The Effect of Therapeutic Music Playlists on Symptoms of Anxiety: A Clinical Trial
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Introduction
Mental health diagnoses affect a significant portion of the population, with 50% of all Americans receiving at least one mental illness diagnosis in their lifetime (American Psychological Association, 2018). The percentage of people who will receive a mental illness diagnosis in their lifetime is higher than the 39.66% who will receive a diagnosis of cancer (American Cancer Association, 2018), and the 47.7% who will be diagnosed with coronary disease (American Heart Association, 2017). Additionally, 45% percent of adults with a mental health diagnosis also meet the criteria for at least one other disorder (American Psychological Association, 2018). The prevalence of Americans diagnosed with specific conditions that the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) lists emotion dysregulation as a key component of are as follows: anxiety disorders at 31.1%, other mood disorders at 21.4%, attention deficit hyperactivity disorder (ADHD) at 8.7%, posttraumatic stress disorder (PTSD) at 6.8%, bipolar disorder at 4.4%, eating disorders at 2.7%, obsessive compulsive disorder (OCD) at 2.3%, and borderline personality disorder (BPD) at 1.4%. (American Psychiatric Association, 2013; National Institute of Mental Health, 2017).
In a survey by Bautch (2019), 84% of participants reported using music for the purposes of regulating emotions. As is noted in a study performed by McFerran et al. (2010), people do not always select music for themselves that will improve their emotional state. In their research they found that it is not uncommon for people who are struggling with mood to select music which can actually intensify rumination and which can have a detrimental effect on their emotions. However, music has the ability to assist in mood elevation. The effectiveness of music listening as a means of improving scores on the state section of the STAI was demonstrated in a study by De La Torre-Luque et al. (2017) where within group differences were found in the experimental group (p
In her 2013 systematic review, Sena Moore explained these results by examining the neural correlates between the structures involved in emotion regulation and the impact of music experiences on those neural structures. Neural structures and activity that are related to emotion regulation include activation of the anterior cingulate cortex (ACC), the orbitofrontal cortex (OFC), and the lateral prefrontal cortex (PFC), the latter of which has a mediating effect on the amygdala. Multiple studies have used neural imaging as well as other measures to demonstrate the effect of music listening experiences on an increase of activation of the OFC, the ACC, and a decrease of activation in the amygdala (Blood & Zatorre, 2001; Brown et al., 2004, Mitterschiffthaler et al., 2007; Berns & Moore, 2012; Berns et al., 2010, Flores-Gutierrez et al., 2007; Koelsch et al., 2006; Levitin, 2013; Alluri et al, 2015; Hou et al., 2017). Activity in the limbic system is also altered by music listening, engaging the limbic and the paralimbic systems and improving functional connectivity of the limbic regions (Brown et al., 2004; Alluri et al., 2015). This indicates that music may facilitate neurological functioning that supports optimal emotion regulation.
Both music listening as well as music therapy has long been utilized as a means of effectively addressing goals of emotion regulation. Beginning in the 1940’s, music therapy was used as a means of addressing symptoms of what eventually became known as PTSD, though it was then called shell shock. Interventions currently used in addressing symptoms of anxiety include music assisted relaxation, guided imagery and music, improvisation, and therapeutic playlists (Wurjatmiko, 2019; Karadag et al., 2019; Ribeiro et al., 2018; Millet & Gooding, 2017; Pavlov et al., 2017; Hwang et al., 2013; Alam et al., 2016; Hammer, 1996; Bradt & Teague, 2018; Zarate, 2016; Hense et al., 2018). Many of these interventions are done in the presence of a music therapist and are not self-administered. Notable exceptions are therapeutic playlists, and music assisted relaxation, which are interventions that can be taught and used in the home environment. A therapeutic playlist is a sequence of songs that are targeted to reach a goal. They are frequently used as a means of addressing dysregulation of emotions, most commonly symptoms of anxiety and/or depression. The present study will address the use of one-directional mood vectoring playlists and musical contour regulation playlists in the treatment of symptoms of anxiety. For the purposes of this study, Shatin’s (1970) definition of mood vectoring will be used, which is “The directed alteration of mood through music- an alteration from one affective pole to it’s opposite or it’s contrast” (pg. 81). Musical contour regulation, on the other hand, alternate between high- and low-arousal music experiences in order to support healthy management of high- and low-arousal situations which may induce symptoms of anxiety (Sena Moore, 2018).
This study will utilize two different kinds of playlists which will be designed to address a range of emotions and assist listeners in shifting from dysregulated to regulated mood states. Music will be participant selected from their own collection of recorded music and organized in collaboration with a board-certified music therapist. Playlists will be designed to facilitate a reduction of anxiety symptoms.
In addition, it is important to also examine the feasibility of both interventions, as well as barriers to faithful adherence to the protocol that participants experienced. This will assist practitioners in the identification of persons who would benefit, as well as those for whom the interventions may not provide optimal results. The results of this study may also provide information as to whether there are changes that could be made to improve accessibility and increase fidelity in the protocol in order to facilitate improved outcomes for patients.
Purpose
This mixed-methods study will examine the effectiveness of mood vectoring playlists and musical contour regulation playlists in order to determine which is a more effective in the treatment of anxiety symptoms. Quantitative data will be used to collect evidence of comparative effectiveness. Qualitative data will be used to discern feasibility as well as identify potential barriers to effective fulfillment of the protocol. Synthesized data will also be used to identify what effects control variables as well as data gathered during the final interviews have over the participant’s response to the intervention. Control variables will include trait anxiety, mental health diagnosis, and previous musical experience. The researcher will collect additional data in order to evaluate differences in effectiveness between two different theoretically-distinct interventions of how to facilitate optimal emotion regulation. These two theories have never been examined in a side by side manner before, as they will be in this study.
