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Mental Health and Music Preferences Data
Mental Health & Wellness
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About
This dataset presents survey results on individuals' music tastes and their self-reported mental health [1]. It aims to explore potential correlations between the types of music people listen to and their experiences with conditions such as anxiety, depression, insomnia, and OCD [1, 2]. The findings could contribute to understanding how music therapy might be more effectively applied or offer intriguing insights into the human mind [1].
Columns
- Timestamp: Date and time when the survey form was submitted [3].
- Age: Respondent's age [4].
- Primary streaming service: Respondent's primary music streaming service [5].
- Hours per day: Number of hours the respondent listens to music per day [5].
- While working: Indicates if the respondent listens to music while studying or working [6].
- Instrumentalist: Indicates if the respondent plays an instrument regularly [6].
- Composer: Indicates if the respondent composes music [7].
- Fav genre: Respondent's favourite or top music genre [7].
- Exploratory: Indicates if the respondent actively explores new artists or genres [7].
- Foreign languages: Indicates if the respondent regularly listens to music with lyrics in a language they are not fluent in [8].
- BPM: Beats per minute of the respondent's favourite genre [8].
- Frequency [Classical]: How frequently the respondent listens to classical music [9].
- Frequency [Country]: How frequently the respondent listens to country music [9].
- Frequency [EDM]: How frequently the respondent listens to EDM music [10].
- Frequency [Folk]: How frequently the respondent listens to folk music [10].
- Frequency [Gospel]: How frequently the respondent listens to Gospel music [10].
- Frequency [Hip hop]: How frequently the respondent listens to hip hop music [11].
- Frequency [Jazz]: How frequently the respondent listens to jazz music [11].
- Frequency [K pop]: How frequently the respondent listens to K-pop music [11].
- Frequency [Latin]: How frequently the respondent listens to Latin music [12].
- Frequency [Lofi]: How frequently the respondent listens to lo-fi music [12].
- Frequency [Metal]: How frequently the respondent listens to metal music [12].
- Frequency [Pop]: How frequently the respondent listens to pop music [13].
- Frequency [R&B]: How frequently the respondent listens to R&B music [13].
- Frequency [Rap]: How frequently the respondent listens to rap music [13].
- Frequency [Rock]: How frequently the respondent listens to rock music [14].
- Frequency [Video game music]: How frequently the respondent listens to video game music [14].
- Anxiety: Self-reported anxiety level, on a scale of 0-10 [15].
- Depression: Self-reported depression level, on a scale of 0-10 [15].
- Insomnia: Self-reported insomnia level, on a scale of 0-10 [16].
- OCD: Self-reported OCD level, on a scale of 0-10 [17].
- Music effects: Indicates whether music improves or worsens the respondent's mental health conditions [17].
- Permissions: Permissions to publicise data [18].
Distribution
The dataset is provided in CSV format [3, 19]. It contains 736 records or rows [3]. The file size is 172.56 kB [3].
Usage
This dataset is ideal for exploring the relationships between music preferences and mental wellbeing [1]. It can be used for research into the effectiveness of different music genres in music therapy applications [1], for data analytics projects examining trends in music listening habits and self-reported mental health [3], and for data visualisations to present findings on these correlations [3].
Coverage
The survey data was collected between 28 August 2022 and 9 November 2022 [3]. Respondents were not limited by age or geographic location [20]. The age range of respondents in the dataset spans from 10 to 89 years old [4].
License
CC0: Public Domain
Who Can Use It
- Music Therapists and Researchers: To inform the selection of music genres for therapeutic interventions [1].
- Mental Health Professionals: To gain insights into the role of music in individuals' mental wellbeing [1].
- Data Analysts and Scientists: For statistical analysis, hypothesis testing, and machine learning model development related to music and health [3].
- Students and Academics: For educational projects and academic research on human behaviour and psychological responses to music.
- General Public: Individuals interested in the personal impact of music on mood and mental state [1].
Dataset Name Suggestions
- Music and Mental Health Survey Results
- MxMH Survey Dataset
- Music Taste and Wellbeing Study
- Mental Health and Music Preferences Data
Attributes
Original Data Source: Mental Health and Music Preferences Data
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