Designing an addiction assessment and treatment platform
Client - Neurotype
Neurotype is working to develop a platform that integrates the use of portable electroencephalogram (EEG) headset into Opioid Use Disorder (OUD) treatment and therapy clinics. This platform, NeuromarkR™, would allow practitioners without specialized training in EEG to incorporate this quantitative metric into their treatment and evaluation process. We were tasked with creating an intuitive, tablet-based experience flow for both the patient and practitioner to use during patient progress assessments as well as a data-visualization dashboard for patient assessment results.
My role
UX Research - Moderated both an initial discovery user interview as well as usability tests with our high-fidelity prototype.
UX Design - User flow and wireframes
UI Design - Co-created the final UI, design system and interactive prototype in Figma.
Deliverables
Interactive prototype*
UI*
Design Style Guide
User flow*
* Played a primary role
Tools
Figma - Design and Prototyping*
Miro - Collaboration
Notion - Project management*
Methodologies
Secondary research
User interviews*
Usability testing*
Information architecture*
Experience mapping*
Interactive prototyping*
Project Overview
The Challenge:
Create an experience that is easily interpretable and learnable by EEG non-experts and approachable to Opioid Use Disorder (OUD) patients.
High-level Goals:
Transition the traditionally lab-based EEG assessment to be used in a clinical setting
Make data understandable to a non-technical audience through effective UX and visual design
Use data to impact and substantiate treatment
Research + Discovery
Stakeholder interview
We began the project with an initial meeting with our client, Dr. Scott Burwell, to talk to him about why he founded Neurotype and what he was looking for in the digital experience.
Secondary research
With a solid understanding of our client’s goals for the product, we then conducted a competitor audit to get a feel for what products were already on the market, what they were doing well, and how Neurotype could differentiate itself in that space.
Both our client and one of the primary user groups (health practitioners) work in a research-driven field. With that in mind, we dug into some academic resources on the following subjects:
- Integrating technology into the mental health field -
- The use of EEG devices to measure cravings -
- Comparing EEG brainwave data to self-reported cravings -
Define
We then began to create a visual structure of the experience to help us identify where the pain points and opportunity spaces of the user were.
This helped us to conceptualize an overall experience early on that we could refer back to and improve upon throughout the project.
User Interviews
With a solid understanding of the space, we began conducting remote discovery interviews with practitioners in addiction therapy and parallel fields.
This helped us gain a feeling for the context of practitioners working in a variety of settings, and gauge their initial reactions to the product concept.
High-level findings:
Practitioner’s needs were very intertwined with patient needs/comfort.
Practitioners made no assumptions that brain reactivity was an important metric to track. They needed to see the research to substantiate value before endorsing the idea or considering bringing it into their own practice.
A NeuromarkR session would need to be under 15 minutes in order for practitioners to realistically integrate the tool into their treatment.
I find the discovery phase to be an extremely important phase of the overall process. This is when you must challenge all your assumptions of the space you are entering into, and if you dont come at it with that perspective you risk losing some of the most valuable insights.
“Testing should be for the sake of the client’s growth. And they should be involved in what that journey looks like…to make sure that what is being created serves the client at the end of the day”
Synthesizing our research findings
Remote group synthesis was done on a Miro board where we organized data gathered in user interviews and began to organize concrete findings that were incorporated into our next design iteration and tested for in our remote usability tests.
Architecting the experience
From what we gathered during our stakeholder interviews and user interviews, I created a user flow that illustrated the experience at a high-level, noting the device handoff interactions between the patient and practitioner.
Wireframes
I created wireframes for the log-in, dashboard, check-in and EEG assessment experience:
The practitioner logs into their Neuromark account
On the homepage, the practitioner can check in a new patient, start and EEG assessment or access past patient reports
Some questions, like this one, is only asked at a patient's first Neuromark appointment
Others are asked each session
When the check-in is completed, the patient is instructed to hand the device back to the practitioner
One the practitioner begins the assessment, the tablet will pair with the EEG device
The practitioner then can begin the assessment and hands the device off to the patient to begin
Images that may or may not elicit a craving response are shown on screen.
UI Design
From there, we created an initial round of designs and packaged it into a clickable Figma prototype for both client review and later, usability testing
We created a color-coded system that assigned purple for the patient and turquoise for the clinitian to add helpful visual cues for the device handoff during the session.
A dark-mode background was used for the experience as a whole as it had a more calming effect for the patient taking the assessment and also helped the data visualization colors stand out more on the data dashboard.
Usability Testing
We used the clickable Figma prototype to conduct usability testing with practitioners to get feedback on the experience we had created so far.
What we heard…
Customization
OUD patients can be triggered by very different images depending on the person. Practitioners therefore wanted to be able to customize the session to each individual patient, particularly the images being shown and the questions being asked.
Understandable data
When first hearing about NeuromarkR, practitioners seemed skeptical about their ability to interpret the data in a way that would be meaningful for their practice. For that reason, making data visuals approachable and easily digestible was essential.
Options for data visualization
Practitioners expressed to us that they would be interested in seeing different types of information for each of their patients. We therefore made sure to include different data visualizations that could be selected for in each patient’s personal settings.
The Solution
The practitioner will administer a check-in at the start of the session to gather information about the patient’s mood and general drug craving. Next, the practitioner will connect the headset to the tablet.
Once connected via Bluetooth, the practitioner will put the EEG headset on the patient’s head making sure the signal is strong.
Before handing the participant the tablet, the practitioner will explain the exercise and attempt to get the patient in a state of calm since jaw clenching and blinking can throw off the data collected by the EEG headset.
Next, the participant will go through a photo viewing activity. Each session will last around 10 minutes with breaks every 2 minutes or so. In this session, the patient’s brain reaction will be recorded for around 300 stimuli.
The photo session starts with a guided walkthrough to explain how to use the assessment.
And the arrow icon on the right if they do not.
Once they start the activity, they get a series of images that include things that are likely to cause a brain reaction (like seen here), as well as images that hope to elicit a more neutral reaction.
The user completes this activity in 5 segments of around 1-2 minutes each with breaks in between.
Once the patient has completed the activity, they are instructed to hand the device back to the practitioner. Now, I’m going to hand it off to Tim to talk about the data gathered during the session.
Once the session is finished, the patient removes their headset and the practitioner can view a breakdown of the session.
They can choose to view the details of individual sessions or a dashboard showing patient progress over time.
Here on the session dashboard, the practitioner can immediately view a high-level overview after the session with a variety of clear data visuals. To help focus on the most useful data, cards on the dashboards can be moved and customized to suit the practitioner's view for each patient.
The gauge card visually compares a patient’s self-reported drug craving to their brain’s reactivity to drug-related images. This allows practitioners to quickly identify a difference between these numbers.
Clicking into the photo timeline card shows a high-level view of brain reactivity data with corresponding photos, allowing practitioners to easily see which photos elicited strong responses.
Here you can view the brain wave data for this photo in comparison to all other sessions where this photo appeared, allowing the practitioner to see changes in reactivity from week to week.
This is the patient dashboard, which gives practitioners a high-level overview of patient progress
If you click into this graph, you’ll jump into a more detailed view of how the patient has progressed through the treatment... here we can see that their self-reported drug craving decreased more quickly than their brain reactivity to drug images. Seeing this information during treatment can help both patients and practitioners understand that, even though they may feel that their drug cravings have decreased, they may still be at high risk for relapse.
They should tap the head icon on the left if they feel stimulated by the image.