Assessing Mental Health Status Among University Students: A Case Study of NUST

Abstract

University students globally face higher mental health issues as compared to the general population. Evidence underscores a spectrum of depression, with prevalence oscillating from 10% to a staggering 85%, culminating in a weighted mean prevalence of 30.6%. This alarming reality not only jeopardizes the academic performance of students but also casts a pervasive shadow on their holistic well-being.. While the discourse on the global stage is fervent, a persistent lacuna exists, demanding targeted studies, interventions, and a call for stakeholder engagement at the university level. . Thisstudy aims to assess the prevalence of anxiety, depression, and stress among students at the National University of Sciences & Technology (NUST) and to identify key factors contributing to these conditions. A second aim of this study is to develop an accessible information system for stakeholders to pinpoint and address key concerns for comprehensive mental health assessments and strategic interventions that resonate among the students in general. A crosssectional study design was employed, utilizing the Depression, Anxiety, and Stress Scale-21 Items (DASS-21) to measure mental health conditions among 530 students. Binary logistic regression analysis was used to identify significant predictors of mental health issues. Machine learning techniques were used to reduce the number of items in DASS-21. Additionally, a Dash-based web application was developed for data visualization. Descriptive statistics indicated that the majority participants (75.28%) were of age 18 to 25 whereas 56.23% were male. Findings indicate a high prevalence of extremely severe depression and anxiety, affecting 27.54% and 31.69% of students, respectively. Conversely, (36.41%) exhibited normal stress levels. Logistic regression analysis revealed that female students are more xiv likely to report all three conditions stress, anxiety, and depression. Depression was also associated with age, financial concerns, and perceived social support. Anxiety correlated with the type of accommodation and social support. Stress was related to gender, educational level, and social support. The Dash-based web application proved effective in visualizing complex data, facilitating better understanding and decision-making. This study fills the research gap by collection and assessment of university level data. The findings highlight an urgent need for university authorities to focus on the mental health of students to improve overall quality of life. The significant impact of depression and anxiety on academic performance warrants the inclusion of management strategies for these conditions in university orientations.