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Well-being Habits Impact Dataset
Mental Health & Wellness
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Free
About
This dataset explores the influence of various lifestyle choices on mental well-being, covering the period from 2019 to 2024. It collects details on daily habits such as exercise routines, dietary patterns, sleep duration, stress indicators, and social engagement, alongside demographic data. This resource is designed to assist in understanding the relationships between lifestyle factors and mental health conditions, thereby supporting the creation of predictive models and focused interventions for mental well-being.
Columns
- Country: The country of the survey respondent.
- Year: The year the survey was conducted.
- Age: The age of the respondent, with values ranging from 18 to 64 years.
- Gender: The self-identified gender of the individual (e.g., Female, Other).
- Sleep Hours: The average number of hours slept per day, ranging from approximately 1.4 to 11.3 hours.
- Diet Type: The type of diet followed, such as Junk Food or Balanced.
- Exercise Level: Describes the frequency and intensity of physical activity (e.g., Low, Moderate).
- Social Interaction Score: A numerical score reflecting the level of social interaction, ranging from 1 to 10.
- Stress Level: A self-reported stress level, categorised as Low, High, or Other.
- Anxiety Score: A severity score indicating anxiety, typically on a 1-10 scale.
- Happiness Score: An overall rating of happiness, provided on a 1-10 scale.
- Mental Health Condition: Identifies diagnosed mental health conditions, such as Anxiety or PTSD.
- Work Hours per Week: The average number of hours worked weekly, ranging from 20 to 59 hours.
- Screen Time per Day (Hours): The average daily screen time in hours, ranging from 2 to 8 hours.
Distribution
The dataset is provided as a CSV file,
Mental_Health_Lifestyle_Dataset.csv, with a size of 187.58 kB. It contains 12 columns and approximately 3000 records.Usage
This dataset is an ideal resource for researchers, data scientists, and mental health professionals. It can be used to:
- Gain insights into correlations between lifestyle choices and mental health outcomes.
- Develop predictive models for mental well-being.
- Design and evaluate targeted interventions aimed at improving mental health through lifestyle adjustments.
Coverage
The dataset covers the period from 2019 to 2024. Geographically, it includes respondents from the USA (15%), Japan (15%), and various other countries (71%). Demographically, it includes individuals across a wide age range of 18 to 64 years and different gender identities.
License
CC0: Public Domain
Who Can Use It
- Academics and Researchers: For studies on public health, psychology, and sociology, exploring the determinants of mental health.
- Data Scientists and Analysts: For building machine learning models to predict mental health conditions based on lifestyle, or identifying key lifestyle indicators.
- Mental Health Professionals and Policy Makers: To inform evidence-based strategies for promoting mental well-being and designing preventative programmes.
Dataset Name Suggestions
- Mental Health and Lifestyle Habits Dataset (2019-2024)
- Lifestyle and Mental Well-being Study (2019-2024)
- Global Mental Health Lifestyle Data
- Well-being Habits Impact Dataset
Attributes
Original Data Source:Well-being Habits Impact Dataset
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