practice. Further establishment of musicians as a unique
population and an understanding of musician identity can help inform the translation of
the research and intervention methods from various other perspectives in a way tailored
specifically to musicians (Stanhope et al., 2020).
1.3.2 Ecology of Musical Performance (EMP) Model
A criticism within current musician literature has been that most existing studies on
musicians utilize a problem-solving approach where barriers are identified, and action plans are
created, evaluated, and modified according to results (Hill-Briggs et al., 2011). Inquiry, a
transactional mode of understanding, may be more appropriate for the complexity of musician
well-being. Transactionalism rejects the dualism of person and context, and acknowledges the
continuous relation of the individual coordinating and re-coordinating their self and their world
(Dickie et al., 2006). Inquiry is an active process of understanding how things relate within a
constantly changing environment (Fritz & Cutchin, 2017). Rather than problem-solving
strategies of applying solutions to a set of pre-identified problems, inquiry takes into account the
person and situation as a whole, opening up possibilities for multiple, interrelated modes of
intervention (Fritz & Cutchin, 2017). Using transactional perspectives of inquiry to holistically
understand musician well-being would require focusing on the occupation of music and
understanding the relations of the individual, occupation, and context – a perspective that is yet
to be seen within musician health literature (Willis et al., 2019).

15
While there is no validated foundational framework to understand musician well-being
and address the unique physical and mental health concerns in musicians (Clark & Lisboa,
2013), in a recent study, a single case study was used to develop the EMP model to understand
and more effectively treat a musician with PRMD (Bastepe-Gray et al., 2021) (Figure 1.1). The
EMP model considers the musician’s personal, environmental, and occupational factors, and it
has the potential to offer both researchers and organizations an informed approach to addressing
the musician's well-being using a transactional lens. The EMP considers the unique needs of the
musician with the aim of reducing strains to maintain the role of the musician. The core of the
model includes the Musician-Instrument-Repertoire Complex (MIRC), an interactive system that
includes the musician’s engagement with their instrument, their role as a musician, and the
musician’s drive. The MIRC is differentiated from the peripheral context, which includes
nonmusical occupations, biomechanical loads, and more, which interact with the central context
of the MIRC (Bastepe-Gray et al., 2021). While this model proposes a new organization of
understanding the musician, it was based on a single case study and has not been validated yet.

16
Figure 1.1. Ecology of Musical Performance (EMP) Model reproduced with permission
(Bastepe-Gray et al., 2021)
1.4 Dissertation Overview
To better understand the EMP model using transactional perspectives of inquiry, this
dissertation examines the model using various levels of analysis and types of data. Given the
gaps in knowledge, the key questions of this study were:
1) What is the state of well-being literature of the five EMP model constructs?
2) How do EMP model well-being contributors affect well-being in music students?
3) How does daily occupational engagement intersect with well-being in music students?
Using the EMP as a foundational framework, I conducted an explanatory mixed-method
study to examine the intersection of musicians’ occupational engagement and well-being. An
explanatory sequential design features two interactive phases, starting with the collection and

17
analysis of quantitative data and followed by qualitative data collection and analysis to explain or
expand on the first phase results. By incorporating both etic and emic perspectives, this mixed
method offers a better understanding than what could be provided with one approach alone
(Creswell & Clark, 2017). Moreover, the sequential mixed method study design lends itself well
to complex research questions and transactional perspectives, as it allows for flexibility in
pursuing emergent findings. As such, the study was conducted in three phases using the newly
developed EMP model as a foundational framework.
• Aim 1: Map out and identify research gaps in the current state of musician well-being
literature on well-being determinants. I conducted a mapping review focusing on the
state of research and literature on musician well-being. Studies were categorized by study
design, sample population, and EMP constructs to identify trends and gaps. (Chapter 2)
• Aim 2: Empirically explore the application of the EMP model with music students. A
national survey of music students in higher education programs within the U.S. was
conducted to collect large-scale quantitative data on well-being determinants defined by
the newly developed EMP model. Music students’ satisfaction, perceived importance,
and quality rating of well-being determinants identified by the EMP Model were
examined and analyzed with various well-being outcomes. Multiple linear regression
analyses were conducted to measure associations of well-being determinants and wellbeing outcomes. (Chapter 3)
• Aim 3. Explore the intersection of daily patterns of occupational engagement and wellbeing of student musicians. Over one week, students’ daily activity patterns and

18
associated well-being experiences were collected repeatedly using a modified day
reconstruction method. Following data collection and analysis of daily activity logs, oneon-one semi-structured interviews were conducted to contextualize findings and gain
further insight into the students’ lived experiences with the intersection of engagement in
activities and well-being experiences. (Chapter 4)

19
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26
CHAPTER 2 Mapping Review of Musician Well-being Literature
2.1 Introduction
Over the past three decades, research and interest in musician health and wellness has
grown. Since the initial groundbreaking article in 1988 showing that 76% of musicians from the
International Conference of Symphony and Opera Musicians had work-related health issues
(Fishbein et al., 1988), a plethora of literature has been published on musicians. Injury
prevalence studies have illuminated the need for intervention, as study after study demonstrates
the high prevalence of injury among musicians. There is a plethora of studies of musician injury
or other facets of well-being, and several studies have synthesized available literature through
systematic reviews. A recent systematic review found that point prevalence of performancerelated musculoskeletal disorders (PRMD) during studies ranged from 37-47%, and lifetime
prevalence was as high as 89% (Betzl et al., 2020). The most common reported injuries often
only affect the hand and wrist. However, even a minor physical injury can drastically impact a
musician’s quality of life (Guptill, 2012). Qualitative studies have begun to explore the
emotional, financial, and social repercussions of injury, including occupational alienation,
occupational deprivation, and underemployment (Guptill, 2011a; Guptill, 2012).
While the literature pertaining to PRMD prevalence and treatment continues to grow,
there is a notable lack of foundational understanding of musician well-being or understanding of
the musician as a whole (Clark et al., 2013; Hansen & Reed, 2006). Beyond musculoskeletal
injuries, how do musicians experience well-being in their daily lives? To date, no study has
engaged in the process of understanding how well-being is experienced holistically by musicians
throughout various daily occupations, both within and outside of music activities. This poses

27
difficulty for health promotion and injury prevention, as musicians often face conflicting needs.
For example, despite the awareness of the risk of repetitive strain injuries, musicians often spend
an unhealthy amount of time engaged in their occupation of music making, leading to various
health detriments (Britsch, 2005). To more effectively intervene and promote well-being, there is
a need for a better theoretical understanding of how occupational engagement specifically
impacts well-being in musicians.
A recent systematic review examined the relation of occupational demands with wellbeing in performing artists (Willis et al., 2019); however, no study to date has systematically
examined the scope of knowledge within musician health literature that focuses on general wellbeing. Given the heterogeneity of existing literature on musician well-being and inconsistency in
conceptualizations of well-being (Baadjou et al., 2016), mapping the field of knowledge to create
a topography of the state of the literature can help guide future research. This mapping review
aimed to further musician well-being research by summarizing the state of knowledge of wellbeing determinants in musicians. A recently developed framework to understand musician
health, the Ecology of Musical Performance (EMP) Model, was used as a foundational
framework to organize the well-being determinants studied within musician well-being literature
(Bastepe-Gray et al., 2021). This review was designed to answer the following questions: What
areas of musician well-being, as defined by the EMP Model, are currently being studied? What
populations of musicians are being studied? What study designs are used to understand musician
well-being?

28
2.2 Methods
2.2.1 Study Design
Mapping reviews provide an overview of the breadth of existing knowledge and identify
gaps to guide future research. The design of this mapping review was informed by the Focused
Mapping Review and Synthesis (FMRS) approach (Bradbury-Jones et al., 2019). Rather than a
traditional review that measures evidence, the FMRS approach is suitable for research questions
where the goal is to methodologically or theoretically understand trends within the literature.
Well-being is an important but poorly defined construct within musician health literature. As
such, the goal of this review was not to measure evidence but to understand how studies
currently define well-being, what well-being determinants are being studied, and what study
designs are used to investigate various areas of well-being. Following the FMRS (Figure 2.1),
this review involved three stages of Focus (develop clear questions, determine
inclusion/exclusion criteria, calibration, retrieve and screen articles), Mapping (template for
individual papers, quantitative analysis, map to review questions, calibration), and Synthesis
(output production and calibration). Calibration was conducted among the research team at every
stage of focus, mapping, and synthesis through multiple iterative discussions and reviews of data.

29
Figure 2.1 Review process adapted from Focused Mapping Review and Synthesis (FMRS)
Approach (Bradbury-Jones et al., 2019).
2.2.2 Article Review Process
Due to the presence of musician well-being literature in a wide variety of journals, rather
than strictly following the FMRS protocol of identifying journals, this review used databases to
identify relevant studies. Searches were conducted in PubMed, PsycINFO, ERIC, and
WebofScience. In order to identify a rigorous search strategy, an iterative process was used to
examine different key terminology in multiple searches across all databases. Final search terms
were selected to capture different terminology referring to musicians and constructs of “physical
health”, “mental health”, and “general well-being.” Musicians were defined using broad terms
(e.g., “musician”), instrument groups, and specific instrument players. All well-being and
musician terms were added using the Boolean operator “OR”, combined with an “AND”
operator to create the final search term. Searches were conducted without any language, region,
or date restrictions. The full search strategies are included in Table 2.1.

30
Table 2.1 Search terms.
Database
Search terms
PubMed ("musicians" OR "musicians" OR "string instrument" OR "brass instrument"
OR "percussion instrument" OR "instrumentalist" OR "instrumentalists" OR
"flautist" OR "flautists" OR "flute players" OR "oboist" OR "oboists" OR
"oboe player" OR "clarinet player" OR "clarinet players" OR "clarinetist" OR
"clarinetists" OR "bassoonist" OR "bassoonists" OR "bassoon players" OR
"hornist" OR "hornists" OR ("tuba" AND "player") OR "trombone player"
OR "trombonist" OR "trombonists" OR ("trombone" AND "players") OR
"trumpet player" OR "trumpeters" NOT "birds" OR "saxophonist" OR
"saxophonists" OR "saxophone player" OR ("recorder" AND "players" AND
"music") OR "guitar player" OR "guitar players" OR "guitarist" OR
"guitarists" OR "cello players" OR "cellist" OR "cellists" OR "harp players"
OR "harpist" OR "harpists" OR "violinist" OR "violinists" OR "violin player"
OR "violin players" OR "violist" OR "violists" OR "viola player" OR "viola
players" OR "percussionist" OR "drummers" OR "percussionists" OR
"percussionist" OR "drummers" OR "percussionists" OR "pianist" OR
"pianists" OR "timpani" AND "percussion" OR ("tambourine" AND
"percussion") OR "organ player" OR "organist" OR (“organist" AND
"music") OR "accordionists" OR "harpsichordists") AND
("burnout"[all fields] OR "mental health"[all fields] OR "stress"[all fields]
OR "anxiety"[mesh terms] OR "anxiety"[all fields] OR "depression"[all
fields] OR "fatigue"[all fields] OR "behavioral symptoms"[mesh terms] OR
"wellness" OR "well-being" OR "wellbeing" OR "health"[mesh terms] OR
"health" OR "quality of life"[mesh terms] OR "quality of life" OR
"occupational health"[mesh terms] OR "physical fitness"[mesh terms] OR
"athletic performance"[mesh terms] OR "musculoskeletal physiological
phenomena"[mesh terms] OR "Nervous system physiological
phenomena"[mesh terms] OR "dystonia"[All Fields] OR "pain"[All Fields]
OR "Musculoskeletal Diseases"[MeSH Terms] OR "injur*"[All Fields] OR
"personal satisfaction"[mesh terms])
PsycINFO ("musician" OR "musician's" OR "musicians" OR "instrumentalists" OR
"flautists" OR "flute players" OR ("flautists" NOT "flute") OR "oboist" OR
“oboists" OR "clarinet players" OR "clarinetists" OR "bassoon players" OR
"saxophone players" OR "guitar player" OR "guitar players" OR "guitarist"
OR "guitarists" OR "cello players" OR "cellist" OR "cellists" OR "harpists"
OR "violinist" OR "violinists" OR "violin player" OR "violin players" OR
"violist" OR "violists" OR "viola player" OR "viola players" OR "double bass
player" OR "bass player” OR "tubist" OR "tuba player" OR ("tuba" AND
"player") OR ("tuba" AND "brass") OR "trombone player" OR "trombonist"
OR "trombonists" OR ("trombone" AND "players") OR "trumpet player" OR
"trumpet players" OR ("trumpet" AND "instrumentalists") OR "hornist" OR
"french horn player" OR "drummers" OR "drummers" AND "music" OR
"percussionist" OR "percussionists" OR "timpanists" OR "pianist" OR
"pianist" AND "music" OR "pianists” OR "organ player" OR "organist" OR

31
“organists" OR "organist" AND "music" OR "harpsichordists") AND
("physical fitness" OR "athletic performance" OR "musculoskeletal
physiological phenomena" OR "Nervous system physiological phenomena"
OR "dystonia" OR "pain" OR "Musculoskeletal Diseases" OR "injur*" OR
"mental health" OR "stress" OR "anxiety" OR "depression" OR "fatigue" OR
"behavioral symptoms" OR "burnout" OR "wellness" OR "well-being" OR
"wellbeing" OR "health" OR "quality of life" OR "quality of life" OR
"occupational health" OR "personal satisfaction")
ERIC (musician OR "musician's" OR "musicians" OR "string instrument" OR
"instrumentalists" OR "flautists" OR "flute players" OR "piccolo player" OR
"oboist" OR "oboists" OR ("oboe" AND "players") OR "clarinet player" OR
"clarinet players" OR "clarinetist" OR "clarinetists" OR "bassoonist" OR
"bassoonists" OR "bassoon players" OR ("bassoon" AND "music") OR
"saxophonist" OR "saxophonists" OR "saxophone player" OR "saxophone
players" OR ("recorder" AND "players" AND "music") OR "guitar player"
OR "guitar players" OR "guitarist" OR "guitarists" OR "cello players" OR
"cellist" OR "cellists" OR "banjo players" OR "violinist" OR "violinists" OR
"violin player" OR "violin players" OR "violist" OR "violists" OR "viola
player" OR "viola players" OR "double bassist" OR "double bass player" OR
"bass player" OR "tuba player" OR ("tuba" AND "brass") OR "trombone
player" OR "trombonist" OR "trombonists" OR ("trombone" AND "players")
OR "trumpeters" OR "trumpet player" OR "trumpet players" OR "trumpet"
AND "instrumentalists" OR "trumpet" AND "music" OR "hornists" OR
"french horn" OR "french horn players" OR ("drummers" AND "music") OR
"percussionist" OR "percussionists" OR ("xylophone" AND "percussion")
OR "pianist" OR "pianist" AND "music" OR "pianists” OR ("timpani" AND
"percussion") OR ("triangle" AND "percussion") OR ("tambourine" AND
"percussion") OR ("organist" AND "music")) AND (physical health OR
"physical fitness" OR "musculoskeletal physiological phenomena" OR
"nervous system physiological phenomena" OR "dystonia" OR "pain" OR
"musculoskeletal diseases" OR "musculoskeletal health" OR "injury" OR
"injuries" OR "mental health" OR "stress" OR "anxiety" OR "depression" OR
"fatigue" OR "behavioral symptoms" OR "burnout" OR "wellness" OR "wellbeing" OR "wellbeing" OR "health" OR "quality of life" OR "occupational
health" OR "personal satisfaction" OR "fulfilment" OR "happiness" OR
"contentment")
WebofScience ("musician" OR "musician's" OR "musicians" OR "instrumental musicians"
OR "instrumentalists" OR "flautists" OR "flute players" OR "oboist" OR
"oboists" OR ("oboe" AND "players") OR "clarinet player" OR "clarinet
players" OR "clarinetist" OR "clarinetists" OR "bassoonist" OR "bassoonists"
OR "bassoon players" OR "saxophonist" OR "saxophonists" OR "saxophone
player" OR "saxophone players" OR "guitar player" OR "guitar players" OR
"guitarist" OR "guitarists" OR “cello players" OR "cellist" OR "cellists" OR
"banjo player" OR "banjo players" OR "violinist" OR "violinists" OR "violin
player" OR "violin players" OR “violist" OR "violists" OR "viola player" OR

32
"viola players" OR "double bass player" OR "bass player" OR "tuba player"
OR "trombonist" OR “trombonists" OR "trumpet player" OR "trumpet
players" OR ("trumpet" AND "instrumentalists") OR "hornist" OR "hornists"
OR "french horn player" OR "french horn players" OR "drummers" OR
"percussionists" OR "pianist" OR “pianists” OR "timpanist" OR ("triangle"
AND "percussionists") OR ("tambourine" AND "percussion") OR "organ
player" OR "organist" OR "organists" OR "accordion player" OR
"accordionist" OR "accordionists" OR "harpsichordist") AND (physical
fitness OR "athletic performance" OR "musculoskeletal physiological
phenomena" OR "Nervous system physiological phenomena" OR "dystonia"
OR "pain" OR "Musculoskeletal Diseases" OR "injur*" OR "mental health"
OR "stress" OR "anxiety" OR "depression" OR "fatigue" OR "behavioral
symptoms" OR "burnout" OR "wellness" OR "well-being" OR "wellbeing"
OR "health" OR "quality of life" OR "quality of life" OR "occupational
health" OR "personal satisfaction")
The final searches were performed on April 18, 2023. Records retrieved from the four
databases were aggregated, duplicates were removed, and the title and abstract of every record
was screened. During the first screening process, any articles that pertained to musician health
were included. Two reviewers independently screened all articles to identify relevant articles
meeting the following inclusion criteria: 1) population of interest was musicians, 2) health or
well-being was studied or measured, and 3) used primary data (e.g., literature reviews and expert
opinions were excluded). Next, records were categorized by the health/well-being topics, and
only studies that focused on general health and well-being were included for further review.
Articles whose focus was not on musicians themselves (e.g., music as a therapeutic modality) or
focused on specific areas of physical or mental health (e.g., tendonitis, performance anxiety)
rather than general well-being were excluded. The remaining articles were sought for retrieval.
Reports that did not have a full text or English translation available were excluded. Through
reading full texts, additional articles that did not measure general health/well-being were
excluded.

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2.2.3 Data Extraction and Analysis
Using a Qualtrics survey that was developed iteratively by the principal investigator (PI)
and two research assistants who were involved in the entire screening process, all remaining
articles were reviewed for data extraction. Data extraction consisted of the publication year,
geographical location, study design, study population, sample size, and well-being determinants
studied. After iterative discussions of the most common study designs, the categories of case
study, cohort, cross-sectional, intervention, and qualitative studies were used. The study
population was categorized by the career stage of the musician using the categories of
professional, higher education students, K-12 students, and amateur. The well-being
determinants were categorized using the EMP model’s five constructs and their subcomponents.
Articles that studied any of the subcomponents within a construct were categorized as studying
the construct. The Musician Continuum construct contains the musician’s predispositions across
musculoskeletal, sensory/motor, cognitive/perceptive, and psychosocial dimensions. This
construct interacts with the immediate context constructs of Physical Environment (temperature,
lighting, noise) and Musical Work Schedule (performance schedule and practice behaviors).
These three constructs interact in the Interface Effectors construct, which includes the
biomechanical efficiency, repertoire demands, and mechanical demands of the musical
instrument. Finally, the interaction of all four constructs happens within the fifth construct, the
Peripheral Variables (activities of daily living, non-musical work, leisure activities).
Data were analyzed using Microsoft Excel and SAS software (Statistical Analysis
Software Version 9.4 Cary, NC, USA). Descriptive statistics were conducted, including various
visualizations to characterize the topography of literature on musician well-being. Publication
trends (i.e., year of publication and geographical location) were visualized using histograms and

34
bar charts. Descriptive characteristics of studies (i.e., mean, standard deviation or frequency,
percentage) were displayed in tables and figures to summarize the state of musician well-being
literature. To understand how musician well-being is currently studied, a bar chart was created of
the frequency of different EMP constructs and subcomponents currently studied. To better
understand how and with whom each EMP construct is studied, a nested bar chart was created to
visualize the intersection of well-being determinants studied within different types of musicians
(e.g., students, professionals, amateurs) and the study designs used within each realm.
2.3 Results
2.3.1 Search Results
After the initial database search, 6795 studies were retrieved. 1921 duplicates were
removed, and the remaining 4874 records were screened. 2950 irrelevant reports were excluded
using inclusion criteria. The remaining 1924 articles were categorized by health/well-being
focus, with the vast majority of articles being excluded due to being focused on musculoskeletal
or other physical health disorders. A total of 369 articles were sought for full-text review, and
251 articles were eliminated, primarily due to the article not including well-being despite the
framing provided in the abstract. The remaining 118 articles met inclusion criteria and were used
as the foundation of this mapping review. The full article screening process is displayed as a
flow diagram in Figure 2.2 (Moher et al., 2009).

