Bibliography

This study analyzes how listening to music impacts stress levels among individuals with reported anxiety, depression, and post-traumatic stress disorder (PTSD), comprising their data using dual models and propensity score matching. Retrieving data from 13,597 Twitter users, researchers examined causal relationships between music listening habits and mental health symptoms, through combining propensity score matching (PSM) and generalized linear mixed models (GLMM). The study’s results demonstrated that listening to music reduced stress levels by 21.3% for anxiety, 15.4% for depression, and 19.3% for PTSD, as well as listeners having an 87.9% greater likelihood of reporting a “zero stress score,” or experiencing emotional neutrality. Taking into account various demographics, including age, gender, and education, this study emphasizes how these variables heavily influence the degree of stress reduction experienced, notably with younger and less formally educated individuals experiencing greater psychological benefits. Through utilizing wide-scale social media metrics (Twitter) and data, this study exceeds prior limitations among small-scale clinical studies in offering a greater scope to allow for a more reliable understanding of music’s therapeutic potential. This study is incredibly relevant for our team’s research objective, in that it provides a thorough examination of music’s impact on mental health symptoms among a broad pool of participants, accounting for key demographics our project leans on, while substantiating a scientifically-proven relationship between music listening and mental health symptoms. Thus, this study paves the way toward the development of more tailored data-led music interventions for managing mental health conditions.           

In this source, Williams argues that listening to personally preferred music genres can significantly reduce stress levels and increase self-awareness, overall contributing to better emotional regulation. With a sample size of 65 people (ages of 18+), Williams used several self-administered questionnaires (STOMP, SAOQ, and PSS-10) and interviews to collect quantitative and qualitative data, comparing stress responses before and after exposure to preferred versus non-preferred genres. There seemed to be a negative correlation in stress rates between older individuals and music genres that were listened to (i.e. stress increased in those who were older and listening to non-preferred genres). This resource is important because it provides a strong psychological foundation for how subjective music experiences affect mental health, connecting emotional and physiological responses. This research offers behavioral evidence that supports our quantitative data analysis and helps us interpret correlations between specific genre preferences and mental health scores in a more real-world context.

In this source, Bowling proposes a biologically led framework for analyzing how music influences mental health, primarily arguing the vast therapeutic potential of music that has been widely unexplored due to a lack of research in biological models. His model follows four core principles of human musicality: tonality, rhythm, reward, and sociality, each of which engage neurological functions connected to emotion and motivation. In particular, this study found that rhythm patterns activate motor and cognitive circuits linked to attention and mood regulation, (high or low) tonal sensitivity impacts emotional processing linked with overall mood and anxiety levels, group neural synchrony and oxytocin release from music impact interpersonal function and feelings of social connectedness or isolation, whereas reward processing activates dopamine pathways that heighten pleasure and motivation, potentially aiding with depression symptoms. Thus, Bowling highlights how these fundamental mechanisms allow greater understanding in how music engagement can enhance mood regulation, diminish symptoms of depression and anxiety, as well as foster social connection. However, it’s important to note that the current array of music-based mental health intervention models vary vastly in both design and findings, creating limits to their clinical reliability. This article is valuable for our project because it provides an in-depth scientific approach for connecting music listening habits and genre preference to mental-health conditions, further supporting the notion of how biological responses to music serve as an underlying backbone to its psychological effects.  

This source presents a unique framework using brain computer interface (BCI) technology for both functional magnetic resonance imaging (fMRI) and meta-learning (ProtoMAML) to categorize specific neural responses to various music genres, despite data limitations. In the study, researchers used fMRI scans from 20 participants exposed to distinct genres, including rock, metal, country, ambient, and symphonic, analyzing blood-oxygen-level-dependent (BOLD) signals to track neural activity patterns in response to each genre. The findings revealed that “high-energy” genres such as metal or rock activated attention and motor-related regions stronger than ambient or symphonic (“low energy”) genres, which produced more neutral, balanced responses among participants. Further, their ProtoMAML framework allowed for significantly high accuracy scores (97.25%) using only 30 samples for each classification, which vastly exceeded reliability of other traditional neural network models. The researchers emphasize the potential of their framework in understanding how music stimuli helps mold both emotional and cognitive neural states, which further provides strong potential in applications surrounding therapeutic and rehabilitation approaches to mental health, as well as overall emotional regulation. This article is incredibly relevant and useful in our project as it explores the intersectionality between music, mental health, and neuroscience from a data-driven lens that goes beyond simple external measures (i.e., behavioral) to decode genre-specific neural responses.      

