Evaluating the impacts of color, graphics, and architectural features on wayfinding in healthcare settings using EEG data and virtual response testing

Why does this study matter?
There has been a lot of research on wayfinding over the years. Research on wayfinding work really began in earnest with Passini, Carpman and Grant, and Peponis going back to the 80s and 90s. Since then, there have been more studies, and we know from the body of knowledge that ineffective wayfinding can increase anxiety, as well as the operational costs of staff time spent helping patients and visitors find where they need to go. That’s one form of inefficiency, but there’s also inefficiency when patients are late for appointments because they went to the wrong place.

How was the study done?
This study was testing the use of VR immersion with physiological EEG sensors as a way to evaluate wayfinding design, so it was not a real-world project. The researchers had a convenience sample of 63 participants (mostly undergraduate and graduate students, and some faculty).

Each was randomly assigned to one of three conditions that included variations of a hospital interior.  Condition A was the baseline design with basic signage. Condition B added color to places like elevator lobbies and information desks so as to better highlight destinations and signs. Condition C was Condition B plus architectural features such as changes in ceiling height, material patterns, and decorative graphics linked to destinations that were added to the signage. Participants followed a scripted scenario, and the researchers looked at:

• EEG measures.
• Self-reported metrics of mental fatigue, stress, and confusion, and
• Behavioral metrics (efficient orientation behaviors, and time taken to reach a destination)

The VR log file automatically recorded the number and identity of signs seen and how long the sign was viewed. The VR data was synchronized with the EEG data, which was focused on a part of the brain associated with the processing of visual information. EEG data for were evaluated using one-way ANOVA to compare Conditions A, B, and C. The researchers also measured when people went in the wrong direction and how long they were on that path, as well as when someone went in the right direction after seeing a sign.

What do we learn from the study?
The findings for self-reported and behavioral data were mostly inconclusive. There were no reductions in self-reported stress, mental fatigue, or confusion. There were not faster navigational times, either, but there were some exceptions. Participants in Condition C looked at signs longer and more often, and they were more likely to choose the right direction compared to Conditions A and B. The EEG data supported these findings with greater neural processing in the occipital cortex when participants viewed signs and decided the next move in both Conditions B and C.

The data also indicated higher levels of cognitive engagement when participants looked at signs in those two conditions, suggesting the creation of better mental maps, especially in Condition C. The EEG data also suggested a broader range of visual processing of the environmental information in Condition C. These results are consistent with prior anecdotal findings and studies using static images.

Can we say the results are definitive?
Are there limitations? Of course. The authors explicitly state a “strong note of caution” due to the finding that improvements didn’t translate into significant reductions in wayfinding times or reductions in the self-reported measures. They suggest, as we always hear, that more research is required to establish whether the lack of significant change in these specific wayfinding metrics is consistent across other studies. Was the task too easy? Was it because they were not real patients experiencing the anxiety of a visit? They argue that the advantage of the VR system for study allows feasibility for testing additional design variations and other participant populations.

What’s the takeaway?
In the end, we have tentative support for adding both manifest cues (what the signs say), as well as environmental affordances (what the structure says). Professionals that specialize in environmental and experiential graphics know this, but there’s typically a disconnect in implementation. We’re so often faced with a solution that has to integrate wayfinding AFTER the building has been designed, or worse, a directive to “Add more signs.”

Continued research about how our brain processes information, in addition to just perceptions, helps us understand what really makes the environment work as a holistic system for navigation. I often talk about the importance of understanding how work is done versus how work is imagined. Maybe this may be a case where work as “imagined” (our actual brain patterns) matters as much as work as done.
 

Summary of:
Kalantari, S., Tripathi, V., Kan, J., Rounds, J. D., Mostafavi, A., Snell, R., & Cruz-Garza, J. G. (2022). Evaluating the impacts of color, graphics, and architectural features on wayfinding in healthcare settings using EEG data and virtual response testing. Journal of Environmental Psychology, 79, 101744. https://doi.org/10.1016/j.jenvp.2021.101744
 

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