The research supporting the development of the musical contour regulation playlist comes from a study conducted by Sena Moore and Hansen-Abromeit (2018). The intervention which they tested was a musical contour regulation facilitation, in which they sought to train the neural pathways associated with emotion regulation through alternating music between high, mid, and low arousal throughout a music therapy session. This study is examining if the same principle could be effective when presented in the format of a playlist. This approach is consistent with the Neurologic Music Therapy (NMT) approach of Music Psychotherapy and Counseling (MPC). The basis for the one-directional mood vectoring playlist is based on the work of Hense et al. (2018), in which they identified healthy and unhealthy use of music listening and proposed a model for healthy use of music to assist with emotion regulation. It also builds off of the iso principle, the origins and use of which is detailed in Heidersheit and Madison’s study (2015). Iso principle states that one must first match the music to the state in which the person is already in before gradually shifting to facilitate the desired change. The one-directional mood vectoring playlist is also consistent with the NMT approach of MPC, as the information detailing said approach is vague enough to apply to both playlist interventions.
This topic was determined to be especially relevant after a study conducted earlier by Bautch, (2019) in which 73.45% of participants reported using music listening to match their emotions. As Hense et al. (2018) outlined in their study, this can be damaging if one is using music in a manner to reinforce negative emotions and increase rumination. This finding is pertinent for persons who are managing mood disorders.
The researcher theorizes that the musical contour regulation playlist will have a greater effect in facilitating relief from symptoms of anxiety over the full course of the study, but that the one-directional mood vectoring playlist will provide greater immediate relief. This is due to the data supporting use of the iso principle in the management of symptoms of anxiety, as well as the study supporting the use of musical contour regulation facilitation in long term improvement.
Quantitative measures will be the self-report treatment log as well as the Spielberger State Trait Anxiety Inventory (1984). Qualitative data will be collected via interview and will examine the barriers to faithful adherence to the protocol which was experienced by the participants in the study, as well as the feasibility of these self-administered interventions. Qualitative data collected in the exit interviews will be recorded, coded, and analyzed using a semantic approach and according to the protocol of Braun and Clarke (2006).
This study will identify whether musical contour regulation playlists are more or less effective than one-directional mood vectoring playlist in the management of anxiety symptoms. It will also examine the feasibility of self-administered therapeutic playlist interventions as well as identify potential barriers.
Method
Research Design
This study was a sequential explanatory mixed-methods study which included a clinical trial and secondary data analysis. It compared the effectiveness of one directional mood vectoring playlists (MV-P) with the effectiveness of musical contour regulation playlists (MCR-P) on improving symptoms of anxiety. This study is also explored the feasibility of self-administered interventions utilized after a psychoeducational session, as well as potential barriers to faithful adherence to treatment protocol. The data from this portion of the study was used to explore how these interventions worked for the participants and alert to any possible counterindications.
Participants
The sample was drawn from the United States. All participants were recruited online through social media. Inclusionary criteria included that all participants must be between the ages of 18 and 70 and report experiencing symptoms of anxiety on a regular basis. This was operationally defined as feeling anxiety and worry more often than not for at least 6 months and finding it difficult to control. These criteria are taken from the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (American Psychiatric Association, 2015) diagnostic criteria for Generalized Anxiety Disorder. No actual diagnoses were made over the course of this study. Exclusionary criteria included being unable to speak and write English, as well as having a medical condition which caused hearing impairment. Participants needed to have access to a computer and a device on which they could listen to recorded music. The participants could have made contact with the researcher via phone or e-mail, whichever was more convenient for them. All meetings took place over Zoom, https://zoom.us/. This study contained a sample of 10 participants.
Intervention
The interventions examined in this study are therapeutic playlists which are designed to reduce symptoms of anxiety. For the creation of both playlists, the researcher and participant collaborated using recorded music the participant selected from their own collection. Playlists lasted no more than 20 minutes as a way of regulating the dose. All playlists were created in collaboration with the researcher who is a board-certified music therapist. Information regarding the intervention was outlined in alignment with the NIH reporting guidelines for music-based interventions (Robb, 2011).
MCR-P Treatment
Participants who used the musical contour regulation playlist (MCR-P) collaborated with the researcher to create a playlist which alternates between various states of arousal, organized as outlined in Sena Moore and Hanson-Abromeit (2018). Playlists alternated between music supporting high, mid, and low arousal states in order to stimulate the neural pathways associated with emotion regulation. Musical contour regulation playlists ended on a mid-level arousal song, which supports a calm state at the end of their session. The researcher instructed participants in how to use said playlists, as well as the options for activities to take part in during music listening.
Activities for both groups included movement, drawing, breathing exercises, or imagery. Music was selected from the participant’s collection in collaboration and followed guidelines for appropriate music for relaxation in the final pieces of the playlist. Guidelines for relaxing properties of music will follow the findings of Hooper’s study (2012) in conjunction with the low-arousal properties of Hanson-Abromeit and Sena Moore’s study (2015). This combination of patient preferred music and incorporation of the relaxing properties of specific musical qualities are expected to reduce a participant’s level of anxiety given neural correlates as well as results from previous studies on the effects of music on emotion (Shatin, 1970; Stratton & Zalanowski, 1991; Sena Moore, 2013; Mitterschiffthaler et al., 2007; Levitin, 2013; Koelsch et al., 2006; Hou et al., 2017; Flores-Gutiérrez & Terán Camarena, 2015; Flores-Gutiérez et al., 2007; de la Torre-Luque, 2017; Brown et al., 2004; Blood & Zatorre, 2001; and Alluri et al. 2015).
MV-P Treatment
Data regarding the mood vectoring playlist (MV-P) was pulled from the researcher’s thesis study on the effectiveness of one-directional mood vectoring playlists in the treatment of symptoms of anxiety. The researcher’s thesis study used the same time frame and the same measures. The MV-Ps were also created collaboratively using participant selected recorded music from their personal collection. The playlist is comprised of music which incrementally vectors from dysregulated anxiety to a regulated emotional state. Music that was selected also followed guidelines for appropriate music for relaxation in the final pieces of the playlist. Guidelines for relaxing properties of music matched those used for the MCR-P.
