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Mobile App Case study

Role                Human Factors/UX Researcher

Team              Individual Project

Timeline         3 weeks

Skills            Human Factors, UX Research, Design 

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Dashboard

Combine reports, giving users

an overview of their data

Introduction & Background

Abbott’s Lingo is a consumer-facing bio-sensing wearable technology that is being designed to track “key signals” in the body – such as glucose, ketones and lactate – adding that it could also be used to track alcohol levels in the future. 

 

The company last year launched a biosensor designed for athletes, called the libre Glucose Support Biowearable with its goal to expand glucose monitoring to people looking to manage their weight, improve energy and think clearer. To present users their health data, Abbott would like to develop the new Lingo app and use what they have learned from the user feedback of its FreeStyle Libre 3 app to inform their design decisions. 

Tasks

  • Imagine you are a Human Factors Research Engineer in the Abbott Lingo mobile app team.
     

  • Conduct user research to identify research questions and areas of improvements for the FreeStyle Libre 3 app user interface that can be used in the development of the Lingo app.
     

  • Explain how you would collaborate with the engineering and design teams to come up with a user interface that satisfies the findings of your research.
     

  • Deliver your findings to the engineering and design teams and include a mock up of what the new graph design should look like.

My Role &
Collaborations

As a human factors engineer, I’ll collaborate with the engineering and design teams and follow a systematic process to ensure the user interface satisfies the findings of my research. Below is the step-by-step explanation of how the collaboration takes place.
 

  1. Conduct user research to understand the needs, preferences and behaviors of the target users. This involves methods, such as interviews, surveys, and observations to gather data on user expectations and challenges.
     

  2. Analyze the research findings and translate them into design recommendations.
     

  3. Host collaborative brainstorming and ideation workshops to deliver research findings and recommendations and exchange ideas to generate innovative concepts that integrate both technical feasibility and user-centered design principles.
     

  4. Define iterative prototypes with engineers and designers in which incorporate user feedback usability testing results.
     

  5. Iteratively refine the design, making adjustments, and improvements with the collaborative team to identify any addressed issues and concerns of the prototype based on research findings.
     

  6. Document the design decisions, user research findings, guidelines for the prototype throughout the collaboration and the entire process of product development. Schedule regular meetings and feedback sessions for continuous collaboration and communication to ensure all the stakeholders are aligned and that the prototype evolve around users’ needs and technological constraints

Problems &
Constraints

​To identify the areas of focus for developing research questions, I conducted online research to gather insights into users' existing complaints and limitations with the app. Below are the feedback I found:
 

  • A common feedback given by users is about the graph size. Currently, the graph shows a range of 50 mg/dL to 350 mg/dL. However, most readings will fall within the values of 80 mg/dL to 250 mg/dL, so there is a lot of wasted space.
     

  • The current version of the FreeStyle Libre 3 app does not allow users to set their own ranges.
     

  • The app does not support a zoom feature that would allow users to zoom in and see how quickly their readings are changing over time.
     

  • While it does send notifications to my iWatch, they have yet to make an app compatible to use with it. Seeing your blood sugar value on your watch is not possible yet.
     

  • The freestyle Libre 3 app can store up to 90 days of information and includes detailed glucose reports, such as daily patterns, time and ranges, low glucose events, average glucose, daily graph and sensor usage.

Research
Questions

  1. Identify the reading's range:

    • What are the average, 95% confidence interval range, and max outliers of most glucose readings using Lingo?
       

  2. Determine the need for calibration: 

    • Does the glucose reading range vary by person? 

    • If so, how different does it vary from person to person? Do need calibration for each person’s reading?
       

  3. Pinpoint the optimal views (e.g., max, min, daily, weekly, monthly, etc.) for users to review time series of their glucose data to facilitate the implementation of the zoom in feature:

    • In what time frames do users usually review their glucose data in order to track the trend of their reading?
       

  4. Discover what data/information do users need to know when they’re on the go and don’t have access to their phone:

    • What do users like to see/know when receiving Lingo’s notifications on their Smart Watch?

    • What types of notification do users prefer to receive in their daily context? For example, haptic (vibration), visual only, or with sound?
       

  5. Uncover usability issues on the UI:

    • What are the pain points of the presentation of the graphs and charts for visual purposes?
       

  6. Discover other health features that users need:

    • What other data can be included in the detailed report that users would like to see when using Lingo in their everyday life?
       

Participant

I aim to recruit 32 participants and targeted to recruit a sample with the following demographics.
 

  • Equal split (50/50) of males and females

  • Equal split (50/50) of diabetics and non-diabetics

  • Diverse age groups to represent the general US population

  • Non-technical occupations to avoid bias and inconsistent adaptation to new interface and technology.

Methods​

The methods I would use include:

  • Usability Testing

  • In-person Interview

  • Cognitive Walking (Think-aloud)

  • Statistical methods

  • Observations

Takeaways &
Recommendations

  • Implement calibration based on the user's glucose reading to personalize their range in the graphs.
     

  • Include minimal and maximum views based on the user's usage behaviors to support the zoom in/out features.
     

  • Sync notifications with Smart Watches and implement the notifications and types of notification that users need based on their preferences and daily usage behaviors.
     

  • Combine the graphs in the detailed report into a summary dashboard. It give users an overview of their data.
     

  • Improve the UI to make it more intuitive and user friendly.
     

  • Include other data that users would like to see on mobile.

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