35
Figure 2.2. Flow diagram of study review and inclusion process.
Records identified from:
Web of Science (n = 2857)
PubMed (n = 2723)
PsycInfo (n = 1008)
ERIC (n = 207)
Records removed before screening:
Duplicate records removed (n = 1921)
Records screened (n = 4874) Records excluded (n = 2950)
Records categorized by topic
(n = 1924) Records excluded due to no well-being
studied (n = 1555)
Excluded topics: musculoskeletal injury,
dystonia, hearing health, performance
anxiety, ocular health, oral health,
respiratory health, skin condition, sleep
health, vocal health
Records on well-being sought for
retrieval (n = 369) Records excluded (total n=48):
Full text unavailable (n = 26)
English translation unavailable (n = 12)
Not general well-being (n = 213)
Identification of studies via databases and registers
Identification Screening Included
Records included in review
(n = 118)

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2.3.2 Descriptive characteristics
Although no date limitations were set for the publication year of articles in the screening
process, the earliest publication date was 1984. A histogram of publication years of included
articles can be seen in Figure 2.3. Five studies were published between 1984-1989 and the
remaining studies were from 1996-2023 (n=113, 95.8%); no studies were identified in the years
between 1989 and 1996. Furthermore, half of all articles were published between the years of
2018 and 2023. There was a wide range of sample sizes ranging from 1 to 2212 with a positively
skewed distribution. Despite the largest sample size being 2212, the mean sample size was 204.4
(sd=327.5) and median sample size was 99, with three quarters of all articles having sample sizes
of 250 or less.
Frequencies across all extracted categorical data can be found in Table 2.2. Nearly twothirds of the studies were conducted in Europe (n=73, 62.4%), with a quarter of the studies
conducted in North America (n=30, 25.6%). The majority of studies were quantitative in nature,
with few and varied types of qualitative studies. Approximately half of the studies were crosssectional studies (n=64, 54.2%), followed by about a quarter of studies being qualitative (n=32,
27.1%). The remaining studies were case study, cohort, or intervention studies. Around half of
studies included musician populations of music students in higher education programs (n=56,
47.5%) and/or professional musicians (n=64, 54.2%). The genre of music or instrument played
by the study participants were not always specified, but Classical musicians were the most
common musical genre (n=46, 39%) and musical instruments from all categories of string,
keyboard, woodwind, voice, brass, and percussion were represented (22.9-36.4%).

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Figure 2.3 Histogram of publication years of included articles.

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Table 2.2 Frequency and percentage of articles, sorted within variable by frequency.
Variable
Frequency (%)
Continent
Europe 73 (62.4)
North America 30 (25.6)
Australia 6 (5.1)
Multi-continental 3 (2.6)
Middle East 2 (1.7)
Asia 2 (1.7)
Africa 1 (0.9)
Study Type
Cross-sectional 64 (54.2)
Qualitative 32 (27.1)
Cohort 12 (10.2)
Intervention 6 (5.1)
Case Study 4 (3.4)
Population Type*
Professional 64 (54.2)
Higher Education students 56 (47.5)
Amateur/hobbyist 16 (13.6)
K-12 students 5 (4.2)
Musical Genre*
Not Specified 60 (50.8)
Classical 46 (39.0)
Pop 15 (12.7)
Jazz 10 (8.5)
Other (e.g., rock, electronic, church) 5 (4.2)
Musical instrument*
Other (e.g., unspecified, orchestral,
instrumentalists)
54 (45.8)
Strings 43 (36.4)
Woodwind 37 (31.4)
Keyboard 33 (28.0)
Voice 32 (27.1)
Brass 30 (25.4)
Percussion 27 (22.9)
*Note: Variables that allowed selection of multiple categories do not add up to a total frequency
(%) of the total included articles.

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2.3.3 Well-being constructs
All included articles studied the EMP construct of the musician continuum, with the
psychosocial function subcomponent studied by all but four articles (n=114, 96.6%). Within
psychosocial function, performance anxiety was a commonly studied topic (Kegelaers et al.,
2022; Simoens & Tervaniemi, 2013; Wills & Cooper, 1984). Slightly fewer than half of the
studies included the musician continuum subcomponent of musculoskeletal function (n=52,
44.9%), with a focus on performance-related injuries (Araújo et al., 2017; Rosset et al., 2022).
The second most common EMP construct studied was peripheral variables (n=72, 61%).
Within the peripheral variables construct, two subcomponents that were not in the original EMP
model were identified through article screening and added for categorization. Sleep and social
support were commonly studied as well-being determinants (n=18, 15.3% and n=38, 32.2%
respectively), but were not explicitly listed as subcomponents in the original EMP model. The
EMP model includes all non-music activities under peripheral variables (i.e., activities of daily
living, nonmusical work, and leisure). All articles that studied sleep or social support were
categorized under the EMP construct of peripheral variables. Another common EMP construct
was musical work schedule (n=50, 42.4%). Both performance schedule and practice behaviors,
subcomponents of the musical work schedule construct, were studied at similar rates (n=32,
27.1% and n=31, 26.3% respectively).
The least studied constructs were interface effectors and physical environment (n=11,
9.3% and n=13, 11% respectively). Interface effectors that were studied included body postures
during music playing (Détári et al., 2020), physical compatibility and the instrument and
musician (Hagglund & Jacobs, 1996; Kegelaers et al., 2022), and repertoire and technique
(Kenny et al., 2016; Kreutz et al., 2008). Amongst articles on the physical environment, there

40
was a focus on the acoustics and noise exposure in connection to hearing loss in musicians
(Hasson et al., 2009; Kenny et al., 2016; Zuhdi et al., 2020). A histogram of EMP constructs
covered by included articles can be found in Figure 2.4.
Studies of all four categories of the sample population (professional, higher education
students, k-12 students, amateur/hobbyist) had similar frequencies of studying various EMP
constructs, with the most studies on musician continuum, peripheral variables, and musical work
schedule, and the least studies on interface effectors and physical environment. The only notable
difference in the frequency of studies on EMP construct was that within professional musicians,
physical environment was studied more than interface effectors, and within higher education
students, almost the same number of studies were conducted on interface effectors and physical
environment. All intervention studies involved students (both K-12 and higher education), and
no intervention studies were conducted with amateur/hobbyist musicians or professional
musicians. All four case studies included in the review were conducted with higher education
students. Further details of study designs of EMP constructs by sample population can be found
in Figure 2.5.

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Figure 2.4. Frequency of included articles covering EMP constructs and subcomponents

42
Figure 2.5 Nested bar chart of distribution of articles by study design across EMP model constructs and study
population

43
2.4 Discussion
This review was the first to create a topography of musician well-being literature using a
framework developed specifically for musicians. There has been a notable exponential increase
in the volume of literature on musician well-being in the past few years, as half of the articles
included in the study were published between 2021-2023. However, descriptive analyses of this
review illuminates several gaps within the literature. The majority of included studies were
cross-sectional quantitative studies and roughly a quarter of included studies were qualitative.
Music students and professional musicians playing Classical music were commonly studied and
other musician populations were rarely included in existing literature. One unusual finding of
this study was the high prevalence of studies from Europe compared to other continents. This
may partly be due to the high prevalence of studies on Classical musicians, as much of Classical
music originated in Europe. However, further study is necessary to understand this finding and
the implications of applicability of studies.
Using the EMP model to categorize articles helped illustrate a vast difference in the
coverage of well-being determinants by included articles. Most articles focused on a handful of
areas, leaving many EMP subcomponents with fewer than 10 existing articles. The musician
continuum, musical work schedule, and peripheral variables were amongst the most studied wellbeing determinants. On the other hand, the EMP construct of interface effectors was rarely
studied. The interface effectors construct is an important well-being determinant to understand as
it highlights the interaction between the musician, instrument, and their repertoire. Similar to the
interface effector, the physical environment was not commonly studied. Understanding the
environment and is a key component to understanding health promotion in occupational groups

44
(Schill & Chosewood, 2013). Further study on physical environments can lead to development of
environments that promote musician engagement and well-being.
One very important finding of this review was the high density of cross-sectional studies,
and sparsity of longitudinal or intervention studies. This finding is consistent with a similar
previous systematic review on risk factors for musculoskeletal disorders in musicians, where
identified studies were predominantly cross-sectional studies (Baadjou et al., 2016). Within
musician health literature, studies on preventive intervention for musculoskeletal injury have
measured efficacy of education workshops and curriculums in student musicians with varying
results (Barton & Feinberg, 2008; Roos & Roy, 2018; Wolff et al., 2021; Zander et al., 2010). A
systematic review on intervention studies found that many articles with effective exercise
programs had lower level study design and higher risk for methodological bias (Stanhope et al.,
2020). Additionally, most intervention studies in a mapping review did not measure long-term
effects of their interventions (Stanhope et al., 2019). While one intervention study of education
and exercise programs on injury prevention with both students and professionals found shortterm effectiveness, the effect was not retained long-term (Roos & Roy, 2018). To better
understand the effect of various interventions on musician health, more rigorous study designs
and longitudinal studies are needed.
Additionally, all intervention articles identified in this mapping review sampled students
(both K-12 and higher education) and not professionals or amateur musicians. Professional and
amateur musicians are also at high risk for developing occupation-related ailments. A systematic
review of the prevalence of musculoskeletal complaints in professional musicians found a 12-
month prevalence between 41-93% and a lifetime prevalence between 62-93% (Kok et al.,
2016). Amateur musicians have also reported musculoskeletal complaints, with high risk for

45
performance-related musculoskeletal disorder (Ajidahun et al., 2017; Kok et al., 2016).
Furthermore, musculoskeletal complaints have been found to be associated with depression in
professional musicians (Kenny & Ackermann, 2015). While musculoskeletal complaints are the
most studied occupational disease in professional musicians, performance anxiety has also been
reported in professional musicians (Kenny, 2005; Kenny et al., 2004; Sousa et al., 2016). Given
the high occupational risks of professional and amateur musicians, there is a need for more
intervention studies on these subgroups of musicians. The lack of intervention studies identified
in this review may partly be due to the logistic difficulty of conducting an intervention study
with professional musicians of varied work systems, compared to the feasibility of accessing
university students through program faculty and staff members. However, solely conducting
intervention studies on music students affects the generalizability of intervention studies on
professional and amateur musicians. Echoing calls from a previous literature review, there is a
need for more intervention studies of more varied subgroups of musicians based on risk factors
identified by the literature (Stanhope et al., 2019).
Finally, there has been a call for more studies on well-being determinants that are
actionable, modifiable factors to develop health promotion and injury prevention interventions.
In both this review and a recent systematic review on injury prevention in musicians, the
majority of studies focused on musician continuum factors (Stanhope et al., 2020). Within injury
prevention literature, there is a lack of studies on factors identified by musicians to be
determinants of musculoskeletal pain, such as posture and positioning, technique, manual tasks,
structure and duration of musical activities, and sleep (Stanhope, 2019). Additionally, a
systematic review found that the majority of musician health literature focused on the musician’s
musculoskeletal health and function, with few studies on the intersection biopsychosocial factors

46
or the environmental factors (Guptill, 2008). Similarly, within this mapping review, there was a
notable lack of studies on modifiable factors, especially within the EMP constructs of interface
effectors and physical environment. More studies in these areas can help illuminate well-being
determinants that can inform policy and interventions to better support musician well-being.
A limitation of this review was that any study that did not explicitly state investigation of
general well-being in the abstract was excluded from the full-text analysis. While this was done
to avoid studies exclusively on physical health or mental health, some articles that studied
general well-being may have been excluded. Additionally, unlike a systematic review or metaanalysis, this mapping review was intended to create a topography of existing literature and did
not assess article quality or complete a full synthesis of findings across included articles. It is
important to note that previous literature reviews on musician health have found that the
generally poor quality of studies impedes the conclusiveness of findings (Baadjou et al., 2016;
Stanhope et al., 2020). While this review provides insight into the distribution of studies across
various well-being determinants, further study needs to be conducted on both the results of the
studies and rigor of research methods to understand the association of well-being determinants
on musician well-being. However, the high prevalence of cross-sectional studies in this review
demonstrates a need for stronger evidence, both through longitudinal observational studies and
intervention studies. Additionally, one limitation of the findings of this study was the high
prevalence of studies from Europe. The lifestyle and well-being experiences may differ
significantly across musicians in different continents, and findings from this study may not be
generalizable to all continents. Finally, only articles with full texts in English were included for
analysis. This may have affected results as manuscripts that weren’t translated to English or
unavailable to the PI were excluded.

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2.5 Conclusion
This review was the first to map out musician health literature with a focus on general
well-being. A plethora of reviews have been conducted on specific areas of health, such as injury
prevalence, injury prevention, or performance anxiety (Amaral Corrêa et al., 2018; Baadjou et
al., 2016; Betzl et al., 2020; Boocock et al., 2007; Bragge et al., 2006; Cardoso et al., 2019; Chi
et al., 2020; Kenny, 2005; Kochem & Silva, 2018; Kok, Huisstede, et al., 2016; Moraes &
Antunes, 2012; Stanhope et al., 2020; Stanhope et al., 2019; Wu, 2007; Zaza, 1998). However,
the majority of reviews conducted have focused on musculoskeletal injury, reflecting a trend
within musician health literature of studying injury prevention rather than supporting the holistic
well-being of musicians. Recently, research has begun to uncover that factors outside of the
physical strain of music-making, such as stress, impact both musculoskeletal health and overall
well-being in musicians (Jacukowicz, 2016). While the EMP Model proposes a more holistic
approach to understanding musician well-being, this review demonstrated that many crucial
well-being determinants highlighted by the model are not currently studied within musician
health research. Additionally, potential well-being determinants to add to the model were
identified through existing well-being studies (i.e., sleep and social support). Findings from this
study can be used to inform specific musician populations, well-being constructs, and study
designs that are currently lacking in the musician well-being research.

48
2.6 References
Ajidahun, A. T., Mudzi, W., Myezwa, H., & Wood, W.-A. (2017). Musculoskeletal problems
among string instrumentalists in South Africa. South African Journal of Physiotherapy,
73(1), 1-7. https://doi.org/10.4102/sajp.v73i1.327
Amaral Corrêa, L., Teixeira dos Santos, L., Nogueira Paranhos, E. N., Minetti Albertini, A. I., do
Carmo Silva Parreira, P., Calazans Nogueira, L. A., Amaral Corrêa, L., Nogueira
Paranhos, E. N., Jr., & do Carmo Silva Parreira, P. (2018). Prevalence and Risk Factors
for Musculoskeletal Pain in Keyboard Musicians: A Systematic Review. PM & R:
Journal of Injury, Function & Rehabilitation, 10(9), 942-950.
https://doi.org/10.1016/j.pmrj.2018.04.001
Araújo, L. S., Wasley, D., Perkins, R., Atkins, L., Redding, E., Ginsborg, J., & Williamon, A.
(2017). Fit to perform: an investigation of higher education music students’ perceptions,
attitudes, and behaviors toward health. Frontiers in Psychology, 8, 1558.
https://doi.org/10.3389/fpsyg.2017.01558
Baadjou, V. A. E., Roussel, N. A., Verbunt, J., Smeets, R., & de Bie, R. A. (2016). Systematic
review: risk factors for musculoskeletal disorders in musicians. Occup Med (Lond),
66(8), 614-622. https://doi.org/10.1093/occmed/kqw052
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CHAPTER 3 National Musician Well-being Survey
3.1 Introduction
Musicians are under immense pressure to perform at very high levels both physically and
psychologically. As a result, many musicians develop health impairments related to their
occupation (Kenny et al., 2004). In the past three decades, a plethora of studies have been
published on musician health, especially pertaining to playing-related musculoskeletal disorders
and music performance anxiety (Stanek et al., 2017). Various factors relating to musicians’ wellbeing have been explored. The physical demands of instrument playing (Kok, Huisstede, et al.,
2016), occupational demands (Willis et al., 2019), interpersonal relationships (Dobson, 2011),
and intrapersonal demands (Kenny et al., 2004) have all been identified as potential facilitators
and barriers to musician well-being. However, a systematic review of performing artist wellbeing found a lack of theoretically informed study designs, as well as a prevalence of studies
using outcome measures that did not align with theoretical frameworks or demonstrate reliability
and validity (Willis et al., 2019). Both shortcomings have limited the field and development of
evidence-based interventions. Additionally, due to the lack of a validated musician well-being
framework to understand the complex factors that contribute to well-being in musicians,
frameworks from musician-adjacent populations, such as athletes, are currently functioning as
primary theoretical foundations within musician health literature (Willis et al., 2019).
Despite the multitude of musician well-being studies, there is a lack of theoretical
understanding of musician well-being as a unique phenomenon. However, while there are no
validated frameworks to understand student musician well-being, the Ecology of Musical
Performance (EMP) Model was recently developed to understand and more effectively treat

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musicians with a performance-related musculoskeletal disorder (Bastepe-Gray et al., 2021). The
model considers many factors unique to musicians that may contribute to well-being outcomes.
However, the model was based on one case study and has yet to be applied in a quantitative
study. Additionally, as it was developed by clinicians, there is limited understanding of musician
stakeholders’ perception of determinants of their own well-being.
In this study, using the EMP Model as a foundational framework, music students in
higher education programs were surveyed to gain a broad understanding of their experiences and
perceptions of well-being determinants and outcomes. Music students in higher education are at
the nexus between student and professional. During this time of transition, musicians have been
found to be at higher risk of developing performance-related health ailments (Spahn et al., 2002).
Studies have demonstrated that music students have low awareness of health behaviors (Britsch,
2005). There is a need for evidence-based measures for student musicians to develop healthpromoting habits and sustain healthy, long careers (Clark & Lisboa, 2013). In this study, music
students’ satisfaction, perceived importance, and quality rating of well-being determinants
identified by the EMP Model were examined and analyzed with various well-being outcomes.
This study contributes to existing knowledge by:
1) Examining student musicians’ perception and experiences of various well-being
contributors
2) Empirically explore the application of the EMP Model with music students

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3.2 Methods
3.2.1 Study Design
To understand broad trends in musician well-being, a national survey was disseminated
to collegiate music students with items on various well-being contributors and outcomes. The
survey was open from April 10, 2023, for Spring semester data collection. After the initial data
collection efforts during the Spring semester, a secondary round of recruitment emails was sent
during the following Fall semester to personnel from university programs with no student
responses during the initial data collection. The survey was closed on October 31, 2023.
Approval was obtained from the University of Southern California’s Institutional Review Board
before all study activities. Students were provided with an information sheet at the beginning of
the survey where they indicated their consent through a check box at the end of the document. A
download link was provided for participants to save the study information sheet.
3.2.2 Subjects and Recruitment
Students 18 and over who were actively enrolled (part-time or full-time) in a higher
education institution, majoring in music performance during the time of data collection, were
eligible for the study. Students in related fields without a focus on performance were excluded
from participating (e.g., music education, music history, music theory, music production). A
multiple recruitment approach was used. First, to identify music programs in the U.S., a Google
search of “Top higher education music programs in the U.S.” was conducted using incognito
mode to minimize potential search bias due to user-based data algorithms. A list of music
programs was developed using the first 15 websites with lists from the Google search. Music

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programs that were mentioned in at least two websites were included, for a total of 52 programs.
Next, suitable relevant personnel from each program (e.g., well-being instructor, student affairs
director, undergraduate/graduate program director) were identified and contacted via email. The
email provided information on the study and asked the personnel to disseminate the survey and
study information to university music students. Furthermore, snowball sampling was encouraged
by providing study participants with a shareable link of the survey and asking respondents to
disseminate the survey to peers at the end of the survey.
The survey was primarily anonymous, with a unique study ID assigned to each response.
After completion of the survey, respondents were given the option to opt in for follow-up study
by sharing their name and contact email. Respondents were also given the option to enter a raffle
to win one of five $50 gift cards by providing email addresses to receive the gift card
electronically. Students were not required to consent to secondary data collection to enter the gift
card raffle. A study ID was linked to contact information for respondents who expressed interest
in follow-up study, and contact information was stored separately on a secure hard drive.
Respondents who only expressed desire to enter the raffle did not have their contact information
linked to their study ID, and all analyses on their survey data were conducted anonymously.
3.2.3 Survey Components
Data was collected through a cross-sectional survey conducted on Qualtrics (Appendix
A). Screening questions were used to identify respondents who met all four inclusion criteria
(e.g., current enrollment in a higher education program, concentration in music performance,
playing a musical instrument, and at least 18 years of age). Respondents who responded “no” to
any of the screening questions were excluded and directed to the end of the survey. The