Procedure
After the participants read and signed the informed consent document online, the researcher contacted the participant to set up the initial meeting time. All meetings took place on Zoom. In the initial meeting, the researcher implemented the psychoeducational component by explaining the procedure for the treatment. The researcher also instructed the participant on the website for recording data and using the apparatus. The researcher reviewed the procedure and allowed time for any questions they had, as well as scheduling the final meeting time. They were also provided with the link for the STAI during this meeting.
The participants were instructed to engage in the listening intervention daily for 2 weeks. The participants took the STAI before starting their 2 weeks of a music listening intervention, as well as after they have finished the study. They also filled out a treatment log as a fidelity check (see attached treatment log form). All participants were contacted via email weekly for a fidelity check and to answer any questions the participant had.
Figure 1
Sample Diary Card
Date
Pre-listening anxiety (1-5)
Post-listening anxiety (1-5)
Activity
At the final session, participants were given the link for the posttest STAI and took part in an exit interview. They were asked what challenges/barriers there were to completion of the protocol, and what their experience was like using the intervention. They then were asked if they had any other questions or observations on the process that they would like to share.
Figure 2
Progression of Study
Instrumentation
Study Variables
The dependent variable in this study is anxiety, which is divided into state, trait, and momentary anxiety. State anxiety is anxiety which fluctuates dependent on circumstances. Trait anxiety is the level of anxiety which a person generally experiences regardless of circumstances. Momentary anxiety, for the purposes of this study, is the anxiety that is experienced by a person which can change quickly and is measured by the pre- to post-listening anxiety scores rated by the Likert-type scale. State and trait anxiety was measured by the Spielberger State Trait Anxiety Inventory (STAI).
The independent variable in this study is the type of playlist. The MV-P consisted of a playlist of songs which began with a piece representing a dysregulated level of anxiety and incrementally shifting toward a piece representing a regulated, calm emotion. The MCR-P consisted of a playlist of songs which shuttled back and forth between songs that cued high, mid, and low arousal states. The data on the MV-P intervention will be collected from the researcher’s thesis study on feasibility and effectiveness of one-directional mood vectoring playlists in the management of symptoms of anxiety.
Measures
The dependent variable is state anxiety. Trait anxiety was analyzed as a covariate. The dependent measure will be the Spielberger State Trait Anxiety Inventory (STAI). The STAI is an interval level self-report questionnaire which consists of 40 questions split evenly between the state and trait subsections. The state portion measures anxiety that a participant experiences in response to a stressful stimulus, whereas the trait portion measures the way a participant generally feels. In this study, the trait subsection will be analyzed as a covariate. The STAI (Spielberger, 1972; Spielberger et al, 1983) is strongly recommended as a measure for anxiety levels (Vitasari et al., 2011), as it shows strong reliability, construct validity, and strong coefficient correlation of the State and Trait portions. Coefficient alpha ranged from .86-.95 for the State portion, and .89-.91 for the Trait portion. This is well above the recommended threshold of .70, giving a strong Cronbach’s alpha in favor of reliability. Test-Retest reliability for the State subtest was high with .73 for males and .77 for females over a period of six months according to Mental Measurements Yearbook (1978). Correlation between State and Trait sections range between .59-.75. There is high correlation between the STAI and other anxiety measures, such as the IPAT and TMAS (r = .73-.85) indicating sufficient validity in measuring the dependent variable.
The self-report dependent measure was the STAI and the treatment log. Data taken on the trait portion of the STAI was examined as a covariate. Interviews were recorded using iTalk on a password protected device. iTalk is a recording app designed by Apple and available on iPhones. It was used to record the interviews, which were then transcribed onto a computer that is password protected. Participants logged all fidelity check data onto Google Docs which was only be accessed by me and that participant. Google Docs is an online application which allows for multiple people to collaborate on a document, and is password protected so only invited participants can alter the text. The diary card was included in the Google Docs. It is a Likert-type scale used to measure pre- and post-listening anxiety is an ordinal measure and ranges from low anxiety represented by a 1 to high anxiety represented by a 5.
Apparatus and Materials
This study required an online copy of the STAI. A treatment log was kept using a Google document, a copy of which is included in the procedure section. They were also given access to a Google document with instructions for the intervention, which was explained during the initial meeting. They also received a document which detailed activities that they could take part in while listening to the music. These activities could include drawing, imagery, movement, or breathing exercises. This study also involved participants using their personal music listening device to listen to the playlists themselves. All meetings with participants took place on Zoom in order to comply with COVID-19 safety measures.
Quantitative Analysis
Descriptive analysis was conducted examining the gender and age range of participants, as well as STAI pre and posttest scores, and pre to post listening scores in order to determine potential interactions. All STAI scores have been converted to percentiles. Inferential statistical examined STAI pre and posttest scores and pre to post listening scores. The values from the MCR-P were then compared to the values from the aforementioned thesis on the MV-P to compare levels of effectiveness.
The STAI is an interval level measure, which allows for the use of a parametric statistical test. When comparing a pretest to a posttest, a two-tailed dependent samples t-test is appropriate with a= 0.05 which is the standard for research in the social sciences. All analyses were conducted using the Statistical Package for the Social Sciences (SPSS). The Likert-style scale is an ordinal level measure, and because of that I chose to take the conservative approach of using a non-parametric test. I chose to use the Wilcoxon signed-rank test, which is the nonparametric equivalent of a two tailed dependent samples t-test (Aron et al., 2013).
