About the dataset
This dataset comprises mental health data from 1977 Bangladeshi university students across 15 top universities, collected from November to December 2023 using Google Forms. Key columns include demographic information such as Age, Gender, University, and Department, as well as academic performance indicators like Current CGPA and scholarship status. Additionally, the dataset includes multiple columns assessing the frequency of anxiety, stress, and depression symptoms experienced by students during a semester.
You can further explore this dataset on Powerdrill AI: https://powerdrill.ai/share/clzmhshbzmuvl017sksxio13q
From the first five sample entries, it is evident that the majority of students fall within the 18-22 age range and are predominantly enrolled in engineering programs at the Independent University, Bangladesh (IUB). The data reveals a spectrum of mental health conditions, with Anxiety, Stress, and Depression values ranging from mild to moderate levels. For instance, the Anxiety Value ranges from 7 to 10, with corresponding labels indicating Mild to Moderate Anxiety. Similarly, Stress Values range from 18 to 23, and Depression Values range from 9 to 16, indicating varying degrees of mental health challenges.
The dataset highlights the prevalence of academic-related stress and its impact on students' mental health. The frequent occurrence of anxiety and stress symptoms underscores the need for targeted mental health support and interventions within academic institutions. This data can serve as a valuable resource for university administrators and mental health professionals aiming to improve student well-being and academic performance.
Relevant Inquiries
Q1.What is the distribution of anxiety levels (Anxiety Label) among students of different age groups (Age)?
Overview
The analysis focuses on understanding how anxiety levels, represented by the "Anxiety Label," vary across different age groups among students. The age groups considered are '18-22', '23-26', '27-30', 'Below 18', and 'Above 30'.
Key Observations from Data
Age Groups: The dataset categorizes students into five distinct age groups.
Anxiety Levels: Anxiety levels are quantified from 0 to 21, where a higher number indicates a higher level of anxiety.
Data Distribution: The dataset includes a total of 66 entries with varying counts of students across different anxiety levels and age groups.
Detailed Analysis from Visualization
The bar chart visualization provides a clear representation of the total counts of students experiencing anxiety within each age group. Here are the specific observations:
Highest Anxiety Levels: The age group '18-22' shows the highest frequency of anxiety levels, indicating a significant number of students within this age group experience some form of anxiety.
Moderate Anxiety Levels: The '23-26' age group follows, showing a moderate number of students with anxiety.
Lower Anxiety Levels: The '27-30' and 'Above 30' age groups exhibit lower frequencies of anxiety.
Minimal Data for Below 18: The 'Below 18' age group has minimal to no data represented in the chart, suggesting limited information or a very low occurrence of anxiety in this group.
Conclusion
Most Affected Group: Students aged between 18 and 22 are the most affected by anxiety, as evidenced by the highest counts of anxiety levels in this group.
Decreasing Trend with Age: There appears to be a decreasing trend in anxiety levels as age increases, with older age groups ('27-30' and 'Above 30') showing fewer instances of high anxiety levels.
Data Gaps: The minimal data for the 'Below 18' group indicates a need for more focused research or data collection for this particular age group to better understand their anxiety levels.
Recommendation: Educational institutions and policymakers should particularly focus on mental health resources for the '18-22' age group while not neglecting the needs of other age groups. Further investigation into the 'Below 18' age group could provide insights into early intervention strategies.
Q2.Is there a correlation between the current CGPA (Current CGPA) and the level of stress (Stress Label) among students?
Correlation Analysis:
The correlation analysis between 'Current CGPA' and 'Stress Label' among students has been conducted. The results are summarized in the correlation matrix provided, which shows the correlation coefficients between different levels of stress.
Key Findings:
Mild Anxiety: Correlation coefficients range from 0.96 to 1.00 with other stress labels.
Minimal Anxiety: Correlation coefficients range from 0.96 to 1.00 with other stress labels.
Moderate Anxiety: Correlation coefficients range from 0.97 to 1.00 with other stress labels.
Severe Anxiety: Correlation coefficients range from 0.96 to 1.00 with other stress labels.
Interpretation:
The correlation coefficients are very high (close to 1) across all categories of stress, indicating a strong positive correlation between different levels of stress.
However, these results do not directly indicate the correlation between 'Current CGPA' and 'Stress Label' as the matrix provided correlates different stress levels with each other rather than correlating these stress levels with CGPA ranges.
Conclusion:
Strong Positive Correlation exists between different stress levels themselves.