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questionnaire used a variety of questions to obtain demographic data, explore well-being
contributors, and examine well-being outcomes. A description of survey items is provided
below, and all items are listed in chronological order in Table 3.1.
Demographic Data. Demographic descriptive information was collected through a series
of multiple-choice and free text questions (e.g., age, gender, race, ethnicity). Career descriptors
of institution of study, primary musical instrument, primary musical genre, major and degree
pursued, and year in program were collected through a series of multiple-choice and free text
questions.
Well-being Contributors. Respondents rated their perception and experiences of various
well-being contributors, identified through the EMP model. Through a series of Likert-type
scales (0-10 scale), respondents rated the importance of each item to their general well-being, the
quality of the item, and their satisfaction with the current state of the item. Closely following the
EMP model, questions covered five well-being determinant model constructs of musician
continuum, interface effectors, peripheral variables, physical environment, and musical work
schedule.
Well-being Outcomes. Five well-being constructs of positive emotion, engagement,
relationships, meaning, and accomplishment were measured using the PERMA-Profiler
(Seligman, 2011). The scale consists of three questions each on the five constructs of the model
for a total of 15 Likert-type questions (0-10 scale), and one additional happiness item. The mean
score of three items was calculated to represent scores for each subcomponent, and the mean of
all 15 items represents an overall well-being score. Following literature recommendation, an
added happiness item of the score was not included as it is not theoretically or empirically
supported by the original PERMA model (Bartholomaeus et al., 2020). Additional general

59
physical and mental health questions were placed at the beginning of the survey. For each health
realm, three follow-up questions were asked on general quality, satisfaction, and comparison
with peers on a scale of 0 to 10 (0=not at all/terrible, 10=completely/excellent). At the end of the
study, an open-ended question was asked for respondents to reflect on any remaining major
contributors to well-being that were not included in the survey.
Table 3.1. Survey construction
Module Variable Items Type/range of scale
Demographics Personal demographic Age, gender, race/ethnicity, Fill in the blank/
Select all that apply
Career descriptors Primary musical instrument, genre of
music, degree pursued, year of study,
educational institution
Fill in the blank/
Multiple choice
General Health Physical health Quality, satisfaction, comparison with
peers
Likert Scale
Mental health Quality, satisfaction, comparison with
peers
Likert Scale
Musician
Continuum
Musculoskeletal dimension &
function
Musculoskeletal health, auditory
health, motor function, cognitive
perceptual function, posture
Likert Scale
Psychosocial dimension Stress management, performance
anxiety management
Likert Scale
Interface
effectors
Repertoire demands Technical difficulty, endurance
demands, mental load of repertoire
Likert Scale
Mechanical demands of the
instrument
Instrument demands Likert Scale
Peripheral
variables
Non-musical occupations School, employment, and leisure
activities
Likert Scale
Physical
environment
General physical environment University and Living space
environment
Likert Scale
Practice space environment Temperature, noise, and lighting in
practice spaces
Musical work
schedule
Performances Frequency and difficulty of
performances
Likert Scale
Practice and Rehearsals Solo practice, mental practice, practice
breaks, ensemble rehearsal
Likert Scale

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Well-being PERMA-Profiler (Butler &
Kern, 2016)
Positive emotion, engagement,
relationships, meaning, and
accomplishment
Likert Scale
3.2.4 Data Management & Analysis
3.2.4.1 Data Screening
All data were screened to determine the final sample. Beyond the four screening
questions, further screening was conducted manually to identify respondents who did not meet
inclusion criteria of being an active instrumental music student in a performance-based program
in the U.S. Incomplete responses were sorted to determine the point of attrition in the survey. All
responses that did not complete the very first general health section were excluded from all
analyses. With all remaining incomplete responses, sensitivity analyses were conducted to assess
for attrition bias by comparison with fully complete data.
3.2.4.2 Multiple Imputation Analysis
Due to the high attrition in survey completion, using listwise deletion of the remaining
incomplete responses would lead to a loss of 36.7% of the total responses. The high amount of
loss leaves the data very vulnerable to attrition bias. Consequently, multiple imputation analyses
were used to generate complete data sets that estimate population parameter estimates. Three
datasets were created using the outcome variables of physical health, mental health, and PERMA
composite score. Ten datasets were imputed for each dataset and regression modeling was
conducted with each outcome variable. Parameter estimates were then pooled to generate
associations of each independent variable to the outcome variables. Categorical variables were
dummy coded based on distribution patterns and composite scores were created for each EMP
construct for multiple imputation and regression analyses due to the high number of survey items

61
and relatively small sample size. Details on variables and multiple imputation analyses can be
found in Appendix B.
3.2.4.3 Data Analysis
Data were analyzed using Microsoft Excel and SAS software (Statistical Analysis
Software Version 9.4 Cary, NC, USA). Personal demographic data of age, gender,
race/ethnicity, and height/weight, as well as career descriptive data of primary instrument, year
in program, major, and musical genre were descriptively analyzed using means and standard
deviation or frequencies and percentages across the full sample. Satisfaction, importance, quality
ratings for each well-being contributor and well-being outcome variables were summarized using
mean, standard deviation, and range of values.
The associations of well-being contributor variables and well-being outcomes were
examined using multiple linear regression analyses with the imputed datasets. Due to the high
number of survey items and relatively small sample size in comparison, demographic and
descriptor variables were dummy coded for multiple selection categorical variables. Categories
with inadequate representation were not added as an independent variable. Well-being
contributor variables were condensed into five EMP composite scores using the model constructs
of Musician Continuum, Peripheral Variables, Physical Environment, Interface Effectors, and
Musician Work Schedule. Out of the three items within each variable (quality rating, satisfaction,
and importance), only quality rating on a Likert scale, “How would you rate your current status
in _____? (0=poor, 10=excellent)”, was included. Composite scores were created as a simple
mean score across the EMP construct items. Further details on the model’s independent variables
can be found in Appendix B.

62
Three models were created using outcome variables of general physical health, general
mental health, and composite general well-being PERMA score (mean score of 15 PERMAProfiler items). In the regression models, a p<0.05 threshold was used to determine a statistically
significant association. No adjustment was made to the p value despite the multiple comparisons
as this was an exploratory analysis. Additionally, no r-square value was reported for the final
three regression models due to the use of multiple imputation analysis and pooled regression
results. No associational analyses of the PERMA-Profiler’s five individual subcomponents with
satisfaction were conducted, as psychometric studies of the scale has only demonstrated
reliability and validity of the general well-being score, and factor loadings of the five
subcomponents have been inconsistent (Bartholomaeus et al., 2020).
3.3 Results
3.3.1 Sample Description
A total of 332 survey responses were collected. 43 respondents did not meet the inclusion
criteria and were directed to the end of the survey. An additional 42 responses were manually
identified as not having met the inclusion criteria of being in instrumental music performance
programs; 51 did not progress beyond the first section of the survey and were excluded from all
analyses. A total of 196 responses (n=124 complete, n=72 incomplete) were included in the final
analysis (see Figure 3.1. Survey Drop-off Flowchart). The 72 incomplete responses were
categorized into 6 groups by percent of survey completion for further analysis. To determine bias
due to survey drop-off, sensitivity analyses were conducted between the 124 complete and 72
incomplete responses (Table 3.2). No statistically significant differences were noted within
demographics and musician descriptives with exception of musical genre (χ2=6.7, p=0.04).

63
However, the difference was not meaningful due to a skewed distribution of musical genres
represented in the sample.
The majority of respondents were white (n=131, 67%) and non-Hispanic (n=157, 80%).
30% of respondents were Asian (n=58) and only 5% (n=10) and 3% (n=5) of respondents were
Black and American Indian/Alaska Native respectively. The majority of respondents identified
their gender as a woman (n=119, 61%) or a man (n=61, 31%). 8% of respondents identified as
either agender, gender queer/genderfluid, non-binary, or prefer not to disclose (n=16). Most
respondents were undergraduate students (n=115, 59%) and the average age was 22 years
(x̄=22.4, s=5.1). Other degrees pursued included masters (n=47, 24%), Doctorate of Musical Arts
(n=20, 10%), and PhD (n=4, 2%). The most common instrument group represented in the sample
was string players (n=71, 36%). Other common instrument groups were brass (n=34, 17%),
keyboard (n=26, 13%), and woodwind (n=30, 15%). Only 4% of respondents were percussion
players (n=8). Most respondents were Classical musicians (n=155, 79%). Other musical genres
included Jazz (n=16, 8%), Contemporary (n=9, 5%), Electronic (n=5, 2.6), and Baroque (n=3,
2%).

64

Survey Sample
Survey responses received:
(n=332)
Responses removed due
embedded four screening
questions:
(n=43)
Responses screened post-hoc:
(n=289)
Responses manually excluded
due to exclusion criteria (nonperformance major)
(n=42)
Responses screened for
completion
(n=247)
Responses partially complete
(n=123)
Incomplete Responses (n=72):
Demographics & general health (n=16)
EMP Musician Continuum (n=6)
EMP Peripheral variables (n=16)
EMP Physical environment (n=15)
EMP Interface effectors (n=10)
EMP Musical work schedule (n=9)
PERMA Well-being Outcome
(n=124)
Total Received Manual Screening Analyzed
Studies included for full analysis
(n=196)
Responses
excluded for
no data:
(n=51)
Figure 3.1 Survey drop-off flowchart

65
Table 3.2 Distribution and comparison of incomplete and complete respondent
demographics, descriptive factors, and general health outcome variables
Incomplete (n=72)
Mean (SD) or
Frequency (%)
Complete
(n=124)
Mean (SD) or
Frequency (%)
T or X
2
value
P value
DEMOGRAPHIC VARIABLES
Age 22.6 (5.7) 22.4 (4.7) 0.29 0.775
Gender identity (man/woman/other) 1.21 0.545
Man 19 (26.4) 42 (33.9)
Woman 47 (65.3) 72 (58.1)
Other 6 (8.3) 10 (8.1)
Race (white/Asian/other) 0.592 0.744
Asian 14 (19.4) 30 (24.2)
White 43 (59.7) 70 (56.5)
Other 15 (20.8) 24 (19.4)
Ethnicity 2.4 0.319
Hispanic 13 (18.1) 13 (10.5)
Non-Hispanic 54 (75) 103 (83.1)
Prefer not to answer 5 (6.9) 8 (6.5)
Instrument Group
(brass/keyboard/percussion/string/woodwind)
2.058 0.725
Brass 13 (18.1) 21 (16.9)
Keyboard 7 (9.7) 19 (15.3)
Percussion 3 (4.2) 5 (4.0)
String 23 (31.9) 48 (38.7)
Woodwind 7 (9.7) 23 (18.6)
Other 19 (26.4) 8 (6.5)
Musical Genre (Classical/jazz/other) 6.7 0.035
Classical 52 (72.2) 103 (83.1)
Jazz 5 (6.9) 11 (8.9)
Other 15 (20.8) 10 (8.1)
Degree (undergrad/grad/doctorate/other) 2.0 0.579
Undergraduate 46 (63.9) 69 (55.7)
Masters 14 (19.4) 33 (26.6)
DMA 8 (11.1) 12 (9.7)
PhD 0 (0) 4 (3.2)
Other 4 (5.6) 6 (4.8)
Year of study 2.4 (1.3) 2.2 (1.1) 1.14 0.257
OUTCOME VARIABLES
Physical health rating 6.4 (1.6) 7 (1.7) -2.59 0.01
Physical health satisfaction 5 (2.3) 5.9 (2.3) -2.48 0.014
Physical health comparison 6.2 (2.1) 6.6 (2.1) -1.31 0.191
Mental health rating 5.3 (2.1) 6 (2) -2.2 0.029
Mental health satisfaction 4.7 (2.6) 5.5 (2.5) -2.02 0.044
Mental health comparison 5.7 (2.5) 6.2 (2.5) -1.33 0.184

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3.3.2 Distribution of Well-being Contributors and Outcomes
Distributions of satisfaction, importance, and quality ratings of each well-being
contributor are in Table 3.3. Apart from auditory health, respondents used the full range of the
Likert scales for each item. No respondents rated auditory health as less important than 4 out of
10, with a mean importance rating of 9.3. Many musician continuum factors were rated high in
both satisfaction and importance to general well-being. Auditory health, cognitive perceptual
function, and motor function mean satisfaction ratings were at least 7.6 and mean importance
ratings were at least 8.1. In contrast, musician continuum items of management of stress and
performance anxiety were some of the lowest rated items in both satisfaction and quality. Both
stress and performance anxiety management were rated as highly important well-being
contributors (mean of 8.8 and 7.6 respectively). Amongst all well-being contributors, most of the
lowest importance ratings were peripheral variable and musical work schedule items. Other than
practice breaks and solo practice sessions, all other musical work schedule items had mean
importance ratings between 6.0 and 6.8. Satisfaction in musical work schedule items were also
low, with mean scores between 5.2 and 6.9. Peripheral variables (i.e., non-music related school,
leisure, and paid activities) were rated low satisfaction, importance, and quality, except for
leisure being an important well-being contributor (M=7.9, s=2.3).
General physical and mental health outcome variables each contained three questions of
satisfaction, comparison with peers, and general quality rating. Responses to both satisfaction
with and comparison with peers encompassed the full range of the scale. However, with the
health quality rating, the lowest physical health was 3 and the lowest mental health was 1. In
both physical and mental health outcomes, satisfaction and quality ratings were statistically
significantly lower in the incomplete responses (n=72) compared to the complete responses

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(n=124) (p<0.05). The average physical health score was 1.6 lower (pooled t=-2.59, p=0.01) and
average mental health score was 0.9 lower (pooled t=-2.48, p=0.01) on a 0-10 Likert-type scale
in incomplete respondents. Similarly, satisfaction with physical health was 0.7 lower (pooled t=-
2.2, p=0.03) and satisfaction with mental health was 0.8 lower (pooled t=-2.02, p=0.04) in
incomplete respondents. Further details on distribution differences of physical and mental health
are in Table 3.4.
Following PERMA-Profiler guidelines, 15 PERMA items were averaged to create five
subcomponent scores (3 items per PERMA construct). The distribution of the five sub scores had
slight variation. Positive emotion, engagement, relationships, and accomplishment had a
unimodal distribution with positive skew, with mean scores ranging from 6.1 to 7 (Figure 3.2).
Meaning was the only subcomponent with a bimodal distribution. Due to the limitations of three
items per subscale and the smaller sample size of PERMA data, no additional analysis was
conducted on PERMA subscale distribution. Following PERMA-Profiler guidelines, the
PERMA outcome variable for regression analysis was created using an average of all 15 items.
Additional details on well-being outcome distribution can be found in Table 3.4.

68
Satisfaction Importance Quality/Ability to meet demands
EMP Model Variable N Mean s min max N Mean s min max N Mean s min max
Musician
Continuum
Auditory Health 178 7.7 2.2 1 10 179 9.3 1.2 4 10 179 8.1 1.6 3 10
Musculoskeletal Health 180 5.8 2.7 0 10 180 8.4 1.9 0 10 180 6.4 2.4 0 10
Posture 179 5.4 2.7 0 10 179 8.1 1.9 0 10 179 6.3 2.2 0 10
Motor Function 178 7.6 2.3 0 10 178 8.9 1.6 0 10 178 8.3 1.7 0 10
Cognitive Perceptual Function 178 7.7 2.1 0 10 178 8.5 1.9 0 10 178 8.1 1.8 0 10
Stress Management 178 5.1 2.6 0 10 178 8.8 1.6 0 10 178 5.9 2.2 0 10
Performance Anxiety 178 4.9 3.0 0 10 177 7.6 2.6 0 10 177 6.1 2.6 0 10
Peripheral
Variables
Non-musical School Activities 171 5.5 2.9 0 10 173 6.2 2.7 0 10 173 5.1 2.9 0 10
Non-musical Paid Activities 73 6.7 2.3 0 10 73 6.2 2.7 0 10 74 6.7 2.1 0 10
Non-musical Leisure Activities 172 5.5 2.7 0 10 174 7.9 2.3 0 10 172 5.8 2.3 0 10
Physical
Environment
Practice Space Temperature 159 6.9 2.5 1 10 159 7.4 2.3 0 10 159 7.0 2.2 1 10
University Environment 158 6.8 2.7 0 10 158 7.3 2.2 0 10 158 7.0 2.3 0 10
Living Space Environment 158 7.2 2.4 0 10 158 8.7 1.7 2 10 158 7.4 2.0 0 10
Practice Space Noise 158 7.2 2.5 0 10 158 7.6 2.5 0 10 158 7.1 2.3 0 10
Practice Space Lighting 158 7.7 2.5 0 10 158 7.3 2.5 1 10 158 7.7 2.3 0 10
Interface
Effector
Instrument Demands 143 7.0 2.5 0 10 143 8.1 2.5 0 10 143 7.9 1.8 0 10
Repertoire Technical Difficulty 143 6.2 2.5 0 10 143 7.1 2.9 0 10 143 7.2 1.9 0 10
Repertoire Endurance Demands 143 6.3 2.8 0 10 143 7.2 2.7 0 10 143 7.0 2.2 0 10
Repertoire Mental Load 143 6.4 2.5 0 10 143 7.7 2.3 0 10 143 7.1 2.1 0 10
Musical Work
Schedule
Frequency of Performances 125 6.2 2.5 0 10 124 6.8 2.5 1 10 125 7.7 2.1 1 10
Practice Physical Repetition 132 6.6 2.2 0 10 132 6.7 2.8 0 10 132 6.9 2.0 0 10
Solo Practice Session 133 5.7 2.6 0 10 133 8.2 2.4 0 10 133 6.5 2.2 0 10
Ensemble Rehearsal 131 6.0 2.9 0 10 132 6.3 3.0 0 10 131 6.5 2.6 0 10
Mental Practice Session 131 5.2 2.9 0 10 132 6.0 3.2 0 10 133 5.7 2.9 0 10
Practice Breaks 133 5.7 2.8 0 10 133 8.2 2.3 0 10 132 5.7 2.6 0 10
Performance Difficulty 125 6.9 2.2 1 10 124 6.5 2.5 0 10 125 7.8 1.9 1 10 Table 3.3. Well-being contributor satisfaction, importance, and quality/ability responses

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Satisfaction Importance Quality/Ability to meet demands
EMP Model Variable N Mean s min max N Mean s min max N Mean s min max
Musician
Continuum
Auditory Health 178 7.7 2.2 1 10 179 9.3 1.2 4 10 179 8.1 1.6 3 10
Musculoskeletal Health 180 5.8 2.7 0 10 180 8.4 1.9 0 10 180 6.4 2.4 0 10
Posture 179 5.4 2.7 0 10 179 8.1 1.9 0 10 179 6.3 2.2 0 10
Motor Function 178 7.6 2.3 0 10 178 8.9 1.6 0 10 178 8.3 1.7 0 10
Cognitive Perceptual Function 178 7.7 2.1 0 10 178 8.5 1.9 0 10 178 8.1 1.8 0 10
Stress Management 178 5.1 2.6 0 10 178 8.8 1.6 0 10 178 5.9 2.2 0 10
Performance Anxiety 178 4.9 3.0 0 10 177 7.6 2.6 0 10 177 6.1 2.6 0 10
Peripheral
Variables
Non-musical School Activities 171 5.5 2.9 0 10 173 6.2 2.7 0 10 173 5.1 2.9 0 10
Non-musical Paid Activities 73 6.7 2.3 0 10 73 6.2 2.7 0 10 74 6.7 2.1 0 10
Non-musical Leisure Activities 172 5.5 2.7 0 10 174 7.9 2.3 0 10 172 5.8 2.3 0 10
Physical
Environment
Practice Space Temperature 159 6.9 2.5 1 10 159 7.4 2.3 0 10 159 7.0 2.2 1 10
University Environment 158 6.8 2.7 0 10 158 7.3 2.2 0 10 158 7.0 2.3 0 10
Living Space Environment 158 7.2 2.4 0 10 158 8.7 1.7 2 10 158 7.4 2.0 0 10
Practice Space Noise 158 7.2 2.5 0 10 158 7.6 2.5 0 10 158 7.1 2.3 0 10
Practice Space Lighting 158 7.7 2.5 0 10 158 7.3 2.5 1 10 158 7.7 2.3 0 10
Interface
Effector
Instrument Demands 143 7.0 2.5 0 10 143 8.1 2.5 0 10 143 7.9 1.8 0 10
Repertoire Technical Difficulty 143 6.2 2.5 0 10 143 7.1 2.9 0 10 143 7.2 1.9 0 10
Repertoire Endurance Demands 143 6.3 2.8 0 10 143 7.2 2.7 0 10 143 7.0 2.2 0 10
Repertoire Mental Load 143 6.4 2.5 0 10 143 7.7 2.3 0 10 143 7.1 2.1 0 10
Musical Work
Schedule
Frequency of Performances 125 6.2 2.5 0 10 124 6.8 2.5 1 10 125 7.7 2.1 1 10
Practice Physical Repetition 132 6.6 2.2 0 10 132 6.7 2.8 0 10 132 6.9 2.0 0 10
Solo Practice Session 133 5.7 2.6 0 10 133 8.2 2.4 0 10 133 6.5 2.2 0 10
Ensemble Rehearsal 131 6.0 2.9 0 10 132 6.3 3.0 0 10 131 6.5 2.6 0 10
Mental Practice Session 131 5.2 2.9 0 10 132 6.0 3.2 0 10 133 5.7 2.9 0 10
Practice Breaks 133 5.7 2.8 0 10 133 8.2 2.3 0 10 132 5.7 2.6 0 10
Performance Difficulty 125 6.9 2.2 1 10 124 6.5 2.5 0 10 125 7.8 1.9 1 10

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Table 3.4. Distribution of well-being outcome variables.
Variable Mean SD Min Max
Physical Health (n=196)
Comparison 6.5 2.1 0 10
Quality 6.8 1.7 3 10
Satisfaction 5.6 2.3 0 10
Mental Health (n=196)
Comparison 6.1 2.5 0 10
Quality 5.8 2.1 1 10
Satisfaction 5.2 2.6 0 10
PERMA Sub Scores
(n=124)
Positive Emotion 6.1 1.8 2 10
Engagement 7.0 1.6 3 10
Relationships 6.9 2.1 1 10
Meaningfulness 7.0 2.0 1 10
Accomplishment 6.7 1.6 2 10

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Positive Emotion
Engagement

72
Relationships
Meaningfulness

73
Accomplishment
Figure 3.2. Distribution of PERMA well-being sub scores (n=124).

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3.3.3 Multiple Linear Regression Analysis
All 196 responses (both the 72 incomplete and 124 complete responses) were included
for regression analysis using multiple imputation analysis to impute missing data. Due to the
differences in outcome variables, three separate linear multiple regression models were created
using multiple imputed data with outcome variables of physical health quality, mental health
quality, and PERMA composite score. Results of the linear multiple regression models were
descriptively compared (Table 3.5), and additional details on differences in outcome variable
and multiple imputation analysis decisions are in Appendix B. Demographic factors of age,
gender, and ethnicity, as well as musician descriptive factors of degree and year in program,
instrument, and musical genre were not significantly correlated with well-being in any of the
three models (p=0.05). Within the physical health model, being Asian was associated with a
higher physical health rating (β=0.76, p=0.01), and within the mental health model, increase in
age was associated with higher mental health rating (β=0.1, p=0.01). Neither race nor age were
significant predictors in any other model.. Within EMP Composite constructs, Musician
Continuum was a significant predictor across all three models (p<0.05). Higher ratings of
Musician Continuum were associated with higher well-being in all three models. Additionally,
high ratings of Musical Work Schedule were associated with higher PERMA scores (β=0.34,
p<0.001).

