Our dataset examines the influence of music on mental health by collecting data from 736 individuals. This is initiated by Catherine Rasgaitis, an undergraduate computer science student at the University of Washington. The data was collected between 04/27/2022 and 11/09/2022, using a Google Form. The variables include various prompts to analyze the respondent’s relationship to music. The dataset includes the respondents’ mental health such as anxiety, depression being rated from 0-10. The respondents also described their opinion on whether music improves their mental health. These results are either numerical or in english. The purpose of the dataset was to identify correlations between music taste and mental health; a more comprehensive understanding of music that may contribute to further applications of music therapy. Some limitations of the dataset include subjectivity of the mental health based prompts as they were self reported. We speculate that age, music genre, composers, instrument players, and number of hours of music listened may be correlated to anxiety, depression, insomnia, and OCD, because of the commonality and impact of music on our lifestyles.

Our dataset provides numerous variables, giving us the freedom to explore our own areas of interest within the dataset. We want to explore the impact of age, music genre, composers, instrument players, and number of hours of music listened to on mental health. Each of us has different connections to music and mental well-being, which has shaped our diverse perspectives toward the dataset. Alyssa hopes to explore if composing or playing an instrument has an impact on mental health. Furthermore, she will study the correlation between how someone perceives the effects of music compared to whether they are actually playing or composing music. Haider will explore the frequency of how often an individual listens to a particular genre, and if these habits have any underlying effects on mental health conditions. Zainab will analyze age with the amount of music listened to, to determine if there are any mental health implications. With such a rich and comprehensive dataset, we believe building a user-facing Dashboard would allow us to explore various perspectives and consider many variables when analyzing relationships.

Given the increasing advocacy towards mental health and mental health support, we aim to explore how music may impact mental wellbeing, considering the perspectives of diverse age groups and how influential music has been in their daily lifestyle. Utilizing our findings, we hope to produce detailed, thoroughly developed, and comprehensive data visualizations that can aid the general public in understanding the influence of music on their mental health. As a dedicated team of students who have experienced our own mental hurdles, our team intends to use this project to provide a greater understanding of mental health with respect to music.

Diverse genres are examined such as classical, country, EDM, folk, gospel, hip hop, jazz, K pop, Latin, lofi, metal, pop, R&B, rap, pop, and video game music which have varying influences on mental health. Furthermore, the respondents' connection to music such as whether they play an instrument or are a composer is studied as well. It will be worthwhile to investigate how all the different variables in this dataset, including the genres of music and overall involvement with music, affect the various mental health attributes in individuals.

Our dataset analyzes the influence of music on mental health by collecting a magnitude of variables from 736 individuals. The variables include each individual’s age, primary streaming service used, hours of day spent listening to music, whether music is listened to during work, and whether they play an instrument or a composer. It also analyzes the type of music as well, such as the favourite genre, whether the respondent explores a variety of genres or listen to music in foreign languages, the beats per minute (BPM) of the music, and how frequently predetermined genres of music are listened to. These genres include classical, country, EDM, folk, gospel, hip hop, jazz, K pop, Latin, lofi, metal, pop, R&B, rap, pop, and video game music. Finally, the dataset analyzes the respondents’ mental health with factors inlcuding amount of anxiety, depression, insomina, OCD, based on a rating from 0-10 with 0 being the lowest and 10 being the highest. The respondents also described their personal opinion on whether music improves their mental health.

• Alyssa : I am a third year in microbiology. I like to play the flute, longboard and play Valorant!
• Haider Mohammad: As a 4th year Management student with an interest in the CPA program, I am currently focused on finance and accounting courses.
• Zainab Mohammad: I am a 4th year Biochemistry and Molecular Biology student, with a profound interest in the field of computer science.