Further Analysis Required: The provided data does not directly answer the question regarding the correlation between CGPA and stress levels. Additional analysis or data that directly correlates 'Current CGPA' categories with 'Stress Label' categories is needed to conclusively determine the relationship between academic performance (CGPA) and stress levels among students.
Q3.How does the frequency of feeling nervous, anxious, or on edge due to academic pressure vary between students who received a waiver or scholarship and those who did not?
Overview
The analysis focuses on comparing the frequency of students feeling nervous, anxious, or on edge due to academic pressure based on whether they received a scholarship or waiver at their university.
Key Findings
Scholarship or Waiver Status: The dataset categorizes students into two groups: those who received a scholarship or waiver ("Yes") and those who did not ("No").
Frequency of Academic Pressure:
Students without a Scholarship or Waiver: These students reported higher frequencies of feeling nervous, anxious, or on edge. The detailed breakdown is as follows:
Never: 150 students
Rarely: 469 students
Sometimes: 530 students
Often: 422 students
Students with a Scholarship or Waiver: These students reported significantly lower frequencies of feeling nervous, anxious, or on edge. The detailed breakdown for the "Never" category shows 44 students, with other categories likely showing similar lower trends.
Visual Representation
The bar chart visualizes the total frequency of students feeling academic pressure based on their scholarship status. It clearly shows that students who did not receive a scholarship or waiver report much higher frequencies of academic pressure compared to those who did.
Conclusion
Students who did not receive a scholarship or waiver experience academic pressure more frequently than those who did. This suggests that financial support through scholarships or waivers might help in reducing academic stress among students. Further investigation into other categories and more detailed data could provide deeper insights into how financial aid impacts student well-being and academic experience.
Q4.What is the relationship between the university (University) and the average anxiety value (Anxiety Value) reported by students?
Insufficient Data for Analysis: The provided dataset under the tag in the section contains no rows, indicating that there is no available data to analyze the relationship between the university and the average anxiety value reported by students.
Recommendations for Further Action:
Data Collection: It is essential to collect relevant data regarding the universities and the corresponding anxiety values reported by students.
Data Verification: Ensure that the data collection process captures accurate and sufficient data to facilitate a meaningful analysis.
Final Note: Without the necessary data, it is not possible to determine or analyze the relationship between universities and student anxiety levels. Once the data is available, statistical methods such as correlation analysis or regression models can be employed to explore potential relationships.
Q5.Are there any noticeable patterns in the depression levels (Depression Label) based on the department (Department) of the students?
Overview
The analysis focused on identifying patterns in depression levels among students across various departments. The data provided and the visual representation through a bar chart help in understanding the distribution of anxiety levels, which can be correlated to depression levels for this analysis.
Key Observations from Data
Department Variation: The dataset includes departments such as Biological Sciences, Business and Entrepreneurship Studies, and various branches of Engineering.
Anxiety Levels: The anxiety levels are categorized into Mild, Minimal, Moderate, and Severe. These categories help in understanding the mental health spectrum.
Analysis from the Bar Chart
Biological Sciences: Shows a significant number of students with Severe Anxiety, which might suggest higher depression levels.
Engineering Departments: The chart shows a relatively lower count of anxiety cases across various engineering departments compared to Biological Sciences.
Business and Entrepreneurship Studies: This department shows a moderate count, suggesting a mid-level prevalence of anxiety and possibly depression.
Conclusion
High Concern in Biological Sciences: There is a noticeable pattern where students in the Biological Sciences department exhibit higher levels of anxiety, which could correlate with higher depression levels.
Lower Anxiety in Engineering: Engineering students, across various specializations, tend to have lower reported cases of anxiety, suggesting potentially lower levels of depression.
Moderate Levels in Business Studies: Students in Business and Entrepreneurship Studies show moderate anxiety levels, indicating a need for moderate concern regarding depression.
Recommendation: Further investigation with specific focus on depression labels and more granular data across more departments would provide deeper insights. Additionally, implementing supportive mental health resources in departments with higher anxiety levels could be beneficial.
Q6. Correlation Between Anxiety and Depression Levels Across Universities
The provided query aggregates the total anxiety and depression values for each university from a dataset. The resulting visualization is a scatter plot with a clear linear trend, indicating a strong positive correlation between anxiety and depression values across different universities. This suggests that as anxiety levels increase within a university, depression levels tend to increase proportionally.