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Table 3.5. Parameter estimates and significance of regression models with three well-being outcome variables.

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3.4 Discussion
This study was the first study to empirically apply the EMP model. Through multiple
linear regression analysis, musician continuum factors were found to be significantly associated
with well-being for all three well-being outcomes of physical health, mental health, and PERMA.
In all three models, there was a positive correlation between well-being contributors and wellbeing outcome. Musician continuum factors being a strong contributor to well-being is congruent
with respondent ratings of importance to well-being, as many musician continuum factors were
rated high in importance to general well-being. Despite its high importance rating, musician
continuum factors of management of stress and performance anxiety were some of the lowest
rated items in both quality and satisfaction.
Musician well-being literature reflects the finding of musician continuum being a
significant well-being contributor. Posture, musculoskeletal health, and motor function have
been a primary focus of musician health studies, with an emphasis on musculoskeletal injury
prevention and treatment (Stanhope et al., 2020). Injuries affect musicians not just physically,
but can drastically alter daily life and general well-being (Zaza et al., 1998). Musical
performance anxiety has also been identified as an important and critical factor when considering
musician well-being (Kenny & Ackermann, 2015; Kenny, 2005). Some musician health
literature has started to uncover the dynamic interrelationship between performance anxiety and
musculoskeletal health (i.e., dystonia) (Nagel, 2018; Zosso & Schoeb, 2012). Additionally,
auditory health has been identified as an area of concern within musician health, with many
studies on the high prevalence of tinnitus in professional musicians (Hagberg et al., 2005;
Jacukowicz & Wężyk, 2018; Lockwood et al., 2001; Vardonikolaki et al., 2021).

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In this dataset, higher average rating of all musician continuum factors was positively
associated with higher ratings in both physical health and mental health, as well as general wellbeing. However, additional analyses into specific associations are needed to understand how
each musician continuum factor contributes to health and well-being differently. A significant
limitation in this finding is that some musician continuum factors were directly related to
physical health (i.e., musculoskeletal health) or mental health (i.e., stress management). To avoid
priming respondents to respond to physical/mental health based on specific health items within
the musician continuum, the general physical/mental health outcome questions were asked at the
very beginning of the survey. However, further study is needed to verify meaningfulness of
musician continuum findings in the physical and mental health models.
Musical work schedule was also significantly associated with the PERMA well-being
outcome model. Items within the work schedule composite score included practice behaviors,
instrument and performance demands, and ensemble rehearsals. Many prevention efforts have
sought to understand and address the practice behaviors of musicians due to the strong
association between practice and musculoskeletal injury (Gembris et al., 2020; Zaza, 1993).
Additionally, studies have applied worker health models to understand the impact of workrelated factors such as job demands on musician health outcomes (Aalberg et al., 2019; Holst et
al., 2012). However, traditional worker health models may not translate to the musician
population well. Outside of the non-traditional work schedule, studies have found that musicians
do not find that work and non-work are separate entities due to the importance of their work to
their identity and sense of self (Vaag et al., 2014). Additional study is needed to understand the
unique work-related challenges that musicians face and how they impact health and well-being.
Furthermore, with a population like music students in higher education programs, there needs to

78
be a more specific model to understand the musical work schedule demands and associations
with well-being outcomes. Other EMP constructs (peripheral variables, physical environment,
and interface effector) were not significantly associated with any health or well-being outcome.
While this may be indicative of a true lack of association, it also may be due to the smaller
number of items within each construct, some items having contrasting associations, or the items
being too varied for meaningful interpretation.
The EMP model was developed to help clinicians understand the unique needs of
musicians (Bastepe-Gray et al., 2021). Based on clinical expertise and one case study, it is the
first theoretical model to create a holistic model specific to musician needs. Findings from this
study demonstrate the presence of association between model components and well-being
outcomes. Nonetheless, the model may benefit from revision prior to empirical validation. The
model contains five constructs with subcomponents listed within each construct. While this may
provide a foundation to facilitate a clinician’s understanding of a musician, further edits are
needed to apply the model in large scale quantitative study. One roadblock to empirical
validation in its current form is the potential for multiple latent variables within each construct.
For example, within musician continuum, there may be value in separating musculoskeletal
health/posture/motor function performance anxiety/stress management for regression modeling
analysis. Additionally, there is an inconsistent number of items within each construct (i.e.,
peripheral variables construct has fewer items than musician continuum construct), making it
difficult to create a composite score that is statistically sound. Creating a more robust list of
items within each construct and separating some constructs into multiple would help prepare the
model for future empirical validation.

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Limitations to this study were primarily due to the representativeness and size of the
sample. There was a lack of representation of many racial and ethnic minority groups as well as
gender identities. Furthermore, the majority of the sample were Classical musicians, making the
findings not applicable to other types of musicians. The lack of a more robust sample size also
limited the rigor of analysis in many ways. Due to the survey organization, drop-off occurred at
the end of each EMP construct where participants hit “next” on the survey. While the PERMA
outcome variable was strategically placed at the end of the survey, this significantly decreased
the number of respondents who completed the intended primary outcome variable due to dropoff. While statistically significant differences were noted in the PERMA subcomponents, the
linear regression model did not account for these differences due to a limitation of sample size as
well as the number of items within each PERMA subcomponent. Additionally, while there were
significant differences in physical and mental health ratings between the incomplete and
complete responses, the multiple imputation analysis was not weighted to account for these
differences due to the limitation of this being a dissertation study. Finally, the EMP well-being
contributors were averaged for a composite score in the model. However, there were unequal
number of items and differences in distribution of individual EMP items within each construct.
Due to the limitation of the sample size, EMP items could not be added to the model
individually. Future, more robust studies with larger sample size and resources should consider
these differences in distributions when modeling well-being contributors to well-being outcome.
3.5 Conclusion
These data provide valuable insight into music student experiences with various wellbeing contributors using the EMP model as a foundational framework. Musician continuum
factors were significantly associated with well-being in all three models of physical health,

80
mental health, and general well-being through the PERMA-Profiler. Findings and methods of
this study can be used to enhance understanding of musician well-being using the newly
developed EMP model. Future study should investigate potential differences in music student
responses to each PERMA subcomponent and empirically measure individual well-being
contributor items in regression models to better understand specific associations between wellbeing contributors and outcomes.

81
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Bartholomaeus, J. D., Iasiello, M. P., Jarden, A., Burke, K. J., & van Agteren, J. (2020).
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Bastepe-Gray, S., Riley, M. A., Klotchkov, N., Supnekar, J., Filippi, L., & Raghavan, P. (2021).
Ecology of musical performance as a model for evaluation and treatment of a musician
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Britsch, L. (2005). Investigating performance-related problems of young musicians. Medical
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39(2), 240-260. https://doi.org/10.1177/030573561037356
Gembris, H., Menze, J., Heye, A., & Bullerjahn, C. (2020). High-Performing Young Musicians'
Playing-Related Pain. Results of a Large-Scale Study. Front Psychol, 11, 564736.
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Hagberg, M., Thiringer, G., & Brandström, L. (2005). Incidence of tinnitus, impaired hearing
and musculoskeletal disorders among students enrolled in academic music education--a
retrospective cohort study. Int Arch Occup Environ Health, 78(7), 575-583.
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Kok, L. M., Huisstede, B. M., Voorn, V. M., Schoones, J. W., & Nelissen, R. G. (2016). The
occurrence of musculoskeletal complaints among professional musicians: a systematic
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015-1090-6Lockwood, A. H., Salvi, R. J., & Burkard, R. F. (2001). Tinnitus and the
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Zaza, C. (1993). Prevention of musicians' playing-related health problems: rationale and
recommendations for action. Medical Problems of Performing Artists, 8, 117-117.
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disorders to classical musicians. Soc Sci Med, 47(12), 2013-2023.
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CHAPTER 4 Intersection of Daily Activity Patterns and Well-being
in Music Students
4.1 Introduction
While participation in music has been shown to contribute to positive psychological wellbeing in the general population, a variety of factors in the occupation of professional musicmaking create complexities in understanding well-being among musicians. To become better
performing artists, musicians spend a lot of time and energy practicing, rehearsing, and
performing. Many musician well-being studies have used a job demands-resources model to
conceptualize engaging in music as protective against the numerous occupational demands of the
career (Willis et al., 2019). Music-making as an occupation has been reported to be a resource
that increases job satisfaction and positively impacts well-being (Ascenso et al., 2017; Brodsky,
2006). However, excessive amounts of occupational participation can become a risk factor for
health issues such as musculoskeletal disorders (Kok, Haitjema, et al., 2016), and musicians have
been identified as a worker group that is exposed to high occupational stress with negative
physical and mental health consequences (Mäkirintala, 2008).
The physical health and psychological stressors of the occupation of music-making have
been studied in various ways. A large-scale study conducted by the British Association for
Performing Arts Medicine found that 52% of musicians experienced physical health issues due
to poor health behaviors related to music making. Behaviors included excessive practicing, poor
posture, not taking breaks, poor performance techniques, lack of exercise, and other misuse of
the body (Parry, 2003). Professional musicians experience many work-related stressors that
traditional 9-5 employees might not be exposed to, including job insecurity, irregular work

85
hours, and travel demands for performances (Aalberg et al., 2019; Holst et al., 2012).
Additionally, occupational stressors specific to the occupation of music-making, such as noise
exposure, social dynamics of a music group, high-performance demands with low control, and
performance anxiety have been identified (Mäkirintala, 2008; Parasuraman & Purohit, 2000;
Simoens & Tervaniemi, 2013; Kenny et al., 2016).
To address this concern, academic music departments have developed instrument-specific
preventive measures and implemented injury prevention programs, and research studies have
explored interventions that advise musicians to improve posture, take practice breaks, and have a
warm-up/cool-down regimen (Kreutz et al., 2008; Parry, 2004). However, no study to date has
explored how well-being is experienced by musicians through their various occupational
engagements, both within and outside of music-related activities. This gap in knowledge creates
difficulty in translating intervention studies toward health promotion and injury prevention. For
example, exercise programs are among the most studied intervention methods in musician injury
prevention, with studies calling for increased exercise intervention in musicians. However, there
is little evidence to support the injury-preventive or health-promoting factor of exercise
intervention in real-life applications (Stanhope et al., 2020).
Furthermore, within the narrative of musicians at risk due to their occupation of musicmaking, the perspective of the musician is often missing. The occupation that one engages is
understood to be formative to one’s sense of meaning and identity, which have significant
implications for health and well-being (Unruh, 2004). Qualitative studies have begun to explore
the complex relationships and intersections of musicians’ perceptions and experiences with their
careers and the impact on their general health and well-being (Guptill, 2011a, 2012). Health and
music undoubtedly have a strong and complex link, which has been described as a life-long

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learning process that requires trial and error in one phenomenological study (Schoeb & Zosso,
2012). The key to promoting and supporting musician health may lie in a better understanding of
occupational engagement and the intersection of music with well-being in musicians.
To explore such a complex phenomenon as musician well-being, there is a need for more
qualitative research (Manchester, 2011). This chapter outlines the qualitative portion of a mixedmethod study to explore the complex intersection of musicians’ occupational engagement and
well-being experiences. This study aimed to contribute to existing knowledge by:
1) Providing insight into how daily activity engagement impacts well-being in music
students.
2) Gaining direct lived experiences of the intersection of occupational engagement
and well-being in music students.
4.2 Methods.
4.2.1 Study Design Overview
This chapter outlines the qualitative portion of an explanatory sequential mixed-method
study, where quantitative data collection was followed by qualitative data collection to further
elaborate and contextualize quantitative findings (Creswell & Clark, 2017). Details on the
quantitative portion of the study, a national survey of music students, can be found in the
previous chapter. This qualitative portion contained two parts: an activity log and interviews.
First, daily patterns of occupational engagement and feelings of well-being associated with each
activity were investigated. To do this, participants completed a modified Day Reconstruction
Method (DRM) at the end of each day for up to seven days. The DRM is a data collection

87
approach that combines aspects of time-use studies to understand affective experiences. It uses
elements of experience sampling methods that eliminate recall bias through collecting data in
real-time, without the participant burden of periodic sampling in traditional experience sampling
methods (Kahneman et al., 2004). While the DRM has never been used to deeply explore
occupational engagement and well-being experiences of musicians, comparative studies of the
DRM with experience sampling studies have demonstrated that the DRM provides comparable
results without the significant study burden on the participants that real-time data collection can
pose (Dockray et al., 2010; Grube et al., 2008; Stone et al., 2006). Following DRM data
collection, individual interviews were conducted to contextualize and further explore the
intersection of occupational engagement and well-being in music students. Individual DRM
results and trends from the entire sample were discussed using semi-structured individualized
interview guides.
4.2.2 Subjects and Recruitment
Ten respondents who consented to the follow-up study and provided email contact
information from a national survey (Chapter 3) were purposively sampled. The sample selection
was based on the national survey demographics and well-being outcome distribution. Students
playing the two most common primary instruments, piano and violin, were selected (five
students playing each instrument). Due to the high representation of undergraduate students, six
undergraduate and four graduate students were selected. The Chapter 3 well-being outcome of
PERMA was also considered, and variability in PERMA scores was sought when identifying
potential study participants (i.e., low, medium, and high PERMA score representation from each
demographic group). Demographics of the initial recruited sample, although not representative of
the final sample included in the study, can be seen in Table 4.1. When selected participants were

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not successfully recruited to participate in the study, an individual with similar characteristics
was recruited until ten participants were recruited. Recruitment was completed over email using
addresses provided in the national survey. Students who agreed to enroll were provided with an
electronic study information sheet and offered a meeting to discuss study details for questions.
Table 4.1. Intended sample demographics.
Undergraduate
student
Graduate student Total
Piano Low PERMA Score
High PERMA Score
Low PERMA Score
High PERMA Score
4
Violin Low PERMA Score
Medium PERMA Score
High PERMA Score
Low PERMA Score
Medium PERMA Score
High PERMA Score
6
Total 5 5 10
4.2.3 Modified Day Reconstruction Method
Qualtrics XM software was used to conduct DRM data collection. For seven consecutive
days, participants were sent email invitations with a Qualtrics survey link to complete the DRM
daily activity log at 6 PM in their respective time zones. When the survey was not completed, a
reminder email was sent the following day, with an option to reschedule the missed date by
extending the data collection period. This process was repeated until the end of their respective
university semester schedules. Data was collected between November 13 and December 10,
2023. Participants logged their activities throughout the day. For each activity, respondents
provided a brief activity name, start and end time, and a 1-3 sentence explanation of the activity.
The following prompt was given to help recall activities:

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“In this section, recount your day in chronological order from the moment you
woke up until right before you started this survey. Think of your day as a
continuous series of scenes or episodes in a film. Give each episode a brief name
that will help you remember it (for example, "orchestra rehearsal", "individual
practice session", or "eat lunch with friend").
Write down the approximate times at which each episode began and ended. The
episodes people identify usually last between 15 minutes and 2 hours. Indications
of the end of an episode might be going to a different location, ending one activity
and starting another, or a change in the people you are interacting with.
For each episode, provide a 1-3 sentence description (for example, the
description for "Individual practice session" can be described as "Practicing in
university's practice rooms on solo/ensemble repertoire") and rate your wellbeing experiences.”
For every logged activity, outcomes of hedonic and eudemonic well-being were
measured using two questions adopted from the PERMA-Profiler Positive Emotion and
Meaningfulness items (Butler & Kern, 2016); “To what extent did you feel contented/happy
during this episode?” and “To what extent did you find this episode valuable and meaningful?”.
Both questions were on 11-point Likert-type scales (0=not at all, 10=completely). The series of
questions were repeated for every activity engaged in from waking up until the time when they
were taking the survey. When participants indicated they had reported all activities, they were
directed to the end of the survey (see Appendix C for the full Qualtrics survey).
All Qualtrics data were exported to Excel, de-identified, and stored on a secure cloud
server for all analysis. All analyses were conducted on SAS software (Statistical Analysis
Software Version 9.4 Cary, NC, USA). Using the Occupational Therapy Practice Framework-4
(OTPF), activities were coded by the principal investigator (PI) into one of nine categories:
Activities of Daily Living, Instrumental Activities of Daily Living, Health Management, Work,
Education, Social Participation, Play, Rest and Sleep, and Leisure (Occupational therapy
practice framework: Domain and Process- Fourth Edition, 2020). All music-related activities,

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even those directly related to university program requirements, were categorized as “Music
Education”.
For each participant, the frequency and durations of activities engaged in across the week
were reported and displayed visually using tables and histograms. Trends in hedonic and
eudemonic well-being were visualized graphically within and between individuals across dates
and types of activity. An Activity Pattern Visual was created to visualize associations of
activities and feelings of well-being. The visual used all days of data for each individual to create
a scatterplot with four quadrants. The horizontal axis represented hedonic well-being, and the
vertical axis represented eudemonic well-being. Dots representing each reported activity were
placed on the four quadrants representing the associated eudemonic and hedonic well-being. The
color of the dots represented different OTPF activity categories, and the dot size was determined
by the duration of activity (i.e., a smaller dot is shorter duration, a larger dot is longer duration).
This visual was prepared to discuss DRM results during the individual follow-up interviews.
4.2.4 Semi-structured Interviews
Every participant was interviewed one-on-one using a semi-structured guide to
contextualize DRM findings and more deeply explore student musicians’ lived experiences of
well-being. The principal investigator scheduled all interviews via email and conducted them
over Zoom for up to 60 minutes. All interviews were conducted between February 12 and 21,
2024. Interviews were audio recorded and stored on a secure cloud server using Zoom’s
recording function, and interviews were transcribed using Zoom’s transcription software.
Preceding and following each interview, the PI took notes on positionality as well as general
takeaways and important findings from the interview. These notes were used as the primary

