Family Mental Health History and Stress Level Analysis

By abhishek.verma75000 · May 28, 2026

This study investigates whether a family history of mental illness significantly affects stress levels across different age groups using comparative…

Two visualizations were generated to show which marital status and number of children combinations are associated with the highest average stress levels. A heatmap displays the full breakdown across all marital status and children count combinations, while a horizontal bar chart highlights the top 10 combinations ranked by average stress.

The analysis successfully produced two bar charts and two data tables showing average stress levels broken down by employment status and job type. You can see exactly which categories carry the highest stress burden in the visualizations generated.

More daily time dedicated to family is clearly associated with better work-family balance scores. The analysis reveals a strong positive correlation of 0.57, meaning people who spend more hours with family tend to report significantly higher work-family balance. Two charts were generated — a bar chart showing average balance scores by daily family hours, and a box plot showing the full distribution — along with supporting data tables.

Surprisingly, family history of mental illness has almost no impact on stress levels. People with a family history average a stress score of 5.70, compared to 5.74 for those without — a negligible difference of just -0.04 points. Two grouped bar charts and box plots were generated showing the breakdown across five age groups (15-20 through 36-40).

Employment contract type has a small but noticeable influence on both work-family balance and stress levels. Permanent employees report slightly better work-family balance (2.21/5) and lower stress (5.45/10) compared to temporary workers (2.14/5 balance, 5.64/10 stress). Two visualizations were generated: a grouped bar chart comparing average work-family balance and stress side-by-side across contract types, and a box plot showing the full distribution of stress levels for each contract type.

Two visualizations were generated to show how stress levels vary across income brackets. A grouped bar chart compares average stress levels side-by-side for personal vs. family income brackets (Very Low through Very High), and a heatmap shows the combined effect of both personal and family income on average stress levels simultaneously.

The analysis successfully produced a horizontal bar chart and data tables showing average stress levels by job type, filtered to only include job types with at least 50 respondents. The chart uses a red color scale to highlight which job types are most stressful, making it easy to visually compare stress levels across categories.

The analysis compared average Stress Level and Work-Family Balance scores across different Education Level categories. A grouped bar chart was generated showing both metrics side by side for each education group, complete with error bars representing the standard deviation. A summary data table was also produced with respondent counts, means, and standard deviations for each group.

The analysis examined the distribution of Number of children and Number of family members, computed key statistics, and explored how these variables relate to stress levels. Three charts were generated: histograms with KDE curves for each variable, and a grouped bar chart showing average stress by count. The data shows that most households have 0 children (mean=0.93, median=0) and family sizes cluster around 2–3 members (mean=2.84, median=3). Both variables show a clear positive relationship with stress — households with more children or larger families consistently report higher stress levels.

The correlation matrix has been computed and visualized for all 8 numeric variables: Age, Stress level, Annual personal income, Annual family income, Number of children, Number of family members, Daily time dedicated to family, and Work family balance. Two interactive charts were generated — a full heatmap showing all pairwise correlations and a bar chart highlighting the top positive and negative relationships. The analysis reveals that correlations across these variables are generally modest, suggesting these factors are largely independent of one another with no single dominant linear relationship.