Sprint 2

Research goals from sprint 1

Is postcode look-up sufficient for looking up air quality?
Do participants understand the daily air quality index (DAQI) score/levels as relevant to them?
Do people read and understand the health advice? Do they regard it as relevant to them?
Do people engage with the measurement stations (location, readings) and do they give credibility to the DAQI score?
Do participants come away appreciating that poor air quality poses a health risk?

Research findings

What worked well

Most of the participants commented that the prototype was in keeping with government websites. It was noted that:

the site is credible and easy to use
the location search did not present any problems; everyone entered a postcode without prompts
the site content was straight forward and easy to understand
The health information was engaging and even showed signs of overturning some air quality myths and creating interest in behavioural change

What needs work

Whilst the beginning of the participant’s journey tested well, once they arrived at a forecast location, it was noted:

scientific language, especially around pollutant names and measures, presented a barrier to participants
the monitoring stations and the process of data collection may not be of high interest, which can lead to key information being completely ignored. Since the names in the prototype were fictional, participants may not have perceived a connection to them.
the location of the pollutant information under related content was often overlooked

What we focussed on in sprint 2

As a team, in sprint 2, we agreed the main points to focus on were:

the flow of the content was affected, as participants were discouraged from reading the ‘related content,’ possibly due to the positioning and the use of scientific terms.
could we increase engagement by emphasising pollutant measurements rather than monitoring site location?
would using accurate monitoring site location names make the information more relatable?

We updated this page to make it easier for participants to learn about the air quality in their area by reorganising the hierarchy and putting it all on one page rather than branching the pollutants off under ‘related content’.

Flow of content

We adapted the headings to show a logical flow that the participant would follow.

‘The air pollution forecast for today is moderate’

The level of air pollution is what participants seem interested in after entering their location.

‘Advice for moderate levels of air pollution’

Next, we tell the participants what this level of air pollution means for them and highlight advice for those at risk or who may have health concerns.

'How air pollutants can affect your health’

Next, we delved deeper into how the individual pollutants can affect the participants’ health. This material was previously on the right-hand side of the page under ‘related content.’ We hope that the heading of this section may encourage participants to select individual pollutants to find out more.

In previous research, participants were often deterred from reading further because scientific terms made them think they wouldn’t understand it.

How air pollutants can affect your health

‘Air pollutants monitored nearby’

We aimed to make this element more engaging, firstly by introducing the pollutant measurements to the page for each station. Secondly, by adding in 2 new columns: ‘trend’ and ‘rising’.

We borrowed this concept from the Check for flooding service. We thought that this information would give the participants more context to the measurements rather than just displaying an arbitrary number.

We have a working hypothesis that we would only display monitoring sites that are within a certain distance, for example, 75 miles and up to a maximum of 3.

Tooltips

From previous user research, the information in the data table has proven to be hard to understand for most participants. We were struggling to think of a way to explain some of the columns without making the design too busy.

Again, looking at the ‘Check for flooding’ service, we noticed they used tooltips in a very similar data table to ours. We had a productive chat with the interaction and content designer from the service who walked through their user research and accessibility findings.

As the use of tooltips had been mentioned by participants during our alpha user research. This made us comfortable in trying them in the iteration for sprint 2.

Pollutant details page

The pollutant pages generally tested well during the first sprint. Participants struggled with the content of the pollutant banding table, so we removed this from each page.
To improve the flow and ensure consistency, we made sure they followed a set format:

what is the pollutant?
what sources does it come from?
what are the short exposure term health effects?
what are the long term exposure health effects?