Once both t-tests and the Wilcoxon signed-rank test have been performed, they were run only using participants with pretest trait anxiety at or above the 85th percentile. This helped to identify how the interventions impact participants with high trait anxiety and may inform patients for whom the interventions are well suited. Shapiro-Wilk normality tests were run to examine the distributions of differences (Aron et al., 2013). All effect sizes were interpreted according to Rosenthal (1994)
Qualitative Analysis
Qualitative analysis involved verbatim transcription of the exit interviews, and analysis for themes. The theoretical framework for thematic analysis followed the six-step process outlined by Braun and Clarke (2006). A semantic approach was taken, focusing solely on direct information from interviews as opposed to extrapolating potential meaning from the participant’s statements. The coding focused on any barriers to completion of the protocol that was noted by the participants, as well as the immediate and long-term perceived effectiveness of the intervention.
Mixed Analysis
A complementary approach was taken in regards to mixing the quantitative and qualitative data gathered. Data was synthesized using a table, focusing on interview themes that arose with those identified as high responders, as well as themes that arose with those identified as low responders. Examining themes noted by participants according to their responsiveness could give information as to for whom this intervention is especially well suited, as well as any barriers that might be addressed in further development and studies. This gives a picture as to how, why, and for whom the intervention works, and can assist in creating best practice in use of these therapeutic playlists.
Results
CHAPTER 4: RESULTS
Sample Characteristics
This sample consisted of 10 participants located in the United States and recruited through social media. Of the 13 people who agreed to participate, 10 completed the study. The people who did not follow through with the study cited being too busy to participate. None of the people who decided not to participate had begun the listening protocol. All participants were between the ages of 18 and 70 and all were fluent in English. No participants had a diagnosis of a medical condition which interfered with their hearing. Data by participant is included in table 1 below
Table 1
Descriptive Data
______________________________________________________________________________
Participant Gender Age mean pre- mean post- mean State Trait
Range listening listening difference
pre post pre post
1 Non- 18-29 3.86 2.14 1.71 77 48 94 80
binary
2 Male 30-49
3 Female 18-29
4 Male 30-49 3.43 2.64 0.79 92 87 98 92
5 Female 18-29 2.96 2.65 0.31 87 73 95 93
6 Female 18-29 2.25 1.58 0.67 30 40 42 54
7 Female 30-49 2.93 1.36 1.57 98 72 99 89
9 Female 50-70 3.54 1.62 1.92 99 32 100 100
10 Male 30-49 1.86 1.68 0.18 70 4 4 24
11 Female 18-29 1.54 1.00 0.54 59 76 80 80
12 Female 18-29 4.08 3.17 0.92 73 56 89 69
15 Male 30-49 2.57 2.07 0.50 87 78 98 97
Quantitative Descriptive Analysis
Participants’ pretest percentiles on the state portion of the STAI ranged from 30 to 99, with a composite mean of 77.2 and an interquartile range of 22. Their posttest percentiles on the state portion of the STAI ranged from 4 to 87, with a composite mean of 56.6 and an interquartile range of 36. This indicates a significantly larger spread between responses on the posttest than on the pretest. While interquartile range would not generally be included, it is important to include here as both pretests had at least one significant outlier, so range would not be appropriate.
Figure 3
Graphic Representation of STAI State Scores
Participants’ pretest percentiles on the trait portion of the STAI ranged from 4 to 100, with a composite mean of 79.9 and an interquartile range of 18. Their posttest percentiles on the trait portion of the STAI ranged from 24 to 100, with a composite mean of 77.8 and an interquartile range of 24. This indicates that there was slightly more variation in posttest scores than in pretest scores. We must again consider the interquartile range of these scores, as there were also significant outliers within the trait pretest and posttest scores, which renders range inappropriate.
Figure 4
Graphic Representation of STAI Trait Scores
Differences between pre and post listening means by participant are outlined below, in figures 6 and 7. The mean differences between pre-listening to post-listening scores ranged from 0.18 to 1.92, with a median of 0.73. Pre and post listening means broken down by participant can be found in appendix d.
Figure 5
Graphic Representation of Pre to Post Listening Means
Figure 6
Graphic Representation of Difference
Quantitative Inferential Analyses
Research Question 1
The first research question asked: To what extent does a course of treatment involving an MCR-P impact state anxiety? This research question examined the effects (pre- to post-program) of the entire music listening program on state anxiety. The null and alternative hypotheses were as follows:
H0: There is no difference between pre and posttest STAI state anxiety scores following a course of treatment using an MCR-P intervention.
Ha: There is a difference between pre and posttest in STAI state anxiety scores following a course of treatment using an MCR-P intervention.
The results of a two-tailed, dependent samples t-test were significant, t(10) = 2.43, p = .026, d = 0.73, wherein there was a significant decrease in state anxiety scores from pre-program (M = 77.2, SD = 19.87) to post-program (M = 57.5, SD = 24.47). An examination of Cohen’s d suggests a large clinical effect.
Research Question 2
The second research question asked: To what extent does a course of treatment involving an MCR-P impact trait anxiety? This question examined whether there was a change (pre- to post-program) in trait anxiety. The null and alternative hypotheses were as follows:
H0: There will be no significant change in STAI trait anxiety scores following a course of
treatment using an MCR-P intervention.
Ha: There will be a significant change in STAI trait anxiety scores following a course of treatment using an MCR-P intervention.
The second research question examined whether there was a change in trait anxiety following a
course of treatment using an MCR-P intervention. The results of a two-tailed, dependent
samples t-test were significant, t(10) = 0.51, p = .62, wherein there was a not significant
decrease in trait anxiety scores from pre-program (M = 79.9, SD = 27.88) to post-program (M =
77.8, SD = 20.43).
Research Question 3
The third research question asked: To what extent does the MCR-P intervention impact daily anxiety, pre to post per administration? This research question examined the impact of the music listening intervention for each daily administration of the MCR-P. The null and alternative hypotheses were as follows:
H0: There is no difference between pre and posttest daily anxiety scores following a single administration of the MCR-P.
Ha: There is a difference between pre and posttest daily anxiety scores following a single administration of the MCR-P.