In this source, Filippis and Al Foysal argue that frequent music listening and genre diversity are associated with improved mental health outcomes, particularly reduced anxiety and depression levels. Using a survey-based, cross-sectional design experiment, the authors analyze self-reported survey data from a large international sample, applying correlation and regression analyses to connect music habits with procedure mental health measures. They discovered that respondents with higher anxiety, depression, insomnia, and OCD scores tend to engage in prolonged music listening, potentially as a coping mechanism. This paper is important as it provides strong factual data connecting everyday music engagement with one’s well-being, and how potential confounders may influence music habits and mental health. This source aligns directly with our thesis, as it offers comparable methods and variables to the Kaggle dataset. In addition, it strengthens our research about identifying statistically significant relationships between self-reported mental health scores and musical preferences.

This source examines how individuals from four different countries utilized music to manage their emotions and enhance their well-being during the early months of the COVID-19 pandemic. Through their online survey, they found that listening to music could be used as a powerful and effective tool to improve an individual’s mood in unprecedented times, such as the COVID-19 pandemic. Additionally, the authors observed that individuals who were more affected by the pandemic and showed symptoms of mental health issues, such as depression and anxiety, were more likely to use music to regulate their emotions to feel better. To regulate negative feelings during the pandemic, it was found that individuals who listened to softer and acoustic music reported feeling better. This article is important to our research because we are exploring how different genres of music and acoustic features (tempo and loudness) influence emotional well-being. The study’s limitations include self-reported biases, small sample limitations, and survey results only from the early pandemic. 

This source explores the benefits of music listening as a therapeutic method and the importance of self-selected music. The research went into detail as to why participants select specific forms of music and why such music types better their mood. Through a survey, it was found that music that was selected based on one’s current mental state was correlated with better emotional regulation, self-awareness of one’s feelings, and improved well-being. Research found that when participants (n=22)  listen to the music that resonates with their emotional needs, they feel more inspired to go out, motivated to improve their mood, and it helps regulate negative emotions. This resource is important to our research because it explores the significance of music and its potential role in improving one’s health, healing, and recovery. This research could help us understand why having the choice to select what music to listen to is powerful in regulating and identifying our emotions. 

In this source, Kurniawan (and other authors) argue that machine learning models can predict an individual’s mental health condition based on their music genre preferences and listening behaviors. For evidence, the authors used survey data on favorite music genres & self-reported mental health scores, which were analyzed using several ML methods, including Logistic Regression, Decision Trees, and Gradient Boosting. This is an important resource because this study demonstrates a data-driven approach that connects music listening with important psychological traits, providing a technical insight on how to quantify emotional well-being through music data. This paper supports our thesis by illustrating how computational models can analyze correlations between musical preferences and mental health outcomes. This reinforces our use of the Kaggle dataset to perform similar predictive or correlational analyses.

In this article, Lauren Wisdom explores the relationship between music and mental health by emphasizing how music serves as a coping mechanism and a useful tool for emotional regulation. She notes that, according to the National Alliance on Mental Illness, 50% of all lifetime mental illnesses begin by age 14 and 75% by age 24, and also that suicide remains the second leading cause of death for people ages 10 to 34. Despite these figures, 40% of students with apparent mental health conditions avoid seeking help due to cultural stigma. Wisdom uses student testimonials to explain how music can improve mood, relieve stress, and generally benefit the overall mental health of an individual. A fourth year student in music therapy studies,  Jennifer Greve, explains that structured approaches such as lyrical analysis, improvisation, active listening, and songwriting can all help manage anxiety and trauma. The article does acknowledge that certain songs might trigger painful memories, however that music ultimately serves as a therapeutic outlet for emotional healing. This source supports our own research because it explains how music fosters mental wellness and self-expression through combining data and real-life student experiences.

