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Mental Wellness and Lifestyle Factors
Mental Health & Wellness
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About
The intricate connections between mental health and a variety of demographic, lifestyle, and work-related factors. It serves as a valuable resource for understanding how conditions related to work and personal life can influence mental well-being. The data is designed for exploratory analysis, predictive modelling, and statistical research, offering insights into potential risk factors for mental health challenges. It can be used to examine the impact of work-life balance and predict mental health outcomes based on lifestyle choices and workplace conditions.
Columns
- Gender: The gender of the individual (Male/Female).
- Age: The age of the individual in years.
- Work Pressure: A rating of work-related pressure on a scale of 1 (low) to 5 (high).
- Job Satisfaction: A rating of satisfaction with one's job on a scale of 1 (low) to 5 (high).
- Sleep Duration: The typical amount of sleep per night, categorised as Less than 5 hours, 5-6 hours, 7-8 hours, or More than 8 hours.
- Dietary Habits: The individual's dietary habits, categorised as Healthy, Moderate, or Unhealthy.
- Have you ever had suicidal thoughts ?: A yes/no indicator of whether the individual has experienced suicidal thoughts.
- Work Hours: The number of work hours per day.
- Financial Stress: A rating of financial stress on a scale of 1 (low) to 5 (high).
- Family History of Mental Illness: A yes/no indicator of a family history of mental illness.
Distribution
The dataset is provided in a single tabular CSV file named
Depression Professional Dataset.csv with a size of 113.66 kB. It contains 2054 records across 11 columns, though information is provided for 10 of these.Usage
Ideal applications for this dataset include:
- Predictive Modelling: Building models to predict mental health outcomes based on lifestyle and demographic data.
- Statistical Research: Conducting studies to identify significant risk factors for depression and other mental health issues.
- Exploratory Data Analysis: Investigating the relationships between work conditions, lifestyle patterns, and mental well-being.
- Work-Life Balance Studies: Analysing the impact of work hours and job satisfaction on mental health.
Coverage
The dataset covers a demographic range of individuals aged 18 to 60. It includes various lifestyle and work-related factors but does not specify a particular geographic region or time frame for data collection.
License
CC0: Public Domain
Who Can Use It
- Researchers and Academics: To study the determinants of mental health in various populations.
- Data Scientists: To develop and test machine learning models for predicting depression risk.
- Public Health Professionals: To understand trends and risk factors for mental health issues to inform policy and interventions.
- Corporate Wellness Planners: To analyse how work pressure and job satisfaction affect employee well-being.
Dataset Name Suggestions
- Mental Wellness and Lifestyle Factors
- Work-Life Balance and Depression Indicators
- Predictors of Mental Health
- Demographic and Lifestyle Impact on Depression
Attributes
Original Data Source: Mental Wellness and Lifestyle Factors
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