import streamlit as st

# Page Title
st.title("📄 Problem Statement")

# Problem Statement Section
st.markdown("""
### Problem Statement:
Mental health issues such as depression are becoming increasingly common among students due to academic stress, lack of sleep, financial strain, and other lifestyle factors.

Early detection of such conditions is essential for timely intervention and support.

This project aims to use machine learning techniques to identify students who are at risk of depression based on multiple socio-academic and behavioral indicators.
""")

# Objective Section
st.markdown("""
### 🎯 Objective:
- Build a classification model using **KNN** to predict student depression.  
- Develop an easy-to-use Streamlit app that collects relevant student data and returns a prediction.  
- Help raise awareness about the contributing factors leading to depression in students.
""")

# Importance Section
st.markdown("""
### ✅ Why is this important?
- Supports early detection of mental health issues.  
- Helps in designing preventive mental health strategies for academic institutions.  
- Demonstrates the application of machine learning in the domain of psychology and education.
""")

if st.button("Next >>"):
    st.switch_page(r"pages/2 Data Understanding.py")

if st.button("<< Back"):
    st.switch_page("Introduction.py")