Home

Data Visualizations for People With Persistent Symptoms After Concussion:

Adaptation of a Pre-existing Visualization Tool for a New User Group

In managing persistent symptoms after concussion (PSAC), patients face difficulties in tracking and understanding their health data, essential for effective symptom management.

Data visualizations offer a potential solution but must be carefully designed to accommodate the cognitive and visual limitations of PSAC patients. Traditional visualization methods, such as those employed in the MyWeekInSight project, can overwhelm these individuals, hindering their ability to use such tools to manage symptoms effectively.

In this project, I aimed to develop accessible, user-friendly data visualizations tailored to the needs of PSAC patients, enabling them to engage with their health information in a way that supports symptom management and facilitates recovery.

The project's inception involved semi-structured interviews with three participants, chosen despite recruitment challenges due to their complex medical conditions and the project's academic nature.

The interviews aimed to assess:

• The perceived value of the tool for PSAC patients.
  
• Patient interaction with technology and preferences in symptom tracking.
  
• Interest in tracking specific symptoms and patterns, such as headaches, fatigue, and anxiety, alongside physical and environmental factors.
  

Findings revealed:

• A positive response to the tool, contingent on its adaptability to visual limitations.
  
• Previous attempts at symptom tracking were hindered by the inadequacies of spreadsheet formats.
  
• A preference for short screen engagement times due to symptom exacerbation from prolonged focus.
  
• A desire for cross-attribute symptom comparisons to discern patterns, triggers, and intensities.
  

In the prototyping phase, I drew inspiration from the MyWeekInSight project's visualizations, aiming to refine and adapt these designs to better suit the needs and limitations of the PSAC population. As such, I implemented the following design choices:

• Separating data into more manageable portions across different screens to distributing information into more digestible portions to minimize cognitive overload and ease interpretation
  
• Introduction of daily and weekly views, simplifying time frame selection, further streamlining the presentation of information and reducing cognitive load
  
• Modification in the use of color: using hue to categorize symptoms, rather than brightness coding for intensity, facilitating easier interaction for those with PSAC related color sensitivities.
  

Key takeaways stressed the necessity of careful project scoping and focus on core functional design elements. Reflecting on the broader scope initially taken, the realization emerged that the project did not fully meet its goals, particularly in designing graphs for effective multiple attribute comparisons. The resulting prototype, although falling short in supporting comprehensive cross-attribute comparisons, did offer visualizations for various aspects of the PSAC experience on separate screens. These were intended to be glanceable and limit data overload but ultimately did not facilitate the intended cross-attribute analysis.

Future directions should concentrate on developing specific visualizations that enable effective comparison across multiple symptoms, refining these aspects before integration into a broader application framework. This approach promises to enhance user engagement with the tool, promoting reflection, awareness, and potentially aiding recovery by facilitating a deeper understanding of symptom patterns and triggers.