Survey Dataset on Understanding Migration Intent and Psychological Stress Among Bangladeshi Youth.
Description
Migration decisions—especially for youth—are influenced by personal ambitions, socio-economic conditions, and global exposure. These decisions involve complex emotional processes like uncertainty, anxiety, and family or societal pressure. Many young Bangladeshi individuals aspire to pursue better opportunities abroad, making it critical to understand their motivations and psychological stressors. This dataset was collected through structured questionnaires distributed via Google Forms and in-person interviews across Bangladesh. It includes diverse responses related to migration interest, stress levels, coping mechanisms, and future plans, gathered from various ages, occupations, and socio-cultural backgrounds. Key Features: Demographics: Age group, Gender, Occupation. Migration Decisions: Whether decided to migrate abroad, intended duration, awareness of migration programs or scholarships. Influencing Factors: Role of social media, family, friends, mentors, and target countries. Psychological Stress Indicators: Type and intensity of stress (e.g., visa anxiety, family pressure, fear of rejection), self-reported emotional challenges in migration planning. Coping Strategies: Stress relief methods such as hobbies, physical activity, social support, and online forums. Barriers to Migration: Financial constraints, lack of experience or qualifications, family obligations or cultural resistance. Return Plans & Impact: Plans to return, perceived impact on family/community, trust in government youth migration support. Recommendation Likelihood: Willingness to recommend migration to peers (scale of 1 to 5). Usage: This dataset is useful for researchers, data scientists, policymakers, and mental health professionals to understand: Psychological aspects of youth migration. Barriers and motivations influencing migration choices. Support strategies for stressed or at-risk individuals. Using machine learning and data analytics, it supports models like: Migration intent prediction (Logistic Regression, Random Forest, XGBoost). Stress level classification (SVM, Decision Tree). Cluster analysis of motivations (K-Means, DBSCAN). Recommendation systems for stress management (ML-kNN, content-based filtering). Return likelihood and family impact prediction. These insights can improve policy decisions, mental health awareness, and personalized services for youth. Data Sources: Collected from 1,614 individuals including university students, professionals, urban and rural residents across Bangladesh through survey online and face-to-face methods; all data standardized via Google Forms. The dataset’s csv file size is 815 kb.
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Institutions
- Daffodil International University