EarthBrain

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Our Inspiration

1 in 5 U.S. adults experience mental illness each year, 53 million people in 2020
1 in 6 U.S. youth, aged 6-17, experience a mental health disorder each year
The average delay between the onset of mental illness symptoms and treatment is 11 years
155 million people live in a designated Mental Health Professional Shortage Area
Inadequate treatment can lead to substance abuse, academic and social harm, and negative consequences on relationships, economic productivity, and more

We recognize the detrimental impacts of mental health illnesses, as well as the damage that can be caused by delayed treatment, and we were inspired by this pressing crisis to create an affordable and easily accessible solution. EarthBrain seeks to address this issue by providing an efficient discussion forum that is tailored towards positive and supportive conversations around mental health between anonymous users with similar interests. For more information on the background of our product, the mental health crisis in the US, our ideas for future improvement, and more, feel free to watch this video link.

What it does

Welcome to EarthBrain, a novel, crowd-sourced mental health assistance forum that matches anonymous users and allows them to have constructive and positive discussions about similar issues or stresses. Communication is vital to providing adequate and targeted mental health treatment that is closely aligned with patients' needs. Our product seeks to do this by connecting users with similar struggles and providing additional resources to connect with licensed therapists and healthcare providers. EarthBrain is especially important as we understand that it is often difficult for many to express their mental health concerns due to fear of judgment or being ignored. To perform the matching, our recommendation algorithm creates a score based on users' age and interests and compares it with others' scores to find the greatest similarity. Our machine learning sentiment classifier ensures all posts are positive and maintain a healthy and compassionate environment, while those that contain hate speech or other offensive/unhelpful/derogatory language are taken down. This vetting algorithm is essential to maintaining a positive online environment and sets us apart from our counterparts. Failing to incorporate a vetting algorithm poses a grave threat to user safety and allows for the propagation of hateful and derogatory comments. To watch a demonstration, check out this link.

How we built it

Our process was split into five parts:

Training the sentiment classifier - Colab notebook
Building the UI interface
Persisting data to firebase
Building the recommendation algorithm
Integrating the recommendation + vetting algorithms, connecting the database and frontend

User Safety, Privacy, and Security

Users post anonymously, this ensures that people aren’t dissuaded from sharing
All data is stored using Firebase, which encrypts data in transit using HTTPS (Firebase)
ML algorithm that vetts negative or unconstructive comments to prevent the propagation of hateful and unproductive comments
Maintains a compassionate and open environment where users are assured positive feedback Easy access to other mental health resources such as licensed therapists and counselor's information,

User Experience

Minimalist UI interface allows for simple and efficient communication between users
Publicly sourced responses allow for fast response times, while the recommendation algorithm promotes responses from users with similar stresses

Challenges we ran into

Due to various time constraints (midterm exams, sports, etc.) we had limited time to work on the project, with additional time we could've improved the UI interface and vetting algorithm
Optimizing the sentiment classification algorithm to increase accuracy
Designing the UI interface and improving the user experience

Accomplishments that we're proud of

Finetuning the vetting algorithm
Creating a clean and simple UI

What's next for EarthBrain

Creating a native app to supplement the website and improve user experience on mobile devices
Increased accuracy and speed of the vetting system by utilizing higher-quality and larger datasets, and optimizing the network architecture
Enhanced recommendation algorithm by better understanding the similarities and differences between users’ causes of stress
Removing/blocking IP addresses that have repeatedly posted hateful feedback in order to maintain a positive online community