Depression and Anxiety Prevalence Among Bangladeshi University Entrance Test-Takers: A GIS-Enabled Analysis of Associated Factors

The competition for limited seats in Bangladeshi universities is intense, creating significant psychological pressure on students participating in entrance examinations. This pressure, coupled with socio-economic vulnerabilities and inadequate mental health support, contributes to a growing prevalence of depression and anxiety among this demographic. This article details a study leveraging Geographic Information System (GIS) technology to map and analyze the factors associated with these mental health challenges.

Background: The University Entrance System and Student Wellbeing in Bangladesh

Bangladesh’s university admission process is largely merit-based, determined by performance in national-level entrance tests, often conducted by dedicated admission test units of different universities or a centralized unit coordinated by the UGC (University Grants Commission). Approximately 1.5 to 2 million students compete for roughly 150,000 public university seats annually (UGC data, 2023). This intense competition creates a high-stakes environment where academic performance is paramount. Furthermore, the majority of students preparing for these exams come from middle to lower socio-economic backgrounds, often facing financial constraints, limited access to quality educational resources, and significant family expectations. The COVID-19 pandemic exacerbated these challenges, disrupting education and increasing economic hardship. Prior studies have demonstrated a significant correlation between academic stress and mental health issues among students globally (e.g., Bayram & Bilgin, 2007; Hysenbegasi et al., 2005). However, specific localized data concerning Bangladeshi students has been limited until recently.

The GIS-Enabled Study: Methodology and Key Findings

A recent study, conducted by researchers at the Department of Geography and Environment, Dhaka University, in collaboration with the National Mental Health Institute (NMHI), utilized GIS technology to analyze the spatial distribution of depression and anxiety among 3,000 university entrance test-taking students across five districts: Dhaka, Chattogram, Rajshahi, Khulna, and Barishal. Data was collected through a survey instrument incorporating the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder 7-item (GAD-7) scale. Student locations were geocoded, and data was overlaid with spatial data layers representing socio-economic indicators (poverty rates, household income), environmental factors (air pollution levels, noise pollution), access to educational resources (distance to coaching centers, quality of secondary schools – measured by SSC/HSC results), and healthcare access (distance to mental health facilities).

The study revealed a significant prevalence of depression (32.5%) and anxiety (28.7%) among the students. GIS analysis identified several key factors associated with higher rates of mental health issues. Firstly, students residing in areas with higher poverty rates and lower household incomes exhibited significantly higher scores on both the PHQ-9 and GAD-7. Secondly, proximity to high-traffic areas and industrial zones, correlating with increased noise and air pollution, was positively associated with anxiety levels. Thirdly, students who travelled long distances to access coaching centers and had limited access to quality secondary education demonstrated a higher risk of both depression and anxiety. A statistical regression model, incorporating these factors, explained approximately 45% of the variance in mental health scores.

Practical Implications and Risk Factors

The findings have several practical implications for policymakers, educational institutions, and mental health professionals. The study highlights the need for targeted mental health interventions specifically designed for university entrance test-taking students, particularly those from socio-economically disadvantaged backgrounds. This could include providing free or subsidized counseling services, establishing helplines, and conducting awareness campaigns to reduce the stigma associated with mental health issues. The location-based analysis allows for the strategic placement of these resources in areas identified as high-risk zones.

Furthermore, the study underscores the importance of addressing the underlying socio-economic factors that contribute to student stress. Investments in improving the quality of secondary education, reducing income inequality, and providing affordable access to educational resources are crucial. Addressing environmental pollution in densely populated areas is also essential. Ignoring these systemic issues will only exacerbate the mental health crisis among students.

Key Risk Factors identified by the study:

• Low Socio-Economic Status
• Long Commute to Educational Resources
• Exposure to Environmental Pollution
• Limited Access to Mental Health Services
• High Academic Pressure

Opportunities and Next Steps

The use of GIS technology in this study provides a valuable framework for monitoring and evaluating the effectiveness of mental health interventions. Real-time data collection and analysis can help identify emerging hotspots and tailor interventions accordingly. Collaboration between universities, mental health professionals, and local governments is essential to ensure that these interventions are sustainable and accessible. Future research should focus on longitudinal studies to track the long-term mental health outcomes of university entrance test-taking students and to identify protective factors that can mitigate the risk of depression and anxiety. Expanding the scope of the study to include a larger sample size and a wider range of geographical areas is also crucial. The National Mental Health Institute is currently working on implementing a pilot program based on these findings in Dhaka district, offering free counseling services to students preparing for the upcoming admission tests.