Mental Health Assessment Web Application

A Flask-based web application designed to help users assess, monitor, and understand their mental well-being. The application provides interactive tests to evaluate depression, anxiety, and stress levels through questionnaires, sentiment analysis, and behavioral tracking.

Features

• Depression Test: A 10-question assessment to help identify the severity of depression symptoms (ranging from Minimal to Severe).
• Anxiety Test: A 7-question assessment for evaluating anxiety levels.
• Daily Check-ins: Users can log their thoughts and feelings. The system calculates a stress score using Rule-Based Sentiment Analysis combined with auto-captured behavioral metrics (session duration, typing delay, click rate).
• Stress Prediction API: Uses a pre-trained Machine Learning model (stress_model.pkl) to predict stress levels based on user interactions.
• Weekly Dashboard: Tracks and visualizes user stress data over the past 7 days, allowing users to monitor trends in their mental health.

Technology Stack

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript (Jinja2 templates)
• Database: SQLite (checkins.db)
• Machine Learning: Scikit-Learn (pickle for model loading), Pandas
• Deployment: Configured with a Procfile (likely for Heroku or similar platforms).

Project Structure

Mental-Health/
│
├── app.py                  # Main Flask application and routes
├── database.py             # SQLite database connections and setup
├── run.py                  # Script to run the application
├── checkins.db             # SQLite database for storing check-in data
│
├── model/                  # Contains pre-trained ML models
│   └── stress_model.pkl    
├── anxiety_model.pkl       # Pre-trained ML model for anxiety prediction
│
├── templates/              # HTML templates (landing, forms, tests, dashboard)
├── static/                 # CSS/JS and static assets
│
└── Procfile                # Deployment configuration

Installation & Setup

1. Clone or Download the repository Navigate to the project directory in your terminal.

   cd Mental-Health

2. Create a Virtual Environment (Recommended)

   python -m venv venv

   • On Windows: venv\Scripts\activate
   • On macOS/Linux: source venv/bin/activate

3. Install Dependencies Make sure you have installed the required Python packages (e.g., via pip install -r requirements.txt if available, or install manually):

   pip install Flask pandas scikit-learn

4. Run the Application

   python app.py

   (Alternatively, you can run python run.py)

5. Access the Application Open your web browser and navigate to http://127.0.0.1:5000/.

How It Works

• Tests: When you submit a test (like the Depression or Anxiety test), the app evaluates your scores against standard medical thresholds.
• Check-ins: The app captures both your text input and how you interact with the form. It searches for predefined positive and negative keywords inside your text and maps a combined final score into a metric of "Low", "Moderate", or "High" Stress. This result is then stored in the local SQLite database.
• Analytics: The dashboard route (/weekly-data) fetches your previous check-ins to present your stress trends as a graph directly on the dashboard page.