A geocached messaging app, for building and maintaining new exercise habits.


Student Project



Interaction Design, Prototyping, Visual Design
Advised by Premera Blue Cross
10 Weeks, Fall 2018
Mike Cardarelli, Sophia Li

Medical caregivers are vital to America's healthcare system.

Unfortunately, they are often overlooked by insurance providers.

Premera Blue Cross wanted to change this, and came to our studio seeking ideas for new products serving caregivers. 

What is Drop-In?

Drop-In is an expressive response to the needs of type 2 diabetes patients, and their caregivers.

Drop-In is an expressive response to the needs of type 2 diabetes patients, and their caregivers.

It's an app that uses messaging to motivate habitual exercise. 
Messages are delivered to a location chosen by the sender.  
The recipient must walk to the message to view it and reply.

How does it work?

Start with a map.

Maps are familiar, a little bit fun, and full of information people can relate to. Drop-In’s home screen is a map showing all the new messages near you. 

Choose a message.

Tap on a message to see who it’s from, how long it will take to walk there, and the best route to take.

Then, get out there and collect it!

You can’t view a message until you travel to it and pick it up. Once found, messages can be watched again later from the inbox.

To send a message, choose a recipient and a destination.

Users can set places they would like to have messages delivered to. Choose one of these areas so your friends can find your messages more easily.
recipient location selection

But first, make sure they can get there.

Terrain and accessibility data from OpenStreetMap and Project Sidewalk can be overlaid on any of Drop-In’s maps. This helps you find the best routes to your messages, and helps you find good places to drop the messages you send to others.
accessibility layer and message location selection
activity history and daily goal achievement

Keep track of your progress.

Drop-In emphasizes consistency and progression, so it only keeps track of essential exercise metrics. But, it can integrate with many first- and third-party apps for those who want in-depth analysis.

How did we arrive at Drop-In?

First, I needed a better understanding of the problem. 

I researched the challenges faced by caregivers in the context of today's healthcare system, and its 10-year trajectory. 

Family members are increasingly taking on caregiving responsibilities. The demand for hired health aides is outpacing supply, and many people are unable to afford outside help. 
However, families today are often geographically dispersed, making it more difficult for relatives to provide caregiving assistance. 
Research probe exploring geographic seperation of families
A research probe verified this finding: every participant had family more than three hours away. 

I saw an opportunity to have an impact on diabetes.

Type 2 diabetes is one of the most prevalent and expensive diseases in Washington and Alaska, where Premera provides coverage. 
Successful treatment is heavily dependent on developing healthy habits. Diet, exercise, and medication routines must be established, and they must last for long periods of time. 

Caregivers can benefit from the same healthy habits as patients.

Relatives of diabetes patients are 2–6 times more likely to be diagnosed themselves, but following the same healthy habits as patients can greatly reduce the risk.

But, following through on new routines is hard. 

“I know what it takes to get to 10,000 steps a day, but walking for the sake of walking is so hard… 

Maybe I’m too goal-oriented.”

—Seth, Interview Participant

How might we help caregivers establish healthy, sustainable habits for newly-diagnosed type 2 diabetes patients?

I explored ideas to motivate and assist habit formation.

We evaluated dozens of concepts and selected three to move forward with. 

After being tasked with coming up with over 100 ideas, we evaluated the 20 most feasible concepts with a decision matrix and the Six Thinking Hats method. 

Geocached messaging stood out as a novel idea, with the potential to address our user's needs in an expressive manner.

I created a storyboard to convey the idea's ability to bring people together and work toward common goals in a more personal way than typical healthcare technologies. 

Drop-In was born from my vision of the experience. 


We saw its value, but would users?

We tested a paper prototype to see if Drop-In made sense to others, and to find out if people would be interested in using it. 

“I think I understand. He has to exercise to see it.”

—Mel, Usability Tester

“I like the concept of maps, I like the concept of video chat. I would probably actually use this.”

—Krissy, Usability Tester

We defined the three pillars of Drop-In: finding messages, sending messages, and tracking exercise. But which of them should be emphasized, which should users see first?

I proposed an interaction model that used a map-based view of available messages, then created wireframes and tested it. 

wireframe of finding a message flow
The goal of the app is to get people out into the world, doing physical activity. A map of destinations directly supports this goal, and it's familiar and intuitive for many users. 
Finding a Message wireflow diagram
wireframe for Send message flow
Adding a floating action button helped users access and create messages, but I found that people needed help deciding where to place their messages on the map. 

Users needed more information to find good locations for their messages, so I added layers for accessibility conditions. 

Sending a message flow

Initially, users could track their exercise by creating custom activity goals and sending challenges to others. 

wireframe of exercise goal flow

We realized this complexity was unnecessary, and simplified this feature to focus on its core purpose. 

Testing revealed numerous usability problems with goal creation, and our deadline was approaching. We decided to revisit our desired outcomes for the project, and rethink our approach to meeting them. 
We decided an automatically calculated target, updated based on each user's prior activity level, would fulfill our aim just as well. 
Maintaining healthy habits flow

The map-based model tested well for finding a message, but the flow for sending a new message wasn't discoverable.