Deer, Journal

Youth education redesigned, AI prompted journaling, Visionboard generation, and OpenCV guided playtime!

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Inspiration

With an increasing demand for therapists and mental health services and a limited supply of these resources, mental health has become a growing issue plaguing Canada, especially our youth. An estimated 1.6 million children and teenagers suffer from mental health issues, yet only 20% will receive adequate care to address this. The goal of “Deer, Journal” is to create an approachable, child-friendly resource for children to develop their self-reflective ability, their goal setting habits, and mental-health coping strategies so they are comfortable with vulnerability and becoming the best version of themselves.

What it does

“Deer, Journal” provides an approachable, child-friendly way for children to get into the habit of journaling, practicing self-reflection, and becoming vulnerable. Through interacting with a deer stuffie, children can recount their day and express their daily feelings through guided, AI-powered prompts. The prompts are child-friendly and adapted depending on the child’s daily conversation history. Additionally, the user can tell the AI their goals for the week and the AI will create a unique, weekly vision board catered towards that child.

How we built it

“Deer, Journal” is primarily built off the OpenAI API to create unique “turbo-gpt-3.5” chatbots that are prompt-engineered towards children in their responses and the questions they are asked. The vision board image generation uses the DALL-E-3 image generation model from the OpenAI API. The entire app is built off React native, Node.JS, and Express.JS.

Challenges we ran into

The biggest problems that we ran into were backend errors. Most of us do not have much experience with the backend so we spent a lot of time trying to understand and trying to integrate and connect everything to each other. Furthermore, the OpenAI API documentation was often wrong so it took a lot of guessing to figure out the correct syntax. Plus, we were too ambitious with the amount of features we wanted to add to “Deer, Journal” which made us focus on features that were much less important to the overall product. Also, a last-minute change caused us to convert all our OpenAI API programs from Python to JavaScript.

Accomplishments that we're proud of

We are proud of the fact that we got a functioning app and got the key features down. Additionally, the UI turned out much better than expected and all OpenAI API integration was highly successful.

What we learned

We learned that next time a majority of us need to better familiar ourselves with the backend because its important was certaintely undermined originally. Plus, we need to avoid feature creeping and trying to add too many features at once without tackling the primary use and functionality of the product.

What's next for Deer, Journal

What’s next for “Deer, Journal” is optimizing its primary AI-prompted journaling features and eventually adding the features we originally wanted to add. This includes computer vision to better recognize facial features so that mood analysis can be completed, and computer vision and help guide users through grounding games.

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