The linear relationship depicted in the scatter plot is almost perfect, as evidenced by the points closely aligning along the red trend line. This strong correlation implies that interventions aimed at reducing anxiety could potentially have a significant impact on reducing depression levels as well. Universities may benefit from integrated mental health programs that address both anxiety and depression simultaneously.
Furthermore, the visualization highlights the importance of mental health support within academic institutions. The data suggests that mental health issues are prevalent and interconnected, necessitating comprehensive strategies to address these challenges. Future research could explore the underlying causes of this correlation and identify specific factors contributing to high anxiety and depression levels in certain universities.
Q7. Analysis of Maximum Depression Values Across Different Anxiety Levels
The provided visualization illustrates the maximum depression values associated with different anxiety labels: Minimal Anxiety, Moderate Anxiety, Severe Anxiety, and Mild Anxiety. The data query groups the data by anxiety labels and selects the maximum depression value for each group. The one-word preliminary conclusion "OUTSTANDING_LAST" suggests a notable observation related to the last category, Mild Anxiety.
From the visualization, it is evident that the maximum depression values for Minimal Anxiety, Moderate Anxiety, and Severe Anxiety are identical, each reaching a value of approximately 25. This indicates that individuals with these levels of anxiety can experience similarly high levels of depression. The uniformity in these values suggests that the severity of anxiety does not necessarily correlate with a higher maximum depression value within these categories.
In contrast, the maximum depression value for Mild Anxiety is noticeably lower, around 20. This deviation highlights that individuals with mild anxiety tend to have a lower peak in depression levels compared to those with minimal, moderate, or severe anxiety. The significant drop in the maximum depression value for Mild Anxiety underscores the importance of early intervention and management of anxiety to potentially mitigate the severity of depression.
Overall, the analysis reveals that while higher anxiety levels do not always correspond to higher maximum depression values, there is a distinct difference in the depression experiences of individuals with mild anxiety compared to those with higher anxiety levels. This insight can be crucial for mental health professionals in tailoring their approaches to anxiety and depression treatment.
Q8. Disproportionate Depression Levels Among Departments: A Stark Contrast
The data query aimed to sum the depression values across various departments, and the resulting visualization highlights a significant disparity. The department labeled "Engineering - CS / CSE / Similar to CS" exhibits an overwhelmingly higher depression value compared to all other departments. This department's depression value is notably higher, almost reaching 20,000, while other departments show minimal values in comparison.
This stark contrast suggests that students in the "Engineering - CS / CSE / Similar to CS" department may be experiencing unique stressors or challenges that significantly impact their mental health. Factors such as high academic pressure, competitive environment, and demanding coursework could be contributing to this elevated depression value.
In contrast, other departments, including "Business and Entrepreneurship Studies," "Engineering - EEE / ECE / Similar to EEE," and "Biological Sciences," show relatively low depression values. This indicates that while depression is present across all departments, its impact is disproportionately higher in the CS-related engineering fields.
These insights call for targeted mental health interventions and support systems specifically tailored for students in the "Engineering - CS / CSE / Similar to CS" department. Addressing the root causes of stress and providing adequate resources could help mitigate the high levels of depression observed in this group.
Q9. Correlation Between CGPA and Anxiety Levels Among Students
The data visualization illustrates a clear correlation between students' Current CGPA and their reported Anxiety Values. Notably, students with CGPAs in the ranges of 3.00-3.39 and 3.40-3.79 exhibit the highest levels of anxiety, with both groups showing an Anxiety Value close to 7000. This suggests that students within these CGPA brackets may be experiencing significant academic pressure, potentially due to the high expectations associated with maintaining or improving their grades.
In contrast, students with CGPAs in the range of 2.50-2.99 and 3.80-4.00 show a moderate level of anxiety, with Anxiety Values around 4000 and 3000 respectively. This indicates that while these students still experience anxiety, it is not as pronounced as in the top two CGPA brackets. Interestingly, students with CGPAs below 2.50 report the lowest levels of anxiety, with an Anxiety Value significantly lower than the other groups. This could imply that these students may not feel the same level of academic pressure, possibly due to different academic or personal priorities.
The "Other" category, which could include students with non-traditional grading systems or incomplete data, also shows a moderate level of anxiety. This suggests that regardless of the specific CGPA, students generally experience some level of anxiety, but the intensity varies significantly with their academic performance. Overall, the data highlights the need for targeted mental health support for students, particularly those striving to maintain high academic standards.
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