A dependent Wilcoxon signed-ranks test indicated that the median posttest daily anxiety scores (Mdn = 1.88), were significantly lower than the pretest daily anxiety scores (Mdn = 2.95), change = -2.80, p = 0.029, r = -.63. Examination of the effect size using r followed parameters as laid out by Cohen (1988) and were found to be large.
Research Question 4
The fourth research question asked: To what extent does a course of treatment involving an MCR-P intervention impact state anxiety in participants with pretest trait anxiety at or above the 85th percentile? This research question examined the effects (pre- to post-program) of the entire music listening program on state anxiety. The null and alternative hypotheses were as follows:
H0: There is no difference between pre and posttest STAI state anxiety scores following a course of treatment using an MCR-P when used by participants with pretest trait anxiety at or above the 85th percentile.
Ha: There is a difference between pre and posttest in STAI state anxiety scores following a course of treatment using an MCR-P when used by participants with pretest trait anxiety at or above the 85th percentile.
This research question examined whether there was a change in state anxiety in participants with pretest trait anxiety at or above the 85th percentile following a course of treatment using an MCR-P intervention. The results of a two-tailed, dependent samples t-test were significant, t(7) = 3.24, p = .023, d = 1.14, wherein there was a significant decrease in state anxiety scores from pre-program (M = 87.57, SD = 9.13) to post-program (M =63.71, SD = 17.78). An examination of Cohen’s d suggests a large clinical effect.
Research Question 5
The fifth research question asked: To what extent does a course of treatment involving an MCR-P intervention impact trait anxiety in participants with pretest trait anxiety at or above the 85th percentile? This question examined whether there was a change (pre- to post-program) in trait anxiety. The null and alternative hypotheses were as follows:
H0: There will be no significant change in STAI trait anxiety scores following a course of
treatment using an MCR-P intervention when used by participants with pretest trait anxiety at or above the 85th percentile.
Ha: There will be a significant change in STAI trait anxiety scores following a course of treatment using an MCR-P intervention when used by participants with pretest trait anxiety scores at or above the 85th percentile.
This research question examined whether there was a change in trait anxiety in participants with pretest trait anxiety at or above the 85th percentile following a course of treatment using an MCR-P intervention. The results of a two-tailed, dependent samples t-test were significant, t(7) = 2.67, p = .037, d = 1.01 wherein there was a significant decrease in trait anxiety scores from pre-program (M = 96.14, SD = 3.52) to post-program (M = 88.57, SD = 9.93). An examination of Cohen’s d suggests a large clinical effect.
Research Question 6
The sixth research question asked: To what extent does the MCR-P intervention impact daily anxiety, pre to post per administration in participants with pretest trait anxiety scores at or above the 85th percentile? This research question examined the impact of the music listening intervention for each daily administration of the MCR-P. The null and alternative hypotheses were as follows:
H0: There is no difference between pre and posttest daily anxiety scores following a single administration of the MCR-P in participants with pretest trait anxiety at or above the 85th percentile.
Ha: There is a difference between pre and posttest daily anxiety scores following a single administration of the MCR-P in participants with pretest trait anxiety at or above the 85th percentile.
A dependent Wilcoxon signed-ranks test indicated that the median posttest daily anxiety scores (Mdn = 2.14), were significantly lower than the pretest daily anxiety scores (Mdn = 3.43), change = -2.37, p = .01, r = -0.63. Examination of the effect size using r followed parameters as laid out by Cohen (1988) and were found to be large.
All data included in table 2 for the MV-P is from the aforementioned thesis and is used to identify relative effectiveness of the MCR-P intervention.
Table 1
Inferential Statistics Data ____________________________________________________________________
Group df State Trait Pre-post
p d p d change p r__
MCR-P 9 *0.026 0.73 0.62 N/A -2.80 *0.029 -0.63
MCR-P 6 *0.023 1.14 *0.037 1.01 -2.37 **0.01 -0.63
high trait
MV-P 8 *0.026 0.90 **0.001 0.84 -2.93 **0.003 -0.88
MV-P 6 *0.028 1.31 **0.001 1.103 -2.67 **0.007 -0.63
high trait *p<0.05. **p<0.01.
Participants took part in activities while listening to their playlist in order to improve attentiveness and mindfulness in the listening task. Upon visual examination, data collected on which activities participants chose did not show any relationship to how a participant responded to the intervention. A graphic representation of which activities participants took part in is displayed below in figure 7.
Figure 7
Participant Activities
Qualitative Analysis
The qualitative analysis for this study included recording, transcription, and analysis of the data for themes using a semantic approach following the six-step protocol of Braun and Clarke (2006). Analysis centered around those participants who were at or above the 85th percentile in pretest trait anxiety in order to target the population who would be most likely to benefit. All recordings were reviewed several times before transcription which was double checked for accuracy, familiarizing me thoroughly with the data. Once this was complete, I created the initial codes for the data and then grouped them together in overarching themes. Those themes included ‘challenges,’ ‘awareness,’ ‘active management,’ and ‘alteration of mood/arousal.’
The theme of ‘challenges’ came from the codes of ‘busy schedule/time,’ ‘no significant barriers,’ ‘setting other tasks aside,’ and ‘grew tired of songs.’ Among these codes, participants overwhelmingly noted having a busy schedule and that it was challenging to find time. Just over half of the participants stated that there were no significant barriers to fulfilment of the protocol, with two participants giving both answers, indicating that they thought it was difficult to find time, but not enough to pose a significant barrier. Other codes within this theme were ‘grew tired of songs’ which 2 participants reported, and ‘setting other tasks aside’ which was only reported by 1 participant.
In the theme of ‘awareness,’ three codes were identified; ‘awareness of use of music,’ ‘awareness of emotions/mindful,’ ‘awareness of positive associations.’ Over half of the participants stated that they were more aware of how they were using music. There were also 2 participants who reported an increase in their awareness of emotions, or greater mindfulness, and 1 reported being more aware of positive associations that they have with music and how that impacts their experience.
