Music is a powerful art form that touches our hearts, stimulates our minds, and enriches our lives. Its ability to communicate emotions, unite people, and provide a means of self-expression makes it an essential part of human culture and a source of joy and inspiration for millions of people worldwide.
Music therapy, or MT, is using music to improve an individual's stress, mood, and overall mental health. MT is also recognized as an evidence-based practice, using music as a catalyst for "happy" hormones such as oxytocin.
The aim of studying the therapeutic effects of music on mental health is to investigate and understand how music can be used as a therapeutic tool to promote psychological well-being, alleviate symptoms of mental disorders, and enhance overall mental health.
In order to carry out this prediction, we had to utilize open-source data, which was gotten from Kaggle
The dataset contains 736 records and 33 features. During the EDA phase, we discovered 8 features have missing values. However, there are no duplicate values in the data.
- Age: The age of the respondent
- Primary streaming service: The streaming service platform the respondent primarily uses for listening to music.
- Hours per day: The number of hours per-day the respondent spends listening to music.
- While working: indicates whether the respondent listens to music while working.
- Instrumentalist: Indicates whether the respondent plays a musical instrument.
- Composer: Indicates whether the respondent composes music.
- Fav genre: The respondent's favourite genre of music.
- Exploratory: Indicates whether the respondent enjoys exploring new genres of music.
- Foreign languages: Indicates whether the respondent listens to music in foreign languages.
- BPM: The average beats per minute of the music the respondent listens to.
- Frequency [Classical]: How frequently the respondent listens to classical music.
- Frequency [Country]: How frequently the respondent listens to country music.
- Frequency [EDM]: How frequently the respondent listens to electronic dance music.
- Frequency [Folk]: How frequently the respondent listens to folk music.
- Frequency [Gospel]: How frequently the respondent listens to gospel music.
- Frequency [Hip hop]: How frequently the respondent listens to hip-hop music.
- Frequency [Jazz]: How frequently the respondent listens to jazz music.
- Frequency [K pop]: How frequently the respondent listens to K-pop music.
- Frequency [Latin]: How frequently the respondent listens to Latin music.
- Frequency [Lofi]: How frequently the respondent listens to Lofi music.
- Frequency [Metal]: How frequently the respondent listens to metal music.
- Frequency [Pop]: How frequently the respondent listens to pop music.
- Frequency [R&B]: How frequently the respondent listens to R&B music.
- Frequency [Rap]: How frequently the respondent listens to rap music.
- Frequency [Rock]: How frequently the respondent listens to rock music.
- Frequency [Video game music]: How frequently the respondent listens to video game music.
- Anxiety: The level of anxiety the respondent experiences.
- Depression: The level of depression the respondent experiences.
- Insomnia: The level of insomnia the respondent experiences.
- OCD: The level of obsessive-compulsive disorder (OCD) the respondent experiences.
- Music effects: The perceived effects of music on the respondent's mental health (e.g., improve, worsen, no effect).
- Permissions: Indicates whether the respondent understands and agrees to participate in the study.