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qualitative data source for the interpretation and contextualization of the DRM data—that is,
interview analyses were limited to reflexive notes for the purposes of this report. An in-depth
qualitative analysis of interview transcripts is planned as a future manuscript beyond the scope of
this dissertation.
The interview consisted of two parts. In the first half of the interview, general
perspectives and experiences with well-being were discussed. The interview was opened with a
discussion of defining well-being and individual experiences of low and high well-being, as well
as common well-being contributors. The identities of being a student and musician and the
intersection of those identities with well-being were also discussed. Then, during the second half
of the interview, PowerPoint slides were shared to discuss individual DRM data. The interviewer
briefly oriented participants to nine activity categories from the OTPF. Then, participants were
shown their activities categorized using the OTPF and prompted to modify the category of each
activity if they desired. All musical activities were initially uncategorized, and participants were
asked to categorize these activities into one of the OTPF categories. Finally, their individual
Activity Pattern Visual, a scatterplot of their activities on a two-scale graph (contentment and
meaningfulness during each activity), was shared to discuss any patterns, surprises, or other
general takeaways.
4.2.5 Investigator Positionality
All interviews were conducted and interpreted solely by the PI. The results reported here
are based on the PI’s notes immediately after the interviews. Transcripts, which were only used
as cross-reference, were developed through Zoom and checked using the audio recording by a
research assistant. As an occupational therapist, the PI’s approach to the interview was informed

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by occupational perspectives and clinical training. Additionally, the PI has personal experience
with being a music major and has a history of a performance-related musculoskeletal disorder
during her time as a music student. Prior to conducting interviews, the PI wrote her own
perceived perspectives and biases about the topic and population to be aware of the biases and as
much as possible, avoid confirmation bias during the interviews (Finlay, 2002).
4.3 Results
4.3.1 Sample Description
Due to non-response or inability to complete the multiple DRM surveys, only eight
participants of the intended sample size of ten were included in the final analysis. DRM data was
collected for a full week from seven participants and six days from one participant. Due to
scheduling or nonresponse, the final sample distribution differed slightly from the intended
demographics (Table 4.2). Five undergraduate and 3 graduate students were included in the final
sample, with three pianists and five violinists. The gender identity of participants was
predominantly woman, with one man and one non-binary participant. Six participants were
music performance majors and two were musicology majors, with two undergraduate
respondents who also had a secondary major/minor outside of their music degrees.
Table 4.2. Sample demographics.
Demographics Frequency or Mean (s)
Age 21.1 (3.2)
Gender
Man 1
Non-binary 1
Woman 6
Race
Asian 3
White 3
Other 2
Primary Instrument

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Piano 3
Violin 5
University Program
Undergraduate 5
Graduate 3
Year of Study
Undergraduate – 1
st 3
Undergraduate – 2
nd 0
Undergraduate – 3
rd 1
Undergraduate – 4
th 1
Graduate – 1
st 1
Graduate – 2
nd 2
Majors
Piano/Violin Performance 6
Musicology/Ethnomusicology 2
Other Majors/Minors
Biology 1
Neuroscience 1
4.3.2 DRM Results
The total number of activities reported by each individual ranged from 23 to 68, with the
number of activities per day ranging from 3 to 14 across all participants. Some participants
reported fewer activities on average than others. No differences were noted in the number of
activities reported between weekdays and weekends. See Figure 4.1 for more details on the
number of activities reported by each participant by day of the week.
Participants used the full range of Likert scales to report hedonic and eudemonic wellbeing (0-10). Across all participants, the average hedonic rating was 7.0 (SD = 2.2) and average
eudemonic well-being was 7.2 (SD = 2.5). Within individual, the average hedonic well-being
ranged from 5.1-8.2, and average eudemonic well-being ranged from 5.1-8.7. Eudemonic and
hedonic well-being were highly correlated for seven of eight participants (p<0.05), with one
participant whose hedonic and eudemonic well-being were not significantly correlated (Pearson

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r=0.26, p=0.06). See Table 4.3 for further details on correlations within individual of hedonic
and eudemonic well-being.
Figure 4.1. Number of activities reported each day by 8 participants.
Table 4.3. Within individual correlation of hedonic and eudemonic well-being.
Participant
ID N
Happiness
Mean (SD)
Meaningfulness
Mean (SD)
Pearson
correlation p value
1 34 5.1 (1.8) 5.1 (1.9) 0.94 <.01
2 23 5.9 (1.2) 5.7 (2.0) 0.51 0.01
3 56 6.6 (1.6) 7.3 (1.6) 0.26 0.06
4 45 8.2 (2.6) 7.3 (3.6) 0.64 <0.01
5 68 7.9 (1.9) 7.8 (2.2) 0.84 <0.01
6 45 7.8 (1.8) 8.7 (2.1)
0.81 <0.01
7 38 7.5 (1.9) 7.7 (2.1) 0.83 <0.01
8 32 5.5 (1.6) 6.0 (2.1) 0.53 <0.01
Activity categories that were present for all 8 participants were IADLs, musical
education, and education (see Appendix C for full list of activities within each OTPF category).
IADLs were commonly reported, ranging from housekeeping tasks to commuting and managing
0
2
4
6
8
10
12
14
16
1
(Total
n=34)
2
(Total
n=23)
3
(Total
n=56)
4
(Total
n=45)
5
(Total
n=68)
6
(Total
n=45)
7
(Total
n=38)
8
(Total
n=32)
Number of Activities Reported
Participant ID
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Sunday

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emergencies. While most participants did not choose to report ADLs, most activities categorized
within ADLs pertained to morning and nighttime routines. Music-related activities of
practice/rehearsal, performance, lessons, and teaching were all categorized as musical education.
Other university activities of attending class, engaging in university clubs, and schoolwork were
categorized as education. Social participation included both in-person and remote social
engagement (i.e., hanging out with roommates, video chatting with family). Work, which
included any paid activity or preparatory activities for employment, was reported by 4 out of 8
participants. Activities within the categories of leisure, rest and sleep, and health management
were only reported by a couple of participants, and no reported activities met the criteria for play.
Hedonic and eudemonic well-being were highly correlated across all nine OTPF
categories (Figure 4.2). Due to the unequal distribution of data across categories, a statistical
comparison of well-being between activity categories was not conducted. Activity Pattern
Graphs, scatterplots that represented the week of activities on two scales of hedonic and
eudemonic well-being for each student, were created to visually display individual activity
patterns for interviews. Although statistical comparisons were not conducted, descriptive
distinctions were noted through the activity pattern graphs. For example, some participants (e.g.,
participant 1) had very strong correlation between hedonic and eudemonic well-being where
most activity bubbles fell on the trend line of an exact same score on the two scales, while others
had more variability (e.g., participant 3 with higher eudemonic ratings and relatively lower
hedonic ratings). Some patterns were able to be discerned within individuals by activity category
as well, such as participant 4 who rated music-related education activities with low hedonic and
eudemonic well-being and all other activities in the upper right quadrant of high hedonic and
eudemonic well-being (see Figure 4.3 for all individual activity pattern graphs).

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Figure 4.2. Boxplot of hedonic and eudemonic well-being distribution across OTPF activity
categories.

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99

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Figure 4.3. Activity pattern visuals mapping out OTPF activity categories on hedonic and
eudemonic scales by participant.
4.3.3 Interview Results
The interviews assisted in contextualizing the types, amounts, and ratings of activities in
the DRM data, which were collected during finals week or the week preceding finals week. The

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end of the semester was a very stressful time for all participants, regardless of their differing
program levels (undergraduate/graduate) or years of study. During the end of the semester, due
to many academic deadlines, students felt that they did not have time for activities that were
meaningful for them. Many had to decrease their musical activities outside of those directly
required by their university programs, which negatively impacted their well-being. The time
constraints also decreased engagement in activities that normally support their well-being, such
as socializing and exercising. Additionally, the end of the semester came with worries about the
future and life after graduating, which increased overall stress. For a couple of participants, the
end of the semester also coincided with the audition season for graduate school, which
compounded stress.
4.3.3.1 Intersection of Daily Activities and Well-being
For all participants, social support was very important and impactful to their well-being.
Many were close to their families and valued the support they received from family members.
Additionally, friends both within and outside of the music program were very important. For
many, during their first year in university as undergraduate students, they felt very overwhelmed
by the high level of playing in other students. Something that helped ease the stress from
comparison with others was feeling supported by music classmates.
Additionally, routine health maintenance activities were mentioned as an important
building block of well-being. With the interviews occurring during the second month of the year,
a couple of participants noted that their New Year’s resolution included healthier habits,
including stable sleep schedules, eating healthier, exercising, and mindfulness. Across most
participants, sleep was mentioned as an important well-being contributor that they have had to
address for their well-being, either in the past or present.

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When asked to categorize their music-related activities (e.g., practice, rehearsals, lessons,
performances), responses were varied. Some described practice sessions as a routine activity
similar to an ADL/IADL, where it has become an integral, habitual part of their daily lives that
they could not be without. Others were comfortable with separating music-related items by the
long-term purpose of the activity. For example, if a practice session was focused on repertoire
for a lesson, ensemble, or performance required by the school, the session was considered part of
their education. However, if a practice session was focused on repertoire for a paid orchestra gig,
this was considered part of their work. Additionally, some stated that practice sessions on
repertoire that were self-chosen for their pleasure were considered to be a part of leisure or play.
4.3.3.2 University Program Supports & Barriers
Discussion of activities highlighted some university program supports and barriers to
well-being. Schoolwork not directly related to music or personal interests, such as general
education courses for undergraduate students, were often rated low happiness and neutral/high
for meaningfulness due to the feeling of wasting time in class/completing coursework, but the
acknowledgment that earning a degree is meaningful. This demonstrated one potential key
distinction in how the two scales were perceived and answered.
Additionally, access to ideal practice room spaces emerged as an important support for
students. Most students reported practicing or rehearsing regularly. Some preferred to practice at
home for various reasons, including convenience, less noise from other musicians practicing, and
availability of practice rooms. Having online scheduling systems for practice rooms was noted as
helpful in multiple ways. One participant noted how they used the scheduling system to build in
natural practice breaks to their sessions. Others noted that they can choose practice
rooms/buildings that they prefer practicing in. Although students only spent a small portion of

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their day practicing/rehearsing, the success of practice/rehearsals was very meaningful and had
lasting effects on students. Productive practice sessions felt meaningful and satisfying, while
unproductive practice sessions often left students frustrated or anxious about their overall
progress as a music student.
4.4 Discussion
This study was a preliminary investigation into the daily activity patterns of music
students and how they intersect with their well-being. Through collecting consecutive data for a
week from each participant, patterns could be identified in associations of certain activities and
well-being experiences. Some occupational groups were identified as supportive across all
participants, while other activity categories, such as education and music, were associated with
varied well-being experiences depending on the individual. There were limited mentions of
leisure activities, and no instances of play activities reported by any participant. Similarities and
differences across individuals highlight a need to better understand individual musician
perspectives of daily occupational engagement to tailor any health-promotive interventions.
During the interviews, it was clear that students had an informed understanding of the
activities that most contributed to their well-being, as well as the activities that negatively
impacted their well-being. For all participants, social support was very important and often the
first mentioned when asked about activities that positively contributed to their well-being. On the
other hand, especially with many extra school-related engagements during finals week, students
acknowledged aspects of their program that were not supportive of their well-being, including
time-consuming program requirements that did not feel meaningful to their hedonic or
eudemonic well-being. The expertise that musicians hold in understanding their unique dynamic

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intersections between activities and well-being may be a very valuable resource for university
programs that strive to support music student health and success.
Through the interview exercise of asking students to categorize their activities to OTPF
categories, it became clear that the traditional OTPF categories did not encompass the unique
experiences of music students. Although most music-making activities could be considered part
of their education, some students felt music-making is a more creative process akin to play or
leisure, rather than education. The OTPF has been criticized in the literature for not being
representative of many people’s experiences of different occupations (Kantartzis & Molineux,
2011). Regardless, the OTPF was used in this study to categorize reported activities to create
visuals for interview discussion. Further investigation is needed to understand the best way to
categorize musicians’ activities in a meaningful way for similar studies in the future.
One important finding was the way that students categorized music activities very
differently. Even within activities that appear very similar (i.e., solo practicing sessions),
students categorized them differently based on the intention and energy during the activity (i.e.,
practicing repertoire for jury performance vs. playing self-selected repertoire in a light-hearted
manner for fun). Additionally, several students described music practice as similar to an ADL: it
is an automatic, regular, and self-preserving activity akin to brushing their teeth or getting
dressed. Guptill (2011a), through qualitative inquiry, explored the differences in musicians’
sense of identity – some feeling that being a musician was all-encompassing of their identity, and
others chastising the idea of having their occupation represent their entire identity (Guptill,
2011a). There may be similar distinctions to be made in how musicians understand the
occupation of practice, and the impact of the differences to the relationship of the occupation of

105
music-making and well-being. Further research is needed to explore these differences and
understand the importance to musician health and well-being.
Despite the data collection period overlapping with students’ busiest week of the
semester due to finals week, the data collection method outlined in this study was feasible and
students were able to provide meaningful information through the daily DRM surveys and
contextualize the findings through interviews conducted two months later. The structure
provided through the DRM survey allowed the students to recall daily activities using the full
range of the two well-being Likert scales. Findings were able to be visualized through various
figures to identify individual patterns in activities and associated feelings of well-being. The
follow-up interviews provided important context to findings, including more in-depth accounts
of personal experiences during the week of data collection, as well as the narrative that led to
their experiences (i.e., previous experiences with injury or performance anxiety changing their
relationship with the occupation of music-making). Additionally, for many participants, the week
of finals was so unlike their other weeks that the interviews illuminated a need for additional data
collection for more representative data of the school semester.
Although the study’s findings provide further evidence of the complex relationship
between participation in the occupation of music-making and well-being experiences among
musicians, multiple limitations in the study limit immediate translation to practice. First, the
sample was purposively determined based on a national survey to focus on groups of students
who were most represented within the sample. The final sample of 8 students does not represent
the breadth of varying musician activities, both due to the size and the sample population of
Classical piano or violin players. Additionally, this study focused on higher education music
students and does not include professional musicians. This limits the generalizability of any

106
findings to the musician population. The timing of data collection being towards the end of the
semester, while it uncovered the stresses that final exams bring to students, may not be
representative of student experiences during the majority of the school semester. Finally, the
results reported in this chapter are preliminary findings without an in-depth analysis of interview
transcripts or iterative comparison of DRM and interview data. These findings provide
preliminary themes and topics that will contribute to a code book for qualitative descriptive
analysis of interview transcripts. Then, interview results will be compared back to individual
DRM data as well as the survey response from Chapter 3’s national survey study for iterative
mixing of quantitative and qualitative data.
4.5 Conclusion
This study was the first to use the DRM combined with interviews to study the
intersection of activity engagement and well-being in music students. Despite limitations to the
study method and analysis, meaningful findings were uncovered on music student experiences
and perceptions. Students reported varying perceptions of their music-making occupations using
the OTPF categories, illuminating a need to better understand how the perception of the
occupation may impact daily activities and well-being outcomes. Additionally, despite most
participants being young adults with an average age of 21 years, all students had individualized
and complex understandings of how their activities impacted their well-being, with an
acknowledgement of the dynamic nature of the intersection between activities and well-being.
Further study is needed to identify the most meaningful way of labeling and categorizing
musicians’ daily activities, especially pertaining to music-making, to conduct similar inquiry on
daily activities using the DRM.

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CHAPTER 5 Discussion and Synthesis
5.1 Summary of Key Findings
The objective of this dissertation was to examine musician health using three
perspectives: existing literature, national trends, and daily lived experiences. The newly
developed Ecology of Musical Performance (EMP) Model was used as a foundational
framework to understand how the model is reflected in the literature, associations of model
constructs with well-being constructs, and lived experiences with well-being. In Chapter 2, a
mapping review was conducted to create a topography of existing musician well-being articles,
using EMP model well-being determinants to categorize articles. Next, in Chapter 3, a national
survey was conducted to quantitatively examine the associations of EMP well-being
determinants with various well-being outcomes. Finally, in Chapter 4, the lived experiences of a
small group of music students were explored using daily activity logs and interviews. This
chapter summarizes key findings and implications of each chapter, provides a synthesis of
findings, and discusses future directions.
5.1.1 Conclusions from Chapter 2: Mapping Review
1. The majority of well-being studies identified by the mapping review focused on the
EMP model construct of musician continuum, with a focus on musculoskeletal health. Other
common areas studied were the musical work schedule and peripheral variables. Many areas
within the EMP model were sparsely studied, including the physical environment and interface
effectors, or the interaction between the musician, their repertoire, and their instrument.
Implication: There is a need to better understand the environmental barriers to wellbeing to inform health promotion efforts. Additionally, better understanding of the

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interface effectors can help inform intervention to prevent injury and support well-being
in musicians.
2. There were very few intervention studies identified in this review, and all intervention
studies had a sample of music students, both at the K-12 level and within higher education
programs.
Implication: The lack of intervention studies hinders the ability to draw conclusive
evidence to inform health promotion efforts in musicians. Additionally, many differences
exist between music students, professional musicians, and amateur musicians. Without
intervention studies within these different populations, existing intervention evidence may
not translate well to other populations.
5.1.2 Conclusions from Chapter 3: National Survey
1. Within the EMP model constructs, higher musician continuum ratings were positively
associated with higher ratings across all three health and well-being outcomes of physical health,
mental health, and the PERMA-Profiler well-being outcome (p<0.05). Additionally, higher
ratings in musical work schedule factors were positively associated with higher PERMA-Profiler
well-being outcomes (β=0.34, p<0.001).
Implication: Musician continuum and musical work schedule factors may be important
well-being contributors in music students. However, further study is needed to
understand how individual components of each factor impact students differently.
2. On a 0-10 scale (0=not important at all, 10=very important), all EMP model
components had an average importance rating between 6.0 and 9.3. and an average satisfaction
rating (0=not satisfied at all, 10=completely satisfied) between 4.9 and 7.7.