The theme of ‘active management’ included two codes which are ‘better able to self-regulate’ and ‘greater sense of control.’ These each were only mentioned by 2 participants during interviews, and as such are likely not as strong of a theme as the others reported. The final theme which was examined was ‘alteration of mood/arousal,’ which included the codes of ‘more relaxed,’ ‘happier/refreshed,’ and ‘decrease in anxiety/improved mood.’ Out of these codes, all but 2 participants reported feeling more relaxed, indicating a shift in arousal state from high to low. There were 2 participants who stated that they felt happier or refreshed, and 3 indicated that they were experiencing less anxiety and/or had an improved mood.
Over the course of the analysis, several codes were condensed as is outlined here. Under the theme of ‘challenges,’ I condensed ‘time’ and ‘busy schedule,’ though I included the wording of both in the updated theme. Additionally condensed codes included feeling happier and feeling refreshed, as well as being increasingly aware of emotions and being more mindful. Similarly to the previous codes, all wording was preserved. I also combined ‘better able to manage emotions’ with ‘better able to manage anxiety’ into a single code, as this was a study on stress and anxiety reduction. The codes of ‘more aware of use of music’ and ‘use music more intentionally’, were combined as they are arguably the same skill. The final codes which were condensed were ‘decrease in anxiety’ and ‘improved mood’, though I preserved the wording of both.
For definitions and example quotes of all thematic analysis, see table 3 below.
Table 3
Themes from Qualitative Data
Codes Themes Supporting Quotations
Challenges: Busy schedule/time: “Just life, you know? It gets busy,
Any barriers or challenges Having a busy schedule or but I just got in the habit of doing
that participants lack of time being a barrier it.”
encountered to faithful to listening to the playlist
adherence to the protocol on a daily basis “Time. Definitely time.”
“I had a lot going on at work. This is
one of our really busy times, and
sometimes I had to work late
which made it harder. Yeah. Just
being busy.”
No significant barriers: “None, really, once I got going. I
No barriers that caused a just made it a part of my day, and I
significant problem with started looking forward to it, so
listening to the playlist that made it easy to work in.”
on a daily basis
“Um, not really any. It seemed like
it was pretty easy to do.”
Setting other tasks aside: “Sometimes it was just hard to set
Having a difficult time things aside that I needed to get
setting other tasks aside done to do the listening. I get why
in order to listen to the we need to really listen to the
playlist on a daily basis music, but it was hard to put
things down when I needed to get
stuff done.”
Grew tired of songs: “Well, towards the end I got kind of
Feeling reluctant to listen tired of listening to the same songs
to the same songs every day. And I mean, I knew
repeatedly that I could have changed it up,
but I just didn’t because I was so
close to being done.”
Active Management: Better able to self-regulate: “I felt like I could regulate things
Greater ability to actively Increased ability to self- better. And like I would still get
manage symptoms as regulate symptoms of the spikes of anxiety like I got
needed anxiety before, but could bring them down
faster. So yeah, I guess I could
just regulate that better.”
“I could manage my anxiety better.
I could handle it after I had
listened and was in that calmer
space.”
Greater sense of control: “Just now I have a tool that I feel
Feeling a greater sense of like I can use when I need it. It
control over symptoms of kind of reminds me of some of the
anxiety. things my therapist has me do
when I have trouble.”
“It made me feel like I had better
control over how I felt. I hadn’t
really noticed the way music does
that before. Or I guess I noticed, I
just never thought to use it like
this.”
Awareness: Awareness of use of music: “It just made me think more about
An increase in awareness Increased awareness of how I use music to make me feel
and/or mindfulness how they use music in better. Music is really important
their lives to me, but I’ve never used it like
this before. I guess it made me
think about the music I listen to
in a different way.”
Awareness of positive “It brought me up, but I think a lot of
associations: that was because I picked songs
A greater awareness of that made me think of certain
positive associations to times, like when I was really
autobiographical events happy, and that made me feel
good.”
Awareness of emotions/ “I felt more mindful, you know?
Mindful: An increase in Like, just more present.”
awareness of emotions
and general mindfulness “I was more aware of how I felt.
Like, sometimes I don’t know if
I’m really aware of how stressed I
am until I don’t feel so stressed.
After listening, though, I would
realize how stressed I had been
before.”
Alteration of Mood/Arousal: More relaxed: “I felt more relaxed. Like, so
A shift in mood or A greater feeling of relaxed I almost fell asleep, and
arousal state relaxation than was that’s not common for me. It was
experienced previous to kind of amazing to feel like that.”
listening to the
intervention “Relaxed. Definitely more relaxed.”
“I’m not sure. I mean, more relaxed.
Yeah, I felt more relaxed at the
end.”
Happier/Refreshed: “Happier! I don’t know if that was
Increased feelings of how I was supposed to feel, like, I
happiness or being think it probably should have been
refreshed more calm or something, but I just
felt happier, which was nice.”
“Kind of refreshed. Like I had taken a break and could get back to life
all refreshed and everything.”
Decrease in anxiety/ “My anxiety wasn’t as bad, which is
improved mood: A saying something because I had
reduced experience of some big things hit during this,
anxiety symptoms and/ including the death of a close
or a more positive mood friend and what happened at the
capitol. But my anxiety just didn’t
hit at the same level it usually
does.”
“I guess, better. Yeah, definitely
better. I don’t know how to really
say it, but my mood was just better
overall.”
