Maternal Depression Dataset: A Machine Learning Perspective on the Mental Health Analysis of Mothers of School-Going Children in Dhaka using the Zung SDS Scale

The dataset contains 594 records classified into four depression severity levels: 1. Not Depressed 2. Mild Depressed 3.

Moderate Depressed 4. Severe Depressed Features: The dataset integrates socio-demographic information, including age range, marital status, education level, and occupation, along with mental health indicators such as: - Emotional Well-being: Downhearted feelings, crying spells, hopelessness - Physiological Symptoms: Sleep disturbances, appetite changes, weight loss, increased heart rate - Cognitive Patterns: Trouble concentrating, decision-making difficulty, restlessness - Suicidal Ideation: Feelings of being "better off dead" Applications in Machine Learning & Health Informatics: - Predictive modeling for maternal depression assessment - Explainable AI (XAI) for interpretable mental health diagnosis - mHealth applications for early detection and intervention - Statistical and behavioral analysis of psychological distress