Student Mental Health Analysis Dashboard

Insight into Student Mental Well-being

This Power BI dashboard offers a comprehensive analysis of student mental health, providing insights into the prevalence of depression, anxiety, and panic attacks among students. It examines various contributing factors such as academic year, age, gender, marital status, CGPA, and specific courses. The dashboard aims to highlight key trends and areas of concern to support student welfare initiatives.

Project Overview & Analytical Goals

The primary objective of this project was to analyze student mental health data to identify patterns and correlations that could inform targeted support strategies. Key questions addressed include:

• What is the overall prevalence of mental health conditions like depression, anxiety, and panic attacks among the student population?
• How do mental health challenges vary across different academic years and age groups?
• Is there a gender disparity in reported mental health issues, particularly depression?
• Does marital status or CGPA influence the likelihood of experiencing mental health conditions?
• Which courses are associated with a higher incidence of mental health concerns?
• How many students have sought professional help?

Data Source

The dataset for this analysis comprises survey or record data pertaining to student mental health, encompassing various demographic and academic attributes.

Methodology

1. Data Cleaning and Transformation: The raw student mental health data was prepared for analysis through a series of cleaning and transformation steps in Power Query. This involved handling missing values by replacing them appropriately (e.g., "Unknown" for categorical fields, averages or zeros for numerical fields where applicable). Data types were accurately set for all columns, ensuring numerical fields (like age, CGPA) and categorical fields (like gender, marital status, course) were correctly interpreted. Consistency was enforced across various text fields to standardize entries and facilitate accurate aggregation and filtering within the dashboard.
2. DAX Calculations: Measures were created to summarize key mental health statistics, including:
   • Total Number of Students: 101
   • Number of Courses: 41
   • Students With Depression: 35
   • Students With Anxiety: 34
   • Students With Panic Attack: 33
   • Students Who Saw a Specialist: 6
3. Interactive Dashboard Design: The Power BI dashboard features several interactive visualizations:
   • Bar charts illustrating the distribution of depression, anxiety, and panic attacks by "Current Year of Study."
   • Line charts showing the trend of mental health conditions across "Age" groups.
   • A pie chart displaying "Gender by Depression," indicating a higher prevalence among female students (29 females vs. 6 males among depressed students).
   • Bar charts analyzing "Marital Status by Depression" (Single: 19, Married: 16) and "CGPA by Anxiety."
   • A bar chart identifying the "Course with the most Depression, Anxiety and Panic Attack."
   • Interactive filters for "Current Year of Study," "Gender," and "CGPA" to allow for detailed exploration.

Key Findings & Insights

• Significant Prevalence of Mental Health Conditions: The analysis of 101 students reveals a notable prevalence of mental health challenges within the student population. Approximately 34.6% of students (35 individuals) reported experiencing depression, 33.7% (34 individuals) reported anxiety, and 32.7% (33 individuals) reported panic attacks. This indicates that roughly one-third of the students surveyed are grappling with at least one of these conditions, underscoring a pressing need for support.
• Gender Disparity in Depression: A stark gender disparity is observed in the incidence of depression. Out of the 35 students reporting depression, a significant majority—29 (82.8%)—are female, compared to only 6 (17.2%) male students. This finding suggests that female students may be disproportionately affected by depression and require targeted mental health interventions.
• Varying Impact Across Academic Years and Age Groups: The dashboard highlights that the prevalence of depression, anxiety, and panic attacks is not uniform across all academic years and age groups. While the exact patterns depend on the dataset, this variation suggests that specific periods of study (e.g., transition into university, final year pressure) or certain age brackets might be particularly vulnerable to mental health stressors.
• Broad Impact Across Demographics: Mental health challenges are not confined to specific demographics, impacting students across different marital statuses and CGPA ranges. While the dashboard shows figures like 19 single students and 16 married students experiencing depression, and anxiety levels varying by CGPA, it reinforces that mental health concerns can affect any student, regardless of their personal or academic standing.
• Course-Specific Pressures: The identification of "Course with the most Depression, Anxiety and Panic Attack" is a crucial insight. This strongly suggests that certain academic programs or fields of study may exert unique pressures or demands that contribute to higher rates of mental health issues among their students. Pinpointing these courses allows for targeted review and support within those departments.
• Underutilization of Professional Help: Despite the significant prevalence of mental health conditions, only 6 out of 101 students (approximately 6%) have sought professional help from a specialist. This alarmingly low rate indicates substantial barriers to accessing or utilizing mental health services, whether due to stigma, lack of awareness, limited resources, or other factors.

Recommendations

• Implement proactive mental health screening programs and awareness campaigns across all academic years to identify students at risk early.
• Develop and promote targeted mental health support resources and programs specifically tailored for female students to address the observed gender disparity in depression.
• Collaborate with academic departments to review course loads and academic support systems in courses with higher reported mental health concerns.
• Launch initiatives to reduce stigma around mental health and improve access to counseling and specialist services, especially given the low number of students who have seen a specialist.
• Provide tailored interventions and workshops based on age groups and academic years to address specific stressors or challenges faced by different student populations.

Project Impact & Value Proposition

This project demonstrates my ability to analyze sensitive data and present complex findings in an accessible manner. The insights gained can be highly valuable for:

• Educational Institutions: To develop targeted mental health programs, allocate resources, and improve student support services.
• Counseling Centers: To understand demographic risk factors and tailor their outreach and interventions.
• Policy Makers: To inform campus policies aimed at fostering a healthier academic environment and promoting student well-being.