Mixed Analysis
The mixed analysis of data is intended to inform who may respond particularly well to this intervention, as well as who may be better served by a different intervention. This could include participants who do not have music with which they strongly identify. Information given on the barriers to this treatment may be used to adapt the protocol so that it is as accessible and feasible as possible. For the purposes of the mixed analysis, I again focused on the participants who had pretest anxiety scores in the 85th percentile or above, as this intervention seeks to target those with high levels of trait anxiety. Incidentally, the participants who had pretest anxiety scores in the 85th percentile or above were also the participants who had a mean initial reported anxiety level of 2.5 or higher, which indicates that they had levels of anxiety high enough that it could cause distress in their lives, and could also be significantly reduced. Among those participants, high responders are identified as those who had a mean pre to post listening difference above the median score of 0.73. Low responders are identified as those participants whose mean pre to post listening difference scores fell below that threshold.
Research question 8
The eighth research question asked: Which themes are present with participants who were high responders to the MCR-P intervention in participants with pretest trait anxiety at or above the 85th percentile? This research question examined which themes were most common in participants who are identified as high responders to the MCR-P and had high pretest trait anxiety as are outlined in previous research questions.
Research question 9
The ninth research question asked: What are the barriers to using self-administered therapeutic playlists for participants who were high responders to the MCR-P intervention with pretest trait anxiety at or above the 85th percentile? This research question examined which barriers were noted most in participants who were identified as high responders who had high pretest trait anxiety.
The first theme that was examined was ‘challenges.’ Participants were then bifurcated into groups of high and low responders so that patterns of responses could be identified. Both high and low responders stated that having a busy schedule and a lack of time were the primary challenge. Participants 5 and 9 both cited schedule but also included that it was not a significant barrier. Only participants who were identified as high responders reported having difficulty setting other tasks aside or growing tired of the songs. As they both still had a high response, however, it does not appear that it caused a serious negative interaction.
Table 4
Mixed Analysis on Challenges in High Responders
____________________________________________________________________
Participant Busy schedule/ No significant Setting other Grew tired
time barriers tasks aside of songs
1 X
4 X X
7 X X
9 X X
12 X X
Table 5
Mixed Analysis on Challenges in Low Responders
____________________________________________________________________Participant Busy schedule/ No significant Setting other Grew tired
time barriers tasks aside of songs
5 X X
13 X
The next theme examined was that of ‘active management’ which had the codes of ‘better able to self-regulate’ and ‘greater sense of control.’ There were only 2 participants who reported each of these, and those were participants 1 and 9. Both of them are considered to be high responders to this intervention. No participants who were considered low responders reported either of these codes. Given the few responses within this theme, it does not appear that this intervention facilitates a sense of active management of symptoms. However, if a participant does report feeling a greater sense of being able to actively manage symptoms, they are likely to be someone who has a strong response to the intervention.
Table 6
Active Management in High Responders
________________________________________________
Participant Better Able to Greater Sense
Self-Regulate of Control
1 X X
4
7
9 X X
12
Table 7
Active Management in Low Responders
________________________________________________
Participant Better Able to Greater Sense
Self-Regulate of Control
5
13
The next theme examined is ‘awareness in high responders’ which contained the 3 codes of ‘awareness of use of music,’ ‘awareness of emotions/mindful,’ and ‘awareness of positive associations.’ Over half of the participants identified as high responders reported an increase in their awareness of how they use music, as did 1 participant who was not a high responder. Only 1 participant reported an increased awareness of positive associations that they have with music, and 2 reported increased awareness of their emotions or mindfulness. All 3 of those participants were identified as high responders.
Table 8
Awareness in High Responders
__________________________________________________________________
Participant Awareness of Awareness of Awareness of
Use of Music Emotions/Mindful Positive Associations
1 X
4
7 X X
9 X X
12 X
Table 9
Awareness in Low Responders
__________________________________________________________________
Participant Awareness of Awareness of Awareness of
Use of Music Emotions/Mindful Positive Associations
5 X
13
The final theme was ‘alteration of mood/arousal,’ and that contained the themes of ‘more relaxed,’ ‘happier/refreshed,’ and ‘decrease in anxiety/improved mood.’ This was interesting as it showed greater patterns of response than some of the other themes. Both of the high pretest trait anxiety participants who were identified as low responders reported feeling more relaxed. Out of the participants who were high responders, over half reported feeling more relaxed as well. The same number of high response participants reported a decrease in anxiety and/or improved mood. There were 2 participants who reported feeling happier or refreshed which indicates a shift in mood/arousal from low to high, but with a positive valence. The codes of ‘more relaxed’ and ‘decrease in anxiety/improved mood’ indicate a shift in mood/arousal from high to low, which aligns with the goal of anxiety reduction. Out of the high responding participants, only 1 did not report either of these codes. Both of the participants who reported feeling happier or refreshed were identified as high responders.
Table 10
Alteration of Mood/Arousal in High Responders
__________________________________________________________________
Participant More Relaxed Happier/Refreshed Decrease in Anxiety/
Improved Mood
1 X X
4 X X
7 X
9 X
12 X X
Table 11
Alteration of Mood/Arousal in Low Responders
__________________________________________________________________
Participant More Relaxed Happier/Refreshed Decrease in Anxiety/
Improved Mood
5 X
13 X
Significance
While many studies note the neural correlates between emotion regulation and music listening, there are no studies investigating the use of self-administered music therapy interventions for the purpose of treating symptoms of anxiety. There are a number of studies, both quantitative and qualitative, which link music to emotion and identify music as an effective tool of emotion regulation (Alluri et al., 2015; Baker et al., 2017; Bautch, 2019; Beck et al., 2018; Bidabadi & Mehryar, 2015; Blood & Zatorre, 2001; Brown et al., 2004; Carr et al., 2012; Flores-Gutiérrez & Terán Camarena, 2015; Garrido et al., 2016; Hou et al., 2017; Jasemi et al., 2016; Koelsch et al., 2016; Krahé & Bieneck, 2012; Landis-Shack et al., 2017; Levitin, 2013; McFerran et al., 2010; Mitterschiffthaler et al., 2017; Nguyen & Graham, 2017; Sena Moore, 2013; Shatin, 1970). This study will build upon previous studies on music listening and emotions, as well as the basic research into neural correlates between the structures involved in emotion regulation and the structures activated during receptive music therapy interventions, in order to fully utilize the neurological effects of music in support of effective emotion regulation. This has the potential to identify effective self-administered music therapy interventions, which would give patients a tool that they could use to assist with symptoms of anxiety at any time when they need support.
