Published: 18 December 2023| Version 1 | DOI: 10.17632/bvvpwb9b85.1
Maharunnasha Antora


The dataset on 803 engineering students from 14 universities of Bangladesh provides a comprehensive insight into various aspects of their lives, encompassing demographic information, lifestyle choices, social media habits, educational concerns, family dynamics, personal relationships, past experiences, and mental health (Major Depressive Disorder) indicators. Here is a breakdown of the key variables: Demographic Information: Age, Gender, Department, Relationship/Marital status, Area of living, Socio-economic status (family), Current living arrangement, Year of study Lifestyle: Religious practices, Exercise habits, Sleep-related issues, Satisfaction with sleep quality, Smoking habits, Drinking (alcohol) habits Social Media Addiction: Eagerness to use social media, Morning routine involving social media, Productivity impact due to social media, Quest for internet connectivity for social media, Purposeless use of social media, Late-night social media activity Educational Issue: Lack of concentration during classes, Worries about academic performance, Concerns about job prospects after graduation, Preoccupation with future after university life, Lack of self-confidence Family Issue: Parental misunderstandings, Belonging to a broken family, Relationship status with family members, Sharing feelings of depression with family Personal Relationship: Current status of the romantic relationship, Relationship-induced stress, Relief when partner isn't around Diminished joy in favorite activities due to the relationship, Consideration of breaking up for mental health preservation Past Experience: History of mental disorder diagnosis, Previous consultation with therapists/psychologists, Childhood problems (abuse, early loss of parent), Past experiences of bullying Major Depressive Disorder: The dataset concludes with a series of questions (following PHQ-9) related to the diagnostic criteria for Major Depressive Disorder, encompassing feelings of sadness, loss of interest, sleep disturbances, fatigue, changes in appetite, negative self-perception, concentration issues, psychomotor changes, and suicidal thoughts. Overall, this dataset provides a holistic understanding of the students' lives, shedding light on both everyday aspects and potential mental health challenges. Researchers and analysts can use this information to explore correlations, patterns, and potential intervention strategies in the context of engineering students in Bangladesh.



Daffodil International University


Mental Health, Structural Equation Modeling, University Student