Subtheme: Ease of Use

While the tool was easy to use, some participants found that the visualizations were crowded with information and suggested simpler visualizations to start with while still enabling the user to add more layers of information to any visualization. All participants favored simple visualizations over complex visualizations. Figure 12, which represents cause-specific mortality by education in Canada, is, in many participants’ opinions, a crowded visualization because it shows many variables, including gender, age groups, causes of death, and education levels.

Figure 12: a Crowded Visualization

5.7.1.2 Participants’ Voice

Participant#5, an assistant professor, hoped that the tool will be simple to use. He believed that the studies presented in the tool should have simpler start up visualizations

that give the first time user a clear message about the content of each study. He compared the tool to Code Red, which is a web-based tool that presents data and interactive

visualization about the social determinants of health in Hamilton in Ontario, and believed that Code Red is simpler than the tool:

“That website [Code Red] has a very simple default, so I think that that makes it welcoming. You just get in, and you find just a few things that you can switch around, and it engages you. It is not overwhelming, and you can get what is being said immediately, then you can add layers on top of that, layers of complexity. You can add more pieces of data, more tools, and more options, but it doesn't scare you away because you don't see tons of options, different checks, and sliders.”

Participant#6, a health records specialist, believed that the more crowded the

visualization is, the less clear it is. She pointed out that some of the visualizations in my tool had too many categories and data points. Even though the provided filters were useful according to all participants, Participant#6 believed that for these crowded visualizations, a user will have to do lots of work to filter the data and simplify the presented chart:

“I found certain things were little overwhelming; I checked the education

visualization, and it was very clear but overwhelming in certain spots. When there is a large number of things to work with, it takes more time to look at the indicators and to get your head around it. It is not that you can't do it, but you need to go back and forth to understand the legends, but things were much easier with the visualized bar chart used in one of the studies. I know, from my experience, that the simpler the graphics, the easier it is. But for people looking at the data, they need the

graphics to indicate clearly or show what is going on. But if you have too much that is going on then it will just get confusing for the person who is looking at it. So, it can be clear, and it doesn't have to be too complex for you to get what you need out of it.”

Participant#3, who is a registered nurse and a Ph.D. student, found the tool to be “fairly easy to learn”, but she said that she might need some training to use it:

“I found it helpful, but I would need some training on how to use it, because you know I have grown up in an age of baby boomers where we were not that

technological but that is no excuse because a lot of baby boomers have learned the technology.”

Participant#4, who is an epidemiologist and a program manager at a health unit, found the tool to be “easy to use and intuitive”:

“It is very easy; I had no problem with it. I am not that tech-savvy, but I had no issues and no problem with navigating with it and play with it, so I felt it was quite good.”

Participant#1, who is a data analyst and epidemiologist, found the tool to be “a nice tool”, and believed that the simple the visualizations the better they are for the users:

“Compared to the traditional format, data visualization is trying to help people make things easier, and facilitating conceptualizing the data. But if you make it more complex and more difficult, then in some sense it loses the initial idea of visualizing the data to help people to accept it, and people need to be trained, or it will be too overwhelming, and they are better off reading the whole [published] papers… If you are presenting it to people like healthcare professionals to help them better understanding the relationships between the factors and the outcomes, I would say the simpler, the better.”

Participant#7, who is an assistant professor and epidemiologist, also believed that the initial screens of the visualizations in the tool were full of information and “very busy to start off”, but he was able to adapt these screens using the provided data filters:

“It might be problematic when I am faced with a screen full of colors and shapes, and it might take me some time to figure that out, but I think they [the colors and shapes] can be effective although the way they are presented in the initial screen provides too much information. So for them to be valuable, I have to start turning off certain things. I find the graphs very busy to start off.”

Participant#2, who is a registered nurse and researcher, found the tools to be easy to use, and the visualizations were easy to understand, and she asserted that it is important to keep the visualizations simple:

“I didn't find any challenges, and I think it is very friendly. I can tell you also that the visualizations used in this tool were very simple, and I think that it is much easy to read the findings if you had simple visualization, and I think that if the

visualizations were too complex they will distract you [as a reader] from seeing the findings.”