MIT Bachelor’s in Mechanical Engineering | Design Minor
UC Berkeley Master’s in Mechanical Engineering | Design Concentration

Mental Health Resources - Jubilant
Student - Fall 2020

Young busy people, especially young working professionals, feel overwhelmed by the existing number of mental health resources on the market. We aim to make the process of identifying the right kind of help and using the resources easy.

We defined a resource as a product that does not provide direct care for a user’s mental health but links users to platforms that directly care for their mental health

We began exploring our user group by thinking about the social, technological, and economic influences of a product that addresses the difficulties experienced by those that struggle with mental health as listed below.

        Supports young adults, particularly underrepresented groups
        Overcome stigma of receiving mental health care
        Empathetic mental health care
        Online mental health care is accessible
        Cheaper alternative to traditional mental health care
        Addressing health issues early is more cost-effective

From here, each team member brainstormed POGs for our group's idea. When we combined our list in mural, we groups each POG into clusters as shown in the image on the left.

We utilized dot voting in mural to narrow our POG list to 6 ideas. To ensure that our team understood each other’s impression of each POG, we each wrote our own definition for each POG and created a more in-depth shared definition to utilize as the project continued.

Ultimately we decided our final POG to be:

Supporting underrepresented groups of young professionals in managing their day to day stress and mental health.

We then approached users who fell into our target group to gain their insight on this topic. We obtained 32 survey results from users with an age range of 19 - 28 and a work experience length of 1 month to 5 years. The main pain points we identified were difficulties with communication and being required to work outside of one’s job description.

From the survey data, I created graphs that visualised the difficulties that users experienced in comparison to their sex or race. I hoped to find a trend unique to the underrepresented groups compared to the more privilege groups in tech. However, there seemed to be no significant difference. This survey did reveal an opportunity to further explore an employee’s struggles in general. Two of the sixteen graphs I created are displayed below.

Of those who felt comfortable with providing their contact information in the survey for future discussions, we chose 4 individuals to hold 1 on 1 interviews with each individual.

Key insights obtained from the interviews:
    1. Current mental health resources aren’t utilized.
    2. Personal resources utilized outside of work.
    3. Stress from work affects home life.
    4. Difficult to separate work and life during covid.
    5. No time to research best resource among countless options.

We then developed two personas from our target user group that we determined best represented their thoughts and desires.

Continuing to concept generation, I acted as team lead to organize the progress of our project and act as a meeting facilitator. I created a shared agenda for each meeting during this section of the project and ensured we used our time efficiently so as to not extend the meeting beyond our projected meeting time.

We used design heuristics to generate a wide potential for solutions. Each team member completed individual brainstorming to spontaneously generate many new ideas so we can explore avenues we did not previously think of and encourage each other to think outside of our comfort zones. We then used a team brainstorming method to share our concepts with each other and generate more ideas by building off of each other.

In the end, we generated around 75 concepts.

To the right is one of the concepts I initially created for the first round we held for an individual brainstorming session. Aspects of this concept were ultimately used in our final product.

We placed our concepts in mural on a positioning map to ensure that we created a well-rounded list of concepts. In the first positioning map we generated below on the left, our y-axis ranged from low to high technology from low to high to explore both physical and digital solutions. On the x-axis, the variable we used was personalization from less personalized to highly personalized. However, we realized that we hoped to create a concept that focused on addressing the needs of each individual user, we changed this axis to synchronicity. We defined asynchronous to mean the user doesn’t have to utilize the product at a specific place or specific time such as completing a questionnaire. We defined synchronous to mean that the user would use the product at a specific place and specific time such as talking to a mental health professional. The second positioning map is below on the right. We completed further concept generation to fill any gaps that were revealed in our second positioning map.
We clustered our ideas to organize our concepts. Then we reduced the number of options through dot voting to narrow down to 7 concepts. From there, we began a pugh chart with a datum and list of ranking categories based on our VOA. We consulted ~20 individuals who applied to our target users to determine how they would weigh each category. We took the average of these results and voted for each category within our team to produce this chart. From here we focused on two prototypes to focus on. Consulting our pugh chart and the discussion we had with Kosa, we created some prototyping goals for the future
As a result, we chose to continue by creating a lo-fi prototype for two concepts to obtain further user insight to narrow down to our final product idea.

The first concept would be an app that would connect with a user’s existing smart watch that tracks physical characteristics such as heart rate and sleep patterns to analyze activities and locations that are associated with higher stress responses. The app would suggest intervention of resources that immediately aid the user and provide a weekly or monthly recap of the data to suggest more long-term preventative solutions.

The second concept would be a website that matches a user to a mental health resource that best fits an individual based on self-reported characteristics and preferences.

As we had chosen our concepts to prototype, the project continued to the prototyping aspect of our project, and I passed the responsibility as team lead to another team member.

We produced a lo-fi prototype for each concept shown below in which we could obtain feedback from two individuals in our target user group.

            First Concept
            Second Concept

After obtaining feedback, we discovered that users prefered the first concept as it translated data to real-life applications and insights without a user adopting the responsibility to self-report. There prefered a mobile application rather than a website. The users greatly want privacy and confidentiality accounted for in the product.
As a result, we chose to continue with the first concept that utilized an application that adopted the physical response user metrics from a smart watch that they already utilize.
We utilized further feedback from the above more fleshed out prototypes to develop our high fidelity prototype

When the app is first downloaded, the user is greeted by a few intro screens and an onboarding process where the user connects their smartwatch to the app to track their health data and a questionnaire for the app to learn the user’s needs and preferences.

The three metrics the app will utilize from the smartwatch are heart rate variability, sleep quality, and cortisol level. These metrics are continually analyzed and alert the user to abnormal spikes that arise during the day. If you click on an abnormal spike, it tells the user why it’s abnormal, provides a user with an immediate actionable resource, and prompts the user to reflect. Additionally, a user’s location will be coupled with the data to allow the user to recognize if certain locations are correlated with higher stress levels and allow the user to understand what activities may be influencing these spikes.
Using collected data and the user’s preferences, the app suggests more preventative personalized mental health resources in the resources app. Clicking on a resource, provides a short description and external link to the resource.