Academic Stress & Mental Health Dataset

Columns

• Gender: Categorical variable indicating Male or Female. Male constitutes 53% of the dataset, while Female accounts for 47%.
• Age: A numerical variable representing age in years. Values range from 18 to 34, with a mean of 26.2 and a standard deviation of 4.89.
• Academic Pressure: An ordinal scale from 1 (low) to 5 (high). The mean value is 3, with a standard deviation of 1.39.
• Study Satisfaction: An ordinal scale from 1 (low) to 5 (high). The mean value is 3.08, and the standard deviation is 1.37.
• Sleep Duration: Categorical variable with options: Less than 5 hours, 5-6 hours, 7-8 hours, and More than 8 hours. Both 7-8 hours and More than 8 hours categories each represent 25% of the data.
• Dietary Habits: Categorical variable describing habits as Healthy, Moderate, or Unhealthy. Moderate and Unhealthy categories each make up 34% of the dataset.
• Have you ever had suicidal thoughts?: A boolean variable (Yes/No). 52% of entries indicate 'true' (Yes), while 48% indicate 'false' (No).
• Study Hours: A numerical variable representing work hours per day. Values range from 0 to 12, with a mean of 6.4 and a standard deviation of 3.74.
• Financial Stress: An ordinal scale from 1 (low) to 5 (high). The mean value is 2.93, with a standard deviation of 1.42.
• Family History of Mental Illness: A boolean variable (Yes/No). 47% of entries indicate 'true' (Yes), while 53% indicate 'false' (No).
• Depression: A boolean variable (Yes/No). 50% of entries indicate 'true' (Yes), and 50% indicate 'false' (No).

Distribution

Usage

• Developing predictive models to identify individuals at higher risk of depression or suicidal ideation.
• Analysing patterns and correlations between various lifestyle factors, academic performance, and mental health indicators among student populations.
• Informing the design and implementation of early intervention strategies and preventative programmes for student mental health.
• Supporting academic research aimed at understanding student well-being and the impact of different stressors.

Coverage

License

Who Can Use It

• Researchers and Academics: For scholarly studies on student mental health and model development.
• Healthcare Professionals: To gain insights into risk factors and to guide early intervention.
• Educational Institutions: To formulate support systems and policies that foster student well-being.
• Policymakers: For crafting public health initiatives focused on enhancing mental health outcomes within student communities.

Dataset Name Suggestions

• Student Mental Health & Depression Factors
• University Student Mental Well-being Data
• Academic Stress & Mental Health Dataset
• Student Depression Risk Factors

Attributes