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Connecting people to support


1 in 4 people in the world will suffer from Mental Illness during their lifetime. For many of these individuals, professional help isn't accessible or is too expensive. A lot of times due to the stigmas around mental illness people are ashamed to admit how they are feeling, and it can be hard or embarrassing to reach out to people close to them, or they may not have anyone around to talk to. I explored how we can use technology to give people support whenever and wherever they might need it. 


I filled all roles on this project, it served as my final project at Domus Academy.  My most significant learnings were the importance of a team with well-balanced skills and digging deeper with ethnographic research while dealing with sensitive matters including trauma and other mental illness issues. 


I conducted interviews with people currently suffering from mental ailments (both diagnosed and undiagnosed). To find interviewees, I created a survey to target the specific types of persons based on personas created. I posted the survey on several Facebook therapy group pages to locate viable candidates for interviews. After interviewing I analyzed and coded the qualitative data through several types of methods such as affinity mapping.


During synthesis, I discovered two distinct groups of users, In Need Peer and the Mentor Peer. 


  • Mentor Peer: is an individual who has previously received treatment, or overcomes specific issues in their life and wants to help people that are currently suffering, by offering guidance and support. 

  • In Need Peer: is the individual that is seeking out aid and guidance. They are currently in need of a little extra support. There are two types of In Need Peers, diagnosed and undiagnosed. Diagnosed meaning previously sought treatment and received a professional diagnosis of their mental state, undiagnosed being never diagnosed professionally. 

Using journey mapping, I created a typical path for the three types of users to highlight the major pain points and find a solution. This was done by using the information I received through interviews with target customers. 

Key Findings

People are willing to seek out help to improve their mental health

Peer support and understanding is helpful during recovery

Anonymity is important in online counseling, privacy is important regardless

several documents and materials that are hand written which is to show the materials used during research synthesis
Empathy Map - papers labeled with do think, say, and feel and post its with the interviewees respones in each category

 Research materials used for quick processing and documentation of observations

User Goals

Graphic created to explain the 


Through insights, we gathered the most effective treatment would be to offer people a platform where they could choose their peer mentor based on their current diagnosis or symptoms. We wanted all people to feel welcome, which is why we included symptoms along with diagnosis filtering. A symptom example would be  “feelings of hopelessness” while the diagnosis may be “depression". Upon completion of the filter screens, you are then given a list of mentors that match your criteria. You choose a mentor, or two, and message them. You are also able to video chat and voice call your mentors when they are online. We also try to push the user to chat via call or video with the mentors for a more personalized feel to increase the chances of recovery by creating a greater sense of connection which in turn will lead to a greater sense of accountability. 

The App
Additional Images