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Depression & Well-being Study
Mental Health & Wellness
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About
This RHMCD-20 dataset focuses on Depression and Mental Health, designed for data analysis and machine learning applications. It comprises survey data collected from a varied group of participants, including teenagers from Bangladesh, college students, housewives, and professionals from businesses and corporations. The dataset provides insights into various aspects of mental well-being, stress, and behavioural changes, particularly in the context of quarantine. It serves as a valuable resource for understanding mental health trends and can assist in the development of related research or data collection efforts.
Columns
- Age: Represents the age group of participants.
- Gender: Indicates the participant's gender.
- Occupation: Details the occupation of the participants.
- Days Indoors: Shows the number of days a participant remained indoors.
- Growing Stress: Indicates if the participant's stress is increasing (Yes/No/Maybe).
- Quarantine Frustration: Captures frustrations experienced during the initial two weeks of quarantine (Yes/No/Maybe).
- Changes Habits: Records significant changes in eating and sleeping habits (Yes/No/Maybe).
- Mental Health_History: Notes any prior mental disorders in the participant's previous generation (Yes/No/Maybe).
- Weight Change: Highlights changes in body weight during quarantine (Yes/No/Maybe).
- Mood Swings: Describes the severity of mood changes (Low/Medium/High).
- Coping Struggles: Indicates the inability to cope with daily problems or stress (Boolean: True/False).
- Work Interest: Represents whether the participant is losing interest in their work (Yes/No/Maybe).
- Social Weakness: Conveys feelings of mental weakness when interacting with others (Yes/No/Maybe).
Distribution
The dataset is primarily provided as a CSV file,
mental_health_finaldata_1.csv, with a size of 60.48 kB. It contains 13 columns and a total of 799 records. Additionally, a Word document is included within the zip file, detailing the data collection methodology, questionnaire, and possible answers, which aids in a deeper understanding of the main dataset.Usage
This dataset is ideal for various data analysis tasks and machine learning initiatives. It can be used for:
- Analysing mental health trends and patterns.
- Developing predictive models for stress and mental well-being indicators.
- Understanding the impact of external factors like quarantine on mental health.
- Informing the design of future mental health surveys and data collection projects.
- Educational purposes in psychology, public health, and data science courses.
Coverage
The dataset's scope includes demographic information from teenagers, college students, housewives, and professionals. Geographically, it incorporates data from Bangladesh for certain participant groups. The data captures experiences, such as frustrations and behavioural changes, specifically within the context of quarantine periods, providing a snapshot from January 2024.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Researchers: For studies on mental health, psychological impacts of global events, and sociological analyses.
- Data Scientists & Machine Learning Engineers: For building and testing models related to mental well-being prediction and analysis.
- Public Health Professionals: To identify trends and inform public health interventions.
- Students: For academic projects in data science, statistics, and health studies.
Dataset Name Suggestions
- Mental Health Survey Data 2024
- Depression & Well-being Study
- Quarantine Mental Health Impact Data
- Global Mental Health Insights
- RHMCD-20 Mental Health & Stress Dataset
Attributes
Original Data Source: Depression & Well-being Study
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