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Implication: Music students perceived EMP model components as important well-being
contributors. Further study is needed on well-being contributors with high importance
and low satisfaction ratings to determine areas for improvement.
5.1.3 Conclusions from Chapter 4: Intersection of Daily Activity and Well-being
1. Across all students, social support was an important facilitator of well-being, while
many time-consuming academic engagements were considered hindrances to overall well-being
that retracted from occupations that were meaningful and/or recuperative. The majority of
academic activities reported were related to final exams, as the data were collected at the end of
the academic semester.
Implication: While the small sample size and timing of the data collection limit the
generalizability of findings, higher education music programs may benefit from
understanding how final exams impact students and identify ways to provide extra
support during this stressful time.
2. Daily activity logs were a feasible method for obtaining feelings of well-being and to
discern patterns at the intersection of occupations and hedonic and eudemonic well-being within
individuals.
Implication: A modified DRM can be a useful tool for understanding individual patterns
in activity engagement and well-being. Collecting this type of data can help inform
intervention at an individual level by increasing self-awareness of how occupations
contribute to their well-being. Additionally, higher education programs may be able to
collect this data to understand the impact of their school programs on their students and
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3. Music-related activities were categorized and described differently among students,
ranging from education, leisure, play, and routine activities.
Implication: The relationship that musicians have with their occupation varies and may
have different implications for individual health and well-being. Further study is needed
to better understand these differences and identify potential for the individualization of
supports and interventions.
5.2 Synthesis of Knowledge Gained
5.2.1 Advancing understanding of the EMP Model
The EMP model contains many elements of previously used frameworks such as sports
medicine and worker wellness, while addressing musician-specific needs. For example, the
detailed considerations within the Musician – Instrument – Repertoire Complex (MIRC) are
similar to some recent frameworks within sports medicine that use a systems understanding
rather than linear causational models to understand injury development. The MIRC is described
as an interactive system that is informed by and informs the musician’s role and drive to
continue. Additionally, the EMP model has similarities with recently developed worker wellness
frameworks, where there is an acknowledgement of the importance of contexts in which
occupations take place. Rather than focusing only on the musician while they are engaging in
music-related occupations, the model includes other variables that may play a significant role in
musicians’ health, such as non-music occupations. These elements help strengthen the model
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This dissertation was the first study to apply the EMP model as a foundational
framework. By applying the model in three different studies—a literature review, a national
survey, and qualitative inquiry into lived experiences—much was uncovered about the model’s
current usefulness and potential areas for modification. It was clear that the model highlights
constructs that are important determinants of musician well-being. The musician continuum was
a central factor in both the literature and national survey findings: it was both the most studied
construct while also having statistically significant positive associations with well-being
outcomes. Similarly, musical work schedule was a commonly studied construct with a
statistically significant association with well-being outcomes. While other model constructs were
not found to be significantly associated with well-being outcomes, survey participants noted the
high importance of all EMP model factors. However, there were gaps in the literature where
some EMP model constructs and subcomponents have yet to be studied. This discrepancy in
student perspectives and literature was reflected in the interviews as well, as students noted a
wide range of well-being contributors. For example, students noted the importance of their
physical environments to their daily well-being experiences, but literature on supportive
environments in musicians is currently very sparse.
5.2.2 Emerging Themes on Intersection of Occupational Identities and Well-being in Musicians
While the mapping review identified many studies on musician well-being, limited
studies have investigated the lived experiences of musicians. Through the daily activity logs and
interviews, preliminary themes emerged that highlight important aspects of music student wellbeing that are often overlooked. The initial goals of this dissertation were meant to explore and
relate music student experiences of activities and well-being to the EMP, which limited the data
analysis to the researcher’s impressions while conducting interviews and reviewing notes made

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during and after each interview. Below are brief descriptions of the potential organizing
constructs of identity and well-being that inform further analyses of the interview data obtained
in this project and additional future research.
“Outside of being a musician, who are you?”
One participant noted a pivotal moment in their recovery from a long hiatus where they
were unable to play their instrument due to mental breakdowns every time they sat with their
instrument. During this time, a healthcare practitioner asked them about their identity outside of
being a musician. When they were unable to answer this question, they became aware that much
of their inability to engage in music was due to their heavy reliance of identity on their ability to
perform music well. After this realization during their hiatus, they spent months engaging in
other hobbies and spending time with loved ones. This allowed them to explore their identity
outside of music and develop relational identities that are not dependent on their music
performance skills.
Just as the music student realized that their identity played a strong role in their wellbeing, this phenomenon has begun to be addressed within musician well-being literature as well.
In one phenomenological study of orchestra musicians with injury, the theme of “identity and
voice” emerged, as musicians spoke of the loss of their identity as a musician and their outlet for
expression (Bourne et al., 2019). Another phenomenological study investigated the complex
identities of professional musicians, where three roles of musician, teacher, and worker
intersected (Guptill, 2011a). Music students may experience a similar mixing of roles unique to
their student status. When students were asked about their perception of their identities of being a
musician and a student, most participants stated that they could not separate being a musician
from being a student. Part of the lack of separation was that they were music students, and most

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of their education was directly related to their musicianship. This lack of separation was
especially pronounced for graduate students, as they did not have the general education
requirements for non-music academic coursework that undergraduate students had. More
prominently, the lack of separation came from the fact that, as musicians, they feel that they are
lifelong students. To be a musician for them was synonymous with being a lifelong learner and
teacher of the craft. Therefore, the student identity was not derived from the fact that they are in
a higher education program but rather from the fact that they are musicians.
Across all participants, maintaining their well-being was of utmost importance. When
asked to describe what well-being means to them, two emerging themes were identified. One
was that well-being encompasses both physical and mental well-being. Furthermore, physical
health was mentioned as even more important to their well-being compared to their nonmusician counterparts because their ability to engage in music is dependent on their physical
health. Comparisons were made to athletes and the importance of managing physical and mental
health for athletic performance by several students. Music students reported heightened
awareness of their health to support their musical engagement and performance. A secondary
theme of well-being that arose was serenity, or being at peace with oneself, their environment,
and their occupations. Experiences of positive well-being were described not just as the lack of
physical and mental ailments, but also the presence of inner peace. This was achieved both
through music-related and non-music occupations and was described as a process that required a
lot of self-awareness and coping strategies.
Despite the acknowledgement of the many challenges of being a music student and
importance of well-being, there was an underlying theme of shame and difficulty around positive
health behaviors such as rest. Practice breaks were often taken with guilt, with students

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mentioning that they were too long or too frequent and felt that they were wasting time. While
leisure and play were minimally reported across all participants, there was an underlying shame
that was noted when engaging in leisure occupations due to feelings of not being “productive.”
Simultaneously, students noted a difficulty with scheduling themselves for more than they are
capable of. Feeling overbooked led to more stress and performance anxiety, as they felt illprepared for each performance when they were too busy. Most participants experienced both
performance anxiety and current or past musculoskeletal injury, but very few had sought
professional healthcare services for either. Medication for anxiety was perceived as a “cheat”
and/or musicians stopped taking medication as they had a dulling effect on music performances.
Multiple students reported having a major breakdown where they became unable to
continue playing music. To return, they took long breaks from practice, changed their major to
decrease the performance component, and sought non-music occupations to support their wellbeing and recovery. To address injury, many reported spending extensive efforts on their
postures and/or re-learning their body mechanics during music playing. For many, this process
took place over the course of many years and was described as an ongoing learning process.
Most students reported working on these adjustments with their primary instrument teachers. The
focus during the sessions working with their teachers was conducting mind-body work to
simultaneously enhance their music performance and body mechanics. During these difficult
moments, the role of being a child was important, as parents were sometimes described as
important support, while other parents were the cause of much of the stress.
Through preliminary description of these accounts, it is clear that music students’ health
behaviors and well-being outcomes are heavily impacted by their identity as a musician and
occupational engagements. These emerging themes echo literature findings on the importance of

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understanding musicians’ occupational identities to better facilitate well-being (Guptill, 2012;
Guptill et al., 2005). More detailed analysis of the interviews, as well as further exploration of
these intersections, may help determine supports for music students to facilitate behaviors that
promote health and well-being.
5.3 Future Directions for Musician Well-being and Occupational Science Research
5.3.1 Future directions for further development of the EMP model
While this dissertation demonstrated the importance of the EMP model constructs, the
studies are preliminary investigations of the application of the EMP model. Prior to this study, no
empirical study was conducted on the application of the model in a research context. The EMP
model was developed to support clinicians’ understanding of musicians for evaluation and
treatment and was not designed in a way that translates to empirical measurement in research
studies easily. This posed some difficulties in the current study. For example, within the national
survey study’s regression analyses, certain analysis decisions had to be made due to the high
number of survey items and proportionately low sample size. To meaningfully and validly
conduct regression analyses, a decision was made to create composite scores of each of the five
model constructs. However, no latent variable analysis was conducted on these constructs prior
to this modeling decision. Further study with larger sample size on latent variables within the
model would increase the validity of large-scale quantitative analysis of the model.
Given its prevalence and the finding that many of its subcomponents can directly overlap
with health outcomes, the musician continuum construct may be an ideal area for the focus of
further investigations. The musician continuum includes musculoskeletal, sensory motor,
cognitive perceptive, and psychosocial dimensions. While it is important to understand how
specific health and function statuses are predeterminants of well-being, there is a major potential

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for bias when conducting statistical modeling with health and well-being outcomes. For example,
within Chapter 3, three regression analyses were conducted with physical health, mental health,
and general well-being. The musician continuum construct being an independent variable to
health and well-being models while containing specific elements of physical and mental health is
a significant limitation to the study and requires further investigation to apply to future largescale quantitative studies.
Another component of the model that calls for further investigation is the central feature
of the model, the Musician-Instrument-Repertoire Complex (MIRC). The MIRC is the system in
which the musician continuum, musical work schedule, and interface effectors constructs all
interact through occupational engagement in music activities to develop musical identity and
drive (Bastepe-Gray et al., 2021). This dynamic relationship of the musician, instrument, and
music-making occupations has only begun to be studied within musician well-being literature.
Within this dissertation, this complex system was only tangentially investigated within Chapter
4. Through the combination of daily activity logs and interviews, there were some meaningful
discussions of the music students’ daily lives that provided insight into lived experiences of the
MIRC. However, further investigation to understand the features of this system that are unique to
musicians can potentially improve the practical usefulness of the model both within research and
clinical settings.
Finally, while the MIRC is placed as a central component to the EMP model, during
Chapter 4 of this dissertation, many non-music occupations were also identified as central
components to musician well-being. Across all participants, social support was mentioned as a
daily support to well-being. While social support being a positive well-being contributor is not
unique to musicians, this may be a construct that is important enough to add to the EMP model.

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The majority of professional musicians work in groups or teams, such as orchestras, choirs,
bands, or music groups, and the social environment plays a significant role in their daily lives
(Guptill, 2011b). A second non-music occupation that was identified through this dissertation
was sleep. Sleep was identified in the literature review as a frequently studied musician wellbeing contributor, and when asked about well-being experiences, multiple students mentioned
sleep being an important aspect of their daily lives. Students cited times when they implemented
strategies to improve their sleep quality due to the significant impact observed on their health,
performance, and well-being.
Specific to applying the EMP to music students, the occupation of being a student may be
another valuable non-music occupation to add to the model. During the daily activity log and
interviews that followed, participants noted many student-specific experiences (e.g., academic
stress, student support resources). Due to the daily activity log data collection taking place during
finals week, we were able to gain insight into students’ experiences that are unique to the end of
semester when they have multiple school engagements. During finals week, the additional
commitments due to final exams caused not just academic stress, but also took time away from
students engaging in their routine meaningful occupations that normally support their well-being.
While schoolwork is not explicitly in the EMP model, further exploration of the model for music
students may contribute to better understanding of supports for students due to these unique
challenges.
Given the importance of various non-music occupations, the EMP may benefit from a
more detailed analysis of the peripheral variables construct where non-music occupations
currently reside, considering these occupations and factors not as periphery variables but as
components central to musician well-being.

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5.3.2 Next steps for musician well-being research
While this dissertation conducted preliminary work of applying the EMP model in
various research studies, there is opportunity for further development in theoretical framework to
facilitate musician well-being. Survey findings demonstrated the importance of well-being
contributors highlighted in the EMP model to well-being outcomes. However, more study is
needed to investigate these associations in order to inform intervention. A mixed method study
with more intentional focus on theoretical understanding of musicians may help inform the
development of a framework and/or modifications to the EMP model needed for future research
and practical applications. Through an exploratory sequential mixed method study, qualitative
inquiry such as focus group interviews can be conducted to gain musician perspectives and
discuss any well-being contributors that have not previously been considered. Building on
knowledge gained through qualitative inquiry, a large-scale study such as a survey can be
conducted on a newly developed framework that investigates the identified well-being
determinants quantitatively. Using the large sample survey data, latent variable analysis can be
conducted to determine the organization of framework constructs and the validity of any
additional components.
This dissertation also illuminated broader implications for musician well-being research.
The majority of musician well-being literature, including this dissertation, focuses on Classical
musicians. Without more study on different populations of musicians, findings continue to not be
generalizable to non-Classical musicians. Additionally, the mapping review identified a
significant gap within intervention research, as there were very few intervention studies, and all
existing studies focused on students. With such little quantity and variety in existing intervention
studies, it is very difficult to inform health promotion interventions for professional musicians.

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The EMP model provides promising future directions in the theoretical framework of
understanding musician well-being. However, further themes of occupational identity and the
intersection of activity engagement and well-being that were identified within the interviews
provide interesting next steps for musician well-being research. Further qualitative inquiry into
the complex and dynamic system of the musician’s occupational identity and well-being can lead
to theoretical development of musician well-being literature.
5.3.3 Opportunities for Occupational Science (OS)
The knowledge gaps within musician well-being literature are a call to action to
occupational scientists, as this study demonstrated the need for more theoretical development in
understanding the occupational identities of musicians and how they transact with well-being.
Nuanced understanding of this dynamic relationship can help identify the unique challenges of
musicians with varying degrees of identity retrieved from their occupation of music-making.
Additionally, this study demonstrated how multifaceted occupational identities are, and the need
to consider not just the musician for their singular occupational identity, but also to consider the
many roles, routines, and occupational identities that also impact musicians. Within OS, there is
an understanding of occupational identity as a construct that evolves as individuals navigate
different life experiences (Unruh, 2004). Occupations can function as building blocks to an
evolving identity (Blank et al., 2015), where the past, present, and future all contribute to the
continual formation of the life story (Christiansen, 1999; Matuska & Christiansen, 2008).
Engaging in projects that are related to identity has been associated with greater well-being
(Christiansen, 2000). OS understanding of occupational identity and existing frameworks such as
the Person, Environment, Occupation, Occupational Performance Model or the Doing, Being,

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Becoming, Belonging model have potential to help further develop theoretical understanding of
occupational identities within musicians (Bass et al., 2017; Wilcock, 2007).
These applications can also provide the groundwork for a practical transferability of OS
perspectives to address other occupational groups as well. Since the COVID-19 lockdowns and
drastic sociopolitical changes that followed, the relationships that people have with their work
and life have changed (Vyas, 2022). With COVID-19 leading to high levels of burnout and the
“Great Resignation”, there is a need to understand burnout and work-life balance in modern
workers (Formica & Sfodera, 2022; Gittleman, 2022). A criticism of previous worker wellness
frameworks has been the lack of acknowledgement and understanding of the “nonwork” factors
that significantly impact people. While more recent worker wellness frameworks try to
understand the worker more holistically through frameworks such as the Total Worker Health
initiative (Schill & Chosewood, 2013), there is room for theoretical development in
understanding how this can be applied to the modern worker. If a methodology of practical
application of existing OS frameworks to musicians is developed, it may be able to be replicated
to various occupational groups that would benefit from better theoretical understanding of the
different roles and occupational identities that members of the group carry and how they transact
with well-being.

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APPENDIX A National Well-being Survey

142
Musician Well-Being Survey
Start of Block: Module 0. Consent
Q91 Please read below for information on the study. If you agree to participate, click yes at the bottom of
this page to proceed.
Study Title: Facilitators and Barriers to Student Musician Well-Being
Investigators: Yoko E. Fukumura, MA, OTR/L, PhD Candidate; Shawn C. Roll, PhD, OTR/L, RMSKS,
FAOTA, FAIUM
You are invited to participate in a research study. Your participation is voluntary. This document explains
information about this study. You should ask questions about anything that is unclear to you.
PURPOSE
The purpose of this study is to understand the importance and impact of various factors to well-being in
collegiate student musicians. We hope to learn student perception and experiences of well-being
determinants and contributors. You are invited as a possible participant because you are an active student
in higher education in a U.S. performance-focused music program. We project that up to 1000
participants will take part in the study.
PROCEDURES
If you agree to participate in this study, you will be asked to complete an online survey which will take
approximately 20 minutes. You do not have to answer any questions you don’t want to; click “next” or
“submit” in the survey to move to the next section.
RISKS AND DISCOMFORTS
Some of the questions may make you feel uneasy or embarrassed. You can choose to skip or stop
answering any questions you don’t want to. While the survey is completely anonymous, there will be an
option at the end to provide a name and contact information for follow up studies. As such, if you decide
to provide contact information, there is a small risk that people who are not connected with this study will
learn your identity or your personal information. However, all information personal identifying
information will be coded and stored separately and appropriate measures will be taken to avoid any
breach of personal information.
BENEFITS
There will be no direct benefit to you for participating. However, the knowledge gained from the study
will help us develop a better understanding of student experiences to improve well-being supports and
facilitators for future students.
PRIVACY/CONFIDENTIALITY
We will keep your records for this study confidential as far as permitted by law. However, if we are
required to do so by law, we will disclose confidential information about you. Efforts will be made to

143
limit the use and disclosure of your personal information, including research study and medical records,
to people who are required to review this information. We may publish the information from this study in
journals or present it at meetings. If we do, we will not use your name. The University of Southern
California’s Institutional Review Board (IRB) and Human Subject’s Protections Program (HSPP) may
review your records. At the end of the survey, you will have the option of providing your contact
information for future follow-up study on student musician well-being. Your responses will be treated
confidentially. The data will be kept for the duration of the study and analysis. All data will be saved on a
secure electronic drive with password protected access, and only approved research personnel will have
access to study data.
PAYMENTS/COMPENSATION
Upon completion of the survey, you will be given the opportunity to join a raffle to win one of five $50
gift cards. To join, you will follow the provided link at the end of the survey and enter your contact email.
This email will not be connected to your survey response and only be used for purposes of the raffle.
VOLUNTARY PARTICIPATION
It is your choice whether to participate. If you choose to participate, you may change your mind and leave
the study at any time. If you decide not to participate, or choose to end your participation in this study,
you will not be penalized or lose any benefits that you are otherwise entitled to.
INVESTIGATOR CONTACT INFORMATION
If you have questions, concerns, complaints, or think the research has hurt you, talk to the primary
investigator, Yoko Fukumura, at fukumura@chan.usc.edu. This research has been reviewed by the USC
Institutional Review Board (IRB). The IRB is a research review board that reviews and monitors research
studies to protect the rights and welfare of research participants. Contact the IRB if you have questions
about your rights as a research participant or you have complaints about the research. You may contact
the IRB at (323) 442-0114 or by email at irb@usc.edu.
o Yes, I agree to participate (1)
o No, I do not want to participate at this time (4)
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144
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145
End of Block: Module 0. Consent
Start of Block: Screening
Q1 Are you 18 or above?
o Yes (1)
o No (2)
Q2 Are you currently an active student (e.g. part time, full time)?
o Yes (1)
o No (2)
Q3 Are you enrolled in a performance-based music program in the U.S.?
o Yes (1)
o No (2)
Q100 Do you play a musical instrument?
o Yes (1)
o No (2)
End of Block: Screening
Start of Block: Module I. Demographics

146
Q93 Thank you for agreeing to participate in the study. Based on your responses, you meet criteria for
this survey.
The following survey is organized into three sections: Demographics & General Health, Playing &
Performance-related Participation, and Well-being.
Click forward to proceed to the first section.
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147
Q69 Demographics Section
The following section includes descriptive questions about you and your student status.
Q4 Age
________________________________________________________________
Q5 Gender identity (select all that apply)
▢ Agender (1)
▢ Genderqueer/Genderfluid (2)
▢ Man (3)
▢ Non-binary (4)
▢ Woman (5)
▢ Prefer not to disclose (6)
▢ Prefer to self-describe: (7)
__________________________________________________

148
Q6 Race (select all that apply)
▢ American Indian or Alaska Native (1)
▢ Asian (2)
▢ Black or African American (3)
▢ Native Hawaiian or Other Pacific Islander (4)
▢ White (5)
▢ Prefer not to answer (6)
▢ Other (please specify) (7) __________________________________________________
Q7 Ethnicity
o Hispanic/Latinx (1)
o Not Hispanic/Latinx (2)
oPrefer not to answer (3)
Q9 What do you consider to be your primary musical instrument?
▼ Violin (1) ... Other (22)

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Q101 If you selected "other", please enter your primary musical instrument.
________________________________________________________________
Q10 Please list any other musical instruments that you currently play?
________________________________________________________________
Q11 What is your primary musical genre?
o Baroque (7)
o Classical (1)
oJazz (2)
o Contemporary (4)
o Electronic (5)
o Other: (3) __________________________________________________
Q14 Are there any other musical genres that you currently play? Please list all genres.
________________________________________________________________
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150
Q15 At what university/institution are you pursuing your current degree?
________________________________________________________________
Q16 What degree(s) are you currently pursuing? (select all that apply)
▢ Associate (1)
▢ Bachelor (2)
▢ Master (3)
▢ Doctor of Musical Arts (4)
▢ PhD (5)
▢ Other: (6) __________________________________________________
Q17 What is your major/area of study?
________________________________________________________________
Q18 If you have a second major or a minor, please indicate all areas of study.
________________________________________________________________

151
Q19 What is your year of study in your current program?
▼ 1st year (1) ... 6th year+ (6)
End of Block: Module I. Demographics
Start of Block: Module II. Musician Continuum
Q30 General Health
The following questions ask about your experiences within various health topics. To rate each item, click
on the bar to activate and register your response from 0 to 10.
Consider each of the following in the context of the past 7 days.
Q107 Physical health is the well-being and functioning of the body, including aspects such as sleep
and nutrition.
0 1 2 3 4 5 6 7 8 9 10
In general, how would you say your physical health
is? (0=terrible, 10=excellent) ()
How satisfied are you with your current physical
health? (0=not at all, 10=completely) ()
Compared to others of your same age and sex, how is
your physical health? (0=terrible, 10=excellent) ()
Q108 Mental health encompasses emotional, psychological, and social well-being, and affects how
you think, feel, and act.
0 1 2 3 4 5 6 7 8 9 10

152
In general, how would you say your mental health is?
(0=terrible, 10=excellent) ()
How satisfied are you with your current mental
health? (0=not at all, 10=completely) ()
Compared to others of your same age and sex, how is
your mental health? (0=terrible, 10=excellent) ()
Page Break

