Mental Health Web App

Inspiration

The increasing prevalence of mental health issues globally, especially among the youth, inspired us to create this web app. We realized that many people don’t have easy access to mental health resources or don’t know where to start. We wanted to create a platform that makes mental health resources easily accessible and helps users understand that they’re not alone.

What it does

Our Mental Health Web App serves as a resource for mental health support. It provides users with a variety of self-help tools, including mindfulness surveys, Mood trackers, and a personal AI chat bot. Users can track their mood and mental health progress over time, helping them understand their own patterns and triggers.

How we built it

We used Python and Flask for the backend, with SQLAlchemy serving as the ORM for our SQLite3 database. The frontend was built using HTML CSS and Javascript, with a focus on a user-friendly and intuitive UI/UX. We also integrated OpenAI's APIs to implement and train our personal chatbot Maybax.

Challenges we ran into

One of the main challenges we faced was initializing and maintaining the database for our app. Implementing Flask and SQLALCHEMY was a challenge at first but once implemented all the individual pages were connected seamlessly. We spent a significant amount of time implementing and training the AI Chat Bot and the imbedded mood tracking calendar.

Accomplishments that we're proud of

We’re also proud of the intuitive and user-friendly interface we were able to create, which makes mental health resources more accessible.

What we learned

Through this project, we learned a lot about mental health resources and the importance of making these resources accessible. We also improved our skills respectively in front and back end development and learned how to effectively integrate APIs into our app.

What's next for Mental Health Web App

We plan to continue expanding the resources available on our app, including more self-help tools and a wider network of mental health professionals. We also aim to incorporate machine learning algorithms to provide personalized resource recommendations to our users.