In this source, Raymond explores the qualitative research on the connection between music, health, and one’s well-being. He proposes a conceptual framework that includes music therapy, music education, music medicine, and the everyday use of music, and how music engagement can contribute to one’s mental and physical health. The research states how music could be used as a coping mechanism and significantly lower levels of anxiety. Raymond notes how people choose music genres that match and regulate their moods, highlighting music’s positive influence on one’s well-being. Additionally, the research notes how preference is a key variable in understanding the therapeutic effects of music engagement. This is important to our research because it shows how musical engagement promotes a valid form of therapy to promote better health. 

This study examines the effects of different musical genres and silence on relaxation and anxiety. High stress levels and anxiety employed by healthy individuals have generally led to pharmacological or non-pharmacological therapies. This study had a randomized controlled trial, utilizing a cross-over design. A sample size of 46 healthy undergraduates randomly received different genres of music (pop, rock, Western classical, and Persian Traditional) and silence for five consecutive days between February and June 2018. Participants were in their own control, and relaxations and anxiety were checked with the Smith Relaxation States Inventory 3 and the State Anxiety Inventory. The findings highlighted that neither of the five procedures were preferred for a relaxation effect, and none of the interventions were preferred to reduce anxiety. The results showed that Pop, Western Classical, and Persian Traditional, and silence moments increased relaxation in the participants, but listening to Rock did not have any significant effect on relaxation. This study is relevant because it provides a step further in understanding and increasing research data in musical therapy, as well as adequate insight into our examination of musical and mental health. 

In this article, Rahman and the other authors dive into how machine learning models can be used to analyze physiological signals to understand how a participant responds emotionally to different music genres. The experiment was conducted using 24 participants who listened to 12 musical pieces from classical, instrumental, and pop genres, while measuring their electrodermal activity (EDA), blood volume pulse, skin temperature, and pupil dilation. The research achieved high classification accuracy, showing up to 99.2% for genre and 98.5% for emotion, using neural network models. The study also introduces a visualization method called “Gingerbread Animation” to represent physiological responses through color-mapped data. This source is valuable to our own research because it connects music therapy with computational signal analysis, which also provides a foundation that is data-driven to understanding how music affects different emotional states. It would be a quantitative approach in examining measurable links between music and mental health. 

This article highlights that recent research on the intertwining of mental health and music suggest that music engagement not only shapes our cultural and personal identity, but plays a significant role in regulating mood. Music is prevalent in the development and the lives of many, becoming an integral part in the human experience. A 2022 meta-analysis has also revealed that music in music therapy found a beneficial effect on stress-related outcomes. It notes that activities such as singing, drumming circles, as well as song-writing can foster a sense of belonging and foster a tight-knit community. Additionally, the article explains that “emerging evidence indicates that music has the potential to enhance prosocial behavior, promote social connectedness, and develop emotional competence” (American Psychiatric Association). This can help us deepen our understanding on how music can beneficially contribute to self-regulation in mood disorders, with the exploration of music through a social context.

This experiment’s sample size consisted of short-stay residents of nursing homes who experienced higher levels of distress in comparison to their community residents. These participants demonstrated new onset mental health symptoms or have had long-term symptoms, which were overlooked. The study highlights that there is an upsurge in mental health distress while in residential care settings, with underlying individual or environmental factors influencing the effects. A modified therapy framework was utilized Effective Music in Therapy. Later, pre/post-sessions were implemented to examine affect, quality of life, and pain. Qualitative interviews were conducted following after. This article is relevant to our project because as we seek to evaluate music and its profound effects on mental health and well-being, particularly whether it improves or worsens its symptoms. Music has played an increasingly vital role in addressing mental health concerns in rehabilitative and medical settings; and oftentimes, music can also communicate a sense of belongingness or cohesion in communities

In this source, Williams argues that listening to personally preferred music genres can significantly reduce stress levels and increase self-awareness, overall contributing to better emotional regulation. With a sample size of 65 people (ages of 18+), Williams used several self-administered questionnaires (STOMP, SAOQ, and PSS-10) and interviews to collect quantitative and qualitative data, comparing stress responses before and after exposure to preferred versus non-preferred genres. There seemed to be a negative correlation in stress rates between older individuals and music genres that were listened to (i.e. stress increased in those who were older and listening to non-preferred genres). This resource is important because it provides a strong psychological foundation for how subjective music experiences affect mental health, connecting emotional and physiological responses. This research offers behavioral evidence that supports our quantitative data analysis and helps us interpret correlations between specific genre preferences and mental health scores in a more real-world context.