153
Q109 General Health
Each of the following items has 3 slider bars regarding quality, satisfaction, and importance.
Consider each of the following in the context of the past 7 days.
Q20 Musculoskeletal health refers to the health of joints, muscles, bones, and adjacent tissue that
allow for efficient, pain-free body movement.
0 1 2 3 4 5 6 7 8 9 10
How would you rate your musculoskeletal health
(0=poor, 10=excellent)? ()
How satisfied are you with your current
musculoskeletal health? (0=not at all, 10=completely)
()
How important is your musculoskeletal health to your
general health and well-being? (0=not important at all,
10=very important) ()
Q21 Posture refers to how you hold your body during instrument-playing and during rest.
0 1 2 3 4 5 6 7 8 9 10
On average, how would you rate your posture?
(0=poor, 10=excellent) ()
How satisfied are you with your posture? (0=not at all,
10=completely) ()
How important is your posture to your general health
and well-being? (0=not important at all, 10=very
important) ()

154
Q110 Auditory health refers to the ability to hear.
0 1 2 3 4 5 6 7 8 9 10
On average, how would you rate your auditory health?
(0=poor, 10=excellent) ()
How satisfied are you with your auditory health?
(0=not at all, 10=completely) ()
How important is your auditory health to your general
health and well-being? (0=not important at all,
10=very important) ()
Q22 Sensory motor function refers to the processing of incoming sensory information (e.g., sound,
touch, vision) and using the information to produce movement. The resulting sensory motor
coordination refers to the quality and speed of your movements.
0 1 2 3 4 5 6 7 8 9 10
How would you rate your sensory motor function
during musical activities? (0=poor, 10=excellent) ()
How satisfied are you with your sensory motor
function? (0=not at all, 10=completely) ()
How important is your sensory motor function to your
general health and well-being? (0=not important at all,
10=very important) ()
Q23 Cognitive perceptual function refers to higher level processing of auditory and visual learning.
An example is mental imagery, the ability to imagine movement and sensation with no external
stimuli.
0 1 2 3 4 5 6 7 8 9 10

155
How would you rate your cognitive perceptual
function? (0=poor, 10=excellent) ()
How satisfied are you with your cognitive perceptual
function? (0=not at all, 10=completely) ()
How important is your cognitive perceptual function
to your general health and well-being?(0=not
important at all, 10=very important) ()
Q24 Stress management refers to the ability to utilize strategies and approaches to reduce the
negative impacts of stress.
0 1 2 3 4 5 6 7 8 9 10
How would you rate your stress management?
(0=poor, 10=excellent) ()
How satisfied are you with your stress management?
(0=not at all, 10=completely) ()
How important is stress management to your general
health and well-being? (0=not important at all,
10=very important) ()
Q25 Performance anxiety, or “stage fright”, is the fear experienced in anticipation of and/or during
a performance.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10

156
How would you rate the amount of performance
anxiety you experience? (0=no anxiety, 10=highly
anxious) ()
How satisfied are you with the amount of performance
anxiety you experience? (0=not at all, 10=completely)
()
How important is performance anxiety to your general
health and well-being? (0=not important at all,
10=very important) ()
End of Block: Module II. Musician Continuum
Start of Block: Module III. Peripheral Variables
Q70 Daily Activities
The following questions ask about your daily activities relative to your health and well-being. The same
rating process (e.g., quality, satisfaction, importance) is continued in this section.
Consider each of the following in the context of the past 7 days.
Q28 Consider the number, amount, and quality of non-musical school activities (e.g., coursework,
clubs)
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How would you rate your current participation in these
activities? (0=poor, 10=excellent) ()
How satisfied are you with your engagement in these
activities? (0=not at all, 10=completely) ()
How important are these activities to your general
health and well-being? (0=not important at all,
10=very important) ()

157
Q33 Consider the number, amount, and quality of non-musical leisure activities (i.e., socializing,
exercising).
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How would you rate your current participation in these
activities? (0=poor, 10=excellent) ()
How satisfied are you with your engagement in these
activities? (0=not at all, 10=completely) ()
How important are these activities to your general
health and well-being? (0=not important at all,
10=very important) ()
Q102 Do you currently participate in any non-musical paid activities (i.e., part-time jobs)
o Yes (1)
o No (2)
Skip To: End of Block If Q102 = 2
Q32 Consider the number, amount, and quality of non-musical paid activities.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How would you rate your current participation in these
activities? (0=poor, 10=excellent) ()
How satisfied are you with your engagement in these
activities? (0=not at all, 10=completely) ()
How important are these activities to your general
health and well-being? (0=not important at all,
10=very important) ()

158
End of Block: Module III. Peripheral Variables
Start of Block: Module IV. Physical Environment
Q71 Physical Environment
The following questions ask about the physical environment during various activities. The same rating
process (e.g., quality, satisfaction, importance) is continued in this section.
Consider each of the following in the past 7 days.
Q34 Consider the temperature in your primary practice space.
0 1 2 3 4 5 6 7 8 9 10
Generally, how would you rate the temperature in
your practice space? (0=poor, 10=excellent) ()
Generally, how satisfied are you with the temperature
in your practice space? (0=not at all, 10=completely)
()
How important is temperature in your practice space
to your general health and well-being (0=not
important at all, 10=very important). ()
Q87 Consider the lighting in your primary practice space.
0 1 2 3 4 5 6 7 8 9 10
Generally, how would you rate the lighting in your
practice space? (0=poor, 10=excellent) ()
Generally, how satisfied are you with the lighting in
your practice space? (0=not at all, 10=completely) ()
How important is lighting in your practice space to
your general health and well-being? (0=not important
at all, 10=very important) ()

159
Q86 Consider the noise in your primary practice space.
0 1 2 3 4 5 6 7 8 9 10
Generally, how would you rate the noise in your
practice space? (0=poor, 10=excellent) ()
Generally, how satisfied are you with the noise in your
practice space? (0=not at all, 10=completely) ()
How important is noise in your practice space to your
general health and well-being? (0=not important at all,
10=very important) ()
Q35 Next, consider the general physical environment (temperature/lighting/noise) in primary
university spaces during non-music activities (i.e., classrooms, study areas)
0 1 2 3 4 5 6 7 8 9 10
Generally, how would you rate the quality of physical
environment of university spaces? (0=poor,
10=excellent) ()
Generally, how satisfied are you with the quality of
physical environment of university spaces? (0=not at
all, 10=completely) ()
How important is your physical environment of
university spaces to your general health and wellbeing? (0=not important at all, 10=very important) ()
Q36 Next, consider the general physical environment (temperature/lighting/noise) in your primary
living spaces (i.e., dorms, apartment).
0 1 2 3 4 5 6 7 8 9 10

160
Generally, how would you rate the quality of physical
environment of your living space? (0=poor,
10=excellent) ()
Generally, how satisfied are you with the quality of
physical environment of your living space? (0=not at
all, 10=completely) ()
How important is your physical environment of your
living space to your general health and well-being?
(0=not important at all, 10=very important) ()
End of Block: Module IV. Physical Environment
Start of Block: Module V. Interface Effectors - Perception - Performance - Satisfaction
Q37 Instrument Demands
Consider the following regarding your primary musical instrument. In this section, please read the items
carefully as there are now 4 scales to rate.
For questions regarding repertoire, consider within the past 7 days.
Q38 Consider the physical bodily demands due to the size, action, weight, and positioning of your
instrument.
0 1 2 3 4 5 6 7 8 9 10
How would you rate the physical demands of your
instrument? (0=no strain, 10=very strenuous) ()
How would you rate your ability to play your
instrument considering the physical demands?
(0=unable, 10=highly able) ()
How satisfied are you with your ability to play your
instrument considering the physical demands? (0=not
at all, 10=completely) ()
How important are the physical bodily demands of
your instrument to your general health and wellbeing? (0=not important at all, 10=very important) ()

161
Q39 Consider technical difficulty as the challenges in accurately playing repertoire (e.g., speed,
precision, coordination).
0 1 2 3 4 5 6 7 8 9 10
How would you rate the technical difficulty of your
current musical repertoire? (0=not difficult, 10=very
difficult) ()
How would you rate your ability to play your current
musical repertoire considering the technical difficulty?
(0=unable, 10=highly able) ()
How satisfied are you with your ability to play your
current musical repertoire considering the technical
difficulty? (0=not at all, 10=completely) ()
How important is the technical difficulty of your
current musical repertoire to your general health and
well-being? (0=not important at all, 10=very
important) ()
Q40 Consider endurance demands as the speed, frequency, and duration of force required to play
repertoire.
0 1 2 3 4 5 6 7 8 9 10
How would you rate the endurance demands of your
current musical repertoire? (0=no demand, 10=high
demand) ()
How would you rate your ability to play your current
musical repertoire considering the endurance
demands? (0=unable, 10=very able) ()
How satisfied are you with your ability to play your
current musical repertoire considering the endurance
demands? (0=not at all, 10=completely) ()
How important are the endurance demands of your
current musical repertoire to your general health and
well-being? (0=not important at all, 10=very
important) ()

162
Q41 Consider mental load as the creative, psychological, and emotional challenges to play
repertoire.
0 1 2 3 4 5 6 7 8 9 10
How would you rate the mental load of your current
musical repertoire? (0=low load, 10=high load) ()
How would you rate your ability to play your current
musical repertoire considering the mental load?
(0=unable, 10=very able) ()
How satisfied are you with your ability to play your
current musical repertoire considering the mental
load? (0=not at all, 10=completely) ()
How important is the mental load of your current
musical repertoire to your general health and wellbeing? (0=not important at all, 10=very important) ()
End of Block: Module V. Interface Effectors - Perception - Performance - Satisfaction
Start of Block: Module VI. Musical Work Schedule
Q94 Musical Engagement
Consider the following regarding your engagement in musical activities. Please continue to read the
items carefully as there are 3-4 scales to rate.
Consider the following within the past 7 days.
Q44 Consider the quality of your solo practice sessions.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10

163
How much of your practicing consists of solo
practicing? (0=none of the time, 10=majority of the
time) ()
How would you rate the quality of your solo practice
sessions? (0=poor, 10=excellent) ()
How satisfied are you with your practice sessions?
(0=not at all, 10=completely) ()
How important are solo practice sessions to your
general health and well-being? (0=not important at all,
10=very important) ()
Q43 Consider the amount of physical repetition during your practice sessions and rehearsals.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How much of your practice sessions consist of
physical repetition? (0=none of the time, 10=majority
of the time) ()
How would you rate the quality of physical repetition
during practice sessions? (0=poor, 10=excellent) ()
How satisfied are you with the physical repetitions
you engage in? (0=not at all, 10=completely) ()
How important is physical repetition during practice to
your general health and well-being? (0=not important
at all, 10=very important) ()
Q47 Consider the frequency, amount, duration, and quality of your practice breaks.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10

164
How often do you take breaks while practicing?
(0=never, 10=always) ()
How would you rate the quality of your practice
breaks? (0=poor, 10=excellent) ()
How satisfied are you with your practice breaks?
(0=not satisfied at all, 10=perfectly satisfied) ()
How important are practice breaks to your general
health and well-being? (0=not important at all,
10=very important) ()
Q46 Consider the quality of your mental practice sessions. Mental practice refers to the engagement
in visual and auditory simulation of repertoire away from the physical instrument.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How much of your practicing consists of mental
practice? (0=none of the time, 10=all the time) ()
How would you rate the quality of your mental
practice sessions? (0=poor, 10=excellent) ()
How satisfied are you with your mental practice
sessions? (0=not at all, 10=completely) ()
How important is mental practice to your general
health and well-being?(0=not important at all, 10=very
important) ()
Q45 Consider the quality of your ensemble rehearsals.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10

165
How much of your practicing consists of ensemble
rehearsals? (0=none of the time, 10=majority of the
time) ()
How would you rate the quality your ensemble
rehearsals? (0=poor, 10=excellent) ()
How satisfied are you with your ensemble rehearsals?
(0=not at all, 10=completely) ()
How important are ensemble rehearsals to your
general health and well-being? (0=not important at all,
10=very important). ()
Q103 Did/will you have any performances in your current semester?
o Yes (1)
o No (2)
Skip To: End of Block If Q103 = 2
Q42 In your current semester, consider the frequency of your performances.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How frequent are your performances? (0=infrequent,
10=very frequent) ()
How would you rate your ability to meet performance
demands in regards to frequency? (0=unable,
10=highly able) ()
How satisfied are you with your performance schedule
in regards to frequency? (0=not at all, 10=completely)
()
How important is the frequency of performances to
your general health and well-being? (0=not important
at all, 10=very important) ()

166
Q75 In your current semester, consider the difficulty of your performances.
Not Applicable
0 1 2 3 4 5 6 7 8 9 10
How would you rate the difficulty level of your
performances? (0=not difficult, 10=very difficult) ()
How would you rate your ability to meet performance
demands in regards to difficulty? (0=unable,
10=highly able) ()
How satisfied are you with your performance schedule
in regards to difficulty? (0=not at all, 10=completely)
()
How important is the difficulty of performances to
your general health and well-being? (0=not important
at all, 10=very important) ()
End of Block: Module VI. Musical Work Schedule
Start of Block: Module VII. Well-being
Q73 Well-being Section
In this final section, consider your general well-being in the past 7 days.
Q76 Please rate the following on a scale of 0=never, 10=always.
Never Always
0 1 2 3 4 5 6 7 8 9 10

167
How much of the time do you feel you are making
progress towards accomplishing your goals? ()
How often do you become absorbed in what you are
doing? ()
In general, how often do you feel joyful? ()
In general, how often do you feel anxious? ()
How often do you achieve the important goals you
have set for yourself? ()
Q77 Please rate the following on a scale of 0=not at all, 10=completely.
Not at all Completely
0 1 2 3 4 5 6 7 8 9 10
In general, to what extent do you lead a purposeful
and meaningful life? ()
To what extent do you receive help and support from
others when you need it? ()
In general, to what extent do you feel that what you do
in your life is valuable and worthwhile? ()
In general, to what extent do you feel excited and
interested in things? ()
How lonely do you feel in your daily life? ()
Q78 Please rate the following on a scale of 0=never, 10=always
Never Always
0 1 2 3 4 5 6 7 8 9 10

168
In general, how often do you feel positive? ()
In general, how often do you feel angry? ()
How often are you able to handle your
responsibilities? ()
In general, how often do you feel sad? ()
How often do you lose track of time while doing
something you enjoy? ()
Q83 Please rate the following on a scale of 0=not at all, 10=completely
Not at all Completely
0 1 2 3 4 5 6 7 8 9 10
To what extent do you feel loved? ()
To what extent do you generally feel you have a sense
of direction in your life? ()
How satisfied are you with your personal
relationships? ()
In general, to what extent do you feel contented? ()
Taking all things together, how happy would say you
are? ()
End of Block: Module VII. Well-being
Start of Block: Module VIII. Other Thoughts
Q74 Lastly, please reflect on the survey contents and your experiences of well-being. Is there anything
that contributes to your general well-being that was not included in this survey? If so, please share the
component and how it impacts your well-being.
________________________________________________________________

169
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
End of Block: Module VIII. Other Thoughts
Start of Block: Follow-up
Page Break

170
Q97 We will be conducting additional research to understand the complex relationships of daily activities
and well-being in musicians. Research will consist of activity logs and a follow up interview to discuss
findings and lived experiences.
Would you like to be contacted to learn more about future studies?
o Yes (1)
o No (4)
Q98 If you would like to be considered in future studies or would like to participate in a raffle for a
chance to win one of five $50 gift cards, please enter your email address.
Your responses will be kept confidential and your email will not be associated with your data at this time.
________________________________________________________________
End of Block: Follow-up

171
APPENDIX B Multiple Imputation Analysis

172
B.1 Methods
Multiple imputation (MI) analysis is a process in which random values are placed for missing
values based on existing complete data, to create a complete dataset for analysis. Studies have shown that
undergoing multiple imputation analysis is more valid than stepwise deletion of participant data due to
missing responses (Schafer & Graham, 2002).
With 124 complete responses and 72 partially complete responses, conducting stepwise deletion
regression analyses would lead to an attrition rate of 36.7%. Through conducting MI analysis, partially
complete survey responses can be used within the final regression modeling.
Prior to conducting MI analysis, extensive examination of the data was conducted to inform
missing data analysis methods. Each section outlined in the table below was designed within the Qualtrics
survey platform as a page of survey items, with an arrow at the bottom of the page to prompt participants
to continue. Response drop-off was most common at the end of each of these pages. Details on survey
drop-off by survey component can be found in Figure B.1.

173
Survey Component Completed N
No data/invalid data 51 exclude
Demographics & general health 16
impute
EMP Musician Continuum 6
EMP Peripheral variables - Daily Activities 16
EMP Physical environment 15
EMP Interface effectors 10
EMP Musical Work schedule 9
PERMA Well-being Outcome (Total Completion) 124 include
Figure B.1. Survey attrition number by content section.
Within the survey, there were multiple potential outcome variables. The PERMA wellbeing scale, the intended outcome variable, was at the end of the survey to avoid biasing of
responses to well-being contributors based on PERMA values of well-being. However, due to
the possibility of survey attrition, two proxy outcome variables were strategically placed at the
beginning of the survey. Those variables were physical and mental health, with three questions
for each area: general quality rating, satisfaction, and comparison with peers on a scale of 0 to
10. Comparing the complete and incomplete respondents, across both physical and mental
health, general quality and satisfaction was lower for respondents who did not complete the
survey. See Table B.1. and Figure B.2. for further details on distribution of physical and mental
health ratings.
N=72

174
Table B.1. Distribution of physical and mental health ratings between complete and
incomplete survey responses.
Variable
Incomplete
(n=72)
mean, s
Complete
(n=124)
mean, s
Equality of
variances
p value
Pooled t value (p
value)
Physical health rating 6.4, 1.6 7, 1.7 0.682 -2.59 (0.01)
Physical health satisfaction 5, 2.3 5.9, 2.3 0.871 -2.48 (0.014)
Physical health comparison 6.2, 2.1 6.6, 2.1 0.776 -1.31 (0.191)
Mental health rating 5.3, 2.1 6, 2 0.673 -2.2 (0.029)
Mental health satisfaction 4.7, 2.6 5.5, 2.5 0.775 -2.02 (0.044)
Mental health comparison 5.7, 2.5 6.2, 2.5 0.896 -1.33 (0.184)

175
Quality Satisfaction
Physical
Health
Mental
Health
Figure B.2. Distribution of quality and satisfaction ratings of physical and mental health.
Based on these findings, three separate multiple imputations and models were run and
descriptively compared. Within each model, all demographic and descriptive variables were
included, with dummy coded variables for multiple selection categorical variables. Race was
dummy coded as Asian (n=44, 23%) or White (n=113, 58%). Ethnicity was coded as Hispanic
(n=26, 13%). Musical genre was dummy coded as Classical musician (n=155, 79%), and the
instrumental groups were dummy coded as Strings (n=71, 42%), Keyboard (n=26, 15%), Brass
(n=34, 20%), and Woodwind (n=30, 18%). The three separate models each contained a different
outcome variable: physical health (general quality rating), mental health (general quality rating),
and PERMA composite score (mean score of all PERMA sub-items). When multiply imputing
datasets for each of these three models, the remaining outcome variables were not included to
conduct descriptive comparison across models. This decision was based on the fact that there
were statistically significant differences observed in physical and mental health between

176
complete and incomplete respondents. Sensitivity analysis of PERMA composite scores was not
possible due to the PERMA outcome variable being placed at the end of the survey, and all 72
incomplete respondents did not complete any portion of the PERMA well-being assessment.
However, within the complete responses, the PERMA composite score was highly correlated
with both physical health (Pearson r=0.36, p<0.01) and mental health (Pearson r=0.56, p<0.01).
Due to the high number of survey items and relatively small sample size in comparison,
well-being contributor variables were condensed into five EMP composite scores using the
model constructs of Musician Continuum, Peripheral Variables, Physical Environment, Interface
Effectors, and Musician Work Schedule. Out of the three items for each variable (quality rating,
satisfaction, and importance), only quality rating on a Likert scale, “How would you rate your
current status in _____? (0=poor, 10=excellent)”, were included. Composite scores were
created as a simple mean score across the EMP construct items. Three items that were dependent
on the respondent engaging in the activity were excluded from the composite score calculation
(paid activities and performances). Survey items within each composite score can be found in
Table B.2.
Table B.2. Survey item description.
EMP Composite Variable
Total # of
Survey
Items
Item Descriptors
Musician Continuum 7 Auditory Health
Musculoskeletal Health
Posture
Motor Function
Cognitive Perceptual Function
Stress Management
Performance Anxiety
Peripheral Variables 2 Non-musical School Activities
Non-musical Leisure Activities
Physical Environment 5 Practice Space Temperature
University Environment