Collaboration with a board-certified music therapist will assist the participant in building a playlist which may assist in management of their symptoms of anxiety. As music can affect our emotions in many different ways, it is important to have a qualified professional guiding the selection of music so that expressionistic qualities, such as the structural characteristics of the music itself, are considered as well as referential characteristics, such as personal associations and memories. The role of the music therapist is to help the participant blend these components in order to create a playlist that will facilitate a reduction in symptoms of anxiety.
Format
Event
Video File
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The Effect of Therapeutic Music Playlists on Symptoms of Anxiety: A Clinical Trial
Mental health diagnoses affect a significant portion of the population, with 50% of all Americans receiving at least one mental illness diagnosis in their lifetime (American Psychological Association, 2018). The percentage of people who will receive a mental illness diagnosis in their lifetime is higher than the 39.66% who will receive a diagnosis of cancer (American Cancer Association, 2018), and the 47.7% who will be diagnosed with coronary disease (American Heart Association, 2017). Additionally, 45% percent of adults with a mental health diagnosis also meet the criteria for at least one other disorder (American Psychological Association, 2018). The prevalence of Americans diagnosed with specific conditions that the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) lists emotion dysregulation as a key component of are as follows: anxiety disorders at 31.1%, other mood disorders at 21.4%, attention deficit hyperactivity disorder (ADHD) at 8.7%, posttraumatic stress disorder (PTSD) at 6.8%, bipolar disorder at 4.4%, eating disorders at 2.7%, obsessive compulsive disorder (OCD) at 2.3%, and borderline personality disorder (BPD) at 1.4%. (American Psychiatric Association, 2013; National Institute of Mental Health, 2017).
In a survey by Bautch (2019), 84% of participants reported using music for the purposes of regulating emotions. As is noted in a study performed by McFerran et al. (2010), people do not always select music for themselves that will improve their emotional state. In their research they found that it is not uncommon for people who are struggling with mood to select music which can actually intensify rumination and which can have a detrimental effect on their emotions. However, music has the ability to assist in mood elevation. The effectiveness of music listening as a means of improving scores on the state section of the STAI was demonstrated in a study by De La Torre-Luque et al. (2017) where within group differences were found in the experimental group (p
In her 2013 systematic review, Sena Moore explained these results by examining the neural correlates between the structures involved in emotion regulation and the impact of music experiences on those neural structures. Neural structures and activity that are related to emotion regulation include activation of the anterior cingulate cortex (ACC), the orbitofrontal cortex (OFC), and the lateral prefrontal cortex (PFC), the latter of which has a mediating effect on the amygdala. Multiple studies have used neural imaging as well as other measures to demonstrate the effect of music listening experiences on an increase of activation of the OFC, the ACC, and a decrease of activation in the amygdala (Blood & Zatorre, 2001; Brown et al., 2004, Mitterschiffthaler et al., 2007; Berns & Moore, 2012; Berns et al., 2010, Flores-Gutierrez et al., 2007; Koelsch et al., 2006; Levitin, 2013; Alluri et al, 2015; Hou et al., 2017). Activity in the limbic system is also altered by music listening, engaging the limbic and the paralimbic systems and improving functional connectivity of the limbic regions (Brown et al., 2004; Alluri et al., 2015). This indicates that music may facilitate neurological functioning that supports optimal emotion regulation.
Both music listening as well as music therapy has long been utilized as a means of effectively addressing goals of emotion regulation. Beginning in the 1940’s, music therapy was used as a means of addressing symptoms of what eventually became known as PTSD, though it was then called shell shock. Interventions currently used in addressing symptoms of anxiety include music assisted relaxation, guided imagery and music, improvisation, and therapeutic playlists (Wurjatmiko, 2019; Karadag et al., 2019; Ribeiro et al., 2018; Millet & Gooding, 2017; Pavlov et al., 2017; Hwang et al., 2013; Alam et al., 2016; Hammer, 1996; Bradt & Teague, 2018; Zarate, 2016; Hense et al., 2018). Many of these interventions are done in the presence of a music therapist and are not self-administered. Notable exceptions are therapeutic playlists, and music assisted relaxation, which are interventions that can be taught and used in the home environment. A therapeutic playlist is a sequence of songs that are targeted to reach a goal. They are frequently used as a means of addressing dysregulation of emotions, most commonly symptoms of anxiety and/or depression. The present study will address the use of one-directional mood vectoring playlists and musical contour regulation playlists in the treatment of symptoms of anxiety. For the purposes of this study, Shatin’s (1970) definition of mood vectoring will be used, which is “The directed alteration of mood through music- an alteration from one affective pole to it’s opposite or it’s contrast” (pg. 81). Musical contour regulation, on the other hand, alternate between high- and low-arousal music experiences in order to support healthy management of high- and low-arousal situations which may induce symptoms of anxiety (Sena Moore, 2018).
This study will utilize two different kinds of playlists which will be designed to address a range of emotions and assist listeners in shifting from dysregulated to regulated mood states. Music will be participant selected from their own collection of recorded music and organized in collaboration with a board-certified music therapist. Playlists will be designed to facilitate a reduction of anxiety symptoms.
In addition, it is important to also examine the feasibility of both interventions, as well as barriers to faithful adherence to the protocol that participants experienced. This will assist practitioners in the identification of persons who would benefit, as well as those for whom the interventions may not provide optimal results. The results of this study may also provide information as to whether there are changes that could be made to improve accessibility and increase fidelity in the protocol in order to facilitate improved outcomes for patients.