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Living Space Environment
Practice Space Noise
Practice Space Lighting
Interface Effectors 4 Instrument Demands
Repertoire Technical Difficulty
Repertoire Endurance Demands
Repertoire Mental Load
Musician Work Schedule 5 Practice Physical Repetition
Solo Practice Session
Ensemble Rehearsal
Mental Practice Session
Practice Breaks
To determine the number of datasets to multiply impute, the fraction of missing data was
examined for all three datasets that were multiply imputed (physical health, mental health, and
PERMA). Out of the three models, the physical and mental health outcome models had a fraction
of missing information (FMI) of 5.6%, and the PERMA outcome model had an FMI of 7.2%.
Following von Hippel (2018)’s two-stage calculation for the proportionate number of datasets to
multiple impute, ten datasets were imputed for all three datasets.
Ten full datasets were imputed for each of the three outcome variables. All MI datasets
converged within 30 iterations. After three datasets were imputed, regression modeling was
conducted on all imputed datasets, and parameter estimates were pooled to generate association
between each independent variable with the outcome variables. The PROC MI, PROC GLM, and
PROC MIANALYZE packages in SAS 9.4 were used to impute datasets, conduct regression
modeling, and pool parameter estimates across datasets. and analyze datasets.
B.2 Limitations
The creation of EMP Composite scores was based on theoretical understanding of
musician well-being using the EMP model, as well as the practicality of the nature of attrition
being mostly at the end of each survey page, which corresponded to EMP constructs. However,

178
through creating composite scores prior to conducting MI analysis, some existing data has been
excluded and multiply imputed instead, because the composite score was only created if every
item within the construct was answered. A larger sample size would have allowed for every
individual survey item to be included, which may have increased the rigor of the regression
results.
An additional important limitation to this analysis is the fact that the data were not
missing at random. Schager & Graham (2002) outline some possible methods to resolve this
problem. In the case of attrition related to the outcome as is the case with the missing data in this
analysis, it is recommended to weight the complete datasets to more closely resemble the
incomplete data. Weighting is based on regression analysis of the existing data, prior to multiple
imputation analysis. Weights are considered to be relatively easy to apply to data missing in a
monotone pattern (attrition at specific points of the survey).
Two methods exist for the weighting of data missing not at random. One is the selection
model, where the outcome measured is directly impacting respondents’ willingness to provide
data. While this method is beneficial for studies that include repetitive data collection or
longitudinal study, due to the cross-sectional design of the survey and the monotone pattern of
attrition (respondents who stopped responding after one section did not complete later sections of
the survey), this method may not provide much additional benefit (Matsuyama, 2004; Schafer &
Graham, 2002). Additionally, it is impossible to test in the survey data whether missingness was
directly impacted by the lower physical and mental health scores.
A pattern-mixture model is an alternative method to imputing non-random missing data.
In this method, observed responses are categorized by missingness and each subset provides
model parameters. There is debate within the statistical community on the effectiveness of

179
pattern-mixture modeling. On one hand, when missingness is truly caused by the measured
variable of interest, not accounting for this attrition bias can lead to significant error in the
multiply imputed datasets and resulting parameter estimates (Collins et al., 2001). However,
similar to the problems with a selection model, with a cross-sectional survey of less than 200
responses, it is impossible to measure the exact cause of correlation of missingness to outcome
variable.
In this study analysis, due to the limitations of the dataset, the statistically significant
difference noted in outcome variables of physical and mental health were not accounted for
directly in the multiple imputation analysis. Instead, three separate models were run and
descriptively compared. Future study should consider methods to increase sample size and
potentially scrambling the survey questionnaire item to decrease attrition that may have been
impacted by the outcome variable.

180
B.3 References
Collins, L. M., Schafer, J. L., & Kam, C.-M. (2001). A comparison of inclusive and restrictive
strategies in modern missing data procedures. Psychological Methods, 6(4), 330.
https://doi.org/10.1037//1082-989X.6.4.330
Matsuyama, Y. (2004). Analysis of Missing Data in Longitudinal Studies: A Review. Japanese
Journal of Biometrics, 25(2), 89-116. https://doi.org/10.5691/jjb.25.89
Schafer, J. L., & Graham, J. W. (2002). Missing data: our view of the state of the art.
Psychological Methods, 7(2), 147. https://doi.org/10.3389/fpsyg.2022.885739

181
APPENDIX C Modified Daily Reconstruction Method

182
Final DRM
Start of Block: Sleep
Q1 Please complete this daily activity log every day before going to bed for 7 consecutive days.
In this log, you will be asked to recount your activities from the past 24 hours, starting with your sleep
the night before and through each activity you engaged in afterwards.
Q368 What is your name?
________________________________________________________________
Q2 What time did you go to sleep last night?
________________________________________________________________
Q3 What time did you wake up this morning?
________________________________________________________________
Q4 On a scale of 0=worst to 10=best quality of sleep,
0 1 2 3 4 5 6 7 8 9 10
How would you rate your sleep last night? ()

183
End of Block: Sleep
Start of Block: NASA TLX
Q1 In this section, reflect on your entire previous day.
Q2 Indicate any symptoms you experienced throughout your day (select all that apply)
▢ Anxiety or nervousness (1)
▢ Low motivation (2)
▢ Trouble concentration (3)
▢ Fatigue or tiredness (4)
▢ Headaches or migraines (5)
▢ Muscle tension or discomfort (6)
▢ Eye-related symptoms (7)
▢ Nose/throat-related symptoms (8)
▢ Skin-related symptoms (9)
▢ Other (please specify) (10)
__________________________________________________
▢ None of the above (11)

184
Q3 On a scale of 0=none, 10=a lot,
0 1 2 3 4 5 6 7 8 9 10
How much mental activity was required for your
whole day? (Thinking, deciding, remembering, etc.) ()
How much physical activity was required for your
whole day? (Pushing, pulling, walking, etc.) ()
How much time pressure did you feel from activities
over your whole day? ()
How hard did you have to work (with your body or
your mind) over your whole day? ()
Q4 On a scale of 0=extremely displeased, 10=extremely pleased
0 1 2 3 4 5 6 7 8 9 10
How pleased were you with your performance of
activities over your whole day? ()
Q5 On a scale of 0=not at all frustrated, 10=very frustrated
0 1 2 3 4 5 6 7 8 9 10
How frustrated were your from your activities over
your whole day? ()
End of Block: NASA TLX
Start of Block: Episode 1

185
Q1 In this section, recount your day in chronological order from the moment you woke up until right
before you started this survey. Think of your day as a continuous series of scenes or episodes in a film.
Give each episode a brief name that will help you remember it (for example, "orchestra rehearsal",
"individual practice session", or "eat lunch with friend").
Write down the approximate times at which each episode began and ended. The episodes people
identify usually last between 15 minutes and 2 hours. Indications of the end of an episode might be
going to a different location, ending one activity and starting another, or a change in the people you are
interacting with.
For each episode, provide a 1-3 sentence description (for example, the description for "Individual
practice session" can be described as "Practicing in university's practice rooms on solo/ensemble
repertoire") and rate your well-being experiences.
For repeated episodes, use the same name used previously and skip the description unless there are
important differences.
Q2 Please provide a brief name for this episode
________________________________________________________________
Q3 About what time did you begin this episode?
________________________________________________________________
Q4 About what time did you end this episode?
________________________________________________________________

186
Q5 If this is a new episode, please provide a 1-3 sentence description of the episode
________________________________________________________________
Q6 On a scale of 0=not at all, 10=completely,
0 1 2 3 4 5 6 7 8 9 10
To what extent did you feel contented/happy during
this episode? ()
To what extent did you find this episode valuable and
meaningful? ()
Q7 Do you have another episode to report?
oYes (1)
o No (2)
Skip To: End of Survey If Do you have another episode to report? = No
End of Block: Episode 1
Start of Block: Episode 2
Q26 Please provide a brief name for this episode
________________________________________________________________
Q27 About what time did you begin this episode?
________________________________________________________________

187
Q28 About what time did you end this episode?
________________________________________________________________
Q29 If this is a new episode, please provide a 1-3 sentence description of the episode
________________________________________________________________
Q30 On a scale of 0=not at all, 10=completely,
0 1 2 3 4 5 6 7 8 9 10
To what extent did you feel contented/happy during
this episode? ()
To what extent did you find this episode valuable and
meaningful? ()
Q31 Do you have another episode to report?
oYes (1)
o No (2)
Skip To: End of Survey If Do you have another episode to report? = No

188
APPENDIX D List of all Reported Activities and Occupational
Therapy Practice Framework (OTPF) Categorization

189
Table D.1. Reported activities and OTPF categorization.
OTPF Category Please provide a brief name for this episode
ADL Morning routine Becoming more awake
ADL Morning routine Breakfast and cleaning
ADL Morning routine Breakfast and computer working
ADL Morning routine Breakfast and get ready for school
ADL Morning routine Breakfast and get ready for work at school
ADL Morning routine Breakfast and get stuff ready
ADL Morning routine breakfast and preparing for school
ADL Morning routine Getting ready for the day
ADL Morning routine Getting up and going to the music building
ADL Morning routine Morning
ADL Morning routine Morning beginning
ADL Morning routine Morning routine
ADL Morning routine Preparing for the day
ADL Morning routine Prepping for the day
ADL Morning routine Start of the day
ADL Nightime routine dinner and bedtime
ADL Nightime routine Dinner and prepare for bedtime
ADL Nightime routine Dinner at home and bedtime
ADL Nightime routine dinner time, homework and bedtime
ADL Nightime routine prepare for bedtime
Education Club Club meeting
Education Club music club training
Education Schoolwork Astronomy lecture
Education Schoolwork Astronomy midterm
Education Schoolwork Aural skills class
Education Schoolwork Class
Education Schoolwork Class 1
Education Schoolwork Class 2
Education Schoolwork Class at case western
Education Schoolwork classes at school
Education Schoolwork Essay writing
Education Schoolwork Evening class
Education Schoolwork Final
Education Schoolwork Finals Work
Education Schoolwork GE Class
Education Schoolwork Global Musicianship Class
Education Schoolwork Go to class
Education Schoolwork Homework
Education Schoolwork Homework / Practicing
Education Schoolwork Homework- essay writing

190
Education Schoolwork homework time - bed time
Education Schoolwork Jazz class discussion
Education Schoolwork Jazz history class
Education Schoolwork Keyboard skills class
Education Schoolwork Lecture watching
Education Schoolwork library research
Education Schoolwork Music Class
Education Schoolwork Music theory class
Education Schoolwork Musicianship class
Education Schoolwork Musicology 1 class
Education Schoolwork Nap and study time
Education Schoolwork Night class at school
Education Schoolwork Political Violence Lecture
Education Schoolwork Taking sexual harassment prevention online class
Education Schoolwork Worked on essay for class
Education Schoolwork Writing
Education_music Career planning Researching Music Festivals
Education_music
Instrument
maintenance Practice tuning the piano
Education_music
Instrument
maintenance Tuning my piano
Education_music Lesson Lesson
Education_music Lesson Piano Class
Education_music Lesson Piano Lesson
Education_music Lesson Sitar Class
Education_music Lesson TA Lesson
Education_music Lesson Violin lesson
Education_music Perform Akron symphony concert
Education_music Perform Choir soundcheck and concert
Education_music Perform Church gig
Education_music Perform Gig
Education_music Perform Preparing for performance, performance, reception
Education_music Perform Studio Class
Education_music Perform Technical jury
Education_music Perform UCLA Lab School Outreach Event
Education_music Practice Akron rehearsal
Education_music Practice Akron Symphony rehearsal
Education_music Practice Break
Education_music Practice Chamber music rehearsal
Education_music Practice Chamber rehearsal
Education_music Practice Chamber strings rehearsal
Education_music Practice Choir Rehearsal
Education_music Practice First practice session

191
Education_music Practice Going to the music building and warming up
Education_music Practice Individual practice session
Education_music Practice Morning practice
Education_music Practice Orchestra Class
Education_music Practice Orchestra rehearsal
Education_music Practice Orchestra rehearsal
Education_music Practice Orchestra soundcheck
Education_music Practice Personal practice
Education_music Practice Personal practice
Education_music Practice Practice
Education_music Practice Practice
Education_music Practice Practice and friend
Education_music Practice Practice session
Education_music Practice Practice session
Education_music Practice Practice session 1
Education_music Practice Practice session 2
Education_music Practice Practice session 3
Education_music Practice Practice session and prepare for work
Education_music Practice Practice session at school
Education_music Practice Practice solo
Education_music Practice Practiced
Education_music Practice Rehearsal
Education_music Practice Rehearsal/recording
Education_music Practice Rehearsing for my chamber group
Education_music Practice School work and rehearsal
Education_music Practice Second practice session
Education_music Practice Solo practice session
Education_music Practice Solo practicing session
Education_music Practice Third practice session
Education_music Teach Prepare recital program
Education_music Teach Preparing for the student recital
Education_music Teach Student recital!
Education_music Teach Teach
Education_music Teach Teach online
Education_music Teach Teach piano lessons
Education_music Teach Teaching
Education_music Teach Uploading recital video online
Health
Management
Health
appointment Alcoholics Anonymous meeting
Health
Management
Health
appointment Attended AA meeting and drove home
Health
Management
Health
appointment Attended Alcoholics Anonymous meeting

192
Health
Management
Health
appointment Optometry Appointment
Health
Management
Health
appointment Therapy session
Health
Management Physical activity Gym
Health
Management Physical activity Running
Health
Management Physical activity Working out
IADL Commute Back to the dorm
IADL Commute Commute to school
IADL Commute Driving to school
IADL Commute Ubered home
IADL Commute Walk back to dorm
IADL Commute Walking back to the dorm and getting dinner
IADL Commute Walking to a cafe by the music building
IADL Commute Winding down
IADL Emergency Lost wallet
IADL Groceries Dinner & procrastinating
IADL Groceries Errands
IADL Groceries groceries and gas loading
IADL Groceries Grocery store trip
IADL Groceries
Went to have brunch with partner, then go to market to
prepare for dinner
IADL Housekeeping breakfast and laundry time
IADL Housekeeping Clean my apartment
IADL Housekeeping
Clean up apartment after hangout and dinner, then do
nothing…
IADL Housekeeping Clean up/fix things around the house
IADL Housekeeping Free Time / Housekeeping
IADL Housekeeping House chores
IADL Housekeeping Morning and Laundry
IADL Mealtime Ate dinner
IADL Mealtime Ate lunch
IADL Mealtime Back to the dorm 2
IADL Mealtime Breakfast
IADL Mealtime Brunch
IADL Mealtime Dinner
IADL Mealtime Dinner
IADL Mealtime Dinner + nap
IADL Mealtime Dinner and relax
IADL Mealtime Dinner break
IADL Mealtime Eat breakfast/make lunch
IADL Mealtime Getting and eating breakfast, preparing to practice

193
IADL Mealtime Lunch
IADL Mealtime Lunch & nap
IADL Mealtime Lunch and miscellaneous study
IADL Mealtime lunch and work off campus
IADL Mealtime Lunch break
IADL Mealtime lunch preparing
IADL Mealtime lunch time and check work at office
IADL Mealtime Lunch/early dinner
IADL Mealtime Meal prep
IADL Mealtime Work at school
IADL Packing Packing
IADL Social Mealtime Ate dinner with a friend
IADL Social Mealtime Dinner and getting into the study zone
IADL Social Mealtime Dinner and hanging out with friends
IADL Social Mealtime Dinner with a Friend
IADL Social Mealtime Dinner with boyfriend
IADL Social Mealtime Dinner with friends, game night, and birthday celebration
IADL Social Mealtime Hanging around with friends and getting dinner
IADL Social Mealtime Hangout
IADL Social Mealtime Have dinner with partner
IADL Social Mealtime Lunch with partner
IADL Social Mealtime Post-performance
IADL Social Mealtime Relaxing
Leisure Leisure Bookstore
Leisure Leisure Danish string quartet concert
Leisure Leisure Drawing/journaling
Leisure Leisure Opera
Leisure Leisure Reading
Leisure Leisure Watched masterclass
Leisure Leisure Watching Ballet
Rest and Sleep Nap Nap
Rest and Sleep Nap Resting
Rest and Sleep Nap Took a nap
Rest and Sleep Procrastinate Procrastinating….
Social
Participation Socialize Calling family and working on this survey
Social
Participation Socialize Coffee with quartet
Social
Participation Socialize Date day with boyfriend
Social
Participation Socialize Fondue night with friends
Social
Participation Socialize Meet friend

194
Social
Participation Socialize Netflix with friends
Social
Participation Socialize Post concert hang
Social
Participation Socialize Post-studio class, back to the dorm with friends
Social
Participation Socialize Quality time with roommates
Social
Participation Socialize Talk to friend
Social
Participation Socialize Video chatting with my partner’s parents
Social
Participation Socialize Video-chatting my parents
Social
Participation Socialize Watched television with dad
Social
Participation socialize Watched television with mom
Work Work Get prizes for event at school - work related
Work Work Internship Interview
Work Work Library work
Work Work Library work
Work Work Music library work
Work Work Training Session
Work Work Weekend Job
Work Work Went to training for new teaching position.
Work Work Work
Work Work Work at music library
Work Work Work off campus
Work Work Work on sunday

Abstract (if available)

Abstract Since its inception, occupational science has theorized the role of occupational engagement in health and well-being outcomes. While different schools of thought have emerged, engaging in meaningful occupations that contribute to one’s identity is generally seen as beneficial. Much of the existing literature on the intersection of occupation and health has focused on instances where obstacles exist to engagement in important occupations (e.g., health conditions or environmental constraints), demonstrating the importance of supporting engagement to facilitate health and well-being. Given this knowledge, one may assume that an occupational group such as musicians who engage in a creative and fulfilling occupation would experience abundant health and wellness. However, on the contrary, musicians are at risk for many health impairments that are directly associated with their career occupation. A plethora of occupation-related health impairments have been identified within musicians, including playing-related musculoskeletal disorders (PRMD), performance anxiety, and hearing loss, among others. While extensive literature exists on the biomechanics of PRMD development or the high prevalence and impacts of performance anxiety, there has been limited focus on interventions to support musician well-being. Overall, despite many wide-scale initiatives to support musician health, occupation-related health impairments remain highly prevalent in musicians.
One component currently missing in the literature is an understanding of musicians as a unique occupational group. Research studies have adopted one of three theoretical foundations to apply to musicians: musician as athlete, musician as worker, or musician as performing artist. Similarly, clinicians often approach musician injury with occupational health frameworks (i.e., worker wellness) or performance-based frameworks (i.e., athlete performance, performing artist), resulting in musicians feeling that practitioners fail to understand their unique needs as performing artists. To better promote health and well-being in musicians, there is a need for a foundational understanding of musicians as a unique occupational group.
While there is no validated foundational framework to understand musician well-being and address the unique physical and mental health concerns in musicians, a recent study used a single case study to develop the Ecology of Musical Performance (EMP) model to understand and more effectively treat a musician with PRMD. Using the EMP model as a foundational framework, this dissertation examined musician health using three perspectives: existing literature, national trends, and daily lived experiences. In Chapter 2, a mapping review was conducted to create a topography of existing musician well-being articles, using EMP model well-being determinants to categorize articles. Next, in Chapter 3, a national survey was conducted to quantitatively examine the associations of EMP well-being determinants with various well-being outcomes. Building on the survey findings, in Chapter 4, the lived experiences of a small group of music students were explored using daily activity logs and interviews.
This dissertation was the first study to apply the EMP model as a foundational framework; much was uncovered about the model’s current usefulness and potential areas for modification. Although the survey illustrated the importance of all five model constructs as well-being determinants, the literature review identified many gaps in the existing literature. There is also an opportunity for further development in the theoretical framework to facilitate musician well-being, as the model was developed to support clinicians’ understanding of musicians for evaluation and treatment and was not designed in a way that translates to empirical measurement in research studies easily. Finally, preliminary interview findings highlighted the impact of multi-faceted occupational identities of musicians on their health behaviors and well-being outcomes. The knowledge gaps within musician well-being literature are a call to action to occupational scientists and other scholars, as this study demonstrated the need for more theoretical development in understanding the occupational identities of musicians and how they transact with well-being.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Fukumura, Yoko Ellie (author)

Core Title Exploring the intersection of occupational engagement and well-being in student musicians: A multi-method study

School School of Dentistry

Degree Doctor of Philosophy

Degree Program Occupational Science

Degree Conferral Date 2024-12

Publication Date 12/02/2024

Defense Date 09/16/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag day reconstruction method,mixed methods,musician health,occupational identity,survey

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Roll, Shawn C. (committee chair), Pyatak, Beth (committee member), Sideris, John (committee member), Wolff, Aviva L. (committee member)

Creator Email fukumura@usc.edu,yoko.e.fukumura@gmail.com

Unique identifier UC11399E4G3

Identifier etd-FukumuraYo-13661.pdf (filename)

Legacy Identifier etd-FukumuraYo-13661

Document Type Dissertation

Format theses (aat)

Rights Fukumura, Yoko Ellie

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Source 20241202-usctheses-batch-1225 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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